Economic and intensity effects of coal consumption in China

Greenhouse gas emissions and reduction strategies for the world's largest greenhouse gas emitters

In the context of climate change, it is crucial to examine the contributions of leading countries in greenhouse gas (GHG) emissions. This research provides an overview of global GHG emissions from 1970 to 2022 for the world's most polluting countries: the United States, China, India, Russia, Brazil, Indonesia, Japan, Iran, Mexico, and Saudi Arabia. These countries collectively account for approximately 64% of GHG emissions. The aim is to understand the impact of various economic sectors, such as industry, energy, agriculture, and transportation, on overall emissions. The analysis highlights the disparity in per capita emissions, with smaller but major oil-producing countries in the Persian Gulf, such as Qatar and the United Arab Emirates, exhibiting high per capita emission levels, while more populated countries like the United States and South Korea show lower per capita values but significant total emission volumes. The study suggests that transitioning to renewable energy, improving energy efficiency in industry, promoting sustainable agriculture, reforestation, and electrifying transportation are key methods to achieve United Nations Sustainable Development Goals (UN SDG). Recommendations include encouraging technological innovations, implementing stringent government regulations and standards, and garnering active support for GHG reduction programs from governments, financial institutions, and the business community. The urgency is emphasized for global efforts to combat climate change for ensuring a sustainable future.

Investigating the dynamic decoupling relationship between regional social economy and lake water environment: The application of DPSIR-Extended Tapio decoupling model

The water environmental problems associated with rapid socioeconomic growth have drawn widespread attention from the government and the public. Revealing the decoupling mechanism between the social economy and lake water environment has become an important breakthrough point to seek the pathways of sustainable economic development. To investigate the decoupling process of the social economy‒lake water environmental system, this study proposes a comprehensive evaluation model, which integrates the Driving force-Pressure-State-Impact-Response (DPSIR) model, projection pursuit method, and Tapio decoupling model; and then applies it to the case study of Hefei City and Lake Chaohu in China in 2021-2035. Three typical scenarios of current, social economy, and water environment are designed and simulated using the DPSIR model to evaluate the dynamic decoupling relationships under various development patterns. We found that the DPSIR indexes had a fluctuating upward trend from 2009 to 2020, with a synchronous improvement trend of the social economy and lake water environment. Meanwhile, the Tapio decoupling analysis showed that the decoupling relationships between socioeconomic driver forces, response strategies and the status of lake water environment was mostly strongly decoupled and weakly decoupled during 2009-2020. However, there was still an inconsistency between the improvement rate of the lake water environment and the increase rate of the response strategies. During the 2021-2035 simulation period, the DPSIR indexes of all scenarios depicts an overall increasing trend. The decoupling states of S&I-D&P and S&I-R generally tend to be consistent under three regulation scenarios. Among them, the water environment scenario outperforms other scenarios, and the social economy scenario performs worst. Overall, the decoupling of the social economy and lake water environment can attribute to both the transformation of socioeconomic development patterns and the increase of water environmental protection efforts.

Russia-Ukraine war impacts on climate initiatives and sustainable development objectives in top European gas importers

Russia holds the position of being the third largest global producer of oil and plays a significant role in the supply of oil and gas to Europe. The ongoing war conflict has the potential to impede the bilateral and multilateral relations between Russia and Europe. The ramifications of this event will have notable reverberations for environmental endeavors in Europe. The aforementioned premise forms the basis of our investigation, wherein we scrutinize the correlation among oil price, coal price, gas price, economic growth, and coal consumption, while taking into account the ramifications of the Russian-Ukrainian conflict. We adopted fully "modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS), and canonical cointegration regression (CCR)" econometric techniques to gauge the nexus between factors of interest in the top 4 European Russian gas importer economies (Poland, Netherland, Hungry, and Germany). The empirical outcomes reveal substantial negative impact of economic growth and coal price elasticity on the coal consumption. On the contrary, oil and gas price elasticities depict significant positive influence on the coal consumption. Hence, this study concludes that a rise in oil and gas prices leads to an increase in coal consumption, which in turn negatively impacts environmental quality. Furthermore, the occurrence of war has the potential to impede the utilization of coal resources in Netherlands and Hungary. On the other hand, the impact of war is noteworthy and constructive in Poland and Germany. Thus, war results ecological imbalance in Poland and Germany in particular. Governments, decision-makers, stakeholders, and environmentalists must develop a long-term plan that calls for a paradigm shift away from gas, oil, and coal usage and toward more environmentally benign renewable energy sources.

Decoupling analysis and peak projection of manufacturing CO2 emissions from the perspective of investment

Reducing carbon emissions has become an urgent task in China. As the category with the largest economic and emissions contribution to the industry, the carbon emissions research of the manufacturing industry is particularly important. This paper uses the LMDI method to decompose manufacturing carbon emissions into seven influencing factors (i.e., population, urbanization, economic development, investment share, energy intensity, energy structure and emission intensity), in order to explore the factors driving manufacturing carbon emissions during 2003-2018. Then, the paper analyzes the decoupling relationship between manufacturing investment and carbon emissions in 30 provinces. Finally, three scenarios are developed to project future manufacturing emissions at the provincial level up to 2035, and whether manufacturing emissions in 30 provinces can realize peak is discussed. The paper results in three main findings. First, we find that energy intensity played the most important role in decreasing the manufacturing emissions during the whole study period, while the economic development and investment share were the main effect promoting manufacturing carbon emissions. Second, China experienced a process from weak decoupling to strong decoupling between manufacturing invest and emissions. Third, China's manufacturing carbon emissions can only achieve the carbon peaking target in 2030 under the High scenario, and 7 provinces cannot reach the peak before 2035 under the three scenarios.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-03047-w.

Dynamic Scenario Analysis of Science and Technology Innovation to Support Chinese Cities in Achieving the "Double Carbon" Goal: A Case Study of Xi'an City

Since the Chinese government proclaimed the "double carbon" goal in 2020, carbon emissions reduction has become an important task for the Chinese government. Cities generate more than 60% of carbon emissions. There are many challenges in achieving the "double carbon" goal for the cities of China. Science and technology innovation (STI) provides a feasible path, and the mechanism of STI influencing carbon emissions is analyzed. The STI factors, economic factors, energy factors, and population factors are studied based on the generalized Divisia index method. According to the decomposing results, science and technology innovation investment is the most important increasing factor in carbon emissions, and technology innovation investment efficiency is the most important decreasing factor, respectively. Three scenarios are set up and simulated with Monte Carlo technology evaluating the city of Xi'an in China. Under the baseline development scenario, it cannot achieve the carbon peak goal, and the uncertainty of carbon emissions increases. Under the green development scenario, it will peak in 2051, with a 95% confidence interval of 6668.47-7756.90 × 10⁴ tons. Under the technology breakthrough scenario, the lower and median boundaries of carbon emissions peak at 4703.94 × 10⁴ tons and 4852.39 × 10⁴ tons in 2026, and the upper boundary peaks at 5042.15 × 10⁴ tons in 2030. According to the Environmental Kuznets Curve theory, it will peak between 2028 and 2029 with a GDP per capita of CNY 153,223.85. However, it will fail to achieve the carbon neutrality goal by 2060, and should rely on the national carbon trading market of China to achieve the goal with a trading volume of 2524.61-3007.01 × 10⁴ tons.

Multiperspective-driven factorial metabolic network analysis framework for energy-water nexus vulnerability assessment and management-policy simulation

Energy and water are rapidly consumed as the most basic strategic resources of various nations. It is of vital importance to systematically explore the environmental and economic impacts of energy-water co-management policies. This study is to develop a multiperspective-driven factorial metabolic network analysis framework (MPDF) to (a) investigate the direct/indirect/total resource consumption response mechanisms induced by changes in production and consumption; (b) explore the factor interactions of different policies in diverse energy and water metabolic networks by initiating factorial analysis; (c) quantify the economic effects of co-management policies by proposing multiple vulnerability indicators. A typical energy-dependent region, Shanxi Province, China was selected as a case study. The results indicated that the production- and consumption-oriented policies have various guidelines for reducing direct and indirect energy-water consumption. Significant interactions in simulation results suggest synergistic effects across sectors. Considering that Shanxi's energy-water nexus economic vulnerability is as high as 2.22%, it is recommended to prioritize the allocation of resources to sectors with significant factor effects to avoid economic losses. Implementing corresponding resource conservation policies for light industry, machinery manufacturing, construction can reduce water consumption by 18.8%. The findings are expected to provide a solid scientific basis for formulating co-management strategies to alleviate resource scarcities.