Abstract
The national architectural ceramic industrial center in east China is suffering from serious ambient fine particle pollution. The study reported herein describes an effort to ascertain the degree and sources of the PM2.5 collected in a ceramic industrial base during winter. The major chemical components in PM2.5 were analyzed, including carbonaceous aerosols, water-soluble ions, and inorganic elements. The chemical mass balance (CMB) model, backward trajectory method and potential source contribution function model, etc. were used to track and identify possible sources and contributions in the formation of the PM2.5. The results showed that the average PM2.5 concentration during sampling period was 134 ± 74.7 µg m–3, which exceeding World Health Organization (WHO) Air Quality Guidelines levels. The dominant components in the PM2.5 at this sampling site were found to be secondary ions (sulfate and nitrate) and carbon fractions. Water-soluble ions and total carbon contributed about 48.7% and 13.9% of the PM2.5 mass, respectively. In addition, the SO42–/NO3– ratio in the ambient PM2.5 during the sampling period was 1.16, indicating that it was the result of primarily emissions from stationary sources. Furthermore, source apportionment using the CMB model indicated that a ceramic industry source was the main contributor to the PM2.5 mass, which accounted for about 27.9%, and this was followed by secondary formation dust sources, and gasoline/diesel vehicle exhaust emissions and motor vehicle non-exhaust emissions. Based on the backward trajectory analysis and potential source apportionment, it was found that PM2.5 regional transmission existed, but it originated primarily from local sources and surrounding areas. Hence, this study provided a scientific basis for identifying the sources of PM2.5 pollution during a typical pollution period and provided important input for PM2.5 control strategies in a typical industrial area.
Highlights
China’s air quality has improved in recent years as a result of the implementation of the Air Pollution Prevention and Control Action Plan, the ambient PM2.5 levels in most industrial areas and cities far exceedsAerosol and Air Quality Research | https://aaqr.org the air quality guidelines of the World Health Organization (WHO) in which the daily average PM2.5 concentration is set at the level of 15 μg m–3 (Cai et al, 2017; Lin et al, 2018)
The results showed that the average PM2.5 concentration during sampling period was 134 ± 74.7 μg m–3, which exceeding World Health Organization (WHO) Air Quality Guidelines levels
3.1.1 Ambient PM2.5 concentration illustrates that changes in the concentration of ambient PM2.5 were somewhat related to local weather conditions and the local aerosol pollution was quite serious during the sampling period
Summary
China’s air quality has improved in recent years as a result of the implementation of the Air Pollution Prevention and Control Action Plan, the ambient PM2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) levels in most industrial areas and cities far exceedsAerosol and Air Quality Research | https://aaqr.org the air quality guidelines of the World Health Organization (WHO) in which the daily average PM2.5 concentration is set at the level of 15 μg m–3 (Cai et al, 2017; Lin et al, 2018). China’s air quality has improved in recent years as a result of the implementation of the Air Pollution Prevention and Control Action Plan, the ambient PM2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) levels in most industrial areas and cities far exceeds. The chemical composition of PM2.5 is as complex as its sources (Heo et al, 2013). Studying the chemical composition and source apportionment of ambient PM2.5 in a select area is a critical way to provide a sound scientific basis for human health protection and air pollution control. Exploring the impact of these industries on local air quality pollution is very important and is urgently needed to control of regional air pollution and improvement the quality of ambient air for local residents (Heo et al, 2013; Cai et al, 2017)
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