Atmospheric Environment最新文献_第8页

Optical properties of carbonaceous aerosols and their radiative effects in arid and semi-arid regions of northwestern India 印度西北部干旱和半干旱地区碳质气溶胶的光学特性及其辐射效应

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-22 DOI: 10.1016/j.atmosenv.2025.121694

Ashish Gupta, Deepika Bhattu

Carbonaceous aerosols (CA) strongly impact regional and global climate through their light-absorbing and scattering properties, yet their effects remain uncertain in dust-influenced regions. We investigated the optical properties, source contributions, and radiative impacts of CA at two climatically distinct regions in northwestern India: an arid region (AR, Jodhpur; post-monsoon) and a semi-arid region (SAR, Kota; winter). Mean absorption Ångström exponent (AAE) values were comparable between the two regions (AR: 1.416 ± 0.173; SAR: 1.395 ± 0.069), but temporal cluster analysis revealed source-specific variability, with lower AAE during traffic-dominated periods (∼1.30) and elevated AAE during solid fuel and biomass combustion (1.68 in AR and 1.52 in SAR). While equivalent BC (eBC) levels were higher in AR with a relatively uniform liquid-fuel contribution (BC_lf = 80.06 ± 1.98 %), the mass absorption cross-section of BC (MAC_BC) in SAR was ∼4.5X greater, driven by local solid fuel combustion and transported biomass burning emissions (BC_sf = 34.61 ± 6.88 %). Mie modelling indicated higher SSA in AR due to higher contribution of mineral dust, in contrast to SAR, where carbonaceous aerosols caused stronger absorption, forward scattering, and higher imaginary refractive index (k_OBD). Although absorption enhancement (E_λ) was slightly higher in AR (∼1.11 vs. ∼0.99), SAR aerosols nearly doubled the warming potential (ΔRFE), with RFE values of ∼0.87 W/m² in SAR versus ∼0.43 W/m² in AR. These findings highlight strong source-specific and site-specific variability in aerosol absorption and radiative, emphasizing the need to integrate region-specific parameters into climate models and air quality assessments for data-scarce arid and semi-arid South Asian environments.

碳质气溶胶（CA）通过其吸光和散射特性强烈影响区域和全球气候，但其在沙尘影响地区的影响仍不确定。我们研究了印度西北部两个气候不同地区的CA的光学特性、源贡献和辐射影响：干旱地区（AR，焦特布尔，季风后）和半干旱地区（SAR，哥打，冬季）。平均吸收Ångström指数（AAE）值在两个区域之间具有可比性（AR: 1.416±0.173;SAR: 1.395±0.069），但时间聚类分析显示了源特异性差异，交通主导时期的AAE较低（~ 1.30），固体燃料和生物质燃烧期间的AAE升高（AR为1.68，SAR为1.52）。虽然在相对均匀的液体燃料贡献下，AR中的等效BC （eBC）水平较高（BClf = 80.06±1.98%），但由于局部固体燃料燃烧和输送的生物质燃烧排放（BCsf = 34.61±6.88%），SAR中BC的质量吸收截面（MACBC）高出约4.5倍。Mie模型表明，由于矿物粉尘的贡献较大，AR中的SSA较高，而SAR中碳质气溶胶的吸收、前向散射和虚折射率（kOBD）较强。虽然吸收增强（λ）在AR中略高（~ 1.11 vs. ~ 0.99），但SAR气溶胶的增温潜势几乎翻了一番（ΔRFE）， SAR的RFE值为~ 0.87 W/m2，而AR的RFE值为~ 0.43 W/m2。这些发现突出了气溶胶吸收和辐射的强源特异性和站点特异性变异，强调需要将区域特异性参数整合到气候模式和数据稀缺的干旱和半干旱南亚环境的空气质量评估中。

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引用次数: 0

Analysis of odor and VOCs pollution in industrial parks of central inner Mongolia autonomous region based on mobile monitoring 基于移动监测的内蒙古中部工业园区异味及VOCs污染分析

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-21 DOI: 10.1016/j.atmosenv.2025.121703

Chaofei Li , Yuanhao Jia , Yu Qiu , Cheryl Marie Cordeiro , Sha Li , Yanying Chen , Jinxing Liu , Heinz W. Siesler , Hongkan Wu , Run Zhao

Odor and volatile organic compound (VOC) pollution were characterized through a 15-month mobile monitoring campaign (January 2024–March 2025) in the Tuoketuo Industrial Park, Hohhot, Inner Mongolia, an area experiencing frequent odor complaints. A portable multi-sensor odor analyzer was deployed across ambient routes, Priority Monitoring Zones (PMZs), and 52 Priority Regulated Enterprises (PREs), covering a total distance of 4072 km. The monitoring results indicated that mean odor unit (OU, dimensionless) values were higher in PMZs at night (10.2) than during the day (8.3) and on ambient routes (7.08). Seasonal peaks occurred in summer (July–August) and winter (December), corresponding to periods of low wind speeds and temperature inversions. Spatial analysis identified recurrent odor hotspots along J Avenue (night-time anomaly probability 65 %) and at the H Street–F Road intersection (48 %). Ammonia (NH₃; peak 10 mg m⁻³), hydrogen sulfide (H₂S; peak 7.85 mg m⁻³), and trimethylamine (TMA) were the dominant odorants, associated mainly with biopharmaceutical, coal-chemical, corn-processing and wastewater treatment activities. Although total VOC (TVOC) concentrations were low (0.11–0.15 mg m⁻³), odor activity values (OAVs) highlighted TMA and methanethiol (MM) as key contributors to perceived odor impact. These findings support targeted night-time enforcement in high-risk corridors and optimization of waste-gas treatment, and motivate the adoption of OAV-based odor management beyond mass-based TVOC metrics.

在内蒙古呼和浩特市托克托工业园区进行了为期15个月（2024年1月- 2025年3月）的气味和挥发性有机化合物（VOC）污染流动监测。在环境路线、优先监测区（PMZs）和52家优先监管企业（PREs）上部署了便携式多传感器气味分析仪，总距离为4072公里。监测结果表明，pmz夜间平均气味单位（OU，无量纲）值（10.2）高于白天（8.3）和周边路线（7.08）。季节高峰出现在夏季（7 - 8月）和冬季（12月），对应于低风速和逆温期。空间分析确定了沿J大道（夜间异常概率为65%）和H街- f路交叉口（48%）反复出现的气味热点。氨（NH3，峰值10 mg m−3）、硫化氢（H2S，峰值7.85 mg m−3）和三甲胺（TMA）是主要的气味剂，主要与生物制药、煤化工、玉米加工和废水处理活动有关。虽然总挥发性有机化合物（TVOC）浓度较低（0.11-0.15 mg m−3），但气味活性值（oav）强调了TMA和甲硫醇（MM）是感知气味影响的关键因素。这些发现支持在高风险走廊有针对性的夜间执法和优化废气处理，并激励采用基于oav的气味管理，而不是基于大规模的TVOC指标。

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引用次数: 0

Classifying ultrafine particle formation using machine learning on total number concentrations 利用机器学习对总数浓度的超细颗粒形成进行分类

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-21 DOI: 10.1016/j.atmosenv.2025.121696

Hosna Movahhedinia , Jonathan M. Wang , Nathan Hilker , Cheol-Heon Jeong , Yushan Su , Greg J. Evans

Ultrafine particles (UFP, less than 100 nm in aerodynamic diameter) pose significant health and environmental risks. These particles can originate from anthropogenic sources such as traffic emissions and fuel combustion, or form through atmospheric reactions. To reduce human exposure to UFP, it is important to understand the processes that can increase UFP concentrations. Current methods typically use particle size data to identify processes such as nucleation events. Recent studies have applied machine learning, particularly the transfer learning method, to this task. However, particle size distribution data is not widely available at many monitoring sites. In this study, we aimed to identify UFP sources using machine learning classification models only based on high time-resolution total number concentration data, rather than size distribution data, making the approach applicable to locations where only total UFP measurements are available. We have previously analyzed particle size data ranging from 6 to 520 nm collected from 2006 to the end of 2021 at the Southern Ontario Centre for Atmospheric Aerosol Research (SOCAAR) near a busy roadway in downtown Toronto, Canada. The days were classified into five categories: Strong Nucleation, Midday Pollution, Traffic Pollution, Baseline, and Mixed. Two machine learning approaches were tried: (1) ensemble learning models, and (2) transfer learning models. Both approaches performed well, achieving average accuracies of 80% and 75%, respectively. While transfer learning models were more robust to missing values, the ensemble learning method was slightly more robust to moderate noise and was also less computationally demanding. The ensemble learning models were then applied to a second monitoring location with a lower UFP level. The predicted classes at this site had similar characteristics to the classified days at the first site, with 78%, 58%, and 50% of the Strong Nucleation, Baseline, and Traffic Pollution days identified at both sites being classified into the same respective categories. These results suggest that the ensemble learning models could be transferred to other locations.

超细颗粒（UFP，空气动力学直径小于100纳米）对健康和环境构成重大风险。这些颗粒可以来自人为来源，如交通排放和燃料燃烧，也可以通过大气反应形成。为了减少人类对UFP的暴露，重要的是要了解可以增加UFP浓度的过程。目前的方法通常使用粒度数据来识别过程，如成核事件。最近的研究已经将机器学习，特别是迁移学习方法应用于这项任务。然而，在许多监测点，颗粒尺寸分布数据并不广泛。在这项研究中，我们的目标是使用机器学习分类模型来识别UFP来源，该模型仅基于高时间分辨率的总数浓度数据，而不是大小分布数据，使该方法适用于只有总UFP测量可用的位置。我们之前分析了2006年至2021年底在加拿大多伦多市中心一条繁忙道路附近的南安大略省大气气溶胶研究中心（SOCAAR）收集的6至520纳米的粒径数据。这些天被分为五类：强核污染、正午污染、交通污染、基线污染和混合污染。我们尝试了两种机器学习方法：(1)集成学习模型，(2)迁移学习模型。两种方法都表现良好，平均准确率分别达到80%和75%。虽然迁移学习模型对缺失值的鲁棒性更强，但集成学习方法对中等噪声的鲁棒性略强，并且计算需求也更少。然后将集成学习模型应用于UFP水平较低的第二个监测位置。该站点的预测类别与第一个站点的分类天数具有相似的特征，两个站点确定的强核日、基线日和交通污染日分别有78%、58%和50%被划分为相同的类别。这些结果表明，集成学习模型可以转移到其他地方。

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引用次数: 0

Inversion of hourly NOx emissions through air quality monitoring data and deep learning response surface modeling 通过空气质量监测数据和深度学习响应面模型反演每小时氮氧化物排放

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-20 DOI: 10.1016/j.atmosenv.2025.121695

Ziyi Liu , Yun Zhu , Ji-cheng Jang , Zhaoxin Dong , Jia Xing , Bin Zhao , Jinying Li , Qipeng Wen , Dian Ding , Yujie Qin

High-resolution emission inventories (EIs) are critical for policymakers to develop air pollution mitigation strategies. However, traditional EIs are often outdated due to data lag. Here, we develop a novel framework for high-resolution EI inversion based on response surface model. Application to a continuous pollution episode in the Pearl River Delta (PRD) demonstrates that the posterior emissions significantly improve the simulation accuracy of NO₂ and O₃, revealing new spatiotemporal distribution patterns of nitrogen oxides (NO_x) and O₃ sensitivity regimes. The posterior NO_x emissions decreased by 12.5 % compared to the prior emissions, with emissions primarily concentrated during the daytime and significantly reduced during nighttime. Besides, emissions decreased in central cities while increasing in peripheral cities, reflecting the notable impact of policies such as transportation electrification and industrial relocation. And changes in emissions notably impacted the spatial distribution of pollutants and atmospheric oxidation capacity, with the VOC-limited regime during the daytime expanding from central cities to surrounding areas. Finally, we uncover that Red Alert measures are insufficient to bring daily maximum 8-h average (MDA8) O₃ concentrations into compliance during extreme weather in the PRD. The framework developed in this study provides policymakers with a robust tool to more effectively and promptly understand local emissions and implement targeted control strategies.

高分辨率排放清单对于决策者制定空气污染缓解战略至关重要。然而，由于数据滞后，传统的环境评价往往已经过时。本文提出了一种基于响应面模型的高分辨率EI反演框架。对珠江三角洲连续污染事件的研究表明，后验排放显著提高了NO2和O3的模拟精度，揭示了新的氮氧化物（NOx）和O3的时空分布模式。与前一阶段相比，后一阶段的氮氧化物排放量减少了12.5%，排放主要集中在白天，夜间显著减少。此外，中心城市的排放量下降，外围城市的排放量增加，反映了交通电气化和产业转移等政策的显著影响。排放变化显著影响污染物的空间分布和大气氧化能力，白天vocs限制状态从中心城市向周边地区扩展。最后，我们发现，在极端天气下，红色预警措施不足以使珠江三角洲的每日最大8小时平均值（MDA8）臭氧浓度达到标准。本研究开发的框架为政策制定者提供了一个强大的工具，可以更有效、更迅速地了解当地的排放情况，并实施有针对性的控制战略。

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引用次数: 0

Atmospheric boundary layer characteristics during severe air pollution and fog events over Delhi: Insights from ground-based Lidar, satellites, and models 德里严重空气污染和雾事件期间的大气边界层特征：来自地面激光雷达、卫星和模型的见解

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-20 DOI: 10.1016/j.atmosenv.2025.121684

Dharmendra Kumar Kamat , Som Kumar Sharma , Prashant Kumar , Kondapalli Niranjan Kumar , Sourita Saha , Aniket , Sukhwinder Kaur , Arun

Delhi experiences severe air quality deterioration during the post-monsoon and winter seasons, driven by anthropogenic emissions and natural meteorological factors. This study investigates the atmospheric boundary layer (ABL) characteristics during heavy air pollution and fog conditions over Delhi from October 2023 to February 2024 using ground-based Lidar, satellite, and reanalysis data. Lidar measurements reveal a persistently shallow ABL (<1 km) from November to January, with nighttime boundary layer height (BLH) suppressed by strong radiative inversions. Elevated PM_2.5 concentrations during this period show an inverse, power-law relationship with BLH. The ventilation coefficient (VC) remained below 800 m²s^-1 from November to January, indicating poor dispersion. INSAT-3D/3DR satellite data showed a peak fog occurrence of 75 % over Delhi, with the highest frequency in January. Analysis showed that the combined frequency of haze, fog, and low-level clouds reached 22.46 % during the study period, with the highest occurrences in November (45.10 %) and January (39.55 %). Ground-based Lidar observations captured fine-scale features such as shallow inversion layers, nighttime ABL collapse, and diurnal boundary layer development more accurately than reanalysis. These insights are crucial for enhancing urban weather models, air quality forecasts, and early warning systems in pollution-affected regions.

在人为排放和自然气象因素的推动下，德里在季风后和冬季经历了严重的空气质量恶化。本研究利用地面激光雷达、卫星和再分析数据，研究了2023年10月至2024年2月德里重污染和雾条件下的大气边界层（ABL）特征。激光雷达测量显示，从11月到1月，一个持续的浅ABL (<1 km)，夜间边界层高度（BLH）被强辐射逆温抑制。在此期间，PM2.5浓度升高与BLH呈反比的幂律关系。11 -1月通风系数（VC）保持在800 m2s-1以下，散度较差。INSAT-3D/3DR卫星数据显示，德里的雾峰值发生率为75%，一月份的频率最高。分析表明，霾、雾和低层云在研究期间的总频率达到22.46%，其中11月（45.10%）和1月（39.55%）出现频率最高。地面激光雷达观测比再分析更准确地捕获了诸如浅层逆温层、夜间ABL塌陷和日边界层发展等精细尺度特征。这些见解对于加强城市天气模型、空气质量预报和污染影响地区的早期预警系统至关重要。

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引用次数: 0

Prediction of the spectral frequencies and relative radiative efficiencies of products from the reactions of glyoxal 乙二醛反应产物的光谱频率和相对辐射效率的预测

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-19 DOI: 10.1016/j.atmosenv.2025.121697

Ashish Rana , Priyanshu Meshram , Vernon R. Morris , Jean M. Andino

Glyoxal-derived nitrogenous organic products are becoming recognized for their role in atmospheric radiative processes. While their absorption in the UV–visible region and their impact on visibility have been extensively studied, their infrared (IR) properties, especially within the atmospheric window region (800–1250 cm⁻¹) remain largely unexplored. This work presents a computational study where the IR vibrational frequencies of compounds generated from glyoxal-ammonium sulfate chemistry and their potential greenhouse impact are calculated. The potential of these chemicals to trap Earth's outgoing radiation within the atmospheric window is assessed by analyzing the calculated frequencies and intensities. The results suggest that the glyoxal-derived products have significant absorption features in the IR spectral region that could potentially influence atmospheric heat trapping. This may impact the output of atmospheric models, particularly in urban areas. A relative radiative efficiency (as compared to CO₂) is calculated to attempt to scale the relative importance of these products of glyoxal reaction. This novel perspective underscores the need to account for the IR absorption of oxidation products of the glyoxal-ammonium sulfate chemistry in assessing their full impact on radiative balance.

乙二醛衍生的含氮有机产品因其在大气辐射过程中的作用而逐渐得到认可。虽然它们在紫外可见区的吸收及其对能见度的影响已被广泛研究，但它们的红外（IR）特性，特别是在大气窗口区域（800-1250 cm−1）内的红外特性仍未被广泛探索。这项工作提出了一个计算研究，其中由乙二醛-硫酸铵化学产生的化合物的红外振动频率及其潜在的温室影响计算。通过分析计算出的频率和强度来评估这些化学物质将地球向外辐射困在大气窗口内的潜力。结果表明，乙二醛衍生产物在红外光谱区具有显著的吸收特征，可能会影响大气的吸热。这可能影响大气模式的输出，特别是在城市地区。计算相对辐射效率（与二氧化碳相比），试图按比例衡量乙二醛反应这些产物的相对重要性。这一新颖的观点强调需要考虑乙二醛-硫酸铵化学氧化产物的红外吸收，以评估其对辐射平衡的全面影响。

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引用次数: 0

A machine learning-based model for aerosol scattering hygroscopic growth factor (f(RH)) prediction in Beijing urban area 基于机器学习的北京市区气溶胶散射吸湿生长因子（f(RH)）预测模型

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-19 DOI: 10.1016/j.atmosenv.2025.121699

Hongfei Tong , Xinyao Hu , Can Xia , Xiaojing Shen , Yangmei Zhang , Quan Liu , Lei Liu , Linlin Liang , Jiayuan Lu , Huizheng Che , Xiaoye Zhang , Junying Sun

The atmospheric aerosol scattering hygroscopic growth factor (f(RH)) is a key parameter for assessing aerosol radiative forcing and atmospheric visibility. In this study, a prediction model for the aerosol scattering hygroscopic growth factor of PM₁₀ at ambient relative humidity (RH) was constructed using a machine learning method based on the observed data of aerosol scattering hygroscopic growth factor (f(RH)) in the urban area of Beijing from 2018 to 2022. CatBoost regression model, utilizing meteorological and air quality data, achieves high accuracy in reconstructing the f(RH), with a coefficient of determination R² of 0.9388 on the testing dataset. SHapley Additive exPlanations (SHAP) showed that: the contribution of SHAP value of RH accounted for 58 % of the total, which was the dominant factor; Nitrogen dioxide (NO₂) indirectly influenced f(RH) by affecting the formation of secondary inorganic salts, NO₂ concentrations below 35 μg/m³ enhanced aerosol hygroscopicity, while concentrations above 35 μg/m³ weakened it. The model was successfully applied to the analysis of heavy pollution events, with good simulation results for low atmospheric visibility periods; the optical parameters reconstructed by the model showed the potential for application in radiative forcing assessment (relative error = 4.04 % at RH = 85 %). This study provides a novel machine learning-based approach for acquiring high time-resolution aerosol f(RH) data, which is helpful in improving the accuracy of aerosol climate effect assessments and atmospheric visibility predictions.

大气气溶胶散射吸湿生长因子（f(RH)）是评估气溶胶辐射强迫和大气能见度的关键参数。基于2018 - 2022年北京城区气溶胶散射吸湿生长因子f（RH）观测数据，采用机器学习方法构建了环境相对湿度（RH）下PM10气溶胶散射吸湿生长因子的预测模型。CatBoost回归模型利用气象和空气质量数据重建f（RH）具有较高的精度，在测试数据集上的决定系数R2为0.9388。SHapley加性解释（SHAP）表明：RH的SHAP值贡献占总贡献的58%，是主导因素；二氧化氮（NO2）通过影响次生无机盐的形成间接影响f(RH)，浓度低于35 μg/m3时气溶胶吸湿性增强，高于35 μg/m3时气溶胶吸湿性减弱。该模式成功地应用于重污染事件的分析，在大气能见度较低时期取得了较好的模拟结果；模型重建的光学参数显示了在辐射强迫评估中的应用潜力（相对误差为4.04%，相对湿度为85%）。本研究提供了一种基于机器学习的获取高时间分辨率气溶胶f（RH）数据的新方法，有助于提高气溶胶气候效应评估和大气能见度预测的准确性。

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引用次数: 0

Factors controlling short-term variability of light-absorption characteristics at a Mediterranean city impacted by severe residential wood burning emissions 地中海城市受重度居民木材燃烧排放影响的光吸收特征短期变异性控制因素

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-19 DOI: 10.1016/j.atmosenv.2025.121702

D.G. Kaskaoutis , G. Grivas , R.E.P. Sotiropoulou , I. Stavroulas , A. Bougiatioti , E. Tagaris , N. Mihalopoulos

This study examines Black Carbon (BC) and Brown Carbon (BrC) spectral absorption properties during contrasting periods dominated by residential wood burning (RWB) emissions (winter), and by regional-background carbonaceous aerosols (summer). The measurements were performed in Ioannina, a medium-sized Greek city, with the objective of understanding the contributions of primary and secondary carbonaceous aerosols (BC, BrC) from various sources (RWB, vehicular emissions, regional sources) to total absorption. During winter, the site experiences a heavy aerosol burden with high concentrations of PM_2.5, organic carbon (OC), BC from wood burning (BC_wb) and levoglucosan. Conversely, in summer, cleaner atmospheric conditions prevail, with increased impacts from vehicle emissions and regional background aerosols. During winter, BrC absorption dominated (64 % of total absorption at 370 nm), influenced by strong emissions, limited dispersion, and secondary aerosol formation. Secondary BrC (BrC_sec) formation was promoted by the abundance of RWB emissions during nighttime, while there was also evidence of increased BrC_sec absorption under enhanced O₃ and low NO_x conditions during midday. In summer, the absorption characteristics differed notably, and were mostly driven by BC from fossil-fuel combustion, regional aerosols, and atmospheric processing including photo-bleaching. An analysis of spectral absorptions at the near-UV and visible spectrum (370, 470, 660 nm) revealed seasonal and diurnal differences in the contributions of various chromophores. During winter, the coating of BC with OC and inorganic species (lensing effect) resulted in absorption enhancement, while strong RWB emissions led in the curvature of spectral absorption, as evidenced by a significant increase in Ångström exponent (AAE) by decreasing wavelength. The observed levels, the variability in spectral absorption properties, and the contributing sources and processes indicate the complexity and challenges of characterizing the radiative effects of urban carbonaceous aerosol.

本研究考察了在住宅木材燃烧（RWB）排放（冬季）和区域背景碳质气溶胶（夏季）主导的对比时期，黑碳（BC）和棕色碳（BrC）的光谱吸收特性。测量是在希腊中型城市约阿尼纳进行的，目的是了解来自不同来源（RWB，车辆排放，区域来源）的初级和次级碳质气溶胶（BC, BrC）对总吸收的贡献。冬季，该站点的气溶胶负担较重，PM2.5、有机碳（OC）、木材燃烧产生的BC （BCwb）和左旋葡聚糖浓度较高。相反，在夏季，更清洁的大气条件普遍存在，车辆排放和区域背景气溶胶的影响增加。在冬季，受强发射、有限扩散和二次气溶胶形成的影响，BrC吸收占主导地位（占370 nm总吸收的64%）。夜间大量的RWB排放促进了次生BrC （BrCsec）的形成，同时也有证据表明，在正午增强的O3和低NOx条件下，BrCsec的吸收增加。在夏季，其吸收特征明显不同，主要受化石燃料燃烧、区域气溶胶和大气处理（包括光漂白）的驱动。近紫外和可见光谱（370,470,660 nm）的光谱吸收分析揭示了各种发色团贡献的季节和昼夜差异。在冬季，有机碳和无机物涂层（透镜效应）增强了BC的吸收，而强RWB发射导致光谱吸收弯曲，表明Ångström指数（AAE）随波长的减小而显著增加。观测到的水平、光谱吸收特性的变率以及贡献源和过程表明了表征城市含碳气溶胶辐射效应的复杂性和挑战性。

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引用次数: 0

Comprehensive assessment of PM10 from home heating using different appliances and biomass fuels: Chemical composition, oxidative potential, and ecotoxicity 使用不同电器和生物质燃料的家庭供暖产生的PM10的综合评估：化学成分、氧化电位和生态毒性

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-19 DOI: 10.1016/j.atmosenv.2025.121700

Yago Alonso Cipoli , Estela D. Vicente , Isabella Charres , Margarita Evtyugina , Marina Alfosea-Simón , Franco Lucarelli , Nora Kováts , Jiří Ryšavý , Manuel Feliciano , Célia Alves

The European Union has implemented policies to promote renewable energy, with an emphasis on biomass for heat generation. However, residential biomass combustion is a major source of particulate matter (PM₁₀), and its chemical constituents pose health concerns worldwide. This study characterised the organic and inorganic composition, oxidative potential (OP), and ecotoxicity of PM₁₀ indoors and outdoors during the operation of two heating appliances fuelled with different types of biomasses: a modern hydronic stove and a traditional wood stove. PM₁₀ concentrations were higher in the room equipped with the traditional system during the combustion of briquettes (95.9 ± 74.9 μg m⁻³) and firewood (50.1 ± 25.6 μg m⁻³), compared to the modern stove using pellets (27.1 ± 11.8 μg m⁻³) and olive stone (23.0 ± 4.5 μg m⁻³). While element oxides accounted for similar PM₁₀ mass fractions (7 %), the wood stove produced higher levels of organic constituents, including carbonaceous fractions, polycyclic aromatic hydrocarbons (PAHs), quinones and saccharides. Significant correlations between OP assays and concentrations of PAHs, quinones and phenolic compounds were found in the room equipped with wood stove, with indoor to outdoor (I/O) ratios higher than 1. In contrast, I/O ratios below 1 were observed for OP in PM₁₀ samples collected during hydronic stove operation. Ecotoxicity assays using Aliivibrio fischeri classified indoor PM₁₀ from the wood stove as 'very toxic', whereas samples from the hydronic stove exhibited lower toxicity and OP levels. These findings highlight the need to reconcile renewable energy goals with air quality and public health.

欧洲联盟实施了促进可再生能源的政策，重点是用于供热的生物质。然而，住宅生物质燃烧是颗粒物（PM10）的主要来源，其化学成分在世界范围内构成健康问题。本研究表征了两种以不同类型生物质为燃料的加热设备（现代水循环炉和传统柴炉）在室内和室外运行过程中PM10的有机和无机成分、氧化电位（OP）和生态毒性。与使用颗粒炉（27.1±11.8 μ m−3）和橄榄石炉（23.0±4.5 μ m−3）的现代炉灶相比，使用传统系统的房间在燃烧型煤（95.9±74.9 μ m−3）和木柴（50.1±25.6 μ m−3）时PM10浓度更高。虽然元素氧化物占PM10质量分数相似（7%），但木炉产生的有机成分含量更高，包括碳质组分、多环芳烃（PAHs）、醌类和糖类。在设有木灶的室内，OP测定结果与多环芳烃、醌类和酚类化合物浓度呈显著相关，室内外（I/O）比值大于1。相比之下，在水循环炉运行期间收集的PM10样品中，观察到OP的I/O比率低于1。使用菲氏阿里弧菌进行的生态毒性分析将木质炉灶的室内PM10分类为“剧毒”，而来自水循环炉灶的样品显示出较低的毒性和OP水平。这些发现强调了将可再生能源目标与空气质量和公众健康协调起来的必要性。

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引用次数: 0

Contributions of tailpipe and non-tailpipe emissions to the oxidative potential of source-resolved PM10 from major LDV- and HDV-dominated freeways in Los Angeles 洛杉矶主要LDV和hdv主导的高速公路上的尾气排放和非尾气排放对源解析PM10氧化电位的贡献

IF 3.7 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment

Pub Date : 2025-11-19 DOI: 10.1016/j.atmosenv.2025.121686

Sahar Fazelvalipour , Yashar Aghaei , Mohammad Mahdi Badami , Mohammad Aldekheel , Ramin Tohidi , Ganesh Subramanian , Vishal Verma , Jiachen Zhang , Constantinos Sioutas

This study assesses the chemical composition, oxidative potential (OP), and source contributions of traffic-related particulate matter with an aerodynamic diameter ≤10 μm (PM₁₀) collected from two major freeways in Southern California, I-110 and I-710, and from a background site in the University of Southern California (USC) campus. On-road samples were collected in fall 2023 and spring 2024 and analyzed for organic and elemental carbon (OC and EC), trace metals, and inorganic ions. The OP of PM₁₀ was evaluated using the dithiothreitol (DTT) assay. Freeway PM₁₀ concentrations exceeded background levels by factors of 4–6 and were consistently higher on I-710, which has a larger proportion of heavy-duty vehicle traffic, compared to I-110. Carbonaceous components were also enriched 5 to 9 times above background, and brake and tire wear metals (e.g., Fe, Cu, Zn, Ba) exceeded the background level by more than an order of magnitude. Both PM₁₀ concentrations and DTT activity in fall were substantially larger than the spring values, possibly due to dilution and lower carbonaceous loadings in the spring. Principal component analysis (PCA) was applied to identify the primary sources contributing to PM₁₀ composition, revealing five major factors, namely tailpipe emissions, brake and tire wear, resuspended road dust, secondary inorganic aerosol, and sea salt. Multiple linear regression (MLR) linked these sources to OP, with brake and tire wear explaining 33 % of the observed DTT response while contributing only 20 % to the PM₁₀ mass, resulting in a dimensionless OP-to-mass ratio of 1.66. These findings underscore the growing importance of non-tailpipe sources as potentially toxic yet unregulated contributors to on-road health risks, reinforcing the need for targeted research and future regulatory attention.

本研究评估了来自南加州I-110和I-710两条主要高速公路以及南加州大学校园背景场地的空气动力学直径≤10 μm的交通相关颗粒物（PM10）的化学成分、氧化电位（OP）和来源贡献。在2023年秋季和2024年春季采集了道路样本，并分析了有机碳和元素碳（OC和EC）、微量金属和无机离子。采用二硫苏糖醇（DTT）法测定PM10的OP值。高速公路上的PM10浓度以4-6倍的倍数超出了背景水平，并且在I-710上的浓度一直较高，因为重型车辆通行的比例高于I-110。碳质成分也比本底富集5 ~ 9倍，制动和轮胎磨损金属（如铁、铜、锌、钡）超过本底水平一个数量级以上。秋季PM10浓度和DTT活性均明显大于春季值，可能是由于春季的稀释和低碳负荷。采用主成分分析（PCA）确定了PM10组成的主要来源，揭示了5个主要因素，即尾气排放、刹车和轮胎磨损、重悬浮道路粉尘、二次无机气溶胶和海盐。多元线性回归（MLR）将这些来源与OP联系起来，制动和轮胎磨损解释了所观察到的DTT响应的33%，而PM10质量仅贡献了20%，导致无因次的OP-质量比为1.66。这些发现强调了非尾气排放源作为潜在有毒但不受管制的道路健康风险来源的重要性日益增加，从而加强了有针对性的研究和未来监管关注的必要性。

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引用次数: 0