Abstract
Air contamination is identified with individuals’ wellbeing and furthermore affects the sustainable development of economy and society. This paper gathered the time series data of seven meteorological conditions variables of Beijing city from 1 November 2013 to 31 October 2017 and utilized the generalized regression neural network optimized by the particle swarm optimization algorithm (PSO-GRNN) to explore seasonal disparity in the impacts of mean atmospheric humidity, maximum wind velocity, insolation duration, mean wind velocity and rain precipitation on air quality index (AQI). The results showed that in general, the most significant impacting factor on air quality in Beijing is insolation duration, mean atmospheric humidity, and maximum wind velocity. In spring and autumn, the meteorological diffusion conditions represented by insolation duration and mean atmospheric humidity had a significant effect on air quality. In summer, temperature and wind are the most significant variables influencing air quality in Beijing; the most important reason for air contamination in Beijing in winter is the increase in air humidity and the deterioration of air diffusion condition. This study investigates the seasonal effects of meteorological conditions on air contamination and suggests a new research method for air quality research. In future studies, the impacts of different variables other than meteorological conditions on air quality should be assessed.
Highlights
Air contamination affects the sustainable and long-term development of both the economy and society
The generalized regression neural network optimized by the particle swarm optimization algorithm (PSOGRNN) model with better robustness and precision is set up by searching for the best parameter SPREAD of GRNN via the particle swarm optimization (PSO) algorithm, the PSO-GRNN model is applied to assess the impacts of meteorological conditions on air quality, which expands on the studies from this discipline and fills the research gap
Among the seven influencing factors, mean atmospheric humidity, mean land surface temperature and mean atmospheric temperature are positively correlated with air quality index (AQI); insolation duration, maximum wind velocity, mean wind velocity and rain precipitation are negatively correlated with AQI
Summary
Air contamination affects the sustainable and long-term development of both the economy and society. Meteorological conditions determine the concentration, spatial and temporal distribution of air pollutants through diffusion and dilution effects [4,5,6,7,8]. Meteorological dynamic factors mainly refer to wind and turbulence, which play a decisive role in the diffusion and dilution of air pollutants in the atmosphere. The temperature decreases as the height increases, forming different temperature stratifications, but on some nights with no wind and little cloud, there will be a temperature inversion In this case, the atmosphere is in a stable state, turbulence is inhibited, the diffusion and dilution capacity of the atmosphere to pollutants is weakened, and the dilution capacity of the atmosphere to pollutants is enhanced, which will lead to air pollution [10,11,12,13,14,15]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
