AIMC Topic: Cities

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Enhancing particulate matter prediction in Delhi: insights from statistical and machine learning models.

Environmental monitoring and assessment
This study advances our approach to modeling particulate matter levels-specifically, PM and PM-in Delhi's dynamic urban environment through an extensive evaluation of traditional time series models (ARIMAX, SARIMAX) and machine learning models (RF, S...

Quantifying urban land cover imperviousness as input for flood simulation using machine learning: South African case study.

Water science and technology : a journal of the International Association on Water Pollution Research
The imperviousness of urban surfaces is an important parameter in simulating urban hydrological responses, but quantifying imperviousness can be challenging and time-consuming. In response, this study presents a new framework to efficiently estimate ...

Social media interaction and built environment effects on urban walking experience: A machine learning analysis of Shanghai Citywalk.

PloS one
In fast-paced urban environments, Citywalk has emerged as a key leisure activity for urban residents to alleviate stress and enhance emotional well-being. From the perspective of virtual-physical interaction, this study integrates social media data w...

Deep learning-based spatial optimization of green and cool roof implementation for urban heat mitigation.

Journal of environmental management
Intensifying urban heat extremes require efficient mitigation strategies; therefore, we propose a methodological framework for optimizing the implementation of urban green and cool roofs to reduce heat stress while maximizing their cost-effectiveness...

Efficient urban flood control and drainage management framework based on digital twin technology and optimization scheduling algorithm.

Water research
Urban flood control and drainage systems often face significant challenges in coordinating municipal drainage with river-lake flood prevention during flood seasons. Rising river levels can create backwater effects, which substantially increase urban ...

Source apportionment of PM particles in the urban atmosphere using PMF and LPO-XGBoost.

Environmental research
Atmospheric particulate matter (PM), as a leading part of air pollution, affects health in many ways. Thus, identifying and quantifying the contribution of atmospheric particulate matter sources of PM is vital for developing effective air quality man...

A measurement-based framework integrating machine learning and morphological dynamics for outdoor thermal regulation.

International journal of biometeorology
This study presents a comprehensive investigation into the interplay between machine learning (ML) models, morphological features, and outdoor thermal comfort (OTC) across three key indices: Universal Thermal Climate Index (UTCI), Physiological Equiv...

Enhancing the resilience of urban drainage system using deep reinforcement learning.

Water research
Real-time control (RTC) is an effective method used in urban drainage systems (UDS) for reducing flooding and combined sewer overflows. Recently, RTC based on Deep Reinforcement Learning (DRL) has been proven to have various advantages compared to tr...

Climate investment and financing, economic growth target constraints and urban green development efficiency.

Journal of environmental management
Climate change constitutes a multidimensional crisis impacting global security and sustainable development, and immediate collective response is necessitated to address this challenge for all humankind. Guiding climate investment and financing (CIF) ...

Is the energy quota trading policy a solution to carbon inequality in China? Evidence from double machine learning.

Journal of environmental management
Implementing China's energy quota trading policy, as a typical market-based environmental regulation, thoroughly deepens the reform of energy market allocation. While the inhibitory effect of energy quota trading on carbon emissions is evident, its i...