Environmental Challenges最新文献

{"title":"Advancing postharvest storage management using sensors and smart technologies: A national and global perspective","authors":"Awais Ahmad ,&nbsp;Fazal Jalal ,&nbsp;Shah Fahad ,&nbsp;Nazia Tahir ,&nbsp;Aqib Iqbal ,&nbsp;Rukhsar Bakhtaj ,&nbsp;Sarir Ahmad ,&nbsp;Zafar Hayat Khan ,&nbsp;Badshah Islam ,&nbsp;Mahmood Hemat ,&nbsp;Tanzeel Ur Rahman ,&nbsp;Shah Saud ,&nbsp;Taufiq Nawaz","doi":"10.1016/j.envc.2025.101379","DOIUrl":"10.1016/j.envc.2025.101379","url":null,"abstract":"<div><div>The transformation of crop yield storage management through sensor technologies is the most promising solution, addressing the critical issue of post-harvest losses that threaten global food security. The present review explains various sensor-based systems in monitoring and controlling environmental factors such as temperature, humidity and gas emissions to maintain crop quality and prevent spoilage. This review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Scoping Reviews) guidelines to ensure transparency, rigor and reproducibility in literature identification, screening and synthesis. The review discusses sensor applications across various crop types that range wide from cereals and pulses to perishable fruits and high-value crops, emphasizing customized solutions targeting specific storage requirements. On a regional basis, disparities in technological advancement are evident, with high-tech automated systems being the predominantly concentrated in developed countries, whereas those that favor innovation with sensor solutions that are cheap and scalable, while developing countries are characterized by infrastructural constrains and a focus on affordable, scalable innovations. Pakistan’s early initiatives in sensor-based storage management illustrate how much technologies can enhance agricultural resilience in similar developing context. The initial disposition of Pakistan toward sensor-centered storage management serves as an emblem of how such technology can promote agricultural resilience in settings of comparable nature. Economic analysis indicates a favorable cost-benefit ratio for sensors deployment, hinged upon a reduction in post-harvest losses, energy efficiency in storage, and socioeconomic upliftment of smallholder farmers. Nevertheless, challenges such as high initial investment, skill gaps, sensor durability, connectivity challenges, and policy hurdles remain acute. The future is one where AI powered smart storage systems, nanotechnology-based sensors, and synergized digital ecosystems will offer precision, automation, and sustainability. This requires joint efforts between governments, the private sector, and international agencies to increase the scale of innovations and build capacity. Overall, sensors technologies are revolutionizing sustainable, technology-enabled agricultural storages systems that preserve food security, promote efficient resource use and improve livelihood worldwide.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101379"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749829","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":"Synthesis, characterization, and response surface methodology-based parametric optimization of copper-modified LSX zeolite for efficient cyanide ion removal","authors":"Leta Dereje Wilessa,&nbsp;Abdi Nemera Imana PhD,&nbsp;Abdisa Jabesa PhD,&nbsp;Gadissa Tokuma Gindaba","doi":"10.1016/j.envc.2025.101385","DOIUrl":"10.1016/j.envc.2025.101385","url":null,"abstract":"<div><div>Cyanide contamination from industrial and mining effluents poses a serious environmental and public health risk. This study reports the synthesis, characterization, and parametric optimization of copper-modified low-silica X (Cu-LSX) zeolite for efficient cyanide ions (CN⁻) removal. The adsorbent was prepared by hydrothermal synthesis and copper ion exchange, and characterized using Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, and Brunauer-Emmett-Teller (BET). The results show that Cu-LSX possesses a higher surface area (432.1 m²/g) than unmodified LSX (285.2 m²/g), along with improved porosity, stability, and a preserved crystalline structure. SEM image confirmed the formation of a porous morphology, which is suitable for adsorption. The equilibrium adsorption isotherm analysis for CN⁻ on the Cu-LSX zeolite showed that the Langmuir model (R² = 0.9975) provided a slightly better fit than the Freundlich model (R² = 0.9930). This suggests that CN⁻ adsorption proceeds predominantly via monolayer coverage on a homogeneous surface, indicating the Langmuir isotherm as the more appropriate model for describing the adsorption process. Optimization of process parameters using response surface methodology (RSM) (central composite design (CCD)) revealed an optimal CN⁻ removal efficiency of 96.7 %. The two-factor interaction (2FI) model provided the best fit (R² = 0.997), confirming the reliability of the predictions. These findings demonstrate that Cu-LSX zeolite is a robust, high-capacity adsorbent with significant potential for industrial wastewater treatment applications.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101385"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749832","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":"AI-driven biomass discrimination of palm fronds using low-cost vision sensors for sustainable waste valorization","authors":"Ramayanty Bulan ,&nbsp;Darwin ,&nbsp;Devianti ,&nbsp;Agustami Sitorus ,&nbsp;Hasanuddin","doi":"10.1016/j.envc.2025.101397","DOIUrl":"10.1016/j.envc.2025.101397","url":null,"abstract":"<div><div>The development of agricultural machinery for palm trees still faces challenges due to differences in the physical and mechanical properties of fronds and leaves between species. Shredding machines that operate without sensors have difficulty adjusting rotational speed and cutting angle, resulting in decreased performance when faced with variations in raw materials. Therefore, the objective of this study is to classify three types of palm fronds and leaves, including <em>Areca catechu</em> L. (AR), <em>Cocos nucifera</em> (CN), and <em>Elaeis guineensis</em> Jacq. (EG), using a low-cost camera with a resolution of 1920 × 1080 pixels, combined with ensemble machine learning. Samples were prepared under fresh, incubated, and dried conditions, comprising a total of 810 fronds and 972 leaves. Three feature extraction methods were applied, including RGB, Oriented FAST and Rotated BRIEF (ORB), and Lab color space, which were then analyzed using two machine learning ensemble algorithms, including gradient boosting for classification (GBC) and histogram-based gradient boosting classification tree (HGBC). The combination of ORB with HGBC achieved the highest accuracy for fronds (79.6%), while Lab with HGBC was superior for leaves (84.6%). The Lab is the most consistent feature, while ORB is clear for fronds structure. This classification system has the potential to be used as a smart sensor integrated into palm shredding machines, enabling automated operation control and increasing biomass processing efficiency.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101397"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939034","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":"Impact of elevated transportation infrastructure on urban thermal environment in Dhaka Megacity, Bangladesh","authors":"Farhad Hossain ,&nbsp;Janifar Hakim Lupin ,&nbsp;Md. Mahin Uddin ,&nbsp;Md. Yousuf Gazi ,&nbsp;Md. Zillur Rahman ,&nbsp;A. S. M. Maksud Kamal","doi":"10.1016/j.envc.2025.101400","DOIUrl":"10.1016/j.envc.2025.101400","url":null,"abstract":"<div><div>Rapid urbanization in developing countries often leads to elevated transportation infrastructure, yet the localized thermal impacts of such linear developments remain understudied. This research provides critical insight into how Dhaka’s newly constructed elevated metro rail (MRT Line-6) disrupts the urban thermal balance, acting as a heat corridor through the city. Using high-resolution satellite data (2015–2023), we quantify a 3–5.5°C rise in Land Surface Temperature (LST) along the metro route, driven by vegetation removal and heat-absorbing concrete structures. Spatio-temporal analysis reveals peak LST (36°C in 2020) during intensive construction, while the Urban Thermal Field Variance Index (UTFVI) shows expansion of extreme Urban Heat Island (UHI) zones from 29.5% (2015) to 33.8% (2023). A reversal in the NDVI-LST relationship from negative (cooling by vegetation) to positive (warming by impervious surfaces) highlights the strong thermal influence of the metro corridor. Climatic data indicate that land-cover modification associated with metro construction played a dominant role in the observed temperature anomalies, while broader urban processes likely contributed to background warming. These findings underscore the need to address linear infrastructure as a distinct contributor to UHI effects. We recommend targeted mitigation strategies (e.g., green roofs, vertical vegetation) to offset thermal impacts. This integrated approach connects the link between rising heat and infrastructure, providing an applied roadmap for designing more sustainable and climate-resilient transport systems in one of the world’s fastest-growing cities.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101400"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939055","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":"Geospatial assessment of environmental liabilities: Water stress and climate resilience along Tanzania's Belt and Road Initiative Corridors","authors":"Kizito Ngowi ,&nbsp;Min Ji ,&nbsp;Hanyu Ji ,&nbsp;Zequn Liu ,&nbsp;Pengfei Song","doi":"10.1016/j.envc.2025.101391","DOIUrl":"10.1016/j.envc.2025.101391","url":null,"abstract":"<div><div>Large-scale infrastructure corridors in developing regions face mounting environmental constraints as hydrological stress intensifies and climate variability accelerates, underscoring the need for diagnostic, spatially explicit risk assessment tools. To address this critical gap, this study implements an enhanced, uncertainty-bounded geospatial framework to quantify environmental liabilities along Tanzania’s three principal development axes—the Central Corridor, Standard Gauge Railway, and Mtwara Corridor—over 2019–2024. The analysis integrates multi-temporal Sentinel-2 MSI, MODIS NDVI, and CHIRPS precipitation datasets to construct a validated Standardized Water Stress Index (WSI) derived from anomaly-based MNDWI Z-scores and independently verified against the Standardized Precipitation Index (Spearman’s ρ = –0.62, <em>p</em> &lt; 0.001). A diagnostic Composite Climate Resilience Index (CRI) developed through PCA (KMO = 0.84; cumulative variance = 81.0 %) enables decomposition of dominant vulnerability drivers. Findings show that 42.1 % (95 % CI: 40.2–43.8 %) of transport infrastructure and 50.0 % (95 % CI: 47.9–52.1 %) of new urban expansion (1810 ha) lie within high water-stress zones (WSI &gt; 0.80), indicating substantial exposure to hydrological deficits. Temperature Stability (35.0 % ± 2.8 %) and Precipitation Consistency (28.0 % ± 2.4 %) were identified as the principal determinants of climate resilience, generating marked regional disparities (CRI range: 0.45–0.75). All workflows were implemented in Google Earth Engine and Python, with full reproducibility ensured through a permanently archived DOI. The study introduces a scalable pre-development screening protocol linking hydrological reliability and climatic stability to infrastructure viability, delivering actionable diagnostics for climate-sensitive planning, targeted adaptation, and SDG-aligned development in data-limited regions.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101391"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939099","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":"Multi-index evaluation of surface water quality at the transboundary section of the Mekong River: A case study of Nakhon Phanom Province, Thailand","authors":"Torpong Kreetachat ,&nbsp;Saksit Imman ,&nbsp;Nopparat Suriyachai ,&nbsp;Nathiya Kreetachat ,&nbsp;Sukanya Hongthong ,&nbsp;Kowit Suwannahong ,&nbsp;Panarat Phadee ,&nbsp;Athicha Janthakhot ,&nbsp;Surachai Wongcharee","doi":"10.1016/j.envc.2026.101414","DOIUrl":"10.1016/j.envc.2026.101414","url":null,"abstract":"<div><div>A seasonal, multi-index examination of surface water quality was performed for the Mekong River at the Thailand-Lao transboundary section in Nakhon Phanom Province, utilizing six internationally recognized Water Quality Indices such as MRC-WQI_al, PCD-WQI, NSF-WQI, CCME-WQI, BIS-WQI, and EU-WQI. The monitoring period showed that the Mekong River always had good oxygen levels (DO = 7.48–8.77 mg/L), which shows that it has a strong ability to clean itself. However, pronounced nutrient amplification during the dry season became the primary ecological control, with ammonium levels rising from 0.03 to 0.04 to 0.27–0.39 mg/L, nitrate levels from 0.23 to 0.32 to 1.86–1.95 mg/L, and total phosphorus levels from 0.04 to 0.06 to 0.43–0.48 mg/L, surpassing eutrophication thresholds by nearly threefold. Microbial contamination exhibited an inverse seasonal trend, with total coliforms reaching their zenith in the wet season (1.69–1.90 × 10⁴ MPN 100 mL⁻¹) because of storm runoff and diffuse fecal loading, subsequently experiencing a 5–6-fold reduction in the dry season. The assessment of heavy metals revealed that most elements had low concentrations. However, cadmium consistently exceeded international safety limits, resulting in hazard quotients as high as 6.67 and dominating the overall ecological risk index. There was a big difference between the WQI frameworks. Ecological indices (MRC-WQIal and CCME-WQI) showed a clear change from good to very good quality in the wet season to bad to marginal quality in the dry season. On the other hand, general-use indices (PCD-WQI, NSF-WQI, BIS-WQI) still rated the river as good to very good, showing that single-index interpretation can hide a lot of risk. The Mekong River has two types of seasonal risks right now: wet-season microbial contamination and dry-season phosphorus-driven eutrophication. There is also a constant risk of cadmium. These results show reliable transboundary river management and early warning of ecological degradation in the Lower Mekong Basin, which need integrated, multi-index, seasonally resolved frameworks.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101414"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077919","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":"Drinking water quality, environmental health risk assessment, and household perceptions of preventive capacity in the Ciliwung Watershed, Indonesia","authors":"Fitri Kurniasari ,&nbsp;Bambang Wispriyono ,&nbsp;Sifa Fauzia ,&nbsp;Ghina Labibah ,&nbsp;Alfian Fauzi Firdaus ,&nbsp;Masashi Kato","doi":"10.1016/j.envc.2026.101416","DOIUrl":"10.1016/j.envc.2026.101416","url":null,"abstract":"<div><div>Limited access to piped water infrastructure has made drinking water quality a critical public health concern in many developing countries, including Indonesia. In densely populated urban areas of Greater Jakarta, households within the Ciliwung Watershed continue to rely heavily on groundwater sources that are vulnerable to chemical and microbiological contamination. This study comprehensively assessed drinking water quality, performed a screening-level environmental health risk assessment, and evaluated household awareness and preventive capacity in the Ciliwung Watershed. Water samples were collected from four locations representing upstream, midstream, and downstream sections of the watershed and analyzed for chemical parameters (Mn, NO3-, Fe, and Zn) and microbiological indicators (total coliforms). A screening-level environmental health risk assessment was performed following the US EPA framework, considering ingestion and dermal contact exposure pathways. Household risk perception and vulnerability were evaluated using the Household Water Insecurity Experiences (HWISE) questionnaire. The results showed that levels of Mn, NO3-, and total coliforms exceeded WHO guideline values at multiple sites, with the highest levels observed downstream, indicating cumulative urban influences on groundwater quality. In contrast, Fe and Zn concentrations remained low and within acceptable limits across all sites. Comparative analysis revealed that well water contained significantly higher levels of Mn, NO3-, and total coliforms than piped water, but not levels of Fe and Zn. Although contaminant concentrations were generally lower in piped water, ingestion remained the dominant pathway of potential health risk concern. While households demonstrated high awareness of water-related risks, preventive capacity differed between well-water and piped-water users. These findings underscore the need for integrated interventions combining risk communication, improved water quality monitoring, and expanded access to safe water in urban watershed settings.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101416"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077921","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":"Achieving zero hunger: A global policy lens on food security drivers and income group disparities","authors":"Nirmani Pulle ,&nbsp;Prasad Sampath ,&nbsp;Sarah Perera ,&nbsp;Dinuli Wijayaweera ,&nbsp;Ruwan Jayathilaka","doi":"10.1016/j.envc.2026.101409","DOIUrl":"10.1016/j.envc.2026.101409","url":null,"abstract":"<div><div>Many countries struggle to meet their daily dietary requirements despite numerous attempts to address the existing demand. Consequently, this study collectively analyses the impact of urbanisation, renewable energy, greenhouse gas emissions, population growth, gross domestic product per capita and agricultural land on food production relying on Sen’s Entitlement Theory, thus providing insights to resolve the long-standing issue of food insecurity, and support the achievement of the Sustainable Development Goals. The study utilises a stepwise panel ordered Probit model on 146 countries, for the years 1993 to 2023. It further categorises the food production index into three categories of food security as; low, moderate and high, thereby enabling discussion of the likelihood of a country falling into one of the aforementioned food security categories over the years. Urbanisation, agricultural land, and the dummy variables introduced to represent the income groups have been identified to have a significant and favourable relationship with the food production index. In contrast, the greenhouse gas emissions and renewable energy variables have a significantly inverse impact on the food production index. This makes a unique contribution to the existing body of literature, especially by comparing odds over the years, across different food secure categories, countries, and their specific income levels. This study enables policymakers to gain a comprehensive historical perspective on each case. This study further promotes the Sustainable Development Goals, highlighting areas where these goals have been negatively impacted. Additionally, the study discusses optimised investment allocations, agricultural research and development, agricultural technology, climate resilient farming, and sustainable urbanisation planning as solutions for extreme cases.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101409"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038087","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":"Machine learning-enhanced air quality forecasting and trend analysis: A five-year comprehensive assessment of PM2.5 concentrations in Bangkok, Thailand","authors":"Jeevan Bhatta ,&nbsp;Shiva Raj Acharya ,&nbsp;Kwang Mo Yang","doi":"10.1016/j.envc.2026.101442","DOIUrl":"10.1016/j.envc.2026.101442","url":null,"abstract":"<div><div>Air pollution forecasting is crucial for protecting public health in rapidly urbanizing Asian megacities; however, comprehensive comparative studies of advanced machine learning approaches are limited in Southeast Asian urban environments. This study developed and systematically compared three state-of-the-art machine learning algorithms for operational PM_2.5 forecasting in Bangkok, Thailand, using comprehensive monitoring data from 2020 to 2024. Daily PM_2.5 concentrations and meteorological variables, including temperature, rainfall, wind speed, atmospheric pressure, and relative humidity, were collected from 12 monitoring stations across Bangkok. Three machine learning approaches were implemented and compared: Random Forest (RF), Gradient Boosting (GB), and Long Short-Term Memory (LSTM) neural networks. Advanced feature engineering incorporated temporal lags, moving averages, and cyclical encoding to capture seasonal and temporal dependencies. The dataset comprised 1827 daily observations across all variables. PM_2.5 concentrations exhibited pronounced seasonal variations, with a mean of 21.89 ± 8.71 μg/m³, ranging from winter highs of 29.78 ± 7.88 μg/m³ to rainy-season lows of 14.58 ± 3.16 μg/m³. Strong positive correlations were observed between PM_2.5 and atmospheric pressure (r = 0.473), while negative correlations were found with rainfall (r = -0.260) and relative humidity (r = -0.237). Gradient Boosting demonstrated superior predictive performance, with an RMSE of 2.17 μg/m³ and an R² of 0.935 on an independent external validation dataset comprising 365 days of 2024 data, withheld entirely from model development, confirming genuine generalization to unseen future data. Random Forest achieved RMSE = 3.34 μg/m³ and R² = 0.845 on the same external validation set. To address overfitting identified in preliminary analyses (training R² = 0.964), hyperparameter regularization was substantially strengthened, yielding R² degradation of only 3.9% (Gradient Boosting) and 5.6% (Random Forest) from training to external validation. Feature importance analysis revealed that PM_2.5 temporal features dominated the predictions, with the 3-day moving average achieving the highest importance in Random Forest (42.17%) and Gradient Boosting (60.41%). Short-term forecasting performance (1–7 days) met operational requirements for early warning systems, but performance degraded significantly beyond 14 days. The validated Gradient Boosting framework provides immediate applicability for environmental agencies across Southeast Asian urban centers, supporting evidence-based air quality management and public health protection in rapidly developing megacities.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101442"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395634","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":"A comparative analysis of farm-level economic and greenhouse gas emissions performance: A case study of an alcoholic beverage company’s suppliers in Ireland","authors":"Carel Johannes Kriek ,&nbsp;Thia Hennessy ,&nbsp;John Quinn ,&nbsp;Fiona Thorne","doi":"10.1016/j.envc.2025.101392","DOIUrl":"10.1016/j.envc.2025.101392","url":null,"abstract":"<div><div>The climate and biodiversity crises have prompted most industries to adopt nature-positive actions that support ecosystem functioning and decarbonisation. This shift is prominent in the food and beverage (F&amp;B) sector, particularly multinational alcoholic beverage companies, where regulatory pressure, capital markets, and consumer demand have accelerated efforts to engage suppliers on sustainability. This paper assessed the environmental and economic performance of spring barley suppliers to a global alcoholic beverage company (BC) in Ireland as a case study. To understand performance variability, identify opportunities for improvement, and provide national context, spring barley farmers supplying the BC in Ireland were compared with a nationally representative sample in 2020 and 2023. Estimates of emissions per euro of output and per tonne of spring barley were produced to support the BC’s understanding of its Scope 3 emissions. BC supplying farms outperformed national farms economically, with higher output and margins. The BC farmers had higher total emissions in 2020, decreasing by 2023, resulting in improved emissions efficiency, with BC farms emitting less per euro of output, whilst national farms increased. Synthetic fertiliser emissions were the highest source of emissions for both years. Differences between the years in emissions and economic performance highlight the environmental and economic volatility farmers face in the tillage industry. Our study produces emission efficiency metrics useful to F&amp;B companies, highlights the importance of harmonised data and verification methods for companies wishing to improve sustainability performance. Our findings support F&amp;B companies in working more effectively with suppliers to reduce Scope 3 emissions accountably.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"22 ","pages":"Article 101392"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798443","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}