Abstract:The purpose of this study was to develop a low impact development-based district unit planning (LID-DP) model and to verify the model by applying it to a test site. To develop the model, we identified various barriers to the urban planning process and examined the advantages of various LID-related techniques to determine where in the urban development process LID would provide the greatest benefit. The resulting model provides (1) a set of district unit planning processes that consider LID standards and (2) a set of evaluation methods that measure the benefits of the LID-DP model over standard urban development practices. The developed LID-DP process is composed of status analysis, comprehensive analysis, basic plan, and sectoral plans. To determine whether the LID-DP model met the proposed LID targets, we applied the model to a test site in Cheongju City, Chungcheongbuk-do Province, Republic of Korea. The test simulation showed that the LID-DP plan reduced nonpoint source pollutants (total nitrogen, 113%; total phosphorous, 193%; and biological oxygen demand, 199%); reduced rainfall runoff (infiltration volume, 102%; surface runoff, 101%); and improved the conservation rate of the natural environment area (132%). The successful application of this model also lent support for the greater importance of non-structural techniques over structural techniques in urban planning when taking ecological factors into account.Keywords: low impact development; urban planning; district unit planning; LID-based district unit planning model; land-use planning

In terms of urban planning, the impact of urbanization and high density on the environment is a major issue. This study intended to analyze the effect of spatial density characteristics of urban air pollution sources on urban air pollution concentration using a panel model. As the total population density, the number of cars registered per capita, and the total emission facility density increased, together with a closer distance to a thermal power plant, the nitrogen dioxide(NO2) concentration increased. Net population density was also found to have the greatest impact on the structure and density of emission sources of ozone(O3) followed by the number of cars registered per person and the total emission facility density. It was confirmed that particular matter(PM10) concentrations are strongly influenced in positive directions by the spatial density characteristics of emission sources that show significant differences between regions.

The goal of this study is to analyze the interrelated direct and indirect impacts of urban development intensity (UDI) characteristics on carbon dioxide (CO 2 ) emissions in Korea. The study also compares the main arguments and analysis results of previous studies on cities that are effective in reducing CO 2 emissions. To do this, factors attributable to the UDI characteristics of Korea were selected, and CO 2 emissions were calculated. Then, the impact of UDI characteristics on CO 2 emissions was analyzed using the partial least squares structural equation model. The main results show that the physical, spatial, and socio-demographic characteristics of UDI have a direct impact on CO 2 emissions, and physical, economic, and city-type characteristics indirectly affect CO 2 emissions. As a result, we reach the following conclusions: (i) dense urban forms reduce CO 2 emissions; (ii) economic characteristics of UDI have impact on total CO 2 emissions, having both negative and positive effects; and (iii) medium and small cities have higher per capita CO 2 emissions than do large cities. communication infrastructure on CO 2 emissions. Land use patterns and density elements represent spatial characteristics, and transportation and communication infrastructure facilities exhibit physical characteristics. Similarly, Guerin et al. [8] found that factors such as age, gender, and education level, which indicate social and economic characteristics, such as income and house ownership, affect energy consumption. Brownstone and Golob [9] found that spatial characteristics, such as residential density, affect vehicle mileage and fuel consumption. Tate et al. [10] and Mendes [11] developed the UDI index based on physical characteristics, such as land coverage and infrastructure, and socio-demographic characteristics, such as census block group.However, as pointed out by Wang et al [7], virtually no studies comprehensively address the UDI characteristics relevant to urban planning. For example, Newman and Kenworthy [6] argued that physical factors, such as transportation-related automobiles and transportation facilities, accelerate CO 2 , but their research fails to include economic factors, such as price or income changes. Similarly, Talbi [12] studied the relationship between CO 2 and economic aspects, such as GDP, fuel consumption, fuel ratio, and energy efficiency, and found that the latter two are important for CO 2 emissions. However, this author did not consider the fact that energy consumption patterns or CO 2 emissions may vary due to other factors, such as age or city type. Schipper et al. [13] and Guerin, Yust and Coopet [8] considered socio-demographic and economic characteristics but limited their study of energy consumption to the residential sector. Similarly, Fragkias et al. [14] examined the relationship between city size and CO 2 emissions based on population, but they did not sufficiently address other characteristics influencing this relationship.Though previous studies do not comprehensively address UDI charac...

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This study intended to develop an integrated governance model and find measures to manage nonpoint source (NPS) pollutions in watershed management. To reach this goal, this study has analyzed NPS pollution management policies in Korea and has employed statistical methods such as expert Delphi survey, analysis of variance, and factor analysis. As a result, this study has found that the favored basic organization form was a private-public cooperative council. The necessary governance-based NPS pollution management measures determined through this study are as follows: to build collaboration mechanisms including those related to motivation provision, trust building, capacity building, and making optimal regulations; to employ financial resources based on principles such as 'polluter-pays', 'recipient-pays', and 'general-tax-source'; and to develop several programs, including system improvement, pilot and management projects, and publicity.