Industrial and mining activities have been recognized as the major sources of soil heavy metal contamination. This study introduced an improved Nemerow index method based on the Nemerow and geo-accumulation index. Taking a typical industrial and mining gathering area in Tianjin (China) as example, this study then analyzed the contamination sources as well as the ecological and integrated risks. The spatial distribution of the contamination level and ecological risk were determined using Geographic Information Systems. The results are as follows: (1) Zinc showed the highest contaminant level in the study area; the contamination levels of the other seven heavy metals assessed were relatively lower. (2) The combustion of fossil fuels and emissions from industrial and mining activities were the main sources of contamination in the study area. (3) The overall contamination level of heavy metals in the study area ranged from heavily contaminated to extremely contaminated and showed an uneven distribution. (4) The potential ecological risk showed an uneven distribution, and the overall ecological risk level ranged from low to moderate. This study also emphasized the importance of partition in industrial and mining areas, the extensive application of spatial analysis methods, and the consideration of human health risks in future studies.
As an inherent characteristic and pervasive market phenomenon of the tourism industry, seasonality plays an important role in tourist business survivability and sustainability. It is also a significant factor for rural households involved in tourism as they plan their livelihood strategies around it. In this study, household surveys were conducted in The Beautiful South, an area for rural tourism in Guangxi of Southern China. We analyzed the livelihood capital and strategy of different household types in response to seasonal fluctuations in tourism by applying a mixed method that integrated livelihood capital index (LCI) evaluation and data envelopment analysis. The results indicate that LCI of tourism income-oriented households ranks second among the four types of households, while the LCI of tourism-engaged households in peak season performed better than that of those not engaged. However, the number of households participating in tourism nearly halved during the off season, and they are mainly diverted to temporary labor work, which may be one of the reasons for the low livelihood capital efficiency of tourism households. The implications of the findings and empirical solutions to mitigate the negative seasonal impact are discussed.
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