To devise an appropriate climate policy dealing with environmental degradation, reliable measurement of CO₂ emissions is essential. In the recent past, most researchers have utilized production-based emissions in their studies, ignoring the important role of consumption-based emissions in environmental degradation. Therefore, the present research examines the drivers of consumption-based CO₂ emissions in SAARC nations over the period 1990 to 2018. By employing traditional and second-generation panel cointegration methodologies, the study, more specifically, explores the link between consumption-based CO₂ emissions and its five macroeconomic determinants, namely, GDP growth, energy consumption, FDI, trade openness (measured by composite trade share index), and urbanization. The study also applies the FMOLS and DOLS techniques for calculating the long-run elasticities of regressors with respect to the explained variable. The results establish a cointegration relationship between the variables and validate an “N-shaped EKC” for the SAARC region. It is also found that in the long run, energy consumption and urbanization amplify the consumption-based CO₂ emissions while FDI and trade openness improve the environmental quality by plummeting emissions. Most importantly, the study rejects the “pollution-haven hypothesis” for the SAARC region based on the outcomes of FDI and trade openness. Lastly, based on the results, some policies are recommended for the abatement of environmental degradation in SAARC countries. As the SAARC nations rely heavily on fossil-based energy, it is suggestive for these economies to enhance the level of energy efficiency and augment the share of renewable energy sources in the energy mix. Furthermore, the policy designers in this region should encourage trade openness and liberalize inward FDI for containing consumption-based emissions.

Using time series data of Pakistan from 1990 to 2019, this study explores the asymmetric effects of political instability on clean energy consumption and CO₂ emissions. The results from the traditional ARDL model show that political stability lessens environmental damage by reducing CO₂ emissions in the long run. However, when we used the nonlinear ARDL approach, we found that political instability not only reduces the consumption of clean energy but also leads to damage environmental quality in the long run in Pakistan,while political stability not only increases the consumption of clean energy but also helps improve environmental quality in the short run in Pakistan. Thus, macroeconomic policies to promote expansion in clean energy consumption will directly stimulate green economic growth and environmental quality.

Numerous studies have examined the influence of macroeconomic factors on environmental quality in Ghana. However, to the best of our knowledge, there has been no study on the connection between green investments, financial development, and environmental quality in the context of this Sub-Saharan African country. This study was therefore conducted to help fill this gap using annual frequency time series data ranging from 1970 to 2018. In attaining the objectives of this study, robust econometric techniques were employed. From the results, all the variables were first differenced stationary and cointegrated in the long run. The dynamic ARDL simulations technique with the support of the ARDL estimator was employed to examine the elastic effects of the predictors on the response variable, and from the discoveries, green investments improved environmental quality in Ghana both in the long and the short run via carbon dioxide mitigations. However, in both the long and the short run, financial development and energy utilization had a detrimental influence on environmental quality due to their positive influence on carbon dioxide emissions. Moreover, the N-shaped association between national income and environmental pollution was validated for Ghana. On the causal directions amidst the variables, there was no causality between green investments and environmental degradation was evidenced; however, a bidirectional causality between financial development and environmental pollution was also discovered. Also, unidirectional causalities running from national income and energy consumption to environmental degradation were discovered. Based on the findings, the study recommend that investments in green sources should be intensified to help improve environmental quality in Ghana. Furthermore, improving developments in the financial sector is a vital means through which the country could attain its sustainable development goals.

In China, the county is not only an important component of industrial areas and a large contributor of carbon emissions, but also a key administrative unit for the implementation of carbon peak and carbon neutrality goals and policies. The spatiotemporal variations and structural characteristics of carbon emissions at the county scale are of great significance to China’s dual goals of regional carbon policy implementation and low carbon spatial planning. Thus, it is important and insightful to conduct an in-depth and detailed examination of these characteristics while focusing on a typical iron and steel industry county-level city in North China. This study systematically calculated the carbon emissions of the county-level city of Wu’an from 2008 to 2017, and explored their structural characteristics and spatiotemporal variations. The results showed that (1) under the influence of macroeconomic and national policies, the carbon emissions of county-level cities dominated by the iron and steel industry show obvious phased characteristics; (2) there is a significant negative correlation between industry carbon emission concentrations and industrial carbon emissions; (3) within the steel industry system, sintering, iron smelting, steelmaking, and metal product processing are the main sources of carbon emissions, and the coal-based production process of the iron and steel industry needs a fundamental reformation; and (4) the carbon emission of Wu’an City shows obvious spatial differentiation characteristics. The geographic distribution of carbon emissions in Wu’an City is very unbalanced and tended to cluster together in urban areas, industrial and mining areas, and major towns. Taking 2014 as the turning point, the spatial pattern of carbon emissions in Wu’an City presents different variation characteristics.

Global travel and tourism have enjoyed a significant boost due to the progress in air transport. However, the debate on air transport and the influx of foreign investments and global energy demand on economic development remains questionable. Therefore, this study is an attempt to contribute to the body of knowledge in the energy-tourism-led growth hypothesis literature. For this purpose, a novel approach to the effects of international tourism on economic growth is introduced for the Next-5 largest economies, namely (China, India, Indonesia, Turkey and the USA) between 1990 and 2018. Empirical results reveal a positive connection between foreign direct investment and income levels, electricity production and income levels, as well as between urbanization and economic growth. Moreover, the validation of the environmental Kuznets curve and the halo effect of foreign direct investment on the environmental degradation process provides a shred of more substantial evidence and fitting environmental instruments for policymakers. The empirical results encourage sustainable economic growth in these countries, mainly through the attraction of clean and high-technology foreign investment, the increase of the share of renewable energy sources in the energy mix and the regulation in the tourism industry. The novel contribution of this study to the empirical literature is the unification in the same research of the TLGH and the EKC for the Next-5 largest economies, establishing recommendations for tourism, energy efficiency and environmental correction process.

Clarifying the time-varying spillovers among pilot carbon emission permit trading markets in China is an important foundation for building the national carbon emission trading market. We calculate the dynamic spillover of carbon price return among the pilot carbon emission permit trading markets in China with the time-varying connectedness approach. The dataset is constructed from transaction data from seven pilot carbon markets in China during the period of June 23, 2014, to December 31, 2020. The quantitative analysis suggests that (i) Beijing and Chongqing carbon emission trading markets are the main spillover markets of carbon price returns, with strong pricing power, while the Guangdong and Tianjin markets are the main receivers of the price return spillover in other pilot carbon emission trading markets. (ii) The spillover effect among China’s carbon markets has a strong policy orientation. The improvement and development of the carbon market driven by macroeconomic regulation and control policies can effectively improve the spillover ability of the carbon market, and the market trading activity, namely the volatility of the carbon price return rate, can amplify the spillover ability of the carbon market in the short term. (iii) There exist three types of price return spillover among China’s pilot carbon emission trading markets, including central divergence, one-way chain transmission, and circular spillover. Along with the improvement of market operation efficiency, the central divergent type of spillover shifts to the pattern of circular spillover. It is necessary for the government to improve market efficiency and ensure the coordinated development of China’s pilot carbon emission trading market and national carbon emission trading market.

Achieving carbon-neutrality has become a global agenda following the ratification of the Paris Agreement. For the developing countries, in particular, attaining a low-carbon economy is particularly important since these economies are predominantly fossil-fuel dependent, to which Bangladesh is no exception. Therefore, this study specifically aimed at evaluating the environmental impacts associated with energy consumption and other key macroeconomic variables in the context of Bangladesh over the 1975–2016 period. As opposed to the conventional practice of using carbon dioxide emissions to proxy environmental quality, this study makes a novel attempt to use the carbon footprints to measure environmental welfare in Bangldesh. The outcomes from this study are expected to facilitate the carbon-neutrality objective of Bangladesh and, therefore, enable the nation to comply with its commitments concerning the attainment of the targets enlisted under the Paris Agreement and the United Nations Sustainable Development Goals declarations. The econometric analysis involved the application of methods that are suitable for handling the structural break issues in the data. The overall findings from empirical exercises reveal that aggregate energy consumption, fossil fuel consumption, and natural gas consumption boost the carbon footprint figures of Bangladesh. In contrast, nonfossil fuel consumption and hydroelectricity consumption are witnessed to abate the carbon footprint levels. Besides, economic growth and international trade are also evidenced to further increase the carbon footprints. Hence, these findings suggest that a clean energy transition within the Bangladesh economy can be the panacea to the nation's persitently aggravating environmental hardships. Furthermore, the causality analysis confirmed the presence of unidirectional causalities stemming from total energy consumption, fossil fuel consumption, natural gas consumption, hydroelectricity consumption, economic growth, and international trade to the carbon footprints. On the other hand, nonfossil fuel consumption is found to be bidirectionally associated with carbon footprints. In line with these aforementioned findings, several key policy suggestions are put forward regarding the facilitation of the carbon-neutrality agenda in Bangladesh.

Environmental degradation is frequently cited as one of the eminent issues in the modern era. To limit environmental degradation, prior literature discerns several macroeconomic, socio-economic, and institutional factors that affect environmental degradation. However, the relationship between geopolitical risk and environmental degradation is understudied in the previous literature. To fill this gap, the inquiry at hand aims to scrutinize the influence of geopolitical risk on environmental degradation for E7 countries while controlling the effect of renewable energy, non-renewable energy, and GDP. Further, we utilize both the ecological footprint and CO₂ emissions as proxies of environmental degradation and employ second-generation panel methods for robust findings. In addition to this, the present study uses augmented mean group (AMG) estimator to provide long-run relationship among the selected variables. The findings from the AMG estimator expound that there exists environmental Kuznets curve (EKC) for E7 countries. Moreover, renewable energy ameliorates environmental quality because it plunges both ecological footprint and CO₂ emissions. On the contrary, non-renewable energy consumption escalates both ecological footprint and CO₂ emissions. Finally, geopolitical risk tends to decrease CO₂ emissions as well as ecological footprint. Our findings deduce a few policy implications to replenish environmental quality. For instance, the share of renewables in the energy mix should be surged to ameliorate the environmental quality. Further, to control both the geopolitical risk and environmental degradation at the same time, policymakers should put forward reforms and initiatives (e.g., policies to escalate R&D, technological innovations, and tax exemptions on imports of renewables) that can help to improve environmental quality without affecting geopolitical risk. At times of low geopolitical risk, environmental degradation will surge; therefore, the rate of environmental control taxes should be increased by the policymakers.

The construction of green finance index is a three-tiered process that involves macroeconomic, ecological, and monetary indicators. Therefore, this research is one of the first thorough assessments of the impacts of green financing regulations in China, examining 30 provinces during the period of 2010 to 2017. Data envelopment analysis models for 30 provinces in China have been tested by using non-radial models and longitudinal datasets. The findings demonstrate that between 2010 and 2017, the efficiency of China’s provinces such as Beijing, Fujian, Guangdong, Hainan, Hebei, Jiangsu, Liaoning, Shandong, Shanghai, Tianjin, and Zhejiang and provinces of central regions as well as western provinces of country green economies has increased with distinct geographical disparities becoming more apparent. The geographical distribution of economic efficacy in the green economy is greatest in the eastern parts and poorest in the Chongqing, Gansu, Guangxi, Guizhou, Inner Mongolia, Ningxia, Qinghai, Shaanxi, Sichuan, Tibet, Xinjiang, and Yunnan. The study revealed that sustainable financial growth may be accomplished via the creation of green financing, which can be achieved by employing different solutions across the macroeconomic, institutional, and ecological considerations. The western and central areas, however, have a significant negative association. There are substantial variations in factors at the state and federal level from the viewpoint of dependent variables. Eventually, the research offers some suggestions for future ecological impact of China, along with the creation of new environmental legislation.

Poverty is a significant global ongoing issue that influences a substantial amount of people despite all efforts to eliminate or lessen it. Although poverty is an eminent problem because of its negative consequences, many people are unaware of the concept of poverty. Poverty not only degrades the human capacity but also undermines economic growth in developing regions. This research aims at exploring the impact and heterogeneity of agricultural factor endowment investment on rural relative poverty. By using the data obtained from China household tracking survey (CFPS-2018), probit model approach was applied to analyze the relationship between agricultural factor endowment investment and rural relative poverty. Finally, the intermediary effect of the selected model was validated through the robustness test. The study findings showed that the input of agricultural factor endowment can alleviate the relative poverty in rural areas of China. Our study findings also revealed that there is a significant heterogeneity in family size, endowment type of agricultural technology elements and the agricultural type. A positive association between the investment in agricultural technology and land factor endowment with relative poverty alleviation by increasing the total value of cash and deposits was revealed from the results. The overall findings of this study provide useful insights to facilitate government institutions to stabilize the agricultural labor force, accelerate the process of agricultural modernization and provide careful consideration to land property rights.