농업환경지표를 이용한 정책의 연계성 분석 및 평가 - 김창길 (한국농촌경제연구원, 2008)
This report is the final result of the 3rd year research on analyzing and evaluating policy linkage using agricultural environmental indicators (AEIs) which was implemented as a detailed project of Evaluating the Feedback of Agricultural Policy Using OECD Agricultural Environmental Indicators which is a national project of Rural Development Administration. The objectives of this study are to review evaluation models to explore the possibility of diagnosis for agricultural environmental status as well as the linkage with agricultural environmental policy using OECD AEIs and to present cases of linkage and application analysis of policy in order to support effective decision making for agricultural environmental policy. As to the composition of this report, the necessity, background, purpose and scope of the research were presented in the chapter 1, the theory and conceptual framework of the development of AEIs in the chapter 2, diagnosis of environmental status using the AEIs in the chapter 3, policy evaluation model using AEIs in the chapter 4, a case of linkage and application of policy using AEIs in the chapter 5 and future tasks for implementation was presented in the chapter 6. Major findings of this research are summarized as follows: First, the concept of AEIs was set as a representative value which was calculated based on a certain criteria which can appropriately explain the reality among the environmental factors that constitute agricultural ecosystems. Theoretically, the AEI may be regarded as specific objective-oriented tailored information under risks and uncertainty. Second, various indicators such as agricultural contextural indicator, nutrient balance indicator, pesticide risk indicator, energy indicator, soil indicator, water use indicator, water quality indicator, atmosphere and climate change indicator, biodiversity indicator and farm management indicator were applied for diagnosis of environmental conditions using the AEIs. Third, the policy evaluation models using AEIs referred to in this report are; Directed Acyclic Graph model of Carnegie Mellon University which used TETRA IV software, stylized agri-environmental policy impact model (SAPIM) of OECD, STONE model of Netherlands and Indicator Reporting on the Integration of Environmental Concerns into Agricultural Policy (IRENA) project of EU. Fourth, as the Directed Acyclic Graph model was a model designed for the analysis of casual relationship and requires considerable data in agricultural environmental field, the model gives considerable constraints for the analysis of many countries. As a solution for these problems, OECD is utilizing SAPIM for the analysis of effect of agricultural environmental policies in many OECD countries including Finland, the U.S.A and Japan. Especially, as Japan has agricultural structure based on paddy field, they are reflecting the effect of the factors such as nutrient runoff, biodiversity and arable land's water retention capacity to the model. In addition, they are reflecting the effects such as arable land's water retention capacity and soil loss through the Universal Soil Loss Equation to the model as well. Fifth, STONE model of The Netherlands was designed for the introduction and monitoring of effective policy program to solve nutrient surplus problems and the evaluation of agricultural environmental policy using AEIs. This model is an integrated result of research tasks performed by various research institutions (Alterra, RIVM, RIZA, Plant Research International, LEI) in the fields of agricultural production, the use of farmland, environment, surface water and agricultural economics. Especially STONE system is being utilized as very useful means for the evaluation of agri-environmental policy instruments for nitrogen and phosphorus leaching in ground water and surface water and the environmental effect of agricultural sector of The Netherlands at national level. Sixth, IRENA (Indicator Reporting on the Integration of Environmental Concerns into Agricultural Policy) project of EU is a project which has a basic DPSIR structure using 35 AEIs and which European Environment Agency and other institutions applies for the evaluation of policies of 15 European countries. In the IRENA project, agricultural policies and environmental policies are integrated by considering environmental conditions, policy objectives, institutional structure, socio-economic factors and attitudes at EU level, and the monitoring and evaluation of policy means and administration is carried out to support the integration. Seventh, a questionnaire survey on the utilization of AEIs was conducted for farmers and policy makers and administrators in order to analyze the policy linkage using AEIs. In the case of farmers, the utilization of soil information among the AEIs showed the highest level of 3.5 point (on 5.0 full marks basis). In relation to the contribution of AEI to farming activities, soil indicator showed 4.2 point level, pesticide residue quantity indicator 3.9 point and water quality indicator 3.7 point level, and biodiversity indicator showed ‘average level’ of 3.3 point. In the case of policy makers and administrators, the result of evaluation of AEI to policy decision showed 3.0~3.3 point level which is regarded to be not so high in the indicators related to biodiversity, air quality, landscape and energy whereas the indicators related to land use, soil, water, farm administration, nutrients, pesticides shower comparatively high level of 3.7~4.1 point. The result of evaluation on the reliability of AEI which policy makers and administrators are provided with showed that the reliability of nutrient management indicator was the highest as 4.1 point, and land use indicator of 3.8 point and soil indicator of 3.7 point followed in order. Eighth, the result of diagnosis of agricultural environmental status using AEIs by country showed that nitrogen balance in the nutrient balance indicator showed 240kg per ha of farmland for Korea, 229kg for Netherlands, 199kg for Luxemburg and 193kg for Belgium in order while phosphorus balance showed 57kg for Luxemburg, 52kg for Japan and 48kg for Korea in order. In the case of pesticide quantity used, Japan and Korea were at very high level of pesticide use per ha of farmland showing the result of 14.86kg for Japan, 9.32kg for Korea and 5.44kg for Italy in order. And in the area of energy use, Netherlands was 2,076kg and Korea was 1,924kg on per ha of farmland basis in order. In the area of water use, Japan was 11,935m² and Korea was 3,778m² in order. In general the result of comparison for the agricultural environmental status among OECD countries through AEIs, Korea seems to have considerably high level of environmental load in agricultural sector. Ninth, the case of Jinan-gun in Jeonbuk province was presented in establishing regional environmentally friendly agriculture promotion plan using AEIs as the case of application of agricultural environmental indicators to pertinent local governments in relation to linkage with policy. The result of the calculation of nutrient balance indicator of Jinan-gun as of 2004 showed that inputs of nutrients were concentrated to particular counties, and as the result it was analyzed that there was a possibility of the pollution of ground water and surface water in some areas where the nutrient inputs were in excess and therefore proper nutrient management measures in the pertinent areas are necessary. Tenth, the implementation plan for Regional-Based Maximum Nutrients Loading System(RMNLS) was presented as a case for the application of AEIs to central government in linkage with policy. For the implementation of RMNLS, items including the calculation of nutrient balance indicator by region, nutrient management method by region, implementation system for gross nutrient quantity system, monitoring of nutrient balance, disclosure of pertinent information, incentive and penalty depending on the level of reduction of nutrients and a demonstration project implementation plan for gross nutrient quantity system for areas subject to special administration were presented. Lastly, as a future tasks in exploring policy linkage plan for AEIs, it is necessary to supplement the AEI continuously more than anything else. As a concrete example, the establishment of database for pertinent data for the calculation of nutrient balance indicator, the introduction of new methodology for more persuasive explanation and plan for the establishment of information sharing system for efficient use of data were presented. For the policy linkage using AEIs, it will be essential to actively cope with international discussions on the utilization of OECD AEIs so that scientific and systematic analysis of domestic agricultural environmental policy is possible. Accordingly, it will be necessary to find appropriate support plan so that in-depth research not only for the development of reliable AEIs but also for the development of model for policy linkage using AEIs can be sustained in the future.