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Huang C, Zhang L, Meng J, Yu Y, Qi J, Shen P, Li X, Ding P, Chen M, Hu G. Characteristics, source apportionment and health risk assessment of heavy metals in urban road dust of the Pearl River Delta, South China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 236:113490. [PMID: 35398649 DOI: 10.1016/j.ecoenv.2022.113490] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/01/2022] [Accepted: 04/02/2022] [Indexed: 05/25/2023]
Abstract
To investigate the characteristics of heavy metals (As, Cd, Cr, Cu, Pb, Hg, Ni and Zn) in urban road dust from different cities and functional areas in the Pearl River Delta (PRD), South China, a total of 294 dust samples were analyzed. The contamination characteristics and health risk of heavy metals in the dust were assessed, their chemical speciation were distinguished, and their sources were identified by the correlations, cluster and principal component analysis (PCA). The mean concentrations of As (15.89 mg/kg), Cd (1.59 mg/kg), Cr (143.75 mg/kg), Cu (184.42 mg/kg), Pb (114.82 mg/kg), Hg (0.11 mg/kg), Ni (41.53 mg/kg) and Zn (645.94 mg/kg) in urban road dust were in high or moderate levels compare with other previous researches. In this case, the contamination of Cr, Cu, Ni and Zn in the industrial area (IA) and the contamination of Cd and Hg in the commercial area (CA) were significantly higher relative to other functional areas (P < 0.05), and the contamination of heavy metals in Foshan City was significantly higher than other cities (P < 0.01). The order of mobility of the heavy metals with higher concentration in urban road dust of the Pearl River Delta declined in the following order: Zn, Ni, Cu, Pb and Cr. Statistical analysis result showed the contaminated heavy metals in urban road dust were mainly contributed by industrial activities, traffic activities and building pollution. There were no significant carcinogenic and noncarcinogenic risks for adults, children however showed significant noncarcinogenic effect caused by As and Cr in partial points, albeit with low contamination level of the two metals. The ingestion was a principal pathway for heavy metals via urban road dust to exposure population. More protection measures should be considered to reduce children's exposure to the dust, especially in the CA and IA.
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Affiliation(s)
- Chushan Huang
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Lijuan Zhang
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Jiuling Meng
- State Key Laboratory of Geological Process and Mineral Resources, School of Earth Sciences, China University of Geosciences, Wuhan 430074, China
| | - Yunjiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Jianying Qi
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Peng Shen
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xin Li
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Ping Ding
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Mianbiao Chen
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Guocheng Hu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China.
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Yao Y, He C, Li S, Ma W, Li S, Yu Q, Mi N, Yu J, Wang W, Yin L, Zhang Y. Properties of particulate matter and gaseous pollutants in Shandong, China: Daily fluctuation, influencing factors, and spatiotemporal distribution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 660:384-394. [PMID: 30640107 DOI: 10.1016/j.scitotenv.2019.01.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 01/02/2019] [Accepted: 01/04/2019] [Indexed: 06/09/2023]
Abstract
Characteristics of the spatial and temporal distribution of air pollutants may reveal the cause of air pollution, especially for large regions where the anthropogenic pollutant emission is concentrated. This study addresses this issue by focusing on Shandong province, which has the highest air pollutant emissions in China. First, the spatial and temporal variation characteristics of the observed concentrations of conventional pollutants are analyzed in detail. The most prominent indicator of the problem (PM2.5), was selected as the key analytical object. On the spatial scale, the Multivariate Moran model was used to identify factors affecting the spatial distribution of PM2.5. On the time scale, wavelet analysis was used to explore the fluctuation characteristics of PM2.5 at different time periods. Results show that there are significant regional differences in pollutant concentration within Shandong province. The concentration of particulate matter and gaseous pollutants in western and northern Shandong is significantly higher than eastern Shandong. The average concentrations of PM2.5, PM10, SO2 and NO2 were highest in winter and lowest in summer, whereas concentration of O3 peaked in summer. For PM2.5, the annual mean concentration has a significant spatial correlation with SO2 emission, GDP per capita, population density and energy consumption per unit of GDP; in addition, the correlation between different regions and various indices is different. On the time scale, the fluctuation energy of PM2.5 concentrated in Dezhou and Liaocheng is the strongest on December 18 and 19, 2015. The inversion temperature has a strong influence on the daily variation of PM2.5 concentration. The formation and evolution of atmospheric pollution, therefore, can be explored by combining the temporal and spatial distribution of pollutants, providing a comprehensive analytical method for atmospheric pollution in different regions.
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Affiliation(s)
- Youru Yao
- School of Environment, Nanjing Normal University, Nanjing 210023, China; School of Geography and Tourism, Anhui Normal University, Wuhu 241003, China
| | - Cheng He
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200082, China.
| | - Shiyin Li
- School of Environment, Nanjing Normal University, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
| | - Weichun Ma
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200082, China
| | - Shu Li
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200082, China
| | - Qi Yu
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200082, China
| | - Na Mi
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Jia Yu
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Wei Wang
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Li Yin
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Yong Zhang
- Department of Geological Sciences, University of Alabama, Tuscaloosa, AL 35487, USA
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The Development of Boundary Layer Structure Index (BLSI) and Its Relationship with Ground Air Quality. ATMOSPHERE 2018. [DOI: 10.3390/atmos10010003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Ambient air quality monitoring data and radar tracking sonde data were used to study the atmospheric boundary layer structure (ABLS) and its changing characteristics over Wuhan. The boundary layer structure index (BLSI), which can effectively describe the ABLS, was accordingly developed and its ability to describe the near-surface air quality was analyzed. The results can be summarized as follows. (1) An analysis of the ABLS during seriously polluted cases revealed that the ABLS was usually dry and warm with a small ventilation index (VI); meanwhile, the ABLS during clean cases was usually wet and cold with a large VI. (2) The correlation between the air quality and BLSI at 100~300 m was good and passed the confidence level limit at 99%. Moreover, the correlation coefficient increased with the altitude at 10~250 m and showed a downward trend at 250~500 m. The correlation between the BLSI at 250 m and the ground air quality was the most significant (r = 0.312), indicating that the layer ranging from 0 to 250 m is essential for determining the ground air quality. (3) The BLSI considers both the vertical diffusion capability and horizontal removal capability of the atmosphere. Therefore, it is highly capable of describing the ABLS and the ground air quality.
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