Emergy evaluation of agricultural sustainability of Northwest China before and after the grain-for-green policy

Wang, Xiuhong; Shen, Jianxiu; Zhang, Wei

doi:10.1016/j.enpol.2013.12.060

Cited by 55 publications

(34 citation statements)

References 28 publications

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“…As a result, improvements in the water use efficiency and water saving irrigation are of vital importance for high intensity agriculture in China. This type of agricultural input not only affects the regional agricultural sustainability but also poses a potential threat to the ecological and environmental stability of the entire country (Wang et al 2014). Under environmental pressure, a reasonable assessment of the environmental risk and early warnings in areas with high intensity agriculture are essential for achieving a Bwin-win^outcome with high food production and low environmental risk.…”

Section: Introductionmentioning

confidence: 99%

Assessing environmental risks for high intensity agriculture using the material flow analysis method —a case study of the Dongting Lake basin in South Central China

Yin

Yuan

2015

Environ Monit Assess

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This study primarily examined the assessment of environmental risk in high intensity agricultural areas. Dongting Lake basin was taken as a case study, which is one of the major grain producing areas in China. Using data obtained from 1989 to 2012, we applied Material Flow Analysis (MFA) to show the material consumption, pollutant output and production storage in the agricultural-environmental system and assessed the environmental risk index on the basis of the MFA results. The results predicted that the status of the environmental quality of the Dongting Lake area is unsatisfactory for the foreseeable future. The direct material input (DMI) declined by 13.9%, the domestic processed output (DPO) increased by 28.21%, the intensity of material consumption (IMC) decreased by 36.7%, the intensity of material discharge (IMD) increased by 10%, the material productivity (MP) increased by 27 times, the environmental efficiency (EE) increased by 15.31 times, and the material storage (PAS) increased by 0.23%. The DMI and DPO was higher at rural places on the edge of cities, whereas the risk of urban agriculture has arisen due to the higher increasing rate of DMI and DPO in cities compared with the counties. The composite environmental risk index increased from 0.33 to 0.96, indicating that the total environmental risk changed gradually but seriously during the 24 years assessed. The driving factors that affect environmental risk in high intensity agriculture can be divided into five classes: social, economic, human, natural and disruptive incidents. This study discussed a number of effective measures for protecting the environment while ensuring food production yields. Additional research in other areas and certain improvements of this method in future studies may be necessary to develop a more effective method of managing and controlling agricultural-environmental interactions.

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Section: Introductionmentioning

confidence: 99%

Assessing environmental risks for high intensity agriculture using the material flow analysis method —a case study of the Dongting Lake basin in South Central China

Yin

Yuan

2015

Environ Monit Assess

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“…Take the data d 2 (x 1 , x α ) = 0.710 and d 2 (x 1 , x β ) = 0.138 into Equation (26), and the Dalian optimal subordinate degree y α 1 without containing the inferior constraint can be obtained: Table 6, we can obtain the corresponding evaluation rankings of 15 sub-provincial cities in a descending order, as shown in Row 2 in Table 6. Second, we calculate the subordinate degree and the evaluation rankings containing inferior constraint.…”

Section: The Determination Of Index Weightmentioning

confidence: 99%

“…equals 0 in Equation (25), the optimal solution y α jS without containing the inferior constraint x Sk is shown in Equation (26).…”

Section: A City Green Economy Evaluation Modelmentioning

confidence: 99%

“…during 2005-2020 by using standard system dynamic models [25]. In order to assess agricultural sustainability development level, Wang et al established an evaluation system including agricultural economic profitability and environmental sustainability [26]. Chen et al calculated the indices' weights by using the AHP method, and then established an industrial green development evaluation model.…”

Section: Introductionmentioning

confidence: 99%

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City Green Economy Evaluation: Empirical Evidence from 15 Sub-Provincial Cities in China

et al. 2016

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City green economy plays an important role in the development of low-carbon economy and the achievement of sustainable development of economy, society and ecological environment. From the perspective of economy, society, environment and resources, the evaluation of the green economy in urban areas tends to offer us a new insight into the green economy of cities. This paper is about the creation of a novel urban green economy evaluation model and its application. First of all, we established a city green economy evaluation index system based on R cluster analysis and coefficient of variation. Secondly, based on the nonlinear weighted utilizing entropy weight method, a city green economy evaluation model is established based on inferior constraints. Thirdly, by comparing the differences between evaluation rankings under inferior constraints and non-inferior constraints, the advantageous factors and the disadvantageous ones in urban green economy development are obtained. The proposed model has been verified with the data on 15 sub-provincial cities in China. Empirical analysis results show that: (1) The proposed approach can accurately find out the advantageous and disadvantageous factors for each sub-provincial city; (2) In the evaluation of green economy development, the order of importance of the three criterion layers is X 1 Economy development > X 2 Social livelihood of the people > X 3 Resources and environment; (3) Local governments should implement differential, reasonable policies in order to improve their green economy development. Moreover, our research is not only significant for developing green economy in China's sub-provincial cities, but also serves as a reference for the development of green economy in other cities in the world.

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“…During the period 1980-2010, the national arable land protection policies produced the changes in the arable land in the northern Shaanxi region to some extent. In particular, the "Grain-for-Green" policy, which was implemented with the goal of improving ecological security in 1999, involved the conversion of arable land to forests or grasslands [21]. After the implementation of the "Grain-for-Green" policy by the state in 1999, the change curves for the year-end arable land proportion of the total area at the three scales (the Baota District, Yan'an City, and northern Shaanxi region) were compared, and the data demonstrated that the Grain-for-Green policy was not an important factor affecting changes in the arable land in the Baota District.…”

Section: Analysis Of the "Grain-for-green" Policy Factors That Producmentioning

confidence: 99%

Analysis of Multi-Scale Changes in Arable Land and Scale Effects of the Driving Factors in the Loess Areas in Northern Shaanxi, China

2014

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Abstract:In this study, statistical data on the national economic and social development, including the year-end actual area of arable land, the crop yield per unit area and 10 factors, were obtained for the period between 1980 and 2010 and used to analyze the factors driving changes in the arable land of the Loess Plateau in northern Shaanxi, China. The following areas of arable land, which represent different spatial scales, were investigated: the Baota District, the city of Yan'an, and the Northern Shaanxi region. The scale effects of the factors driving the changes to the arable land were analyzed using a canonical correlation analysis and a principal component analysis. Because it was difficult to quantify the impact of the national government policies on the arable land changes, the contributions of the national government policies to the changes in arable land were analyzed qualitatively. The primary conclusions of the study were as follows: between 1980 and 2010, the arable land area decreased. The trends of the year-end actual arable land proportion of the total area in the northern Shaanxi region and Yan'an City were broadly consistent, whereas the proportion in the Baota District had no obvious similarity with the northern Shaanxi region and Yan'an City. Remarkably different factors were shown to influence the changes in the arable land at different scales. Environmental factors exerted a greater effect for smaller scale arable land areas (the Baota District). The effect of socio-economic development was a major driving factor for the changes in the arable land OPEN ACCESS Sustainability 2014, 6 1748 area at the city and regional scales. At smaller scales, population change, urbanization and socio-economic development affected the crop yield per unit area either directly or indirectly. Socio-economic development and the modernization of agricultural technology had a greater effect on the crop yield per unit area at the large-scales. Furthermore, the qualitative analysis indicated that government policies had a more significant impact on the large-scale arable land areas.

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Emergy evaluation of agricultural sustainability of Northwest China before and after the grain-for-green policy

Cited by 55 publications

References 28 publications

Assessing environmental risks for high intensity agriculture using the material flow analysis method —a case study of the Dongting Lake basin in South Central China

Assessing environmental risks for high intensity agriculture using the material flow analysis method —a case study of the Dongting Lake basin in South Central China

City Green Economy Evaluation: Empirical Evidence from 15 Sub-Provincial Cities in China

Analysis of Multi-Scale Changes in Arable Land and Scale Effects of the Driving Factors in the Loess Areas in Northern Shaanxi, China

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