Previous studies have extensively examined effects of urbanization on mean wind speed, but few studies were aimed at gust wind speed, while large wind gust could cause safety and economic hazard to a variety of activities. In this study, the effect of urbanization on the gust wind speed in Nanjing, China is assessed using the Weather Research and Forecasting model (WRF) with a parameterization of the gust wind speed. The WRF simulations are run for the summer period of 2013 with the underlying surface before and after the urbanization. The results indicate that although the mean wind speed is reduced, the gust wind speed in the urban areas is increased significantly due to the enhanced friction velocity and less atmospheric stability induced by the urbanization, while the contribution of deep convection is relatively small. The gust wind speed increases more in the nighttime (0.6-0.9m s-1) than in the daytime (less than 0.3m s-1), since the turbulence is enhanced more in the nighttime than in the daytime after the urbanization. The probability distribution shows that the increase of gust wind speed is mainly between 0.0-0.5m s-1 in the urban areas. In different urban land categories, the increase of the gust wind speed is larger in the commercial or industrial areas than in high-intensity and low-intensity residential urban areas. Averagely, the gust wind speed in the entire city after the urbanization increases by 0.02, 0.36 and 0.19m s-1 for the daytime, nighttime and daily mean, respectively.

A wind gust parameterization scheme combined with the Weather Research and Forecasting (WRF) model used as the regional climate model (RCM) is employed to simulate and project the gust wind speed at 10‐m height above ground level for the whole China in the historical and future period 1981–2005 and 2036–2060. The gust wind speed is compared between the historical and future period to investigate its long‐term change under the background of warming climate within the CORDEX‐EA‐II project under the RCP8.5 scenario. First, the gust wind speed simulated by the gust parameterization inputted with the RCM simulations driven by the ERA‐Interim reanalysis data is compared with the ERA5 reanalysis data and their discrepancy is discussed. Then the historical/future gust wind speed is simulated/projected with the RCM simulations driven by four global climate models' results. The comparisons between the historical simulations and future projections show the gust wind speeds overall change slightly with little response to the future warming climate as the whole China is concerned, and the maximal increment and decrement of averaged annual maximal gust wind speed are, respectively, 2.25 and −2.57 m·s−1. The increases greater than 1 m·s−1 are mostly located in the eastern and southeastern coast and northwestern inland while the decreases less than −1 m·s−1 are mostly located in part of the Tibet Plateau and northwestern inland.

In this study, a latest reanalysis dataset of atmospheric composition, the Global Exposure Mortality Model and a log-linear exposure-response function were employed to estimate the national deaths attributable to fine particulate matter (PM2.5) and ozone (O3) pollution in China for the period 2016-2020, including the lockdown due to COVID-19 pandemic in 2020. The national mortality attributable to long-term PM2.5 exposure decreased year by year from 2.18 million [95% confidence interval (1.83, 2.51), the same hereinafter] in 2016 to 1.99 million (1.66, 2.30) in 2020. In particular, the number in 2020 was 133.16 thousand less than 2019 owing to the reduced emissions during the pandemic, and the mortality attributable to short-term PM2.5 exposure dropped from 46.86 thousand in 2019 to 36.56 thousand in 2020. However, because O3 concentrations have kept increasing during the period, the national mortality attributable to long-term O3 exposure increased from 132.79 thousand (128.58, 137.00) in 2016 to 197.00 thousand (190.98, 203.03) in 2020. In addition, compared to before the pandemic, the national mortality attributable to short-term O3 exposure showed an increase in February, April and May of 2020, and the sharpest year-on-year increase of 162% occurred in April. The different trends of mortality after anthropogenic emissions were reduced pose a challenge for policy-makers and researchers.