ABSTRACT
Meteorological normalization refers to the removal of meteorological effects on air pollutant concentrations for evaluating emission changes. There currently exist various meteorological normalization methods, yielding inconsistent results. This study aims to identify the state-of-the-art method of meteorological normalization for characterizing the spatiotemporal variation of NOx emissions caused by the COVID-19 pandemic in China. We obtained the hourly data of NO2 concentrations and meteorological conditions for 337 cities in China from January 1, 2019, to December 31, 2020. Three random-forest based meteorological normalization methods were compared, including (1) the method that only resamples meteorological variables, (2) the method that resamples meteorological and temporal variables, and (3) the method that does not need resampling, denoted as Resample-M, Resample-M&T, and Resample-None, respectively. The comparison results show that Resample-M&T considerably underestimated the emission reduction of NOx during the lockdowns, Resample-None generates widely fluctuating estimates that blur the emission recovery trend during work resumption, and Resample-M clearly delineates the emission changes over the entire period. Based on the Resample-M results, the maximum emission reduction occurred during January to February 2020, for most cities, with an average decrease of 19.1 ± 9.4% compared to 2019. During April of 2020 when work resumption initiated to the end of 2020, the emissions rapidly bounced back for most cities, with an average increase of 12.6 ± 15.8% relative to those during the strict lockdowns. Consequently, we recommend using Resample-M for meteorological normalization, and the normalized NO2 concentration dynamics for each city provide important implications for future emission reduction.
ABSTRACT
BACKGROUND: To evaluate the impact of air pollution exposure on semen quality parameters during COVID-19 outbreak in China, and to identify potential windows of susceptibility for semen quality. METHODS: A retrospective observational study was carried out on 1991 semen samples collected between November 23, 2019 and July 23, 2020 (a period covering COVID-19 lock-down in China) from 781 sperm donor candidates at University-affiliated Sichuan Provincial Human Sperm Bank. Multivariate mixed-effects regression models were constructed to investigate the relationship between pollution exposure, windows of susceptibility, and semen quality, while controlling for biographic and meteorologic confounders. RESULT(S): The results indicated multiple windows of susceptibility for semen quality, especially sperm motility, due to ambient pollution exposure. Exposure to particulate matters (PM2.5 and PM10), O3 and NO2 during late stages of spermatogenesis appeared to have weak but positive association with semen quality. Exposure to CO late in sperm development appeared to have inverse relationship with sperm movement parameters. Exposure to SO2 appeared to influence semen quality throughout spermatogenesis. CONCLUSION(S): Potential windows of susceptibility for semen quality varied depending on air pollutants. Sperm motility was sensitive to pollution exposure. Findings from current study further elucidate the importance of sensitive periods during spermatogenesis and provide new evidence for the determinants of male fertility.