Nairui Liu

TL;DR: In this article, the authors proposed a method to estimate the UHI mitigation effect of cool coatings via increasing the albedo values in the Weather Research and Forecasting (WRF) model.

TL;DR: In this paper, a deep learning technique called Long Short-Term Memory (LSTM) was used to extend the use of air quality monitor data via deep learning techniques, which can be used to provide indicative information about air pollutants around the training location.

TL;DR: In this paper, the authors investigated the trends of number, frequency, and duration of pollution episodes and compared these with the baseline trend in air pollution, and showed that the factors contributing to these events are complex; however, longterm measures to abate emissions from all anthropogenic sources at all times is also the most efficient way to reduce the occurrence of severe air pollution events.

TL;DR: It is concluded that EKC theory is not a useful tool to predict the location of the turning points, and policy makers should not anchor their hopes on predicting turning points from previous studies, but should put more effort into dealing with present particulate matter pollution.