Atmospheric Environment: X最新文献

{"title":"Urgent issues regarding real-time air quality monitoring data in India: Unveiling solutions and implications for policy and health","authors":"Karn Vohra , Madhumitha S. , Abhishek Chakraborty , Hitansh Shah , Bharrathi AS. , Jayaraju Pakki","doi":"10.1016/j.aeaoa.2024.100308","DOIUrl":"10.1016/j.aeaoa.2024.100308","url":null,"abstract":"<div><div>Deteriorating air quality in India has heightened the emphasis on air quality monitoring. This has resulted in a 16-fold increase in the number of Continuous Ambient Air Quality Monitoring Sites (CAAQMS) across the country over the last decade. The CAAQMS datasets are used globally, but concerns about data quality have also been raised. Missing is a comprehensive assessment quantifying the scale of these air quality data issues and the impact these have on policy- and health-relevant metrics. So, we develop the first open-source automated tool to identify and address data issues and apply it to six pollutants (PM<sub>2.5</sub>, PM<sub>10</sub>, NO, NO<sub>2</sub>, NO<sub>x</sub>, and O<sub>3</sub>) from 213 CAAQMS in 2019–2023. Typical issues in CAAQMS datasets include similar values that repeat continuously for durations exceeding 24 h and outliers that occur at almost the same time every day. We also reveal hidden issues for nitrogen oxides (NO<sub>x</sub> ≈ NO + NO<sub>2</sub>) that include (1) reporting of NO and NO<sub>2</sub> in units not compliant with the Central Pollution Control Board parameter reporting protocol and (2) inconsistency in data reporting when either NO or NO<sub>2</sub> is recorded as “Not Available” but valid NO<sub>x</sub> data is reported. The proportion of data influenced by consecutively similar observations and outliers has remained fairly consistent but sites affected by unit inconsistency issues have grown between 2019 and 2023. No significant difference in data quality issues was observed between CAAQMS maintained by central and state pollution control boards illustrating the country-wide extent of these issues. We find that removing consecutively similar observations and outliers changes annual mean pollutant concentrations by only <5% but correcting for the yet unaddressed issue of unit inconsistency increases annual mean NO<sub>2</sub> concentrations by a dramatic >80% for sites affected by it. We conducted a separate analysis to confirm that the unit inconsistency issue was not identified and addressed in multiple peer-reviewed studies examining the impact of the COVID-19 lockdown, and this is likely to have resulted in reporting of inaccurate absolute air quality improvements.</div><div>A substantial impact of data cleaning on air quality-derived metrics is observed for nitrogen oxides. The impact is marginal for other pollutants. We find that after data cleaning, 23 sites in 2019 became non-compliant with national ambient air quality standards for NO<sub>2</sub>. Worsening of NO<sub>2</sub> data quality over the years increased the number of non-compliant sites to 45 in 2023 after using our tool. For PM<sub>2.5</sub> and PM<sub>10</sub>, fewer than 5 sites changed compliance post-data cleaning. Given marginal changes in concentrations of PM<sub>2.5</sub> and O<sub>3</sub>, premature mortality attributable to exposure to these in Delhi, Mumbai, and Kolkata changed only by <10% after data c","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"25 ","pages":"Article 100308"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158866","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":"Optimisation and validation of Plume Chasing for robust and automated NOx and particle vehicle emission measurements","authors":"Christina Schmidt ,&nbsp;C. David Carslaw ,&nbsp;J. Naomi Farren ,&nbsp;N. René Gijlswijk ,&nbsp;Markus Knoll ,&nbsp;E. Norbert Ligterink ,&nbsp;Jan Pieter Lollinga ,&nbsp;Martin Pechout ,&nbsp;Stefan Schmitt ,&nbsp;Michal Vojtíšek ,&nbsp;Quinn Vroom ,&nbsp;Denis Pöhler","doi":"10.1016/j.aeaoa.2025.100317","DOIUrl":"10.1016/j.aeaoa.2025.100317","url":null,"abstract":"<div><div>High-emitting vehicles comprise a small proportion (<span><math><mrow><mo>&lt;</mo><mn>20</mn><mspace></mspace><mstyle><mtext>%</mtext></mstyle></mrow></math></span>) of the vehicle fleet, yet are responsible for the majority (<span><math><mrow><mo>&gt;</mo><mn>50</mn><mspace></mspace><mstyle><mtext>%</mtext></mstyle></mrow></math></span>) of vehicle emissions. Plume Chasing is a reliable, high-precision measurement technique that derives emissions without interfering with the vehicle being tested. Its characteristics make it well suited for high emitter identification. In this study, the influence of several Plume Chasing measurement and data processing methods on the results of derived on-road <span><math><msub><mrow><mi>NO</mi></mrow><mrow><mi>x</mi></mrow></msub></math></span> and particle fuel-specific emission factors are investigated. A range of vehicles, representative of a common vehicle fleet, were tested under different driving conditions on a test track. The derived results were evaluated against on-board SEMS (Smart Emission Measurement System) emission measurements. We found that one of the best performing Plume Chasing data processing methods is based on the use of a rolling minimum for background determination. The average absolute deviation of the determined <span><math><mrow><msub><mrow><mi>NO</mi></mrow><mrow><mi>x</mi></mrow></msub><mo>/</mo><msub><mrow><mi>CO</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></math></span> emission ratios from the reference was <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>2</mn><mrow><mo>(</mo><mn>46</mn><mo>)</mo></mrow><mspace></mspace><mstyle><mi>p</mi><mi>p</mi><mi>m</mi></mstyle><mo>/</mo><mstyle><mtext>%</mtext></mstyle></mrow></math></span> for the heavy duty vehicle and <span><math><mrow><mn>0</mn><mo>.</mo><mn>3</mn><mrow><mo>(</mo><mn>29</mn><mo>)</mo></mrow><mspace></mspace><mstyle><mi>p</mi><mi>p</mi><mi>m</mi></mstyle><mo>/</mo><mstyle><mtext>%</mtext></mstyle></mrow></math></span> for the light duty vehicles tested. The methods were easy to automate and suitable for high emitter detection and quantification of emissions from two-wheeled vehicles. Inaccurate emission factors derived from Plume Chasing measurements occurred only in situations when emissions were significantly influenced by a strong plume from vehicles driving directly ahead of the vehicle of interest.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"25 ","pages":"Article 100317"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143237363","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":"A real world assessment of European medium-duty vehicle emissions and fuel consumption","authors":"Nikiforos Zacharof ,&nbsp;Stijn Broekaert ,&nbsp;Theodoros Grigoratos ,&nbsp;Evangelos Bitsanis ,&nbsp;Georgios Fontaras","doi":"10.1016/j.aeaoa.2024.100307","DOIUrl":"10.1016/j.aeaoa.2024.100307","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Emissions of road vehicles have a significant impact on climate change and air quality and in order to address these problems there have been regulatory actions globally in the last decades. Such actions have focused mainly on light and heavy-duty vehicles, which comprise the highest share of the fleet and are responsible for the majority of emissions in the field. However, there are also medium-duty vehicles with a maximum permissible mass between 3.5 and 12 tonnes in the European categories, which have been mostly overlooked until recently. These vehicles could have a low market share, but they are important as they circulate mainly in urban and suburban areas under transient conditions and often with congestion. This has a detrimental impact on the environment and human health due to greenhouse gas and pollutant emissions. However, there are limited studies for this vehicle category. The current work undertook to address this issue by focusing on medium-duty vehicles in Europe by attempting to establish a methodology to calculate reference emission values for CO&lt;sub&gt;2&lt;/sub&gt;, NO&lt;sub&gt;x&lt;/sub&gt; and CO to improve fleet monitoring. For this reason, two state-of-the-art vehicles were measured on-road under the EU verification test procedure. Naturally, the measurements represented the anticipated average European conditions of the route in terms of speed profile, road grade and distance. In order to provide emissions values that are representative of the European conditions a normalization process was needed. For this reason, the measurements were used to set up vehicle simulations in VECTO, the official simulation tool of the European Commission for calculating type-approval fuel consumption and CO&lt;sub&gt;2&lt;/sub&gt; emissions. In this way, the simulations provided values ranging from 297 g/km to 373 g/km. Using the ratio of fuel consumption for NO&lt;sub&gt;x&lt;/sub&gt; and CO from the measurements, it was possible to derive reference pollutant values. For NO&lt;sub&gt;x&lt;/sub&gt;, they were found to be between 0.0557 and 0.0963 g/km, while for CO the values were at 0.047 g/km. These values could be used as emissions factors as in the Guidebook, which is the official tool for monitoring fleet emissions of the European Commission. The Guidebook offers several approaches to calculate emissions, depending on data availability with the most sophisticated being a calculation method using vehicle speed, loading share and road grade. Taking this into consideration, the current work developed a similar methodology using the simulation time-series to derive regression coefficients that enable the calculation of CO&lt;sub&gt;2&lt;/sub&gt;, NO&lt;sub&gt;x&lt;/sub&gt; and CO emissions under different operating conditions. In this way, this methodology can be applied to representative vehicles of the medium and heavy-duty categories that have been through the verification test procedure to determine representative emission factors for these vehicles. This methodology could be used to improve fleet emiss","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"25 ","pages":"Article 100307"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158447","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":"Real-world emission characteristics and driving factors of diesel trucks: Insights from plume chasing experiments","authors":"Jiahao Yang ,&nbsp;Xiang Che ,&nbsp;Jiani Tan ,&nbsp;Xiaoliang Qin ,&nbsp;Jiahao Duan ,&nbsp;Dengguo Liu ,&nbsp;Yusen Duan ,&nbsp;Sheng Xiang ,&nbsp;Nanchi Shen ,&nbsp;Xi Zhai ,&nbsp;Yi Zhang ,&nbsp;Zhi Ning ,&nbsp;Li Li","doi":"10.1016/j.aeaoa.2025.100311","DOIUrl":"10.1016/j.aeaoa.2025.100311","url":null,"abstract":"<div><div>On-road transportation is gradually becoming one of the major source contributors to air pollutants and carbon emissions in China. In this study, a chasing experiment was conducted on 487 diesel trucks in Shanghai using a mobile plume chasing and analysis system to obtain the real-world emission characteristics of air pollutants and carbon dioxide (CO₂). The average emission factors (EFs) of nitrogen oxide (NOx), fine particulate matter (PM_2.5), volatile organic compounds (VOCs) and carbon monoxide (CO) of the measured vehicles are 22.8 ± 13.5, 0.38 ± 0.26, 5.6 ± 4.9, and 4.5 ± 4.0 g/kg fuel, respectively. The observed decrease in EFs of air pollutants from China IV to China VI suggests a potential correlation between stricter emission standards and reduced emissions in diesel truck fleets. Additionally, the EFs increase with the gross vehicle weights (GVW). The driving speed, registration year and wind direction were the main drivers of NOx EFs. The measured CO₂ EFs is 3182.2 ± 5.8 g/kg fuel, showing little variations with emission standards and GVW, which is different from the abovementioned air pollutants. We found a significant negative correlation between the EFs of CO₂ and NO_x (p &lt; 0.05), indicating that as NOx emissions decrease, CO₂ emissions tend to increase. Therefore, we recommend integrating CO₂ emission limits into new standards to achieve synergistic control of pollutants and greenhouse gases.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"25 ","pages":"Article 100311"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158867","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":"Distribution of polycyclic aromatic compounds among various phases in an urban road microenvironment of a tropical megacity","authors":"Dheeraj Alshetty ,&nbsp;S.M. Shiva Nagendra ,&nbsp;Andrea Mueller ,&nbsp;Uwe Schlink","doi":"10.1016/j.aeaoa.2024.100309","DOIUrl":"10.1016/j.aeaoa.2024.100309","url":null,"abstract":"<div><div>Quantitative research on characteristics of PAHs prevalent in urban road microenvironments (URM) is vital to emphasize the seriousness of health risks and reduce exposure among commuters and nearby residents, especially in Indian cities where the traffic emissions (exhaust and non-exhaust) are the major contributors to atmospheric particulates in an urban area. The present research investigates the distribution and correlation of Polycyclic Aromatic Hydrocarbons (PAHs) found in various phases (PM₁₀, PM_2.5, resupendable road dust (RRD) and gaseous phase) at urban road microenvironment (URM) using Two-way ANOVA analysis. The sources and health risk associated with PAH exposure is also estimated. PM₁₀ and PM_2.5 samples were collected on the kerbside using high-volume samplers, and RRD was collected at eight contrasting locations using EPA AP-42 methodology. A total of 64 PAHs were analyzed using GC-MS and incremented life cancer risk (ILCR) was estimated for children and adults by calculating toxicity equivalents using three different approaches. Average PAHs concentration varied from 75 to 175 μg/g for PM₁₀, 30–80 μg/g for PM_2.5, and 01–03 μg/g for RRD. Gaseous phase ∑PAH was found to be in the range of 0.5–2.75 μg/m³. It was found that high molecular weight PAHs such as Coronene, Pyrene, Indeno(1,2,3-c,d)pyrene and Benzo ghi perylene were the major contributing compounds in the urban road microenvironment. A strong correlation between PAHs bound to PM₁₀ and RRD was found at all the sampling locations. Further, ILCRs of total cancer risk due to inhalation of PM were in the range of 1.61E-05 to 2.05E-03. However, the risk due to exposure to RRD was within an acceptable risk of 1E-06. The current study highlights the scientific backing for RRD-specific regulations, which are currently absent, to control non-exhaust emissions in India.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"25 ","pages":"Article 100309"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158448","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":"A multiscale geographically weighted regression approach to emphasize the effects of traffic characteristics on vehicular emissions","authors":"Farzane Omrani,&nbsp;Rouzbeh Shad,&nbsp;Seyed Ali Ziaee","doi":"10.1016/j.aeaoa.2025.100315","DOIUrl":"10.1016/j.aeaoa.2025.100315","url":null,"abstract":"<div><div>The rapid growth in motor vehicle numbers over the years has notably increased air pollution levels, particularly in developing countries. According to the International Energy Agency, road transport significantly contributes to air pollution more than other transportation. This study aims to investigate the spatial distribution impact of various built environment, sociodemographic, meteorological, and traffic-related features across buffer distances on vehicular emissions from all vehicle types at the link level. Initially, this study restructured data to perform 25 combination models for five emissions from all vehicles, classified into five types. Secondly, regression models were created using Ordinary Least Squares (OLS) and Multiscale Geographically Weighted Regression (MGWR) in ArcGIS Pro, assessing the spatial impact of these features on emissions for each road segment in North Carolina in 2019. Model performance was evaluated using adjusted R-squared and R-squared metrics, with the MGWR model outperforming the OLS model, achieving adjusted R-squared values between 74% and 97%. Finally, it analyzes the spatial distribution impact of each feature on each emission from vehicle types at the link level. Particularly, the significant impact of traffic-related features on vehicular emission offers valuable insights for governments and decision-makers to develop targeted transportation planning strategies and meet air pollution targets set by the state.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"25 ","pages":"Article 100315"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158446","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":"A comprehensive provincial-level VOCs emission inventory and scenario analysis for China: Enhanced sectoral resolution through GAINS-China model","authors":"Yuhang Zhao ,&nbsp;Hong Sun ,&nbsp;Younha Kim ,&nbsp;Yun Shu ,&nbsp;Han Wang ,&nbsp;Hui Li ,&nbsp;Yinhe Deng","doi":"10.1016/j.aeaoa.2025.100316","DOIUrl":"10.1016/j.aeaoa.2025.100316","url":null,"abstract":"<div><div>Volatile organic compounds (VOCs) are key precursors to secondary organic aerosol (SOA) and ground-level ozone, posing significant challenges to air quality and public health in China. Although previous studies have established VOCs inventories and projected emission trends, many lack the granularity needed to capture sectoral and regional emission variations, especially within the highly contributive solvent use sector. To address this gap, this study aims to develop a detailed VOCs emission inventory for China at the provincial level for 2020, utilizing the GAINS-China model and covering 5 major sectors, 20 subsectors, and 80 distinct emission sources. Uniquely, this inventory subdivides the solvent use sector into 5 subsectors and 22 specific sources, enabling a more precise analysis of VOCs emission sources. Future emission trends and reduction potentials were projected for the period 2020–2050 under two scenarios: reference (REF) and current legislation (CLE). The results revealed that the total anthropogenic VOCs emissions in China were estimated to be 23,114.8 kt in 2020, with solvent use contributing 56.0%, followed by the residential (17.0%), others (11.0%), transportation (10.0%), and industry and power (6.0%) sectors. Under the REF scenario, VOCs emissions are expected to decline to 19,162.2 kt by 2040 but remain stable thereafter. This reduction is driven mainly by the replacement of household solid fuels with clean fuels in the residential sector, especially in Sichuan Province. Compared with those in the REF scenario, the total VOCs emissions in the CLE scenario continuously decreased throughout 2020–2050, with the solvent use sector contributing the most to the reductions (46.1%–81.7%), followed by transport (16.8%–41.3%). A provincial analysis highlights that high-emission regions such as Guangdong, Jiangsu, and Shandong offer the greatest reduction potential. To effectively and precisely reduce VOCs emissions, key subsectors contributing to emissions, including paint use, non-road machinery, industrial processes, and agriculture, should be prioritized for further control measures. This study provides essential insights into sectoral and regional VOCs emissions, offering a robust foundation for formulating targeted emission control policies.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"25 ","pages":"Article 100316"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158869","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":"Investigating the spatiotemporal distribution of fine particulate matter sources during persistent cold air pools in Salt Lake County","authors":"Jonathan Silberstein ,&nbsp;Daniel Mendoza ,&nbsp;Emma Rieves ,&nbsp;Colleen E. Reid ,&nbsp;Michael Hannigan","doi":"10.1016/j.aeaoa.2024.100305","DOIUrl":"10.1016/j.aeaoa.2024.100305","url":null,"abstract":"<div><div>Persistent cold air pools (PCAP), also referred to colloquially as inversions, are responsible for some of the greatest enhancements in air pollution in Utah’s Wasatch Front. PCAPs, which can last for a period of days or weeks, trap warm air beneath a layer of colder air, which results in the accumulation of particulates during the inversion. Fine particulate matter (PM_2.5) sampling occurred in seven field sites across Salt Lake County (SLCo) during Wintertime (November–April). Concentrations of the organic mass of PM_2.5 increased during inversion events (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mi>i</mi><mi>n</mi><mi>v</mi></mrow></msub></math></span> = 4.0 <span><math><mrow><mi>μ</mi><msup><mrow><mi>g/m</mi></mrow><mrow><mn>3</mn></mrow></msup></mrow></math></span>) when compared to the wintertime baseline (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mi>b</mi><mi>a</mi><mi>s</mi><mi>e</mi><mi>l</mi><mi>i</mi><mi>n</mi><mi>e</mi></mrow></msub></math></span> = 3.5 <span><math><mrow><mi>μ</mi><msup><mrow><mi>g/m</mi></mrow><mrow><mn>3</mn></mrow></msup></mrow></math></span>). However, organic mass enhancements during PCAPs were most pronounced at lowest-altitude field sites situated near potential PM_2.5 sources. Four sources of organic carbon were identified, comprised of industrial, abrasive, wood burning, and onroad sources. During PCAP events, PM_2.5 species profiles exhibited greater spatial heterogeneity, due to lower wind speeds and caps on vertical mixing (Coefficient of Determination<span><math><msub><mrow></mrow><mrow><mi>i</mi><mi>n</mi><mi>v</mi></mrow></msub></math></span> = 0.51, Coefficient of Determination<span><math><msub><mrow></mrow><mrow><mi>b</mi><mi>a</mi><mi>s</mi><mi>e</mi><mi>l</mi><mi>i</mi><mi>n</mi><mi>e</mi></mrow></msub></math></span> = 0.43). These results indicate both elevation and local source emissions may be of increased importance in understanding PM_2.5 concentrations during PCAP events.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"24 ","pages":"Article 100305"},"PeriodicalIF":3.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747546","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":"Quantification of braking particles emission by PIV analysis — Application on railway","authors":"Matthieu Ems ,&nbsp;Damien Méresse ,&nbsp;Jérémy Basley ,&nbsp;Marc Lippert ,&nbsp;David Boussemart ,&nbsp;Laurent Keirsbulck ,&nbsp;Laurent Dubar ,&nbsp;Karine Pajot","doi":"10.1016/j.aeaoa.2024.100306","DOIUrl":"10.1016/j.aeaoa.2024.100306","url":null,"abstract":"<div><div>The work focuses on particle trajectories from a railway braking device. We have developed an experimental method based on Particle Image Velocimetry analysis to evaluate the dispersion of the particulate matter. The motion of a train is simulated with an airflow imposed in a wind tunnel and a reduced-scale braking bench is embedded in the test section. The particle motion can be observed using a laser sheet in the rubbing contact plane. Images are recorded with cameras synchronized with braking bench measurements such as braking pressure, disc and pad temperature, sliding speed. The results demonstrate some correlation with particle counters and the stages of braking events regarding the concentration. They highlight opposing effects of the flow induced by the disc and by the wind tunnel. The particle motions are initially dominated by the disc induced airflow until they leave the boundary layer. The induced airflow becomes dominant.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"24 ","pages":"Article 100306"},"PeriodicalIF":3.8,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706904","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":"Variability of aerosol particle concentrations from tyre and brake wear emissions in an urban area","authors":"Mailin Samland ,&nbsp;Ronny Badeke ,&nbsp;David Grawe ,&nbsp;Volker Matthias","doi":"10.1016/j.aeaoa.2024.100304","DOIUrl":"10.1016/j.aeaoa.2024.100304","url":null,"abstract":"<div><div>Air pollution is a risk to human health, especially in urban areas. While exhaust emissions from road traffic have decreased over the last decades, non-exhaust emissions remain and tend to increase. In this study, tyre and brake wear emissions are quantified applying a bottom-up model for the city of Hamburg in 2018. Their dispersion and contribution to total particulate matter (PM) concentrations are investigated with the urban scale chemistry transport model EPISODE-CityChem. For this purpose, EPISODE-CityChem has been extended to include six new particle components. These are tyre and brake wear in three size classes, <span><math><msub><mrow><mi>PM</mi></mrow><mrow><mn>2</mn><mo>.</mo><mn>5</mn></mrow></msub></math></span>, <span><math><msub><mrow><mi>PM</mi></mrow><mrow><mn>2</mn><mo>.</mo><mn>5</mn><mo>−</mo><mn>10</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>PM</mi></mrow><mrow><mn>10</mn><mo>+</mo></mrow></msub></math></span>, each.</div><div>PM concentrations at traffic stations show a higher monthly mean contribution of tyre and brake wear to the total <span><math><msub><mrow><mi>PM</mi></mrow><mrow><mn>2</mn><mo>.</mo><mn>5</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>PM</mi></mrow><mrow><mn>10</mn></mrow></msub></math></span> than at urban background stations. The sum of airborne tyre and brake wear can locally exceed annual mean concentrations of 10 µg<!--> <!-->m⁻³, with the highest concentrations in the inner city of Hamburg.</div><div>The contribution of tyre and brake wear to the total particle concentrations varies locally and seasonally, which could be a difficulty in adhering to the recommended guideline values for particle concentrations.</div><div>The results of this study can be transferred to other large European cities with high traffic volumes and can help to understand the problem’s scope, as measurements rarely differentiate between particles caused by exhaust vs. non-exhaust emissions.</div></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":"24 ","pages":"Article 100304"},"PeriodicalIF":3.8,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706903","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}