
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13015-0
10.1016/j.heliyon.2024.e36984
e36984
Research Article
Exploring the impact of renewable energy, green taxes and trade openness on carbon neutrality: New insights from BRICS countries
Li Yanfeng yanfeng.li@bnu.edu.cn
a⁎⁎
Liu Jingru liujingru@sdepci.com
b⁎
Li Yanlei liyanlei@spic.com.cn
cd
a State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
b Shandong Electric Power Engineering Consulting Institute Corp., Ltd., Jinan 250013, China
c MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
d State Power Investment Group Beijing Electric Power Corp., Ltd., Beijing 100032, China
⁎ Corresponding author. liujingru@sdepci.com
⁎⁎ Corresponding author. yanfeng.li@bnu.edu.cn
27 8 2024
30 9 2024
27 8 2024
10 18 e3698422 3 2024
14 8 2024
26 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The world faces two significant challenges: promoting sustainable economic growth and reaching carbon neutrality. In BRICS countries, these challenges are shaped by renewable energy, green taxes, and trade openness. These countries were selected for their strategic location and the abundance of relevant data collected over the period of 1990–2021, providing a distinctive window into the energy and economic dynamics of the area. The link between renewable energy consumption, green taxes, trade openness, and natural resources and their effects on carbon emissions in BRICS countries is examined in this study using the Fully Modified Ordinary Least Square Method (FMOLS) estimator and the Drisc Kraay estimator for the robustness test. The findings indicate that using renewable energy and green taxes primarily contribute to reducing emissions, particularly at higher emissions levels. The study reveals that various factors, namely financial globalization, trade openness, efficient resource management, and population growth, substantially impact carbon neutrality. Population growth positively impacts carbon neutrality, while using renewable energy sources mitigates it. Furthermore, the empirical findings show a statistically significant positive association between financial globalization, efficient resource management, and carbon neutrality in BRICS nations. Therefore, it is necessary to implement an integrated ecological governance strategy to control and direct financial resources towards sustainable development and green energy.

Keywords

Renewable energy
Green taxes
Trade openness
Carbon neutrality
BRICS countries
==== Body
pmc1 Introduction

For a nation's economy and society to thrive, it is necessary to have an environment that is clean, healthy, and comfortable. This ecosystem is essential for preserving both living and non-living natural resources, including humans, for societal and economic purposes [1]. As a result of both natural and artificial pollutants, environmental conditions might worsen [2]. Emissions of carbon dioxide are one of these pollutants that degrade environmental quality. The ozone layer is a stratospheric protecting barrier that safeguards life from damaging UV radiation; its depletion could result from the emission of CO2, a dangerous gas. Consequently, CO2 emissions trap heat within the Earth's crust, leading to global warming, an unbalanced climate loop, human and animal health destruction, and a decline in environmental quality overall [3,4]. On top of that, another robust layer's CO2 emissions prevent the sun's rays from re-entering the sky, leading to global warming [5]. Consequently, we expect a significant increase in the average world temperature. Carbon dioxide emissions and their effects, such as climate change, have far-reaching ramifications for Earth's ecosystems, weather systems, and the quality of its naturally existing resources, such as soil, food, minerals, and water [6]. A nation's sustained growth is unlikely since sustainable economic development necessitates a conducive and Productive working environment, abundant high-quality minerals, clean water, high bio-production, fertile land, and efficient labor. Khan et al. [7], Abbasi et al. [8], and others have shown that reducing CO2 emissions can mitigate environmental degradation.

Therefore, reducing emissions of carbon and greenhouse gases is the only way to achieve the goals of the Paris Global Climate Conference (COP21), according to experts, governments, and academics [9,10]. On the other hand, Wen et al. [11] think that there hasn't been enough done to combat climate change and global warming. Therefore, policies and regulations that benefit the environment must be in place. Environmental degradation is a significant problem, but economists, specialists, and scholars face the formidable task of devising a coordinated strategy to combat it [12].

Several policy choices must be considered while developing an environmental strategy to lower carbon emissions. The following claims are significant primarily from ecological, global, macroeconomic, and governance viewpoints: (1) Green energy, often known as renewable energy, (2) incorporating environmentally friendly levies (GT), (3) encouraging free trade (TO), (4) enhancing financial integration (FG), (5) fostering effective management of resources (ERM), and (6) fostering population expansion (PGR).

The first proposal is based on the idea that renewable energy usage should be encouraged since it contributes to a decrease in carbon emissions. According to Wang et al. [13], the leading cause of CO2 emissions and ecological damage is the use of energy from fossil fuels. Renewable energy usage is set to skyrocket, with a predicted 60 % growth by 2040 [14]. According to Samour et al. [15], a clean and green environment requires 50–80 % of energy from renewable sources. According to recent research, sustainable and green economics are supposedly reshaping the world's industrial structure, decreasing in CO2 emissions [16]. Several studies have shown that transitioning to renewable energy sources would create a more sustainable environment. These include Yi et al. [17], Xie et al. [18], Hu et al. [19], and Luo et al. [20].

The second proposal encourages green taxes (GT), which reduce carbon emissions. Green taxes are the most significant and successful public policy measure to reverse climate change, achieve the SDGs (particularly objectives 7 and 13), and reduce pollution. According to Akeel et al. [21], GTs reduce environmental harm by internalizing negative externalities and incorporating production factor costs into the market process. Pigouvian taxation aims not to eliminate environmental degradation but rather to reduce it to an optimal level, and this point must be emphasized. But that's not all GTs do; they also aid in reducing pollution. By incentivizing business owners to develop innovative technology, GTs also contribute to expanding green innovation. Furthermore, by persuading companies that being environmentally conscious is more advantageous than paying taxes, GTs play a long-term role in the battle against climate change. According to Dudek et al. [22], traditional energy firms are anticipated to be motivated to develop green energy solutions in response to the punitive character of ETs. Additionally, companies with high energy consumption tend to select environmentally friendly options. Therefore, reducing emissions of carbon and greenhouse gases is the only way to attain the goals of the Paris Global Climate Conference (COP21), according to experts, governments, and academics [23,24]. On the other hand, Funhas et al. [25] think that there hasn't been enough done to combat climate change and global warming. Therefore, policies and regulations that benefit the environment must be in place. Environmental degradation is a significant problem, but economists, specialists, and scholars face the formidable task of devising a coordinated strategy to combat it [26].

The third proposal encourages free trade, which lowers carbon dioxide emissions. It plays a significant role in personal, professional, and societal life. According to Ahmed et al. [27], it links economies through financial globalization and economic growth but also leads to ecological degradation through sulfur and carbon emissions. The demand for goods and services has increased due to globalization, which speeds up financial activity [28,29] found that economic activities upsurge energy use, leading to environmental degradation. Prior research has yielded conflicting results concerning TO and its environmental effects. Research by Gnangoin et al. [30], Khan et al. [31] and Nan et al. [32] supports the idea that TO enhances environmental quality. But there's also evidence that TO contributes to greenhouse gas emissions [33,34].

Economic growth (GDP), environmental quality, and financial globalization (FG) are all interrelated in the fourth argument [35]. Economic activity occurs due to loans made by the financial sector to private creditors via institutions. According to Wei et al. [36], Huan et al. [37], Sun et al. [38], and [39], there is still debate about whether financial development enhances environmental quality. Shabir et al. [40] and Piwowar-Sulejet al. [41] believe that FG increases the quality of the environment. The trends of these factors can be seen in Fig. 1.Fig. 1 Trend of study factors in BRICS

Fig. 1

When we narrow our focus to the BRICS economies, we find that this group of nations accounts for 42 % of the planet's population and 23 % of its GDP. According to Musah et al. [42], the BRICS economies are accountable for 40 % of the world's energy consumption and 43 % (15.5 billion tons) of its carbon emissions in 2015. This is because they are among the top 10 energy users worldwide. The fast-economic expansion of the BRICS nations significantly contributes to their high pollution levels. This makes it harder for economies to reach sustainable development targets despite their promises to limit global temperature increases through increased efforts to tackle environmental problems. Given the gravity of the situation, investigating potential strategies for these economies to reduce their GHG emissions is crucial. What policies and tactics would be most helpful in this kind of scenario? As previously said, the BRICS economies face challenges from institutions related to their rapid economic expansion and significant carbon emissions. To meet this aim, drastic policy changes are necessary [43]. Regarding “geo-economies, rapid productivity growth and involvement in international economic integration,” the BRICS countries are reportedly the most noteworthy examples of recently rising economies. China has accounted for 30 % of the planet's emissions in 2020, making it one of the biggest carbon producers globally and other countries' contributions to global emissions were 6 % for Russia, 4.71 % for India, 1.29 % for Brazil, and 1.09 % for South Africa [44]. Therefore, these nations should guide other economies to reduce damaging emissions through sustainable activities. Still, their capacity to do so is constantly questioned due to their huge carbon emission shares. Therefore, to fulfil the vow, BRICS nations must face terrible hurdles; this study helps the policymakers in overcoming these challenges. According to the study, carbon taxes, renewable energy, free trade, and effective management of resources are some of the tools that might be used to reduce emissions [45].

With the aforementioned environmental challenges in mind, this research delves deeply into the following areas: economics, energy, regional connections, governance, and ecology: one, this study addresses a knowledge vacuum in the literature by developing a multivariate framework to explain carbon neutrality (CO2) using green energy (GRN), green taxes (GT), trade openness (TO), financial globalization (FG), and efficient resources management (ERM) as its main explanatory variables. Furthermore, as control variables, we also included demographic and socioeconomic trends. As far as we know, green energy, trade openness, financial globalization, and green levies on carbon emissions have yet to be studied. Second, past research has yielded contradictory findings while looking for explanatory variables that affect environmental quality (CO2). In response to these concerns, we will explain how institutions, lawmakers, and others can reduce carbon emissions by creating new regulations, policies, and practices. Third, a panel technique, the “Generalized Method of Moment” (GMM), was utilized to ensure dependable results in our dynamic system. The Hansen-Sargan test and the supplementary information regarding autocorrelation AR (1) and AR (2) set it apart from other econometric methods in treating heterogeneity and endogeneity. In addition, we verified the interdependence of the variables by applying panel Granger causality. In the fourth place, we have chosen a sample of 31 years, beginning in 1990 and ending in 2021, and it consists of BRICS countries. The work aims to add to the current body of research in this way. According to Kutieshat et al. [46] and Chaudhry et al. [47], it lays out the theoretical groundwork by integrating environmental elements and revealing the combined impact of the described structure on CO2 emissions.

Section 2 reviews the previous studies, Section 3 lays out the theoretical framework and applicable methodology, Section 4 comprises the results and discusses them, and Section 5 gives the conclusion and policy implications. This is the overall structure of the study.

2 Literature review

An essential prerequisite for any nation's progress is a conducive environment comprising fundamental components such as soil, air, water, minerals, energy sources, forests, agricultural produce, and biodiversity. The superior quality of these resources contributes to the country's development, which is stimulated by a pristine and healthful environment. In contrast to the argument, a significantly contaminated environment contains non-renewable resources that have detrimental effects on the health of living organisms [48]. Environmental degradation poses a hindrance to the country's progress. Carbon dioxide (CO2) is a highly destructive element for the ecosystem. It disrupts the climate equilibrium, disturbs climate patterns, and negatively impacts the quality of natural resources [49,50]. To promote a pristine and salubrious environment nationwide, it is imperative to decrease CO2 emissions. Green financing, eco-innovation, green energy generation and consumption, and carbon taxes effectively mitigate CO2 emissions by optimizing company resources and processes and minimizing CO2 emissions.

2.1 Renewable energy and carbon neutrality

Fossil fuels are finite resources derived from ancient organic matter and are widely recognized as a highly efficient energy source. The use of these resources for energy need leads to the emission of CO2, and there is a growing trend in the consumption of fossil fuels for this reason. However, in contrast, using renewable energy sources does not result in the emission of any substances that generate CO2 [51]. Işık et al. [52] studied the effects of green energy consumption, non-green energy use, urban population, R&D expenditures, and technical innovation on carbon dioxide emissions. China provided data in a yearly period spanning from 1990 to 2019. The researchers employed the ARDL simulation approach. The study demonstrated that the use of green energy, albeit to a restricted degree, does not have a substantial effect on carbon dioxide emissions. However, substituting fossil fuels with renewable energy sources leads to a significant reduction in CO2 emissions as well as other detrimental gasses. Li et al. [53] to assessed the effects of Green energy (GRN) consumption on CO2 emissions. They proposed that the increasing usage of GRN for both household and economic activities contributes to reducing the total reliance on fossil fuels. It reduces the consumption of carbon-containing fuels prone to emitting CO2 when burned. Consequently, it is projected that the increase in GRN consumption will reduce CO2 emissions. Mngumi et al. [54] asserted that there is an inverse correlation between GRN consumption and CO2 emissions. Specifically, countries with more GRN consumption tend to emit lower levels of CO2.

Both the consumption and generation of GRN effectively combat environmental pollutants, such as CO2 emissions. Renewable energy generation directly sequesters carbon from the atmosphere, relieving people from pollution and its associated consequences. Furthermore, the rise in GRN production promotes utilizing resources and technologies that specifically rely on low-voltage clean energy sources. Consequently, it decreases the carbon dioxide emissions resulting from energy-related activities. Thus, the impact of GRN on CO2 emissions is negative, as demonstrated by Nasir et al. [55] and Hailiang et al. [56]. In their study, Işık et al. [57] ascertain the contribution of renewable energy output in reducing CO2 emissions. Data on GRN and CO2 was gathered from over one hundred nations, divided into four subpanels based on income, during the period spanning from 1995 to 2015. Several econometric methodologies were employed to analyze the dependence of CS and the heterogeneity of slopes. The study suggests that renewable energy output relies on naturally occurring materials such as heat, water, light, CO2, and human activity waste.

The rising renewable energy production decreases the current CO2 emissions and mitigates the risk of CO2 emissions from polluting trash. An inverse correlation exists between GRN output and CO2 emissions. Işık et al. [58] examined the correlation between GRN production and both the sustainability of energy and the sustainability of the environment, as measured by CO2 emissions. The research data was collected from hybrid renewable systems that generate electric power in Iran. The HOMER software was used to evaluate the correlation between these characteristics. According to the authors, the supply of sustainable energy is enhanced when there is a rise in GRN output, such as bioenergy, hydroelectric power, wind power, and solar power. Under these circumstances, the companies primarily conduct their commercial operations by utilizing GRN sources and actively minimizing carbon dioxide emissions. According to Zhou et al. [59], there is an negative correlation between GRN output and CO2 emission.

Similarly, the study [60] also examined the impact of GRN use on the carbon footprint of newly industrialized nations (NICs) between 1990 and 2018. Their findings diverge from the previously discussed studies and affirm the efficacy of utilizing GRN across all pollution levels. Research indicates that using GRN substantially reduces carbon emissions, particularly in Indonesia, where pollution levels are high. In addition, other studies conducted by,Ameer et al. [61] for BRICS, Xu et al. [62] for MENA [63], for Asian nations, and Tang et al. [64] for OECD countries acknowledged the impact of GRN on carbon emissions in the context of migration.

2.2 Carbon taxes & carbon emissions

When CO2 is emitted into the atmosphere by various human activities—personal, social, and economic—it undergoes a chemical reaction with oxygen. Because carbon taxes can reduce emissions, the government collects them from businesses and individuals who engage in carbon activities [65]. Examining how carbon prices affect CO2 emissions and ecological quality was the goal of Bulut et al. [66]. The scientists tested two scenarios involving European economies: one with carbon prices already in place and another with plans to install them. Using the propensity score matching method, we looked at how carbon prices affect CO2 emissions and environmental quality. The study's findings demonstrated that when implemented effectively, carbon taxes hasten the decline in CO2 emissions. Carbon taxes as an environmental control are supposedly well-imposed and implemented in countries where individuals want to minimize their use of non-carbon-producing activities, communication tools, and transportation options. Consequently, carbon taxes do an excellent job of reducing carbon dioxide emissions.

Upon reviewing the empirical literature, one cannot help but notice the contradictory findings of the few researches that have looked at the link between GTs and either CO2 emissions or environmental sustainability. Li et al. [67] claims that GTs don't work when looking at OECD nations. However, Wei et al. [68] highlight the inverse results. A link between GTs and CO₂ emissions that looks like an inverted U is implied by Usman et al. [69] for countries in the EU and Lin et al. [70] for China. In their respective studies, Chen et al. [71] and Qashou et al. [72] contend that GTs do not effectively decrease CO2 emissions in the G-20 and Turkey equally. In their respective studies. While Zhang et al. [73] find that GTs are not successful and Usman et al. [74] stress the fractional effectiveness of GTs or diverse findings, Nakhli et al. [75] discover that GTs efficiently cut CO2 emissions.

2.3 Trade openness and carbon emissions

When it comes to empirical research, the trade-environment nexus literature is vast. However, these investigations typically yield contradicting or, at most, unclear evidence. Contrary to claims that trade liberalization deteriorates environmental conditions, other studies have shown that it enhances environmental quality via multiple pathways [76]. On the other hand, other research found strong evidence that more trade openness does not harm the environment [77].

According to research by Dagher et al. [78], trade openness improved the ecological quality of ASEAN members from 1995 to 2018. Similarly, Banmairuroy et al. [79] found that commerce in Latin America had a net positive effect on the environment from 1970 to 2019. The ecological quality of the G-7 countries is improved by increased trade openness, as shown by Cheng et al. [80]. To accomplish this, two methods are used: CS-ARDL and AMG. Using the mean group (MG) and CCEMG estimator in the case of G-20 nations, Zastempowski et al. [81] also found that trade openness slows down ecological deterioration. Also, TO is environmentally benign and helps with regional environmental quality, according to Xu et al. [82], who used it as a metric for TO for 48 Sub-Saharan African nations from 2005 to 2014. Using the CCEMG and AMG methods, Farida et al. [83] demonstrate that trade openness is becoming more critical.

When looking at the effects of GDP, urbanization, TO, FG, and GRN use on CO2 emissions in Pakistan from 1985 to 2018, Jahanger et al. [84] found that TO degrades ecological quality. Similarly, Sarfraz et al. [85] found that commercial openness significantly worsened environmental deterioration in France when comparing 1980 to 2020. Similarly, Gossel et al. [86] used quantile regression estimators, the FM-OLS and a system GMM, to find that TO is considerably related to environmental deterioration in G20 nations. Furthermore, research by Liu et al. [87] on the effects of TO and innovation on middle-income nations' ability to reduce CO2 emissions found that when trade openness is raised, ecological degradation is worse in low-middle-income nations compared to upper-middle-income nations. Also, between 1995 and 2018, environmental quality declined in ten Asian economies, and Xue et al. [88] found that TO was a significant factor in this deterioration. Sharma et al. [89] found a similar pattern in their empirical study, demonstrating that trade liberalization exacerbates the environmental crisis in Pakistan. This empirical evidence is further supported by Iftikhar et al. [90], who discovered that TO enhances CO2 emissions in the G-7.

Similarly, Naor et al. [91] found that TO influenced the ecological conditions in 66 developing nations from 1971 to 2017. According to Li et al. [92], who used the difference and system generalized approach of moments to analyze 88 developing nations from 2000 to 2014, trade openness boosts CO2 emissions. Furthermore, the environmental situation in the OIC nations is worsened when their markets are opened to foreign goods, as stated by Zheng [93]. This is supported by the research carried out by Yi et al. [94] for India and China from 1996 to 2016. Further literature is given in Table 1.Table 1 Literature review on green energy, green taxes, trade openness, and CO2 emissions.

Table 1Authors	Period	Countries	Methods	Findings	
Asghar et al. [95]	1985–2020	Newly Industrialized economies	PCSER & QR method	TI = (+) GRN	
TO= (−) GRN	
PGR= (−) GRN	
Ma et al. [96]	1995–2021	BRICST	FMOLS, DOLS, MMQR	GRN= (−) CO2	
GT= (−) CO2	
GI= (−) CO2	
Azam et al. [97]	2010–2019	G-20-member countries	FMOLS, DOLS, VECM	PGR=(−) CO2	
NRE= (+) CO2	
GRN=(−) CO2	
Zhao et al. [98]	2000–2021	Chinese listed companies	OLS, two stage GMM	GT= (+) GRN	
GF=(+) GRN	
Shi et al. [99]	1990–2019	Saudi Arabia	NARDL, DOLS	FD= (−) CO2	
GR=(−) CO2	
In negative shock results are adverse.	
Lee et al. [100]	2000–2019	30 provinces of China	Mechanism analysis	GRN,	
Energy structure& Industrial structure = Reduce Carbon intensity	
Shobande et al. [101]	1994–2019	OECD countries	GMM method	GI* GRN=(+) CO2	
GRN* SI=(−) CO2	
Jahanger et al. [102]	1990–2020	10- Manufacturing countries	MMQR method	EE, GRN= (−) CO2	
Manufacturing sector=(+) CO2	
Ullah et al. [103]	1995–2018	7-green economies	QQ method	Mixed and asymmetric impact of GT on ecological sustainability	
Javed et al. [104]	1994–2019	Italy	Dynamic simulated ARDL method	GT=(−) CO2	
GTI=(−) CO2	
GRN=(−) CO2	
Chen et al. [105]	2001–2019	64-BRI Countries	Panel Quantile regression	TO=(+) CO2	
TO*GDP=(+) CO2	
Note: PCSER: panel-corrected standard errors regression, QR: Quantile regression, SI: Social inclusiveness, GRN: Green energy, NRE: Non-renewable energy, EE; Energy efficiency, GTI: Green technology Innovation, GI: Green innovation, FMOLS: fully modified ordinary least square, DOLS: dynamic ordinary least square, GMM: generalized method of moments, VECM: vector error correction model, GT: Green Taxes, TO: Trade openness, PGR: Population growth.

Following the above discussion and a profound literature review of previous studies, it can be concluded that no prior studies have worked on these variables in the context of BRICS countries, such as green energy, green taxes, trade openness, natural resources management, financial globalization, and population growth. Secondly, a novel estimation method, the FMOLS, and the Drisc Kraay test, have been employed for robustness. In addition, this study gives policy recommendations for these economies to combat the issue of environmental pollution and help attain the goal of sustainable development.

3 Data and methodology

To attain carbon neutrality, the study integrated green energy (GRN), efficient resource management (ERM), financial globalization (FG), green tax (GT), trade openness (TO), and population growth rate (PGR) as critical factors. Consequently, a panel dataset covering the BRICS economies from 1990 to 2021 was assembled. Implementing green taxes, such as carbon emission taxes, has been proven to reduce fossil fuel consumption and emissions. According to Wang et al. [106], implementing taxes on carbon emissions has a substantial impact on reducing the consumption of gasoline, natural gas, and other fossil fuels. However, some policymakers argue that such environmental levies could impede economic growth. Moreover, according to Ref. [107], optimum utilization of natural resources, productivity enhancement, and increased trade openness are key factors that significantly impact the attainment of carbon neutrality.

Further, Gwani et al. [108] revealed that adopting green energy instead of traditional fossil fuel consumption is swiftly gaining traction on a global scale. Both developed and developing economies devote significant attention to the transition towards energy transformation. An explanation for the processes that have an effect on ecological stability is provided by the Environmental Trophic Cascade Hypothesis. According to Jeanne et al. [109], who introduced the idea of the carbon curse, nations that rely heavily on fossil fuels tend to have high carbon intensities. The methodology of Selseng et al. [110] is expanded upon in this study. It appears that GDP per capita has a significant impact on CO2 emissions, according to the growth-induced EKC. The research and analysis are grounded on an existing practical model, which is provided by the empirical specification. Table 2 summarizes the variables.Table 2 Variable Description.

Table 2Sign	Parameters	Measurement units	Source	
CRN	Carbon neutrality	CO2 Emission (Metric tons per capita)	WDI	
GRN	Green energy	Renewable energy (% of total energy Consumption)	WDI	
GT	Green tax	Carbon emission taxes	WDI	
TO	Trade openness	(% of GDP)	WDI	
ERM	Efficient resource management	Total natural resource rent	WDI	
FG	Financial globalization	financial globalization	WDI	
PGR	Population growth	(% of GDP)	WDI	

To provide a concise overview of the study elements, a descriptive analysis was utilized. The mean, minimum, and maximum values were utilized to determine the central tendency, while the standard deviation was employed to assess the deviation from the mean. Moreover, skewness was utilized to evaluate the symmetry of the data, and kurtosis was utilized to examine the high and low tails of the dataset. Furthermore, the Jarque-Berra (JB) test was utilized to determine the normality of the factors. The results of the analysis are presented in Table 3.Table 3 Summary Statistics.

Table 3Variables	Mean	Min	Max	SD	Skewness	Kurtosis	JB	
 CRN	1.313	−0.438	2.682	0.913	−0.210	1.633	8.640	
 GRN	2.849	1.157	3.969	0.972	−0.529	1.851	6.260	
 GT	−1.409	−6.166	2.477	2.013	−0.313	2.084	6.462	
 TO	3.625	2.718	4.706	0.390	−0.438	2.536	6.542	
 ERM	1.422	−0.146	3.068	0.728	0.330	2.579	4.084	
 FG	3.824	2.398	4.500	0.378	−1.176	5.121	0.614	
 PGR	−0.140	−3.503	1.124	0.826	−1.747	6.284	0.864	

To attain carbon neutrality, the study integrated green energy (GRN), efficient resource management (ERM), financial globalization (FG), green tax (GT), trade openness (TO), and population growth rate (PGR) as critical factors. Consequently, a panel dataset covering the BRICS economies from 1990 to 2021 was assembled. Implementing green taxes, such as carbon emission taxes, has been proven to reduce fossil fuel consumption and emissions. According to Pacheco-Velázquez et al. [111], implementing taxes on carbon emissions has a substantial impact on reducing the consumption of gasoline, natural gas, and other fossil fuels. However, some policymakers argue that such environmental levies could impede economic growth. Moreover, optimum utilization of natural resources, productivity enhancement, and increased trade openness are key factors that significantly impact the achievement of carbon neutrality. The general form of the theoretical is given in Equations 1, 2).1 CRN=(GRN,ERM,FG,GT,TO,PGR)

2 CRNit=κo+δ1GRNit+δ2ERMit+δ3FGit+δ4GTit+δ5TOit+δ6PGRit+μt

The notation used in the equation represents various concepts, with CRN symbolizing carbon neutrality, GRN signifying green energy, FG denoting financial globalization, GT representing green tax, TO standing for trade openness, and PGR indicating population growth rate.

3.1 Slope homogeneity

Subsequent to evaluating the slope variance of each factor in a given research study, one employs the slope heterogeneity, which quantifies the variance in the slope mathematically expressed as (Eq (3)):3 Δ=S(S−1F%−L2L)andΔadj=S(S−1F%−L2L(M−L−1)M+1)

The study employs the Pesaran CD test to determine whether the groups are cross-sectionally independent or dependent. This test is used to assess the cross-sectional independence of the groups. Specifically, the test is used to determine whether the groups are independent or dependent in the cross-sectional dimension. The results of the test are reported in the study. The mathematical form is given in equation (4).4 CD=2MS(S−1)(∑z=1S−1∑x=z+1Sρˆzx)∼S(0,1)

It is appropriate to implement the second-generation unit root test in the presence of cross-sectional dependence (CIPS and PSADF), as this method accounts for cross-sectional dependence and has been shown to be effective in previous research. The mathematical form is given in equations 5, 6).5 CIPS=1S∑Z=1Smz(S,M)

6 ΔBzm=φz+ζZBz,m−1+δzB‾m−1+∑x=0qδzxB‾m−1+∑x=1qλzxΔBz,m−1+εzm

While also affirming the cointegration among green energy, efficient resource management, financial globalization, green tax, trade openness, population growth rate, and carbon neutrality. The study will employ the cointegration test, such as the Kao, Pedroni, and Westerlund test, which is mathematically reported as (see Eq. 7, 8).7 Yzm=αz+ϒzmβ+ωzmωzm=Ρωzm−1+Vzmωzm=Ρωzm−1+∑x=1qϕxΔωzm−x+Vzm

8 Xzm=αz+δzm+∑t=1Tβtz,Ytzm+μzm

9 Ea=1S∑z=1Saz′FR(az′)Em=1S∑z=1SMaz′az′(1)Qm=a′FR(a′)Qa=Ma′

The use of strong evidence enables us to utilize the Pooled Mean Group Estimator to establish the long-term link among the variables under investigation. The Panel FMOLS presents several advantages, including the capacity to address issues related to serial correlation, endogeneity, and cross-sectional heterogeneity. Additionally, it allows for the examination of both within-dimension and between-dimension factors, as expressed in the results.10 ωGEM=S−1∑z=1s[∑m=1M(Yzm−Y′z)2]−1[∑m=1M(Yzm−Yz′)ϒzm′−Mγz′]

Where ωGFM=S−1∑z=1SωFMz, ω FMz is the FMOLS estimator for individual variable.

4 Results and discussion

Before applying the central technique, it is customary to first conduct a pairwise correlation analysis. This analysis assesses the correlation among the study factors, while pairwise correlation specifically quantifies the correlation between each pair of factors individually. The outcomes of this analysis are presented in Table 4.Table 4 Pairwise correlation.

Table 4Variables	CRN	GRN	ERM	FG	GT	TO	PGR	
CRN	1.000							
GRN	−0.924a	1.000						
(0.000)							
ERM	0.609a	−0.730a	1.000					
(0.000)	(0.000)						
FG	0.556a	−0.416a	0.201a	1.000				
(0.000)	(0.000)	(0.011)					
GT	−0.774a	0.624a	−0.365a	−0.263a	1.000			
(0.000)	(0.000)	(0.000)	(0.003)				
TO	0.671a	−0.704a	0.575a	0.470a	−0.325a	1.000		
(0.000)	(0.000)	(0.000)	(0.000)	(0.000)			
PGR	−0.554a	0.630a	−0.530a	−0.238a	0.187a	−0.414a	1.000	
(0.000)	(0.000)	(0.000)	(0.005)	(0.038)	(0.000)		
Note: ***p < 0.01, **p < 0.05.

a p < 0.1.

The results shown in Table 3 imply a significant association between GRN and TO, while ERN with CRN and GT with CRN have demonstrated a moderate correlation. This may indicate the presence of multicollinearity within the dataset. To verify this, a multicollinearity analysis was conducted utilizing the variance inflation factor (VIF), and the outcomes are presented in Table 5.Table 5 Outcomes of VIF.

Table 5Variables	VIF	1/VIF	
 GR	3.811	0.262	
 GT	1.913	0.523	
 TO	3.308	0.302	
 ERM	1.460	0.685	
 FG	1.593	0.628	
 PGR	1.176	0.85	
 Mean VIF	2.210	.	

The findings in Table 5 suggest that there is no issue of multicollinearity, as all values are within the acceptable range of ±5 or ±10. This indicates that the strong correlations observed in Table 4 do not pose a problem, as confirmed by the VIF values. Therefore, this study supports previous research.

Next, the study utilizes slope heterogeneity to measure the variability of each factor, employing the methodology introduced by Yamagata et al. [112] and Westerlund et al. [113]. The results are presented in Table 6.Table 6 Slope heterogeneity test.

Table 6(Pesaran, Yamagata. 2008. Journal of Econometrics)
H0: slope coefficients are homogenous.	(Blomquist, Westerlund. 2013. Economic Letters)
H0: slope coefficients are homogenous.	
	Delta	p-value		Delta	p-value	
	10.112	0.0870		0.103	0.918	
adj.	11.676	0.0832	adj.	0.118	0.906	

The objective of these analyses is to assess the uniformity of the slopes of the coefficients, which pertain to the incorporation of study factors. The results of both tests revealed a uniform slope of coefficients, indicating substantial homogeneity among the variables under investigation. This suggests that the relationships between these economic factors are significant and exert similar influences on the variables that were examined.

The cross-sectional independence of the dataset was analyzed using the CD test, which assesses the degree of independence or dependence among the cross sections of the data. The results of this analysis are presented in Table 7.Table 7 CD test.

Table 7Variable	CD-test	p-value	average joint T	mean ρ	mean abs(ρ)	
CRN	+7.389	0.022	32.00	+0.41	0.56	
GRN	+9.957	0.015	32.00	+0.56	0.56	
GT	+1.327	0.184	32.00	+0.07	0.53	
TO	+5.411	0.000	32.00	+0.30	0.45	
ERM	+10.032	0.025	32.00	+0.56	0.56	
FG	+15.235	0.000	32.00	+0.85	0.85	
PGR	+2.629	0.009	32.00	+0.15	0.30	
Notes: CD ∼ N(0,1), p-values close to zero show data are connected across panel groups.

The data presented in Table 7 reveals that cross sections are not isolated entities, suggesting that cross-sectional dependency is pervasive among the datasets. Considering this, the second-generation unit root test would be an appropriate method to evaluate the stationarity of the datasets, as it considers both the time series and cross-sectional dimensions of the data. The test results are presented in Table 8.Table 8 Second Generation Unit root test.

Table 8Variables	CIPS	PSADF	
Level	1st Diff	Level	1st Diff	
CRN	−2.339**	−3.355 ***	−2.536**	−2.424*	
GRN	−2.353**	−3.840***	−2.553**	−2.706**	
GT	0.242	−4.990***	−3.219***	−2.592**	
TO	−2.795***	−4.333***	−3.123***	−4.109***	
REM	−3.840	−5.107***	−1.849	−4.586***	
FG	−2.705***	−5.675***	−2.460**	−4.329***	
PGR	−2.825***	−4.003***	−2.209	−4.473***	

The information presented suggests that for CIPS and PSADF, REM and PGR do not exhibit a stationary pattern at the level, while all the factors of concern exhibit a unit root at the first difference. As a result, it may be inferred that all factors in the study display a zero mean and constant variance at the first difference.

We utilize the Kao, Pedroni, and Westerlund methods to assess cointegration among the study variables. These methods are employed to measure cointegration in the presence of stationary and cross-sectional dependence, respectively. The results of these analyses are presented in Table 9.Table 9 Cointegration tests.

Table 9Kao	Statistics	P-value	
Modified Dickey-Fuller t	−3.6680	0.0001	
Dickey-Fuller t	−1.9685	0.0245	
Augmented Dickey-Fuller t	−1.6972	0.0448	
Unadjusted modified Dickey-Fuller t	−2.0438	0.0205	
Unadjusted Dickey-Fuller t	−1.5586	0.0595	
Pedroni	
Modified Phillips-Perron t	1.2520	0.1053	
Phillips-Perron t	−1.5358	0.0623	
Augmented Dickey-Fuller t	−1.5358	0.0241	
Westerlund	
Variance ratio	2.5680	0.0051	

The relationship between CRN, GRN, ERM, FG, GT, To, and PGR is demonstrated through the findings of cointegration. The Westerlund test, which includes the variance ratio, and the Kao tests both show robust evidence of cointegration among the variables. This reinforces the idea that the various elements of the study are connected and enduring.

The FM-OLS method is a valuable tool for economic analyses as it incorporates lagged values of both independent and dependent variables, instrumental variables, and residual correction terms derived from error correction models. These features enable the FM-OLS to provide more accurate and unbiased regression coefficient estimates, particularly in situations where the OLS assumptions may not be met. This makes the FM-OLS a more reliable and robust foundation for statistical inference in economic analyses, leading to more dependable outcomes. The results of the FM-OLS are presented in Table 10.Table 10 Fully modified ordinary least square method.

Table 10CRN	Coeffi	Std. err	z	P > z	[95 % conf. interval]	
GRN	0.567	0.108	−5.24	0.000	−0.779	−0.355	
GT	0.139	0.012	−11.4	0.000	−0.163	−0.115	
TO	0.247	0.108	−2.29	0.022	−0.458	−0.036	
ERM	0.037	0.013	−2.77	0.006	−0.063	−0.011	
FG	0.519	0.075	6.90	0.000	0.372	0.667	
PGR	0.278	0.042	−6.56	0.000	−0.360	−0.195	
linear	0.004	0.002	1.98	0.048	0.000	0.007	
_cons	1.504	0.665	2.26	0.024	0.200	2.809	

The findings in Table 9 indicate that GRN, ERM, FG, GT, TO, and PGR have a significant impact on carbon neutrality in the BRICS economies, suggesting that these study factors are contributing to the achievement of carbon neutrality in the region. To validate these findings, a robust test is reported in Table 11.Table 11 Robustness Test (Drisc Kraay test).

Table 11CRN	Coeffi.	std. errs	t	P > t	[95 % conf. interval]	
GRN	0.854	0.068	−12.65	0.000	−0.992	−0.717	
GT	0.109	0.015	−7.13	0.000	−0.140	−0.078	
TO	0.284	0.090	−3.14	0.004	−0.469	−0.1	
ERM	0.012	0.006	−2.20	0.036	−0.023	−0.001	
FG	0.505	0.048	10.42	0.000	0.406	0.604	
PGR	0.167	0.043	−3.86	0.001	−0.256	−0.079	
_cons	2.788	0.484	5.76	0.000	1.801	3.775	

The data presented in Table 11 lends credence to the results of the FMOLS analysis, which suggest that GRN, ERM, FG, GT, TO, and PGR are key factors in achieving carbon neutrality in the context of the BRICS region.

5 Discussion

Global warming is intensifying due to the overexploitation of natural resources, excessive carbon emissions and climate change. Therefore, it is crucial to implement measures to decrease carbon emissions and alleviate environmental degradation. To achieve this, the current study analyzed panel data (1990–2022) to determine the relationship between GRN, ERM, FG, GT, TO, and PGR in pursuit of carbon neutrality.

The insertion of green energy and green taxes has considerably transformed the world's landscape. Research indicates that these initiatives have helped BRICS countries achieve carbon neutrality by roughly 0.567 % and 0.139 %. The effects of green energy and green taxes on the environment are multifaceted and intricate, as demonstrated by various authors' findings. The green tax's ability to manage resources effectively, minimize waste, and promote green energy use can contribute to reducing carbon emissions and fostering sustainability. Energy-intensive infrastructures such as data centers can be made eco-friendlier by utilizing renewable energy sources like wind or solar power. Additionally, efficient use of natural resources and financial globalization can help optimize energy use and further the goal of carbon neutrality. Employing artificial intelligence, machine learning, and expanding financial resources can aid in optimizing energy consumption in data centers, reducing energy waste, and promoting efficient resource management. These results align with [114,115].

Furthermore, effective resource management can foster sustainability by implementing a circular economy that incorporates financial globalization to minimize waste and enhance the financial system, while imposing green taxes to curb carbon emissions [116]. The BRICS countries, with a particular focus on China, are a significant force in the green energy sector and have the potential to make significant contributions to carbon neutrality efforts. However, this region also faces unique challenges, such as a heavy reliance on coal-based energy sources. To overcome these obstacles, the BRICS countries are taking steps to promote sustainability in the digital economy. For instance, China has established goals for reducing carbon emissions and has implemented policies to encourage the use of renewable energy sources, like wind and solar power [117,118].

The results indicate that the green tax implemented by BRICS is effective in promoting sustainability, as it has a positive effect on the long-term carbon neutrality efforts in the country. This link has also been observed in other developed and rapidly developing economies, where the production process has been closely monitored and its standards have been enhanced. Thus, these outcomes were consistent with [119], and [120]. Moreover, the outcomes show that effective resource management can have an impact on achieving carbon neutrality, which is a positive factor. These results are in line with those [121], and [122]. Financial globalization has been found to have a positive correlation with carbon neutrality in energy transition and carbon taxation. It has been observed that financial globalization enhances the efficiency and sustainability of green energy and resource management. As a result, green energy sources are well-aligned with the process of achieving carbon neutrality in the BRICS countries, as stated by Ref. [123], and [124].

Although green taxes are now implemented to protect the environment from harmful emissions, recent studies suggest that imposing an environmental tax of just 1 % could push the economy towards carbon neutrality, amounting to approximately 0.139 %.These results are consistent with the study by Ref. [125]. One of the most important factors in achieving carbon neutrality is free trade. A decrease of about 0.247 % is predicted for every 1 % improvement in carbon neutrality and trade openness, according to the results. These results are in line with [124,126,[127], [128]].

6 Conclusion and policy implication

The world is facing a grave threat from environmental degradation, pollution, and rising temperatures. To combat this, it is essential to develop policies aimed at achieving carbon neutrality, a zero-carbon economy, or a carbon-free society. To this end, various strategies such as green energy, efficient resource management, financial globalization, open trade, and population growth have been implemented. Among these factors, green energy, efficient resource management, financial globalization, and green taxation have emerged as the most critical for achieving a sustainable environment and growth. To test this hypothesis, a dataset covering the BRICS countries between 1990 and 2021 was used. The Kao, Pedroni, and Westerlund methodology demonstrated long-term relationships among the variables.

The use of FMOLS was implemented to assess the impact of the study variables. The results of the FMOLS analysis indicate that the factors are relevant in determining long-term commitment to achieving carbon neutrality. Moreover, the Drisc Kraay test demonstrates that all variables are important for attaining carbon neutrality. This research demonstrates that the environmental Kuznets curve is present in the country and has a significant impact on reducing carbon emissions. Additionally, the use of green energy and the implementation of green tax policies contribute to this reduction. Furthermore, the development and implementation of new environmental patents and technologies are helping to create a greener environment. Overall, the study highlights the importance of these factors in achieving a sustainable and environmentally friendly future.

6.1 Policy implications

1. When it comes to policy consequences, the BRICS nations must limit their reliance on fossil fuels. The BRICS are a group of developing nations that prioritize economic growth; nevertheless, they also rank high in importing non-renewable energy. Achieving a low-carbon economy is thus possible through the use of renewable energy sources in both production and consumption.

2. There is a stronger positive relationship between trade openness and carbon neutrality, and trade is crucial to the economic growth of the BRICS nations. It suggests that the BRICS nations work on long-term trade strategies with other nations. It needs to impose stringent carbon taxes on BRICS countries' polluting exports to other countries that buy their products.

3. Targeting more industries with environmentally friendly manufacturing techniques will promote knowledge spillovers from clean technology into various sectors of the economy, which will help mitigate the negative consequences of trade openness in BRICS states. If host nations want to see a successful know-how spillover, they need to beef up their absorption capacity mechanisms.

4. Given these outcomes, it is essential that legislative and administrative bodies take the lead in formulating environmental policies. The government must actively encourage and enthusiastically support the adoption of green energy and green taxes, which are critical for achieving carbon neutrality. Enabling green innovations is crucial for achieving zero carbon emissions.

6.2 Limitations and further study directions

The five BRICS economies are the only ones considered in this analysis while we can include more countries which are also important. The main variables in this study are green energy, trade openness and green taxes while many other crucial variables can be taken for further study. That is why future research should consider things like trade, FDI, remittances, uncertainty, institutional quality, monetary, climate policy and political stability.

Ethical approval and consent to participate

The authors declare that they have no known competing financial interests or personal relationships that seem to affect the work reported in this article. We declare that we have no human participants, human data or human tissues.

Consent for publication

N/A.

Availability of data and materials

The data will be made available on request.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

CRediT authorship contribution statement

Yanfeng Li: Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Jingru Liu: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Project administration. Yanlei Li: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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