Greenhouse Gas Emissions In China Research Articles

Transition towards sustainable diets: Multi-objective optimization of dietary pattern in China

Global diversity in food cultures has led to a variety of dietary patterns, the evolution of which can significantly impact greenhouse gas (GHG) emissions. To address the dual challenge of climate change and malnutrition, we need to examine feasible pathways towards sustainable diets that balance nutritional adequacy, environmental impact, and cultural acceptability. We propose an optimized dietary transition pathway in China, which aligns with the nation's dietary guidelines (DGs) while aiming to reduce diet-associated GHG emissions and maintain the cultural food preferences. We also examine how the current dietary patterns will change under three different scenarios: 1) meeting nutritional needs (N), minimizing GHG emissions while maintaining nutritional standards (NE), and sustaining cultural acceptance and maintain GHG emissions at a low level while ensuring standard nutrient intake (NEC). We analyze data from 31 provinces in China between 2000 and 2020 to explore sustainable dietary patterns. In this period, plant-based food consumption has experienced a substantial 12 % decrease, in contrast to the 68 % increase in animal-sourced food intake. Meanwhile, diet-associated GHG emissions in China have increased by 17 %. However, dietary nutrition remains below national standards. The diet-associated GHG emission under NEC is 63.43% lower than N and is 7.04% higher than NE, while NEC in cultural unacceptability is 28.39% lower than NE. Our optimized dietary patterns demonstrate the potential to achieve the national nutrition standard, significantly cut GHG emissions, and retain higher cultural acceptability. Acknowledging the regional disparities in sustainable dietary pathways, we propose the implementation of customized provincial directives aimed at fostering compliance with these favorable trends. Our study offers critical policy implications towards achieving a sustainable diet in China, which contributes to managing the complex trade-offs among nutrition, cultural preferences, and environmental impact.

Evaluation of the role of urban domestic wastewater treatment systems for greenhouse gases emissions in China

Rapid urbanization has exacerbated the dual challenge of mitigating water pollution and reducing greenhouse gas (GHG) emissions. The present study offers insights into the actual role of urban domestic wastewater treatment systems by shedding light on their capacity to act as GHG emitters. We introduce a modelling framework to calculate GHG emissions from wastewater treatment systems in China over the past two decades. Our analysis showed that treated wastewater volume increased by over 4.5 times, but GHG emissions also increased by 2.9 times. The annual emissions from wastewater treatment were -on average- nearly 60 Tg CO2-eq over the past two decades, accounting for <1% of the total national emissions. We also found a significant spatial variability with thirteen developed areas contributing >70% of the GHG emissions. Constructions and operations of wastewater treatment systems approximately accounted for 17% and 83% of the GHG emissions, respectively. Our study also proposes a hierarchical governance framework based on ten major regions that could maximize the efficiency in mitigating water pollution and GHG emissions in China.

Assessing the impact of geopolitical, economic, and institutional factors on China's environmental management in the Russian-Ukraine conflicting era

In contemporary times, geopolitical risk, and natural resources prices are susceptible due to the Russian-Ukraine conflict. In the meantime, emerging economies are struggling to explore the factors that could reduce ecological challenges and enhance environmental management. This research aims to analyze several economic, environmental, political, and institutional variables to ascertain their influence on greenhouse gas emissions in China. Covering the latest period from 1990 to 2022, various time series tests, including normality, stationarity, and cointegration tests. The results confirm that the variables studied have a stable pattern over time and are connected in the long run. The non-normal distribution of variables leads to opt novel moment quantile regression, where the results are tested for robustness via parametric approaches. The empirical results asserted that economic growth, natural resource prices, and trade significantly enhance ecological challenges (emissions). However, globalization, geopolitical risk, and institutional quality significantly reduce such environmental challenges. The results are robust, and both unidirectional and bidirectional causal associations confirm the importance of these variables in environmental management. Based on the results, this study recommends engagement in environmentally-friendly trading, investment in clean and green energy, and strengthening institutional quality for the region's environmental recovery.

Can we design food taxes to reduce agricultural greenhouse gas emissions in China? A perspective from animal protein intake of low-income populations

PurposeStudies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.Design/methodology/approachThe authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.FindingsThe results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.Originality/valueThis study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

Spatial-temporal characteristics and driving factors' contribution and evolution of agricultural non-CO2 greenhouse gas emissions in China: 1995-2021.

Comprehending the spatial-temporal characteristics, contributions, and evolution of driving factors in agricultural non-CO2 greenhouse gas (GHG) emissions at a macro level is pivotal in pursuing temperature control objectives and achieving China's strategic goals related to carbon peak and carbon neutrality. This study employs the Intergovernmental Panel on Climate Change (IPCC) carbon emissions coefficient method to comprehensively evaluate agricultural non-CO2 GHG emissions at the provincial level. Subsequently, the contributions and spatial-temporal evolution of six driving factors derived from the Kaya identity were quantitatively explored using the Logarithmic Mean Divisia Index (LMDI) and Geographical and Temporal Weighted Regression (GTWR) methods. The results revealed that the distribution of agricultural non-CO2 GHG emissions is shifting from the central provinces to the northwest regions. Moreover, the dominant driving factors of agricultural non-CO2 GHG emissions were primarily economic factor (EDL) with positive impact (cumulative promotion is 2939.61 million metric tons (Mt)), alongside agricultural production efficiency factor (EI) with negative impact (cumulative reduction is 2208.98 Mt). Influence of EDL diminished in the eastern coastal regions but significantly impacted underdeveloped regions such as the northwest and southwest. In the eastern coastal regions, EI gradually became the absolute dominant driver, demonstrating a rapid reduction effect. Additionally, a declining birth rate and rural-to-urban population migration have significantly amplified the driving effects of the population factor (RP) at a national scale. These findings, in conjunction with the disparities in geographic and socioeconomic development among provinces, can serve as a guiding framework for the development of a region-specific roadmap aimed at reducing agricultural non-CO2 GHG emissions.

An integrated economic, energy, and environmental analysis to optimize evaluation of carbon reduction strategies at the regional level: A case study in Zhejiang, China

China plays a crucial role in responding to global climate change. Provinces are the main sources of energy consumption and greenhouse gas emissions in China's economic and social development. However, it is still unclear how to achieve dual-carbon goals by formulating and implementing local policies to adapt to climate change. In this study, we take Zhejiang Province in China as the research object, based on the LEAP (Low Emissions Analysis Platform) model to construct four social scenarios under different policies, comprehensively considering regional economic characteristics, population, and energy consumption patterns. The results show that to achieve Zhejiang Province's goal of carbon peaking by 2030 while maintaining steady economic growth, additional measures are required to reduce energy consumption intensity or improve the power generation structure. Otherwise, energy demand will increase to 228.06 million tonnes of coal equivalent and carbon emissions will be 487.76 million tonnes in 2050. Moreover, developing clean energy and promoting CCUS technology can continuously reduce carbon emissions to 293.59 and 210.76 million tonnes respectively. The economic viability of CCUS power generation is contingent upon the development of carbon taxes in the future. Once the growth rate reaches 7.2%, power cost will be 167.77 billion RMB and CCUS will become economically advantageous in 2050.

Repositioning fertilizer manufacturing subsidies for improving food security and reducing greenhouse gas emissions in China

China removed fertilizer manufacturing subsidies from 2015 to 2018 to bolster market-oriented reforms and foster environmentally sustainable practices. However, the impact of this policy reform on food security and the environment remains inadequately evaluated. Moreover, although green and low-carbon technologies offer environmental advantages, their widespread adoption is hindered by prohibitively high costs. This study analyzes the impact of removing fertilizer manufacturing subsidies and explores the potential feasibility of redirecting fertilizer manufacturing subsidies to invest in the diffusion of these technologies. Utilizing the China Agricultural University Agri-food Systems model, we analyzed the potential for achieving mutually beneficial outcomes regarding food security and environmental sustainability. The findings indicate that removing fertilizer manufacturing subsidies has reduced greenhouse gas (GHG) emissions from agricultural activities by 3.88 million metric tons, with minimal impact on food production. Redirecting fertilizer manufacturing subsidies to invest in green and low-carbon technologies, including slow and controlled-release fertilizer, organic–inorganic compound fertilizers, and machine deep placement of fertilizer, emerges as a strategy to concurrently curtail GHG emissions, ensure food security, and secure robust economic returns. Finally, we propose a comprehensive set of government interventions, including subsidies, field guidance, and improved extension systems, to promote the widespread adoption of these technologies.

Decoupling tourism growth from carbon emissions: Evidence from Chengdu, China.

The fast growth increases in energy use and greenhouse gas emissions in China's tourism industry. This article assessed the carbon emissions of tourist Chengdu's traffic patterns and how they are expected to change between 2005 and 2021 and explains why tourism carbon decoupling is important for sustainable tourism development. In order to investigate how carbon emissions from tourism may expand without necessarily increasing in tandem with GDP and the variables that influence it, the Tapir model and the LMDI (logarithmic mean Divisia index) method were used. In our study, we looked at six important variables, including (1) the number of visitors, (2) the level of tourism spending per capita, (3) the contribution rate of the tourism sector with according to the country's total national income, (4) the amount of passenger traffic relative to GDP, and (5) the energy consumption relative to the volume of passenger traffic. There have been five stages in the correlation: positively charged decoupling, weak decoupling, negative decoupling, strong coupling, and strong decoupling. All of these describe the relationship between the expansion of China's tourist industry and the country's carbon emissions. Findings highlighted the importance of large numbers of visitors, high levels of per-person tourism spending, and low passenger traffic volume per unit of energy consumption as key positive factors. The rise of carbon emissions may also be slowed by increasing the number of passengers transported per unit of GDP. Carbon emissions from tourists in Chengdu are fluctuating, and this influences the city's economy. The findings have significant theoretical and practical implications for Chengdu's transition to a low-carbon economy and for the formulation of policies to reduce emissions. During the research period, most Chinese provinces exhibited ideal decoupling situations. This research has the potential to be used as a scientific resource for guiding the long-term growth as a result of China's tourist sector.

Climate impact of coal-to-clean-energy shift policies in rural Northern China

China has implemented the coal-to-clean-energy shift policy in rural areas of northern China to improve air quality, optimize energy structure and reduce greenhouse gas emissions, resulting in a significant increase in natural gas and electricity consumption. The policies shifts can reduce CO2 emissions, but methane emissions from switching processes may contribute to short-term climate impacts. The climate impact during the policy transition is still unclear. Thus, this paper developed a lifecycle greenhouse gas (GHG) emissions framework for coal-to-clean-energy policies in rural northern China. The GHG emissions for heating and cooking, the two most energy intensive activities, were calculated. Four scenarios were designed based on energy types and equipment. Uncertainties in estimating lifecycle GHG emissions under different scenarios were analyzed. The technology warming potential values were calculated for the conversion of scenarios. Besides, the environmental benefits of natural gas versus electricity under emission reduction targets were compared. According to our findings, the total GHG emissions reduction of coal-to-clean-energy shift policies in rural northern China under global warming potential on a 100-year scale (GWP 100) is 1.83 million metric ton CO2 equivalent (MMT CO2 eq) in 2018. Since the climate benefits of policy shifts are driven by chosen technical routes, replacing coal with natural gas should be prioritized; heating with natural gas boilers can maximize GHG emissions reduction and climate benefits. By 2038, the climate benefits of electricity will be far superior to those of natural gas, based on emission reduction targets and electrical mix. There are numerous opportunities to reduce GHG emissions in China's energy sector, and there is a need for the energy industry to obtain better emissions data as well as to increase efforts to reduce GHG emissions.

Mitigation of Fully Fluorinated Greenhouse Gas Emissions in China and Implications for Climate Change Mitigation.

Fully fluorinated greenhouse gases (FFGHGs), including sulfur hexafluoride (SF6), nitrogen trifluoride (NF3), and perfluorocarbons (PFCs), have drawn attention because they have long atmospheric lifetimes (up to thousands of years) and high global warming potential. Targeting SF6, NF3, and four PFCs (CF4, C2F6, C3F8, and c-C4F8), this study projects future FFGHG emission patterns in China, explores their mitigation potential, and evaluates the effects of FFGHG emission reduction on the achievement of the country's carbon neutrality goal and climate change. FFGHG emissions are expected to increase consistently, ranging from 506 to 1356 Mt CO2-eq yr-1 in 2060 under the business-as-usual (BAU) scenario. If mitigation strategies are sufficiently employed, FFGHG emissions under three mitigation scenarios: Technologically Feasible 2030, Technologically Feasible 2050, and Technologically Feasible 2060, will eventually decrease to approximately 49-78, 70-110, and 98-164 Mt CO2-eq yr-1 in 2060, respectively, compared to the BAU scenario. Extensive implementation of FFGHG emission mitigation technologies will curb temperature rise by 0.008-0.013 °C under the slowest mitigation scenario, compared to 0.013-0.026 °C under the BAU scenario. Well-coordinated policies and reforms on FFGHG emission mitigation are recommended to prevent potential adverse effects on the climate to a certain extent.

Maximizing Grains While Minimizing Yield-Scaled Greenhouse Gas Emissions for Wheat Production in China

Researchers have previously described the response of crop productivity and greenhouse gas (GHG) emissions to fertilizer nitrogen (N) additions, but they have not determined how to maximize yields while minimizing GHG emissions. We conducted an experiment at 2293 sites with four N levels to simulate both grain yield and yield-scaled GHG emissions in response to the N addition. The yield-scaled GHG emissions decreased by 16% as the N rate increased from treatments without the N addition to the minimum yield-scaled GHG emissions, which was comparable to the values associated with the maximum grain yields. The sites with both high soil productivity and high crop productivity had the highest yield and lowest yield-scaled GHG emissions, with 43% higher yield and 38% lower yield-scaled GHG emissions than sites with low soil and low crop productivity. These findings are expected to enhance evaluations of wheat production and GHG emissions in China, and thereby contribute to addressing disparities in the global food and GHG budget.

The potential for bioenergy generated on marginal land to offset agricultural greenhouse gas emissions in China

Rational use of marginal land for cultivation of bioenergy crops is an effective means to solve land use competition and is an important way to reduce greenhouse gas (GHG) emissions and improve energy supply. This study conducted an evaluation of the suitability of marginal land for growing energy crops in China during 1990–2020 using the GIS and multi-factor analysis method and revealed the quantitative relationship between bioenergy produced by marginal land energy crops and carbon reduction potential. The Intergovernmental Panel on Climate Change (IPCC) coefficient method and life cycle method were applied to measure the biofuel yield of the Jatropha curcas and assessed its potential to offset agricultural greenhouse gas emissions. The findings are: (1) The marginal land area available for energy crops in 2020 is 1.63 × 106 km2, which is 8.35 % lower than the area planted in 1990. (2) When the reclamation index is 60 %, all suitable marginal land can be used to grow energy crops, and biofuels can replace 3.31 × 1011 tons of conventional energy. (3) In 2020, agricultural greenhouse gas emissions will be 9.02 × 108 tons, and the potential of bioenergy crop cultivation to offset agricultural greenhouse gas emissions amounts to 4.31 × 108 tons, or 47.88 %. In the future, the pressure of agricultural GHG emission reduction will be further exacerbated by population growth and agricultural land supply, etc. Rational use of marginal land and development of bioenergy crops are effective ways for China to cope with climate change and realize its renewable energy strategy.

Strategies for fertilizer management to achieve higher yields and environmental and fertilizer benefits of rice production in China

The challenge in China is to retain high yields while lowering greenhouse gas (GHG) emissions in the context of the increasing global and Chinese demand for rice yield. Better fertilizer management is a key factor that favors intensive rice systems toward more intensive, diverse, and sustainable development to obtain higher yield and environmental benefits. Thus, we used a data-intensive approach to estimate yield, fertilizer productivity (FP) and GHG emissions based on fertilizer and soil characteristics across major Chinese rice-producing regions. The common rice production model showed medium yield, low emission intensity and FP, and low or high GHG emissions. Approximate 41 % and 10 %, 34 % and 3 %, 8 % and 2 %, and 8 % and 1 % probabilities for medium and high yield (MY and HY)-low emission intensity (LI)-low GHG emissions (LG)-high FP (HF) (MY-LI-LG-HF and HY-LI-LG-HF) were achieved in Northeast, South, Southwest, Central and East China, respectively, by adjusting basal, tillering and panicle fertilization and soil pH, N, P and K. Our results provide insights for adjusting soil nutrient traits and fertilizer inputs according to regional production potentials for higher yields and FP and lower GHG emissions in China.

Carbon emissions and economic growth in China: Based on mixed frequency VAR analysis

This study endeavors to examine the association between carbon emissions and economic growth in China spanning the period from 1992 to 2018, employing a mixed frequency vector autoregressive model (MF-VAR). In contrast to the low frequency vector autoregressive model (LF-VAR), the MF-VAR model employed in this research does not involve any filtering procedure; instead, it directly employs variables with distinct frequencies for regression computation. Comparative analysis of the findings reveals that the utilization of the MF-VAR model yields bidirectional causality between carbon emissions and economic growth, a relationship that cannot be validated through employment of the LF-VAR model. Furthermore, the prediction error variance decomposition outcomes of the MF-VAR model exhibit a higher level of explicatory capacity when compared to those of the LF-VAR model. These outcomes carry significant implications for China, as well as other global economies, in the pursuit of the Sustainable Development Goals (SDGs). The analysis outcomes further underscore the necessity of effectively curbing greenhouse gas emissions in China, while simultaneously maintaining a certain level of economic development.

The green wave for climate: overcoming financial intermediation challenges in climate change mitigation through credit subsidies.

The aim of this research is to investigate the role of credit subsidies in overcoming financial intermediation challenges. The study seeks to evaluate the current financial intermediation landscape in both countries with respect to climate change mitigation, and to determine the effectiveness of credit subsidies as a policy instrument for promoting mitigation efforts. We apply the unit root test and the error correction modeling technique in examining data from 2012 to 2018 originating from China and Japan, respectively. After that, an explanation for the data is constructed utilizing a regression method. Among the most important findings are the contributions of credit subsidies to eliminating fiscal imbalances, the positive effects they have on global commerce, and the relevance of credit subsidies in reducing greenhouse gas emissions in China and Japan. A 28% and 37% reduction in climate change, respectively, can be achieved by implementing credit subsidy programs for local residents in China and Japan. To provide households with the finance they require to tackle climate change, the financial systems of the industrialized world, particularly those in China and Japan, need to be upgraded.

ANN-based prediction of ammonia nitrogen for wastewater discharge indicators under carbon neutral trend

IntroductionWith the rapid development of society and urbanization, greenhouse gas emissions have increased, leading to environmental problems such as global warming. The rise in urban water consumption has also resulted in increased sewage discharge, exacerbating freshwater scarcity and water pollution. Understanding the current status and spatial distribution of greenhouse gas emissions in China's sewage treatment industry is crucial for emission reduction measures and controlling ammonia nitrogen pollution.MethodsThis study comprehensively investigates greenhouse gas emissions from sewage treatment plants, analyzing influencing factors and predicting future spatial and temporal distributions. The uncertainty of ammonia nitrogen emissions is calculated using the IPCC's error propagation method, considering uncertainty ranges of variables. Additionally, an artificial neural network is employed to predict ammonia nitrogen content in sewage discharge, aiming to prevent excessive levels in wastewater.Results and discussionThe proposed model outperforms others with an R-Squared score of 0.926, demonstrating its superior accuracy in predicting ammonia content in wastewater. These findings contribute to better emission reduction strategies and control of ammonia nitrogen emissions. This model can effectively prevent excessive ammonia nitrogen content in discharged wastewater, contributing to water pollution control. In conclusion, this study highlights the importance of understanding greenhouse gas emissions from sewage treatment plants and their impact on water pollution. The research provides valuable insights into emission reduction measures, emission prediction, and technological innovations suitable for China's specific conditions. By effectively managing ammonia nitrogen emissions and adopting the proposed predictive model, the goals of carbon neutrality and environmental sustainability can be better achieved.

Yield- and protein-neutral reduction in fertilizer rate for wheat, maize and rice can reduce the release of reactive nitrogen and greenhouse gas emissions in China

Seeking food security, contemporary Chinese agriculture has followed a trajectory of overfertilization and associated environmental problems, hence the need for nitrogen-balancing practices that do not compromise yield and quality. Here we present a national meta-analysis using 224 studies with 1972 comparisons to quantify the potential to reduce nitrogen (N) fertilization to improve environmental outcomes while maintaining yield and grain protein. We calculated a nitrogen reduction ratio (NRR), as 100 × (N C − N T)/N C; where N is N fertilizer rate and subscripts indicate farmer practice (C) and reduced N rate treatment (T). Our meta-analysis showed that the NRR that maintained yield and grain protein content at the level of current practice was up to 10% in wheat and up to 30% in maize and rice. Larger yield-neutral NRR could be achieved in more fertile, heavier-textured soils, and with practices including enhanced-efficiency N fertilizer, combined application of organic and inorganic N fertilizer, and incorporated straw. Assuming a reduction in N fertilizer usage by 10% for wheat and by 30% for maize and rice in the current cropping area, there is a potential to save 5.7 Mt N yr−1; reduce loss of reactive nitrogen by 1.26 Mt N yr−1, equivalent to 63% of annual total Nr losses for rice in China, reduce N-related greenhouse emissions by 75.2 Mt CO2-eq yr−1, equivalent to 14.5%–25% of the emissions associated with the N fertilizer chain in China; and improve N use efficiency by 23%. Our results highlight the feasibility of maintaining yield and grain protein, and achieving substantial environmental benefits with reduced fertilization rate, and the environmental and agronomic scenarios where these outcomes are more likely.

The Effect of Eco-Preneurship and Green Technology Management on Greenhouse Gas Discharge: An Analysis on East Asian Economies

This study finds that eco-preneurship and green technology initiatives have the potential to improve the environmental quality of selected East Asian economies in the short term, but in the long term, the impact is negative, and there is a need for a better understanding of their effects on greenhouse gas emissions. The pressing need to address the negative impact of human activity on the environment has given rise these initiatives worldwide. However, there is a lack of research on the effectiveness of these initiatives in East Asian economies. In this study, we examine the short-term and long-term effects of eco-preneurship and green technology on greenhouse gas emissions in China and Japan. The results show that in the short term, both linear and non-linear estimations of eco-preneurship have a significant impact on reducing greenhouse gas emissions in China and Japan. Similarly, short-term linear estimations are significant in both China and Japan, but non-linear estimates are only significant in Japan. The same is true for positive shocks related to green technology in China and Japan, although the estimated coefficient for negative shocks is negative only in Japan. Taken together, these results indicate that eco-preneurship and green technology can improve the environmental quality of these selected economies in East Asia to some extent.

Revisiting electric vehicle life cycle greenhouse gas emissions in China: A marginal emission perspective

The accurate estimation of electric vehicle (EV) life cycle greenhouse gas (GHG) emissions is critical for policymakers to predict and manage the reduction of GHG emissions due to transportation electrification. Most previous studies in the Chinese context evaluated the EV life cycle GHG based on the annual average emission factor (AAEF). However, the hourly marginal emission factor (HMEF), which is conceptually more appropriate than AAEF for evaluating the GHG implications of EV growth, has not been applied in China. This study fills this gap by estimating the EV life cycle GHG in China based on the HMEF and comparing it with AAEF-based estimates. It is found that the estimates based on the AAEF substantially underestimate the EV life cycle GHG in China. Moreover, the influences of the electricity marketization reform and changes in the EV charging mode on the EV life cycle GHG in China are analyzed.

The assessment of energy-related greenhouse gas emissions in China's chemical industry

The chemical industry has a large production scale, many products, and very complex processes, so estimating the greenhouse gas (GHG) it produces is not easy. Few comprehensive assessment models at the national level are studied. Emission sources of most models are not complete, and data are outdated. The paper conducts a comprehensive assessment of GHG emissions in China's chemical industry. The emission sources cover direct and indirect emissions. The chemical industry is divided into three main sub sectors to explore GHG flows. GHG flows are examined through chemical production and consumption, and then the emission reduction potential is predicted based on technological developments. The assessment results show that crude oil and coal are the main sources of direct GHG emissions. The indirect GHG emissions are mainly from North China and Northwest China. GHG emissions in the power grid regions are directly related to the distribution of the chemical industry in China. Coal chemical industry has the most GHG emissions. The analysis of driving factors shows that the output effect is the main factor of GHG emissions. Scenario analysis shows that the baseline scenario will reach 6195.95 Mt in 2030. Under the technological improvement scenarios, 589.01 Mt emission reduction can be achieved by 2030 compared with the baseline scenario. Based on the results of the study, this paper provides some policy recommendations.