Emission Reduction In China Research Articles

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.

Impact of intelligence on the carbon emissions of energy consumption in the mining industry based on the expanded STIRPAT model

The intelligent construction of the mining industry has become an emerging trend in its future development plans. As a traditional high energy consumption industry, its energy conservation and emissions reduction have become particularly urgent concerns. Therefore, it is of great significance to study the impact of intelligence on the carbon emissions from energy consumption in the mining industry. This paper first uses dynamic indirect energy emissions factors to build an accounting model for carbon emissions from energy consumption in the mining industry and calculates the related carbon emissions from 2001 to 2020 by sector. Then, an expandable stochastic environmental impact assessment (STIRPAT) model is established to analyze the impact of intellectualization on the carbon emissions intensity of China’s mining industry. At the same time, many other important factors are included in the model, and the model is fitted using ridge regression. The results show that the order of influence, from large to small, is as follows: energy intensity, industrial output value, per capita output value, the proportion of output value of large and medium-sized enterprises, per capita stock of fixed assets, average enterprise output value, R&D intensity and proportion of indirect energy. Each 1% increase in the above factors will increase the corresponding carbon emissions intensity by 0.2005%, −0.1271%, −0.1207%, 0.7467%, −0.0595%, −0.09813%, 0.1143% and −0.1419%, respectively. Then, the prediction values of the independent variables are obtained by using the scenario analysis method and grey prediction model, and 12 scenarios are set up to predict the carbon emissions intensity of the mining industry energy consumption from 2021 to 2035 by using the expanded STIRPAT model. By analyzing the prediction results, we conclude that Scenario 8, Scenario 9, Scenario 10, Scenario 11 and Scenario 12 can achieve the emissions reduction goals of the mining industry in 2025 and 2030; the optimal path of emissions reduction is given for various scenarios. Finally, a development strategy for emissions reduction in China’s mining industry is proposed.

Does the Digital Economy Successfully Facilitate Carbon Emission Reduction in China? Green Technology Innovation Perspective

How to reduce carbon emissions is a critical problem in the world, especially when the emerging economy grows and technology breakthrough happens frequently. In this study, we systematically evaluate China’s digital economy based on regional data experience and construct a nonlinear dynamic threshold model to incorporate a heterogeneous threshold of green technology innovation into the influential mechanism to figure out whether the digital economy can effectively reduce regional carbon emissions. According to the results, China’s digital economy currently shows a trend of overall upward and local fluctuation and there is a large ‘gap’ between the rich and poor. Interestingly, green technology innovation has a heterogeneous threshold effect between the digital economy and carbon emissions: a lesser level of green technology innovation promotes the carbon emission impact of the digital economy to a certain extent, but when green technology innovation rises and exceeds a threshold, the digital economy can dramatically inhibit regional carbon emissions. This study answers the question of how to use the threshold effect of green technology innovation to reduce carbon emissions in the digital economy, which has significant theoretical and practical value to reduce carbon emissions in developing countries.

Fine mapping and multidimensional analysis of carbon emission reduction in China

With the escalating impacts of global climate change, carbon peaking and carbon neutrality have become pressing issues of mutual concern for nations worldwide. Accurately measuring carbon emissions at regional and municipal levels in order to design differentiated reduction policies and promote carbon neutrality has become a challenging problem. To tackle this challenge, we developed a 250 m resolution grid map of carbon footprint data and constructed a national-level database (comprised of 2,800 county-level units) to analyze China’s carbon footprint from multiple angles such as overall characteristics, urban agglomerations, county-level units, population density, per capita disposable income, and more. This research provides fresh insights for studying multi-scale footprint spatial pattern dynamics. Our findings indicate that (1) The 250 m resolution Carbon Footprint Database developed in this study covers the national, provincial, county, urban, and rural areas, enabling dynamic research on multi-scale footprint spatial patterns; (2) The top 5% of areas with the highest carbon footprints account for approximately 1/5 of total carbon footprints in China, and approximately 1/4 of areas account for more than 50% of total carbon footprints; (3) The potential for reducing carbon emissions in China’s rural areas has been underestimated by over 10%, while those in the western regions are growing rapidly due to poverty alleviation efforts; (4) An inverted U-shaped “environmental Kuznets curve” emerges between disposable income and emissions intensity, with different regions exhibiting different consumption patterns. This study offers a novel approach for formulating reduction policies at different levels throughout the country.

Experimental investigation on co-combustion characteristics of semi-coke and coal: Insight into synergy and blending method

Co-combustion of semi-coke and coal is a prospective technique for large-scale disposal or utilization of the solid waste. In this paper, the co-combustion behaviors and kinetics of semi-coke and coal were studied by thermogravimetric analysis with a focus on the influence of blending method and synergy. The results indicated that the semi-coke combustion was improved by blending with coal, and the interaction between fuels tended to promote the co-combustion. The ignition and burnout temperatures were positively correlated with the carbon content of the mixture, while the comprehensive combustion index and stability index were negatively correlated with it. The layer blending and partition blending method seemed to show stronger promotion than uniform blending method, and the layer blending method with coal in the upper layer was recommended due to the better combustion behavior. The promotion of coal on semi-coke combustion was less affected in devolatilization stage but weakened by the decrease of O2 concentration in char burnout stage. The apparent activation energy (Ea) of the mixture decreased with the increasing faction of coal. The layer blending method with coal in the upper layer had the lowest Ea in devolatilization stage and relatively high Ea in char burnout stage. The work can give some new insights into waste co-disposal strategy and carbon emission reduction in China.

The energy conservation and emission reduction potentials in China's iron and steel industry: Considering the uncertainty factor

Energy conservation and emission reduction in China's iron and steel industry are crucial for mitigating its environmental pressures. However, uncertainties raise significant management risks when setting energy conservation and emission reduction pathways. Therefore, this paper explores the energy conservation and emission reduction potential in China's iron and steel industry. A 10,000-time Latin hypercube sampling is conducted to simulate the distribution of five types of uncertain factors. In addition, this study uses a Sobol’ sensitivity analysis method to recognize the most sensitive factor, and, in specific, analyzes the cost-effectiveness of the technologies via conservation supply curve. The results show that: (1) The uncertainty factors lead to significant fluctuate to the results. In particular, energy conservation will fluctuate by 18.24–40.77%, carbon mitigation by 28.96–55.34%, and SO2, NOx and PM mitigation effects will fluctuate by 48.32–79.53%, 22.12–51.77% and 23.92–50.03%, respectively. (2) Structure and equipment parameters are more the most sensitive to energy conservation and carbon mitigation targets, whose Sobol’ indices are beyond 0.45. End-of-pipe treatment technologies are more the most sensitive to SO2 and PM reduction targets with Sobol’ indices above 0.9. Penetration rates and equipment parameters are more the most sensitive to economic cost targets above 0.8. (3) In 2035, 33 energy conservation technologies and 34 emission reduction technologies will be cost-effective, and they can achieve 69.05–70.14% of energy conservation and 79.03–81.58% of emission reduction potentials, respectively. Based on these findings, this study proposes policy recommendations such as changing the raw material/product structure, upgrading equipment, cooperating actively, and introducing economic incentives and guidelines for technology application.

To what extent can clean energy development advance the carbon peaking process of China?

Many studies have demonstrated the importance of clean energy development for China to meet its carbon peaking commitments and to contribute to solving world environmental problems. However, few studies have integrated spatial correlation and carbon peaking process to fully reveal the spatial spillover effects of carbon emissions and the urgency of emission reduction. The unexpected power cuts in 2020 poses a new requirement to deeply grasp China's clean energy development and carbon peaking attainment. To this end, the spatial econometric panel model and GM (1, N) are used to explore the development of clean energy, the spatial characteristics of carbon emissions, the process of carbon peaking, and the association between them. And all these are based on the real-life dilemma of power cuts and the underlying development-emission conflict in China. The results show that: (1) clean energy development in a region will increase local carbon emissions, but will significantly suppress carbon emissions in neighboring regions; (2) there is an inverted "U" curve relationship between clean energy development and carbon emissions, and China is still in the early stage of positive correlation; (3) fossil energy saved in a region tends to flow to neighboring regions with similar scale of economic development; (4) under the current development model, only 17% of the regions with clean energy development will be able to reduce emissions and successfully reach the peak by 2030, which implies a major emissions reduction challenge for China. The situation of carbon emission reduction in China is far from optimistic. Corresponding policy recommendations are given at the end. In short, we believe that greater clean energy support, stricter emission reduction policies, more diverse emission reduction approaches, and more synergistic emission reduction models are needed simultaneously.

The effects of carbon pricing instruments on carbon emission reduction in China's refining industry: an evolutionary game between heterogeneous refineries.

Carbon emissions from the refining industry are receiving increasing national attention. In view of long-term sustainable development, a carbon pricing mechanism oriented to carbon emission reduction needs to be developed. Currently, the two most common carbon pricing instruments are emission trading system and carbon tax. Therefore, it is important to study the carbon emission problems in the refining industry under emission trading system or carbon tax. Based on the current situation of China's refining industry, this paper constructs an evolutionary game model for backward and advanced refineries to explore which instrument is more effectively applied in the refining industry and identify the effective factors that can promote carbon emission reduction in refineries. According to the numerical results, if the heterogeneity of enterprises is small, the government's implementation of an emission trading system is the most effective measure, while carbon tax can only ensure that the equilibrium strategy solution is (1,1) when the tax rate is high. If the heterogeneity is large, the carbon tax policy will not have any effect, indicating that government implementation of an emission trading system is more effective than the carbon tax. In addition, there is a positive relationship between carbon price, carbon tax, and refineries' agreement to carbon emission reduction. Finally, consumers' preference for low-carbon products, R&D investment level, and R&D spillover effect have nothing to do with carbon emission reduction. Only by reducing refinery heterogeneity and improving the R&D efficiency of backward refineries can all enterprises agree to carbon emission reduction.

Predicting the Potential of China’s Geothermal Energy in Industrial Development and Carbon Emission Reduction

The goal of carbon peaking and carbon neutrality requires major systemic changes in the energy supply sector. As one of the major non-carbon-based energy sources, geothermal energy is characterized by large reserves, stability, and reliability. This paper summarizes the current situation of geothermal resource endowment and industrial development in China. Based on this, a system dynamics model of geothermal industrialization is established, and the potential of geothermal industrialization and carbon emission reduction in China is predicted. The prediction results show that the growth rate of geothermal heating and cooling areas in the next 40 years will follow a trend of acceleration followed by deceleration. China’s geothermal energy heating and cooling area will reach 11.32–14.68 billion m2 by 2060, an increase of about 9–12 times compared to 2020. The proportion of geothermal heating and cooling area to the total building area in China will reach 13.77–17.85%. The installed capacity of geothermal power generation will reach 14,452.80–20,963.20 MW by 2060 under the scenario with electricity subsidies. The proportion of geothermal energy in China’s primary energy consumption structure will reach 3.67–5.64%. The annual carbon emission reduction potential of the geothermal industry will reach 436–632 million tons, equivalent to 4.41–6.39% of China’s carbon emissions in 2020. The results of this study can provide a reference for the healthy and high-quality development of China’s geothermal industry and help to achieve carbon peaking and carbon neutrality goals.

Industrial Upgrading, Total Factor Energy Efficiency and Regional Carbon Emission Reduction in China

Industrial Upgrading, Total Factor Energy Efficiency and Regional Carbon Emission Reduction in China

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.

Understanding Carbon Emissions Reduction in China: Perspectives of Political Mobility

Climate change is one of the largest challenges facing mankind, and the question of how to reduce carbon emissions has raised extensive concern all over the world. However, due to the lack of mechanisms to explain the impact of political factors on environmental regulatory tools, the evaluation of carbon emissions reduction is insufficient in the majority of previous studies. How to better explore the path of carbon emissions reduction has become the key for China to achieve carbon neutralization as soon as possible. Based on a quasi-natural experiment regarding China’s carbon emission trading policy, this paper adopts a difference-in-differences model to address the impact of political mobility on China’s carbon emissions trading policy, and the selected pilot and non-pilot provinces of this policy in China enabled the model to be matched. Using a panel database with 30 provincial administrative units as the observation objects, the results show that China’s carbon emissions trading policy and the horizontal mobility experience of the provincial governors exert a significant positive effect on carbon emission reduction. Additionally, this study identifies a latent factor previously ignored by the existing literature: the correlation between political factors and carbon emissions. This verifies our theoretical hypothesis that officials transferred from the provincial level tend to have higher performance regarding carbon emission reduction. This paper also provides suggestions for the central government to further plan and implement carbon emission reduction policies and mobilize the incentives of local officials in environmental governance.

The impact of fiscal transfer payments on energy conservation and emission reduction in China: Does the development stage matter?

Fiscal transfer payments (TRANS) are the institutional supplement of Chinese-style fiscal decentralization, which is of great significance to economic development. However, the relationship between TRANS and energy conservation and emission reduction (ECER) remains to be further discussed. Using panel data of 30 provinces in China from 2003 to 2020, this study empirically examines the impact of TRANS on energy-environmental performance (EEP) from the perspectives of influence mechanism, regional heterogeneity and nonlinearity. The results show that the influence of TRANS on ECER presents an obvious U-shaped relationship, and this influence has regional heterogeneity. At the same time, the investment-driven effect, infrastructure effect and industrial structure effect are important channels through which TRANS affect ECER. The partially linear functional coefficient models show that TRANS have different effects in different development stages. With the continuous improvement of economic level and urbanization level, the promotion effect of TRANS on ECER is more and more obvious. These results indicate that the government should increase fiscal investment in ECER, and pay attention to the development stage of different regions.

Introducing soil air injection device to reduce carbon footprint of rice production system in China

Improving soil aeration in paddy fields using mechanical device reduces methane (CH4) emissions, whereas it also increases the contribution of other sources (device production, agricultural inputs, etc.). Here, this study applied the life cycle assessment (LCA) method to evaluate the carbon footprint of a soil air injection device (SAID) in rice field. We further analyzed the prospects of this device in promoting carbon emission reduction in China's main rice-producing areas, which was combined with economic benefit calculation and revised knowledge-attitude-practice (KAP) model. Results showed that the reduction of net carbon emissions from paddy fields under SAID treatment was 4.51–241.95% higher than the total carbon emissions from the production, transportation, operation, and recycling of SAID. The economic output of using SAID in rice fields could just offset the cost of it. With reasonable government subsidies (142.80–349.95 yuan SAID−1 yr−1), SAID can reduce carbon emissions from Chinese rice fields by ∼ 41.60 Tg CO2-eq yr−1. This study suggests that using SAID in some rice planting areas in China may be an effective way to reduce carbon emissions.

Emission reduction mode of China's provincial transportation sector: Based on “Energy+” carbon efficiency evaluation

Because the transportation sector relies heavily on fossil energy, especially petroleum, this sector has become one of the most challenging regarding a reduction of carbon emissions. However, because of the variability of regional development, the emission reduction pathways in the transportation sector vary from region to region. This study develops two sets of methods that consider only the energy factor and multiple other factors including energy (energy +), to evaluate and analyse the carbon reduction performance of China's provincial transportation sector, identify the provincial patterns of reducing carbon emissions and propose targeted pathways. The results show that there are obvious differences in energy-based and energy + -based carbon efficiency values across provinces, indicating that energy is an important element of carbon emission reduction in China's transportation sector, but factors such as the economic development level and structure and level of transportation infrastructure also have an important impact on carbon emission reduction. Both the “energy+“-based carbon efficiency and shadow price in the developed eastern provinces are higher than that of the central, western and north-eastern provinces. Considering the regional carbon shadow price and carbon efficiency, we found four different carbon peaking patterns for China's provincial transportation sector.

Carbon peak forecast and low carbon policy choice of transportation industry in China: scenario prediction based on STIRPAT model.

As the second largest CO2 emission department, transportation industry's carbon peak and carbon reduction are very important for China to smoothly achieve carbon peak by 2030 and carbon neutrality by 2060. This paper analyzes the influencing factors from the perspectives of population, economy, technology and transportation equipment structure, subdivides 20 scenarios to predict the carbon emissions of the transportation industry of the whole China and various regions based on scenario analysis method, explores the carbon peak path, and puts forward corresponding policy recommendations. The study found that (1) from the overall trend of carbon emissions, the total carbon emissions of China's transportation industry showed an overall upward trend from 2010 to 2019 while the growth rate of carbon emissions showed a downward trend. (2) From the perspective of influencing factors, population size, urbanization rate, economic scale, traffic development, traffic carbon intensity, and highway mileage have positive effect on the growth rate of China's transportation CO2 emissions. The increase in the proportion of energy structure and railway cargo turnover has the negative effect on carbon emissions in the transportation industry. (3) From the prediction results at the national level, technological breakthroughs have a limited effect on carbon emission reduction in China's transportation industry, while structural equipment optimization has the most significant effect on its emission reduction. When technological breakthroughs and equipment structure optimization are carried out simultaneously, the carbon emission reduction effect is the best. The carbon peak of China's transportation industry would achieve as early as 2030, with a peak range of 70,355.54-84,136.17 million tons. (4) From the perspective of prediction results at the regional level, the provinces with rapid population growth and per capita GDP growth, the provinces with rapid population growth and per capita GDP growth, and the provinces with low population growth and per capita GDP growth should control their average annual growth rate of carbon emissions of the transportation industry to 1.13%, 0.72% and 0.58% respectively in 2019-2030, in order to ensure the achievements of the carbon peak target.

Extreme Emission Reduction Requirements for China to Achieve World Health Organization Global Air Quality Guidelines.

A big gap exists between current air quality in China and the World Health Organization (WHO) global air quality guidelines (AQG) released in 2021. Previous studies on air pollution control have focused on emission reduction demand in China but ignored the influence of transboundary pollution, which has been proven to have a significant impact on air quality in China. Here, we develop an emission-concentration response surface model coupled with transboundary pollution to quantify the emission reduction demand for China to achieve WHO AQG. China cannot achieve WHO AQG by its own emission reduction for high transboundary pollution of both PM2.5 and O3. Reducing transboundary pollution will loosen the reduction demand for NH3 and VOCs emissions in China. However, to meet 10 μg·m-3 for PM2.5 and 60 μg·m-3 for peak season O3, China still needs to reduce its emissions of SO2, NOx, NH3, VOCs, and primary PM2.5 by more than 95, 95, 76, 62, and 96% respectively, on the basis of 2015. We highlight that both extreme emission reduction in China and great efforts in addressing transboundary air pollution are crucial to reach WHO AQG.

A Review of the Role of Understory Technologies for Carbon Neutrality

Carbon emissions are considered the main cause of global warming. The mainstream scientific community has reached a consensus on this, which stimulates international political responses and promotes research on carbon emissions and their reduction in the economics community. At the 75th session of the UN General Assembly, President Xi Jinping solemnly promised that China will strive to peak its carbon emissions by 2030 and achieve carbon neutrality by 2060. Carbon emission reduction has received more attention. At the same time, the under-forest economy is regarded as a new growth point for carbon emission reduction. This paper focuses on reviewing the history of carbon emissions, the development of carbon emission reduction in China, and the economic analysis of China's carbon emission reduction policies. China's carbon emission reduction policy has been implemented for more than ten years, especially the carbon trading pilot policy, which has been implemented for seven years. Are state efforts effective? What is the current state of the carbon emission reduction market? What is the role of understory economy in reducing carbon emissions? The article also answers the above points.

Substantial short- and long-term health effect due to PM2.5 and the constituents even under future emission reductions in China

Heavy pollution events of fine particulate matter (PM2.5) frequently occur in China, seriously affecting the human health. However, how meteorological factors and anthropogenic emissions affect PM2.5 and the major constituents, as well as the subsequent health effect, remains unclear. Here, based on regional climate and air quality models Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ), the PM2.5 and major constituents in China at present and mid-century under the carbon neutral scenario Shared Socioeconomic Pathways (SSP)1–2.6 are simulated. Due to anthropogenic emission reduction, concentrations of PM2.5 and the constituents decrease substantially in SSP1–2.6. The long-term exposure premature deaths at present are 2.23 million per year in mainland China, which is projected to increase by 76 % under SSP1–2.6 despite emission reduction, primarily attributable to aging which strikingly offsets the effect of air quality improvement. The number of annual premature deaths resulting from short-term exposure is 228,104 in mainland China at present, which is projected to decrease in the future. Using North China Plain as an example, we identify that among the major constituents of PM2.5, organic carbon leads to the most short-term exposure deaths considering the largest exposure-response coefficient. Regarding the abnormally meteorological conditions, we find, relative to low relative humidity (RH) and non-stagnation, the compound events, defined as concurrence of high RH and atmospheric stagnation, exhibit an amplified role inducing larger premature deaths compared to the additive effect of the individual event of high RH and atmospheric stagnation. This nonlinear effect occurs at both present and future, but diminished in future due to emission reductions. Our study highlights the importance of considering both the long- and short-term premature deaths associated with PM2.5 and the constituents, as well as the critical effect of extreme weather events.

Driving factors of NOX emission reduction in China's power industry: based on LMDI decomposition model.

Under the policy background of "joint prevention and control" of global greenhouse gas emission reduction and regional air pollutants, the power industry, as an important target industry of energy conservation and emission reduction policies, has become an effective choice to release dual pressures. In this paper, the "bottom-up" emission factor method was used to measure the emission of CO2 and NOX from 2011 to 2019. Then, the contributions of six factors to NOX emission reduction in China's power industry were identified using the Kaya identity and logarithmic mean divisia index (LMDI) decomposition methods. The research results show that (1) there is a significant synergistic emission reduction effect between CO2 emission reduction and NOX emission reduction; (2) the factor that inhibits the growth of NOX emissions reduction in the power industry is economic development factor; and (3) the main factors that promote the reduction of NOX emission from the power industry are synergy effect, energy intensity, power generation intensity, and power production structure factors. Several suggestions are proposed, which are the power industry should adjust its structure, improve energy intensity, focus on applying low-nitrogen combustion technology, and improve the air pollutant emission information disclosure system to reduce NOX emissions.