[Spatial distribution and accumulation of heavy metal in arable land soil of China].

Based on the domestic and foreign published papers about soil heavy metal contents, the present study explored the spatial variations of heavy metal contents in agricultural soil in China. Totally, 173 studies on soil Pb, 138 on Cd, 156 on Cu, 139 on Zn and 140 on Cr were collected. Firstly, the abnormal values were selected and removed, then the spatial distributions were obtained through Kriging method and the average values in the provinces were calculated. Results show that the spatial distributions of heavy metals have obvious regional characteristics and the southwest part of China has relatively high heavy metal concentrations in soils. Compared with the background value of soil heavy metal concentrations, nearly all of the provinces have higher Pb, Cd, Cu and Zn concentrations. Pb and Cd have the most obviously higher values than the background values. The highest difference of Pb concentration is in Yunnan Province with 1.91 times of the background, and the highest Cd difference is in Liaoning Province with 23.04 times of the background; The highest Zn enrichment is in Yunnan, with 1.55 times of the background; and the highest Cu difference with 2.92 times of the background value.

[Spatial pattern evolution of carbon emission intensity from energy consumption in China].

Using Theil index and spatial autocorrelation analysis methods, the characteristics, regional disparity and spatial pattern evolution of carbon emission intensity from energy consumption were analyzed on national, regional and provincial level from 1999 to 2007 in China. The results indicate that: (1) total energy carbon emission in China has increased from 0.91Gt in 1999 to 1.83Gt in 2007, while carbon emission intensity has decreased from 0.83 t x (10(4) yuan) (-1) to 0.79 t x (10(4) yuan) (-1); (2) carbon emission intensity of eight major economic blocks showed the trend of three-level differentiation, with that of northeast regions, the middle reaches of Yellow River regions and northwest regions above 1.0 t x (10(4) yuan)(-1); northern coastal regions, the middle reaches of Yangtze River regions and southwest regions 0.7-1.0 t x (10(4) yuan) (-1); eastern and northern regions 0.32-0.51 t x (10(4) yuan) (-1); (3) Theil index analysis indicates that the within-region carbon emission intensities were similar, and the expanding total disparity of carbon emission intensity was primarily due to between-region inequalities. (4) spatial autocorrelation analysis shows that Global Moran's I has increased from 0.19 to 0.25, indicating that there were positive spatial correlations among provincial regions in China, and regions of similar carbon emission intensity agglomerated in space. The "cold spot" areas of carbon emission intensity were relatively stable, while the "hot spot" areas has gradually shifted from northwest regions to the middle reaches of Yellow River regions and northeast regions. (5) spatial disparity of carbon emission intensity is closely related to factors such as regional resources endowment, economic development, industrial structure and energy utilization efficiency. The study of regional disparity and spatial autocorrelation provides insight into spatial heterogeneity and spatial pattern evolution of carbon emission intensity in China, and also provides references for the development of differential regional objectives of carbon emission reduction and related regulation policies.

[Application of spatial autocorrelation analysis to the COD, SO2 and TSP emission in Jiangsu province].

Spatial autocorrelation is an effective tool of spatial statistics, which is used to disclose the spatial structure of regional disparity. There are two different scales to measure regional spatial dependence: global spatial autocorrelation and local spatial autocorrelation. Based on environmental data of 13 cities in Jiangsu province from 1990 to 2006, the regional disparity of COD, SO2 and TSP emission was discussed by using spatial autocorrelation analysis methods. The results show that total emission of COD and TSP decreased respectively from 596 353 t and 1 101 404 t in 1990 to 291 762 t and 704734 t in 2006, while total emission of SO2 kept steady. In 2006, Global Moran's I of COD, SO2 and TSP emission was 0.465 7, 0.214 2 and 0.510 1 respectively. It is identified that positive spatial autocorrelation is presented and spatial aggregation pattern of COD, SO2 and TSP emission are appeared. However, spatial aggregation pattern of COD emission appears earlier than that of SO2 and TSP, and spatial aggregation degree of COD is also higher than that of SO2 and TSP. There are different spatial patterns between southern and northern Jiangsu. In southern Jiangsu, Global Moran's I of COD, SO2 and TSP emission had increased to 0.499 7, 0.320 2 and 0.298 3 up to 2006, and spatial aggregation pattern appeared remarkably. In northern Jiangsu, most of the Global Moran's I were less than -0.2, and spatial aggregation pattern disappeared accordingly. High cluster region of COD emission is Suzhou, Wuxi and Changzhou, and high cluster region of SO2 emission is Suzhou and Wuxi. However, spatial pattern of TSP emission does not change much and five cities of southern Jiangsu (Suzhou, Wuxi, Changzhou, Zhenjiang, Nanjing) are still the high cluster region. The last, the research provides an important cognition to regional environment disparity and macro-environmental strategy, and a significant means to harmonious society and eco-province construction in Jiangsu province.

[Impact of rural land market on farm household's behavior of soil & water conservation and its regional difference: A case study of Xingguo, Shangrao, and Yujiang County in Jiangxi province ecologically vulnerable districts].

The paper analyzed the farm households' decision-making progress of soil & water conservation and its two-stage conceptual model. It also discussed the impacts of rural land market on the farm households' behavior of soil & water conservation. Given that, the article established models for the relations between the land market and soil & water conservation, and the models' parameters were estimated with Heckman's two-stage approach by using the farm household questionnaires in Xingguo, Shangrao and Yujiang counties of Jiangxi province. The paper analyzed the impact o f rural land market on farm household's behavior of soil & water conservation and its regional difference with the result of model estimation. The results show that the perception of soil & water loss and the tax & fee on the farm land have significant influence upon the soil and water conservation from the view of the population; however, because of different social and economic condition, and soil & water loss, there are differences of the influence among the three sample counties. These differences go as follows in detail: In Xingguo County, the rent-in land area and its cost have remarkable effect on the farm households' soil & water conservation behavior; In Yujiang County, the rent-in land area, rent-in cost and rent-out land area remarkably influence the farm households' behavior of soil and water conservation, with the influence of the rent-in land area being greater than Xingguo County; In Shangrao County, only rent-out land area has significant influence on the behaviors of soil & water conservation; In all samples, Xingguo County and Yujiang County samples, the rent-out income has no significant influence on the farm household's decision-making behavior soil and water conservation. Finally, the paper put forward some suggestions on how to bring the soil & water loss under control and use land resource in sustainable ways.