An exploration of spatial human health risk assessment of soil toxic metals under different land uses using sequential indicator simulation.

A modified method was proposed which integrates the spatial patterns of toxic metals simulated by sequential indicator simulation, different exposure models and local current land uses extracted by remote-sensing software into a dose-response model for human health risk assessment of toxic metals. A total of 156 soil samples with a various land uses containing farm land (F1-F25), forest land (W1-W12) and residential land (U1-U15) were collected in a grid pattern throughout Xiandao District (XDD), Hunan Province, China. The total Cr and Pb in topsoil were analyzed. Compared with Hunan soil background values, the elevated concentrations of Cr were mainly located in the east of XDD, and the elevated concentrations of Pb were scattered in the areas around F1, F6, F8, F13, F14, U5, U14, W2 and W11. For non-carcinogenic effects, the hazard index (HI) of Cr and Pb overall the XDD did not exceed the accepted level to adults. While to children, Cr and Pb exhibited HI higher than the accepted level around some areas. The assessment results indicated Cr and Pb should be regarded as the priority pollutants of concern in XDD. The first priority areas of concern were identified in region A with a high probability (>0.95) of risk in excess of the accepted level for Cr and Pb. The areas with probability of risk between 0.85 and 0.95 in region A were identified to be the secondary priority areas for Cr and Pb. The modified method was proved useful due to its improvement on previous studies and calculating a more realistic human health risk, thus reducing the probability of excessive environmental management.

[Assessment model for heavy metal pollution in sediment based on trapezoidal fuzzy numbers and case study].

Due to the practical shortcomings of the classical deterministic pollution assessment model, the theory of trapezoidal fuzzy numbers was introduced to the environmental assessment system. A fuzzy risk assessment model was built based on the geoaccumulation index and biotoxicity coefficients of heavy metals. Using the fuzzy pollution risk assessment model, the risk of heavy metal pollution was evaluated for the surface sediment of Dongting Lake. The results showed that the pollution risk in a descending order was Hg > Cd > Pb > Cu > Cr > Zn > As, with Hg,Cd and Pb being the priority pollutants in Dongting Lake. Both the intervals of possible values for the geoaccumulation indexes of heavy metals and their credible levels were calculated using this model. Compared with the results of the deterministic assessment model, the fuzzy pollution risk assessment model gave a better characetriztaion of the actual pollution status and spatial distribution difference of the heavy metals in the sediment of the studied region which is more objective and comprehensive.

Demand for private health insurance in Chinese urban areas.

Between 1993 and 2003, the proportion of urban residents without health insurance rose from 27 to 50%. The probability of outpatient visits in the previous 2 weeks dropped from 19.9 to 11.8% in urban areas between 1993 and 2003, and from 16.0 to 13.9% in rural areas. To improve risk-pooling and risk-sharing, private health insurance should play an important role in China's health insurance system. This paper estimates the demand for private health insurance in urban areas using contingent valuation methods. Individuals were asked about their willingness-to-pay (WTP) for major catastrophic disease insurance (MCDI), inpatient expenses insurance (IEI), and outpatient expenses insurance (OEI). The study was based on a household survey conducted in four small cities in China in 2004 and included 2671 respondents. More people would like to buy IEI and MCDI (48.5 and 43.0%, respectively) than OEI (24.5%). In addition, individuals would pay a higher premium for MCDI and IEI than for OEI. The price elasticities of demand for MCDI, IEI, and OEI were -0.27, -0.34, and -0.42, respectively. The determinants of enrollment in the three private health insurance programs were similar with employment status, age, education, and income.