ABSTRACT
To analyze social-economic causes of the regional ecological degradation, and avoid such problems as the complex circulation network and difficulty to identify laws caused by extended exergy analysis (EEA) previously applied at the national scale, this paper reduced spatial scale to the county scale and took Pengyang County in Ningxia as an example. Eco-economic system in Peng-yang County was divided into seven interrelated sectors. The exergy value of circulations in the eco-economic system including materials, labor and capital were calculated respectively to analyze the extended exergy characteristics of the driving sectors, factors and paths and evaluate their ecological efficiency. The results showed that agriculture and households were the main driving sectors of the eco-economic system in Pengyang County. The average exergy value of 31 flow paths among the sectors was 0.80 PJ. There were only 8 flow paths whose exergy values were higher than the average value. Eco-economic system in Pengyang County development was driven by two continuous flow paths, labor output of the households sector and demands of the households sector supported by other sectors. The mineral resources were massively exploited, and then directly exported to the outside, which could not promote the local development from the inside, but, on the contrary, increase the ecological environment pressure because of the over-exploitation. The eco-efficiency of Pengyang County in 2014 was 68.1%, almost equivalent to the by-level of the national scale at home and abroad ten years ago, mainly because of the lower eco-efficiencies of the service sector and households sector. EEA had the advantage of networking and structuring, could specify the sectors, factors and driven paths, and break through the bottleneck of driving mechanism research of the eco-economic system. EEA had certain adaptability to explore the operational principle and optimal pattern of the regional eco-economic system. Compared with the national scale, EEA at the regional scale could more easily identify the driving mechanism of eco-economic system, and could clearly guide the regional administrative department to reduce the ecological environment pressure.
Subject(s)
Conservation of Natural Resources , Ecology , Agriculture , EnvironmentABSTRACT
For deep analysis on the regional environmental economic system, the paper analyzes the mutual relation of regional economy development, environmental quality, environmental pollution, and builds the theoretical basis. Then, the economy-pollution-environment quality three-dimensional coupling evaluation model for district is constructed. It includes economic development level index, environmental pollution index, and environmental quality index. The model is a cube, which has spatialization and visualization characteristics. The model includes 8 sub cubes, which expresses 8 types of state, e. g. low pollution-inferior quality-low level of economic development etc. The model can be used to evaluate the status of region, divide development phase, analyze evolution trend etc. It has two ways including relative meaning evaluation (RME) and absolute meaning evaluation (AME). Based on the model, Yinchuan City in the Ningxia Hui Autonomous Region is used as an example for the empirical study. Using RME, compared with Guangzhou city, The result shows that the Yinchuan City has been a high pollution-low quality-low level of economic development state for a long period during 1996-2010. After 2007, the state changed to a high pollution-high quality-low level of economic development. Now, the environmental quality of Yinchuan city gets better, but pollutant discharge pressure is high, and tends to be the break point of high environment quality and low environment. With AME, using national standard, the Yinchuan City remains a high pollution-low quality-low level of economic development state during 1996-2010. Empirical research verifies that different target reference areas and relevant national standards have different main parameters, the evaluating result has an flexible range. The dimensionless data enhances the coupling of index. The data position in model increases the visibility to the environmental management decisions. The model improves mismatches of calculated data size, time asymmetry of spatial data, verification of the former multi-target coupling model.
Subject(s)
Economic Development , Environmental Pollution , Models, Theoretical , EnvironmentABSTRACT
Livelihood capital has a close relationship with the income and expenditure of farmers' households. For example, the survival strategies of farmers' households are determined by it and it also influences regional development mechanisms and models. Under the analysis framework of sustainable livelihoods, this study evaluated farmers' livelihood capital, income, and expenditure, based on a participatory rural appraisal and a statistical method, in the development-restricted ecological district of Ningxia, decomposed into the nationality, terrain, and type of farmers' household. Further, by using an index of non-farm business households, the correlations between the livelihood capital and income with the expenditure of farmers' households and the index of non-farm business households were quantified to understand the mechanism of regional development. The results showed that livelihood capital was generally low in the study area. In particular, the livelihood capital of Hui nationality households was slightly higher than that of Han nationality households, that of river valley households was higher than that of mountain households, and that of combined occupation households and non-farm business households was significantly higher than that of agricultural households. Moreover, there was a significant positive correlation between the net annual income of farmers' households and the non-agricultural index, human capital, physical capital, and financial capital, while a significant negative correlation existed between net annual income and natural capital. These findings suggested that efforts were required to enhance the capacity of the non-agricultural index and the human, material, and other capital in the study area. They also served as a guideline for the circulation of peasants' means of production in order to accelerate the polarization of natural capital.
Subject(s)
Economic Development , Poverty Areas , Rural Population , Agriculture , China , Ecology , Family Characteristics , Humans , IncomeABSTRACT
UNLABELLED: Concentrations of Zn, Cu, Cr, Pb and Cd in 96 topsoil samples collected from the northern Hebin Industrial Park were measured by the atomic absorption detector (AAD). Spatial variability was identified by geostatistical analysis with the aid of GS + 3.0 and ArcGIS 9.0. Temporal variability of five heavy metals was contrasted to the concentration in 1985 of the Ningxia second soil census. Google earth maps in years of 2003, 2004, 2009 and 2011 have been analyzed to find the variation of the geographical distribution of factories in study Area. Result showed that mean concentrations of Zn, Cu, Cr, Pb and Cd were 100.29, 352.86, 77.56, 50.52, 4.06 mg x kg(-1), respectively, and were all higher than the background values. Using the second level of environmental quality standard for soils of China as the criterion, Zn, Cr, Pb were not risk, Cu, Cd were mild contamination and serious contamination. Spatial distribution of the concentration of the five heavy metals varies with prevailing wind direction, from the northwest to southeast, increasing gradually. Meanwhile, there were several hotspots. Google earth map analysis showed that in the northeast and southeast part appeared a large number of factories after 2009, which should be the main sources of the five heavy metals in soils. In the lowlying southwest part, although there was no factory, soils still have been polluted heavily because of another adjacent industrial area in Inner Mongolia Autonomous Region and the smoke dust was blocked by the Helan Mountain along its west. CONCLUSIONS: (1) The number of the enterprise increased and trans-boundary pollution led to the high heavy metal concentration in surface soil of study area; (2) In northwest China, because of the strong wind, smoke dusts spread very long and distribution range was extensive, and low terrain area and enterprise distribution pattern lead to the island distribution.
