Industrial Structure Optimization and Low-Carbon Transformation of Chinese Industry Based on the Forcing Mechanism of CO2 Emission Peak Target
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Abstract:
The setting of a CO2 emission peak target (CEPT) will have a profound impact on Chinese industry. An objective assessment of this impact is of great significance, both for understanding/applying the forcing mechanism of CEPT, and for promoting the optimization of China’s industrial structure and the low-carbon transformation of Chinese industry at a lower cost. Based on analysis of the internal logic and operation of the forcing mechanism of CEPT, we employed the STIRPAT model. This enabled us to predict the peak path of China’s CO2 emissions, select the path values that would achieve the CEPT with the year 2030 as the constraint condition, construct a multi-objective and multi-constraint input/output optimization model, employ the genetic algorithm to solve the model, and explore the industrial structure optimization and low-carbon transformation of Chinese industry. The results showed that the setting of CEPT will have a significant suppression effect on high-carbon emission industries and a strong boosting effect on low-carbon emission industries. The intensity of the effect is positively correlated with the target intensity of the CO2 emissions peak. Under the effect of the forcing mechanism of CEPT, Chinese industry can realize a low-carbon transition and the industrial structure can realize optimization. The CEPT is in line with sustainable development goals, but the setting of CEPT may risk causing excessive shrinkage of basic industries—which should be prevented.Keywords:
Forcing (mathematics)
Emission intensity
Carbon fibers
In response to concerns put forward by the US government, decreases of greenhouse gas emissions could be used as a basis for emission reduction commitments. This paper identifies the dominant factors influencing decreases in greenhouse gas emissions. Quantitative analyses of historical trends were used to identify the relationships between decreases rate of greenhouse gas emissions and the GDP growth rate, between carbon emission elasticity and the GDP, and between the energy consumption intensity and the carbon content of the energy supply. Analysis of the effect of the carbon content on the economic development of different countries with different economic structures shows that the carbon emission intensity can reflect their contribution to climate change for developing countries, but for developed countries, a single index reflecting the carbon emissions is not enough and other factors must be considered to determine whether the carbon emission intensity reduction is faster than the GDP growth.
Emission intensity
Carbon fibers
Intensity
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As for the research of reduction of Chinese agricultural greenhouse gas emissions,carbon trading which belong to Tokyo Protocol is introduced as a method to governance GHG.Agricultural greenhouse gas emissions will be integrated into the international emissions trading market,providing a way to reduce emissions of GHG,In order to theoretically explore the feasibility of this study,fist,established theoretical model of international emissions,the absolute and Intensity control was defined to analyze the role of countries played in international emissions market.As a result,intensive control is more likely to become suppliers in international emissions market,however,The result depends on the relative value between degree of the intensity emission and intensity control,If the level of intensity control emission is lower than the level of intensity emission of this country,the country will become suppliers in international emissions market.In order to verify conclusions,GTAP-E model with the data of Chinese greenhouse gas emission is used to evaluate the potential of Chinese agriculture green house emission in participating carbon trade in international market,finally the theoretical conclusions is validated.
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Industrial sector is one of the highest energy consumption and greenhouse gas (GHG) emission in Thailand. There are around 6,000 designated factories which consume large amount of energy and emit vast GHG volume each year. In this study, we investigate and validate the energy consumption and efficiency data from Thailand's designated factory database and converted into GHG value. With the assumption of the top 80% of GHG emission threshold to be considered, it can be concluded that there are only up to 7% of number of designated factories but emitted at around 80% of total emission from designated factory of the country. In the context of GHG emission reduction potential estimation, the carbon intensity difference concept have been applied to the factories over the threshold. The results show that when compare with Best carbon intensity scenario, Thailand will reduce around 29 MtCO 2 or 31% of the GHG emission emitted in 2018 in industrial sector, while the figure would be 15 MtCO2 reduction potential or 16% for the Average Carbon Intensity scenario.
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Intensity
Carbon fibers
Factory (object-oriented programming)
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Every year since 1990, the Australian Federal Government has estimated national greenhouse-gas (GHG) emissions to meet Australia’s reporting commitments under the United National Framework Convention on Climate Change (UNFCCC). The National Greenhouse Gas Inventory (NGGI) methodology used to estimate Australia’s GHG emissions has altered over time, as new research data have been used to improve the inventory emission factors and algorithms, with the latest change occurring in 2015 for the 2013 reporting year. As measuring the GHG emissions on farm is expensive and time-consuming, the dairy industry is reliant on estimating emissions using tools such as the Australian Dairy Carbon Calculator (ADCC). The present study compared the emission profiles of 41 Australian dairy farms with ADCC using the old (pre-2015) and new (post-2015) NGGI methodologies to examine the impact of the changes on the emission intensity across a range of dairy-farm systems. The estimated mean (±s.d.) GHG emission intensity increased by 3.0%, to 1.07 (±0.02) kg of carbon dioxide equivalents per kilogram of fat-and-protein-corrected milk (kg CO2e/kg FPCM). When comparing the emission intensity between the old and new NGGI methodologies at a regional level, the change in emission intensity varied between a 4.6% decrease and 10.4% increase, depending on the region. When comparing the source of emissions between old and new NGGI methodologies across the whole dataset, methane emissions from enteric fermentation and waste management both increased, while nitrous oxide emissions from waste management and nitrogen fertiliser management, CO2 emissions from energy consumption and pre-farm gate (supplementary feed and fertilisers) emissions all declined. Enteric methane remains a high source of emissions and so will remain a focus for mitigation research. However, these changes to the NGGI methodology have highlighted a new ‘hotspot’ in methane from manure management. Researchers and farm managers will have greater need to identify and implement practices on-farm to reduce methane losses to the environment.
Emission intensity
Carbon dioxide equivalent
Tonne
Emission inventory
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<p>Sheep production in Canada is a small industry in comparison to other livestock systems. Because of the potential for expansion of the sheep industry in Canada, the GHG emissions budget of this industry was assessed in this paper. The GHG emissions from Canadian lamb production were compared with those from the Canadian beef industry using the ULICEES model. The GHG emission intensity of the Canadian lamb industry was 21% higher than lamb production in France and Wales, and 27% higher than northern England. Enteric methane accounts for more than half of the GHG emissions from sheep in Canada. The protein based GHG emission intensity is 60% to 90% higher for sheep than for beef cattle in Canada. The GHG emission intensity for sheep in Eastern Canada is higher than for sheep in Western Canada. Protein based GHG emission intensity is more sensitive to the difference between sheep and beef than LW based emission intensity. This paper demonstrated that protein based GHG emission intensity is a more meaningful indicator for comparing different livestock species than live weight (LW) based GHG emission intensity.</p>
Emission intensity
Beef Cattle
Intensity
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Forcing (mathematics)
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Emission intensity
Energy supply
Emission inventory
Embodied Energy
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Often, solution values are forced by implication of some of the constraints. A forcing substructure is a portion of the linear program that forces some of the variables to have only one value in every feasible solution. In some cases, finding a forcing substructure reveals an error, and in other cases, it leads to a reduction of the linear program. Discovering and explaining forcing substructures are aspects of good model management. Besides its role when debugging a model, understanding forcing substructures deepens our understanding of the solution by revealing some activity levels that are determined by implications of the constraints, not by economic preference.
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Substructure
Value (mathematics)
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The reduction of greenhouse gas emission currently becomes more urgent task for Korean Industries, especially for the paper industries because of the new regulation based on the low carbon-green growth law. In order to reduce effectively the greenhouse gas emission, the development of greenhouse gas emission inventory has been widely considered as one of the basic processes and has been applied to many industries. In this study, the fundamental schemes and the cases of greenhouse gas inventories were investigated. Especially, the major considering units for paper industries were suggested to develope greenhouse emission inventory of paper industry.
Emission inventory
Fugitive emissions
Greenhouse effect
Carbon fibers
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