A5101966308- Atmospheric chemistry and aerosols
- Urban Heat Island Mitigation
- Air Quality and Health Impacts
- Air Quality Monitoring and Forecasting
- Atmospheric aerosols and clouds
- Building Energy and Comfort Optimization
- Urban Green Space and Health
- Wind and Air Flow Studies
- Land Use and Ecosystem Services
- Energy, Environment, and Transportation Policies
- Urban Transport and Accessibility
- Noise Effects and Management
- Atmospheric and Environmental Gas Dynamics
- Metaheuristic Optimization Algorithms Research
- Meteorological Phenomena and Simulations
- Environmental Impact and Sustainability
- Smart Parking Systems Research
- Calibration and Measurement Techniques
- Safety and Risk Management
- Hygrothermal properties of building materials
- Topology Optimization in Engineering
- Advanced Multi-Objective Optimization Algorithms
- Regional Development and Environment
- Environmental Sustainability in Business
- Remote Sensing and Land Use
Tongji University
2021-2025
Shanghai Tongji Urban Planning and Design Institute
2023-2025
Shanghai Meteorological Bureau
2015-2023
National University of Singapore
2020-2023
Air quality forecasting is crucial to reducing air pollution in China, which has detrimental effects on human health. Atmospheric chemical-transport models can provide pollutant forecasts with high temporal and spatial resolution are widely used for routine predictions (e.g., 1–3 days advance). However, the model’s performance limited by uncertainties emission inventory biases initial boundary conditions, as well deficiencies current chemical physical schemes. As a result, experimentation...
A visibility forecast model called a boosting-based fusion (BFM) was established in this study. The uses machine learning based on multisource data, including air pollutants, meteorological observations, moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) and an operational regional atmospheric environmental modeling System for eastern China (RAEMS) outputs. Extreme gradient boosting (XGBoost), light (LightGBM), numerical prediction method, i.e., RAEMS were...
The aim of this paper is to assess the influence meteorological conditions on variability haze in Shanghai during 1981-2013.Based observational data and air quality period National Centers for Environmental Prediction final analysis data, long-term spatial distribution was analyzed as well with relationship between atmospheric variables, including visibility, relative humidity, quality.Temporal evolution showed that annual number days represented a rapid decline last decade, which caused by...
Air pollution has become one of the most challenging problems in China, especially economically developed and densely populated regions such as Shanghai. In this study, long short-term memory (LSTM) model is introduced for application extended-range forecasting PM 2.5 Shanghai by incorporating three members Subseasonal-to-Seasonal Prediction project (S2S) forecasting, moderate-resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data, large-scale circulation factors...
This study aims to evaluate and compare the indoor air velocities thermal environment inside different generations of public residential buildings developed by Housing Development Board (HDB) Singapore analyze impact façade design on environment. To achieve this goal, several case studies were carried out, namely, five typical HDB blocks built in from 1970s recent years. Firstly, these with features simulated obtain temperatures for both window-closed window-open scenarios using EnergyPlus...
The wide variation in household characteristics, such as size, income, and age, can lead to significant differences carbon footprints. Based on data from 1132 Chinese households 2021, this study examines the structural differences, multiple influencing factors, mitigation strategies of footprints (HCFs) China. results indicate that indirect emissions, primarily energy food consumption, account for largest share footprints, making up over 65% total emissions. Households with lower are...