Atmospheric Pollution Research最新文献_第4页

Advanced NOx emission modeling for diesel trucks: Incorporating exhaust temperature and load dynamics 先进的氮氧化物排放建模柴油卡车：纳入排气温度和负载动态

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.2025.102703

Xin Wang , Jianchang Huang , Xue Lei , Xianfei Yue , Leqi Zhang , Shubin Li , Huanqin Yu , Shenzhen Ding

Heavy-duty diesel trucks (HDDTs), although a small portion of the total vehicle population in China, are a significant source of air pollution. The selective catalytic reduction (SCR) systems employed to reduce NOx in these trucks depend largely on exhaust temperature, which varies with vehicle load and operating conditions. However, most existing emission models do not consider these dynamic factors, resulting in inaccurate NOx emission predictions under different load conditions. This study proposes a novel NOx emission modeling framework that integrates exhaust temperature behavior and real-time load dynamics into the estimation process. The model couples a NOx conversion rate module with a physically grounded exhaust temperature model, both parameterized by vehicle operating power. By integrating a NOx conversion rate model with an exhaust temperature model, this research offered a more accurate framework for estimating NOx emissions across various load conditions and speeds. Quantitatively, the model reduced NOx emission errors compared to traditional methods by 5.4 % for no-load, 16.6 % for half-load, and 14.8 % for full-load conditions. The study also investigated NOx emission characteristics under different load conditions, identifying key intersections and inverse correlations in emission factors at different speeds. These findings highlight the model's enhanced predictive ability under complex, real-world driving conditions. Overall, this study enhanced the accuracy of emission estimates and supported the development of more effective environmental regulatory strategies.

重型柴油卡车（HDDTs）虽然只占中国车辆总数的一小部分，但却是空气污染的重要来源。这些卡车采用选择性催化还原（SCR）系统来减少氮氧化物，这在很大程度上取决于排气温度，而排气温度随车辆负载和操作条件的变化而变化。然而，现有的排放模型大多没有考虑这些动态因素，导致不同负荷条件下的NOx排放预测不准确。本研究提出了一种新的氮氧化物排放建模框架，该框架将排气温度行为和实时负载动态集成到估计过程中。该模型将氮氧化物转化率模块与物理接地排气温度模型耦合在一起，两者都由车辆运行功率参数化。通过将NOx转化率模型与排气温度模型相结合，本研究为估算不同负载条件和速度下的NOx排放量提供了更准确的框架。从数量上看，与传统方法相比，该模型在空载、半载和满载情况下分别将NOx排放误差降低了5.4%、16.6%和14.8%。研究还考察了不同负荷工况下的NOx排放特征，确定了不同车速下的关键交叉口及排放因子的负相关关系。这些发现凸显了该模型在复杂的真实驾驶条件下的预测能力。总的来说，这项研究提高了排放估计的准确性，并支持制定更有效的环境监管战略。

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引用次数: 0

Spatial heterogeneity in precipitation physico-chemical characteristics: From elemental solubility and organics volatility to absorbance 降水物理化学特征的空间异质性：从元素溶解度和有机物挥发性到吸光度

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.2025.102708

Bharrathi Angammal Saravanan, Abhishek Chakraborty

The chemical characteristics of rainwater samples were investigated at three locations (Hostel, ESED building and YP gate) inside the Indian Institute of Technology Bombay campus. Rainwater pH, conductivity, optical characteristics, organic carbon, ions, and metals were determined. The average pH of the rainwater was greater than six at all three locations. The average sum of the measured ions in the Hostel, YP Gate and ESED Building was 1334, 1236, and 1045 μeq/l, respectively, indicating the presence of substantial atmospheric pollution. Na⁺ and Cl⁻ were the main ions in the Hostel and ESED building, whereas NO₃⁻ and Mg²⁺ dominated the YP gate location, accounting for 47 %, 45 % and 43 % of the total ions, respectively. The optical mass absorption cross-section (MAC) of rainwater samples was significantly (by 75–95 %) altered (reduced) after filtration, indicating a dominant role of insoluble organics in light absorption. Absorption Ångström exponent (AAE) of light-absorbing species was highest at the YP Gate location. Water soluble organics (WSOC) dominate (60–80 %) the overall rainwater organics (OC). Least volatile organics (OC3) completely dominate (55–65 %) the WSOC fractions, while more volatile OC fractions (OC1) dominate (30–55 %) water-insoluble OC (WIOC). Different metallic elements, including toxic metals like As, Cr, Pb and Cd, were present in appreciable quantities in the rainwater samples. The solubility of various elements was found to vary substantially with sampling location, indicating the presence of different forms/compounds of elements. Enrichment factor (EF) values of several elements present in rainwater samples were very high, indicating the influence of anthropogenic activities.

在印度理工学院孟买校区内的三个地点（宿舍、ESED大楼和YP大门）调查了雨水样本的化学特性。测定了雨水pH值、电导率、光学特性、有机碳、离子和金属。在所有三个地点，雨水的平均pH值都大于6。宿舍楼、YP门和ESED楼的实测离子平均值分别为1334、1236和1045 μeq/l，表明存在较大的大气污染。在宿舍和ESED建筑中，Na+和Cl−是主要离子，而NO3−和Mg2+在YP门位置占主导地位，分别占总离子的47%、45%和43%。过滤后的雨水样品的光学质量吸收截面（MAC）发生了显著（75 ~ 95%）的改变（降低），表明不溶性有机物在光吸收中起主导作用。吸光物种的吸收Ångström指数（AAE）在YP Gate位置最高。水溶性有机物（WSOC）在整个雨水有机物（OC）中占主导地位（60 - 80%）。最低挥发性有机物（OC3）在WSOC组分中占主导地位（55 ~ 65%），而挥发性有机物（OC1）在水不溶性有机物（WIOC）中占主导地位（30 ~ 55%）。不同的金属元素，包括有毒金属如砷、铬、铅和镉，在雨水样品中存在相当数量。发现各种元素的溶解度随采样位置的不同而有很大变化，表明存在不同形式/化合物的元素。雨水样品中存在的几种元素的富集因子（EF）值非常高，表明人类活动的影响。

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引用次数: 0

Air quality affected by biomass burning at the Paraná River Delta on rural and industrial coastal areas of greater Rosario, Argentina 阿根廷大罗萨里奥农村和工业沿海地区帕拉纳<e:1>河三角洲生物质燃烧对空气质量的影响

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.2025.102712

M.V. Binet , G.A. Piñol , M.F. Valle Seijo , M.I. Micheletti , R.D. Piacentini

Biomass combustion releases various gaseous pollutants and aerosol particles, impacting human health and climate. This study evaluates the effects of biomass burning in the Paraná River Delta on air quality in coastal areas of Greater Rosario, Argentina, focusing on the industrial site of San Lorenzo (SL) and the rural site of Fighiera (FI), from September 6 to 17, 2022. The research examines the transport of pollutants, specifically NO₂, CO, and (total and Black Carbon) aerosols, and their correlations. During this period, the Tropospheric Vertical Column Density (VCDtrop) for NO₂ peaked at over 1.40 × 10¹⁶ molecules/cm² in Fighiera on September 16, 2022, while CO reached 3.29 × 10¹⁸ molecules/cm² in San Lorenzo on September 13, 2022. Aerosol optical depth (AOD) exceeded 0.5 at both sites on September 13, 2022, linked to air masses from the fire-affected region. Additionally, the Fire Radiative Power (FRP) of the fires reached approximately 10 GW on September 13, 2022. A comparison with non-fire periods revealed that Fighiera, typically showing good air quality with lower pollutant levels than San Lorenzo, experienced a rise in pollutant concentrations during the biomass burning events, highlighting the significant impact of fire on local air quality.

生物质燃烧释放各种气体污染物和气溶胶颗粒，影响人类健康和气候。本研究于2022年9月6日至17日评估了阿根廷大罗萨里奥沿海地区帕拉纳河三角洲生物质燃烧对空气质量的影响，重点是圣洛伦佐（SL）的工业基地和菲吉埃拉（FI）的农村地区。该研究考察了污染物的运输，特别是二氧化氮、一氧化碳和（总碳和黑碳）气溶胶，以及它们之间的相关性。在此期间，fifiera地区NO2的对流层垂直柱密度（VCDtrop）在2022年9月16日达到峰值，超过1.40 × 1016分子/cm2， San Lorenzo地区CO在2022年9月13日达到3.29 × 1018分子/cm2。2022年9月13日，这两个地点的气溶胶光学深度（AOD）都超过了0.5，这与来自火灾影响地区的气团有关。此外，2022年9月13日，火灾的火灾辐射功率（FRP）达到约10吉瓦。与非火灾时期的比较显示，通常表现出良好的空气质量，污染物水平低于圣洛伦佐，但在生物质燃烧事件期间，污染物浓度上升，突出了火灾对当地空气质量的重大影响。

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引用次数: 0

Significant contribution of primary brown carbon to the light absorption at Delhi, India: An implication for incomplete oxidation 初级棕色碳对印度德里光吸收的重要贡献：不完全氧化的含义

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.2025.102722

Atar Singh Pipal , Parminder Kaur , Atul Kumar Srivastava , Yu-Hsiang Cheng , Deewan Singh Bisht , Vivek Singh , Yi-Wen Chen , Kuan-Ting Liu

Primary brown carbon (pBrC), constitutes a significant portion of BrC light absorption coefficient, has been examined at an urban megacity, Delhi using the ground-based Aethalometer measurements. The light absorption of pBrC was significantly contributed (83 - 86 %) to BrC absorption at lower wavelengths (370–470 nm) than the secondary brown carbon (sBrC: ∼17 %). This indicates that the pBrC play a significant role to solar radiation absorptions by ∼25 % more as compared to sBrC. The diurnal nature of BrC and its fractions (pBrC & sBrC) showed a bimodal pattern, with peaks occurring around 08:00–10:00 h and, more prominently in the 20:00–23:00 h. Diurnal pattern of pBrC over Delhi identified the abundant emission sources for spectral light absorption. The mean Absorption Angestrom Exponent (AAE) was 1.27 ± 0.11 (0.80–1.60) indicates the dominancy of primary combustion sources. Further the ignition of fossil fuels (FF) is found the ample sources of BrC (AAE: 1.27 ± 0.11) attributed to ∼80 % contribution in Delhi. A very strong significant correlation between AAE_470/950 and AAE_370/950 was observed (R²: 0.95) as a function of FF contribution and B_abs (at 880 nm). The concentration-weighted trajectory (CWT) analysis suggests that local and regional sources are dominated in Delhi, significantly contribute (∼70 %) to the total absorption of aerosols reaching Delhi. Further, the pBrC is directly emitted from the predominant local emissions (i.e., fossil fuels and biomass burning). Whereas the sBrC shows a dispersed pattern with lower values, generally forms through atmospheric chemical reactions and aging processes during transport and influenced by local and regional atmospheric conditions.

主要棕色碳（pBrC），构成BrC光吸收系数的重要部分，已经检查了一个城市的特大城市，德里使用地面大气浓度计测量。在较低波长（370 ~ 470 nm）， pBrC的光吸收比仲棕色碳（sBrC: 17%）显著贡献（83 ~ 86%）BrC吸收。这表明，与sBrC相比，pBrC对太阳辐射吸收的作用要大~ 25%。BrC及其组分（pBrC & sBrC）的日特征表现为双峰型，峰值出现在08:00-10:00左右，在20:00-23:00时段更为显著。德里地区pBrC的日特征表明了丰富的光谱光吸收发射源。平均吸收角指数（AAE）为1.27±0.11(0.80 ~ 1.60)，表明一次燃烧源占主导地位。此外，化石燃料（FF）的点火被发现是BrC的充足来源（AAE: 1.27±0.11），在德里贡献了约80%。AAE470/950和AAE370/950之间存在非常强的显著相关（R2: 0.95），作为FF贡献和Babs （880 nm）的函数。浓度加权轨迹（CWT）分析表明，本地和区域源在德里占主导地位，显著贡献（~ 70%）到达德里的气溶胶的总吸收。此外，pBrC直接来自主要的当地排放（即化石燃料和生物质燃烧）。而sBrC则呈分散分布模式，其值较低，一般是在输送过程中通过大气化学反应和老化过程形成，受局地和区域大气条件的影响。

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引用次数: 0

Air pollution levels in American Indian communities in the Great Plains and Southwest: The Strong Heart Study 美国大平原和西南地区印第安人社区的空气污染水平：强心脏研究

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

Atmospheric Pollution Research

Pub Date : 2025-12-11 DOI: 10.1016/j.apr.2025.102860

Jada L. Brooks , Anne Weaver , Baiming Zou , Maggie Li , Jessica A. Reese , Cavin K. Ward-Caviness , Joseph Yracheta , Susan B. Racette , Kimberly Malloy , Ying Zhang , Nora Franceschini , Giselle M. Corbie , Marianthi-Anna Kioumourtzoglou , Gail Currin Fallon , Ana Navas-Acien

Differences in environmental exposures—particularly to ambient air pollution—have been consistently documented across communities in the United States (U.S.). However, relatively few studies on air pollution have focused on American Indians. In this paper, we combine demographic data from Phase IV (2001–2003) and Phase V (2006–2009) of the Strong Heart Study—the largest ongoing longitudinal epidemiologic cohort study of cardiovascular disease in American Indians—and 1 km² modeled PM_2.5 data in the Northern Plains, Southern Plains, and Southwestern United States. We analyzed data at the U.S. ZIP code level to estimate 30-day and annual residential exposures of participants to PM_2.5 and assess for regional, temporal, and seasonal variations in PM_2.5 exposure. We found significantly higher mean 30-day and annual PM_2.5 concentrations among participants in the Southwest and Southern Plains (>7.4 μg/m³ and >7.6 μg/m³, respectively) than in the Northern Plains (<6.6 μg/m³ and <6.2 μg/m³, respectively). We observed heterogeneity in participants' mean 30-day and annual PM_2.5 exposure within and across regions. Furthermore, seasonal differences in ambient PM_2.5 concentrations among participants varied by region; in the Northern Plains, we generally observed higher mean 30-day PM_2.5 exposure levels in the summertime and lower levels in the wintertime, whereas levels remained relatively constant in the Southern Plains and Southwest. These findings offer essential baseline data to advance accurate and equitable exposure assessment across tribal communities in the Northern Plains, Southern Plains, and Southwest regions.

环境暴露的差异，特别是对环境空气污染的差异，在美国的各个社区都有一致的记录。然而，针对美国印第安人的空气污染研究相对较少。在本文中，我们结合了美国印第安人心血管疾病最大的纵向流行病学队列研究——强心脏研究第四阶段（2001-2003年）和第五阶段（2006-2009年）的人口统计数据，以及美国北部平原、南部平原和西南部1平方公里PM2.5模型数据。我们分析了美国邮政编码水平的数据，以估计参与者对PM2.5的30天和年度居住暴露，并评估PM2.5暴露的区域、时间和季节变化。我们发现西南和南部平原参与者的平均30天和年PM2.5浓度（分别为>；7.4 μg/m3和>；7.6 μg/m3）显著高于北部平原参与者（分别为<；6.6 μg/m3和<；6.2 μg/m3）。我们观察到参与者在区域内和跨区域的平均30天和年PM2.5暴露量的异质性。此外，参与者环境PM2.5浓度的季节性差异因地区而异；在北部平原，我们通常观察到夏季较高的平均30天PM2.5暴露水平，冬季较低，而南部平原和西南部的水平保持相对稳定。这些发现为促进北部平原、南部平原和西南地区部落社区的准确和公平的暴露评估提供了基本的基线数据。

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引用次数: 0

Current major sources of black carbon aerosols over Delhi: Implications to health risks 目前德里上空黑碳气溶胶的主要来源：对健康风险的影响

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

Atmospheric Pollution Research

Pub Date : 2025-12-01 DOI: 10.1016/j.apr.2025.102697

Vaneet Kumar , Atinderpal Singh , Swati Joshi , Shantanu Kumar Pani , Karamjit Singh , Neeraj Rastogi

This study provides vital insights into the major sources and health implications of black carbon (BC) in one of India's most populous cities. The ratio of fossil fuel (ff) derived BC to total BC ranged from 0.49 to 0.82 (0.66 ± 0.07) throughout the study, indicating that fossil fuel combustion is a primary source of BC over Delhi. Further, we utilized BC concentration as a proxy for evaluating health risks related to passively smoked cigarettes (PSC) across four major health outcomes: low birth weight (LBW), percentage lung function decrement (PLFD), cardiovascular mortality (CM), and lung cancer (LC). This method treated BC health risks as equivalent to the health risks attributed to exposure to environmental tobacco smoke. The PSCs from BC_ff were consistently greater than those from biomass burning-derived BC, underscoring the substantial impact of fossil fuel-related BC on health outcomes in the study area, which signals an urgent need for stricter control of fossil fuel emissions. These findings emphasize the significant burden posed by lung function impairment, the most sensitive respiratory effect, suggesting that the vulnerable groups, particularly children and the elderly, may face a greater risk. A sensitivity analysis was conducted to quantify the health benefits resulting from reduced BC mass concentration. The findings indicated that PLFD exhibited the most sensitivity, averaging a reduction of 3.51 PSC per 0.5 μg m⁻³ BC, followed by LBW (1.58), CM (1.53), and LC (0.72). This research offers a meaningful contribution to regional and global efforts in air pollution mitigation and public health protection.

这项研究为印度人口最多的城市之一的黑碳（BC）的主要来源和健康影响提供了重要的见解。在整个研究过程中，化石燃料（ff）衍生的BC与总BC的比例在0.49至0.82（0.66±0.07）之间，表明化石燃料燃烧是德里上空BC的主要来源。此外，我们利用BC浓度作为评估与被动吸烟（PSC）相关的健康风险的代理，包括四种主要健康结局：低出生体重（LBW）、肺功能下降百分比（PLFD）、心血管死亡率（CM）和肺癌（LC）。该方法将不列颠哥伦比亚省的健康风险等同于暴露于环境烟草烟雾造成的健康风险。生物燃料燃烧产生的多氯甲烷含量始终高于生物质燃烧产生的多氯甲烷含量，这突显了化石燃料相关的多氯甲烷对研究区域健康结果的重大影响，这表明迫切需要更严格地控制化石燃料排放。这些发现强调了肺功能损害（最敏感的呼吸效应）带来的重大负担，表明弱势群体，特别是儿童和老年人，可能面临更大的风险。对降低BC质量浓度所带来的健康益处进行了敏感性分析。结果表明，PLFD表现出最高的敏感性，平均每0.5 μ m−3 BC降低3.51 PSC，其次是LBW (1.58)， CM（1.53）和LC（0.72）。这项研究为区域和全球在减少空气污染和保护公众健康方面的努力作出了有意义的贡献。

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引用次数: 0

Future projections of dust storm dynamics and sources in the Middle East: Insights from CMIP6 models 中东地区沙尘暴动力和来源的未来预测：来自CMIP6模式的见解

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

Atmospheric Pollution Research

Pub Date : 2025-12-01 DOI: 10.1016/j.apr.2025.102775

Abbas Ranjbar Saadat Abadi , Nasim Hossein Hamzeh , Dimitris G. Kaskaoutis , Bowen Xu , Li Li , Zahra Ghassabi

Sand/Dust storms are significant natural hazards in the Middle East region. This study investigates variations and trends of meteorological parameters and surface dust concentrations through CMIP6 models, focusing on 14 main dust sources affecting the Middle East, providing future predictions until the end of the 21st century. For this purpose, the outputs of three CMIP6 models — GFDL-ESM, MRI-ESM2-0 and ACCESS-CM2 — were analyzed over the period 2015–2100. Additionally, surface dust concentration was studied in two sub-periods: 2024–2060 and 2061–2100, under three scenarios, optimistic (SSP126), intermediate (SSP245) and pessimistic (SSP585). The 2m-temperature from ERA5 data displayed the highest positive trend with 0.1 °C per year during the 40-year period (1983–2022), while an increasing trend in wind speed was also noted across the study region at 0.006 m/s per year. Furthermore, decreasing trends were observed in Volumetric Soil Water Layer (0–7 cm) from ERA5 data at a rate of −0.0017 in eastern Iran, indicating less soil moisture. The spatial distribution of changes in dust concentration during 2024–2060 indicates that all climatic scenarios predict activation of new dust sources, especially in Oman and Yemen. Moreover, all scenarios agree that the expansion of dust source areas will accelerate in the 2061–2100 period compared to 2024–2060. The ensemble of all models indicates a positive trend in surface dust concentration (0.05 μg m⁻³ per year), suggesting an increase in dust activity over the Middle East. The mean monthly values of temperature, relative humidity, wind speed and precipitation, as projected from nine models across the fourteen dust-source areas and in the entire Middle East from 2015 to 2100, revealed great consistency and low discrepancies between the model outputs. However, in all dust sources, higher discrepancies in precipitation between the models occurred in the cold period and in temperature and surface wind speed during the warm period.

沙尘暴是中东地区的重大自然灾害。本研究利用CMIP6模式研究了影响中东地区的14个主要沙尘源的气象参数和地面沙尘浓度的变化和趋势，提供了到21世纪末的未来预测。为此，我们分析了2015-2100年期间三个CMIP6模型（GFDL-ESM、MRI-ESM2-0和ACCESS-CM2）的输出。在乐观（SSP126）、中等（SSP245）和悲观（SSP585） 3种情景下，研究了2024 ~ 2060和2061 ~ 2100两个亚期的地表粉尘浓度。ERA5数据的2m温度在40 a期间（1983-2022）表现出最高的正趋势（0.1°C /年），而风速也在研究区域呈增加趋势（0.006 m/s /年）。此外，ERA5数据显示，伊朗东部土壤体积水层（0-7 cm）呈下降趋势，速率为- 0.0017，表明土壤水分减少。2024-2060年沙尘浓度变化的空间分布表明，所有气候情景都预示着新的沙尘源的激活，特别是在阿曼和也门。与2024-2060年相比，2061-2100年期间沙源面积的扩大将加速。所有模式的综合结果表明，中东地区地面沙尘浓度呈上升趋势（0.05 μ m−3 /年），表明沙尘活动有所增加。2015 - 2100年9个模式对14个沙尘源区和整个中东地区的月平均温度、相对湿度、风速和降水的预测结果显示，模式输出结果一致性好，差异小。然而，在所有沙源中，模式之间的降水差异在寒冷期较大，而在温暖期温度和地面风速差异较大。

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引用次数: 0

In vitro toxicity of indoor and outdoor PM10 from a university cafeteria 某高校食堂室内和室外PM10的体外毒性研究

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

Atmospheric Pollution Research

Pub Date : 2025-12-01 DOI: 10.1016/j.apr.2025.102661

Daniela Figueiredo , Estela D. Vicente , Cátia Gonçalves , Isabel Lopes , Célia A. Alves , Helena Oliveira

University cafeterias are popular spaces where students and staff can have quick meals and snacks, socialise and relax. Despite their frequent use, the health impacts of airborne particles in these environments remain unexplored. This study aimed to evaluate the mutagenicity and the potential toxicological effects of PM₁₀ in a university cafeteria using human alveolar epithelial cells (A549). PM₁₀ samples were collected both indoors, during periods of activity and when unoccupied (background air), and outdoors. The MTT assay was used to assess the metabolic activity of A549 cells following PM₁₀ exposure, while flow cytometry was used to evaluate the intracellular reactive oxygen species (ROS) levels and disruptions in cell cycle dynamics. Additionally, the Ames test was performed to determine the mutagenic activity of PM₁₀-bound polycyclic aromatic hydrocarbon (PAH) extracts using the Salmonella typhimurium TA98 with and without metabolic activation. The findings revealed a significant decrease in A549 metabolic activity, particularly with PM₁₀ extracts collected indoors during occupancy. Elevated ROS levels and cell cycle arrest in the G0/G1 phase were observed for these indoor samples. Moreover, the concentration of specific organic compounds detected in the PM₁₀ extracts were significantly correlated with the observed biological effects. None of the PAH extracts tested showed mutagenic effects, both with and without metabolic activation. These findings suggest that PM₁₀ exposure in cafeterias, particularly during occupancy, may cause oxidative stress and disrupt cell cycle dynamics, highlighting potential health risks. While no mutagenic effects were detected, further research is needed to explore long-term impacts and develop strategies to enhance indoor air quality in these environments.

大学食堂是学生和员工享用快餐和小吃、社交和放松的热门场所。尽管它们经常被使用，但这些环境中空气传播颗粒对健康的影响仍未得到探索。本研究旨在利用人肺泡上皮细胞（A549）评估大学食堂中PM10的致突变性和潜在毒理学效应。PM10样本分别在室内（活动期间和无人居住时）和室外采集。MTT法用于评估PM10暴露后A549细胞的代谢活性，而流式细胞术用于评估细胞内活性氧（ROS）水平和细胞周期动力学的破坏。此外，利用鼠伤寒沙门氏菌TA98进行了Ames试验，以确定有和没有代谢激活的pm10结合的多环芳烃（PAH）提取物的致突变活性。研究结果显示，A549的代谢活性显著下降，特别是在室内居住期间收集的PM10提取物。在这些室内样品中观察到ROS水平升高和细胞周期阻滞在G0/G1期。此外，PM10提取物中检测到的特定有机化合物浓度与观察到的生物效应显著相关。测试的多环芳烃提取物没有显示出诱变作用，无论是否有代谢激活。这些发现表明，在自助餐厅接触PM10，特别是在用餐期间，可能会引起氧化应激并破坏细胞周期动力学，突出潜在的健康风险。虽然没有检测到诱变效应，但需要进一步研究以探索长期影响并制定策略以提高这些环境中的室内空气质量。

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引用次数: 0

High-resolution city-scale cooking emission inventory based on internet big data 基于互联网大数据的高分辨率城市烹饪排放清查

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

Atmospheric Pollution Research

Pub Date : 2025-12-01 DOI: 10.1016/j.apr.2025.102657

Min He , Hao Yang , Zhen Yang , Yuan Li , Qichao Long , Liangzhen Jian , Yuming He , Jie Xiao

A high-resolution cooking emission inventory in 2023 was developed for the city of Chengdu, China, utilizing multisource internet big data and cuisine-specific emission factors related to the number of diners and edible oil consumption. A total of 105,005 commercial, 19,817 residential, and 7604 canteen cooking point sources were identified. The activity data for each cooking point source were estimated via a linear regression model developed in this study or by leveraging relevant parameters from internet big datasets. This methodology facilitates the development of highly spatially resolved cooking emission inventories. The estimated emissions from cooking were 916–949 tons of fine particulate matter (PM_2.5), 2455–3886 tons of volatile organic compounds (VOCs), 1342–2219 tons of intermediate-volatile organic compounds (IVOCs), and 827–2154 tons of semivolatile organic compounds (SVOCs). Commercial cooking emerged as the dominant contributor, accounting for 70.3–72.3 % of the total PM_2.5 emissions, 71.0–78.8 % of the total VOC emissions, 84.0–88.9 % of the total IVOC emissions, and 83.3–92.6 % of the total SVOC emissions. Major contributors within the commercial cooking sector included Sichuan–Hunan cuisine, barbecue, hot pot and home-style cooking. Uncertainties in the cooking emission estimates were quantified via Monte Carlo simulation, revealing that the uncertainties associated with edible oil consumption were greater than those associated with the number of diners. The high-resolution emission map demonstrated that cooking emissions in Chengdu were primarily concentrated in the developed areas of the city's subdivisions. Besides population size and economic activity, transportation accessibility has emerged as a key factor influencing the spatial distribution of cooking-related point sources and emissions.

利用多源互联网大数据和与食客数量和食用油消费量相关的特定烹饪排放因子，为中国成都市开发了2023年高分辨率烹饪排放清单。共确定了105,005个商业、19,817个住宅和7604个食堂烹饪点源。每个烹饪点源的活动数据通过本研究开发的线性回归模型或利用互联网大数据集的相关参数进行估计。这种方法有助于开发高度空间分辨的烹饪排放清单。烹饪产生的细颗粒物（PM2.5）排放量为916-949吨，挥发性有机化合物（VOCs）排放量为2455-3886吨，中间挥发性有机化合物（IVOCs）排放量为1342-2219吨，半挥发性有机化合物（SVOCs）排放量为827-2154吨。商业烹饪成为主要贡献者，占PM2.5总排放量的70.3 - 72.3%，占VOC总排放量的71.0 - 78.8%，占IVOC总排放量的84.0 - 88.9%，占SVOC总排放量的83.3 - 92.6%。商业烹饪领域的主要贡献者包括川湘菜、烧烤、火锅和家常菜。通过蒙特卡罗模拟量化了烹饪排放估计中的不确定性，揭示了与食用油消耗相关的不确定性大于与用餐者数量相关的不确定性。高分辨率排放图显示，成都烹饪排放主要集中在城市细分的发达地区。除人口规模和经济活动外，交通可达性已成为影响烹饪相关点源和排放空间分布的关键因素。

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引用次数: 0

SHAP explainable PSO-CNN-BiLSTM for 6-hour prediction analysis of urban PM2.5 and O3 concentrations 基于SHAP可解释的PSO-CNN-BiLSTM的城市PM2.5和O3浓度6小时预测分析

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

Atmospheric Pollution Research

Pub Date : 2025-12-01 DOI: 10.1016/j.apr.2025.102705

Kun Lei , Mingya Wang , Mingshi Wang , QingWei Liu , Fan Zhang , MingFei Xing , Wei Wu , Fengcheng Jiang , Xiaoming Guo , Qiao Han , Fayang Guo , Huiyun Pan , Kewu Liu , Jing Wang , Zhengbo Yu

PM_2.5 and O₃ continue to be the dominant air pollutants in China, exhibiting intricate spatiotemporal variability influenced by a combination of meteorological conditions and emission sources. Accurate and long-term forecasting is crucial for enabling timely emergency responses, thereby enhancing the strategic planning and operational effectiveness of air quality management. In this study, a hybrid deep learning framework integrating CNN and BiLSTM networks is proposed. The model is optimized using PSO and further enhanced through SHAP to improve interpretability. The model is applied to predict hourly concentrations of PM_2.5 and O₃ based on aggregated data from multiple air quality monitoring stations in Jiaozuo's urban area, with the aim of improving forecasting accuracy and model transparency. Experimental results indicate that PSO significantly improves predictive performance across all forecast horizons while reducing computation time by more than 50 %. The optimized CNN-BiLSTM model consistently outperforms baseline models including LSTM, CNN, and XGBoost in forecasting O₃ concentrations, particularly under extended lead times. The model demonstrates strong short-term predictive capabilities (O₃: RMSE = 17.43–17.89 μg/m³, R² = 0.88; PM_2.5: RMSE = 13.94–16.73 μg/m³, R² = 0.84–0.89), and maintains acceptable accuracy for 6-h ahead forecasts (O₃: RMSE = 19.93 μg/m³, R² = 0.85; PM_2.5: RMSE = 23.76 μg/m³, R² = 0.67). SHAP-based interpretability analysis reveals that T, NO₂, and UVI are the primary contributors to O₃ prediction, while PM₁₀, T, and RH are the key drivers for PM_2.5. These findings highlight the effectiveness of the PSO-CNN-BiLSTM model in advancing air quality forecasting and offer valuable insights for pollution mitigation strategies and policy development.

PM2.5和O3仍然是中国主要的大气污染物，受气象条件和排放源的综合影响，呈现出复杂的时空变异性。准确和长期的预报对于能够及时作出应急反应，从而加强空气质量管理的战略规划和业务效率至关重要。本文提出了一种融合CNN和BiLSTM网络的混合深度学习框架。利用粒子群算法对模型进行优化，并通过SHAP进一步增强模型的可解释性。该模型基于焦作市市区多个空气质量监测站的汇总数据，用于预测PM2.5和O3的每小时浓度，旨在提高预测精度和模型透明度。实验结果表明，粒子群算法显著提高了所有预测水平的预测性能，同时将计算时间减少了50%以上。优化后的CNN- bilstm模型在预测O3浓度方面一直优于基准模型，包括LSTM、CNN和XGBoost，特别是在延长交货时间的情况下。该模型具有较强的短期预测能力（O3: RMSE = 17.43 ~ 17.89 μg/m3, R2 = 0.88; PM2.5: RMSE = 13.94 ~ 16.73 μg/m3, R2 = 0.84 ~ 0.89），对未来6 h的预测精度也较好（O3: RMSE = 19.93 μg/m3, R2 = 0.85; PM2.5: RMSE = 23.76 μg/m3, R2 = 0.67）。基于shap的可解释性分析表明，T、NO2和UVI是O3预测的主要因子，而PM10、T和RH是PM2.5预测的主要因子。这些发现突出了PSO-CNN-BiLSTM模型在推进空气质量预测方面的有效性，并为污染缓解战略和政策制定提供了有价值的见解。

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引用次数: 0