In-depth bibliometric analysis of over five decades of Aerosol Optical Depth revealing trends, key contributors, and new research directions.

In-depth bibliometric analysis of over five decades of Aerosol Optical Depth revealing trends, key contributors, and new research directions. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article In-depth bibliometric analysis of over five decades of Aerosol Optical Depth revealing trends, key contributors, and new research directions. Emmanuel Yohanna, Hwee Lim San This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7763043/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Numerous studies have shown that air pollutants affect climatic change, air quality, and public health and how particulate matter (PM2.5, PM10) contributes to respiratory and environmental impacts. This study comprehensively examines aerosol optical depths and thicknesses, climate connections, and pollution-related health impacts using bibliometric and visualization analyses. We retrieved documents from the Scopus database regarding aerosol optical depth/thickness between 1960 and 2025. A total of 4,131 documents were initially generated. Articles and conferences were selected as document types for a more comprehensive analysis. Filtering from Earth and planetary sciences, physics and astronomy, and environmental science documents, we generated 3,542 documents. We explored VOSviewer, Python, and MapChart. The United States of America has 1,202, 35.86% (73,523); China 518, 14.62% (10,230); France 419, 11.83% (25,370); Germany 376, 10.62% (17,013); and Japan 371, 10.47% (10,888) papers published and citations, respectively. NASA Goddard Space Flight Center, Greenbelt, MD, United States, was the journal with the highest number of papers published, with 74 documents and 7,380 citations. The most common occurring terms are “aerosols,” “aerosol optical depth/thickness,” and “air quality.” This study was novel because it was the first bibliometric analysis based on aerosol optical depth that used data retrieved from Scopus for visualization and network mapping. Highest publication was observed in 2011 with a drop in 2020. Researchers needs to continue to investigate aerosol optical depth/thickness of growing global climatic change and weather dynamics. Aerosols Aerosol optical depth/thickness Air quality Bibliometric Scopus VOSviewer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Over the course of the past centuries, scientists have shown a great deal of interest in aerosols, which are tiny particles that are suspended in the air (Hinds et al., 2022; Zhang, 2020 ; Anderson et al., 2020 ). This interest has been particularly focused on those scientists who are concerned with climate change and public health. At the end of the nineteenth century, a scientist named John Aitken used the term "aerosol" to describe the minute, invisible particles that have a significant influence on the weather, climate, and the health of humans (Folch, 2025 ). The size of these particles, which can range from a few micrometers to tens of nanometers, has an effect on how they interact with solar radiation and how they behave in the atmosphere (Wijeratne, 2021 ). It is possible to make aerosols in two different ways, either naturally or artificially. Pollen and mineral dust are examples of biological particles that come from natural sources (Huffman et al., 2020 ). Other natural sources include volcanic eruptions and aerosols from the ocean. In contrast, secondary aerosols are produced as a result of human activities such as the combustion of biomass, the emission of exhaust from automobiles, and industrial processes (Munsif et al. 2021 ; Luo et al. 2024 ). Recent studies have highlighted the importance of knowing aerosols, particularly their dual role as both cooling and warming agents (Li et al. 2022 ). Aerosols are a challenging topic in conversations about climate change (Mondal et al., 2021 ), and recent research has highlighted the need to understand them. For the purpose of illustrating this concept, some aerosols contribute to an increase in temperature by reflecting sunlight, whereas others contribute to an increase in temperature by absorbing heat (Sokhi et al. 2021 ). To properly evaluate the effects that aerosols have on public health, it is essential to have a solid understanding of their origins and the repercussions they have. This is especially true in urban areas, where high concentrations of aerosols can result in a major decline in air quality (Hinds et al. 2022). As a consequence of this, it is essential to continue study into the origins and effects of aerosols in order to create efficient methods for preventing the adverse impacts that aerosols have on both the environment and human health. Yu et al. ( 2020 ) stated that, as a result of recent developments in aerosols research, these constituents have been divided into primary and secondary groups, according to the sources from which they originate and the methods by which they are manufactured. Primary aerosols are naturally occurring particles that are released into the atmosphere. Some examples of primary aerosols include mineral dust, sea spray, smoke from wildfires, and volcanic ash. Chemical reactions that result in the development of secondary aerosols are responsible for the generation of sulfate aerosols (Liu et al. 2021 ). These events take place when gases that are emitted by human activities, specifically sulfur dioxide from industrial processes, experience chemical reactions (World Health Organization, 2021 ). This category has made it easier to make progress in the study of the behavior of aerosols (Hinds et al. 2022; Feng et al. 2020 ), particularly with regard to the effects that aerosols have on precipitation, cloud formation, and regional climate systems (López-Romero et al. 2021 ). Recent research has shown that both forms of aerosols have a significant impact on the global radiation balance, which in turn contributes to the cooling and warming impacts that make climate modeling more difficult (Akinyoola et al. 2024 ). Irfan et al. ( 2024 ) reported that black carbon is a primary aerosol. When black carbon is deposited on polar ice, it reduces the reflectivity of the ice and contributes to the warming of the planet by absorbing sunlight (Zhu et al. 2021 ). As the amount of literature continues to grow, it is becoming increasingly clear that it is necessary to monitor and comprehend the dynamics of aerosols in relation to climate systems and public health (Liu et al. 2020 ). Shen et al. (2023) and Mathew et al. ( 2025 ) reported that as urbanization increases, the impacts of aerosols on air quality and human health become more pronounced. As a result, it is necessary to develop a comprehensive approach to the research of these particles that takes into account the various forms of aerosols and the interactions they have with the environment. As part of the process of determining how aerosols influence the dynamics of radiation and climate, the Aerosol Optical Depth/Thickness (AOD/T) is a significant statistic that is taken into consideration (Jin et al. 2023 ). The reduction in sunlight intensity that is induced by aerosol scattering and absorption is quantified by this metric, which also serves as a dimensionless measure of atmospheric aerosol loading (Jadhav et al. 2024 ). In addition, this metric provides a quantitative depiction of the problem. The advancement of remote sensing technology, in particular satellite-based observations, has significantly facilitated our capacity to monitor AOD/T on a global scale (Ranjan et al. 2021 ). This capability has been significantly enhanced. For the purpose of determining the dispersion of aerosols, the Sentinel-5P satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) from the National Aeronautics and Space Administration (NASA) both provide highly important data (Reshi et al. 2024 ; Yilmaz et al. 2023 ). According to Sogacheva et al. ( 2020 ), validating satellite observations and providing information on the localized AOD/T, solar photometers, and other ground-based sensors are absolutely necessary. Measurements of AOD/T that are more exact have the potential to improve our understanding of the impact that aerosols have on the quantity of solar energy that is produced as well as climate systems, as indicated by the findings of recent research as reported by Dumka et al. ( 2021 ) and Fountoulakis et al. ( 2021 ). Measurement of AOD/T is required in order to acquire an understanding of the impact that aerosols have on the energy balance of the Earth through the processes of light extinction and absorption. This understanding is vital in order to find out how aerosols affect the energy balance of the Earth. The amount of solar radiation that reaches the surface of the Earth can be altered by aerosols through the processes of absorption and deflection (Spiridonov et al. 2025 and Stieglitz et al. 2024). The interaction has the potential to have an effect on a variety of phenomena, including shifts in the global temperature, alterations in weather patterns, and the phenomenon of cloud formation. This is due to the fact that particulate matter is an essential statistic for studying the impact of aerosols on a wide range of scales, including regional air quality evaluations and global climate models (Van Donkelaar et al. 2021 ). With regard to the utilization of renewable energy sources, a significant amount of focus has been placed on gaining an understanding of the connection that exists between AOD/T and the dynamics of climate (Schmale et al. 2021 ). There are a number of essential characteristics that are included in the formula for Ångström turbidity, which is utilized in the calculation of AOD/T. These parameters have an effect on the solar spectrum as well as the efficiency of solar panels (Annapurna et al. 2024 ; Jin et al. 2023 ; Jadhav et al. 2024 ). Recent studies (Spiridonov et al. 2025 ; Dangayach and Pandey, 2024 ; Kouklaki et al. 2023 ) have shown that changes in spectrum irradiance, which are regulated by AOD/T, can drastically diminish the amount of electricity that photovoltaic (PV) systems are able to release into the environment. Kaufman et al. ( 1997 ) reported that aerosol models demonstrate the impact of multiple-scattering effects. The estimation of phytoplankton-pigment concentration and aerosol thickness yields errors of less than 20% and 10%, respectively. Photovoltaic systems are able to generate electricity by converting sunlight into electricity. The importance of keeping this in mind cannot be overstated, especially during times of extreme weather, such as when dust storms or wildfires are occurring. Based on the findings of the studies by (Li et al. 2020 ; Isaza et al. 2023 ; Mammadov et al. ( 2022 ), it was determined that a decrease in AOD/T could result in some percent reduction in the amount of solar energy that is produced. On the other hand, this is especially true for solar systems that have a high efficiency in addition to a high sensitivity to changes in the spectral distribution of light. Remer et al. ( 2005 ) stated that daily observations of Earth from 0.41 to 15 µm are provided by NASA's Terra and Aqua satellites' Moderate Resolution Imaging Spectroradiometer. Reflected spectral solar flux and optical thickness at various wavelengths are examples of land aerosol products. These measurements over land and ocean determine the optical thickness and size of aerosols. The optical thickness of ocean aerosols is measured in seven wavelengths, along with effective radius and other aerosol data. MODIS aerosol retrievals are within expected uncertainty limits, according to validation using Aerosols Robotic Network (AERONET) data from 132 stations. Reducing aerosol radiative forcing uncertainties is necessary to comprehend the effects on the global climate, and MODIS aerosol data accuracy makes this possible. Recent developments in aerosol research have demonstrated that the application of machine learning techniques can considerably improve the efficiency of AOD/T retrievals and monitoring (Tian et al. 2021 ; Liang et al. 2022 ; Yu et al. 2024 ). Traditional methods of measuring AOD/T sometimes encounter difficulties as a result of cloud cover, high fluctuation, and an inadequate amount of data density (Sayer et al. 2020 ). Presello et al. (2022) and Mutawa et al. ( 2025 ) reported that methods such as random forests, support vector machines, and deep learning models are examples of techniques that are capable of rapidly evaluating enormous datasets that are created from ground-based measurements and satellite observations. Improvements in the accuracy and timeliness of forecasts have been brought about as a result of the success of these methods in addressing difficulties related to aerosol fluctuation and atmospheric interference. These capabilities have been demonstrated by recent breakthroughs. The use of machine learning has been implemented in order to improve the degree of resolution and quality of the data (Budach et al. 2022 ; Du et al. 2020 ). It has been utilized specifically for the purpose of improving AOD/T retrievals in areas that are frequently covered by clouds (Zhang et al. 2020 ). Furthermore, the implementation of ensemble learning approaches has resulted in improved prediction capacities, which has led to an improvement in the modeling of aerosol behavior across a wide range of environmental variables. Mirzael et al. (2023); Wang et al. ( 2025 ); Bhatti & Sun, ( 2025 ) reported their findings that the precision of AOD/T evaluations has been greatly improved as a result of the introduction of multispectral and multisource data into machine learning frameworks. This is absolutely necessary in order to acquire a comprehensive understanding of the effects that aerosols have on public health, air quality, and climate change. The application of machine learning to the study of aerosols offers the potential to intensely improve our understanding of the dynamics of aerosols, which will, in turn, have an impact on public health measures and efforts to address the effects of climate change (Li et al. 2022 ; Rahman et al. 2024 ). In order to advance monitoring systems and improve our understanding of aerosols and the complex interactions they have with the atmosphere, bibliometric visualization analysis has shown that there is a need for further studies in the aspect of AOD/T, as stated by Pippal et al. ( 2023 ). Particles in the atmosphere such as dust, smoke, and pollution can block sunlight by absorbing or scattering light. AOD/T tells us how much direct sunlight is prevented from reaching the ground by these aerosol particles, where higher AOD/T (e.g., 1) is hazy and lower AOD/T (e.g., 0.1 or lower) is clear sky (Provençal et al. 2017 ). Hu et al. ( 2024 ) conducted a thorough visualization analysis on CALIPSO-related aerosol research, yielding substantial insights into three research avenues with aerosol characteristics and classifications, their spatiotemporal distributions, and spatial heterogeneity along with influencing factors. Heating the atmosphere could cause precipitation and temperature extremes in North and South America and affect Arctic and Antarctic sea ice by causing unusual Rossby waves in each hemisphere (Yang et al. 2024 ). The current state of global development has resulted in a rising degree of environmental pollution. Currently, there is a significant concern regarding environmental pollution as it impacts various facets of our everyday existence (Lim et al. 2009 ). According to Ginoux et al. ( 2001 ), the GOCART model simulates dust aerosol distribution worldwide based on the idea that topographic depressions with exposed soil can be dust sources and that wind velocity and moisture levels affect uplift. The model overestimates dust transport from Asian sources to the North Pacific due to an overestimate of small particle emissions, but satellite and ground-based measurements show consistency. Yang et al. ( 2025 ) also conducted a comprehensive analysis of temporal patterns in PM2.5 concentrations in Grenada, an island with scant historical research on air quality trends, and observed a concentration that exhibited recurrent peaks and increases at the conclusion of the dry season and the onset of the rainy season annually, alongside a gradual upward trend over time. This bibliometric analysis of the Aerosol Optical Depth (AOD/T) study is to improve our understanding of aerosols and the global impact they have on human health and the environment. This was accomplished through a comprehensive utilization of cutting-edge technologies and techniques that can be applied across multiple disciplines. An attempt to integrate data acquired from numerous sources, such as satellites, ground-based monitoring stations, and aerial sensors, has been a key step forward for researchers in AOD/T study. This has been a significant step forward (Reshi et al. 2024 ; Lim et al. 2009 ; Wei et al. 2020 ). Annapurna et al. ( 2024 ), Zhou et al. ( 2023 ), and Ranjan et al. ( 2021 ) reported that in order to improve models that anticipate the behavior of aerosols throughout a variety of time periods, it is necessary to conduct a comprehensive global assessment of aerosols that are more precise and consistent, and harmonization of researchers is a better method that should be utilized in order to accomplish such enhancements. In order to compare data over time using the bibliometric analysis method, vital trends in aerosols on a worldwide basis were explored. Materials and methods Experimental and Technical Design Bibliographic analysis involves both quantitative and qualitative evaluations of documents sourced from a singular or multiple databases (Pippl et al. 2023; Semeniuk and Dastoor 2020 ; Bellouin et al. 2020 ; Huang et al. 2020 ; Li et al. 2021 ; Bauer et al. 2022 ). Research databases hold significant importance, with the Scopus database being the most frequently utilized by scholars (Zhu and Liu 2020 ). This study utilized the Scopus database to identify the publication trend of Aerosols Optical Depth/Thickness (AOD/T). Scopus encompasses a diverse array of academic literature, including peer-reviewed journals, conference proceedings, book series, and others. For the purpose of this study, articles and conferences were selected from the document type from 1960 to 2025 for a more comprehensive bibliometric analysis and in-depth study of AOD/T and to critically analyze the volume of articles over 5 decades. The meticulous source selection process employed by Scopus typically guarantees the integrity of the data provided. The content specialists at Scopus ensure the accuracy and quality of the data by implementing necessary adjustments. Scopus provides the capability to utilize advanced search parameters, including author, publication, affiliation, keyword, and citation. Citation metrics, accessible through Scopus and frequently utilized in bibliometric analyses, assess the influence and impact of research articles and their authors. The indicators encompass citation counts, h-index, and co-citation analysis. Analytics platforms and data visualization tools exemplify the integration of Scopus with various software and technologies, enhancing the processing and display of bibliometric data. A thorough search was carried out from the Scopus database to pinpoint research publications and cutting-edge reviews related to Aerosols Optical Depth or Aerosols Optical Thickness (AOD/AOT). The search keyword “TITLE-ABS-KEY (Aerosols optical Depth OR AOD OR Aerosols optical thickness) AND PUBYEAR > 1959 AND PUBYEAR < 2026” was used, and the language selected for this study was English. A total of 4,131 documents were initially. Selection was made to narrow the study to focus on the scope of the study and the trend of Aerosols Optical Depth/Thickness. Earth and planetary sciences, physics and astronomy, and environmental science documents, and English language were selected for this analysis of the documents. The documents were further sorted to 3,542. In the document type. After the selections and sorting, 3,542 documents were sorted, cleaned, and exported to Excel in CSV file format for the analysis. Several software programs were explored for thorough analysis of this study, which include VOSviewer version 1.6.20, which was used for the network and overlay and network visualization, and MapChart and Python version 3.13.5 were utilized. Results and discussion Analysis of Publication Trends In this bibliometric analysis, Fig. 1 b illustrates the trends in research interest over time, highlighting peaks that correspond with significant events and advancements from 1960 to 2025. From 1960 to 1980, it could be seen that in the year 1960, there was no publication until the early years in 1964 that show a relatively low level of research and publication activity, with only 2 publications, and also no publication in 1965 and 1966. Then, from 1967 through 1980, 8 publications were observed. There was a gradual and noticeable increase from 1980 through 1990, with the highest publication of 19 documents, which shows some research interest in the topic had begun within that decade. Scholars started to explore more specific aspects of the field, leading to a gradual increase in the number of publications from 8 to 19 in that decade. This study observed a spark rise in 1991 all through, suggesting a crucial moment in research activity. This peak could be attributed to significant advancements in methodologies, groundbreaking studies, and heightened awareness of the topic's implications in broader contexts. It also coincided with major conferences, papers, and publications that catalyzed further investigation. The highest publication year was observed in 2011 with a total of 162 documents. Though the interest in research and publication remains high, some years still experience a drop in the number of publications, indicating that the field has gained substantial grip. There were fluctuations from the latter years that show fluctuations in research interest, with a significant dip in 2012. This decline is linked to various factors, such as shifts in funding priorities, changes in research focus, and external events impacting academic activities. However, a rebound occurs in 2013, suggesting renewed interest and the emergence of new research questions that reignite academic engagement, with a drastic drop in 2024. Figure 1 c depicts the decadal global trend in publishing in a 10-year span. This transition occurred between the years 1960 and 2025. The significance of tackling issues such as smoke from wildfires, urban pollution, and the connection between aerosols and climate is brought into sharper focus by this increase. From the years 1960 to 1970 there were only 12 published documents, while from the year 1971 to 1980 there were 39 documents published. In the years 1981 to 1990, there were 114 publications, which signifies much interest in the topic in these years. The years 1991 to 2000 recorded 511 documents published. This has made it easier to gain a more profound understanding of the relationship that exists between these phenomena. An enormous amount of change has taken place in the field of AOD/T research from 2001 to 2010, with 1,183 published documents, which shows the decade with the highest number of publications. Similarly, from 2011 to 2020 there was a drop in the number to 1,221 documents published, and from 2021 to 2025 the number went down to 464, which suggests more studies need to be carried out for more understanding of the topic. The year 2011, which falls within the sixth decade, recorded the highest number of published documents, with 162 documents. There was a steady state of publication between the fifth (2001–2010) and the sixth (2011–2020) decades before a drop in the number of publications from 2020 to 2025. The significance of AOD/T in contemporary geoscience is highlighted by this bibliometric trajectory, which also suggests two potential paths that could be pursued for additional investigation. The fact that research on AOD/T is going from strength to strength is evidence of the major contribution it makes to addressing the urgent climate and environmental concerns that we are currently facing. Analysis of co-authorship The network visualization in Fig. 2 depicts the interwoven links between significant individuals in the field by their co-authorship patterns, emphasizing how collaboration drives scientific progress. Mapping these linkages enables the identification of prominent groups whose coordinated efforts frequently result in groundbreaking discoveries in the field of remote sensing. The network visualization depicts writers who frequently collaborate, forming tightly connected groups that affect research orientations in their respective areas. Figure 2 shows Nakajima, in the blue cluster, and Zhang, in the red cluster, linking many other authors, with Holben and Brent N. in the yellow cluster linking other authors, showing a strong co-authorship with robust co-authorship relationships, which usually indicate dependable collaborations, in which combined knowledge stimulates innovation and elevates the quality of published research. Furthermore, these links highlight knowledge-sharing hubs, where significant authors connect distinct research clusters, facilitating the flow of ideas across disciplines. Through the analysis of these links, we can see how scientific discoveries result from collaborative efforts rather than lone ones, emphasizing the importance of teamwork in the progression of knowledge. This network visualization designed by VOSviewer is used as a strategic tool to find possible collaborators, improve ecosystems, and forecast future areas of growth. Analysis by Countries A total of one hundred twenty-eight (128) countries were sorted in the research field. The results of this study showed that the United States of America has the most documents published as retrieved from the Scopus database, with 1,202 documents and 73,523 citations, followed by China, having 518 documents with 10,230 citations; France, having 419 documents with 25,370 citations; Germany, having 376 documents with 17,013 citations; and Japan, having 371 documents with 10,884 citations. Table 1 shows the top 20 countries with the highest documents and citations by percentage from this study. Figure 3 depicts the map chart of the top 20 countries with the highest number of published documents, highlighting the United States of America as the leading country in terms of annual publications among the countries. The map chart presented in Fig. 3 illustrates the international collaboration in research that has taken place between 71 countries after selecting a minimum of 3 documents per country from the total of 1,202 countries, with each country contributing a minimum of 3 papers. The map chart clearly shows the distribution and the size of the label that the United States of America demonstrated the most robust collaborative efforts across national boundaries, followed by China, France, Germany, and Japan. The quantity of research that has been conducted on AOD/T by various nations is to a substantial degree distinct from one another. Based on this comprehensive bibliometric research, it was determined that 118 countries produced contributions to the subject matter between the years 1960 and 2025. From Table 1 , the United States of America tops with 1,202 documents (23.69%), followed by China with 518 documents (10.21%), followed by France with 419 documents (8.26%). Germany and Japan are fourth and fifth with 376 (7.41%) and 371 (7.31%). As seen in this study, one of the reasons why the United States of America has been able to make such rapid advancements is because of its commitment to enhancing its satellite capabilities and lowering the amount of air pollution in the country. Figure 3 displays the annual publishing patterns on a MapChart, which shows that the United States continues to maintain its position on this topic. This is especially true after the year 2010, when AOD research became a key topic of discussion in climate policy discussions. As can be seen in Fig. 3 , the United States of America plays a crucial part in a complex network of alliances that spans the entire world, which adds to the significance of the country. There are strong linkages to the global integration of these countries of higher publications on AOD/T. These relationships, which commonly center on similar themes such as the transboundary transport of aerosols and the influence of climate change on local climates, are a demonstration of the collaborative and multidisciplinary nature of the work that is being done in this sector. Table 1 Top 20 countries with the most documents published in the retrieved papers Ranking Country Number of Documents % 1st United States 1202 23.69 2nd China 518 10.21 3rd France 419 8.26 4th Germany 376 7.41 5th Japan 371 7.31 6th Italy 194 3.82 7th Russian Federation 181 3.57 8th United Kingdom 171 3.37 9th Netherlands 129 2.54 10th India 121 2.38 11th South Korea 109 2.15 12th Spain 109 2.15 13th Greece 101 1.99 14th Poland 74 1.46 15th Switzerland 64 1.26 16th Canada 58 1.14 17th Finland 57 1.12 18th Israel 55 1.08 19th Australia 53 1.04 20th Brazil 49 0.97 Table 2 shows the United States having 73,523 citations, with 35.45% of the top 20 countries with the highest citations in this study. The table also shows France second, having 25,370 number of citations with 12.23%; Germany having 17,013 number of citations with 8.26%; and Japan having 10,884 number of citations with 5.25%. China is the fifth country with 10,230 citations, with 4.93%. The United States of America, China, Germany, France, Japan, and Italy, as well as the United Kingdom and the other top 20 countries listed in Table 2 , have all established significant partnerships through their respective countries. Figure 4 points to the various deficiencies, as seen from the map chart, where countries in Africa and certain portions of Southeast Asia continue to be underrepresented, despite the fact that substantial aerosol-related issues have been addressed. As a result of this imbalance, concentrated efforts are required in order to improve equal involvement in research on AOD in such regions. Table 2 Top 20 countries with the highest citations from the published documents in the retrieved papers Ranking Country Number of Citations % 1st United States 73523 35.45 2nd France 25370 12.23 3rd Germany 17013 8.20 4th Japan 10884 5.25 5th China 10230 4.93 6th Italy 7386 3.56 7th United Kingdom 5802 2.80 8th Netherlands 5571 2.69 9th Switzerland 5072 2.45 10th South Korea 4286 2.07 11th Spain 3500 1.69 12th Greece 3216 1.55 13th Canada 2997 1.45 14th Israel 2638 1.27 15th Finland 2410 1.16 16th Russian Federation 2141 1.03 17th Poland 2095 1.01 18th India 1871 0.90 19th Brazil 1564 0.75 20th Australia 1529 0.74 Analysis by Organizations Twenty (20) organizations were considered to be the most productive in this study, as listed in Table 3 . A minimum of 4 documents were selected from an organization of which 460 organizations met the thresholds of the total number of documents published. The top 20 organizations published a total of 447 documents, of which 74 were published in the NASA Goddard Space Flight Center, Greenbelt, MD, United States, which was the bulk of the documents, with 7,380 citations. NASA Goddard Space Flight Center, Greenbelt, MD 20771, and NASA Langley were also listed as the second and third most productive organizations, with a total of 61 and 33 publications with 6,778 and 1,644 citations. From Table 3 , it shows that from the study, though some documents were cited more than some documents, as seen in the 6th and 7th documents having more citations compared to the 5th document published from that organization. The table shows most of the organizations coming from NASA, which indicates NASA contributions and support in the field of research for aerosol optical depth/thickness in relation to the atmosphere, as NASA is one of the leading organizations concerned with the study and research about the atmosphere and the entire globe. Figure 5 depict the comprehensive overlay visualization of the different organizations showing both strong and weak connections between organizations with the thick and thin lines of different colours. Table 3 Top 20 organizations with the highest number of publications. Ranking Organizations Documents Citations 1st Nasa Goddard Space Flight Center, Greenbelt, Md, United States 74 7380 2nd Nasa Goddard Space Flight Center, Greenbelt, Md 20771, United States 61 6778 3rd Nasa Langley Research Center, Hampton, Va, United States 33 1644 4th Leibniz Institute For Tropospheric Research, Leipzig, Germany 24 1395 5th University Of Chinese Academy Of Sciences, Beijing, 100049, China 24 398 6th Jet Propulsion Laboratory, California Institute Of Technology, Pasadena, Ca, United States 20 1585 7th Laboratory For Atmospheres, Nasa Goddard Space Flight Center, Greenbelt, Md, United States 20 2129 8th National Institute For Environmental Studies, Tsukuba, Japan 19 565 9th Earth System Science Interdisciplinary Center, University Of Maryland, College Park, Md, United States 18 863 10th Institute Of Environmental Physics, University Of Bremen, Bremen, Germany 16 599 11th Laboratory For Atmospheres, Nasa Goddard Space Flight Center, Greenbelt, Md 20771, United States 16 5084 12th Nasa Ames Research Center, Moffett Field, Ca, United States 16 1024 13th Nasa Goddard Institute For Space Studies, New York, Ny 10025, 2880 Broadway, United States 15 1232 14th Nasa Goddard Institute For Space Studies, New York, Ny, United States 15 560 15th Science Systems And Applications Inc., Lanham, Md, United States 14 3988 16th Department Of Land Surveying And Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong 13 327 17th National Center For Atmospheric Research, Boulder, Co, United States 13 629 18th Department Of Atmospheric Sciences, University Of North Dakota, Grand Forks, Nd, United States 12 421 19th Department Of Computing, London Metropolitan University, London N7 8Db, 166–220 Holloway Road, United Kingdom 12 142 20th Marine Meteorology Division, Naval Research Laboratory, Monterey, Ca, United States 12 665 Analysis of Citations In accordance with the findings of the citation analysis, the selected articles were found to have a total of 123,504 citations, with the highest citation count of 2,682. Citations ranging from 0 to 2,682 were discovered. Out of the total of 3,542 articles that were found, there were a total of 521 that were found with no citations at the time of this study, whereas 2,762 publications were able to successfully accumulate from 1 to 100 citations, and likewise 259 had a number of citations from 101 to 2,682 citations recorded. There was a total of 19,554 citations that were accumulated by the top 20 publications. Table 4 shows the total number of citations for the study as 2,682. Remer L.A. et al. is the author with the highest citation for the paper titled “The MODIS aerosol algorithm, products, and validation,” followed by Ginoux P. et al. with 1,657 citations for the paper titled “Sources and distributions of dust aerosols simulated with the GOCART model” and other authors. The astounding total of 123,504 citations has proven the significant influence and significance of AOD studies in the advancement of climate science, the evaluation of air quality, and the improvement of public health. The citation range, which extends from 0 to 2,682 terms, is illustrative of the differences that exist in the impact that academic research has. It is possible that the specialist nature of these topics or the relatively recent publication dates of these works contributed to the fact that 512 of these works were not cited. While on the other hand, 259 of these noteworthy papers each garnered more than one hundred citations. While there were some documents that are not cited, the citation metrics demonstrate the overall influence as well as trends in the impact of AOD/T research as shown in Fig. 6 . Table 4 Top 20 Authors and Titles of the Papers, Year, Source, and Number of Citations Ranking Author Title Year Source Title Cited by 1st Remer L.A. et al The MODIS aerosol algorithm, products, and validation 2005 Journal of the Atmospheric Sciences 2682 2nd Ginoux P. et al Sources and distributions of dust aerosols simulated with the GOCART model 2001 Journal of Geophysical Research Atmospheres 1657 3rd Gordon H.R and Wang M. Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with seawifs: A preliminary algorithm 1994 Applied Optics 1615 4th Kaufman Y.J et al Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer 1997 Journal of Geophysical Research Atmospheres 1564 5th Chin M. et al Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements. 2002 Journal of the Atmospheric Sciences 1203 6th Hsu N.C. et al Aerosol properties over bright-reflecting source regions 2004 IEEE Transactions on Geoscience and Remote Sensing 1101 7th Hsu N.C. et al Enhanced Deep Blue aerosol retrieval algorithm: The second generation ion 2013 Journal of Geophysical Research Atmospheres 934 8th King M.D. et al Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from the Moderate Resolution Imaging Spectrometer (MODIS) 1992 IEEE Transactions on Geoscience and Remote Sensing 906 9th Kaufman Yoram J. et al MODIS 2.1-µm channel – correlation with visible reflectance for use in remote sensing of aerosol 1997 IEEE Transactions on Geoscience and Remote Sensing 838 10th Wang J. and Christopher S.A. Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies 2003 Geophysical Research Letters 827 11th Tanré D. et al Remote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiradiances ances 1997 Journal of Geophysical Research Atmospheres 818 12th Baret F. et al LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm 2007 Remote Sensing of Environment 693 13th Husar R.B. et al Characterization of tropospheric aerosols over the oceans with the NOAA advanced very high resolution radiometer optical thickness operational product 1997 Journal of Geophysical Research Atmospheres 645 14th Hsu N.C.et al Deep Blue retrievals of Asian aerosol properties during ACE-Asia 2006 IEEE Transactions on Geoscience and Remote Sensing 641 15th King M.D. et al Spatial and temporal distribution of clouds observed by MODIS onboard the terra and aqua satellites 2013 IEEE Transactions on Geoscience and Remote Sensing 611 16th Mishchenko M.I. et al Modeling phase functions for dustlike tropospheric aerosols using a shape mixture of randomly oriented polydisperse spheroids 1997 Journal of Geophysical Research Atmospheres 579 17th Tegen I. and Fung I. Modeling of mineral dust in the atmosphere: sources, transport, and optical thickness 1994 Journal of Geophysical Research 577 18th Kinne S. A. et al An AeroCom initial assessment – Optical properties in aerosol component modules of global models 2006 Atmospheric Chemistry and Physics 564 19th Gupta P.et al Satellite remote sensing of particulate matter and air quality assessment over global cities 2006 Atmospheric Environment 561 20th Main-Knorn M. et al Sen2Cor for sentinel-2 2017 Proceedings of SPIE – The International Society for Optical Engineering 538 Analysis of Journals Based on their level of output, the 20 most productive journals in this study are listed in Table 5 . The top 20 journals published a total of 1,686 papers, which is equivalent to 84.3% of the total number of documents published and an average citation of 98.61 with a Q1 quartile. There were 280 publications that were published in the Journal of Geophysical Research Atmospheres, which was the bulk of the documents. Utilizing a total of 205 publications, Atmospheric Chemistry and Physics was ranked as the second most prolific publication, followed by Atmospheric Environment with 114 publications and Atmospheric Measurement Techniques with 114 publications as well, but with different numbers of citations, as seen in Table 5 . Figure 7 listed all the journals recognized as significant contributors to the field of AOD/T research, with thick colors of red, blue, green, and yellow showing the strong connection of relationships of journals on this research topic. The multidisciplinary aspect of AOD/T research in climate science is underscored by the Journal of Geophysical Research: Atmospheres 41 ranking third. The prevalence of these papers signifies an increasing emphasis on research pertinent to policy, particularly in climate modeling, air quality applications, and remote sensing. AOD/T significantly influences atmospheric science and environmental policy, as demonstrated by the extensive research and high citation rates associated with the topic. The observations indicate both similarities and shifts in focus within the studies published in these reputable journals concerning AOD/T. The primary subjects of articles in Atmospheric Environment and Remote Sensing of Environment illustrate significant progress in observational technology. This body of research primarily addresses the integration of data from multiple sensors, validation techniques, and AOD/T retrieval methods. The significance of AOD/T in radiative forcing, aerosol-cloud interactions, and climate feedback mechanisms is emphasized in the Journal of Geophysical Research Atmospheres and Atmospheric Chemistry and Physics. The prevalence of journals with high impact factors indicates a rigorous peer review process, as most of the journals are in the Q1 quartile as indicated in Table 5 ; only for applied optics, the International Journal of Remote Sensing, Atmosphere, and others are in Q2, and atmospheric and ocean physics in Q3 as of the time of this study, which depicts the quality of the topic and the necessity for establishing a foundation for further research on the societal and environmental effects of AOD/T. Figure 8 illustrates the bar chart of the distribution of the journals and their numbers of publications and citations for more understanding of the top 20 journals that make the top contributions in this study, showing the Journal of Geophysical Research Atmospheres with 280 documents and 27,610 citations as the highest and Izvestiya - Atmospheric and Ocean Physics with 22 documents and 140 citations as the lowest among the top 20 journals with significant contributions in the documents published and cited of all the journals in this topic. Table 5 Top 20 journals and the quartile from the retrieved papers Ranking Sources Documents Citations Avg. citations SNIP SJR SJR Year Quartile 1st Journal of Geophysical Research Atmospheres 280 27610 98.61 1.13 1.55 2024 Q1 2nd Atmospheric Chemistry and Physics 205 10046 49.00 1.41 2.11 2024 Q1 3rd Atmospheric Environment 114 4877 42.78 1.15 1.21 2024 Q1 4th Atmospheric Measurement Techniques 114 3347 29.36 1.34 1.31 2024 Q1 5th Geophysical Research Letters 112 6616 59.07 1.40 4.82 2024 Q1 6th Applied Optics 107 6518 60.92 0.80 0.45 2024 Q2 7th International Journal of Remote Sensing 97 2880 29.69 0.85 0.68 2024 Q2 8th Remote Sensing 89 1634 18.36 1.30 1.02 2024 Q1 9th Remote Sensing of Environment 80 6888 86.10 3.28 3.97 2024 Q1 10th Atmospheric Research 79 1551 19.63 1.34 1.44 2024 Q1 11th Journal of Geophysical Research: Atmospheres 74 3541 47.85 1.13 1.55 2024 Q1 12th Ieee Transactions on Geoscience and Remote Sensing 60 6116 101.93 2.37 2.40 2024 Q1 13th Journal of Aerosol Science 55 307 5.58 1.20 0.82 2024 Q1 14th Journal of Quantitative Spectroscopy and Radiative Transfer 47 2009 42.74 1.19 0.68 2024 Q1 15th Journal of the Atmospheric Sciences 41 6609 161.20 1.11 1.68 2024 Q1 16th Atmosphere 32 310 9.69 0.80 0.63 2024 Q2 17th Tellus, Series B: Chemical and Physical Meteorology 26 1429 54.96 0.95 1.01 2024 Q2 18th Icarus 26 972 37.38 1.09 1.06 2024 Q1 19th Journal of the Meteorological Society of Japan 26 762 29.31 0.94 1.12 2024 Q2 20th Izvestiya - Atmospheric and Ocean Physics 22 140 6.36 0.46 0.26 2024 Q3 Co-occurrence analysis In order to develop the co-occurrence network, we identified the most significant research paths and difficulties that are essential for monitoring the progression of scientific knowledge. A total of 132 detected terms were arranged into three unique clusters, as shown in Fig. 7 . These terms had a minimum recurrence of over 50 in titles and abstracts. The terms that are associated with aerosol proper are linked with air pollution, burning mass, and optical depth in the blue cluster. The relationship between aerosols and cloud cover in the green cluster and the aerosol linking to black carbon, remote sensing, cloud optical thickness, and air pollution risk in the red cluster are prominently featured on the map. Analysis of keywords For this study, keywords serve as concise markers of the subject content. Figure 9 clearly shows how research hotspots, fundamental links, and domain-precise frontiers are brought to light by the frequency, relevance, and emergence of concepts. Scientific vocabulary like “aerosols,” “air quality,” “climate change,” and “health impacts” shows the scientific community’s focus on specific research areas and its goals. Larger network map nodes represent more commonly used words, and higher keyword frequency is often associated with important literature topics. This bibliometric mapping has illuminated several scientific topics. This category covers aerosol optical depth (AOD/AOT) and public health, climate change, and pollution reduction. Figure 10 depicts aerosol as the highest occurring keyword, and aerosols as used by different authors. This analysis shows how important AOD/AOT research areas have grown over time. The growing importance of satellite-based data and interest in aerosol-cloud interactions are highlighted. Moreover, this bibliometric analysis enhances understanding of the inherent connections among various research topics within the realm of AOD/AOT. Lines in the network map in Fig. 9 illustrate the frequency with which terms appear together in the same study for keyword co-occurrence. The thickness of these lines serves as an indicator of the strength of the correlation, providing a visual representation of the interconnections among different areas of research. Conclusion This study utilizes an in-depth bibliometric visualization analysis approach to examine existing research on aerosols optical depth/thickness (AOD/AOT), with the scope of identifying key trends, gaps, and future prospects. Previous studies have primarily focused on the predictions, particulate matter, radiative characteristics, classification of aerosols, their spatiotemporal distribution patterns, and the underlying reasons for aerosol variability. There have been significant study advancements, but there is a need for additional thorough investigation. This study explored Scopus data to create network visualizations for the analysis of citation networks, author collaborations, organizational contributions, influence of countries, and keyword co-occurrences and documents published over five decades. We focused on retrieved documents from the Scopus database with the search key TITLE-ABS-KEY (Aerosols optical Depth OR AOD OR Aerosols optical thickness) AND PUBYEAR > 1959 AND PUBYEAR < 2026 on the topic of aerosol optical depth/thickness between 1960 and 2025. A total of 4,131 documents were initially generated. Selections from articles and conferences were selected on the document type for a more comprehensive analysis. Filtering from Earth and planetary sciences, physics and astronomy, and environmental science documents. 3,542 documents were sorted and used for the analysis. Due to the volume of the documents, we explored VOSviewer version 1.6.20, Python version 3.13.5, and MapChart for the analysis. The analysis reveals that the United States of America has 1,202, 35.86% (73,523); China 518, 14.62% (10,230); France 419, 11.83% (25,370); Germany 376, 10.62% (17,013); and Japan 371, 10.47% (10,888) papers published and citations, respectively. NASA Goddard Space Flight Center, Greenbelt, MD, United States, was the journal with the highest number of papers published, with 74 documents and 7,380 citations. The most common occurring terms are aerosols, aerosol optical depth/thickness, and air quality. It was observed that Remer L.A. et al. is the author with the highest citation for the paper titled “The MODIS aerosol algorithm, products, and validation,” followed by Ginoux P. et al. with 1,657 citations for the paper titled “Sources and distributions of dust aerosols simulated with the GOCART model.” Based on our knowledge and recent studies, this study was novel for being the first bibliometric analysis based on aerosol optical depth/thickness that used data retrieved from Scopus for visualization and network mapping. Identifying a drastic drop in 2020, with an upward and downward trend between the years 2021, 2022, 2023, and 2024, there is a need for researchers to continue to investigate immensely on aerosol optical depth/thickness for better understanding of the vast growing global climatic change and weather dynamics. Limitations and Future Direction Though few studies show that there are a variety of methods and technological improvements that are being applied in order to improve the accuracy, scalability, and usefulness of measurements of aerosol optical depth (AOD). It is essential to incorporate AOD/AOT data from a variety of sources, including satellites, ground-based surveys, and airborne sensors, in order to enhance the method by which aerosols are evaluated on a global scale. The harmonization of health effect assessments, climate forecasts, and air quality management has the potential to significantly enhance these areas by addressing data gaps and making it better to simulate aerosol behavior with better precision. A number of different aerosols, including black carbon, sulfates, and organic compounds, are areas that need more studies to get a deeper comprehension of the ways in which pollutants can have an impact on human health, notably respiratory and cardiovascular issues. This will enhance the effectiveness of public health interventions and mitigation efforts by enhancing the connection between aerosol exposure and specific sources of pollution. In-depth assessments of aerosol attributes, such as particle size, shape, and composition, should be explored using machine learning, which can contribute to an improvement in our understanding of how aerosol optical depth relates to the environments and climatic change. The World Meteorological Organization (WMO) and a number of other organizations are participating in projects such as the Global Atmosphere Watch (GAW), which are aimed at enhancing the flow of data across countries and regions, as well as providing standardized standards for the reporting of aerosol optical depth (AOD/AOT). The implementation of uniformity in the creation of AOD/AOT measurements and reporting systems is absolutely necessary in order to evaluate the progress that nations have achieved in achieving their climate goals. Through the use of advanced machine learning algorithms, it is possible to sift through mountains of data about aerosol optical depth (AOD/AOT), discover trends, and develop models in order to forecast how particles will react to particular meteorological circumstances. The evaluations of air quality will be improved, and legislators will be able to make decisions based on reliable evidence with the assistance of these technologies. Declarations Acknowledgement The authors will like to acknowledge the School of Physics, Universiti Sains Malaysia for providing all the available resources in making this study successful. Funding statement The authors declare that no funds, grants, or other support were received during the preparation of this manuscript Author Contributions Conception and design were done by Emmanuel Yohanna and Hwee San Lim. Materials preparation, data collection and analysis were performed by Emmanuel Yohanna and Hwee San Lim . 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Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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5","display":"","copyAsset":false,"role":"figure","size":238216,"visible":true,"origin":"","legend":"\u003cp\u003eOverlay visualization of different organizations\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7763043/v1/1f2dfb7272491161a607f7ce.jpeg"},{"id":96925893,"identity":"4350499c-6b62-4bd3-912c-f4daf5f166fc","added_by":"auto","created_at":"2025-11-27 14:24:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":110649,"visible":true,"origin":"","legend":"\u003cp\u003eTop 20 authors and the number of citations and years\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7763043/v1/2839a2a23dce4211910e4d34.png"},{"id":97135987,"identity":"1a0c99ac-d530-4914-b2cf-59f4ced333e3","added_by":"auto","created_at":"2025-12-01 09:54:51","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":168716,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork visualization of journals and interrelationships.\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7763043/v1/5179153d18e7bf302739877b.jpeg"},{"id":96925903,"identity":"2bdbc26b-845a-4805-9fc7-454429c9e108","added_by":"auto","created_at":"2025-11-27 14:24:56","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":102464,"visible":true,"origin":"","legend":"\u003cp\u003eTop 20 journals with highest publications and citations\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7763043/v1/a3b0d48d86f8cb95febe62e0.png"},{"id":96925753,"identity":"afc194ac-f545-4904-bf6f-4b27b7138359","added_by":"auto","created_at":"2025-11-27 14:24:54","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":818059,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurring keywords from the retrieved papers\u003c/p\u003e","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7763043/v1/16567cc68c5d9f64f3b5d42b.jpeg"},{"id":96925759,"identity":"22d5a84a-d991-44bb-9066-d60c4cdd13cb","added_by":"auto","created_at":"2025-11-27 14:24:54","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":184302,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of occurrences of the retrieved keywords\u003c/p\u003e","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7763043/v1/c22e1c0674f6c1aeeb817b89.png"},{"id":105035896,"identity":"69a58ca4-00b8-4a9f-a432-acdf4fba0c95","added_by":"auto","created_at":"2026-03-20 07:26:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3570994,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7763043/v1/b804f78f-0336-4a92-8994-2d8159b72f8b.pdf"}],"financialInterests":"","formattedTitle":"In-depth bibliometric analysis of over five decades of Aerosol Optical Depth revealing trends, key contributors, and new research directions.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOver the course of the past centuries, scientists have shown a great deal of interest in aerosols, which are tiny particles that are suspended in the air (Hinds et al., 2022; Zhang, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Anderson et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This interest has been particularly focused on those scientists who are concerned with climate change and public health. At the end of the nineteenth century, a scientist named John Aitken used the term \"aerosol\" to describe the minute, invisible particles that have a significant influence on the weather, climate, and the health of humans (Folch, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The size of these particles, which can range from a few micrometers to tens of nanometers, has an effect on how they interact with solar radiation and how they behave in the atmosphere (Wijeratne, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is possible to make aerosols in two different ways, either naturally or artificially. Pollen and mineral dust are examples of biological particles that come from natural sources (Huffman et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Other natural sources include volcanic eruptions and aerosols from the ocean. In contrast, secondary aerosols are produced as a result of human activities such as the combustion of biomass, the emission of exhaust from automobiles, and industrial processes (Munsif et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Luo et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Recent studies have highlighted the importance of knowing aerosols, particularly their dual role as both cooling and warming agents (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Aerosols are a challenging topic in conversations about climate change (Mondal et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and recent research has highlighted the need to understand them. For the purpose of illustrating this concept, some aerosols contribute to an increase in temperature by reflecting sunlight, whereas others contribute to an increase in temperature by absorbing heat (Sokhi et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To properly evaluate the effects that aerosols have on public health, it is essential to have a solid understanding of their origins and the repercussions they have. This is especially true in urban areas, where high concentrations of aerosols can result in a major decline in air quality (Hinds et al. 2022). As a consequence of this, it is essential to continue study into the origins and effects of aerosols in order to create efficient methods for preventing the adverse impacts that aerosols have on both the environment and human health.\u003c/p\u003e\u003cp\u003eYu et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) stated that, as a result of recent developments in aerosols research, these constituents have been divided into primary and secondary groups, according to the sources from which they originate and the methods by which they are manufactured. Primary aerosols are naturally occurring particles that are released into the atmosphere. Some examples of primary aerosols include mineral dust, sea spray, smoke from wildfires, and volcanic ash. Chemical reactions that result in the development of secondary aerosols are responsible for the generation of sulfate aerosols (Liu et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These events take place when gases that are emitted by human activities, specifically sulfur dioxide from industrial processes, experience chemical reactions (World Health Organization, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This category has made it easier to make progress in the study of the behavior of aerosols (Hinds et al. 2022; Feng et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), particularly with regard to the effects that aerosols have on precipitation, cloud formation, and regional climate systems (L\u0026oacute;pez-Romero et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Recent research has shown that both forms of aerosols have a significant impact on the global radiation balance, which in turn contributes to the cooling and warming impacts that make climate modeling more difficult (Akinyoola et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Irfan et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) reported that black carbon is a primary aerosol. When black carbon is deposited on polar ice, it reduces the reflectivity of the ice and contributes to the warming of the planet by absorbing sunlight (Zhu et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As the amount of literature continues to grow, it is becoming increasingly clear that it is necessary to monitor and comprehend the dynamics of aerosols in relation to climate systems and public health (Liu et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Shen et al. (2023) and Mathew et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) reported that as urbanization increases, the impacts of aerosols on air quality and human health become more pronounced. As a result, it is necessary to develop a comprehensive approach to the research of these particles that takes into account the various forms of aerosols and the interactions they have with the environment.\u003c/p\u003e\u003cp\u003eAs part of the process of determining how aerosols influence the dynamics of radiation and climate, the Aerosol Optical Depth/Thickness (AOD/T) is a significant statistic that is taken into consideration (Jin et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The reduction in sunlight intensity that is induced by aerosol scattering and absorption is quantified by this metric, which also serves as a dimensionless measure of atmospheric aerosol loading (Jadhav et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In addition, this metric provides a quantitative depiction of the problem. The advancement of remote sensing technology, in particular satellite-based observations, has significantly facilitated our capacity to monitor AOD/T on a global scale (Ranjan et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This capability has been significantly enhanced. For the purpose of determining the dispersion of aerosols, the Sentinel-5P satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) from the National Aeronautics and Space Administration (NASA) both provide highly important data (Reshi et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yilmaz et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to Sogacheva et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), validating satellite observations and providing information on the localized AOD/T, solar photometers, and other ground-based sensors are absolutely necessary. Measurements of AOD/T that are more exact have the potential to improve our understanding of the impact that aerosols have on the quantity of solar energy that is produced as well as climate systems, as indicated by the findings of recent research as reported by Dumka et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Fountoulakis et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMeasurement of AOD/T is required in order to acquire an understanding of the impact that aerosols have on the energy balance of the Earth through the processes of light extinction and absorption. This understanding is vital in order to find out how aerosols affect the energy balance of the Earth. The amount of solar radiation that reaches the surface of the Earth can be altered by aerosols through the processes of absorption and deflection (Spiridonov et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2025\u003c/span\u003e and Stieglitz et al. 2024). The interaction has the potential to have an effect on a variety of phenomena, including shifts in the global temperature, alterations in weather patterns, and the phenomenon of cloud formation. This is due to the fact that particulate matter is an essential statistic for studying the impact of aerosols on a wide range of scales, including regional air quality evaluations and global climate models (Van Donkelaar et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWith regard to the utilization of renewable energy sources, a significant amount of focus has been placed on gaining an understanding of the connection that exists between AOD/T and the dynamics of climate (Schmale et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). There are a number of essential characteristics that are included in the formula for \u0026Aring;ngstr\u0026ouml;m turbidity, which is utilized in the calculation of AOD/T. These parameters have an effect on the solar spectrum as well as the efficiency of solar panels (Annapurna et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Jin et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Jadhav et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Recent studies (Spiridonov et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Dangayach and Pandey, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kouklaki et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) have shown that changes in spectrum irradiance, which are regulated by AOD/T, can drastically diminish the amount of electricity that photovoltaic (PV) systems are able to release into the environment. Kaufman et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) reported that aerosol models demonstrate the impact of multiple-scattering effects. The estimation of phytoplankton-pigment concentration and aerosol thickness yields errors of less than 20% and 10%, respectively. Photovoltaic systems are able to generate electricity by converting sunlight into electricity. The importance of keeping this in mind cannot be overstated, especially during times of extreme weather, such as when dust storms or wildfires are occurring. Based on the findings of the studies by (Li et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Isaza et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mammadov et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), it was determined that a decrease in AOD/T could result in some percent reduction in the amount of solar energy that is produced. On the other hand, this is especially true for solar systems that have a high efficiency in addition to a high sensitivity to changes in the spectral distribution of light. Remer et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) stated that daily observations of Earth from 0.41 to 15 \u0026micro;m are provided by NASA's Terra and Aqua satellites' Moderate Resolution Imaging Spectroradiometer. Reflected spectral solar flux and optical thickness at various wavelengths are examples of land aerosol products. These measurements over land and ocean determine the optical thickness and size of aerosols. The optical thickness of ocean aerosols is measured in seven wavelengths, along with effective radius and other aerosol data. MODIS aerosol retrievals are within expected uncertainty limits, according to validation using Aerosols Robotic Network (AERONET) data from 132 stations. Reducing aerosol radiative forcing uncertainties is necessary to comprehend the effects on the global climate, and MODIS aerosol data accuracy makes this possible.\u003c/p\u003e\u003cp\u003eRecent developments in aerosol research have demonstrated that the application of machine learning techniques can considerably improve the efficiency of AOD/T retrievals and monitoring (Tian et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yu et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Traditional methods of measuring AOD/T sometimes encounter difficulties as a result of cloud cover, high fluctuation, and an inadequate amount of data density (Sayer et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Presello et al. (2022) and Mutawa et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) reported that methods such as random forests, support vector machines, and deep learning models are examples of techniques that are capable of rapidly evaluating enormous datasets that are created from ground-based measurements and satellite observations. Improvements in the accuracy and timeliness of forecasts have been brought about as a result of the success of these methods in addressing difficulties related to aerosol fluctuation and atmospheric interference. These capabilities have been demonstrated by recent breakthroughs. The use of machine learning has been implemented in order to improve the degree of resolution and quality of the data (Budach et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Du et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It has been utilized specifically for the purpose of improving AOD/T retrievals in areas that are frequently covered by clouds (Zhang et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, the implementation of ensemble learning approaches has resulted in improved prediction capacities, which has led to an improvement in the modeling of aerosol behavior across a wide range of environmental variables. Mirzael et al. (2023); Wang et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2025\u003c/span\u003e); Bhatti \u0026amp; Sun, (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) reported their findings that the precision of AOD/T evaluations has been greatly improved as a result of the introduction of multispectral and multisource data into machine learning frameworks. This is absolutely necessary in order to acquire a comprehensive understanding of the effects that aerosols have on public health, air quality, and climate change. The application of machine learning to the study of aerosols offers the potential to intensely improve our understanding of the dynamics of aerosols, which will, in turn, have an impact on public health measures and efforts to address the effects of climate change (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rahman et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In order to advance monitoring systems and improve our understanding of aerosols and the complex interactions they have with the atmosphere, bibliometric visualization analysis has shown that there is a need for further studies in the aspect of AOD/T, as stated by Pippal et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Particles in the atmosphere such as dust, smoke, and pollution can block sunlight by absorbing or scattering light. AOD/T tells us how much direct sunlight is prevented from reaching the ground by these aerosol particles, where higher AOD/T (e.g., 1) is hazy and lower AOD/T (e.g., 0.1 or lower) is clear sky (Proven\u0026ccedil;al et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Hu et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) conducted a thorough visualization analysis on CALIPSO-related aerosol research, yielding substantial insights into three research avenues with aerosol characteristics and classifications, their spatiotemporal distributions, and spatial heterogeneity along with influencing factors. Heating the atmosphere could cause precipitation and temperature extremes in North and South America and affect Arctic and Antarctic sea ice by causing unusual Rossby waves in each hemisphere (Yang et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The current state of global development has resulted in a rising degree of environmental pollution. Currently, there is a significant concern regarding environmental pollution as it impacts various facets of our everyday existence (Lim et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). According to Ginoux et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), the GOCART model simulates dust aerosol distribution worldwide based on the idea that topographic depressions with exposed soil can be dust sources and that wind velocity and moisture levels affect uplift. The model overestimates dust transport from Asian sources to the North Pacific due to an overestimate of small particle emissions, but satellite and ground-based measurements show consistency. Yang et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) also conducted a comprehensive analysis of temporal patterns in PM2.5 concentrations in Grenada, an island with scant historical research on air quality trends, and observed a concentration that exhibited recurrent peaks and increases at the conclusion of the dry season and the onset of the rainy season annually, alongside a gradual upward trend over time.\u003c/p\u003e\u003cp\u003eThis bibliometric analysis of the Aerosol Optical Depth (AOD/T) study is to improve our understanding of aerosols and the global impact they have on human health and the environment. This was accomplished through a comprehensive utilization of cutting-edge technologies and techniques that can be applied across multiple disciplines. An attempt to integrate data acquired from numerous sources, such as satellites, ground-based monitoring stations, and aerial sensors, has been a key step forward for researchers in AOD/T study. This has been a significant step forward (Reshi et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lim et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Wei et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Annapurna et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), Zhou et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and Ranjan et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that in order to improve models that anticipate the behavior of aerosols throughout a variety of time periods, it is necessary to conduct a comprehensive global assessment of aerosols that are more precise and consistent, and harmonization of researchers is a better method that should be utilized in order to accomplish such enhancements. In order to compare data over time using the bibliometric analysis method, vital trends in aerosols on a worldwide basis were explored.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eExperimental and Technical Design\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBibliographic analysis involves both quantitative and qualitative evaluations of documents sourced from a singular or multiple databases (Pippl et al. 2023; Semeniuk and Dastoor \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bellouin et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Huang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bauer et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Research databases hold significant importance, with the Scopus database being the most frequently utilized by scholars (Zhu and Liu \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study utilized the Scopus database to identify the publication trend of Aerosols Optical Depth/Thickness (AOD/T). Scopus encompasses a diverse array of academic literature, including peer-reviewed journals, conference proceedings, book series, and others. For the purpose of this study, articles and conferences were selected from the document type from 1960 to 2025 for a more comprehensive bibliometric analysis and in-depth study of AOD/T and to critically analyze the volume of articles over 5 decades. The meticulous source selection process employed by Scopus typically guarantees the integrity of the data provided. The content specialists at Scopus ensure the accuracy and quality of the data by implementing necessary adjustments. Scopus provides the capability to utilize advanced search parameters, including author, publication, affiliation, keyword, and citation. Citation metrics, accessible through Scopus and frequently utilized in bibliometric analyses, assess the influence and impact of research articles and their authors. The indicators encompass citation counts, h-index, and co-citation analysis. Analytics platforms and data visualization tools exemplify the integration of Scopus with various software and technologies, enhancing the processing and display of bibliometric data.\u003c/p\u003e\u003cp\u003eA thorough search was carried out from the Scopus database to pinpoint research publications and cutting-edge reviews related to Aerosols Optical Depth or Aerosols Optical Thickness (AOD/AOT). The search keyword \u003cem\u003e\u0026ldquo;TITLE-ABS-KEY (Aerosols optical Depth OR AOD OR Aerosols optical thickness) AND PUBYEAR\u0026thinsp;\u0026gt;\u0026thinsp;1959 AND PUBYEAR\u0026thinsp;\u0026lt;\u0026thinsp;2026\u0026rdquo;\u003c/em\u003e was used, and the language selected for this study was English. A total of 4,131 documents were initially. Selection was made to narrow the study to focus on the scope of the study and the trend of Aerosols Optical Depth/Thickness. Earth and planetary sciences, physics and astronomy, and environmental science documents, and English language were selected for this analysis of the documents. The documents were further sorted to 3,542. In the document type. After the selections and sorting, 3,542 documents were sorted, cleaned, and exported to Excel in CSV file format for the analysis. Several software programs were explored for thorough analysis of this study, which include VOSviewer version 1.6.20, which was used for the network and overlay and network visualization, and MapChart and Python version 3.13.5 were utilized.\u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cp\u003eAnalysis of Publication Trends\u003c/p\u003e\u003cp\u003eIn this bibliometric analysis, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eb illustrates the trends in research interest over time, highlighting peaks that correspond with significant events and advancements from 1960 to 2025. From 1960 to 1980, it could be seen that in the year 1960, there was no publication until the early years in 1964 that show a relatively low level of research and publication activity, with only 2 publications, and also no publication in 1965 and 1966. Then, from 1967 through 1980, 8 publications were observed. There was a gradual and noticeable increase from 1980 through 1990, with the highest publication of 19 documents, which shows some research interest in the topic had begun within that decade. Scholars started to explore more specific aspects of the field, leading to a gradual increase in the number of publications from 8 to 19 in that decade. This study observed a spark rise in 1991 all through, suggesting a crucial moment in research activity. This peak could be attributed to significant advancements in methodologies, groundbreaking studies, and heightened awareness of the topic's implications in broader contexts. It also coincided with major conferences, papers, and publications that catalyzed further investigation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe highest publication year was observed in 2011 with a total of 162 documents. Though the interest in research and publication remains high, some years still experience a drop in the number of publications, indicating that the field has gained substantial grip. There were fluctuations from the latter years that show fluctuations in research interest, with a significant dip in 2012. This decline is linked to various factors, such as shifts in funding priorities, changes in research focus, and external events impacting academic activities. However, a rebound occurs in 2013, suggesting renewed interest and the emergence of new research questions that reignite academic engagement, with a drastic drop in 2024.\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003ec depicts the decadal global trend in publishing in a 10-year span. This transition occurred between the years 1960 and 2025. The significance of tackling issues such as smoke from wildfires, urban pollution, and the connection between aerosols and climate is brought into sharper focus by this increase. From the years 1960 to 1970 there were only 12 published documents, while from the year 1971 to 1980 there were 39 documents published. In the years 1981 to 1990, there were 114 publications, which signifies much interest in the topic in these years. The years 1991 to 2000 recorded 511 documents published. This has made it easier to gain a more profound understanding of the relationship that exists between these phenomena. An enormous amount of change has taken place in the field of AOD/T research from 2001 to 2010, with 1,183 published documents, which shows the decade with the highest number of publications. Similarly, from 2011 to 2020 there was a drop in the number to 1,221 documents published, and from 2021 to 2025 the number went down to 464, which suggests more studies need to be carried out for more understanding of the topic. The year 2011, which falls within the sixth decade, recorded the highest number of published documents, with 162 documents. There was a steady state of publication between the fifth (2001\u0026ndash;2010) and the sixth (2011\u0026ndash;2020) decades before a drop in the number of publications from 2020 to 2025. The significance of AOD/T in contemporary geoscience is highlighted by this bibliometric trajectory, which also suggests two potential paths that could be pursued for additional investigation. The fact that research on AOD/T is going from strength to strength is evidence of the major contribution it makes to addressing the urgent climate and environmental concerns that we are currently facing.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of co-authorship\u003c/p\u003e\u003cp\u003eThe network visualization in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e depicts the interwoven links between significant individuals in the field by their co-authorship patterns, emphasizing how collaboration drives scientific progress. Mapping these linkages enables the identification of prominent groups whose coordinated efforts frequently result in groundbreaking discoveries in the field of remote sensing. The network visualization depicts writers who frequently collaborate, forming tightly connected groups that affect research orientations in their respective areas. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows Nakajima, in the blue cluster, and Zhang, in the red cluster, linking many other authors, with Holben and Brent N. in the yellow cluster linking other authors, showing a strong co-authorship with robust co-authorship relationships, which usually indicate dependable collaborations, in which combined knowledge stimulates innovation and elevates the quality of published research. Furthermore, these links highlight knowledge-sharing hubs, where significant authors connect distinct research clusters, facilitating the flow of ideas across disciplines. Through the analysis of these links, we can see how scientific discoveries result from collaborative efforts rather than lone ones, emphasizing the importance of teamwork in the progression of knowledge. This network visualization designed by VOSviewer is used as a strategic tool to find possible collaborators, improve ecosystems, and forecast future areas of growth.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis by Countries\u003c/p\u003e\u003cp\u003eA total of one hundred twenty-eight (128) countries were sorted in the research field. The results of this study showed that the United States of America has the most documents published as retrieved from the Scopus database, with 1,202 documents and 73,523 citations, followed by China, having 518 documents with 10,230 citations; France, having 419 documents with 25,370 citations; Germany, having 376 documents with 17,013 citations; and Japan, having 371 documents with 10,884 citations. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the top 20 countries with the highest documents and citations by percentage from this study. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e depicts the map chart of the top 20 countries with the highest number of published documents, highlighting the United States of America as the leading country in terms of annual publications among the countries. The map chart presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the international collaboration in research that has taken place between 71 countries after selecting a minimum of 3 documents per country from the total of 1,202 countries, with each country contributing a minimum of 3 papers. The map chart clearly shows the distribution and the size of the label that the United States of America demonstrated the most robust collaborative efforts across national boundaries, followed by China, France, Germany, and Japan.\u003c/p\u003e\u003cp\u003eThe quantity of research that has been conducted on AOD/T by various nations is to a substantial degree distinct from one another. Based on this comprehensive bibliometric research, it was determined that 118 countries produced contributions to the subject matter between the years 1960 and 2025. From Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the United States of America tops with 1,202 documents (23.69%), followed by China with 518 documents (10.21%), followed by France with 419 documents (8.26%). Germany and Japan are fourth and fifth with 376 (7.41%) and 371 (7.31%). As seen in this study, one of the reasons why the United States of America has been able to make such rapid advancements is because of its commitment to enhancing its satellite capabilities and lowering the amount of air pollution in the country. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the annual publishing patterns on a MapChart, which shows that the United States continues to maintain its position on this topic. This is especially true after the year 2010, when AOD research became a key topic of discussion in climate policy discussions. As can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the United States of America plays a crucial part in a complex network of alliances that spans the entire world, which adds to the significance of the country. There are strong linkages to the global integration of these countries of higher publications on AOD/T. These relationships, which commonly center on similar themes such as the transboundary transport of aerosols and the influence of climate change on local climates, are a demonstration of the collaborative and multidisciplinary nature of the work that is being done in this sector.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 20 countries with the most documents published in the retrieved papers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRanking\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of Documents\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1st\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnited States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2nd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e518\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3rd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGermany\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRussian Federation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNetherlands\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouth Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGreece\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSwitzerland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCanada\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFinland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIsrael\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBrazil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the United States having 73,523 citations, with 35.45% of the top 20 countries with the highest citations in this study. The table also shows France second, having 25,370 number of citations with 12.23%; Germany having 17,013 number of citations with 8.26%; and Japan having 10,884 number of citations with 5.25%. China is the fifth country with 10,230 citations, with 4.93%. The United States of America, China, Germany, France, Japan, and Italy, as well as the United Kingdom and the other top 20 countries listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, have all established significant partnerships through their respective countries. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e points to the various deficiencies, as seen from the map chart, where countries in Africa and certain portions of Southeast Asia continue to be underrepresented, despite the fact that substantial aerosol-related issues have been addressed. As a result of this imbalance, concentrated efforts are required in order to improve equal involvement in research on AOD in such regions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 20 countries with the highest citations from the published documents in the retrieved papers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRanking\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of Citations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1st\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnited States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e73523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2nd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3rd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGermany\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5802\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNetherlands\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSwitzerland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouth Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGreece\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCanada\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIsrael\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2638\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFinland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2410\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRussian Federation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1871\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBrazil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1529\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis by Organizations\u003c/p\u003e\u003cp\u003eTwenty (20) organizations were considered to be the most productive in this study, as listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. A minimum of 4 documents were selected from an organization of which 460 organizations met the thresholds of the total number of documents published. The top 20 organizations published a total of 447 documents, of which 74 were published in the NASA Goddard Space Flight Center, Greenbelt, MD, United States, which was the bulk of the documents, with 7,380 citations. NASA Goddard Space Flight Center, Greenbelt, MD 20771, and NASA Langley were also listed as the second and third most productive organizations, with a total of 61 and 33 publications with 6,778 and 1,644 citations. From Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, it shows that from the study, though some documents were cited more than some documents, as seen in the 6th and 7th documents having more citations compared to the 5th document published from that organization. The table shows most of the organizations coming from NASA, which indicates NASA contributions and support in the field of research for aerosol optical depth/thickness in relation to the atmosphere, as NASA is one of the leading organizations concerned with the study and research about the atmosphere and the entire globe. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e depict the comprehensive overlay visualization of the different organizations showing both strong and weak connections between organizations with the thick and thin lines of different colours.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 20 organizations with the highest number of publications.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRanking\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganizations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDocuments\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCitations\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1st\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNasa Goddard Space Flight Center, Greenbelt, Md, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7380\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2nd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNasa Goddard Space Flight Center, Greenbelt, Md 20771, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6778\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3rd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNasa Langley Research Center, Hampton, Va, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1644\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeibniz Institute For Tropospheric Research, Leipzig, Germany\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1395\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity Of Chinese Academy Of Sciences, Beijing, 100049, China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e398\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJet Propulsion Laboratory, California Institute Of Technology, Pasadena, Ca, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1585\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLaboratory For Atmospheres, Nasa Goddard Space Flight Center, Greenbelt, Md, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2129\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational Institute For Environmental Studies, Tsukuba, Japan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e565\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEarth System Science Interdisciplinary Center, University Of Maryland, College Park, Md, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e863\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInstitute Of Environmental Physics, University Of Bremen, Bremen, Germany\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e599\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLaboratory For Atmospheres, Nasa Goddard Space Flight Center, Greenbelt, Md 20771, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5084\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNasa Ames Research Center, Moffett Field, Ca, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1024\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNasa Goddard Institute For Space Studies, New York, Ny 10025, 2880 Broadway, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1232\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNasa Goddard Institute For Space Studies, New York, Ny, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e560\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScience Systems And Applications Inc., Lanham, Md, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3988\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepartment Of Land Surveying And Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e327\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational Center For Atmospheric Research, Boulder, Co, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e629\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepartment Of Atmospheric Sciences, University Of North Dakota, Grand Forks, Nd, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e421\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepartment Of Computing, London Metropolitan University, London N7 8Db, 166\u0026ndash;220 Holloway Road, United Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e142\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarine Meteorology Division, Naval Research Laboratory, Monterey, Ca, United States\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e665\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnalysis of Citations\u003c/p\u003e\u003cp\u003eIn accordance with the findings of the citation analysis, the selected articles were found to have a total of 123,504 citations, with the highest citation count of 2,682. Citations ranging from 0 to 2,682 were discovered. Out of the total of 3,542 articles that were found, there were a total of 521 that were found with no citations at the time of this study, whereas 2,762 publications were able to successfully accumulate from 1 to 100 citations, and likewise 259 had a number of citations from 101 to 2,682 citations recorded. There was a total of 19,554 citations that were accumulated by the top 20 publications. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the total number of citations for the study as 2,682. Remer L.A. et al. is the author with the highest citation for the paper titled \u0026ldquo;The MODIS aerosol algorithm, products, and validation,\u0026rdquo; followed by Ginoux P. et al. with 1,657 citations for the paper titled \u0026ldquo;Sources and distributions of dust aerosols simulated with the GOCART model\u0026rdquo; and other authors. The astounding total of 123,504 citations has proven the significant influence and significance of AOD studies in the advancement of climate science, the evaluation of air quality, and the improvement of public health. The citation range, which extends from 0 to 2,682 terms, is illustrative of the differences that exist in the impact that academic research has. It is possible that the specialist nature of these topics or the relatively recent publication dates of these works contributed to the fact that 512 of these works were not cited. While on the other hand, 259 of these noteworthy papers each garnered more than one hundred citations. While there were some documents that are not cited, the citation metrics demonstrate the overall influence as well as trends in the impact of AOD/T research as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 20 Authors and Titles of the Papers, Year, Source, and Number of Citations\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRanking\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAuthor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTitle\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSource Title\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCited by\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1st\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRemer L.A. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe MODIS aerosol algorithm, products, and validation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of the Atmospheric Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2682\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2nd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGinoux P. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSources and distributions of dust aerosols simulated with the GOCART model\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of Geophysical Research Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1657\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3rd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGordon H.R and Wang M.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRetrieval of water-leaving radiance and aerosol optical thickness over the oceans with seawifs: A preliminary algorithm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eApplied Optics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1615\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKaufman Y.J et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOperational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of Geophysical Research Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1564\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChin M. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of the Atmospheric Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1203\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHsu N.C. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAerosol properties over bright-reflecting source regions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIEEE Transactions on Geoscience and Remote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHsu N.C. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnhanced Deep Blue aerosol retrieval algorithm: The second generation ion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of Geophysical Research Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e934\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKing M.D. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRemote Sensing of Cloud, Aerosol, and Water Vapor Properties from the Moderate Resolution Imaging Spectrometer (MODIS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIEEE Transactions on Geoscience and Remote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e906\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKaufman Yoram J. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMODIS 2.1-\u0026micro;m channel \u0026ndash; correlation with visible reflectance for use in remote sensing of aerosol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIEEE Transactions on Geoscience and Remote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e838\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWang J. and Christopher S.A.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIntercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGeophysical Research Letters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e827\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTanr\u0026eacute; D. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRemote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiradiances ances\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of Geophysical Research Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e818\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBaret F. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRemote Sensing of Environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e693\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHusar R.B. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCharacterization of tropospheric aerosols over the oceans with the NOAA advanced very high resolution radiometer optical thickness operational product\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of Geophysical Research Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e645\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHsu N.C.et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeep Blue retrievals of Asian aerosol properties during ACE-Asia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIEEE Transactions on Geoscience and Remote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e641\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKing M.D. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpatial and temporal distribution of clouds observed by MODIS onboard the terra and aqua satellites\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIEEE Transactions on Geoscience and Remote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e611\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMishchenko M.I. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModeling phase functions for dustlike tropospheric aerosols using a shape mixture of randomly oriented polydisperse spheroids\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of Geophysical Research Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e579\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTegen I. and Fung I.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModeling of mineral dust in the atmosphere: sources, transport, and optical thickness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJournal of Geophysical Research\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e577\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKinne S. A. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAn AeroCom initial assessment \u0026ndash; Optical properties in aerosol component modules of global models\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAtmospheric Chemistry and Physics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e564\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGupta P.et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSatellite remote sensing of particulate matter and air quality assessment over global cities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAtmospheric Environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e561\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMain-Knorn M. et al\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSen2Cor for sentinel-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProceedings of SPIE \u0026ndash; The International Society for Optical Engineering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e538\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnalysis of Journals\u003c/p\u003e\u003cp\u003eBased on their level of output, the 20 most productive journals in this study are listed in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The top 20 journals published a total of 1,686 papers, which is equivalent to 84.3% of the total number of documents published and an average citation of 98.61 with a Q1 quartile. There were 280 publications that were published in the Journal of Geophysical Research Atmospheres, which was the bulk of the documents. Utilizing a total of 205 publications, Atmospheric Chemistry and Physics was ranked as the second most prolific publication, followed by Atmospheric Environment with 114 publications and Atmospheric Measurement Techniques with 114 publications as well, but with different numbers of citations, as seen in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e7\u003c/span\u003e listed all the journals recognized as significant contributors to the field of AOD/T research, with thick colors of red, blue, green, and yellow showing the strong connection of relationships of journals on this research topic. The multidisciplinary aspect of AOD/T research in climate science is underscored by the Journal of Geophysical Research: Atmospheres 41 ranking third. The prevalence of these papers signifies an increasing emphasis on research pertinent to policy, particularly in climate modeling, air quality applications, and remote sensing. AOD/T significantly influences atmospheric science and environmental policy, as demonstrated by the extensive research and high citation rates associated with the topic.\u003c/p\u003e\u003cp\u003eThe observations indicate both similarities and shifts in focus within the studies published in these reputable journals concerning AOD/T. The primary subjects of articles in Atmospheric Environment and Remote Sensing of Environment illustrate significant progress in observational technology. This body of research primarily addresses the integration of data from multiple sensors, validation techniques, and AOD/T retrieval methods. The significance of AOD/T in radiative forcing, aerosol-cloud interactions, and climate feedback mechanisms is emphasized in the Journal of Geophysical Research Atmospheres and Atmospheric Chemistry and Physics. The prevalence of journals with high impact factors indicates a rigorous peer review process, as most of the journals are in the Q1 quartile as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; only for applied optics, the International Journal of Remote Sensing, Atmosphere, and others are in Q2, and atmospheric and ocean physics in Q3 as of the time of this study, which depicts the quality of the topic and the necessity for establishing a foundation for further research on the societal and environmental effects of AOD/T. Figure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e8\u003c/span\u003e illustrates the bar chart of the distribution of the journals and their numbers of publications and citations for more understanding of the top 20 journals that make the top contributions in this study, showing the Journal of Geophysical Research Atmospheres with 280 documents and 27,610 citations as the highest and Izvestiya - Atmospheric and Ocean Physics with 22 documents and 140 citations as the lowest among the top 20 journals with significant contributions in the documents published and cited of all the journals in this topic.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 20 journals and the quartile from the retrieved papers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRanking\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSources\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDocuments\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCitations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAvg. citations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSNIP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSJR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSJR Year\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQuartile\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1st\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of Geophysical Research Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e98.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2nd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAtmospheric Chemistry and Physics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e49.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3rd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAtmospheric Environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4877\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAtmospheric Measurement Techniques\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGeophysical Research Letters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e59.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApplied Optics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6518\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e60.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternational Journal of Remote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRemote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1634\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRemote Sensing of Environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e86.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAtmospheric Research\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1551\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of Geophysical Research: Atmospheres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e47.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIeee Transactions on Geoscience and Remote Sensing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e101.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of Aerosol Science\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of Quantitative Spectroscopy and Radiative Transfer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of the Atmospheric Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e161.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAtmosphere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTellus, Series B: Chemical and Physical Meteorology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e54.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIcarus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournal of the Meteorological Society of Japan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e762\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20th\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIzvestiya - Atmospheric and Ocean Physics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eCo-occurrence analysis\u003c/p\u003e\u003cp\u003eIn order to develop the co-occurrence network, we identified the most significant research paths and difficulties that are essential for monitoring the progression of scientific knowledge. A total of 132 detected terms were arranged into three unique clusters, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e7\u003c/span\u003e. These terms had a minimum recurrence of over 50 in titles and abstracts. The terms that are associated with aerosol proper are linked with air pollution, burning mass, and optical depth in the blue cluster. The relationship between aerosols and cloud cover in the green cluster and the aerosol linking to black carbon, remote sensing, cloud optical thickness, and air pollution risk in the red cluster are prominently featured on the map.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of keywords\u003c/p\u003e\u003cp\u003eFor this study, keywords serve as concise markers of the subject content. Figure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003e clearly shows how research hotspots, fundamental links, and domain-precise frontiers are brought to light by the frequency, relevance, and emergence of concepts. Scientific vocabulary like \u0026ldquo;aerosols,\u0026rdquo; \u0026ldquo;air quality,\u0026rdquo; \u0026ldquo;climate change,\u0026rdquo; and \u0026ldquo;health impacts\u0026rdquo; shows the scientific community\u0026rsquo;s focus on specific research areas and its goals. Larger network map nodes represent more commonly used words, and higher keyword frequency is often associated with important literature topics. This bibliometric mapping has illuminated several scientific topics. This category covers aerosol optical depth (AOD/AOT) and public health, climate change, and pollution reduction. Figure\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e10\u003c/span\u003e depicts aerosol as the highest occurring keyword, and aerosols as used by different authors. This analysis shows how important AOD/AOT research areas have grown over time. The growing importance of satellite-based data and interest in aerosol-cloud interactions are highlighted.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eMoreover, this bibliometric analysis enhances understanding of the inherent connections among various research topics within the realm of AOD/AOT. Lines in the network map in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003e illustrate the frequency with which terms appear together in the same study for keyword co-occurrence. The thickness of these lines serves as an indicator of the strength of the correlation, providing a visual representation of the interconnections among different areas of research.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study utilizes an in-depth bibliometric visualization analysis approach to examine existing research on aerosols optical depth/thickness (AOD/AOT), with the scope of identifying key trends, gaps, and future prospects. Previous studies have primarily focused on the predictions, particulate matter, radiative characteristics, classification of aerosols, their spatiotemporal distribution patterns, and the underlying reasons for aerosol variability. There have been significant study advancements, but there is a need for additional thorough investigation. This study explored Scopus data to create network visualizations for the analysis of citation networks, author collaborations, organizational contributions, influence of countries, and keyword co-occurrences and documents published over five decades. We focused on retrieved documents from the Scopus database with the search key TITLE-ABS-KEY (Aerosols optical Depth OR AOD OR Aerosols optical thickness) AND PUBYEAR\u0026thinsp;\u0026gt;\u0026thinsp;1959 AND PUBYEAR\u0026thinsp;\u0026lt;\u0026thinsp;2026 on the topic of aerosol optical depth/thickness between 1960 and 2025. A total of 4,131 documents were initially generated. Selections from articles and conferences were selected on the document type for a more comprehensive analysis. Filtering from Earth and planetary sciences, physics and astronomy, and environmental science documents. 3,542 documents were sorted and used for the analysis. Due to the volume of the documents, we explored VOSviewer version 1.6.20, Python version 3.13.5, and MapChart for the analysis. The analysis reveals that the United States of America has 1,202, 35.86% (73,523); China 518, 14.62% (10,230); France 419, 11.83% (25,370); Germany 376, 10.62% (17,013); and Japan 371, 10.47% (10,888) papers published and citations, respectively. NASA Goddard Space Flight Center, Greenbelt, MD, United States, was the journal with the highest number of papers published, with 74 documents and 7,380 citations. The most common occurring terms are aerosols, aerosol optical depth/thickness, and air quality. It was observed that Remer L.A. et al. is the author with the highest citation for the paper titled \u0026ldquo;The MODIS aerosol algorithm, products, and validation,\u0026rdquo; followed by Ginoux P. et al. with 1,657 citations for the paper titled \u0026ldquo;Sources and distributions of dust aerosols simulated with the GOCART model.\u0026rdquo; Based on our knowledge and recent studies, this study was novel for being the first bibliometric analysis based on aerosol optical depth/thickness that used data retrieved from Scopus for visualization and network mapping. Identifying a drastic drop in 2020, with an upward and downward trend between the years 2021, 2022, 2023, and 2024, there is a need for researchers to continue to investigate immensely on aerosol optical depth/thickness for better understanding of the vast growing global climatic change and weather dynamics.\u003c/p\u003e\u003cp\u003eLimitations and Future Direction\u003c/p\u003e\u003cp\u003eThough few studies show that there are a variety of methods and technological improvements that are being applied in order to improve the accuracy, scalability, and usefulness of measurements of aerosol optical depth (AOD). It is essential to incorporate AOD/AOT data from a variety of sources, including satellites, ground-based surveys, and airborne sensors, in order to enhance the method by which aerosols are evaluated on a global scale. The harmonization of health effect assessments, climate forecasts, and air quality management has the potential to significantly enhance these areas by addressing data gaps and making it better to simulate aerosol behavior with better precision. A number of different aerosols, including black carbon, sulfates, and organic compounds, are areas that need more studies to get a deeper comprehension of the ways in which pollutants can have an impact on human health, notably respiratory and cardiovascular issues. This will enhance the effectiveness of public health interventions and mitigation efforts by enhancing the connection between aerosol exposure and specific sources of pollution.\u003c/p\u003e\u003cp\u003eIn-depth assessments of aerosol attributes, such as particle size, shape, and composition, should be explored using machine learning, which can contribute to an improvement in our understanding of how aerosol optical depth relates to the environments and climatic change. The World Meteorological Organization (WMO) and a number of other organizations are participating in projects such as the Global Atmosphere Watch (GAW), which are aimed at enhancing the flow of data across countries and regions, as well as providing standardized standards for the reporting of aerosol optical depth (AOD/AOT). The implementation of uniformity in the creation of AOD/AOT measurements and reporting systems is absolutely necessary in order to evaluate the progress that nations have achieved in achieving their climate goals.\u003c/p\u003e\u003cp\u003eThrough the use of advanced machine learning algorithms, it is possible to sift through mountains of data about aerosol optical depth (AOD/AOT), discover trends, and develop models in order to forecast how particles will react to particular meteorological circumstances. The evaluations of air quality will be improved, and legislators will be able to make decisions based on reliable evidence with the assistance of these technologies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors will like to acknowledge the School of Physics, Universiti Sains Malaysia for providing all the available resources in making this study successful.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConception and design were done by Emmanuel Yohanna and Hwee San Lim. Materials preparation, data collection and analysis were performed by Emmanuel Yohanna and\u0026nbsp;\u003c/em\u003eHwee San Lim\u003cem\u003e. The first draft of the manuscript was written by Emmanuel Yohanna and both authors edited and commented on previous versions of the manuscript. Both authors read and approved the final manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: Not applicable\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth authors provided informed consent and involvement in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors provide written consent to the publication of the data contained in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that there are no competing interest related to this study and have no relevant financial or non-financial interests to disclose.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData can be found in https://www.scopus.com/pages/home#basic using the keyword provided in the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkinyoola, J. 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A tale of two databases: the use of Web of Science and Scopus in academic papers. \u003cem\u003eScientometrics\u003c/em\u003e, \u003cem\u003e123\u003c/em\u003e(1), 321-335.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Aerosols, Aerosol optical depth/thickness, Air quality, Bibliometric, Scopus, VOSviewer","lastPublishedDoi":"10.21203/rs.3.rs-7763043/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7763043/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNumerous studies have shown that air pollutants affect climatic change, air quality, and public health and how particulate matter (PM2.5, PM10) contributes to respiratory and environmental impacts. This study comprehensively examines aerosol optical depths and thicknesses, climate connections, and pollution-related health impacts using bibliometric and visualization analyses. We retrieved documents from the Scopus database regarding aerosol optical depth/thickness between 1960 and 2025. A total of 4,131 documents were initially generated. Articles and conferences were selected as document types for a more comprehensive analysis. Filtering from Earth and planetary sciences, physics and astronomy, and environmental science documents, we generated 3,542 documents. We explored VOSviewer, Python, and MapChart. The United States of America has 1,202, 35.86% (73,523); China 518, 14.62% (10,230); France 419, 11.83% (25,370); Germany 376, 10.62% (17,013); and Japan 371, 10.47% (10,888) papers published and citations, respectively. NASA Goddard Space Flight Center, Greenbelt, MD, United States, was the journal with the highest number of papers published, with 74 documents and 7,380 citations. The most common occurring terms are \u0026ldquo;aerosols,\u0026rdquo; \u0026ldquo;aerosol optical depth/thickness,\u0026rdquo; and \u0026ldquo;air quality.\u0026rdquo; This study was novel because it was the first bibliometric analysis based on aerosol optical depth that used data retrieved from Scopus for visualization and network mapping. Highest publication was observed in 2011 with a drop in 2020. Researchers needs to continue to investigate aerosol optical depth/thickness of growing global climatic change and weather dynamics.\u003c/p\u003e","manuscriptTitle":"In-depth bibliometric analysis of over five decades of Aerosol Optical Depth revealing trends, key contributors, and new research directions.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-27 14:16:36","doi":"10.21203/rs.3.rs-7763043/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"785a95cc-942e-44a3-af62-01b99e65c991","owner":[],"postedDate":"November 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T03:26:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-27 14:16:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7763043","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7763043","identity":"rs-7763043","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}