Effects of Quasi-Steady Environment for PM2.5 Laser-based Monitoring System During Dry Season in Two Consecutive Years

Effects of Quasi-Steady Environment for PM2.5 Laser-based Monitoring System During Dry Season in Two Consecutive Years | 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 Effects of Quasi-Steady Environment for PM2.5 Laser-based Monitoring System During Dry Season in Two Consecutive Years Haryo Tomo, Kania Dewi, Puji Lestari This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3781195/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract PM2.5 particulates are known to be air pollutant species that can be transported over long distances. The movement of PM2.5 in certain conditions is not only influenced by changes in microclimate, especially wind speed, wind direction and radiative transfer mechanisms, but also because of the nature of Brownian motion. In this paper, the behaviour of the presence of PM2.5 during the Dry Season will be presented in two consecutive years (2017 and 2018) where monitoring uses laser-based instruments. Monitoring is carried out in locations that have calm wind distribution characteristics that reach more than 60%, meaning that convective air mass movements occur in a minimum (quasi-steady) amount. By locating monitoring equipment at this location, it is expected to provide an overview of the PM2.5 concentration patterns both daily and monthly and prove the preposition that the two pollutant parameters are able to be present in locations that have quasi-steady conditions due to non-convective transport mechanisms. calm wind dry season quasi-steady PM10/PM2.5 Figures Figure 1 Figure 2 Figure 3 Introduction Air pollution episodes are related to seasonal patterns in an area, both local and regional ([13], [5], [3], [8], [12]). This relationship can be caused by anthropogenic pollution sources or wind distribution patterns that move pollutants from one area to another. In tropical regions, the incidence of air pollution in the ambient mostly takes place in the dry season. ([4], [2], [7], [17]). Indonesia, as one of the tropical countries, also has the highest episode of air pollution in the dry season. In the Figure 1 it can be shown that the increase in air pollution in bigger city, like Jakarta, the last 3 years reached its highest in the dry season. This event has the potential to increase the morbidity of air pollution affected diseases, including ARI (Acute Respiratory Infection), hypertension and others ([14], [9], [16], [10]). It is also known that some parameters of air pollution are long distance transported. This means that the pollution of an area can also be caused by its formation in other regions. Cases such as forest and land fires, massive volcanic eruptions and extensive land clearance will play a role in the occurrence of this phenomenon [11]. Likewise, current issues about microplastics, which is proven can be transported in a very long distance and time scale ([6], [1], [15]). The method of rapid identification using laser-based instruments is an emerging technology that can evaluate changes in the amount of PM2.5 concentration in the air. In recent years, this method has been developed as an alternative to identifying PM2.5 in gravimetric-based ambient air. Low-cost sensor is recently utilized to measure the ambient particulate matter (PM) based on the scaling of total light scattering intensity by particles. It should enable wide-ranging and high-density spatiotemporal measurements to be conducted. Instantaneous response can be identified on changes of light scattering-based low-cost PM sensors (LCSs) as a function of the variability of air quality. Immediately, the level of air quality can be seen by users to respond to it. The laser with intensity about 650 nm, a phototransistor and a focusing lens are the general main components of LCSs. This paper will present the results of an assessment of air pollution concentration of PM2.5 (Particulate Matter <2.5 micron) and PM10 (Particulate Matter <10 Micron) in the city of Bandung, especially in the ITB Sports Facility area. Where the selected location is based on the preposition that in an environment that has topographic characteristics such as a 'bowl', the calm wind distribution can be very dominant. This study is aimed for researchers and engineers to consider the environmental behavior surrounding PM 2.5 and PM10 monitoring system. Moreover, it is also for the regulator, this study also provides an insight understanding on mitigation to reduce the concentration of ambient PM2.5 and PM10 based on certain local meteorological aspects. Methods The method used for this study is the analysis of data from the primary monitoring produced by the low-cost sensor PMS7005 (Plant Tower) instrument with PM2.5 parameters during the period May 2017 - August 2019. While the meteorological instrument is used Ambient PWS Weather 1002. Both of these instruments were installed at the ITB Sports Facility, Jl. Tamansari Bandung (6°53'10.4"S 107°36'35.3"E) at an altitude of 4 m above ground level. Where the source of electricity is AC 220 Volt / 55Hz. While the data is stored to the cloud server using the GPRS network. Quasi-steady in the Sampling Location Quasi-steady is defined as the event where the change of certain parameters with respect to time approaches 0. Wind is the main vector driving the mass of air in an area with a certain vector. When the amount of calm wind is very dominant to more than 60%, the horizontal driving vector approaches steady state. So that the movement of air will be dominated by a microclimate that moves air at very close distances. The results of monitoring the direction and speed of air at the study site show the distribution as shown in Figure 2. In long-term monitoring (30 years) the amount of calm wind reaches 71% of the overall direction and speed of the wind. Whereas the dry season of 2017 and 2018 (June-August) shows a similar profile to long-term observations, but with a calm wind of 61% and 62% respectively. While in the dry season 2019 shows the amount of 50%. This data was obtained from a simulation of global satellite observations by EUMETSAT and US-NOAA in collaboration with the University of Basel, Switzerland. Another thing to note in this depiction is that the prevailing direction of the vector of wind movement is from East to South. Where in the 30-years monitoring there was an extension from the Northwest to the Northeast. In terms of discussion, the pollutants in the study area are dominated from South to East. Due to the meteorological conditions approaching quasi-steady conditions, the decay mechanism of PM2.5 in ambient air will depend on the deposition pattern, both wet and dry. In the dry season, the deposition mechanism will be influenced by horizontal and vertical wind vectors. Where for the vertical wind direction is a further effect of changes in temperature due to sun exposure. During the day, there is potential for up-lifting because the ground surface temperature is higher than in the air, while at night the opposite occurs. Whereas in the rainy season, the wet deposition mechanism is dominant, where the decay of PM2.5 will be affected by the increase in moisture in individual particles and the rain mechanism. The addition of moisture to the grain particles will increase the speed of settling discretely. PM2.5 in Dry Season PM2.5 can be produced from anthropogenic or natural processes. Anthropogenic processes that have great potential to produce primary PM2.5 are transportation, industry, and biomass burning. While secondary PM2.5 products such as Bioaerosol and Inorganic Aerosol can be generated from photochemical processes. The physical properties of PM2.5, which are small with a density slightly above the weight of the air cause the pattern of movement and distribution has a unique character. At large horizontal wind speeds PM2.5 can be carried along. But at low air speeds PM2.5 can still move to follow Brownian Motion. This condition is described by researchers in this paper as PM2.5 movements under quasi-steady environment. The dry season is a critical position in the formation of air pollutants in the atmosphere due to the absence of inhibitor aspects that can reduce levels, namely rain and wind. Rain will help the wet deposition of particles while the wind can disperse pollutants to further locations so that the concentration will decrease. PM2.5 has the potential to cause health problems to mortality. Study given by [18] and [19] show a significant correlation between PM2.5 increase with mortality and hospitalization in developed and developing countries. In more detail it is mentioned that there is a linear relationship between PM2.5 on the ambient level with the exposure level at the receptor. In Figure 2 it is shown that at the study site, the profile of wind speed and direction is highly dominated by calm wind, so that the generation of pollutants is reinforced. PM2.5 generation at the site will have difficulty dispersing further or vertical deposition. PM2.5 monitoring results at the study site June 2017 – December 2018 (N=529) can be seen in Figure 3. In the dry season, the average concentration of hours for the PM2.5 parameter is always higher than in the rainy season. In the case of 2018 there was a specific activity in the form of repairing a soccer field in the middle of the area in preparation for the 2018 Asian Games so that there was a very significant increase in PM2.5 concentration. Where the peak on July 8, 2018, reached 520 ug / m3. Unlike the conditions in 2017, there are no specific activities other than undergraduate graduation that directly contribute to PM2.5 ambient level. However, the average concentration in 2017 was still slightly higher (216 μg / m3) compared to 2018 (213 μg / m3). Associated with the influence of quasi-steady conditions can be shown by the component standard deviation on the monitoring results. Sequentially, the magnitude of the standard deviation in the dry season shows a value of 27.79 ug / m3 (13% deviation to the mean) while 2018 is 33.06 ug / m3 (15% deviation to the average). This standard deviation value is much smaller than the overall data which reaches 47.1 ug / m3. That is, although the dry season Windrose profile is similar to the 30-years profile, it has little impact on changes in the mean PM2.5 concentration. The only mechanism that changes behavior is rainfall, which can cause a decrease in the mean PM2.5 value in the study location, which is indicated by its effect on the magnitude of the overall standard deviation. Conclusion The conclusion that can be obtained in this study is that the quasi-steady environment temporarily causes the distribution of concentration at the PM2.5 generation rate to be more constant, both daily and monthly. Especially in the dry season, high concentrations will continue for 3 months. The deposition factor, wet or dry, plays a very significant role in decreasing PM2.5 concentration in quasi-steady environment. As a result, the PM2.5 decay will be determined by the rain and vertical vector of air velocity at that location naturally. To reduce receptor exposure, it is important to maintain the deposition of PM2.5 to a certain level by periodic water spraying or limit the activity duration within the location. References Alam, F. C., Sembiring, E., Muntalif, B. S., & Suendo, V. Microplastic distribution in surface water and sediment river around slum and industrial area (case study: Ciwalengke River, Majalaya district, Indonesia). Chemosphere, 224, 637-645. (2019). Amaral, Simone Simões, Maria Angélica Martins Costa, Turibio Gomes Soares Neto, Marillia Pereira Costa, Fabiana Ferrari Dias, Edson Anselmo, José Carlos dos Santos, and João Andrade de Carvalho Jr. CO2, CO, hydrocarbon gases and PM2. 5 emissions on dry season by deforestation fires in the Brazilian Amazonia. Environmental Pollution 249: 311-320. (2019). Casal, P., Castro-Jiménez, J., Pizarro, M., Katsoyiannis, A., & Dachs, J. Seasonal soil/snow-air exchange of semivolatile organic pollutants at a coastal arctic site (Tromsø, 69° N). Science of the Total Environment, 636, 1109-1116. (2018). Chowdhury, S., Dey, S., Di Girolamo, L., Smith, K. R., Pillarisetti, A., & Lyapustin, A. Tracking ambient PM2. 5 build-ups in Delhi national capital region during the dry season over 15 years using a high-resolution (1 km) satellite aerosol dataset. Atmospheric Environment, 204, 142-150. (2019). Emami, F., Masiol, M., & Hopke, P. K. Air pollution at Rochester, NY: long-term trends and multivariate analysis of upwind SO2 source impacts. Science of The Total Environment, 612, 1506-1515. (2018). Gao, F., Li, J., Sun, C., Zhang, L., Jiang, F., Cao, W., & Zheng, L. Study on the capability and characteristics of heavy metals enriched on microplastics in marine environment. Marine pollution bulletin, 144, 61-67. (2019). Kiely, Laura, Dominick Spracklen, Stephen Arnold, John Marsham, Carly Reddington, Luke Conibear, Christoph Knote, Mikinori Kuwata, and Sri Hapsari Budisulistiorini. "Impact of Indonesian fires on Equatorial Asian air quality between 2002 and 2015." In EGU General Assembly Conference Abstracts, 20, p. 14579. (2018). Laban, T. L., Van Zyl, P. G., Beukes, J. P., Vakkari, V., Jaars, K., Borduas-Dedekind, N., ... & Laakso, L. Seasonal influences on surface ozone variability in continental South Africa and implications for air quality. Atmospheric Chemistry and Physics. (2018). Lehtomäki, H., Korhonen, A., Asikainen, A., Karvosenoja, N., Kupiainen, K., Paunu, V. V., ... & Kukkonen, J. Health impacts of ambient air pollution in Finland. International journal of environmental research and public health, 15(4), 736. (2018). Lestari, P., & Hendra, Y. Fine and Coarse Particle Concentration and Composition Measured In Urban And Non-Urban Area Bandung, West Java-Indonesia. In IOP Conference Series: Earth and Environmental Science, 303(1), p. 012043. IOP Publishing. (2019). López-Martín, M., González-Vila, F. J., & Knicker, H. Distribution of black carbon and black nitrogen in physical soil fractions from soils seven years after an intense forest fire and their role as C sink. Science of the Total Environment, 637, 1187-1196. (2018). Manzano, C. A., Dodder, N. G., Hoh, E., & Morales, R. Patterns of Personal Exposure to Urban Pollutants Using Personal Passive Samplers and GC× GC/ToF–MS. Environmental science & technology, 53(2), 614-624. (2018). Meng, Xianyong, Yiping Wu, Zhihua Pan, Hao Wang, Gang Yin, and Honggang Zhao. Seasonal Characteristics and Particle-size Distributions of Particulate Air Pollutants in Urumqi. International journal of environmental research and public health 16, no. 396. (2019). Nhung, N. T. T., Schindler, C., Dien, T. M., Probst-Hensch, N., Perez, L., & Künzli, N. Acute effects of ambient air pollution on lower respiratory infections in Hanoi children: An eight-year time series study. Environment international, 110, 139-148. (2018). Obbard, R. W. Microplastics in polar regions: the role of long-range transport. Current Opinion in Environmental Science & Health, 1, 24-29. (2018). Rana, J., Uddin, J., Peltier, R., & Oulhote, Y. Associations between Indoor Air Pollution and Acute Respiratory Infections among Under-Five Children in Afghanistan: Do SES and Sex Matter? International journal of environmental research and public health, 16(16), 2910. (2019). Thepnuan, D., Chantara, S., Lee, C. T., Lin, N. H., & Tsai, Y. I. Molecular markers for biomass burning associated with the characterization of PM2. 5 and component sources during dry season haze episodes in Upper South East Asia. Science of The Total Environment, 658, 708-722. (2019). Uju Shin, Sang-Hun Park, Joon-Sung Park, Ja-Ho Koo, Changhyun Yoo, Soontae Kim, Jae-bum Lee, Predictability of PM2.5 in Seoul based on atmospheric blocking forecasts using the NCEP global forecast system, Atmospheric Environment, Volume 246, ISSN 1352-2310, https://doi.org/10.1016/j.atmosenv.2020.118141 . (2021) Yitshak-Sade M, Bobb JF, Schwartz JD, Kloog I, Zanobetti A. The association between short and long-term exposure to PM2.5 and temperature and hospital admissions in New England and the synergistic effect of the short-term exposures. Sci Total Environ. 2018 Oct 15;639:868-875. doi: 10.1016/j.scitotenv.2018.05.181. (2018) Declarations Acknowledgement The authors would like to thank the ITB P3MI research scheme, KK Sport Science ITB and ITB Sports Facility Managers for providing support in this research. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3781195","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264097381,"identity":"036b583f-cee6-4ec6-898a-c88d2ac7bf5d","order_by":0,"name":"Haryo Tomo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACAziLvQHEtSBWSwIQ8xwAcSVI0SIBIhiI0GLOfvaZxMcfNtH8ks+vbvhRIMHA396dgFeLZU+6meSMhLTcmbNzym72AB0mcebsBvwOO5DGJs2TcDh3w+2ctBs8QC0GErkEtJx/BtVy80zazT9EabkBs+UG+7HbxNly4xmz5Yw0oF96cthuyxhI8BD2y/k0xhsfbGxy+9mPP7v55o+NHH97L34tQMACjQsecBzxEFIOAswfIDT7A2JUj4JRMApGwQgEACmwSCCiV4W1AAAAAElFTkSuQmCC","orcid":"","institution":"Air and Waste Management FTSL - Institute of Technology Bandung","correspondingAuthor":true,"prefix":"","firstName":"Haryo","middleName":"","lastName":"Tomo","suffix":""},{"id":264097382,"identity":"91da96a9-c3bf-45b2-8bee-d7a1445fff13","order_by":1,"name":"Kania Dewi","email":"","orcid":"","institution":"Air and Waste Management FTSL - Institute of Technology Bandung","correspondingAuthor":false,"prefix":"","firstName":"Kania","middleName":"","lastName":"Dewi","suffix":""},{"id":264097383,"identity":"c929db9b-edc8-4930-a87d-dda5383c56b4","order_by":2,"name":"Puji Lestari","email":"","orcid":"","institution":"Air and Waste Management FTSL - Institute of Technology Bandung","correspondingAuthor":false,"prefix":"","firstName":"Puji","middleName":"","lastName":"Lestari","suffix":""}],"badges":[],"createdAt":"2023-12-20 09:59:18","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3781195/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-3781195/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53748421,"identity":"146ad97b-f8de-4ffd-871c-b07b109aa1a3","added_by":"auto","created_at":"2024-03-29 18:23:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":231208,"visible":true,"origin":"","legend":"\u003cp\u003ePM 2.5 concentration (ug/m3) in Central Jakarta\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3781195/v2/ae88494a02d4f096149f9486.png"},{"id":53748420,"identity":"e5a2ca18-eebb-4ba7-94f1-4b72cfdcae0e","added_by":"auto","created_at":"2024-03-29 18:23:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153099,"visible":true,"origin":"","legend":"\u003cp\u003eWindrose of Several Time Reference at Location\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3781195/v2/74ada510ed015d2340da0089.png"},{"id":53749350,"identity":"a5d28494-95c3-4237-8a52-46ae57720f17","added_by":"auto","created_at":"2024-03-29 18:31:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10978,"visible":true,"origin":"","legend":"\u003cp\u003ePM2.5 Monitoring at Location June 2017 - Dec 2018\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3781195/v2/071155cef2208a04339d6c51.png"},{"id":53750378,"identity":"16cc333f-c595-49ba-b7c7-5c39f7906cf7","added_by":"auto","created_at":"2024-03-29 18:39:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":465069,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3781195/v2/a32b7006-d047-4510-a197-66d7fd139c09.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"Effects of Quasi-Steady Environment for PM2.5 Laser-based Monitoring System During Dry Season in Two Consecutive Years","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAir pollution episodes are related to seasonal patterns in an area, both local and regional ([13], [5], [3], [8], [12]). This relationship can be caused by anthropogenic pollution sources or wind distribution patterns that move pollutants from one area to another. In tropical regions, the incidence of air pollution in the ambient mostly takes place in the dry season. ([4], [2], [7], [17]).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIndonesia, as one of the tropical countries, also has the highest episode of air pollution in the dry season. In the Figure 1 it can be shown that the increase in air pollution in bigger city, like Jakarta, the last 3 years reached its highest in the dry season. This event has the potential to increase the morbidity of air pollution affected diseases, including ARI (Acute Respiratory Infection), hypertension and others ([14], [9], [16], [10]).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt is also known that some parameters of air pollution are long distance transported. This means that the pollution of an area can also be caused by its formation in other regions. Cases such as forest and land fires, massive volcanic eruptions and extensive land clearance will play a role in the occurrence of this phenomenon [11]. Likewise, current issues about microplastics, which is proven can be transported in a very long distance and time scale ([6], [1], [15]).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe method of rapid identification using laser-based instruments is an emerging technology that can evaluate changes in the amount of PM2.5 concentration in the air. In recent years, this method has been developed as an alternative to identifying PM2.5 in gravimetric-based ambient air. Low-cost sensor is recently utilized to measure the ambient particulate matter (PM) based on the scaling of total light scattering intensity by particles. It should enable wide-ranging and high-density spatiotemporal measurements to be conducted. Instantaneous response can be identified on changes of light scattering-based low-cost PM sensors (LCSs) as a function of the variability of air quality. Immediately, the level of air quality can be seen by users to respond to it. The laser with intensity about 650 nm, a phototransistor and a focusing lens are the general main components of LCSs.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis paper will present the results of an assessment of air pollution concentration of PM2.5 (Particulate Matter \u0026lt;2.5 micron) and PM10 (Particulate Matter \u0026lt;10 Micron) in the city of Bandung, especially in the ITB Sports Facility area. Where the selected location is based on the preposition that in an environment that has topographic characteristics such as a \u0026apos;bowl\u0026apos;, the calm wind distribution can be very dominant.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study is aimed for researchers and engineers to consider the environmental behavior surrounding PM 2.5 and PM10 monitoring system. Moreover, it is also for the regulator, this study also provides an insight understanding on mitigation to reduce the concentration of ambient PM2.5 and PM10 based on certain local meteorological aspects.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe method used for this study is the analysis of data from the primary monitoring produced by the low-cost sensor PMS7005 (Plant Tower) instrument with PM2.5 parameters during the period May 2017 - August 2019. While the meteorological instrument is used Ambient PWS Weather 1002.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBoth of these instruments were installed at the ITB Sports Facility, Jl. Tamansari Bandung (6°53'10.4\"S 107°36'35.3\"E) at an altitude of 4 m above ground level. Where the source of electricity is AC 220 Volt / 55Hz. While the data is stored to the cloud server using the GPRS network.\u003c/p\u003e\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"},{"header":"Quasi-steady in the Sampling Location","content":"\u003cp\u003eQuasi-steady is defined as the event where the change of certain parameters with respect to time approaches 0. Wind is the main vector driving the mass of air in an area with a certain vector. When the amount of calm wind is very dominant to more than 60%, the horizontal driving vector approaches steady state. So that the movement of air will be dominated by a microclimate that moves air at very close distances.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eThe results of monitoring the direction and speed of air at the study site show the distribution as shown in Figure 2. In long-term monitoring (30 years) the amount of calm wind reaches 71% of the overall direction and speed of the wind. Whereas the dry season of 2017 and 2018 (June-August) shows a similar profile to long-term observations, but with a calm wind of 61% and 62% respectively. While in the dry season 2019 shows the amount of 50%. This data was obtained from a simulation of global satellite observations by EUMETSAT and US-NOAA in collaboration with the University of Basel, Switzerland.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eAnother thing to note in this depiction is that the prevailing direction of the vector of wind movement is from East to South. Where in the 30-years monitoring there was an extension from the Northwest to the Northeast. In terms of discussion, the pollutants in the study area are dominated from South to East.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eDue to the meteorological conditions approaching quasi-steady conditions, the decay mechanism of PM2.5 in ambient air will depend on the deposition pattern, both wet and dry. In the dry season, the deposition mechanism will be influenced by horizontal and vertical wind vectors. Where for the vertical wind direction is a further effect of changes in temperature due to sun exposure. During the day, there is potential for up-lifting because the ground surface temperature is higher than in the air, while at night the opposite occurs. Whereas in the rainy season, the wet deposition mechanism is dominant, where the decay of PM2.5 will be affected by the increase in moisture in individual particles and the rain mechanism. The addition of moisture to the grain particles will increase the speed of settling discretely.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"PM2.5 in Dry Season","content":"\u003cp\u003ePM2.5 can be produced from anthropogenic or natural processes. Anthropogenic processes that have great potential to produce primary PM2.5 are transportation, industry, and biomass burning. While secondary PM2.5 products such as Bioaerosol and Inorganic Aerosol can be generated from photochemical processes.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eThe physical properties of PM2.5, which are small with a density slightly above the weight of the air cause the pattern of movement and distribution has a unique character. At large horizontal wind speeds PM2.5 can be carried along. But at low air speeds PM2.5 can still move to follow Brownian Motion. This condition is described by researchers in this paper as PM2.5 movements under quasi-steady environment.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003eThe dry season is a critical position in the formation of air pollutants in the atmosphere due to the absence of inhibitor aspects that can reduce levels, namely rain and wind. Rain will help the wet deposition of particles while the wind can disperse pollutants to further locations so that the concentration will decrease.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003ePM2.5 has the potential to cause health problems to mortality. Study given by [18] and [19] show a significant correlation between PM2.5 increase with mortality and hospitalization in developed and developing countries. In more detail it is mentioned that there is a linear relationship between PM2.5 on the ambient level with the exposure level at the receptor.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eIn Figure 2 it is shown that at the study site, the profile of wind speed and direction is highly dominated by calm wind, so that the generation of pollutants is reinforced. PM2.5 generation at the site will have difficulty dispersing further or vertical deposition. PM2.5 monitoring results at the study site June 2017 – December 2018 (N=529) can be seen in Figure 3.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eIn the dry season, the average concentration of hours for the PM2.5 parameter is always higher than in the rainy season. In the case of 2018 there was a specific activity in the form of repairing a soccer field in the middle of the area in preparation for the 2018 Asian Games so that there was a very significant increase in PM2.5 concentration. Where the peak on July 8, 2018, reached 520 ug / m3. Unlike the conditions in 2017, there are no specific activities other than undergraduate graduation that directly contribute to PM2.5 ambient level. However, the average concentration in 2017 was still slightly higher (216 μg / m3) compared to 2018 (213 μg / m3).\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eAssociated with the influence of quasi-steady conditions can be shown by the component standard deviation on the monitoring results. Sequentially, the magnitude of the standard deviation in the dry season shows a value of 27.79 ug / m3 (13% deviation to the mean) while 2018 is 33.06 ug / m3 (15% deviation to the average). This standard deviation value is much smaller than the overall data which reaches 47.1 ug / m3. That is, although the dry season Windrose profile is similar to the 30-years profile, it has little impact on changes in the mean PM2.5 concentration. The only mechanism that changes behavior is rainfall, which can cause a decrease in the mean PM2.5 value in the study location, which is indicated by its effect on the magnitude of the overall standard deviation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe conclusion that can be obtained in this study is that the quasi-steady environment temporarily causes the distribution of concentration at the PM2.5 generation rate to be more constant, both daily and monthly. Especially in the dry season, high concentrations will continue for 3 months.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe deposition factor, wet or dry, plays a very significant role in decreasing PM2.5 concentration in quasi-steady environment. As a result, the PM2.5 decay will be determined by the rain and vertical vector of air velocity at that location naturally. To reduce receptor exposure, it is important to maintain the deposition of PM2.5 to a certain level by periodic water spraying or limit the activity duration within the location. \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eAlam, F. C., Sembiring, E., Muntalif, B. S., \u0026amp; Suendo, V. Microplastic distribution in surface water and sediment river around slum and industrial area (case study: Ciwalengke River, Majalaya district, Indonesia).\u0026nbsp;Chemosphere,\u0026nbsp;224, 637-645. (2019).\u003c/li\u003e\n \u003cli\u003eAmaral, Simone Sim\u0026otilde;es, Maria Ang\u0026eacute;lica Martins Costa, Turibio Gomes Soares Neto, Marillia Pereira Costa, Fabiana Ferrari Dias, Edson Anselmo, Jos\u0026eacute; Carlos dos Santos, and Jo\u0026atilde;o Andrade de Carvalho Jr. CO2, CO, hydrocarbon gases and PM2. 5 emissions on dry season by deforestation fires in the Brazilian Amazonia. 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(2018)\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the ITB P3MI research scheme, KK Sport Science ITB and ITB Sports Facility Managers for providing support in this research.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"calm wind, dry season, quasi-steady, PM10/PM2.5","lastPublishedDoi":"10.21203/rs.3.rs-3781195/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3781195/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePM2.5 particulates are known to be air pollutant species that can be transported over long distances. The movement of PM2.5 in certain conditions is not only influenced by changes in microclimate, especially wind speed, wind direction and radiative transfer mechanisms, but also because of the nature of Brownian motion. In this paper, the behaviour of the presence of PM2.5 during the Dry Season will be presented in two consecutive years (2017 and 2018) where monitoring uses laser-based instruments. Monitoring is carried out in locations that have calm wind distribution characteristics that reach more than 60%, meaning that convective air mass movements occur in a minimum (quasi-steady) amount. By locating monitoring equipment at this location, it is expected to provide an overview of the PM2.5 concentration patterns both daily and monthly and prove the preposition that the two pollutant parameters are able to be present in locations that have quasi-steady conditions due to non-convective transport mechanisms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Effects of Quasi-Steady Environment for PM2.5 Laser-based Monitoring System During Dry Season in Two Consecutive Years","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2024-03-29 18:23:38","doi":"10.21203/rs.3.rs-3781195/v2","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}},{"code":1,"date":"2023-12-28 17:40:55","doi":"10.21203/rs.3.rs-3781195/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":"ddc0a183-03c5-41e1-aaab-ee58c9898a15","owner":[],"postedDate":"March 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-03T15:14:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-29 18:23:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-3781195","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3781195","identity":"rs-3781195","version":["v2"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}