Atmospheric Pollution Research最新文献

{"title":"Impact of indoor plant-induced relative humidity on PM concentration in indoor urban environment","authors":"Supreet Kaur ,&nbsp;Sumit Kumar Mishra ,&nbsp;Vikas Goel ,&nbsp;Mayank Kumar ,&nbsp;Rishabh Singh ,&nbsp;Mamta Devi ,&nbsp;Harish Chandra ,&nbsp;Vijayan Narayanasamy ,&nbsp;S.P. Singh ,&nbsp;Parag Sharma ,&nbsp;Prashant Kumar","doi":"10.1016/j.apr.2025.102468","DOIUrl":"10.1016/j.apr.2025.102468","url":null,"abstract":"<div><div>The study investigates the influence of indoor plants on relative humidity (RH) and the subsequent reduction in particulate matter (PM) in a naturally ventilated office room at CSIR- NPL, Delhi. PM concentrations were compared under two conditions: control (without plants) and experimental (with eight potted <em>Epipremnum aureum</em> plants). The comparison was conducted under two distinct cases: background PM, and induced PM from incense burning.</div><div>The presence of plants resulted in an average RH increase of 13.55% and a temperature decrease of 4.1%. Plant-induced RH elevation led to a sixfold reduction in PM <em>I/O</em> ratios. RH values (&gt;60%) were negatively correlated with ultrafine, fine, and coarse particles. Plant-induced RH accelerates the deposition loss rate of all sized particles by ∼44% and reduces the infiltration rate by ∼78%. During pre-emission, in addition to PM dry deposition, plant-induced RH contributed to a substantial reduction of fine PM by 6.53% and coarse PM by 26.45% respectively. During incense burning, in the presence of plants, ultrafine PM concentrations dropped by 23.41%, fine PM by 72.39%, and coarse PM by 71.49%. It demonstrates that PM chemical composition significantly influences PM reduction, as it alters particle hygroscopicity. There was a decrease in the mass percentage of elements like Na, Mg, Al, Si, Cl, and K by 1.87, 1.23, 2.26, 5.48, 0.66, and 0.91 percent respectively. It can be inferred that to achieve a 13% increase in the average RH, plants with a leaf area size equivalent to ∼6% of the room surface would be required.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 6","pages":"Article 102468"},"PeriodicalIF":3.9,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"A decade of changes in potential sources and chemical composition of PM2.5 from Huangshi in central China","authors":"Shan Liu ,&nbsp;Changlin Zhan ,&nbsp;Ziguo Liu ,&nbsp;Jihong Quan ,&nbsp;Hongxia Liu ,&nbsp;Jingru Zheng ,&nbsp;Xuefen Yang ,&nbsp;Yanni Li ,&nbsp;Zhong Gao ,&nbsp;Juan Liu","doi":"10.1016/j.apr.2025.102465","DOIUrl":"10.1016/j.apr.2025.102465","url":null,"abstract":"<div><div>This study investigates decadal changes in PM_2.5 sources and chemical composition in Huangshi, a metallurgical and industrial city in Central China. PM_2.5 samples were collected from 2021 to 2023 and analyzed for water-soluble inorganic ions, carbonaceous species, and inorganic elements using ion chromatography, thermal-optical reflectance, and X-ray fluorescence. Positive Matrix Factorization and the HYSPLIT model were applied to determine pollution sources and transport pathways. Compared to 2012–2013, PM_2.5 concentrations declined significantly, primarily due to reduced local emissions. However, secondary aerosols originating from long-range transport, particularly from northern China, Mongolia, and Kazakhstan, now dominate PM_2.5 composition. Contributions from fossil fuel combustion, industrial activities, and vehicular emissions have decreased, while an increased NO₃⁻/SO₄²⁻ ratio suggests a shift from stationary to mobile sources. These findings highlight the effectiveness of emission control policies in reducing local anthropogenic pollution, leading to a greater relative contribution from secondary aerosols. This study provides critical insights into the evolving PM_2.5 composition and its sources, supporting the development of more effective air quality management strategies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102465"},"PeriodicalIF":3.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Quantitative assessment of urban-rural spatiotemporal heterogeneity in air pollutants using GEE multi-source data across the Anhui province, China","authors":"Hongliang Gu,&nbsp;Wenqian Zhang","doi":"10.1016/j.apr.2025.102464","DOIUrl":"10.1016/j.apr.2025.102464","url":null,"abstract":"<div><div>Air pollution in urban areas has garnered considerable attention in recent years. However, from an equity perspective, the air pollution situation in non-urban areas warrants more in-depth investigation. Limited research still exists on the non-urban air pollution. This study examined the urban-rural spatiotemporal heterogeneity of NO₂, CO, and O₃ in the Anhui Province from 2019 to 2023. Using Google Earth Engine (GEE), ArcGIS, and R language, the analysis integrated TROPOMI column concentration data with natural and social influencing factors. The results revealed the following: (1) The concentrations of NO₂, CO, and O₃ exhibit a declining trend during the annual plum rain season. NO₂ and CO concentrations show inter-annual fluctuating decreases, whereas O₃ demonstrates a fluctuating increase. NO₂ and CO concentrations are lowest in summer and increase synchronously during autumn and winter. The highest correlation coefficient between NO₂ and O₃ concentrations occurs in spring, at −0.946. (2) From January to March each year, the maximum concentrations of CO and O₃ are more likely to occur in non-urban built-up areas. Compared to 2019, the average area proportions of increased CO and NO₂ concentrations in urban built-up areas across all four seasons in 2023 are 8.91% and 4.93%, respectively, significantly lower than those in non-urban built-up areas (91.08% and 95.05%). Except for summer, O₃ concentrations show an increasing trend throughout the entire province. (3) The standard deviations of the multi-year average concentrations of CO, NO₂, and O₃ among the 16 prefecture-level cities are 0.002, 2.19 × 10⁻⁵, and 0.0027, respectively. This suggests that the variation in NO₂ pollution among cities is relatively small, while the spatial imbalance of O₃ pollution is pronounced, with the highest average O₃ concentrations observed in cities in northern Anhui. (4) The correlation coefficients between each air pollutant and the perimeter-area fractal dimension of water, forests, and buildings exceed 0.64, and the correlation coefficients with the aggregation index of forests and buildings exceed 0.58. These findings indicate that the complexity and dispersion of landscape patterns resulting from human disturbance may have a significant impact on air pollution levels.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102464"},"PeriodicalIF":3.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Estimating and characterizing spatiotemporal distributions of elemental PM2.5 using an ensemble machine learning approach in Taiwan","authors":"Chun-Sheng Huang ,&nbsp;Kang Lo ,&nbsp;Yee-Lin Wu ,&nbsp;Fu-Cheng Wang ,&nbsp;Yi-Shiang Shiu ,&nbsp;Chu-Chih Chen ,&nbsp;Yuan-Chien Lin ,&nbsp;Cheng-Pin Kuo ,&nbsp;Ho-Tang Liao ,&nbsp;Tang-Huang Lin ,&nbsp;Chang-Fu Wu","doi":"10.1016/j.apr.2025.102463","DOIUrl":"10.1016/j.apr.2025.102463","url":null,"abstract":"<div><div>This paper presents an ensemble machine learning approach that combines Generalized Additive Model (GAM) with eXtreme Gradient Boosting (XGBoost) to estimate and characterize the spatiotemporal distributions of elemental PM_2.5 in Taiwan. Daily field measurements of 12 PM_2.5 elemental components were collected from 28 air quality monitoring stations between June 2021 and May 2022. Time-variant meteorological factors and time-invariant land-use patterns were incorporated as predictors. Results showed that the ensemble model effectively captured spatial variations in elemental PM_2.5 levels, as demonstrated by the identification of numerous time-invariant features using Shapley additive explanations analysis. A comparative analysis was conducted with a model using only XGBoost, which outperformed the ensemble model with higher cross-validated <em>R</em>^<em>2</em> and lower prediction errors. While the XGBoost-only model is recommended for exposure prediction, the ensemble model offers superior interpretability for investigating air pollution sources and aids in formulating air quality strategies from a spatial perspective.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102463"},"PeriodicalIF":3.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Reducing PM2.5 and O3 through optimizing urban ecological land form based on its size thresholds","authors":"Xin Chen,&nbsp;Fang Wei","doi":"10.1016/j.apr.2025.102466","DOIUrl":"10.1016/j.apr.2025.102466","url":null,"abstract":"<div><div>Optimizing the size and form of urban ecological land (UEL) is an effective approach to addressing PM_2.5-O₃ composite pollution in China. However, existing strategies are usually proposed based on the impact of one type of UEL on individual pollutants, while overlooking UEL forms’ different pollution reduction effects across its size intervals. This study identifies UELs (including forest, shrub, grassland, water, and wetland) of 1068 counties within the Yangtze River Economic Belt (YREB) and calculates their size and form metrics. Then the cross-sectional threshold regression model is used to analyze the threshold effect of UEL size on fitting models of pollutant concentrations. Finally, quadrant analysis is extended to categorize counties and provide differentiated planning strategies. The conclusions show: (1) UEL size presents a triple threshold effect on PM_2.5 concentrations at 4.302%, 8.055%, and 23.742%, and a single threshold effect on O₃ concentrations at 3.275%. Size and form metrics are not always significant across UEL size intervals. (2) Counties are categorized into 6 types based on their primary pollutants and UEL sizes, showing spatial clustering within each type. (3) With size increasing, dispersed and irregular UEL form helps more in reducing PM_2.5, while O₃ reduction prefers aggregated one, thereby the evolutionary UEL planning strategy is proposed.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102466"},"PeriodicalIF":3.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Modelling lung deposition of fine particulate matter in males and females during urban cycle commuting","authors":"Gustavo Oneda ,&nbsp;Gabriel Moresco ,&nbsp;Danilo Fonseca Leonel ,&nbsp;Leonardo Hoinaski ,&nbsp;Joseph F. Welch ,&nbsp;Sarah Koch ,&nbsp;Ramon Cruz","doi":"10.1016/j.apr.2025.102467","DOIUrl":"10.1016/j.apr.2025.102467","url":null,"abstract":"<div><div>Exposure to fine particulate matter (PM_2.5) from urban areas may be modified by structural (e.g., airway anatomy) and functional (e.g., ventilatory pattern) sex-related physiological differences during exercise, resulting in greater PM_2.5 deposition in females versus males. Beyond the total PM_2.5 deposition, further insights concerning regional differences in PM_2.5 deposition are needed to understand females’ hyperresponsiveness to PM_2.5. Thus, a modelling-based analysis of structural and functional characteristics of PM_2.5 deposition in the human respiratory tract was conducted simulating an urban cycle commute of 30 min. Two scenarios were considered to estimate the PM_2.5 deposition: 1) greater minute ventilations in females versus males (p &lt; 0.001); and 2) minute ventilations matched between males and females (p = 0.710). We found that females experience 51.32% and 0.62% greater total PM_2.5 deposition for Scenarios 1 and 2, respectively (both p &lt; 0.001). Regardless of total minute ventilation, there was greater PM_2.5 deposition into the bronchiolar and alveolar region in females compared to males (p &lt; 0.001 for both). These data indicate a greater likelihood of bronchial hyperresponsiveness in females compared with males when exposed to PM_2.5 while cycle commuting in urban areas.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102467"},"PeriodicalIF":3.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Environmental impacts and costs of ozone formation in Bangkok Metropolitan Region","authors":"Soe Htet Aung ,&nbsp;Shabbir H. Gheewala ,&nbsp;Ekbordin Winijkul ,&nbsp;Sirima Panyametheekul ,&nbsp;Trakarn Prapaspongsa","doi":"10.1016/j.apr.2025.102450","DOIUrl":"10.1016/j.apr.2025.102450","url":null,"abstract":"<div><div>Ozone formation is an important environmental factor causing impacts on human health and ecosystem. Previous research relating to ozone formation often had limited scopes on direct emissions or focused on limited sectors of cities. This study aimed to quantify environmental impacts and costs due to ozone formation caused by energy generation, industry, agriculture, residential and commercial sectors, transport, fugitive gas emissions and waste treatment in the Bangkok Metropolitan Region (BMR) in 2022. The assessment applied spatially differentiated life cycle assessment framework, quantifying impacts on human health and ecosystem using local and global factors for on-site and supply chain emissions. The baseline situation in 2022 revealed that total emissions (on-site and supply chain) were 3.97E+05 tonnes of NO_x and 1.15E+05 tonnes of NMVOC. NO_x and the transport sector were the main stressor and hotspot causing impacts and costs of ozone formation in BMR. Total impact scores (on-site and supply chain) were 4.39E+02 disability-adjusted life year (human health impact) and 3.50E+01 species.year (ecosystem damage). The impacts were mainly contributed by on-site activities in BMR costing 6 billion Thai Baht. Scenarios were developed focusing primarily on the on-road transport since it was the hotspot causing health impacts and ecosystem damage. The scenarios indicated that upgrading fuel technology from diesel to compressed natural gas and modification of vehicles from diesel to electric were found to be very effective for overall reduction by more than 50% on average for health impacts and by more than 40% on average for ecosystem damage.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102450"},"PeriodicalIF":3.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A significant reduction in the coal contribution to PM2.5 and exposed health risks due to the energy structure transition","authors":"Dongmei Hu ,&nbsp;Mingyang Yuan ,&nbsp;Yulong Yan ,&nbsp;Xiaolin Duan ,&nbsp;Yafei Guo ,&nbsp;Yueyuan Niu ,&nbsp;Wen Yan ,&nbsp;Lin Peng","doi":"10.1016/j.apr.2025.102457","DOIUrl":"10.1016/j.apr.2025.102457","url":null,"abstract":"<div><div>By collecting PM_2.5 samples containing heavy metals in a typical coal resource-based city, we analyzed the interannual variation of heavy metal concentrations over an extended time period (2018–2022). This analysis involved apportioning the sources of these heavy metals and evaluating the carcinogenic and non-carcinogenic health risks posed to different populations via the respiratory route. Results showed that Cd (83.99%), Zn (62.56%), Pb (56.97%), and As (2.60%) were associated with coal combustion, exhibiting decreasing trends. The maximal information coefficient (MIC) indicated that most of the elements with strong correlations were associated with coal combustion. Four sources, namely coal combustion, resuspended dust, traffic emission, and industry, were determined using positive matrix factorization. Cr posed the highest carcinogenic risk, particularly among adults. Coal consumption and its contribution showed significant reductions due to the energy structure transition of coal reduction. Notably, the top three metals in terms of carcinogenic risk were all associated with coal combustion. The carcinogenic risk associated with Cd and As from coal combustion was significantly lower in 2022 than in 2018.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102457"},"PeriodicalIF":3.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Research on the impact of land use and meteorological factors on the spatial distribution characteristics of PM2.5 concentration","authors":"Xiaoxia Wang ,&nbsp;Hongtao Zhang ,&nbsp;Zhihai Fan ,&nbsp;Hong Ding","doi":"10.1016/j.apr.2025.102462","DOIUrl":"10.1016/j.apr.2025.102462","url":null,"abstract":"<div><div>Precisely capturing the spatial distribution characteristics of fine particulate matter (PM_2.5) is the key to air pollution prevention and control. Researches suggests that PM_2.5 concentrations is jointly affected by meteorological factors and urban land use. This study comprehensively considered these factors, with land cover, meteorology and road traffic as potential independent variables. The land use regression (LUR) model was used to identify the main influences on the spatial distribution of PM_2.5 concentration under different types of land use, and the importance of these factors was assessed using a random forest (RF) model. The research findings indicate that: (1) The fluctuations of PM_2.5 concentration in residential and industrial land use are relatively severe, ranging from 0 to 50 μg/m³. The changes in commercial and public service land use range from 0 to 40 μg/m³. And the in green space range from 15 to 33 μg/m³ (2) The distribution of PM_2.5 concentration in residential land is primarily influenced by precipitation and relative humidity, with relative importance of 36.3% and 23.9%, respectively. And that in industrial land use is primarily influenced by wind speed, with a relative importance of 30.6%. (3) The most influential determinant of spatial distribution of PM_2.5 concentration is meteorological factors, with relative importance exceeding 62%. The relative importance of road traffic ranges from 15.6% to 24.9%. And that of land cover factors ranges from 9.9% to 22.4%. This study analyzes the coupling connection between urban land use and spatial distribution of PM_2.5 concentration, and elaborates the specific influence of the former on the latter.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102462"},"PeriodicalIF":3.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Household PM2.5 in a South African urban and rural setting: A comparative analysis using low-cost sensors","authors":"Matthew Benyon ,&nbsp;Ngwako Kwatala ,&nbsp;Tracey Laban ,&nbsp;Thandi Kapwata ,&nbsp;Chiara Batini ,&nbsp;Samuel Cai ,&nbsp;Lisa K. Micklesfield ,&nbsp;Rikesh Panchal ,&nbsp;Siyathemba Kunene ,&nbsp;Sizwe B. Zondo ,&nbsp;Brigitte Language ,&nbsp;Bianca Wernecke ,&nbsp;Scott Hazelhurst ,&nbsp;F. Xavier Gómez-Olivé ,&nbsp;Joshua Vande Hey ,&nbsp;Caradee Y. Wright","doi":"10.1016/j.apr.2025.102459","DOIUrl":"10.1016/j.apr.2025.102459","url":null,"abstract":"<div><div>Household air pollution (HAP) is responsible for millions of premature deaths each year<em>.</em> Exposure to household air pollutants as a risk factor for poor health has not been adequately quantified in many parts of the world, especially Sub-Saharan Africa. We aimed to assess HAP, specifically PM_2.5, and its associations with dwelling and household characteristics in urban (Soweto) and rural (Agincourt) settings in South Africa. We monitored indoor PM_2.5 concentrations in 40 unique households using low-cost sensors, across two study sites and seasons. Low-cost sensors were calibrated by collocation, and associations between dwelling and household characteristics with indoor PM_2.5 concentrations were assessed using a log-linear regression model. PM_2.5 concentrations were greater in urban households in the summer (50 μg/m³ (95% CI: 41–63) and in the winter (82 μg/m³ (95% CI: 62–109)) compared to rural households (summer: 19 μg/m³ (95%: CI 14–26) and winter: 48 μg/m³ (95% CI: 44–53)). The log-linear model (n = 39) explained 74% of the variance in leave-one-out cross validation. Significant associations with household PM_2.5 were observed with the following: the season, study setting, presence of tobacco smoking, presence of incense burning inside the dwelling, and the use of heating. This study found significant variations in HAP concentrations within and across the urban and rural communities, likely influenced by differences in ambient outdoor concentrations and individual behaviours such as incense burning. It is crucial to enhance community and policy maker awareness regarding the dangers of indoor smoking and the harmful effects of burning incense indoors.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102459"},"PeriodicalIF":3.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}