Contamination, risk assessment and source apportionment of the heavy metals in the soils of apple orchard in Qixia City, Shandong Province, China

2022 ◽  
Author(s):  
Chunyu Hua ◽  
Huimin Zhuo ◽  
Ailin Kang ◽  
Zhaotong Fang ◽  
Mengyuan Zhu ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Source Apportionment ◽  
Apple Orchard ◽  
Shandong Province ◽  
Contamination Risk

scholarly journals Seasonal Variations, Source Apportionment, and Health Risk Assessment of Heavy Metals in PM2.5 in Ningbo, China

2019 ◽  
Vol 19 (9) ◽  
pp. 2083-2092 ◽  
Author(s):  
Yue Wu ◽  
Beibei Lu ◽  
Xinlei Zhu ◽  
Aihong Wang ◽  
Meng Yang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Health Risk ◽  
Source Apportionment ◽  
Health Risk Assessment ◽  
Seasonal Variations

Risk assessment, spatial patterns and source apportionment of soil heavy metals in a typical Chinese hickory plantation region of southeastern China

Geoderma ◽  
2020 ◽  
Vol 360 ◽  
pp. 114011 ◽  
Author(s):  
Keli Zhao ◽  
Luyao Zhang ◽  
Jiaqi Dong ◽  
Jiasen Wu ◽  
Zhengqian Ye ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Source Apportionment ◽  
Spatial Patterns ◽  
Southeastern China ◽  
Soil Heavy Metals

scholarly journals Assessment of Pollution and Health Risks of Heavy Metals in Particulate Matter and Road Dust Along the Road Network of Dhanbad, India

2021 ◽  
Vol 11 (29) ◽  
Author(s):  
Shweta Kumari ◽  
Manish Kumar Jain ◽  
Suresh Pandian Elumalai
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
Particulate Matter ◽  
Health Risk ◽  
Human Health ◽  
Source Apportionment ◽  
Health Risks ◽  
Mass Concentration ◽  
Road Dust

Background. The rise in particulate matter (PM) concentrations is a serious problem for the environment. Heavy metals associated with PM10, PM2.5, and road dust adversely affect human health. Different methods have been used to assess heavy metal contamination in PM10, PM2.5, and road dust and source apportionment of these heavy metals. These assessment tools utilize pollution indices and health risk assessment models. Objectives. The present study evaluates the total mass and average concentrations of heavy metals in PM10, PM2.5, and road dust along selected road networks in Dhanbad, India, analyzes the source apportionment of heavy metals, and assesses associated human health risks. Methods. A total of 112 PM samples and 21 road dust samples were collected from six stations and one background site in Dhanbad, India from December 2015 to February 2016, and were analyzed for heavy metals (iron (Fe), lead (Pb), cadmium (Cd), nickel (Ni), copper (Cu), chromium (Cr), and zinc (Zn)) using atomic absorption spectrophotometry. Source apportionment was determined using principal component analysis. A health risk assessment of heavy metal concentrations in PM10, PM2.5, and road dust was also performed. Results. The average mass concentration was found to be 229.54±118.40 μg m−3 for PM10 and 129.73 ±61.74 μg m−3 for PM2.5. The average concentration of heavy metals was found to be higher in PM2.5 than PM10. The pollution load index value of PM10 and PM2.5 road dust was found to be in the deteriorating category. Vehicles were the major source of pollution. The non-carcinogenic effects on children and adults were found to be within acceptable limits. The heavy metals present in PM and road dust posed a health risk in the order of road dust> PM10> and PM2.5. Particulate matter posed higher health risks than road dust due to particle size. Conclusions. The mass concentration analysis indicates serious PM10 and PM2.5 contamination in the study area. Vehicle traffic was the major source of heavy metals in PM10, PM2.5, and road dust. In terms of non-carcinogenic risks posed by heavy metals in the present study, children were more affected than adults. The carcinogenic risk posed by the heavy metals was negligible. Competing Interests. The authors declare no competing financial interests

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