Avian Conservation Areas as a Proxy for Contaminated Soil Remediation

Source apportionment of potentially toxic elements in soils of the Yellow River Delta Nature Reserve, China: The application of three receptor models and geostatistical independent simulation

The Yellow River Delta (YRD) wetland, the most important estuary wetland in eastern China, has an important ecosystem service function. Rapid and intensive development has inevitably led to the accumulation of potentially toxic elements (PTEs) in soils. Therefore, identifying quantitative sources and spatial distributions of PTEs is essential for soil environmental protection in the YRD. A total of 240 topsoil samples (0-20 cm) were collected in the Yellow River Delta Nature Reserve (YRDNR) and analyzed the PTE contents. To avoid the biases of the single receptor model, positive matrix factorization, factor analysis with nonnegative constraints, and maximum likelihood principal component analysis-multivariate curve resolution-alternating least squares were used for source apportionment of soil PTEs. To promote the efficiency of multivariate geostatistical simulation, a minimum/maximum autocorrelation factor-sequential Gaussian simulation was built to map the spatial patterns of PTEs. Three factors were derived by the three receptor models, and their contributions to the source explanation were similar. As, Cr, Cu, Mn, Ni, and Zn originated from natural sources, with contributions of 85.6%-96.4 %. A total of 61.5 % of Hg was associated with atmospheric deposition of coal combustion and wastewater from upstream. Agricultural activities and oil exploitation contributed 33.5 % and 15.9 % of the Cd and Pb concentrations. Spatial distributions of soil PTEs were controlled by sedimentary grain size. A total of 47.2 % of the total study area was identified as hazardous area for Cd, 10.3 % for As, and 5.4 % for Hg. This work is expected to provide references for soil pollution assessment and management of YRDNR.

Energy-Saving Strategies and their Energy Analysis and Exergy Analysis for In Situ Thermal Remediation System of Polluted-Soil

The environmental safety of soil has become a severe problem in China with the boost of industrialization. Polluted-soil thermal remediation is a kind of suitable remediation technology for large-scale heavily contaminated industrial soil, with the advantages of being usable in off-grid areas and with a high fuel to energy conversion rate. Research on energy-saving strategies is beneficial for resource utilization. Focused on energy saving and efficiency promotion of polluted-soil in situ thermal remediation system, this paper presents three energy-saving strategies: Variable-condition mode (VCM), heat-returning mode (HRM) and air-preheating mode (APM). The energy analysis based on the first law of thermodynamics and exergy analysis based on the second law of thermodynamics are completed. By comparing the results, the most effective part of the energy-saving strategy for variable-condition mode is that high savings in the amount of natural gas (NG) used can be achieved, from 0.1124 to 0.0299 kg·s−1 in the first stage. Energy-saving strategies for heat-returning mode and air-preheating mode have higher utilization ratios than the basic method (BM) for the reason they make full use of waste heat. As a whole, a combination of energy-saving strategies can improve the fuel savings and energy efficiency at the same time.

A decision-making approach for delineating sites which are potentially contaminated by heavy metals via joint simulation

This work develops a new approach for delineating sites that are contaminated by multiple soil heavy metals and applies it to a case study. First a number of contaminant sample data are transformed into multiple spatially un-correlated factors using Uniformly Weighted Exhaustive Diagonalization with Gauss iterations (U-WEDGE). Sequential Gaussian simulation (sGs) is then used to generate sets of realizations of each resultant factor. These are then transformed into sets of sGs contaminant distribution realizations, which are then used to analyze the local and spatial (global) uncertainties in the distribution and concentration of contaminants via joint simulation. Finally, Info-Gap Decision Theory (IGDT) is used to consider different monitoring and or remediation regimes based on the analysis of contaminant realization spatial uncertainty. In our case study each heavy metal contaminant was considered individually and together with all other heavy metals; as the number of heavy metals considered increased, higher critical proportion values of local probability were chosen to obtain a low global uncertainty (to provide high reliability). Info-Gap Decision Theory (IGDT) yielded the most appropriate critical proportion values which minimized information loss in terms of specific goals. When the false negative rate is set to zero, meaning that it is necessary to monitor all potentially polluted areas, the corresponding false positive rates are at least 63%, 65%, 66%, 68%, 70%, and 78% to yield robustness levels of 0.50, 0.60, 0.70, 0.80, 0.90, and 1.00 respectively. However, when the false negative rate tolerance threshold is raised to 50%, the false positive rate tolerance which yields robustness levels of 0.50, 0.60, 0.70, 0.80, 0.90 and 1.00 drop to 12%, 14%, 15%, 18%, 20%, and 39%. The case study demonstrates the effectiveness of the developed approach at making robust decisions concerning the delineation of sites contaminated by multiple heavy metals.