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1st International Conference on Pollution Control for Clean Environment, ICPCCE 2023

作者： Nawale, Prashant Sahu, Manoranjan Aerosol and Nanoparticle Technology Laboratory Environmental Science and Engineering Department Indian Institute of Technology Bombay Mumbai400076 India Interdisciplinary Program in Climate Studies Indian Institute of Technology Bombay Mumbai400076 India Centre for Machine Intelligence and Data Science Indian Institute of Technology Bombay Mumbai400076 India

ISBN: (纸本)9789819778454

Air pollution has become a serious global issue, which has significant impacts on both human health and the environment. Over the past decade, air quality has deteriorated due to various anthropogenic activities including construction, urbanization and industrialization. These activities release hazardous particles and harmful gases into the atmosphere, contributing to poor air quality. Developing countries such as India have been particularly affected, with some of their cities among the most polluted worldwide. To address this serious concern, it is imperative to develop and implement air pollution control technologies for both indoor and outdoor environments. This study focuses on the structured investigation of the performance of locally available air filter media in terms of their removal efficiency for submicron and micron-size particles. Various indigenous air filter media are subjected to rigorous testing to evaluate their overall and size-specific filtration efficiency and corresponding differential pressure drop. The results of these performance evaluations are then compared to their effectiveness in removing coarse and fine particles from the air. This research aims to provide valuable insights into the development of effective air filtration systems to combat air pollution. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Air filters Air pollution control technology Air purification Coarse PM Fine PM

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Increasing risk of oppressive heatwaves over India in the future warming

arXiv

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arXiv 2025年

作者： Sudharsan, Naveen Singh, Jitendra Ghosh, Subimal Karmakar, Subhankar Environmental Science and Engineering Department Indian Institute of Technology Maharashtra Bombay India Department of Environmental Systems Science ETH Zürich Zürich Switzerland Department of Civil Engineering Indian Institute of Technology Maharashtra Bombay India Interdisciplinary Program in Climate Studies Indian Institute of Technology Maharashtra Bombay India Centre for Urban Science & Engineering Indian Institute of Technology Maharashtra Bombay India

The frequency of heatwave events has been increasing with climate change across the globe, causing devastating impacts on human and natural systems. Particularly, the co-occurrence of high temperature with high humidity has the potential of worse impacts on human health than extreme temperature alone. We use observations to examine the characteristics of extreme (high temperature and low humidity) and oppressive (high temperature and high humidity) heatwaves and their impacts on human mortality. We also use climate model simulations to understand the likelihood of heatwaves under varied warming conditions in future climates. We find an increasing trend in the number of days of extreme and oppressive heatwaves, with surprisingly a higher rate of increase in oppressive heatwaves. We also observe a higher correlation between oppressive heatwaves and historical heat-stress-related human deaths than extreme heatwaves, indicating more substantial impacts of oppressive heatwaves on the human population than extreme heatwaves. Further, our results show a five-fold increase in the number of days of oppressive heatwaves under 1.5°warming in both mid (2035-2065) and end (2070- 2100) of the 21st century, relative to the historical period (1975 to 2005) whereas the number of extreme heatwave days remains relatively constant in mid and end of this century. Remarkably, 2°warming results in an eight-fold and almost two-fold increase in the number of days of oppressive heatwaves by the end of the century relative to the historical period and 1.5°warming conditions. These results suggest that limiting the mean global warming to 1.5°can reduce the likelihood of oppressive and extreme heatwaves by 44% and 25% by the end of the century relative to the 2°warming world. Moreover, the remarkable increase in oppressive heatwave days highlights the elevated risk of heatwaves over densely populated countries and indicates an imminent need for adaptation measures. © 2025, CC BY.

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Relationship between PM_(10) and PM_(2.5) levels in high-traffic area determined using path analysis and linear regression

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Journal of environmental sciences 2018年第7期30卷 105-114页

作者： Narut Sahanavin Tassanee Prueksasit Kraichat Tantrakarnapa Interdisciplinary Program of Environmental Science Graduate School Chulalongkorn University Department of Environmental Science Faculty of Science Chulalongkorn University Department of Social and Environmental Medicine Faculty of Tropical Medicine Mahidol University

The objective of this study was to determine the relationship between PM10 and PM2.5 levels as related to meteorological conditions and traffic flow using both a linear regression analysis and a path analysis. The Particulate matter（PM） samples were collected from Sukhumvit road, Bangkok, Thailand, at both open（104 samples） and covered（92 samples）areas along the road. Fifteen percent of all samples were separated before the statistical models were run and used for model validation. The results from the path analysis were more elaborate than those from the linear regression, thus indicating that meteorological conditions had a direct effect on the particulate levels and that the effects of traffic flow were more variable in open areas. The model also indicated that meteorological conditions had an indirect effect and that traffic flow had a direct effect on particulate levels in covered areas. The model validation results indicated that for open areas, the R^2 values were not very different between the path analysis and the linear regression model, but that the path analysis was more accurate than the linear regression model at very low PM concentrations. At high PM concentrations, the path analysis model also had a better fit than did the linear regression, so the predictions from the path analysis model were more accurate than those from the linear regression.

关键词： Path analysis PM10 PM2.5 Open roadside area Covered roadside area

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CIWARS: A Web Server for Antibiotic Resistance Surveillance Using Longitudinal Metagenomic Data

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Journal of Molecular Biology 2025年

作者： Emon, Muhit Islam Cheung, Yat Fei Stoll, James Rumi, Monjura Afrin Brown, Connor Choi, Joung Min Moumi, Nazifa Ahmed Ahmed, Shafayat Song, Haoqiu Sein, Justin Yao, Shunyu Khan, Ahmad Gupta, Suraj Kulkarni, Rutwik Butt, Ali Vikesland, Peter Pruden, Amy Zhang, Liqing Department of Computer Science Virginia Tech Blacksburg 24060 VA United States Fralin Life Science Institute Virginia Tech Blacksburg 24060 VA United States Department of Civil and Environmental Engineering Virginia Tech Blacksburg 24060 VA United States The Interdisciplinary PhD Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg 24060 VA United States

The rise of antibiotic resistance (AR) poses a substantial threat to human and animal health, food security, and economic stability. Wastewater-based surveillance (WBS) has emerged as a powerful strategy for population-level AR monitoring, providing valuable data to guide public health and policy decisions. Metagenomic sequencing is especially promising, as it can yield comprehensive profiles of antibiotic resistance genes (ARGs) and other genes relevant to AR in a single run. However, online analytical platforms to facilitate analysis of longitudinal metagenomic data are lacking. To address this, we introduce CyberInfrastructure for Waterborne Antibiotic Resistance Surveillance (CIWARS), a web server configured for characterizing key AR trends from longitudinal metagenomic WBS data. CIWARS offers comprehensive profiling of ARGs and taxonomic profiling of pathogen-associated bacterial taxonomic groups, identifies potential associations of ARGs with mobile genetic elements (MGEs) and pathogen-containing taxa, and assesses resistome risk based on the co-occurrence of ARGs, MGEs, and pathogen-like sequences. Additionally, it detects anomalous AR indicators over time, aiding in identifying potential events of concern, such as the emergence of resistant strains or outbreaks. Through interactive temporal data visualization, CIWARS enables AR monitoring and can serve as a tool to inform effective and timely interventions to mitigate the spread and transmission of AR. Here, CIWARS is demonstrated using longitudinal metagenomic data from a wastewater treatment plant (WWTP) influent and effluent, but it can be extended to any environment. CIWARS provides a valuable tool to support global efforts to combat the evolution and spread of AR, while also guiding agricultural and public health efforts aimed at optimizing antibiotic use. The web server is freely available at https://***/. © 2025 Elsevier Ltd

关键词： anomaly detection antibiotic resistance (AR) AR indicator profiling longitudinal metagenomics wastewater-based surveillance

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Adaptive governance in the water-energy-food-ecosystem nexus for sustainable community sanitation

World Development Sustainability

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World Development Sustainability 2025年 6卷

作者： Sofiyah, Evi Siti Sianipar, Imelda Masni Juniaty Rahman, Ari Caesarina, Naila Putri Suhardono, Sapta Suryawan, I Wayan Koko Lee, Chun-Hung Department of Environmental Engineering Faculty of Infrastructure Planning Universitas Pertamina Jalan Sinabung II Terusan Simprug Jakarta 12220 Indonesia Department of International Relations Faculty of Social Science and Political Science Universitas Kristen Indonesia Jakarta 13630 Indonesia Environmental Sciences Study Program Faculty of Mathematics and Natural Sciences Universitas Sebelas Maret Surakarta 57126 Indonesia Department of Natural Resources and Environmental Studies College of Environmental Studies and Oceanography National Dong Hwa University Hualien 97401 Taiwan Center for Environmental Solution (CVISION) Universitas Pertamina Jalan Sinabung II Terusan Simprug Jakarta 12220 Indonesia Center for Interdisciplinary Research on Ecology and Sustainability College of Environmental Studies and Oceanography National Dong Hwa University Hualien 97401 Taiwan

As the intensity of global environmental challenges increases, so does the need to understand and strengthen the resilience of interconnected systems. This research underscores the crucial role of adaptive governance in navigating the complexities of the Water-Energy-Food-Ecosystem nexus, particularly under the pressures of changing climatic conditions. The study conducts an in-depth analysis of adaptive capacities by identifying critical components such as assets, flexibility, organization, learning, and agency as fundamental elements of adaptive governance in sanitation practices. Data were collected through structured questionnaires and analyzed using binary probit and logit models to examine how these attributes influence community engagement in sanitation. Descriptive analysis was also used to summarize respondent characteristics and attribute distributions. © 2025 The Author(s)

关键词： Adaptive governance Community engagement environmental sustainability Sanitation resilience Water-energy-food-ecosystem nexus

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Urban food waste generation and sustainable management strategies: a case study of Nonthaburi Municipality, Thailand

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Scientific reports 2025年第1期15卷 18405页

作者： Pantakan Choochote Nuta Supakata Department of Environmental Science Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. Interdisciplinary Program in Environmental Science Graduate School Chulalongkorn University Chulalongkorn University Bangkok 10330 Thailand. Department of Environmental Science Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. nuta.s@chula.ac.th. Interdisciplinary Program in Environmental Science Graduate School Chulalongkorn University Chulalongkorn University Bangkok 10330 Thailand. nuta.s@chula.ac.th. Research Unit (RU) of Waste Utilization and Ecological Risk Assessment Chulalongkorn University Bangkok 10330 Thailand. nuta.s@chula.ac.th.

Although increasing global attention has been devoted to food waste management, there is still a critical research gap in understanding waste patterns and developing contextualized solutions for rapidly urbanizing areas in developing nations, where waste management infrastructure lags behind urban expansion. Using stratified random sampling of 244 sources encompassing markets, restaurants, institutions, and residential areas in Nonthaburi Municipality, Thailand, this study identified and characterized three distinct food waste categories: edible surplus food (FW1), food preparation waste, including spoiled items and bones (FW2), and postconsumption remnants (FW3). Analysis of the waste proportion patterns revealed that FW2 predominated (65.53%), followed by FW3 (32.55%) and FW1 (1.92%). Fresh markets constituted the principal source of waste generation (294.1 ± 42.3 kg/day), yielding a significantly greater quantity than private markets (117.61 ± 35.7 kg/day) and supermarkets (20.4 ± 12.8 kg/day). Statistical analyses revealed significant variations (p < 0.05) in food waste proportions across source categories. Given these findings and local infrastructure limitations, this study proposes a systematic, three-phase implementation strategy: (1) Immediate application of FW3 conversion to aquaculture feed, with an estimated food waste diversion potential of 10.72 ± 7.15 tons/day; (2) medium-term establishment of FW1 redistribution programs, which target 1.92% of total waste identified as edible surplus food, with a projected daily redistribution capacity of 0.153 ± 0.11 tons; and (3) long-term development of FW2 biofertilizer facilities, with an estimated food waste diversion potential of 52.62 ± 18.95 tons/day. This integrated approach simultaneously advances multiple sustainable development goals and establishes a replicable framework for sustainable food waste management in rapidly urbanizing regions of developing nations. The findings provide essential guidance for

关键词： Food waste management Nonthaburi municipality Sustainable urban food waste management

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Deep learning-based high-throughput detection of flowered maize (Zea mays L.) plots from UAS imagery across environments

Plant Phenome Journal

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Plant Phenome Journal 2025年第1期8卷

作者： Shepard, Nicholas R. DeSalvio, Aaron J. Arik, Mustafa Adak, Alper Murray, Seth C. Varela, Jose Ignacio Department of Molecular & Environmental Plant Science (Department of Biochemistry and Biophysics) Texas A&M University College Station TX United States Interdisciplinary Graduate Program in Genetics and Genomics (Department of Biochemistry and Biophysics) Texas A&M University College Station TX United States Department of Soil and Crop Sciences Texas A&M University College Station TX United States Department of Plant and Agroecosystem Sciences University of Wisconsin–Madison Madison WI United States

Flowering time is a critical phenological trait in maize (Zea mays L.) breeding programs. Traditional measurements for assessing flowering time involve semi-subjective and labor-intensive manual observation, limiting the scale and efficiency of genetics and breeding improvement. Leveraging unoccupied aerial system (UAS, also known as unoccupied aerial vehicles or drones) technology coupled with convolutional neural networks (CNNs) presents a promising approach for high-throughput detection of flowered plots in maize. Most CNN image analysis is overly complicated for simple tasks relevant to plant scientists. Here, a methodology for extracting tasseling from UAS red/green/blue imagery using a CNN-based approach was applied to 220 hybrids and 30 test lines grown in eight diverse environments (Wisconsin and Texas) and then validated through an unrelated set of hybrids. Overall accuracies of 0.946, 0.911, 0.985, and 0.988 were obtained for classifying maize images with or without tassels from College Station, TX, in 2020;College Station, TX, in 2021;Arlington, WI, in 2021;and Madison, WI, in 2021, respectively. By employing deep learning techniques, larger volumes of phenotypic data can be processed enabling high-throughput phenotyping in breeding programs. Although large datasets are required to train CNN models, the proposed methodology prioritizes simplicity in computational architecture while maintaining effectiveness in identifying flowered maize across diverse genotypes and environments. © 2025 The Author(s). The Plant Phenome Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy and Crop science Society of America.

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Irreversible Land Water Availability Changes From a Potential ITCZ Shift During Temperature Overshoot

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Earth's Future 2025年第5期13卷

作者： Steinert, Norman Julius Schwinger, Jörg Chadwick, Robin Kug, Jong-Seong Lee, Hanna NORCE Norwegian Research Centre Bjerknes Centre for Climate Research Bergen Norway CICERO Center for International Climate Research Oslo Norway Met Office Hadley Centre Exeter United Kingdom Global Systems Institute Department of Mathematics and Statistics University of Exeter Exeter United Kingdom School of Earth and Environmental Sciences Seoul National University Seoul South Korea Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul South Korea Department of Biology Norwegian University of Science and Technology Trondheim Norway

Without rapid emission reduction, it is increasingly likely that global temperatures will overshoot 1.5°C before carbon dioxide removal may help reverse warming. Such temperature overshoots affect the future hydrological cycle, with implications for land water availability. However, the hydrological response to such temperature overshoots is not well understood. Here, we investigate regional and seasonal changes of precipitation minus evaporation (P − E) in an ensemble of Earth system model simulations of temperature overshoot. Most climate models broadly show P − E reversibility after overshoot. However, models exhibiting an irreversible shift of the intertropical convergence zone (ITCZ) during the temperature overshoot experience reduced wet-season and enhanced dry-season land water availability in tropical regions, which has long-lasting effects on the amplitude of P − E seasonality after the overshoot, constituting irreversible changes on human timescales. While some regions may experience alleviating seasonal hydrological conditions, others are subject to more intense seasonality. Half a century of CO₂-stabilization after the temperature overshoot only halves the legacy effects of the overshoot on land water availability on over 23% of the world population in 12% of the global land area, covering regions of various hydrological regimes. Based on the model ensemble presented here, a strong irreversible shift of the ITCZ after an overshoot is a low-probability but high-impact outcome that would entail long-lasting hydrological changes with consequences for ecosystems and human societies. © 2025 The Author(s).

关键词： carbon dioxide removal hydrological cycle intertropical convergence zone precipitation minus evaporation (P − E) temperature overshoot water availability

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引用

BIRTH DEFECTS RESEARCH 2017年第15期109卷 1236-1236页

作者： Desai, Rahat Wadhwa Smith, Mary Alice Interdisciplinary Toxicology Program Center for Food Safety University of Georgia Athens Georgia Regenerative Bioscience Center University of Georgia Athens Georgia Environmental Health Science Department University of Georgia Athens Georgia

About one in seven cases of listeriosis occurs in pregnant women, and, although listeriosis is rare, it is the third leading cause of death from food-borne infections. Pregnancy-related listeriosis increases the risk for fetal and neonatal mortality by approximately 21%. During pregnancy, infections are more likely to occur in the third trimester (66%) than the first trimester (3%). However, fetal and neonatal adverse effects are less common as gestational age increases or with older gestational age at birth. Pregnant women seem highly susceptible in some listeriosis outbreaks making up a large percentage of cases, whereas others contain very few. Whether this results from differences in strains of L. monocytogenes, exposures, or other factors remains to be determined. Food and Agriculture Organization of United Nations/World Health Organization (FAO/WHO) estimates the human lethal dose for 50% (LD50 ) for fetal/neonatal loss is 1.9 × 106 colony forming units (CFUs) L. monocytogenes. Animal models have been developed for pregnancy-related listeriosis showing similar susceptibility and clinical outcomes as in humans. Nonhuman primate and guinea pig animal models have similar (LD50 ) values to the estimated human LD50 . Additional animal studies are needed to understand the pathways leading to fetal and neonatal listeriosis in humans. More information is needed to understand dose response, to model risk for listeriosis at lower concentrations, and to determine why some pregnant women may be more susceptible than others. To better treat listeriosis during pregnancy, biomarkers for early diagnosis of listeriosis are also needed. Last, pregnant women need to be educated about avoiding high-risk foods, like Mexican-style cheese and ready-to-eat meats. Birth Defects Research 109:324-335, 2017.© 2017 Wiley Periodicals, Inc.◆ (© 2017 Wiley Periodicals, Inc.)

关键词： Listeria monocytogenes emerging infections listeriosis pregnancy pregnancy-related listeriosis

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Advancing Understanding of Urgent Gaps and Needs in Atmospheric science Key Insights from the Climate, Weather, and Water Forum

Advancing Understanding of Urgent Gaps and Needs in Atmosphe...

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作者： Zhang, Lujia Song, Yurong Cheng, Tat Fan Lu, Mengqian Interdisciplinary Program Office Hong Kong University of Science and Technology Hong Kong Department of Civil and Environmental Engineering Hong Kong University of Science and Technology Hong Kong

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