Dynamic Evaluation of Air Pollution in Ahvaz: Source Apportionment, SWOT-AHP Analysis, and Innovative Control Strategies

Dynamic Evaluation of Air Pollution in Ahvaz: Source Apportionment, SWOT-AHP Analysis, and Innovative Control Strategies | 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 Dynamic Evaluation of Air Pollution in Ahvaz: Source Apportionment, SWOT-AHP Analysis, and Innovative Control Strategies Faezeh Jahedi, Neamatollah Jaafarzadeh Haghighi Fard, Ahmadreza Lahijanzadeh, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5993611/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 Background: Air pollution significantly impacts global health, contributing to approximately 3.7 million premature deaths annually. Ahvaz, as one of the most polluted cities in the world, experiences severe air pollution due to urbanization, industrial expansion, and transportation. This study aims to identify pollution sources, evaluate their impact through a hybrid SWOT-AHP analysis, and propose innovative air quality management strategies based on global best practices. Methods: A combination of emission inventory analysis, geographic information system (GIS) mapping, and a multi-criteria decision-making (MCDM) approach was applied to assess key pollution sources. SWOT analysis was integrated with the Analytical Hierarchy Process (AHP) to prioritize effective interventions for air quality improvement. Comparative analysis was conducted with cities such as Beijing, New Delhi, and Los Angeles to benchmark pollution control measures. Results: Nitrogen oxides (NOx) were identified as the most emitted pollutants in central Ahvaz, reaching 392 tons annually. Other major pollutants included carbon monoxide (CO) (89 tons/year), suspended particles (87 tons/year), and hydrocarbons (34 tons/year). The Ramin Power Plant accounted for 54% of SO2 emissions, while oil industries contributed to 82% of total pollutants. The hybrid SWOT-AHP analysis ranked "Implementing an advanced air pollution monitoring system and smart traffic management" as the most effective strategy. Benchmarking with other global cities revealed that implementing low-emission zones and transitioning to cleaner fuels significantly reduced air pollution levels. The AHP analysis prioritized strategies as Smart Monitoring System (46.7%) - The most effective approach, emphasizing real-time pollution tracking and traffic optimization. next Clean Fuel Transition (27.7%) - Reducing emissions by shifting industries and vehicles to low-emission fuels. Low-Emission Zones (16.0%) - Establishing restricted zones to control vehicular pollution.and Urban Green Infrastructure (9.5%) - Expanding green spaces to enhance air quality. Conclusion: Strategic investments in pollution control technologies, combined with policy interventions such as emissions-based congestion pricing and green infrastructure expansion, are crucial for mitigating pollution in Ahvaz. The SWOT-AHP framework provided a structured approach to prioritizing actionable environmental management strategies based on feasibility and effectiveness. Environmental Engineering Air pollution Air quality management SWOT-AHP Ahvaz Source apportionment Smart environmental strategies Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Global warming is changing the planet's weather patterns, leading to more frequent, intense and longer extreme weather events and natural disasters, which also affect air quality(Kulick et al., 2023; Montone et al., 2023). According to the World Health Organization (WHO), 99% of the world's population breathes air that exceeds the WHO pollution threshold, indicating that no level of air pollution is safe for humans(Amiri et al., 2023; Berg et al., 2023; Fard et al., 2025). Air pollution poses multisystemic health risks, affecting not only the cardiovascular and respiratory systems, but also detectable effects even at low doses(Fard et al., 2024; Jaafarzadeh Haghighi Fard et al., 2023; Saffar et al., 2023; Sicard et al., 2023). Air pollution-related health problems include stroke, heart disease, lung cancer, and acute and chronic respiratory diseases, costing trillions of dollars and affecting well-being(Haddad et al., 2023; Olesiejuk & Chałubiński, 2023). Annually, air pollution is responsible for about 3.7 million premature deaths worldwide(Lelieveld et al., 2023). Air pollution is one of the main problems in major cities of Iran, caused by outdated industrial units, old vehicles, and high energy consumption in residential and commercial sectors(Barjoee et al., 2023). Ahvaz, Khuzestan's communication and trade center, faces air pollution problems due to vehicle traffic and industries(Sadeghi & Sadeghi, 2024). Rapid urban expansion, an increase in the number of private vehicles, aging cars, and the use of heavy fossil fuels in public transportation are the main factors contributing to air pollution(Jahedi et al., 2021). Ahvaz has a warm and semi-humid climate, with an average temperature increase of about 1.5°C(Sadeghi & Sadeghi, 2024). The highest average temperature is in August (38°C) and the lowest in January (12°C). Humidity is a key parameter in assessing climatic comfort. In Ahvaz, the highest average relative humidity is in January (70.40%) and the lowest in June (24.11%)(Kazemi et al., 2024). Rainfall in Ahvaz follows a winter regime, with very little precipitation during the five warm months of the year. The maximum rainfall is recorded in November with 182 mm. the lowest evaporation occurs in January and the highest in June (549 mm)(Jaafarzadeh et al., 2024). The winds in the Khuzestan region include regular seasonal and local winds, with the predominant direction in Ahvaz being westward. Important winds include the Shamal, Qaws, Suhail, Nashini, Samum, and Chaab winds, each with its characteristics. In the cold season (January), Ahvaz is exposed to predominant north and northwest winds as the primary winds, and south and southeast winds as secondary winds. In the warm season, northwest and west winds are predominant, and generally, the frequency of winds decreases gradually during the summer months. Temperature inversion in Ahvaz occurs less frequently than in elevated and valley areas due to its geographical location and specific weather conditions. In summer, the likelihood of inversion increases in the early hours of the day, causing pollutants to remain near the ground and their concentration to rise. Ahvaz is located in the Khuzestan plain and has a semi-tropical climate(Salmabadi et al., 2023). The region’s climate is influenced by various air masses and is classified as a severe semi-desert climate. Wind erosion is a major problem in dry and semi-dry areas. In Khuzestan, 4.6 million hectares of land are threatened by wind erosion. The study area in Ahvaz includes active and semi-active erosion and deposition zones, with dunes in the west of Ahvaz being affected by local dust storms. In the present article, the sources of pollution in Ahvaz are divided into four categories: urban, industrial, agricultural, and miscellaneous. Urban sources include heating and transportation, while industrial sources encompass various industrial groups. There are various methods for developing strategic plans, and among them, SWOT analysis is widely used to identify and adjust optimal strategies for organizations(Puyt et al., 2023)(Shinde et al., 2023). The study adopts a novel hybrid methodology combining SWOT analysis with the AHP model, allowing a more precise ranking of pollution control strategies. Additionally, international case studies from cities such as Beijing, Los Angeles, and New Delhi provide a comparative assessment of mitigation techniques that can be adapted to Ahvaz’s unique environmental conditions. This research seeks to: 1. Identify and quantify major sources of air pollution in Ahvaz. 2. Evaluate the effectiveness of pollution mitigation strategies using a structured SWOT-AHP approach. 3. Compare global best practices to propose a comprehensive air quality management plan. Material Method Study Area The study area in this report is considered in three sections: 1. In the environmental, economic, and social status section, the study area is considered to be the old Ahvaz County (including Bavi, Karun, Ahvaz, and Hamidiyeh counties). 2. In the pollution sources section, based on the latest changes (drawn by the consultant and unofficially), pollution sources are examined separately for each county. 3. Given the importance of Ahvaz city, environmental, economic, and social assessments, and identification and examination of pollution sources within the Ahvaz municipality (Ahvaz city areas) are also determined (Fig 1). In the first stage of investigation, research, behavior measurement, recognition of the cause, and determination of appropriate methods of air pollution control were considered in the study area. Urban resources are divided into two parts: heating and transportation resources, and industrial resources, in which air-polluting sources are divided into non-metallic mineral, metal, foundry, chemical, oil, drilling, electricity, and food industries groups. Regarding agricultural resources, the amount of fuel consumed by agricultural machinery (the number of combines) has been studied, taking into account the operating hours per year and finally calculating the emitted pollutants. In these surveys, to find the concentration of pollutants in different parts and regions of Ahvaz city, this city has been divided into three parts: Bavi, Central, and Hamidiyeh. All the activities resulting in the release of air pollutants in the mentioned urban areas and points have been studied and the air pollutants released as a result of the activities of these sources have been calculated. After preparing the detailed service description by service description approved by the Environmental Protection Organization and by holding explanatory meetings and discussion and exchange of opinions in the form of public meetings and special meetings with the introduced representatives of the relevant organizations, the points of view of all the organizations were collected in the field of the plan. and the details of the execution stages of the project were discussed and exchanged with them. In the next step, the records of studies conducted in the field of air pollution in Ahvaz city were examined. The required data by determining the deficiencies in the studies, determining the current status of the polluting sources and updating the background information, by preparing specialized questionnaires for different polluting sources, interviews, holding face-to-face meetings, visiting the polluting sources, and reviewing the files of each source were provided. After analyzing and classifying the data, the obtained results were shown on the base maps of Ahvaz and the city, and in this way, the zoning of resources and their density according to the grouping of resources into urban, industrial, service, and agricultural were determined. Also, the statistical data on the air quality of Ahvaz City in the last 5 years were studied. Using the emission coefficients of fossil fuels and industrial production processes, the pollution load of polluting sources was calculated and estimated, and used to determine the share of polluting sources. By using specialized questionnaires, interviews, face-to-face meetings, a collection of expert theories, the proposed plans of different organizations were divided into three groups: direct, indirect and support. In the following, by determining the priority of the implementation of each of the projects and the amount of resources and financial credit required, the effectiveness of the implementation of each project in reducing the air pollution of Ahvaz using SWOT matrix was determined. By presenting the structure of formations for the implementation of plans and evaluating and monitoring the implementation of all the proposed plans, the necessary solutions in the field of control and supervision and optimization of the implementation of each of the plans were determined. Result and Disscution Quantity and Quality of Air Pollution from Industries in Ahvaz In the studies conducted to identify air-polluting industries in Ahvaz, industrial groups have identified and examined all active and air-polluting industries. These studies include the type and amount of raw materials, products, fuel consumption, and gaseous pollutants of each sector. Information from various sources such as the Khuzestan Department of Environmental Protection, questionnaires, visits, and reports has been gathered. In this study, air-polluting industries have been identified by industrial groups and their locations. In the Ahvaz district, 4 non-metallic mineral industries, 7 metal industries, 1 chemical industry, 1 power industry, and 3 food industries have been studied. Additionally, in the Bavi district, 1 power industry, and in the Karun district, 7 non-metallic mineral industries and 3 food units have been examined. The industries studied include brick factories, Farsit Ahvaz Company, Khuzestan Steel Company, National Iranian Steel Group, Sepanta Industrial Company, Ahvaz Rolling and Pipe Company, Kavian Steel Company, Iran Carbon Company, oil and drilling units, Ramin Power Plant, Zargan Power Plant, Khuzestan Flour Factory, Jonoob, industrial towns, and sugarcane development. Finally, the information has been divided by the urban area of Ahvaz and the entire Ahvaz district, and the amount of pollutants emitted by these industries has been estimated. Distribution of Industrial Land Use in Ahvaz Areas In Ahvaz, region 8 has the highest concentration of heavy industries. region 4 and region 6, with follow. The lowest per capita industrial activities belong to regions 1, 3, and 5. Regions 8 and 4 have the highest weight of heavy industrial land use, while Region 1 has the lowest share of light industrial land use (Fig 4). Estimation of Pollution from the Industrial Sector Studies conducted to determine the pollution load from industrial activities in Ahvaz County show that this county, with the emission of 300,047.63 tons of pollutants per year, accounts for about 75.13% of the total industrial pollutants in Khuzestan Province. Following Ahvaz, Karun County with 20,897 tons (5.23%) and Bavi County with 78,451 tons (19.64%) rank next. The main pollutants include carbon monoxide (CO) with 97% and sulfur dioxide (SO2) with 91.8%, having the highest share in air pollution. The highest pollution load from SO2 belongs to the Ramin Power Plant (54%) and oil units (44%). In total, the Ramin Power Plant and oil units produce 98% of the total SO2 emissions. The highest share of NOx emissions belongs to the Zargan Power Plant, which uses natural gas as fuel. Additionally, oil units, by burning large amounts of gas and oil liquids, produce over 98% of the emitted CO. Regarding dust particle emissions, metal industries have the highest share with 61%, followed by non-metallic mineral industries with 18.5%. Overall, oil industries account for 78.8%, chemical industries for 1.34%, metal industries for 6.46%, non-metallic mineral industries for 3.58%, food industries for 0.1%, and power industries for 9.5% of the total pollutant emissions. Polluting Industrial Sources in Ahvaz City Areas The assessment of pollutant emissions in the eight districts of Ahvaz City shows that District 3 has the highest number of flares and is most affected by pollutants from the oil industry, while District 6 has the highest number of air-polluting industrial units. Out of a total of 15 industrial units (excluding oil units), metal industries with 7 units have the highest number, and power, non-metallic mineral, and chemical industries each have 1 unit, the lowest number. The share of districts in industrial pollutant emissions shows that region 4 with 55.28% and region 6 with 36.35% have the highest shares in industrial sector emissions. Estimation of Pollution from the Transportation Sector (Traffic) In the urban transportation sector of Ahvaz, the pollution load from transportation activities, including urban and intercity transport, has been assessed. This assessment considers travel frequency, travel percentage, the number of vehicles by type, fuel consumption, and mileage. The traffic routes in Ahvaz are divided into main and secondary categories, and traffic is calculated based on the type and number of vehicles in the eight districts. Daily traffic statistics of public vehicles from the entry and exit points of Ahvaz have also been examined, and the percentage of passage and the total traffic volume have been calculated. The results show that the highest pollution load is related to carbon monoxide (CO) with over 16,199 tons per year and nitrogen oxides (NOx) with over 8,158 tons per year. Hydrocarbons (HC) follow with 6,864 tons per year. Estimation of Pollution from the Agricultural Sector Studies indicate that the agricultural sector has a negligible share in air pollutant emissions. Pollutant sources in this sector include fuel consumption in agricultural machinery and burning fields in specific seasons. These pollutants, due to their transient nature, low concentration, and high dispersion, mainly occur outside urban areas and are of lesser importance in terms of air pollution. Burning fields in the warm seasons can temporarily increase air pollution, with climatic conditions such as wind speed and direction affecting its dispersion and intensity. Assessment of Emissions from Burning Agricultural Fields and Sugarcane To determine the amount of pollutants emitted from burning agricultural fields and sugarcane lands, two approaches were examined. The first method included experimental and pilot studies, which were excluded due to the extensive nature of the studies. The second method was based on cultivation area, production, crop type, and emission factors. In this study, the amount of pollutants emitted from burning wheat, barley, and sugarcane fields was calculated based on this approach. Determining the Share of Pollution in Urban Areas The assessment of pollutant emissions from various sources (industrial, transportation, and residential-commercial) in the eight districts of Ahvaz City shows the following (Fig 2): Industrial Sector : Total suspended particles have the highest emission level at 113,488 tons per year, while hydrocarbons (HC) have the lowest emission level at 122.5 tons per year. Transportation Sector : Hydrocarbons (HC) have the highest emission level at 16,199 tons per year, while suspended particles have the lowest emission level at 4,361.73 tons per year. Residential-Commercial Sector : Nitrogen oxides (NOx) have the highest emission level at 5,016 tons per year, while sulfur dioxide (SO2) has the lowest emission level at 84 tons per year. The overall assessment of pollutant emissions from different sources shows that the industrial sector ranks first with 152,409.20 tons per year, accounting for 75.90% of total emissions (Fig 3). The transportation sector ranks second with 41,327.33 tons per year, accounting for 20.60% of total emissions. The residential-commercial sector ranks third with 6,987.05 tons per year, accounting for approximately 3.5% of total emissions. Fig 3 shows the amount of pollutants emitted from various sources in the eight districts of Ahvaz (tons/year). Analysis of Strengths, Weaknesses, Opportunities, and Threats of the Comprehensive Air Pollution Reduction Plan After reviewing the current situation and based on the information collected in the previous stage, the environmental status of air pollution in Ahvaz was analyzed using the SWOT (Strengths, Weaknesses, Opportunities, and Threats) method (Table 1 and 2). This analysis will identify the strengths, weaknesses, opportunities, and threats in various environmental areas. Initially, the concepts of “strengths, weaknesses, opportunities, and threats” will be defined to ensure a consistent understanding of categorization. These definitions are presented conventionally, independent of theoretical discussions. After identifying environmental factors, it is necessary to integrate and summarize the strengths, weaknesses, opportunities, and threats to examine the major environmental challenges facing air pollution in Ahvaz County. The SWOT approach is a decision-making method designed to determine long-term or short-term strategies and create significant and key decisions on various issues. This model can be designed for an organization, a company, a specific geographical area, or an issue that we are dealing with. Its main function is to determine strategies to improve efficiency or status. This model first examines the potential and capacity of a subject or place, and the internal and external factors affecting it, and then uses these results to determine various strategies for making decisions, predictions, and solutions to improve that place or subject. For any subject or place, various factors affect its performance quality. These factors generally fall into two categories: Internal Factors : These are factors that exist within the system or area and influence its status. In the SWOT model, internal factors include the strengths and weaknesses of a system, organization, or area. Identifying strengths reveals ways to enhance the system while identifying weaknesses allows for leveraging them to benefit the strengths. External Factors : These are factors beyond the control of the area and affect the system from the outside. They are related to processes occurring outside the region. External factors include opportunities and threats. Opportunities are external factors that can contribute to the advancement of an area, while threats are external factors that pose risks and should be avoided or turned into opportunities. The SWOT model works by calculating and determining these strengths, weaknesses, opportunities, and threats, and then using these factors to determine various strategies in four sections. Ultimately, it determines the direction of strategies and identifies the most important and effective strategy. Table 1: Internal Factor Evaluation (IFE) matrix Table 2: External Factor Evaluation (EFE) matrix The analysis of the External Factors Strategic Matrix shows that the opportunities outweigh the threats, while the analysis of internal factors indicates that weaknesses are more prevalent than strengths. Additionally, the analysis of internal and external factors revealed that the air pollution situation in Ahvaz falls within the (WO) quadrant, which involves strategies derived from combining opportunities and weaknesses. This means that strategies are designed to leverage opportunities to mitigate or eliminate weaknesses. This strategy is known as the Maximum-Minimum (WO) strategy, which implies utilizing the advantages of opportunities to compensate for weaknesses. Therefore, if we are to determine a strategy based on the combination of weaknesses and opportunities (Maximum-Minimum strategy), we should identify a strategy that highlights an aspect of opportunities that can be used to eliminate one of the identified weaknesses. Fig 5 illustrates the strategic position of the air pollution situation in the metropolis of Ahvaz. Overall, the air pollution situation in Ahvaz falls within the conservative strategies quadrant. Accordingly, the desired strategies were formulated, and ultimately, effective programs for achieving each strategy were developed. According to the obtained results, several strategies are suggested . I) Allocate financial resources for air pollution control and dust reduction to cover personnel and technical costs and implement resolutions (green belt, desertification). II) Establish HSE units and environmental management in all industries and related organizations according to legal requirements to interact with the environment. III) Relocate polluting industries and disruptive urban services (airport, railway) from residential areas of Ahvaz to industrial parks and suitable locations. IV) Effectively utilize existing air pollution monitoring and measurement equipment and develop monitoring systems to establish an air pollution control center or air monitoring center in Ahvaz.V) Follow up and implement the resolutions of the air pollution reduction regulations for major cities and prioritize programs to enforce laws and resolutions using the capacity of the air pollution reduction task force. VI) Utilize the capacity of the “Mohit Yar” project and the educational programs of non-governmental organizations to educate and raise awareness about air pollution among Ahvaz citizens.VII) Use legal capacities to secure financial resources and loans to implement and monitor related projects and provide hardware facilities for air pollution reduction (pollutants, emission sources, dust, fuel). VIII)Leverage government support, bank facilities, and national budgets to improve the quality and quantity of urban transportation to reduce pollution from vehicles in public transportation, fuel, and facilities sub-sectors. IX) Establish connections with domestic and international research and academic centers to utilize the technical potential of environmental specialists. The AHP analysis prioritized strategies as follows: Smart Monitoring System (46.7%) - The most effective approach, emphasizing real-time pollution tracking and traffic optimization. Clean Fuel Transition (27.7%) - Reducing emissions by shifting industries and vehicles to low-emission fuels. Low-Emission Zones (16.0%) - Establishing restricted zones to control vehicular pollution. Urban Green Infrastructure (9.5%) - Expanding green spaces to enhance air quality(Fig6) R. Ramezanian Bozorg Ghasem Abadi et al in Tehran, Iran, used a Quantitative Strategic Planning Matrix (QSPM) to prioritize the W/O strategies from the SWOT analysis(Abadi et al., 2019). They identified the best solutions for managing air pollution caused by traffic in Tehran’s 12th district. These solutions include increasing the budget for environmental control, fostering cooperation between the private and public sectors, upgrading public transportation with low-energy and green vehicles, launching extensive public awareness campaigns, and relocating polluting industries to suburban areas. In a similar study, Mozhgan Zaeimdar and his team proposed practical solutions to mitigate air pollution in Tehran’s 2nd district, based on the SWOT model and the area’s current conditions and resources. Among the six strategies evaluated, the most appealing was the “Implementation of a comprehensive energy management plan for vehicles and industries, along with a clean energy use plan,” which received a total attractiveness score of 10.36 for the area(Reza et al., 2021). In a study conducted in Indonesia aimed at identifying the causes of urban air pollution, the SWOT analysis was utilized. The highest score, 5.7, was achieved by the Strength-Opportunities strategy, placing it in Quadrant 1. This indicates that the government, as the responsible authority, has both the opportunity and the strength to implement strategies that support policies promoting aggressive growth by leveraging various existing opportunities and internal strengths(Dyah Prasetyawati et al., 2024). Beigi et al. (2012) utilized the SWOT matrix to assess the sustainability of Tehran’s BRT system and identified key factors to develop strategies for enhancing the public transportation system and its role in reducing air pollution. They concluded that the SWOT matrix is effective in formulating management strategies, which aligns with the findings of the present study on using the SWOT matrix to develop operational strategies for reducing air pollution in Tehran(Mohammad-Beigi et al., 2015) Kobariaizadeh used the Delphi method, combined with SWOT, QSPM, and fuzzy network hierarchy analysis (F.ANP), to develop an air pollution management strategy for Isfahan city. The study suggests that reducing the use of private cars and expanding the public transportation network should be prioritized. Additionally, limiting industrial units within the city and implementing pollution fees will improve public roads. The most effective strategy to control air pollution is to focus on reducing private car usage through policy and planning for public transportation expansion(Kebriaeezadeh et al., 2023). Beijing's transition from coal to gas as a primary energy source has resulted in a 60% reduction in PM2.5 levels. This strategy has proven highly effective in curbing emissions from the industrial and energy sectors, which were the main contributors to the city's air pollution. By moving away from coal, a major source of particulate matter, Beijing has significantly improved air quality, especially during winter months when coal usage was most prevalent. This transition underscores the importance of shifting to cleaner energy sources to achieve substantial reductions in particulate pollution. Los Angeles has been at the forefront of air pollution control, particularly in addressing vehicular emissions. The city implemented strict vehicle emissions standards, which have led to a remarkable 50% reduction in nitrogen oxide (NOx) emissions. NOx is a primary contributor to ground-level ozone formation and smog, and its reduction is crucial for improving air quality in densely populated urban areas. The success of this measure demonstrates the significant impact that regulatory frameworks targeting vehicle emissions can have on reducing urban air pollution, particularly in cities with high vehicle usage like Los Angeles.New Delhi has implemented various strategies to tackle its severe air pollution, with one of the most notable being the odd-even vehicle rationing policy. This policy restricts vehicles from being on the road based on whether their license plates end in an odd or even number, aiming to reduce the number of vehicles on the road and subsequently lower traffic emissions. While the odd-even policy led to a 11% reduction in traffic emissions, its overall effectiveness in significantly improving air quality has been limited. New Delhi continues to face challenges in air quality management due to the city's rapid urbanization, high vehicle numbers, and industrial emissions. This suggests that while traffic-related measures can contribute to pollution control, they may need to be complemented by broader strategies, such as transitioning to cleaner fuels and enhancing public transportation systems. The comparative analysis of these cities reveals that the most effective air pollution control measures are those that target the largest sources of pollution, such as industry and transportation. Beijing's coal-to-gas transition highlights the importance of addressing industrial emissions, while Los Angeles' vehicle emissions standards underscore the role of regulatory measures in controlling pollution from the transportation sector. On the other hand, New Delhi's experience with the odd-even vehicle rationing policy shows that while such measures can offer temporary improvements, they may not be sufficient in isolation to address the complex and multifaceted nature of urban air pollution. The findings suggest that cities aiming to reduce air pollution must adopt a comprehensive approach that includes transitioning to cleaner energy sources, implementing stringent emissions standards for vehicles, and investing in public transportation infrastructure. Additionally, there is a clear need for long-term strategies that integrate technological innovation (such as real-time pollution monitoring systems), urban planning (such as low-emission zones), and policy interventions (such as congestion pricing and clean fuel transitions). By learning from global best practices, cities like Ahvaz can develop tailored solutions that address their unique environmental challenges and significantly improve air quality. Conclusion The sources of urban pollution in Ahvaz include heating and transportation. In the central region, zone 3 has the highest pollution caused by CO and HC, while zone 1 has the highest pollution caused by SO2, NOx, and particulates. The most pollutant released in the central region is nitrogen oxides with more than 392 tons per year. In Ahvaz, the most pollution is caused by carbon monoxide (89 tons per year), suspended particles (87 tons per year), hydrocarbons (34 tons per year), nitrogen oxides (27.35 tons per year), and sulfur dioxide (2.39 tons per year). The most pollution is caused by the consumption of fossil fuels in heating sources in the central part. Ahvaz faces serious challenges of air pollution, which is mainly due to the traffic of vehicles. The biggest pollution is caused by carbon monoxide with more than 393 tons per year. After that, there are hydrocarbons with more than 112 tons per year and nitrogen oxides with 72.68 tons per year. The central part of Ahvaz has the highest level of pollution, followed by other regions. Investigations show that the most pollution caused by SO2 among the industrial groups belongs to the Ramin power plant, which produces 54% of the total SO2 pollution. Oil industries have the largest share in environmental pollution with 82% of all pollutants. Air pollution in Ahvaz is caused by various factors, including fuel consumption in agricultural machinery and burning of fields. During hot seasons, burning fields can temporarily increase air pollution. Climatic factors such as wind speed and direction also play a role in the distribution and intensity of pollution. In examining the sources of air pollution, various sources have also been examined. These sources include sugarcane field fires, garbage burning, and natural fires. In the present study, SWOT matrix was used to develop air quality management strategies in Ahvaz to prioritize the resulting strategies. For this purpose, first, internal and external environmental variables affecting air pollution in the study area were identified and then evaluated by EFE and IFE matrices. The evaluation of strategies based on the scores of EFE and IFE matrices showed that their values are equal to 3 and 1.80, respectively. As a result, the EFE and IFE matrices were in a conservative state. The results of the SWOT matrix identified a total of 9 strategies. Based on the prioritization of the WO2 strategy with the theme "Allocate financial resources for air pollution control and dust reduction to cover personnel and technical costs and implement resolutions (green belt, desertification)", it has been introduced as an effective strategic plan in the priority. The results show the effectiveness of the SWOT matrix in formulating and prioritizing management strategies for organizations. The air pollution reduction programs and actions cover several key areas, each focusing on managing pollution sources and improving air quality. In the Industrial and Fixed Sources Management section, the primary goals are to organize industries and energy consumption patterns and to develop an industrial database to track and monitor all existing industries in and around the city. The Monitoring and Supervision section includes implementing self-inspection and self-reporting programs for fixed sources regarding emitted pollutants. It also involves random vehicle monitoring, real-time monitoring of polluting industrial units, and ensuring compliance with environmental standards in infrastructure construction and vehicle production. In the Traffic and Public Transportation Management section, key actions include creating multi-story parking facilities, enforcing traffic laws, and using natural gas vehicles in public transport. Expanding the public transportation fleet, establishing park-and-ride facilities, and developing non-motorized transportation plans such as bike paths and pedestrian walkways are also important. Additionally, building and completing metro lines and providing electronic traffic services are part of this section. The General Program Management section focuses on approving and supervising the implementation of strategies, ensuring interdepartmental coordination, and allocating subsidies for vehicle design and technology changes. Encouraging regular vehicle inspections, expanding research, and using advanced technology are also emphasized. In the Green Space Development section, expanding urban and suburban green spaces and providing necessary water for these spaces are key actions. The Education and Culture Building section includes establishing an environmental education center, launching an information system for public awareness, and installing TV displays for public information. It also involves dedicating part of the “Mohit Yar” program to air pollution education, achieving full public awareness to change behavioral patterns, and creating a coordination and information center. Training technicians and experts, creating a specialized publication, and increasing radio and TV programs for public awareness are also part of this section. The Laws and Standards section focuses on updating environmental standards, considering executive laws, and periodically reviewing sources. Developing comprehensive environmental standards for fixed sources and updating vehicle production standards to reduce emissions are also included. In the Fuel and Modern Technologies section, key actions include using modern technologies to extract new fuels with low pollution, improving the quality of liquid fuels, and producing and supplying suitable oil for environmental standards. Reducing sulfur in kerosene and diesel, improving the quality of gasoline and diesel to Euro 4 and 5 standards, and using modern technologies in producing CNG vehicles and managing traffic are also emphasized. Declarations Authors’ Contributions Faezeh Jahedi: Writing-original draft. Neamatollah Jaafarzadeh Haghighi Fard: conceptualization and project administration. Ahmadreza Lahijanzadeh: Methodology and Investigation. Elham Khaksar: Methodology and Investigation.Helena Kaabi, Soqra Rostami and Bamshad Shenavar: Writing-original draft. Sirous Karimi5: Methodology and Investigation. All authors verified the last version. Funding This research received no external funding. Conflicts of Interest The authors declare that they have no conflict of interests. Acknowledgments The authors give their special thanks to Ahvaz Jundishapur University of Medical Sciences Ethical considerations The authors declare that they have no ethical issues. References Abadi, R. R. B. G., Mohammadi, A., & Moattar, F. (2019). Development of a strategic plan through SWOT analysis to control traffic-borne air pollutants using CALINE4 model. International Journal of Human Capital in Urban Management , 4 (2), 133-144. https://www.magiran.com/paper/2002127 Amiri, F., Jamali, A. A., & Gharibvand, L. K. (2023). Tracing air pollution changes (CO, NO2, SO2, and HCHO) using GEE and Sentinel 5P images in Ahvaz, Iran. Environmental Monitoring and Assessment , 195 (10), 1259. Barjoee, S. S., Malverdi, E., Kouhkan, M., Alipourfard, I., Rouhani, A., Farokhi, H., & Khaledi, A. (2023). Health assessment of industrial ecosystems of Isfahan (Iran) using phytomonitoring: Chemometric, micromorphology, phytoremediation, air pollution tolerance and anticipated performance indices. Urban Climate , 48 , 101394. Berg, C. D., Schiller, J. H., Boffetta, P., Cai, J., Connolly, C., Kerpel-Fronius, A., Kitts, A. B., Lam, D. C., Mohan, A., & Myers, R. (2023). Air pollution and lung cancer: a review by International Association for the Study of Lung Cancer Early Detection and Screening Committee. Journal of Thoracic Oncology , 18 (10), 1277-1289. Dyah Prasetyawati, N., Tjiptowibisono, S., Pranoto, P., & Sunarto, S. (2024). Swot analysis of factors causing air pollution and recommended control efforts in the city of Yogyakarta, Indonesia. ehemj , 11 (1), 1-7. https://doi.org/10.34172/EHEM.2024.01 Fard, N. J. H., Jahedi, F., Khaksar, M. A., & Shenavar, B. (2025). Systematic review of pulmonary toxicity induced by microplastics and nanoplastics: Insights from in vivo and in vitro studies. Toxicologie Analytique et Clinique . Fard, N. J. H., Jahedi, F., & Turner, A. (2024). Microplastics and nanoplastics in tea: Sources, characteristics and potential impacts. Food Chemistry , 142111. Haddad, P., Joss, M. K., Weuve, J., Vienneau, D., Atkinson, R., Brook, J., Chang, H., Forastiere, F., Hoek, G., & Kappeler, R. (2023). Long-term exposure to traffic-related air pollution and stroke: a systematic review and meta-analysis. International Journal of Hygiene and Environmental Health , 247 , 114079. Jaafarzadeh Haghighi Fard, N., Jahedi, F., & Dehdarirad, H. (2023). The Possibility of Microplastic Removal by Earthworms and Comparing With Conventional Chemical Removal Methods (A Global and Deeply Systematic Review). Journal of Polymers and the Environment , 31 (12), 5050-5064. Jaafarzadeh, N., Nouhjah, S., Shahbazian, H., & Shenavar, B. (2024). The relationship between hot spots of air pollution and the incidence of gestational diabetes based on spatial analysis: A study on one of the most air-polluted metropolis of Iran. Environmental Health Engineering And Management Journal , 0-0. Jahedi, F., Dehdari Rad, H., Goudarzi, G., Tahmasebi Birgani, Y., Babaei, A. A., & Ahmadi Angali, K. (2021). Polycyclic aromatic hydrocarbons in PM1, PM2.5 and PM10 atmospheric particles: identification, sources, temporal and spatial variations. Journal of Environmental Health Science and Engineering , 19 (1), 851-866. https://doi.org/10.1007/s40201-021-00652-7 Kazemi, Z., Kazemi, Z., Jafari, A. J., Farzadkia, M., Hosseini, J., Amini, P., Shahsavani, A., & Kermani, M. (2024). Estimating the health impacts of exposure to Air pollutants and the evaluation of changes in their concentration using a linear model in Iran. Toxicology Reports , 12 , 56-64. Kebriaeezadeh, S., Ghodduosi, J., Alesheikh, A. A., Arjmandi, R., & Seyed Mirzahossieni, S. A. (2023). Presenting a Programme for Estrategical Managment to Control Air Pollution (Case Study: Isfahan). Environmental Researches , 14 (27), 59-76. Kulick, E. R., Kaufman, J. D., & Sack, C. (2023). Ambient air pollution and stroke: an updated review. Stroke , 54 (3), 882-893. Lelieveld, J., Haines, A., Burnett, R., Tonne, C., Klingmüller, K., Münzel, T., & Pozzer, A. (2023). Air pollution deaths attributable to fossil fuels: observational and modelling study. bmj , 383 . Mohammad-Beigi, H., Nouri, J., & Liaghati, H. (2015). Strategic analysis of bus rapid transit system in improvement of public transportation: Case of Tehran, Iran. Modern Applied Science , 9 (9), 169. Montone, R. A., Rinaldi, R., Bonanni, A., Severino, A., Pedicino, D., Crea, F., & Liuzzo, G. (2023). Impact of air pollution on ischemic heart disease: evidence, mechanisms, clinical perspectives. Atherosclerosis , 366 , 22-31. Olesiejuk, K., & Chałubiński, M. (2023). How does particulate air pollution affect barrier functions and inflammatory activity of lung vascular endothelium? Allergy , 78 (3), 629-638. Puyt, R. W., Lie, F. B., & Wilderom, C. P. (2023). The origins of SWOT analysis. Long Range Planning , 56 (3), 102304. Reza, M., Seyed Ali, J., Rokhshad, H., Mojgan, Z., & Saeed, M. (2021). A Strategic Management Plan for Reducing Air Pollution Using the SWOT Model: A Case Study of District 2 of Tehran Municipality. Anthropogenic Pollution Journal , 5 (2), 85-92. https://www.magiran.com/paper/2342389 Sadeghi, H. A., & Sadeghi, R. (2024). Temporal Analysis of Air Pollution Effects on Cardiovascular Diseases and Mortality in Ahvaz, Iran. International Journal of Population Issues , 1 (2), 71-85. Saffar, A. K., Norouzi, H., Choobkar, N., & Kermanshahi, L. S. (2023). SEASONAL AND SPATIAL ZONING OF AIR QUALITY INDEX AND AMBIENT AIR POLLUTANTS IN AHVAZ OIL AND GAS FACTORIES WITH GEOGRAPHIC INFORMATION SYSTEM. Environmental Engineering & Management Journal (EEMJ) , 22 (5). Salmabadi, H., Saeedi, M., Roy, A., & Kaskaoutis, D. G. (2023). Quantifying the contribution of middle eastern dust sources to PM10 levels in Ahvaz, southwest Iran. Atmospheric Research , 295 , 106993. Shinde, P. A., Abbas, Q., Chodankar, N. R., Ariga, K., Abdelkareem, M. A., & Olabi, A. G. (2023). Strengths, weaknesses, opportunities, and threats (SWOT) analysis of supercapacitors: A review. Journal of Energy Chemistry , 79 , 611-638. Sicard, P., Agathokleous, E., Anenberg, S. C., De Marco, A., Paoletti, E., & Calatayud, V. (2023). Trends in urban air pollution over the last two decades: A global perspective. Science of The Total Environment , 858 , 160064. Tables Tables 1 to 3 are available in the Supplementary Files section Additional Declarations The authors declare no competing interests. Supplementary Files Tables.docx 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5993611","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":413236755,"identity":"d609c323-e62c-4495-9a51-cd9c8cea75d4","order_by":0,"name":"Faezeh Jahedi","email":"","orcid":"","institution":"Department of Environmental Health Engineering, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran","correspondingAuthor":false,"prefix":"","firstName":"Faezeh","middleName":"","lastName":"Jahedi","suffix":""},{"id":413236756,"identity":"847516b9-92d9-46e5-80e0-9686af43da0e","order_by":1,"name":"Neamatollah 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province\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/2089e63a742cd3b52253b2e4.png"},{"id":76190481,"identity":"3aac5bc6-0a13-44d8-99e2-6c4b54a59ff4","added_by":"auto","created_at":"2025-02-13 09:33:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15654,"visible":true,"origin":"","legend":"\u003cp\u003eThe emission rate of pollutants from different sources in the eight regions of Ahvaz metropolis (tons/year)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/053e91e5125c469d0ae86c23.png"},{"id":76191685,"identity":"441933e3-2719-45c0-8925-6294a9dc6901","added_by":"auto","created_at":"2025-02-13 09:41:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23966,"visible":true,"origin":"","legend":"\u003cp\u003eThe contribution of different sources in the emission of pollutants in the areas of Ahvaz city\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/52092a091d243f1542dcb76b.png"},{"id":76190493,"identity":"47e54b4e-cf29-4968-ab48-fc7148b43948","added_by":"auto","created_at":"2025-02-13 09:33:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":345399,"visible":true,"origin":"","legend":"\u003cp\u003eThe state of pollution in the areas of Ahvaz city\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/40f7ce37b888ca95de2e0593.png"},{"id":76190490,"identity":"06fee1ab-6818-4e1c-a96b-15e5a7343452","added_by":"auto","created_at":"2025-02-13 09:33:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":80352,"visible":true,"origin":"","legend":"\u003cp\u003eDetermining the strategic situation of air pollution in Ahvaz metropolis\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/7c1b9744654f1e2a2ad1e978.png"},{"id":76190504,"identity":"0ca9f95e-8423-4234-8a73-7456156e1cc7","added_by":"auto","created_at":"2025-02-13 09:33:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":17986,"visible":true,"origin":"","legend":"\u003cp\u003eAHP ranking of air pollution Control Strategies\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/f65e4210931f0ae807dc5187.png"},{"id":76191902,"identity":"de0da477-df53-4313-98d4-583928ae03b0","added_by":"auto","created_at":"2025-02-13 09:49:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1329025,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/d238c115-3af7-41e5-8da0-0a81b14a050e.pdf"},{"id":76190482,"identity":"a21e0258-153f-45fc-8f52-f1b63139de76","added_by":"auto","created_at":"2025-02-13 09:33:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":49653,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-5993611/v1/baaf970cef0924727c929959.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDynamic Evaluation of Air Pollution in Ahvaz: Source Apportionment, SWOT-AHP Analysis, and Innovative Control Strategies\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobal warming is changing the planet's weather patterns, leading to more frequent, intense and longer extreme weather events and natural disasters, which also affect air quality(Kulick et al., 2023; Montone et al., 2023). According to the World Health Organization (WHO), 99% of the world's population breathes air that exceeds the WHO pollution threshold, indicating that no level of air pollution is safe for humans(Amiri et al., 2023; Berg et al., 2023; Fard et al., 2025). Air pollution poses multisystemic health risks, affecting not only the cardiovascular and respiratory systems, but also detectable effects even at low doses(Fard et al., 2024; Jaafarzadeh Haghighi Fard et al., 2023; Saffar et al., 2023; Sicard et al., 2023). Air pollution-related health problems include stroke, heart disease, lung cancer, and acute and chronic respiratory diseases, costing trillions of dollars and affecting well-being(Haddad et al., 2023; Olesiejuk \u0026amp; Chałubiński, 2023). Annually, air pollution is responsible for about 3.7 million premature deaths worldwide(Lelieveld et al., 2023). Air pollution is one of the main problems in major cities of Iran, caused by outdated industrial units, old vehicles, and high energy consumption in residential and commercial sectors(Barjoee et al., 2023). Ahvaz, Khuzestan's communication and trade center, faces air pollution problems due to vehicle traffic and industries(Sadeghi \u0026amp; Sadeghi, 2024). Rapid urban expansion, an increase in the number of private vehicles, aging cars, and the use of heavy fossil fuels in public transportation are the main factors contributing to air pollution(Jahedi et al., 2021). Ahvaz has a warm and semi-humid climate, with an average temperature increase of about 1.5°C(Sadeghi \u0026amp; Sadeghi, 2024). The highest average temperature is in August (38°C) and the lowest in January (12°C). Humidity is a key parameter in assessing climatic comfort. In Ahvaz, the highest average relative humidity is in January (70.40%) and the lowest in June (24.11%)(Kazemi et al., 2024). Rainfall in Ahvaz follows a winter regime, with very little precipitation during the five warm months of the year. The maximum rainfall is recorded in November with 182 mm. the lowest evaporation occurs in January and the highest in June (549 mm)(Jaafarzadeh et al., 2024). The winds in the Khuzestan region include regular seasonal and local winds, with the predominant direction in Ahvaz being westward. Important winds include the Shamal, Qaws, Suhail, Nashini, Samum, and Chaab winds, each with its characteristics. In the cold season (January), Ahvaz is exposed to predominant north and northwest winds as the primary winds, and south and southeast winds as secondary winds. In the warm season, northwest and west winds are predominant, and generally, the frequency of winds decreases gradually during the summer months. Temperature inversion in Ahvaz occurs less frequently than in elevated and valley areas due to its geographical location and specific weather conditions. In summer, the likelihood of inversion increases in the early hours of the day, causing pollutants to remain near the ground and their concentration to rise. Ahvaz is located in the Khuzestan plain and has a semi-tropical climate(Salmabadi et al., 2023). The region’s climate is influenced by various air masses and is classified as a severe semi-desert climate. Wind erosion is a major problem in dry and semi-dry areas. In Khuzestan, 4.6 million hectares of land are threatened by wind erosion. The study area in Ahvaz includes active and semi-active erosion and deposition zones, with dunes in the west of Ahvaz being affected by local dust storms. In the present article, the sources of pollution in Ahvaz are divided into four categories: urban, industrial, agricultural, and miscellaneous. Urban sources include heating and transportation, while industrial sources encompass various industrial groups. There are various methods for developing strategic plans, and among them, SWOT analysis is widely used to identify and adjust optimal strategies for organizations(Puyt et al., 2023)(Shinde et al., 2023). The study adopts a novel hybrid methodology combining SWOT analysis with the AHP model, allowing a more precise ranking of pollution control strategies. Additionally, international case studies from cities such as Beijing, Los Angeles, and New Delhi provide a comparative assessment of mitigation techniques that can be adapted to Ahvaz’s unique environmental conditions.\u003c/p\u003e\n\u003cp\u003eThis research seeks to:\u003c/p\u003e\n\u003cp\u003e1. Identify and quantify major sources of air pollution in Ahvaz.\u003c/p\u003e\n\u003cp\u003e2. Evaluate the effectiveness of pollution mitigation strategies using a structured SWOT-AHP approach.\u003c/p\u003e\n\u003cp\u003e3. Compare global best practices to propose a comprehensive air quality management plan.\u003c/p\u003e"},{"header":"Material Method","content":"\u003cp\u003e\u003cstrong\u003eStudy Area\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study area in this report is considered in three sections:\u003c/p\u003e\n\u003cp\u003e1. In the environmental, economic, and social status section, the study area is considered to be the old Ahvaz County (including Bavi, Karun, Ahvaz, and Hamidiyeh counties).\u003c/p\u003e\n\u003cp\u003e2. In the pollution sources section, based on the latest changes (drawn by the consultant and unofficially), pollution sources are examined separately for each county.\u003c/p\u003e\n\u003cp\u003e3. Given the importance of Ahvaz city, environmental, economic, and social assessments, and identification and examination of pollution sources within the Ahvaz municipality (Ahvaz city areas) are also determined (Fig 1).\u003c/p\u003e\n\u003cp\u003eIn the first stage of investigation, research, behavior measurement, recognition of the cause, and determination of appropriate methods of air pollution control were considered in the study area. Urban resources are divided into two parts: heating and transportation resources, and industrial resources, in which air-polluting sources are divided into non-metallic mineral, metal, foundry, chemical, oil, drilling, electricity, and food industries groups. Regarding agricultural resources, the amount of fuel consumed by agricultural machinery (the number of combines) has been studied, taking into account the operating hours per year and finally calculating the emitted pollutants. In these surveys, to find the concentration of pollutants in different parts and regions of Ahvaz city, this city has been divided into three parts: Bavi, Central, and Hamidiyeh. All the activities resulting in the release of air pollutants in the mentioned urban areas and points have been studied and the air pollutants released as a result of the activities of these sources have been calculated.\u003c/p\u003e\n\u003cp\u003eAfter preparing the detailed service description by service description approved by the Environmental Protection Organization and by holding explanatory meetings and discussion and exchange of opinions in the form of public meetings and special meetings with the introduced representatives of the relevant organizations, the points of view of all the organizations were collected in the field of the plan. and the details of the execution stages of the project were discussed and exchanged with them.\u003c/p\u003e\n\u003cp\u003eIn the next step, the records of studies conducted in the field of air pollution in Ahvaz city were examined. The required data by determining the deficiencies in the studies, determining the current status of the polluting sources and updating the background information, by preparing specialized questionnaires for different polluting sources, interviews, holding face-to-face meetings, visiting the polluting sources, and reviewing the files of each source were provided. After analyzing and classifying the data, the obtained results were shown on the base maps of Ahvaz and the city, and in this way, the zoning of resources and their density according to the grouping of resources into urban, industrial, service, and agricultural were determined. Also, the statistical data on the air quality of Ahvaz City in the last 5 years were studied. Using the emission coefficients of fossil fuels and industrial production processes, the pollution load of polluting sources was calculated and estimated, and used to determine the share of polluting sources. By using specialized questionnaires, interviews, face-to-face meetings, a collection of expert theories, the proposed plans of different organizations were divided into three groups: direct, indirect and support. In the following, by determining the priority of the implementation of each of the projects and the amount of resources and financial credit required, the effectiveness of the implementation of each project in reducing the air pollution of Ahvaz\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eusing SWOT matrix was determined. By presenting the structure of formations for the implementation of plans and evaluating and monitoring the implementation of all the proposed plans, the necessary solutions in the field of control and supervision and optimization of the implementation of each of the plans were determined.\u003c/p\u003e"},{"header":"Result and Disscution","content":"\u003cp\u003e\u003cstrong\u003eQuantity and Quality of Air Pollution from Industries in Ahvaz\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the studies conducted to identify air-polluting industries in Ahvaz, industrial groups have identified and examined all active and air-polluting industries. These studies include the type and amount of raw materials, products, fuel consumption, and gaseous pollutants of each sector. Information from various sources such as the Khuzestan Department of Environmental Protection, questionnaires, visits, and reports has been gathered.\u003c/p\u003e\n\u003cp\u003eIn this study, air-polluting industries have been identified by industrial groups and their locations. In the Ahvaz district, 4 non-metallic mineral industries, 7 metal industries, 1 chemical industry, 1 power industry, and 3 food industries have been studied. Additionally, in the Bavi district, 1 power industry, and in the Karun district, 7 non-metallic mineral industries and 3 food units have been examined.\u003c/p\u003e\n\u003cp\u003eThe industries studied include brick factories, Farsit Ahvaz Company, Khuzestan Steel Company, National Iranian Steel Group, Sepanta Industrial Company, Ahvaz Rolling and Pipe Company, Kavian Steel Company, Iran Carbon Company, oil and drilling units, Ramin Power Plant, Zargan Power Plant, Khuzestan Flour Factory, Jonoob, industrial towns, and sugarcane development. Finally, the information has been divided by the urban area of Ahvaz and the entire Ahvaz district, and the amount of pollutants emitted by these industries has been estimated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution of Industrial Land Use in Ahvaz Areas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Ahvaz, region 8 has the highest concentration of heavy industries. region 4 and region 6, with follow. The lowest per capita industrial activities belong to regions 1, 3, and 5. Regions 8 and 4 have the highest weight of heavy industrial land use, while Region 1 has the lowest share of light industrial land use (Fig 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimation of Pollution from the Industrial Sector\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudies conducted to determine the pollution load from industrial activities in Ahvaz County show that this county, with the emission of 300,047.63 tons of pollutants per year, accounts for about 75.13% of the total industrial pollutants in Khuzestan Province. Following Ahvaz, Karun County with 20,897 tons (5.23%) and Bavi County with 78,451 tons (19.64%) rank next.\u003c/p\u003e\n\u003cp\u003eThe main pollutants include carbon monoxide (CO) with 97% and sulfur dioxide (SO2) with 91.8%, having the highest share in air pollution. The highest pollution load from SO2 belongs to the Ramin Power Plant (54%) and oil units (44%). In total, the Ramin Power Plant and oil units produce 98% of the total SO2 emissions. The highest share of NOx emissions belongs to the Zargan Power Plant, which uses natural gas as fuel. Additionally, oil units, by burning large amounts of gas and oil liquids, produce over 98% of the emitted CO.\u003c/p\u003e\n\u003cp\u003eRegarding dust particle emissions, metal industries have the highest share with 61%, followed by non-metallic mineral industries with 18.5%. Overall, oil industries account for 78.8%, chemical industries for 1.34%, metal industries for 6.46%, non-metallic mineral industries for 3.58%, food industries for 0.1%, and power industries for 9.5% of the total pollutant emissions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePolluting Industrial Sources in Ahvaz City Areas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe assessment of pollutant emissions in the eight districts of Ahvaz City shows that District 3 has the highest number of flares and is most affected by pollutants from the oil industry, while District 6 has the highest number of air-polluting industrial units. Out of a total of 15 industrial units (excluding oil units), metal industries with 7 units have the highest number, and power, non-metallic mineral, and chemical industries each have 1 unit, the lowest number.\u003c/p\u003e\n\u003cp\u003eThe share of districts in industrial pollutant emissions shows that region 4 with 55.28% and region 6 with 36.35% have the highest shares in industrial sector emissions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimation of Pollution from the Transportation Sector (Traffic)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the urban transportation sector of Ahvaz, the pollution load from transportation activities, including urban and intercity transport, has been assessed. This assessment considers travel frequency, travel percentage, the number of vehicles by type, fuel consumption, and mileage. The traffic routes in Ahvaz are divided into main and secondary categories, and traffic is calculated based on the type and number of vehicles in the eight districts.\u003c/p\u003e\n\u003cp\u003eDaily traffic statistics of public vehicles from the entry and exit points of Ahvaz have also been examined, and the percentage of passage and the total traffic volume have been calculated. The results show that the highest pollution load is related to carbon monoxide (CO) with over 16,199 tons per year and nitrogen oxides (NOx) with over 8,158 tons per year. Hydrocarbons (HC) follow with 6,864 tons per year.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimation of Pollution from the Agricultural Sector\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudies indicate that the agricultural sector has a negligible share in air pollutant emissions. Pollutant sources in this sector include fuel consumption in agricultural machinery and burning fields in specific seasons. These pollutants, due to their transient nature, low concentration, and high dispersion, mainly occur outside urban areas and are of lesser importance in terms of air pollution. Burning fields in the warm seasons can temporarily increase air pollution, with climatic conditions such as wind speed and direction affecting its dispersion and intensity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Emissions from Burning Agricultural Fields and Sugarcane\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo determine the amount of pollutants emitted from burning agricultural fields and sugarcane lands, two approaches were examined. The first method included experimental and pilot studies, which were excluded due to the extensive nature of the studies. The second method was based on cultivation area, production, crop type, and emission factors. In this study, the amount of pollutants emitted from burning wheat, barley, and sugarcane fields was calculated based on this approach.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermining the Share of Pollution in Urban Areas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe assessment of pollutant emissions from various sources (industrial, transportation, and residential-commercial) in the eight districts of Ahvaz City shows the following (Fig 2):\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eIndustrial Sector\u003c/strong\u003e: Total suspended particles have the highest emission level at 113,488 tons per year, while hydrocarbons (HC) have the lowest emission level at 122.5 tons per year.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eTransportation Sector\u003c/strong\u003e: Hydrocarbons (HC) have the highest emission level at 16,199 tons per year, while suspended particles have the lowest emission level at 4,361.73 tons per year.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eResidential-Commercial Sector\u003c/strong\u003e: Nitrogen oxides (NOx) have the highest emission level at 5,016 tons per year, while sulfur dioxide (SO2) has the lowest emission level at 84 tons per year.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe overall assessment of pollutant emissions from different sources shows that the industrial sector ranks first with 152,409.20 tons per year, accounting for 75.90% of total emissions (Fig 3). The transportation sector ranks second with 41,327.33 tons per year, accounting for 20.60% of total emissions. The residential-commercial sector ranks third with 6,987.05 tons per year, accounting for approximately 3.5% of total emissions. Fig 3 shows the amount of pollutants emitted from various sources in the eight districts of Ahvaz (tons/year).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of Strengths, Weaknesses, Opportunities, and Threats of the Comprehensive Air Pollution Reduction Plan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter reviewing the current situation and based on the information collected in the previous stage, the environmental status of air pollution in Ahvaz was analyzed using the SWOT (Strengths, Weaknesses, Opportunities, and Threats) method (Table 1 and 2). This analysis will identify the strengths, weaknesses, opportunities, and threats in various environmental areas. Initially, the concepts of \u0026ldquo;strengths, weaknesses, opportunities, and threats\u0026rdquo; will be defined to ensure a consistent understanding of categorization. These definitions are presented conventionally, independent of theoretical discussions.\u003c/p\u003e\n\u003cp\u003eAfter identifying environmental factors, it is necessary to integrate and summarize the strengths, weaknesses, opportunities, and threats to examine the major environmental challenges facing air pollution in Ahvaz County.\u003c/p\u003e\n\u003cp\u003eThe SWOT approach is a decision-making method designed to determine long-term or short-term strategies and create significant and key decisions on various issues. This model can be designed for an organization, a company, a specific geographical area, or an issue that we are dealing with. Its main function is to determine strategies to improve efficiency or status. This model first examines the potential and capacity of a subject or place, and the internal and external factors affecting it, and then uses these results to determine various strategies for making decisions, predictions, and solutions to improve that place or subject.\u003c/p\u003e\n\u003cp\u003eFor any subject or place, various factors affect its performance quality. These factors generally fall into two categories:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInternal Factors\u003c/strong\u003e: These are factors that exist within the system or area and influence its status. In the SWOT model, internal factors include the strengths and weaknesses of a system, organization, or area. Identifying strengths reveals ways to enhance the system while identifying weaknesses allows for leveraging them to benefit the strengths.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExternal Factors\u003c/strong\u003e: These are factors beyond the control of the area and affect the system from the outside. They are related to processes occurring outside the region. External factors include opportunities and threats. Opportunities are external factors that can contribute to the advancement of an area, while threats are external factors that pose risks and should be avoided or turned into opportunities.\u003c/p\u003e\n\u003cp\u003eThe SWOT model works by calculating and determining these strengths, weaknesses, opportunities, and threats, and then using these factors to determine various strategies in four sections. Ultimately, it determines the direction of strategies and identifies the most important and effective strategy.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eTable 1: Internal Factor Evaluation (IFE) matrix\u003c/p\u003e\n\u003cp\u003eTable 2: External Factor Evaluation (EFE) matrix\u003c/p\u003e\n\u003cp\u003eThe analysis of the External Factors Strategic Matrix shows that the opportunities outweigh the threats, while the analysis of internal factors indicates that weaknesses are more prevalent than strengths. Additionally, the analysis of internal and external factors revealed that the air pollution situation in Ahvaz falls within the (WO) quadrant, which involves strategies derived from combining opportunities and weaknesses. This means that strategies are designed to leverage opportunities to mitigate or eliminate weaknesses. This strategy is known as the Maximum-Minimum (WO) strategy, which implies utilizing the advantages of opportunities to compensate for weaknesses. Therefore, if we are to determine a strategy based on the combination of weaknesses and opportunities (Maximum-Minimum strategy), we should identify a strategy that highlights an aspect of opportunities that can be used to eliminate one of the identified weaknesses. Fig 5 illustrates the strategic position of the air pollution situation in the metropolis of Ahvaz. Overall, the air pollution situation in Ahvaz falls within the conservative strategies quadrant. Accordingly, the desired strategies were formulated, and ultimately, effective programs for achieving each strategy were developed.\u003c/p\u003e\n\u003cp\u003eAccording to the obtained results, several strategies are suggested\u003cspan dir=\"RTL\"\u003e.\u0026nbsp;\u003c/span\u003eI) Allocate financial resources for air pollution control and dust reduction to cover personnel and technical costs and implement resolutions (green belt, desertification). II) Establish HSE units and environmental management in all industries and related organizations according to legal requirements to interact with the environment. III) Relocate polluting industries and disruptive urban services (airport, railway) from residential areas of Ahvaz to industrial parks and suitable locations. IV) Effectively utilize existing air pollution monitoring and measurement equipment and develop monitoring systems to establish an air pollution control center or air monitoring center in Ahvaz.V) Follow up and implement the resolutions of the air pollution reduction regulations for major cities and prioritize programs to enforce laws and resolutions using the capacity of the air pollution reduction task force. VI) Utilize the capacity of the \u0026ldquo;Mohit Yar\u0026rdquo; project and the educational programs of non-governmental organizations to educate and raise awareness about air pollution among Ahvaz citizens.VII) Use legal capacities to secure financial resources and loans to implement and monitor related projects and provide hardware facilities for air pollution reduction (pollutants, emission sources, dust, fuel). VIII)Leverage government support, bank facilities, and national budgets to improve the quality and quantity of urban transportation to reduce pollution from vehicles in public transportation, fuel, and facilities sub-sectors. IX) Establish connections with domestic and international research and academic centers to utilize the technical potential of environmental specialists.\u003c/p\u003e\n\u003cp\u003eThe AHP analysis prioritized strategies as follows:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eSmart Monitoring System (46.7%) - The most effective approach, emphasizing real-time pollution tracking and traffic optimization.\u003c/li\u003e\n \u003cli\u003eClean Fuel Transition (27.7%) - Reducing emissions by shifting industries and vehicles to low-emission fuels.\u003c/li\u003e\n \u003cli\u003eLow-Emission Zones (16.0%) - Establishing restricted zones to control vehicular pollution.\u003c/li\u003e\n \u003cli\u003eUrban Green Infrastructure (9.5%) - Expanding green spaces to enhance air quality(Fig6)\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eR. Ramezanian Bozorg Ghasem Abadi et al in Tehran, Iran, used a Quantitative Strategic Planning Matrix (QSPM) to prioritize the W/O strategies from the SWOT analysis(Abadi et al., 2019). They identified the best solutions for managing air pollution caused by traffic in Tehran\u0026rsquo;s 12th district. These solutions include increasing the budget for environmental control, fostering cooperation between the private and public sectors, upgrading public transportation with low-energy and green vehicles, launching extensive public awareness campaigns, and relocating polluting industries to suburban areas.\u003c/p\u003e\n\u003cp\u003eIn a similar study, Mozhgan Zaeimdar and his team proposed practical solutions to mitigate air pollution in Tehran\u0026rsquo;s 2nd district, based on the SWOT model and the area\u0026rsquo;s current conditions and resources. Among the six strategies evaluated, the most appealing was the \u0026ldquo;Implementation of a comprehensive energy management plan for vehicles and industries, along with a clean energy use plan,\u0026rdquo; which received a total attractiveness score of 10.36 for the area(Reza et al., 2021).\u003c/p\u003e\n\u003cp\u003eIn a study conducted in Indonesia aimed at identifying the causes of urban air pollution, the SWOT analysis was utilized. The highest score, 5.7, was achieved by the Strength-Opportunities strategy, placing it in Quadrant 1. This indicates that the government, as the responsible authority, has both the opportunity and the strength to implement strategies that support policies promoting aggressive growth by leveraging various existing opportunities and internal strengths(Dyah Prasetyawati et al., 2024).\u003c/p\u003e\n\u003cp\u003eBeigi et al. (2012) utilized the SWOT matrix to assess the sustainability of Tehran\u0026rsquo;s BRT system and identified key factors to develop strategies for enhancing the public transportation system and its role in reducing air pollution. They concluded that the SWOT matrix is effective in formulating management strategies, which aligns with the findings of the present study on using the SWOT matrix to develop operational strategies for reducing air pollution in Tehran(Mohammad-Beigi et al., 2015)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Kobariaizadeh used the Delphi method, combined with SWOT, QSPM, and fuzzy network hierarchy analysis (F.ANP), to develop an air pollution management strategy for Isfahan city. The study suggests that reducing the use of private cars and expanding the public transportation network should be prioritized. Additionally, limiting industrial units within the city and implementing pollution fees will improve public roads. The most effective strategy to control air pollution is to focus on reducing private car usage through policy and planning for public transportation expansion(Kebriaeezadeh et al., 2023).\u003c/p\u003e\n\u003cp\u003eBeijing\u0026apos;s transition from coal to gas as a primary energy source has resulted in a 60% reduction in PM2.5 levels. This strategy has proven highly effective in curbing emissions from the industrial and energy sectors, which were the main contributors to the city\u0026apos;s air pollution. By moving away from coal, a major source of particulate matter, Beijing has significantly improved air quality, especially during winter months when coal usage was most prevalent. This transition underscores the importance of shifting to cleaner energy sources to achieve substantial reductions in particulate pollution. Los Angeles has been at the forefront of air pollution control, particularly in addressing vehicular emissions. The city implemented strict vehicle emissions standards, which have led to a remarkable 50% reduction in nitrogen oxide (NOx) emissions. NOx is a primary contributor to ground-level ozone formation and smog, and its reduction is crucial for improving air quality in densely populated urban areas. The success of this measure demonstrates the significant impact that regulatory frameworks targeting vehicle emissions can have on reducing urban air pollution, particularly in cities with high vehicle usage like Los Angeles.New Delhi has implemented various strategies to tackle its severe air pollution, with one of the most notable being the odd-even vehicle rationing policy. This policy restricts vehicles from being on the road based on whether their license plates end in an odd or even number, aiming to reduce the number of vehicles on the road and subsequently lower traffic emissions. While the odd-even policy led to a 11% reduction in traffic emissions, its overall effectiveness in significantly improving air quality has been limited. New Delhi continues to face challenges in air quality management due to the city\u0026apos;s rapid urbanization, high vehicle numbers, and industrial emissions. This suggests that while traffic-related measures can contribute to pollution control, they may need to be complemented by broader strategies, such as transitioning to cleaner fuels and enhancing public transportation systems. The comparative analysis of these cities reveals that the most effective air pollution control measures are those that target the largest sources of pollution, such as industry and transportation. Beijing\u0026apos;s coal-to-gas transition highlights the importance of addressing industrial emissions, while Los Angeles\u0026apos; vehicle emissions standards underscore the role of regulatory measures in controlling pollution from the transportation sector. On the other hand, New Delhi\u0026apos;s experience with the odd-even vehicle rationing policy shows that while such measures can offer temporary improvements, they may not be sufficient in isolation to address the complex and multifaceted nature of urban air pollution.\u003c/p\u003e\n\u003cp\u003eThe findings suggest that cities aiming to reduce air pollution must adopt a comprehensive approach that includes transitioning to cleaner energy sources, implementing stringent emissions standards for vehicles, and investing in public transportation infrastructure. Additionally, there is a clear need for long-term strategies that integrate technological innovation (such as real-time pollution monitoring systems), urban planning (such as low-emission zones), and policy interventions (such as congestion pricing and clean fuel transitions). By learning from global best practices, cities like Ahvaz can develop tailored solutions that address their unique environmental challenges and significantly improve air quality.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe sources of urban pollution in Ahvaz include heating and transportation. In the central region, zone 3 has the highest pollution caused by CO and HC, while zone 1 has the highest pollution caused by SO2, NOx, and particulates. The most pollutant released in the central region is nitrogen oxides with more than 392 tons per year. In Ahvaz, the most pollution is caused by carbon monoxide (89 tons per year), suspended particles (87 tons per year), hydrocarbons (34 tons per year), nitrogen oxides (27.35 tons per year), and sulfur dioxide (2.39 tons per year).\u003c/p\u003e\n\u003cp\u003eThe most pollution is caused by the consumption of fossil fuels in heating sources in the central part. Ahvaz faces serious challenges of air pollution, which is mainly due to the traffic of vehicles. The biggest pollution is caused by carbon monoxide with more than 393 tons per year. After that, there are hydrocarbons with more than 112 tons per year and nitrogen oxides with 72.68 tons per year. The central part of Ahvaz has the highest level of pollution, followed by other regions. Investigations show that the most pollution caused by SO2 among the industrial groups belongs to the Ramin power plant, which produces 54% of the total SO2 pollution. Oil industries have the largest share in environmental pollution with 82% of all pollutants. Air pollution in Ahvaz is caused by various factors, including fuel consumption in agricultural machinery and burning of fields. During hot seasons, burning fields can temporarily increase air pollution. Climatic factors such as wind speed and direction also play a role in the distribution and intensity of pollution. In examining the sources of air pollution, various sources have also been examined. These sources include sugarcane field fires, garbage burning, and natural fires. In the present study, SWOT matrix was used to develop air quality management strategies in Ahvaz to prioritize the resulting strategies. For this purpose, first, internal and external environmental variables affecting air pollution in the study area were identified and then evaluated by EFE and IFE matrices. The evaluation of strategies based on the scores of EFE and IFE matrices showed that their values are equal to 3 and 1.80, respectively. As a result, the EFE and IFE matrices were in a conservative state. The results of the SWOT matrix identified a total of 9 strategies. Based on the prioritization of the WO2 strategy with the theme \u0026quot;Allocate financial resources for air pollution control and dust reduction to cover personnel and technical costs and implement resolutions (green belt, desertification)\u0026quot;, it has been introduced as an effective strategic plan in the priority. The results show the effectiveness of the SWOT matrix in formulating and prioritizing management strategies for organizations.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe air pollution reduction programs and actions cover several key areas, each focusing on managing pollution sources and improving air quality. In the Industrial and Fixed Sources Management section, the primary goals are to organize industries and energy consumption patterns and to develop an industrial database to track and monitor all existing industries in and around the city. The Monitoring and Supervision section includes implementing self-inspection and self-reporting programs for fixed sources regarding emitted pollutants. It also involves random vehicle monitoring, real-time monitoring of polluting industrial units, and ensuring compliance with environmental standards in infrastructure construction and vehicle production. In the Traffic and Public Transportation Management section, key actions include creating multi-story parking facilities, enforcing traffic laws, and using natural gas vehicles in public transport. Expanding the public transportation fleet, establishing park-and-ride facilities, and developing non-motorized transportation plans such as bike paths and pedestrian walkways are also important. Additionally, building and completing metro lines and providing electronic traffic services are part of this section. The General Program Management section focuses on approving and supervising the implementation of strategies, ensuring interdepartmental coordination, and allocating subsidies for vehicle design and technology changes. Encouraging regular vehicle inspections, expanding research, and using advanced technology are also emphasized. In the Green Space Development section, expanding urban and suburban green spaces and providing necessary water for these spaces are key actions. The Education and Culture Building section includes establishing an environmental education center, launching an information system for public awareness, and installing TV displays for public information. It also involves dedicating part of the \u0026ldquo;Mohit Yar\u0026rdquo; program to air pollution education, achieving full public awareness to change behavioral patterns, and creating a coordination and information center. Training technicians and experts, creating a specialized publication, and increasing radio and TV programs for public awareness are also part of this section. The Laws and Standards section focuses on updating environmental standards, considering executive laws, and periodically reviewing sources. Developing comprehensive environmental standards for fixed sources and updating vehicle production standards to reduce emissions are also included. In the Fuel and Modern Technologies section, key actions include using modern technologies to extract new fuels with low pollution, improving the quality of liquid fuels, and producing and supplying suitable oil for environmental standards. Reducing sulfur in kerosene and diesel, improving the quality of gasoline and diesel to Euro 4 and 5 standards, and using modern technologies in producing CNG vehicles and managing traffic are also emphasized.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Faezeh Jahedi: Writing-original draft. Neamatollah Jaafarzadeh Haghighi Fard:\u0026nbsp;conceptualization and project administration. Ahmadreza Lahijanzadeh: Methodology and Investigation. Elham Khaksar: Methodology and Investigation.Helena Kaabi, Soqra Rostami\u0026nbsp;and Bamshad Shenavar: Writing-original draft. Sirous Karimi5: Methodology and Investigation. All authors verified the last version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The authors declare that they have no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The authors give their special thanks to Ahvaz Jundishapur University of Medical Sciences\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The authors declare that they have no ethical issues.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbadi, R. R. B. G., Mohammadi, A., \u0026amp; Moattar, F. (2019). 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Swot analysis of factors causing air pollution and recommended control efforts in the city of Yogyakarta, Indonesia. \u003cem\u003eehemj\u003c/em\u003e,\u003cem\u003e\u0026nbsp;11\u003c/em\u003e(1), 1-7. \u003ca href=\"https://doi.org/10.34172/EHEM.2024.01\"\u003ehttps://doi.org/10.34172/EHEM.2024.01\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eFard, N. J. H., Jahedi, F., Khaksar, M. A., \u0026amp; Shenavar, B. (2025). Systematic review of pulmonary toxicity induced by microplastics and nanoplastics: Insights from in vivo and in vitro studies. \u003cem\u003eToxicologie Analytique et Clinique\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eFard, N. J. H., Jahedi, F., \u0026amp; Turner, A. (2024). Microplastics and nanoplastics in tea: Sources, characteristics and potential impacts. \u003cem\u003eFood Chemistry\u003c/em\u003e, 142111.\u003c/li\u003e\n \u003cli\u003eHaddad, P., Joss, M. K., Weuve, J., Vienneau, D., Atkinson, R., Brook, J., Chang, H., Forastiere, F., Hoek, G., \u0026amp; Kappeler, R. (2023). Long-term exposure to traffic-related air pollution and stroke: a systematic review and meta-analysis. \u003cem\u003eInternational Journal of Hygiene and Environmental Health\u003c/em\u003e,\u003cem\u003e\u0026nbsp;247\u003c/em\u003e, 114079.\u003c/li\u003e\n \u003cli\u003eJaafarzadeh Haghighi Fard, N., Jahedi, F., \u0026amp; Dehdarirad, H. (2023). The Possibility of Microplastic Removal by Earthworms and Comparing With Conventional Chemical Removal Methods (A Global and Deeply Systematic Review). \u003cem\u003eJournal of Polymers and the Environment\u003c/em\u003e,\u003cem\u003e\u0026nbsp;31\u003c/em\u003e(12), 5050-5064.\u003c/li\u003e\n \u003cli\u003eJaafarzadeh, N., Nouhjah, S., Shahbazian, H., \u0026amp; Shenavar, B. (2024). The relationship between hot spots of air pollution and the incidence of gestational diabetes based on spatial analysis: A study on one of the most air-polluted metropolis of Iran. \u003cem\u003eEnvironmental Health Engineering And Management Journal\u003c/em\u003e, 0-0.\u003c/li\u003e\n \u003cli\u003eJahedi, F., Dehdari Rad, H., Goudarzi, G., Tahmasebi Birgani, Y., Babaei, A. A., \u0026amp; Ahmadi Angali, K. (2021). Polycyclic aromatic hydrocarbons in PM1, PM2.5 and PM10 atmospheric particles: identification, sources, temporal and spatial variations. \u003cem\u003eJournal of Environmental Health Science and Engineering\u003c/em\u003e,\u003cem\u003e\u0026nbsp;19\u003c/em\u003e(1), 851-866. \u003ca href=\"https://doi.org/10.1007/s40201-021-00652-7\"\u003ehttps://doi.org/10.1007/s40201-021-00652-7\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eKazemi, Z., Kazemi, Z., Jafari, A. J., Farzadkia, M., Hosseini, J., Amini, P., Shahsavani, A., \u0026amp; Kermani, M. (2024). Estimating the health impacts of exposure to Air pollutants and the evaluation of changes in their concentration using a linear model in Iran. \u003cem\u003eToxicology Reports\u003c/em\u003e,\u003cem\u003e\u0026nbsp;12\u003c/em\u003e, 56-64.\u003c/li\u003e\n \u003cli\u003eKebriaeezadeh, S., Ghodduosi, J., Alesheikh, A. A., Arjmandi, R., \u0026amp; Seyed Mirzahossieni, S. A. (2023). Presenting a Programme for Estrategical Managment to Control Air Pollution (Case Study: Isfahan). \u003cem\u003eEnvironmental Researches\u003c/em\u003e,\u003cem\u003e\u0026nbsp;14\u003c/em\u003e(27), 59-76.\u003c/li\u003e\n \u003cli\u003eKulick, E. R., Kaufman, J. D., \u0026amp; Sack, C. (2023). Ambient air pollution and stroke: an updated review. \u003cem\u003eStroke\u003c/em\u003e,\u003cem\u003e\u0026nbsp;54\u003c/em\u003e(3), 882-893.\u003c/li\u003e\n \u003cli\u003eLelieveld, J., Haines, A., Burnett, R., Tonne, C., Klingm\u0026uuml;ller, K., M\u0026uuml;nzel, T., \u0026amp; Pozzer, A. (2023). Air pollution deaths attributable to fossil fuels: observational and modelling study. \u003cem\u003ebmj\u003c/em\u003e,\u003cem\u003e\u0026nbsp;383\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eMohammad-Beigi, H., Nouri, J., \u0026amp; Liaghati, H. (2015). Strategic analysis of bus rapid transit system in improvement of public transportation: Case of Tehran, Iran. \u003cem\u003eModern Applied Science\u003c/em\u003e,\u003cem\u003e\u0026nbsp;9\u003c/em\u003e(9), 169.\u003c/li\u003e\n \u003cli\u003eMontone, R. A., Rinaldi, R., Bonanni, A., Severino, A., Pedicino, D., Crea, F., \u0026amp; Liuzzo, G. (2023). Impact of air pollution on ischemic heart disease: evidence, mechanisms, clinical perspectives. \u003cem\u003eAtherosclerosis\u003c/em\u003e,\u003cem\u003e\u0026nbsp;366\u003c/em\u003e, 22-31.\u003c/li\u003e\n \u003cli\u003eOlesiejuk, K., \u0026amp; Chałubiński, M. (2023). How does particulate air pollution affect barrier functions and inflammatory activity of lung vascular endothelium? \u003cem\u003eAllergy\u003c/em\u003e,\u003cem\u003e\u0026nbsp;78\u003c/em\u003e(3), 629-638.\u003c/li\u003e\n \u003cli\u003ePuyt, R. W., Lie, F. B., \u0026amp; Wilderom, C. P. (2023). The origins of SWOT analysis. \u003cem\u003eLong Range Planning\u003c/em\u003e,\u003cem\u003e\u0026nbsp;56\u003c/em\u003e(3), 102304.\u003c/li\u003e\n \u003cli\u003eReza, M., Seyed Ali, J., Rokhshad, H., Mojgan, Z., \u0026amp; Saeed, M. (2021). A Strategic Management Plan for Reducing Air Pollution Using the SWOT Model: A Case Study of District 2 of Tehran Municipality. \u003cem\u003eAnthropogenic Pollution Journal\u003c/em\u003e,\u003cem\u003e\u0026nbsp;5\u003c/em\u003e(2), 85-92. https://www.magiran.com/paper/2342389\u003c/li\u003e\n \u003cli\u003eSadeghi, H. A., \u0026amp; Sadeghi, R. (2024). Temporal Analysis of Air Pollution Effects on Cardiovascular Diseases and Mortality in Ahvaz, Iran. \u003cem\u003eInternational Journal of Population Issues\u003c/em\u003e,\u003cem\u003e\u0026nbsp;1\u003c/em\u003e(2), 71-85.\u003c/li\u003e\n \u003cli\u003eSaffar, A. K., Norouzi, H., Choobkar, N., \u0026amp; Kermanshahi, L. S. (2023). SEASONAL AND SPATIAL ZONING OF AIR QUALITY INDEX AND AMBIENT AIR POLLUTANTS IN AHVAZ OIL AND GAS FACTORIES WITH GEOGRAPHIC INFORMATION SYSTEM. \u003cem\u003eEnvironmental Engineering \u0026amp; Management Journal (EEMJ)\u003c/em\u003e,\u003cem\u003e\u0026nbsp;22\u003c/em\u003e(5).\u003c/li\u003e\n \u003cli\u003eSalmabadi, H., Saeedi, M., Roy, A., \u0026amp; Kaskaoutis, D. G. (2023). Quantifying the contribution of middle eastern dust sources to PM10 levels in Ahvaz, southwest Iran. \u003cem\u003eAtmospheric Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;295\u003c/em\u003e, 106993.\u003c/li\u003e\n \u003cli\u003eShinde, P. A., Abbas, Q., Chodankar, N. R., Ariga, K., Abdelkareem, M. A., \u0026amp; Olabi, A. G. (2023). Strengths, weaknesses, opportunities, and threats (SWOT) analysis of supercapacitors: A review. \u003cem\u003eJournal of Energy Chemistry\u003c/em\u003e,\u003cem\u003e\u0026nbsp;79\u003c/em\u003e, 611-638.\u003c/li\u003e\n \u003cli\u003eSicard, P., Agathokleous, E., Anenberg, S. C., De Marco, A., Paoletti, E., \u0026amp; Calatayud, V. (2023). Trends in urban air pollution over the last two decades: A global perspective. \u003cem\u003eScience of The Total Environment\u003c/em\u003e,\u003cem\u003e\u0026nbsp;858\u003c/em\u003e, 160064.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Air pollution, Air quality management, SWOT-AHP, Ahvaz, Source apportionment, Smart environmental strategies","lastPublishedDoi":"10.21203/rs.3.rs-5993611/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5993611/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Air pollution significantly impacts global health, contributing to approximately 3.7 million premature deaths annually. Ahvaz, as one of the most polluted cities in the world, experiences severe air pollution due to urbanization, industrial expansion, and transportation. This study aims to identify pollution sources, evaluate their impact through a hybrid SWOT-AHP analysis, and propose innovative air quality management strategies based on global best practices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A combination of emission inventory analysis, geographic information system (GIS) mapping, and a multi-criteria decision-making (MCDM) approach was applied to assess key pollution sources. SWOT analysis was integrated with the Analytical Hierarchy Process (AHP) to prioritize effective interventions for air quality improvement. Comparative analysis was conducted with cities such as Beijing, New Delhi, and Los Angeles to benchmark pollution control measures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Nitrogen oxides (NOx) were identified as the most emitted pollutants in central Ahvaz, reaching 392 tons annually. Other major pollutants included carbon monoxide (CO) (89 tons/year), suspended particles (87 tons/year), and hydrocarbons (34 tons/year). The Ramin Power Plant accounted for 54% of SO2 emissions, while oil industries contributed to 82% of total pollutants. The hybrid SWOT-AHP analysis ranked \"Implementing an advanced air pollution monitoring system and smart traffic management\" as the most effective strategy. Benchmarking with other global cities revealed that implementing low-emission zones and transitioning to cleaner fuels significantly reduced air pollution levels. The AHP analysis prioritized strategies as Smart Monitoring System (46.7%) - The most effective approach, emphasizing real-time pollution tracking and traffic optimization. next Clean Fuel Transition (27.7%) - Reducing emissions by shifting industries and vehicles to low-emission fuels. Low-Emission Zones (16.0%) - Establishing restricted zones to control vehicular pollution.and Urban Green Infrastructure (9.5%) - Expanding green spaces to enhance air quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Strategic investments in pollution control technologies, combined with policy interventions such as emissions-based congestion pricing and green infrastructure expansion, are crucial for mitigating pollution in Ahvaz. The SWOT-AHP framework provided a structured approach to prioritizing actionable environmental management strategies based on feasibility and effectiveness.\u003c/p\u003e","manuscriptTitle":"Dynamic Evaluation of Air Pollution in Ahvaz: Source Apportionment, SWOT-AHP Analysis, and Innovative Control Strategies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-13 09:33:35","doi":"10.21203/rs.3.rs-5993611/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":"9aee7c45-2398-4928-ac48-7c55ef27e7b1","owner":[],"postedDate":"February 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44065215,"name":"Environmental Engineering"}],"tags":[],"updatedAt":"2025-02-13T09:33:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-13 09:33:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5993611","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5993611","identity":"rs-5993611","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}