Journal articles on the topic 'Industriel emissions'
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1
Wang, Zhaoqiu, Yong Zhang, and Bo Wu. "Exploring Industrial Restructuring Pathways Based on Regional Carbon Productivity Variations: A Case Study of Jiangsu and Zhejiang Regions in China." E3S Web of Conferences 406 (2023): 04018. http://dx.doi.org/10.1051/e3sconf/202340604018.
Abstract:
The reduction of carbon emissions has emerged as a critical issue that requires urgent attention in the Jiangsu and Zhejiang regions as environmental concerns continue to grow. This paper examined how to achieve carbon emission reduction through industrial restructuring. The influence rela-tionship between industrial restructuring and carbon emissions was investigated using the Kaya constant equation LMDI decomposition method, while the coefficient of variation (CV) method was utilized to explore practical ways of promoting carbon emission reduction through industrial re-structuring. Data on carbon emissions and the economy from 12 core cities and 24 industries in the Jiangsu and Zhejiang regions from 2010 to 2020 were analyzed. The key findings of this study in-dicate that economic growth remains the primary driver of local carbon emission growth, while industrial restructuring and carbon emission intensity changes exhibit both positive and negative effects on carbon emission growth. The inhibitory effect of industrial structure upgrading on carbon emission growth can be weakened by regional industrial isomorphism. Furthermore, regional dis-parities in carbon emission intensity exist among some industries in the Jiangsu and Zhejiang regions, and industrial restructuring based on carbon productivity variations has greater potential for emission reduction. The cities in these regions can encourage the development of industries with superior carbon productivity while regulating the growth of industries with inferior carbon productivity, allowing the optimal allocation of carbon emission credits from industries with lower productivity to those with higher efficiency, resulting in carbon emission reduction.
2
Zhou, Aishuang, Jinsheng Zhou, Jingjian Si, and Guoyu Wang. "Study on Embodied CO2 Emissions and Transfer Pathways of Chinese Industries." Sustainability 15, no. 3 (January 25, 2023): 2215. http://dx.doi.org/10.3390/su15032215.
Abstract:
Industries with low direct CO2 emissions downstream in the industry chain have significant carbon emissions upstream, which is similar to how carbon leakage in interprovincial regions and international commerce affects these regions. Due to the interchange and transit of goods, there are intermediate production and consumption processes across industrial sectors. The CO2 emissions produced by each sector are insufficient to satisfy the sector’s ultimate demand. It will also move along with the industrial chain. Investigating embodied carbon transfer across industrial sectors is crucial to strike a balance between economic growth and greenhouse gas emissions. Locating the key sectors to reduce carbon emissions provides a basis for formulating resource conservation and environmental protection policies. In this study, the industrial sector divides into 24 subsectors, and the embodied CO2 emissions and carbon transfer pathways of each are examined from the viewpoint of the industrial chain using the Economic Input–Output Life Cycle Assessment (EIO-LCA) and the Hypothetical Extraction Method (HEM). The indirect CO2 emissions downstream of the industrial chain are higher than the direct carbon dioxide emissions, and the intersectoral carbon transfer constitutes a significant part of the total carbon emissions of the industrial sector. The upstream sector of the industry chain has a significantly higher direct carbon emission intensity than the indirect CO2 emission intensity, while the downstream sector is the opposite. The production and supply of electricity, gas and water, and raw material industries transfer significant CO2 to other sectors. The manufacturing industry is mainly the inflow of CO2. CO2 flows from the mining industry to the raw material industry and from the raw material industry to the manufacturing industry constitute the critical pathway of carbon transfer between industries. A study on the embodied carbon emissions and transfer paths of various industrial sectors is conducive to clarifying the emission reduction responsibilities and providing a basis for synergistic emission reduction strategies.
3
Yang, Shun Shun, and Huan Zhi Wang. "Industrial Carbon Emissions Accounting from Energy and Non-Energy Consumption and Input-Output Model Construction for Trans-Sector Carbon Emissions Shift Assessment, China." Advanced Materials Research 703 (June 2013): 328–31. http://dx.doi.org/10.4028/www.scientific.net/amr.703.328.
Abstract:
This paper describes an industrial energy combustion use and industrial process emissions accounting method. By utilizing three set of widely used energy combustion carbon emission factors, Chinas industrial energy consumption carbon emissions are calculated. By using the methods provided by the IPCC, the industrial process carbon emissions for extractive industries, chemical industries and metal industries are calculated. The results show that in 2010 China's industrial energy consumption carbon emissions reached approximately 6.91×108 t C (2.53×109 t CO2), 85% from coal burning. The industrial process emitted approximately 9.47×108 t C (3.48×109 t CO2). About 5.55×108 t C (2.04×109 t CO2) is emitted by providing heat and power to industrial processes. In addition, this paper also proposed an improved model coupling industrial carbon emissions data and input-output analysis. It will help to quantify and evaluate the trans-sector carbon emissions shift.
4
Duan, Haiyan, Xize Dong, Pinlei Xie, Siyan Chen, Baoyang Qin, Zijia Dong, and Wei Yang. "Peaking Industrial CO2 Emission in a Typical Heavy Industrial Region: From Multi-Industry and Multi-Energy Type Perspectives." International Journal of Environmental Research and Public Health 19, no. 13 (June 26, 2022): 7829. http://dx.doi.org/10.3390/ijerph19137829.
Abstract:
Peaking industrial carbon dioxide (CO2) emissions is critical for China to achieve its CO2 peaking target by 2030 since industrial sector is a major contributor to CO2 emissions. Heavy industrial regions consume plenty of fossil fuels and emit a large amount of CO2 emissions, which also have huge CO2 emissions reduction potential. It is significant to accurately forecast CO2 emission peak of industrial sector in heavy industrial regions from multi-industry and multi-energy type perspectives. This study incorporates 41 industries and 16 types of energy into the Long-Range Energy Alternatives Planning System (LEAP) model to predict the CO2 emission peak of the industrial sector in Jilin Province, a typical heavy industrial region. Four scenarios including business-as-usual scenario (BAU), energy-saving scenario (ESS), energy-saving and low-carbon scenario (ELS) and low-carbon scenario (LCS) are set for simulating the future CO2 emission trends during 2018–2050. The method of variable control is utilized to explore the degree and the direction of influencing factors of CO2 emission in four scenarios. The results indicate that the peak value of CO2 emission in the four scenarios are 165.65 million tons (Mt), 156.80 Mt, 128.16 Mt, and 114.17 Mt in 2040, 2040, 2030 and 2020, respectively. Taking ELS as an example, the larger energy-intensive industries such as ferrous metal smelting will peak CO2 emission in 2025, and low energy industries such as automobile manufacturing will continue to develop rapidly. The influence degree of the four factors is as follows: industrial added value (1.27) > industrial structure (1.19) > energy intensity of each industry (1.12) > energy consumption types of each industry (1.02). Among the four factors, industrial value added is a positive factor for CO2 emission, and the rest are inhibitory ones. The study provides a reference for developing industrial CO2 emission reduction policies from multi-industry and multi-energy type perspectives in heavy industrial regions of developing countries.
5
Zhang, Lu, Yan Yan, Wei Xu, Jun Sun, and Yuanyuan Zhang. "Carbon Emission Calculation and Influencing Factor Analysis Based on Industrial Big Data in the “Double Carbon” Era." Computational Intelligence and Neuroscience 2022 (February 28, 2022): 1–12. http://dx.doi.org/10.1155/2022/2815940.
Abstract:
The arrival of the “double carbon” era indicates that industrial carbon reduction with high energy consumption and high carbon emission is imperative. From the perspective of carbon emission driving factors, industrial carbon emission is decomposed into five influencing factors: energy intensity, energy structure, industrial structure, economic efficiency, and employee scale. Taking the data of 41 subindustries of industrial industry in Liaoning Province from 2010 to 2019 as the research sample, the carbon emission is calculated. The LMDI model is used to analyze and point out the difference in the driving contribution of carbon emissions of each subindustry. The results show that the total carbon emission of Liaoning province gradually decreases, decreases for the first time in 2014, and gradually turns from flat to upward. Economic efficiency is the only and most important reason to drive the increase of industrial carbon emissions in Liaoning Province, and energy efficiency is the primary factor to curb carbon emissions. High carbon industries play a significant role in promoting the increase of carbon emissions, while the medium and low carbon industries have a better effect on restraining carbon emissions. It provides reference and theoretical basis for the government to adjust the industrial structure, control industrial overcapacity, and realize the “double carbon” goal as soon as possible. It is of great significance for the country to optimize energy layout, ensure energy security, and implement the new energy strategy.
6
Guo, Xiurui, Yaqian Shen, Wenwen Liu, Dongsheng Chen, and Junfang Liu. "Estimation and Prediction of Industrial VOC Emissions in Hebei Province, China." Atmosphere 12, no. 5 (April 21, 2021): 530. http://dx.doi.org/10.3390/atmos12050530.
Abstract:
The study of industrial volatile organic compound (VOC) emission inventories is essential for identifying VOC emission levels and distribution. This paper established an industrial VOC emission inventory in 2015 for Hebei Province and completed an emission projection for the period 2020–2030. The results indicated that the total emissions of industrial VOCs in 2015 were 1017.79 kt. The use of VOC products accounted for more than half of the total. In addition, the spatial distribution characteristics of the industrial VOC emissions were determined using a geographic information statistics system (GIS), which showed that the VOCs were mainly distributed the central and southern regions of Hebei. Considering the future economic development trends, population changes, related environmental laws and regulations, and pollution control technology, three scenarios were defined for forecasting the industrial VOC emissions in future years. This demonstrated that industrial VOC emissions in Hebei would amount to 1448.94 kt and 2203.66 kt in 2020 and 2030, with growth rates of 42.36% and 116.51% compared with 2015, respectively. If all industrial enterprises took the control measures, the VOC emissions could be reduced by 69% in 2030. The analysis of the scenarios found that the most effective action plan was to take the best available control technologies and clean production in key industries, including the chemical medicine, coke production, mechanical equipment manufacturing, organic chemical, packaging and printing, wood adhesive, industrial and construction dye, furniture manufacturing, transportation equipment manufacturing, and crude oil processing industries.
7
Li, Ying, Lei Li, Ming Na, and Shengjiang Zhao. "Analysis on the Efficiency of Anhui’s Industrial Sectors under the Carbon Emission Constraints." Journal of Finance Research 3, no. 1 (April 29, 2019): 33. http://dx.doi.org/10.26549/jfr.v3i1.1363.
Abstract:
This paper uses the SBM-DDF model to measure the green inefficiency of all kinds of industries in Anhui Province under the constraint of carbon emissions from 2006 to 2014. The results show that whether from the perspective of the overall industries in Anhui Province or from the perspective of separate industry groups, the sources of the green inefficiency are mainly from insufficient industrial output, followed by excessive emissions of CO2. The green inefficiency values of each group (from big to small) are sized down by high-emission industries, medium-emission industries and low-emission industries respectively. During the period of research, the effect of the emission reduction in high-emission industries was not significant, and the potential of reducing the green inefficiency in the medium-emission and low-emission industries by increasing the output was not large.
8
Song, J., W. J. Du, and F. Wang. "Carbon Emission and Industrial Structure Adjustment in the Yellow River Basin of China: Based on the LMDI Decomposition Model." Nature Environment and Pollution Technology 22, no. 4 (December 1, 2023): 2249–59. http://dx.doi.org/10.46488/nept.2023.v22i04.053.
Abstract:
In the context of promoting high-quality development in the Yellow River Basin (YRB) of China, urgent action is needed to achieve the “Dual Carbon” goal through energy savings, emission reductions, and industrial upgrading. This study measures carbon emissions from eight types of energy consumption across 43 industries from 2000 to 2019. Using the Kaya-LMDI model, factors affecting carbon emissions are analyzed, and the relationship between industrial structure and carbon emissions is explored through the coefficient of variation (CV). The findings reveal that coal consumption remains significantly higher than other energy sources, and the effect of energy structure adjustment on carbon emission reduction is limited compared to the impact of energy consumption increase on carbon emission growth. Moreover, the economic output effect is identified as the primary driving factor of carbon emissions, while energy utilization rate is crucial in achieving energy savings and emission reductions. Finally, the CV of carbon emissions across 43 industries is increasing. Based on these results, we suggest several policy recommendations, including prioritizing ecological concerns, developing comprehensive and scientifically sound plans, optimizing energy consumption structure, improving energy utilization efficiency, and adjusting industrial structure to promote sustainable development in the YRB.
9
CHEN, Zi, Changyi LIU, and Shenning QU. "China’s Industrialization and the Pathway of Industrial CO2 Emissions." Chinese Journal of Urban and Environmental Studies 03, no. 03 (September 2015): 1550019. http://dx.doi.org/10.1142/s2345748115500190.
Abstract:
Industrial sector is the largest CO2 emission sector in China, thus the peak of China’s total CO2 emissions relies heavily on its industrial sector. After rapid industrialization during the last three decades, China now is between the intermediate and the late industrialization stage in general. Looking at the production and emission structures of China’s industries, especially the heavy and chemical industrial sectors which are energy- and emission-intensive industries, we claim that the output of these heavy and chemical industries will peak at around 2020, the industrialization process will complete at around 2025 and after that, China will enter the post-industrialization era. According to the CO2 emission pathways of developed countries during their industrialization, i.e. the so-called “Carbon Kuznets Curve”, and based on the characteristics of China’s industrialization and urbanization process, it is estimated that the CO2 emissions from the industrial sector will keep rising over time and reach its peak at around the year 2040 in the business-as-usual scenario; while in the low-carbon scenario, it will peak between 2025 and 2030 and decline after the year 2040.
10
Li, Wenchao, Zhihao Wei, Lingyu Xu, and Shumin Jiang. "Research on the Emission Reduction Effect of International Technology Import in China’s Key Industries." Atmosphere 14, no. 7 (July 14, 2023): 1146. http://dx.doi.org/10.3390/atmos14071146.
Abstract:
In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction in key industries. Based on the panel data of 30 provinces. from 2011 to 2020, this paper used the fixed-effect model to analyze the emission reduction effect in key industries on the development status of technology import. The spatial econometric model was used to analyze the spatial characteristics of carbon emissions of technology import and key industries. Then, the mediating effect model was used to bring industrial technological innovations into the research category to analyze the mediating role of technology imports on the carbon emissions of key industries. Finally, a robustness test proved the reliability of the model. The findings were as follows: (1) Technology import significantly promoted carbon emission reduction in key industries; (2) In terms of the spatial relationship, technology import and carbon dioxide emissions had significant spillover effects, and there were trends of high and high aggregation and low and low aggregation, with the impact of technology import on carbon dioxide emissions having a siphon effect; (3) Industrial technological innovation played an intermediary role in this path, but it was a negative role, which was not, in general, conducive to the reduction of carbon emissions of key industries. On this basis, the paper puts forward several policy suggestions.
11
Jiang, Qingquan, Jinhuang Lin, Qianqian Wei, Rui Zhang, and Hongzhen Fu. "Demystifying the Economic Growth and CO2 Nexus in Fujian’s Key Industries Based on Decoupling and LMDI Model." Sustainability 15, no. 4 (February 20, 2023): 3863. http://dx.doi.org/10.3390/su15043863.
Abstract:
Faced with peaking carbon emissions and carbon neutrality goals, low-carbon transformation has become an important part of China’s current economic construction. Fujian is one of the provinces with the fastest economic development in China and the core area of the 21st Century Maritime Silk Road. Therefore, its low-carbon economic development path is of great significance to China. This study focused on the key carbon emission industries in Fujian Province, using energy and carbon emission data from industrial sectors in Fujian Province from 2005 to 2019 to establish the Tapio decoupling model. Then, we decomposed the carbon emission drivers of each industry using the LMDI decomposition method, and finally analyzed the decoupling efforts made by each carbon emission driver on the basis of the Tapio decoupling model and LMDI decomposition model. The results showed that (1) carbon emissions in Fujian Province were mainly concentrated in the manufacturing industry and the electricity, heat, gas, water production and supply industries; (2) to date, some industries in Fujian Province have achieved the decoupling of carbon emissions, but the decoupling status was not stable; and (3) both energy structure and energy intensity have facilitated increasing decoupling efforts for carbon emissions. Industrial structure has contributed less to decoupling, and population size has not yet to make an impact on decoupling. Therefore, in the future, Fujian Province should increase expenditure on green technology research and development to improve energy efficiency and gradually use renewable energy to replace fossil energy, continue to adjust the industrial structure, and increase the government’s supervision on corporate carbon emissions.
12
Chai, Yi, Xueqin Lin, and Dai Wang. "Industrial Structure Transformation and Layout Optimization of Beijing-Tianjin-Hebei Region under Carbon Emission Constraints." Sustainability 13, no. 2 (January 12, 2021): 643. http://dx.doi.org/10.3390/su13020643.
Abstract:
To address the issue of global warming, there is a trend towards low-carbon economies in world economic development. China’s rapid economic growth and high carbon energy structure contribute to its large carbon emissions. To achieve sustainable development, China must transform its industrial structure to conserve energy, reduce emissions, and adapt to climate change. This study measured the carbon entropy and carbon emission efficiency of 25 industries in the Beijing-Tianjin-Hebei region from 2000 to 2015 by building carbon entropy models and total factor industrial carbon emission efficiency evaluation models. The study showed that: (a) Priority development industries in the Beijing-Tianjin-Hebei region were expanding, the regional competitiveness of the moderate development industry was improving, and the proportion of restricted development industries had dropped significantly; (b) the spatial distribution of the three types of industries presented a pattern of concentric rings, with priority industries at the core, surrounded by moderate, then by restricted development industries; (c) the status of medium- and high-efficiency industries had improved, while the status of low-efficiency industries had decreased. Spatially, high- and low-efficiency industries were becoming concentrated, and medium-efficiency industries were becoming dispersed; (d) considering carbon entropy and carbon emission efficiency, the path of industrial structure transformation and upgrading and layout optimization in Beijing-Tianjin-Hebei region was proposed.
13
Liang, Jing, and Lingying Pan. "Effect of Scale and Structure Changes of China’s High-Carbon Industries on Regional Carbon Emissions." Energies 16, no. 18 (September 18, 2023): 6676. http://dx.doi.org/10.3390/en16186676.
Abstract:
China’s carbon emissions have a stable industrial concentration. In recent years, the carbon emissions of the six major high-carbon industries have accounted for approximately 80% of the national total and are thus priority areas for emission reduction. With the promotion of energy-saving and emission-reduction policies, the structure and scale of high-carbon industries in various regions have undergone changes, but their carbon reduction effects show significant regional differences. Based on China’s provincial panel data from 2006 to 2020, this study discusses the structural characteristics of high-carbon industries with their proportion of energy-based industries and measures their scale characteristics with their output values. On this basis, a fixed-effects model is used to analyze the single and synergistic effects of the scale and structure of high-carbon industries on carbon emissions in each province. The results indicate that changes in the scale and structure of high-carbon industries significantly affect carbon emissions but show regional differences in both the single and synergistic effects. When considering these synergistic effects, the single effect of high-carbon industries on carbon emissions will be weakened. In regions with large-scale high-carbon industries, the increase in the proportion of energy-based industries significantly increases carbon emissions, but this effect gradually weakens as the overall scale expands. In areas with small-scale high-carbon industries, the increase in the proportion of energy-based industries has a relatively small effect on carbon emission growth that gradually increases with the overall scale. In addition, the implementation of the carbon emission trading policy has a significant moderating effect on the carbon emissions of high-carbon industries and strongly promotes its reduction.
14
Zhuang, Zhipeng, Weijian Zhou, Zhihua Pang, Yutao Lei, and Wenzhong Liang. "Analysis on Comprehensive Treatment of VOCs in Key Industries of A City." E3S Web of Conferences 145 (2020): 02060. http://dx.doi.org/10.1051/e3sconf/202014502060.
Abstract:
Vocs have become a weak base for air pollution control compared to particulate matter, sulfur dioxide and nitrogen oxide. Petrochemical, chemical, industrial coating, packaging and printing, oil storage and Marketing Industries (hereinafter referred to as key industries) are China’s key sources of VOCs emissions. In order to win the battle of protecting the blue sky and improve the air quality, it is urgent to strengthen the comprehensive treatment of VOCs in key industries. In order to fully understand the comprehensive treatment and emission control of industrial sources of organic waste gases in the city, an updated survey was conducted on the emission of VOCs from industrial sources in the region, and the results of the survey were analyzed Analysis report on VOCs emission and comprehensive treatment in key industries.
15
Tong, Qing, Sheng Zhou, Yuefeng Guo, Yang Zhang, and Xinyang Wei. "Forecast and Analysis on Reducing China’s CO2 Emissions from Lime Industrial Process." International Journal of Environmental Research and Public Health 16, no. 3 (February 11, 2019): 500. http://dx.doi.org/10.3390/ijerph16030500.
Abstract:
China greenhouse gas inventories show that CO2 emissions from the lime industrial process are large scales and closely related to the development of its downstream industries. Therefore, there is high importance to analyze and forecast on reducing China’s CO2 emissions from lime industrial process. The aims of this paper are to make up the research gaps in China and provide a quantitative reference for related authorities to formulate relevant policies. The prediction method in this paper is consistent with the published national inventory, which is an activity data based method to predict carbon dioxide emissions from the industrial process of four categories of lime products. Three future scenarios are assumed. The business as usual scenario (BAU) is a frozen scenario. There are two emission reduction scenarios (ERS and SRS) assumed under different emission reduction strength considering combined industrial process CO2 emission reduction approaches from both the production side and the consumption side. The results show that between 2020 and 2050, China’s lime industrial process has an increasingly significant CO2 emission reduction potential, enabling both emission intensity reductions and total emission reductions to be achieved simultaneously. Based on the simulation results from emission reduction scenarios, compared with 2012 level, in 2050, the emission intensity can be reduced by 13–27%, the total lime production can be reduced by 49–78%, and the CO2 emissions in the lime industrial process can be reduced by 57–85%.
16
Yue, Jiachen, Huasheng Zhu, and Fei Yao. "Does Industrial Transfer Change the Spatial Structure of CO2 Emissions?—Evidence from Beijing-Tianjin-Hebei Region in China." International Journal of Environmental Research and Public Health 19, no. 1 (December 29, 2021): 322. http://dx.doi.org/10.3390/ijerph19010322.
Abstract:
As an important cause of global warming, CO2 emissions have become a research hotspot in recent years. Industrial transfer impacts regional CO2 emissions and is related to the low-carbon development of regional industries. Taking the Beijing-Tianjin-Hebei region (BTH region) as an example, this study analysed industrial transfer’s direct and indirect impacts on CO2 emissions based on a mediating model and two-way fixed effect panel regression. The results obtained indicate that industrial transfer-in has promoted CO2 emissions to a small extent, and the positive impact of industrial transfer-in on CO2 emissions wanes over time. Industrial transfer affects CO2 emissions by acting on the economic level, on population size, and on urbanisation level, but the indirect effect is weaker than the direct effect. Industrial transfer does not lead to technological upgrading, but the latter is an effective means of carbon emission reduction. Industrial transfer-in has shown a positive effect on CO2 emissions for most cities, but there are exceptions, such as Cangzhou. In the future, the BTH region should maintain coordinated development among cities and improve the cooperative innovation mechanism for energy conservation and emission reduction.
17
Lv, Hao, Beibei Shi, Nan Li, and Rong Kang. "Intelligent Manufacturing and Carbon Emissions Reduction: Evidence from the Use of Industrial Robots in China." International Journal of Environmental Research and Public Health 19, no. 23 (November 23, 2022): 15538. http://dx.doi.org/10.3390/ijerph192315538.
Abstract:
Driven by the information technology revolution, using artificial intelligence to promote intelligent manufacturing while achieving carbon emissions reduction is increasingly the focus of international attention. Given this, based on the fact that China’s industrial manufacturing is more intelligent, this paper uses industrial sector data and robot data from 2000 to 2017 to examine the impact of intelligent manufacturing on industrial carbon dioxide emissions and to discuss its internal mechanism. The research found that intelligent manufacturing significantly inhibits carbon dioxide emissions in the industrial sectors. The emission reduction effect is more obvious in industries with higher carbon emissions and intelligence. The mechanism test shows that intelligent manufacturing mainly achieves industrial emission reduction by reducing fossil energy consumption in the production process and improving energy use efficiency. The research findings of this paper provide favorable evidence for using new technologies, such as artificial intelligence, to achieve carbon emissions reduction, and validate the importance of intelligent manufacturing in tackling climate change in the future. It provides an essential reference for developing countries to use artificial intelligence for their carbon emissions reduction goals.
18
Zhang, Ren-Long, Xiao-Hong Liu, and Wei-Bo Jiang. "How Does the Industrial Digitization Affect Carbon Emission Efficiency? Empirical Measurement Evidence from China’s Industry." Sustainability 15, no. 11 (June 2, 2023): 9043. http://dx.doi.org/10.3390/su15119043.
Abstract:
Based on the panel data of China’s industrial carbon emissions from 2015 to 2022, the S-SBM model is scientifically used to measure the industrial carbon emission efficiency, and a spatial model is constructed to empirically analyze the spatial effect of industrial digitalization on carbon emission efficiency. From the regional perspective, it is interesting to find that industrial digitization has shown an overall downward trend of the central, western and northeastern regions showing a roughly N-shaped trend of change. From an industry perspective, we also find that industrial digitization has a relatively high overall impact on the carbon emissions performance of the mining industry with significant changes in the performance of electricity and heat and gas and water production and supply industries. Therefore, the experimental results effectively provide the substantive empirical evidence for policy makers on how to best promote the development of industrial digitization and strengthen the effective application of digital technology affecting carbon emission control in China.
19
Ye, Anning, Yuguo Ji, and Min Zhang. "Research on Carbon Emissions of Industrial Clusters in China." Academic Journal of Science and Technology 3, no. 2 (October 28, 2022): 65–70. http://dx.doi.org/10.54097/ajst.v3i2.2094.
Abstract:
At present, the global warming problem is becoming more and more serious, and effective carbon emission reduction is urgent, and the cooperation between industries within a specific supply chain can provide a new method to reduce emissions. Whith 2017 year as the research period, 30 industrial sectors in China as the research object, using the new method proposed by Kanemoto et al. to identify high carbon emission industrial clusters. Combined with modified normalized cut function, we find out high carbon emission industrial clusters among 30 industrial sectors from the supply chain perspective with multiple clustering methods, and based on this, the relative position of each industrial sector in the industrial chain is studied through minimum spanning tree to find the key industrial chain. The results show that the clustering effect performs best at k=7, where cluster 1 accounts for 89% of the total carbon emissions of all clusters, indicating that this industrial cluster has more potential for emission reduction compared with other industrial clusters and is the focus of future emission reduction efforts, while the upstream and downstream industrial chains with the construction industry as the core are the key industrial chains of this cluster as shown by the minimum spanning tree.
20
Ren, Songyan, Peng Wang, Zewei Lin, and Daiqing Zhao. "The Policy Choice and Economic Assessment of High Emissions Industries to Achieve the Carbon Peak Target under Energy Shortage—A Case Study of Guangdong Province." Energies 15, no. 18 (September 15, 2022): 6750. http://dx.doi.org/10.3390/en15186750.
Abstract:
In recent years, due to the rise in energy prices and the impact of COVID-19, energy shortages have led to unsafe power supply environments. High emissions industries which account for more than 58% of the carbon emissions of Guangdong Province have played an important role in achieving the carbon peak goal, alleviating social energy shortage and promoting economic growth. Controlling high emissions industries will help to adjust the industrial structure and increase renewable energy investment. Therefore, it is necessary to comprehensively evaluate the policies of energy security and the investments of high emission industries. This paper builds the ICEEH-GD (comprehensive assessment model of climate, economy, environment and health of Guangdong Province) model, designs the Energy Security scenario (ES), the Restrict High Carbon Emission Sector scenario (RHS) and the Comprehensive Policy scenario (CP), and studies the impact of limiting high emissions industries and renewable energy policies on the transformation of investment structure, macro-economy and society. The results show that under the Energy Security scenario (ES), carbon emissions will peak in 2029, with a peak of 681 million tons. Under the condition of ensuring energy security, the installed capacity of coal-fired power generation will remain unchanged from 2025 to 2035. Under the Restrict High Carbon Emission Sector scenario (RHS), the GDP will increase by 8 billion yuan compared with the ES scenario by 2035. At the same time, it can promote the whole society to increase 10,500 employment opportunities, and more investment will flow to the low emissions industries. In the Comprehensive Policy scenario (CP), although the GDP loss will reach 33 billion yuan by 2035 compared with the Energy Security scenario (ES), the transportation and service industries will participate in carbon trading by optimizing the distribution of carbon restrictions in the whole society, which will reduce the carbon cost of the whole society by more than 48%, and promote the employment growth of 104,000 people through industrial structure optimization. Therefore, the power sector should increase investment in renewable energy to ensure energy security, limit the new production capacity of high emissions industries such as cement, steel and ceramics, and increase the green transition and efficiency improvement of existing high emissions industries.
21
Chu, Jie, and Anuj Kumar. "Assessment of wood industrial pollutants based on emission coefficients in China." Holzforschung 74, no. 11 (November 26, 2020): 1071–78. http://dx.doi.org/10.1515/hf-2019-0201.
Abstract:
AbstractThe implementation of circular economy in wood industries is an effective way for future sustainable development. The wood industries in China are not in the direction of circular economy approach due to less availability of assessment/calculation data of pollutants as per life cycle assessment (LCA) criteria. The present study focuses on the calculation of emission and pollutants from wood industries as per LCA; the emission and pollution data were collected from fiberboard Medium-density fiberboard (MDF), plywood and particleboard (PB) production. The comparative analysis of dust emissions, industrial waste gases and chemical oxygen demand (COD) were performed among three wood industries. The results revealed that the fiberboard industry was the highest emitter of dust, industrial waste gas and COD; and particleboard industry was the least emitter. Further, results indicated that pollutant index of wood industries were significantly changed between 2015 and 2017; the industrial waste water discharge increased five folds and the COD, dust and industrial gases increased two times. This study provides with the emission and pollutants data of wood industries as per LCA to promote the sustainable development for circular and low carbon economics.
22
Xu, Minglong, Huimin Li, and Xianghui Deng. "Measuring the Synergistic Effect of Pollution and Carbon Reduction in China’s Industrial Sector." Sustainability 16, no. 3 (January 25, 2024): 1048. http://dx.doi.org/10.3390/su16031048.
Abstract:
The industrial sector is a major source of CO2 and atmospheric pollutants in China, and it is important to promote industrial pollution reduction and carbon reduction to improve the quality of China’s atmospheric environment and meet CO2 peak targets. In this paper, based on 2005 to 2021’s panel data from the industrial sector, we construct a computational model of the synergistic effect of pollution reduction and carbon reduction, quantitatively evaluate the synergistic effect of industrial CO2 emissions and air pollutants, and explore its evolutionary mechanism. The results showed that between 2005 and 2021, there was a clear synergistic effect between CO2 and air pollutants in China’s industrial sector, and the synergistic effect is increasing. For different pollutants, CO2 and SO2 have the strongest synergies, and CO2 and particulate matter have relatively weak synergies. For different energy types, the synergies between coal-related carbon emissions and air pollutants gradually increase, while gas-related carbon emissions and pollutants tend to decrease. From different industry types, the synergies between CO2 and air pollutants are weaker in high-polluting and high-emission industries than in other industries. These results have strong policy implications. First, the focus of synergistic measures should be on source reduction. The second is to make high-polluting and high-emission industries the focus of pollution reduction and carbon reduction. Third is harmonized management of air quality standards and carbon peaking should be promoted. The formulation of relevant policies from the above three aspects will help synergize pollution reduction and carbon reduction in the industrial sector.
23
Le, Dong, Fei Ren, Yiding Tang, and Yuke Zhu. "The Effect of Environmental Policy Uncertainty on Enterprises’ Pollution Emissions: Evidence from Chinese Industrial Enterprise." International Journal of Environmental Research and Public Health 19, no. 16 (August 10, 2022): 9849. http://dx.doi.org/10.3390/ijerph19169849.
Abstract:
In response to the global call for emission reduction, China has assumed international responsibility for energy conservation and emission reduction by enacting several environmental policies to save energy and reduce consumption. However, it is debatable whether the increased uncertainty in environmental policies negatively affects firms’ emission reduction. Few studies have examined this relationship based on micro-level data. Therefore, this study constructs a theoretical framework of environmental policy uncertainty affecting firms’ pollution emissions. Based on comprehensive data from the Chinese Industrial Enterprise Database, the Chinese Industrial Enterprise Pollution Emission Database, and the Chinese Patent Database from 2002 to 2014, we empirically analyzed the impact of environmental policy uncertainty on firms’ pollution emissions. The results show that (1) environmental policy uncertainty significantly aggravates the pollution emission intensity of industrial enterprises; (2) environmental policy uncertainty inhibits the improvement of enterprises’ innovation capacity, reduces their human capital stock and foreign investment, and aggravates their pollution emission; (3) environmental policy uncertainty has significant heterogeneity on enterprise pollution emissions, that is, environmental policy uncertainty has a greater impact on non-export enterprises, large enterprises, young enterprises, capital-intensive enterprises, state-owned enterprises, and enterprises in polluting industries and central regions. This study provides a useful reference for the improvement of environmental policy and the green transformation of enterprises.
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Simmonds, Peter G., Matthew Rigby, Alistair J. Manning, Sunyoung Park, Kieran M. Stanley, Archie McCulloch, Stephan Henne, et al. "The increasing atmospheric burden of the greenhouse gas sulfur hexafluoride (SF<sub>6</sub>)." Atmospheric Chemistry and Physics 20, no. 12 (June 23, 2020): 7271–90. http://dx.doi.org/10.5194/acp-20-7271-2020.
Abstract:
Abstract. We report a 40-year history of SF6 atmospheric mole fractions measured at the Advanced Global Atmospheric Gases Experiment (AGAGE) monitoring sites, combined with archived air samples, to determine emission estimates from 1978 to 2018. Previously we reported a global emission rate of 7.3±0.6 Gg yr−1 in 2008 and over the past decade emissions have continued to increase by about 24 % to 9.04±0.35 Gg yr−1 in 2018. We show that changing patterns in SF6 consumption from developed (Kyoto Protocol Annex-1) to developing countries (non-Annex-1) and the rapid global expansion of the electric power industry, mainly in Asia, have increased the demand for SF6-insulated switchgear, circuit breakers, and transformers. The large bank of SF6 sequestered in this electrical equipment provides a substantial source of emissions from maintenance, replacement, and continuous leakage. Other emissive sources of SF6 occur from the magnesium, aluminium, and electronics industries as well as more minor industrial applications. More recently, reported emissions, including those from electrical equipment and metal industries, primarily in the Annex-1 countries, have declined steadily through substitution of alternative blanketing gases and technological improvements in less emissive equipment and more efficient industrial practices. Nevertheless, there are still demands for SF6 in Annex-1 countries due to economic growth, as well as continuing emissions from older equipment and additional emissions from newly installed SF6-insulated electrical equipment, although at low emission rates. In addition, in the non-Annex-1 countries, SF6 emissions have increased due to an expansion in the growth of the electrical power, metal, and electronics industries to support their continuing development. There is an annual difference of 2.5–5 Gg yr−1 (1990–2018) between our modelled top-down emissions and the UNFCCC-reported bottom-up emissions (United Nations Framework Convention on Climate Change), which we attempt to reconcile through analysis of the potential contribution of emissions from the various industrial applications which use SF6. We also investigate regional emissions in East Asia (China, S. Korea) and western Europe and their respective contributions to the global atmospheric SF6 inventory. On an average annual basis, our estimated emissions from the whole of China are approximately 10 times greater than emissions from western Europe. In 2018, our modelled Chinese and western European emissions accounted for ∼36 % and 3.1 %, respectively, of our global SF6 emissions estimate.
25
Zhou, Chunli, Xiqiao Lin, Renhao Wang, and Bowei Song. "Real-Time Carbon Emissions Monitoring of High-Energy-Consumption Enterprises in Guangxi Based on Electricity Big Data." Energies 16, no. 13 (July 3, 2023): 5124. http://dx.doi.org/10.3390/en16135124.
Abstract:
Real-time carbon emissions monitoring at the enterprise level is a crucial tool in shifting macrolevel carbon peak and carbon neutrality plans toward micro-level implementations. This study extends the existing CO2 emissions accounting framework to enterprise emissions monitoring. We analyze the correlation mechanism between electricity consumption and CO2 emissions by industries, calculate the electricity–CO2 coefficients, and finally model an enterprise-level real-time carbon emissions monitoring method based on electricity big data. Taking Guangxi region as a sample, the results show that (1) the proportion of electricity-related emissions is on the rising stage in Guangxi, with 441 g CO2/KWh emitted from electricity consumption in 2020, (2) the carbon emissions from the energy-intensive industries account for over 70% of the whole society, and they all have high electricity–CO2 coefficients, far exceeding the industry average of 1129 g/kWh, and (3) the monitoring method is applied to 1338 enterprises from over 40 industries. The emission characteristics reflect the regional and industrial heterogeneity. This enterprise-level monitoring method aims to optimize the carbon emissions calculation method toward higher temporal and spatial resolutions, so as to provide an important numerical basis for promoting carbon emission reduction and sustainable development.
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Yang, Na, Zilong Zhang, Bing Xue, Junxia Ma, Xingpeng Chen, and Chenyu Lu. "Economic Growth and Pollution Emission in China: Structural Path Analysis." Sustainability 10, no. 7 (July 23, 2018): 2569. http://dx.doi.org/10.3390/su10072569.
Abstract:
The relationship between economic growth and environmental pollution has long been a controversial topic. However, simply the detection of the existence of environmental Kuznets curve (EKC) is not enough to understand how economic growth induced environmental pollution. This study investigated the path and mechanism of the effect of economic growth on the emission of two types of environmental pollutants, that is, industrial smoke and dust and sulfur dioxide, by using a structural equation model and a sample of 283 prefecture-level cities in China in 2005 and 2015. The research results show that economic growth exerted both direct and indirect effects on the emission of the two environmental pollutants. In addition to a direct impact through the economic scale effect, economic growth also indirectly impacted the two environmental pollutants emissions through three mediators, that is, industrial structure, technological innovations and environmental regulations. For different pollutants, the effect paths of economic growth on their emission showed both similarities and differences. First, with regards to industrial smoke and dust emissions and sulfur dioxide emissions, the effects of economic growth on the amount of these two emissions through environmental regulations and the industrial structure were negative inhibitory effects and positive promoting effects, respectively. This means that in prefectural-level cities in China, environmental regulation factors have produced some effects in reducing the emissions of these two pollutants while the industrial structure (level of industrialization) can increase the emissions of these two pollutants. However, the effect strength of these two paths shows a gradual weakening. Second, these two paths differ in effect strength and its changes. The positive promoting effects of the industrial structure on pollutant emission are significantly higher than the inhibitory effects of environmental regulation. In addition, our study also found that the direct impact path of economic growth on environmental pollution also passed significance testing, particularly in 2015. This shows that other reasons affect pollutant emission, such as system factors, spatial migration of industries and so forth.
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Jun, Lyu, Shuang Lu, Xiang Li, Zeng Li, and Chenglong Cao. "Spatio-Temporal Characteristics of Industrial Carbon Emission Efficiency and Their Impacts from Digital Economy at Chinese Prefecture-Level Cities." Sustainability 15, no. 18 (September 13, 2023): 13694. http://dx.doi.org/10.3390/su151813694.
Abstract:
In the pursuit of China’s dual carbon goals, identifying spatio-temporal changes in industrial carbon emission efficiency and their influencing factors in cities at different stages of development is the key to effective formulation of countermeasures to promote the low-carbon transformation of Chinese national industry and achieve high-quality economic development. In this study, we used balanced panel data of 270 Chinese cities from 2005 to 2020 as a research object: (1) to show spatio-temporal evolution patterns in urban industrial carbon emission efficiency; (2) to analyze the aggregation characteristics of industrial carbon emission efficiency in Chinese cities using Global Moran’s I statistics; and (3) to use the hierarchical regression model for panel data to assess the non-linear impact of the digital economy on the industrial carbon emission efficiency of cities. The results show the following: (1) the industrial carbon emission efficiency of Chinese cities exhibited an upward trend from 2005 to 2020, with a spatial distribution pattern of high in the south and low in the north; (2) China’s urban industrial carbon emission efficiency is characterized by significant spatial autocorrelation, with increasing and stabilizing correlation, and a relatively fixed pattern of spatial agglomeration; (3) there is a significant inverted-U-shaped relationship between the digital economy and the industrial carbon emission efficiency of cities. The digital economy increases carbon emissions and inhibits industrial carbon emission efficiency in the early stages of development but inhibits carbon emissions and promotes industrial carbon emission efficiency in mature developmental stages. Therefore, cities at all levels should reduce pollution and carbon emissions from high-energy-consuming and high-polluting enterprises, gradually reduce carbon-intensive industries, and accelerate the digital transformation and upgrading of enterprises. Western, central, and eastern regions especially should seek to promote the sharing of innovation resources, strengthen exchanges and interactions relating to scientific and technological innovation, and jointly explore coordinated development routes for the digital economy.
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Guo, Hai Bo, Ying Zhu, and Zheng Wang. "Low Carbon Strategies for Industry Energy Plan of Heilongjiang Province." Advanced Materials Research 361-363 (October 2011): 1009–12. http://dx.doi.org/10.4028/www.scientific.net/amr.361-363.1009.
Abstract:
Heilongjiang Province, whose pillar industries are made up of petroleum and coal exploitation, chemicals fabrication and mechanical devices manufacture, is one of the most important industrial bases in China. The leading enterprises from the three pillar industries make up the 59.2% of the total quantity and contribute the 57.3% of the total GDP in Heilongjiang Province. But as a matter of fact, according to the latest statistics, unit GDP carbon emissions of these three industrials are as high as 4. They are the typical industries whose characteristics are high energy consumed and intense carbon emission. As a result, adopting new energy and switching the developmental pattern to a low carbon model are a crucial step in Heilongjiang Province. The authors study this research by the methods of calculating the relevant datum and comparative analysis, and put forward three low carbon energy strategies: making full use of the bio-energy with the leading representatives of Ethanol Alcohol Gasoline and Dimethyl Ether (DEM); increasing investment on wind power project, and utilizing the potential water resources. With the operation of these strategies, we can reduce the carbon emissions and lead the industry to a green and sustainable way.
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Li, Congxin, and Xu Zhang. "The Influencing Mechanisms on Global Industrial Value Chains Embedded in Trade Implied Carbon Emissions from a Higher-Order Networks Perspective." Sustainability 14, no. 22 (November 15, 2022): 15138. http://dx.doi.org/10.3390/su142215138.
Abstract:
As the division of labor in global industrial value chains deepens, the embedded relationships and carbon emission relationships among countries become more complex. First, calculate the embedding indices of forward and backward global industrial value chains and establish the Multi-Regional Input Output (MRIO) model to calculate trade-implied carbon emissions. Second, construct higher-order weighted networks characterized by hypergraphs from 2000 to 2018, and calculate a high-dimensional vector of characteristic indicators based on apices and hyperedges. Finally, time exponential random graph models are constructed using maximum pseudo-likelihood estimation and Markov Monte Carlo simulation methods to dynamically observe the evolution of the impact mechanism of forward and backward industrial value chains embedded in trade-implied carbon emissions networks. The conclusions obtained are as follows: First, most countries tend to develop backward industries when embedded in global industrial value chains. Second, based on the Global Industry Classification Standard (GICS) criteria, industries deeply embedded in global forward value chains are mainly concentrated in materials and utilities, etc., while industries more deeply embedded in global backward value chains are mainly concentrated in consumer discretionary and real estate industries, etc. Third, “carbon transfer” and “carbon leakage” gradually widen the gap between developed and developing countries, both on the production and consumption sides. Fourth, we decompose the factors influencing industrial carbon emissions into carbon intensity effects, industrial structure effects, and output scale effects and analyze their influence mechanisms. Fifth, for countries with different carbon flow attributes, their forward and backward embedded global industrial value chains have different effects on trade-implied carbon emissions. Sixth, the effective paths of trade that lead to a reduction in carbon emissions are different for countries with different carbon flow characteristics.
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WU, Yiqun, Zhu WANG, Xiaoqing ZHU, Huifang YU, and Suer·Abula JIA. "Construction and Spatial-Temporal Characteristic Analysis of the Carbon Atlas of Low-Carbon Villages in the Yangtze River Delta." Journal of South Architecture 1, no. 1 (March 30, 2024): 10. http://dx.doi.org/10.33142/jsa.v1i1.10431.
Abstract:
Countryside is an integral part of China's social and economic systems. For a long time, the continuous growth of rural carbon emissions has led to a series of social, economic and ecological consequences. Carbon emission reduction has become a critical task for rural revitalization and sustainable development in China. Existing studies on low-carbon assessment mainly focus on urban areas, resulting in limited studies on rural areas. What's more, most of the planning strategies for low-carbon villages are also based on subjective evaluation and qualitative analysis, lacking support from quantitative simulation. Combining relevant theories, the concept of a rural "carbon atlas" was proposed in this study. The current rural carbon emissions and mathematics, graphics, and rationales of the temporal-spatial evolutionary characteristics were investigated using the GIS system as the technical platform for information storage and processing. The spatial domain of carbon emission units based on microscopic residential sites, factories and markets was defined and investigated. Carbon emissions of each unit were estimated according to energy consumptions for life, production and transportation. Later, carbon emissions were expressed and presented visually within the "atlas". Meanwhile, temporal and spatial distribution patterns of carbon emissions in various types of rural areas dominated by different industries were analyzed to provide resources and guidelines for building and planning low-carbon countryside and villages.An empirical study was undertaken on four different village types dominated by different industries in the Yangtze River Delta. Results show that the rural carbon atlas has apparent characteristics of tendentious distribution, periodical changes, and typified structures:(1) Different village types have different regional tendencies of high carbon emission. This phenomenon is most evident in industrial villages, where most of the carbon emissions happen in large factories or family workshops with large homestead areas. Traditional fishing and agricultural villages are the least representative in this regard because rural industries are mainly small fishing and agricultural families, and the industrial link among families is weak. (2) Due to the industry's cyclical nature, the fluctuation of carbon emissions in different types of villages is significantly different. Since the leisure tourism industry is greatly affected by festivals and seasons, the carbon emissions in leisure tourism villages fluctuate the most. Carbon emission of professional markets is the most stable, which is attributed to their immunity to seasonal and climatic changes. (3) The rural carbon emission map has prominent typified structural characteristics, including the scattered homogeneous pattern (traditional fishing and agricultural village), the group infiltration pattern (industrial production village), the dissipative fragmentation pattern (leisure tourism village), and the kernel domain recursive pattern (professional market village). Different industrial types lead to noticeable regional differences in the temporal-spatial characteristics and trends of carbon atlas. Hence, there is an urgent need to develop an overall optimization strategy and mechanism model. The outcomes from the current study explore the method and practical application of a rural carbon emission atlas, yet more extensive research exploring various facets of the atlas are still required.
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Wang, Feng, Changhai Gao, Wulin Zhang, and Danwen Huang. "Industrial Structure Optimization and Low-Carbon Transformation of Chinese Industry Based on the Forcing Mechanism of CO2 Emission Peak Target." Sustainability 13, no. 8 (April 15, 2021): 4417. http://dx.doi.org/10.3390/su13084417.
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.
32
Zhou, Jianguo, Yushuo Li, Xuejing Huo, and Xiaolei Xu. "How to Allocate Carbon Emission Permits Among China’s Industrial Sectors Under the Constraint of Carbon Intensity?" Sustainability 11, no. 3 (February 11, 2019): 914. http://dx.doi.org/10.3390/su11030914.
Abstract:
With the official launch of China’s national unified carbon trading system (ETS) in 2017, it has played an increasingly important role in controlling the growth of carbon dioxide emissions. One of the core issues in carbon trading is the allocation of initial carbon emissions permits. Since the industry emits the largest amount of carbon dioxide in China, a study on the allocation of carbon emission permits among China’s industrial sectors is necessary to promote industry carbon abatement efficiency. In this study, industrial carbon emissions permits are allocated to 37 sub-sectors of China to reach the emission reduction target of 2030 considering the carbon marginal abatement cost, carbon abatement responsibility, carbon abatement potential, and carbon abatement capacity. A hybrid approach that integrates data envelop analysis (DEA), the analytic hierarchy process (AHP), and principal component analysis (PCA) is proposed to allocate carbon emission permits. The results of this study are as follows: First, under the constraint of carbon intensity, the carbon emission permits of the total industry in 2030 will be 8792 Mt with an average growth rate of 3.27%, which is 1.57 times higher than that in 2016. Second, the results of the carbon marginal abatement costs show that light industrial sectors and high-tech industrial sectors have a higher abatement cost, while energy-intensive heavy chemical industries have a lower abatement cost. Third, based on the allocation results, there are six industrial sub-sectors that have obtained major carbon emission permits, including the smelting and pressing of ferrous metals (S24), manufacturing of raw chemical materials and chemical products (S18), manufacturing of non-metallic mineral products (S23), smelting and pressing of non-ferrous metals (S25), production and supply of electric power and heat power (S35), and the processing of petroleum, coking, and processing of nuclear fuel (S19), accounting for 69.23% of the total carbon emissions permits. Furthermore, the study also classifies 37 industrial sectors to explore the emission reduction paths, and proposes corresponding policy recommendations for different categories.
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Chen, Bin, Guoxuan He, Jing Qi, Meirong Su, Shiyi Zhou, and Meiming Jiang. "Greenhouse Gas Inventory of a Typical High-End Industrial Park in China." Scientific World Journal 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/717054.
Abstract:
Global climate change caused by greenhouse gas (GHG) emissions, which severely limits the development of human society and threatens the survival of humanity, has drawn the international community's long-term attention. Gathering the most important production factors in the region, an industrial park usually represents the development level of specific industries in the region. Therefore, the industrial park should be regarded as the base unit for developing a low-carbon economy and reducing GHG emissions. Focusing on a typical high-end industrial park in Beijing, we analyze the carbon sources within the system boundary and probe into the emission structure in view of life-cycle analysis. A GHG inventory is thereby set up to calculate all GHG emissions from the concerned park. Based on the results, suggestions are presented to guide the low-carbon development of the high-end industrial park.
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Lyu, Yang, Zheng Ji, Han Liang, Tao Wang, and Yanqiao Zheng. "Has Information Infrastructure Reduced Carbon Emissions?—Evidence from Panel Data Analysis of Chinese Cities." Buildings 12, no. 5 (May 7, 2022): 619. http://dx.doi.org/10.3390/buildings12050619.
Abstract:
Human activities have increased greenhouse gas emissions since the Industrial Revolution, and “emission peaking” and “carbon neutrality” have become serious concerns at this point. The role of information infrastructure in reducing carbon emissions is a critical issue that has received little attention and needs to be addressed. Using panel data from 289 cities in China between 2011 and 2017, this research empirically explores the impact of information infrastructure on urban carbon emission intensity and the mechanism behind this effect. We discover that the construction of information infrastructure significantly reduces urban carbon emissions, and this finding holds true after a series of robustness tests. The mechanism is optimization of industrial structure, agglomeration of producer service industries, and innovation of green technologies. According to the heterogeneity test, the carbon emission reduction is greater in mega cities with higher technological levels and larger urban scales, as well as large cities with better traditional infrastructure. The present work’s findings give empirical support for promoting green and low-carbon development and mitigating global warming.
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Bityukova, V. R., and A. A. Shimunova. "Regional analysis of differentiation in air pollution from manufacturing at the post-Soviet territories." Regional nye issledovaniya, no. 4 (2020): 82–96. http://dx.doi.org/10.5922/1994-5280-2020-4-7.
Abstract:
The article considers the dynamics of air emissions in 12 post-Soviet countries by region depending on the dynamics of GDP (GRP), the volume and structure of industrial production, changes in the structure of the fuel balance and energy intensity. During the crisis of the 1990s, pollution decreased in all countries and most regions, but at a slower rate than production, and as a result, specific emissions increased due to the greater resilience of the most “dirty” industries to the crisis. Pollution in the largest countries was the most persistent, and within countries in the largest emission regions. During the growth period, there was an increase in emissions in the regions of hydrocarbon production. Regional differences in emissions are mainly due to industrial production for Russia and Ukraine, with high consistency between production and pollution trends. In Ukraine, the decline in production in the Eastern regions has led to a shift in pollution to areas of population concentration. In Kazakhstan, the territorial structure of emissions is determined by the volume of coal-fired power generation and the location of energy- intensive industries. In the post-Soviet space, inherited development factors determine pollution from the energy sector, where outdated funds and the structure of the fuel balance have been preserved to the greatest extent. Large industrial regions tend to stabilize their emissions, while small regions either reduce their emissions or increase them.
36
Xu, Xiaoxiang, and Mingqiu Liao. "Prediction of China’s Economic Structural Changes under Carbon Emission Constraints: Based on the Linear Programming Input–Output (LP-IO) Model." Sustainability 14, no. 15 (July 29, 2022): 9336. http://dx.doi.org/10.3390/su14159336.
Abstract:
China has established a carbon emission reduction goal for 2030. For the Chinese government, there is a dilemma between reducing carbon emissions while still striving to maintain continuous economic growth in future. To achieve these “dual goals”, it is necessary to predict the optimal industrial structure under these constraints in 2030. By integrating the linear programming input–output model (LP-IO) with the RAS updating technique, this paper predicts the industrial structure in China in 2030 and compares it with the year 2018. The results show that China’s industry structure will experience major changes. In particular, most of the industries related to manufacturing, such as mining, petroleum, and metal, will lose their important positions in the economic system, while service industries such as culture, sports, and public service will take over the position as pillars of the economy. Additionally, carbon emissions in 2030 will be at least 12.8 billion tons. Based on these findings, it is suggested that the Chinese government should increase investment in service industries in advance to meet the goal of reducing carbon emissions earlier.
37
Liu, Jian, Qingshan Yang, Yu Zhang, Wen Sun, and Yiming Xu. "Analysis of CO2 Emissions in China’s Manufacturing Industry Based on Extended Logarithmic Mean Division Index Decomposition." Sustainability 11, no. 1 (January 4, 2019): 226. http://dx.doi.org/10.3390/su11010226.
Abstract:
China is the world’s largest emitter of CO2. As the largest sector of China’s fossil energy consumption and carbon emissions, manufacturing plays an important role in achieving emission reduction targets in China. Using the extended logarithmic mean division index (LMDI) decomposition model, this paper decomposed the factors that affect the CO2 emissions of China’s manufacturing industry into eight effects. The results show the following: (1) China’s manufacturing CO2 emissions increased from 1.91 billion tons in 1995 to 6.25 billion tons in 2015, with an average annual growth rate of 6%. Ferrous metal smelting and rolling were the largest sources of carbon dioxide emissions, followed by chemical raw materials and products and then non-metallic minerals. (2) During the research period, the industrial activity effects were the most important factor leading to increased CO2 emissions in manufacturing and energy intensity was the most important factor in promoting the reduction of CO2 emissions from manufacturing. The investment intensity was the second most influential factor leading to the increase in China’s manufacturing CO2 emissions after the industrial scale and this even exceeded the industrial activity effect in some time periods (2000–2005). R&D efficiency and R&D intensity were shown to have significant roles in reducing CO2 emissions in China’s manufacturing industry. The input of R&D innovation factors is an effective way to achieve emission reductions in China’s manufacturing industry. (3) There were differences in the driving factors of CO2 emissions in the manufacturing industry in different periods that were closely related to the international and domestic economic development environment and the relevant policies of the Chinese government regarding energy conservation and emission reduction. (4) Sub-sector research found that the factors that affect the reduction of CO2 emissions in various industries appear to be differentiated. This paper has important policy significance to allow the Chinese government to implement effective energy-saving and emission reduction measures and to reduce CO2 emissions from the manufacturing industry.
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Zhou, Jin-Feng, Juan Wu, Wei Chen, and Dan Wu. "Carbon Emission Reduction Cost Assessment Using Multiregional Computable General Equilibrium Model: Guangdong–Hong Kong–Macao Greater Bay Area." Sustainability 14, no. 17 (August 29, 2022): 10756. http://dx.doi.org/10.3390/su141710756.
Abstract:
Carbon emissions reduction is an urgent global call to action, and for China, the nation with the largest carbon dioxide emissions, the task is especially arduous. For a country like China with many provinces and cities and unbalanced regional economic development, how to balance carbon emission reduction targets with economic development goals has become a social concern. Estimating the emission reduction costs of economic entities at all levels and reasonably allocating emission reduction tasks are the basic prerequisites for sustainable urban development. Based on an input–output (IO) table analysis of the socioeconomic data of Guangdong Province from 2017, this paper uses RAS and other data reconciliation methods to decompose various statistical data based on cities and industries. A multiregional IO table of nine cities in Guangdong Province in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is obtained, and a multiregional computable general equilibrium (CGE) model of Guangdong Province is established. Using this model, this paper explores city-level differences in carbon emissions reduction costs while accounting for differences in economic development under industry-wide coverage. A scientific basis for the allocation of urban carbon quotas is provided, which is particularly important for the sustainable development of cities. First, the carbon emissions reduction cost (carbon price) of each city is related to the intensity of emissions reduction and the present carbon intensity, both of which are affected by cities’ industrial and trade structures. Second, under neoclassical closure conditions, carbon emissions reduction is found to have less impact on the overall gross domestic product (GDP). At the industrial level, the high-carbon sectors are the most affected, whereas the low-carbon sectors are less affected. Notably, some industries become beneficiary sectors. Under Keynesian closure conditions, carbon emissions reduction has a greater impact on overall GDP, and all cities and industries are generally affected, especially those that are currently carbon- and trade-intensive. Third, to ensure the achievement of emissions reduction targets and minimize negative economic impacts, it is determined that the direct and opportunity costs of carbon emissions reduction must be fully considered when allocating carbon allowances, and optimal solutions should be derived from the combined perspective of fairness and efficiency.
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Wan, Lu, Yuling Mao, Yizhong Fu, and Xiya Wan. "The impact of intermediate product imports on industrial pollution emissions: Evidence from 30 industries in China." PLOS ONE 18, no. 10 (October 4, 2023): e0292347. http://dx.doi.org/10.1371/journal.pone.0292347.
Abstract:
Open and sustainable development is the theme that underpins a country’s high-quality economic development. This study uses GMM regression, mediation effect test to conduct empirical tests based on the panel data of China’s industrial sectors from 2003 to 2015 to analyze the internal mechanism of the impact of intermediate product imports on China’s industrial pollution emissions. The results show that (1) Intermediate product imports can significantly promote the emission reduction of industrial wastes, including wastewater, waste gas and solid waste. (2) Considering the differences in the level of pollution intensity, this paper classified the sample and found the impact is heterogeneous that for the heavily, moderately, lightly polluted industries, intermediate product imports have different negative impacts on their pollution emissions. (3) Intermediate products imports reduce industrial pollution emissions through import competition effect, variety effect and technology spillover effect, and all of them play a partial mediating role.
40
Yin, Chong, Yue Liu, and Yingxin Cui. "Virtual Carbon Flow in China’s Capital Economic Circle: A Multi-Regional Input–Output Approach." Sustainability 14, no. 18 (September 19, 2022): 11782. http://dx.doi.org/10.3390/su141811782.
Abstract:
The Capital Economic Circle (CEC) is the area with the largest economic aggregate in northern China and has a strong status in driving the economic development of China. However, the industrial structure dominated by high energy consuming industries leads to a large number of carbon dioxide emissions, and the imbalance between economic development and carbon emissions in CEC is serious; therefore, it is necessary to explore how to solve the carbon imbalance problem of the CEC by relying on interregional cooperation. Based on China’s multi-regional input–output tables of 2012, 2015 and 2017, this paper proposes the CEC carbon-extended, multi-regional input–output model to measure virtual carbon flow and analyze how the industrial structure leads to the imbalance of carbon flow distribution in CEC. Indicators such as direct carbon emission coefficients, complete carbon emission coefficients and carbon emissions pull coefficients of the industrial sectors in CEC are calculated and the physical carbon emission and virtual carbon flows among the industrial sectors and the regions are evaluated. The results show that there are potential constraints from the uncoordinated configuration of industrial innovation chains among the CEC, and the “carbon imbalance” of CEC is mainly reflected in the backward production technology of Hebei and its inefficient connection with the industrial innovation chain of Beijing and Tianjin. It is suggested that policymakers should promote the low-carbon production system and strengthen green energy development and utilization to enhance green development in CEC. In future research, we should pay attention to the updating method of the input–output table and the development of carbon circular networks. This study has implications for some areas of China and developing countries in Asia, which also have an imbalance between industrial economy development and carbon emissions, and a similarity in space structure and industry layout with CEC.
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Wu, Hui, and Yaodong Li. "Does the Emissions Trading System Promote Clean Development? A Re-Examination based on Micro-Enterprise Data." Sustainability 14, no. 24 (December 19, 2022): 17023. http://dx.doi.org/10.3390/su142417023.
Abstract:
In 2007, the SO2 emissions trading pilot policy was established to offer a framework for the management of the industrial environment. The evaluation of the effect of this policy on the industrial enterprise environment is expected to be of great importance for the development of the industrial economy. Our paper aimed to analyze the implementation effects and mechanisms of emissions trading systems using data collected from the China Industrial Enterprise Database and China Industrial Enterprise Pollution Discharge Database from 1998 to 2012. It was found that the policy decreased the emissions intensity of industrial enterprises; moreover, the emission reduction effect was most apparent in the eastern region, in non-state-owned enterprises, in large-scale enterprises, and in low-pollution industries. The findings of the intermediate effect test revealed that the emissions trading system positively affects the environment through the “innovation compensation” effect and “resource allocation” effects. Based on these findings, we make the following recommendations for policy: we should continue to comply with the improvement strategy of joining “market decision” with “government regulation”, actively encourage the construction of an emissions trading system, and guide industrial enterprises to fabricate a plan for working on environmental performance under the motivation of technological innovation.
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Wang, Haiqiao, Li Shang, Decai Tang, and Zhijiang Li. "Research Themes, Evolution Trends, and Future Challenges in China’s Carbon Emission Studies." Sustainability 16, no. 5 (March 1, 2024): 2080. http://dx.doi.org/10.3390/su16052080.
Abstract:
A profound analysis of China’s research achievements in the realm of carbon emissions holds the potential to furnish insightful references for analogous endeavors and inquiries in other nations. Employing the CiteSpace tool, this paper identifies five major focal points in Chinese scholars’ research on carbon emissions: carbon emission computation and prediction, influencing factors of carbon emissions, carbon footprint, carbon emission efficiency, and differential analysis of carbon emissions. Subsequently, this article systematically scrutinizes and dissects the outcomes of Chinese scholars’ endeavors in the aforementioned five focal points, culminating in recommending China’s forthcoming research on carbon emissions. (1) The research findings reveal a diversified evolution in the methods employed for calculating and predicting carbon emissions in China. However, due to the limited exploration of delineating carbon emission boundaries, instances of overlap and deviation in carbon emission quantification have emerged. (2) Factors influencing carbon emissions can be categorized into five major classes: economic, demographic, energy-related, policy-driven, and others. Yet, studies investigating industry-specific influencing factors remain relatively scarce. (3) Overcoming challenges associated with cross-boundary measurements, comprehensive effects, and policy applications is imperative in carbon footprint research. (4) Significantly disparate levels of carbon emission efficiency prevail across distinct regions or industries, with intricacies characterizing the influencing factors and a notable dearth of micro-level investigations. (5) The analysis of carbon emission differentials primarily encompasses regional disparities, industrial differentials, and temporal variations, lacking sustained tracking studies on the nuances of carbon emission disparities.
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Zhang, Kerong, Liangyu Jiang, Yanzhi Jin, and Wuyi Liu. "The Carbon Emission Characteristics and Reduction Potential in Developing Areas: Case Study from Anhui Province, China." International Journal of Environmental Research and Public Health 19, no. 24 (December 7, 2022): 16424. http://dx.doi.org/10.3390/ijerph192416424.
Abstract:
Global warming and world-wide climate change caused by increasing carbon emissions have attracted a widespread public attention, while anthropogenic activities account for most of these problems generated in the social economy. In order to comprehensively measure the levels of carbon emissions and carbon sinks in Anhui Province, the study adopted some specific carbon accounting methods to analyze and explore datasets from the following suggested five carbon emission sources of energy consumption, food consumption, cultivated land, ruminants and waste, and three carbon sink sources of forest, grassland and crops to compile the carbon emission inventory in Anhui Province. Based on the compiled carbon emission inventory, carbon emissions and carbon sink capacity were calculated from 2000 to 2019 in Anhui Province, China. Combined with ridge regression and scenario analysis, the STIRPAT model was used to evaluate and predict the regional carbon emission from 2020 to 2040 to explore the provincial low-carbon development pathways, and carbon emissions of various industrial sectors were systematically compared and analyzed. Results showed that carbon emissions increased rapidly from 2000 to 2019 and regional energy consumption was the primary source of carbon emissions in Anhui Province. There were significant differences found in the increasing carbon emissions among various industries. The consumption proportion of coal in the provincial energy consumption continued to decline, while the consumption of oil and electricity proceeded to increase. Furthermore, there were significant differences among different urban and rural energy structures, and the carbon emissions from waste incineration were increasing. Additionally, there is an inverted “U”-shape curve of correlation between carbon emission and economic development in line with the environmental Kuznets curve, whereas it indicated a “positive U”-shaped curve of correlation between carbon emission and urbanization rate. The local government should strengthen environmental governance, actively promote industrial transformation, and increase the proportion of clean energy in the energy production and consumption structures in Anhui Province. These also suggested a great potential of emission reduction with carbon sink in Anhui Province.
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Shi, Yalan, and Miaojing Yu. "Assessing the Environmental Impact and Cost of the Tourism-Induced CO2, NOx, SOx Emission in China." Sustainability 13, no. 2 (January 10, 2021): 604. http://dx.doi.org/10.3390/su13020604.
Abstract:
Tourism, as one economic activity, results in a full range of environmental impacts globally as well as in China. However, the evaluation of environmental impacts is insufficient because of the strong correlation effect between tourism and other industries. This study attempted to assess the environmental impact and cost of the tourism-induced pollutant emissions (in a broad sense) at the national scale through constructing the environmental-economic input-output model. Our results suggested that the China’s total emission of CO2, NOx, SOx related to tourism industry increased from 42 × 106 t, 162 kt, 345 kt in 1995 to 157 × 106 t, 527 kt, 854 kt in 2009. The indirect CO2, NOx, and SOx emissions of tourism and related industries were nearly 6.8–11 times of their direct emission in travel agency. Most of these indirect emissions (73% of CO2 in 2009, 54% of NOx in 1995, 62% of SOx in 2009) are derived from the energy plants and industrial sectors. The sustainable tourism should largely depend on the realization of sustainable mobility and transportation, through the low-emission behavior and energy-saving technology. The emission reduction cost of tourism industry in China was 30,170 and 172,812 million CNY in 1995 and 2009, accounting for nearly 14% of the total tourism revenue.
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Shi, Yalan, and Miaojing Yu. "Assessing the Environmental Impact and Cost of the Tourism-Induced CO2, NOx, SOx Emission in China." Sustainability 13, no. 2 (January 10, 2021): 604. http://dx.doi.org/10.3390/su13020604.
Abstract:
Tourism, as one economic activity, results in a full range of environmental impacts globally as well as in China. However, the evaluation of environmental impacts is insufficient because of the strong correlation effect between tourism and other industries. This study attempted to assess the environmental impact and cost of the tourism-induced pollutant emissions (in a broad sense) at the national scale through constructing the environmental-economic input-output model. Our results suggested that the China’s total emission of CO2, NOx, SOx related to tourism industry increased from 42 × 106 t, 162 kt, 345 kt in 1995 to 157 × 106 t, 527 kt, 854 kt in 2009. The indirect CO2, NOx, and SOx emissions of tourism and related industries were nearly 6.8–11 times of their direct emission in travel agency. Most of these indirect emissions (73% of CO2 in 2009, 54% of NOx in 1995, 62% of SOx in 2009) are derived from the energy plants and industrial sectors. The sustainable tourism should largely depend on the realization of sustainable mobility and transportation, through the low-emission behavior and energy-saving technology. The emission reduction cost of tourism industry in China was 30,170 and 172,812 million CNY in 1995 and 2009, accounting for nearly 14% of the total tourism revenue.
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Xiao, Sun Xi, and Lin Wu. "Carbon Emissions Measurement of Jiangsu Province Industrial Energy Consumption Based on LMDI Method." Advanced Materials Research 1010-1012 (August 2014): 1932–36. http://dx.doi.org/10.4028/www.scientific.net/amr.1010-1012.1932.
Abstract:
Energy consumption is the major source of industrial carbon emissions. Energy consumption carbon emission factor method and LMDI (Logarithmic Mean Divisia Index) method was used to analyze the carbon emission evolution of industrial economy energy consumption in Jiangsu Province with collected data on industrial energy consumption in 1995-2012. Results showed that Jiangsu province economic industrial carbon emissions keep increasing in 1995-2012 years. The results of carbon emission increase analysis of energy consumption structure effects, industrial energy consumption intensity effects and output scale effects in 1999-2012 showed that energy consumption intensity effect has the maximum contribution to carbon emissions in industrial carbon emissions Jiangsu Province. Therefore, the main way to control carbon emissions of industrial energy consumption in Jiangsu Province is reasonably control the growth of energy consumption.
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Bian, Yahui, Zhijiong Huang, Jiamin Ou, Zhuangmin Zhong, Yuanqian Xu, Zhiwei Zhang, Xiao Xiao, et al. "Evolution of anthropogenic air pollutant emissions in Guangdong Province, China, from 2006 to 2015." Atmospheric Chemistry and Physics 19, no. 18 (September 20, 2019): 11701–19. http://dx.doi.org/10.5194/acp-19-11701-2019.
Abstract:
Abstract. Guangdong Province (GD), one of the most prosperous and populous regions in China, still experiences haze events and growing ozone pollution in spite of the substantial air-quality improvement in recent years. Integrated control of fine particulate matter (PM2.5) and ozone in GD calls for a systematic review of historical emissions. In this study, emission trends, spatial variations, source-contribution variations, and reduction potentials of sulfur dioxide (SO2), nitrogen oxides (NOx), PM2.5, inhalable particles (PM10), carbon monoxide (CO), ammonia (NH3), and volatile organic compounds (VOCs) in GD from 2006 to 2015 were first examined using a dynamic methodology, taking into account economic development, technology penetration, and emission controls. The relative change rates of anthropogenic emissions in GD during 2006–2015 are −48 % for SO2, −0.5 % for NOx, −16 % for PM2.5, −22 % for PM10, 13 % for CO, 3 % for NH3, and 13 % for VOCs. The declines of SO2, NOx, PM2.5, and PM10 emissions in the whole province mainly resulted from the stringent emission control in the Pearl River delta (PRD) region, where most previous control measures were focused, especially on power plants (SO2 and NOx), industrial combustion (SO2, PM2.5, PM10), on-road mobile sources (NOx), and dust sources (PM2.5 and PM10). Emissions from other areas (non-PRD, NPRD), nevertheless, remain relatively stable due to the lax control measures and rapidly growing energy consumption. In addition, emission leaks of SO2 and NOx from industries are observed from PRD to NPRD in 2010 and 2011. As a result, emissions in NPRD are increasingly important in GD, particularly those from industrial combustion. The contribution of NPRD to the total SO2 emissions in GD, for example, increased from 27 % in 2006 to 48 % in 2015. On-road mobile sources and solvent use are the two key sources that should receive more effective control measures in GD. Current control-driven emission reductions from on-road mobile sources are neutralized by the substantial growth of the vehicle population, while VOC emissions in GD steadily increase due to the growth of solvent use and the absence of effective control measures. Besides, future work could focus on power plants and industrial combustion in GD and industrial process sources in NPRD, which still have large emission reduction potentials. The historical emission inventory developed in this study not only helps to understand the emission evolution in GD, but also provides robust data to quantify the impact of emission and meteorology variations on air quality and unveil the primary cause of significant air-quality change in GD in the recent decade.
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Shan, Wanyue, Shaobo Chen, Gang Wang, Jianhui Li, and Xin Bo. "Clearing the Air: Assessing the Effectiveness of Emission Policy in Qinhuangdao’s Key Industries." Atmosphere 14, no. 8 (July 28, 2023): 1218. http://dx.doi.org/10.3390/atmos14081218.
Abstract:
China has successively put forward ultra-low emission (ULE) transformation plans to reduce the air pollutant emissions of industrial pollutants since 2014. To assess the benefits of the ULE policy on regional air quality for Qinhuangdao, this study developed an emission inventory of nine atmospheric pollutants in 2016 and evaluated the effectiveness of the emission policy in Qinhuangdao’s key industries under different scenarios with an air quality model (CALPUFF). The emissions of air pollutants in 2016 were as follows: Sulfur dioxide (SO2) emitted 48.91 kt/year, nitrogen oxide (NOx) emitted 86.83 kt/year, volatile organic compounds (VOCs) emitted 52.69 kt/year, particulate matter (PM10 and PM2.5) emitted 302.01 and 116.85 kt/year, carbon monoxide (CO) emitted 1208.80 kt/year, ammonia (NH3) emitted 62.87 kt/year, black carbon (BC) emitted 3.79 kt/year, and organic carbon (OC) emitted 2.72 kt/year, respectively. The results showed that at the regional level in 2025, the iron and steel industry under the PPC (Peak Production Capacity) scenario had the highest potential for reducing SO2 and NOx emissions, while the cement industry under the PPC scenario excelled in reducing PM10 emissions. As for the industrial level in 2025, the flat glass industry under the ULE scenario would reduce the most SO2 emitted, while the iron and steel industry and the cement industry under the PPC scenario demonstrated the best reduction in NOx and PM10 emissions, respectively. Furthermore, the average annual contribution concentration of SO2, NOx, and PM10 in the air monitoring stations of Qinhuangdao under the PPC scenario was significantly lower than that under the BAU scenario revealed by air quality simulation. It can be concluded that the emission policy in Qinhuangdao will help improve the air quality. This study can provide scientific support for policymakers to implement the ULE policy in industrial undeveloped cities and tourist cities such as Qinhuangdao in the future.
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Guo, Rong, Xiaochen Wu, Tong Wu, and Chao Dai. "Spatial–Temporal Pattern Characteristics and Impact Factors of Carbon Emissions in Production–Living–Ecological Spaces in Heilongjiang Province, China." Land 12, no. 6 (May 30, 2023): 1153. http://dx.doi.org/10.3390/land12061153.
Abstract:
Under the threat of global climate change, China has proposed a dual carbon goal of peak carbon and carbon neutrality. As the vital carrier for territorial spatial planning, production–living–ecological (PLE) spaces drive carbon emissions and are important to the dual carbon goals. In this study, carbon emissions and sinks of PLE spaces in cities in Heilongjiang Province from 2005 to 2020 were calculated and spatial–temporal changes were analyzed. The carbon emission structure was analyzed in segmentation sectors. The land use changes and socioeconomic factors on carbon emissions were analyzed, and emission reduction strategies were implemented. The results show the following: (1) Carbon emissions from production and living spaces increased yearly. Carbon sinks were smaller than emissions, but capacity was stable. (2) Higher-emission cities were concentrated in southwest Heilongjiang, and carbon emission differences between regions gradually increased. (3) Among carbon emission sectors, agricultural and household made up smaller proportions, while animal husbandry, industrial, transportation, and traffic travel contributed most. Carbon emission structures were transformed by adjusting urban development and industrial structure. (4) For most cities, industrial space was the main emission space, but agricultural production and urban–rural living spaces dominated in some cities. (5) GDP, urbanization rate, and area of city paved roads suppressed emissions in cities with decreased carbon emission grades. The industrial structure and coal consumption inhibited emissions in cities with maintaining and increasing carbon emissions grades.
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Vestreng, V., G. Myhre, H. Fagerli, S. Reis, and L. Tarrasón. "Twenty-five years of continuous sulphur dioxide emission reduction in Europe." Atmospheric Chemistry and Physics Discussions 7, no. 2 (April 11, 2007): 5099–143. http://dx.doi.org/10.5194/acpd-7-5099-2007.
Abstract:
Abstract. During the last twenty-five years European emission data have been compiled and reported under the Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP) as part of the work under the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP). This paper presents emission trends of SO2 reported to EMEP and validated within the programme for the period 1980–2004. These European anthropogenic sulphur emissions have been steadily decreasing over the last twenty-five years, amounting from about 55 Tg SO2 in 1980 to 15 Tg SO2 in 2004. The uncertainty in sulphur emission estimates for individual countries and years are documented to range between 3% and 25%. The relative contribution of European emissions to global anthropogenic sulphur emissions has been halved during this period. Based on annual emission reports from European countries, three emission reduction regimes have been identified. The period 1980–1989 is characterized by low annual emission reductions (below 5% reduction per year and 20% for the whole period) and is dominated by emission reductions in Western Europe. The period 1990–1999 is characterised by high annual emission reductions (up to 11% reduction per year and 54% for the whole period), most pronounced in Central and Eastern Europe. The annual emission reductions in the period 2000–2004 are medium to low and reflect the unified Europe, with equally large reductions in both East and West. The sulphur emission reduction has been largest in the sector Combustion in energy and transformation industries, but substantial decreases are also seen in the Non-industrial combustion plants together with the sectors Industrial Combustion and Industrial Production Processes. The majority of European countries have reduced their emissions by more than 60% between 1990 and 2004, and one quarter have already achieved sulphur emission reductions higher than 80%. At European level, the total sulphur target for 2010 set in the Gothenburg Protocol (16 Tg) has apparently already been met by 2004. However, still half of the Parties to the Gothenburg Protocol have to reduce further their sulphur emissions in order to attain their individual country total emission targets for 2010. It is also noteworthy that, contrasting the Gothenburg Protocol requirements, a growing number of countries have recently been reporting increasing sulphur emissions, while others report only minor further decreases. The emission trends presented here are supported by different studies of air concentrations and depositions carried out within and outside the framework of the LRTAP Convention.