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Current research on greenhouse gas(GHG) inventories supports the view that waste disposal is an important source of urban GHG emissions. Studying the driving factors behind the changes in greenhouse gas emissions from municipal waste treatment can provide better information support for emission reduction. This paper systematically evaluates the city-scale GHG emission determinants in waste disposal process using a system dynamics model. Subsequently, an empirical analysis was conducted on Baoding City. This research brings some interesting results: (1) The impact of the population is paramount. The emission reduction effect of controlling the size of the city and improving the quality of the population is remarkable. (2) Policy is another key factor. Comprehensive and appropriate policies are more effective than introducing and applying advanced technologies. Including urban land management, waste separation and metering and charging can be used for it. (3) It is necessary to formulate appropriate emission reduction policies for different industrial sectors by focusing on GHG generated from solid waste. Because the combined effect of factors is not equal to the simple sum of each factor. Policy implications in terms of our study results are discussed.
Can Lu; Wei Li; Changle An. The GHG emission determinants research for waste disposal process at city-scale in Baoding. Sustainable Cities and Society 2020, 59, 102203 .
AMA StyleCan Lu, Wei Li, Changle An. The GHG emission determinants research for waste disposal process at city-scale in Baoding. Sustainable Cities and Society. 2020; 59 ():102203.
Chicago/Turabian StyleCan Lu; Wei Li; Changle An. 2020. "The GHG emission determinants research for waste disposal process at city-scale in Baoding." Sustainable Cities and Society 59, no. : 102203.
Unprecedented huge mitigation task should be associated with profound efforts in facilitating emission reduction process over the globe. As the largest CO2 emitting country, China has been strenuously promoting the mitigation resilient development pathways in conjunction with the 2030 carbon emission peak commitment from Nationally Determined Contribution document which submitted under the Paris Agreement. Based on the peaking objective, carbon emission in heavy chemical industry should be received most attentions in terms of its large proportion with respect to the emission sources from other sectors. Particle swarm optimization (PSO) algorithm optimized back propagation neural network (BP) model is employed to predict future carbon emission for heavy chemical industry with the timeframe of 2017–2035 on the basis of the previous data. The significant magnitude of each carbon emission driving force is acquired in terms of the absolute influence coefficient method. The results indicated that, carbon emission in heavy chemical industry and its corresponding sub-sectors could be achieved peak under the implementation of the predetermined mitigation scenarios. The proportion of carbon emission in energy processing industry, steel industry, and building material industry is accounted for a larger fraction over the cumulative carbon emission in heavy chemical industry during the simulation period upon 2035.
Can Lu; Wei Li; Shubin Gao. Driving determinants and prospective prediction simulations on carbon emissions peak for China’s heavy chemical industry. Journal of Cleaner Production 2019, 251, 119642 .
AMA StyleCan Lu, Wei Li, Shubin Gao. Driving determinants and prospective prediction simulations on carbon emissions peak for China’s heavy chemical industry. Journal of Cleaner Production. 2019; 251 ():119642.
Chicago/Turabian StyleCan Lu; Wei Li; Shubin Gao. 2019. "Driving determinants and prospective prediction simulations on carbon emissions peak for China’s heavy chemical industry." Journal of Cleaner Production 251, no. : 119642.
Global climate change is a significant environmental problem. A major trigger of climate change is the excess carbon emissions. Based on 44 scenarios in the second generation of new dry cement technology systems, this paper establishes IPSO-BP model to forecast the carbon emissions peak of China‘s cement industry for 2016 to 2050 years. The results indicate that China’s cement industry only implements capacity reduction plans and the second generation of new dry cement technology systems, so that carbon emissions can reach the peak before 2030. It is up to 19 years ahead of the carbon emissions peak of the basic scenario and the carbon emissions peak is reduced by 38 Mt. Moreover, this paper analyzes the technical combination of the earliest carbon emissions and the lowest carbon emissions. As for the earliest carbon emissions technical combination, China's cement industry carbon emissions will peak at 789.95Mt in 2021.According to the lowest carbon emissions technical combination, China's cement industry carbon emissions will peak at 742.37Mt in 2025. Accordingly, the conclusions will be helpful for making carbon emissions reduction policies for China's cement industry.
Wei Li; Shubin Gao. Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry. Energy 2018, 165, 33 -54.
AMA StyleWei Li, Shubin Gao. Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry. Energy. 2018; 165 ():33-54.
Chicago/Turabian StyleWei Li; Shubin Gao. 2018. "Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry." Energy 165, no. : 33-54.
Cities represent a critical source and primary unit of Greenhouse Gas (GHG) emissions. The accurate emission accounts of cities provide robust and solid data support for further emission analysis as well as the local low-carbon policy making. Restricted by the data and method lacking, there is a relative lag in city-level emission accounts. Thus, this study attempts to build an investigation-based GHG emission inventory framework for cities. We include CO2, CH4, N2O, and SF6 emissions from five sources: energy activity, industrial processes/product use, agriculture, land use change/forestry, and waste disposal. This study then uses Baoding as a case study to analyse its emission characteristics. Baoding is a low-carbon pilot city in China, which is a core and crucial city in Jing-Jin-Ji area. It is also the origin of the recently established Xiongan New Area, which has great strategic development significance. The results show that energy activity is the highest emission source followed by waste disposal processes in Baoding. Emissions induced by electricity input that brought from other provinces or cities account for another considerable emission proportion as well. Moreover, agricultural activity, which is a pillar industry in Baoding, contributes the most to methane emissions. Several emissions reduction policy recommendations are provided.
Can Lu; Wei Li. A comprehensive city-level GHGs inventory accounting quantitative estimation with an empirical case of Baoding. Science of The Total Environment 2018, 651, 601 -613.
AMA StyleCan Lu, Wei Li. A comprehensive city-level GHGs inventory accounting quantitative estimation with an empirical case of Baoding. Science of The Total Environment. 2018; 651 ():601-613.
Chicago/Turabian StyleCan Lu; Wei Li. 2018. "A comprehensive city-level GHGs inventory accounting quantitative estimation with an empirical case of Baoding." Science of The Total Environment 651, no. : 601-613.
China, as the world’s largest emitter, intends to achieve the peaking of carbon dioxide (CO2) emissions around 2030 and to make best efforts to peak early to mitigate global change. Under this strategy, a dynamic, recursive computable general equilibrium (CGE) model is used to analyze the economy, energy, and environment impact of CO2 emission reduction policy based on 17 scenarios in China: carbon tax, emission trading scheme (ETS), and the mixed policy in different price level, in order to find out which kind of emission reduction strategy is more feasible. The results show that CO2 emission in 2030 will be reduced with the implementation of tax, ETS and mixed policy, by 10–13 %, 12–14 %, and 18–28 %, respectively. From 2016 to 2030, China can reduce 18,338–24,156 Mt CO2 through the implementation of mixed policy. Furthermore, relative to single policy, mixed policy has stronger effects on primary energy consumption cut, by 738–1124 Mtoe or 18–28 %, which will make CO2 emissions reach a peak before 2030 and the peak emission is not greater than 12 billion tons which is in line with the reduction demand in China. Thus, the mixed policy is the most effective strategy so that mixed policy is recommended to parties included in Annex I in United Nations Framework Convention on Climate Change Kyoto Protocol and other countries with large potential of emission reduction, while ETS is suggested to countries with low carbon emissions per capita which can balance economic development and CO2 mitigation.
Wei Li; Zhijie Jia. Carbon tax, emission trading, or the mixed policy: which is the most effective strategy for climate change mitigation in China? Mitigation and Adaptation Strategies for Global Change 2016, 22, 973 -992.
AMA StyleWei Li, Zhijie Jia. Carbon tax, emission trading, or the mixed policy: which is the most effective strategy for climate change mitigation in China? Mitigation and Adaptation Strategies for Global Change. 2016; 22 (6):973-992.
Chicago/Turabian StyleWei Li; Zhijie Jia. 2016. "Carbon tax, emission trading, or the mixed policy: which is the most effective strategy for climate change mitigation in China?" Mitigation and Adaptation Strategies for Global Change 22, no. 6: 973-992.
In order to explore the decoupling relationship and its influence factors between economic growth and carbon emissions in China, the decoupling elasticity decomposition quantitative model of carbon emissions based on extended Log-Mean Divisia Index and Tapio decoupling models is established in this paper. The carbon emissions induced by household (HOU) sector ranked fifth among the nine sectors; hence, we analyzed the HOU sector with the production (PRO) sector together. The results show that, first, the carbon emissions increased from 3.95 billion tons in 1996 to 10.49 billion tons in 2012, and the contributions of manufacturing sector and electric power, gas and water production and supply sector to carbon emissions account for approximately 81 %. Second, the economic output effect is the main contributor, and the energy intensity effect is the major inhibitor factor to the carbon emissions in both the PRO sector and HOU sector, respectively. Third, the decoupling state of the PRO sector mainly stayed at weak decoupling, while the decoupling state of HOU sector mainly stayed at strong decoupling. Fourth, the impact factors of the carbon emissions and the decoupling elasticity values are in complete agreement. At the end of this paper, we present some policy recommendations for China’s government to realize the decoupling between CO2 emissions and economic growth in the near future.
Wei Li; Shuang Sun; Hao Li. Decomposing the decoupling relationship between energy-related CO2 emissions and economic growth in China. Natural Hazards 2015, 79, 977 -997.
AMA StyleWei Li, Shuang Sun, Hao Li. Decomposing the decoupling relationship between energy-related CO2 emissions and economic growth in China. Natural Hazards. 2015; 79 (2):977-997.
Chicago/Turabian StyleWei Li; Shuang Sun; Hao Li. 2015. "Decomposing the decoupling relationship between energy-related CO2 emissions and economic growth in China." Natural Hazards 79, no. 2: 977-997.
China’s emissions continue to rise rapidly in line with its mounting energy consumption, which puts considerable pressure on China to meet its emission reduction commitments. This paper assesses the impacts of CO2 mitigation measures in China during the period from 2010 to 2050 by using a computable general equilibrium method, called AIM/CGE. Results show that renewable energy makes a critical difference in abating emissions during the period from 2010 to 2020. The scenarios with emission trading would drive more emission reductions, whereby the emission-cutting commitment for 2020 would be achieved and emission reductions in 2050 would be more than 57.90%. Meanwhile, the share of non-fossil energy increases significantly and would be more than doubled in 2050 compared with the BAU scenario. A carbon tax would result in a significant decline in emissions in the short term, but would have an adverse effect on economic growth and energy structure improvements. It is also observed that the integrated measures would not only substantially decrease the total emissions, but also improve the energy structure.
Wei Li; Hao Li; Shuang Sun. China’s Low-Carbon Scenario Analysis of CO2 Mitigation Measures towards 2050 Using a Hybrid AIM/CGE Model. Energies 2015, 8, 3529 -3555.
AMA StyleWei Li, Hao Li, Shuang Sun. China’s Low-Carbon Scenario Analysis of CO2 Mitigation Measures towards 2050 Using a Hybrid AIM/CGE Model. Energies. 2015; 8 (5):3529-3555.
Chicago/Turabian StyleWei Li; Hao Li; Shuang Sun. 2015. "China’s Low-Carbon Scenario Analysis of CO2 Mitigation Measures towards 2050 Using a Hybrid AIM/CGE Model." Energies 8, no. 5: 3529-3555.