Assessment of contaminants in the northwestern Bay of Bengal

Modelling of soil environmental quality and early warning of integrated ecological risk

The knowledge of dynamic trend in soil heavy metal contamination and associated risk is important for soil pollution prevention, safe utilization and early warning of soil environmental quality and ecological risk. In this study, a modified integrated risk index (NIRI) was adopted to evaluate ecological risk in agricultural soil in Wenzhou with 70 samples, which is located in the southeast of China. In addition, two scenarios with different metal fluxes (optimistic and default scenario) were constructed to predict future dynamic trend of metal concentrations. Results showed the agricultural soil was mainly contaminated by Cd and Pb. The NIRI indicated moderate to considerable risk in most sites and Cd posed the greatest contribution to NIRI value. Besides, higher risk was determined in paddy soil than that in vegetable. Scenario simulation results revealed general declining trend in optimistic scenario while increasing trend in default scenario for metal concentration. However, exceedance varied with prediction period, soil types and metals. Ecological risk probability showed similar trend with metal concentration, indicating significant shift to higher risk level in default scenario while insignificant decrease in optimistic scenario. The proposed scenario simulation results provide reference to support soil quality improvement and risk management.

VFS-based OFSP model for groundwater pollution study of domestic waste landfill

The groundwater quality is essential for high quality of life and social development. Thus, the importance and necessity of the accurate and rigorous requirements for contaminated groundwater assessment has increasingly attracted engineers' and researchers' attentions. In order to improve the precision and robustness of the groundwater quality evaluation of domestic waste landfills, based on the variable fuzzy set (VFS) pair and the optimized N.L. Nemerow index, we develop an optimized fuzzy set pair (OFSP) model for groundwater quality assessment. Then, we devise the OFSP model by five key elements of optimized synthesis operator "C", relative difference[Formula: see text], connection degree"ui", optimized N.L. Nemerow index "Pi," and pollution load ratio "Ji", which can achieve the reasonable groundwater quality assessment model, the stable groundwater quality evaluation process, and the convincing evaluation results. Finally, a case study on groundwater quality assessment of various domestic landfills in China is conducted to explore the comprehensive impacts of domestic landfills in different regions and types on groundwater pollution from multiple perspectives, and demonstrate the effectiveness of the proposed OFSP model. The groundwater quality assessment results of various domestic landfills indicate that the pollution level of groundwater under unregulated domestic landfills in eastern and southern China is the worst. Based on the assessment results of groundwater quality, we compare the groundwater quality levels obtained by various mainstream methods. In line with precision (0.985), correlation (0.934), robustness (0.953), and rationality (0.946), our designed OFSP model has the best performance. In addition, according to the indexes of discrimination (0.217) and versatility (0.837), the designed OFSP model also has a good ability. Results of experiments well prove that the proposed OFSP model could play a good performance on groundwater quality evaluation in domestic landfills, compared with other mainstream models.

Evaluation of trace elements pollution in deposited dust on residential areas and agricultural lands around Pb/Zn mineral areas using modified pollution indices

Dust deposited on residential and agricultural lands can have serious consequences for the ecosystem when toxic trace elements are present. This study aimed to assess the ecological risk of the trace elements found in the deposited dust around the Mehdi Abad Pb/Zn mine, Yazd, Iran, using several modified pollution indices. The dust samples were collected by the grid method and a Marble Dust Collector (MDCO) sampler to evaluate the concentration of thirty trace elements: nickel (Ni), lead (Pb), barium (Ba), beryllium (Be), chromium (Cr), copper (Cu), dysprosium (Dy), lanthanum (La), lithium (Li), niobium (Nb), tin (Sn), neodymium (Nd), praseodymium (Pr), rubidium (Rb), Ferrum (Fe), sulfur (S), selenium (Se), strontium (Sr), tantalum (Ta), terbium (Tb), zirconium (Zr), tellurium (Te), thorium (Th), titanium (Ti), uranium (U), vanadium (V), yttrium (Y), ytterbium (Yb), thulium (Tm), and cobalt (Co). This study employed multivariate statistical techniques, including Hierarchical cluster analysis (HCA) and the IDW interpolation technique, as well as modified pollution indices such as Enrichment Factor (EF), Modified Pollution Index (MPI), Modified Potential Ecological Risk Index (MRI), and Modified Hazard Quotient (mHQ). All the statistical data analyses were performed via SPSS Statistics, version 22.00. The HCA results showed that all of these trace elements, except Fe, form a group and had similar behavior. The average levels of all elements in the dust samples except for Cr, S, Sr, Ta, Tb, and Te exceeded the background value. The results confirmed that both anthropogenic activities and natural factors were responsible for the trace elements found in the dust. The average EF value for Pb (43.26) indicated its extremely high enrichment in the study area. The MPI, mHQ, and MRI results showed that 33%, 100%, and 33.33% of the dust samples were in the heavily polluted, extreme severity, and high risk categories, respectively. The IDW analysis results revealed that the highest value of the MRI and mHQ indices was in agricultural lands and residential areas; the predominant wind direction also played a role in transferring the elements from the mine to these areas. In general, the results indicated that mining activities increased the ecological risk in Mehdi Abad due to the presence of trace elements, especially Pb.