Driving forces analysis of energy-related carbon dioxide (CO 2 ) emissions in Beijing: an input–output structural decomposition analysis

Wei, Jing; Huang, Kai; Yang, Shenmiao; Li, Yan; Hu, Tingting; Zhang, Yue

doi:10.1016/j.jclepro.2016.05.086

Cited by 156 publications

(54 citation statements)

References 39 publications

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“…These drivers include gross domestic product (GDP) growth, energy efficiency, carbon efficiency, production structure, consumption structure, and population (Minx et al, 2009). China's carbon emission drivers have been quantified 4 using this method (Su and Ang, 2012;Wei et al, 2016). Guan et al (2008) (Su and Ang, 2011;Weber and Matthews, 2007;Wiedmann, 2009).…”

Section: Introductionmentioning

confidence: 99%

Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030

Wei

Wang

et al. 2017

Journal of Cleaner Production

372

116

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Abstract:China is the largest emitter of carbon emissions in the world. In this paper, we present an Integrated Model of Economy and Climate (IMEC), an optimization model based on the input-output model. The model is designed to assess the tradeoff between emission deceleration and economic growth. Given that China's projected average growth rate will exceed 5% over the next two decades, we find that China may reach its peak CO2 emissions levels by 2026. According to this scenario, China's carbon emissions will peak at 11.20 Gt in 2026 and will then decline to 10.84 Gt in 2030.Accordingly, approximately 22 Gt of CO2 will be removed from 2015 to 2035 relative to the scenario wherein China's CO2 emissions peak in 2030. While this earlier peaking of carbon emissions will result in a decline in China's GDP, several sectors, such as Machinery and Education, will benefit. In order to reach peak CO2 emissions by 2026, China needs to reduce its annual GDP growth rate to less than 4.5% by 2030 and decrease energy and carbon intensity levels by 43% and 45%, respectively, from 2015 to 2030.

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Section: Introductionmentioning

confidence: 99%

Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030

Wei

Wang

et al. 2017

Journal of Cleaner Production

372

116

View full text Add to dashboard Cite

show abstract

“…As far as the influencing factors are concerned, resource endowment, investment intensity, industrial structure, market factors, technological effects, industrial policies and other factors have an impact on the production and development of the high-carbon manufacturing industry [17][18][19][20][21][22][23][24] and cause the regional lock-in of carbon emissions from different aspects. In the early stage of the economic development of the high-carbon manufacturing industry, due to industry attribute factors, the areas with abundant mineral resources lead to a higher return rate on capital and the increasing return on scale makes the capital continuously concentrate to the areas with higher resource endowment levels, which leads to the continuous expansion of production scale.…”

Section: Carbonmentioning

confidence: 99%

Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

et al. 2020

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There are industry lock-in and regional lock-in phenomena in China's manufacturing industry carbon emissions. However, the existing researches often focus on global carbon emissions, which is not adverse to finding the main problems of manufacturing industry carbon emissions. The biggest contributions of this study are the identification of the industry lock-in and regional lock-in of China's manufacturing industry and the finding of the regional factors that affect the carbon lock-in of the manufacturing industry, which points out the direction for the low-carbon transformation of the local manufacturing industry. This paper is based on the IPCC (Intergovernmental Panel on Climate Change) carbon emissions coefficient method and energy consumption data from 2000 to 2016 to count the manufacturing industry carbon emissions of 30 provinces in China (except Hong Kong, Macao, Taiwan and Tibet). On this basis, the paper uses a spatial-temporal geographical weighted regression (GTWR) model to analysis the regional influencing factors of the high-carbon manufacturing industry. Results demonstrate that China's high-carbon manufacturing industry mainly concentrates on the ferrous metal processing industry, non-metallic mineral manufacturing industry and other sectors. In addition, the carbon emissions of high-carbon manufacturing industries are mainly concentrated in Bohai Bay and the North China Plain. The industrial structure and economic scale are the main reasons for the regional carbon lock-in of the high-carbon manufacturing industry, and the strength of the lock-in has continued to increase. Resource endowment is a stable factor of carbon lock-in in high-carbon regions. Technological progress helps to unlock carbon, while foreign direct investment results in the enhancement of carbon regional lock-in. This study focuses on the regional factors of carbon lock-in in the manufacturing industry, hoping to provide decision support for the green development of China's manufacturing industry.

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“…Xu (2015) [36] used logarithmic mean Divisia index decomposition method to analyze the driving factors in water footprint from 1978 to 2012, and found that Beijing should improve water saving technology and adjust plantation structure, especially for agriculture. Yin (2014) [37] calculated eco-efficiency using a DEA model to measure urban sustainable development and found that Beijing was among the top three most eco-efficient cities, and Wei (2016) [38] showed that the impacts of pollution-climate environment, mainly from carbon dioxide, have drastically increased, thus negatively affecting the sustainability of Beijing according to an energy-related CO 2 emission of environmental impact assessment model. These studies assumed that Beijing is an area that showed different problem in different aspects.…”

Section: Study Areamentioning

confidence: 99%

An Empirical Study of the Assessment of Green Development in Beijing, China: Considering Resource Depletion, Environmental Damage and Ecological Benefits Simultaneously

et al. 2018

Sustainability

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Urban green development (UGD) is a highly topical issue. To assess the degree of UGD, in this paper, we use the driving forces, pressures, states, impacts, and responses (DPSIR) model to evaluate UGD with a collection of 40 indicators based on the three aspects of resource depletion, environmental damage and ecological benefits. The established system of indicators is then applied to evaluate the UGD in Beijing from 2000 to 2014 as a case study. The results demonstrate that it is essential to analyze the trend in the change in resource depletion, which had a high weight of 0.556 because environmental damage and ecological benefits partly changed in response to this driving force and pressure. However, the UGD index value of environmental damage (positive index) has decreased since 2010. By ranking the degree of correlation among indicators, it can be seen that UGD is highly related to the lifestyle, status quo, technology and education, industrialization, environmental quality, and ecological environment of a city. The health situation in Beijing has improved in the past 15 years; it was determined to be very unhealthy (75% at the very unhealthy level (V) and 9% at the very healthy level (I)) in 2000 but very healthy (8% at the very unhealthy level (V) and 60% at the very healthy level (I)) in 2014. However, there are internal problems due to imbalanced development in Beijing related to aspects such as the ecological environment, population and economy, social life, investment management, energy consumption and urban infrastructure. And government should adjust the energy structure, formulate detailed plans and policies on urban environment, and increase investment in education and business development.

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Driving forces analysis of energy-related carbon dioxide (CO 2 ) emissions in Beijing: an input–output structural decomposition analysis

Cited by 156 publications

References 39 publications

Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030

Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030

Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

An Empirical Study of the Assessment of Green Development in Beijing, China: Considering Resource Depletion, Environmental Damage and Ecological Benefits Simultaneously

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