Renewable energy, GDP and CO2 emissions in high-globalized countries

Introduction: Policymakers devote significant efforts to decrease CO₂ emissions, as climate change has Q7 numerous adverse impacts on society. While the global level of CO₂ emissions has been gradually rising since the 1990s, the highest growth was observed in low- and middle-income economies. This study differs from nascent research as it fills the gap by exploring the GDP-energy-CO₂ emissions nexus for the top 50 highly globalized countries under analysis. Our study explores the multidimensional relationship between economic growth, renewable energy, globalization, and climate change, using CO₂ emissions as a proxy for air pollution, and focusing on the most globalized countries.

Methods: In this study, we rely on dynamic panel estimators such as the two-step system GMM estimator. System GMM estimator is recommended to use with the panel data when 1) the correlation between a dependent variable and its lag is above 0.8; and 2) the number of countries (i.e., 50 countries) exceeds the time frame (i.e., 19 years). As our study design fits these conditions, we use extension of a two-step system GMM estimator which restricts the expansion of instruments. Moreover, a two-step system GMM estimator is especially efficient as it controls for heteroskedasticity.

Results: We find that renewable energy and globalization decrease CO₂ emissions. If causal, a 1 percentage point increase in the share of renewable energy in total energy consumption leads to a 0.26% decrease in per capita CO₂ emissions. Similarly, we find that a larger representation of women in national parliament contributes to the reduction in CO₂ emissions. GDP per capita has an inverted U-shaped relationship with CO₂ emissions and the turning point is approximately 67,200 international dollars adjusted for PPP.

Discussion: Our results suggest that renewable energy significantly contributes to the reduction of carbon emissions while GDP per capita has an inverted U-shaped link with CO₂ emissions. Thus, we confirm the presence of the EKC hypothesis for highly-globalized countries. Consequently, our study offers several policy implications. Firstly, it is important for developing countries to increase the share of energy consumed from renewable energy sources. This will have a positive effect not only on air quality, but also on economic growth. Thus, it is essential to increase investment in the renewable energy sector and create conditions and benefits for the rapid adoption of renewable technologies by the private sector and households. Secondly, it is crucial to increase the quality of investment climate. Developing countries can significantly gain from globalization-driven FDI as this can lead to technology transfer, especially in the energy sector. Thirdly, our results suggest that improving female empowerment can significantly reduce the vulnerability to climate change. This can be achieved by increasing women’s human capital and investing in women-led organizations and communities.

Introduction

Policymakers devote significant efforts to decrease CO₂ emissions, as climate change has numerous adverse impacts on society. While the global level of CO₂ emissions has been gradually rising since the 1990s, the highest growth was observed in low- and middle-income economies. Scholarly literature suggests that economic growth and energy consumption are considered as main antecedents of CO₂ emissions at global and regional levels (Acaravci and Ozturk, 2010; Saboori and Sulaiman, 2013). As a result, the transition towards energy efficient and green economic growth has been acknowledged as a new sustainable development agenda. Indeed, the examination of the GDP-energy-CO₂ emissions links has grown considerably in size over the past two decades. Along these lines, with the focus on environmental degradation, the literature can be separated into three streams. The first line of research explores the relationship between economic development and CO₂ emissions through the underpinnings of the Environmental Kuznets curve (EKC) framework stemming from the study by Grossman and Krueger (Grossman and Krueger, 1991). The EKC theory suggests inverted U-shape relationship between economic growth and environmental degradation and posits that “environmental pressure increases faster than income in the early stage of development and slows down relative to GDP growth in higher income levels” (Dinda, 2004). In low-income countries, industrialization and rapid growth of related industries spur pollution due to intensified economic activities and prioritization of economic growth. However, as GDP per capita increases the adoption of energy-efficient technologies and the development of industries with lower carbon footprint remove thepressure on the environment, and carbon emissions decrease. The empirical assessment of the existence of the EKC has proliferated with the increased availability of cross-country data [see, e.g., Anwar et al. (2022) for an excellent bibliometric analysis]. For example, the EKC has been confirmed for single countries such as Kenya (Sarkodie and Ozturk, 2020), Malaysia (Suki et al., 2020), Bangladesh (Murshed et al., 2021) and Brazil (Polloni-Silva et al., 2021). In a similar vein, inverted U-shaped link between GDP and CO₂ emissions has been validated for various regions, including PIIGS countries (Balsalobre-Lorente et al., 2022), E7 countries (Bekun et al., 2021), East African countries (Demissew Beyene and Kotosz, 2020), among others. At the same time some studies fail to identify EKC [see, e.g., Dogan and Inglesi-Lotz (2020) for European region, Dogan et al. (2020) for BRICST, Haliru et al. (2020) for West African countries, Ansari et al. (2020) for GCC countries].

The second group of studies explores how renewable energy in the total energy mix influences air quality, and, especially how it can mitigate climate change effects without harming economic growth trajectories. Indeed, a meta-analysis of more than 79,000 studies by (Kılıç Depren et al., 2022) shows that “the number of renewable energy-related studies has exceeded the number of fossil fuel-related studies regarding environmental degradation” (p. 1). Energy is considered an instrumental driver of economic growth (Tang et al., 2016) but it has also been shown to be linked to air pollution (Wang et al., 2018). In contrast, a shift towards the use of renewable energy as a replacement for fossil fuels has been documented to increase air quality and improve energy security (Aized et al., 2018). Moreover, numerous studies confirm the positive contribution of renewable energy to quality of life by showing that investment in renewable energy increases longevity (Rodriguez-Alvarez, 2021) and decreases human mortality (Shah et al., 2022) and income inequality (Topcu and Tugcu, 2020). The International Energy Agency expects that global renewable energy supply can increase by more than 60% compared to the year 2020 (IEA, 2021). Thus, increase deployment of renewables can have numerous positive implications as suggested by extant research. The third strand of studies considers the role of additional macroeconomic factors beyond renewable energy and GDP per capita. Within this stream of published evidence global integration is recognized as one of the essential predictors of CO₂ emissions. Under the assumptions of the pollution haven hypothesis (PHH), globalization drives the relocation of carbon-intensive industries to countries with less stringent environmental regulations. Thus, PHH conjectures a positive link between globalization and CO₂ emissions. However, the pollution halo hypothesis postulates that globalization leads to the export of green energy-efficient technologies which expands economic activity without pressure on the environment (Zhang and Zhou, 2016). A number of studies have indeed confirmed that globalization improves environmental quality and increases energy efficiency (Baloch et al., 2021; Liu et al., 2022). The analysis of the effects of renewable energy and GDP per capita on CO₂ emissions in the context of high-globalized countries is exceptionally relevant. A significant breakthrough in globalization can affect CO₂ emissions via shifts in energy demand (Doğan et al., 2022), effective distribution of production inputs, technological diffusion, and increased exchange of knowledge (Samimi and Jenatabadi, 2014). To the best of our knowledge, extant studies have explored the joint effects of economic growth, renewable energy, and globalization on CO₂ emissions and reported mixed results. This study differs from nascent research as it fills the gap by exploring the GDP-energy-CO₂ emissions nexus for the top 50 highly globalized countries under analysis. Our study explores the multidimensional relationship between economic growth, renewable energy, globalization, and climate change, using CO₂ emissions as a proxy for air pollution, and focusing on the most globalized countries. As (Leal and Marques, 2020) suggest “globalization is a complex phenomenon made up of many components. Its effect on the environment, when studied as a whole, leaves many questions unanswered” (p. 37). Over the last two decades, two important trends have emerged: a surge in renewable energy deployment and increased globalization in less-developed countries. All these advancements indicate that renewable energy use and economic growth are thus likely to have impacts on greenhouse gas emissions depending. The rest of the study is structured as follows. Section 2 provides a brief overview of the recent empirical literature. Section 3 presents the data and methodology. Section 4 discusses the main results while Section 5 concludes the study.

Literature review

Carbon emissions and GDP per capita

Theoretical claims and empirical studies of the link between GDP per capita and CO₂ emissions overall suggest the existence of an inverted U-shaped (the so-called EKC) relationship. (Murshed et al., 2020) investigated the EKC hypothesis for OPEC member states using panel spatial regression models. The results for the years 1992–2015 confirm the validity of the EKC hypothesis. At the same time, the sectoral analysis also shows the significance of the non-linear relationship between value added and air pollution varies depending on the sub-sector. (Dogan and Inglesi-Lotz, 2020) examined the relationship between GDP, economic structure, and CO₂ emissions, under the EKC framework for Europe for the years 1980–2014. The study discovered that aggregate economic growth exerts an inverted U-shaped link with CO₂ emissions. However, economic structure has a U-shaped effect on air pollution. (Bibi and Jamil, 2021) tests the existence of the EKC hypothesis for six regions over the period 2000–2018. The study using random effects and fixed effects models documents that EKC is valid for the majority of the regions. Using panel data for EU countries, (Bekun et al., 2021) endorses the existence of an inverted U-shaped relationship between economic development and environmental degradation. The Granger causality test further shows that causality runs from GDP growth to air pollution. (Heidari et al., 2015) found that economic growth is non-monotonically related to CO₂ emissions in ASEAN countries. The panel smooth transition regression (PSTR) validates the EKC hypothesis with the threshold regime at 4,686 USD. (Leal and Marques, 2020) examined the presence of the EKC hypothesis in the top 20 highest CO₂ producing economies over the period 1990–2016. The Driskoll-Kraay estimator showed that EKC is only valid for highly-globalized countries. Noteworthy, a number of studies explored the EKC hypothesis focusing on a single country. (Pata, 2018) analyzed Turkey over the period 1974–2014 using ARDL and FMOLS regressions, documenting the statistically significant inverted U-shaped evidence between GDP and CO₂ emissions. However, the long-run estimates showed that the turning point is 13,523–14,077 US Dollars which is outside the sample data. (Katircioğlu, 2014) document the validity of the tourism-driven EKC hypothesis for Singapore between 1971–2010, using Maki cointegration and other time series regression methods. At the same time, (Ișik et al., 2020) explored the presence of the tourism-induced EKC hypothesis for G7 countries from 1995–2015. The authors discovered that the tourism-induced EKC hypothesis holds only for France.

Renewable energy and CO₂ emissions

The relationship between renewable energy and carbon emissions was examined by using regional and single-country cases. The majority of these studies report that renewable energy deployment mitigates CO₂ emissions. Using a number of panel data methods (Haldar and Sethi, 2021) found that renewable energy decreases CO₂ emissions in the long run in the case of 39 developing countries over the period 1995–2017. Moreover, the study highlights that it is instrumental to improve quality of institutions and increase the use of renewable energy to raise air quality. (Zoundi, 2017) tests the hypothesis of whether renewable energy can act as an efficient replacement for fossil fuels for 25 African countries over the period 1980–2012. While the study fails to confirm EKC for selected African countries, renewable energy has a negative and significant effect on CO₂ emissions. By using the cointegration estimator and Granger causality test, (Ben Jebli et al., 2019a) examines the relationship between renewable energy, GDP growth, and CO₂ emissions across 22 Central and South American countries between 1995–2010. The study found that there is unidirectional causality from renewable energy and FDI to CO₂ emissions. The study stresses the need to encourage renewable energy adoption to mitigate climate change. (Dogan and Seker, 2016) assess the drivers of CO₂ emissions in EU member states over the period 1980–2012. Using the dynamic OLS regression method, the authors find that renewable energy mitigates CO₂ emissions and GDP has an EKC type relationship with air pollution. The study also documents bi-directional causality between renewable energy and CO₂ emissions. In turn, using the generalized spatial two-stage least squares (GS2SLS) method, (Radmehr et al., 2021) found a unidirectional causality running from renewable energy to CO₂ emissions. (Leitão and Lorente, 2020) confirms that trade, tourism, and renewable energy reduce climate change in EU member states, using FMOLS, DOLS, and GMM estimators. At the same time, the study showed that economic growth is positively associated with environmental degradation. In turn, (Huang et al., 2021) focus on major energy-consuming economies to assess the relationship between renewable energy and carbon emissions over the period of 2000–2015. Using a two-step GMM estimator, the authors show that the renewable energy sector has substantial potential to mitigate climate change effects in countries with the highest demand for energy use. Mentel et al. (2022b) examine the relationship between industrialization, renewable energy, and CO₂ emissions in 48 countries of Europe and Central Asia (ECA). The study using a two-step GMM estimator finds that 1) renewable energy decrease CO₂ emissions; 2) renewable energy offsets the positive effect of industrialization on CO₂ emissions; 3) the EKC hypothesis is verified for ECA countries. In the case of single-country studies, the importance of renewable energy to decrease CO₂ emissions was verified for Ecuador, Thailand, China, India, and Portugal, among others (Robalino-López et al., 2014; Sinha and Shahbaz, 2018; Chen et al., 2019; Abbasi et al., 2021a; Adebayo et al., 2022).

Globalization and CO₂ emissions

A separate strand of studies has explored the role of globalization in the presence of EKC framework. For example, Farooq et al. (2022) assessed the relationship between globalization and environmental quality in a sample of 180 nations over the period 1980–2016. Using panel quantile regression methods, the authors find that only economic dimension of globalization has negative effect on CO₂ emissions. Liu et al. (2020), using semi-parametric fixed effects regression estimator for a sample G7 countries over the period 1970–2015, find that globalization exerts non-linear impact on CO₂ emissions. Mehmood (2021) documents that social and economic globalization decrease CO₂ emissions in Singapore using ARDL estimator. Mehmood and Tariq (2020) observed mixed results for South Asian countries over the period 1972–2013. The authors find that inverted U-shaped relationship exists in Nepal, Afghanistan, Bangladesh and Sri Lanka, while U-shaped relationship is observed for Pakistan and Bhutan. Nguyen and Le (2020) use ARDL estimator to assess the relationship between globalization and CO₂ emissions in Vietnam over the period 1990–2016. The results show that globalization increases CO₂ emissions while export oriented policies lead to a reduction in environmental degradation. Overall, the review of studies shows that the effects of globalization are at best mixed for different regions and countries.

Empirical model and data

Empirical model

Although there is no universally adopted empirical model for CO₂ emissions, numerous scholars such as (Mirziyoyeva and Salahodjaev, 2022b; Khoshnevis Yazdi and Shakouri, 2018; Sun et al., 2022; Satrovic and Muslija, 2019; Salahodjaev et al., 2022) included urbanization, tourism, and women’s presence in parliament among others to model the relationship between renewable energy, GDP per capita, and CO₂ emissions. These studies report that these variables are essential and exhibit significant effects on greenhouse gas emissions. Therefore, our suggested model, which appears to be in line with the general empirical literature on CO₂ emissions discussed above can be expressed as:

${CO}_2=f\left(GDP,RE,URB,TR,WP,KOF\right)(1)$

This generally implies that CO₂ emissions is a function of GDP per capita (GDP), renewable energy consumption (RE), urban population growth (URB), tourism receipts (TR), proportion of women in parliament (WP) and KOF index of Globalization as a proxy for globalization. Considering the panel structure of our data, Eq. 1 can be re-written in the following manner:

$\begin{array}{ll}\hfill {CO}_{2i,t}& =a_0+a_1{GDP}_{i,t}+a_2{GDP}_{i,t}^2+a_3{RE}_{i,t}+a_4{URB}_{i,t}+a_5{TR}_{i,t}\hfill \\ \hfill & +a_6{WP}_{i,t}+a_7{KOF}_{i,t}+{\epsilon }_{i,t}\hfill \end{array}(2)$

where i represents country (in this research, we have 50 countries), t stands for time (the time period for this study is between 2000 and 2019) and ε is an error term. We also include GDP squared term to examine the presence of the EKC hypothesis in our sample.

Data and summary statistics

The data applied in this paper come from the World Bank and cover 2000–2019. The variables used are CO₂ emissions (measured in metric tons per capita), GDP per capita (measured in constant 2017 international $), renewable energy consumption (measured in percentage of total final energy consumption), urbanization (measured in annual urban population growth, %), tourism (as a ratio to GDP), female parliamentarians (proportion of seats held by women in national parliaments) and KOF index as a proxy for globalization.

The descriptive statistics are reported in Table 1. In this study, following related research on CO₂ emissions, we rely on dynamic panel estimators such as the two-step system GMM estimator. For example, (Asongu et al., 2017), highlights that “(system GMM estimator) considers cross-country variations; accounts for potential endogeneity in all regressions via instrumentation and controls for the unobserved heterogeneity and eliminates potential small sample biases from the difference estimator” (p. 355). System GMM estimator is recommended to use with the panel data when 1) the correlation between a dependent variable and its lag is above 0.8; and 2) the number of countries (i.e., 50 countries) exceeds the time frame (i.e., 19 years). As our study design fits these conditions, we use (Roodman, 2009) extension of a two-step system GMM estimator which restricts the expansion of instruments. Moreover, a two-step system GMM estimator is especially efficient as it controls for heteroskedasticity. The GMM estimator has been intensively used in energy and environmental studies to model the predictors of CO₂ emissions (Bakhsh et al., 2021; Mentel et al., 2022a; Mentel et al., 2022b; Jiang and Khan, 2023). Our suggested model under the condition of a two-step GMM estimator can be presented as follows:

${CO2}_{i,t}={\sigma }_0+{\sigma }_1{CO2}_{i,t-\tau }+{\sigma }_2{RE}_{i,t}+{\displaystyle \sum _{h=1}^k}{\gamma }_h{X}_{h,i,t-\tau }+v_{i,t}(3)$

$\begin{array}{ll}\hfill {CO2}_{i,t}-{CO2}_{i,t-\tau }& ={\sigma }_1\left({CO2}_{i,t-\tau }-\mathit{ln}{CO2}_{i,t-2\tau }\right)+{\sigma }_2\left({RE}_{i,t}-{RE}_{i,t-\tau }\right)\hfill \\ \hfill & +{\displaystyle \sum _{h=1}^k}{\delta }_h\left(X_{h,i,t-\tau }-X_{h,i,t-2\tau }\right)+\left(v_{i,t}-v_{i,t-\tau }\right)\hfill \end{array}(4)$

where σ are the coefficients to be estimated, X is the vector of control variables (GDP, WP, URB, TR, KOF), τ is the coefficient of auto-regression and υ is two-way disturbance term.

TABLE 1

TABLE 1. Summary statistics.

Results

We present our empirical results in Table 2. We use both fixed and random effects estimators, although the Hausman test suggests that a fixed effects estimator is suitable for the baseline analysis (Chi-Sq. stat = 204.77, Chi-sq. Prob. = 0.0000). Therefore, we only interpret the results from a fixed effects regression (Table 2). First, we find that GDP per capita has an inverted U-shaped association with CO₂ emissions. The turning point for GDP per capita beyond which economic growth decreases CO₂ emissions is 90,000 international dollars. The estimate of the RE is in line with theoretical assumptions. The obtained estimate of −0.0100 documented for renewable energy use is statistically significant at the 1% level. The results suggest that one standard deviation increase in RE is associated with a 14% decrease in CO₂ emissions. In a similar trend, the representation of women in parliament leads to improvement in air quality. These results confirm the importance of female empowerment for environmental sustainability documented by (Lv and Deng, 2019) and (Mirziyoyeva and Salahodjaev, 2022a). We observe that urban population growth decreases CO₂ emissions in high-globalized countries. In accordance with (Ben Jebli et al., 2019b), we find that tourism contributes to the decrease in carbon emissions: one standard deviation increase in per capita tourism receipts leads to a 2.7% decrease in CO₂ emissions. The KOF index of globalization is negative, although statistically insignificant. This may imply that globalization does not induce direct reduction in CO₂ emissions, once countries pass certain threshold levels. The impact of globalization may be moderated by other variables such as economic development or tourism sector development.

TABLE 2

TABLE 2. Fixed effects regression.

However, the results in Table 2 only offer correlational evidence for our variables of interest. Thus, to assess the impact of renewable energy and globalization on CO₂ emissions we need to correct for the potential endogeneity. Therefore, Table 3 reports the results for the two-step system GMM estimator. Hansen J-test and second-order autocorrelation [AR (2)] tests confirm the validity of the instruments based on the difference and level equations.

TABLE 3

TABLE 3. System GMM results.

We find that renewable energy and globalization decrease CO₂ emissions. If causal, a 1 percentage point increase in the share of renewable energy in total energy consumption leads to a 0.26% decrease in per capita CO₂ emissions. These results can be compared to findings from other regions. For example, Mirziyoyeva and Salahodjaev (2022) find that 1 percentage point increase in renewable energy leads to 0.98% decrease in CO₂ emissions in top carbon intense economies. Radmehr et al. (2021) for the EU member states show that 1% increase in per capita renewable energy use leads to 0.05% decrease in CO₂ emissions. In addition, these results are similar to (Abbasi et al., 2021b) for Thailand and (Fu et al., 2021) for BRICS. The enhancing impact of globalization on air quality can be interpreted by the fact that globalization promotes the transfer of technologies that are friendly to air quality (Rahman, 2020). Similarly, we find that a larger representation of women in national parliament contributes to the reduction in CO₂ emissions. Extant research suggests that an increase in the women’s share of seats in parliament improves the quality of institutions and the adoption of policies aimed at improvement in quality of life (Ergas and York, 2012; Mavisakalyan and Tarverdi, 2019; Salahodjaev and Jarilkapova, 2019). GDP per capita has an inverted U-shaped relationship with CO₂ emissions and the turning point is approximately 67,200 international dollars adjusted for PPP. The AR (2) test and Hansen p-value estimates confirm the validity of the use of the econometric approach and the credibility of instruments derived by the system GMM estimator.

We test the robustness of our main results by considering whether the effect of renewable energy on CO₂ emissions in high-globalized countries holds after accounting for the dynamics in the GDP structure. We do so by including the level of industrialization to capture the shift from agriculture to industry driven economic growth. A number of studies how that (Li and Lin, 2015; Liu and Bae, 2018) industrialization increases energy consumption and contributes to CO₂ emissions. At the same time, Mehmood and Tariq (2020) and Mentel et al. (2022c) show that renewable energy consumption can influence the effect of industrialization on CO₂ emissions. Therefore, we check whether the effect of renewable energy on CO₂ emissions retains its significance once we account for the level of industrialization in high-globalized countries (Table 4). The results show that industry value added as a share of GDP is positively linked to per capita CO₂ emissions. At the same time, the interaction term between renewable energy and CO₂ emissions is negative and significant, at the 1% level. This suggests that increasing renewable energy consumption can help to promote industrial transformation, not at the expense of environmental degradation. The estimates for other variables are not affected and remain robust.

TABLE 4

TABLE 4. Industrialization, renewable energy, and CO₂ emissions.

Conclusion

Greenhouse gas emissions have emerged as one of the key topics of discussion within the international agenda. Consequently, policymakers in developed and developing countries attempt to identify the predictors of CO₂ emissions that can help to select and enforce policies which can lead to a reduction in air pollution without harming economic growth. Against this backdrop, environmental research suggests that energy consumption and GDP are among the core predictors of CO₂ emissions in global and single-country studies. Despite that research on renewable energy, economic growth, and CO₂ emissions has grown considerably over the past decade, no study explored the effect of GDP growth and renewable energy consumption on CO₂ emission in highly-globalized countries. Our results are based on panel data between 2000 and 2019. We particularly focused on the top 50 countries by KOF index of Globalization. Our results suggest that renewable energy significantly contributes to the reduction of carbon emissions while GDP per capita has an inverted U-shaped link with CO₂ emissions. Thus, we confirm the presence of the EKC hypothesis for highly-globalized countries. Moreover, we found that an increase in the share of female parliamentarians decreases CO₂ emissions. Consequently, our study offers several policy implications. Firstly, it is important for developing countries to increase the share of energy consumed from renewable energy sources. This will have a positive effect not only on air quality, but also on economic growth. Thus, it is essential to increase investment in the renewable energy sector and create conditions and benefits for the rapid adoption of renewable technologies by the private sector and households. Secondly, it is crucial to increase the quality of investment climate. Developing countries can significantly gain from globalization-driven FDI as this can lead to technology transfer, especially in the energy sector. Thirdly, our results suggest that improving female empowerment can significantly reduce the vulnerability to climate change. This can be achieved by increasing women’s human capital and investing in women-led organizations and communities. The adoption of these measures can be anticipated to help emerging economies in decreasing CO₂ emissions under the international greenhouse gas emissions targets. Our study has a number of limitations that can serve as avenue for future research. For example, we did not assess the bi-directional causality between globalization, renewable energy and CO₂ emissions. However, scholars can test these relationships for single top-globalization countries to extend our understanding of the interlinks between renewable energy and carbon emissions. In addition, it is essential to assess the impact of other energy-related variables on the CO₂ emissions in high-globalized countries such as energy intensity, fossil fuel consumption or electricity consumption.

Data availability statement

Publicly available datasets were analyzed in this study. This data can be found here: World Bank.

Author contributions

ZM and RS: data collection and methodology. RS: formal analysis. ZM: writing original draft and conceptualization. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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