Carbon Dioxide Emission Intensity Research Articles

Spatial threshold effect of tax competition on carbon dioxide emissions intensity in China

ABSTRACT Tax policymaking in China has created conditions for local governments to strategically leverage tax policies (e.g. tax preferences, tax collection and management efficiency, and fiscal subsidies) to have carbon dioxide (CO2) emissions peak before 2030 and carbon neutrality before 2060. By constructing an endogenous growth model with tax competition, capital mobility, technological innovation, and carbon emissions, this study investigates how tax competition is influencing firm-level behaviour and providing climate-relevant policy implications. It has theoretically demonstrated that this effect depends on technological innovation and operates through the capital mechanism. This finding is empirically confirmed in this analysis using a spatial panel threshold model with fixed effects designed to fit a balanced provincial panel dataset in China over the period 2005–2018. The main results are fourfold. First, provinces with similar carbon emissions intensity (CEI) tend to cluster spatially. That is, a province with a high CEI usually has neighbours with high CEIs. Second, a threshold effect is confirmed, revealing that higher tax collection and management efficiency (lower tax competition) decreases CEI if technological innovation is below the threshold value; otherwise, lower tax competition usually increases CEI. Third, capital mobility is a potential mechanism through which tax competition influences CEI. Specifically, provinces with a high level of technological innovation attract more knowledge- and technology-intensive firms and crowd out firms with low innovation capacities, potentially reducing local CEI. Finally, as indicated in our spatial heterogeneity analysis, the effect of higher tax competition decreasing CEI is only observed in the western region. These findings suggest the need for cross-provincial collaboration in developing taxation policies to ensure these policies help to advance the transition to a low-carbon economy and raise capital entry barriers for high-carbon emission projects in provinces with a low level of technological innovation. Key policy insights: Cross-provincial taxation policies can be designed to encourage the transition to a low-carbon economy due to spatial agglomeration and heterogeneity of carbon emissions intensity (CEI). The focus of tax competition should be knowledge- and technology-intensive firms with a high level of technological innovation. Tax competition can be relaxed in China’s provinces with a low level of technological innovation to reduce CEI; otherwise, it should be strengthened. The central government in China could usefully raise capital entry barriers for high-carbon emission projects in provinces with low levels of technological innovation and guide local governments to attract more projects with high returns and low carbon emissions to avoid a race to the bottom.

Is the R&D Expenditure of Listed Companies Green? Evidence from China's A-Share Market.

Whether the company’s R&D expenditure has the green attribute is the focus of current environmental economics research. This paper empirically tests the relationship between R&D expenditure and CO2 emission intensity by taking Chinese A-share listed companies, from 2016 to 2020, as samples. The research found that the R&D expenditure of the company has a significant green effect of reducing its carbon dioxide emission intensity. Further research shows that the institutional investors play a mediating role in the relationship between R&D expenditure and CO2 emission intensity. And the “governance effect” of institutional investors is affected by “short-termism”, which leads to the “myopic” of enterprises’ management and urges them to invest in the short term, thus being detrimental to the company’s environmental performance. In addition, the green attribute of R&D expenditure only exists in the company which has a high concentration of institutional investors, indicating that the institutional investors possess the ability to identify the green value of R&D investment. Extended discussion shows that the investment of R&D personnel plays a moderating role in the first half path of the above mediating mechanism, which weakens the negative relationship between institutional investors and R&D investment. This paper provides empirical evidence for the government to improve environmental performance at the enterprise level. The results of this study show that, in order to reduce the CO2 emission intensity of enterprises, the government should improve incentives for enterprise R&D, make rational use of the information identification ability of institutional investors, advocate long-term investment philosophy, and strengthen the training of R&D team leaders and technicians.

Exploring the effect of a low-carbon city pilot policies on carbon dioxide emission intensity: Based on the PSM-DID method

In 2010, the National Development and Reform Commission launched the low-carbon city (LCC) pilot program. The scope of the pilot program was then gradually expanded to address the dilemma concerning economic development and low-carbon transition. Selecting the second batch of LCCs in China, this study uses a combination of propensity score matching and difference-in-differences models to determine the effect of LCC pilot policies on CO2 emission intensity. We also used the mediation effect model to further investigate its internal mechanism. The findings of the study are as follows. First, the LCC pilot policy plays an important role in reducing carbon emissions. Second, LCC pilots policies reduce CO2 emissions through intermediary paths of output adjustment and technological innovation. Third, our heterogeneity analysis reveals that cities with higher levels of economic growth and better levels of human capital have superior carbon emission reduction effects; lastly, non-resource-based cities have better carbon emission reduction effects.

Innovation-driven development and urban carbon emission reduction: a quasi-natural experiment in China.

Constructing a quasi-natural experiment based on China's National Independent Innovation Demonstration Zone (NIDZ) pilot, this study applies the time-varying difference-in-differences (DID) model to estimate the impact of innovation-driven development on urban carbon emission reduction. We use panel data on 285 cities which covers 95.96% of Chinese cities during the period of 2003 to 2017. Compared with non-pilot cities, our results indicate that total carbon dioxide emissions and emission intensity of pilot cities decreased by 4.8% and 5.8%, respectively. The results suggest that the construction of NIDZs can significantly promote urban carbon emission reductions. Moreover, our mechanism tests indicate that this pilot policy can encourage technological innovation and optimize industrial structure, which in turn suppresses urban carbon dioxide emissions. Additionally, further analysis shows that the policy effect increases over years and is stronger in urban areas with higher levels of human capital, government finance, and information infrastructure. This study enriches the relevant research on carbon emission reduction.

Sources of carbon dioxide emissions on a cattle dairy farm

The great concern of scientists is the rise in the average temperature of the Earth's atmosphere associated with the greenhouse effect caused by higher concentration of some gases, carbon dioxide included. Animals and their wastes are one of the carbon dioxide sources. Annually there is the growing need in livestock products. This leads to a bigger number of farm animals and consequent higher carbon dioxide emissions into the environment. Theoretical and experimental studies of 2015-2021 at the premises of the Institute for Engineering and Environmental Problems in Agricultural Production and agricultural enterprises in the Leningrad Region of the Russian Federation were aimed at identifying the main sources, intensity and patterns of carbon dioxide emissions in dairy cow barns with due account for the effect of animal housing conditions. The main carbon dioxide sources on a cattle dairy farm are the air exhaled by animals and manure. From the study results, a dairy cow exhales from 4.5 to 8.5 kg of carbon dioxide per day depending on its productivity and mass. The carbon dioxide emission from manure accumulated in a barn is below 1 % of the carbon dioxide exhaled by animals. Modern innovative technologies allow for more efficient use of genetic potential of animals and reduce the negative impact on the environment. The revealed patterns and modelling of carbon dioxide emissions showed that with an increase in cow milk yield from 10 to 30 kg/day, the carbon dioxide emission per 1 kg of milk can decrease 2.3 to 2.5 times.

Exergetic and environmental assessments of hydrogen production via waste tire gasification with co-feeding of CO2 recycled

Hydrogen can be produced from natural gas, coal, biomass, and waste materials as an energy source applicable in many industries. Waste tires can be converted into energy by gasification because they contain numerous organic components, higher heating value, and high volatile content. The purpose of this study is to present the simulation of the hydrogen production via waste tire gasification using recycled CO2 as a gasifying agent. The influences of steam and CO2 to waste tire ratios on hydrogen yield were identified. The energetic and exergetic analyses were applied to evaluate the performance of the waste tire gasification process. From an environmental point of view, the carbon dioxide emission intensity was used to determine the CO2 emission of the waste tire gasification process. The simulation showed that the highest yield of hydrogen occurs at the gasifier temperature of 800 °C with the steam and CO2 to waste tire ratios of 2.0, and 0.1, respectively. The utilization of CO2 as a gasifying agent can enhance the yield of hydrogen, resulting in an increase of energetic and exergetic efficiencies of 59.58 and 49.39%, respectively. In addition, the use of CO2 recycled with a mixture of air and steam produces the lowest CO2 emission intensity of 10.56 tonne CO2/ tonne H2.

Life cycle assessment of ceramic roof tiles: A temporal perspective

The production of ceramic roof tiles is energy intensive, leading to high carbon dioxide emissions intensity. The aim of this study is to conduct a life cycle assessment study to evaluate the environmental profile of ceramic roof tiles produced in two Portuguese ceramic plants (T1 and T2) that use different technologies. This assessment is performed on a temporal basis (over a 10-year period) to evaluate the effect that ceramic processual changes have on environmental impacts. System boundaries include the whole life cycle—from extraction and acquisition of raw materials up to tile end of life. Environmental impacts were calculated for eight impact categories. The impact results show an overall improvement in the environmental performance of roof tiles produced in T1 and T2 for all impact categories over the 10-year period as a result of the continued introduction of technical and energy saving measures during the tile manufacturing. Overall, roof tile 2 shows the worst environmental profile for all impact categories, with the exceptions of acidification and photochemical oxidant formation, due to the use of refractory material in the firing process. These exceptions can be explained by the existence of a dry flue gas cleaning adsorber with a filter coupled at kilns in T2. • Ceramic roof tile LCA study with inventory data over a 10-year period enables an integrated timeframe perspective of roof tiles environmental burdens. • Overall, improvement in the environmental performance of the T1 and T2 plants for all impact categories over the 10-year period was observed. • Changes to production technology affect the potential environmental impacts of ceramic roof tiles. • Overall, the production stage (modules A1–A3) is the hotspot for all impact categories.

Analysis of agricultural greenhouse gas emissions using the STIRPAT model: a case study of Bangladesh.

The agriculture sector is one of the leading emitters of greenhouse gases in Bangladesh, owing to increasing mechanization, changing population patterns and increasing cultivation of irrigation intensive crops like rice. The objective of this research is to analyze how population trends, energy use and land use practices impact the emissions of three greenhouse gases from the agriculture sector in Bangladesh. The gases studied are carbon dioxide, methane and nitrous oxide. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and ridge regression are used to analyze the drivers of emissions covering the period from 1990 to 2014. Explanatory factors of emissions are the total and rural population, affluence, urbanization, fertilizer intensity and quantity, carbon and energy intensity, irrigation, rice cultivation, cultivated land and crop yield. The findings reveal that the country’s total population has a negative effect, and the rural population has a negative, nonlinear impact on the emissions of methane. Affluence affects emissions of all the gases. The energy intensity and carbon intensity of agriculture increase carbon dioxide emissions. The cultivated land area, rice cultivation quantity and crop yield increase methane emissions, while irrigated land area decreases it. Rural population, total population and urbanization have a positive linear effect on carbon dioxide and nitrous oxide emissions. Fertilizer quantity and intensity increase nitrous oxide emissions. The findings imply that increasing agricultural mechanization should be based on clean energy, and land management should be regulated to enable the country to meet its Nationally Determined Contribution (NDC) targets as well as the targets of Sustainable Development Goal (SDG) 7 of increasing the share of clean energy.Graphic abstract

Determinants and regional contributions of industrial CO2 emissions inequality: A consumption-based perspective

The assessment of industrial consumption-based carbon dioxide emissions could explain interregional differences in carbon dioxide emissions resulting from economic activity. This study aims to assess per capita industrial consumption-based carbon dioxide emissions inequality across provinces, municipalities, and autonomous regions in China from 2002 to 2017. The status and main determinants of per capita industrial consumption-based carbon dioxide emissions inequality are calculated using environmentally multi-regional input–output models and the Theil index, respectively. Comparisons with accounting results from the production side are then analyzed. The main conclusions are as follows: (1) From 2002 to 2012, both per capita industrial consumption-based carbon dioxide emissions and per capita industrial production-based carbon dioxide emissions in China show an obvious upward trend, and gradually stabilize in 2015 and beyond. (2) Economic trade leads to obvious carbon leakage among Chinese provinces and industrial sectors: the consumption-based carbon dioxide emissions of the downstream sector of the industrial supply chain is less than its production-based carbon dioxide emissions, while the carbon dioxide emissions of upstream industrial sectors is on the contrary. (3) China's per capita industrial production-based carbon dioxide emissions inequality is significantly greater than consumption-based inequality, and this gap is gradually widening. Among them, between-group inequality is the key component, but the contribution of within-group inequality is gradually increasing, which tends to exceed between-group inequality. (4) Among the eight economic groups in China, per capita consumption is the main driving factor of consumption-based carbon dioxide emissions inequality, but the industrial production carbon dioxide emissions intensity is the main contributor to production-based inequality. The above findings would provide certain theoretical support and policy references for policymakers when formulating industrial carbon emissions reduction policies.

The heterogeneous impacts of Sino-African trade relations on carbon intensity in Africa

Studies on the environmental impacts of China–African trade relations are scarce. To fill the gap, this research examines the effects of Sino–African trade relations on carbon dioxide (CO2) emissions intensity in Africa, employing panel quantile regression for 39 African countries over the period of 1992–2015. The results indicate that imports have a negative and significant effect on CO2 emissions intensity across all quantile distributions, whereas exports have a positive and significant effect, except at the 25th and 35th quantiles. The findings also confirm the inverted U-shaped environmental Kuznets curve hypothesis, particularly for countries at higher emissions points. The study also demonstrates that urbanisation and energy intensity positively affect CO2 intensity, while the effect of foreign direct investment is negative and significant, confirming the pollution halo hypothesis. Finally, policy implications are presented based on the findings of the study.

The Effect of Chemicals of Plant Protection Products on Soil Microbiocenoses

With the emergence of agriculture, humankind faced numerous difficult tasks. For example, how to use the potential of the soil while saving its quality and functional properties, how to apply agricultural technologies effectively and environmentally friendly, how to make them safe for human health and biota, and many others. There are several informative and reliable recording criteria and indicator systems that fully and comprehensively describe changes in the ecological condition of the soil and agrocenoses. However, all these systems have one defect – the time from the impact of the factor to the “reaction” of the indicator. Early diagnosis of changes in the agrocenosis is possible due to the biological component of the soil, namely the microbiocenosis. Notably, that microorganisms have a large contact surface with the environment, high rates of reproduction in space and time, sensitivity to changing living conditions. The reaction of soil microbiocenosis and its activity (number of microorganisms of ecologicaltrophic and taxonomic groups, respiration intensity, microbial biomass content, and soil phytotoxicity) under the action of chemicals that are the basis of plant protection products (PPP) was studied in the laboratory. It was found that the number of microorganisms of different ecological-trophic and taxonomic groups under the action of a composition of cymoxanil with dimetomorph decreased by 1.5-4.5 times relative to control, chlorperifosmethyl in 1.1-2 times, and prometryn – not more than 1.5. The content of microbial biomass and the intensity of carbon dioxide emissions when using cymoxanil with dimethomorph compared to the control variant decreased by 44% and 51.4-64.8%, respectively; prometryn – by 10-13% and by 8-12%. The highest level of soil phytotoxicity was observed for variants using prometryn (20-24%), the lowest for a composition of cymoxanil with dimetomorph (7-12%). It was shown, that the high level of inhibition of test culture development with the use of prometryn associated with the class of PPP and the mechanism of its effect on the plant organism. Low indicators of soil phytotoxicity and microbiocenosis activity when using cymoxanil with dimetomorph are explained by the influence of the studied composition not only on phytopathogenic micromycetes, but also on all groups of soil micromycetes (cellulose-destroying, saprophytic) that dominate. Therefore, the influence of PPP chemicals on the microbiocenosis can be shown as follows: PROMETRYN (the lowest level of influence) → CHLORPYRIFOS-METHYL → CYMOXANIL + DIMETOMORF (the highest level of influence)

The Impact of Digital Finance Development on CO<sub>2</sub> Emissions in China

The problem of environmental pollution caused by massive CO2 emissions is becoming increasingly serious. As an environment-friendly financial service, digital finance is conducive to the development of a low-carbon economy. Based on the panel data of 287 cities in China from 2011 to 2019, this paper uses a two-way fixed-effect model and an intermediary model to study the impact of digital finance on carbon emissions. The empirical analysis results show that: in the whole of China, digital finance has an obvious effect on reducing carbon dioxide emission intensity; the impact of digital finance on carbon emission intensity has regional heterogeneity, and the development of digital finance in eastern China can play a significant role in reducing carbon dioxide emissions. The impact of digital finance on carbon emission intensity is dimensionally heterogeneous, and the development of the usage depth of digital finance and the digitization level can reduce carbon emission intensity; technological progress plays a partial intermediary role in the process of digital finance affecting carbon emissions. Digital finance can drive low-carbon development by promoting the optimization and upgrading of technology. Based on the above conclusions, this paper puts forward corresponding suggestions for the development of China’s green and low-carbon economy.

The effect of foreign investment on Asian coal power plants

Asia has built 90% of new coal-fired capacity worldwide in the past 20 years, attracting billions of dollars of foreign investment. This paper explores how such foreign investment has affected the environmental performance of a set of 2108 Asian coal power plants. The findings suggest that foreign-funded power plants are on average 3.4% cleaner in terms of carbon dioxide (CO2) emissions intensity than their domestically funded counterparts, with an effect that varies by foreign country, from 8.9% cleaner (South Korea) to 2.0% dirtier (Russia). Better technology (heat rate) explains 96% of this improved environmental performance, while cleaner coal (emission factor) explains the remaining 4%. The environmental performance of foreign-funded coal power plants has only a negligible spillover effect on the performance of domestically funded plants. Although foreign investment slightly reduces CO2 emissions per unit of electricity, overall, it increases global reliance on coal, thus undermining global ambitions to curb greenhouse gases.

Policy influence in the dynamic of energy and carbon dioxide emissions intensity of Brazilian road transport

The transport system is a key sector for the development of a country, but it demands significant energy from fossil fuels which emit considerable amounts of greenhouse gases. Given the importance of the sector and its polluting potential, this paper aims to evaluate the energy consumption and CO2 emission from road transport in Brazil given some policies foreseen in the country. A System Dynamics (SD) model involved different policies focusing on the energy matrix: increased participation of ethanol, biodiesel, and electricity, as well as a policy aimed at increasing the energy efficiency of vehicles. Six scenarios were simulated over 11 years, between 2019 and 2030, from different perspectives. The results showed that the increase in bioenergy use such as ethanol and biodiesel is not sufficient for reducing energy consumption and CO2 emissions in a significant way. The same results were obtained when considering the introduction of electricity and energy efficiency improvement at expected rates. Despite the attempt to make the energy matrix of the transport sector less dependent on fossil fuels, the fleet and GDP continue to grow, even smoothly, which minimizes the effect of the proposed changes. More audacity will be required from government actions, in addition to integration with other proposals, such as mode choice, vehicle utilization, network connectivity, and new technologies, to effectively change energy consumption and emissions in the sector.

Drivers of the peaking and decoupling between CO2 emissions and economic growth around 2030 in China.

Reaching the peak of carbon dioxide emissions is the basis and premise of carbon neutrality. In this paper, the factor decomposition model was used to analyze the influencing factors and effects of carbon dioxide emissions. Causal chain model of elastic decoupling was established. The historical decoupling state between carbon dioxide emissions and economic growth and the decoupling effect of its influencing factors were analyzed. The prediction model of carbon dioxide emissions was used to explore the change trend of China's carbon dioxide emissions and its peak in the short and medium term in the future. The elastic decoupling trend between carbon dioxide emissions and economic growth was predicted. The results show that economic growth is the main force driving carbon dioxide emissions. Both energy intensity and energy consumption structure have a strong inhibiting effect on carbon dioxide emissions except for a few years, but the former has a more significant inhibiting effect than the latter. In general, the elastic decoupling between carbon dioxide emissions and economic growth has experienced a state from weak decoupling to growth linkage and then to weak decoupling. And this weak decoupling trend will continue to increase in the short and medium term. During the 14th Five-year and 15th Five-year period, if the average annual economic growth rate will be maintained at 4.61 to 5.85%, energy intensity will be reduced by 16.14 to 18.37%, and the proportion of non-fossil energy in the energy consumption structure at the end of the 14th, 15th, and 16th Five-Year Plan period will be around 19.9%, 23.2%, and 26.1%, respectively, and then the intensity of carbon dioxide emissions will continue to decline. It is expected to reach the peak of carbon dioxide emissions between 10,453 and 10,690 billion tons from 2025 to 2027. And the earlier the peak time is, the smaller the peak is, which would provide valuable time for carbon neutrality and room to reduce carbon dioxide emissions in the medium and long term.

Globalization and environment: Effects of international trade on emission intensity reduction of pollutants causing global and local concerns

International trade's impact on the pollution reduction, especially varied reduction effects dealing with global or local pollutants has not been thoroughly researched empirically. We explored effects of international trade participation on both the carbon dioxide emission intensity and sulfur dioxide emission intensity with a panel data of 179 major countries during 20 years when globalization thrived. Carbon dioxide causing climate change is a global concern. While sulfur dioxide is one major air pollutant causing local health problems. Empirically, international trade participation mainly reduces carbon dioxide emission intensity but not sulfur dioxide emission intensity. Also, trade in goods form is more effective than in service form. However, international trade participation does little to improving a country's overall technology level, implying that regulation enhancement under international norm is the main mechanism. Compared with developed countries, developing countries can reduce both kinds of pollutant emission intensities more effectively by participating into international trade. A case study of China's entering into World Trade Organization (WTO)'s impact on pollutant reduction can provide more evidence. Also, developing countries with higher industrialization level experiences a bigger improvement in cleaner production. And developing countries with higher democratization level pay more attention to reduce local environmental concerns.

An Examination of Green Credit Promoting Carbon Dioxide Emissions Reduction: A Provincial Panel Analysis of China

The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.

Complete decomposition analysis of CO2 emissions intensity in the transport sector in Europe

This article identifies which effects contribute to the carbon dioxide emissions (CO2) intensity in the transport sector in the period 2008–2018, in EU 27 European countries. The technique of Complete Decomposition was applied to calculate six effects: (i) CO2 emissions, compared to the consumption of fossil fuels (Effect CF); (ii) consumption of fossil fuels compared to electricity (Effect FE); (iii) electricity consumption compared to the total energy consumption (Effect EEn); (iv) total energy consumption compared to the capital used (Effect EnK); (v) capital per capita (Effect KP) and (vi) inverse work average of productivity (Effect LVA). The study revealed that emissions intensity in the transport sector have diminished and that the more relevant effects were Effect EnK and Effect KP in the majority of the countries analyzed. Denmark and Lithuania show a distinctive pattern with Effect CF, Effect LVA and Effect Een presented as the more important. This article add value as its results are relevant for adequating environmental policies to the transport sector, and as there is a main shortcoming found in the literature review, related with the lack of studies applied to Europe regarding the analysis of CO2 emissions intensity and in particular for the transport sector.

An empirical analysis of the environmental performance of China’s overseas coal plants

China’s ongoing commitment to overseas infrastructure investment through the Belt and Road Initiative (BRI) has ignited concern over environmental impacts. The BRI’s environmental impacts will be determined by China’s decisions not only on what kinds of projects to fund, but also how those projects end up operating relative to projects without Chinese involvement. It is critical to understand current performance and establish a baseline understanding of the environmental impacts of China’s overseas projects thus far. We examine the environmental performance of coal-fired power plants in Asia in terms of carbon dioxide emissions intensity. Using generating unit-level data and a regression-based analysis, we estimate the comparative emissions intensity of overseas coal plants owned, designed, or constructed, by Chinese and non-Chinese companies. We find that Chinese coal plants tend to have significantly lower emissions intensity than similar non-Chinese coal plants. Given that total emissions rather than relative emissions intensity primarily drive the global warming impact of a plant, we also estimate total annual emissions and committed lifetime emissions of the plants in our dataset. We find that while Chinese plants may have relatively lower emissions intensity, their total emissions will grow as a proportion of the coal plant emissions in Asia over time.

Effects of renewable energy use in the energy mix on social welfare

This article examines the effects of energy policy on social welfare under the pseudo-social planner's problem. To assess the social welfare effects, we focus on the energy mix as a policy tool and incorporate two factors into the model: cost-efficiency and climate damage. For model calibration, we use U.S. data of levelized cost of energy, carbon dioxide emission intensity, and carbon dioxide concentration in the atmosphere; thus, the analysis is within the scope of the U.S. energy policy. The results show that a 10% increase in the proportion of renewable energy in the energy mix decreases social welfare by 0.753% in the long run. This negative welfare effect of the increase in renewable energy use occurs because the negative effect of reduced cost-efficiency outweighs the positive effect of less climate damage on social welfare. We also find that increased energy policy uncertainty further reduces social welfare. This is because a higher degree of energy policy uncertainty leads to a greater uncertainty in return on capital, which makes rational agents postpone their investment. • The article examines the effects of renewable energy use on social welfare. • The proportion of renewable energy in the energy mix serves as a policy tool. • The trade-off between cost-efficiency and climate damage is considered in the model. • Increasing the proportion of renewable energy in the energy mix reduces social welfare. • Increased energy policy uncertainty also reduces social welfare through investment.