Regional Carbon Dioxide Emissions Research Articles

Prediction method of regional carbon dioxide emissions in China under the target of peaking carbon dioxide emissions: A case study of Zhejiang

AbstractAll provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom‐up energy consumption prediction and top‐down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom‐up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy‐consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently.

Can China Reach Its Carbon Peak Before 2030? An Empirical Study Based on China's Carbon Emission Data

The global surge in the warming trend is predominantly attributed to the substantial release of greenhouse gases, notably carbon dioxide. Despite continuous international efforts to curb these emissions, our country, marked by the largest population and energy consumption, stands as a major contributor to carbon dioxide emissions. Unlike developed nations, we face a more formidable challenge in reducing emissions, demanding intensified endeavors. To address climate change, our nation has set a crucial carbon emission target: achieving a carbon peak before 2030 and attaining carbon neutrality by 2060. The "14th Five-Year Plan" of each province underscores the significance of "carbon peaking and carbon neutrality," tailoring emission reduction policies to individual economic landscapes. Current research inadequacies hinder theoretical guidance needed to meet the 2030 carbon peak. Crafting province-specific emission reduction strategies is thus imperative. This study aims to scrutinize national and regional carbon dioxide emissions in four distinct Chinese regions, utilizing the STIRPAT model to predict emissions from 2020 to 2030 under the "low development and strong low carbon" paradigm. Initial analysis from 2004 to 2019 showed an annual increase in national and provincial carbon dioxide emissions, revealing significant regional differences. Six prominent factors influencing emissions were identified. The STIRPAT model predicted emissions for 2020 to 2030, indicating that achieving carbon peaking before 2030 is unfeasible under the baseline scenario. However, within the "low development and strong low carbon" framework, attaining this goal becomes plausible.

Digital Economy, Energy Structure Transformation, and Regional Carbon Dioxide Emissions

For China to reach its “dual carbon” aim, the digital economy presents both opportunities and obstacles. This paper examines the potential impact of digital economy development on regional carbon dioxide emissions, concluding that while the direct impact on regional carbon dioxide emissions through industrial structure upgrading and technological progress is unclear, the indirect impact through promoting energy structure transformation is both positive and clear. This research experimentally validates the results of a theoretical analysis using panel data from 30 Chinese provinces from 2011 to 2019 and the STIRPAT model and discovers an inverted U-shaped association between digital economy development and regional carbon dioxide emissions. According to the transmission path test, the digital economy primarily achieves its carbon dioxide emission reduction effect by promoting energy structure transformation, while the carbon dioxide emission reduction effect from upgrading industrial institutions and technological progress is insignificant. By region, the expansion of the digital economy in eastern China has a large carbon dioxide emission reduction effect but not in central and western China. The policy implication of this paper is that curbing new carbon dioxide emissions caused by digital infrastructure construction using the digital economy to accelerate energy structure transformation and accelerating digital economy development in central and western China can be effective policy options for the Chinese government to achieve the goal of carbon dioxide emission reduction.

Analysis of influencing factors of CO2 emissions based on different coal dependence zones in China

There are differences in economic level, population size, and technical level in different stages. At the same time, as a coal-dependent country, other regions have foreign dependence on coal. Then the primary factors and influence degrees of CO2 emissions in different stages and areas with different coal dependents will be various. This paper adds urbanization rate, industrial structure, and energy consumption structure to the traditional STIRPAT model. Based on the expanded STIRPAT model, the panel data of 30 regions in China from 2005 to 2019 are used to analyze the different stages and areas with foreign coal dependence. The main influencing factors and degree of influence of CO2 emissions. Regression finds that population size, energy consumption, and industrial structure will increase regional carbon dioxide emissions. There is an “inverted U-shaped” curve relationship between economic development, technological level, and carbon dioxide emissions. The improvement of the urbanization rate can reduce carbon dioxide emissions. Carbon dioxide emissions. An “inverted U-shaped” curve relationship between per capita GDP and CO2 emissions in three research periods from 2005 to 2010, 2011 to 2015, and 2016 to 2019. At the same time, the inhibition effect of the urbanization rate is constantly strengthened, and the promotion effect of the coal consumption ratio is decreasing year by year. The influence of population size, technical level, and industrial structure on carbon dioxide emissions in the whole country and areas with different coal dependents varies with the study period. To provide a theoretical basis for local conditions and regional management in the future direction of energy-saving and carbon reduction.

Heterogeneous Environmental Regulation, Foreign Direct Investment, and Regional Carbon Dioxide Emissions: Evidence from China

As an important means to reduce carbon dioxide (CO2) emissions, environmental regulation (ER) and foreign direct investment (FDI) have become popular research topics in recent years. Most studies have examined the single impact of ER or FDI on CO2 emissions, while few investigated the regional heterogeneity and the spillover effect of different environmental regulations (ERs) on CO2 emissions and neglected the impact of the interaction mechanism between ER and FDI on CO2 emissions. This paper applies the spatial Durbin model (SDM) to explore the impact of different ERs and FDIs on regional CO2 emissions in China’s 30 provinces from 2003 to 2019. The results indicate that there are significant differences and regional heterogeneity in the effects of different environmental regulations on CO2 emissions at the national level. FDI has a significant promoting effect on CO2 emissions in the early years (2003–2009), especially in the eastern and western regions, but its effect is not significant in the late period (2010–2019). At the regional level, the abatement effects of the interaction term between FDIs and ERs are generally significant, indicating that ERs can influence the reduction effect of FDIs. Regulatory environmental regulation (RER) in the eastern region, command environmental regulation (CER), and economic environmental regulation (EER) in the central region can significantly affect the emission reduction effect of local FDI.

Chinese cities exhibit varying degrees of decoupling of economic growth and CO2 emissions between 2005 and 2015

Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

Examining the effects of urbanization and industrialization on carbon dioxide emission: Evidence from China's provincial regions

With rapid economic development and expansion of built environment since the year 2000, urbanization has led to great challenge of reduction targets in energy intensity and carbon dioxide emissions. This paper aims to explore the disaggregate driving force of different sectors and investigate the potential of carbon dioxide reduction of them in the context of rapid urbanization. By using the panel datasets at a provincial level in a LMDI (Logarithmic Mean Divisia Index) model, we investigated the effects of various energy-related and socioeconomic factors on regional carbon dioxide emissions in 30 China's provinces from 2000 to 2013. The results show that the factors of economic development are the largest drivers of regional carbon dioxide emissions, compared with the factors of structural change, energy intensity, and social transition. Meanwhile, evidence is found that the urbanization process has contributed to the regional CO2 emissions in China's provinces through a variety of approaches, including changing the energy use characteristics of urban households, transportation, and business sectors. Finally, we found that the changing trend of these influence factors' effect on regional CO2 emissions varied across different provinces, which means there are significant regional heterogeneity in the influence mechanisms of urbanization process on regional CO2 emissions.

Driving factors of carbon dioxide emissions in China: an empirical study using 2006-2010 provincial data

The rapid urbanization of China has increased pressure on its environmental and ecological well being. In this study, the temporal and spatial profiles of China’s carbon dioxide emissions are analyzed by taking heterogeneities into account based on an integration of the extended stochastic impacts using a geographically and temporally weighted regression model on population, affluence, and technology. Population size, urbanization rate, GDP per capita, energy intensity, industrial structure, energy consumption pattern, energy prices, and economy openness are identified as the key driving factors of regional carbon dioxide emissions and examined through the empirical data for 30 provinces during 2006‒2010. The results show the driving factors and their spillover effects have distinct spatial and temporal heterogeneities. Most of the estimated time and space coefficients are consistent with expectation. According to the results of this study, the heterogeneous spatial and temporal effects should be taken into account when designing policies to achieve the goals of carbon dioxide emissions reduction in different regions.

Structural Decomposition Analysis of Carbon Emissions and Policy Recommendations for Energy Sustainability in Xinjiang

Regional carbon dioxide emissions study is necessary for China to realize the emissions mitigation. An environmental input–output structural decomposition analysis (IO-SDA) has been conducted in order to uncover the driving forces for the increment in energy-related carbon dioxide emissions in Xinjiang from both production and final demands perspectives from 1997 to 2007. According to our research outcomes, emissions increase can be illustrated as a competition between consumption growth (per capita GDP) and efficiency improvement (carbon emission intensity). Consumption growth have caused an increase of 109.98 Mt carbon dioxide emissions during 1997 to 2007, and efficiency improvement have caused a 97.03 Mt decrease during the same period. Per capita GDP is the most important driver for the rapid emission growth, while carbon emission intensity is the significant contributor to offset these increments. In addition, production structure changes performed as a new major driver for the steep rise in carbon dioxide emissions in recent years (2002–2007), indicating that the rapid emission growth in Xinjiang is the result of structural changes in the economy making it more carbon-intensive. From the viewpoint of final demands, fixed capital formation contributed the highest carbon dioxide emission, followed by inter-provincial export and urban residential consumption; while inter-provincial imports had the biggest contributions to offset emission increments. Based on our analysis results, Xinjiang may face great challenges to curb carbon dioxide emissions in the near future. However, several concrete mitigation measures have been further discussed and then raised by considering the regional realities, aiming to harmonize regional development and carbon dioxide emissions reduction.

International diversification of investments in climate change mitigation

Numerous studies have shown that international emissions trading can significantly lower the costs of greenhouse gas (GHG) abatement. Economic models, however, ignore the substantial economic and political risks associated with investments in developing countries, where—according to these models—a large share of global GHG abatement takes place. We use a mean-variance approach to compute international portfolios of carbon abatement activities that balance low abatement costs and investment risks. Expected returns are derived from marginal abatement cost curves. The volatility of the growth rate of regional carbon dioxide emissions is used as an indicator of investment risk. We find, first, that well-diversified portfolios can significantly reduce investment risks. Second, the least-risk portfolio is distinct from the cost-efficient allocation based on equalization of marginal abatement costs, and much more costly to implement. This indicates that existing models which neglect investment risks overestimate the cost-savings due to international emissions trading.