Atmospheric Pollution Research最新文献_第3页

Unraveling the complex drivers of ozone pollution in high-altitude urban areas: Insights from source apportionment and spatiotemporal variations 揭示高海拔城市地区臭氧污染的复杂驱动因素：来自污染源分配和时空变化的见解

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102700

Yiping Zuo , Jiasong Hou , Yanyan Chi , Siyang Liu , Wen Dong

Tropospheric ozone (O₃) pollution in high-altitude urban systems presents unique challenges due to intensified photochemistry, complex topography-driven stagnation, and cross-boundary transport - a critical yet underexplored nexus in atmospheric science. This study pioneers an integrated framework combining 5-year monitoring (2018–2022), high-resolution trajectory modeling (HYSPLIT-PSCF/CWT), and WRF-CAMx with OSAT module simulations to dissect the interplay between local emissions, regional transport, and altitudinal meteorology in driving O₃ extremes. This system consists of an emission source model, the Weather Research and Forecasting (WRF) mesoscale meteorological model, and the Comprehensive Air Quality Model with extensions (CAMx). The OSAT (Ozone Source Apportionment Technology) method is a key extension of the CAMx model, serving as an integrated approach combines sensitivity analysis and process analysis. Contrary to lowland cities where summer dominates O₃ peaks, our results reveal a paradigmatic springtime surge (March–May) linked to pre-monsoon stagnation and valley wind inversions, amplifying precursor accumulation by 40–60 %. Source apportionment uncovers natural sources (45 % annually; 82 % in summer) as the dominant contributor - a striking deviation from industrial/urban narratives - attributed to biogenic VOC emissions enhanced by high-altitude UV radiation. Transboundary transport from southwestern regions contributes 35 % of episodic O₃, demonstrating the vulnerability of mountainous basins to cross-jurisdictional pollution. Crucially, we identify VOC-limited regimes as the linchpin for mitigation, with industrial coatings and architectural paints accounting for 52 % of anthropogenic precursors. This work establishes a mechanistic template for O₃ management in global mountain cities, emphasizing the need for altitude-sensitive policies and transregional governance frameworks.

高海拔城市系统中的对流层臭氧（O3）污染由于加剧的光化学、复杂地形驱动的停滞和跨界运输（大气科学中一个关键但尚未充分探索的联系）而面临独特的挑战。本研究率先建立了一个综合框架，将5年监测（2018-2022年）、高分辨率轨迹建模（HYSPLIT-PSCF/CWT）和WRF-CAMx与OSAT模块模拟相结合，剖析了当地排放、区域运输和高度气象在驱动O3极端事件中的相互作用。该系统由排放源模式、天气研究与预报（WRF）中尺度气象模式和综合空气质量扩展模式（CAMx）组成。臭氧源解析技术（OSAT）方法是CAMx模型的重要扩展，是灵敏度分析和过程分析相结合的综合方法。与夏季主导臭氧峰值的低地城市相反，我们的研究结果显示，典型的春季（3 - 5月）高峰与季风前停滞和山谷风逆温有关，将前兆积累放大了40 - 60%。来源分配揭示了自然来源（每年45%，夏季82%）是主要的贡献者，这与工业/城市叙述的显著偏离，归因于高海拔紫外线辐射增强的生物源性VOC排放。来自西南地区的跨界运输贡献了35%的幕式臭氧，表明山区盆地容易受到跨辖区污染的影响。至关重要的是，我们确定voc限制制度是缓解的关键，工业涂料和建筑涂料占人为前体的52%。这项工作为全球山地城市的臭氧管理建立了一个机制模板，强调需要制定高度敏感的政策和跨区域治理框架。

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引用次数: 0

Advancing data processing for microplastics characterization: Laser direct infrared (LDIR) analysis of atmospheric deposition in Cienfuegos, Cuba 微塑料表征的先进数据处理：激光直接红外（LDIR）分析古巴西恩富戈斯大气沉积

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102715

Yasser Morera-Gómez , Marco Antonio García-Varens , Bárbaro Miguel Pescoso-Torres , Yusmila Helguera-Pedraza , Arianna García-Chamero , Abel Alonso-Morejón , Nathalie Bernard , Carlos M. Alonso-Hernández

This study developed and applied an automated workflow for post-processing laser direct infrared (LDIR) data, enabling efficient microplastics characterization, including particle count, size, shape, chemical composition, mass, and error estimation. The method was used to evaluate atmospheric microplastics in a rural and an urban coastal environment in Cienfuegos, Cuba, providing valuable insights into microplastic loads and addressing gaps in quantification methods. A total of 11 different synthetic polymers, consistently representing less than 6 % of the total collected particles across both sites, were identified. Polyamide, polypropylene, polyurethane, and polyethylene, accounting for over 55 % of the particles in each sample, were the predominant polymers at both sites. Size and shape analysis revealed that most particles were smaller than 100 μm (>75 %), with low variability between the studied sites. Atmospheric deposition rates exhibited significant monthly variability (23–260 microplastics m⁻² day⁻¹), and mass deposition rates suggested that Cienfuegos may experience an annual microplastic discharge of 1.4–4.4 kg km⁻² consistent with findings from other regions of the world. While the study emphasizes the need for further research to refine methodologies, it fills crucial gaps by examining microplastics in typically understudied areas and achieving a more comprehensive and harmonized assessment of microplastics in environmental studies.

本研究开发并应用了激光直接红外（LDIR）数据后处理的自动化工作流程，实现了高效的微塑料表征，包括颗粒计数、大小、形状、化学成分、质量和误差估计。该方法被用于评估古巴西恩富戈斯农村和城市沿海环境中的大气微塑料，为微塑料负荷提供了有价值的见解，并解决了量化方法的空白。总共鉴定了11种不同的合成聚合物，在两个地点收集的颗粒总数中始终占不到6%。聚酰胺、聚丙烯、聚氨酯和聚乙烯占每个样品中55%以上的颗粒，是两个地点的主要聚合物。尺寸和形状分析显示，大多数颗粒小于100 μm (> 75%)，研究位点之间的差异很小。大气沉积速率表现出显著的月变化（23-260微塑料m−2天−1），质量沉积速率表明西恩富戈斯可能经历1.4-4.4 kg km−2的年微塑料排放，这与世界其他地区的发现一致。虽然该研究强调需要进一步研究以完善方法，但它通过在通常研究不足的领域检查微塑料，并在环境研究中对微塑料进行更全面和协调的评估，填补了关键的空白。

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引用次数: 0

Estimating daily surface O3 concentrations in China from 2005 to 2023 based on the STMO3Net model 基于STMO3Net模式的2005 - 2023年中国地表O3日浓度估算

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102704

Qiaolin Zeng , Yaoyu Qi , Meng Fan , Liangfu Chen , Jinhua Tao , Hao Zhu , Sizhu Liu , Yuanyuan Zhu

In recent years, ground-level ozone (O₃) has replaced particulate matter (PM_2.5) as a major air pollution concern. O₃ concentrations rise sharply during periods of high temperature, posing increasing risks to public health. Previous studies have relied heavily on machine learning to estimate ground-level O₃ concentrations, but these approaches inadequately capture spatiotemporal characteristics. Moreover, the lack of ground-level O₃ monitoring data before 2013 in China has hindered long-term trend studies. To address these issues, this study developed a hybrid spatiotemporal framework that used a point-plane approach to estimate the ground-level O₃ concentrations, named STMO3Net. The model integrated a Transformer-based multi-head self-attention to capture long-range temporal dependencies, and a temporal convolutional network was introduced to improve sensitivity of short-term variations. For spatial modelling, STMO3Net incorporated residual blocks and coordinate-based spatial attention to adaptively adjust the importance of each grid cell based on its spatial position. Additionally, a channel attention module was combined with multi-scale asymmetric convolutions using different kernel sizes to capture spatial features at various scales and enhance feature fusion. The R² (RMSE) of 0.92 (12.27

μ g / m^{3}

) was obtained by the sample-based cross-validation. Using Ozone Monitoring Instrument and TROPOspheric Monitoring Instrument (TROPOMI) satellite data, the model estimated daily ground-level O₃ concentrations over China from 2005 to 2023.

近年来，地面臭氧（O3）已取代颗粒物（PM2.5）成为主要的空气污染问题。在高温时期，臭氧浓度急剧上升，对公众健康构成越来越大的风险。以前的研究严重依赖于机器学习来估计地面臭氧浓度，但这些方法不能充分捕捉时空特征。此外，中国缺乏2013年之前的地面O3监测数据，阻碍了长期趋势研究。为了解决这些问题，本研究开发了一个混合时空框架，使用点平面方法来估计地面臭氧浓度，名为STMO3Net。该模型集成了基于transformer的多头自关注来捕获长期时间依赖性，并引入了时间卷积网络来提高短期变化的灵敏度。对于空间建模，STMO3Net结合残差块和基于坐标的空间注意，根据每个网格单元的空间位置自适应调整其重要性。此外，将通道关注模块与不同核大小的多尺度非对称卷积相结合，捕获不同尺度的空间特征，增强特征融合。经样本交叉验证，R2 （RMSE）为0.92 （12.27 μg/m3）。该模式利用臭氧监测仪和对流层监测仪（TROPOMI）卫星数据，估算了2005 - 2023年中国地面臭氧的日浓度。

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引用次数: 0

Modeling the mass transfer coefficients (MTCs) of PCBs, PAHs, OCPs, and PCDD/Fs using a water surface sampler (WSS) 利用水面采样器（WSS）模拟多氯联苯、多环芳烃、OCPs和PCDD/Fs的传质系数（MTCs）

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102718

Abdul Alim Noori, Berke Gülegen, Yücel Tasdemir

In this study, the mass transfer coefficients (MTCs) characterizing the air-water exchange of PCDD/Fs were investigated. Evaporation and dissolved oxygen (DO) experiments were carried out using a water surface sampler (WSS), and the MTCs of semi-volatile organic compounds (SVOCs) were then modeled based on the data obtained from these experiments. As a result of the calculations made using the evaporation flux observed in the WSS, the average air-side individual MTC [k_g _(H2O)] was determined as 1.33 ± 0.58 cm/s k_{g (H2O)} values were correlated against u_10, and a model for the WSS was derived. The water-side individual MTC [(k_w _(O2)] for oxygen was calculated using two methods, flux and absorption. According to the results of the calculations, k_w _(O2) values were determined as 9.35 × 10⁻⁴ ±7.65 × 10⁻¹ cm/s and 1.30 × 10⁻³ ±6.60 × 10⁻¹ cm/s by flux and absorption methods, respectively. The obtained k_{w (O2)} values were also correlated against u₁₀, and k_{w(O2)_flux} and k_{w(O2)_abs} models were constructed for the WSS. Consequently, by applying the findings to the two-film theory, the overall MTC [K_g _(SVOCs)] in the gas phase was calculated as 0.03 ± 0.03 cm/s for PCBs, 0.19 ± 0.18 cm/s for PAHs, 0.11 ± 0.08 cm/s for OCPs, and 0.07 ± 0.01 cm/s for PCDD/Fs. MTC values showed seasonal variation, with higher values observed during cold periods. There was also an oscillation in the MTCs among the species of SVOCs. When the chlorine number and molecular weight increased, the MTCs also increased. The results found by modeling are in line with the measurement results obtained by using the WSS but are somewhat lower.

研究了表征PCDD/Fs空气-水交换特性的传质系数。利用水面采样器（WSS）进行了蒸发和溶解氧（DO）实验，并在此基础上建立了半挥发性有机化合物（SVOCs）的MTCs模型。利用WSS观测到的蒸发通量进行计算，确定了平均空侧单个MTC [kg (H2O)]为1.33±0.58 cm/s kg (H2O)，其值与u10相关，并推导了WSS的模型。用通量和吸收两种方法计算了氧在水侧的单个MTC [(kw (O2)]。根据计算结果，通过通量法和吸收法测定的kw （O2）值分别为9.35 × 10−4±7.65 × 10−1 cm/s和1.30 × 10−3±6.60 × 10−1 cm/s。得到的kw（O2）值也与u10相关，并建立了WSS的kw(O2)_flux和kw(O2)_abs模型。因此，将研究结果应用于双膜理论，可计算出PCBs气相中总MTC [Kg (SVOCs)]为0.03±0.03 cm/s， PAHs为0.19±0.18 cm/s， OCPs为0.11±0.08 cm/s， PCDD/Fs为0.07±0.01 cm/s。MTC值呈现季节变化，在寒冷期较高。SVOCs种间的MTCs也存在振荡。随着氯数和分子量的增加，MTCs也随之增加。通过建模得到的结果与使用WSS得到的测量结果一致，但略低。

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引用次数: 0

Using the AP-42 model to estimate dust emission factors for high traffic roads 利用AP-42模型估算高流量道路扬尘排放因子

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102727

Yifan Ding , Amir Saeidi , Tianyi Wang , Hongpufan Huang , Olivia Halseth , Francesca Hopkins , Akula Venkatram

Road dust emissions, predominantly comprising PM10, are significant contributors to ambient particulate matter (PM) concentrations in urban areas. The emission factor model recommended by the U.S. Environmental Protection Agency (USEPA) in AP-42 is based on data that exclude high-traffic roads such as California freeways. This study addresses this limitation by: (1) developing a mobile platform for measuring PM2.5 and PM10 emission factors on high-traffic roads, and (2) proposing a mechanistic model to overcome the shortcomings of the AP-42 model.

The mobile measurement platform combined PurpleAir particulate-matter sensors, meteorological instruments, and a custom dust sampler to collect real-time data without interrupting traffic. Field campaigns spanned eight California roadways, six freeways and two urban arterials. Observations of PM concentrations, silt loading, micrometeorology, and traffic flow were used both to test the U.S. EPA AP-42 road-dust model on heavily trafficked roads and to develop a physics-based alternative. With site-specific silt loading, the AP-42 equation produced credible PM2.5 and PM10 emission factors. The mechanistic model, which omits silt loading, yielded PM₁₀ emission factors comparable in accuracy to those from AP-42.

Implication

This study provides improved methods to measure and model PM10 and PM2.5 emissions from urban roads. Current AP-42 models are unreliable for high-traffic roads due to their dependence on silt loading values, which require traffic disruptions to measure accurately. The proposed mobile platform eliminates this challenge, and the mechanistic model offers an alternative to the empirical AP-42 approach. These innovations contribute significantly to advancing air quality management in urban areas with heavy vehicular traffic.

道路粉尘排放主要由可吸入颗粒物（PM10）组成，是城市地区环境颗粒物（PM）浓度的重要贡献者。美国环境保护署（USEPA）在AP-42中推荐的排放因子模型是基于不包括加州高速公路等高流量道路的数据。本研究通过以下方法解决了这一问题：(1)开发了一个移动平台来测量高流量道路上的PM2.5和PM10排放因子；(2)提出了一个机制模型来克服AP-42模型的不足。移动测量平台结合了PurpleAir颗粒物传感器、气象仪器和定制粉尘采样器，在不中断交通的情况下收集实时数据。现场活动横跨加州的8条公路，6条高速公路和2条城市主干道。通过对PM浓度、泥沙负荷、微气象学和交通流量的观测，在交通繁忙的道路上测试美国环保署AP-42道路粉尘模型，并开发基于物理的替代方案。在不同场地泥沙荷载下，AP-42方程得到可信的PM2.5和PM10排放因子。该机制模型忽略了泥沙荷载，其PM10排放因子的准确性与AP-42模型相当。本研究为城市道路PM10和PM2.5排放的测量和建模提供了改进的方法。目前的AP-42模型在高流量道路上是不可靠的，因为它们依赖于淤泥加载值，这需要交通中断才能准确测量。提出的移动平台消除了这一挑战，并且机制模型提供了经验AP-42方法的替代方案。这些创新为推进城市交通繁忙地区的空气质量管理做出了重大贡献。

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引用次数: 0

Quantifying the direction and distance characteristics of regional transport contribution to achieve joint emission controls of PM2.5 and O3 in Hefei 量化区域交通贡献的方向和距离特征，实现合肥市PM2.5和O3的联合排放控制

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102731

Kangjia Gong, Lin Huang, Wenxing Fu, Yongliang She, Jianlin Hu

Regional transport has important impacts on fine particulate matter (PM_2.5) and ozone (O₃) pollution. Quantifying the direction and distance characteristics of regional transport contribution is crucial to formulating effective regional joint prevention and control policies. This study utilized the source-oriented WRF/CMAQ chemical transport model to quantify the contributions from various regions, categorized by direction and distance within Hefei and its surrounding areas, to PM_2.5 and O₃ in Hefei. The results indicate that local emissions in Hefei contributed 39 % during the modeled PM_2.5 pollution episode, while other areas in Anhui Province contributed 21 %. For transport distances of 50, 100 and 150 km, contributions were 12.9 %, 8.6 %, and 4.8 %, respectively, with eastern transport in these regions showing a higher impact, and contributions from areas 150 km away comprising 34.3 %. During O₃ pollution events, Hefei's local contribution to non-background O₃ was 62.5 %, while contributions from other areas in Anhui Province were primarily from western Anhui by 7.2 % and other regions by 6.4 %. By directional and distance analysis, northern Hefei contributed 30.5 %, western Anhui 25.2 %, with distances of 50, 100 and 150 km contributing 9.5 %, 5.6 %, and 4.3 %, and transport from 150 km away accounting for 16 %. For PM_2.5, sulfate and nitrate were mainly affected by long-range transport (>150 km), while primary particles and secondary organic aerosols were largely from local emissions (<50 km). For O₃, the formation contributions attributed by NOx were driven by regional transport, whereas the contributuions attributed by volatile organic compounds (VOC) were dominated by local emissions.

区域交通对细颗粒物（PM2.5）和臭氧（O3）污染有重要影响。量化区域交通贡献的方向和距离特征，对于制定有效的区域联防联控政策至关重要。本研究利用面向源的WRF/CMAQ化学输运模型，量化了合肥及周边地区各区域对PM2.5和O3的贡献，并按方向和距离进行了分类。结果表明，在模拟的PM2.5污染事件中，合肥的局部排放贡献了39%，而安徽省其他地区贡献了21%。对于50、100和150 km的运输距离，贡献分别为12.9%、8.6%和4.8%，其中东部运输对这些区域的影响更大，150 km的贡献占34.3%。在O3污染事件中，合肥对非本底O3的贡献为62.5%，而安徽省其他地区对非本底O3的贡献主要来自皖西地区，占7.2%，其他地区占6.4%。从方向和距离分析来看，合肥北部占30.5%，皖西占25.2%，其中50、100和150 km距离占9.5%、5.6%和4.3%，150 km距离占16%。对于PM2.5，硫酸盐和硝酸盐主要受远程输送（>150 km）的影响，而一次颗粒和二次有机气溶胶主要来自局地排放（<50 km）。对于O3， NOx对形成的贡献主要由区域运输驱动，而挥发性有机化合物（VOC）对形成的贡献主要由局部排放驱动。

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引用次数: 0

Impact of residential combustion on black carbon levels in Palapye, Botswana: Field measurements and GEOS-chem simulations 博茨瓦纳Palapye地区住宅燃烧对黑碳水平的影响：现场测量和地球物理系统化学模拟

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102707

Janica N.D. Gordon , Kelsey R. Bilsback , Marc N. Fiddler , Jeffrey R. Pierce , Gizaw Mengistu Tsidu , Solomon Bililign

Over half of the population in Africa still rely on solid fuels such as wood, coal, dung, crop waste, and charcoal for household heating and cooking. Combustion of such fuels leads to high levels of PM_2.5 emissions, where a large fraction of PM_2.5 is composed of black carbon (BC) and organic carbon (OA). Additionally, there is a lack of continuous ground-based monitors in Africa to measure emissions and chemical composition, which is essential for monitoring changes in air quality. To better understand air pollution in Africa, we conducted a five-week field campaign in June and July of 2022 at Botswana International University of Science and Technology (BIUST) located in Palapye, Botswana and ran numerous GEOS-Chem simulations to understand which anthropogenic sources had the potential to impact the field-measured BC. BC field measurements were collected using a micro-aethalometer. Simulations were used to quantify the effect of four anthropogenic sources (energy, industry, residential, and transportation) on ambient BC in Southern Africa during June and July of 2018 and 2022. The average BC concentrations from field measurements at BIUST were 0.34 μg m⁻³. GEOS-Chem, simulation results showed that those residential emissions contributed 52 % and 49 % of the average ambient BC during both months in 2018 and 2022, respectively, at the observation site at BIUST. Compared to the other three combustion sources, residential emissions contributed the largest to the average ambient BC concentrations in this region.

非洲一半以上的人口仍然依赖固体燃料，如木材、煤炭、粪便、农作物废料和木炭来进行家庭取暖和烹饪。这些燃料的燃烧导致PM2.5的高水平排放，其中PM2.5的很大一部分由黑碳（BC）和有机碳（OA）组成。此外，非洲缺乏连续的地面监测仪来测量排放和化学成分，这对监测空气质量的变化至关重要。为了更好地了解非洲的空气污染，我们于2022年6月和7月在位于博茨瓦纳Palapye的博茨瓦纳国际科技大学（BIUST）进行了为期五周的实地调查，并进行了大量的GEOS-Chem模拟，以了解哪些人为来源有可能影响实地测量的BC。BC现场测量使用微血压计收集。模拟用于量化2018年6月和2022年7月期间四个人为来源（能源、工业、住宅和交通）对南部非洲环境BC的影响。BIUST现场测量的BC平均浓度为0.34 μg m−3。GEOS-Chem的模拟结果显示，2018年和2022年两个月，北京科技大学观测点的居民排放分别占平均环境碳排放量的52%和49%。与其他三种燃烧源相比，居民排放对该地区平均环境BC浓度的贡献最大。

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引用次数: 0

Drivers of fine particulate matter improvement and ozone increase in Shandong, China from 2013 to 2017 2013 - 2017年中国山东省细颗粒物改善和臭氧增加的驱动因素

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102724

Na Zhao , Sen Yao

The air quality in China improved during 2013–2017 due to the implementation of the strictest clean air actions in the country's history. However, the driving factors behind the improvement in air quality in Shandong Province remain unclear. To address this challenge, we designed eight sensitivity experiments and conducted 32 simulations using the Weather Research and Forecasting-Comprehensive Air Quality Model with Extensions (WRF-CAMx) to quantify the contributions of emission reductions and meteorological conditions to changes in fine particulate matter (PM_2.5) and ozone (O₃) concentrations. Emissions of most major pollutants decreased substantially, while volatile organic compounds increased by 4.5 % during 2013–2017. Emission reductions and meteorological variations contributed to a 19.6 % and 9.5 % decrease in PM_2.5 concentrations, respectively, with emission control measures proving most effective in winter and meteorological conditions showing contrasting seasonal influences. Sectoral analysis revealed varying contributions to PM_2.5 improvements, with residential sources having the most significant impact, particularly in winter, driven by the expansion of centralized heating coverage and clean energy initiatives. The increase in O₃ concentrations was driven by both emission reductions and meteorological variations, resulting in increases of 17.4 % and 7.3 %, respectively. Emission reductions drove O₃ increases across all seasons, while meteorological conditions exhibited varying seasonal impacts on O₃ concentrations. Spring conditions contributed to an 8.9 % improvement in O₃ concentrations, while other seasons experienced rebounds. Nearly all emission reductions contributed to O₃ increases, with residential and industrial sources showing the most substantial impacts. These founding can provide support for the refined control of PM_2.5 and O₃ pollution.

由于实施了中国历史上最严格的清洁空气行动，2013-2017年中国的空气质量有所改善。然而，山东省空气质量改善背后的驱动因素尚不清楚。为了应对这一挑战，我们设计了8个敏感性实验，并使用天气研究与预报-综合空气质量模型扩展（WRF-CAMx）进行了32次模拟，以量化减排和气象条件对细颗粒物（PM2.5）和臭氧（O3）浓度变化的贡献。2013-2017年，大多数主要污染物排放量大幅下降，挥发性有机物排放量增长4.5%。减排和气象变化对PM2.5浓度的贡献分别为19.6%和9.5%，其中排放控制措施在冬季最为有效，而气象条件的季节性影响则截然不同。行业分析显示，PM2.5的改善有不同的贡献，在集中供暖覆盖范围扩大和清洁能源倡议的推动下，住宅污染源的影响最为显著，尤其是在冬季。O3浓度的增加是由减排和气象变化共同驱动的，分别增加了17.4%和7.3%。排放减少驱动O3在所有季节的增加，而气象条件对O3浓度的影响表现出不同的季节性。春季条件对臭氧浓度的改善贡献了8.9%，而其他季节则出现反弹。几乎所有的减排都导致了臭氧的增加，其中住宅和工业排放的影响最大。这些发现可以为PM2.5和O3污染的精细化控制提供支持。

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引用次数: 0

Chemical composition, source apportionment and formation mechanisms of PM2.5 in urban and background areas of northwestern China 西北城市与背景区PM2.5化学成分、来源解析及形成机制

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102734

Kai Cheng , Yuting Zhong , Xinchun Liu , Xia Li , Maulen Ayitken , Shuting Li , Hongna Chen , Bingbing Leng , Wang Zhang , Haiyang Cai

The urban agglomeration on the northern slope of the Tianshan Mountains is the most severely polluted areas in northwestern China with respect to fine particulate matter (PM_2.5) during winter. Owing to a weak research foundation, the understanding of the physicochemical properties of PM_2.5 during pollution episodes in this region remains limited. Utilizing filter sampling data along with measurements of conventional pollutants and meteorological parameters collected at Urumqi (UR, an urban site) and Akedala (AK, a background site) in January 2024, determined the characteristics of the chemical components, pollution sources, and formation mechanisms of PM_2.5 in both urban and background areas. During the sampling period, the average PM_2.5 concentration at UR was 99.2 ± 16.6 μg m⁻³, which was 5.7 times higher than that at AK. Under extreme stagnant weather conditions, the daily maximum PM_2.5 concentration at UR reached 189 μg m⁻³. Secondary inorganic aerosols (SNA), which include sulfate (SO₄²⁻), nitrate (NO₃⁻), and ammonium (NH₄⁺), were the predominant chemical constituents at both UR and AK, accounting for 66.0 % and 50.4 % of the total PM_2.5 mass, respectively. Source apportionment results demonstrated the significant contribution of secondary sources to PM_2.5 at UR (53.3 %) and AK (62.2 %). Notably, primary emissions from UR coal combustion sources (28.5 %) formed about 19.4 % of SO₄²⁻. Mean sulfur oxidation ratios (SOR) at UR (0.8 ± 0.1) and AK (0.6 ± 0.3) were extremely high under stationary weather. The high liquid water content (LWC) and acidic pH observed at UR indicated that aqueous-phase and heterogeneous reactions were the primary contributors to sulfate formation, whereas at AK, it was predominantly influenced by aqueous-phase reactions. In ammonia-rich environments, gas-phase reactions and heterogeneous hydrolysis of N₂O₅ played an important role at UR nitrate formation, whereas at AK, more reliance was placed on gas-phase processes.

天山北坡城市群是西北地区冬季细颗粒物（PM2.5）污染最严重的地区。由于研究基础薄弱，对该地区污染期间PM2.5的理化性质了解有限。利用2024年1月在乌鲁木齐市（乌鲁木齐）和阿克达达拉（AK）采集的过滤采样数据、常规污染物测量数据和气象参数，确定了城市和背景区PM2.5的化学成分特征、污染源及其形成机制。在采样期间，UR的PM2.5平均浓度为99.2±16.6 μ m−3，是AK的5.7倍。在极端停滞天气条件下，乌鲁木齐PM2.5日最大浓度达到189 μg m−3。次生无机气溶胶（SNA）主要由硫酸盐（SO42−）、硝酸盐（NO3−）和铵态氮（NH4+）组成，分别占PM2.5总质量的66.0%和50.4%。源分配结果表明，二次源对PM2.5的贡献显著，在UR（53.3%）和AK（62.2%）。值得注意的是，来自UR煤燃烧源的一次排放（28.5%）形成了约19.4%的SO42−。静止天气下，平均硫氧化比（SOR）在UR（0.8±0.1）和AK（0.6±0.3）极高。高液态水含量（LWC）和酸性pH值表明，水相和非均相反应是硫酸盐形成的主要因素，而在AK，水相反应主要影响硫酸盐的形成。在富氨环境中，气相反应和N2O5的非均相水解在UR硝酸盐的形成中起重要作用，而在AK中，气相反应更依赖于气相过程。

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引用次数: 0

Investigation of the settling dynamics and behaviour of PM2.5 and PM1.0 present in coal dusts in controlled environmental conditions 受控环境条件下煤尘中PM2.5和PM1.0沉降动态及行为研究

IF 3.5 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Pollution Research

Pub Date : 2026-01-01 DOI: 10.1016/j.apr.2025.102711

Chinmoy Mandal, Basanta Kumar Prusty, Khanindra Pathak, Aditya Kumar Patra

Fine particulate matter (PM_2.5 and PM_1.0) is a major pollutant in coal processing industries. These particles exhibit Brownian motion but do not remain suspended indefinitely, settling over time. This study investigates the deposition characteristics of PM_2.5 and PM_1.0 in a confined setup, analysing how concentration diminishes under varying initial conditions. The experimentation involved introducing 250 mg, 500 mg, 750 mg and 1 g coal dust into a chamber of size (100 cm × 30 cm × 40 cm), where calibrated PMS7003 sensors recorded the concentration level of PM₁ and PM_2.5 at four different levels, viz. at ground levels, 30 cm, 60 cm and 90 cm height.

The analysis showed that the concentration depletion rate due to deposition is governed by diffusion deposition and coagulation. A universal equation has been developed for varying initial concentration and lapsed time. Coagulation is mostly observed in high concentration. Deposition rate constant reduce with increase in initial concentration. At low initial concentration 50 percent concentration reduction time is 15–16 min for both PM₁ and PM_2.5 which increases at higher concentration. Same pattern is observed for 90 percent concentration reduction time. Time to reach the permissible limit as per Indian National Ambient Air Quality Standards increases gradually from 35 min to 2.5 h.

细颗粒物（PM2.5和PM1.0）是煤炭加工行业的主要污染物。这些粒子表现出布朗运动，但不会无限期地悬浮，而是随时间沉淀。本研究在密闭环境中研究了PM2.5和PM1.0的沉积特征，分析了不同初始条件下浓度的衰减规律。实验将250毫克、500毫克、750毫克和1克煤尘引入一个大小为100厘米× 30厘米× 40厘米的室内，校准后的PMS7003传感器记录了地面、30厘米、60厘米和90厘米高度四个不同水平的PM1和PM2.5浓度水平。分析表明，沉积引起的浓度损耗速率受扩散沉积和混凝控制。对于不同的初始浓度和时间，已经建立了一个通用的方程。凝血多见于高浓度。沉积速率常数随初始浓度的增加而减小。在初始浓度较低时，PM1和PM2.5的50%浓度降低时间为15-16 min，浓度越高，浓度降低时间越长。对于90%的浓度降低时间，观察到相同的模式。根据印度国家环境空气质量标准，达到允许限值的时间从35分钟逐渐增加到2.5小时。

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引用次数: 0