Air Quality Atmosphere and Health最新文献

{"title":"Overcoming monitoring gaps: multi-sensor satellite fusion and machine learning for high-resolution PM₂.₅ prediction in Lahore, Pakistan","authors":"Muhammad Haseeb,&nbsp;Zainab Tahir","doi":"10.1007/s11869-026-02119-w","DOIUrl":"10.1007/s11869-026-02119-w","url":null,"abstract":"<div><p>Air-quality monitoring in Lahore remains constrained by the limited availability of continuous, publicly accessible ground-based PM₂.₅ observations, despite substantial spatial variability across the city, even though pollution varies sharply across the city’s dense urban and industrial neighborhoods. To overcome this gap, we developed a fused satellite–machine learning framework capable of generating 250-m PM₂.₅ maps, significantly enhancing the spatial detail of the coarser 1-km EDGAR (Emissions Database for Global Atmospheric Research) dataset used for training. The model integrates a comprehensive multi-sensor dataset combining Sentinel-5P atmospheric pollutants (CO, NO₂, SO₂, UVAI), MODIS aerosol optical depth (AOD), Sentinel-2 vegetation and built-up indices (NDVI, NDBI), industrial and road-density layers, Digital Elevation Model (DEM), and EDGAR PM₂.₅ from 2020 to 2023. After harmonizing the predictors into a unified monthly grid, the XGBoost model achieved high internal predictive performance against the EDGAR target under an 85:15 random train–test split (test R² = 0.990; RMSE = 3.63 µg/m³; MAE = 1.50 µg/m³). However, stricter leave-one-month-out temporal validation showed season-dependent generalization, held-out-month R² ranging from 0.30 to 0.92; performance was strongest during winter and weaker during transitional months. Feature-importance and SHAP analyses identified NO₂, CO, AOD, and UVAI as the dominant predictors, while industrial density provided a secondary spatial contribution, underscoring the central role of traffic emissions, industrial clusters, and winter inversion conditions in Lahore’s smog dynamics. The predicted PM₂.₅ fields for 2024 successfully reproduced the city’s characteristic seasonal cycle, capturing intense winter pollution and cleaner monsoon months while revealing model-derived fine-scale spatial contrasts not represented in the native 1-km target. Point-scale validation against the U.S. Consulate monitoring station demonstrated strong temporal correspondence, with Pearson <i>r</i> = 0.874 for EDGAR versus ground observations during 2020–2023 and <i>r</i> = 0.889 for the 2024 predictions versus ground observations. However, substantial systematic underestimation was observed, with mean biases of − 76.8 µg/m³ and − 79.8 µg/m³, respectively, indicating that the framework reproduces seasonal and temporal variability more reliably than absolute concentration magnitude. A single-station bias-correction test substantially reduced magnitude error, but because calibration was based on only one monitoring site, the 250-m outputs should presently be interpreted primarily as spatially refined relative-pattern estimates rather than fully calibrated neighbourhood-level exposure fields. Citywide regulatory or health-risk applications require denser ground-based validation and multi-site calibration.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149133002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Worker exposure to particulate matter and volatile organic compounds during semiconductor failure analysis: assessment of local exhaust ventilation using field measurements and computational fluid dynamics","authors":"Yongsoon Park,&nbsp;Moung-hun Choung,&nbsp;Ji-seck Oh,&nbsp;Haeng-sub Roh,&nbsp;Chankyu Kang","doi":"10.1007/s11869-026-02123-0","DOIUrl":"10.1007/s11869-026-02123-0","url":null,"abstract":"<div><p>Manual wafer cutting during semiconductor failure analysis generates particulate matter (PM), volatile organic compounds (TVOCs), and process odors that may contribute to worker inhalation exposure. This study evaluated PM and TVOC exposure conditions during wafer cutting and examined how a hybrid containment workbench (HCW) modified airflow patterns that may influence contaminant movement toward the worker breathing zone. PM and TVOC measurements were used to characterize exposure conditions during wafer-cutting operations, while airflow measurements, steady-state CFD analysis, qualitative smoke visualization, and worker questionnaires were used to evaluate changes associated with HCW implementation. Airflow characteristics were analyzed using computational fluid dynamics (CFD), quantitatively compared with measured air velocities, and qualitatively evaluated using smoke visualization. Worker questionnaires assessed perceived odor and dust exposure before and after HCW installation. TVOC concentrations observed during patterned-wafer cutting (0.12–0.15 mg/m³) were higher than those observed during bare-wafer cutting (0.02–0.03 mg/m³). CFD-predicted air velocities showed relative errors of 5.3–18.2% compared with the experimentally measured velocities. The HCW produced airflow directed toward the rear exhaust system, and reduced recirculation was observed near the breathing zone. Smoke visualization showed a similar airflow pattern. These findings indicate airflow conditions that may reduce the potential for contaminant movement toward the operator. Before HCW installation, 84.2% of workers (16/19) reported process odor perception, while worker-rated odor and dust control scores improved following HCW implementation. The results indicate that local airflow should be considered together with contaminant concentrations when evaluating worker exposure and local exhaust ventilation in semiconductor failure-analysis laboratories.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149133003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-severity environmental alarms as reference signals: Evidence from Beijing’s first red haze alerts","authors":"Wei Wang,&nbsp;Boyuan Lu,&nbsp;Xiuling Zhang,&nbsp;Xinran Fan,&nbsp;Weisheng Zhang","doi":"10.1007/s11869-026-02117-y","DOIUrl":"10.1007/s11869-026-02117-y","url":null,"abstract":"<div><p>Self-reported estimates of air pollution often diverge from monitoring-station data, which has implications for risk communication, public trust, and emergency response. Whether high-severity official alerts can narrow this estimation gap among the people who receive them, however, remains poorly understood. The first issuance of red-level haze alerts in Beijing in December 2015 provides a rare quasi-natural experiment to examine this question. Combining official air-quality monitoring data with a survey experiment of 947 university students randomly assigned to report their perceptions of pollution conditions either before or after the red-level alerts, we estimate the impact of the red haze alert on (i) the gap between students’ self-reported and monitored pollution levels, (ii) their evaluations of government mitigation efforts, and (iii) their self-reported protective behavior. Among students who reported awareness of the alert, mean overestimation relative to monitoring values fell from + 49.90% to + 30.53% for PM₂.₅ concentrations and from + 178.89% to + 87.43% for yellow-level haze days. Multivariate models confirm these reductions (19–27% for PM_2.5 overestimation; 92–147% for yellow-level pollution days overestimation). However, shifts in evaluations of government efforts were selective based on measure visibility: only the highly visible vehicle restriction policy was more likely to be recognized, while assessments of factory shutdowns, urban greening, and restaurant regulations did not change. Protective behaviors showed modest but statistically insignificant changes, and gender had no significant effect on overestimation. Overall, these findings reveal that environmental alerts can narrow the gap between self-reported and monitored pollution levels during severe pollution episodes, but sustaining public trust requires pairing warning signals with transparent and well-communicated policy action.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linking human respiratory tract dose from diesel exhaust particles to lung tumor responses observed in rats","authors":"Sofia Eirini Chatoutsidou,&nbsp;Eleftheria Chalvatzaki,&nbsp;Eleni Mammi-Galani,&nbsp;Lila Diapouli,&nbsp;Maria I. Gini,&nbsp;Manousos I. Manousakas,&nbsp;Maria-Iosifina Kasdagli,&nbsp;Evangelia Samoli,&nbsp;Klea Katsouyanni,&nbsp;Kostas Eleftheriadis,&nbsp;Mihalis Lazaridis","doi":"10.1007/s11869-026-02115-0","DOIUrl":"10.1007/s11869-026-02115-0","url":null,"abstract":"<div><p>Traffic generated nanoparticles are toxic and linked with carcinogenicity. This work estimated lung deposition and clearance from exposure to diluted diesel exhaust and urban particles. Besides lungs, dosimetry simulations included estimations for clearance and translocation of particles to the other regions of the respiratory tract and to different parts of the human body (lymph nodes, oesophagus, blood). An 8 h per day inhalation of diesel particles was considered to better approximate occupational exposure with the remaining 16 h resulting from exposure to urban particles. Simulation showed that 86% of nanoparticles were deposited into lungs after 1 day, highlighting the relative burden of lungs compared to the rest of the respiratory tract. Different receptors (male/female, inhalation rate, weight) were examined to investigate variations in the deposited dose. Long-term lung response was modeled by exponential functions whereby the retained dose was used to estimate the equivalent dose for rats. Accordingly, the long-term retained dose was in the same order of magnitude for the different receptors investigated and was linked with the same exposure conditions considered. Conversion to lung rat dose by implementation of allometric scaling showed that the equivalent dose in rats lied in the lower region for carcinogenicity. Specifically, in vivo toxicological data suggested a 2.42% (95% CI: 0.073–6.12%) for carcinogenicity in rat lugs based on the equivalent retained dose modeled for human lungs. These results highlight the potential adverse impact from long-term exposure to diesel exhaust particles.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11869-026-02115-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From atmospheric loading to passive smoking: Black Carbon exposure as a health risk indicator in Medellín, Colombia","authors":"D. A. Grajales-González,&nbsp;J. E. Cañón-Barriga,&nbsp;M. Gómez-Marín,&nbsp;E. P. Blanco-Donado,&nbsp;O. Ramírez","doi":"10.1007/s11869-026-02116-z","DOIUrl":"10.1007/s11869-026-02116-z","url":null,"abstract":"<div><p>Equivalent black carbon (eBC) remains poorly characterized in topographically confined tropical cities despite its relevance as a combustion tracer and health risk indicator. This study examines five years of continuous eBC measurements (2019–2023) at an urban background site in Medellín, Colombia, integrating spectral source apportionment, a passive smoking equivalence framework, and a spatial gradient analysis between background and near-road environments to characterize urban BC exposure across contrasting emission regimes. The COVID-19 mobility restrictions revealed that while median concentrations declined 37%, the temporal exposure structure remained intact even under maximum suppression, 56.1% of hourly observations still exceeded 1 µg m^− 3. Fossil fuel combustion dominated across all periods (mean AAE = 1.05 ± 0.12), with biomass burning acting as an episodic regional modifier. The baseline urban exposure was found to be 10.1 passive cigarette equivalents per day, declining to 6.3 during the restriction period and rebounding to 8.0 post-restriction. It is estimated that between 78 and 198 cardiovascular deaths were averted during the restriction period, depending on the concentration–response scenario assumed. The near road to background concentration ratio expanded from 3.6 before restriction to 4.66 post-restriction, indicating that spatial exposure heterogeneity within the valley widened rather than contracted after the perturbation. These results demonstrate that continuous aethalometer deployments at urban background sites, complemented by near-road monitoring, provide a viable and reproducible framework for characterizing BC exposure structure in tropical cities with limited observational infrastructure.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of indoor airflow with sleep quality and duration in Chinese older adults","authors":"Cai Xu,&nbsp;Deidra Newville,&nbsp;Yen-Han Lee","doi":"10.1007/s11869-026-02104-3","DOIUrl":"10.1007/s11869-026-02104-3","url":null,"abstract":"<div><p>Sleep is essential for healthy aging, yet population-level evidence on seasonal household window-opening patterns and sleep among older adults remains limited. This study examined associations between household window-opening patterns and sleep-related outcomes among Chinese older adults, with attention to rural–urban differences. We analyzed cross-sectional data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). Latent class analysis (LCA) identified household window-opening patterns based on seasonal variation in window-opening frequency. Associations with sleep quality and duration were examined using logistic and linear regression models, with rural–urban differences assessed using interaction terms. Among 10,128 older adults, 52.86% reported good sleep quality, and mean sleep duration was 7.46 h/day (SD = 2.36). LCA identified three distinct window-opening patterns: <i>Frequent Year-Round Window Opening</i> (70.29%), <i>Infrequent Window Opening</i> (18.52%), and <i>Summer-Predominant Window Opening</i> (11.19%). Compared with <i>Infrequent Window Opening</i>, both <i>Summer-Predominant Window Opening</i> (OR = 1.18, 95% CI: 1.02–1.38, <i>p</i> = 0.03) and <i>Frequent Year-Round Window Opening</i> (OR = 1.24, 95% CI: 1.12–1.38, <i>p</i> &lt; 0.001) were associated with higher odds of good sleep quality. <i>Frequent Year-Round Window Opening</i> was also associated with longer sleep duration (β = 0.35 h/day, SE = 0.06, <i>p</i> &lt; 0.001). The association between <i>Frequent Year-Round Window Opening</i> and good sleep quality was stronger among urban residents (interaction OR = 1.36, 95% CI: 1.10–1.68, <i>p</i> &lt; 0.01). Window-opening patterns were associated with sleep quality and duration, with some variation by residential context. These findings should be interpreted cautiously given the observational design and lack of objective measures of indoor air exchange.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11869-026-02104-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 25-year analysis of aerosol optical depth dynamics over Nigeria (2000–2024): spatial-temporal dynamics, seasonal regimes, and extreme event characterization","authors":"Ekpenyong Ekpenyong Ekpe,&nbsp;Chong Shi,&nbsp;Shuai Yin,&nbsp;Hengqi Wang,&nbsp;Yuxin Zhao,&nbsp;Husi Letu,&nbsp;Md Zia Uddin Raihan","doi":"10.1007/s11869-026-02111-4","DOIUrl":"10.1007/s11869-026-02111-4","url":null,"abstract":"&lt;div&gt;&lt;p&gt;Aerosol optical depth (AOD) significantly influences climate systems, air quality, and public health. The recent availability of long-term ground observations presents an unprecedented opportunity to characterize aerosol properties and establish a robust climatological baseline for Nigeria’s aerosol science. This study presents a bias-corrected, boundary-clipped 25-year daily MODIS Terra AOD record for Nigeria (2000–2024). The dataset was constructed using a Gradient Boosting Quantile Regression (GBR-q50) framework trained on fourteen AERONET sites across nine West African countries. At the Nigeria-Ilorin site, the GBR-q50 correction reduced the raw MODIS mean bias from &lt;span&gt;(:-0.252)&lt;/span&gt; to &lt;span&gt;(:-0.015)&lt;/span&gt; and improved expected-error (EE) agreement from 23.0% to &lt;span&gt;(:95%)&lt;/span&gt;, with the leave-one-site-out spatial test yielding EE = 74.5%. While the 25-year national annual linear trend is not statistically significant (slope &lt;span&gt;(:-0.0020:{yr}^{-1},:p=0.226))&lt;/span&gt;, seasonal decomposition revealed a small, suggestive dry season decline (&lt;span&gt;(:-0.0043:{yr}^{-1};:approx:16%)&lt;/span&gt; reduction). This decline is near significant under lag-1 pre-whitening (&lt;i&gt;p&lt;/i&gt; = 0.059), indicating an indicative rather than conventionally significant trend. It is contrasted by only a marginal, non-significant wet-season decrease &lt;span&gt;(:(-0.0012:{yr}^{-1},:p=0.082))&lt;/span&gt;. The monthly climatology is predominantly unimodal, peaking in February &lt;span&gt;(:left(0.865right))&lt;/span&gt; and reaching a minimum in November &lt;span&gt;(:left(0.370right))&lt;/span&gt;. Unsupervised K-means clustering classified daily aerosol states into three distinct regimes: Clean (57.7% of days; mean AOD: 0.399), Transitional (31.6%; mean AOD: 0.647), and Extreme (10.7%; mean AOD: 1.163). Extreme events are heavily concentrated in the dry season, occurring on 18.1% of dry-season days compared to just 3.2% of wet-season days. Empirical return periods were estimated at 12.5 days (Exceedances: 711; 95% CI: 11.6–13.4) for AOD &gt; 1.0, 61 days (Exceedances: 145; 95% CI: 52.1–72.0) for AOD &gt; 1.5, and 6.06 years (Exceedances: 4; 95% CI: 3.03–24.25) for AOD &gt; 2.0, providing climatological recurrence benchmarks relevant for atmospheric hazard characterization. Global spatial autocorrelation analysis yielded a Moran’s I of 0.949 (&lt;span&gt;(:p=0.001,:z=163.9))&lt;/span&gt; confirming highly significant positive spatial clustering. Local Indicators of Spatial Association (LISA) identified 40.1% of grid cells as significant after false-discovery-rate correction revealing a stable High-High hotspot belt across the Southern/Southwestern Nigeria and Low-Low spots in the Northeast. Temporal memory analysis demonstrated a strong lag-1 daily autocorrelation of 0.75 that decayed to 0.21 by lag 30, supporting short-range predictability; an ARIMA (2,0,2) model successfully captured these synoptic dynamics (pseudo &lt;span&gt;(:{R}^{2}=0.58)&lt;/span&gt;). These findings establish a rigorous, long-term atmospher","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tobacco and substitute use, secondhand smoke exposure, and serious injuries among adolescents: A multinational analysis of 58 countries","authors":"Manman Chen,&nbsp;Zichen Ye,&nbsp;Yuankai Zhao,&nbsp;Yimin Qu,&nbsp;Xijie Wang,&nbsp;Wanzhou Wang,&nbsp;Mengyue Gu","doi":"10.1007/s11869-026-02112-3","DOIUrl":"10.1007/s11869-026-02112-3","url":null,"abstract":"<div><p>Serious injuries remain a leading cause of adolescent mortality worldwide, yet evidence on their associations with behavioral and environmental factors is limited. Using data from 176,635 adolescents aged 12–17 years across 58 countries in the Global School-based Student Health Survey (2013–2019), this study examined the associations of tobacco and substitute use and secondhand smoke exposure with reported serious injury occurrence, as well as whether these associations differed across country-level PM_2.5 groups. Injury outcomes and causes were assessed through standardized questionnaires, and multivariable logistic regression models were applied, with subgroup analyses by sex and country-level PM_2.5 concentration. The prevalence of serious injuries was 38.99%, and was higher among boys (45.60%) than girls (33.32%). Current tobacco and substitute use (OR = 2.07, 95%CI 1.95–2.19) and secondhand smoke exposure among non-smokers (OR = 1.43, 95%CI 1.37–1.49) were associated with higher odds of reported serious injury occurrence in the primary analysis. After additional adjustment for survey year, the association for current tobacco and substitute use was attenuated but remained statistically significant (OR = 1.49, 95%CI 1.44–1.55), whereas the estimate for secondhand smoke exposure was largely unchanged. Stratified analyses showed slightly higher association estimates among girls and in the high-PM_2.5 country group; most subgroup differences were not statistically significant, although secondhand smoke exposure among girls showed a stronger association with serious injury in the high-PM_2.5 group (<i>P</i> for subgroup difference &lt; 0.001). These findings highlight the substantial burden of adolescent serious injuries and identify active and passive tobacco exposure as factors associated with reported serious injury occurrence, with some variation in the magnitude of associations across sex and country-level PM_2.5 groups.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy mix, technological innovation, and air quality nexus: A STIRPAT-extended analysis using machine learning and econometric techniques","authors":"S. Arafat Ayon,&nbsp;Mohammad Ridwan,&nbsp;Md. Emran Hossain,&nbsp;Md. Istiak Hossain Joy,&nbsp;Mohd Ziaur Rehman,&nbsp;Miguel Angel Esquivias","doi":"10.1007/s11869-026-02103-4","DOIUrl":"10.1007/s11869-026-02103-4","url":null,"abstract":"<div><p>Fine particulate matter (PM2.5) pollution remains a critical global public health concern. Hence, this study investigates the determinants of PM2.5 concentration across G7 and EU nuclear-consuming countries from 1990 to 2021, focusing on the roles of energy supply mix, economic development, and technological innovation. Energy mix is operationalized as the disaggregated, source-specific elasticities of coal, oil, nuclear, and biofuels and their interactions with income and innovation, rather than a single composite diversification index. We combine panel regression methods with XGBoost machine learning and SHAP (Shapley Additive Explanations) to capture both linear and nonlinear relationships. The baseline model applies fixed-effects estimation with Driscoll–Kraay standard errors, while quantile regression and Feasible Generalized Least Squares (FGLS) are used for robustness. The results identify coal as the dominant driver of PM2.5 pollution, with a 1% increase in coal use raising levels by approximately 0.22%. Oil consumption also increases pollution, though to a lesser extent. In contrast, nuclear energy consistently reduces PM2.5 levels, while biofuels contribute to emission reductions only at higher adoption levels. Economic growth follows an inverted U-shaped pattern, supporting the Environmental Kuznets Curve hypothesis, a finding reinforced by SHAP analysis. Innovation activity significantly mitigates pollution across all models, and urbanization is associated with lower emissions in advanced economies. SHAP further reveals nonlinear dynamics, including S-shaped patterns for oil and inverted S-shaped relationships for biofuels, that traditional methods cannot capture. The findings point to four key policy priorities: accelerating coal phase-out, scaling biofuel adoption above critical thresholds, cautiously expanding nuclear capacity while monitoring diminishing returns at high penetration levels, and linking energy transitions to innovation investment for sustained air quality gains.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Key modulation of PM2.5–O3 responses to emission reductions by sea–land breeze in coastal megacities","authors":"Kexin Liu,&nbsp;Lin Wu,&nbsp;Miaomiao Lu,&nbsp;Xiao Tang,&nbsp;Lei Kong,&nbsp;Yufen Zhang,&nbsp;Zifa Wang","doi":"10.1007/s11869-026-02038-w","DOIUrl":"10.1007/s11869-026-02038-w","url":null,"abstract":"<div><p>This study quantifies the impacts of emission controls (2017–2020) and meteorology on PM_2.5 and ozone (O₃) under sea–land breeze (SLB) circulation in coastal Tianjin using observations and the WRF–NAQPMS model. Emission reductions contributed to a PM_2.5 decline (− 7.1 µg m^–3), primarily from carbonaceous components and sulfate, but tiggered an O₃ increase (+ 24.5 µg m^–3) (net observed rise: +23.0 µg m⁻³). Annual meteorological contributions were − 1.7 µg m^–3 for PM_2.5 and − 1.4 µg m^–3 for O₃. However, these averages masked substantial variations across circulation regimes. Sea breeze days were the only type in which meteorology increased O₃, contributing + 2.2 µg m^–3, while offsetting PM_2.5 reductions by 5.1 µg m^–3. Concurrent increases in nitrate and EC were also observed during sea-breeze periods. On LB days, interannual meteorological changes favored PM_2.5 reduction, with meteorology contributing − 32.70 µg m^–3, accompanied by substantial reductions in nitrate and EC, much larger than the annual mean PM_2.5 decline. Under stagnant stable conditions, meteorological factors were the primary driver of the interannual PM_2.5 increase, contributing + 30.80 µg m^–3, with PM_2.5 peaks exceeding 150 µg m^–3 even under the mitigating effect of emission reductions. Diurnal asymmetry was pronounced: daytime sea breezes dominated O₃ production, whereas nocturnal land-breeze stage favored pollutant accumulation and secondary formation. Regime-specific meteorological contributions were much larger than annual averages, demonstrating that SLB fundamentally modulates pollutant responses and highlighting the need for circulation-specific co-control strategies in coastal megacities.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}