Atmospheric Pollution Research最新文献_第5页

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

CausalMedZone: A pathway analysis model of ozone formation based on causal inference CausalMedZone：基于因果推理的臭氧形成通路分析模型

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.2025.102696

Chenyang Jia , Chang Liu , Chenguang Yan , Erhong Duan

Ozone is a significant atmospheric pollutant with notable hazards to human health, and its formation mechanism is complex, but current research on ozone formation mechanisms often neglects the exploration of causal relationships. This study develops the CausalMedZone (Causality and Mediation pathway analysis for ozone) model, a causal inference-based framework designed to investigate ozone formation mechanisms. This model aims to identify key explanatory variables in the ozone formation process by explicitly modeling causal relationships among pollutants, thereby uncovering the true drivers of ozone pollution. Additionally, CausalMedZone integrates mediation and moderation effects to construct ozone formation pathways, providing a comprehensive understanding of how key pollutants and meteorological conditions interact to influence ozone formation. CausalMedZone effectively elucidates the causes of ozone pollution in Shijiazhuang, reveals a dual pathway where PM_2.5 directly promotes ozone formation and indirectly inhibits it through NO₂, with CO and relative humidity significantly moderating the PM_2.5

\to

NO₂ and NO₂

\to

O₃ pathways, respectively (R² = 0.70). Furthermore, the model demonstrates broad applicability in heterogeneity analysis across the Beijing-Tianjin-Hebei region, revealing significant differences in ozone formation mechanisms among cities: Beijing exhibits a NO₂-dominated ozone suppression pathway (R² = 0.70), while Shijiazhuang and Tianjin show a PM_2.5

\to

NO₂ coupling pathway (R² = 0.80 & 0.75). These findings provide a scientific foundation for developing region-specific and precise ozone pollution control strategies.

臭氧是一种对人类健康危害显著的重要大气污染物，其形成机制复杂，但目前对臭氧形成机制的研究往往忽略了对因果关系的探索。本研究开发了CausalMedZone（臭氧的因果关系和中介途径分析）模型，这是一个基于因果推理的框架，旨在研究臭氧的形成机制。该模型旨在通过明确模拟污染物之间的因果关系，确定臭氧形成过程中的关键解释变量，从而揭示臭氧污染的真正驱动因素。此外，CausalMedZone整合调解和调节效应构建臭氧形成路径，全面了解关键污染物和气象条件如何相互作用影响臭氧形成。CausalMedZone有效地阐明了石家庄市臭氧污染的成因，揭示了PM2.5直接促进臭氧形成和通过NO2间接抑制臭氧形成的双重途径，CO和相对湿度分别显著调节PM2.5→NO2和NO2→O3的途径（R2 = 0.70）。此外，该模型在京津冀地区的异质性分析中具有广泛的适用性，揭示了城市间臭氧形成机制的显著差异：北京表现为NO2主导的臭氧抑制途径（R2 = 0.70），而石家庄和天津表现为PM2.5→NO2耦合途径（R2 = 0.80 & 0.75）。这些研究结果为制定具有区域特色的精确臭氧污染控制策略提供了科学依据。

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引用次数: 0

Modeling PM2.5 dispersion from diesel generators in Beirut: Identifying urban hotspots under data scarcity 贝鲁特柴油发电机PM2.5扩散模型：数据稀缺下的城市热点识别

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.2025.102686

Elissar Al Aawar , Jennifer Karam , Abdelkader Baayoun , Mohamad Ghadban , Sara Najem , Najat A. Saliba , Issam Lakkis

Diesel generators are emerging as community-initiated solutions to compensate for electricity shortages in cities facing economic crises and infrastructure collapse. In dense urban environments, emissions from these generators pose a significant air quality concern. In the absence of periodic observations from properly distributed sensors, as is the case in Beirut, physically based computational modeling serves as an effective tool for predicting pollutant distribution and assessing mitigation strategies. In this study, we employ the GRAMM-GRAL Lagrangian transport modeling system to simulate PM_2.5 dispersion originating from diesel generators in Beirut under different meteorological and urban conditions. The simulations account for topography, atmospheric stability, wind speed and direction, building geometry, generator distribution, and exhaust stack heights, referring to the elevation at which generator emissions are released. We evaluate various scenarios by examining overall dispersion patterns, and mean street-level PM_2.5 concentrations. Using the World Health Organization’s AirQ+ tool, we also estimate the potential health impacts based on model-predicted PM_2.5 concentrations across the city. The results highlight the sensitivity of pollutant dispersion to wind patterns and generator exhaust elevation. Increasing the generator exhaust stack height notably reduces near-ground PM_2.5 levels, especially under high wind speeds. This study provides a scalable framework for air quality assessment and risk estimation in data-scarce urban environments and informs future urban planning and environmental policy efforts.

柴油发电机正在成为社区发起的解决方案，以弥补面临经济危机和基础设施崩溃的城市的电力短缺。在人口密集的城市环境中，这些发电机的排放对空气质量造成了重大影响。在没有适当分布的传感器的定期观测的情况下，如贝鲁特的情况，基于物理的计算建模可作为预测污染物分布和评估缓解战略的有效工具。在本研究中，我们采用gram - gral拉格朗日输运模型系统模拟了贝鲁特不同气象和城市条件下柴油发电机产生的PM2.5扩散。模拟考虑了地形、大气稳定性、风速和风向、建筑物几何形状、发电机分布和排气堆高度（指发电机排放的高度）。我们通过检查总体分散模式和平均街道PM2.5浓度来评估各种情景。使用世界卫生组织的AirQ+工具，我们还根据模型预测的整个城市的PM2.5浓度估计了潜在的健康影响。结果强调了污染物扩散对风型和发电机排气高度的敏感性。增加发电机排气烟囱高度可显著降低近地PM2.5水平，特别是在高风速下。本研究为数据稀缺的城市环境中的空气质量评估和风险评估提供了一个可扩展的框架，并为未来的城市规划和环境政策工作提供了信息。

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引用次数: 0

Impacts of photochemical losses of VOCs on ozone formation and source apportionment in a typical industrial city of Central Plains, China during summer 典型中原工业城市夏季VOCs光化学损失对臭氧形成及源分配的影响

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.2025.102778

Leitao Sun , Liya Fan , Haomin Huang , Daiqi Ye

Volatile organic compounds (VOCs) play a key role in ozone (O₃) formation, but conventional studies typically neglect photochemical losses, which reduces the effective VOCs available for O₃ formation and may bias O₃ formation potential (OFP) estimates and source apportionment. Using hourly VOCs data from Hebi in June 2024, this study employed the photochemical age-based parameterization method to estimate initial VOCs concentrations and quantify the photochemical losses. The average initial concentration of total VOCs (TVOCs) was 44.15 ppbv, 2.21 times that of the observed concentration (19.96 ppbv), with a photochemical loss of 24.19 ppbv (54.79 % of the initial concentration). During the daytime (6:00-19:00), the average photochemical loss of TVOCs accounted for 66.88 % of their average initial concentration. The O₃ pollution period showed a 3.9 times higher photochemical loss of TVOCs compared with the non-O₃ pollution period. During the daytime (06:00-19:00) of the whole study period, alkenes (37.54 ppbv, 57.36 %) and oxygenated VOCs (OVOCs) (18.56 ppbv, 30.06 %) were the major contributors to the total photochemical loss of TVOCs (40.81 ppbv). OFP comparisons revealed that OFP based on the initial (OFP_IC) and loss (OFP_LC) concentrations yielded higher total values and showed better correlations with observed O₃ than OFP based on the observed (OFP_OC) concentrations. Source apportionment showed that secondary formation (30.51 %), diesel vehicle emissions (15.34 %), and biogenic emissions (14.68 %) were the primary sources of consumed VOCs, defined as the fraction of VOCs lost via photochemical reactions during atmospheric transport. During the O₃ pollution period, secondary formation contributed 36.16 % (7.72 ppbv), which was 8.87 times that of the non-O₃ pollution period. Diesel vehicle emissions (19.25 %) and solvent usage (12.69 %) also increased, while liquefied petroleum gas/natural gas (LPG/NG) usage remained stable. This study provides critical insights into the role of photochemical losses in VOCs concentrations, OFP, and source apportionment, which will help improve the regional O₃ pollution control strategies.

挥发性有机化合物（VOCs）在臭氧（O3）的形成中起着关键作用，但传统的研究通常忽略了光化学损失，这减少了O3形成的有效VOCs，并可能影响O3形成势（OFP）的估计和来源分配。利用鹤壁地区2024年6月每小时VOCs数据，采用基于光化学年龄的参数化方法估算初始VOCs浓度，并量化光化学损失。总挥发性有机化合物（TVOCs）的平均初始浓度为44.15 ppbv，是观测浓度（19.96 ppbv）的2.21倍，光化学损失为24.19 ppbv（初始浓度的54.79%）。在白天（6:00-19:00），TVOCs的平均光化学损失占其平均初始浓度的66.88%。O3污染期TVOCs光化学损失比非O3污染期高3.9倍。在整个研究时段的白天（06:00-19:00），烯烃（37.54 ppbv, 57.36%）和含氧VOCs （18.56 ppbv, 30.06%）是TVOCs总光化学损失的主要来源（40.81 ppbv）。OFP比较显示，基于初始（OFPIC）和损失（OFPLC）浓度的OFP产生更高的总价值，并且与观测到的O3的相关性优于基于观测到的（OFPOC）浓度的OFP。来源分析表明，次生形成（30.51%）、柴油车排放（15.34%）和生物源排放（14.68%）是VOCs消耗的主要来源，VOCs消耗指的是大气运输过程中通过光化学反应损失的VOCs的比例。在O3污染期，次生地层贡献36.16% (7.72 ppbv)，是非O3污染期的8.87倍。柴油车排放量（19.25%）和溶剂使用量（12.69%）也有所增加，而液化石油气/天然气（LPG/NG）的使用量则保持稳定。该研究对光化学损失在VOCs浓度、OFP和来源分配中的作用提供了重要的见解，这将有助于改进区域O3污染控制策略。

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引用次数: 0

Commonly existence of additive effects of nitrogen deposition and precipitation changes on soil properties 氮沉降和降水变化对土壤性质普遍存在加性效应

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.2025.102663

Xiaomei Chen , Yujin Liu , Qiaojuan Zhou , Tianyi Wen , Hui Wei

Global change and the ecological consequences have been intensively studied for decades, with linear versus nonlinear interactive effects of multiple-factor global change being a longstanding hotspot due to be short of multifactor manipulation experiments. By employing the meta-analysis technique, we aimed to unveil the interactive effect of atmospheric nitrogen (N) deposition and precipitation changes on soil properties in the terrestrial ecosystems. Resultantly, we observed that regardless of reduced or increased precipitation manipulation, the interactive effects of N deposition and precipitation changes were commonly additive for most of the investigated soil parameters in this study (such as soil carbon content, microbial biomass and diversity). The observation indicated that it could be acceptable to estimate the two-factor overall effects of N deposition and precipitation changes by totalizing the two single-factor effects. However, such a simplification was not suitable in N cycling related studies, due to significant synergistic or antagonistic effects of N deposition and precipitation changes on soil ammonia and nitrate contents. Totally, our results imply commonly existence of additive effects of N deposition and precipitation changes on the soil ecosystem except the available soil N contents.

全球变化及其生态后果的研究已经深入了几十年，由于缺乏多因素操纵实验，多因素全球变化的线性与非线性相互作用是一个长期的热点。利用meta分析技术，揭示大气氮沉降和降水变化对陆地生态系统土壤性质的交互作用。因此，我们观察到，无论降水控制是减少还是增加，氮沉降和降水变化的交互效应在本研究中研究的大多数土壤参数（如土壤碳含量、微生物生物量和多样性）中通常是相加的。观测结果表明，将两个单因素效应相加，可以估计出氮沉降和降水变化的双因素总体效应。然而，这种简化并不适用于氮循环相关的研究，因为氮沉降和降水变化对土壤氨氮和硝态氮含量具有显著的协同或拮抗作用。综上所述，除速效氮含量外，氮沉降和降水变化对土壤生态系统普遍存在加性效应。

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引用次数: 0

Methodological insights for accurate quantification of trace elements in soluble and insoluble fractions of bulk atmospheric deposition 对大量大气沉积中可溶和不溶部分微量元素精确定量的方法学见解

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.2025.102682

Filippo Brugnone , Walter D'Alessandro , Lorenzo Brusca , Filippo Saiano , Marcello Liotta , Francesco Parello , Salvatore Giammanco , Anna Maria Abita , Sergio Calabrese

This study explores the distribution of 16 trace elements between soluble and insoluble fractions of atmospheric deposition in Sicily, Italy, based on EU protocols for monitoring pollutants. Using a standardised deposimeter, we collected 149 atmospheric deposition samples over two years. Additionally, we analysed the rinse solution of the deposimeter separately. Higher deposition values for elements like Sr, B, Ba, Zn, As, and Cu were found in the soluble fraction, whereas Fe, Ti, Al, Cr, Co, Li, Mn, V, Ni, and Pb were prevalent in the insoluble fraction. The rinse fraction typically accounted for lower deposition values (from 1 % to 19 %), except for Pb and B, which accounted for 42 % and 31 % of the total deposition. We compared trace element distribution during a "dry period" and a "wet period." During the dry period, the insoluble fraction represented up to 97 % for elements like Ti and Fe, while the rinse fraction was notable for B (∼51 %) and Pb (∼33 %). In the wet period, insoluble contributions were higher for Li, Al, Ti, Cr, Fe, Co, and Pb, and soluble contributions increased for B, V, Mn, Zn, As, Sr, Ba, and Cu. While soluble elements were affected by temporal precipitation distribution, less soluble elements like Ti, Fe, and Al showed no significant differences between periods. Overall, the study highlights varying degrees of solubility among trace elements. Although the rinse fraction was generally negligible for most elements, overlooking it could lead to underestimating total atmospheric deposition for some elements, especially after extended dry periods.

本研究基于欧盟污染物监测协议，探讨了意大利西西里岛大气沉积中可溶性和不可溶性组分之间16种微量元素的分布。使用标准化沉积物计，我们在两年内收集了149个大气沉积物样本。另外，对沉积仪的冲洗液进行了单独分析。Sr、B、Ba、Zn、As和Cu等元素在可溶部分沉积值较高，而Fe、Ti、Al、Cr、Co、Li、Mn、V、Ni和Pb等元素在不可溶部分沉积值较高。除Pb和B分别占总沉积的42%和31%外，漂洗馏分通常占较低的沉积值（从1%到19%）。我们比较了“干期”和“湿期”的微量元素分布。在干燥期，像Ti和Fe这样的元素的不溶性分数高达97%，而B（~ 51%）和Pb（~ 33%）的漂洗分数显著。在湿润期，Li、Al、Ti、Cr、Fe、Co和Pb的不溶性贡献较高，而B、V、Mn、Zn、As、Sr、Ba和Cu的可溶性贡献增加。可溶性元素受降水时间分布的影响，较难溶性元素Ti、Fe和Al在不同时期间差异不显著。总的来说，该研究强调了微量元素之间不同程度的溶解度。虽然对于大多数元素来说，漂洗部分通常可以忽略不计，但忽略它可能会导致低估某些元素的大气沉积总量，特别是在长时间干燥后。

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引用次数: 0

Investigation of temporal PCDD/F concentration levels and gas/particle partitioning employing recent models in the ambient air of a wastewater treatment plant site 采用最新模型对污水处理厂现场环境空气中PCDD/F浓度水平和气体/颗粒划分的时间调查

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

Atmospheric Pollution Research

Pub Date : 2025-11-10 DOI: 10.1016/j.apr.2025.102823

Berke Gülegen, Abdul Alim Noori, Yücel Taşdemir

Polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) are persistent organic pollutants posing a serious threat to human health and the environment. The present work measured PCDD/F atmospheric concentrations in the ambient air of Bursa's largest wastewater treatment plant over four seasons. The average PCDD/F concentration was 410 ± 178 fg/m³ (30.83 ± 4.85 fg WHO TEQ/m³). This value was in agreement with many studies conducted worldwide. Ambient air PCDD/Fs were found to originate mainly from sewage sludge in the aeration basin and motor vehicle emissions. However, the risk values were less than 10⁻⁶, indicating that PCDD/F pollution in the site does not pose a health risk. The gas/particle (G/P) distribution is a significant concern from many different perspectives, including the mechanisms of atmospheric deposition, long-distance transport and health risks. Traditionally, adsorption and absorption-based models have been employed to define the PCDD/F G/P partitioning. In the present study, five different models (Li-Ma-Yang, Dachs-Eisenreich, QSPR, pp-LFER, mp-pp-LFER) were utilized along with these two models. Among these models, the Li-Ma-Yang model presented successful performance and revealed the importance of absorption and deposition mechanisms for the G/P transitions. Also, the model of pp-LFER generally performed well and showed that it could predict PCDD/F partitioning.

多氯二苯并对二恶英/二苯并呋喃是对人类健康和环境构成严重威胁的持久性有机污染物。目前的工作测量了四个季节布尔萨最大的污水处理厂环境空气中PCDD/F的大气浓度。PCDD/F平均浓度为410±178 fg/m3（30.83±4.85 fg WHO TEQ/m3）。这一数值与世界范围内进行的许多研究结果一致。环境空气PCDD/Fs主要来源于曝气池内的污水污泥和机动车尾气。然而，风险值小于10−6，表明该场地的PCDD/F污染不构成健康风险。气体/颗粒（G/P）分布从许多不同的角度来看都是一个重大问题，包括大气沉积机制、远距离运输和健康风险。传统上，基于吸附和吸附的模型被用来定义PCDD/F G/P的分配。本研究采用Li-Ma-Yang、Dachs-Eisenreich、QSPR、pp-LFER、mp-pp-LFER五种不同的模型。在这些模型中，Li-Ma-Yang模型表现出成功的性能，并揭示了吸收和沉积机制对G/P转变的重要性。此外，pp-LFER模型总体表现良好，可以预测PCDD/F的分配。

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引用次数: 0

Investigating temporal PM2.5 exposure in relation to rapid lung-function decline among COPD patients: A retrospective study 慢性阻塞性肺病患者暴露于PM2.5时间与肺功能快速下降的关系：一项回顾性研究

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

Atmospheric Pollution Research

Pub Date : 2025-11-08 DOI: 10.1016/j.apr.2025.102822

Kang-Yun Lee , Rachel Chien , Kuan-Yuan Chen , Ying-Ying Chen , Wen-Te Liu , Po-Hao Feng , Kun-Ta Lee , Shu-Chuan Ho , Arnab Majumdar , Jiunn-Horng Kang , Wun-Hao Cheng , I-Jung Liu , Yen-Ling Chen , Cheng-Yu Tsai

Fine particulate matter (PM) is associated with chronic obstructive pulmonary disease (COPD) development, particularly the rapid-decline phenotype. However, its differential impacts across exposure periods remain unclear. In this study, we investigated associations between temporally stratified PM_2.5 exposure and lung-function decline in COPD.

A retrospective analysis was performed on data from COPD cohorts (2016–2023), including subjects with three pulmonary function tests (PFTs) conducted over at least 18 months. PM_2.5 exposure was estimated using inverse distance weighting based on residential proximity to monitoring stations. Temporal exposure was modeled via an exponentially weighted moving average (EWMA) across baseline (year before cohort entry and first PFT), early (first to second PFT), and late follow-up (second to third PFT) exposure periods. A multivariable regression was used to assess associations with lung-function decline and rapid-decline risk. The rapid-decline group (n = 59) showed significantly higher annual reductions in the forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC) than the non-rapid-decline group (n = 183). Models assigning the highest weight to the baseline exposure period demonstrated significant negative associations between PM_2.5 and annualized FEV₁ (−291.19 mL/year, p < 0.01) and FVC (−225.89 mL/year, p < 0.05). Additionally, PM_2.5 exposure was significantly linked to higher odds of a rapid decline in FEV₁ when emphasizing the baseline or late follow-up periods.

Collectively, baseline PM_2.5 exposure was associated with accelerated lung-function decline and increased risk of rapid decline, underscoring the cumulative impact of early exposure and the importance of exposure timing in COPD progression.

细颗粒物（PM）与慢性阻塞性肺疾病（COPD）的发展有关，特别是快速下降的表型。然而，其在不同暴露期的不同影响尚不清楚。在这项研究中，我们调查了时间分层PM2.5暴露与COPD肺功能下降之间的关系。对COPD队列（2016-2023）的数据进行回顾性分析，包括至少18个月进行三次肺功能测试（pft）的受试者。PM2.5暴露量的估算采用基于居民区与监测站距离的逆距离加权法。时间暴露通过指数加权移动平均（EWMA）在基线（队列进入前一年和第一次PFT），早期（第一次到第二次PFT）和后期随访（第二次到第三次PFT）暴露期间建模。使用多变量回归来评估与肺功能下降和快速下降风险的关联。快速衰退组（n = 59）的1 s用力呼气量（FEV1）和用力肺活量（FVC）的年降幅明显高于非快速衰退组（n = 183）。对基线暴露期赋予最高权重的模型显示，PM2.5与年化FEV1 （- 291.19 mL/年，p < 0.01）和FVC （- 225.89 mL/年，p < 0.05）之间存在显著的负相关。此外，当强调基线或后期随访时，PM2.5暴露与FEV1快速下降的可能性显著相关。总的来说，PM2.5基线暴露与肺功能加速下降和快速下降的风险增加有关，强调了早期暴露的累积影响和暴露时间在COPD进展中的重要性。

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引用次数: 0

Development and application of a generalized empirical model of BVOC emission (GEMBE) using observations from four Chinese forests 基于中国四种森林观测数据的BVOC排放广义经验模型（GEMBE）的建立与应用

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

Atmospheric Pollution Research

Pub Date : 2025-11-08 DOI: 10.1016/j.apr.2025.102814

Jianhui Bai , Zhixiang Wu , Chuan Yang , Alex B. Guenther

Based on the measurements of emissions of biogenic volatile organic compounds (BVOCs), solar radiation and meteorological variables in three representative forests from temperate to subtropical zone in China, a primary empirical model of BVOC emissions (EMBE) has been developed. During 2018 and 2019, BVOC emission fluxes were measured in a tropical rubber tree plantation in China, and EMBE was improved to a generalized empirical model of BVOC emissions (GEMBE) and evaluated. This paper presents GEMBE as a fully empirical modeling framework, developed directly from ecosystem-scale flux observations, and compares this approach with MEGAN, a widely-used model that includes both empirical and process-based components. Isoprene emission estimated with GEMBE, using an emission factor based on the average for other sites, overestimated the observation by 34.8 % and monoterpenes by 41.0 %. A summary of the BVOC emission fluxes in the four typical forests in China is reported. With site-specific flux measurements the GEMBE model can be used to calculate BVOC emissions in China. Using GEMBE, the responses of BVOC emissions to their driving factors showed that isoprene and monoterpene emissions were more sensitive to the change in PAR than to changes in other factors. The responses of BVOC emissions to their driving factors were discussed for the four representative forests. The emission factors (EFs) calculated using GEMBE and MEGAN were summarized for the typical forests and grassland. The MEGAN estimated isoprene EF at this rubber plantation is lower, and the monoterpene EF is higher. Both GEMBE and MEGAN showed reasonable agreement in simulations of temporal trends over one year and two years, and well reproduced the evident monthly and seasonal BVOC emissions. As a fully empirical model, GEMBE provides a framework for estimating regional BVOC emissions, and investigating their impact on atmospheric chemistry, with an alternative approach to more complex process-based models that require biophysical parameterization.

基于对中国温带至亚热带3个代表性森林的生物源性挥发性有机化合物（BVOCs）排放、太阳辐射和气象变量的测量，建立了BVOC排放的初步经验模型。2018年和2019年，对中国热带橡胶林的BVOC排放通量进行了测量，并将EMBE改进为BVOC排放的广义经验模型（GEMBE）进行了评价。本文将GEMBE作为一个完全经验的建模框架，直接从生态系统尺度的通量观测中开发出来，并将这种方法与MEGAN进行了比较，MEGAN是一个广泛使用的模型，包括经验和基于过程的组件。使用GEMBE估算异戊二烯排放量，使用基于其他站点平均值的排放因子，将观测值高估了34.8%，单萜烯高估了41.0%。本文综述了中国四种典型森林的BVOC排放通量。GEMBE模型可用于计算中国的BVOC排放量。利用GEMBE分析，BVOC排放对其驱动因素的响应表明，异戊二烯和单萜烯排放对PAR的变化比其他因素的变化更敏感。探讨了四种典型森林BVOC排放对驱动因子的响应。总结了利用GEMBE和MEGAN计算的典型森林和草地的排放因子。梅根估算该橡胶林的异戊二烯EF较低，单萜烯EF较高。GEMBE和MEGAN在一年和两年的时间趋势模拟中表现出合理的一致性，并很好地再现了明显的月度和季节性BVOC排放。作为一个完全经验的模型，GEMBE提供了一个估算区域BVOC排放的框架，并研究其对大气化学的影响，与需要生物物理参数化的更复杂的基于过程的模型相比，它是一种替代方法。

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引用次数: 0

Dust microbial contamination in typical indoor environments: Concentration, pathogenic composition and exposure assessment 典型室内环境中的粉尘微生物污染：浓度、致病性组成和暴露评估

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

Atmospheric Pollution Research

Pub Date : 2025-11-07 DOI: 10.1016/j.apr.2025.102821

Tantan Tan , Gaoshan Zhang , Ke Lu , Yanpeng Li

Indoor air quality is critically influenced by microbial contaminants in settled dust, yet existing studies predominantly focus on airborne microorganisms, leaving dust-associated microbial exposure poorly characterized. This study investigated microbial contamination in dust from four university indoor environments (offices, laboratories, dormitories, and classrooms) to assess their concentration, pathogenic composition, and human exposure risks. Dust samples were analyzed via fluorescence staining, high-throughput sequencing, and the dust daily intake model (DDIM). Results revealed significant spatial heterogeneity in microbial concentrations: dormitories exhibited the highest bacterial levels (4068.88 × 10⁴ ± 3386.55 × 10⁴ CFU/g), while offices had the highest fungal concentrations (146.16 × 10⁴ ± 152.93 × 10⁴ CFU/g). Factors such as occupancy density, cleaning frequency, and indoor plant presence are strongly associated with microbial distribution. Three dominant genera (Fusobacterium, Pseudomonas, and Corynebacterium) and four dominant fungal genera (Aspergillus, Penicillium, Fusarium, and Streptomyces) were observed in all indoor dust samples, with a potential risk of association with respiratory diseases and skin infections. Exposure assessment indicated that dust ingestion dominated microbial intake, with dormitories posing the highest bacterial exposure (EDI up to 35,086 CFU/(kg·day)) and offices the highest fungal exposure (EDI up to 1263 CFU/(kg·day)). These findings highlight the urgent need for targeted interventions, such as improved ventilation, regular cleaning, and microbial monitoring, to mitigate health risks in high-exposure indoor environments. This study provides a scientific foundation for refining indoor air quality standards and safeguarding occupants in densely populated educational settings.

室内空气质量受到沉降尘埃中的微生物污染物的严重影响，但现有的研究主要集中在空气中的微生物上，使得与灰尘相关的微生物暴露缺乏特征。本研究调查了四所大学室内环境（办公室、实验室、宿舍和教室）粉尘中的微生物污染，以评估其浓度、致病成分和人类暴露风险。通过荧光染色、高通量测序和粉尘日摄入量模型（DDIM）对粉尘样品进行分析。结果表明，各办公室微生物浓度存在明显的空间差异，其中宿舍最高（4068.88 × 104±3386.55 × 104 CFU/g），办公室最高（146.16 × 104±152.93 × 104 CFU/g）。诸如占用密度、清洁频率和室内植物存在等因素与微生物分布密切相关。在所有室内粉尘样本中观察到3个优势属（梭杆菌、假单胞菌和杆状杆菌）和4个优势真菌属（曲霉、青霉菌、镰刀菌和链霉菌），具有与呼吸道疾病和皮肤感染相关的潜在风险。暴露评估表明，灰尘摄入主要是微生物摄入，宿舍的细菌暴露最高（EDI高达35,086 CFU/(kg·day)），办公室的真菌暴露最高（EDI高达1263 CFU/(kg·day)）。这些发现突出表明，迫切需要有针对性的干预措施，如改善通风、定期清洁和微生物监测，以减轻高暴露室内环境中的健康风险。本研究为完善室内空气质量标准和保护人口密集的教育环境中的居住者提供了科学依据。

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引用次数: 0