Combination of hydroxyapatite (HAP) and potassium chloride (KCl) was used to stabilize lead and cadmium in contaminated mining soils. Pot experiments of chilli (Capsicum annuum) and rape (Brassica rapachinensis) were used to evaluate the stabilization efficiency. The results were the following: (1) the optimal combination decreased the leachable lead by 83.3 and 97.27 %, and decreased leachable cadmium by 57.82 and 35.96% for soil HF1 and soil HF2, respectively; (2) the total lead and cadmium concentrations in both plants decreased 69 and 44 %, respectively; (3) The total lead and cadmium concentrations in the edible parts of both vegetables also decreased significantly. This study reflected that potassium chloride can improve the stabilization efficiency of hydroxyapatite, and the combination of hydroxyapatite and potassium chloride can be effectively used to remediate lead and cadmium contaminated mining soil. 相似文献
This study demonstrates that prior to Typhoon Morakot, the index of heavy metals such as Cd, Pb, and Cr was above moderate pollution levels in Dapeng Bay and the three neighboring rivers. During January 2007, the content of Zn metal in Dapeng Bay and Tungkang River was also above moderate pollution levels, while after the Typhoon Morakot event, all metals were at levels below the criteria for low pollution. This work has demonstrated that the samples collected from Dapeng Bay and the three neighboring river systems displayed individual crowd–distribution phenomena, indicating variability between the heavy metal content of sediments collected from Dapeng Bay and the three neighboring rivers. Understanding the spatial and temporal variability of heavy metal pollutants in the sediments of Dapeng Bay, along with pollution sources from three neighboring rivers, provides useful information in the fields of disaster management, habitat recovery, operative management, as well as ecotourism specification. 相似文献
Identification of different pollution sources in groundwater is challenging, especially in areas with diverse land uses and receiving multiple inputs. In this study, principal component analysis (PCA) was combined with geographic information system (GIS) to explore the spatial and temporal variation of groundwater quality and to identify the sources of pollution and main factors governing the quality of groundwater in a multiple land-use area in southwestern China. Groundwater samples collected from 26 wells in 2012 and 38 wells in 2018 were analyzed for 13 water quality parameters. The PCA results showed that the hydro-geochemical process was the predominant factor determining groundwater quality, followed by agricultural activities, domestic sewage discharges, and industrial sewage discharges. Agriculture expansion from 2012 to 2018 resulted in increased apportionment of agricultural pollution. In contrast, economic restructure and infrastructure improvement reduced the contributions of domestic sewage and industrial pollution. Anthropogenic activities were found the major causes of elevated nitrogen concentrations (NO3?, NO2?, NH4+) in groundwater, highlighting the necessity of controlling N sources through effective fertilizer managements in agricultural areas and reducing sewage discharges in urban areas. The applications of GIS and PCA successfully identified the sources of pollutants and major factors driving the variations of groundwater quality in tested years.
Geostatistical models play an important role in spatial data analysis, in which model selection is inevitable. Model selection methods, such as AIC and BIC, are popular for selecting appropriate models. In recent years, some model averaging methods, such as smoothed AIC and smoothed BIC, are also applied to spatial data models. However, the corresponding averaging estimators are outperformed by optimal model averaging estimators (Hansen in Econometrica 75:1175–1189, 2007) for the ordinary linear models. Therefore, this paper focuses on the optimal model averaging method for geostatistical models. We propose a weight choice criterion for the model averaging estimator on the basis of the generalized degrees of freedom and data perturbation technique. We further theoretically prove the resultant estimator is asymptotically optimal in terms of the mean squared error, and numerically demonstrate its satisfactory performance. Finally, the proposed method is applied to a mercury data set. 相似文献
Journal of Material Cycles and Waste Management - Fluorescent powder plays an important role in the modern electronic lighting products. During the production of electronic lighting products, a... 相似文献