Abstract

     The utilization of renewable energy (RE) is a meaningful way to realize the low-carbon transformation of energy systems. However, due to the imbalance of resources, economy, technology, society, and environment among regions, the coordinated development of regional RE may be restricted by different factors, which brings challenges to the formulation of relevant development policies. This paper focuses on the development of RE in 30 provinces in China from 2011 to 2019. It uses the AHP-EM integrated evaluation model to evaluate the constructed multilayer indicator system for the comprehensive development of RE. The characteristics of the coupling and coordination relationship between indicators are explored, and the critical driving factors affecting the coordinated development and change in RE in different regions are quantitatively identified through the logarithmic mean Divisia index method. The results show that the comprehensive development level of RE in each province is relatively low, and the relatively high-level areas gradually move eastward in terms of spatial distribution. The degree of coupling and coordination between indicators is still in a low-level coupling stage, and RE in each region has not achieved coordinated development. In addition, the comprehensive development of regional RE is consistent with the spatial evolution characteristics of the degree of coordination among indicators, emphasizing the importance of coordinated development among indicators for RE. These findings will provide broader insights for improving the comprehensive development level of regional RE and formulating differentiated policies.

Introduction

     The development of renewable energy (RE) is closely related to the issue of carbon emission reduction, which has attracted widespread attention. From a long-term perspective, the development of RE has become a key measure to address global climate change and achieve carbon emission reduction [1,2], as well as an essential means to promote the low-carbon development of the energy structure [3]. On a global scale, RE (wind energy, solar energy) has become a necessary force to replace fossil energy due to its nonpolluting and environmentally friendly nature, and excellent resource potential [4,5]. It is estimated that RE in the EU and the US has received sufficient attention as advocates of a global low-carbon energy system. It is manifested in the rapid growth of wind power and solar installed capacity, increased investment in the RE industry [6–8], and an increase in the proportion of RE power generation [9]. However, with the scale development and widespread use of RE, issues such as social acceptance [10–12], infrastructure construction [13,14], and grid transmission technology [15,16] related to the RE industry also follow.

Conclusions and Policy Implications

     For the low-carbon transformation of China’s current energy system, RE has become a necessary force to replace fossil energy with its advantages of being nonpolluting and environmentally friendly. Based on the panel data of 30 provinces in China from 2011 to 2019, this study constructed a multidimensional comprehensive development evaluation system for RE. It calculated the comprehensive degree of RE development in each region. This paper explores the coupling and coordination relationship between various dimensions. It quantitatively identifies the dominant factors that affect the changes in the coupling and coordination relationship of the comprehensive development of RE in different regions. This provides directions for further improving the development level of RE in various regions. The specific conclusions are as follows:

     The overall development of China’s RE is at a relatively low level (0.3558), and the development of the RE industry is still in its infancy. The spatial distribution of provinces with a high level of comprehensive regional RE development shifted to the east. Moreover, the development potential difference between regions is still apparent. As of 2019, the leading provinces in the comprehensive development of RE (>0.40) include Qinghai, Beijing, Jiangsu, Guangdong, Zhejiang, and Shanghai and play the role of leaders in the comprehensive development of RE. These regions benefited from resource endowment and social development, with an average contribution of 2.20% and 1.50%, respectively. At the same time, limited by environmental sustainability, the average contribution is −0.47%. The number of provinces with relatively backward comprehensive RE development (<0.30) decreased, including only Heilongjiang, Hunan, Liaoning, Sichuan, and Xinjiang. Among them, Heilongjiang, Liaoning, and Sichuan are mainly limited by economic benefits (−2.38%; −2.92%; and −5.51%), Hunan is mainly limited by environmental sustainability (−0.62%), and Xinjiang is mainly limited by technical support (−31.52%).

Abstract

     This paper evaluates the impact of climate policy uncertainty on renewable and non-renewable energy consumption in the United States over the quarterly data from 2000Q1 to 2021Q3. Economic growth and crude oil prices are added to the energy consumption functions as control variables. The paper considers several approaches to model both renewable and non-renewable energy demand. It is found that crude oil prices promote non-renewable energy demand and climate policy uncertainty reduces it. Surprisingly, the impact of economic growth on non-renewable energy consumption is positive but insignificant. It is also observed that economic growth promotes renewable energy demand, and crude oil prices reduce it. Furthermore, climate policy uncertainty positively affects renewable energy demand in the long run. Some policy implications are provided for reducing non-renewable energy consumption and promoting renewable energy use in the United States through climate policy implementation.

Introduction

     Climate change is one of the leading problems in the 21st century. Scholars have demonstrated that risks and uncertainties related to climate change can affect various dimensions of the global economic system [1,2]. Climate change is attributed to global warming, environmental pollution, and caused by greenhouse gas emissions. Also, CO2 emissions are driven by fossil fuels and non-renewable energy sources [3,4]. Therefore, the transition from fossil fuels to green renewable energy is an important policy tool to transfer economies to the low carbon economy. It is suggested that higher renewable energy consumption can slow down the negative consequences of climate change on the economic system [5,6]. Similarly [7], argued that promoting renewable energy usage in consumption and production activities can also reduce the adverse impact of climate change and global warming on living human beings and natural habitats in the long run. Therefore, the determinants of the non-renewable and renewable energy demand are crucial for designing climate change policies in developing and developed economies.

Conclusion

     The determinants of energy consumption patterns have been an important issue in achieving sustainable environmental quality in the current context of energy depletion, climate change, and global warming. The following facts motivated us to explore the topic. The first fact is that the concept of “green recovery” or “green economic growth” in 2020 has reignited the debate among scholars about the influence of climate policy uncertainty, economic growth and crude oil prices on the pattern of energy consumption (non-renewable and renewable) pressure. The second fact is that the relevant empirical findings are inconclusive when they are based on the influences of economic growth and crude oil prices on the energy consumption pattern. This evidence suggests that we should use climate policy uncertainty as to the key factor in non-renewable and renewable energy consumption functions, which need to be further investigated empirically using the right methods. The third fact is that advanced economies like the United States are the leading energy consumers and second-best pollution creating countries globally; experiencing the factual findings can provide effective policy recommendations for their authorities and departments to adopt energy sustainability measures. This result can promote sustainable environmental quality for the United States and other growing economies in the long run.

     In this connection, we argue that this is the first study that motivates us to examine the effects of climate policy uncertainty on renewable and non-renewable energy consumption in the United States over the quarterly data from 2000Q1 to 2021Q3. As control variables, economic growth and crude oil prices are added to non-renewable and renewable energy functions. This objective is modelled by applying the ARDL bounds test to cointegration. This model helps us to estimate the long-run and short-run results. Moreover, the DOLS and the FMOLS techniques are used as results of robust checking purposes.

Even though standard growth models do not consider energy as an input for economic activities, energy is a basic factor of production in a modern economy (Rafiq and Salim 2009). Sadorsky (2009) denotes that energy consumption level is considered as a development indicator in the energy economics literature. Increases in economic activities and in industrialization and acceleration of urbanization result in increases in energy demand (Salim et al. 2008; Bilgili et al. 2016b). Hence, demand for energy sources rapidly increased in the last 50 years (Aslan et al. 2014). As British Petroleum (BP 2016) and World Bank (2016) exhibit, while the world primary energy demand grew by 17.7% from 2005 to 2013, the share of fossil energy sources, such as oil, natural gas and coal, in total primary energy demand was 81% in 2013. Put differently, the world counts on fossil energy sources, since most of the energy is produced through fossil energy sources (Salim et al. 2014). This dependence leads to major environmental problems, such as global warming, climate change and air pollution (Lau et al. 2012; Nejat et al. 2015; Kocak and Sarkgunesi 2017) because greenhouse gas emissions (GHGs), such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and fluorinated gases, arise from the usage of fossil sources. With regard to the World Bank (2016) and US Environmental Protection Agency (EPA 2017) data, global GHGs almost doubled from 1970 to 2012, and CO2 had the greatest share in global GHGs with 76% in 2014. Therefore, CO2 emissions seem to be the main reason of the environmental problems, especially global warming and climate change (Wuebbles et al. 2002; Lau et al. 2012; Saboori and Sulaiman 2013; Nejat et al. 2015; Bilgili et al. 2017). CO2 intensity in the atmosphere has rapidly risen since the industrial revolution and has warmed the Earth (Maslin 2004; Narayan 2007; Swapnesh et al. 2014; Bilgili et al. 2017). One can observe that global CO2 emissions increased by 45% from 2000 to 2013 through the World Bank (2016) data. Since environmental pollution has become one of the largest global issues because of great increases in GHGs (Dogan and Seker 2016a), many meetings have been organized since 1970s in order to decrease environmental problems. The United Nations Conference on the Human Environment held in Stockholm in 1972, Rio de Janeiro Earth Summit in 1992, Kyoto Protocol shaped in 1997 and entered into force in 2005, and the 2015 United Nations Climate Change Conference in Paris were principal attempts to reduce environmental problems stemming from fossil energy sources.

Due to large increases in greenhouse gas emissions (GHG) in recent decades, environmental pollution has become one of the most critical global issues. Many countries, including those of the European Union (EU), signed the Kyoto Protocol, which entailed specific target goals per country (Dogan and Seker 2016). This Protocol proposed a 5.2% reduction in GHG emissions, taking 1990 levels as a reference. Developed countries which subsequently ratified the Protocol committed themselves to reduced targets while developing countries were encouraged to reduce their emissions on a voluntary basis (United Nations 1998). Irrespective of its commitment under the Kyoto Protocol, the EU adopted stricter environmental targets through binding legislation with the 2020 climate-energy package, which aims to make Europe a low-carbon economy and increase energy efficiency. The goal is a 20% reduction in greenhouse gas emissions and an increase of up to 20% in the use of renewable resources by 2020. Disengaging economic growth from carbon dioxide emissions has become an environmental ambition. Governments are committed to reducing their greenhouse gas emissions without undermining their economic development, based on the assumption that greater economic growth does not always lead to increased emissions. Italy ratified the Kyoto Protocol and has adopted European energy initiatives, such as the European Emissions Trading Scheme, the White Certificate Scheme in Italian legislation, financial incentives, and the legislative framework for increasing energy efficiency, in an attempt to meet their 2020 targets for CO2 emissions (Bento and Moutinho 2016). Several research studies have highlighted the relationship between CO2 emissions, GDP (or economic growth), and energy consumption (electricity). Other studies investigate the relationships between renewable energy, non-renewable energy, and economic growth, while a third group of studies analyzes the link between CO2 emissions, GDP, and energy consumption from renewable and non-renewable sources. This research has mainly been carried out in Turkey (Halicioglu 2009; Ozturk and Acaravci 2010a; Say and Yücel 2006; Soytas and Sari 2009; Soytas et al. 2007), France (Ang 2007), Malaysia (Ang 2008), Central American countries (Apergis and Payne 2009), Central and Eastern Europe (Atici 2009), Albania, Bulgaria, Hungary, and Romania (Ozturk and Acaravci 2010b), BRICS countries (Cowan et al. 2014; Pao and Tsai 2011), China (Du et al. 2012; Jalil and Feridun 2011), Russia (Pao et al. 2011), Pakistan (Nasir and Ur Rehman 2011), panel of newly industrialized countries (Sharif Hossain 2011; Park and Hong 2013), MENA countries (Farhani and Shahbaz 2014; Omri 2013), Asia (Chandran and Tang 2013), Malaysia (Bölük and Mert 2014; Shahbaz et al. 2013; Farhani and Ozturk 2015; Shahbaz et al. 2014), Turkey (Bölük and Mert 2015; Dogan 2015; Seker et al. 2015; Yavuz 2014), G7 countries (Ajmi et al. 2015; Sadorsky 2009), Saudi Arabia (Alshehry and Belloumi 2015), European Union countries (Bengochea and Faet 2012; Kasman and Duman 2015; López-Menéndez et al. 2014), Canada, Denmark, Iceland, Finland, Norway, Sweden, USA (Baek 2015), 93 countries (Al-Mulali et al. 2015), Vietnam (Al-Mulali et al. 2015; Tang and Tan 2015), OECD countries (Apergis and Payne 2010a; Chiu and Chang 2009; Inglesi-Lotz 2015; Ben Jebli and Ben Youssef 2015; Apergis and Payne 2012b), emerging countries (Nicholas Apergis and Payne 2011a),