Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …

Heating is a major source of air pollution. To improve air quality, a range of clean heating
policies were implemented in China over the past decade. Here, we evaluated the impacts …

Abstract Machine learning (ML) is an advanced computer algorithm that simulates the
human learning process to solve problems. With an explosion of monitoring data and the …

Deterioration of surface ozone (O 3) pollution in Northern China over the past few years
received much attention. For many cities, it is still under debate whether the trend of surface …

The escalating prevalence of extreme heat events has intensified scholarly interest in
understanding the nexus between urban built environments and extreme heat. This study …

The variation of surface ozone (O 3) is linked to changes in meteorology and emission. A
record-breaking high temperature struck China in the summer of 2022, resulting in positive …

Abstract A long-term (2013–2019) PM 2.5 speciation dataset measured in Tianjin, the
largest industrial city in northern China, was analyzed with dispersion normalized positive …

The air quality in China has been improved substantially, however fine particulate matter
(PM 2.5) still remain at a high level in many areas. PM 2.5 pollution is a complex process …

In this study, a machine learning (ML) framework is developed toward target-oriented
inverse design of the electrochemical oxidation (EO) process for water purification. The …

High concentrations of PM 2.5 and ozone (O 3) seriously threaten human health. In this
study, we constructed a machine learning-based model to predict PM 2.5 and O 3 …