How renewable energy consumption and digitalization contribute to environmental sustainability: Evidence from One Belt One Road countries

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124379 - 124379

Published: March 10, 2025

Language: Английский

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Strengthening Climate Resilience: Urban Water Technologies for Heat-Resilient Physical Infrastructure in Southeast Asia Cities Amidst Extreme Temperature Events and El Niño Challenges

ACS ES&T Water, Journal Year: 2024, Volume and Issue: 4(9), P. 3713 - 3724

Published: Aug. 15, 2024

In the face of escalating climate change impacts, Southeast Asia is witnessing a growing urgency to fortify regional cities against extreme temperatures and exacerbating effects El Niño events. This work delves into role urban water technologies in bolstering heat-resilient infrastructure across region. also assesses that can contribute development areas. involves examining innovative approaches help mitigate impacts on enhance its resilience change. They include green infrastructure, decentralized systems, advanced cooling have potential improve heat stress temperatures. Through empirical studies, this study underscores imperative for proactive measures The implications offer practical insights policymakers, planners, stakeholders bolster region, emphasizing mitigating risks enhancing adaptive capacity. By integrating such as systems southeast region not only heat-related but foster sustainable pathways.

Language: Английский

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Modeling PM10 Emissions in Quarry and Mining Operations: Insights from AERMOD Applications in Malaysia

Atmosphere, Journal Year: 2025, Volume and Issue: 16(4), P. 369 - 369

Published: March 24, 2025

PM10 emissions have been a significant concern in rock crushing and quarry operations (study site #1) iron ore mining projects #2) certain regions of Malaysia, posing fears to the health well-being nearby communities with severe air pollution. To address this issue, it is crucial develop effective mitigation strategies reduce dust particle like ambient air. The AERMOD model was applied predict during projects, both without control measures. results indicated that were reduced when measures implemented. modeling result shows mean concentration study #1 74.85 µg/m3 20,557.69 µg/m3, respectively. In comparison, average #2 53.95 135.69 µg/m3. Therefore, measure has successfully concentrations by 99.90% 60.24% sites #2, respectively, ensures quality complies Malaysian Ambient Air Quality Guidelines (MAAQG) 24 h threshold limits at 100 addition, showed performed better than case study.

Language: Английский

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Human-Centered and Regenerative Design: Leveraging Biomaterials for Climate-Responsive Built Environment

IntechOpen eBooks, Journal Year: 2025, Volume and Issue: unknown

Published: April 14, 2025

As communities face growing pressures, such as rapid urbanization and climate change, transitioning to a regenerative built environment is crucial for more sustainable equitable future. Thus, this chapter explores strategies human-centered that addresses the challenges of urbanization, societal needs through biomaterials. This approach focuses on creating housing infrastructure enhances people’s quality life while reducing environmental footprints, prioritizing sustainability, resilience, adaptability changing conditions. Key considerations include indoor air quality, thermal comfort, restoration. Regenerative design principles focus systems restore regenerate natural ecosystems. Emerging innovations, biomaterials, circular economy concepts are fundamental in implementing these principles. By using renewable resources waste, buildings infrastructures can contribute positively rather than depleting it. Finally, case studies will illustrate how impact health, resilience.

Language: Английский

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Evaluation of Machine Learning Models in Air Pollution Prediction for a Case Study of Macau as an Effort to Comply with UN Sustainable Development Goals

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7477 - 7477

Published: Aug. 29, 2024

To comply with the United Nations Sustainable Development Goals (UN SDGs), in particular SDG 3, 11, and 13, a reliable air pollution prediction model must be developed to construct sustainable, safe, resilient city mitigate climate change for double win. Machine learning (ML) deep (DL) models have been applied datasets Macau predict daily levels of roadside peninsula, situated near historical sites Macau. welcomed over 28 million tourists 2023 as popular tourism destination. Still, an accurate quality forecast has not place many years due lack emission inventory. This work will develop dependable Macau, which is also novelty this study. The methods, including random forest (RF), support vector regression (SVR), artificial neural network (ANN), recurrent (RNN), long short-term memory (LSTM), gated unit (GRU), were successful was trained using meteorological data from 2013 2019 validated 2020 2021. performance evaluated based on root mean square error (RMSE), absolute (MAE), Pearson’s correlation coefficient (PCC), Kendall’s tau (KTC). RF best predicted PM10, PM2.5, NO2, CO concentrations highest PCC KTC prediction. In addition, SVR had stability repeatability compared other models, lowest SD RMSE, MAE, PCC, after five runs. Therefore, results study show that more efficient performs better than dataset

Language: Английский

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Landfill mining: A step forward to reducing CH4 emissions and enhancing CO2 sequestration from landfill

Journal of Hazardous Materials Advances, Journal Year: 2024, Volume and Issue: unknown, P. 100512 - 100512

Published: Oct. 1, 2024

Language: Английский

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Techno-Economic, Environmental, Policy Status and Perspectives on Sustainable Resource Conversion Into Transportation Fuels

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

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Demonstrating multi-benefits of green infrastructure to schools through collaborative approach

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 958, P. 177959 - 177959

Published: Dec. 20, 2024

Language: Английский

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