Air Pollution Characteristics and Meteorological Correlates in Lin'an, Hangzhou, China

Abstract

The concentration and distribution of atmospheric particulate matter depend primarily on the meteorological conditions associated with a fixed pollution source. The effects of meteorological factors on particulate matter have been analyzed on the meteorological seasonal scale, but few researchers have considered the climatic season, which is divided based on the distribution feature of climatic factors. In addition, the hysteresis effect of meteorological factors is easily neglected. Here, we reviewed the characteristics and influential factors of particle pollution based on particle concentration and meteorological data from January 2013 through December 2013. Results from nonparametric tests and Spearman's nonparametric correlation coefficient showed that particle pollution exhibited a statistically significant seasonal trend. The pollution on workdays was slightly less than that on holidays, but no significant difference was found. The air pressure 1-2 days earlier showed a higher positive correlation with the current particle concentrations (except in winter), and the temperature 2-3 days earlier in summer and fall showed a stronger negative correlation with the particle concentration. Lower moisture and frequent precipitation would significantly reduce the pollution on the current day and the next day (except in summer). The variation of particulate matter concentration in summer exhibited a high-low-high variation, caused mainly by temperature and precipitation; the air quality during the plum rain period was significantly better than that in the period before the plum rain. The fine particle pollution level during the high-temperature and heat wave days was the lowest, after which the concentration increased.

Prediction of Potentially High PM2.5 Concentrations in Chengdu, China

“…The average surface wind speed decreases with increasing sea-level pressure, which is not favorable for the horizontal dispersion of pollutants. Moreover, the high sealevel pressure may cause a weakening of the vertical diffusion of PM 2.5 , favoring the formation of heavy PM 2.5 pollution gradually (Ning et al, 2018;Lin et al, 2019). The different lag days of our study are probably due to different distance from the sea, climate, elevation, and terrain characteristics.…”

“…These results confirm that sea-level pressure 5-7 days in advance is a strong predictor for elevated PM 2.5 in Chengdu. Lin et al (2019) found that air pressure 1-2 days earlier showed a higher positive correlation with the current particle concentrations (except in winter) in the city of Lin'an in the Yangtze River Delta region. The average surface wind speed decreases with increasing sea-level pressure, which is not favorable for the horizontal dispersion of pollutants.…”

“…PM 2.5 concentrations were positively correlated with daily maximum temperature and the radiosonde air temperature in the bottom layer (< 1,000 m) at 8 a.m. PM 2.5 concentrations were negatively correlated with air temperature, daily minimum relative humidity, wind speed, and precipitation. High wind speed and high daily average temperature favor the dispersion of air pollutants, and high relative humidity and precipitation facilitate PM 2.5 deposition (Fang et al, 2017;Zhao et al, 2018;Lin et al, 2019).…”

Impact of Income, Density, and Population Size on PM2.5 Pollutions: A Scaling Analysis of 254 Large Cities in Six Developed Countries

“…In other words, a 1% increase in density increased PM 2.5 concentrations from 0.029% to 0.06%, while the effects from other factors such as income, industrial structure, electricity intensity, traffic intensity, and several others held constant. The other two articles by Hao and Liu [2] and Lin et al [24] showed positive but no statistically significant density coefficients.…”