Mahsa Ashouri, Frederick Kin Hing Phoa, Chun-Hhouh Chen, Galit Shmueli
Examining PM2.5 (atmospheric particulate matter with a maximum diameter of 2.5 micrometers), seasonal patterns is an important research area for environmental scientists. An improved understanding of PM2.5 seasonal patterns can help environmental protection agencies (EPAs) make decisions and develop complex models for controlling the concentration of PM2.5 in different regions. This work proposes an R Shiny App web-based interactive tool, namely a “model-based time series clustering” (MTSC) tool, for clustering PM2.5 time series using spatial and population variables and their temporal features, like seasonality. Our tool allows stakeholders to visualize important characteristics of PM2.5 time series, including temporal patterns and missing values, and cluster series by attribute groupings. We apply the MTSC tool to cluster Taiwan’s PM2.5 time series based on air quality zones and types of monitoring stations. The tool clusters the series into four clusters that reveal several phenomena, including an improvement in Taiwan's air quality since 2017 in all regions, although at varying rates, an increasing pattern of PM2.5 concentration when moving from northern towards southern regions, winter/summer seasonal patterns that are more pronounced in certain types of areas (e.g., industrial), and unusual behavior in the southernmost region. The tool provides cluster-specific quantitative figures, like seasonal variations in PM2.5 concentration in different air quality zones of Taiwan, and identifies, for example, an annual peak in early January and February (maximum value around 120 μg m-3). Our analysis identifies a region in southernmost Taiwan as different from other zones that are currently grouped together with it by Taiwan EPA (TEPA), and a northern region that behaves differently from its TEPA grouping. All these cluster-based insights help EPA experts implement short-term zone-specific air quality policies (e.g., fireworks and traffic regulations, school closures) as well as longer-term decision-making (e.g., transport control stations, fuel permits, old vehicle replacement, fuel type).
{"title":"An Interactive Clustering-Based Visualization Tool for Air Quality Data Analysis","authors":"Mahsa Ashouri, Frederick Kin Hing Phoa, Chun-Hhouh Chen, Galit Shmueli","doi":"10.4209/aaqr.230124","DOIUrl":"https://doi.org/10.4209/aaqr.230124","url":null,"abstract":"Examining PM2.5 (atmospheric particulate matter with a maximum diameter of 2.5 micrometers), seasonal patterns is an important research area for environmental scientists. An improved understanding of PM2.5 seasonal patterns can help environmental protection agencies (EPAs) make decisions and develop complex models for controlling the concentration of PM2.5 in different regions. This work proposes an R Shiny App web-based interactive tool, namely a “model-based time series clustering” (MTSC) tool, for clustering PM2.5 time series using spatial and population variables and their temporal features, like seasonality. Our tool allows stakeholders to visualize important characteristics of PM2.5 time series, including temporal patterns and missing values, and cluster series by attribute groupings. We apply the MTSC tool to cluster Taiwan’s PM2.5 time series based on air quality zones and types of monitoring stations. The tool clusters the series into four clusters that reveal several phenomena, including an improvement in Taiwan's air quality since 2017 in all regions, although at varying rates, an increasing pattern of PM2.5 concentration when moving from northern towards southern regions, winter/summer seasonal patterns that are more pronounced in certain types of areas (e.g., industrial), and unusual behavior in the southernmost region. The tool provides cluster-specific quantitative figures, like seasonal variations in PM2.5 concentration in different air quality zones of Taiwan, and identifies, for example, an annual peak in early January and February (maximum value around 120 μg m-3). Our analysis identifies a region in southernmost Taiwan as different from other zones that are currently grouped together with it by Taiwan EPA (TEPA), and a northern region that behaves differently from its TEPA grouping. All these cluster-based insights help EPA experts implement short-term zone-specific air quality policies (e.g., fireworks and traffic regulations, school closures) as well as longer-term decision-making (e.g., transport control stations, fuel permits, old vehicle replacement, fuel type).","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135007918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaotian Mu, Wen-huan Wang, Kai Zhang, Honglei Ding, Weiguo Pan
Mullite catalysts have become one of the most widely studied catalysts due to their highly stable structure and unique coordination with oxygen. In this work, Ce-modified mullite-type oxides Y 1-x Ce x Mn 2 O 5 have been prepared by sol-gel method to explore their Ce doping amount-dependent catalytic performance for acetone elimination. Experimental results confirm that Y 0.9 Ce 0.1 Mn 2 O 5 had optimum acetone oxidation activity, completely achieving 100% acetone conversion at 120 ° C under the reaction conditions of acetone concentration = 1000 ppm, 20 vol% O 2 /N 2 and WHSV = 36000 mL g –1 h –1 . This excellent catalytic activity comes from its larger specific surface area and higher Mn 4+ /Mn 3+ molar ratio. XRD and TEM results show that YMn 2 O 5 and CeO 2 phases form a multiphase oxide and interfacial structure. XPS results show that the content of doped CeO 2 mainly affects the surface adsorbed oxygen (Oads) and Mn 4+ content of the catalyst. Manganese species with higher chemical states are indeed more favorable for oxidation reactions on manganese-based catalysts. In addition, the reduction temperature of mixed oxides shifts to the lower temperature region, indicating that manganese and cerium oxides are more reducible, where the mobility of oxygen species is greatly enhanced. Y 0.9 Ce 0.1 Mn 2 O 5 also exhibits strong long-term stability and has good resistance to acetone elimination, showing excellent potential in eliminating acetone.
{"title":"Promoted Catalytic Properties of Acetone over Cerium-Modified Mullite Catalyst YMn2O5","authors":"Xiaotian Mu, Wen-huan Wang, Kai Zhang, Honglei Ding, Weiguo Pan","doi":"10.4209/aaqr.220302","DOIUrl":"https://doi.org/10.4209/aaqr.220302","url":null,"abstract":"Mullite catalysts have become one of the most widely studied catalysts due to their highly stable structure and unique coordination with oxygen. In this work, Ce-modified mullite-type oxides Y 1-x Ce x Mn 2 O 5 have been prepared by sol-gel method to explore their Ce doping amount-dependent catalytic performance for acetone elimination. Experimental results confirm that Y 0.9 Ce 0.1 Mn 2 O 5 had optimum acetone oxidation activity, completely achieving 100% acetone conversion at 120 ° C under the reaction conditions of acetone concentration = 1000 ppm, 20 vol% O 2 /N 2 and WHSV = 36000 mL g –1 h –1 . This excellent catalytic activity comes from its larger specific surface area and higher Mn 4+ /Mn 3+ molar ratio. XRD and TEM results show that YMn 2 O 5 and CeO 2 phases form a multiphase oxide and interfacial structure. XPS results show that the content of doped CeO 2 mainly affects the surface adsorbed oxygen (Oads) and Mn 4+ content of the catalyst. Manganese species with higher chemical states are indeed more favorable for oxidation reactions on manganese-based catalysts. In addition, the reduction temperature of mixed oxides shifts to the lower temperature region, indicating that manganese and cerium oxides are more reducible, where the mobility of oxygen species is greatly enhanced. Y 0.9 Ce 0.1 Mn 2 O 5 also exhibits strong long-term stability and has good resistance to acetone elimination, showing excellent potential in eliminating acetone.","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70294284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Yuan, Jun-Hao Ceng, Po-Hsuan Yen, Kuan-Chen Chiang, Yu-Lun Tseng, Kwok-Wai Wong, M. Jeng
This study investigated the temporospatial variation, chemical composition, and source resolution of fine particles (PM 2.5 ) in the southeastern seas of the Taiwan Island. 24-hr PM 2.5 was sampled simultaneously at two remote sites, the Green Island (West Pacific Ocean; WPO) and the Kenting Peninsula (northern Bashi Channel; BC), in four seasons. After sampling, the chemical fingerprints of PM 2.5 were characterized and further applied to resolve the potential sources of PM 2.5 and their contribution by using a receptor model on the basis of chemical mass balance (CMB), enrichment factor (EF), and backward trajectory simulation. It showed that PM 2.5 concentrations in winter (10.8 µ g m –3 ) and spring (12.0 µ g m –3 ) (i.e., during the period of Asian Northeastern Monsoons; ANMs) were higher than those in summer (4.0 µ g m –3 ) and fall (6.6 µ g m –3 ). In terms of chemical composition of PM 2.5 , secondary inorganic aerosols (SIAs = NO 3– , SO 42– , and NH 4+ ) (56.7–67.2%) were the dominant component of water-soluble ions (WSIs) in PM 2.5 , while crustal elements (Mg, Al, Ca, Fe, and K) (44.0–61.2%) dominated the metallic contents in PM 2.5 . High EF values ( > 10) showed that V, Mn, Ni, Cu, and Zn were potentially contributed from anthropogenic sources. Moreover, organic carbon (OC) (0.6 µ g m –3 ) was superior to elemental carbon (EC) (0.3 µ g m –3 ) in PM 2.5 . The OC/EC ratios higher than 2.0 showed the potential chemical formation of secondary organic aerosols (SOAs) in the atmosphere in winter and spring. Trajectory simulation indicated that high PM 2.5 concentrations were mostly originated from North and Central China, Japan islands, and Korea Peninsula. Major sources of PM 2.5 resolved by CMB receptor modeling were ordered as: sea salts (19.9%) > fugitive dust (19.8%) > industrial boilers (oil-fired) (10.8%) > secondary sulfate (9.8%) > mobile sources (8.0%).
摘要本文研究了台湾岛东南海域细颗粒物(PM 2.5)的时空变化、化学成分和来源分辨率。WPO)和垦丁半岛(巴士海峡北部);公元前)，四季分明。采样后，利用化学质量平衡(CMB)、富集因子(EF)和反向轨迹模拟的受体模型，对pm2.5的化学指纹图谱进行了表征，并进一步分析了pm2.5的潜在来源及其贡献。结果表明:冬季(10.8µg m -3)和春季(12.0µg m -3)(即亚洲东北季候风期间)pm2.5浓度显著高于冬季(10.8µg m -3);ANMs)高于夏季(4.0µg m -3)和秋季(6.6µg m -3)。在化学成分上，次级无机气溶胶(SIAs = no3 -、so42 -和nh4 +)是PM 2.5中水溶性离子(wsi)的主要成分(56.7-67.2%)，而地壳元素(Mg、Al、Ca、Fe和K)(44.0-61.2%)是PM 2.5中金属含量的主要成分。高的EF值(bbb10)表明，V、Mn、Ni、Cu和Zn可能来自人为来源。此外，有机碳(OC)(0.6µg m -3)在pm2.5中的表现优于元素碳(EC)(0.3µg m -3)。OC/EC比值大于2.0表明冬季和春季大气中潜在的二次有机气溶胶化学形成。轨迹模拟表明，高PM 2.5浓度主要来自华北和华中地区、日本列岛和朝鲜半岛。CMB受体模型分解的pm2.5主要来源依次为:海盐(19.9%)>逸散粉尘(19.8%)>工业锅炉(燃油)(10.8%)>次生硫酸盐(9.8%)>移动源(8.0%)。
{"title":"Temporospatial Variation, Chemical Composition, and Source Resolution of PM2.5 in the Southeastern Taiwan Island","authors":"C. Yuan, Jun-Hao Ceng, Po-Hsuan Yen, Kuan-Chen Chiang, Yu-Lun Tseng, Kwok-Wai Wong, M. Jeng","doi":"10.4209/aaqr.220350","DOIUrl":"https://doi.org/10.4209/aaqr.220350","url":null,"abstract":"This study investigated the temporospatial variation, chemical composition, and source resolution of fine particles (PM 2.5 ) in the southeastern seas of the Taiwan Island. 24-hr PM 2.5 was sampled simultaneously at two remote sites, the Green Island (West Pacific Ocean; WPO) and the Kenting Peninsula (northern Bashi Channel; BC), in four seasons. After sampling, the chemical fingerprints of PM 2.5 were characterized and further applied to resolve the potential sources of PM 2.5 and their contribution by using a receptor model on the basis of chemical mass balance (CMB), enrichment factor (EF), and backward trajectory simulation. It showed that PM 2.5 concentrations in winter (10.8 µ g m –3 ) and spring (12.0 µ g m –3 ) (i.e., during the period of Asian Northeastern Monsoons; ANMs) were higher than those in summer (4.0 µ g m –3 ) and fall (6.6 µ g m –3 ). In terms of chemical composition of PM 2.5 , secondary inorganic aerosols (SIAs = NO 3– , SO 42– , and NH 4+ ) (56.7–67.2%) were the dominant component of water-soluble ions (WSIs) in PM 2.5 , while crustal elements (Mg, Al, Ca, Fe, and K) (44.0–61.2%) dominated the metallic contents in PM 2.5 . High EF values ( > 10) showed that V, Mn, Ni, Cu, and Zn were potentially contributed from anthropogenic sources. Moreover, organic carbon (OC) (0.6 µ g m –3 ) was superior to elemental carbon (EC) (0.3 µ g m –3 ) in PM 2.5 . The OC/EC ratios higher than 2.0 showed the potential chemical formation of secondary organic aerosols (SOAs) in the atmosphere in winter and spring. Trajectory simulation indicated that high PM 2.5 concentrations were mostly originated from North and Central China, Japan islands, and Korea Peninsula. Major sources of PM 2.5 resolved by CMB receptor modeling were ordered as: sea salts (19.9%) > fugitive dust (19.8%) > industrial boilers (oil-fired) (10.8%) > secondary sulfate (9.8%) > mobile sources (8.0%).","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70294695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arup Bhattacharya, Mohammad Saleh Nikoopayan Tak, Shervin Shoai-Naini, F. Betz, E. Mousavi
Cleanroom ventilation systems are well-established; however, the advantages and limitations of current practices need to be examined and explained further. This study begins by looking over the history of cleanroom ventilation systems that creates the basis for understanding ventilation rate specifications, terminologies employed in ventilation effectiveness, and recognizing scientific studies that correlate ventilation effectiveness with air change rates. This systematic review includes a comprehensive summary that contains a set of historical data and evidence that may be used to specify ventilation requirements in cleanrooms. Scientific articles are classified in terms of laboratory experiments, simulations/numerical analysis, or hybrid. HVAC designers and operators can use published codes and guidelines more efficiently if the terminology is properly understood and the design solutions are easy to implement. The present study aims to provide a deep insight into understanding the role of ventilation on the transport mechanisms of unwanted particles in cleanrooms. Historically, the ventilation rate is typically over-estimated, based on the experience of the designer, to ensure indoor air quality and thermal performance. However, the excess rate significantly impacts the system’s energy consumption. Hence, it is crucial to investigate existing recommendations to ensure if they have a scientific basis or could be proven theoretically before further implementations. Besides, any possible risks and influences associated with the traditional methods must be assessed to guarantee the facility’s performance, sustainability, and energy efficiency.
{"title":"A Systematic Literature Review of Cleanroom Ventilation and Air Distribution Systems","authors":"Arup Bhattacharya, Mohammad Saleh Nikoopayan Tak, Shervin Shoai-Naini, F. Betz, E. Mousavi","doi":"10.4209/aaqr.220407","DOIUrl":"https://doi.org/10.4209/aaqr.220407","url":null,"abstract":"Cleanroom ventilation systems are well-established; however, the advantages and limitations of current practices need to be examined and explained further. This study begins by looking over the history of cleanroom ventilation systems that creates the basis for understanding ventilation rate specifications, terminologies employed in ventilation effectiveness, and recognizing scientific studies that correlate ventilation effectiveness with air change rates. This systematic review includes a comprehensive summary that contains a set of historical data and evidence that may be used to specify ventilation requirements in cleanrooms. Scientific articles are classified in terms of laboratory experiments, simulations/numerical analysis, or hybrid. HVAC designers and operators can use published codes and guidelines more efficiently if the terminology is properly understood and the design solutions are easy to implement. The present study aims to provide a deep insight into understanding the role of ventilation on the transport mechanisms of unwanted particles in cleanrooms. Historically, the ventilation rate is typically over-estimated, based on the experience of the designer, to ensure indoor air quality and thermal performance. However, the excess rate significantly impacts the system’s energy consumption. Hence, it is crucial to investigate existing recommendations to ensure if they have a scientific basis or could be proven theoretically before further implementations. Besides, any possible risks and influences associated with the traditional methods must be assessed to guarantee the facility’s performance, sustainability, and energy efficiency.","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70295126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ruoxin Wang, Kangping Cui, Hwey-Lin Sheu, Lin-Chi Wang, Xueyan Liu
The effects of 9 precipitation events in Suzhou City in Anhui Province, China, on the air quality index (AQI), PM2.5, and dry deposition flux of PCDD/Fs (polydibenzo-p-dioxins and polydibenzofurans) were investigated. A total of 7 precipitation events were positive contributes to the reduction of AQI;among them, the AQI were between 23 and 216, with an average of 75, the PM2.5 concentrations were between 5.0 and 169 mu g m-3, with an average of 25 mu g m-3, while the total-PCDD/F-TEQ dry deposition flux ranged from 149 to 1034 pg WHO2005-TEQ m-2 day-1 and averaged 315 pg WHO2005-TEQ m-2 day-1. By comparing the average AQI and PM2.5, respectively, during and after rainfall with that before rainfall, the results indicated that the average reduction fractions of AQI were 26% and 44%, respectively, while those of PM2.5 were 58% and 43%. In addition, the effect of precipitation on the average reduction fraction of total PCDD/F-TEQ dry deposition flux was 31%. However, in the other 2 AQI elevation events, the AQI were between 23 and 100, and averaged 51;when comparing the average AQI and PM2.5 concentrations, during and after the rain with that before the rain, the increases in AQI were 42% and 49%, respectively, while the increases in PM2.5 concentration were 26% and 29%, respectively. The above results show that, on the whole, rain and snow improved the air quality. This is because rainwater removes particles or dissolved gaseous pollutants from the atmosphere and brings aerosols to the ground. However, in some cases, the increase of source emissions and atmospheric vertical convection, the effect of precipitation or air humidity increased the AQI and elevated the concentration of PM2.5, and dry deposition flux of PCDD/Fs. The results of this study provide useful information for both scientific communities and air quality management.
{"title":"Effects of Precipitation on the Air Quality Index, PM2.5 Levels and on the Dry Deposition of PCDD/Fs in the Ambient Air","authors":"Ruoxin Wang, Kangping Cui, Hwey-Lin Sheu, Lin-Chi Wang, Xueyan Liu","doi":"10.4209/aaqr.220417","DOIUrl":"https://doi.org/10.4209/aaqr.220417","url":null,"abstract":"The effects of 9 precipitation events in Suzhou City in Anhui Province, China, on the air quality index (AQI), PM2.5, and dry deposition flux of PCDD/Fs (polydibenzo-p-dioxins and polydibenzofurans) were investigated. A total of 7 precipitation events were positive contributes to the reduction of AQI;among them, the AQI were between 23 and 216, with an average of 75, the PM2.5 concentrations were between 5.0 and 169 mu g m-3, with an average of 25 mu g m-3, while the total-PCDD/F-TEQ dry deposition flux ranged from 149 to 1034 pg WHO2005-TEQ m-2 day-1 and averaged 315 pg WHO2005-TEQ m-2 day-1. By comparing the average AQI and PM2.5, respectively, during and after rainfall with that before rainfall, the results indicated that the average reduction fractions of AQI were 26% and 44%, respectively, while those of PM2.5 were 58% and 43%. In addition, the effect of precipitation on the average reduction fraction of total PCDD/F-TEQ dry deposition flux was 31%. However, in the other 2 AQI elevation events, the AQI were between 23 and 100, and averaged 51;when comparing the average AQI and PM2.5 concentrations, during and after the rain with that before the rain, the increases in AQI were 42% and 49%, respectively, while the increases in PM2.5 concentration were 26% and 29%, respectively. The above results show that, on the whole, rain and snow improved the air quality. This is because rainwater removes particles or dissolved gaseous pollutants from the atmosphere and brings aerosols to the ground. However, in some cases, the increase of source emissions and atmospheric vertical convection, the effect of precipitation or air humidity increased the AQI and elevated the concentration of PM2.5, and dry deposition flux of PCDD/Fs. The results of this study provide useful information for both scientific communities and air quality management.","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70295300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Black Carbon (BC) aerosols are not only substantial climate-forcing drivers but also impact human health. The spatial distribution of BC aerosols depends on the combination of anthropogenic activities and meteorological conditions. In this study, we used the India Meteorological Department (IMD) Black Carbon Observational Network datasets to assess the diurnal, seasonal, and long-term BC trends for the period, 2016–2021. The majority of the IMD’s BC monitoring stations show an overall declining trend in the BC mass concentration during the study period in India. Maximum BC concentrations are observed in the post-monsoon and winter seasons due to the stubble-burning activity and lower values of Atmospheric Boundary Layer Height (ABLH). Minimum concentrations are observed at all stations in the monsoon season due to the wet scavenging of aerosols by rain. There is a clear decrease in the BC mass concentration from winter to monsoon months and an increase in the post-monsoon months. Regional emissions from crop residue burning in the post-harvesting seasons are the main contributing factor for extremely high levels of BC mass concentration. Low wind speed and shallow mixed layer were found to be the main reasons for high levels of aerosol concentration during the winter season. There is an increasing trend in Biomass Burning (BB) at most of the stations except for Thiruvananthapuram, where a prominent decreasing trend in BC concentration is also noticed. In the present study, the impact of local meteorological parameters such as wind, temperature, rainfall and Atmospheric Boundary Layer Height on BC mass concentration is investigated. The results show a negative correlation with rainfall, relative humidity, wind speed, temperature and ABL height. Both local activity and long-range transport at each study site are also found to be responsible for the significant changes in BC mass concentration.
{"title":"Multisite Scenarios of Black Carbon and Biomass Burning Aerosol Characteristics in India","authors":"Vivek Kumar, P. Devara, V. Soni","doi":"10.4209/aaqr.220435","DOIUrl":"https://doi.org/10.4209/aaqr.220435","url":null,"abstract":"Black Carbon (BC) aerosols are not only substantial climate-forcing drivers but also impact human health. The spatial distribution of BC aerosols depends on the combination of anthropogenic activities and meteorological conditions. In this study, we used the India Meteorological Department (IMD) Black Carbon Observational Network datasets to assess the diurnal, seasonal, and long-term BC trends for the period, 2016–2021. The majority of the IMD’s BC monitoring stations show an overall declining trend in the BC mass concentration during the study period in India. Maximum BC concentrations are observed in the post-monsoon and winter seasons due to the stubble-burning activity and lower values of Atmospheric Boundary Layer Height (ABLH). Minimum concentrations are observed at all stations in the monsoon season due to the wet scavenging of aerosols by rain. There is a clear decrease in the BC mass concentration from winter to monsoon months and an increase in the post-monsoon months. Regional emissions from crop residue burning in the post-harvesting seasons are the main contributing factor for extremely high levels of BC mass concentration. Low wind speed and shallow mixed layer were found to be the main reasons for high levels of aerosol concentration during the winter season. There is an increasing trend in Biomass Burning (BB) at most of the stations except for Thiruvananthapuram, where a prominent decreasing trend in BC concentration is also noticed. In the present study, the impact of local meteorological parameters such as wind, temperature, rainfall and Atmospheric Boundary Layer Height on BC mass concentration is investigated. The results show a negative correlation with rainfall, relative humidity, wind speed, temperature and ABL height. Both local activity and long-range transport at each study site are also found to be responsible for the significant changes in BC mass concentration.","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70295825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The recent surge in the use of filtering facepiece respirators (FFRs) during the SARS-CoV-2 pandemic triggered economic and environmental concerns with regards to their safe reuse and/or disposal. Their decontamination through ultraviolet (UV) irradiation has proven efficient in bench tests. Nevertheless, no study has yet investigated to what extent the decontamination method’s performance was impacted by the contamination method. In this study, Bacillus subtilis spores were inoculated in three suspensions used to contaminate coupons of FFRs via aerosols nebulisation or 2 µ L drops deposition. The contaminated coupons were then exposed to UV irradiation in a monochromatic UVC lamp collimated beam reactor. The results revealed that contamination and decontamination were more efficient for drops (maximum 0.72 log losses and 3 log inactivation at 150 mJ cm –2 ) than for aerosols (maximum 2.47 log losses and 1.75 log inactivation at 150 mJ cm –2 ). Inactivation was greater in coupons contaminated using artificial saliva, followed by phosphate buffer solution, and finally artificial saliva with mucin which also presented the highest fraction of resistant spores, based on kinetic modeling. Disinfection was determined sensitive to the method of contamination ( p < 0.001). However, the composition of the contaminating suspension was the most important performance predictor for decontamination by UV irradiation ( p = 9.2 × 10 –10 ).
最近在SARS-CoV-2大流行期间，过滤式面罩呼吸器(ffr)的使用激增，引发了对其安全再利用和/或处置的经济和环境担忧。通过紫外线(UV)照射对其进行净化，在台架试验中证明是有效的。然而，目前还没有研究调查污染方法在多大程度上影响了去污方法的性能。在本研究中，枯草芽孢杆菌孢子接种于三种悬浮液中，通过气溶胶雾化或2µL滴滴沉积的方式污染ffr。然后在单色UVC灯准直光束反应器中暴露于紫外线照射下。结果表明，液滴(在150 mJ cm -2下最大0.72对数损失和3对数失活)比气溶胶(在150 mJ cm -2下最大2.47对数损失和1.75对数失活)的污染和去污效率更高。根据动力学模型，用人工唾液污染的孢子失活程度更高，其次是磷酸盐缓冲液，最后是用粘蛋白污染的人工唾液，后者也呈现出最高的抗性孢子比例。消毒对污染方法敏感(p < 0.001)。然而，污染悬浮液的组成是紫外线照射去污最重要的性能预测因子(p = 9.2 × 10 -10)。
{"title":"Impact of the Contamination Method on the Disinfection of N95 Respirators: Drops versus Aerosols","authors":"Mirna Alameddine, Oluchi Okoro, Loïc Wingert, Geneviève Marchand, Benoit Barbeau","doi":"10.4209/aaqr.230018","DOIUrl":"https://doi.org/10.4209/aaqr.230018","url":null,"abstract":"The recent surge in the use of filtering facepiece respirators (FFRs) during the SARS-CoV-2 pandemic triggered economic and environmental concerns with regards to their safe reuse and/or disposal. Their decontamination through ultraviolet (UV) irradiation has proven efficient in bench tests. Nevertheless, no study has yet investigated to what extent the decontamination method’s performance was impacted by the contamination method. In this study, Bacillus subtilis spores were inoculated in three suspensions used to contaminate coupons of FFRs via aerosols nebulisation or 2 µ L drops deposition. The contaminated coupons were then exposed to UV irradiation in a monochromatic UVC lamp collimated beam reactor. The results revealed that contamination and decontamination were more efficient for drops (maximum 0.72 log losses and 3 log inactivation at 150 mJ cm –2 ) than for aerosols (maximum 2.47 log losses and 1.75 log inactivation at 150 mJ cm –2 ). Inactivation was greater in coupons contaminated using artificial saliva, followed by phosphate buffer solution, and finally artificial saliva with mucin which also presented the highest fraction of resistant spores, based on kinetic modeling. Disinfection was determined sensitive to the method of contamination ( p < 0.001). However, the composition of the contaminating suspension was the most important performance predictor for decontamination by UV irradiation ( p = 9.2 × 10 –10 ).","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70296171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, low-cost sensors (LCSs) have been widely used in monitoring particulate matter (PM) mass concentrations. Maintaining the accuracy of the sensors is important and requires rigorous calibration and performance evaluation. In this study, two commercial LCSs, Plantower PMS3003 and Plantower PMS7003, were evaluated in the laboratory and in the field using a reference-grade PM monitor (GRIMM 11-D). Laboratory evaluation was conducted with polystyrene latex (PSL) particles in a 1 m 3 chamber at 20 ° C with a relative humidity of 20%. Each LCS indicated higher mass concentrations than GRIMM 11-D for small-sized PSL particles (0.56 µ m); however, the LCSs indicated lower mass concentrations than GRIMM 11-D for PSL particles larger than 0.56 µ m. In addition, the difference in mass concentrations between the LCS and GRIMM 11-D became higher with particle sizes greater than 0.56 µ m. Nonetheless, a high correlation (R 2 > 0.9) between each LCS and GRIMM 11-D was obtained. Field evaluation was conducted at Yonsei University (Seoul, South Korea) from February 12 to March 31, 2022. The LCSs showed generally higher PM mass concentrations than GRIMM 11-D; however, some data points of the LCSs revealed different trends. We observed that outdoor PM 10 /PM 2.5 and relative humidity had notable impacts on the LCS data; in addition, LCS sensitivity depended on whether the PM concentration was low or high. Based on these observations, regression-based calibration models were constructed using the selected independent variables (outdoor PM 10 /PM 2.5 and relative humidity) after dividing the PM concentration into low and high sections. Consequently, the accuracy of the LCSs was significantly enhanced. Therefore, using LCSs with the calibration models can replace the use of expensive reference PM monitors, resulting in cost savings.
{"title":"Calibration of Low-cost Sensors for Measurement of Indoor Particulate Matter Concentrations via Laboratory/Field Evaluation","authors":"Doheon Kim, Dongmin Shin, Jungho Hwang","doi":"10.4209/aaqr.230097","DOIUrl":"https://doi.org/10.4209/aaqr.230097","url":null,"abstract":"Recently, low-cost sensors (LCSs) have been widely used in monitoring particulate matter (PM) mass concentrations. Maintaining the accuracy of the sensors is important and requires rigorous calibration and performance evaluation. In this study, two commercial LCSs, Plantower PMS3003 and Plantower PMS7003, were evaluated in the laboratory and in the field using a reference-grade PM monitor (GRIMM 11-D). Laboratory evaluation was conducted with polystyrene latex (PSL) particles in a 1 m 3 chamber at 20 ° C with a relative humidity of 20%. Each LCS indicated higher mass concentrations than GRIMM 11-D for small-sized PSL particles (0.56 µ m); however, the LCSs indicated lower mass concentrations than GRIMM 11-D for PSL particles larger than 0.56 µ m. In addition, the difference in mass concentrations between the LCS and GRIMM 11-D became higher with particle sizes greater than 0.56 µ m. Nonetheless, a high correlation (R 2 > 0.9) between each LCS and GRIMM 11-D was obtained. Field evaluation was conducted at Yonsei University (Seoul, South Korea) from February 12 to March 31, 2022. The LCSs showed generally higher PM mass concentrations than GRIMM 11-D; however, some data points of the LCSs revealed different trends. We observed that outdoor PM 10 /PM 2.5 and relative humidity had notable impacts on the LCS data; in addition, LCS sensitivity depended on whether the PM concentration was low or high. Based on these observations, regression-based calibration models were constructed using the selected independent variables (outdoor PM 10 /PM 2.5 and relative humidity) after dividing the PM concentration into low and high sections. Consequently, the accuracy of the LCSs was significantly enhanced. Therefore, using LCSs with the calibration models can replace the use of expensive reference PM monitors, resulting in cost savings.","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70297102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhiyong Li, Chen Liu, Chengjing Cao, Z. Zhai, Changtao Huang, Zhuangzhuang Ren, Jixiang Liu, Lan Chen, Songtao Guo, Ding-Guor Yang
A unique study was enacted during the heating season (HS) in 2020 and 2021 at a rural site in the Beijing-Tianjin-Hebei region to evaluate the policy impacts of “Coal to Gas” (CTG) on ambient volatile organic compounds (VOCs). A total of 58 VOCs in air and flue gas from wall-mounted gas stoves (WMGS) were concurrently analyzed. The total VOCs decreased from 38.6 µ g m –3 in 2020 to 32.8 µ g m –3 in 2021, indicating the CTG played a positive role. However, the ozone formation potentials (OFPs) increased from 31.5 to 44.9 µ g m –3 . Toluene, vinylidene chloride, ethylbenzene, o, m, p-xylene, 4-methyl-2-pentanone, n-butylbenzene, trans-1,2-dichloroethylene, and 1,2,4-trimethylbenzene were the main contributors to the OFPs. Halohydrocarbons contributed the most to ∑ 58 VOCs of 54.8% and 54.4% in 2020 and 2021, respectively. It should be noted that the sustained CTG made WMGS the largest VOC source, replacing coal combustion (CC) in 2020. The CC contributions decreased from 33.2% in 2020 to 28.7% in 2021, while the WMGS far increased from 22.5% to 35.6%. Potential source contribution function (PSCF) modelling showed that the WMGS originated mainly from local emissions. High VOCs appeared surprisingly in clean days, because the WMGS and advanced coal-burning stoves with low particle emission prevailed in heating modes. The recognition of WMGS was achieved by coefficients of correlation and divergence between the positive matrix factorization (PMF) identified factor and field measured profiles of WMGS. This study firstly evidenced that the use of WMGS was becoming a major VOC source in rural north China. Meanwhile, the coal combustion for heating was still serious in rural area despite the “Coal Prohibition” law. The study was expected to provide some novel strategies for further VOC control and air quality improvement in rural area.
在2020年和2021年采暖季(HS)期间，在京津冀地区的一个农村地区进行了一项独特的研究，以评估“煤制气”(CTG)对环境挥发性有机化合物(VOCs)的政策影响。同时分析了壁挂式燃气灶空气和烟气中58种挥发性有机化合物。总VOCs从2020年的38.6µg m -3下降到2021年的32.8µg m -3，表明CTG发挥了积极作用。然而，臭氧形成电位(OFPs)从31.5µg m -3增加到44.9µg m -3。甲苯、偏氯乙烯、乙苯、o, m，对二甲苯、4-甲基-2-戊酮、正丁基苯、反式-1,2-二氯乙烯和1,2,4-三甲苯是OFPs的主要贡献者。卤代烃对∑58 VOCs的贡献最大，2020年和2021年分别为54.8%和54.4%。值得注意的是，持续的CTG使WMGS成为最大的VOC来源，在2020年取代煤炭燃烧(CC)。碳排放贡献率从2020年的33.2%下降到2021年的28.7%，而WMGS则从22.5%大幅上升到35.6%。潜在源贡献函数(PSCF)模型表明，WMGS主要来源于局地排放。由于WMGS和先进的低颗粒排放的燃煤炉在供暖模式中占了上风，因此在晴天出现了高VOCs。利用正矩阵分解(PMF)识别因子与WMGS实测剖面的相关系数和散度系数实现WMGS的识别。该研究首次证明了WMGS的使用正在成为中国北方农村VOC的主要来源。与此同时，尽管有了“禁煤法”，农村地区烧煤取暖的现象依然严重。该研究有望为进一步控制挥发性有机化合物和改善农村空气质量提供一些新的策略。
{"title":"Impacts of the “Coal to Gas” Policy on Rural Air VOC Level and Ozone Potentials in North China","authors":"Zhiyong Li, Chen Liu, Chengjing Cao, Z. Zhai, Changtao Huang, Zhuangzhuang Ren, Jixiang Liu, Lan Chen, Songtao Guo, Ding-Guor Yang","doi":"10.4209/aaqr.230136","DOIUrl":"https://doi.org/10.4209/aaqr.230136","url":null,"abstract":"A unique study was enacted during the heating season (HS) in 2020 and 2021 at a rural site in the Beijing-Tianjin-Hebei region to evaluate the policy impacts of “Coal to Gas” (CTG) on ambient volatile organic compounds (VOCs). A total of 58 VOCs in air and flue gas from wall-mounted gas stoves (WMGS) were concurrently analyzed. The total VOCs decreased from 38.6 µ g m –3 in 2020 to 32.8 µ g m –3 in 2021, indicating the CTG played a positive role. However, the ozone formation potentials (OFPs) increased from 31.5 to 44.9 µ g m –3 . Toluene, vinylidene chloride, ethylbenzene, o, m, p-xylene, 4-methyl-2-pentanone, n-butylbenzene, trans-1,2-dichloroethylene, and 1,2,4-trimethylbenzene were the main contributors to the OFPs. Halohydrocarbons contributed the most to ∑ 58 VOCs of 54.8% and 54.4% in 2020 and 2021, respectively. It should be noted that the sustained CTG made WMGS the largest VOC source, replacing coal combustion (CC) in 2020. The CC contributions decreased from 33.2% in 2020 to 28.7% in 2021, while the WMGS far increased from 22.5% to 35.6%. Potential source contribution function (PSCF) modelling showed that the WMGS originated mainly from local emissions. High VOCs appeared surprisingly in clean days, because the WMGS and advanced coal-burning stoves with low particle emission prevailed in heating modes. The recognition of WMGS was achieved by coefficients of correlation and divergence between the positive matrix factorization (PMF) identified factor and field measured profiles of WMGS. This study firstly evidenced that the use of WMGS was becoming a major VOC source in rural north China. Meanwhile, the coal combustion for heating was still serious in rural area despite the “Coal Prohibition” law. The study was expected to provide some novel strategies for further VOC control and air quality improvement in rural area.","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70297812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Air quality issues, including health and environmental challenges, have recently become more relevant in urban areas with large populations and active industries. Therefore, particulate matter (PM) estimation with high accuracy using various methods is required. In this study, PM 10 and PM 2.5 in Cheongju city, South Korea, were estimated using the attenuated backscatter coefficient of the ceilometer and meteorological observation data from an automatic weather station with supervised machine learning (ML). The backscatter coefficient data were obtained from the vertical layer with the highest correlation with PM 10 and PM 2.5 . The estimation methods utilized were tree, vector, neural, and regularization-based supervised ML. The extreme gradient boosting method yielded the highest PM estimation accuracy. The estimation of PM 10 and PM 2.5 for the test data set was more accurate than that in previous studies that used satellite and ground-based meteorological data (bias = 0.10 µ g m –3 , root mean square error (RMSE) = 14.44 µ g m –3 , and R = 0.92 for PM 10 ; and bias = 0.12 µ g m –3 , RMSE = 7.16 µ g m –3 , and R = 0.91 for PM 2.5 ). Particularly, the correlation coefficient was the highest for the estimation results for strong haze cases (1 km < visibility ≤ 5 km) ( R = 0.95 for PM 10 ; R = 0.89 for PM 2.5 ). Therefore, PM estimation using meteorological observation data can help obtain meteorological and PM information simultaneously, making it useful for air quality monitoring.
{"title":"Estimation of PM10 and PM2.5 Using Backscatter Coefficient of Ceilometer and Machine Learning","authors":"Bu-Yo Kim, Joo Wan Cha, Yong Hee Lee","doi":"10.4209/aaqr.230033","DOIUrl":"https://doi.org/10.4209/aaqr.230033","url":null,"abstract":"Air quality issues, including health and environmental challenges, have recently become more relevant in urban areas with large populations and active industries. Therefore, particulate matter (PM) estimation with high accuracy using various methods is required. In this study, PM 10 and PM 2.5 in Cheongju city, South Korea, were estimated using the attenuated backscatter coefficient of the ceilometer and meteorological observation data from an automatic weather station with supervised machine learning (ML). The backscatter coefficient data were obtained from the vertical layer with the highest correlation with PM 10 and PM 2.5 . The estimation methods utilized were tree, vector, neural, and regularization-based supervised ML. The extreme gradient boosting method yielded the highest PM estimation accuracy. The estimation of PM 10 and PM 2.5 for the test data set was more accurate than that in previous studies that used satellite and ground-based meteorological data (bias = 0.10 µ g m –3 , root mean square error (RMSE) = 14.44 µ g m –3 , and R = 0.92 for PM 10 ; and bias = 0.12 µ g m –3 , RMSE = 7.16 µ g m –3 , and R = 0.91 for PM 2.5 ). Particularly, the correlation coefficient was the highest for the estimation results for strong haze cases (1 km < visibility ≤ 5 km) ( R = 0.95 for PM 10 ; R = 0.89 for PM 2.5 ). Therefore, PM estimation using meteorological observation data can help obtain meteorological and PM information simultaneously, making it useful for air quality monitoring.","PeriodicalId":7402,"journal":{"name":"Aerosol and Air Quality Research","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134882992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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