Recently, Life Cycle Assessment (LCA) has been recognized as an effective tool for evaluating the environmental impacts of regional activities. The main issue, when applying LCA to region-based studies, is how best to consider and reflect the regional characteristics, as they need to be as close to reality as possible. Several Life Cycle Inventory (LCI) analysis and Life Cycle Impact Assessment (LCIA) studies have been undertaken to study site-specific considerations. However, due to practicalities, very few attempts have been made at identifying the regions affected by regional activities and consider their regional characteristics. Therefore, the purpose of this study is to suggest the direction of a forthcoming study by showing the necessity of regional characteristic consideration in regional evaluation, and to suggest a synthetic, region-based LCA method which can reflect the differences of regional characteristics for direct and indirect effects of regional activities. In this study, the Life Cycle Region-specific Assessment Method (LCRAM) was proposed as a new site-specific LCA method. As an example, we used LCRAM to observe the effects of 4 environmental burdens (CO2, NOx, SOx, and SPM) to human health (DALY) in 47 regions (prefectures in Japan). LCRAM consists of a regional database and an analysis method (EIOM). In order to reflect the regional characteristics, including structural (regional production and consumption, interregional trade, and the structure of energy consumption) and environmental features (geographical location, climate, natural conditions, and population density), we first constructed a regional database. This includes an Interregional Trade Matrix (ITM), Regional Environmental Burden Coefficients (REBC), and Regional Damage Factors (RDF). Second, for considering the regional characteristics by using the regional database to the each region, it is a necessary to identify the environmental burden emitting regions (Emitting Regions) of indirect effects due to regional activity. To do this, we developed the Expanded Interregional Input Output Method (EIOM) to take the place of the Multi-Regional Input Output method (Multi-Regional IO) by applying the Two-Regional IO method and the ITM. This is because it is difficult to apply Multi-Regional IO to many regions and industries owing to practical constraints. Upon comparison between the regional database, it was found to show considerable differences due to regional characteristics. It is possible to identify how much the difference of REBC influences the evaluation results by calculating the Deviation Effect Index with REBC and, thus, it was found that the effects from the iron and steel, and electric power industries were more than three times that of other industries. Also the size of RDF varies according to the property of the Environmental Burden (EB) and region; and the more site-specific EB, such as SPM in this study shows, the more distinct the difference. Therefore, it seems reasonable to recommend that the proper regional database is applied to the Emitting Regions. Meanwhile, a comparison with a 9-region IO table (a Multi-Regional IO table made by the Ministry of Economy, Trade and Industry in Japan) was performed to verify the reliability of EIOM. The results indicated a high consistency of over 95%, which verifies that EIOM can be used instead of a Multi-Regional IO method. Finally, as a comparison between LCRAM and Region-Generic Method (RGM) for nine activity regions, we confirmed that the results produced by RGM may be an underestimation or overestimation; as an example, the largest difference among the regions for DALY reached 48% of the RGM result. In this study, it was clearly shown that the evaluation results will be different depending on the structure and environmental features of each region. It is necessary to reflect the proper regional characteristics to evaluate the actual regional activity. LCRAM is an efficient method to consider the regional characteristics for direct and indirect effects to regions, through all stages of the activities. Also, it is possible to apply a regional evaluation for more regions and more detail in the industry classification. Furthermore, it discusses the interdependence and transportation effects due to interaction between the regions. Thus, it may enable us to make an appropriate decision in region-based evaluations such as nourishment and inducement of industry, infrastructure, recycle system, etc. Finally, it is also expected that further discussion and continuous examination will contribute to enabling us to frame an actual and efficient policy based on the regional structural features and environmental features for a sustainable community.

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