Chemical characteristics and source apportionment of PM2.5 in Wuhan, China

Fan, Hongsong; Zhou, Jiabin; Chen, Nan; Li, Yuhua; Li, Kuan; Wu, Shi

doi:10.1007/s10874-019-09395-0

Cited by 40 publications

(30 citation statements)

References 45 publications

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“…In addition, epidemiological studies have shown that most air pollutants can cause respiratory tract infection and lung cancer and even shorten humans’ life span [ 5 , 6 ]. Among air pollutants, PM 2.5 caused more than 1.3 million premature deaths in China in 2013 [ 7 , 8 ], and PM 2.5 and PM 10 were also the main research pollutant in many studies [ 9 , 10 ]. The main focus of research in recent years on air pollutants is mostly the variation in the mass concentration and composition of PM 2.5 .…”

Section: Introductionmentioning

confidence: 99%

Pollution Characteristics, Transport Pathways, and Potential Source Regions of PM2.5 and PM10 in Changchun City in 2018

Meng

et al. 2020

IJERPH

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Air pollution has attracted increasing attention in recent years. Cluster analysis, scene analysis, and the potential source contribution function (PSCF), based on the backward trajectory model, were used to identify the transport pathways and potential source regions of PM2.5 and PM10 (particulate matter with an aerodynamic diameter of not more than 2.5 µm and 10 µm) in Changchun in 2018. In addition, the PSCF was slightly improved. The highest average monthly concentrations of PM2.5 and PM10 appeared in March and April, when they reached 53.9μg/m3 and 120.0 μg/m3, respectively. The main potential source regions of PM2.5 and PM10 were generally similar: western Jilin Province, northwestern Inner Mongolia, northeastern Liaoning Province, and the Yellow Sea region. The secondary potential source regions were southern Russia, central Mongolia, western Shandong Province, eastern Hebei Province, and eastern Jiangsu Province. The northwest and southwest directions were found to be the two pathways that mainly affect the air quality of Changchun City. Moreover, the northwestern pathway had a larger potential contribution source area than the southwestern pathway. The airflow in the southwest direction came from Liaoning Province, Shandong Province, and the Yellow Sea region. This mainly occurred in summer; its transmission distance was short; it had a relatively higher weight potential source contribution function (WPSCF) value; it can be regarded as a local source; and its representative pollutants were SO2 (sulfur dioxide), CO (carbon monoxide), and O3 (ozone). The northwestern pathway passed through Russia, Mongolia, and Inner Mongolia. The transmission distance of this pathway was longer; it had a relatively lower WPSCF value; it can be considered as a natural source to a certain extent; it mainly occurred in autumn and, especially, in winter; and the representative pollutants of this pathway were NO (nitric oxide), NOx (nitrogen oxide), PM2.5, and PM10.

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Section: Introductionmentioning

confidence: 99%

Pollution Characteristics, Transport Pathways, and Potential Source Regions of PM2.5 and PM10 in Changchun City in 2018

Meng

et al. 2020

IJERPH

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“…The primary sources of PM 2.5 are dust, construction dust, coal dust, smelting dust, sulphate, automobile dust, and coal dust that contributes 30.34% to PM 2.5 (Huang, Liu, & Jiang, ). Gieré et al () held that coal‐fired soot contains a large amount of PM 2.5 , which has a seriously impact on the environment and health.…”

Section: Empirical Analysismentioning

confidence: 99%

Study of haze emission efficiency based on new co‐opetition data envelopment analysis

Chen

Zhao

et al. 2019

Expert Systems

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As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co‐opetition matrices of Chinese provinces, then builds the co‐opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co‐opetition DEA cross‐efficiency model that integrates haze's feature of cross‐border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision‐making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co‐opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co‐opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.

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“…The proportion of traffic (16%) was equal to the sum of coal burning (15%) and industrial factors (1%), and was double other sources (8%) and quadruple biomass burning (4%). After 2013, not only the contribution rates of secondary source (18%) and dust (18%) occupied an important position, but also that of traffic and industrial factors climbed to 18% and 21%, changing into another two important pollution sources [61,[114][115][116][117][118][119][120][121][122]. The percentage of coal burning dropped to 10%, while that of biomass burning (8%) was twice as much as before, equal to other sources and the largest in the same category in China.…”

Section: Major Source Of Haze Pm In Different Regionsmentioning

confidence: 99%

Research Progress of HP Characteristics, Hazards, Control Technologies, and Measures in China after 2013

Wei

Wang

2019

Atmosphere

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In recent years, hazy weather (hazy weather (HW) has frequently invaded peoples’ lives in China, resulting in the disturbance of social operation, so it is urgent to resolve the haze pollution (HP) problem. A comprehensive understanding of HP is essential to further effectively alleviate or even eliminate it. In this study, HP characteristics in China, after 2013, were presented. It was found that the situation of HP is getting better year by year while it has been a pattern of high levels in the north and low levels in the south. In most regions of China, the contribution of a secondary source for HP is relatively large, and that of traffic is greater in the regions with rapid economic development. Hazards of HP were then summarized. Not only does HP cause harm to human health, but it also has effects on human production and quality of life, furthermore, property and atmospheric environment cannot be ignored. Next, the source and non-source control technologies of HP were first reviewed to recognize the weakness of HP control in China. This review provides more systematic information about HP problems and the future development directions of HP research were proposed to further effectively control HP in China.

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Chemical characteristics and source apportionment of PM2.5 in Wuhan, China

Cited by 40 publications

References 45 publications

Pollution Characteristics, Transport Pathways, and Potential Source Regions of PM2.5 and PM10 in Changchun City in 2018

Pollution Characteristics, Transport Pathways, and Potential Source Regions of PM2.5 and PM10 in Changchun City in 2018

Study of haze emission efficiency based on new co‐opetition data envelopment analysis

Research Progress of HP Characteristics, Hazards, Control Technologies, and Measures in China after 2013

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