[Application of the LUR Model in the Prediction of Spatial Distributions of Soil Heavy Metals].

Using the Jintan District of Changzhou City, Jiangsu Province as an example, the LUR model was used to study the spatial distribution of heavy metals and to simulate the spatial distribution of heavy metals in the study area. Compared with the traditional LUR model and the ordinary Kriging interpolation model, the following conclusions were obtained. ① The soil heavy metal content in the study area was highly and significantly correlated with land factors, with the main factor of land use and influencing factors of heavy metals in the soil environment (P<0.01). In terms of influencing factors, the soil Cu and Zn contents were significantly correlated with the area related to traffic in a 2000 m buffer area and 2000 m buffer zone, respectively. The soil Cr, Cu, and Zn contents were significantly correlated with OM, Corg, TC, and TN (P<0.01). ② The R2 of the LUR-S models of the spatial distribution of the heavy metals, Pb, Cr, Cu, and Zn, in the study area were improved by 0.041, 0.406, 0.102, and 0.501, respectively, compared with the traditional LUR model. The accuracy test R2 values were improved by 0.1477, 0.0116, 0.2310, and 0.081, respectively; and the RMSE was reduced by 2.413, 0.631, 1.112, and 2.138, respectively. It was shown that the LUR-S model, which considered the source-sink relationship, had a higher accuracy than the traditional LUR model and ordinary Kriging interpolation model. ③ The LUR-S model was more suitable for the prediction of the spatial distribution of heavy metals with lower pollution and smaller variations, while results for the prediction of the heavy metals with higher pollution and larger variations were worse.

[Simulation of the Absorption, Migration and Accumulation Process of Heavy Metal Elements in Soil-crop System].

Soil-crop system is an important way that heavy metals harm the ecological environment and human health. To research and understand the process of heavy metal absorption, migration and accumulation in soil-crop system is important for the prevention and control of heavy metal pollution and the health of human beings. In this paper, we established a model for crop uptake of heavy metals to calculate the heavy metals contents of wheat roots, stems, leaves and grains, and we analyzed the accumulation process of heavy metals in roots, stems, leaves and grains in the growth cycle of wheat. The predicted values were compared with the measured values to test the accuracy of the model. The results demonstrated that different parts of wheat had different heavy metal absorption capacity, the absorption of the roots was the strongest, followed by leaves, and the absorption capacity of stems and grains was weak. In addition, the contents of different heavy metals in each part of wheat were also significantly different. The content of Cu was the highest, followed by Ni, while the contents of Pb and Cd were small. In the process of wheat growth, the heavy metal accumulation rate of stem, leaf and grain began to slow down at 90, 60 and 100 days respectively, and the concentration of heavy metals reached the maximum gradually, while the accumulation rate of heavy metals in roots showed a growing trend. We studied the process of absorption, migration and accumulation of heavy metals in soil-crop system by using numerical simulation technology, which can provide scientific basis for preventing the ecological and health risks of heavy metal pollution.

Polycyclic aromatic hydrocarbons in soils from urban to rural areas in Nanjing: Concentration, source, spatial distribution, and potential human health risk.

Polycyclic aromatic hydrocarbons (PAHs) have become a major type of pollutant in urban areas and their degree of pollution and characteristics of spatial distribution differ between various regions. We conducted a comprehensive study about the concentration, source, spatial distribution, and health risk of 16 PAHs from urban to rural soils in Nanjing. The mean total concentrations of 16 PAHs (∑16PAHs) were 3330 ng g(-1) for urban soils, 1680 ng g(-1) for suburban soils, and 1060 ng g(-1) for rural soils. Five sources in urban, suburban, and rural areas of Nanjing were identified by positive matrix factorization. Their relative contributions of sources to the total soil PAH burden in descending order was coal combustion, vehicle emissions, biomass burning, coke tar, and oil in urban areas; in suburban areas the main sources of soil PAHs were gasoline engine and diesel engine, whereas in rural areas the main sources were creosote and biomass burning. The spatial distribution of soil PAH concentrations shows that old urban districts and commercial centers were the most contaminated of all areas in Nanjing. The distribution pattern of heavier PAHs was in accordance with ∑16PAHs, whereas lighter PAHs show some special characteristics. Health risk assessment based on toxic equivalency factors of benzo[a]pyrene indicated a low concentration of PAHs in most areas in Nanjing, but some sensitive sites should draw considerable attention. We conclude that urbanization has accelerated the accumulation of soil PAHs and increased the environmental risk for urban residents.

[Mapping Critical Loads of Heavy Metals for Soil Based on Different Environmental Effects].

China's rapid development of industrialization and urbanization causes the growing problem of heavy metal pollution of soil, threatening environment and human health. Therefore, prevention and management of heavy metal pollution become particularly important. Critical loads of heavy metals are an important management tool that can be utilized to prevent the occurrence of heavy metal pollution. Our study was based on three cases: status balance, water environmental effects and health risks. We used the steady-state mass balance equation to calculate the critical loads of Cd, Cu, Pb, Zn at different effect levels and analyze the values and spatial variation of critical loads. In addition, we used the annual input fluxes of heavy metals of the agro-ecosystem in the Yangtze River delta and China to estimate the proportion of area with exceedance of critical loads. The results demonstrated that the critical load value of Cd was the minimum, and the values of Cu and Zn were lager. There were spatial differences among the critical loads of four elements in the study area, lower critical loads areas mainly occurred in woodland and high value areas distributed in the east and southwest of the study area, while median values and the medium high areas mainly occurred in farmland. Comparing the input fluxes of heavy metals, we found that Pb and Zn in more than 90% of the area exceeded the critical loads under different environmental effects in the study area. The critical load exceedance of Cd mainly occurred under the status balance and the water environmental effect, while Cu under the status balance and water environmental effect with a higher proportion of exceeded areas. Critical loads of heavy metals at different effect levels in this study could serve as a reference from effective control of the emissions of heavy metals and to prevent the occurrence of heavy metal pollution.

Fraction distribution and bioavailability of soil heavy metals in the Yangtze River Delta--a case study of Kunshan City in Jiangsu Province, China.

Mobility and bioavailability of soil heavy metals strongly depend on their fractions. Secondary-phase fraction (SPF) of heavy metal, including acid-soluble, reducible and oxidizable fractions, is considered as direct and potential hazardous fraction to organisms. The ratio of SPF to the total concentration of heavy metal represents its bioavailability. In this study, 126 topsoil samples were collected in Kunshan, Jiangsu, China. Fraction concentrations of heavy metals, and their bioavailability and spatial distributions were determined, and relationships between their fractions and types of industry zones were analyzed. Results showed that Cd and Pb had the greatest SPFs among all metals (78.61% and 62.60%, respectively). Great SPFs of Cd and Pb were observed in the dyeing and paper-making industry zone, while great SPFs of Cr, Cu, Zn, Ni were in the smelting and plating industry zone. For most metals, fraction distributions were controlled by soil organic matter and clay contents. Spatial principal component analysis showed SPFs of heavy metals can be explained by two principle components (PCs). PC1 represented SPFs of Cd, Cr, Cu, Pb and Zn, while PC2 represented SPFs of Ni and Co. The spatial distributions of SPFs were influenced by geochemical character, industrial sewage irrigation and soil physico-chemical properties.

[Prediction of As in soil with reflectance spectroscopy].

In the present study, visible-near infrared reflectance spectroscopy (VNIR) measured in laboratory was evaluated for prediction of the content of As in soils. Calibrations between As and reflectance were developed using cross-validation under partial least squares regression (PLSR). Prediction accuracy was tested via separate validation samples. The reflectance was pre-processed by several techniques like smoothing, multiplicative scatter correction (MSC), Log(1/R), first/second derivative (F/ SD) and continuum removal (CR). The accuracy of prediction was evaluated with three statistics: coefficients of determination (R2), ratio of performance to deviation (RPD), and root mean square error of prediction (RMSEP). The results of calibration, cross-validation and prediction of different pre-processing techniques, spectral resolution and OM content were compared. MSC provided better prediction (Prediction R2 = 0.711, RPD = 1.827, RMSEP = 1.613) than other methods because it removed the effects of light scattering and sample thickness. All the results of different resolution are acceptable (Prediction 0.678 < R2 < 0.711, 1.750 < RPD < 1.827, 1.613 < RMSEP < 1.685). The prediction accuracy of subsets with lower OM content(Prediction R2 = 0.694, RPD = 1.697, RMSEP = 1.644) was better than that with higher content. The study indicates that it is feasible to predict As element in soils using reflectance spectroscopy and the prediction accuracy can be improved by pre-processing. Thus this new rapid and cost-effective technique can be used in the monitoring of soil contamination.

[Evaluation of soil heavy metals accumulation in the fast economy development region].

Evaluation of soil heavy metals accumulation was studied in Kunshan City, a typical region of the fast economy development region in China. 126 soil samples were collected and analyzed, and evaluation indexes of soil heavy metal accumulation, which including total concentration of soil heavy metal index (THMI), soil available heavy metal index (AHMI) and fractionation of soil heavy metal index (FHMI), were established, and the heavy metal accumulation conditions of soil in this region were also discussed. Results showed as follows: the spatial variability of THMI was relative lower, with a mean value of 42.57%, whereas strong variability was found in AHMI and FHMI (especially active fraction of soil heavy metals), with the average value of 82.75% and 77.83%, respectively. Judging by each index reference standard of C Horizon, THMI was low-grade with a mean value of 1.01, while the AHMI and FHMI reached to medium accumulation and serious accumulation, with the average values of 2.46 and 4.32, respectively. The synthetic accumulation index of soil heavy metals (SHMI) was 2.56, reaching to medium grade level and with strong variability. 21.54% land area was in low-grade accumulation and 54.70% land area was in medium grade accumulation, while 23.76% land area was in serious accumulation under SHMI evaluation system. All the accumulation evaluation indexes in livestock breeding zone were the lowest, while the indexes in the smelting and plating zone were the highest, but the indexes difference between two zones were unobvious. There were markedly differences in soil types, which the accumulation indexes in Wushan soil were significantly higher than those in Huangni soil and Qingni soil.

[Coregionalization, spatial-correlation and spatial-factor analysis of soil available heavy metals in a typical region of the Yangtze River Delta].

The method of factorial kriging based on the theory of coregionalization is developed by the combination of multi-statistics, geostatistics and GIS. Soil available heavy metals of 126 topsoil samples in Kunshan city, a typical region of Yangtze River Delta, were analyzed, and the spatial distribution pattern was investigated by the method of factorial kriging. Based on the analysis of multi-scale spatial structure characteristics of available heavy metals, we discussed the pollution source and cause of this spatial distribution by means of spatial scale-correlation analysis and spatial principal component analysis. Our results show that all the available heavy metals distribute normally or lognormally with great variability, and the contamination of available Cd is the biggest. The available heavy metals are categorized into three spatial scales, i.e. nugget, short-range (15 km) and long-range (40 km), respectively, and a linear model of coregionalization comprising these three spatial scales is fitted to the experimental auto-and cross-variograms of the soil available heavy metals. Significant relationship is found between Cd and Zn in the three scales. The spatial correlation of available heavy metals in short-range and long-rang are stronger than it in nugget, while the long-rang has more obvious negative correlation than the other two spatial scales. The results of spatial principal component analysis show the pollution sources are different in the three spatial scales. The kriging interpolation method was applied to work out the distribution maps of first and second principal component of available heavy metal, which indicate that available heavy metal concentrations in the soils are closely related to their industry activity, sewage irrigation and soil characteristics.