ACS ES&T Air最新文献

{"title":"Plume Detection and Emissions Quantification Potential Using a Dense Sensor Network","authors":"Milan Y. Patel,&nbsp;Yishu Zhu,&nbsp;Anna R. Winter,&nbsp;Naomi G. Asimow and Ronald C. Cohen*,&nbsp;","doi":"10.1021/acsestair.5c0006910.1021/acsestair.5c00069","DOIUrl":"https://doi.org/10.1021/acsestair.5c00069https://doi.org/10.1021/acsestair.5c00069","url":null,"abstract":"<p >Densely spaced sensor networks provide a unique opportunity for describing emissions from stationary and moving point sources and from intermittent events like fires or industrial flaring. As an example of what sensor networks can achieve, we describe quantification of emissions from a small urban fire in the Bay Area of California using the Berkeley Environmental Air-quality and CO₂ Network (BEACO₂N), a dense air quality and greenhouse gas monitoring network. Pollutant enhancements are measured at multiple sites, and the ensemble of observations are fit to a 2-D Gaussian model to characterize the extent of dilution prior to observation and derive emissions at the location of the fire. Distinct approaches are used for calibration of the CO₂, air quality gases, and PM_2.5 instruments. Consistency of the ratios at multiple locations downwind of the fire supports the precision of the network. We find that the fire emitted approximately 770 ± 30 kg of PM_2.5, 70,000 ± 20,000 kg of CO₂, 2500 ± 300 kg of CO, and 28 ± 9 kg of NO_<i>x</i>. The emission ratios are in the range of typical wildland fires. Using this example, we explore the minimum plume emissions that could be observed and quantified by the network.</p><p >This study demonstrates the potential of an air quality and greenhouse gas monitoring network to detect plumes and quantify emissions from point sources.</p>","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 6","pages":"1099–1106 1099–1106"},"PeriodicalIF":0.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsestair.5c00069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144269849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine-Learning-Based Estimation of Marine CHBr3 Emissions around Asia and the Implication on Bromine Radicals and Ozone Depletion","authors":"Jing Chen,&nbsp;Yuchen Liu,&nbsp;Jie Li,&nbsp;Chuang Qin,&nbsp;Xianyi Sun and Xiao Fu*,&nbsp;","doi":"10.1021/acsestair.4c0035710.1021/acsestair.4c00357","DOIUrl":"https://doi.org/10.1021/acsestair.4c00357https://doi.org/10.1021/acsestair.4c00357","url":null,"abstract":"<p >Ocean-produced, very short-lived bromine substances, such as bromoform (CHBr₃), can significantly affect the tropospheric and stratospheric bromine loading and ozone budget. However, large uncertainties exist for marine CHBr₃ emission estimations, especially around Asia. In this study, we establish a new marine emission inventory of CHBr₃, considering the physical and biogeochemical forces in the interaction of the ocean and atmosphere. The surface seawater concentrations are predicted based on expanded in situ CHBr₃ measurements and the machine-learning approach. The marine CHBr₃ emission is estimated to be 55.9 Gg Br yr^–1 around Asia, accounting for 20.4% of the global total. Our estimate is 18.7 Gg Br yr^–1 higher than the previously widely used bottom-up emission inventory, primarily due to discrepancies in the Western Pacific and the South China Sea. Higher estimated marine CHBr₃ emissions significantly affect the stratospheric bromine radicals and ozone over Asia, leading to a maximum increase of 13.6% in Br and 12.2% in BrO concentrations and thus up to a 2.5 ppbv reduction in stratospheric ozone. This study highlights the need for additional marine CHBr₃ observations in data-sparse regions to better quantify marine CHBr₃ emissions and assess their potential atmospheric impacts. This new approach also provides a valuable model framework to calculate sea–air fluxes for other compounds of interest.</p>","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 6","pages":"1069–1078 1069–1078"},"PeriodicalIF":0.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144269979","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}

{"title":"Influence of Vehicle Design on Near-Road Concentrations of Traffic-Related Air Pollutants","authors":"Samuel Wilson,&nbsp;Naomi J. Farren,&nbsp;Yoann Bernard,&nbsp;Marvin D. Shaw,&nbsp;Kaylin Lee,&nbsp;Mallery Crowe,&nbsp;James D. Lee and David C. Carslaw*,&nbsp;","doi":"10.1021/acsestair.5c0005910.1021/acsestair.5c00059","DOIUrl":"https://doi.org/10.1021/acsestair.5c00059https://doi.org/10.1021/acsestair.5c00059","url":null,"abstract":"<p >Exposure to traffic-related air pollution (TRAP) is an ongoing health concern worldwide, particularly close to roads where concentrations are the highest. Near-road exposure is influenced by factors such as vehicle exhaust emission rates, pollutant composition, and dispersion behavior. In this work we apply a recently developed technique called <i>plume regression</i> based on fast-response roadside measurements, to better understand the variables affecting near-road TRAP concentrations. Of specific interest is determining the extent to which vehicle design and physical characteristics affect roadside exposure to important pollutants such as nitrogen oxides (NO_<i>x</i> = NO + NO₂). We find that the position of passenger car’s exhaust (tailpipe)─whether on the left or right side─results in a 40% difference in pollutant concentration contribution at the curbside. In the UK, only 20.1% of diesel passenger cars, the most significant vehicle class contributors to NO_<i>x</i> emissions, have their exhausts positioned on the right, the position associated with the lowest concentrations. If all diesel cars in the UK were equipped with right-positioned exhausts─the side farthest from the curb, curbside concentrations from these vehicles would be reduced by one-third. We also find evidence that electric vehicles (EVs) act to dilute the exhaust plumes of proximate fossil-fueled vehicles through vehicle-induced turbulence, reducing near-road TRAP exposure, a hitherto unrealized benefit of EVs.</p><p >Fast-response measurements of traffic-related pollutants show the physical attributes of a vehicle such as exhaust position influences near-road concentrations.</p>","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 6","pages":"1089–1098 1089–1098"},"PeriodicalIF":0.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsestair.5c00059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144269831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anthropogenic Oxygenated Volatile Organic Compounds Dominate Atmospheric Oxidation Capacity and Ozone Production via Secondary Formation of Formaldehyde in the Urban Atmosphere","authors":"Hongtao Qian,&nbsp;Bingye Xu,&nbsp;Zhengning Xu*,&nbsp;Qiaoli Zou,&nbsp;Qianxin Zi,&nbsp;Hanfei Zuo,&nbsp;Fei Zhang,&nbsp;Jing Wei,&nbsp;Xiangyu Pei,&nbsp;WenXin Zhou,&nbsp;Lingling Jin,&nbsp;Xudong Tian,&nbsp;Wenlong Zhao* and Zhibin Wang,&nbsp;","doi":"10.1021/acsestair.4c0031710.1021/acsestair.4c00317","DOIUrl":"https://doi.org/10.1021/acsestair.4c00317https://doi.org/10.1021/acsestair.4c00317","url":null,"abstract":"<p >Oxygenated volatile organic compounds (OVOCs) play an important role in the photochemical formation of ozone (O₃). Comprehensive measurements and chemical box model analysis conducted in Hangzhou, China reveal that the formation of O₃ is strongly attributed to the increased atmospheric oxidation capacity (AOC). The observed OVOCs contribute 46.5 ± 8.3% to the AOC, especially during the pollution periods, with formaldehyde (HCHO) and acetaldehyde (CH₃CHO) accounting for 19 ± 3.8% and 13.8 ± 4.1%, respectively. Various OVOCs (especially CH₃CHO) act as key precursors for the initial production of the crucial radicals. These include the hydroperoxy radical (HO₂), methyl peroxy radical (CH₃O₂), and acetyl peroxy radical (CH₃CO₃), accounting for 53.7 ± 5.0%, 13.9 ± 2.5%, and 10.0 ± 2.4% of the daytime O₃ production (P(O₃)), respectively. HCHO acted as the key accelerator of HO₂ radical production and subsequently speeded up O₃ production. Model simulation and observational evidence reveal that the OVOC initiated secondary channel dominates the HCHO formation. The radical propagation chain of CH₃CO₃ → CH₃O₂→ CH₃O→ HO₂ accounts for 62.4 ± 6.9% of HCHO production. CH₃CHO chemistry can account for 14.0% of the production of O₃, and degradation of secondary HCHO derived from CH₃CHO accounts for 5.2% of total HO₂ production. These findings underscore the significant effect of OVOCs, particularly CH₃CHO, on AOC and O₃ production in the urban atmosphere in eastern China. Given the decreasing trend of NO_X concentration, model simulations under different NO_X levels further imply that reducing anthropogenic emission sources of OVOCs is a crucial strategy for current O₃ control, and excessive reduction of NO_X emissions (the daytime average concentration of NO_X decreases to below ∼ 2 ppb) may affect the effectiveness of reducing VOCs and promote a radical self-reaction.</p>","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 6","pages":"1033–1041 1033–1041"},"PeriodicalIF":0.0,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144269603","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}

{"title":"Improving Temporal and Spatial Coverage of UK Black Carbon Measurements by Applying a Machine Learning Approach","authors":"I. S. Wong*,&nbsp;James D. Allan*,&nbsp;Gary W. Fuller and Anna Font,&nbsp;","doi":"10.1021/acsestair.4c0030610.1021/acsestair.4c00306","DOIUrl":"https://doi.org/10.1021/acsestair.4c00306https://doi.org/10.1021/acsestair.4c00306","url":null,"abstract":"<p >The WHO Global Air Quality Guidelines suggest that continuous and systematic monitoring of black carbon (BC) should be implemented due to BC from both transport and residential wood burning posing adverse health effects. Beyond PM₁₀ and PM_2.5, BC serves as a strong indicator for the study of health risks related to primary combustion sources. In the UK, only 14 monitoring stations report BC concentrations, contrasting with the extensive network measuring NO_<i>x</i>, SO₂, O₃, CO, PM₁₀ and PM_2.5 and meteorological parameters (more than 170 stations across the country). The sparse spatial and temporal coverage of BC data caused by this limitation constrains scientists’ research and policy makers’ decisions. This study applies machine learning algorithms to address this challenge: first, filling gaps in missing BC data at 9 urban and 4 rural background sites in the UK between 2009 and 2020, and then further estimating hourly concentrations of BC at 7 sites without observations (1 urban and 6 rural background sites). The result is a new data set with greater temporal and spatial coverage of BC data, providing a resource for further research on BC impacts such as epidemiological studies on health outcomes. Although the data are specific to the UK, the proposed methodology can potentially be applied to other countries.</p>","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 6","pages":"1020–1032 1020–1032"},"PeriodicalIF":0.0,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144269599","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}

{"title":"","authors":"Natalie Brett*,&nbsp;Steve R. Arnold,&nbsp;Kathy S. Law,&nbsp;Jean-Christophe Raut,&nbsp;Tatsuo Onishi,&nbsp;Brice Barret,&nbsp;Elsa Dieudonné,&nbsp;Meeta Cesler-Maloney,&nbsp;William Simpson,&nbsp;Slimane Bekki,&nbsp;Joel Savarino,&nbsp;Sarah Albertin,&nbsp;Robert Gilliam,&nbsp;Kathleen Fahey,&nbsp;George Pouliot,&nbsp;Deanna Huff and Barbara D’Anna,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acsestair.5c00030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144451990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Sara Bjerre Sørensen,&nbsp; and ,&nbsp;Kasper Kristensen*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acsestair.5c00005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144451994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Shemphang Hynniewta*,&nbsp; and ,&nbsp;Asit K. Chandra,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acsestair.5c00041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144452521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Xiangyu Zhang,&nbsp;Hongxia Liu,&nbsp;Jianlin Cheng,&nbsp;Wei Song,&nbsp;Haichao Wang,&nbsp;Yanli Zhang and Xinming Wang*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acsestair.4c00353","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144452525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Lu Lei,&nbsp;Wei Xu*,&nbsp;Chunshui Lin,&nbsp;Baihua Chen,&nbsp;Kirsten N. Fossum,&nbsp;Darius Ceburnis,&nbsp;Colin O’Dowd and Jurgita Ovadnevaite*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"2 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acsestair.4c00331","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144452527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}