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您的检索式：作者名="HOU Fangxin"
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| 1 | Exploring the driving factors and their mitigation potential in global energy-related CO2 emission显示文摘In order to quantify the contribution of the mitigation strategies,an extended Kaya identity has been proposed in this paper for decomposing the various factors that influence the CO2 emission.To this end,we provided a detailed decomposition of the carbon intensity and energy intensity,which enables the quantification of clean energy development and electrification.The logarithmic mean divisia index(LMDI)has been applied to the historical data to quantify the contributions of the various factors affecting the CO2 emissions.Further,the global energy interconnection(GEI)scenario has been introduced for providing a systematic solution to meet the 2℃goal of the Paris Agreement.By combining LMDI with the scenario analysis,the mitigation potential of the various factors for CO2 emission has been analyzed.Results from the historical data indicate that economic development and population growth contribute the most to the increase in CO2 emissions,whereas improvement in the power generation efficiency predominantly helps in emission reduction.A numerical analysis,performed for obtaining the projected future carbon emissions,suggests that clean energy development and electrification are the top two factors that can decrease CO2 emissions,thus showing their great potential for mitigation in the future.Moreover,the carbon capture and storage technology serves as an important supplementary mitigation method. | Zhiyuan Ma Shining Zhang Fangxin Hou Xin Tan Fengying Zhang Fang Yang Fei Guo | 2020 | Global Energy Interconnection2020，3，5： | 9 |
| 2 | Energy Demand Prediction of the Building Sector Based on Induced Kernel Method and MESSAGEix Model显示文摘The building sector,including resident,commercial and public services,is one of the most energy-intensive sectors nowadays.The share of buildings’energy consumption in the final energy dramatically increases in various scenarios.As the preliminary work of the final energy prediction,the prediction of useful energy demand of the building sector is essential in the fields of energy-related research,especially for the scenarios design.To this end,this paper presents the prediction of energy demand in the building sector based on the Induced Kernel Method(IKM)for the useful energy.First,similar to other learning-based prediction methods,a database is constructed for the training.Specifically,the database contains not only the historical data of the useful energy demand and related indicators,but also some development templates to induce the prediction.Second,the detailed process is mathematically deduced to predict the useful energy demand components of the building sector,including electricity and heating.Finally,using various countries as examples,prediction results of the useful energy are presented in the numerical analysis.Furthermore,by using useful energy prediction results as the input of the MESSAGEix model,the paper further predicts global final energy of the building sector. | TAN Xin ZHAO Zijian LIU Changyi ZHANG Shining CHEN Xing HOU Fangxin YANG Fang GUO Fei | 2019 | Chinese Journal of Urban and Environmental Studies2019，7，4： | 1 |
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