AIMC Topic: Cities
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Assessment of urban flood susceptibility based on a novel integrated machine learning method.
Environmental monitoring and assessment
Dec 5, 2024
Flood susceptibility assessment is the premise and foundation to prevent flood disaster events effectively. To accurately assess urban flood susceptibility (UFS), this study first analyzes the advantages and disadvantages of multi-layer perceptron (M...
Evaluating drivers of PM air pollution at urban scales using interpretable machine learning.
Waste management (New York, N.Y.)
Dec 1, 2024
Reducing urban fine particulate matter (PM) concentrations is essential for China to achieve the Sustainable Development Goals (SDGs). Identifying the key drivers of PM will enable the development of targeted strategies to reduce PM levels. This stud...
Regional PM prediction with hybrid directed graph neural networks and Spatio-temporal fusion of meteorological factors.
Environmental pollution (Barking, Essex : 1987)
Nov 28, 2024
Traditional statistical prediction methods on PM often focus on a single temporal or spatial dimension, with limited consideration for regional transport interactions among adjacent cities. To address this limitation, we propose a hybrid directed gra...
Spatiotemporal variations of PM and ozone in urban agglomerations of China and meteorological drivers for ozone using explainable machine learning.
Environmental pollution (Barking, Essex : 1987)
Nov 22, 2024
Ozone pollution was widely reported along with PM reduction since 2013 in China. However, the meteorological drivers for ozone varying with different regions of China remains unknown using explainable machine learning, especially during the COVID-19 ...
Can big data policy drive urban carbon unlocking efficiency? A new approach based on double machine learning.
Journal of environmental management
Nov 22, 2024
In recent years, data has increasingly become the "new oil" for 21st-century economic development. However, there is still a gap in how the development of big data promotes the improvement of urban carbon unlocking efficiency (UCUE). Utilizing advanc...
Incorporating dynamic drainage supervision into deep learning for accurate real-time flood simulation in urban areas.
Water research
Nov 19, 2024
Urban flooding has become a prevalent issue in cities worldwide. Urban flood dynamics differ significantly from those in natural watersheds, primarily because of the intricate drainage systems and the high spatial heterogeneity of urban surfaces, whi...
A spatial machine learning approach to exploring the impacts of coal mining and ecological restoration on regional ecosystem health.
Environmental research
Nov 19, 2024
Ecosystem health is an important approach to measuring urban and regional sustainability. In previous studies, the spatiotemporal changes of ecosystem health have been addressed using comprehensive assessment index system. However, the quantitative c...
Evaluation of machine learning and deep learning models for daily air quality index prediction in Delhi city, India.
Environmental monitoring and assessment
Nov 19, 2024
The air quality index (AQI), based on criteria for air contaminants, is defined to provide a shared vision of air quality. As air pollution continues to rise in global cities due to urbanization and climate change, air pollution monitoring and foreca...
Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence.
Journal of hazardous materials
Nov 15, 2024
Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcinogenic health hazards. This study reveals the sources of contaminants in groundwater, their health i...
Big data from population surveys and environmental monitoring-based machine learning predictions of indoor PM in 22 cities in China.
Ecotoxicology and environmental safety
Nov 5, 2024
Many studies have confirmed that PM exposure can cause a variety of diseases. Because people spend most of their time indoors, exposure to PM in indoor environments is critical to population health. Large-population, long-term, continuous, and accura...
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