Characterizing the physical and demographic variables associated with heavy metal distribution along urban-rural gradient.
This paper describes a study of how the demographic and physical variables affected the heavy metal (HM) contamination along the urban-rural gradient in PuDong New District, Shanghai. The road density (RDi) and the percentage of built-up areas (BAi) were calculated for various widths of buffers around the soil sampling sites. Through distance allocation, the demographic values of the population change index (PCI) were assigned, with the value being associated with the nearest town. We initiated the use of the population migration rate from 2000 to 2010, i.e., PCI, to represent the urbanization rate. Regression analysis between the soil HM concentrations and the PCI, the RD, and the BA was estimated. The results indicated that the PCI significantly affected the Cd and Cu distribution (p < 0.05), while the RD of the 3-km buffer affected the Pb concentrations. The BA of 2-km buffers affected the spatial distribution of Cd, Cu, and Zn. Zn was also affected by the RD within the 4-km buffer. Using the median values of the PCI and the BA of the 2-km buffer, and the RD of the 3-km buffer, logistic analysis was performed to identify the priority areas for managing HM hazards. The two identified priority areas were the towns of Kangqiao and Zhuqiao, both of which were rapidly urbanized areas with higher PCI values. Our research demonstrated that understanding the rate of urbanization may be as important as the degree of urbanization when examining associated HM contamination patterns.
Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Shanghai Ocean University, Ministry of Education, Shanghai, 201306, People's Republic of China.
Shubo
S
Fang
Yajun
Y
Qiao
Chunsheng
C
Yin
Xiaoying
X
Yang
Ning
N
Li
D002681:China; D004784:Environmental Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D019216:Metals, Heavy / Q000032:analysis*; D011157:Population Dynamics; D012044:Regression Analysis; D012424:Rural Population / Q000706:statistics & numerical data; D012989:Soil Pollutants / Q000032:analysis*; D014505:Urban Population / Q000706:statistics & numerical data; D014507:Urbanization
D019216:Metals, Heavy; D012989:Soil Pollutants