The Influence of Foreign Direct Investment and Tourism on Carbon Emission in China

The aim of this research is to examine the potential influence of FDI inflows and tourism industry on carbon dioxide emissions in China using System GMM models for a sample period of 1980–2019. Using FMOLS and DOLS models, this research examines the long-term relationship between the variables, as well as the long-term association among components. Co-joining the boards of FMOLS and DOLS models shows a general correlation between the investigation elements and CO₂ emissions in China. FDI, tourism sector, and environment-friendly electricity use have all been major contributors to rising CO₂ emissions in China for a long time. Using System GMM, FMOLS, and DOLS models in China, we examined the influence of the travel sector on carbon dioxide emissions as well as environment-friendly electricity usage and foreign direct investment. The government of China is being pushed to attract more foreign direct investment in order to improve the system and expand the transportation industry. As a reasonable responsibility to an unnatural climate change, methods for developing the movement business and theories relating to the movement business should be adopted.

Introduction

A different type of research examines the impact of income and the tourism sector on CO₂ emissions (Peng et al., 2020a; Zhao et al., 2022). While using inventive examination strategies on diverse topographical settings, a writing hole is still obvious, and adding additional components necessary to include the muddled relationship between human monetary activities and natural corruption is important to consider. Regardless, the connections between the transportation industry and the rise in carbon dioxide emissions are not clear. Additionally, Qi et al. (2020) studied the relationship between China’s GDP and the spread of carbon dioxide (CO₂) in China. Low carbon emissions should be linked to an increase in financial outcomes (Peng et al., 2021b; Wang et al., 2021), according to the researchers, who used cointegration and fragmented mix methodologies to arrive at this conclusion. An investigation conducted by Mahrinasari et al. (2019) found a positive correlation between rising carbon emissions and trade activity in Asian countries. As Katircioglu et al. (2020) have shown, China’s transportation industry is a major source of fossil fuel byproducts. Carbon surge has been found to have a negative influence on the movement industry in the evaluation test economies, according to Tugcu and Topcu. As an example, Sadorsky (2009) has examined the relationship between the use of viable power assets and financial development and discovered that a gain in yield is supported by the activity of such assets. Many factors contribute to a location’s popularity, but environmental degradation, excessive energy consumption, and abundant water use are the most critical (Sheng et al., 2019; Ciacci et al., 2021; Elahi et al., 2022a; Elahi et al., 2022b). No matter how you slice it, the data reveal a drop in the amount of people who want to express themselves in countries that were founded (Khan et al., 2020). Framework GMM and FMOLS models will be used to study the impact of sustainable power and direct speculation on carbon emissions in China, as well as global exchange and tourism industry interactions. During the 1980s to the present, the transportation industry, international commerce, and economic growth were all impacted by carbon emissions (Tu et al., 2019). Even without an event to create countries that illustrate this global expansion in movement business raise release, the transportation industry has a good impact on carbon spread.

The current research provides significant insight into the role of various financial activities in CO₂ emissions in order to better understand the impact of various financial elements on environmental pollution. In addition, the same technique used in the focus enables us to understand the differences in environmental change relief methods between developed and agrarian countries. According to Yu and Xu (2019), the FDI in China played a substantial role in the country’s decreased CO₂ emissions on a national level. The travel industry’s CO₂ emissions have been measured using a variety of monetary models in order to indicate environmental change (Zhao et al., 2020; Peng et al., 2021a; Zhao et al., 2021) (Balsalobre-Lorente, et al., 2020). For the most part, the econometric models focused on the direct link between the travel industry’s growth and climate change (Wu et al., 2021; Agbanike et al., 2019). It is becoming increasingly clear that environmental change, particularly in high-emanation areas, will have a significant impact on the tourism industry’s long- and medium-term prospects (Lemieuxa, 2010). Research on financial and environmental impacts of travel industry activities has increased in recent years (Croes and colleagues 2021), and the earthy people have also been concerned about the development of an ITO that is manageable (Usman et al., 2020).

The remaining of this manuscript is structured as follows: Brief Literature is presented in Segment 2. Methods and data used are explained in Segment 3, while results and dialogues are provided in Segment 4. Finally, Segment 5 concludes this investigation with recommendations on how to proceed.

Literature Review

Effectively advance the good impact of the travel industry advancement on the environment and work on the natural familiarity with tourists via preparation of instruction and remove the unrefined conduct of eradicating the climate in exercises of the travel industry (Jing Zhao, 2018). The travel sector globally is positively impacted by our environmental effect variables, such as environmentally sustainable electricity and transportation administrations; agriculture, ranger service, and fishery (AFF); and gross domestic product development (Khan, 2021). It has emerged as one of the fastest-growing ventures in the world, creating a large number of positions, expanding the global pay, halting expansion, and causing foundation advancement for what it is worth, as it is considered essential for the development of the travel industry open doors (Meo et al. (2020)).

Manageable travel industry advancement implies an integrated approach that points practically at future amicable preparation with inclusion of all its social, financial, and ecological aspects by making and securing a beneficial harmony between the needs of people and the greatest conceivable supportability of normal assets, including the travel industry objections (Lasisi et al., 2020). A few challenges for policymakers are posed by the growth of the travel business economically and by its executives; thus, an investigation into the relationship between natural quality and travel industry improvement is necessary (Okumus and Erdogan 2021). Progress in the tourism industry’s biological aspects depends heavily on monetary measures that have an impact on environmental concerns (Lasisi et al., 2020). The country’s monetary growth enables it to endure consumption on ecological maintainability and strengthens its power to exhibit natural practices that are environmentally friendly (Peng et al., 2020b; Tu et al., 2020; Nguyen and Su 2021; Zhong et al., 2021). The travel business is a major consumer of energy; therefore, understanding the interrelationships among the key variables associated with the economy, climate, energy, and the travel industry is vital to developing an economically viable travel industry system (Lasisi et al., 2020).

A global transition to the use of renewable energy sources, such as wind and solar, is being promoted from coast to coast in order to reduce emissions of ozone-depleting greenhouse gases (GHGs) (Zhang et al., 2020) (An et al., 2021). For Li et al. (2021), financial development is measured by gauging the contributions, spending, and contributions of tourists and merchants, particularly those from outside China. Higher GDP growth also has an important role in the growth of the outbound tourism sector. The expectations of eight South African nations for day-to-day comforts based on twenty years of information were investigated by Sarpong et al. (2020) in another review. It has been suggested by several researchers, including Nguyen and Su (2021) and Gössling et al. (2012), travelers will pay a premium for destinations that can be maintained. Despite protests from tourists, one option to make the tourism sector more viable is to use renewable energy sources. In spite of the fact that it will cost more money for the passengers, they will choose to pay the additional fee because of their moral convictions (Nguyen et al., 2020). As a result, the travel industry has a direct impact on four of the previously mentioned economic sectors (Buckley 2011). The improvement of the travel industry and travel system that ensures a proper balance between all four previously mentioned perspectives, as now sightseers consider these four viewpoints essential for their decision of objective and extreme fulfilment, can be characterized as the sustainability of the travel industry (Sharpley 2000).

In order to protect the climate and the environment, the most pressing concern for the travel industry’s bottom line is the amount of fossil fuel waste it generates (Nguyen and Su 2021). One of the challenges the travel industry will be facing in the future is the need for a drastic change to reduce CO₂ emissions to prevent environmental degradation (Peeters and Dubois 2010). Access to and use of energy assets are critical determinants of financial outcomes (Udi et al., 2020), and as a result, nations lacking sufficient energy assets face obvious financial issues (Peng et al., 2021c). The tourism sector has recently been viewed as a source of natural corruption (Işk et al., 2019). Travel sector energy nexus research is scarce and linked to a variety of activities, including transportation, as compared with research on the travel industry’s overall development nexus. Travelers’ concerns about energy usage, water use, and waste management have led to several observational studies concluding that the two industries are intertwined (Dwyer et al., 2010).

Solarin (2014) investigates the relationship between Malaysia’s tourism sector and the country’s energy use. According to a separate analysis, the usage of travel industry-related energy has negative ecological implications, such as increased CO₂ emissions as a result of movement and transportation. Travel and CO₂ emissions might eventually co-develop, according to Koçak et al. (2020). The travel industry’s usage of land is another cause of ecological incapacity. Green transportation, green technology, and the efficient use of renewable energy are all part of an eco-friendly travel system (Paramati et al., 2017; Shen et al., 2019; Zhong et al., 2020; Huang et al., 2021). High water use, ecological pollution, as well as increased energy use are all factors that limit the travel sector’s ability to sustain itself (Skillet et al., 2018). Observational findings show that the travel business has a growing influence on contamination and CO₂ emissions (2019). A large portion of the energy used by the travel and tourism business is used by transportation, convenience, and education (Tsagarakis 2011). Travel sector development and energy-climate nexuses are explained by the review’s findings, which have not previously been seen (Işk et al., 2019). In 10 contaminated emissions nations, Eluwole et al. (2019) found a non-critical link between the tourism sector and ecological maintainability, whereas other studies found a significant link between travel and toxin emissions (Lasisi et al., 2020). With the goal of finding a link between China’s tourism business and fossil fuel goods, Zhang and Zhang (2020) investigated the relationship between these two industries. Zhang and Gao (2016) found that the tourism sector had a negative impact on CO₂ emissions in China’s eastern region. On the other hand, emissions of CO₂ in China’s central and western regions are mostly unaffected. Predicted by Tang et al. (2017), the travel sector is a major consumer of energy and a major contributor to the emission of ozone-damaging substances. They found a link between the scale of the travel sector and the amount of waste produced as a result of using fossil fuels. As a result of global travel industry and development, Zhang and Gao (2016) conclude that the travel sector in China is one of the top carbon producers in the country. The industrial sector contributed to environmental emissions enormously and damaged human health (Gu et al., 2019; Gu et al., 2020a; Gu et al., 2020b). As an indicator of ecological quality, Tian and colleagues (2020) use CO₂ emission levels as a measure of gross domestic product (GDP) growth and sustainable power consumption in the travel industry’s progress and the climate. The travel sector is impacted by a number of variables, some of which are directly related.

Calderón-Vargas et al. (2019) analyzed the relationship between RESC and the travel industry by examining the potential for breeze/sun-based energy based on the progress of the spatial-worldly traveler stream in another maintainable travel industry research. A study by Dogru et al. (2020) found that although improvements in the travel business have a detrimental influence on CO₂ emissions in Turkey and Canada, they basically have a certain effect on emissions from the European Union countries of Italy, Slovakia, and Luxemburg. Travel industry groups, sightseers, and travel industry networks are all together referred to as the travel industry by Butowski (2021), even if these entertainers have an equal stake in preserving reasonable travel business. According to Khan et al. (2019), the impact of Coronavirus, which has decimated the tourism sector over the last two years, is also being examined. The study by Moreno et al. (2021) examines the impact of Coronavirus on the tourism business in different regions of Spain. The Spanish travel sector is very valuable, but it has been hit hard by the pandemic’s effects due to the Coronavirus outbreak. The combined impact of wind energy projects and the tourism sector on neighborhood progress in the Amazon region is examined by Calderón et al. (2019).

In terms of biodiversity, it is an ideal location for the tourism business. Environmentally friendly electricity, green advancements, and green transportation are among the key factors that Skillet et al. (2018) believe are necessary for a sustainable travel sectors. Using 40 years of data and causation between development and CO₂ emissions, Hafeez et al. (2020) discovered a vital link between CO₂ emissions and globalization in South Asian countries. The findings of Paramati et al. (2017) show that improving the travel sector has a negative impact on CO₂ emissions in the near term, but a beneficial impact in the long term. According to Lopez and Bhaktikul’s (2018) research, a big part of Thailand’s tourism sector can be traced back to the mountains’ easy ascent, which is followed by visits to historical sites and then sanctuaries. Relative methods should be focused on the plans of integrated administration, a healthy lifestyle, and a sustainable tourism business that uses green technology. Lastly, there must be no preconceived notions that argue that the tourism business is unrelated to growth (Razzaq et al., 2021).

A favorable correlation was found between the degree of financial change and the development of the travel sector by Asadzadeh (2017). An increase in financial resources leads to more innovation, which may be used to reimagine natural boundaries. According to Rembeci, (2016), the travel sector has a significant impact on the economy, and he recommends greater research into the role of economics, climate, and energy in managing the travel industry (2020). The next year, (Abdouli M, 2020) the GMM assessor was used to investigate the link between financial development, FDI, ecological quality, and monetary advancement, and found that FDI is a decent driver of financial development, but it reduces the character of the climate (Abdouli M, 2020). Foreign direct investment (FDI) in SSA countries has increased moderately, although new projects by global organizations rely on the host nation’s usual assets, such as agriculture, assembly and oil production (Adegboye et al., 2020). It also determines their utility by taking into account activities such as the tourism sector, urbanization, and population growth (Shahzad et al., 2021).

A recent study by Jiang and Ma (2019) found that rising prices for fossil fuel waste are a positive development. He said that FMOLS assessors rely heavily on parametric assessment to answer concerns about sequential linkage and endogeneity, as well as to evaluate the long-term consequences of the chosen illustrative factors on FDI in BRICS economies (Muhammad Azam, 2021). For example, FMOLS and DOLS assessors were designed to correct for the OLS assessor’s endogeneity and sequential connection (Phillips, 1995). In contrast to FMOLS assessors, Kao and Chiang (2001) found that the DOLS assessor is less biased and has unmatched small example features. A board co-combination approach is then used to examine the long-term relationship between the variables under consideration.

To begin, we use the board fully modified ordinary least square (FMOLS) and dynamic normal least square (DOLS) to examine the relationship that has existed for some time (Nikolaos Dritsakis, 2017). A standard pooling OLS for sequential relationship and endogeneity is critical for FMOLS assessors here (Baltagi and Kao, 2001). As soon as the long-term run relationship is established by the cointegration test, we use FMOLS strategic approach to examine long-term links between oil shocks and genuine absolute exchange balance, real oil exchange equilibrium, and genuine non-oil exchange balance (Shudhasattwa Rafiq, 2016). Using the DOLS and FMOLS, Doan et al. (2019) discovered that financial complexity had a positive effect on ecological corruption. It was predicted that the Ramzan et al. (2021) study on Latin American economies using the FMOLS and DOLS would have a negative and crucial influence on the byproducts of fossil fuels. The theoretical framework of the current research is visualized in Figure 1 below.

FIGURE 1

FIGURE 1. Conceptualization of the anticipated research.

Research Methods and Data Collection

The exploration has connected with fixed, energetic, and since quite a while ago run assessors to find the intense and since a long time ago run connections among the chose factors. We have retrieved all information from the World Development Indictor of the World Bank. The reliant variable of the review is CO₂ emissions estimated in metric tons per capita. The free factors incorporate unfamiliar direct venture (FDI) estimated as net inflows as a percent of gross domestic product, per capita gross domestic product, environmentally friendly power utilization (RE) determined as the level of absolute last energy, and the travel industry (Visit) as worldwide travel industry receipt. Additionally, the metropolitan populace, public consumption, exchange receptiveness, and workforce are utilized as control factors in the static and dynamic models. Following (Dong, and Jiang, 2020) the basic direct useful connection among CO₂ and informative factors can be depicted as follows:

$C{O}_{2it}={\displaystyle \int \left(R{E}_{it},TOU{R}_{it},I{T}_{it},FD{I}_{it},GDPP{C}_{it},X_{it}\right)}.(1)$

Eq. 1 can be rewritten as follows after adding a constant term $\left(S_0\right)$ and an error term ${\epsilon }_{it}$ where in $\left(S_k\right)$ (k = 1,2,..,6) represent the coefficients. The error term is assumed to be normally distributed at zero mean value and constant variance (Elahi et al., 2021; Zhang et al., 2022).

$C{O}_{2it}=S_0+S_{1}R{E}_{it}+S_{2}TOU{R}_{it}+S_{3}I{T}_{it}+S_{4}FD{I}_{it}+S_{5}GD{P}_{it}+S_6{X}_{it}+{\epsilon }_{it}.(2)$

We have applied customary least square (OLS) fixed-impact model, completely adjusted standard least square (FMOLS), dynamic conventional least square model (DOLS), and framework summed up strategy for minutes (SGMM) to analyze the since a long time ago run relationship among factors. The SGMM model is useful as it is the chiefly capable assessor of OLS and set result models and has been tried by numerous observational investigations. The test model can be shown as follows:

$C{O}_{2it}=S_0+S_{1}C{O}_{2it-1}+S_{2}R{E}_{it}+S_{3}TOU{R}_{it}+S_{4}I{T}_{it}+S_{5}FD{I}_{it}+S_{6}GDPP{C}_{it}+S_7{X}_{it}+{\epsilon }_{it}.(3)$

In this situation, CO₂, RE, FDI, GDPPC, and Visit represent carbon dioxide, environmentally friendly power usage, unfamiliar direct speculation, total national output per capita, and the global travel industry. CO_{(2 it-1)} is the main slack of distinct factors in condition (1), which specifies the earlier year strain on the current year. Simultaneously, X_it addresses the control factors of the examination. The control factors remembered for the model are city individuals, public use, exchange receptiveness, and workforce. The addendums in the situation assign (I = 1,....., N), (t = 2000,....,2020) index country and example, correspondingly.

The linear ℇ_it addresses the since quite a while ago run evenness divergences from the since quite a while ago run. Following the board unit root and reconciliation tests, the since a long time ago run assessment was determined. For long-term assessment of model coefficients, the review connected since quite a while ago run evaluation of FMOLS and DOLS models, which were liked over OLS model to stay away from one-sided outcomes. Fortifying the motivation behind lessening assessor favoritism, (Pedroni 2004) technique is used for the co-mix of factors by using the FMOLS model. They involve non-parametric cycles in FMOLS model for progressive association and endogeneity concerns adjustment. Furthermore, DOLS model of assessment proposed by Imprint and Sul, (2003) was also carried out for the heartiness of the board information examination results.

Empirical Results and Discussion

Test Results of Panel Unit Root and Co-Integration

The consequence of four assorted board unit root tests directed on the chose factors at level and first contrasts for the time of 1980–2019 are given in Table 1. All of the unit root tests disposed of the invalid speculation of participation of unit root and set up the stationarity of all factors at level or first qualification.

TABLE 1

TABLE 1. Panel unit root tests.

The co-joining in the sheet is undaunted after testing the stationarity of the factors by utilizing board unit root tests. For this reason, Pedroni (2004) procedure was utilized to examine the turnout of co-coordination among the researching factors. The aftereffects of all board co-mix tests dismissed the invalid theory of no cointegration and affirmed the cointegration among factors of the examination. In Table 2, the consequences of board co-mix test for Asia Pacific and European nations from 1980 to 2019 are shown.

TABLE 2

TABLE 2. Panel co-integration test results.

The Outcomes of Long-Run Estimates

Table 3 shows the outcomes of consistent effect model and method GMM appraisal to check the relationship among CO₂, overall trade and OLS, harmless to the ecosystem power usage, new direct theory, and the movement business of the picked country’s board. The eventual outcomes of the system GMM for China particularly show the strong quantifiable significance of the loosened subordinate elements which exhibits the sensibility of the model. Basically, the p-assessments of Sargan test, autoregressive of solicitation 1(AR1) and (AR2) similarly show that the picked model is reasonable. The surveyed coefficient of reasonable power shows negative association with carbon transmission for China attesting the diminishing in carbon outpouring as indicated by extended usage of feasible power sources. Even more expressly, the outcome of OLS model exhibits that 1% improvement in practical power use diminishes CO₂ emissions by 0.335 and 0.459% in China respectively. Nevertheless, as demonstrated by fixed effect models, 1% development in supportable power utilization decreases carbon dioxide emissions by 0.137 and 0.459%, respectively, for China. Basically, the system GMM results in the like manner shows that 1% development is harmless to the ecosystem power utilization and will reduce carbon dioxide emissions by 0.46 and 0.214% in China independently. The results additionally uncovered that the evaluated coefficient of new direct endeavor on carbon dioxide emissions is significantly enormous through OLS, set effect model, and structure GMM for European countries. The result shows that a percent increase in new tourist adventure, it will assemble carbon dioxide emissions by 0.0011% in fixed effect model while decrease carbon dioxide emissions by 0.035% in the structure GMM model.

TABLE 3

TABLE 3. Results of OLS, fixed effect, and system GMM models.

Moreover, for China, the coefficient of the development business is also essentially fundamental in all models. The relationship among development industry and carbon dioxide transmission is productive in long-lasting outcome models in structure GMM for Asia Pacific nations, in any case on the other hand, essential for Asia Pacific nations in OLS and framework GMM. For representation, the results of framework GMM for Asia Pacific nations show that 1% improvement in the development business builds the carbon dioxide freedom by .024%. As indicated by the outcomes, there is a critical coefficient for China of exchange receptiveness in all models together while in OLS, FE, and SGMM models the relationship through carbon dioxide emissions is agreed for Asia Pacific nations appearing to some development consequently straight imposition will expand carbon dioxide ejection. Considerably, further unequivocally, the postponed results of OLS and fixed impact models show 1% augmentation in widespread business; it will broaden carbon dioxide emissions by 0.41% in Asia Pacific nations.

Fundamentally, on the off chance, the SGMM result also displays that here there is a 1% improvement in overall exchange and it will develop carbon dioxide freedom by 0.33% in Asia Pacific nations. For European countries, the trade openness coefficient is fundamentally essential with the relationship through carbon dioxide freedom in all negative models which shows that assuming exchange straight imposition increases by 1%, carbon dioxide conveyance will diminish by 0.66% in OLS, 0.24% in structure GMM model, and 0.31% in set outcome model. Meanwhile, per capita gross domestic product is besides found fundamental to paying little mind to models from the OLS model anyplace. The relationship through carbon dioxide emissions is positive in framework GMM. Similarly, for China to create in per capita, absolute public result will develop carbon dioxide freedom. The outcomes of fixed effect model are opposite; that is increase in per capita gross domestic product reduces carbon dioxide emissions.

FMOLS and DOLS Model Long-Run Measurement

Table 4 shows extended results of all the examination factors together for Asia Pacific and European nations by since using FMOLS and DOLS techniques for long -run association among variables. The estimation of the outcomes shows that all common coefficients are quantifiably essential. On the other hand, for Asia Pacific countries, the short-term outcomes of FMOLS incorporate that FDI and legitimate power use are the basic drivers for developing CO₂ removal. Our exposures show that expansion in the development business decreases CO₂ conveyances can be related with green the development business speculation since there have been adding to the zone by remaining beneficial level of voyagers which transport princely bio combination and tidiness also untamed greatness.

TABLE 4

TABLE 4. Long-run valuation of DOLS and FMOLS models.

Also, our disclosures show that expansion in cash-related progression of Asia Pacific nations lessen carbon dioxide ejection which are contrasting with the results of (Ben Jebli, 2015) who depicts to enhance in monetary improvement rot carbon dioxide freedom in Tunisia. The results of DOLS model show that travel industry business, worldwide exchange, and FDI are the significant drivers to develop carbon dioxide release. Our revelations with respect to FDI are in understanding through the disclosures of (Salahud racket et al., 2018) acquainting with FDI redesigns CO₂ emissions in Kuwait, however, contrary to the outcomes of Zhu et al. (2016). The revelations of DOLS of the force examination on feasible power use and 1% extension in harmless to the ecosystem power use reduces CO₂ emissions by 0.8% which can be achieved by substitutability of harmless to the ecosystem power in addition to remnant while increase the activity of viable impact as opposed to going before energy.

According to Table 4, European countries’ results of FMOLS and DOLS tests are shown, where FDI, movement business, and supportable power use are the primary drivers of increasing carbon dioxide expulsion in Europe, but supportable power use and financial turn of events and trade openness are primarily responsible for decreasing carbon dioxide expulsion in Europe. The results of our analysis, while different when compared to those of Salahuddin et al. (2018), challenge that design changes in FDI increase emissions, and this is reflected in our disclosures about FDI (Zhu et al., 2016). CO₂ emissions are reduced by 0.15 percent and 1.50 percent in FMOLS and DOLS models, respectively, when a 1% increase in practical power consumption is taken into account. This is consistent with FMOLS and DOLS results as for supportable power use. Similarly, Ben Jebli and Ben Youssef (2015) found that CO₂ emissions decreased in Tunisia as a result of an increase in the country’s GDP.

Conclusion and Suggestions

When it comes to carbon dioxide emissions in China, the review looks at how FDI inflows and tourism have an influence using OLS, fixed effect, and system GMM models. Using FMOLS and DOLS models, the examination examines the long-term link between the variables, as well as the long-term association between components. The combination of FMOLS and DOLS models shows a general correlation between the investigation elements and CO₂ emissions in China.Using system of GMM,FMOLS and DOLS model China gross domestic product , foreign direct investment (FDI), the tourism industry, and environmentally friendly electricity use have all been major contributors in rising CO2 emissions for some time in China..

We examined the influence of the travel sector on carbon dioxide emissions as well as environmentally friendly electricity usage and foreign direct investment (FDI). A negative correlation was found between direct ventures and the travel sector and carbon emissions. They are seen as useful in the development of environmentally friendly power consumption, foreign direct investment (FDI), travel industry plans, and exchange receptivity to work on natural grandeur in the future FDI and the tourism sector which are the two major sources of artificial carbon dioxide emissions, as shown by the DOLS model for China. As a result of China’s rapid economic growth and increased consumption of electricity, carbon dioxide emissions have risen. More FDI in the system-building process is also encouraged in China, which will help the transportation sector grow as a result. As a reasonable responsibility to an unnatural climate change, methods for developing the movement business and theories relating to the movement business should be adopted.

Future Research Work

In order to develop in a way that is not harmful to the environment, it may be helpful to look at how approaches related to the mobility business region may be implemented. A large capacity for environmental corruption also necessitates greater trade openness between the two countries.

Ethics Statement

Ethics review and approval/written informed consent was not required as per local legislation and institutional requirements.?

Author Contributions

Conceptualization: YAK, MA, ZM, and HW; methodology: YAK, AS and DX; formal analysis and (field/laboratory) investigation: HW ,YAK and AA; writing—original draft preparation: YAK, ZI and HW; and writing—review and editing: YAK, AS, AA.

Funding

This research is funded by “Key Development Project of Department of Science and Technology (2015C03bd051)”.

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.

Acknowledgments

The authors express their gratitude to Princess Nourah bint Abdulrahman University Researchers supporting Project (Grant No. PNURSP2022R124).

Abbreviations

CO₂, Carbon Dioxide emissions; DOLS, Dynamic Ordinary Least Square Model; FDI, Foreign Direct Investment; FMOLS, Fully Modified Ordinary Least Square; GDP, Gross Domestic Product; RE, Renewable Energy; SGMM, System Generalized Method of Moments; TOUR, Tourism.

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