Emission Reduction Path Research Articles

Driving factors and key emission reduction paths of Xinjiang industries carbon emissions: An industry chain perspective

As a typical resource-based region, Xinjiang is under increasing pressure to reduce carbon emissions. The ability to identify the drivers of carbon emissions in the industry and mapping out key emission reduction paths are core components of achieving carbon emission reduction in Xinjiang. This research incorporates energy and environmental factors, constructs a hybrid input–output model of “energy-environment-economy,” and uses the environmental input–output structural decomposition (EIO-SDA) and structural path decomposition (SPD) methods to analyze the drivers of carbon emissions from energy consumption and key emission reduction paths in Xinjiang. First, it shows that the economic-scale effect and the energy-intensity effect are the biggest facilitators of carbon emissions and most significant barriers to carbon emission reduction in Xinjiang. Second, capital formation and domestic trade are the primary sources of demand driving changes in carbon emissions in Xinjiang. Third, sectors involving the production and supply of electricity and heat, such as heavy manufacturing and energy industries, including petroleum processing, coking, nuclear, fuel processing, and chemical industries, are the key sectors responsible for carbon emission reduction in Xinjiang. Last, in terms of industry chains, “metal smelting and rolling processing industry/non-metallic mineral products industry—construction industry—fixed capital formation” and “oil and gas extraction industry (S20)—(intermediate sector)—final demand” are the most important paths driving the growth and decline of carbon dioxide (CO2) emissions from Xinjiang industries, respectively. To promote Xinjiang's carbon emission reduction targets, the Xinjiang government should actively improve its energy structure, promote a change in demand growth patterns, and formulate comprehensive management policies for high-carbon-transfer industries according to an industry chain perspective.

Urbanization Influences CO2 Emissions in the Pearl River Delta: A Perspective of the “Space of Flows”

As the largest carbon emitter in the world, China is facing increasing challenge to reduce CO2 emissions. Given this issue, exploring the influencing factors is of great significance for scientific low-carbon emission policymaking. Although previous literature has explored the effects of urbanization on CO2 emissions, the impact of the space of flow on urban carbon emissions have been less explored. Due to the increasing connection between cities, its impact on urban carbon emissions cannot be ignored. Thus, this paper takes the space of flows into account as an aspect of urbanization to supplement the existing literature and empirically examines the multiple effects of urbanization on CO2 emissions in the Pearl River Delta (PRD) urban agglomeration. By using a STIRPAT model, statistical data, and web crawler data, we examined impacts of different types of urbanization on CO2 emissions. Our empirical results show that: (1) Within the PRD urban agglomeration, urban linkage intensity is strongly connected to urban socioeconomic growth, establishing a geographical structure with Guangzhou and Shenzhen as the double core. (2) Our results show that urbanization exerts two opposite effects on CO2 emissions: positively connects carbon emissions with population urbanization, integrated urban linkage flow, and energy intensity, whereas economic urbanization and social urbanization are shown to be negatively correlated. However, spatial urbanization has no significant positive effect on urban CO2 emissions. (3) It is worth noting that urban linkage flows are the second most important factor affecting urban carbon emissions after economic urbanization. Our study could formulate effective planning suggestions for future CO2 emission reduction paths and development modes in the PRD.

Research on Energy Structure Optimization and Carbon Emission Reduction Path in Beijing under the Dual Carbon Target

In the context of China’s dual carbon target, Beijing, as the capital of China, should play an exemplary role in carbon emission reduction. On the premise of optimizing high-emission sectors such as coal and industry, Beijing is still a certain distance from the goal of carbon neutrality. Therefore, on the basis of Beijing’s energy resource endowment, considering Beijing’s economic development and carbon neutrality goals and scientifically and reasonably planning Beijing’s carbon emission reduction path are important tasks. We construct an energy structure optimization model to achieve the goal of carbon neutrality by 2050. The model analysis concludes that the residents and transportation sectors will account for a large proportion of Beijing’s total carbon emissions in the future. To achieve the goal of carbon neutrality, the electricity substitution of fossil energy and the high proportion of external power are two necessary measures, and the optimal path of carbon emission reduction is proposed.

Towards Sustainable Development: A Study of Cross-Regional Collaborative Carbon Emission Reduction in China

Exploring a scientific and reasonable cross-regional carbon emission reduction path in China is essential to achieving sustainable development and the carbon neutrality target. This study constructs a simulation model of China’s cross-regional carbon emission reduction (CER) system and adopts a multi-agent approach to simulate cross-regional CER scenarios to predict the pathway. The conclusions are as follows: (1) under the national unified CER policy scenarios, carbon emissions are on a continuous growth trend with fast economic growth not matching emission reduction efforts in Scenario I. Scenario II has a lower economic scale, and carbon emissions peak in 2029. Scenario III has smooth economy and reaches the carbon emission peak in 2026. The economy of Scenario IV grows fast, carbon emissions grow slowly, and the peak does not appear in 2030. (2) In three scenarios with provinces as the main agent for CER, if provinces sacrifice the economy to strengthen CER, the peak of carbon emissions will appear in 2020. While the economy of non-synergistic and synergistic CER scenarios in each province is growing steadily, the peak in two modes is reached in 2026 and 2032. The peak is reached four years earlier in 2026 in the synergistic model and 2032 in the non-synergistic model, and the economic growth of some energy-intensive provinces slows down. (3) The synergistic low-carbon model is best for balancing economic development and carbon emission control. Policy recommendations are presented based on the above findings for China’s CER and sustainable development.

Carbon Emission Characteristics and Reduction Pathways of Urban Household in China

With China’s rapid urbanization and rising living standards, the household sector has become the second largest contributor to urban carbon emissions and important pathway to achieve China’s carbon reduction targets. Based on data of Chinese Residential Energy Consumption Survey in 2014, this paper establishes standard households in 54 cities to identify the carbon emission characteristics and explores the emission reduction paths of urban households. We present evidence that rich households tend to increase their use of clean energy, low-income households will not completely abandon inferior energy because of their usage habits and costs and they always live in suburban areas and urban villages. Cities with high household carbon emissions are almost located in north of Huai River/Qinling Mountains line, while cities with low carbon emissions are mostly located around the line and which are mainly on the south side. Monocentric urban development patterns and frigid climates are easy to increase higher household carbon emissions. In this regard, policy makers should help low-income households to escape from inferior energy dependence, encourage the use of new energy vehicles and green housing technologies, introduce a two-part pricing system for central heating services and maintain relative balance of residential and public resources in urban planning.

Carbon emission of China's power industry: driving factors and emission reduction path.

The low-carbon development of power industry is the key to low-carbon development of the whole society. In order to determine appropriate and feasible emission reduction policies, it is necessary to identify the contribution of different drivers to the change of carbon emissions in China’s power sector and to simulate the potential evolution trend of carbon emissions. This paper constructs LMDI model to analyze the driving factors of carbon emission changes in China’s power industry from 2000 to 2018 and uses Monte Carlo algorithm to simulate the evolution trend of carbon emission under different scenarios. We can find (1) economic output effect reached 3.817 billion tons from 2000 to 2018, which was the primary factor to increase the carbon emission. Population scale effect reached 251million tons, which had a weak promotion impact on carbon emission. (2) Conversion efficiency effect played a role in restraining carbon emissions, reaching 699 million tons from 2000 to 2018. (3) Emission factor effect and power intensity effect have obvious volatility. The power structure effect showed great volatility before 2013 and mainly played a role in restraining carbon emission after 2013. (4) Under the baseline scenario, the carbon emission of China’s power industry shows a growth trend. Under green development scenario and enhanced carbon reduction scenario, the carbon emission shows a trend of first increasing and then decreasing.

Carbon Emission Peak Paths Under Different Scenarios Based on the LEAP Model—A Case Study of Suzhou, China

Environmental pollution caused by energy consumption is a global problem. Optimization of the energy system will contribute to the sustainable development of city, especially of the industrial cities. Based on the Long-term Energy Alternative Planning System (LEAP) model, the LEAP-Suzhou model was established to explore the energy system optimization and emission reduction path of Suzhou to 2050. By accounting for current energy consumption and carbon emissions, the baseline scenario (BAU) was established. According to the different methods and intensities of energy transformation, an industrial structure optimization scenario (ISO), an energy structure optimization scenario (ESO), and an energy transformation optimization scenario (ETD) were created. Combined with the energy flow diagram, the energy structure and the direction of optimization were analyzed. The results showed that the baseline scenario will consume 259.954 million tons of standard coal by 2050, and the carbon emission will be 677.6 Mt. Compared with BAU, the ISO, ESO, and ETD scenarios will reduce energy consumption by 37.9%, 37.4%, and 74.8%, respectively, by 2050. ETD had the best carbon dioxide reduction, followed by ESO, and finally ISO. Among them, the carbon emission of ETD will reach its peak around 2030 and decrease to 73.8 Mt in 2050, resulting in the best emission reduction effect. This scenario is the best path for Suzhou to achieve the goal of “carbon peak and neutrality” and sustainable development. The LEAP-Suzhou model successfully explores the low carbon path of Suzhou, provides policy guidance for the optimization of energy transition and carbon neutrality of industrial cities, In the future, the energy structure should be further optimized in Suzhou, and advanced energy technologies should be introduced to improve energy efficiency, especially for the power generation sector, and the proportion of clean energy such as gas should be further expanded.

Simulation of China’s Carbon Emission based on Influencing Factors

China is one of the world’s largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China’s carbon emissions by constructing a system dynamics model of China’s carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China’s carbon emissions. The contribution rates of the five factors to China’s carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China’s carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China’s carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small.

Optimization of carbon emission reduction paths in the low-carbon power dispatching process

With the development of low-carbon electricity, the scale of wind power is expanding continuously and carbon trading for thermal power is popularized gradually. In this context, the optimal combination of thermal power and wind power needs to be further promoted to build up the synergy of carbon reduction. To solve such low-carbon power dispatching problem in the wind power integrated system imported with carbon trading, this paper firstly presents a distributed robust optimization model. Next, the scenario-based characterization of wind power and allocation methods of initial carbon emission rights are discussed for model solution. Finally, empirical analysis shows that: (1) the proposed model proves to be rational and feasible, which can accomplish a good compromise between economy, environment and robustness of power system, (2) wind power integration dose help carbon reduction ratio to achieve up to 50% with lower operating costs and carbon emissions, while carbon trading is really an effective approach for tapping greater carbon reduction potential of thermal power, and (3) more reasonable proportions of wind power in coping with its inherent uncertainties, and more appropriate cooperation modes of thermal power for dealing with carbon trading unpredictability are determined under the different requirement of carbon reduction.

Emission Characteristics, Transformation Mechanism, and Reduction Potential of Ammonia Emissions from a Crop Rotation System in Yangtze River Delta

To study the characteristics and reduction potential of the ammonia emissions of a crop rotation system in the Yangtze River Delta, we monitored and compared the ammonia fluxes from two rotation systems:a conventional rice/winter wheat rotation system and a rice-shrimp cultivation/Chinese milk vetch rotation system. This study was conducted through closing chamber methods to investigate the influencing factors and transformation mechanism of ammonium emissions between the two studied cultivation patterns. Additionally, we established the temporal-spatial emission inventory by sorting out the local ammonia emission factors of farmland in the Yangtze River Delta in the last ten years. The emission reduction effects under different ammonia emission reduction paths were also obtained. The results showed that, the cumulative amount of ammonia emissions throughout the whole monitoring year for the conventional rice/winter wheat rotation system (CR-W) and the rice-shrimp cultivation/Chinese milk vetch rotation system (RS-C) were 65.95 and 20.31 kg·hm-2, respectively, whereas the ammonia loss rates of CR-W and RS-C were 10.86% and 9.20%, respectively. Field surface water NH4+-N, field surface water pH, and topsoil NH4+-N were the major internal factors of ammonia emissions from paddy fields, whereas topsoil NH4+-N and atmospheric temperature had an important impact on ammonia emissions in the wheat season. The ammonia flux/field NH4+-N ratio (ARN) of field surface water under the CR and RS modes in the rice season reached 0.35±0.27 and 0.14±0.19, respectively, which was 10-25 times that of topsoil in the wheat season, such that the ammonia emission flux in the rice season was significantly higher than that in the wheat season. Under the conditions of high field water pH (8.0-9.0), atmospheric temperature (>28℃), and wind speed (>5.0 m·s-1), the ammonia flux/field NH4+-N ratios (ARN) were around 1.6-4.6 times that under low pH, temperature, and wind speed conditions, indicating that those three factors were the main factors affecting the conversion of NH4+-N from farmland to atmospheric NH3. Fertilization types also had significant effects on ARN; under different conditions, the ARN of urea was 1.5-5.5 times that of organic fertilizer. In 2019, the ammonia emission flux of rice and wheat under a conventional planting pattern in the Yangtze River Delta were (49.2±17.6) kg·hm-2 and (16.0±13.5) kg·hm-2, respectively, whereas the ammonia loss rates of rice and wheat were (20.1±5.7)% and (5.9±3.6)%, respectively. The ammonia emission loss rate of the former was about three times that of the latter. The ammonia emission inventory built by local factors shows that the total ammonia emissions of the farmland rotation system in the Yangtze River Delta reached (400.3±206.4) kt in 2019, which was mainly concentrated in the central and northern regions of Anhui province and Jiangsu province, and the ammonia emission intensity reached (1.33±1.39) t·km-2. The selection of different emission factors had a relatively large impact on the change range of the inventory results, reaching the standard of -51.6%~51.6%. Through combing and analyzing the six main paths of ammonia emission reduction in farmland, it was found that nitrogen fertilizer synergism was the best way to reduce ammonia emissions, with the efficiency of (30.9±51.4)%; however, the grain yield increase rate was (-4.2±17.4)%, with great uncertainty. The ammonia emission reduction effect of adding soil additives was relatively poor (-5.4±45.1)%; however, the grain yield increase rate was the highest among those of the six emission reduction paths, reaching (6.8±23.9)%. The ammonia emission reduction effect and grain yield increase rate of the ecological planting and breeding mode were (22.3±15.1)% and (5.6±3.8)%, respectively, which had the advantages of reducing ammonia emissions and increasing crop yield.

The role of China's aluminum recycling on sustainable resource and emission pathways

Aluminum is an indispensable metal because of its tremendous industrial demand, which inevitably places pressure on natural reservoirs, and its continuous production intensifies greenhouse gas emission and energy consumption issues. China is the top producer and consumer of aluminum, resulting in substantially negative trajectories in both the global and national anthroposphere compared with other aluminum-producing countries. The rising stock of end-of-life scrap suggests improving more recycling opportunities to acquire sustainable resource use. Here, we use two modelling approaches in accordance with the life cycle thinking to forecast cumulative demand, GHG emission, and energy performance with six different recycling rates. We show that a recycling rate between 40% and 50% can significantly contribute to sustaining resource consumption while convincingly higher rates readily support increasing sustainable use. However, if the recycling increment is subsidized to reduce carbon dioxide emissions and energy use in production processes, then the authorized reduction up to 50% by 2050 (compared to China's 2000 emission level) cannot be reached by only practicing recycling optimization. The required target is still a challenge, but solutions can be obtained mainly through the serious commitment towards emission reduction paths such as the integration of innovative modern technologies with scrap recycling and product substitution.

Differential Characteristics of Carbon Emission Efficiency and Coordinated Emission Reduction Paths Under Different Economic Development Stages: Evidence from China's Yangtze River Delta

Differential Characteristics of Carbon Emission Efficiency and Coordinated Emission Reduction Paths Under Different Economic Development Stages: Evidence from China's Yangtze River Delta

Co2 Emission Reduction Path and Cost Analysis for a Chemical Industry Company in East China Based on Ccus

Co2 Emission Reduction Path and Cost Analysis for a Chemical Industry Company in East China Based on Ccus

Influencing Factors and Forecasting of Carbon Emissions in China's Logistics Industry——Based on GM-ARIMA Model

As an important industry in China's national economy, the logistics industry has an increasing proportion of carbon emissions year by year. In order to achieve China's carbon emission reduction target, it is urgent to study the emission reduction path of the logistics industry. In this paper, GM and ARIMA are combined in a weighted way to improve the prediction accuracy, uses the GM-ARIMA method to select 12 influencing factors such as population, per capita GDP, and per capita urban road area to establish a carbon emission prediction model for China's logistics industry. And take the carbon emission data from 2000 to 2020 as an example to conduct empirical research. The results show that: Compared with the GM (1,1), the GM-ARIMA prediction has a 4.33% reduction in error, which has a better prediction effect on the carbon emissions of the logistics industry. The carbon emission of China's logistics industry will peak at 967.45Mt CO2 in 2028. To achieve the carbon peaking target, China should introduce more emission reduction policies related to logistics.

Simulation of China's carbon emission reduction path based on system dynamics

Simulation of China's carbon emission reduction path based on system dynamics

Low-Carbon Development of Livestock in China: Evolution, Predicaments and Paths Ahead

Livestock production is an important source of carbon emissions, and the low-carbon transformation of the livestock sector is a critical path to achieving sustainable development of the global economy and society. China is one of the most important livestock-producing countries in the world, so it is necessary to study the evolution and predicaments of low-carbon development in the livestock sector and put forward a scientific and reasonable emission reduction path. Our study first describes the development process of the low-carbon livestock sector in China and calculates the carbon emissions of the livestock sector from 2000 to 2019. It is found that carbon emissions from China’s livestock sector show a trend of increasing and then decreasing continuously from 2000 to 2019, which has a great potential for emission reduction. Then the predicament of low-carbon development of the livestock sector in China is put forward. Finally, from the perspectives of the government, livestock farmers, enterprises, the public, and other social institutions, a multi-subject collaborative mechanism is constructed, and corresponding implementation paths are designed, to provide theoretical support and suggestions for accelerating the low-carbon transformation of the livestock sector in China.

Does the Agglomeration of Producer Services and the Market Entry of Enterprises Promote Carbon Reduction? An Empirical Analysis of the Yangtze River Economic Belt

As the world’s largest carbon emitter, China has been committed to carbon emission reduction and green development. Under the goal of “double carbon”, adjusting the industrial structure and promoting the development of producer services are regarded as effective emission reduction paths. In this paper, from the perspective of market entry of enterprises, we firstly investigate the transmission mechanism between market entry of enterprises and industrial agglomeration and summarize the carbon emission reduction mechanism of producer services. Based on the panel data of 110 prefecture-level cities in China’s Yangtze River Economic Belt (YREB) from 2003 to 2017, we analyze the impact of producer services on carbon emission reduction by using the dynamic spatial panel model. The empirical results show that China’s urban carbon dioxide emissions have noticeable spatial spillover effects and high emission club clustering characteristics and exhibit a noticeable snowball effect and leakage effect in time and space dimensions. The development of the producer services can effectively reduce carbon emission levels, effectively solving the dilemma of “stabilizing growth and promoting emission reduction”. Furthermore, there is an apparent synergistic effect between enterprises’ market entry and industrial agglomeration. The agglomeration of producer services can effectively promote the entry of innovative new enterprises, thus increasing the carbon emission reduction effect. However, due to resource mismatch and isomorphic development, this carbon emission reduction effect has apparent industrial heterogeneity and regional heterogeneity. Finally, this paper makes suggestions for optimizing regional industrial structure, strengthening inter-regional linkage cooperation, and promoting the advanced development of the producer services.

Analyzing driving forces of China's carbon emissions from 1997 to 2040 and the potential emission reduction path: through decomposition and scenario analysis.

Energy and environmental policies are important methods for the government to restrain carbon emissions growth. Identifying the potential dynamic trends of China's carbon emissions under different scenarios has important reference significance for the government's policy implementation. This paper firstly predicted China's carbon emissions from 2017 to 2040 based on three energy transition scenarios at the industrial level. Then, Logarithmic Mean Divisia Index decomposition model was applied to evaluate the driving forces of emissions changes during 1997–2040. Finally, the Spatial–Temporal Logarithmic Mean Divisia Index model was used to explore the emissions reduction potential and the potential reduction path at provincial level. The results showed that (1) as the reduction in energy intensity cannot offset the growth of industrial scale, the carbon emissions of all industries have shown an increasing trend from 1997 to 2017; (2) In the current policies scenario, China's carbon emissions cannot reach the peak before 2040. And only in the sustainable development scenario, the carbon emissions of the three industries will all reach the peaks before 2030. And the development of non-fossil energy will reduce carbon emissions by more than 30%; (3) Hebei, Shanxi, Inner Mongolia, Ningxia, and Heilongjiang are key provinces and improving energy efficiency of the secondary industry is a potential way to promote carbon emissions reduction.Graphical abstract The framework and main content of this paper.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10098-021-02240-7.

Accounting and red uction path of carbon emission firom facility agriculture in China.

Facility agriculture, a typical agricultural production management mode, could affect carbon cycle due to its unique production environmental conditions and highly intensive utilization. With the five main sources as accounting objects, including agricultural film investment, energy consumption, pesticide and fertilizer application, CO2 fertilizer application, and facility soil, we estimated the amount and intensity of carbon emission of three facility agriculture (continuous greenhouse, solar greenhouse, and plastic greenhouse) in 31 provinces in 2018. The results showed that the total carbon emission of facility agriculture in China was 210.3817 million t CO2e, with the three facility agriculture types of plastic greenhouse, solar greenhouse, and continuous greenhouse accounting for 60.2%, 37.4% and 2.4%, respectively. Carbon emission of facility agriculture was mainly contributed by soil greenhouse gas, agricultural film and supplies investment. Carbon emission per unit area of continuous greenhouses was significantly lower than that of solar and plastic greenhouses. The scientific capital allocation rate and facility agriculture scale were the two main factors influencing the carbon emission in facility agriculture. Based on all the results, we presented the carbon emission reduction path from the three perspectives of improving the scientific investment, material consumption utilization rate, and facility area utilization rate of facility agriculture.

Forest Carbon Sequestration Demand Based on Emissions Reduction in China’s Thermal Power and Steel Industries: Implications for Tobacco Industry

Objectives: China is a large country of tobacco production and consumption. In the construction and development of carbon market, the tobacco industry is expected to realizing energy conservation and emission reduction by participating in carbon trading, especially focusing on the forest carbon sequestration demand based on emissions reduction. Compared with the tobacco industry, the heavy pollution industries participate in the carbon market more deeply and widely. Therefore, this paper takes thermal power and steel industries as the research object, in order to provide some implications for the emission reduction path of tobacco industry. It considers the CO2 emissions intensity and marginal abatement costs (MAC) between China’s thermal power and steel industries during 2005–2017, and quantifies the forest carbon sequestration (FCS) demand level of these two industries to account for the role and potential of the forests for China’s green and low-carbon development. Methods: It uses a logistic algorithm to reflect the relationship among FCS demand, MAC and other influencing factors, and the cloud model to simulate FCS demand in different scenarios. Results: It shows an average decline of 54.06% and 56.05% in the carbon intensity of the two industries over the period. The average annualMAC are 11.82–25.55 CNY/ton across pilots, while the annual FCS demand expectation is 35 and 45 million tons for the thermal power and steel industries, respectively. If the MAC increases by 10%, the annual FCS demand will increase to 90 and 50 million tons, respectively. Other factors such as the prices of carbon emissions rights, carbon emission quotas, and industry output show little effect on FCS demand. Conclusion: The economic and technological efficiency of emissions reduction in different industries should be considered comprehensively, and that the consumer to producer subsidy for FCS in the carbon market should be adjusted for resource distribution optimization. This would promote emissions reduction, stimulate FCS demand, and improve the carbon market mechanism.