Assessment of pollution of potentially harmful elements in soils surrounding a municipal solid waste incinerator, China

We assessed the contamination levels of Mn, Zn, Cr, Cu, Ni, Pb, As and Hg and the risks posed by these potentially harmful elements in top-soils around a municipal solid waste incinerator （MSWI）. We collected 20 soil samples, with an average pH of 8.1, and another fly ash sample emitted from the MSWI to investigate the concentrations of these elements in soils. We determined the concentrations of these elements by inductively coupled plasma-optical emission spectrometer （ICP-OES）, except for Hg, which we measured by AF-610B atomic fluorescence spectrometer （AFS）. We assessed the risks of these elements through the use of geoaccumulation index （/geo）, potential ecological risk index （R/）, hazard quotient （HQi） and cancer risk （Riski）. The results showed that concentrations of potentially harmful elements in soil were influenced by the wind direction, and the concentrations of most elements were higher in the area northwest of the MSWI, compared with the area southeast of the incinerator, with the exception of As; these results were in accordance with those results acquired from our contour maps. According to the I^o values, some soil samples were clearly polluted by Hg emissions. However, the health risk assessment indicated that the concentrations of Hg and other elements in soil did not pose non-carcinogenic risks to the local populations. This was also the case for the carcinogenic risks posed by As Cr and Ni. The carcinogenic risk posed by As was higher in the range 6.49 × 10 -9.58 × 10 -6, but this was still considered to be an acceptable level of risk.

Predictive models for the assessment of bodily harm

The Spanish scale to quantify or qualify bodily harm resulting from any unintentional traffic accident prior to 1 January 2016 is established by Royal Legislative Decree(RDL)8/2004.This scale assigns points to the sequelae,which are converted into Euros using a table that is updated annually.The objective of this study is to develop a predictive model of sequelae points that will enable the estimation of compensation a short time after the accident.This will facilitate the calculation of the money reserve and rapid access to compensation for the injured party.To conduct this study,we developed a database with information from 999 individuals who had suffered car crash injuries which were evaluated according to the scale contained in RDL 8/2004 for medical experts.Predictive models based on logistic regression models were designed on this database.To choose the best model,we calculated Mallow’s Cp.The use of hurdle models made it possible to predict the points received by an injured party within a relatively short period of time after the accident.Once these points are known,it is a simple matter to calculate the corresponding compensation.The prediction models developed provide an easy way to predict the compensation to be awarded to the injured party.These models use days of hospitalization,sex,age and the results of international scales based on the Abbreviated Injury Scale.These variables can be used soon after the occurrence of the crash.