Zhou Yong-zhang

The Impact on Environmental Kuznets Curve by Trade and Foreign Direct Investment in China

Abstract Based on data of trade, foreign direct investment (FDI), economic development and environmental conditions in Chinas 30 provinces between 1990–2002, this paper deals with the impact on Environmental Kuznets Curve (EKC) of trade and FDI in China. The results show no direct impact on EKC of trade, on the one hand. However, trade contributes significantly to economic growth, and has played a positive role in introducing advanced pollution prevention technology and environmental management methodology to China. Therefore, a proactive trade policy will help solve the environmental pollution problem brought by economic growth. On the other hand, there is a positive correlation between FDI and pollutant emission, which proves that FDI does have some negative influence on environment in China due to hasty introduction of foreign capital and inadequate environmental management system in China.

Using Multivariate Statistical and Geostatistical Methods to Identify Spatial Variability of Trace Elements in Agricultural Soils in Dongguan City, Guangdong, China

Abstract Dongguan City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, including vegetable and orchard soils in the city, and eight heavy metals (As, Cu, Cd, Cr, Hg, Ni, Pb, and Zn) and other items (pH values and organic matter) have been analyzed, to evaluate the influence of anthropic activities on the environmental quality of agricultural soils and to identify the spatial distribution of trace elements and possible sources of trace elements. The elements Hg, Pb, and Cd have accumulated remarkably here, incomparison with the soil background content of elements in Guangdong Province. Pollution is more serious in the western plain and the central region, which are heavily distributed with industries and rivers. Multivariate and geostatistical methods have been applied to differentiate the influences of natural processes and human activities on the pollution of heavy metals in topsoils in the study area. The results of cluster analysis (CA) and factor analysis (FA) show that Ni, Cr, Cu, Zn, and As are grouped in factor F1, Pb in F2, and Cd and Hg in F3, respectively. The spatial pattern of the three factors may be well demonstrated by geostatistical analysis. It is shown that the first factor could be considered as a natural source controlled by parent rocks. The second factor could be referred to as “industrial and traffic pollution sources”. The source of the third factor is mainly controlled by long-term anthropic activities, as a consequence of agricultural activities, fossil fuel consumption, and atmospheric deposition.

A Grey Fuzzy Comprehensive Model for Evaluation of Geological Structure Complexity

Abstract Several structure sets (faults and folds) are characterized by their self-similarity properties. Herein, we discuss the degrees of complexity of fractures by introducing the box-counting fractal dimension of faults as a key criterion to be used in comprehensive fuzzy analysis model for evaluation of the complexity of structures. Totally, eight criteria including density, intensity, length of faults, types and box-counting fractal dimension of faults, the intersection angle between faults and coal beds, gradient coefficients, dip angles of the coal beds, and variation coefficients of dip angles of the coal seams, were used for the evaluation purpose. The grey fuzzy comprehensive assessment model was used to rank the relative importance of these criteria. Scores indicating the complexity of structure were calculated on the base of criteria values and their weights for each sub-area of the study area in the Pansan coal mine district in the southern Anhui Province, China. The result on the calculated complexity of structure is useful for mining planning in the study area.

Uncertainty, Irreversibility and the Timing Problems of Environmental Policy

Abstract Most environmental issues and policy designing are uncertain and irreversible; therefore, the timing of environmental policy implementation becomes especially important. This paper establishes a random dynamic programming model and analyzes the optimal timing problems in environmental policy under uncertain variables. This model results indicate that two variables have a significant impact on the timing of environmental policy implementation and they work in opposite directions: on one hand, the more uncertain the economy is, the higher the cost of policies implementation will be, and consequently the incentive to immediately adopt the policy will be stronger. On the other hand, the higher the uncertainty of the environment is, the stronger the irreversibility of ecological harm caused by pollutants per unit will be. Therefore, the government should implement new environmental policies as early as possible in order to gain more ecological benefits.

Study on Disturbances and Its Effects on Nature Reserves

Abstract As a widespread natural phenomenon, disturbances are considered a discrete event occurring in a natural ecosystem within various spatial and temporal scales. The present paper discusses the types of disturbances and their influence on the ecologic system in nature reserves. It is shown that nature reserves are facing a great challenge dealing with these disturbances. A rational control for disturbances should be improved in order to promote the healthy development of nature reserves this could be done by enhancing the publicity and training of environment protection, coupling management with communities around and other nature reserves, effective management methods, rational planning, and supporting nature servers.

The Effect of Jump on Evaluating Natural Resource Investments

Abstract The evaluation of mining and other natural resource projects is made particularly difficult by the high degree of uncertainty attaching to output prices. It is shown that the techniques of continuous time arbitrage and stochastic control theory may be used not only to value such projects but also to determine the optimal policies for developing managing. This paper describes a model for evaluating natural resource investments under uncertainty from a new perspective. The previous works in this field mostly regard the movements of natural resource prices as a continuous GBM process, which pays few attentions to the shock of unexpected bad news. Our model provides the first theoretical method to analyze the impact of such “jump” on investment decisions. It concludes that the more frequently bad news happens, the earlier a project will be invested.