農業では食料や資材などの人間の福利を支えるバイオマス生産が可能な反面，栽培管理に伴う多大な温室効果ガス(GHG: Green House Gas)の排出があり，生態系サービス利用と気候システム問題の間にトレードオフ構造が生じている．そこで，本研究ではそのトレードオフ構造が顕著である施設園芸を対象として，バイオマス生産とGHG排出削減の相乗便益モデルの開発を目的として，鑑賞用キク生産プラントを事例として温度および肥培管理の変更に伴うバイオマス生産とGHG排出の応答を分析し，栽培管理の最適化のモデルケースの導出を行った．分析では，DNDC (DeNitrification-DeComposition)モデルによる農地からのバイオマス生産量とGHG発生量の解析，温室暖房燃料消費試算ツールによる温度管理による暖房燃料消費量の解析，LCAツールであるMiLCAによる投入肥料製造に伴うGHG排出量の解析を統合して，様々な栽培管理ケースに対する炭素窒素収支の挙動を評価した．結果，対象プラントにおいて栽培管理の最適化により，現状から95%以上のバイオマス生産量を確保しつつ，GHG排出量を34.6%削減することが可能であるという結論を得た．今回構築した栽培管理の最適化のモデルケースは他の施設園芸においても有効に適用できると考えられる．
1,4-Dioxane migrates in groundwater with low sorption, low degradation, and low volatilization according to its physicochemical properties. 1,4-Dioxane migration therefore strongly depends on groundwater flow. Hydraulic conductivities, the most uncertain parameters and critical to groundwater flow, should be precisely determined. In a conventional approach, groundwater flow is estimated by calibration to optimize hydraulic conductivities, and then the calibrated groundwater flow is used for predicting 1,4-dioxane distribution considering other parameters such as source location and concentration. Although other parameters are properly set, 1,4-dioxane distribution cannot be always precisely predicted because the calibrated groundwater flow model does not perfectly present the real groundwater flow. Thus, the calibrated groundwater flow should be reevaluated to define the most suitable hydraulic conductivities considering 1,4-dioxane distribution. This study proposes a new approach with verification process of groundwater flow estimation for precisely predicting 1,4-dioxane distribution in groundwater. In this approach, several acceptable sets of hydraulic conductivities in term of groundwater heads are estimated by calibration and each groundwater flow is verified to match between calculated and observed 1,4-dioxane concentrations. The effectiveness of our new approach comparing to the conventional one was proved by a case study at an illegal dumping site in Japan where three aquifers have been contaminated by 1,4-dioxane for about 15 years. Eight acceptable sets of hydraulic conductivities of the three aquifers were determined by calibration using observed groundwater heads, and then verified to minimize the errors in 1,4-dioxane concentration. As a result, 1,4-dioxane distribution was predicted by our approach more precisely than the conventional approach.
Water pipeline is the most important infrastructure in our daily life. However, pipeline deterioration is now causing problems for water supply service in Korea. Aged water pipelines need to be efficiently replaced to prevent problems. The present study aims to introduce efficient, gradual pipeline replacement plans, particularly analyzing risks through predicting the number of pipeline damages, the restoration time and water shortage volume. The results were put together and the overall risk ranking was estimated using predicted risk index (PRI). As a result, the highest PRI was given the highest priority for replacement. From these analyses, pipelines were assessed and given a risk ranking. In order to confirm replacement effects utilizing the PRI order, the Monte Carlo simulation was applied to three case studies with changed replacement order. Due to the random occurrence of pipeline accidents in terms of space and time, the Monte Carlo simulation can yield approximate solutions. The results of the Monte Carlo simulations in each case allowed us to confirm the effects of replacement in order of PRI, and can contribute to the decision-making concerning pipeline replacement plans for distribution networks.
This paper focuses on carbon footprints of steel production in China. Following the enforcement of the Kyoto Protocol in 2005, China has promoted energy efficient technological renovation in existing industrial zones as well as by the construction of new environmentally-friendly industrial zones. On the contrary, geographical fragmentation of production in China and East Asia has deepened the interdependency on regional transactions of goods and services that are part of spreading global value chains or vertical specialization. Based on the above background, we attempt to evaluate the multi-regional carbon footprint of steel-related low-carbon technological renovation by using input-output analysis. First, we created a dataset for input coefficient changes in an I-O table, corresponding to the low-carbon technologies that are implemented in the “global sectorial approach” to the steel industry. Second, we set up scenarios to implement a set of low-carbon technologies in the steel sector. Finally, we evaluated backward and forward linkage effects of low-carbon technology transfers in terms of their carbon footprints. As a result of the analysis, it was revealed that: 1) implementation of low-carbon technologies would provide a significant contribution to carbon footprint reduction in steel production; 2) the structures of carbon footprint reduction are different among regions due to variations of multi-regional steel production and consumption linkages; 3) the interdependencies among the different carbon footprints in each region can be used as basic information regarding regional collaboration to reduce carbon dioxide emissions in the spreading global value chain.