Impacts of Environmental Regulations on Tourism Carbon Emissions

Renewable energy transition to sustainable tourism: extrapolating from core density and non-parametric approaches

The globe has faced severe challenges recently, and environmental deterioration has become more prominent. Therefore, the world has taken several initiatives to deal with environmental issues while the problem remains intact. Interestingly, the OECD economies are the leading example to understand the accurate picture of sustainability across the near regions. This study makes an effort to introduce the core factors such as economic development, renewable energy, tourism, natural resources, and innovations in OECD economies over the period of 2000-2021. Similarly, to investigate the study's objectives, this study employs the quantile autoregressive distributed lag model (Q-ARDL). The analyzed results show the significant contribution of renewable energy, tourism, and natural resources to environmental sustainability. In contrast, income and innovations contribute to ecological deterioration. Moreover, the quantile causality is being used by this empirical study to investigate the causal association among studied variables. However, using green energy in sustainable tourism is highly recommended for specified economies. In order to deal with environmental pressure, this research proposes green implications to attain the desired sustainability level.

The role of green financing to enhance tourism growth by mitigating carbon emission in China

The tourism industry has undergone rapid inquiry in modern times. Based on climatic importance, current research intends to inquire about the role of green financing in enhancing tourism growth by mitigating carbon emissions in China. The study used Data Envelopment Analysis to infer the efficiency of the study model in the study context based on research topicality. Our findings highlighted that China's local tourism destination, renowned for its health and wellness tourism, indicated tourist inspiration to visit climate-supporting visit stations. Study results extended that using green financing for climate change mitigation in a Chinese tourist destination is essential. Empirical results confirmed that green funding directly mitigated climate change and enhanced tourism growth in Chinese settings by solving related issues. On such findings, the study yielded the practical implications for green financing institutions, climate change policymakers and Chinese officials for tourism development.

Do Environmental Regulations Facilitate a Low-Carbon Transformation in China's Resource-Based Cities?

Resource-based cities (RBCs) are not only important for ensuring national resource and energy security, but they also face serious ecological and environmental problems. To achieve China's carbon peaking and neutrality goals in the coming years, RBCs' achievement of a low-carbon transformation has become increasingly significant. The core of this study is an investigation as to whether governance, including environmental regulations, can facilitate the low-carbon transformation of RBCs. Based on RBC data from 2003 to 2019, we establish a dynamic panel model to research the influence and mechanism of environmental regulations on low-carbon transformation. We found that China's environmental regulations facilitate a low-carbon transformation in RBCs. Mechanism analysis identified that the environmental regulations facilitate the low-carbon transformation in RBCs by strengthening foreign direct investment, enhancing green technology innovation and promoting industrial structure upgrading. Heterogeneity analysis found that the environmental regulations play a greater role in facilitating the low-carbon transformation of RBCs in regions with more developed economies and less dependence on resources. Our research provides theoretical and policy implications for environmental regulations for the low-carbon transformation of RBCs in China, applicable to other resource-based areas.

Will the imposition of carbon tariffs enhance or worsen the carbon performance of China's export industries? A reality check based on 28 manufacturing industry segments

Carbon tariffs are directly linked to carbon performance and have an impact on export sectors. This paper examines the relationship between carbon tariffs and carbon performance based on China's manufacturing sector, helping to visually quantify the impact of carbon tariffs and to adopt more favourable strategies to address the impact. This paper uses data from 28 manufacturing industry segments in China from 2009 to 2019, estimating carbon performance using an SBM model incorporating non-desired outputs. The panel Tobit model is also used to explore the driving role of carbon tariffs and related variables on carbon performance. The results show the following: First of all, China's manufacturing carbon performance is generally on an upward trend but is mainly driven by improvements in the light textile and machinery manufacturing industries. Secondly, in terms of drivers of carbon performance, the imposition of carbon tariffs will increase the carbon performance of China's manufacturing sector. Furthermore, R&D investment is positively correlated with carbon emission performance. The significant positive impact of export dependence is manifested in the light and textile industry. Energy intensity has a significant positive impact on the textile industry and a significant negative impact on the resource processing industry. Environmental regulations have a negative impact on the light textile industry. China should optimize the industrial chain of resource processing industry. At the same time, China should increase R&D investment in emission reduction and product upgrades, encourage the export of light and textile industrial products, increase the import of resource processing industrial products. Also, the government should formulate environmental regulatory policies that are close to the nature of the industry.

The effect of China's leading officials' accountability audit of natural resources policy on provincial agricultural carbon intensities: the mediating role of technological progress

China is one of the largest agricultural countries in the world. In the context of China's efforts to achieve dual carbon goals (carbon peak and carbon neutral), the need for carbon emissions reductions in the agricultural sector cannot be ignored. This study collected 2007 to 2018 data from 30 Chinese provinces and used a difference in differences (DID) model to investigate the relationships between China's leading officials' accountability audit of natural resources policy (LOAANR), agricultural technological progress, and agricultural carbon emissions intensities (CEI). A common trend test, placebo test, PSM-DID, and other test methods were used to verify the reliability of the results. The results show that (1) compared with the non-pilot areas, the policy implementation could significantly reduce CEI; (2) the LOAANR was able to stimulate patented technological progress (ATI) and mechanical technological progress (AMT), but different types of technological progress had different mediation effect sizes; and (3) the policy effects shows obvious regional heterogeneity, manifesting as west > east > central; and the policy effects were more obvious in the non-major grain-producing areas, but had no inhibition effects on the CEI in the major grain-producing areas; compared with low intensity market-based environmental regulation (MER) regions, high-intensity MER regions have stronger LOAANR emission reduction effects. Based on the study findings, policy suggestions are given to reduce agricultural carbon emissions and promote higher quality agricultural development.

Spatiotemporal Differences and Spatial Spillovers of China's Green Manufacturing under Environmental Regulation

Faced with the real demand of manufacturing industry to achieve the goal of green and high-quality development, exploring spatiotemporal heterogeneity and the spatial spillover effect of green manufacturing efficiency under environmental regulation can help reveal the path and mechanism of green development in the manufacturing industry. By using the SBM-DEM model to measure green manufacturing efficiency at the urban scale in China, exploratory spatial analysis is used to characterize the spatiotemporal differentiation of urban green manufacturing efficiency from 2003 to 2018. With the help of the spatial Durbin model, the impact of environmental regulation on green manufacturing efficiency and the spatial spillover effect are demonstrated. The results show that: (1) The green manufacturing efficiency of cities has developed in a gradual and balanced manner in time series, and the degree of equalization is stronger in the eastern coast than in the western inland; (2) Urban green manufacturing efficiency patterns are misaligned with economic scale patterns, indicating that green manufacturing is not traditionally dominated by economic factor inputs; (3) The practice of Chinese cities has proved that environmental regulation can significantly inhibit the development of green manufacturing efficiency in local cities. The crowding-out effect and optimization effect of environmental regulation on other external factors indirectly affect green development. By comparing different spatial weight matrices, it is shown that the economic relationship between cities can offset the inhibition of environmental regulation; (4) Although environmental regulation under spatial interaction would have significantly contributed to the green manufacturing efficiency of neighboring cities, this contribution effect is insignificant and weak due to the economic interactions between cities. Empirical research provides a theoretical foundation for the development of green manufacturing from the standpoint of environmental regulation, allowing green development research in manufacturing to move further.

Spatial-Temporal Characteristics and Driving Factors of the Eco-Efficiency of Tourist Hotels in China

At present, COVID-19 is seriously affecting the economic development of the hotel industry, and at the same time, the world is vigorously calling for "carbon emission mitigation". Under these two factors, tourist hotels are in urgent need of effective tools to balance economic and social contributions with ecological and environmental impacts. Therefore, this paper takes Chinese tourist hotels as the research object and constructs a research framework for Chinese tourist hotels by constructing a Super-SBM Non-Oriented model. We measured the economic efficiency and eco-efficiency of Chinese tourist hotels from 2000 to 2019; explored spatial-temporal evolution patterns of their income, carbon emissions, eco-efficiency, and economic efficiency through spatial hotspot analysis and center of gravity analysis; and identified the spatial agglomeration characteristics of such hotels through the econometric panel Tobit model to identify the different driving factors inside and outside the tourist hotel system. The following results were obtained: (1) the eco-efficiency of China's tourist hotels is higher than the economic efficiency, which is in line with the overall Kuznets curve theory, but the income and carbon emissions have not yet been decoupled; (2) most of China's tourist hotels are crudely developed with much room for improving the economic efficiency, and most of the provincial and regional tourist hotels are at a low-income level, but the carbon emissions are still on the increase; and (3) income, labor, carbon emissions, waste emissions, and water consumption are the internal drivers of China's tourist hotels, while industrial structure, urbanization rate, energy efficiency, and information technology are the external drivers of China's tourist hotels. The research results provide a clear path for the reduction in carbon emissions and the improvement of the eco-efficiency of Chinese tourist hotels. Under the backdrop of global climate change and the post-COVID-19 era, the research framework and conclusions provide references for countries with new economies similar to China and countries that need to quickly restore the hotel industry.

Research and Analysis on the Influencing Factors of China’s Carbon Emissions Based on a Panel Quantile Model

Since the beginning of the new century, China’s carbon emissions have increased significantly, and the country has become the world’s largest carbon emitter. Therefore, determining the influencing factors of carbon emissions is an important issue for policymakers. Based on the panel data of 30 provinces and cities across the country from 2000 to 2018, this study empirically tested how per capita disposable income, industrial structure, urbanization level, average family size, and technological innovation level impacts carbon emissions at different quantile levels by using the panel quantile STIRPAT model. The results showed that per capita disposable income and industrial structure had significant promoting effects on carbon emissions, while urbanization level, average family size, and technological innovation level had significant inhibitory effects on carbon emissions. The main thing is that the emission distributions of the 10th and 90th quantiles of the independent variables were quite different, which shows that the influence of each factor on carbon emissions has obvious heterogeneity at different levels. Specifically, the impact of per capita disposable income and technological innovation level on carbon emissions in low carbon emission areas were higher than that in high carbon emission areas, and the impact of industrial structure, urbanization level, and average household size on carbon emissions in high carbon emission areas was higher. Finally, specific policy implications are provided based on these results.

Does Circular Economy Contribute to Smart Cities’ Sustainable Development?

The purpose of this research paper is to investigate and identify the factors which can support the development of one characteristic of smart cities, namely, the smart environment. More specifically, the main goal is to measure the extent to which air pollution may be reduced, taking as determinants several circular economy, fiscal, and environmental factors. The Ordinary Least Squares, the Fixed Effects, and Random Effects regression models using balanced panel data were employed, over the 2011–2019 period, for 28 European states. After rigorously studying the literature, 11 indicators with a predictable impact on the exposure to air pollution were kept. According to current analysis, the most effective methods of reducing air pollution are the use of renewable energy, the investments in educating the population to reduce pollution, the proper implementation of the circular economy, and the adoption of the most suitable policies by the European Union governments. Particular attention needs to be paid to factors such as carbon dioxide-generating activities, which are significantly increasing the air pollution. Another strong value is that of providing information on the assessment of ambient air quality, and on the promotion of appropriate policies to achieve two major objectives: well-being, and sustainable cities.

Heterogeneous Environmental Regulation, Foreign Direct Investment, and Regional Carbon Dioxide Emissions: Evidence from China

As an important means to reduce carbon dioxide (CO2) emissions, environmental regulation (ER) and foreign direct investment (FDI) have become popular research topics in recent years. Most studies have examined the single impact of ER or FDI on CO2 emissions, while few investigated the regional heterogeneity and the spillover effect of different environmental regulations (ERs) on CO2 emissions and neglected the impact of the interaction mechanism between ER and FDI on CO2 emissions. This paper applies the spatial Durbin model (SDM) to explore the impact of different ERs and FDIs on regional CO2 emissions in China’s 30 provinces from 2003 to 2019. The results indicate that there are significant differences and regional heterogeneity in the effects of different environmental regulations on CO2 emissions at the national level. FDI has a significant promoting effect on CO2 emissions in the early years (2003–2009), especially in the eastern and western regions, but its effect is not significant in the late period (2010–2019). At the regional level, the abatement effects of the interaction term between FDIs and ERs are generally significant, indicating that ERs can influence the reduction effect of FDIs. Regulatory environmental regulation (RER) in the eastern region, command environmental regulation (CER), and economic environmental regulation (EER) in the central region can significantly affect the emission reduction effect of local FDI.

Carbon Emissions of the Tourism Telecoupling System: Theoretical Framework, Model Specification and Synthesis Effects

The flows of people and material attributed to international tourism exert a major impact on the global environment. Tourism carbon emissions is the main indicator in this context. However, previous studies focused on estimating the emissions of destinations, ignoring the embodied emissions in tourists’ origins and other areas. This study provides a comprehensive framework of a tourism telecoupling system. Taking China’s international tourism as an example, we estimate the carbon emissions of its tourism telecoupling system based on the Tourism Satellite Account and input–output model. We find that (1) the proposal of a tourism telecoupling system provides a new perspective for analyzing the carbon emissions of a tourism system. The sending system (origins) and indirect spillover system (resource suppliers) have been ignored in previous studies. (2) In the telecoupling system of China’s international tourism, the emission reduction effect of the sending system is significant. (3) The direct spillover system (transit) and indirect spillover system’s spatial transfer effects of environment responsibility are remarkable. (4) There is a large carbon trade implied in international tourism. This study makes us pay attention to the carbon emissions of tourists’ origins and the implied carbon trading in tourism flows.