Detection and differentiation of pollution in urban surface soils using magnetic properties in arid and semi-arid regions of northwestern China

Increasing urbanization and industrialization over the world has caused many social and environmental problems, one of which drawing particular concern is the soil pollution and its ecological degradation. In this study, the efficiency of magnetic methods for detecting and discriminating contaminates in the arid and semi-arid regions of northwestern China was investigated. Topsoil samples from six typical cities (i.e. Karamay, Urumqi, Lanzhou, Yinchuan, Shizuishan and Wuhai) were collected and a systematic analysis of their magnetic properties was conducted. Results indicate that the topsoil samples from the six cities were all dominated by coarse low-coercivity magnetite. In addition, the average magnetite contents in the soils from Urumqi and Lanzhou were shown to be much higher than those from Karamay, Yinchuan, Shizuishan and Wuhai, and they also have relatively higher χlf and χfd% when compared with cities in eastern China. Moreover, specific and distinctive soil pollution signals were identified at each sampling site using the combined various magnetic data, reflecting distinct sources. Industrial and traffic-derived pollution was dominant in Urumqi and Lanzhou, in Yinchuan industrial progress was observed to be important with some places affected by vehicle emission, while Karamay, Shizuishan and Wuhai were relatively clean. The magnetic properties of these latter three cities are significantly affected by both anthropogenic pollution and local parent materials from the nearby Gobi desert. The differences in magnetic properties of topsoil samples affected by mixed industrial and simplex traffic emissions are not obvious, but significant differences exist in samples affected by simplex industrial/vehicle emissions and domestic pollution. The combined magnetic analyses thus provide a sensitive and powerful tool for classifying samples according to likely sources, and may even provide a valuable diagnostic tool for discriminating among different cities.