Pub Date : 2025-08-01DOI: 10.1016/j.aeaoa.2025.100368
Hao Yang , Kuang Xiao , Xing Xiang , Xing Wang , Xi Wang , Yunsong Du , Guangming Shi , Xin Zheng , Hongli Tao , Huanbo Wang , Fumo Yang
On-road carbon emissions represent a significant portion of transportation emissions in China and are a critical focus for future carbon reduction efforts. High spatio-temporal resolution emission inventories are vital for facilitating dynamic carbon reduction in cities. This study employs the Multilayer Perceptron (MLP) model to simulate variations in road traffic volume at the segment level and predict on-road CO2 emissions with high spatio-temporal resolution. The results demonstrate that this method can effectively reproduce the spatio-temporal distribution of on-road traffic, with R2 exceeding 0.6 for most road types and overall RMSE of 88 vehicles/h, respectively. Applied in Chengdu's Jinniu District, southwestern China, results show CO2 emissions peak during morning (7–9 a.m.) and evening (16–18 p.m.) commutes, concentrated on main roads. Morning peaks are lower but grow faster than evening peaks. CO2 emissions significantly increase on holidays and weekends with moderate temperatures and no or light rain. These insights support urban dynamic carbon reduction planning.
{"title":"Prediction of on-road CO2 emissions with high spatio-temporal resolution implementing multilayer perceptron","authors":"Hao Yang , Kuang Xiao , Xing Xiang , Xing Wang , Xi Wang , Yunsong Du , Guangming Shi , Xin Zheng , Hongli Tao , Huanbo Wang , Fumo Yang","doi":"10.1016/j.aeaoa.2025.100368","DOIUrl":"10.1016/j.aeaoa.2025.100368","url":null,"abstract":"<div><div>On-road carbon emissions represent a significant portion of transportation emissions in China and are a critical focus for future carbon reduction efforts. High spatio-temporal resolution emission inventories are vital for facilitating dynamic carbon reduction in cities. This study employs the Multilayer Perceptron (MLP) model to simulate variations in road traffic volume at the segment level and predict on-road CO<sub>2</sub> emissions with high spatio-temporal resolution. The results demonstrate that this method can effectively reproduce the spatio-temporal distribution of on-road traffic, with R<sup>2</sup> exceeding 0.6 for most road types and overall RMSE of 88 vehicles/h, respectively. Applied in Chengdu's Jinniu District, southwestern China, results show CO<sub>2</sub> emissions peak during morning (7–9 a.m.) and evening (16–18 p.m.) commutes, concentrated on main roads. Morning peaks are lower but grow faster than evening peaks. CO<sub>2</sub> emissions significantly increase on holidays and weekends with moderate temperatures and no or light rain. These insights support urban dynamic carbon reduction planning.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100368"},"PeriodicalIF":3.4,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145018848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sophisticated standard instruments are not always available for high-density multipoint air quality observations owing to their relatively high cost, large size, and high-power consumption. Low-cost sensors may be used as supportive or potential solutions for atmospheric observations. This study aimed to evaluate applicability of the compact and useful PM2.5 instrument with gas sensors (CUPI-G), which can measure real-time temperature, humidity, particulate matter (PM2.5), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidant, Ox (O3+NO2), and to observe the respective air pollution patterns in the suburban areas of developed and developing countries, selected as Japan and Thailand, respectively. The CUPI-G was validated with collocated standard instruments at both sites using a mathematical correction method to improve reproducibility before observation. Air quality observations were conducted for two weeks respectively from June 1st to June 14th, 2022, in Kyoto City, Japan and from October 28th to November 12th, 2022, in Nong Khaem District, Bangkok Province, Thailand, using CUPI-G. In Japan, applicability of the CUPI-G revealed different correlations, r = −0.30 to 0.89 with data from the nearest air monitoring station. In Thailand, it achieved strong correlations, r = 0.71 to 0.82 with the results of the nearest station. This study revealed the applicability performance, aiding future deployment of the CUPI-G and corresponding air pollution characteristics at observatories. Our results suggest a better performance of CUPI-G at polluted sites and recommend its use in developing countries having less-developed sites with lack of routine measurement equipment.
{"title":"Applicability of compact and useful PM2.5 instrument with gas sensors in Japan and Thailand","authors":"Humm Kham Zan Zan Aung , Suwanna Kitpati Boontanon , Jiaru Li , Yosuke Sakamoto , Kentaro Murano , Narin Boontanon , Yoshizumi Kajii","doi":"10.1016/j.aeaoa.2025.100350","DOIUrl":"10.1016/j.aeaoa.2025.100350","url":null,"abstract":"<div><div>Sophisticated standard instruments are not always available for high-density multipoint air quality observations owing to their relatively high cost, large size, and high-power consumption. Low-cost sensors may be used as supportive or potential solutions for atmospheric observations. This study aimed to evaluate applicability of the compact and useful PM<sub>2.5</sub> instrument with gas sensors (CUPI-G), which can measure real-time temperature, humidity, particulate matter (PM<sub>2.5</sub>), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO<sub>2</sub>), and oxidant, O<sub>x</sub> (O<sub>3</sub>+NO<sub>2</sub>), and to observe the respective air pollution patterns in the suburban areas of developed and developing countries, selected as Japan and Thailand, respectively. The CUPI-G was validated with collocated standard instruments at both sites using a mathematical correction method to improve reproducibility before observation. Air quality observations were conducted for two weeks respectively from June 1<sup>st</sup> to June 14<sup>th</sup>, 2022, in Kyoto City, Japan and from October 28<sup>th</sup> to November 12<sup>th</sup>, 2022, in Nong Khaem District, Bangkok Province, Thailand, using CUPI-G. In Japan, applicability of the CUPI-G revealed different correlations, r = −0.30 to 0.89 with data from the nearest air monitoring station. In Thailand, it achieved strong correlations, r = 0.71 to 0.82 with the results of the nearest station. This study revealed the applicability performance, aiding future deployment of the CUPI-G and corresponding air pollution characteristics at observatories. Our results suggest a better performance of CUPI-G at polluted sites and recommend its use in developing countries having less-developed sites with lack of routine measurement equipment.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100350"},"PeriodicalIF":3.4,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dispersion models are essential for predicting pollutant behavior in the atmosphere, but discrepancies between models can introduce uncertainties. Validating models with real data is crucial to ensuring accuracy. Previous studies have highlighted differences between CALPUFF and the particle model LAPMOD: while both yield relatively similar results for point sources, significant discrepancies arise for area sources. This study assesses the performance of both models using experimental datasets. The analysis shows that CALPUFF estimates higher concentrations than LAPMOD and performs better against observed values, meeting all validation criteria. LAPMOD is less consistent, with a non-optimal FAC2 and high VG due to outliers caused by receptor arrangement. However, both models align well with experimental data under ideal conditions. In conclusion, CALPUFF proves more reliable, whereas LAPMOD, despite its tendency to underestimate, provides useful results once outliers are excluded.
{"title":"Area source emissions: a validation study of CALPUFF and LAPMOD models","authors":"Francesca Tagliaferri, Alessandra Rota, Marzio Invernizzi","doi":"10.1016/j.aeaoa.2025.100348","DOIUrl":"10.1016/j.aeaoa.2025.100348","url":null,"abstract":"<div><div>Dispersion models are essential for predicting pollutant behavior in the atmosphere, but discrepancies between models can introduce uncertainties. Validating models with real data is crucial to ensuring accuracy. Previous studies have highlighted differences between CALPUFF and the particle model LAPMOD: while both yield relatively similar results for point sources, significant discrepancies arise for area sources. This study assesses the performance of both models using experimental datasets. The analysis shows that CALPUFF estimates higher concentrations than LAPMOD and performs better against observed values, meeting all validation criteria. LAPMOD is less consistent, with a non-optimal FAC2 and high VG due to outliers caused by receptor arrangement. However, both models align well with experimental data under ideal conditions. In conclusion, CALPUFF proves more reliable, whereas LAPMOD, despite its tendency to underestimate, provides useful results once outliers are excluded.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100348"},"PeriodicalIF":3.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-22DOI: 10.1016/j.aeaoa.2025.100349
Dylan Geissbühler , Thomas Laemmel , Mathieu Antoni , Philip Gautschi , Lukas Wacker , Sönke Szidat
Cement production currently emits approximately 8 % of global CO2. However, the fossil content of these emissions can vary significantly due to methods used to reduce fossil emissions, such as the increased use of alternative fuels. Here, we investigated three CO2 sampling methods used to analyse 14CO2 and estimate the fossil fraction (in terms of F14C) of emissions from three Swiss cement factories. First, direct stack exhaust gas sampling was conducted at a main study site over 6 months and 14CO2 measurements were compared with 14C values from producer fuel use data. A positive offset in F14C was observed with theoretical values compared to the measurements. This could be reduced by adjusting the assumed 14C content of some fuels, particularly shredded wood waste. Second, repeated downwind CO2 emission plume sampling campaigns were carried out at all sites, allowing for a remote estimation and comparison of their F14C signatures. These measurements yielded realistic average values but also demonstrated sensitivity to local wind conditions, i.e. wind speed and direction. Lastly, we analysed the bulk 14C content of tree leaves collected around each site to assess their long-term atmospheric fossil CO2 exposure. Although the observed 14C depletion and fossil fraction were generally small (close to uncertainty ranges), trees near the factories consistently showed lower F14C values than background trees. Direct stack exhaust gas sampling proved to be the most reliable approach for quantifying fossil CO2 emissions from cement production. Crucially, adjustments made to fuel 14C contents to match measurements suggested an underestimation of fossil CO2 emissions from the producer at our main site by more than 2 %.
{"title":"Verification of fossil CO2 emissions from Swiss cement factories using direct and indirect 14CO2 measurements","authors":"Dylan Geissbühler , Thomas Laemmel , Mathieu Antoni , Philip Gautschi , Lukas Wacker , Sönke Szidat","doi":"10.1016/j.aeaoa.2025.100349","DOIUrl":"10.1016/j.aeaoa.2025.100349","url":null,"abstract":"<div><div>Cement production currently emits approximately 8 % of global CO<sub>2</sub>. However, the fossil content of these emissions can vary significantly due to methods used to reduce fossil emissions, such as the increased use of alternative fuels. Here, we investigated three CO<sub>2</sub> sampling methods used to analyse <sup>14</sup>CO<sub>2</sub> and estimate the fossil fraction (in terms of F<sup>14</sup>C) of emissions from three Swiss cement factories. First, direct stack exhaust gas sampling was conducted at a main study site over 6 months and <sup>14</sup>CO<sub>2</sub> measurements were compared with <sup>14</sup>C values from producer fuel use data. A positive offset in F<sup>14</sup>C was observed with theoretical values compared to the measurements. This could be reduced by adjusting the assumed <sup>14</sup>C content of some fuels, particularly shredded wood waste. Second, repeated downwind CO<sub>2</sub> emission plume sampling campaigns were carried out at all sites, allowing for a remote estimation and comparison of their F<sup>14</sup>C signatures. These measurements yielded realistic average values but also demonstrated sensitivity to local wind conditions, i.e. wind speed and direction. Lastly, we analysed the bulk <sup>14</sup>C content of tree leaves collected around each site to assess their long-term atmospheric fossil CO<sub>2</sub> exposure. Although the observed <sup>14</sup>C depletion and fossil fraction were generally small (close to uncertainty ranges), trees near the factories consistently showed lower F<sup>14</sup>C values than background trees. Direct stack exhaust gas sampling proved to be the most reliable approach for quantifying fossil CO<sub>2</sub> emissions from cement production. Crucially, adjustments made to fuel <sup>14</sup>C contents to match measurements suggested an underestimation of fossil CO<sub>2</sub> emissions from the producer at our main site by more than 2 %.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100349"},"PeriodicalIF":3.8,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-09DOI: 10.1016/j.aeaoa.2025.100347
Lukas Hey , Katharina H.E. Meurer , Hermann F. Jungkunst
{"title":"On the potential of biogeochemical models to predict hot moments of N2O following dry-wet cycles","authors":"Lukas Hey , Katharina H.E. Meurer , Hermann F. Jungkunst","doi":"10.1016/j.aeaoa.2025.100347","DOIUrl":"10.1016/j.aeaoa.2025.100347","url":null,"abstract":"","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100347"},"PeriodicalIF":3.8,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-09DOI: 10.1016/j.aeaoa.2025.100345
Ceder R. Raben , Hans J. Erbrink , Serigne B. Lô , Gerard Hoek , Dick J.J. Heederik , Wietske Dohmen
Ammonia (NH3) and primary PM10 emitted by livestock production affect health and biodiversity, making their reduction essential. Quantities of emitted NH3 and PM10 vary across different livestock species, potentially leading to different regional spatial patterns of NH3 and PM10. This complicates the development of effective mitigation strategies. This study aims to provide insight into how different livestock production animals affect spatial patterns of NH3 and PM10.
The study area of ∼40 x 50 km2 encompassed a livestock-dense area with ∼2000 farms, several residential clusters and nature parks in the Netherlands. Spatial concentration patterns were predicted for ∼100,000 receptor points on a 100 x 100 m2 grid using a dispersion model based on farm emissions. Model assumptions were evaluated through sensitivity analyses.
Livestock production emissions significantly increased local levels of NH3 and more moderately elevated local levels of PM10. Spatial concentration patterns were strongly driven by geospatial distributions of farms as well as livestock species, with elevated concentrations observed in areas where farms were densely clustered. The distribution of farm contributions to total NH3 concentrations at receptor points was characterized by numerous small contributions from multiple farms across the study area. Concentrations were higher in rural parts of the study area and characterized by the combination of these small contributions with a few large contributions from nearby farms. Inclusion of farms in a wide radius was especially important for modelling NH3 concentrations in nature areas. These findings imply that generic reduction of livestock farm emissions should be investigated for the formulation of mitigation strategies.
畜牧业生产排放的氨（NH3）和初级PM10影响健康和生物多样性，因此减少它们至关重要。不同家畜种类的NH3和PM10排放量存在差异，可能导致不同区域NH3和PM10的空间分布格局。这使制定有效的缓解战略变得复杂。本研究旨在揭示不同畜牧业生产动物对NH3和PM10空间格局的影响。研究区域面积约40 x 50 km2，包括荷兰一个牲畜密集区，约2000个农场，几个住宅区和自然公园。使用基于农场排放的分散模型，预测了100 x 100 m2网格上约100,000个受体点的空间浓度模式。通过敏感性分析评估模型假设。畜牧业生产排放显著增加了当地的NH3水平，而PM10水平则略微升高。农场和牲畜种类的地理空间分布强烈地驱动了空间浓度格局，在农场密集聚集的地区观察到浓度升高。农场对总NH3浓度在受体点的贡献分布的特征是来自研究区域内多个农场的大量小贡献。研究区的农村地区的浓度较高，其特点是这些小贡献与附近农场的一些大贡献相结合。将农场纳入广泛的半径范围对于模拟自然地区NH3浓度尤为重要。这些研究结果表明，应该对牲畜养殖场排放的普遍减少进行调查，以制定缓解战略。
{"title":"Contributions of different livestock production animals to dispersion-modelled ambient ammonia and particulate matter in a livestock-dense area","authors":"Ceder R. Raben , Hans J. Erbrink , Serigne B. Lô , Gerard Hoek , Dick J.J. Heederik , Wietske Dohmen","doi":"10.1016/j.aeaoa.2025.100345","DOIUrl":"10.1016/j.aeaoa.2025.100345","url":null,"abstract":"<div><div>Ammonia (NH<sub>3</sub>) and primary PM10 emitted by livestock production affect health and biodiversity, making their reduction essential. Quantities of emitted NH<sub>3</sub> and PM10 vary across different livestock species, potentially leading to different regional spatial patterns of NH<sub>3</sub> and PM10. This complicates the development of effective mitigation strategies. This study aims to provide insight into how different livestock production animals affect spatial patterns of NH<sub>3</sub> and PM10.</div><div>The study area of ∼40 x 50 km2 encompassed a livestock-dense area with ∼2000 farms, several residential clusters and nature parks in the Netherlands. Spatial concentration patterns were predicted for ∼100,000 receptor points on a 100 x 100 m<sup>2</sup> grid using a dispersion model based on farm emissions. Model assumptions were evaluated through sensitivity analyses.</div><div>Livestock production emissions significantly increased local levels of NH<sub>3</sub> and more moderately elevated local levels of PM10. Spatial concentration patterns were strongly driven by geospatial distributions of farms as well as livestock species, with elevated concentrations observed in areas where farms were densely clustered. The distribution of farm contributions to total NH<sub>3</sub> concentrations at receptor points was characterized by numerous small contributions from multiple farms across the study area. Concentrations were higher in rural parts of the study area and characterized by the combination of these small contributions with a few large contributions from nearby farms. Inclusion of farms in a wide radius was especially important for modelling NH<sub>3</sub> concentrations in nature areas. These findings imply that generic reduction of livestock farm emissions should be investigated for the formulation of mitigation strategies.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100345"},"PeriodicalIF":3.8,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-09DOI: 10.1016/j.aeaoa.2025.100346
Snigdha Aziz , Shahid Uz Zaman , Shatabdi Roy , Farah Jeba , Md Safiqul Islam , Mohammad Moniruzzaman , Abdus Salam
Indoor air pollution and its associated health risks have become a critical concern in developing countries. This study analyzed particulate matter (PM2.5) collected from six indoor locations in Dhaka, Bangladesh. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was used for measuring the concentration of thirteen heavy metals (Pb, Cd, Cr, Zn, Be, V, Ni, Hg, As, Co, Se, Mn, and Cu). Among these, Mn, Cd, Hg, and Pb exceeded United States Environmental Protection Agency (USEPA) guideline values, with Hg surpassing USEPA thresholds by over 50 times, Cd by more than 6-fold, and Pb by over fourfold, indicating substantial anthropogenic influence. Zn and Pb were identified as the primary contributors to indoor PM2.5, with high enrichment of Zn, Pb, Hg, Se, and Cd indicating strong anthropogenic influence. Principal Component Analysis (PCA) revealed two major components, explaining 71.26 % of the total variance. Acidity-alkalinity analysis revealed that PM2.5 in Dhaka was predominantly acidic, with greater concentrations of NO3− and SO42− further supporting the role of anthropogenic activities. Non-carcinogenic risk assessment showed hazard index (HI) values exceeding 10 at three locations, with Ni, Mn, and Cd posing the greatest risks for both children and adults. For carcinogenic risks, Total Cancer Risk (TCR) values at all sites exceeded acceptable thresholds. Cr, Cd, and As were the dominant contributors to TCR, and adults consistently exhibited higher risks than children due to lifetime exposure. This study provides novel, policy-relevant evidence on indoor air quality challenges in Dhaka, highlighting the urgent need for targeted interventions to mitigate heavy metal exposure and safeguard public health in dense urban environments.
{"title":"Comprehensive analysis of heavy metals in indoor PM2.5: Source identification and health risk assessment in Dhaka, Bangladesh","authors":"Snigdha Aziz , Shahid Uz Zaman , Shatabdi Roy , Farah Jeba , Md Safiqul Islam , Mohammad Moniruzzaman , Abdus Salam","doi":"10.1016/j.aeaoa.2025.100346","DOIUrl":"10.1016/j.aeaoa.2025.100346","url":null,"abstract":"<div><div>Indoor air pollution and its associated health risks have become a critical concern in developing countries. This study analyzed particulate matter (PM<sub>2.5</sub>) collected from six indoor locations in Dhaka, Bangladesh. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was used for measuring the concentration of thirteen heavy metals (Pb, Cd, Cr, Zn, Be, V, Ni, Hg, As, Co, Se, Mn, and Cu). Among these, Mn, Cd, Hg, and Pb exceeded United States Environmental Protection Agency (USEPA) guideline values, with Hg surpassing USEPA thresholds by over 50 times, Cd by more than 6-fold, and Pb by over fourfold, indicating substantial anthropogenic influence. Zn and Pb were identified as the primary contributors to indoor PM<sub>2.5</sub>, with high enrichment of Zn, Pb, Hg, Se, and Cd indicating strong anthropogenic influence. Principal Component Analysis (PCA) revealed two major components, explaining 71.26 % of the total variance. Acidity-alkalinity analysis revealed that PM<sub>2.5</sub> in Dhaka was predominantly acidic, with greater concentrations of NO<sub>3</sub><sup>−</sup> and SO<sub>4</sub><sup>2−</sup> further supporting the role of anthropogenic activities. Non-carcinogenic risk assessment showed hazard index (HI) values exceeding 10 at three locations, with Ni, Mn, and Cd posing the greatest risks for both children and adults. For carcinogenic risks, Total Cancer Risk (TCR) values at all sites exceeded acceptable thresholds. Cr, Cd, and As were the dominant contributors to TCR, and adults consistently exhibited higher risks than children due to lifetime exposure. This study provides novel, policy-relevant evidence on indoor air quality challenges in Dhaka, highlighting the urgent need for targeted interventions to mitigate heavy metal exposure and safeguard public health in dense urban environments.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100346"},"PeriodicalIF":3.8,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-07DOI: 10.1016/j.aeaoa.2025.100344
Chih-Yuan Chang , Yen-Chen Chen , Jia-Lin Wang , Wen-He Kao , Chieh-Heng Wang , Xiang-Xu Pan , Chang-Feng Ou-Yang , Hsin-Cheng Hsieh , Wen-Tzu Liu , Chih-Chung Chang
Incineration is a waste treatment method that involves burning the organic components of waste. While this process significantly reduces the volume of waste sent to landfills, it also generates environmental pollution and poses potential risks to public health. Although volatile organic compounds (VOCs) emitted from some combustion processes have been studied, VOCs released in the form of aerial plumes from incinerator smokestacks have rarely been evaluated. This knowledge gap is primarily due to the lack of suitable observation techniques for accurately detecting and capturing smokestack plumes. In this study, we employed novel drone-based observation and sampling techniques to investigate the characteristic VOCs emitted from a waste incineration smokestack. Additionally, we analyzed VOC emissions from landfills to provide a comparative assessment. Our findings indicate that incinerator plumes presented higher proportions of ethane, propane, ethyne, benzene, acetone, methyl ethyl ketone, and benzaldehyde, while nonanal and decanal originated mainly from landfills. Another species of interest is trimethylsilanol (TMSiOH), which has been observed in particularly high concentrations in both incinerator plumes and landfill emissions. TMSiOH levels from these sources were significantly higher than those detected in urban, rural, roadside, and background atmospheric environments, highlighting its potential as a characteristic marker of incinerator plumes and landfill emissions to identify pollution sources. Overall, this study demonstrates that unmanned aerial vehicle (UAV)-based sounding enables real-time detection of aerial plumes and characterization of incinerator plumes and landfill emissions. In addition, we proposed TMSiOH as a potential marker for incinerator plume and landfill emissions, which may provide important assistance in identifying pollution sources.
{"title":"A study of VOCs in waste incinerator plumes and landfill emissions via drone sounding","authors":"Chih-Yuan Chang , Yen-Chen Chen , Jia-Lin Wang , Wen-He Kao , Chieh-Heng Wang , Xiang-Xu Pan , Chang-Feng Ou-Yang , Hsin-Cheng Hsieh , Wen-Tzu Liu , Chih-Chung Chang","doi":"10.1016/j.aeaoa.2025.100344","DOIUrl":"10.1016/j.aeaoa.2025.100344","url":null,"abstract":"<div><div>Incineration is a waste treatment method that involves burning the organic components of waste. While this process significantly reduces the volume of waste sent to landfills, it also generates environmental pollution and poses potential risks to public health. Although volatile organic compounds (VOCs) emitted from some combustion processes have been studied, VOCs released in the form of aerial plumes from incinerator smokestacks have rarely been evaluated. This knowledge gap is primarily due to the lack of suitable observation techniques for accurately detecting and capturing smokestack plumes. In this study, we employed novel drone-based observation and sampling techniques to investigate the characteristic VOCs emitted from a waste incineration smokestack. Additionally, we analyzed VOC emissions from landfills to provide a comparative assessment. Our findings indicate that incinerator plumes presented higher proportions of ethane, propane, ethyne, benzene, acetone, methyl ethyl ketone, and benzaldehyde, while nonanal and decanal originated mainly from landfills. Another species of interest is trimethylsilanol (TMSiOH), which has been observed in particularly high concentrations in both incinerator plumes and landfill emissions. TMSiOH levels from these sources were significantly higher than those detected in urban, rural, roadside, and background atmospheric environments, highlighting its potential as a characteristic marker of incinerator plumes and landfill emissions to identify pollution sources. Overall, this study demonstrates that unmanned aerial vehicle (UAV<em>)</em>-based sounding enables real-time detection of aerial plumes and characterization of incinerator plumes and landfill emissions. In addition, we proposed TMSiOH as a potential marker for incinerator plume and landfill emissions, which may provide important assistance in identifying pollution sources.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100344"},"PeriodicalIF":3.8,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-03DOI: 10.1016/j.aeaoa.2025.100343
Amgad Saber , Ahmad E. Samman , Abdallah Abdaldym , Motirh Al-Mutairi , Mohamed Eid , Heshmat Abdel Basset
Air pollution poses significant threats to ecosystems, public health, and urban areas. This study analyzed the spatiotemporal patterns of O3, CO, NOx, and SO2 across Saudi Arabia (KSA), comparing industrial Al-Ahsa (east) with mountainous Al-Baha (west). Using CAMS data (2003–2023), we examined pollutant distributions and wind relationships across 15 pressure levels. O3 peaks in summer (110 DU) due to high temperatures and subsiding air, with winter lows (70 DU). Summer O3 is also influenced by vertical motion. CO concentrations are highest in winter (22 g/m2), linked to fuel combustion, and lowest in summer due to higher temperatures and elevated hydroxyl radicals. In the western region, NOx peaks in summer (0.8 g/m2) and dips in winter/early spring. SO2 is highest in autumn (1.4 g/m2) and lowest in summer. Eastern NOx and SO2 fluctuations are tied to local emissions and meteorology, with summer minima. CO shows the least variability, while SO2 has the most, followed by NOx and O3. Trends reveal O3 significantly increasing in southwestern KSA, CO generally decreasing but rising in the southwest and southeast, NOx showing weak increases (except central decreases), and SO2 increasing in industrial areas but declining broadly. These diverse trends highlight the strong regional impact of emissions and human activities on pollutant behavior across KSA.
{"title":"Pollutants variability over the Kingdom of Saudi Arabia","authors":"Amgad Saber , Ahmad E. Samman , Abdallah Abdaldym , Motirh Al-Mutairi , Mohamed Eid , Heshmat Abdel Basset","doi":"10.1016/j.aeaoa.2025.100343","DOIUrl":"10.1016/j.aeaoa.2025.100343","url":null,"abstract":"<div><div>Air pollution poses significant threats to ecosystems, public health, and urban areas. This study analyzed the spatiotemporal patterns of O<sub>3</sub>, CO, NO<sub>x</sub>, and SO<sub>2</sub> across Saudi Arabia (KSA), comparing industrial Al-Ahsa (east) with mountainous Al-Baha (west). Using CAMS data (2003–2023), we examined pollutant distributions and wind relationships across 15 pressure levels. O<sub>3</sub> peaks in summer (110 DU) due to high temperatures and subsiding air, with winter lows (70 DU). Summer O<sub>3</sub> is also influenced by vertical motion. CO concentrations are highest in winter (22 g/m<sup>2</sup>), linked to fuel combustion, and lowest in summer due to higher temperatures and elevated hydroxyl radicals. In the western region, NO<sub>x</sub> peaks in summer (0.8 g/m<sup>2</sup>) and dips in winter/early spring. SO<sub>2</sub> is highest in autumn (1.4 g/m<sup>2</sup>) and lowest in summer. Eastern NO<sub>x</sub> and SO<sub>2</sub> fluctuations are tied to local emissions and meteorology, with summer minima. CO shows the least variability, while SO<sub>2</sub> has the most, followed by NO<sub>x</sub> and O<sub>3</sub>. Trends reveal O<sub>3</sub> significantly increasing in southwestern KSA, CO generally decreasing but rising in the southwest and southeast, NO<sub>x</sub> showing weak increases (except central decreases), and SO<sub>2</sub> increasing in industrial areas but declining broadly. These diverse trends highlight the strong regional impact of emissions and human activities on pollutant behavior across KSA.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100343"},"PeriodicalIF":3.8,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Exposure to elevated levels of fine particulate matter (PM2.5) has been a major public health concern for decades. However, the specific sources of air toxics associated with PM2.5 remain unclear. In this study, we investigate PM2.5 pollution in Taichung, Taiwan—a representative East Asian metropolitan area— during March and November of 2021–2023 using an advanced two-stage positive matrix factorization (PMFxPMF) approach. This method enables detailed source apportionment of both bulk PM2.5 and PM2.5-bound heavy metals. Our analysis reveals that, during the East Asian winter monsoon seasons, regional transboundary pollution contributed 38 % to the PM2.5 load, while local sources—such as carbonaceous aerosols, industrial processes, ammonium nitrate/chloride, and transformed sea spray—contributed between 9 % and 20 %. Furthermore, the formation of nitrate was the primary driver of air quality deterioration. Heavy metals constituted 1.2 %–1.5 % of PM2.5 mass (0.24–0.32 μg m−3). By incorporating heavy metal fingerprints from two major local sources—coal-fired power plants and steel sintering facilities—as constraints in our PMF analysis, we reveal that ambient non-Fe heavy metals were mainly associated with suspended dust (34 %), implying significant health risk of dust exposure. Besides, vehicular pollution accounted for 14 % of non-Fe heavy metals, highlighting the need for a stronger control on non-exhaust vehicular emissions. Substantial contributions arose from coal combustion (9 %), steel sintering (5 %) and various industrial sources (22 %). Our results underscore the importance of accelerating the timeline for coal phaseout, and warrant a further investigation on the emissions of heavy metals from industrial activities.
{"title":"Observation-based investigation reveals major sources of heavy metals associated with fine particulate matter (PM2.5) in an East Asian urban area","authors":"Shane S.-E. Sun, Yi-Tang Huang, Mei-June Chen, Xuan-Ru Huang, Shu-Hui Huang, Wen-Yu Liao, Charles C.-K. Chou","doi":"10.1016/j.aeaoa.2025.100342","DOIUrl":"10.1016/j.aeaoa.2025.100342","url":null,"abstract":"<div><div>Exposure to elevated levels of fine particulate matter (PM<sub>2.5</sub>) has been a major public health concern for decades. However, the specific sources of air toxics associated with PM<sub>2.5</sub> remain unclear. In this study, we investigate PM<sub>2.5</sub> pollution in Taichung, Taiwan—a representative East Asian metropolitan area— during March and November of 2021–2023 using an advanced two-stage positive matrix factorization (PMFxPMF) approach. This method enables detailed source apportionment of both bulk PM<sub>2.5</sub> and PM<sub>2.5</sub>-bound heavy metals. Our analysis reveals that, during the East Asian winter monsoon seasons, regional transboundary pollution contributed 38 % to the PM<sub>2.5</sub> load, while local sources—such as carbonaceous aerosols, industrial processes, ammonium nitrate/chloride, and transformed sea spray—contributed between 9 % and 20 %. Furthermore, the formation of nitrate was the primary driver of air quality deterioration. Heavy metals constituted 1.2 %–1.5 % of PM<sub>2.5</sub> mass (0.24–0.32 μg m<sup>−3</sup>). By incorporating heavy metal fingerprints from two major local sources—coal-fired power plants and steel sintering facilities—as constraints in our PMF analysis, we reveal that ambient non-Fe heavy metals were mainly associated with suspended dust (34 %), implying significant health risk of dust exposure. Besides, vehicular pollution accounted for 14 % of non-Fe heavy metals, highlighting the need for a stronger control on non-exhaust vehicular emissions. Substantial contributions arose from coal combustion (9 %), steel sintering (5 %) and various industrial sources (22 %). Our results underscore the importance of accelerating the timeline for coal phaseout, and warrant a further investigation on the emissions of heavy metals from industrial activities.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"27 ","pages":"Article 100342"},"PeriodicalIF":3.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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