CO2 Emission Reduction In China Research Articles

Exploring hydrogen metallurgy to CO2 emissions reduction in China’s iron and steel production: An analysis based on the life cycle CO2 emissions – LEAP model

Previous research has primarily assessed the environmental impact of hydrogen metallurgy from technical or project perspectives, lacking a life cycle perspective. The impact of continued cleanliness of the hydrogen production mix and power generation structure on carbon dioxide (CO2) emissions from the hydrogen metallurgy production process has not been investigated on a medium to long-term scale, which does not provide an adequate and comprehensive view of the contribution of hydrogen metallurgy to China’s emissions reduction, resulting in short-sighted technology choices. To address this lack, we construct a bottom-up energy system model that combines life cycle CO2 emissions with long-range energy alternatives planning (LEAP), including iron and steel (IS) production, power generation, and hydrogen production. Setting development paths of two typical hydrogen metallurgy technologies, including business-as-usual (BAU) and hydrogen metallurgy (HM) scenarios, we carefully evaluate the CO2 emissions impact of hydrogen metallurgy from a whole industry perspective and in each IS production stage. The results suggest that the hydrogen metallurgy transition will help the iron and steel industry (ISI) to achieve peak and deep carbon reduction. Under the HM scenario, CO2 emissions from the ISI would decrease to 816.28 million tons (Mt) in 2050, representing an additional 281.13 Mt reduction over the BAU scenario. Hydrogen metallurgy can accelerate CO2 reduction in raw material acquisition and material processing phases but may increase CO2 emissions in manufacturing and recycling phases. In 2050, hydrogen metallurgy will contribute an additional 12.49 Mt and 300.95 Mt of CO2 reduction to the raw material acquisition and material processing phases, respectively. However, CO2 emissions in the manufacturing and recycling phases would be 32.15 Mt and 0.22 Mt more than in the BAU scenario due to the increased electricity consumption and scrap demand of electric arc furnace (EAF) steelmaking, respectively. Over time, the optimization of hydrogen production and power supply mix will gradually reduce CO2 emissions in each IS production process. In 2050, the CO2 intensity of the hydrogen-rich shaft furnace direct reduced iron (H2-DRI)-EAF process will drop to 753.41 kgCO2/t, which is lower than all other processes except the 100 % scrap-based EAF process. Advancing the development of the H2-DRI-EAF process can effectively achieve CO2 emissions reduction while alleviating dependence on scrap resources. The results are expected to inform government policy on the development of hydrogen metallurgy in China and other countries.

Towards the prospect of carbon-neutral power system 2060: A Power-Meteorology-Society systematic view

With the target of achieving carbon peaking and neutrality in the power sector in China, both State Grid and China Southern Power Grid have made plans of a rapid increase of renewables in future years towards 2060. However, considering the interactions between the power system and meteorological, society factors, whether those plans would lead to CO2 emission peak in 2030 and carbon neutrality in 2060 is still questionable and needs further analysis. Therefore, a Power-Meteorology-Society System is formulated and interactions between these factors will impact the CO2 emission of the power system is studied. Case study shows that these environmental, social factors as well as their interactions will have significant negative impact to the CO2 emission reduction in China's power grid; With current trend of generation and transmission development and higher-than-expected CO2 emission, while the grid could still reach its target of carbon peak in 2030, there will be some challenge for the grid to reach carbon neutrality in the year 2060. Based on that, the authors analyze some potential solutions such as transmission construction, energy storage and the Carbon Capture, Utilization and Storage (CCUS), and try to find a relatively cost-benefit path to reach carbon-neutrality for the grid in 2060.

How does the coal-to-gas policy mitigate carbon emissions? The role of fintech development

As energy transition becomes an important way to achieve carbon dioxide (CO2) emission reduction globally, this paper takes China as an example and uses the difference-in-difference (DID) model suitable for policy research to explore the impact of coal-to-gas (CTG) policy, which aims at promoting energy transition and reducing pollutant emissions, on CO2 emissions, and explores the mechanism of action and the spatial spillover effects of the policy. The results of the study show that, first, the implementation of the CTG policy can reduce CO2 emissions in China, and the results still hold under a series of robustness tests. Second, the CTG policy can achieve CO2 emission reduction through regional industrial restructuring, and the rapid development of financial technology promotes the process of CO2 emission reduction in China. Finally, the implementation of the CTG policy may cause the problem of CO2 leakage due to regional differences in the policy. This study not only provides a reference for setting global energy transition policies, but also provides new ideas for China's CO2 emission reduction and CO2 leakage, and provides data support for policy formulation.

Simulation study on the effect of differentiated carbon tax adjustment on CO2 emissions reduction in China from the perspective of carbon footprint

The carbon tax is an efficient environmental and economic method for lowering CO2 emissions, and effective carbon taxes should not only aim to reduce CO2 emissions but also consider their impact on socio-economic and resource utilization. The carbon footprint reflects actual carbon emissions and trade connections between sectors, providing a reference for levying carbon taxes on different sectors and examining their impact on the economy. This study utilizes the 2017 non-competitive input-output table of China and CO2 emissions and water consumption data from 27 sectors. Firstly, the research calculates carbon and water footprints of each sector through input-output analysis. Then, utilizing the input-output price model, the article compares the effect of differentiated carbon taxes on CO2 emissions and GDP across sectors in China, examining both direct carbon emissions and carbon footprint. Lastly, the survey constructs a carbon tax optimization model, aiming to maximize carbon and water footprint reduction while minimizing reduction in labor compensation. The key findings are: (1) Different sectors display varying characteristics in terms of direct carbon emissions and carbon footprints. 19 sectors exhibit higher direct carbon emissions than carbon footprints, while 8 sectors show the opposite. (2) Implementing carbon taxes on all sectors in China based on direct carbon emissions and carbon footprints effectively reduces CO2 emissions. However, at the same tax revenue, a reduction of 10^4 yuan in GDP leads to a further decrease of 0.47 × 10^6 tons of CO2 emissions from the carbon footprint perspective compared to direct carbon emissions. (3) In the optimal differentiated carbon tax plan based on carbon footprints, water production sector bears the highest carbon tax at 5.45 yuan/ton, while electricity production sector bears the lowest at 0.1 yuan/ton. This plan declines CO2 emissions by 7.82% and water consumption by 6.21%, but also results in a 0.02% decrease in GDP. The research findings recommend that sectoral differentiated carbon taxes consider economic development and resource impacts. Implementing refund policies to compensate for the economic losses caused by carbon taxes is essential, while also conserving resources and reducing CO2 emissions. These recommendations provide valuable guidance for the future introduction and implementation of differentiated carbon tax policies.

A market-based framework for CO2 emissions reduction in China's civil aviation industry

This paper proposes a novel aviation CO2 emissions reduction method by introducing a market-based incentive mechanism. An aviation carbon emissions prediction model is proposed to characterize both the microscopic flight dynamics and the macroscopic air traffic demand trend. Based on emissions prediction, a linear climate response model is applied to evaluate the environmental impact of the aviation carbon emissions. Finally, a market-based framework for aviation CO2 emissions reduction is established based on a two-phase carbon trading model, which provides a piecewise charge method through emission taxation and cap-and-trade. A case study is carried out to demonstrate the effectiveness of the proposed framework using a real-world dataset from the Hefei Air Traffic Control Zone in China. Three scenarios are defined to describe the possible development speed of sustainable aviation fuel application in the future: not applied, medium-speed development, and high-speed development. The results show that the carbon peak will be reached in 2025 in the high-speed development scenario, when the emission amount and associated environmental impact will be reduced by 23.7% and 22.3%, respectively. Thus, the market-based framework proposed in this paper can effectively reduce aviation CO2 emissions and mitigate the effects of global warming.

Will Trade Protection Trigger a Surge in Investment-Related CO2 Emissions? Evidence from Multi-Regional Input–Output Model

Current research has revealed that global trade promotes transnational investment and contributes to large amounts of CO2 emissions. Recently, trade protectionism has gradually emerged. This study aims to explore the effect of global trade protection on investment-related CO2 emissions. We construct an accounting framework for investment-related CO2 emissions under trade freedom and trade restriction based on the MRIO model for the first time, and investment-related CO2 emissions in 16 economies are determined in both trade freedom and trade restriction scenarios. The study uses normal trade and no-trade scenarios instead of free trade and restricted trade scenarios. Then, based on the comparison of the two scenarios, the effect of global trade protection on investment-related CO2 emissions is revealed from the three levels of country, section, and trade links. It is found that global trade protection would lead to an increase of up to 546.17 million tons in investment-related CO2 emissions under current trade structures. Transnational investment in the trade of end-stage intermediary goods contributed 81.6% of the total effect. In terms of countries, trade protection is quite disadvantageous to CO2 emission reduction in China and India, and their CO2 emissions would respectively increase by 105 million tons and 141.5 million tons compared to normal trade. The electricity, gas, and water supply sectors and the manufacturing sector are the main sectors for investment-related CO2 emissions. This study reveals the effect of trade freedom and trade protection on the environment of various countries from the viewpoint of investment-related CO2 emissions, which has important reference value for global CO2 emission reduction in the context of the evolving trade situation.

The impact of green technology innovation on carbon dioxide emissions: The role of local environmental regulations

Environmental pollution has become a global issue attracting ever-increasing attention. Green technology innovation (GTI) is considered an effective strategy in countering this problem and helping achieve sustainability goals. However, the market failure suggests that intervention from the government is necessary to promote the effectiveness of technological innovation and hence, its positive social impacts on emissions reduction. This study investigates how the environmental regulation (ER) influences the relationship between green innovation and CO2 emissions reduction in China. Employing data from 30 provinces from the period 2003 to 2019, the Panel Fixed-effect model, the Spatial Durbin Model (SDM), the System Generalised Method of Moments (SYS-GMM) and the Difference-In-Difference (DID) models are applied to take issues relating to endogeneity and spatial impact into consideration. The results indicate that environmental regulations positively moderate the impact of green knowledge innovation (GKI) on CO2 emissions reduction but have a much weaker moderation effect when green process innovation (GPI) is considered. Among different types of regulatory instruments, investment-based regulation (IER) is the most effective in promoting the relationship between green innovation and emissions reduction, followed by command-and-control-based regulation (CER). Expenditure-based regulation (EER) is less effective and can encourage short-termism and opportunistic behaviour among firms, who can accept the paying of fines as a cheaper cost over the short-term than investment in green innovation. Moreover, the spatial spillover effect of green technological innovation on carbon emissions in neighbouring regions is confirmed, in particular when IER and CER are implemented. Lastly, the heterogeneity issue is further examined by considering differences in the economic development and the industrial structure across different regions, and the conclusions reached remain robust. This study identifies that the market-based regulatory instrument, IER, works best in promoting green innovation and emissions reduction among Chinese firms. It also encourages GKI which may assist firms in achieving long-term sustained growth. The study recommends further development of the green finance system to maximise the positive impact of this policy instrument.

Scaling of Chinese urban CO2 emissions and multiple dimensions of city size

Cities are both the primary cause of global climate change and the key to the mitigation agenda. China's unprecedented urbanization has paralleled a growth in energy demand and urban areas have emerged as the crux of CO2 emissions reduction in China. There is a crucial need for policymakers to understand how CO2 emissions scale with city size and adopt economies of scale (cost savings) for mitigation, particularly through a multidimensional lens of city size. This study reveals a set of scaling relations between urban scope 1 CO2 emissions and five dimensions of city size in 340 Chinese cities, including population (POP), built-up area (BA), building height (BH), specific built-up area (SBA), and built-up volume (BV). The findings show that CO2 emissions in Chinese cities scale linearly with POP and BA but sublinearly with BA, SBA, and BV, and more diverse regimes exist across various geographic zones, population hierarchies, administrative hierarchies, and governance contexts. The prevalent sublinear scaling regime between CO2 emissions and SBA and BV demonstrates the potential importance of optimizing the vertical built-up landscapes for establishing a zero‑carbon society. Furthermore, the top 10 % and bottom 10 % performance of individual cities in emissions identified by the Scale-Adjusted Metropolitan Indicator (SAMI) (the smaller the better) highlights the imprints of the socioeconomic context (e.g., Low Carbon City Initiative) on the scaling of CO2 emissions in Chinese cities, which is critical for developing decarbonization strategies. Our multidimensional analysis can assist in the local-tailored low-carbon development of Chinese cities.

Combined effects of carbon pricing and power market reform on CO2 emissions reduction in China's electricity sector

China is pursuing aggressive action to reduce greenhouse gas emissions from its coal-dominated electric power system. Two key strategies are power market reform and carbon pricing. This paper investigates the combined effects of these two strategies in reducing CO2 emissions from power system operations. We develop an economic dispatch model to simulate hourly power supply system operation in China Southern Power Grid in 2018 under fifteen carbon pricing scenarios; these reflect a wide range of policy ambition, from today's carbon prices to much higher ones that aim to instigate aggressive emission mitigation. Our results show that moderate carbon pricing alone is insufficient to effectively reduce CO2 emissions without concurrent power market reform. With power market reform and as carbon prices increase, large coal units supplemented by energy storage witness higher use rates as they supplant smaller coal-fired generators, until a carbon price of 300 RMB/TCO2 phases out coal use in favor of natural gas. Only at carbon prices higher than 300 RMB/TCO2 do emissions begin to decrease appreciably. Geographic disparities emerge among the five provinces that comprise the Southern Power Grid, with Guangdong witnessing the most CO2 emission reduction at high carbon prices, while emission reductions in other provinces are negligible. Carbon pricing also dramatically increases total power system costs, even at low carbon prices. Our results show the necessity of introducing power market reform and carbon pricing policies concurrently if the goal is to reduce CO2 emissions, with the ultimate goal being a carbon price significantly greater than 300 RMB/TCO2. Because both options will be necessary, our research maps a path to deep emission reductions in China Southern Power Grid for investors, analysts, and policy makers as discussions regarding both reforms accelerate.

How Does Perceived Neighborhood Environment Affect Commuting Mode Choice and Commuting CO2 Emissions? An Empirical Study of Nanjing, China.

Exploring the impacts of perceived neighborhood environment on commuting behavior and travel-related CO2 emissions helps policymakers formulate regional low-carbon transport policies. Most studies have examined the impact of the objective measures of built environment on travel behavior and related CO2 emissions, and few studies have focused on perceived neighborhood environment. This study develops a structural equation model and uses data from a self-administered survey of urban full-time employees in Nanjing, China to examine the direct and indirect effects of perceived neighborhood environment on commuting mode choice and commuting CO2 emissions. The study shows that perceived service facilities has a significant direct effect on commuting mode and a significant indirect effect on commuting CO2 through the mediating effect of commuting mode choice. While socio-demographic variables such as gender have a significant direct impact on commuting mode and commuting CO2 emissions, they have an indirect impact on commuting mode and commuting CO2 emissions through the intermediate variables (such as car ownership, perceived neighborhood environment and commuting distance). The conclusions of this study show that the potential of commuting CO2 emissions reduction in China is enormous, and that policy interventions on commuting would help developing countries such as China achieve the goals of low-carbon transport and sustainable development.

Key mitigation regions and strategies for CO2 emission reduction in China based on STIRPAT and ARIMA models.

China is facing increasing pressure to reduce CO2 emissions from energy consumption. Given this issue, understanding the characteristics, influencing factors, and trends can provide adequate information for decision-makers to solve the CO2 emission problem. This study analyzes the characteristics of CO2 emissions from energy consumption in 30 regions of China from 2005 to 2018 and applies the STIRPAT model to identify the impact of the influencing factors. Combined with the CO2 emission trend in 2030 as predicted by the ARIMA model, the key mitigation regions and strategies reduction have been determined. Results indicate that CO2 emissions have been increasing from 2005 to 2018 in China, thus showing the characteristic of the east being larger than the west spatially. Under the baseline scenario, these emissions will continue to rise in 2030. Carbon emissions intensity is declining, and the gap between provinces with the highest and lowest per capita CO2 emissions is widening. Although per capita GDP is significantly positively correlated with provinces, population is the key factor influencing more provinces, followed by the proportion of the secondary industry and urbanization rate. To achieve low-carbon sustainable development, Shandong, Shanxi, Inner Mongolia, Guangdong, Shaanxi, Xinjiang, and Ningxia are considered the key regions of concern for emission reduction. The heterogeneity of CO2 emission characteristics and influencing factors among regions provides a direction for the development of targeted and differentiated regional emission reduction strategies.

Green technology innovations, urban innovation environment and CO2 emission reduction in China: Fresh evidence from a partially linear functional-coefficient panel model

• We use a partially linear function-coefficient model to explore the nonlinear moderating effect of the urban innovation environment on the impact of green technology innovation on carbon dioxide emissions. • There are heterogeneous impacts of green technology innovations on CO2 emissions in different periods and different types of cities. • Green technology innovation can reduce CO2 emissions indirectly through industrial structure upgrading. • Government fiscal expenditure cannot significantly impact the CO2 reduction effect of green technologies. • The effect of green technology innovations on CO2 emissions is only significant when the human capital level of a city has reached a certain level. Green technology innovations have a better carbon emission reduction effect in cities with higher human capital levels. Green technology innovations are deemed as effective channels through which economic growth and environmental governance are balanced. However, empirical research on the nexus between green technology innovations and CO 2 emissions, especially in developing countries, remains scant. Employing panel data on 264 prefecture-level cities from 2006 to 2017 in China, we explore the impact of the urban innovation environment on the effect of green technological innovations on CO 2 emissions. The empirical results indicate that green technology innovations have a heterogeneous impact in different types of cities. Meanwhile, green technological innovations can contribute to CO 2 emission mitigation after 2010, while the effect is not significant in Chinese cities before 2010. Secondly, green technology innovations can reduce CO 2 emissions indirectly through industrial structure upgrading. Thirdly, when the urban innovation environment is considered, government fiscal expenditure cannot significantly impact the marginal effect of green technologies. Meanwhile, the marginal mitigation effect of green technology innovations on CO 2 emissions is only significant when the human capital level of a city has reached a certain level. There is a better carbon emission reduction effect in cities with higher human capital levels. The results provide important enlightenment to realize the coordination and unity of economic transition to innovation-driven and green and low-carbon development.

Detection of fossil-fuel CO2\xa0plummet in China due to COVID-19 by observation at Hateruma

The COVID-19 pandemic caused drastic reductions in carbon dioxide (CO2) emissions, but due to its large atmospheric reservoir and long lifetime, no detectable signal has been observed in the atmospheric CO2 growth rate. Using the variabilities in CO2 (ΔCO2) and methane (ΔCH4) observed at Hateruma Island, Japan during 1997–2020, we show a traceable CO2 emission reduction in China during February–March 2020. The monitoring station at Hateruma Island observes the outflow of Chinese emissions during winter and spring. A systematic increase in the ΔCO2/ΔCH4 ratio, governed by synoptic wind variability, well corroborated the increase in China’s fossil-fuel CO2 (FFCO2) emissions during 1997–2019. However, the ΔCO2/ΔCH4 ratios showed significant decreases of 29 ± 11 and 16 ± 11 mol mol−1 in February and March 2020, respectively, relative to the 2011–2019 average of 131 ± 11 mol mol−1. By projecting these observed ΔCO2/ΔCH4 ratios on transport model simulations, we estimated reductions of 32 ± 12% and 19 ± 15% in the FFCO2 emissions in China for February and March 2020, respectively, compared to the expected emissions. Our data are consistent with the abrupt decrease in the economic activity in February, a slight recovery in March, and return to normal in April, which was calculated based on the COVID-19 lockdowns and mobility restriction datasets.

Multi-objective optimization of synergic energy conservation and CO2 emission reduction in China's iron and steel industry under uncertainty

Industrial energy conservation and CO2 emission reduction (ECCER) management is a multi-objective optimization problem with multiple uncertainty factors. However, most studies have used deterministic optimization approaches, and neglected the uncertainty factors that affect the effectiveness of the management strategies. This study adopts a multi-objective optimization model under uncertainty to solve the ECCER management problem in China's iron and steel industry. Three objectives: minimum energy intensity, maximum CO2 emission reduction, and minimum cost, are optimized simultaneously. This study simulates the perturbation of the uncertainty parameters within their fluctuation ranges via Latin Hypercube Sampling, adopts the mean objective function value mechanism to calculate the objective value, and obtains the optimized results using the second generation of the Non-dominated Sorting Genetic Algorithm (NSGA-II). Lastly, this study sets three types of preferences to generate final decision strategies via a Vague set-based approach. Results show: (1) The algorithm is reliable as per the verification of Hypervolume indicator and Spacing Metric; (2) The average values of energy intensity and CO2 emission reduction amount in optimal solutions are 524.00 kgce and 125.03 kg per ton steel respectively, which are 6.3% and 7.6% lower than the deterministic optimal ones; (3) The decision strategies encourage the wider application of large-sized process equipment, identify 8-9 advanced technology and eight reutilization approaches as key measures, but find the use of renewable energy will still be in low level. This study aims to solve the industrial ECCER optimization problem under uncertainty, and put forward policy suggestions in sustainable manufacturing in this industry.

Prospect of near-zero-emission IGCC power plants to decarbonize coal-fired power generation in China: Implications from the GreenGen project

An integrated gasification combined cycle (IGCC) power plant with pre-combustion CO2 capture provides a solution to achieve energy security with CO2 emission reduction in China, which has a coal-dominant energy resource structure. This study utilizes the electricity generation and cost information of the GreenGen IGCC plant (265 MW), which is the first and, to date, the only IGCC facility in China, to evaluate the economic performance and competitiveness of this emerging clean coal technology. In the construction stage, the initial investment on the GreenGen plant was approximately $565 million (capital cost: 2133 $/kW; in constant 2017 US dollars). Compared with the US, China incurred significantly lower costs of initial investment for the construction of the IGCC plant, owing to the adoption of a self-developed gasifier. During the operation stage, the levelized cost of electricity (LCOE) without CO2 capture for the GreenGen plant was calculated as 103 $/MWh, whereas it increased to 131 $/MWh with pre-combustion CO2 capture (CO2 capture cost: 42 $/tonne). Currently, an IGCC plant with integrated CO2 capture remains too expensive to be widely used in China. However, simulation results indicate that the LCOE of China’s IGCC plants could be potentially reduced to 80 $/MWh in the future owing to technology innovation, large-scale application and cumulative production. Government policy and financial support to stimulate the research and development of gas turbine and low-rank coal gasification technologies and to subsidize the operation of IGCC plants owing to their environmental benefits would play critical roles in accelerating the development of near-zero-emission IGCC power plants in China.

Research on the Impact of Carbon Tax on CO2Emissions of China’s Power Industry

Based on the TIMES model, a system for CO2emission reduction in China’s power industry is built in this paper. Four scenarios including different carbon tax levels are set up, simulating the CO2emissions of China’s power industry in 2020–2050 by using scenario analysis method. The power consumption demand, primary energy consumption structure, CO2emission characteristics, emission reduction potential, and cost of different carbon tax levels are quantitatively studied. In combination with the impact on China’s macroeconomy, the carbon tax level corresponding to the best CO2emission reduction effect of China’s power industry is obtained, aiming to provide key data and a theoretical basis for China’s low-carbon development as well as the optimization and adjustment of global power production system. The results show that with the development of economy and society in the future, China’s power consumption demand will increase year by year, while the primary energy consumption of the power industry will maintain a rapid growth. The power industry still relies heavily on fossil energy, which will cause great pressure on China’s economic development and ecological environment. Carbon tax will have an important impact on the primary energy supply structure of China’s power industry, and renewable energy can be developed in different degrees. CO2emissions will be significantly reduced, reaching the peak value during 2030–2040 in China’s power industry. The medium carbon tax level (TAX-2) set in this paper can meet the requirements of both CO2emission reduction effect and cost in the power industry, with the most elastic impact on the national economy and the smallest GDP loss, which can be used as an effective environmental economic policy tool.

Cost and potential for CO2 emissions reduction in China’s petroleum refining sector—A bottom up analysis

The petroleum refining sector is energy intensive and has been identified as one of the target industries for CO2 emissions control by China’s emissions trading scheme. A detailed accounting of the cost of emissions reduction is of great significance for the petroleum refining sector to comply with emission reduction target. In this paper, six categories of CO2 abatement technologies are identified in China’s petroleum refining sector, their CO2 emissions reduction cost as well as the potential are estimated using a bottom-up method. Most of the technologies in the sector are cost-effective, which has contributed approximately 76.4% of sectoral total emissions reduction. New equipment technology provides the greatest contribution to emissions reduction, while new materials technology offers the lowest contribution. The implementation of the emissions trading scheme will increase the potential for emissions reduction only if the CO2 price can be higher than 200 CNY/t. Given the amount of emissions reduction that technologies can provide will not exceed 40% of the total emissions; firms must find more diversified ways when facing more stringent emissions control.

Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets

CO2 emissions caused by socioeconomic development and energy consumption in China have put enormous pressure on emissions reduction for Chinese government. In response to CO2 emissions reduction in China, this study integrated the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) stable nighttime light (SNL) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) composite data, and established the integrated nighttime light datasets from 1992 to 2016. The estimated CO2 emissions model utilizing the integrated nighttime light datasets and statistical CO2 emissions at the provincial level from 1995 to 2016 were established. Finally, spatiotemporal dynamics of CO2 emissions were simulated from multiscale. The results clearly showed that: (1) The fitting results of regression relationship between DMSP-OLS SNL data and NPP-VIIRS composite data met the accuracy requirements. The CO2 emissions estimated model was valid. (2) The total amount of energy consumption CO2 emissions in China had increased from 1889.3340 Mt in 1995 to 4683.3165 Mt in 2016, with a total growth of 2.47 times. (3) The high CO2 emissions regions were clearly agglomerated in eastern coastal China from the pixel scale, the highest CO2 emissions provinces were concentrated in Hebei and Shandong, the high CO2 emissions prefecture cities were concentrated in Around Bohai Gulf area, eastern coastal China and some developed cities, and the high CO2 emissions counties were concentrated in eastern coastal China and western energy intensive counties. (4) The relatively-slow growth accounted for the highest proportion among the five growth types, and the CO2 emissions rapid growth regions were concentrated in eastern China at provincial, prefectural and county scale. The western regions accounted for the largest area proportion in five growth types at prefectural scale. We provided policy implications based on the results, which was beneficial to propose mitigation CO2 emissions reduction in China.

Identifying industrial restructuring strategy for CO2 emissions reduction in China: A multi-region input-output linear programming model

The current paper combines multi-regional input-output model and linear programming model to identify industrial shift strategies for CO2 emissions reduction in China. As a supplement to the previous studies, the optimal sequence of demand regulation for various products is explored. The results show that demand side regulation would pose negative effect on both GDP and CO2 emissions. However, certain strategies can be adopted to decrease CO2 emissions at the minimum decrease in GDP. According to the optimal sequence analysis, a group of key final products, such as the metallurgy products, the nonmetal products, the metal products, and the chemical products should be firstly regulated. Most of these key products concentrate in the eastern and coastal regions in China. Our model can be used to aid policy makers in design of effective industrial restructuring policy to achieve the national emissions targets.

Challenges for China's carbon emissions peaking in 2030: A decomposition and decoupling analysis

Investigation of China's Carbon dioxide (CO2) emissions peaking has become a popular topic. Under the mandatory push of the national policy, exploring the challenges of achieving carbon emission peaking deserves enough attention. In this study, a hybrid method combing logarithmic mean divisia index (LMDI) and decoupling index approach, called LMDI-D, is proposed to model the challenges faced by China to achieve its CO2 emissions peaking in 2030. This problem is examined from the perspective of historical trend and future prediction. The results indicate the following: (1) The effects of economic growth are far much larger than the other inhibiting effects of energy intensity and carbon emissions coefficient on the increase of China's CO2 emissions; (2) Increment of total CO2 emission in China shows a steady downward trend under the together influence of different factors, which is good news for the “2030 target”; (3) The decoupling relationship between China's CO2 emissions and economic growth will be stronger during 2015–2030, which is the necessary condition for China to reach its “2030 target”. Overall, the goal for China's to peak its CO2 emissions in 2030 is a challenging task. Finally, several suggestions were put forward to achieve total CO2 emissions reduction in China.