Environmental Advances最新文献

{"title":"Weekend highs: Rising ketamine levels in Australian wastewater","authors":"Emma Keller,&nbsp;Ben Tscharke,&nbsp;Brock Peake,&nbsp;Rory Verhagen,&nbsp;Richard Bade,&nbsp;Jake O’Brien,&nbsp;Phong Thai,&nbsp;Kevin Thomas,&nbsp;Jochen Mueller,&nbsp;Jason White,&nbsp;Bradley Simpson,&nbsp;Cobus Gerber","doi":"10.1016/j.envadv.2026.100687","DOIUrl":"10.1016/j.envadv.2026.100687","url":null,"abstract":"<div><div>Ketamine is an anaesthetic drug with dissociative effects and is used in hospitals and for emergency treatment. Over the past four years, there has been increasing interest in the non-medical (recreational) use of ketamine in Australia. This study aimed to interrogate patterns in ketamine loads found in wastewater in Australia between December 2020 and April 2025. Daily influent wastewater samples were collected from up to 50 wastewater treatment plants over a week across state and territory capital city and regional sites every 4 months from all states and territories of Australia covering on average 53% of the total population. Wastewater was concentrated using solid phase extraction followed by quantitative analysis using liquid chromatography tandem mass spectrometry to determine concentrations of the metabolite norketamine, with final concentrations flow and population normalised to units of excreted mg/day/1000 people. Norketamine excreted mass loads were compared with regionality and socioeconomic status. Considering the intended application, substantially higher mass loads of norketamine on weekends compared to weekdays would suggest the non-medical use of ketamine at weekends. Nationally, norketamine mass loads were higher for sites located in major city areas compared to those in ‘inner’ and ‘outer’ regional Australia. In addition, sites with higher socioeconomic status had higher mass loads of norketamine. Overall, norketamine mass loads have been increasing in Australia from 2022 to 2025, particularly in sites with higher socioeconomic status. This study demonstrates the value of ongoing wastewater monitoring, revealing both within-week and long-term shifts in ketamine excreted loads in Australia.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"23 ","pages":"Article 100687"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Source apportionment of PM2.5 and its chemical components in Hanoi, Vietnam: A comparison of PMF and CMAQ-ISAM approaches","authors":"Huong Quang Le ,&nbsp;Thao Thi Phuong Pham ,&nbsp;Thuy Minh Le ,&nbsp;Minh Quang Bui ,&nbsp;Trung Quang Nguyen ,&nbsp;Nanthapong Chantaraprachoom ,&nbsp;Katsushige Uranishi ,&nbsp;Tomohito Matsuo ,&nbsp;Akira Kondo ,&nbsp;Hikari Shimadera","doi":"10.1016/j.envadv.2026.100688","DOIUrl":"10.1016/j.envadv.2026.100688","url":null,"abstract":"<div><div>This study investigated the source apportionment of ambient PM_2.5 and its chemical components in Hanoi, Vietnam, during 2023, using both receptor modeling and regional chemical transport modeling approaches. PM_2.5 samples were collected and analyzed for major water-soluble inorganic ions and trace metals. The observed annual mean PM_2.5 concentrations were 49.2 µg/m³ (range: 17.0–157 µg/m³), markedly exceeding the WHO annual guideline (5 µg/m³). Secondary inorganic aerosols were the dominant components, with mean concentrations of sulfate (7.8 µg/m³), nitrate (7.9 µg/m³), and ammonium (5.5 µg/m³), whereas chloride was minor (0.2 µg/m³). Among trace metals, Fe (1.7 µg/m³), Mn (0.6 µg/m³), and Zn (0.4 µg/m³) were most abundant. Source apportionment using the Positive Matrix Factorization (PMF) identified six source categories: secondary sulfate (30.7%), secondary nitrate (23.1%), traffic emissions (18.1%), industrial activities (11.1%), biomass burning (9.7%), and soil dust (7.4%). The Community Multiscale Air Quality (CMAQ) model with the Integrated Source Apportionment Method (ISAM) simulated PM_2.5 concentrations and apportioned contributions from predefined sectors. The largest contributions were attributed to household (H.H, 31.5%), long-range transport (LRT, 23.1%), and industry (IND, 15.5%). Other sources included open biomass burning (OBB, 5.0%), on-road transport (ROA, 3.3%), power generation (POW, 1.8%), natural sources (NAT, 0.4%), other anthropogenic sources (OAN, 5.7%), and non-road traffic (OTR, 0.5%). Although the CMAQ system slightly underestimated PM_2.5 levels (simulated mean 42.7 µg/m³ vs. observed 48.3 µg/m³), both approaches consistently demonstrated the dominant role of secondary formation and combustion-related emissions in shaping PM_2.5 pollution. PMF directly reflects observation-based chemical signatures at the receptor site, providing explicit secondary factors, whereas CMAQ-ISAM links secondary aerosol to specific sectors and regional transport. Integrating these two methods therefore provides a more comprehensive understanding of PM_2.5 sources in Hanoi and a solid scientific foundation for targeted mitigation strategies.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"23 ","pages":"Article 100688"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal seagrass mapping using machine learning and field-validated satellite imagery to inform restoration and management","authors":"Laney Callahan ,&nbsp;Oliver Dalby ,&nbsp;Rhys A Coleman ,&nbsp;Mary A Young ,&nbsp;Daniel Ierodiaconou ,&nbsp;Craig DH Sherman","doi":"10.1016/j.envadv.2026.100686","DOIUrl":"10.1016/j.envadv.2026.100686","url":null,"abstract":"<div><div>Seagrasses are vital coastal ecosystems, but their growth and ecological dynamics in response to seasonal and interannual changes are still poorly understood, limiting our ability to detect their responses to climate and human-driven impacts. Remote sensing is increasingly used to assess seagrass presence and extent to support management and restoration. However, most remote sensing approaches provide only a static snapshot of seagrass distribution making it difficult to identify seasonal and interannual trends in seagrass dynamics. In this study we mapped seagrass extent at a restoration site in Western Port, Victoria, using Sentinel-2 imagery calibrated with drone-derived ground control data, and cloud-based processing platform Google Earth Engine (GEE). A Random Forest classifier was trained to identify seagrass from satellite imagery achieving an overall accuracy of 87.0%. This model was then back-cast through the catalogue of available Sentinel-2 imagery to characterise seasonal dynamics, ephemerality, and trajectories of seagrass meadows in the region. Although seagrass extent remained relatively stable at the regional scale, the focal restoration site showed high variability, with patterns of seasonal dieback and regrowth. Developing semi-automated seagrass mapping pipelines can therefore offer vital temporally explicit insights into intra- and inter- annual seagrass dynamics, providing essential context for conservation and restoration outcomes.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"23 ","pages":"Article 100686"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The accumulation of microplastics and their associated heavy metals on the surfaces of microplastics in various tissues of the pelagic fish Rastrelliger kanagurta, from the northern coast of Central Java, Indonesia","authors":"Asriningsih Suryandari ,&nbsp;Agoes Soegianto ,&nbsp;Eko Prasetyo Kuncoro","doi":"10.1016/j.envadv.2026.100689","DOIUrl":"10.1016/j.envadv.2026.100689","url":null,"abstract":"<div><div>Microplastics (MP) and heavy metals present considerable risks to aquatic ecosystems and human health, therefore requiring attention to their accumulation in the pelagic zone of the North coast of Central Java, Indonesia. This study examines the physical and chemical properties of MP and the presence of heavy metals bind to the surface of microplastics in various tissues of pelagic mackerel <em>Rastrelliger kanagurta</em> from the northern coast of Central Java. Samples were obtained from four distinct locations along the coastline. The study's findings indicated that microplastics in the gills, stomach, intestines, and liver of <em>R. kanagurta</em>, as well as in seawater, were predominantly fragment-shaped, black in color, and measured less than 500 µm. The concentration of microplastics in seawater ranges from 10 to 42 particles/L, while in the tissues of <em>R. kanagurta</em>, it ranges from 9 to 13 particles/ind. The Tegal site showed a significant correlation between microplastic concentration and <em>R. kanagurta</em> length or weight, but other sites did not. Seven types of MPs polymers were identified in the tissues of <em>R. kanagurta</em> collected from the north coast of Central Java: polyamide, polypropylene, polyethylene terephthalate, polystyrene, polyethylene, polyvinyl chloride, and nylon. Four categories of plastic additives were detected in the tissues of <em>R. kanagurta</em>: plasticizers, emulsifiers, antioxidants, and thermal stabilizers. Metal elements detected on the surface of MP include Mn, Cr, Al, Ni, Cu, Zn, As, Cd, Co, Sn, Hg, Fe, and Pb. Additionally, non-metallic elements including O, Na, Ca, Mg, C, Si, and K were identified on the surface of MPs.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"23 ","pages":"Article 100689"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Daily and spatial variation of particulate matter air pollution in industrial, urban and rural areas from central Burkina Faso","authors":"Marin Moïse Zouma ,&nbsp;Geoffroy Gueswindé Ouédraogo ,&nbsp;Sylvain Ilboudo ,&nbsp;Aude Nikiema ,&nbsp;Jean Claude Romaric Pingdwindé Ouédraogo ,&nbsp;Adama Sawadogo ,&nbsp;Alix Tougma ,&nbsp;Paul W. Savadogo ,&nbsp;Dramane Zongo ,&nbsp;Rasmané Semdé","doi":"10.1016/j.envadv.2025.100682","DOIUrl":"10.1016/j.envadv.2025.100682","url":null,"abstract":"<div><div>Particulate air pollution is a major health and environmental concern facing countries worldwide. Burkina Faso represents a typical case of an industrially recovering nation, where the characteristics of particulate matter pollution vary across urban and rural areas. This study aimed to determine the level of PM air pollution and their daily and spatial vairiation in industrial (Kossodo and Polesgo), urban (Nioko 2) and rural (Saponé) areas from central Burkina Faso. PM were measured using a Grimm dust monitor model 11-D dust meter during the months of March and April 2025. The results showed twenty-four hours (24 h) average levels up to 7, 5 and 4 times the national air quality guidelines recorded for TSP at Kossodo, Polesgo and Nioko 2 respectively. For PM₁₀, daily average levels exceeding &gt;22, 12 and 12 times the WHO normative thresholds were recorded respectively at Kossodo, Polesgo and Nioko 2. PM levels also reached values of 4, 2 and 3 times the WHO standards for PM_2.5 at Kossodo, Polesgo and at Nioko 2. Although there is no standard for PM₁, levels exceeding the daily standard for PM_2.5 were recorded at Kossodo, Polesgo and Nioko 2. Daily average levels of TSP, PM₁₀ and PM_2.5 differed significantly depending on the measurement site (<em>p</em> &lt; 0.05). Daily variation of PM concentrations showed that mornings and evenings in all areas are the most polluted, with pollution increasing during nighttime. This study provides new data on PM pollution levels and their daily and spatial variation in industrial and urban areas. It demonstrates a real need to establish a program for controlling and reducing atmospheric emissions in order to to preserve the health of the populations.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"23 ","pages":"Article 100682"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disparities in drinking water services: Private well dependence and public supply inequities in Western Sweden","authors":"Nadine Gärtner,&nbsp;Andreas Lindhe","doi":"10.1016/j.envadv.2026.100692","DOIUrl":"10.1016/j.envadv.2026.100692","url":null,"abstract":"<div><div>Studies show that minority and low-income populations often receive lower quality drinking water, increasing their risk for waterborne diseases and adverse health effects. However, most research on this topic has focused on the United States, Canada, South Africa, and India, leaving Scandinavia unexplored. This study examines whether similar disparities exist in Sweden by analysing drinking water access in the Gothenburg region. Using geospatial analysis to intersect drinking water provision areas with socio-economic data, we compare private well-users with municipally supplied populations and then assess whether disparities also appear within municipal supply systems, considering water quality parameters, water price, and pipe breaks. The analysis reveals two key patterns. First, untreated drinking water use among private well-owners is slightly more common in socio-economically advantaged communities, contrasting with evidence from other regions where exposed private well-use is typically associated with disadvantaged groups. Second, within the municipal supply, we find no clear regionwide trends, although the tail end of the distribution shows disparities between the wealthiest and less affluent municipalities, especially in microbial and chemical test results with noted issues and in pipe-break frequency. Sweden’s high-resolution socio-economic data and municipal collaboration in sharing drinking water service areas enable these detailed assessments without relying on coarse geospatial proxies. By identifying disparities in both private and municipal drinking water access, this study provides a structured approach that can support Swedish water-expansion planning and contributes to emerging discussions on water justice in high-income countries.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"23 ","pages":"Article 100692"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microplastic pollution in agriculture: How exposure pathway (Seed, Leaf, Root) dictates phytotoxicity in lettuce (Lactuca sativa L.)","authors":"Golnaz Ehteshami ,&nbsp;Mohammad Etemadi ,&nbsp;Javad Karimi ,&nbsp;Mohamad Jamal Saharkhiz","doi":"10.1016/j.envadv.2025.100679","DOIUrl":"10.1016/j.envadv.2025.100679","url":null,"abstract":"<div><div>The accumulation of microplastics (MPs) in arable soil poses a significant risk to food safety and crop growth. However, research has often focused on single exposure mechanisms, making it difficult to comprehend the actual environmental effects. This study investigated the effects of polyethylene (PE) microplastics on lettuce (Lactuca sativa L. var. ‘Little Gem Green’) applied via three different pathways (seed, leaf, and root) at different concentrations (0, 50, 250, and 1000 µg/mL). The results demonstrated that the plant exposure technique significantly dictated the phytotoxic outcome. Direct root application, particularly at 1000 µg/mL, was the most detrimental, significantly reducing aerial biomass and height and disrupting the antioxidant defense system. In contrast, seed and leaf administration produced complex responses. Seed treatment (1000 µg/mL) resulted in the shortest plants but the largest leaf areas, indicating an adaptive growth behavior. A possible hormetic effect was observed with 250 µg/mL foliar application, which recorded the maximum plant height. Pathway-dependent differences in photosynthetic pigments, proline accumulation, and antioxidant enzyme activation (e.g., catalase, ascorbate peroxidase) confirmed that plant tolerance and response are highly dependent on the exposure conditions. This comparison of three exposure pathways highlights the variability of plant-MP interactions and stresses the importance of pathway-specific risk assessments for mitigating microplastic pollution in agricultural settings.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"23 ","pages":"Article 100679"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring bacterial contamination of West African surface waters using Earth observation data and machine learning methods","authors":"Marc-Antoine Mant ,&nbsp;Elodie Robert ,&nbsp;Hedwige Nikiema ,&nbsp;Moussa Boubacar-Moussa ,&nbsp;Amadou Abdourhamane-Toure ,&nbsp;Beatriz M. Funatsu ,&nbsp;Manuela Grippa ,&nbsp;Laurent Kergoat ,&nbsp;Javier Perez-Saez ,&nbsp;Hugo Pradalier ,&nbsp;Emma Rochelle-Newall ,&nbsp;Marc Robin","doi":"10.1016/j.envadv.2025.100678","DOIUrl":"10.1016/j.envadv.2025.100678","url":null,"abstract":"<div><div>In 2021, diarrheal diseases caused approximately 434,000 deaths in sub-Saharan Africa, mainly due to water contamination by fecal pathogens such as <em>Escherichia coli</em>. While environmental conditions and human activities are known to influence bacterial contamination in surface waters, their respective impacts remain poorly quantified, complicating efforts to model this health risk. In this context, developing approaches to monitor contamination without relying solely on field-based analyses has become increasingly important. This study explores the potential of Earth observation (EO) data to monitor bacterial contamination in surface waters in West Africa. It investigates the relationship between <em>E. coli</em> concentrations and various water quality parameters, some measured in situ (water quality parameters, suspended particulate matter (SPM), etc.), and others derived from EO data (rainfall, specific humidity, etc.). These variables are integrated into eight machine learning models capturing the temporal dynamics of <em>E. coli</em> concentrations in two sites: the Bagré reservoir (Burkina Faso) and Kongou Lake (Niger). Using all available variables, ensemble tree-based models provided the best predictive performance for both sites. When using only EO variables, these models maintained good performance, achieving R² values of approximately 0.7 for Kaporé and 0.65 for Kongou. For both sites, the variables playing the strongest role are SPM (or NIR band) and rainfall, to which are added, for Kaporé, air humidity and NDVI. These results demonstrate the feasibility of using EO data alone to monitor <em>E. coli</em> contamination in West African surface waters. This approach can enable remote monitoring of microbial water quality.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"22 ","pages":"Article 100678"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145680926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of traffic volumes and meteorological conditions on particulate matter levels at highway toll stations: A case study in inner and outer Bangkok, Thailand","authors":"Narut Sahanavin ,&nbsp;Siriphat Intrakun ,&nbsp;Wissanupong Kliengchuay ,&nbsp;Kraichat Tantrakarnapa","doi":"10.1016/j.envadv.2025.100670","DOIUrl":"10.1016/j.envadv.2025.100670","url":null,"abstract":"<div><div>Particulate matter (PM) serves as a widely recognized proxy indicator for air pollution, with vehicle emissions being a major contributing factor. This study assessed the influence of traffic emissions and meteorological conditions on PM₁₀ and PM_2.5 at highway toll stations in Bangkok, including Chatuchot (outer) and Rama IV-1 (inner), using low-cost air quality monitoring sensors. The results revealed that the PM₁₀ and PM_2.5 concentrations at Rama IV-1, averaging 52.22 ± 26.06 and 35.86 ± 22.20 μg/m³, respectively, were significantly higher than those at Chatuchot, averaging 42.26 ± 16.77 and 25.59 ± 9.64 μg/m³, respectively (<em>p</em> &lt; 0.05). At Rama IV-1, average PM concentrations during weekdays were significantly higher than weekends (<em>p</em> &lt; 0.05), while the opposite trend was observed at Chatuchot. The average PM₁₀ and PM_2.5 concentrations were significantly higher than the background levels at both sites (<em>p</em> &lt; 0.05). The average PM_2.5/PM₁₀ ratio across both stations was 0.64 ± 0.10. The LULC map revealed that built-up areas accounted for 98.91 % and 64.06 % of total areas at Rama IV-1 and Chatuchot, respectively. PM₁₀ and PM_2.5 concentrations were significantly correlated with light-duty trucks and passenger vehicles at Chatuchot, while only PM₁₀ was significantly correlated with passenger vehicles at Rama IV-1. Temperature and relative humidity were primarily linked to PM concentration at Chatuchot, whereas additional influences of wind speed, pressure, and boundary layer height were observed at Rama IV-1. The study provides a baseline understanding of site-specific interactions between PM concentrations, traffic density, and meteorological conditions, but further research is needed to strengthen the evidence base for developing effective policy decisions.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"22 ","pages":"Article 100670"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air quality and health impacts in Nepal’s urban valley: PM2.5 pollution patterns and public health risks","authors":"Jeevan Bhatta ,&nbsp;Shiva Raj Acharya ,&nbsp;Srijya Thapa ,&nbsp;Pongpaiboon Tularag ,&nbsp;Saroj Adhikari","doi":"10.1016/j.envadv.2025.100672","DOIUrl":"10.1016/j.envadv.2025.100672","url":null,"abstract":"<div><div>The Kathmandu Valley exemplifies how monsoon climate dynamics create deceptive pollution patterns that mask persistent public health threats. Seasonal PM_2.5 variability suggests that the monsoon \"relief\" pollution, but even the cleanest periods pose severe health risks. We analyzed 1,710 daily PM_2.5 observations spanning 2020-2024 using machine learning and advanced statistical methods, developing predictive models, identifying meteorological thresholds, and assessing health risks across Nepal's five distinct seasons. PM_2.5 measurements were obtained using a BAM-1020 Beta Attenuation Monitor with rigorous quality control procedures ensuring 97.3 % data completeness. Extreme seasonal variability was observed, ranging from 51.5 ± 30.5 μg/m³ during the monsoon to 146.7 ± 27.3 μg/m³ in winter; however, across all seasons, the values were 3.4-9.8 times higher. Temperature exhibited the strongest PM_2.5 control (r = -0.710, p &lt; 0.001), while Random Forest models achieved superior prediction accuracy (R² = 0.941, RMSE = 12.04 μg/m³, MAPE = 10.3 %) compared to linear regression (R² = 0.572) following systematic hyperparameter optimization across 18 parameter combinations using 5-fold cross validation (CV R² = 0.933 ± 0.017). Critical meteorological thresholds were identified: rainfall exceeding 15.9 mm/day and wind speed exceeding 5.8 m/s reduce pollution, but not sufficiently for safety. Concentrations show a systematic annual increase of 6.7 μg/m³ (p &lt; 0.001), with all vulnerable populations facing year-round health risks (hazard quotients &gt;1), and people with asthma experiencing the highest risks (HQ = 4.4 in winter). Multi-year patterns demonstrate that monsoon washing effects, while substantial, cannot compensate for extreme baseline pollution levels, revealing the urgent need for emission controls that transcend seasonal pollution management approaches.</div></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":"22 ","pages":"Article 100672"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}