Dataset Information

Spatial and Temporal Distribution of PM2.5 Pollution in Xi'an City, China.

ABSTRACT: The monitoring data of the 13 stations in Xi'an city for the whole years of 2013 and 2014 was counted and analyzed. Obtaining the spatial and temporal distribution characteristics of PM2.5 was the goal. Cluster analysis and the wavelet transform were utilized to discuss the regional distribution characteristics of PM2.5 concentration (?(PM2.5)) and the main features of its yearly changes and sudden changes. Additionally, some relevant factors were taken into account to interpret the changes. The results show that ?(PM2.5) in Xi'an during 2013 was generally higher than in 2014, it is high in winter and low in summer, and the high PM2.5 concentration centers are around the People's Stadium and Caotan monitoring sites; For the regional PM2.5 distribution, the 13 sites can be divided into three categories, in which Textile city is Cluster 1, and High-tech Western is Cluster 2, and Cluster 3 includes the remaining 11 monitoring sites; the coefficient of goodness of the cluster analysis is 0.6761, which indicates that the result is acceptable. As for the yearly change, apart from June and July, the average ?(PM2.5) concentration has been above the normal concentration criteria of Chinese National Standard (50 g/m3); cloudy weather and low winds are the major meteorological factors leading to the sudden changes of ?(PM2.5).

SUBMITTER: Huang P

PROVIDER: S-EPMC4483719 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Spatial and Temporal Distribution of PM2.5 Pollution in Xi'an City, China.

Huang Ping P Zhang Jingyuan J Tang Yuxiang Y Liu Lu L

International journal of environmental research and public health 20150610 6

The monitoring data of the 13 stations in Xi'an city for the whole years of 2013 and 2014 was counted and analyzed. Obtaining the spatial and temporal distribution characteristics of PM2.5 was the goal. Cluster analysis and the wavelet transform were utilized to discuss the regional distribution characteristics of PM2.5 concentration (ρ(PM2.5)) and the main features of its yearly changes and sudden changes. Additionally, some relevant factors were taken into account to interpret the changes. The ...[more]

PMID: 26068090

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Project description:Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM2.5 and PM10 during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis. Four meteorological factors and two socioeconomic factors, i.e., the decline of intra-city mobility intensity (dIMI) representing the effect of traffic mobility and the decline rates of the secondary industrial output values (drSIOV), were adopted in the regression analysis. Then, multi-scale geographically weighted regression (MGWR), a model allowing the particular processing scale for each independent variable, was applied for investigating the relationship between PM pollution reductions and influencing factors. For comparison, ordinary least square (OLS) regression and the classic geographically weighted regression (GWR) were also performed. The research found that there were 16% and 20% reduction of PM2.5 and PM10 concentration across China and significant PM pollution mitigation in central, east, and south regions of China. As for the regression analysis results, MGWR outperformed the other two models, with R2 of 0.711 and 0.732 for PM2.5 and PM10, respectively. The results of MGWR revealed that the two socioeconomic factors had more significant impacts than meteorological factors. It showed that the reduction of traffic mobility caused more relative declines of PM2.5 in east China (e.g., cities in Jiangsu), while it caused more relative declines of PM10 in central China (e.g., cities in Henan). The reduction of industrial operation had a strong relationship with the PM10 drop in northeast China. The results are crucial for understanding how the decline pattern of PM pollution varied spatially during the COVID-19 outbreak, and it also provides a good reference for air pollution control in the future.

Project description:The impact of COVID-19 control on air quality have been prevalent for the past two years, however few studies have explored the toxicity of atmospheric particulate matter during the epidemic control. Therefore, this research highlights the characteristics and sources of oxidative potential (OP) and the new health risk substances environmentally persistent free radicals (EPFRs) in comparison to city lockdown (CLD) with early days of 2019-2020. Daily particulate matter (PM2.5) samples were collected from January 14 to February 3, 2020, with the same period during 2019 in Xi'an city. The results indicated that the average concentration of PM2.5 decreased by 48% during CLD. Concentrations of other air pollutants and components, such as PM10, NO2, SO2, WSIs, OC and EC were also decreased by 22%, 19%, 2%, 17%, 6%, and 4% respectively during the CLD, compared to the same period in 2019. Whereas only O3 increased by 30% during CLD. The concentrations of EPFRs in PM2.5 was considerably lower than in 2019, which decreased by 12% during CLD. However, the OP level was increased slightly during CLD. Moreover, both EPFRs/PM and DTTv/PM did not decrease or even increase significantly, manifesting that the toxicity of particulate matter has not been reduced by more gains during the CLD. Based on PMF analysis, during the epidemic period, the contribution of traffic emission is significantly reduced, while EPFRs and DTTv increased, which consist of significant O3 and secondary aerosols. This research leads to able future research on human health effect of EPFRs and oxidative potential and can be also used to formulate the majors to control EPFRs and OP emissions, suggest the need for further studies on the secondary processing of EPFRs and OP during the lockdown period in Xi'an. .The COVID-19 lockdown had a significant impact on both social and economic aspects. The city lockdown, however, had a positive impact on the environment and improved air quality, however, no significant health benefits were observed in Xi'an, China.

Dataset Information

Spatial and Temporal Distribution of PM2.5 Pollution in Xi'an City, China.

Publications

Spatial and Temporal Distribution of PM2.5 Pollution in Xi'an City, China.

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