Air Quality Atmosphere and Health最新文献

{"title":"Gender-specific association between PM2.5 exposure and cognitive function in middle-aged and elderly chinese: Evidence from CHARLS","authors":"Man Quan,&nbsp;Jing Cui,&nbsp;Yukui Chen,&nbsp;Jiayi Hao,&nbsp;Chenshu Ge,&nbsp;Xiaomei Li,&nbsp;Juan Wang,&nbsp;Duolao Wang,&nbsp;Leilei Pei,&nbsp;Yijun Kang,&nbsp;Lu Ye","doi":"10.1007/s11869-026-01975-w","DOIUrl":"10.1007/s11869-026-01975-w","url":null,"abstract":"<div>\u0000 \u0000 <p>With rapid industrialization and urbanization in China, ambient air pollution—particularly PM_2.5—has become a major public health concern. Existing evidence suggests that chronic exposure to fine particulate matter may contribute to neurodegenerative processes and cognitive decline, yet the sex-specific effects remain underexplored, especially in vulnerable aging populations. This study aimed to assess the gender-specific impact of PM_2.5 exposure intensity and duration on cognitive function in the middle-aged and elderly Chinese population, identify higher risk groups for cognitive impairment, and offer insights into strategies for prevention and early intervention. Integrated datasets from the China Health and Retirement Longitudinal Study (CHARLS) for adults aged 45 to 96 and PM2.5 exposure data from 2001 to 2018 through satellite observations. Cognitive function was evaluated using the CHARLS-HCAP Neurocognitive Test Scale. We employed linear mixed-effects quantile regression models to investigate gender-specific disparities in the association between PM2.5 exposure intensity and duration and cognitive function across diverse cognitive levels. The models were adjusted for demographic, lifestyle, socioeconomic factors, and medical history. Among 17,147 participants contributing 45,242 observations, higher PM2.5 exposure intensity and extended duration were associated with reduced cognitive function in both genders (females: q ≥ 0.66, males: q ≥ 0.96). Notably, these associations were more pronounced among females than males at the same cognition score quantiles. In participants with no or mild cognitive impairment, females exhibited lower cognitive function scores due to higher PM2.5 exposure intensity and prolonged duration (PM2.5 levels ≥ 36 µg/m3) compared to males. These findings indicated differing impacts of PM2.5 exposure on cognitive function relative to gender and cognitive status. These results supported existing evidence of gender-specific differences in the impact of PM2.5 exposure on cognitive decline, identifying females with no or with mild cognitive impairment as the most vulnerable subgroup due to PM2.5 exposure.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642879","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":"Prediction of influencing factors of PM2.5 in the Yellow River Basin based on Bayesian iterative Dirichlet model","authors":"Jingya Liu,&nbsp;Weifu Ding,&nbsp;Lifen Chen,&nbsp;Hangzhi Yu","doi":"10.1007/s11869-026-01977-8","DOIUrl":"10.1007/s11869-026-01977-8","url":null,"abstract":"<div>\u0000 \u0000 <p>This study first constructs a Geographically Weighted Random Forest (GW-RF) model to analyze the importance scores and spatial distribution of the factors influencing PM_2.5 concentrations across 76 cities in the Yellow River Basin from 2017 to 2022. Subsequently, we developed a Bayesian Iterative Dirichlet Model (BIDM). In this model, the Dirichlet distribution describes the prior probability distribution of the key factors affecting PM_2.5 concentrations. The key influencing factors identified by the GW-RF model then establish a state transition matrix. The columns and vectors of this matrix serve as the observation count vectors for the likelihood function, which derives from the multinomial distribution of these observation count vectors. Finally, Bayesian inference forecasts the probability of occurrence of these key factors in future PM_2.5 concentrations across cities in the Yellow River Basin. The results indicate that: (1) During the study period, the monthly average PM_2.5 concentration in the Yellow River Basin exhibited a distinct “U” shaped curve, with annual average concentrations showing a downward fluctuation. Spatially, a “higher in the east and lower in the west” distribution pattern appeared. (2) The importance scores of factors influencing PM_2.5 concentrations in the cities of the Yellow River Basin reveal that local PM₁₀ concentration and surrounding urban PM_2.5 concentration have relatively high importance scores, with average values of 0.5602 and 0.4254, respectively. Local CO and NO₂ concentrations also exert some influence on PM_2.5 concentrations, with their average values ranging from 0.2145 to 0.3438. In contrast, meteorological factors have a relatively weak impact on PM_2.5 concentrations. (3) The key factors influencing future PM_2.5 concentrations in the Yellow River Basin are local PM₁₀ concentration, surrounding urban PM_2.5 concentration, and local CO concentration, with predicted probabilities ranging from 0.3000 to 0.5907, 0.2353 to 0.4783, and 0.0591 to 0.1478, respectively.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642471","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":"The impact of urban trees on temperature, humidity, noise, and particulate matter in Chattogram City, Bangladesh","authors":"Tonima Hossain,&nbsp;Mehedi Hasan Rakib,&nbsp;Shyamal Karmakar,&nbsp;Mohammed Shafiul Alam,&nbsp;Tarit Kumar Baul,&nbsp;Tapan Kumar Nath","doi":"10.1007/s11869-026-01971-0","DOIUrl":"10.1007/s11869-026-01971-0","url":null,"abstract":"<div>\u0000 \u0000 <p>The advent of personal transportation, industrial and construction activity in urban areas and growth center, air and noise pollution become increasing concerns to urban environmental health. The reduction of green spaces in urban environments has intensified these environmental issues. However, there is a lack of integrated research in Bangladesh that investigates the effects of urban vegetation on particulate matter (PM) concentration, noise pollution, temperature, and humidity levels. In this study, we aimed to assess the effects of urban trees on atmospheric PM concentration, noise levels, temperature, and humidity across residential, roadside, and industrial sites of Chattogram city, Bangladesh. We measured atmospheric PM_2.5 and PM_0.5 and noise levels in three vegetated and three non-vegetated sites under residential, industrial, and roadside areas on weekdays and weekends from August 2023 to July 2024. We also collected leaves from five tree species over 12 months to quantify the variation in PM deposition on tree leaves. To see variations in temperature and humidity in the vegetated and non-vegetated areas, temperature and humidity data were recorded for the same year. This study demonstrated that the presence of vegetation can significantly (<i>p</i> ≤ 0.05) reduce levels of PM, temperature, and noise, while simultaneously increasing relative humidity, which has cooling effects in urban environments, compared to the non-vegetated sites. Atmospheric PM concentration (PM_0.5 and PM_2.5) was negatively correlated with outdoor temperature but positively correlated with relative humidity. Among five tree species, <i>Ziziphus mauritiana</i> accumulated the highest amount of PM, and <i>Polyalthia longifolia</i> the lowest in all sites; these accumulations were affected by leaf shape and surface as well as site with tree densities. These findings highlight urban greening as a successful, locally based intervention for enhancing urban air quality and microclimate.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642472","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":"Mineralogical profiling of fine particulate matter (PM2.5) over the Megacity Delhi and the Central Himalayan Region Nainital, India","authors":"Anjali Rana,&nbsp;Preeti Tiwari,&nbsp;Priyanka Srivastava,&nbsp;Sakshi Gupta,&nbsp;Manish Naja,&nbsp;Surinder P. Singh,&nbsp;Sudhir Kumar Sharma,&nbsp;Sachchidanand Singh","doi":"10.1007/s11869-026-01964-z","DOIUrl":"10.1007/s11869-026-01964-z","url":null,"abstract":"<div>\u0000 \u0000 <p>Mineral dust aerosols constitute dominant fraction of atmospheric particles, so it is crucial to undertake an in-depth analysis to unravel their various physical attribute. This study investigates the mineralogical composition of the fine particulate matter (PM_2.5) using Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) and X-ray Diffraction (XRD) analytical techniques for megacity Delhi and Himalayan region of Nainital from January to December 2023. PM_2.5 concentrations were critically high in Delhi (109 ± 70.9 µg m⁻³), while levels in Nainital (34 ± 12 µg m⁻³) remained near the threshold at National Ambient Air Quality Standards (NAAQS). ATR-FTIR analysis revealed the presence of albite, calcite, dolomite, gypsum, hematite, magnetite and quartz minerals in PM_2.5 samples indicating geogenic, anthropogenic and biogenic sources. Further validation was done by using XRD to understand the various mineral phases present in the particulate matter (PM) which included calcite, quartz, montmorillonite, illite, hematite, magnetite, kaolinite, cerussite and other. Particular emphasis is placed on detecting dominating minerals crystalline phases identified in PM_2.5 including calcite, quartz, illite, montmorillonite, kaolinite, hematite and magnetite. Crystallite size was computed which ranged from ~ 11 nm to 55 nm. Also, the XRD analysis enabled the calculation of crystallinity percentage ranging from for Delhi (20.03–60.80%) and Nainital (23.17–53.05%) indicating heterogeneous formation pathways. Trajectory cluster analysis revealed strong seasonal variability in air-mass transport at both sites, with Delhi largely influenced by Indo-Gangetic Plain and transboundary pathways. Nainital exhibited a mix of transboundary, regional, and local influences, with Indo-Gangetic Plain (IGP) transport dominating air masses. The comprehensive approach for mineral identification and assessment of the physical properties under the present study can help better understand the behaviour of particulate matter for these locations.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642542","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":"Revisiting trace metal pollution, sources, and risks in road dust from Dhaka megacity, Bangladesh","authors":"Md. Eusuf Sarker,&nbsp;Sumaya Nasrin,&nbsp;Mir Md. Mozammal Hoque,&nbsp;Md Sariful Islam,&nbsp;Yeasmin Nahar Jolly,&nbsp;Shirin Akhter,&nbsp;Abu Sayed Md. Faysal,&nbsp;Mehedi Hasan Jony,&nbsp;Nafis Wadud,&nbsp;Tanmoy Roy Tusher","doi":"10.1007/s11869-026-01967-w","DOIUrl":"10.1007/s11869-026-01967-w","url":null,"abstract":"<div>\u0000 \u0000 <p>Dhaka megacity, characterized by dense population, rapid urbanization, and intense vehicular and industrial activities, faces growing concerns over trace metal pollution in its urban environment. This study comprehensively assessed the levels, spatial patterns, potential sources, and ecological and human health risks of trace metals in road dust across the city. Ninety samples from thirty high-traffic locations were analyzed for Ti, Cr, Mn, Fe, Ni, Cu, As, Zn, Rb, Sr, Zr, and Pb using energy-dispersive X-ray fluorescence spectroscopy. Multiple pollution indices, GIS-based mapping, and multivariate statistical tools were employed to evaluate pollution status, identify hotspots and possible sources. Results revealed severe contamination by As, Cr, Cu, and Pb, with Gabtoli and Kawran Bazar emerging as major hotspots. Source apportionment indicated predominantly anthropogenic origins, particularly vehicular exhaust, non-exhaust emissions, and industrial activities. Ecological risk assessment showed low overall risk, but As posed the highest potential threat to ecosystems. While most metals presented non-carcinogenic risks within acceptable limits, Fe and Zr exceeded safety thresholds for certain exposure groups, and carcinogenic risk analysis revealed alarming vulnerability in children, especially from As, Cu, Cr, and Pb. These findings highlight the urgent need for targeted pollution control strategies to safeguard environmental and public health in Dhaka.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642541","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":"Carbonaceous signatures of ambient particles down to ultrafine particles (PM0.1) across upper Southeast Asia: linking biomass burning, urban emissions and transboundary exposure","authors":"Worradorn Phairuang,&nbsp;Sotasing Ho,&nbsp;Chanreaksmey Taing,&nbsp;Srean Aun,&nbsp;Leakhena Hang,&nbsp;Thaneeya Chetiyanukornkul,&nbsp;Phuchiwan Suriyawong,&nbsp;Phakphum Paluang,&nbsp;Mai Kai Suan Tial,&nbsp;Aye Myat Kyi Phyu,&nbsp;April Nway Nway Htet,&nbsp;Zaw Htet Myint,&nbsp;Masami Furuuchi","doi":"10.1007/s11869-026-01981-y","DOIUrl":"10.1007/s11869-026-01981-y","url":null,"abstract":"<div>\u0000 \u0000 <p>Air pollution in Mainland Southeast Asia (MSEA) threatens human health and the environment, making it urgent. This study investigates size-fractionated carbonaceous particulate matter (PM) down to PM_0.1. Ambient PMs in six size fractions (PM_&gt; 10, PM_2.5−10, PM_1.0−2.5, PM_0.5−1.0, PM_0.1−0.5, and PM_&lt; 0.1) were collected from 4 sites in Phnom Penh, Cambodia; Chiang Mai, Thailand; and Yangon and Mandalay, Myanmar, during a haze episode (March 2020) using an Ambient Nano-Sampler. Analysis of carbon content yielded organic carbon (OC1-OC4), elemental carbon (EC1-EC3), and pyrolytic organic carbon. The average PM mass concentrations and carbon contents were higher in Myanmar than in Thailand and Cambodia. The dominant markers for biomass burning, OC3, and EC1, were observed across all fine particles in three countries. The elevated char-EC/soot-EC ratios in PM_0.5−1.0 are consistent with biomass burning, especially in biomass fires in Chiang Mai and Mandalay. These indicate that biomass fires were the primary contributors to PMs in this region. The findings are consistent with the elevated primary OC in the smaller PM compared to the larger PM. The smaller particles are attributed to direct emissions from regional biomass fires. Referring to the effective carbon ratio, smaller PMs absorb energy and warm the atmosphere during smoke haze in MSEA.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606707","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":"Health risks and oxidative toxicity of size-resolved PAHs in fine and ultrafine particles from a megacity atmosphere","authors":"Molla Nageswar Rao,&nbsp;Atar Singh Pipal,&nbsp;Rakesh P.S,&nbsp;Midhun M. Nair,&nbsp;Arkabanee Mukherjee,&nbsp;Akash S. Vispute,&nbsp;Hardeep Sharma,&nbsp;Pankaj Sharma,&nbsp;Sandip S. Nivdange,&nbsp;Chaitri Roy,&nbsp;Abhilash S. Panicker,&nbsp;Sachin D. Ghude","doi":"10.1007/s11869-026-01946-1","DOIUrl":"10.1007/s11869-026-01946-1","url":null,"abstract":"<div>\u0000 \u0000 <p>Airborne polycyclic aromatic hydrocarbons (PAHs) associated with particulate matter (PM) are recognized contributors to carcinogenic and oxidative health risks in urban environments, yet their size-resolved distribution and redox activity remain insufficiently characterized in megacities. This study presents an integrated observational assessment of 16 priority PAHs in PM₁₀, PM₂.₅, and PM₁ collected at an urban rooftop site in Delhi, India, during a winter early summer campaign (January–June 2024). Chemical speciation was combined with dithiothreitol (DTT) based oxidative potential measurements, molecular diagnostic ratios, Positive Matrix Factorization (PMF), and scanning electron microscopy energy dispersive X-ray spectroscopy (SEM–EDX) to examine size-dependent composition, source patterns, and health-relevant indicators. Total PAH concentrations exhibited pronounced temporal variability, with winter maxima (PM₁₀: 496 ± 36 ng/m³; PM₂.₅: 312 ± 19 ng/m³; PM₁: 212 ± 23 ng/m³), consistent with enhanced combustion emissions and reduced atmospheric dispersion. While PM₁₀ contained the highest total PAH mass, high-molecular-weight (5–6 ring) carcinogenic PAHs were preferentially enriched in PM₂.₅ and PM₁. The ultra fine particle fractions showed enhanced mass-normalized oxidative potential (OPm), with wintertime mean values reaching ~ 0.5 nmol/min/µg, indicating a greater capacity to induce oxidative stress per unit particle mass. PMF analysis identified traffic-related emissions, biomass burning, coal combustion, waste/plastic burning, and an aged/secondary combustion factor, although source mixing and atmospheric processing were evident. SEM–EDX observations revealed soot-like agglomerates with associated sulfur (S), potassium(K), and chlorine (Cl) signals, supporting mixed combustion influences. Screening-level health risk assessment using a U.S. EPA based inhalation model indicated that wintertime incremental lifetime cancer risk (ILCR) associated with PM₂.₅ and PM₁-bound PAHs approached or exceeded ~ 10⁻⁴, surpassing commonly applied acceptable risk thresholds and indicating a potential carcinogenic risk, particularly for adults. PM₁ accounted for a substantial fraction of PM₂.₅-associated cancer risk, underscoring the health relevance of ultrafine PAH-bearing particles. A composite particulate health risk index (PHRI) further suggested elevated potential risk for outdoor workers and socioeconomically vulnerable population groups. Overall, the findings highlight the disproportionate toxicological importance of fine and ultrafine PM-bound PAHs in Delhi and emphasize the need to target combustion-related sources to mitigate health-relevant exposures in megacity atmospheres.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606706","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":"Effects of marginal CO₂ emissions on life Expectancy: A linear and nonlinear panel analysis of Asean","authors":"Mohd Shahidan Shaari,&nbsp;Amri Sulong,&nbsp;Abdul Hayy Haziq Mohamad","doi":"10.1007/s11869-026-01970-1","DOIUrl":"10.1007/s11869-026-01970-1","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigates the asymmetric effects of marginal carbon dioxide (CO₂) emissions, defined as CO₂ emissions per unit of energy use, on life expectancy in ASEAN countries from 1990 to 2023. Unlike most existing studies that focus on total CO₂ emissions, this paper introduces a novel and policy-relevant indicator that more accurately reflects energy efficiency: marginal CO₂ emissions. Using both linear and nonlinear panel Autoregressive Distributed Lag (ARDL and NARDL) models, the findings reveal that rising marginal CO₂ emissions have a significant negative impact on life expectancy. In contrast, reductions in marginal emissions are associated with improvements in public health, confirming the presence of asymmetric effects. Interestingly, health expenditure and economic expansion exhibit unexpected negative long-term associations with life expectancy, whereas inflation shows contrasting short- and long-term effects. The nonlinear model demonstrates superior explanatory power compared to the linear approach, particularly in capturing these asymmetric dynamics. ASEAN countries are selected due to their rapid economic growth, high environmental vulnerability, and wide heterogeneity in energy efficiency and health systems, making them a critical and timely context for this analysis. Therefore, policymakers should prioritise enhancing energy efficiency and reducing emissions intensity to improve population health outcomes across the region.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606908","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":"Deciphering the temporal sequence of sustainability transitions in India: does carbon mitigation precede renewable energy adoption?","authors":"Ugur Korkut Pata,&nbsp;Anam Ul Haq Ganie","doi":"10.1007/s11869-026-01978-7","DOIUrl":"10.1007/s11869-026-01978-7","url":null,"abstract":"<div>\u0000 \u0000 <p>Over the past three decades, India’s rapid economic growth has required a complex balance between industrial expansion and mounting environmental pressures. As the world’s third-largest carbon emitter, India provides a critical context for examining the non-linear relationships among income growth, atmospheric quality, and energy transitions. This study tests the Environmental Kuznets Curve (EKC) and Renewable Energy Kuznets Curve (RKC) hypotheses for India from 1990 to 2024. To address structural instabilities and policy changes in the Indian economy, the study employs a Fourier-based cointegration framework combined with Fully Modified Ordinary Least Squares (FMOLS) and Canonical Cointegrating Regression (CCR). Empirical results confirm an inverted U-shaped EKC, indicating that carbon emissions decouple after a certain income threshold is reached. In contrast, the RKC follows a U-shaped pattern, showing that renewable energy consumption initially declines before increasing as economic capacity matures. A key finding is that the turning point for CO₂ emissions occurs significantly earlier than the acceleration point for renewable energy adoption, suggesting that early emission reductions are primarily driven by regulatory efficiency and technological modernization rather than a full transition to clean energy. Additionally, while renewable energy significantly reduces carbon intensity, fossil fuel dependence remains a statistically significant driver of environmental degradation. These results highlight the critical need for synergistic policy frameworks that simultaneously drive large-scale clean energy deployment and deliver prompt emission reductions. In doing so, they advance SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action), while strengthening India’s pathway to carbon neutrality and sustainable development amid ongoing energy and climate challenges.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606513","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":"Air quality evaluation in Ethiopian major cities through Monte Carlo simulation, principal component analysis, and T test-integrated statistical frameworks","authors":"Mehmet Ali Çelik,&nbsp;Melahat Batu Ağırkaya,&nbsp;Mitiku Badasa Moisa,&nbsp;Dessalegn Obsi Gemeda","doi":"10.1007/s11869-026-01976-9","DOIUrl":"10.1007/s11869-026-01976-9","url":null,"abstract":"<div>\u0000 \u0000 <p>Air pollutants significantly impact both humans and the environment. This study quantifies the levels of seven major air pollutants, namely, carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), formaldehyde (HCHO), the aerosol index (AI), and methane (CH₄), across 15 cities in Ethiopia. Satellite-based measurements of atmospheric pollutants were downloaded from the Tropospheric Monitoring Instrument (TROPOMI), which offers a spatial resolution of 5.5 × 5.5 km. The data were accessed via the Google Earth Engine platform for preprocessing, which included cloud filtering, the exclusion of pixels whose quality assurance flags failed and temporal aggregation. The datasets were standardized into a unified spatial grid format and prepared for integration within the Monte Carlo simulation, principal component analysis (PCA), and t test statistical frameworks. The results revealed spatial heterogeneity in atmospheric pollutant concentrations across Ethiopian cities. Gambella, Semera, and Jijiga have consistently been identified as high-pollution hotspots because of their relatively warm climates and relatively warm vegetation, which can absorb atmospheric pollutants. Gambella and Semera emerged as critical hotspots due to combustion-related and dust-driven emissions, whereas cities such as Dessie and Jijiga presented comparatively lower pollution burdens. With the exceptions of Semera, all cities have a negative AI index. This negative aerosol index has less capacity to absorb ultraviolet (UV) radiation. The AI in Semera varies from − 0.3 in the month of October to 0.57 in April and June, with a mean annual value of 0.04. Elevated levels of CO were detected in cities such as Gambella and Asosa, indicating the likely influence of intensive fuel combustion, possible biomass burning, and increased temperatures that contribute to HCHO production. Carbon monoxide, ozone, nitrogen dioxide, and formaldehyde all presented p values below 0.05, indicating that their mean concentrations differed significantly between low and high air quality conditions. The results revealed a highly heterogeneous spatial distribution of air pollution risk, contradicting the common belief that pollution levels increase directly with the intensity of urbanization. This study underscores the importance of city-specific pollutant mitigation strategies.</p>\u0000 </div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"19 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606514","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}