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This paper aims to analyze the link between environmental degradation and institutional quality and the price of oil moderated by economic complexity and the underground economy. We use quantile regressions with annual panel data for 15 countries in the Middle East and North Africa during 1995-2021. The findings indicate that institutional quality, economic complexity, and output positively and heterogeneously impact environmental degradation. However, the square of production has a negative impact, confirming an inverted U relationship between production and environmental degradation. Likewise, we find that the price of oil and the underground economy have a negative and heterogeneous impact on environmental degradation. Based on our results, a potential recommendation for policymakers is that the institutional framework of Middle Eastern and North African countries should be accompanied by a more significant concern for the environment instead of prioritizing extractive growth that is detrimental to the environment's environmental sustainability. Likewise, economic diversification will mitigate environmental degradation and improve formal employment. Our findings are relevant to policymakers and researchers interested in promoting ecological sustainability., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Though construction sector development and economic openness contribute to regional economic development, they have also been debated to pose some environmental challenges. Along these lines, we explored the long- and short-term connections of intensive energy consumption, economic openness, and construction sector development with the chemical oxygen demand throughout the scales of regional development of China's 30 provincial units over the 2004-2021 period. Theoretically, we contribute to the existing knowledge by incorporating chemical oxygen demand pollution, construction sector development, and economic openness to the Kaya identity's baseline framework. Empirically, we apply a series of advanced methods of panel data econometrics for robust results. Our key findings are as follows: First, we revealed a long-term stable cointegrating association among our variables of interest. Second, using the common correlated effect mean group estimator, we unfolded that the intensive energy consumption showed a chemical oxygen demand pollution reduction influence in both the long and short term, demonstrating the most substantial influence in the high regional development panel while expressing the least powerful influence the least regional development setting. Third, we unveiled that economic openness and construction sector development showed a linear chemical oxygen demand pollution enhancement influence in moderately and least developed regions. Nevertheless, both established an inverted U-shaped linkage with chemical oxygen demand pollution for the whole country as well as for high regional development data samples. Eventually, we found consistent estimates across long- and short-term investigations regarding signs of relationships; however, long-term effects remained more powerful than short-term ones. These findings would serve as factual scientific knowledge to help local as well as national governments create the optimal environmental regulations for the construction sector to achieve the sustainable development goals (SDGs), especially the Climate Action Plan (i.e., SDG-13)., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study examines the impact of government spending, income, and tourism consumption on CO 2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO 2 emissions varies across states, with some US states experiencing a decrease while others see an increase., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

While economic development-driven anthropogenic emissions pose challenges to ecological sustainability, the international travel and tourism sector has appeared as a hot contestant to bring sustainability to the ecological systems across varying development levels. This work investigates the diversified effects of the international travel and tourism sector and economic development on ecological deterioration, in the presence of urban agglomeration and energy use efficiency, across the development levels of China's 30 provincial units from 2002 to 2019. It contributes in two ways. (i) The stochastic estimation of environmental impacts by regression on population, affluence, and technology (STIRPAT) is modified to integrate the variables like international travel and tourism sector, urban agglomeration, and energy use efficiency. (ii) We measured an international travel and tourism sector index (ITTI) and made use of a continuously updated bias correction strategy (CUBCS) and a continuously updated fully modified strategy (CUFMS) for the long-term estimations. Besides, we used the bootstrapping-based causality technique for determining causality directions. The core results are as follows: Firstly, ITTI and economic development produced an inverse U-type association with ecological deterioration for the aggregate panels. Secondly, provinces exhibited a diverse range of links in that ITTI mitigated (boosted) the ecological deterioration in eleven (fourteen) provinces presenting diversified shapes of linkages. Economic development established the environmental Kuznets curve (EKC) theory with ecological deterioration in merely four provinces; however, the non-EKC theory is verified in twenty-four divisions. Thirdly, in China's east zone (high development scale), the ITTI revealed the ecological deterioration reduction (promotion) impact in eight (two) provinces. China's central zone (moderate development scale) exhibited ecological deterioration promotion in half of the provinces, and the other half showed a reduction impact. In China's west zone (low development scale), it promoted ecological deterioration in eight provinces. Economic development promoted (reduced) ecological deterioration in a single (nine) province(s). In China's central zone, it boosted (mitigated) the ecological deterioration in five (three) provinces. In China's west zone, it promoted (reduced) ecological deterioration in eight (two) provinces. Fourthly, urban agglomeration and energy use efficiency deteriorated and improved the environmental quality in aggregated panels, respectively; however, a diverse range of effects are observed for provinces. Finally, a unilateral bootstrap causality, from ITTI (economic development) to ecological deterioration, is revealed in twenty-four (fifteen) provinces. A bilateral causality is established in a single (thirteen) province(s). Based on empirical findings, policies are suggested., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental sustainability investigation has been a hotly debated topic of the modern literature; however, past studies have primarily overlooked its transmissibility or spillover outreach across economies. Herein, we investigate the novel aspect of whether transportation-based environmental taxation spatially induces spillover impacts across Italy, Germany, and France over the 1994-2020 period by employing a simultaneous spatial equation with multi-country dynamic stochastic general equilibrium modeling (DSGEM) framework. Transportation-based environmental taxation of the domestic economy negatively impacts its own investment and consumption, while it impacts the economy of neighboring economies positively. Change in output and investment in the domestic economy can be well explained by the environmental volatility of the domestic economy, whereas the environmental volatility of neighboring economies does not contribute much to explain the change in investment and output of the domestic economy. Volatility in pollution discharge occurs more by environmental volatility in the neighboring economy than in the domestic economy, and validating that environmental sustainability is transmissible across regions and economies. It urgently calls for environmental protection policies integrated and coordinated across the countries and regions to spread and capitalize on environmentally and economically favorable and sustainable effects globally. Achieving the spatially transmitted positive environmental and economic outcomes would help strengthen the Sustainable Development Goals (SDG), with a particular focus on Climate Action (SDG13), Sustainable Production and Consumption (SDG12), and Affordable and Sustainable Energy for All (SDG7)., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We looked at the long-term and short-term diversified relationships between industrial agglomeration, aggregate energy consumption, residential construction sector growth, and air pollution in China's 30 provincial units from 2004 through 2020. We contributed to the existing knowledge by calculating a holistic air pollution index (API) and applying advanced methods. We also augmented the Kaya identity by including industrial agglomeration and residential construction sector growth in the baseline framework. Based on empirical results: First, we revealed long-term stability among our covariates through panel cointegration analysis. Second, we uncovered a positive bilateral relationship between residential construction sector growth and industrial agglomeration in the long and short term. Third, we unfolded a unilateral positive correlation emerging from aggregate energy consumption to API, displaying the greatest influence in the east zone of China. Fourth, we observed a unilateral positive connection stemming from industrial agglomeration and residential construction sector growth to aggregate energy consumption and API in the long- and short-term dimensions. Finally, the linking nature was homogeneously prevailing across the long term and short term; however, the long-term impact size outweighed that of the short term. Given our empirical results, useful policy insights are discussed to provide the readers with a take-home message for substantiating sustainable development goals., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We aim to analyze the existence of a novel agricultural production-augmented environmental Kuznets curve (EKC-AP) theory for energy transition, urban agglomeration, and financial depth. To conduct this research, we use a global panel of selected 54 countries belonging to low, medium, and high levels of economic development from 1971 to 2017. Since our data are distributed into three development levels, it is highly likely to face cross-sectional dependence across the countries within and between the development levels, which may provide biased empirical results. To outpace such possibility, we employ advanced econometric strategies, which are robust to cross-sectional dependence and slope heterogeneity issues. We found that agricultural production, energy transition, urban agglomeration, financial depth, and ecological degradation experience a long-term cointegrating equilibrium association. We also confirm that exists an EKC-AP linkage of agricultural production with ecological degradation in highly developed economies, while those at the low and medium levels of development reveal a positive exponential and monotonic impact, respectively, of agricultural production on ecological degradation. The energy transition is found to promote ecological sustainability in developed countries through technique impact, while it deteriorates the ecological quality in countries at the medium development level. Moreover, urban agglomeration adversely impacts the ecological quality in the economies at low and medium development levels, whereas it improves the ecological sustainability in developed economies. Besides, financial depth proves harmful to ecological sustainability, with less subtle effects in developed economies. Based on our findings, for countries at low and medium levels of development, we propose advancing farming techniques using ecologically friendly technologies, promoting green energy transition, expanding the share of the services sector, and providing green financial systems to support green investment projects to achieve the Sustainable Development agenda of the United Nations., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

For the first time, this study introduces-proposes using the Armey curve hypothesis (ACH) for testing the environmental Kuznets curve hypothesis (EKCH) in the relevant literature. The rationale for this new proposed methodology is that both hypotheses are expected to have similar inverted U-shaped curves. Hence, we combine the aforementioned hypotheses to obtain a single composite model. This single model may allow us to calculate a maximum (optimum) level of government expenditures that will increase or decrease CO 2 emissions for USMCA (the USA-Mexico-Canada Agreement) countries. To this end, our study employs an augmented mean group (AMG) estimator. The results demonstrate that the EKCH is verified by way of the AC model only for Mexico. Additionally, with the advantage of this approach, we calculated the optimal government spending level, which will increase both per capita real GDP (RGDPPC) and CO 2 emissions in this country by around 26.4% of RGDPPC. This level of spending will be a kind of threshold point for the Mexican government's policymakers. Hence, they will know that if they continue to spend more than this level, both the RGDPPC and CO 2 emissions will decrease, implying either a lower RGDPPC or a cleaner environment. The primary purpose of the proposed methodology in this study is to reveal the possible effects of the government's economic growth-oriented increased public expenditures on the environment in a single composite model. In other words, the relationship between economic growth and the environment is approached from the perspective of public spending, and it is reminded that governments should have harmonious and sustainable public spending policies for both economic growth and a cleaner environment., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China seems ambitious to achieve a "carbon emissions peak" before 2030 and "carbon neutrality" before 2060. To deal with this emissions mitigation plan, technology innovations are regarded as a crucial factor. However, considering its rebound effect (CO 2 emissions driving effect) through economic growth, technology innovations might not prove a promising contributor to CO 2 reduction. Therefore, there is a need to investigate further the nexus between technology innovations and CO 2 emissions for conclusive debate. Based on the data of 215 cities in China, this paper uses mediating effects model to investigate the direct and indirect impacts (through economic growth and industrial structure transformation) of technology innovations on CO 2 emissions from a microeconomic perspective. The main results suggest that technology innovations generally increase CO 2 emissions in China both directly and indirectly. The impact of technology innovations and economic growth on CO 2 emissions indicated the EKC characteristics. Furthermore, the contributions of technology innovations to CO 2 emissions are distinguished in different regions. Thus, there is an urgent need for China to promote innovations in "clean technology" and to transform industrial structure to the tertiary industry to achieve the targets of carbon neutrality and emissions peaking., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Energy security, job development, and minimal environmental damage are just a few of the reasons why green energy technologies have gained popularity. Still, developing these technologies in underdeveloped countries is sluggish due to several bottlenecks. To find and prioritize the bottlenecks to development of green energy technologies (GETs), this study has used the case of South Africa. In this study, technical, financial, social, regulatory, geographical, and institutional bottlenecks are six headings under which 22 bottlenecks are further subdivided. For prioritizing these bottlenecks, a Multi-Objective Optimization based on Ratio Analysis (MOORA) strategy combined with an Evaluation based on Distance from Average Solution (EDAS) method was used. The top three bottlenecks impacting the GETs' development involved social, institutional, and regulatory, whereas in sub-headings, corrupt political systems, knowledge of the public, and fixed investments were revealed to be the most significant hurdles. In addition to that, a framework is also developed for assessing how each bottleneck hinders the development of green energy technologies. The results of this study recommend that formulation of policy using the bottom-up approach is important. Notably, politicians at the highest levels should work together to bolster government agencies so that they can monitor and carry out the policies designed to advance GETs. Building the institutional capacity of government offices is crucial for eliminating corruption in political offices and progressing GETs in South Africa., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research intends to identify influential factors in adopting and diffusing solar energy technology (SET) by micro-, small-, and medium-sized enterprises (MSMEs) in two tehsils of Multan district in Pakistan's Punjab province. To this end, the influential factors are identified through studying literature surveys and conducting questionnaires. Following that, partial least squares-based path modeling is employed. The results showed that (1) enterprises' size, perceived SET's ease of use, and perceived SET's reliability are the top three driving factors. (2) The perceived SET's price, perceived level of competition's pressure, and MSME's energy cost intensity are the barriers to the adoption and diffusion of SET, while the lack of technical knowledge about SET is a neutral factor. (3) Perceived SET's price, MSMEs' energy cost intensity, and enterprises' size are among the most important factors based on the effect size and path coefficients, while the lack of technical knowledge about SET, preferences of MSMEs' customers, and eco-labels and green stickers have lower importance. Since the adoption of SET is a rational decision that is concretely dependent on economic incentives, it is recommended to lower the price of SET to scale up the adoption and diffusion of SET by Pakistani MSMEs., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We investigate the validity of the environmental Kuznets curve (EKC) hypothesis for the NAFTA countries. In this investigation, we approach this hypothesis from a different methodology and propose employing the ARMEY curve hypothesis since the mathematical-functional propositions of both hypotheses were constructed on the same inverted U-shaped relationships. Thus, for the first time, it can be interpreted that the EKC hypothesis is empirically tested through a transmission mechanism of the ARMEY curve hypothesis in a single composite model. Therefore, this approach makes our study different from all empirical studies in the relevant literature. We apply the Augmented Mean Group (AMG) estimator to this aim. Empirical findings indicate that the ARMEY curve hypothesis was verified only for the USA. However, this new approach proposed in this study cannot test the EKC hypothesis through the ARMEY curve model for any NAFTA country since this approach requires verification of the ARMEY curve hypothesis and a significant composite model for the same NAFTA country. If our composite model was significant, it might make it possible to numerically determine a maximum real GDP per capita level that would minimize or maximize CO 2 emission levels for the USA. Therefore, this study introduces-proposes this new methodology as an alternative way of testing the EKC hypothesis in the relevant literature for future empirical studies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Nanoparticles have numerous applications related to human uses. Titanium dioxide nanoparticles (TiO 2 -NPs) are extensively used in many daily utilities. The small size particles and larger uses in the industry have led them to become a threatening entity to the living organisms. The unchecked use and dumping in the environment poses a significant toxicological risk to the developing mammalian embryo. The present study was conducted to determine the developmental toxicity and teratogenic effects of TiO 2 -NPs in murine embryos. The TiO 2 -NPs were introduced intravenously into pregnant mice graded as T1 (0.52 mg/g BW), T2 (0.7 mg/g BW), and T3 (1.05 mg/g BW) along with control with no dose administration T0 (0.00 mg/g BW). Results recorded after 14 days were resorbed fetuses, dropped wrist, hemorrhages, sacral hygromas, and kinked tails. It was concluded that the exposure of TiO 2 -NPs in mentioned doses from any source may lead to deleterious effects on the development of an embryo., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study reinvestigates the EKC hypothesis for US states with a new methodology that differs from all previous empirical studies using traditional EKC models. To this aim, this methodology, for the first time, unifies two seemingly different but strongly interrelated hypotheses (models), namely the Armey curve (AC) and traditional EKC models, into one single composite model. The rationale for creating this composite model is twofold. First, the functional propositions of these two hypotheses are depicted with inverted U-shaped curves. Second, they also have economically interrelated-causal relationships. This means that rising government spending (through the AC hypothesis) increases real GDP per capita (RGDPPC) and, consequently, increases in RGDPPC (through the EKC hypothesis) increase CO 2 emissions. The composite model created may also allow US state policymakers to determine a single maximum spending level that will maximize or minimize CO 2 emissions. Empirical findings indicate that the composite model is capable of testing the EKC hypothesis for 7 US states. Additionally, for 7 US states, maximum spending level was calculated to be around 15% of their RGDPPCs. Hence, with this calculated spending level, policymakers of these states may be able to determine-adjust their golden spending levels so as not to cause environmental degradation and declines in GDP., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Based on the panel data of 46 countries in "Belt and Road" (B&R) from 2004 to 2016, this paper studies the impact of innovation investment and institutional quality on green total factor productivity (GTFP). Firstly, the ICRG database, World Bank WDI database, Traditional Foundation database, and Wind database are matched to obtain the balanced panel data of 46 countries along the B&R from 2004 to 2016. Secondly, the Malmquist-Luenberger index, which can be included in the unexpected output, is used to calculate the GTFP of countries along B&R. Thirdly, the evaluation system of national institutional quality of B&R is constructed from three dimensions (political institutional quality, economic institutional quality, and legal institutional quality), and the overall system quality of different countries is measured by entropy method. Finally, an empirical study is made on the relationship among innovation investment, institutional quality, and green total factor productivity. The results show that innovation investment has significantly promoted the GTFP of the B&R countries. It is worth noting that there is a non-linear relationship between innovation investment and GTFP in the B&R countries. With the improvement of overall system quality, political system quality, economic system quality, and legal system quality, the promotion effect of innovation investment on GTFP is further enhanced. In addition, the heterogeneity regression results show that the impact of innovation investment on GTFP is significantly heterogeneous in different regions of the B&R countries. Specifically, innovation investment has the greatest impact on GTFP in South Asia, followed by East Asia and Pacific, Europe and Central Asia, Middle East, and North Africa., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

A rapid process of industrialization, on the one hand, transformed the economies from agrarian to industrial societies to improve the living standards and welfare of people. On the other hand, the urbanized and industrialized economies have posed challenging threats to environmental sustainability. The query at hand is whether the growing environmental emissions are driven by industrialization and urbanization or not. This research aims to empirically examine the combined role of industrialization and urbanization in achieving carbon neutrality in Pakistan by considering foreign direct investment and economic growth as control variables in the model. The core empirical results are the following: firstly, industrialization and economic growth exhibit negative but statistically insignificant impacts on CO 2 emissions, imparting a neutral role in determining the environmental degradation in Pakistan. Secondly, urbanization and foreign direct investment disclose positive and statistically significant (at 1% level of significance) impacts on CO 2 emissions, manifesting an environmental degradation driving impact in the country. Thirdly, given the slope coefficients of urbanization and foreign direct investment (0.058 and 0.035), urbanization proved to be a stronger driver than foreign direct investment. Finally, foreign direct investment is revealed to make the Pakistani economy a "Pollution Haven" for the foreign enterprises in the country. Based on empirical results, none of the variables predicted the support for carbon neutrality in Pakistan., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As the digital economy develops rapidly and the network information technology advances, new development models represented by the network economy have emerged, which have a crucial impact on green economic growth. However, the relevant previous studies lacked the role of analyzing the direct and indirect effects of internet development on green economic growth at the prefecture-level city level. For this purpose, this paper aims to examine the intrinsic mechanism of the impact of internet development on green economic growth and provide empirical support for cities and regions in China to increase internet construction. Furthermore, the mixed model (EBM), which includes both radial and non-radial distance functions, is applied to calculate the green economic growth index. Fixed effect model and mediation effect model are also employed to test influence mechanisms of the internet development on green economic growth using panel data of 269 prefecture-level cities in China from 2004 to 2019. The statistical results reveal that internet development has contributed significantly to green economic growth. When the internet development level increases by 1 unit, the green economic growth level increases by an average of 5.0372 units. However, regional heterogeneity is evident between internet development and green economic growth, that is, the promoting effect of internet development on green economic growth is gradually enhanced from the eastern region to the western region. We also find that internet development guides industrial structure upgrading improves environmental quality and accelerates enterprise innovation, which indirectly contributes to green economic growth. And internet development mainly achieves green economic growth through enterprise innovation. Based on the above findings, we concluded that policymakers should not only strengthen the guiding role of social actors to promote the stable development of the internet industry, but also foster the construction of the three models of "internet+industry integration," "internet+environmental governance," and "internet+enterprise innovation" to promote green economic growth., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As a new production factor, digitalization plays a vital role in society, economy, and the environment. Based on the expanded STIRPAT model, this paper empirically tests the impact of energy structure and digital economy on carbon emissions by panel data from 2011 to 2017 in 30 provinces of China. The results show that the energy structure mainly based on coal has a significant driving effect on carbon emissions. Compared with non-resource-based provinces, the increase of energy structure dominated by coal has a greater effect on carbon emission in resource-based provinces. It is worth noting that this kind of influence has a greater impact on the central region of China, followed by the western region and the eastern region. Besides, the digital economy has a significant moderating effect. With the development of digital economy, the impact of coal-based energy structure on carbon emissions is gradually decreasing. This effect is more significant in non-resource-based provinces and eastern China, but not significant in resource-based cities and central and western China., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The outbreak of novel coronavirus (COVID-19) has become a global concern that is deteriorating environmental quality and damaging human health. Though some researchers have investigated the linkage between temperature and COVID-19 transmissibility across different geographical locations and over time, yet these studies are scarce. This study aims to bridge this gap using daily temperature and COVID-19 cases (transmissibility) by employing grey incidence analysis (GIA) models (i.e., Deng's grey incidence analysis (DGIA), the absolute degree GIA (ADGIA), the second synthetic degree GIA (SSDGIA), the conservative (maximin) model) and correlation analysis. Data on temperature are accessed from the NASA database, while the data on COVID-19 cases are collected from the official website of the government of Pakistan. Empirical results reveal the existence of linkages between temperature and COVID-19 in all Pakistani provinces. These linkages vary from a relatively stronger to a relatively weaker linkage. Based on calculated weights, the strength of linkages is ranked across provinces as follows: Gilgit Baltistan (0.715301) > Baluchistan (0.675091) > Khyber Pakhtunkhwa (0.619893) > Punjab (0.619286) > Sindh (0.601736). The disparity in the strength of linkage among provinces is explained by the discrepancy in the intensity of temperature. Besides, the diagrammatic correlation analysis shows that temperature is inversely linked to COVID-19 cases (per million persons) over time, implying that low temperatures are associated with high COVID-19 transmissibility and vice versa. This study is among the first of its kind to consider the linkages between temperature and COVID-19 transmissibility for a tropical climate country (Pakistan) using the advanced GIA models. Research findings provide an up-to-date glimpse of the outbreak and emphasize the need to raise public awareness about the devastating impacts of the COVID-19. The educational syllabus should provide information on the causes, signs, and precautions of the pandemic. Additionally, individuals should practice handwashing, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to ensure a secure and supportive atmosphere for preventing and controlling the current pandemic., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since the developed world's economic prosperity has been heavily reliant on excessive fossil-based energy consumption, it has posed severe environmental quality challenges. This research attempts to revisit the relationship between income and anthropogenic emissions in the context of the environmental Kuznets curve (EKC) theory by considering electric power consumption, urbanization, and democratic accountability index in the Gulf Cooperation Council (GCC) region. It employs annual frequency panel data from 1990 through 2019 and three alternative advanced econometric estimation techniques. The main findings are as follows: Firstly, the EKC results for the whole sample strongly support the proposition of an inverse U-shaped connection between anthropogenic emissions and affluence in the long run. Secondly, the country-specific results confirm EKC only in Saudi Arabia and Bahrain, while the remaining countries demonstrate a U-shaped connection. Thirdly, the democratic accountability promoted anthropogenic emissions implying that it failed to contribute to environmental protection. It means that democratic setup in the GCC region performs poorly in accomplishing climate change mitigation and Sustainable Development Goals (SDGs). Fourthly, electric power consumption and urbanization impart positive and negative impacts on anthropogenic emission, respectively. These findings are found robust across the fully modified ordinary least square (FMOLS), bias-corrected LSDV (least squares dummy variable) (LSDV), and pooled mean group (PMG) estimators. Finally, Dumitrescu-Hurlin panel causality shows that (i) income and urbanization establish a two-way causality with the anthropogenic emissions. (ii) However, a unidirectional causal connection is revealed from electric power consumption and democratic accountability index to anthropogenic emissions. The findings suggest that the GCC region should prioritize environmental protection and SDGs across the political aims' recipe since it would direct the region on the path of climate change mitigation., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since renewable energy has the paramount importance of achieving environmental sustainability, developing countries like Pakistan have been facing numerous renewable energy generation (REG) development challenges. Thus, the REG development in any country can be attributed to its crucial drivers as well as crucial barriers. This work aims to identify crucial influence factors of REG development by conducting multi-facet content analysis as well as partial least square-based structural equation modeling analysis on data collected through a questionnaire survey. It has been conducted based on academicians from four Pakistani universities as well as professionals from Islamabad Electric Supply Company. The key outcomes are as follows: First, through multi-facet content analysis, ten crucial influence factors are identified. Among those factors, lack of good governance, renewable energy adaptation, and governmental energy policies are revealed to be the crucial barriers to REG development, whereas endowed resources, power production approach, renewable energy demand, investment environment for renewable energy projects, economic returns of renewable energy projects, environmental effects, and public acceptance are found to be the crucial drivers of REG development. Based on relative significance, the lack of good governance is unveiled to be the most significant factor, while environmental effects is found to be the least significant one. Moreover, among the drivers of REG development, public acceptance is found to be the prime contributor. At the same time, among crucial barriers, lack of good governance has shown the largest contribution to REG development., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Developing countries are enthusiastically on the road to economic progress and economic openness, which is proved to be a silver bullet for them. However, it has put their environmental quality at stake. This study examines whether economic openness and electricity consumption matter for environmental deterioration by controlling for the influence of economic progress. For this, we have used time series frequency data of Pakistan from 1971 to 2016 and employed the state-of-the-art dynamic autoregressive distributed lag (ARDL) simulation model. The model has the advantage over traditional ARDL in determining the positive and negative environmental deterioration variations induced by economic openness, electricity consumption, and economic progress. The main findings are as follows: Firstly, electricity consumption in both long and short run positively and significantly influenced CO 2 emissions, while long-run influence exceeded that of short run. Secondly, economic progress validated an environmental Kuznets curve hypothesis and thus limited the environmental degradation. Thirdly, economic openness showed an insignificant influence on CO 2 emissions both in the long and short run. Based on research findings, it is suggested that economic progress and economic openness are not the direct culprits to deteriorate a developing country's environmental condition like Pakistan; rather, electricity consumption remained the key role player. Therefore, the transition from fossil-based electricity consumption to renewable energy consumption would provide a sustainable pathway towards achieving sustainable economic openness in the future., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon dioxide emission and GHGs are associated with fossil fuels which have adverse effects on the environment. The key intention of this paper was to determine the asymmetric effect of CO 2 emission on expenditures, trade, FDI, and renewable energy consumption in Pakistan. An asymmetrical technique (nonlinear autoregressive distributed lag) was employed to validate the constructive and adverse relation among variables. Furthermore, the Granger causality test was also used to verify the unidirectional association amid variables. Study outcomes revealed that the adverse shocks of renewable energy consumption exposed expressively to upsurge CO 2 emission in the short-run dynamics. Conversely, constructive shocks of renewable energy consumption display an adversative association with CO 2 emission. Furthermore, the decreasing trend in foreign direct investment tends to impede the detrimental effects of CO 2 emission. Additionally, the variable expenditures also create the non-eco-friendly impacts and manifest the positive linkage through CO 2 emission. Trade possesses statistically insignificant linkage with environmental degradation. The results also disclose that positive as well as negative variations in the foreign direct investment expose to degrade the environmental eminence. Long-run results suggest the direct association between downward trend in renewable energy consumption and CO 2 emission signifying that the pollution level decreases, and the upward trend in renewable energy consumption, however, demonstrates insignificantly positive effects. The results also disclose that positive as well as negative variations in the FDI lead to degrade the CO 2 emission. Moreover, it is found that the expenditures soar the issue of pollution again in the long run. Finally, the consequence of trade on CO 2 emission is adverse, as the outcome suggests. In order to improve the environmental policies for sustainable growth, the study provides direction toward a sustainable environment by reducing carbon dioxide emission., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since the development of the service sector and renewable energy reduce fossil-based energy consumption which mitigates CO 2 emissions and this nexus provides a better understanding of the environmental sustainability. Considering the substantially increasing contribution of service sector and tremendous potential for renewable energy in ASEAN5 countries, leaning forward from ASEAN's energy and growth nexus, this study examines the impact of service sector contribution and renewable energy on the environmental quality of ASEAN5 using annual data from 1990 to 2018. The results of the fully modified ordinary least squared, dynamic ordinary least squared, and canonical co-integrating regressions depicted that the service sectors of Thailand, the Philippines, and Singapore augment CO 2 emissions; however, the service sectors of Malaysia and Indonesia could reduce CO 2 emissions. The increasing share of renewable energy can enhance environmental quality, but its magnitude varies in ASEAN5 economies; non-renewable energy, population, and economic development deteriorate the environment. Our results confirm the existence of environmental Kuznets curve in all the ASEAN5; the Gregory-Hansen test confirmed that results are robust. Finally, the Granger causality designated that economic development and non-renewable energy have a significant causal relationship with CO 2 emission of ASEAN5 countries. These findings suggest that the ASEAN5 economies need to optimize their economic structure for promoting sustainable development in the long run.Graphical abstract., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO 2 emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO 2 emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO 2 emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the "Conclusions" section., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The present study aims to investigate the effects of information and communication technology, foreign direct investment, trade and renewable energy use with GDP growth in Pakistan using time series data ranging from 1985 to 2017. Stationarity of data was verified by using unit root tests including ADF and P-P, while an autoregressive distributed lag (ARDL) model was used to check the dynamic association amid prescribed variables with long- and short-run analysis. Furthermore, cointegrating regression analysis with FMOLS, DOLS and CCR was applied to validate the variables causality. The outcomes during long-run analysis show that ICTE, trade and renewable energy have constructive linkage to GDP growth, while foreign direct investment has adverse influence to GDP growth in Pakistan. Similarly, the outcomes from cointegrating regression technique exposed that all variables including foreign direct investment, ICTE and trade have positive and constructive association with GDP growth except renewable energy that causes the adverse association to GDP growth in Pakistan. On the basis of outcomes, we will discuss the policy recommendations., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The Paris agreement (COP21) emphasized the need to progress toward using low-carbon energy technologies, including nuclear power, that is favorably looked for to meet the challenges to reduce an enormous increase in global temperature to below 2 °C. The cost of carbon pollution is highly induced by the energy sector that damages the global environmental sustainability plan. The alternative and nuclear energy demand is an optimized solution to decrease carbon damages, which can be better work under the imposition of carbon taxes on polluting industries. This study works in a given direction to analyze the role of alternative and nuclear energy, carbon pricing, FDI inflows, fossil fuel combustion, economic growth, and population density on the cost of carbon pollution in a panel of 90 selected countries for a period of 1995-2018. The results confirmed a "nuclear energy-augmented environmental Kuznets curve" with a turning point of 39.974% of total energy demand across countries. The result implies that alternative and nuclear energy initially increases carbon damages. Simultaneously, it decreases at the later stages of atomic energy expansion; thus, nuclear power growth is imperative for long-term sustainable development. A positive relationship is found between carbon pricing and carbon damage, while a negative relationship is between fossil fuel combustion and carbon damage across countries. The results conclude that expansion in nuclear energy would help reduce the cost of carbon pollution to achieve environmental sustainability agenda across countries., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

Since preceding several decades, the carbon emissions based standard Environmental Kuznets Curve (EKC) has been tested and supported by a plethora of studies in countries around the globe. The current study estimated the inward foreign direct investment (IFDI)-augmented EKCs for China's 27 provincial divisions employing the advanced econometric methodologies involving cross-sectional dependence, slope heterogeneity, and second generation-based estimation procedures. The study has further contributed through a modification to "Stochastic Influence by Regression on Population, Affluence, and Technology" (STIRPAT) in terms of including IFDI to the standard model. Accordingly, this work estimated the standard EKC (involving economic development-carbon emissions linkage) as well as IFDI-carbon emissions linkage within the STIRPAT framework, by employing a panel vector error-correction-based estimation procedure. The findings revealed that (1) the conventional EKC estimates for national and regional samples (i.e., aggregate samples) presented linkages differing from the EKC links for the provincial divisions. It suggested that the EKC at the aggregated levels is likely the consequence of aggregation bias problem. (2) The links between IFDI (in power and non-power sector) and carbon emissions provided inverse U shape for the aggregate samples, while the provincial divisions presented heterogeneous results. This is perhaps because of the aggregation bias. Hence, the aggregation bias puzzle is unriddled. (3) Also, heterogeneous patterns are found in terms of turning points, degree of impact, and nature of the association of income and IFDI with carbon emissions. The meaningful policies can be extracted for the large countries encompassing varied economic development levels, such as China, if the EKC is evaluated at the disaggregate scales., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

The present study seeks to investigate the sector-level energy consumption of oil and natural gas and to explore the linkage between economic growth, households, agriculture, industry, power, fertilizers, and commercial sector in Pakistan for the period of 1980-2016. The energy sector of Pakistan is facing severe crisis from the last few years due to inadequate production and supply. Long-lasting deficits of natural gas and oil, the two supreme types of fuel in Pakistan, had detrimental consequences for the growth as well as for the economic development. An autoregressive distributed lag (ARDL) method and Granger causality test under vector error correction model (VECM) were employed to check the association among the variables. Furthermore, the innovative accounting method was used to investigate the responsiveness of each variable to another within the study framework. Empirical results show long-run association among the variables, as oil consumption in the agriculture and power sector show a positive effect on Pakistan's economic growth. Similarly, energy consumption from natural gas in the households and fertilizers as well as in the industry sector has had a constructive association with economic growth. In contrast, energy consumption from oil in the households and industry sectors has adverse association with economic growth, while natural gas consumption in the commercial sector has negative linkage with economic growth. Possible steps should be taken by the Government of Pakistan to enhance the production of oil and natural gas from other alternatives to meet the requirements of these sectors., (© 2020. Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon dioxide emission and climatic variation have a detrimental influence on the atmosphere as well as on agriculture production. The key aim of the present study was to investigate the influence of carbon dioxide emission on livestock, cereal crops production, rainfall and temperature in China by utilizing the vector autoregressive model and Granger causality test for the period 1988-2017. Variables stationarity was verified by using ADF, P-P and KPSS unit root tests. The outcomes through long-run dynamics exposed that agriculture value added and rainfall have a positive influence on carbon dioxide emission, while cereal crops production, livestock production and temperature have an adverse interaction with carbon dioxide emission. Similarly, the results of the short-run analysis also demonstrate that agriculture value added, cereal crops production, livestock production, rainfall and temperature have a significant influence on carbon dioxide emission with their p-values (0.0488), (0.0885), (0.0263), (0.0096) and (0.5141) respectively. Furthermore, the Granger causality test outcomes also exposed a unidirectional linkage amid the variables. In order to improve agricultural productivity, the Chinese government should take potential steps to minimize the carbon dioxide emission from various industries that trigger climate change.

In this paper, we investigate the validity of the environmental Kuznets curve (henceforth, EKC) hypothesis for 8 OECD countries. To this aim, we decompose the per capita GDP series into its increases and decreases and consider only increases by excluding decreases from the model. Therefore, this method may enable us to test the EKC hypothesis more accurately, in accordance with the original theory. Following decomposition, we apply the fixed-effect regression model with Driscoll-Kraay standard errors, and the common correlated effects mean group (CCEMG) estimator. Empirical findings indicate that while the undecomposed model with undecomposed per capita GDP series supports the EKC hypothesis for 4 out of 8 countries, the decomposed model with decomposed per capita GDP series does not do so for any country. Hence, these mixed results reveal a need to employ different alternative techniques, such as the data transformation/decomposition applied in this study, for testing the EKC hypothesis.

The objective of the study is to analyze the dynamic linkages between technology factors and carbon emission in a panel of 26 selected European countries from 2000 to 2017. The results of the panel fixed-effect regression model show the monotonic increasing function between agriculture technology and carbon emissions. In contrast, panel quantile regression confirmed the inverted U-shaped 'Agriculture Technology Kuznets curve (ATKC)' of carbon emissions at 30th quantile distribution to 80th quantile distribution with the turning points of 12,60,000 tractors to 9,68,000 tractors, respectively. The results further exhibit the negative relationship between high-technology exports and carbon emissions, as high-technology exports have a positive impact on environmental quality in order to reduce carbon emissions across countries. The relationship between ICT goods exports and carbon emissions is complimentary, while R&D expenditures have a negative relationship with carbon emissions in a given period. The study substantiates the 'pollution haven hypothesis (PHH)' that is controlled by trade liberalization policies. The telephone and mobile penetrations have a differential impact on carbon emissions in both of the prescribed statistical techniques, which needs fair economic policies in order to delimit carbon emissions through green ICT infrastructure. The results further exhibit the 'material footprint' that is visible at the earlier stages of economic development while it is substantially decreasing at the later stages to verify 'environmental Kuznets curve (EKC)' hypothesis with a turning point of US$45,700. Finally, the study shows the positive relationship between industry value-added and carbon emissions that sabotaged the process of green development across countries. The study concludes that green ICT infrastructure is imperative for sustainable production and consumption, and climate change protection with cleaner production techniques and environmental regulations that reshape the international policies towards sustained growth.

Since developing countries experience economic and environmental sustainability challenges, it is desirable digging into the linkages between economic and environmental parameters. The purpose of this work is to evaluate the existence of the environmental Kuznets curve (EKC) theory (i.e., the inverse U-shape connection between real GDP per capita and per capita carbon dioxide emissions) in the sample of 11 developing countries. By using balanced annual panel data in the period between 1992 and 2014 and two alternative estimation techniques, we explored the potential inverted U-shaped linkage between carbon dioxide emissions and real GDP per capita in the sample of interest. For analysis purposes, Pedroni and Westerlund co-integration techniques are employed. Then, fully modified ordinary least squares, pooled mean group methods are applied for long-run parameter estimations. And, the Dumitrescu-Hurlin causality approach is employed for causal directions. Firstly, this work's findings provide the supportive evidence to the inverse U-shaped linkage in the long-run, indicating that an increase in real GDP per capita and electricity consumption tends to mitigate long-run carbon dioxide emissions in the developing countries, for the whole sample. Secondly, the country-specific findings suggested the presence of EKC theory for Brazil, China, India, Malaysia, the Russian Federation, Thailand, and Turkey. It implicated that these countries are on the path of attaining environmental sustainability in the long-run. However, Mexico, Philippines, Indonesia, and South Africa failed to lend credence to the EKC theory. It manifested that these countries need to design strategies directed to reduce carbon dioxide emissions from economic activity and electricity generation through efficiency improvement or promotion of renewables. Finally, bidirectional causal links are observed among all the variables of interest. The findings suggest that country-specific targeted action plans should be implemented to ensure the environmental sustainability in the developing world.

The accelerated urbanization in China was already coupled with a steadily increasing demand for energy usage. The present study major aim was to determine the asymmetric influence of urbanization, energy utilization, fossil fuel energy and CO 2 emission on economic progress in China by using an annual time series data varies from 1975 to 2017. Stationarity amid variables was verified by applying the unit root tests, while non-linear autoregressive distributed lag (NARDL) bounds testing model was used to examine the asymmetric impacts on variables with short- and long-run dynamics. Outcomes revealed that via short-run estimates, the negative shocks of energy usage cause significantly to increase the economic efficiency, but positive shocks of energy utilization display the adverse linkage with the economic progress. Similarly, the negative shocks of GDP per capita growth demonstrate a substantial upsurge in the economic progress, and the positive shocks establish the adverse influence towards economic growth. Further, the outcomes of short-run dynamics also exposed the negative shocks of urbanization significantly affected the economic growth, but positive shocks exposed the adversative influence on economic growth. The outcomes display that fossil fuel energy consumption showed a constructive impact to economic progress, and additionally, the variable CO 2 emission also uncovered a positive shocks having significant impact on economic progress. Furthermore, the outcomes of long-run analysis express that energy utilization has negative and positive shocks that expose the adverse influence on economic progress of China. GDP per capita growth exposed the constructive influence on the economic growth in both shocks. The negative and positive shocks of urbanization demonstrate a noteworthy influence on economic growth. The variable fossil fuel energy consumption also exposed an optimistic influence on economic progress, and finally the influence of CO 2 emission on economic growth is insignificant as the results exposed. The reducing carbon alteration target aims to be reached for China, and in the next several decades, it will encourage the green energy options in order to decrease carbon dioxide emission to avoid environmental pollution by raising its energy intensity.

Since the exports' nature and the productive capabilities of economies and regions play an essential role in driving the energy demand and carbon dioxide (CO 2 ) emissions, the modern literature focuses on the importance of export composition in determining the environmental quality. For this purpose, this study aims to test the composition impact of the trade by using export product diversification, extensive margin, and intensive margin on energy use and environment in a case study for the ten newly industrialized countries (NICs) from 1970 to 2014. Additionally, this study employs some other indicators such as income, urbanization, and economic complexity during our investigations. The obtained results from different panel estimations demonstrate that not only the composition of export products but also the income, urbanization, and economic complexity promote energy use and CO 2 emissions. The panel causality results revealed a bidirectional linkage between overall diversification and CO 2 emissions, and the intensive margin and CO 2 emissions. In contrast, a unidirectional causality ran from CO 2 emissions to the extensive margin. Energy consumption presented a bidirectional causality with the overall diversification, intensive margin, economic complexity, and urbanization. Finally, a unidirectional causality is observed from energy consumption to the extensive margin. Based on findings, applicable policies are discussed.

The lower ecological footprint (EF) is the sine qua non condition of cleaner energy. The purpose of this study is to investigate the convergence of per capita ecological footprint for the USMCA (The North American Free Trade Agreement) countries, involving the USA, Canada, and Mexico, over the 1961 to 2016. To this aim, the TAR (threshold autoregressive) panel unit root test is applied. Empirical findings indicate that convergence of the EF exists in the second regime, which represents 48.08 percent of the sample, and divergence in the first. Canada is the transition country between two regimes. These results signify common environmental policies-actions among the USMCA countries to mitigate-stop their environmental degradation. Additionally, detected convergence and divergence also might help the policymakers of the USMCA countries to understand which strategies-policies-actions converge or diverge them in the case of EF.

This research investigates the dynamic interactive associations among sustainable investment in the energy sector, air pollution, and sustainable development. To this end, it employs a "one-step" system-generalized method of moments (GMM) and "one-step" differential-GMM estimators, covering the period between 1996 and 2017. In this context, it utilizes the simultaneous equations of the dynamic panel data model for panel data of 27 Chinese provinces and municipalities. We have developed a new model of sustainable development, which incorporates sustainable investment in the energy sector and air pollution to offer a robust theoretical foundation for considering the underlying relations. The system-GMM estimator is used for the full data set; however, differential-GMM is utilized for the subsets of data, in order to tackle the small sample bias problem. The empirical outcomes provide several vital insights in that they yield mixed findings for the aggregated sample and subsets of data. For example, a two-way causal relationship occurs for all the panels, except the central part (medium development regions), between sustainable investment in the energy sector and sustainable development. Contrary to this, causality runs from air pollution to sustainable investment in the energy sector in a full data set and the central part (medium dev.). Nevertheless, the opposite is true in the case of the eastern part (most developed regions) of China. Still, the same relationship runs in either direction in the case of the western part (least developed regions). On the other way around, the feedback hypothesis of causality is confirmed, across all the samples, between air pollution and sustainable development. Hence, sustainable development and air pollution are overwhelmingly interdependent, in the country as well as the province and municipality level of the Chinese economy.

Turkish people are facing several problems because of the novel coronavirus (COVID-19), as the pandemic has brought about drastic changes to their daily routines. This study mainly investigates the impact of this pandemic on the daily routines of Turkish. It also unveils how COVID-19 affects the air environment. The adopted methods for data collection are based on open-ended questions and Facebook interviews as per recommended by QSR-International (2012). The sample of this study comprises of Turkish students as well as professional workers. The findings of the research show that there are eighteen different results of COVID-19 that have been identified according to the Turkish people's daily routines. Results reveal that increasing unemployment, decrease in air contamination, high stress and depression, a slowdown in the economic growth, and the tourism industry are profoundly affected due to the COVID-19 in Turkey. Furthermore, on the one hand, the consequences of the pandemic are segregated into social problems and psychological issues in daily routines. On the other hand, they have shown a positive impact on the air environment. This study concludes that, amid the COVID-19 pandemic, the lives of the people in Turkey are subject to deterioration, while the air environment of Turkey is gradually improving., (© Springer Nature B.V. 2020.)

This study investigates the heterogeneous causal linkages between urbanization, the intensity of electric power consumption, water-based pollutant emissions, and GRP in regional China by developing an urbanization-augmented "Stochastic Impacts by Regression on Population, Affluence, and Technology" (STIRPAT) model. A whole country panel of 29 provinces as well as region sub-panels of China, for the period 1999 to 2018, are estimated employing common correlated effects mean group approach (CCEMGA), which offers robustness against heterogeneous characteristics and cross-sectionally dependent series. From the theoretic modeling aspect, the intensity of electric power consumption and urbanization have been introduced as the determinants of water-based pollutant emissions in the STIRPAT modeling framework. Based on empirical results, first, GRP growth has shown appealing behavior in the form of its heterogeneous impacts on water-based pollutant emissions growth in the case of different regions. For instance, its impact is noted to be positive and statistically significant for the western region, which turned positive but statistically insignificant for the intermediate region. And it further turned significantly negative in the case of the eastern region. We call this phenomenon as "development level-based emission mitigation effect." Second, in terms of the impact of GRP growth on urbanization, the "development-based urbanization ladder effect" has been found. Based on heterogeneous causal links, firstly, the existence of a positive bilateral causal link between the intensity of electric power consumption and GRP growth and urbanization and GRP growth has been validated. Secondly, a positive unidirectional causal link emerged from urbanization to the intensity of electric power consumption and water-based pollutant emissions growth. Thirdly, the causal connection between GRP growth and water-based pollutant emissions growth remained very interesting and of mixed nature. Based on empirical findings, useful policies are extended. Graphical abstract.

This study aims to explore the dynamic association among crop production, livestock production, power consumption in agriculture, forest area, and carbon dioxide (CO 2 ) emissions. Based on the annual data of China, spanning the period 1990 to 2016, the study applied the auto-regressive distributed lag (ARDL) bounds testing approach. In addition, the fully modified ordinary least squares (FMOLS) canonical cointegration regression (CCR) and the Granger causality tests are employed to check the robustness of the ARDL estimations. The ARDL-bounds testing approach indicated that all variables share a long-run connection. The long- and short-run ARDL estimations confirmed that crop production, as well as livestock production, has a significant positive effect on CO 2 emissions in both cases. However, power consumption in agriculture and forest area has a negative effect on it, indicating that both variables reduce CO 2 emissions in the long and short run. These results stood robust under various regression estimators and confirmed the findings of the ARDL method. Additionally, the results of the causality approach specified that a unidirectional causality is running from crop production, power consumption in agriculture, and forest area to CO 2 emissions. The causality between livestock production and CO 2 emissions is bidirectional. Therefore, the directions of this connection also validate the outcomes under various techniques used for robustness. These findings suggest that the government must reconsider its policies related to agricultural and livestock production and adopt environment-friendly practices in the agriculture sector that may reduce the carbon footprints in the long run.

Carbon dioxide emission and greenhouse gas emissions are considered core issue in the world that influence agricultural production and also cause climate change. The present study seeks to investigate the linkage of methane emissions, nitrous oxide emissions, carbon dioxide emission, and greenhouse gas emissions with agricultural gross domestic product in China. The long-term association was checked by using an autoregressive distributed lag (ARDL) bounds testing approach, fully modified least squares method, and canonical cointegrating regression analysis. The results from long-run analysis exposed that carbon dioxide emission and greenhouse gas emissions have positive coefficients that demonstrate the long-run linkage with the agricultural gross domestic product having p values of 0.5709 and 0.3751, respectively. Similarly, results also revealed that agricultural methane emissions and agricultural nitrous oxide emissions have a negative association with the agricultural gross domestic product having p values of 0.1737 and 0.0559. China is a huge emitter of CO 2 emission and greenhouse gas emissions. Possible conservative policies are required to form the Chinese government to tackle this challenge to decrease CO 2 emission in order to increase agricultural production.

This work investigates the dynamic heterogeneous causal links among financial development, construction industry, energy use, and environmental quality across the development levels, for 30 Chinese provinces during the period 2001-2016. For this purpose, a model of environmental quality has been constructed introducing the financial development and construction industry as endogenous factors. A Pedroni's cointegration is employed and found the long-run cointegrating mechanism among the variables of interest. The dynamic common correlated effects mean group approach (DCCEMGA) is adopted to estimate the impact elasticities. Moreover, for robustness check, a sensitivity analysis is conducted employing common correlated effects mean group approach (CCEMGA). The main results are first, a two-way positive causal bridge is existent between gross domestic product (GDP) and energy use, construction industry and GDP, and financial development and GDP. In terms of the contribution of the construction industry to economic performance, construction industry-driven growth acceleration impact is observed. Second, a one-way positive causal link is identified running from financial development (both the banking sector and stock market) to the construction industry and is termed as finance-driven construction promotion effect. Also, a one-sided positive causal connection is operating from financial development and construction industry to energy use and carbon dioxide emissions. Finally, a standard environmental Kuznets curve (EKC), financial development-augmented EKC, and construction industry-augmented EKC hypotheses are found valid in the whole country and eastern region of China. Based on empirics, a regional heterogeneity has been observed in terms of the degree of impact and statistical significance while comparing the regional panels. The sensitivity analysis proved the empirical results to be robust and reliable. Moreover, based on the findings, policy recommendations are documented. Graphical abstract.

Massive investments in energy industry may either promote or mitigate the air pollution which is likely to influence the economic performance. In light of this, the current work is an empirical examination of heterogeneous dynamic causal interactions among energy investment, sulphur dioxide (SO 2 ) emissions and economic growth in regional China. A modified STIRPAT model is developed to introduce energy investment as a determinant of technology. Based on a modified model, a simultaneous equations system has been established to examine the three-way causal interactions among the variables of interest. As a first step, an error-correction-based second generation Westerlund (Oxford Bulletin of Economics and Statistics 69: 0305-9049, (2007). cointegration has been employed and found the long-run relationship. The simultaneous equations have been estimated by employing second generation dynamic common correlated effects mean group estimator (DCCEMGE) for 30 Chinese provinces and cities from 2001 to 2017. The empirical analysis has revealed that the energy investment induces emissions promotion effect while economic growth introduces emissions curtailment effect. However, the emissions curtailment effect remained slightly stronger than emissions promotion effect both at country and regional levels. Further, the energy investment growth uncovered economic performance enhancement effect. Furthermore, the SO 2 emissions growth induced economic performance deterioration effect. In this regard, the economic performance deterioration effect exceeded the economic performance enhancement effect. Besides, there is a bidirectional causality operative between SO 2 emissions and gross regional product (GRP) growth for the country as well as regional samples. On the contrary, a positive bilateral causal relationship between energy investment and GRP growth is found for the country as well as regional samples. Similarly, it has been found that there exists a positive bilateral causal association between SO 2 emissions and energy investment. Graphical abstract.

This paper is a maiden empirical attempt to analyze the dynamic causal linkages among urban agglomeration, electricity consumption, construction industry, and economic performance, making use of simultaneous structural equations. A national panel of 30 provinces and three sub-national panels of China, for time span 2000 to 2016, have been estimated employing system and difference generalized method of moments (GMM) estimator. A construction industry-augmented model of economic growth has been proposed, incorporating construction industry and urban agglomeration as exogenous shocks to the aggregate production and electricity consumption as the input of production function. The core empirical results are first, the urban agglomeration and construction industry positively cause electricity consumption but are not caused by the same. It revealed the critical role played by urban agglomeration along with construction industry in boosting electricity consumption. Second, the economic performance positively causes electricity consumption, urban agglomeration, and construction industry and is also caused by the same. Third, urban agglomeration causes the construction industry and is caused by the same. It exposed the mutual role of urban agglomeration and urban industry in reinforcing each other in the times of high economic performance. Finally, among the three regions, the eastern zone is found to be strongest in terms of linkages among urban agglomeration, construction industry, electricity consumption, and economic performance. The intermediate zone is moderately strong, while the western zone is found to have the least strong linkages as compared with the two regions. These results are in line with the sub-national level of economic development of China. These findings, in terms of statistical significance, are highly robust across all the panels. Furthermore, depending upon empirical results, the related strategies are proposed.

This work systematically examines the empirical interactions among foreign direct investment (FDI), renewable power generation (RPG), hydropower generation (HPG), non-hydropower generation (NHPG), and CO 2 emissions in the long run and short run. To test the existence of long-run equilibrium association among those variables, Bayer-Hanck combined cointegration and autoregressive distributed lag (ARDL) model have been employed on time series of China for the period 1991-2017. The vector error correction model-based short-run impacts among the variables of interest are also estimated. Besides, Toda-Yamamoto causality and Granger causality are employed to confirm the direction of causal links. The existence of a long-run equilibrium relationship is revealed in case of all types of specification. The expansion of both FDI and CO 2 emissions boosted RPG, HPG, and NHPG in the short run and long run, with greater intensity of impacts in the long run. To reflect comparisons, it is found that the renewables generation driving the impact of CO 2 emissions and FDI on NHPG is greater than RPG, which further exceeds HPG. In turn, the RPG, HPG, and NHPG mitigated CO 2 emissions both in the long run and short run, with stronger impacts in the long run. Moreover, the CO 2 emissions inhibition impact of HPG dominated NHPG, which further exceeded that of RPG. The FDI boosted CO 2 emissions in a way that the long-run pollution haven impact is revealed to be powerful than that of the short run. A unidirectional causality has been observed running from FDI to CO 2 emissions, RPG, HPG, and NHPG. A bidirectional causality is found operative between CO 2 emissions and RPG/HPG/NHPG. Interestingly, the long-run and short-run impacts remained homogeneous in terms of directionality. Nevertheless, strict heterogeneity is observed in terms of the degree of impacts. Based on empirics, both long-term and short-term policies on FDI, renewables generation, and CO 2 emissions are vital for decision-makers in China. Graphical abstract.

Energy affects the economic growth and development of a country. Renewable energy has become an important part of the world's energy consumption. The use of fossil fuel energy contributes to global warming and carbon dioxide emissions, and has a detrimental effect on the environment. The long-run and short-run causality relationships between electric power consumption, renewable electricity output, renewable energy consumption, fossil fuel energy consumption, energy use, carbon dioxide emissions, and gross domestic product per capita for Pakistan over the period of 1990-2017 were investigated in this paper using the autoregressive distributed lag bounds testing approach to cointegration. The augmented Dickey-Fuller unit root test and the Phillips-Perron unit root test were used to check the stationarity of the variables, while the Johansen cointegration test was applied to check the robustness of the long-run relationships. The Granger causality test under the vector error correction model extracted during the short-run estimation showed a unidirectional relationship among all variables except for the relationship between gross domestic product per capita and carbon dioxide emission, which was bidirectional (feedback hypothesis). The evidence showed that in the long run, carbon dioxide emissions, electric power consumption, and renewable electricity output had a positive and significant relationship with the gross domestic product per capita, while the relationship of renewable energy consumption, energy use, and fossil fuel energy consumption with the gross domestic product per capita had a negative effect. Overall, the long-run effects of the variables were found to have a stronger effect on the gross domestic product per capita than the short-run dynamics, which indicated that the findings were heterogeneous. The evidence suggests that the government of Pakistan should take steps to enhance the use of renewable energy resources to resolve the energy crisis in the country and introduce new policies to reduce carbon dioxide emissions.

Date palm waste-derived biochar (DBC) was produced through pyrolysis (600 °C) and modified with zeolite (Z-DBC), silica (S-DBC), or nano-zerovalent iron (nZVI-DBC) to design efficient sorbents. The pristine and engineered biochars were characterized by SEM, XRD, BET, TGA, CHNS-O, and FTIR to investigate the surface, structural, and mineralogical composition. The nZVI-DBC exhibited lowest pH (6.15) and highest surface area (220.92 m 2  g -1 ), carbon (80.55%), nitrogen (3.78%), and hydrogen (11.09%) contents compared with other biochars. Isotherm sorption data for chlortetracycline (CTC) removal from aqueous solutions was described well by Langmuir and Redlich-Peterson isotherms showing the highest fitness (R 2 values in the range of 0.88-0.98 and 0.88-0.99, respectively). Langmuir predicted maximum CTC adsorption capacity was in order of nZVI-DBC (89.05 mg g -1 ) > S-DBC (45.57 mg g -1 ) > Z-DBC (30.42 mg g -1 ) > DBC (28.19 mg g -1 ). Kinetics adsorption data was best described by power function model (R 2  = 0.93-0.99), followed by interaparticle diffusion (R 2  = 0.85-0.96) model. The nZVI-DBC performed outclass by removing 98% of CTC, followed by S-DBC (68%), Z-DBC (35%), and DBC (36%). Chemisorption, H-bonding, and interaparticle diffusion were the operating mechanisms for CTC adsorption onto DBC, S-DBC, and Z-DBC, while π-π electron donor-accepter interactions and redox reactions augmented these mechanisms for highest CTC adsorption onto nZVI-DBC. Therefore, nZVI-DBC may serve as an efficient green technology for the removal of CTC from aqueous solutions and to reduce surface date palm waste pollution. Graphical abstract .

The current study empirically examines the influencing mechanisms among energy consumption, financial development, international trade, environment, and economic growth for 29 Chinese provinces and cities for periods 1997 to 2016. A new augmented growth model has been developed, introducing financial development as a shift factor of aggregate production, international trade as determinant of total factor productivity, and energy consumption as input of production function. The key empirical findings include (1) financial development exposed dual nature in terms of its influence on energy consumption and carbon emissions. Banking-based financial development is revealed to add in energy consumption and carbon emissions, while stock market-based financial development curtailed energy consumption and mitigated the carbon emissions, improving the environmental quality, (2) GDP growth is uncovered to add to international trade with varying magnitudes in all samples; however international trade imparted negative to neutral to positive influence on GDP growth in W-region, C-region, and E-region, respectively. It is named as competitiveness driven growth deceleration/neutrality/acceleration influence. It states that as regions/countries develop, the domestic industry gets competitive in international trade markets; consequently, the influence of international trade on economic growth transforms from negative to neutral to positive, (3) both type of financial development measures imparted significant positive influence on GDP growth which confirms the Schumpeterian view to be valid in regional China, (4) based on causality from quadratic terms of GDP, international trade, and financial development ratio to carbon emissions growth confirm the existence of conventional EKC as well as international trade and financial development based EKC in all regions except W-region for which conventional EKC and international trade based EKC are not confirmed. Finally, based on empirical influencing mechanisms, the relevant policies are recommended.

This is the first attempt to explore linkages among industrialization, urbanization, energy consumption, CO2 emissions, and economic growth based on estimations in simultaneous equations framework. An economic growth model is extended to incorporate industrialization as shift factor and pollutant emissions as determinant of total factor productivity. A country panel of 30 Chinese provinces/cities and three regional panels, for periods 2000-2016, are estimated employing Augmented Mean Group (AMG) estimator as well as Common Correlated Effects Mean Group (CCEMG) estimator that are robust to both cross-sectional dependence and cointegration. The empirical findings are as follows: (i) the impact of urbanization on economic growth varied from negative to neutral to positive for western-, intermediate-, and eastern-economic zone, respectively, and is known as "urbanization ladder effect," (ii) moving from western to eastern economic zone, as regions develop, industry expansion has more powerful impact on economic growth, and thus, we define it as "industry expansion effect," (iii) industrialization promotes rapid urbanization in less developed and less employment saturated regions; hence, we name it as "employment saturation effect," (iv) economic growth in more developed regions pulled the CO2 emissions downward, while pushed it upward in case of less developed regions; therefore, we call it "growth pull/push effect," and (v) in bidirectional causality between energy consumption and economic growth, the "feedback effect" of economic growth remained dominant for all four panels. Based on empirical findings, policies are suggested for Chinese economy. Further, these policies have potential to extract implications for the rest of the world.