Influencing factors of carbon emissions in transportation industry based on CD function and LMDI decomposition model: China as an example

Globally, the transportation industry is one of the leading fields that generate the largest share of greenhouse gas emissions. While undergoing rapid development, countries worldwide aim to solve the problems involved in high energy consumption. Taking China as an example, this paper studies the main factors of carbon emissions in the transport sector and analyses the decoupling states between carbon emission and economic growth, making energy efficiency policies accordingly. In order to better demonstrate the dependence of the economy on the carbon emissions in China's transportation industry comprehensively, combined with the CD production function, this paper develops the decomposition and decoupling technology based on the LMDI approach. Additionally, it quantifies seven effects: energy emission intensity effect, energy structure effect, energy intensity effect, transportation intensity effect, technology state effect, labor input effect and capital input effect. The results show three major points: (1) From 2001 to 2018, the cumulative carbon emissions of China's transportation industry increased by 633.46 million tons, in which the capital input effect is the key factor driving carbon emissions, accounting for 157.70% of the total cumulative increased emissions, followed by energy structure effect at 10.39%. The labor input effect accounted for the smallest proportion at 2.26%. In this case, the technology state effect is the primary factor in restraining carbon emissions. During the study period, it reduced carbon emissions by 292.27 million tons, accounting for 46.14%. To a certain extent, energy intensity effect, transportation intensity effect and energy emission intensity inhibited carbon emissions, representing 16.67%, 5.32% and 2.22%, respectively. (2) During the research period, two decoupling states existed between carbon emissions and economic growth in China's transportation industry, specifically weak decoupling and expansive coupling. (3) The analysis of decomposition and decoupling state of influencing factors of carbon emissions shows that, on the one hand, factors promoting carbon emissions (capital input effect, energy structure effect and labor input effect) hinder the decoupling process. On the other hand, factors restraining carbon emissions (technology state effect, transportation intensity effect, energy intensity effect and energy emission intensity effect) accelerate the decoupling process. The research findings provide a new perspective for achieving carbon emission reduction in the transportation industry and curbing energy consumption growth.     

Assessing the impact of environmental regulation on pollution abatement and collaborative emissions reduction: Micro-evidence from Chinese industrial enterprises

Given the rapid industrialization and urbanization of China, environmental problems have gradually become major constraints that hinder its sustainable economic development. Moreover, China's pollution abatement and reduction of greenhouse gas emissions have been severely affected by pressures coming from domestic environmental appeals and international environmental diplomacy. By using integrated data from the Chinese Industrial Enterprise and the Chinese Enterprise Environmental Survey and Reporting databases, this study constructs comprehensive indicators of pollutant discharge intensity and carbon emissions index at the enterprise level and uses the panel fixed effect model, Kaya identity, and mediation effect model to assess the effects of environmental regulations on pollution abatement and collaborative emissions reduction from the micro-perspective. Results show that these regulations can abate the pollution emissions of Chinese industrial enterprises and verify the effectiveness of environmental policies. These regulations can also efficiently reduce the carbon dioxide emissions of enterprises through pollution abatement. In other words, environmental regulations facilitate a collaborative emissions reduction of pollutant and greenhouse gas emissions from enterprises. Such collaborative emissions reduction effect is also influenced by the energy structure and consumption of enterprises. This paper presents empirical evidence and policy basis for further improving China's environmental regulation policy system and achieving coordinated progress in China's economic development and environmental governance.     

Agricultural trade shocks and carbon leakage: Evidence from China's trade shocks to the Belt & Road economies

Existing literature on carbon leakage mostly focused on polluting industries or at the national level. Agriculture is one of the main sources of carbon emissions, however, research on agricultural carbon leakage is still insufficient. To fill this gap, this paper investigates the impact of China's agricultural trade shocks on carbon emissions in a panel of 62 economies along the Belt and Road (B&R) over the period 1990–2017. The results show that China's supply shocks have a significant inhibitory effect on the agricultural carbon emissions of the B&R economies, and this inhibitory effect is very stable and will not be disturbed by other factors. On the contrary, China's demand shocks only have a significant inhibitory effect on the carbon emission intensity of economies with a higher proportion of agriculture, but it will significantly increase the agricultural carbon emissions share in all economies.     

Assessing the impact of emissions trading scheme on low-carbon technological innovation: Evidence from China

A global consensus on carbon emission reductions has been reached for combating climate change. The Chinese government has clearly stated that it is necessary to make full use of market means to improve the level of environmental governance. Emissions trading scheme (ETS) is a typical market means to accelerate low-carbon economic transition. Low-carbon technological innovation is one of the key factors affecting carbon emissions. However, literature on the relationship between ETS and low-carbon technological innovation is relatively scarce at present. This study assesses the effect of pilot ETSs on low-carbon technological innovation, and a difference in differences (DID) model is adopted to analyze China's provincial panel data from 2003 to 2017. The results indicate that China's pilot ETSs can significantly promote low-carbon technological innovation, and changing the window period, PSM-DID and placebo test all verify the robustness of this finding. The dynamic effect test reveals that China's pilot ETSs will gradually increase the effect on low-carbon technological innovation over time. The heterogeneity analysis shows that the effect of China's pilot ETSs on low-carbon technological innovation is more obvious in Guangdong, Hubei, Tianjin and Chongqing. The mechanism analysis suggests that marketization degree and green consumption concept can positively moderate the impact of China's pilot ETSs on low-carbon technological innovation, and industrial structure upgrading plays a positive mediating role between China's pilot ETSs and low-carbon technological innovation. This study is conducive to assessing the policy effectiveness of China's pilot ETSs and provides an empirical evidence for promoting the development of the carbon emissions trading market.     

Can buildings sector achieve the carbon mitigation ambitious goal: Case study for a low-carbon demonstration city in China?

China is committed to peaking its carbon emissions by 2030 and become a carbon-neutral society by 2060. The building sector that accounts for over one-third of the total carbon emissions is expected to face a great challenge in helping China achieve this goal. Shenzhen, as a low-carbon pilot city, whether its low-carbon work of urban buildings reaches the target is crucial. An attempt has been made in this study to assess the intensity of carbon emissions and associated reduction efficiency of urban buildings (operation stage) in Shenzhen by using the life cycle assessment method. The results show that the total carbon emissions generated from the buildings' operation stage have increased from 22 million metric tons (Mt) CO₂eq in 2005 to 42 (±13%) Mt. CO₂eq in 2019. Carbon emissions mainly result from the buildings' electricity use (79%), followed by refrigerant release emissions (12%). The energy conservation and carbon emissions reduction intensity in Shenzhen is at the middle level in China, and there is considerable space for improvement. According to scenario-based analysis, the carbon emission of the buildings sector can probably reach its peak by 2025 with the implementation of suitable policies – 5 years earlier than national target by 2030. Overall, this study makes a systemic analysis of the characteristics of urban buildings energy consumption and carbon emissions reduction, which can provide supportings for justifying the effectiveness of low-carbon activities in Shenzhen and beyond.     

Energy-related carbon emissions mitigation potential for the construction sector in China

China is undertaking a huge number of building and infrastructure projects. As a large consumer of energy-intensive building material, the construction activities provoke large direct carbon emissions in upstream industrial sectors (i.e. embodied carbon emissions). This paper aims to explore how construction-related climate policies could contribute to future national carbon emission mitigation efforts by employing a demand-side input-output model and scenario analysis. First, a hypothetical extraction approach is used to estimate the overall carbon emissions induced by the construction sector in the base year. Then scenario analysis is conducted to quantify the sector's technical potential for carbon mitigation in 2030 and 2050. We find that implementing construction-related climate measures in China could mitigate 2.5 Gt construction-induced CO2 in 2030, and 6.4 Gt in 2050 — more than Europe's annual total carbon emissions in 2015. More efficient electricity use could make a substantial contribution in the short-term. However, material-related initiatives, especially those focused on metal recycling, could yield significant carbon mitigation from 2030 onwards. Our findings suggest China to optimize the relationship between urbanization and construction to comply with the country's climate commitments better. Mechanisms to reform supply-side incentives, such as mandatory carbon labelling for construction material throughout the supply chain, could offer immediate benefits.     

Estimating transportation carbon efficiency (TCE) across the Belt and Road Initiative countries: An integrated approach of modified three-stage epsilon-based measurement model

Transportation systems are vital links for intercountry. However, the transportation industry is associated with high energy consumption and carbon emissions. In this paper, the transportation carbon efficiency (TCE) across the Belt and Road Initiative (BRI) countries during 2005–2017 is estimated by modifying a three-stage epsilon-based measurement model, and the carbon emission reduction potential (CERP) is identified. Based on the results, countries are classified into four categories by comparing a country's TCE and CERP with the average of all BRI countries. The results show that the average TCE of BRI countries is only 0.341, while their average CERP is 0.750, which is tremendous. It also shows that the higher the income levels, the more prone countries are to have a higher TCE. By considering the differences among the countries' environmental factors, TCEs, and the current state or trends of the CERPs, customized low-carbon policies are proposed to increase the TCE and reduce emissions.     

Global warming implications of facade parameters: A life cycle assessment of residential buildings in Bahrain

On a global scale, the Gulf Corporation Council Countries (GCCC), including Bahrain, are amongst the top countries in terms of carbon dioxide emissions per capita. Building authority in Bahrain has set a target of 40% reduction of electricity consumption and associated CO₂ emissions to be achieved by using facade parameters. This work evaluates how the life cycle CO₂ emissions of buildings are affected by facade parameters. The main focus is placed on direct and indirect CO₂ emissions from three contributors, namely, chemical reactions during production processes (Pco₂), embodied energy (Eco₂) and operational energy (OPco₂). By means of the life cycle assessment (LCA) methodology, it has been possible to show that the greatest environmental impact occurs during the operational phase (80–90%). However, embodied CO₂ emissions are an important factor that needs to be brought into the systems used for appraisal of projects, and hence into the design decisions made in developing projects. The assessment shows that masonry blocks are responsible for 70–90% of the total CO₂ emissions of facade construction, mainly due to their physical characteristics. The highest Pco₂ emissions factors are those of window elements, particularly aluminium frames. However, their contribution of CO₂ emissions depends largely on the number and size of windows. Each square metre of glazing is able to increase the total CO₂ emissions by almost 30% when compared with the same areas of opaque walls. The use of autoclaved aerated concrete (AAC) walls reduces the total life cycle CO₂ emissions by almost 5.2% when compared with ordinary walls, while the use of thermal insulation with concrete wall reduces CO₂ emissions by 1.2%. The outcome of this work offers to the building industry a reliable indicator of the environmental impact of residential facade parameters.     

Does the high–tech industry consistently reduce CO2 emissions? Results from nonparametric additive regression model

China is currently the world's largest carbon dioxide (CO₂) emitter. Moreover, total energy consumption and CO₂ emissions in China will continue to increase due to the rapid growth of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO₂ emissions at the moment or in the future. However, ignoring the existing nonlinear links between economic variables, most scholars use traditional linear models to explore the impact of the high–tech industry on CO₂ emissions from an aggregate perspective. Few studies have focused on nonlinear relationships and regional differences in China. Based on panel data of 1998–2014, this study uses the nonparametric additive regression model to explore the nonlinear effect of the high–tech industry from a regional perspective. The estimated results show that the residual sum of squares (SSR) of the nonparametric additive regression model in the eastern, central and western regions are 0.693, 0.054 and 0.085 respectively, which are much less those that of the traditional linear regression model (3.158, 4.227 and 7.196). This verifies that the nonparametric additive regression model has a better fitting effect. Specifically, the high–tech industry produces an inverted “U–shaped” nonlinear impact on CO₂ emissions in the eastern region, but a positive “U–shaped” nonlinear effect in the central and western regions. Therefore, the nonlinear impact of the high–tech industry on CO₂ emissions in the three regions should be given adequate attention in developing effective abatement policies.     

Environmental assessment and investment strategies of provincial industrial sector in China — Analysis based on DEA model

As an energy-intensive industry, the industrial sector consumes 70% of energy consumption and causes serious environmental pollution in China. Also, the government emphasized the promotion of R&D investment in the industrial sector in China's National Plan on Climate Change (2014–2020). It is meaningful and contributes to assessing energy and environmental performance, as well as R&D and industrial pollution control (IPC) investment strategies of China's industrial sector. A non-radial DEA model, as with natural and managerial disposability, was adopted to evaluate this from provincial and regional perspectives during the 2008–2012 period. Energy and environmental performance was evaluated by unified efficiency under natural disposability (UEN), unified efficiency under managerial disposability (UEM), and unified efficiency under natural and managerial disposability (UENM). The empirical results indicated that Shandong and Hainan were efficient under natural and managerial disposability, while other provinces had the potential to improve their energy and environmental performance. The number of provinces that was fit for investments of R&D and IPC increased from 2008 to 2010, then decreased in 2011 and 2012. In spite of this, many provincial industrial sectors should make efforts to reduce pollution by investment on technology. Tianjin, Heilongjiang, Jiangxi and Henan were especially the best investment objects because investments of R&D and IPC turned to be effective for them during the whole study period. Moreover, western China had the highest average UENM, followed by eastern China and central China. Eastern China and central China were rewarding to expand investments. Coal consumption was the main factor to negatively affect unified efficiency whereas the increase in economic development level was primarily responsible for the improvement of unified efficiency. According to the results, differentiated suggestions to further improve energy and environmental performance were proposed.     

An Integrated Multicriteria Decision Analysis System for Reducing Air Emissions from Mining Process

The selection of a best alternative method to minimize air pollution and energy consumption for mine sites is a critical task because it encompasses evaluation of different techniques. The aim of this paper is to select most suitable technology for mining system which helps in reducing air pollution and carbon footprints by implementing the multicriteria decision analysis (MCDA) method. The existing methods or frameworks in the mining sector, which have been used in the past to select the sustainable solution, are lacking aid of MCDA, and there is a need to contribute more in this field with a promising decision system. The MCDA method is applied as a probabilistic integrated approach for a mine site in Canada. The analysis involves processing inputs to the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method which assists in identifying the alternatives, defining the criteria, and thus outranking of the final choice. Moreover, criteria weighting has been determined using analytical hierarchical process (AHP) method. Three categories: reduction of dust/fugitive emission control strategies, reduction in fuel consumption to minimize carbon footprint, and cyanide destruction methods are selected. The probability distributions of criteria weights and output flows are defined by performing uncertainty analysis using the Monte Carlo simulation (MCS). The sensitivity analysis is conducted using Spearman’s rank correlation method and walking criteria weights. The results indicate that the integrated framework provides a reliable way of selecting air pollution control solutions and help in quantifying the impact of different criteria for the selected alternatives.

     

Meat,Dairy and Climate Change: Assessing the Long-Term Mitigation Potential of Alternative Agri-Food Consumption Patterns in Canada

We use a newly developed model of the entire Canadian energy system (TIMES-Canada) to assess the climate change mitigation potential of different agri-food consumption patterns in Canada. For this, our model has been extended by disaggregating the agricultural demand sector into individual agri-food demands to allow for a more in-depth analysis. Besides a business-as-usual (baseline) scenario, we have constructed four different agri-food scenarios to assess the viability of reducing Canadian meat and dairy consumption in order to diminish Canada’s agricultural sector energy consumption and greenhouse gas (GHG) emissions. Our policy scenarios progressively restrict the consumption of different meat and dairy agricultural products until the year 2030. Our results suggest that the implementation of a meat and dairy consumption reduction policy would lead to a 10 to 40 % reduction in agricultural GHG emissions, depending on the severity of the scenario. This translates to a 1 to 3 % decrease in total Canadian GHG emissions by the year 2030. Besides these environmental benefits, health benefits associated with a reduction in meat and dairy consumption (as inferred from other studies) are presented as an additional source of motivation for implementing such a policy in Canada.     

Examining the uncertainty of carbon emission changes: A systematic approach based on peak simulation and resilience assessment

Efforts to achieve carbon peak is one of the Chinese government's commitments, but the diversity of future development paths leads to the uncertainty of carbon emissions. Based on the carbon peak simulation, this study develops a framework to assess the carbon emission uncertainty, aiming to explore the potential low-carbon paths. The STIRPAT model is firstly introduced to explore the influence of population, economic and technology factors on carbon emissions, which is followed by emission peaks simulation. The resilience theory is then introduced to define the concept of low-carbon resilience (LCR), which refers to the ability to maintain a low level of carbon emissions. The uncertainty of carbon emission changes between different scenarios is identified by considering peaking time, cumulative increase and mitigation process. This study taking 10 Chinese coastal provinces as an example, and results show that all provinces can achieve the target of carbon emission peak in low-emissions scenario, the cumulative growth of carbon emissions is low and can be mitigated over a relatively short term, showing a strong LCR. In high-emissions scenario, Liaoning, Tianjin, Fujian and Guangxi may not have a peak before 2050, the uncertainty of carbon emission changes is relatively high, while Hebei, Jiangsu, Shanghai and Guangdong show relatively low uncertainty for the clear peaking time. The study also designs intermediate scenario to reduce the uncertainty of carbon emission changes to provide reference for each province's emission reduction path. These findings help to understand carbon uncertainty to reduce the risk of increasing cumulative emissions under the scenario of only focusing on peaking times, and provide a basis for future carbon resilience and sustainable emission reduction policies.     

大连市夏季近地面臭氧污染数值模拟和控制对策研究

通过区域空气质量模型CAMx对大连市2015年8月近地面臭氧(O_3)污染进行模拟,探讨了O_3及其生成前体物(NOx和VOCs)的来源,O_3生成控制区,并根据敏感性分析结果对前体物排放的控制效果进行了定量评估。结果表明:本地NOx排放对大连地区的NOx浓度贡献占90%以上,本地VOCs排放对大连地区的VOCs浓度贡献占80%以上,而本地NOx和VOCs排放对大连地区O_3浓度贡献仅占29%;大连市整体上为VOCs控制区,控制VOCs能有效降低O_3污染,还能有效削减O_3的峰值浓度;通过敏感性分析结果计算得出,削减大连本地工业源VOCs和民用源VOCs能够有效降低大连地区O_3浓度,削减10%的工业源VOCs能使市区O_3平均浓度降低2%左右,削减10%的民用源VOCs能使大连市区平均O_3浓度降低1%左右。建议NOx与VOCs削减比例为1∶2,对大连市O_3和PM2.5污染进行协同控制。     

中国水泥行业2011—2022年二氧化碳和大气污染物排放分析

2011—2021年,熟料产量呈波动上升趋势。水泥行业整体生产运行水平不断提高,熟料单条生产线平均规模由43.8万t/条提升至115.3万t/条,熟料单位产品综合能耗下降14.4%,熟料单位产品CO₂排放强度下降6.3%,但CO₂排放总量增加了13.8%,与氮氧化物减排趋势形成较大反差,碳污治理水平差距明显。熟料生产中石灰石分解和煤炭燃烧过程的CO₂排放合计占比为92.9%~93.8%,是CO₂排放的主要来源。由于熟料系数偏高、非碳酸盐原料替代不足、综合能耗仍然较高等原因,安徽等7个熟料产量大的省份的CO₂排放强度高于全国。建议实行碳酸盐熟料产量总量控制,逐步降低熟料应用比例,加快建材市场熟料产品和非碳酸盐原料替代,降低高标号水泥使用比例。应大力推广水泥行业节能降耗增效技术,加快熟料落后产能淘汰。对熟料产量大、碳排放强度高的地区,应结合当地碳排放特点,实行差别化降碳策略。各大气污染防治重点区域应因地施策推进水泥行业减污降碳工作。     

System Dynamics Modeling and Policy Simulation for Urban Traffic: a Case Study in Beijing

This paper constructs a system dynamics model for simulating the impact of different strategies on urban traffic’s energy consumption and carbon emissions. Based on a case study in Beijing, the model includes three subsystems: (1) urban traffic, (2) population and economy, and (3) energy consumption and carbon emissions. First, the model is used to decompose the impact of different vehicles on energy consumption and carbon emissions. Decomposition results show that private cars have the most significant impact on urban traffic’s energy consumption and carbon emissions; however, total vehicle kilometers traveled by private cars are the smallest among four trip modes. Then, the model is used to simulate different urban traffic policies. Policies are categorized as follows: (a) driving restrictions on vehicle registration numbers, (b) a scheme for vehicle registrations via a lottery system, and (c) development of public transportation infrastructures. Scenario simulation results show that all those measures can reduce energy consumption and carbon emissions. Though the last strategy (c) contains several delays, its effect is more stable and far-reaching. Finally, some recommendations about easing traffic pressure and reducing traffic emissions are given.     

新疆准东经济技术开发区二氧化碳排放现状与降碳对策研究

通过分析新疆准东经济技术开发区各行业的二氧化碳排放量及排放特征,研究新疆准东经济技术开发区碳达峰碳中和的实现路径。分析结果显示,准东经济技术开发区最主要的二氧化碳排放源是化石燃料燃烧,其对二氧化碳排放量的贡献比例在95.2%以上。能源活动二氧化碳排放量占总排放量的98.5%以上;工业生产过程排放的二氧化碳较少,占比在1.5%以下。新疆准东经济技术开发区主要二氧化碳排放行业是煤电、电解铝、煤化工、硅基新材料。在此基础上,结合各行业特点,提出发展园区循环经济、制定低碳行业标准和培育低碳产业等详细对策。     

电力跨区域调配隐含的污染转移效应

为研究中国30个省/自治区/直辖市之间电力区域调配的污染物转移效应,构建了电力传输的污染转移模型,并以SO_2和NO_x为例对2006、2015年数据进行测算。结果表明,2015年电力行业SO_2、NO_x排放强度分别由2006年的4.03、2.18 g/(kW·h)下降到0.69、0.77 g/(kW·h)。2015年,16个电力净输入区通过电力跨区域传输的SO_2、NO_x转移量分别为47.8×10~4、53.0×10~4t,占这些地区电力行业SO_2、NO_x排放量的24.1%、24.2%;14个电力净输出区通过电力跨区域传输的SO_2、NO_x转移量分别为-54.6×10~4、-52.1×10~4t,占这些地区电力行业SO_2、NO_x排放量的26.5%、22.8%。研究结果对于分析区域物质流动所隐含的污染流动,全面认识区域污染物排放格局,制定合理的区域污染减排目标具有一定借鉴意义。     

Using E-PRTR data on point source emissions to air and water—First steps towards a national chemical footprint

There is a great need for indicators to monitor the use and potential impacts of hazardous chemicals. Today there is a huge lack of data, methods and results and method development and studies should be given urgent priority. The aim of this paper was to develop and test an approach to calculate the potential environmental impacts of chemicals for a whole country using the E-PRTR (European Pollutant Release and Transfer Register) as a database and Sweden as an example. Swedish data from 2008 on emissions to air and water for 54 substances from point sources were retrieved from an open database. The data were transformed and aggregated using USEtox, a life-cycle impact assessment (LCIA) method for calculating potential human toxicity and ecotoxicity, both from industrial emissions directly and after input–output analysis (IO analysis) to reallocate emissions to product categories. Zinc to air and water contributed most to human toxicity followed by mercury to air. The largest contribution by industry to potential human toxicity came from the metal industry, followed by the paper and paper product industry. For potential ecotoxicity, zinc, fluoranthene and copper contributed the most. The largest contributions by industry came from the paper and paper products manufacturing sector, followed by the basic metals manufacturing sector. The approach used here can be seen as the first step towards a chemical footprint for nations. By adding data from other countries and other sources, a more complete picture can be gained in line with other footprint calculations. Furthermore, diffuse emissions from, for example, transport or emissions of pesticides could also be added for a more holistic assessment. Since the area of chemicals is complicated, it is probably necessary to develop and use several indicators that complement each other. It is suggested that the approach outlined here could be useful in developing a method for establishing a national chemical footprint.     

Comparative life cycle assessments: The case of paper and digital media

The consumption of the written word is changing, as media transitions from paper products to digital alternatives. We reviewed the life cycle assessment (LCA) research literature that compared the environmental footprint of digital and paper media. To validate the role of context in influencing LCA results, we assessed LCAs that did not compare paper and print, but focused on a product or component that is part of the Information and Communication Technology (ICT) sector. Using a framework that identifies problems in LCA conduct, we assessed whether the comparative LCAs were accurate expressions of the environmental footprints of paper and print. We hypothesized that the differences between the product systems that produce paper and digital media weaken LCA's ability to compare environmental footprints. We also hypothesized that the characteristics of ICT as an industrial sector weaken LCA as an environmental assessment methodology. We found that existing comparative LCAs offered problematic comparisons of paper and digital media for two reasons — the stark material differences between ICT products and paper products, and the unique characteristics of the ICT sector. We suggested that the context of the ICT sector, best captured by the concept of “Moore's Law”, will continuously impede the ability of the LCA methodology to measure ICT products.