| Literature DB >> 35206218 |
Ji-Biao Zhang1,2, Yu-Mei Rong1, Qi-Feng Yin1, Peng Zhang1, Li-Rong Zhao1, Chun-Liang Chen3.
Abstract
Water-soluble anions and suspended fine particles have negative impacts on ecosystems and human health, which is a current research hotspot. In this study, coastal suburb, coastal urban area, coastal tourist area, and coastal industrial area were explored to study the spatiotemporal variation and influencing factors of water-soluble anions and total suspended particles (TSP) in Zhanjiang atmosphere. In addition, on-site monitoring, laboratory testing, and analysis were used to identify the difference of each pollutant component at the sampling stations. The results showed that the average concentrations of Cl-, NO3-, SO42-, PO43-, and TSP were 29.8 μg/m3, 19.6 μg/m3, 45.6 μg/m3, 13.5 μg/m3, and 0.28 mg/m3, respectively. The concentration of Cl-, NO3-, PO43-, and atmospheric TSP were the highest in coastal urban area, while the concentration of SO42- was the highest in coastal industrial area. Moreover, there were significantly seasonal differences in the concentration of various pollutants (p < 0.05). Cl- and SO42- were high in summer, and NO3- and TSP were high in winter. Cl-, SO42-, PO43-, and TSP had significant correlations with meteorological elements (temperature, relative humidity, atmospheric pressure, and wind speed). Besides, the results showed the areas with the most serious air pollution were coastal urban area and coastal industrial area. Moreover, the exhaust emissions from vehicles, urban enterprise emissions, and seawater evaporation were responsible for the serious air pollution in coastal urban area. It provided baseline information for the coastal atmospheric environment quality in Zhanjiang coastal city, which was critical to the mitigation strategies for the emission sources of air pollutants in the future.Entities:
Keywords: TSP; Zhanjiang; anions; coastal atmosphere; influencing factor
Mesh:
Substances:
Year: 2022 PMID: 35206218 PMCID: PMC8871972 DOI: 10.3390/ijerph19042030
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Location of the monitoring sites in Zhanjiang city.
Longitude and latitude of each station and the distance from sea.
| Station | Longitude (N) | Latitude (E) | Distance from Sea (km) |
|---|---|---|---|
| S1 | 21°9′40.68″ | 110°17′43.44″ | 6.3 |
| S2 | 21°11′8.52″ | 110°23′35.52″ | 0.9 |
| S3 | 21°1′33.59″ | 110°31′32.52″ | 0.3 |
| S4 | 21°1′33.95″ | 110°31′13.44″ | 2.0 |
The statistics results of meteorological factors from June 2018 to June 2019.
| Season | T(℃) | RH (%) | Air Pressure (hPa) |
|---|---|---|---|
| Spring | 24.9 | 86.1 | 1009.8 |
| Summer | 30.8 | 79.6 | 998.6 |
| Autumn | 24.9 | 81.4 | 1011.7 |
| Winter | 19.6 | 81.2 | 1015.2 |
| Maximum | 34.1 | 100.0 | 1019.7 |
| Minimum | 16.5 | 55.5 | 989.1 |
| Average | 25.2 | 82.0 | 1008.6 |
Figure 2Wind rose diagram of Zhanjiang City from June 2018 to June 2019.
Seasonal air pollutant concentration in each station from June 2018 to June 2019.
| Station | Range and Average | Cl− | NO3− | SO42− | PO43− | TSP |
|---|---|---|---|---|---|---|
| S1 | Maximum | 53.5 | 29.7 | 52.0 | 31.2 | 0.45 |
| Minimum | 12.1 | 5.3 | 8.5 | 5.0 | 0.08 | |
| Average | 26.4 ± 17.6 | 19.0 ± 5.2 | 29.6 ± 14.9 | 10.6 ± 13.6 | 0.26 ± 0.17 | |
| S2 | Maximum | 69.5 | 51.6 | 72.2 | 32.5 | 0.59 |
| Minimum | 12.7 | 10.8 | 28.6 | 3.6 | 0.05 | |
| Average | 33.0 ± 19.5 | 25.1 ± 7.0 | 50.3 ± 13.7 | 15.1 ± 11.1 | 0.34 ± 0.22 | |
| S3 | Maximum | 60.8 | 24.8 | 70.6 | 29.0 | 0.58 |
| Minimum | 11.0 | 7.6 | 15.0 | 8.1 | 0.03 | |
| Average | 30.5 ± 16.1 | 14.7 ± 4.6 | 49.1 ± 16.2 | 17.2 ± 10.7 | 0.25 ± 0.20 | |
| S4 | Maximum | 62.1 | 32.0 | 84.3 | 40.1 | 0.41 |
| Minimum | 17.2 | 11.5 | 10.5 | 5.4 | 0.12 | |
| Average | 29.3 ± 16.5 | 19.5 ± 3.9 | 53.2 ± 18.1 | 11.0 ± 11.0 | 0.28 ± 0.19 | |
| Sum | Maximum | 69.5 | 51.6 | 84.3 | 40.1 | 0.59 |
| Minimum | 11.0 | 5.3 | 8.5 | 3.6 | 0.03 | |
| Average | 29.8 ± 11.1 | 19.6 ± 4.7 | 45.6 ± 16.1 | 13.5 ± 12.4 | 0.28 ± 0.18 |
Figure 3Relationship between temperature and atmospheric pollutant concentration.
Figure 4Relationship between relative humidity and atmospheric pollutant concentration.
Figure 5Relationship between atmospheric pressure and atmospheric pollutant concentration.
Figure 6Relationship between wind speed and atmospheric pollutant concentration.
Pearson correlation between meteorological factors and atmospheric pollutant concentrations (n = 228).
| Correlation Coefficient | Temperature (°C) | Relative Humidity (%) | Atmospheric Pressure (hPa) | Wind Speed (m·s−1) |
|---|---|---|---|---|
| Cl− | 0.343 ** | 0.315 ** | −0.238 * | −0.204 * |
| NO3− | 0.027 | −0.014 | −0.010 | −0.021 |
| SO42− | 0.140 | −0.197 | −0.249 * | −0.266 * |
| PO43− | −0.216 * | 0.224 * | 0.217 * | −0.202 * |
| TSP | −0.303 ** | −0.224 * | 0.291 * | −0.325 ** |
* Refers to the correlation is significant at p < 0.05 (two-tailed). ** Refers to the correlation is significant at p < 0.01.
Figure 7Atmospheric pollutant concentrations in different seasons.
Figure 8Concentration of atmospheric pollutants at different environmental areas (S1, coastal suburb; S2, coastal urban area; S3, coastal tourist area; S4, coastal industrial area).