Environmental Challenges最新文献

{"title":"Increasing the recycling rates of post-use fishing ropes: the role of cleaning processes and the possibilities of a systematic Individual-Producer-Responsibility implementation","authors":"Thomas Potempa ,&nbsp;Nguyen Van Nhi Tran ,&nbsp;Max Ehleben ,&nbsp;Quang Nguyen Pham ,&nbsp;Le Binh Do ,&nbsp;Xuan Huyen Vo ,&nbsp;Robin Führmann ,&nbsp;Welf Graf v. Luxburg-Marten ,&nbsp;Julia Tetzner","doi":"10.1016/j.envc.2025.101314","DOIUrl":"10.1016/j.envc.2025.101314","url":null,"abstract":"<div><div>Plastics from fishing gear represent a significant source of marine pollution, with post-use fishing ropes made of high-density polyethylene (HDPE) and polypropylene (PP) posing both environmental challenges and recycling opportunities. This study investigates the mechanical recyclability of post-use fishing ropes and the effect of washing processes on material recovery. Used ropes collected from Vietnamese fisheries were sorted, subjected to up to five washing cycles, and analyzed through FTIR spectroscopy, differential scanning calorimetry (DSC), and mechanical testing. Results indicate that washing significantly reduces surface impurities, leading to improved flexural modulus and yield strength of the recyclates, while impact strength remains largely unaffected. Both old bright (OBR) and old dark ropes (ODR) retain accessible crystallinity and mechanical properties comparable to virgin material when optimally washed. The study demonstrates that the mechanical properties of recycled material are sufficient for reintegration as up to 25 % recyclate in new fishing ropes, supporting circular economy goals and forthcoming EU requirements for recycled content. Our findings underscore the feasibility of closed-loop recycling for fishing gear polymers and advocate for integrating washing steps and producer responsibility schemes to improve material circularity and reduce marine plastic pollution.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101314"},"PeriodicalIF":0.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047588","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":"Bayesian spatial prediction of soil organic carbon stocks in eastern DRC using INLA-SPDE and environmental covariates","authors":"Alain Matazi Kangela ,&nbsp;Bitaisha Nakishuka Shukuru ,&nbsp;Serge Mugisho Mukotanyi ,&nbsp;Gerard Imani ,&nbsp;Yannick Mugumaarhama ,&nbsp;Daniel Muhindo Iragi ,&nbsp;Dieudonné Shamamba Bahati ,&nbsp;Janvier Bigabwa Bashagaluke ,&nbsp;Wivine Munyahali","doi":"10.1016/j.envc.2025.101303","DOIUrl":"10.1016/j.envc.2025.101303","url":null,"abstract":"<div><div>Soil organic carbon (SOC) plays a critical role in climate mitigation and agricultural sustainability, yet its spatial distribution in the eastern Democratic Republic of the Congo (DRC) remains poorly quantified. This study employs a Bayesian spatial modeling framework, Integrated Nested Laplace Approximation with Stochastic Partial Differential Equations (INLA-SPDE), to predict SOC stocks across Kalehe and Kabare territories, integrating 177 field observations with environmental covariates (soil properties, topography, and vegetation indices). The INLA-SPDE approach was chosen for its ability to handle sparse datasets effectively while providing robust uncertainty quantification, a key advantage for regions with limited observational data. Key drivers of SOC variability included soil pH, sand,clay content, bulk density, elevation, and vegetation indices (Normalized Difference Vegetation Index(NDVI), Soil-Adjusted Vegetation index (SAVI)). The INLA-SPDE model outperformed the global SoilGrids250m dataset, achieving a significantly higher correlation with observed data (<span><math><mrow><mi>r</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>49</mn><mspace></mspace><mtext>vs</mtext><mspace></mspace><mn>0</mn><mo>.</mo><mn>045</mn><mo>,</mo><mi>p</mi><mo>&lt;</mo><mn>0</mn><mo>.</mo><mn>001</mn></mrow></math></span>). Higher SOC stocks were predicted in forested southern regions (<span><math><mrow><mn>105</mn><mo>.</mo><mn>11</mn><mo>±</mo><mn>11</mn><mo>.</mo><mn>36</mn></mrow></math></span> MgC ha⁻¹), while data-sparse northern areas exhibited greater uncertainty, with a posterior standard deviation of up to <span><math><mrow><mn>32</mn><mo>.</mo><mn>68</mn><mo>±</mo><mn>5</mn><mo>.</mo><mn>46</mn></mrow></math></span> MgC ha⁻¹, (vs. the spatial field’s global standard deviation averaged to 12.74 MgC ha⁻¹ at the 97.5% quantile). Posterior distributions revealed significant spatial heterogeneity, linked to land use and observational density. Our results underscore the importance of localized SOC mapping for informed land management and climate resilience strategies in tropical Africa, demonstrating the INLA-SPDE framework’s superior predictive accuracy and interpretability in data-scarce environments.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101303"},"PeriodicalIF":0.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047587","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":"Long-term monitoring of PM2.5 and PM10: Implications for air quality and public health in urban Bangkok, Thailand","authors":"Mushtaq Ahmad ,&nbsp;Sirima Panyametheekul ,&nbsp;Phailin Thaveevong ,&nbsp;Thawat Ngamsritrakul ,&nbsp;Boonrat Tassaneetrithep ,&nbsp;Titaporn Supasri ,&nbsp;Chonlada Bennett","doi":"10.1016/j.envc.2025.101312","DOIUrl":"10.1016/j.envc.2025.101312","url":null,"abstract":"<div><div>Air pollution, particularly ambient particulate matter (PM) PM_2.5 and PM₁₀, poses serious health risks and is linked to high mortality rates in urban areas. A five-year study used Aeroqual Dust Profiler to measure PM levels hourly. PM_2.5 and PM₁₀ were measured at the Faculty of Engineering, Chulalongkorn University in Bangkok from 2019 to 2023, and their correlation with meteorological parameters was investigated. The ratios of PM_2.5 to PM₁₀ were estimated to assess the dominance of either PM size. The exposure risk of PM_2.5 in urban Bangkok was assessed by calculating the relative risk (RR) and attributable fraction (AF) for health outcomes, including cardiovascular and respiratory mortality, lung cancer mortality, childhood asthma, and strokes. The Air Quality Index (AQI) for PM_2.5 was also determined using the single pollutant method. During the cool dry season in Bangkok (December to February), PM_2.5 and PM₁₀ concentrations are significantly higher due to reduced mixing heights, lower wind speeds, and increased anthropogenic activities. In urban Bangkok, coarse PM is mainly attributed to road dust resuspension, construction, and regional pollutant transport. In urban Bangkok, PM_2.5 to PM₁₀ ratios were high (&gt;0.5), indicating a significant presence of fine and secondary particulates. There was a strong positive correlation between PM_2.5 to PM₁₀ each year. Fine and coarse particles correlate differently with meteorological parameters. The RR for health outcomes was high during the cool dry season, while the annual mean AQI remained in the excellent to satisfactory range over the studied years. The monthly mean AQI is categorized as unhealthy during the cool dry season, except in 2022. In urban Bangkok, the mean annual concentrations of PM_2.5 and PM₁₀ over five years are within the limits established by the Pollution Control Department (PCD) but exceed the ambient air quality standards of the World Health Organization (WHO). The cool dry season poses a higher PM_2.5 exposure risk than the rest of the year. During the cool dry season, the monthly AQI is hazardous for vulnerable individuals. The study's limitations include relying on a single monitoring site, which may not reflect PM variability in urban Bangkok. The absence of chemical composition and number concentration analysis hinders source attribution and toxicity assessment. Multi-site studies with comprehensive analysis are needed to better understand PM-related health risks.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101312"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047586","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":"Spatial assessment of potentially toxic elements (PTEs) pollution in the vicinity of a cement plant through magnetic and chemical testing in plants and soil","authors":"Teresa Salazar-Rojas ,&nbsp;Sara Murillo-Murillo ,&nbsp;Ricardo Ulate-Molina ,&nbsp;Fredy Ruben Cejudo-Ruiz ,&nbsp;Guillermo Calvo-Brenes","doi":"10.1016/j.envc.2025.101313","DOIUrl":"10.1016/j.envc.2025.101313","url":null,"abstract":"<div><div>Cement plants are a potential source of environmental pollutants, particularly potentially toxic elements (PTEs). Some PTEs are trapped in clinker, while others volatilize, adhering to dust particles and contributing to atmospheric pollution. These PTEs persist in the environment, bioaccumulate, and are toxic, posing risks to ecosystems, agriculture, and health. This study employs both magnetic and chemical methods to evaluate soil and plant contamination in the vicinity of a cement plant. Soil magnetic susceptibility (χlf) was twice the background level at 80% of sites, indicating significant anthropogenic enrichment. While plants (<em>C. equisetifolia and C. lusitanica</em>) showed lower χlf values than the soil, and notably more superparamagnetic (SP) material, this suggests airborne particulate contamination. Elevated Cu, Cr, and As levels were found in soils, with Cr, Ni, V, Pb, and Zn elevated in plants. Nevertheless, considering the spatial distribution, year-round wind direction, and the long-term accumulation of these metals in soil, their enrichment by PTEs is likely more influenced by urban activities such as traffic and agriculture rather than the cement plant. Correlations between χlf and metals like Cu, Ni, As, Zn, and Cd suggest magnetic measurements are reliable pollution indicators.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101313"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047561","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":"Spatiotemporal analysis of land use and land cover using random forest in Google Earth engine: A case study of the Grand Ethiopian Renaissance Dam basin and reservoir, Upper Blue Nile, Ethiopia","authors":"Yilak Taye Bihon,&nbsp;Abdella Kemal Mohammed,&nbsp;Elias Gebeyehu Ayele","doi":"10.1016/j.envc.2025.101311","DOIUrl":"10.1016/j.envc.2025.101311","url":null,"abstract":"<div><div>Land use and land cover (LULC) changes have significant positive and negative impacts on the environment. The increasing water demand, the limited water resources, high soil erosion, and dynamic LULC and climate changes of the Grand Ethiopian Renaissance Dam (GERD) basin prompted this study to analyse LULC changes as an initial step toward further research. This study aims to analyse LULC changes in the GERD basin from 1986 to 2024 using Landsat images, as well as the GERD and Aswan High Dam (AHD) reservoir areas during GERD reservoir water filling with Sentinel-2 images (2019–2024). The classification was initially performed at 15 sub-basins using Random Forest machine learning in GEE and then mosaicked using ArcMap GIS. Approximately 39,000 points have been used for training and validation in 1986, 2000, 2014, and 2024 for the entire basin. The overall accuracy and Kappa coefficient for all sub-basins considering the auxiliary data sets were greater than 85% and 0.81, respectively. Eucalyptus trees, built-up areas, water, agricultural land, and bare land expanded by 4505%, 1537%, 56%, 36%, and 9%, while shrubs, forests, grassland, and wetlands shrank by 38%, 27%, 19%, and 10%, respectively, from 1986 to 2024. The GERD reservoir annual water filling based on the ALOS PALSAR 12.5 m Digital Elevation Model (DEM) indicated that the first filling started in 2020 rainy season (560 m, 300 km², 4.82 billion m³), 2021 (580 m, 460 km², 10.5 billion m³), 2022 (600 m, 840 km², 22 billion m³), 2023 (620 m, 1350 km², 43 billion m³), 2024 (637 m, 1765 km², 69.3 billion m³). On 9 September 2025, the full supply level was reached and inaugurated. When the GERD reservoir filled with water, the AHD reservoir's excess water overflowed into the Toshka lakes due to the high flow of the Nile River since 2020. The forest and shrubs in the GERD reservoir area were cleared before filling to prevent greenhouse gas emissions, decayed deposition on dead storage, and water quality issues. Ensemble, coupling, and comparisons of tools, methods, and factors should be considered for better classification accuracy. Effective LULC management that enhances ecosystem services and alleviates water stress on the GERD basin requires cooperation from all responsible stakeholders.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101311"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047562","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":"From accurate to actionable: Interpretable PM2.5 forecasting with feature engineering and SHAP for the Liverpool–Wirral region","authors":"Seyed Matin Malakouti","doi":"10.1016/j.envc.2025.101290","DOIUrl":"10.1016/j.envc.2025.101290","url":null,"abstract":"<div><div>Fine particulate matter (PM_2.5) poses a significant threat to public health worldwide, contributing to millions of premature deaths annually, according to the World Health Organization. At the regional scale, Europe and the United Kingdom continue to experience PM_2.5 episodes influenced by transboundary pollution, industrial emissions, and meteorological patterns. Locally, the Liverpool–Wirral area faces specific challenges due to dense urban traffic, port activities, and mixed industrial–residential land use, which can lead to localized pollution hotspots. Despite advances in air quality modeling, there remains a gap in producing highly accurate and interpretable short-term PM_2.5 forecasts tailored to local conditions using dense networks of low-cost sensors. To address this gap, machine learning models—ExtraTrees, LightGBM, and a weighted ensemble—were developed in this study to forecast daily PM_2.5 concentrations from 2019 to 2024 using a rich set of engineered time-series features. These features included lagged values (1, 7, 14, 30 days), rolling averages (3, 7, 14, 30 days), day-over-day raw and percentage changes, day of the week, weekend indicator, month, and cyclical day-of-year components (sine and cosine) to capture short-term autocorrelation, medium- and long-term trends, and seasonal effects. The models were trained and validated on a Liverpool–Wirral dataset, and their performance was evaluated on early-2024 observations. To interpret feature contributions, SHAP (SHapley Additive exPlanations) values were computed for the LightGBM model, revealing that the 3-day rolling mean, day-over-day change, and 1-day lag dominated the predictive power. The ensemble model achieved the lowest test-set RMSE (0.54 <span><math><mi>μ</mi></math></span>g/m³, <span><math><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>=</mo><mn>0</mn><mo>.</mo><mn>990</mn></mrow></math></span>). A full-year 2025 forecast indicated modest seasonal variability, with ensemble predictions remaining stable around 6–6.2 <span><math><mi>μ</mi></math></span>g/m³. These results demonstrate that careful feature engineering, coupled with SHAP-based interpretation, can yield highly accurate and transparent PM_2.5 forecasts.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101290"},"PeriodicalIF":0.0,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020591","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":"Development of probabilistic flood forecast based on ensemble weather forecast and historical flood simulation database for resource-constrained area. Case study: Semarang City, Indonesia","authors":"Rusmawan Suwarman ,&nbsp;Mohammad Farid ,&nbsp;Muhammad Rais Abdillah ,&nbsp;Ahmad Nur Wahid ,&nbsp;Tri Wahyu Hadi ,&nbsp;Edi Riawan ,&nbsp;Faiz Rohman Fajary ,&nbsp;Yogi Simanjuntak ,&nbsp;Siti Azizah ,&nbsp;Rinaldi Sirait ,&nbsp;Mohammad Bagus Adityawan ,&nbsp;Azman Syah Barran Roesbianto ,&nbsp;Jovian Javas ,&nbsp;Ferrari Pinem","doi":"10.1016/j.envc.2025.101308","DOIUrl":"10.1016/j.envc.2025.101308","url":null,"abstract":"<div><div>A novel, resource-efficient framework for a semi-online, pre-running database probabilistic flood forecasting system is presented in this manuscript. The system was designed for deployment in resource-constrained areas, with its application demonstrated through a case study in Semarang City, Indonesia. The substantial computational demands of traditional full-online numerical simulations, which are often prohibitive in developing countries, are circumvented by this approach. To achieve this, the framework utilizes pre-running databases built from historical rainfall, hydrologic, and hydraulic model data. It integrates daily calibrated probabilistic rainfall forecasts that are derived from a multi-model time-lagged ensemble analysis of outputs from the Global Forecast System (GFS) and Weather Research &amp; Forecasting (WRF) models. This integration produces a daily probabilistic inundation map, valid for 24 h with a 14-hour lead time, to assist decision-makers in assessing future uncertainty. The historical simulations of the model were found to exhibit good agreement with observational data, and a probabilistic rainfall forecast evaluation demonstrated a low Brier score, confirming its accuracy. While the model has acknowledged limitations, the framework represents a crucial step towards developing practical and accessible forecasting and prediction parts of flood early warning systems (FEWS) in similar regions.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101308"},"PeriodicalIF":0.0,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047560","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":"Transitioning from linear to circular systems offers sustainable solutions for smallholder agriculture in the Global South","authors":"Noluthando Noxolo Aruwajoye,&nbsp;Rojanette Coetzee","doi":"10.1016/j.envc.2025.101300","DOIUrl":"10.1016/j.envc.2025.101300","url":null,"abstract":"<div><div>Agriculture remains central to economies across the Global South despite lower average productivity. It provides livelihoods for much of the rural workforce and contributes a meaningful share of gross domestic product (GDP). Smallholder farmers face persistent challenges that include water scarcity, limited energy access and weak institutional support. These pressures are intensified by linear “take, use, dispose” systems that deplete natural resources and generate waste. This review synthesizes insights from over 150 studies published between 2005 and 2025 in Web of Science, Google Scholar, Scopus, and international organizations such as FAO databases to examine how circular economy (CE) interventions can enhance the sustainability of smallholder agriculture. Circular practices such as composting, vermicomposting, biochar application and Black Soldier Fly (BSF) bioconversion are already emerging in smallholder contexts. Many of these practices are implemented in silos and need integration within a coherent cross farm framework. The review also identifies a previously overlooked interdisciplinary connection between regenerative practices and digital agriculture tools such as IoT sensors and precision input systems. Used together, these approaches help smallholders reduce waste, close nutrient loops and improve input efficiency and soil health. Emerging business opportunities include localized composting and BSF enterprises, biochar supply services and farmer led cooperatives that offer climate smart products. High potential options such as hydroponics and aquaponics remain constrained by infrastructure and energy demands and require localized adaptation. The literature suggests that investors can play a catalytic role when risk adjusted returns are clear. CE interventions must therefore deliver environmental impact and financial viability to engage farmers and attract capital. To accelerate adoption, future research and policy should address financing barriers, capacity gaps and policy misalignment through microcredit schemes, peer led demonstration farms and co-developed policy roadmaps. This review advances that CE practices in smallholder agriculture across the Global South are not optional but essential, offering a pathway to greater resource efficiency, resilience, and economic viability than conventional linear systems. The urgency lies in the accelerating threats of resource depletion, environmental degradation, and climate change which, if unaddressed, will undermine smallholder livelihoods and jeopardize regional food security.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101300"},"PeriodicalIF":0.0,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027551","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":"Association between ambient air pollutants and major infectious diseases in Singapore","authors":"Baihui Xu,&nbsp;Jue Tao Lim,&nbsp;Chen Chen","doi":"10.1016/j.envc.2025.101297","DOIUrl":"10.1016/j.envc.2025.101297","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Introduction&lt;/h3&gt;&lt;div&gt;Infectious diseases remain a major cause of morbidity and mortality worldwide, posing significant challenges to public health, especially in low- and middle-income countries. These diseases are caused by a variety of pathogens, including bacteria, viruses, and parasites, and can be exacerbated by environmental factors. Among these factors, air pollution has been identified as a significant risk. It is however unknown how mixtures of ambient air pollutants affect different infectious diseases with different transmission pathways. To address this gap, this study investigates the nonlinear and potential interactive association between ambient air pollutants mixtures and multiple infectious diseases. Infectious diseases chosen were those which had the highest reported burden in Singapore and were plausibly affected by ambient air pollutants.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;We harmonized weekly data on ambient air pollutants (PM&lt;sub&gt;2.5&lt;/sub&gt;, PM&lt;sub&gt;10&lt;/sub&gt;, SO&lt;sub&gt;2&lt;/sub&gt;, NO&lt;sub&gt;2&lt;/sub&gt;, O&lt;sub&gt;3&lt;/sub&gt;, and CO), environmental exposures such as rainfall, absolute humidity and mean temperature as well as weekly disease surveillance data from 2012 to 2019. We utilized generalized linear models (GLMs) and generalized additive models (GAMs) to examine both linear and non-linear associations between pollutants and disease incidences, adjusting for confounders, lagged effects, and autocorrelation. Incidence rate ratios (IRRs) and excess incidence ratios (EIRs) were derived to interpret exposure–response relationships. Additionally, we conducted a sensitivity analysis using Gaussian Process (GP) regression with various kernel functions and five-fold cross-validation to assess model robustness and potential interactive effects among pollutants.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Our analyses revealed significant associations between pollutant concentrations and several disease EIRs. High PM&lt;sub&gt;10&lt;/sub&gt; levels were linked to an immediate increase in the incidence rates compared to the reference level for acute conjunctivitis and acute upper respiratory infections. Elevated SO&lt;sub&gt;2&lt;/sub&gt; concentrations were associated with higher contemporaneous incidence rates for acute conjunctivitis and varying effects for Hand, food, and mouth disease (HFMD) depending on concentration levels and the time lag. NO&lt;sub&gt;2&lt;/sub&gt; concentrations had delayed effects on HFMD at 1-week and 4-week lags, and the effects were such that as concentration increased EIR decreased. CO and O&lt;sub&gt;3&lt;/sub&gt; showed minor effects on the infectious diseases studied. No significant interactive effects between pollutants were found.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;Specific pollutant concentration thresholds influence the incidence of various infectious diseases. Targeted air quality management strategies are essential to mitigate public health risks. The absence of interactive effects simplifies the design of policies aimed at reducing individual pollu","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"21 ","pages":"Article 101297"},"PeriodicalIF":0.0,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047585","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 hidden burden of dual climate threats: Region-specific additive impacts of PM2.5 and temperature extremes on cardiovascular and respiratory mortality in a tropical climate","authors":"Phichet Khunthong,&nbsp;Panuwat Vittayapraparat,&nbsp;Sitthichok Puangthongthub","doi":"10.1016/j.envc.2025.101276","DOIUrl":"10.1016/j.envc.2025.101276","url":null,"abstract":"<div><h3>Background</h3><div>Climate change has increased the frequency and intensity of extreme temperature events (ETEs; heat and cold waves), alongside fluctuations in PM_2.5. However, limited research has explored the additive interaction between ETEs and PM_2.5 on mortality, especially in tropical regions where interactions may differ from temperate settings.</div></div><div><h3>Methods</h3><div>A two-stage time-series using distributed lag non-linear models was applied to estimate region-specific relative risks (RRs) of ETEs and PM_2.5 on daily cardiovascular and respiratory mortality. Additive interaction was quantified using the Relative Excess Risk due to Interaction (RERI).</div></div><div><h3>Results</h3><div>Cold waves had the strongest effect in the central region (cardio RR = 1.044, lag0) and the south (respiratory RR = 1.038, lag21). In the north, heat waves showed the highest risks (cardio = 1.032, lag0; respiratory = 1.041, lag0). PM_2.5 significantly elevated mortality in all regions, especially the south (cardio = 1.013, lag0) and east (respiratory = 1.018, lag0). Cold wave-PM_2.5 interaction was greatest in the central region (respiratory RERI = 0.308; cardio = 0.203), followed by Bangkok (respiratory = 0.019; cardio = 0.070). Heat wave-PM_2.5 interaction was also significant in Bangkok and the south. Bangkok residents were vulnerable to both ETEs; the south experienced only heat wave-PM_2.5 effects. In sensitive subgroups, interactions heightened cardiovascular susceptibility among females (cold wave = 0.117; heat wave = 0.045), older adults ≥65 (cold wave = 0.066; heat wave = 0.031), and in sub-diseases like pulmonary heart disease (cold wave = 0.054; heat wave = 0.141) and lung diseases from external causes (cold wave = 0.264; heat wave = 0.306).</div></div><div><h3>Conclusions</h3><div>Interactions between ETEs and PM_2.5 significantly increased mortality risks in tropical subpopulations, particularly during cold waves. These findings support urgent global preparedness to mitigate health impacts from the convergence of climate extremes and air pollution in tropical contexts.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"20 ","pages":"Article 101276"},"PeriodicalIF":0.0,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144866825","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}