During COVID-19, Shenyang implemented strict household isolation measures, resulting in a sharp reduction in anthropogenic emission sources, providing an opportunity to explore the impact of human activities on air pollution. The period from January to April of 2020 was divided into normal period, blockade period and resumption period. Combined with meteorological and pollutant data, mathematical statistics and spatial analysis methods were used to compare with the same period of 2015–2019. The results showed that PM 2.5 , PM 10 , NO 2 and O 3 increased by 32.6%, 13.2%, 4.65% and 22.7% in the normal period, among which the western area changed significantly. During the blockade period, the concentration of pollutants decreased by 35.79%, 35.87%, 32.45% and -4.84%, of which the central area changed significantly. During the resumption period, the concentration of pollutants increased by 21.8%, 8.7%, 5.7% and -6.3%, and the area with the largest change was located in the western. During the blockade period, a heavy pollution occurred with PM 2.5 as the main pollutant. The WRF-Chem model and the HYSPLIT model were used to reproduce the pollution occurrence process. The result showed that winds circulated as zonal winds during the pollution process at high altitudes. These winds were controlled by straight westerly and weak northwesterly airflows in front of the high pressure, and the ground was located behind the warm low pressure. Weather conditions were relatively stable. Thus, high temperatures (average > 10 ℃), high humidity (40%-60%) and slow wind (2 m/s) conditions prevailed for a long time in the Shenyang area. The unfavorable meteorological conditions lead to the occurrence of pollution. The backward trajectory showed that the potential source areas were concentrated in the urban agglomeration around Shenyang, and sporadic contributions came from North Korea.
Air pollution is one of the most serious environmental problems faced by mankind. It is regional and highly complex, and it is more prominent in China. With the development of air quality management in China, the research on cross-regional transmission of air pollutants is particularly important. This paper reports on pollution characteristics, transport path, and distribution of pollution sources of major contaminants in Shenyang. For this purpose, pollution-monitoring data were gathered from November 2017 to March 2018. Data were analyzed using the HYSPLIT back trajectory model, the potential source contribution function (PSCF), and the concentration weighted trajectory (CWT) model. Results indicated that PM2.5 was the main pollutant in Shenyang during the study period. Air pollution was mainly affected by coal combustion, traffic emissions, and long-distance transmission. Among the 11 monitoring points, the pollution of Shenliaoxilu was relatively serious. Mongolia, eastern Inner Mongolia, northwestern Jilin, and most of Liaoning were the main potential sources of PM2.5 in Shenyang during the winter.
A study designed different parameter schemes for a weather research and forecasting model to simulate hourly winter and summer wind speed and direction at a wind-farm tower in China. The schemes were found to reproduce the local wind conditions accurately and simulate wind direction very well. The results showed that one scheme performed better for the wind speed and wind direction simulation at 10 m and 90 m heights in the winter, while another performed better for simulation at 10 m height in the summer. The results for these schemes showed that the correlation coefficient of wind speed and wind direction was 0.75 and 0.62 in winter and 0.55 and 0.44 in summer, respectively. Overall the parameterised model exhibited better simulation of the wind speed than wind direction, and was better in winter than in summer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.