Climate change is an inescapable global challenge for technological evolution, and a global consensus has formed to jointly address the global warming caused by GHG emissions. Understanding the main drivers of CO2 emissions and their links to economic growth is very pertinent. Numerous studies have examined the association between green innovation and CO2 emissions in different countries or economies, with mixed results (Bilal et al. 2021; Razzaq et al. 2021; Ali et al. 2022). Therefore, this study addresses this gap by sorting out and summarizing the literature and by conducting further empirical investigations.
2.1 Green innovation and CO2 emissions
From the perspective of carbon emissions, an important dimension in the study of the impact mechanism of CO2 emissions is whether the environmental Kuznets curve (EKC) holds. Despite much discussion, there is still no consensus in the literature on the underlying cause of this relationship. Theoretically, in the framework of economic development, technological progress to improve sectoral green productivity and eco-environmental quality will receive further attention.
As a means of adapting to the challenges of climate change, green technology (such as cleaner production and pollution control technologies) has attracted the attention of researchers, and many research conclusions state that green technology can effectively capture non-desired pollutant emissions and achieve sustainable development goals (Bilal et al. 2021; Yuan et al. 2021; Ali et al. 2022; Li et al. 2022). Compared with technological progress and development in the traditional sense, green innovation aims to reduce environmental pollutant and CO2 emissions and achieve ecological benefits and green economic growth. Likewise, the advantage of green innovation lies in its dual externality. Green innovation can not only generate positive externalities in the form of knowledge spillovers, but can also have positive externalities characterized by saving resources and eliminating negative impacts on the environment (Chen 2020). Nevertheless, because the remarkable contribution of green innovation to reducing CO2 emissions may depend on specific social or economic circumstances, there are some obstacles in the way of innovation and the application of green technologies (Ahmad et al. 2020; Ali et al. 2020). The fundamental point is that decisions to invest in green innovation, from the level of regions and countries to that of individual enterprises, will depend on whether green technologies contribute to increasing clean energy productivity and reduce CO2 emissions. Empirical studies provide mixed results in this context. For instance, in the context of different countries and the organization of economic activities, Jiang et al. (2022) used the DCCEMG method to investigate the conditional establishment path of green innovation with negative impact on CO2 emissions in BRICS countries over the period 1985-2018. Empirical research found that green innovation could significantly curb CO2 emissions in the long-term perspective. A study by Erdoğan et al. (2020) for G20 countries found that the continuous increase in innovation expenditure in the industrial sector has had a significantly inhibiting implication on CO2 emissions. In line with the findings of Khattak et al. (2022), government innovation support can reduce CO2 emissions and improve green development efficiency in China. On the contrary, using the CCEMG estimation technique, Khattak et al. (2020) examined complex influences on carbon emissions in BRICS countries and found that innovative activities had a mitigating effect, but only on Brazil’s CO2 emissions. Likewise, Lingyan et al. (2021) examined the mechanisms of environmental innovation on CO2 emissions in highly decentralized countries through asymmetric analysis. Their findings show that environmental innovations restrict CO2 emissions only when quantities are medium to large.
The relationship between green innovation and CO2 emissions in China has also been investigated from various perspectives, with mixed conclusions. Li et al. (2022) used the NARDL model to examine the asymmetric relationship between green innovation and CO2 emissions in China and concluded that implementing green innovation contributed to the continuous promotion of CO2 abatement in China, and vice versa. Yuan et al. (2021) found that green innovation has significantly reduced CO2 emissions in China, but that institutional quality has a negative regulatory effect in this process. In other words, when institutional quality is consistently kept at a high level, green innovation a more vigorous presence on continuously reducing CO2 emissions, and this effect is more significant in the eastern and western regions. It cannot be ignored that the potential role of green innovation in reducing natural resource consumption and ecological damage is spatially heterogeneous between regions. (Xu et al. 2022) empirically examined the spatial interaction and spillover effects of green innovation and CO2 emissions in the 30 Chinese provinces using a spatial econometric model. The study revealed that inter-regional joint improvements in green innovation technologies were more effective in curbing CO2 emissions, and green innovation transformation and technology-oriented industrial upgrading were highlighted.
Finally, some researchers believe that to achieve simultaneous economic development and green transformation, the work of achieving carbon emissions reduction must include enterprises as a breakthrough generator (Desheng et al. 2021; Zhu et al. 2022). As a core component of green innovation, cleaner production technology can indirectly reduce CO2 emissions by optimizing production processes. The extensive application of green technology in enterprise production can boost green energy consumption and reduce pollution emissions from the production side. At the same time, green innovation can help transform the energy-intensive industries into a cleaner, lower-carbon direction by empowering the coupled coordination and transformation of the industrial structure, thus restricting CO2 emissions from production processes in enterprises (Zhang et al. 2020; Gao et al. 2022). For example, using China as a case study for analysis, Zhu et al. (2022) revealed that green technology innovation by enterprises could decrease regional CO2 emissions intensity under the influence of two-way foreign direct investment. Moreover, the findings, by constructing a quasi-natural experiment as a test method, show that while political connections hinder firms’ green technology innovation, carbon emissions can be further reduced and environmental quality improved by increasing investment in innovation (Desheng et al. 2021). Equally important, carbon-related technologies belonging to green innovation are being widely used by heavily polluting sectors and enterprises. For example, CO2 utilization, capture, and storage technologies can effectively control the cost of decarbonization and empower end-of-pipe treatment, thereby reducing pollutant emissions and environmental governance costs simultaneously (Xie et al. 2019).
2.2 Environmental regulation and CO2 emissions
The relationship between environmental regulations and CO2 emissions has been extensively studied and discussed, with the mainly focus on whether such regulations can yield practically meaningful fruit in mitigating global warming. There is still no unified conclusion on the action mechanism of different types of environmental regulations and proxy variables of pollution control on CO2 emissions. What we know about environmental regulations are largely based on empirical studies that have investigated how environment-related legislation mitigates CO2 emissions to emphasize the importance of ecological protection behavior. For example, the results of Zhu and Ruth (2015)’s study in China revealed that energy-saving policies introduced by the government could improve the energy use efficiency of industrial enterprises and gradually decreasing CO2 emissions. Regarding the impact of three types of environmental regulations (command-and-control, market-based, and informal regulations) on environmental performance in China, Li and Ramanathan (2018) concluded that compared with market-based regulation, there was a non-linear correlation between command-and-control regulations, the legal means to regulate the behavior of enterprise pollution emissions, and environmental performance. Similarly, using environmental taxation to illustrate the practical implications of environmental regulation, Hashmi and Alam (2019) investigated the impact of environmental regulation on declining CO2 emissions in OECD countries. The empirical result was that environmental quality were effectively improved with the strengthening of environmental taxation. However, the obvious inverted “U-shaped” relationship expressing the determinant factor of environmental regulations toward CO2 emissions has received attention from researchers. In other words, with the tightening of environment-friendly policies and legislations, carbon emissions show a trend of increasing first and then decreasing. By investigating panel data from the 30 provinces in mainland China, Lan and Wang (2019) found that investment in industrial pollution control had a double threshold effect on carbon emission performance and that regional carbon performance presented a “U-shaped” development trend. On the contrary, when studying the dynamic threshold effect of industrial pollutant abatement expenditure on environmental degradation in China’s industrial green transition, Hou et al. (2018) reached conclusions that were almost contradictory. In summary, combining the publications just discussed, there are complex viewpoints on the impact path between environmental regulations, including the selection of proxy indicators, and CO2 emissions, as well as the causes of their formation and the conclusions to be drawn, and the relationship is still worthy of further discussion.
2.3 Energy consumption and CO2 emissions
Energy is an instrumental contributor to the industrialization of emerging economies and survival and development of human societies (Li et al. 2022). On the one hand, it is continuously exploited and utilized to satisfy the prosperous and stable economic development in various countries and regions, but on the other hand, it also brings problems such as environmental pollution and CO2 emissions (Muhammad et al. 2021). Existing research classifies energy use into two main types: renewable and non-renewable. Non-renewable energy is dominated by fossil energy, with coal as the main component. On the contrary, renewable energy consists mainly of energy derived from natural sources, and adequate, reliable, and clean energy supply is the fundamental direction for economic growth and environmental improvement (Li et al. 2022a). Therefore, renewable energy is considered as a fundamental requirement for building a resource-saving society and achieving sustainable development goals. According to the findings of an investigation conducted by Musah et al. (2021) for North African countries, Oil-based energy consumption, a potential factor that cannot be ignored, has exacerbated further CO2 emissions. In another study on the driving factors of economic growth in the BRICS countries, Chang et al. (2017) found that the interactive relationship between coal consumption and economic development was not proven, and that its unidirectional facilitating effect was only established in China. Furthermore, based on the STIRPAT framework, Usman and Hammar (2020) investigated the characteristics of activity associations between technological innovation, renewable energy consumption and ecological footprint for APEC from 1990 to 2017. They found that use of renewable resources could significantly improve environmental quality, but that technological innovation activities and economic growth had a chronically deteriorating trend on environmental quality. Similarly, in the case of China, the persistent impact of clean energy consumption and green economy development, i.e., a potential pathway to mitigate pollutant emissions, on the abatement of CO2 emissions was studied by Wan (2022). According to their results, the practical role of clean energy consumption in decreasing CO2 emissions is verified; in this regard, this impact comes from continuous increase and structural transformation of clean energy consumption.
In summary, the existing literature has yielded fruitful results on the study of carbon emissions and environmental issues, as shown in Table 1, but there are still certain drawbacks and room for improvement. Further investigation is needed to reach a consensus on a clear understanding of the mechanisms of generation and mitigation of CO2 emissions. Flaws in methodology, unclear results, and insufficient evidence for individual countries create a motivation to consider the dynamic relationship among green innovation, environmental regulation, energy consumption, and CO2 emissions in China. Overall, this paper attempts to provide new perspectives on the driving factors of carbon reduction and improves our understanding of the impact mechanisms, implementation pathways, and policy designs needed to successfully achieve synergistic development of the green economy and environmental protection in China.
Table 1. Overview of related literature on the nexus between GI, ER, EC and CO2 emissions.
Authors
|
Research area
|
Period
|
Methods
|
Key findings
|
Yuan et al. (2021)
|
China
|
2005-2017
|
Fixed-effect model
|
GI significantly reduced CO2 emissions.
|
Ali et al. (2022)
|
BRICS economies
|
1990-2014
|
AMG estimators
|
GI significantly reduced CO2 emissions.
|
Li et al. (2022)
|
China
|
1992-2014
|
NARDL method
|
GI contribute to reducing CO2 emissions.
|
Jiang et al. (2022)
|
BRICS countries
|
1985-2018
|
DCCEMG method
|
GI can significantly curb CO2 emissions.
|
Erdoğan et al. (2020)
|
G20 countries
|
1997-2017
|
CCE and AMG estimators
|
Innovation expenditure significantly reduced CO2 emissions.
|
Lingyan et al. (2021)
|
Highly decentralized countries
|
1990-2018
|
Moment quantile regression method
|
Environmental innovations reduce CO2 emissions.
|
Xu et al. (2022)
|
China
|
2009-2018
|
Spatial econometric model
|
Green innovation technologies can significantly curb CO2 emissions.
|
Zhu et al. (2022)
|
China
|
2004-2018
|
Mediation effect model
|
Green technology innovation can decrease regional CO2 emission intensity.
|
Li and Ramanathan (2018)
|
China
|
2004-2014
|
Quadratic function regression model
|
ER has a positive impact on environmental performance.
|
Hashmi and Alam (2019)
|
OECD countries
|
1999-2014
|
GMM model
|
Environmental taxes can effectively reduce CO2 emissions.
|
Hou et al. (2018)
|
China
|
2010-2015
|
Dynamic
threshold model
|
ER significantly facilitates a decrease in carbon intensity.
|
Musah et al. (2021)
|
North Africa countries
|
1990-2015
|
AMG and CCEMG estimators
|
EC significantly exacerbated CO2 emissions.
|
Usman and Hammar (2020)
|
APEC countries
|
1990-2017
|
FGLS, AMG, and CCEMG estimators
|
The utilization of renewable resources can significantly improve environmental quality.
|
Wang et al. (2022)
|
China
|
2000-2019
|
VAR model
|
Clean energy consumption contributed to the abatement of CO2 emissions.
|
Abbreviations: AMG, Augmented Mean Group; NARDL, Nonlinear Autoregressive Distributed Lag; DCCEMG, Dynamic Common Correlated Effect Mean Group; CCE, Common Correlated Effect; AMG, Augmented Mean Group; GMM, Generalized Method of Moment; FGLS, Feasible Generalized Least Squares; VAR, Vector Autoregression.