The Experts below are selected from a list of 33177 Experts worldwide ranked by ideXlab platform
Lirong Liu - One of the best experts on this subject based on the ideXlab platform.
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dynamic input output analysis for Energy metabolism system in the province of guangdong china
Journal of Cleaner Production, 2018Co-Authors: Mengyu Zhai, G H Huang, Lirong LiuAbstract:Abstract The development of human society is inseparable from Energy. The exploration of Urban Energy metabolism plays an essential role in improving sustainable development. Combing input-output analysis with ecological network analysis help academics to shed light into the complicated system interactions and interior Energy flows. In this study, using Guangdong as a case study, the Energy Ecological Network model is developed to account for the intensity of the embodied Energy Consumption using monetary input-output tables from 2000, 2002, 2005, 2007, 2010, and 2012. Sectors and Energy flows are treated as nodes and paths to compile the corresponding physical input-output tables, which can facilitate a more comprehensive and balanced understanding of Urban Energy Consumption by integrating various accounting perspectives. In detail, network control analysis is extended to reveal inter relationships and relative contribution rate of each sector. Network utility analysis gives an overall consideration of the dynamic changes in Energy metabolism relations from multiple perspective. Furthermore, the modified robustness method penetrates into how each sector affects the stability of the system. The results show that the Energy metabolic level in Guangdong is relatively low and indirect flows are the key to improving the system efficiency. The advanced manufacturing (AM) sector relied on other sectors in Energy trade and have limited reciprocal relationships in the study period. Therefore, it is urgent to adjust the external structure and internal circulation of AM sector. The comprehensive dynamic analysis will give a scientific support to guide the development of Energy reform in an attempt to promoting healthier development of Energy metabolism system.
Et Al. Feng - One of the best experts on this subject based on the ideXlab platform.
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System Dynamics Modeling for Urban Energy Consumption and CO2 Emissions : A Case Study of Beijing, China
Ecological Modelling, 2013Co-Authors: Et Al. FengAbstract:It is clear that city must be part of the solution if an Urbanizing world is to grapple successfully with ecological challenges such as Energy depletion and climate change. A system dynamics model was devel- oped in this study using STELLA platform to model the Energy Consumption and CO2 emission trends for the City of Beijing over 2005–2030. Results show that the total Energy demand in Beijing is predicted to reach 114.30 million tonnes coal equivalent (Mtce) by 2030, while that value in 2005 is 55.99 Mtce, which is 1.04 times higher than the level in 2005. Accordingly, the total CO2 emissions in 2030 will reach 169.67 million tonnes CO2 equivalent (Mt CO2-eq), 0.43 times higher than that of 2005. The change of Energy structure from carbon rich fuel as coal to low-carbon fuel as natural gas will play a very essential role in carbon emission reduction activities of Beijing. The modeling results also shows that the service sector will gradually replace the industrial dominant status in Energy Consumption as the largest Energy consuming sector, followed by industrial and transport sector. The sensitive analysis suggests that change of economic development mode and control of rational population growth will have a far-reaching influ- ence on Energy Consumption and on carbon emissions. All these results will provide essential information for Beijing’s future Energy and carbon emission profiles. ©
Yan Zhang - One of the best experts on this subject based on the ideXlab platform.
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analysis of Urban Energy Consumption in carbon metabolic processes and its structural attributes a case study for beijing
Journal of Cleaner Production, 2015Co-Authors: Yan Zhang, Hongmei Zheng, Zhifeng Yang, Xinan Yin, Gengyuan LiuAbstract:Abstract Based on Urban metabolism theory, Urban Energy Consumption and carbon emission can be analyzed and the Urban Energy structure and carbon metabolic processes can be specified. By combining input–output analysis with ecological network analysis, the embodied Energy and carbon footprint implied in Urban products and services can be quantified. On this basis, we introduced Energy structure indices based on the embodied Energy per unit carbon emitted (i.e., the emission efficiency), which we used to evaluate the Energy structure attributes of the metabolic actors. This approach provides a scientific basis for Energy conservation and carbon emission reduction. Beijing is trying to control pollution (especially the smog produced by coal combustion), and this task is complicated by its large metabolic fluxes and strong metabolic influence. In this study, we analyzed the Energy Consumption structure of 28 sectors in Beijing from the perspective of their carbon footprint, and divided the sectors into four categories based on the relationship between their embodied Energy Consumption and the emission efficiency. We found that most sectors had high Energy Consumption and low emission efficiency, and that from 2000 to 2010, Beijing's overall Consumption structure alternated between high and low embodied Energy per unit of carbon emission, but the overall trend of emission efficiency changed toward higher. The insights provided by our analysis reveal ways to reduce carbon emission. Based on the carbon footprints of the 28 sectors, we propose how managers could adjust its Energy Consumption structure to decrease Energy Consumption and carbon emission.
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Urban Energy Consumption and co2 emissions in beijing current and future
Energy Efficiency, 2015Co-Authors: Suyan Pan, Baojun Tang, Yan Zhang, Yiming WeiAbstract:This paper calculates the Energy Consumption and CO2 emissions of Beijing over 2005–2011 in light of the Beijing’s Energy balance table and the carbon emission coefficients of IPCC. Furthermore, based on a series of Energy conservation planning program issued in Beijing, the Long-range Energy Alternatives Planning System (LEAP)-BJ model is developed to study the Energy Consumption and CO2 emissions of Beijing’s six end-use sectors and the Energy conversion sector over 2012–2030 under the BAU scenario and POL scenario. Some results are found in this research: (1) During 2005–2011, the Energy Consumption kept increasing, while the total CO2 emissions fluctuated obviously in 2008 and 2011. The Energy structure and the industrial structure have been optimized to a certain extent. (2) If the policies are completely implemented, the POL scenario is projected to save 21.36 and 35.37 % of the total Energy Consumption and CO2 emissions than the BAU scenario during 2012 and 2030. (3) The POL scenario presents a more optimized Energy structure compared with the BAU scenario, with the decrease of coal Consumption and the increase of natural gas Consumption. (4) The commerce and service sector and the Energy conversion sector will become the largest contributor to Energy Consumption and CO2 emissions, respectively. The transport sector and the industrial sector are the two most potential sectors in Energy savings and carbon reduction. In terms of subscenarios, the Energy conservation in transport (TEC) is the most effective one. (5) The macroparameters, such as the GDP growth rate and the industrial structure, have great influence on the Urban Energy Consumption and carbon emissions.
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Urban Energy Consumption and co2 emissions in beijing current and future
Research Papers in Economics, 2014Co-Authors: Suyan Pan, Baojun Tang, Yan Zhang, Yiming WeiAbstract:This paper calculates the Energy Consumption and CO2 emissions of Beijing over 2005-2011 in light of the Beijing's Energy balance table and the carbon emission coefficients of IPCC. Furthermore, based on a series of Energy conservation planning program issued in Beijing, the LEAP-BJ model is developed to study the Energy Consumption and CO2 emissions of Beijing's six end-use sectors and the Energy conversion sector over 2012-2030 under the BAU scenario and POL scenario. Some results are found in this research: (1) during 2005-2011, the Energy Consumption kept increasing, while the total CO2 emissions fluctuated obviously in 2008 and 2011. The Energy structure and the industrial structure have been optimized to a certain extent. (2) If the policies are completely implemented, the POL scenario is projected to save 21.36% and 35.37% of the total Energy Consumption and CO2 emissions than the BAU scenario during 2012 and 2030. (3) The POL scenario presents a more optimized Energy structure compared with the BAU scenario, with the decrease of coal Consumption and the increase of natural gas Consumption. (4) The commerce and service sector and the Energy conversion sector will become the largest contributor to Energy Consumption and CO2 emissions, respectively. The transport sector and the industrial sector are the two most potential sectors in Energy savings and carbon reduction. In terms of sub-scenarios, the TEC is the most effective one. (5) The macro parameters, such as the GDP growth rate and the industrial structure have great influence on the Urban Energy Consumption and carbon emissions.
Gengyuan Liu - One of the best experts on this subject based on the ideXlab platform.
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analysis of Urban Energy Consumption in carbon metabolic processes and its structural attributes a case study for beijing
Journal of Cleaner Production, 2015Co-Authors: Yan Zhang, Hongmei Zheng, Zhifeng Yang, Xinan Yin, Gengyuan LiuAbstract:Abstract Based on Urban metabolism theory, Urban Energy Consumption and carbon emission can be analyzed and the Urban Energy structure and carbon metabolic processes can be specified. By combining input–output analysis with ecological network analysis, the embodied Energy and carbon footprint implied in Urban products and services can be quantified. On this basis, we introduced Energy structure indices based on the embodied Energy per unit carbon emitted (i.e., the emission efficiency), which we used to evaluate the Energy structure attributes of the metabolic actors. This approach provides a scientific basis for Energy conservation and carbon emission reduction. Beijing is trying to control pollution (especially the smog produced by coal combustion), and this task is complicated by its large metabolic fluxes and strong metabolic influence. In this study, we analyzed the Energy Consumption structure of 28 sectors in Beijing from the perspective of their carbon footprint, and divided the sectors into four categories based on the relationship between their embodied Energy Consumption and the emission efficiency. We found that most sectors had high Energy Consumption and low emission efficiency, and that from 2000 to 2010, Beijing's overall Consumption structure alternated between high and low embodied Energy per unit of carbon emission, but the overall trend of emission efficiency changed toward higher. The insights provided by our analysis reveal ways to reduce carbon emission. Based on the carbon footprints of the 28 sectors, we propose how managers could adjust its Energy Consumption structure to decrease Energy Consumption and carbon emission.
Fan Zhang - One of the best experts on this subject based on the ideXlab platform.
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Input-output modeling for Urban Energy Consumption in Beijing: Dynamics and comparison
PLoS ONE, 2014Co-Authors: Lixiao Zhang, Qiuhong Hu, Fan ZhangAbstract:Input-output analysis has been proven to be a powerful instrument for estimating embodied (direct plus indirect) Energy usage through economic sectors. Using 9 economic input-output tables of years 1987, 1990, 1992, 1995, 1997, 2000, 2002, 2005, and 2007, this paper analyzes Energy flows for the entire city of Beijing and its 30 economic sectors, respectively. Results show that the embodied Energy Consumption of Beijing increased from 38.85 million tonnes of coal equivalent (Mtce) to 206.2 Mtce over the past twenty years of rapid Urbanization; the share of indirect Energy Consumption in total Energy Consumption increased from 48% to 76%, suggesting the transition of Beijing from a production-based and manufacturing-dominated economy to a Consumption-based and service-dominated economy. Real estate development has shown to be a major driving factor of the growth in indirect Energy Consumption. The boom and bust of construction activities have been strongly correlated with the increase and decrease of system-side indirect Energy Consumption. Traditional heavy industries remain the most Energy-intensive sectors in the economy. However, the transportation and service sectors have contributed most to the rapid increase in overall Energy Consumption. The analyses in this paper demonstrate that a system-wide approach such as that based on input-output model can be a useful tool for robust Energy policy making.
