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The Sub-Saharan African (SSA) region remains the world's largest recipient of remittances. Due to growing concerns over climate change issues, recent studies have examined how these financial flows have affected environmental quality. Sundry variables were controlled in such studies concerning the remittances-environment nexus, including institutional quality. Notwithstanding that remittance and institutional quality are imperative, their combined effect on environmental quality has been overlooked. The present study has inspected how remittances and institutional quality have jointly influenced environmental quality in 44 economies in the SSA region between 2000 and 2022. Using PMG-ARDL analysis, the findings revealed that remittances had a negative long-term impact on environmental quality. Conversely, the study found that institutional quality positively affected the per capita ecological footprints, as measured by the six indicators' average. Furthermore, the results indicated that improvements in institutional quality over time mitigated the adverse impact of remittances on the environment in the sampled SSA countries. Additionally, a threshold level of institutional quality effectively moderates remittances' detrimental effects on environmental quality were identified. Therefore, most regional countries must enhance their institutional quality to mitigate the negative environmental impact of remittances., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Unlike previous studies that have examined the association between different economic development parameters and environmental sustainability, the present study utilised an index of productive capacity to offer an in-depth understanding of the ecological impact of improving a nation's productive resources. It also emphasised the importance of remittances in reducing environmental degradation in uncertain economic and political environments. This study applied the system GMM technique and an advanced panel quantile regression technique to 36 Sub-Saharan Africa (SSA) region countries from 2000 to 2022. The findings showed that improvements in productive capacity might exert pressure on environmental quality, uncertainty, and the inflow of remittances, which tended to have a positive effect, ultimately leading to better environmental outcomes. Furthermore, the study indicated that these variables' impacts differed depending on each country's prevailing ecological conditions. It is, therefore, vital that efforts to achieve sustainable development in the SSA region consider the combined impact of these factors on environmental quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Rapid economic growth and human activities have seriously damaged the environment and hindered the achievement of Sustainable Development Goals (SDGs). Hence, this study aims to explore the impact of economic complexity, uncertainty, and remittance on environmental degradation in 134 countries from 2000 to 2022. In addition, it examines whether uncertainty moderates the relationship between remittance and environmental degradation. Two proxies (ecological footprint and CO 2 ) were used to measure environmental degradation. The analysis was conducted using a cross-sectional dependency test, second-generation unit root test, and panel quantile regression. The results revealed that economic complexity significantly and positively impacted environmental degradation, while uncertainty and remittance significantly and negatively impacted environmental degradation. Furthermore, uncertainty weakened the negative relationship between remittance and environmental degradation. Accordingly, this paper discusses various recommendations and policy implications regarding economic complexity, uncertainty, remittance, and environmental degradation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The world is currently facing urgent climate and environmental issues, such as global warming, ecosystem collapse, and energy shortages. In this context, this study selected data from 2000 to 2021 and employed the Method of Moment Quantile Regression (MMQR) to thoroughly investigate the impact of renewable energy consumption, economic complexity, and geopolitical risks on the ecological footprint of the Group of Twenty (G20) countries. The results indicate that in countries with lower quantiles, renewable energy consumption significantly reduces the ecological footprint, whereas its effect is not prominent in countries with higher quantiles. Economic complexity has a negative impact on the ecological footprint, and this impact becomes stronger as the quantile of the ecological footprint rises. Additionally, economic complexity moderates the effect of renewable energy on the ecological footprint. Geopolitical risks facilitate the growth of the ecological footprint. Likewise, robustness tests such as DOLS, FMOLS, and quantile regression confirm these estimates in the same framework. This study has conducted a profound analysis of global environmental issues, offering innovative perspectives and recommendations for achieving goals related to sustainable energy utilization, mitigating climate change, and improving the ecological environment. The findings of this research will guide policymakers in G20 countries to adopt more effective environmental protection measures, thereby contributing to the construction of a sustainable future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Coal is crucial for economic progress but equally baneful to the environment. Thus, the coal consumption-environmental sustainability nexus attracted the attention of both policymakers and scholars. This study evaluates the coal consumption-environment nexus in developed and developing countries over the period 2000-2020. We used panel data econometric techniques and the Augmented Anderson-Hsiao (AAH) two-step GMM estimator to assess and compare the impact of coal consumption on CO 2 . The findings revealed that the consumption of coal aggravates environmental pollution and hinders environmental sustainability. Thus, this study confirms the environment-destroying effect of coal consumption. However, the findings reveal that the negative consequence of coal consumption on the environment is more for the sample of developed countries than that of developing countries. This suggests that coal use harms the environment developed economies than the developing countries. Specifically, we found that the carbon emissions emanating from a one percent (1%) increase in coal consumption of the developed countries is about six-fold more than that of the developing countries. Therefore, this study suggests a gradual phase-out, rather than sudden phase-out, of coal consumption with greater emphasis on developed countries. The implementation of the coal phase-out policy and the removal of fossil fuel subsidies should start with the developed countries or be made more stringent in such countries than the developing economies. The developed countries should relinquish a greater proportion of their coal consumption than the developing countries., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

This paper investigates the role of nuclear energy in promoting ecological sustainability in India, focusing on three ecological indicators: ecological footprint (EF), CO2 emissions (CO 2 ), and load capacity factor (LF). In addition to nuclear energy, the study considers the influence of gas consumption and other drivers of ecological sustainability using data spanning from 1970 to 2018. The analysis also takes into account the impact of the 2008 global financial crisis on the model, employing the autoregressive distributed lag (ARDL) and frequency domain causality approaches to assess the relationships. Unlike previous studies, this research evaluates both the Environmental Kuznets Curve (EKC) and load capacity curve (LCC) hypotheses. The ARDL results support the validity of both the EKC and LCC hypotheses in the Indian context. Furthermore, the findings reveal that nuclear energy and human capital contribute positively to ecological quality, while gas consumption and economic growth have a negative impact on ecological sustainability. The study also highlights the increasing effect of the 2008 global financial crisis on ecological sustainability. Additionally, the causality analysis demonstrates that nuclear energy, human capital, gas consumption, and economic growth can serve as predictors of long-term ecological sustainability in India. Based on these findings, the research presents policy recommendations that can guide efforts towards achieving SDGs 7 and 13., (© 2023. The Author(s).)

A lot of attention has been paid to environmental pollution worldwide, due to the increase in anthropogenic activities. Massive investment in non-renewable energy options raises questions regarding environmental sustainability and how to maximize food and non-food output while still preserving a healthy ecosystem. To this end, the present study explores the three-way nexus between economic growth, CO 2 emission, and agriculture-value added will accounting for other control variables across a balanced panel of selected African economies from 1997 to 2020. Panel econometrics method of the generalized method of moments (two-step difference GMM) is used to obtain a robust result. From the present study, the environmental pollution model shows that economic growth significantly contributes to environmental pollution in Africa. Additionally, the food price index, capital, and FDI promote pollution, while agricultural production and labor decrease pollution. In the case of the economic growth model, the findings reveal that environmental pollution supports the growth-led pollution hypothesis. Also, the food price index and capital ameliorate economic growth, while foreign direct investments decrease economic growth. Finally, the agricultural production model indicates that economic growth increases agricultural production when the interaction term between GDPC and FDI is included in the model. In summary, the combination of explanatory variables, environmental pollution, capital, and foreign direct investment decreases agricultural production. On the contrary, the food price index and labor promote agricultural production in Africa. Furthermore, the study provides a lot of policies for authorities and stakeholders in Sub-Saharan African countries and other developing economies., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Tourism is one of the important factors that can affect the environmental and economic situation of any economy. This study investigates the relationship between tourist arrivals and CO2 emission in the top 20 tourist destinations using data from quarterly observations from 1995 to 2018. A unique technique via quantile-on-quantile regression and Granger causality in quantiles was used. In particular, how the quantiles of tourist arrivals impact quantiles of CO2 emission was analyzed. The empirical results suggest a combination of both positive and negative effects of tourist arrivals and CO2 emission in most tourist destinations. Predominantly, at both high and low tails, in the USA, Spain, Hong Kong, and Austria, tourist arrival has a positive effect on CO2 emission, whereas in the case of Canada, France, Germany, Mexico, and Malaysia, the association was negative. On the other hand, China, Greece, Russia, Japan, Italy, South Korea, Thailand, and Turkey have both positive and negative effects of tourism on CO2 emissions at low and high tails. Tourism can be an important factor while formulating policy for environmental and climate aspects.

The present study major aim was to examine the impact of globalization, economic growth, population growth, renewable energy usage and nuclear energy on CO 2 emissions globally by taking the annual data varies from 1985 to 2020. Stationarity among study variables were tested via unit root testing, while nonlinear autoregressive distributed lag (NARDL) technique was used to demonstrate the linkages among variables with the estimation of long-run and short-run. Study results reveal that both in the short run and long run, negative globalization and economic growth shocks positively and negatively influence CO 2 emissions, respectively. Besides, higher population growth is found to positively influence CO 2 emissions while renewable energy consumption cannot influence the CO 2 emission figures. Lastly, positive and negative shocks to alternative nuclear energy consumption are evidenced to negatively influence CO 2 emissions both in the short run and long run. Hence, in line with these findings, several new policies and strategies are recommended for reducing carbon emissions globally., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The primary goal of this study was to examine the relationship between fossil fuel energy, electricity production from nuclear sources, renewable energy, CO 2 emissions, and economic growth in Pakistan. Data ranging from 1975 to 2019 were utilized, and the stationarity of this data was verified through the unit root testing. The dynamic connections between variables were investigated by utilizing the linear autoregressive distributed lag technique. Long-run analysis results uncover that fossil fuel energy, renewable energy use, CO 2 emissions, and GDP per capita have a productive relationship with economic progress in Pakistan, whereas electric power consumption, electricity produced from nuclear sources, and energy utilization have an adverse effect on economic growth. Furthermore, the consequences revealed that fossil fuel energy, renewable energy consumption, carbon dioxide emissions, and GDP per capita have a significant linkage to Pakistan's economic growth via short run, whereas we revealed that the variables electric power consumption, electricity produced from nuclear sources, and energy usage have an adversative linkage to Pakistan's economic growth. Feasible progressive policies are required from the Pakistani government to pay more attention for tackling the energy and power sectors' issues in terms of fulfilling the country's energy requirements., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The present paper aims to analyze the influence of environmental practices over the sustainable development of economies which create economic resilience for the economies classified according to different income levels. The authors aim to assess the impact of high environmental degradation (HED) on GDP growth volatility and GDP growth for economies over the long term and short term for the period of 1955-2020 in 124 countries. The findings of empirical analysis conclude that HED economies will have high growth in the long term than their counterparts. The economies of HED have a significant mean difference in volatility with their counterpart control group that implies HED economies have low volatility than the control group. Economies with HED have higher financial development relative to their control economies. The empirical analysis of robustness checks shows that economies with HED have low volatility in GDP and higher growth rates. HED economies enjoy high and sustainable financial development and high gross fixed capital formation, which signifies a high level of investment in their economy than their control counterpart., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist's attention across the globe due to its long-term harmful effects on agricultural production, food supply, water supply, and livelihoods of rural households. The present study aims to explore the asymmetrical dynamic relationship between climate change and rice production with other explanatory variables. Based on the time series data of India, covering the period 1991-2018, the current study applied the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach. The results of the NARDL reveal that mean temperature negatively affects rice production in the long run while positively affecting it in the short run. Furthermore, positive shocks in rainfall and carbon emission have negative and significant impacts on rice production in the long and short run. In comparison, negative rainfall shocks significantly affect rice production in the long and short run. Wald test confirms the asymmetrical relationship between climate change and rice production. The Granger causality test shows feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production. While no causal relationship between increasing temperature and decreasing carbon emission. Based on the empirical investigations, some critical policy implications emerged. Toward sustainable rice production in India, there is a need to improve irrigation infrastructure through increasing public investment and to develop climate-resilient seeds varieties to cope with climate change. Along with, at the district level government should provide proper training to farmers regarding the usage of pesticides, the proper amount of fertilizers, and irrigation systems., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The most serious challenge to the global facade is figuring out how to mitigate pollution levels without compromising agricultural productivity. The spillover effect of environmental change is predicted to be very high, although it will differ by region and crop. Considering this view, this study tries to address this issue by adopting comprehensive methodologies to assess the influence of carbon dioxide (CO 2 ) emissions, agricultural labor, land, feeds, and fertilizers on agricultural productivity in Pakistan from 1961 to 2018. The autoregressive distributive lag (ARDL) and wavelet transform coherence (WTC) approaches are applied to estimate the long-run and short-run elasticity estimates. The empirical findings discover that CO 2 emissions, agricultural land, labor, feed, and fertilizers exert high pressure on agricultural productivity which is backed up by the WTC findings. Furthermore, the gradual shift causality test results reveal the presence of a unidirectional causality relationship between all regressors and agriculture productivity, demonstrating that all the factors significantly influence agriculture productivity. Moreover, these findings are robust to different robustness tests that we perform to test the reliability/accuracy of our core results. From policy perspectives, regulations must be developed to explore a practicable expansion strategy that includes the use of efficient fertilizers and feed at optimal levels, as well as environmental protection through public-private investment in the agricultural sector., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent years, there is concerted efforts to boost the tourism industry in Nigeria, and regulatory bodies were created for the tourism industry. This study is contributing to the ongoing debate on the tourism-energy-environment literature. Thus, we explore the linkage between tourism development, energy consumption, carbon dioxide (CO 2 ) emission, and renewable energy consumption in Nigeria for the period of 1995-2016. The present study leverages on Bounds testing to cointegration in a carbon-income function environment while incorporating renewable energy consumption to the econometric framework. Subsequently, autoregressive distributed lag methodology alongside dynamic ordinary least square (DOLS) is utilized for robustness of estimations. Empirical results give credence to the energy-induced emission hypothesis in Nigeria. This outcome is suggestive to policymakers as fossil fuel-based energy consumption deplete the quality of the environment. Similarly, the study also affirms the environmental Kuznets curve (EKC) phenomenon. The emphasis on Nigerian growth trajectory (real income level) relative to her quality of environment via the channel of economic development and energy consumption from fossil-fuel source is indicated. On the other hand, renewable energy consumption in Nigeria shows significant ability to reduce emission level in Nigeria. This result is insightful, which implies that environmental quality is not threatened with an increase in tourist arrivals, hence tourism does not degrade the environment but is sustainable to the environment. Interesting and laudable for stakeholders' international tourism arrival did not deplete the quality of the environment. The plausible explanation is attributed to the scale of tourism in Nigeria which at the moment is still low or much more there is caution/awareness on ecotourism for sustainable environment., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Population growth has been a leading driver of global CO 2 emissions over the last several decades. CO 2 emission and greenhouse gas emissions are a key issue in the world that affects food production and also causes the climate change. The core purpose of this study was to inspect the influence of carbon dioxide emission to population growth, food production, economic growth, livestock and energy utilization in Pakistan. The STIRPAT (Stochastic Impact by Regression on Population, Affluence and Technology) model with the extension of an ARDL (Autoregressive Distributed Lag) method was utilized to demonstrate the linkage amid variables. Outcomes during short-run investigation reveal that variables population growth, economic growth, rural population growth, livestock production uncovered a productive association with CO 2 emission. Furthermore, via long-run population growth, economic growth, rural population growth, livestock production and energy utilization have positive interaction with CO 2 emission, while the variables food production and urban population growth demonstrated an adverse influence to CO 2 emission during long- and short-run interaction. Similarly, the error correction model exposed that population growth, economic progress, livestock and energy utilization have constructive interaction to CO 2 emission, while the variables food production, urban and rural population growth exposed an adverse impact to CO 2 emission. On the basis of this analysis, we will address the strategic consequences., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965-2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO 2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO 2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The reduction in oil prices might make crude oil a cheaper alternative to renewable energy (RE). Given this, the present paper examines the effect of fluctuation of oil prices on the use of RE in the United States (US) during the period 1970 to 2018. We constructed two nonlinear autoregressive distributed lag (NARDL) models to examine the effect of the positive and negative oil price shocks on the use of RE in the US. The RE consumption is taken as the dependent variable and the gross domestic product (GDP), Brent crude prices, population density, trade openness, and price index as independent variables. The result revealed that the rise in crude oil price, GDP, and population density will increase RE use in the short run and in the long run as well. Moreover, the study finds that any decrease in oil prices will decrease RE use in the short run and its effect will eventually diminish in the long run. On the policy front, it is suggested that US should raise its energy security by reducing its dependency on imported crude oil and increase the role of RE through the imposition of taxes on oil and increase the base of production and consumption through a series of measures., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

One of the major challenges to the survival of life on earth is the increasingly evolving climate change. The key source of environmental pollution is global warming. With the combustion of fossil fuels, greenhouse gas (GHG), which is generated in the external environment, is increased and air pollutant as well. The present analysis key intention was to examine the CO 2 emission and climatic effects on major agricultural crop production and land use in Pakistan. The study used time span annual data varies from 1970 to 2019, and data stationarity was rectify by utilizing the unit root tests. A generalized method of moments with two-stage least squares technique was applied to expose the variables' association with CO 2 emission. The study consequences uncover that the wheat, maize, sugarcane, cotton, bajra, gram, sesamum crops, and land use have constructive association with CO 2 emission having positive coefficients with probability values (0.3762), (0.0435), (0.2287), (0.2303), (0.2272), (0.0192), (0.4535), and (0.0017) correspondingly, while rainfall, temperature, rice, jowar, and barley uncovered an adversative linkage to CO 2 emission in Pakistan. As Pakistan is an emerging country, potential constructive measures must be introduced in directive to reduce CO 2 emissions to improve the agricultural productivity., (© 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.)

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 largest challenge still remains in enhancing the living conditions and economic progress, while growing the environmental footprint is related to energy. The move towards renewable sources means that energy utilization can be increased and environmental impacts reduced. The key purpose of the present analysis was to investigate the CO2 emissions interaction to industrialization, energy imports, carbon intensity, economic progress, and gross capital formation by using time span data ranging from 1971 to 2019. Variable stationarity was confirmed by utilizing the unit root tests, while quantile regression analysis was utilized to check the CO2 emission influence on the independent variables. Outcomes showed that industrialization has constructive influence with CO2 emission having coefficient (0.161636) with probability value (0.0000). Similarly the variable energy imports, carbon intensity, and gross capital formation have positive coefficients (0.206843), (0.895212), and (0.442922) with probability values (0.2171), (0.0004), and (0.0002) correspondingly that exposed the positive interaction with CO2 emission in Pakistan. The variable economic progress exposed an adverse impact to CO2 emission with having coefficient (-0.002841) with probability value (0.8795). In directive to improve the economic progress, the government of Pakistan should take future action to minimize carbon dioxide emission from different sectors that cause the climate change., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In reality, economic expansion cannot be paced-up enough. This account for a potential trade-off between income and environmental degradation that is expectedly feasible at a maximum level of income. On this note, the current study looked at the validity of income-environmental degradation (Environmental Kuznets Curve, EKC) hypothesis especially amidst risk to investment in the United States over the period 1984-2017. Considering that the burning of fossil fuels constitutes the largest source of Greenhouse gas (GHG) in the United States, this study employed energy carbon emissions as a proxy for environmental quality and as a dependent variable. While the study employed renewable energy production as additional explanatory variable, it implemented the Autoregressive Distributed Lag (ARDL) technique in addition to a set of cointegration techniques. Importantly, the study found that the EKC hypothesis is valid for the case of the United States but not without a non-significant trade-off of risk to investment. Additionally, renewable energy production exhibits a statistically significant and desirable impact on environmental quality in both the short and long-run. In general, the study posited that while environmental sustainability is achievable at maximum level of income, it is likely attainable at the detriment of risk to investment. Hence, this observation should trigger a potential policy mechanism that minimizes risk to investment in light of the attainment of the country's sustainable development goals (SDGs)., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The previous literature presents conflicting outcomes on the relationship between financial development and CO 2 emissions. This study fixes this puzzle by testing both the direct and indirect effects of financial development on environmental pollution using Environmental Kuznets Curve (EKC) framework. Our empirical investigation relies upon difference and system generalized method of moments for a large sample of 88 developing countries during 2000-2014 period. The estimated outcomes, based on five different indicators of financial development, support the pollution inhibiting role of financial development for the selected countries. We also validate the existence of EKC hypothesis for the panel of economies. More importantly, the results of the indirect channels show that financial development also reduces the adverse effects of income, trade openness and FDI on the pollution emissions. Further, the validity of pollution heaven hypothesis (PHH), tested through trade openness and FDI variables, is also contingent upon the existence of weak financial structure. When financial development traverses certain limits, PHH ceases to exist for both these variables. Lastly, population size augments pollution emissions while human capital reduces the later. Based on these results, we propose some very important policy implications for the sample economies., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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.)

Globally, the use of modern technologies is increasing along with carbon emission due to the consumption of fossil fuels to operate modern technologies. Therefore, in this study, we aimed to investigate the relationship between carbon emission, renewable energy consumption, forestry, and agricultural value added per capita from 1998 to 2018. The auto-regressive distribution lag model was estimated for long-run and short-run correlation analysis. The results of this study revealed that carbon emission decreases owed increases in forest areas in the long and well as short-run nexus. Furthermore, in the short run, carbon emission decreases due to an increase in renewable energy consumption. In addition, the carbon emission was run in an upward direction parallel to agricultural financial development. Furthermore, this study confirmed that the unidirectional causality between variables by estimating the non-Granger causality test. Therefore, this study suggests that to combat carbon emissions with carbon emission, it is necessary to switch from nonrenewable energy to renewable energies and organic fertilizer consumption along with afforestation to make the climate free from carbon., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Rapid evolution in the population age structure of the Middle East countries has major economic, social, and environmental outcomes. Therefore, to fill the gap in the previous literatures, in this study, the effect of age structure on environmental degradation was investigated in the Middle East region. To achieve this goal, a panel data of 10 Middle East countries were examined over the period of 1990 to 2014. Moreover, the carbon dioxide emission per capita was used as an environmental pollution index in this study. According to the stationary property of the variables, small sample size data, and the assumptions of the model, the panel autoregressive distributed lag method of mean group, pooled mean group, and dynamic fixed effect estimators were investigated in this study. The empirical results implied that the pooled mean group model emerged as the most efficient among the three estimators. Also, results revealed that the age structure have a significant relationship with environmental pollution. Children and working age population have a positive elasticity, whereas elderly people have negative elasticity. Furthermore, the results showed that the working age population has the greatest explanatory power on the carbon emissions. Also, the relationship between per capita energy consumption and gross domestic product per capita with air pollution was positive. Overall, the empirical results showed that any attempt to decrease carbon dioxide emissions in the Middle East region should consider the population age structure., (© 2020. Springer-Verlag GmbH Germany, 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.

The aim of this research is to explore the association between financial development, research and development (R&D) expenditures, globalization, institutional quality, and energy consumption in India by using the quarterly data of 1995-2018. Quantile Autoregressive Distributed Lag (QARDL) approach is employed to examine the relationship. An application of the QARDL approach suggests that the R&D, financial development, globalization, and institutional quality significantly influence energy utilization in India. R&D and institutional quality have a negative effect on energy utilization which shows that due to the increase in the quality of institutions and R&D in the country, energy utilization is likely to decrease. However, globalization and financial performance have a positive influence on energy which depicts that due to the increase in financial performance and globalization in India the energy consumption is likely to increase. According to the outcomes of this research, India should make a policy to ease the penalties of energy utilization by monitoring resource transfer by means of globalization and by implementing energy conversation procedures through the advancement of the financial sector., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This study examined the long-run and short-run heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions index across the regional development levels of 31 Chinese provinces. By employing the augmented mean group method and Dumitrescu-Hurlin causality, the following results are drawn: Firstly, a bidirectional positive linkage was existent between the economic development and urban concentration in both the long-run and short-run across regional development levels. Secondly, a unidirectional positive linkage emerged from non-renewable energy use intensity to environmental emissions index, with the most influential effect in EER China (highest development level). Thirdly, bidirectional mixed linkages prevailed between economic development and non-renewable energy use intensity. Economic development mitigated the non-renewable energy use intensity (inverted U-shaped curve) in the national data set and EER China (highest development level); nevertheless, the linear linkage was observed in IER China (medium development level) and WER China (lowest development level). Fourthly, unidirectional mixed linkages were found from urban concentration to non-renewable energy use intensity and environmental emissions index. Urban concentration demonstrated a U-shaped linkage with non-renewable energy use intensity and environmental emissions index in the national data set and EER China. But it unveiled a linear linkage with both variables in IER China and WER China. Fifthly, economic development showed an environmental Kuznets curve with environmental emissions index in the national data set and EER China. Conversely, it showed a linear linkage with the environmental emissions index in IER China and WER China. In turn, the environmental emissions index linearly hampered the economic development in the national data set as well as regional samples. Finally, the long-run and short-run effects showed homogeneity of the linkages' nature; yet, the degree of effects in the long-run surpassed those in the short-run for all development levels., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Environmental Kuznets curve (EKC) is a statistical tool to examine the cointegration and causality nexus between economic growth and carbon emissions. The EKC is widely used in energy and environmental economics studies. Although a large number of researchers have analyzed the EKC by applying different statistical models, some review work has been summarized to draw a pictorial view of extending studies in this research field. However, still, the macroscopic overview needs to be considered. Therefore, this study aims to contribute to the literature for finding a new pathway for further research employing, and to facilitate this research, scientometric analysis is carried out by feature in CiteSpace. The dataset was screened and found 2384 records out of 59,225 Web of Science (WoS) references, and the records for the timespan 1999-2019 was used to visualize the knowledge map and outcome of the scientific enterprise. The visualization results reveal the most influencing studies, institutions, authors, countries, keywords, and category cloud, in the research field of EKC. This article reveals that the research on EKC in alignment with green and sustainable technology science requires more attention. Further, this article would help authors and publishers make their decisions for the research of EKC and planning for future perspectives to contribute to academic development and applied methodology.

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.

Maintaining a balance between environmental quality and economic growth is now one of the common goals of fiscal and monetary policies in developed and developing economies. This study examines the asymmetric impacts of fiscal and monetary policy instruments on environmental pollution in Pakistan over the period 1985-2019 by employing the asymmetric or nonlinear autoregressive distributed lag (NARDL) framework. The outcomes indicate that in Pakistan, a positive and negative shock in fiscal policy instruments has a significant increasing influence on carbon emissions in the short run, while a positive and negative shock in fiscal policy instruments has a significant decreasing impact on environmental pollution in long run. However, negative and positive shock in monetary policy instruments enhances carbon emissions in short-run, whereas positive shock in monetary policy instruments decreases carbon emissions in the long run. Therefore, the policymakers may consider the usage of fiscal and monetary policy instruments to maintain economic growth along with lowering the environmental pollution.

As the adoption of renewable energy (RE) is a complex and intricate procedure affected by a wide range of factors, it prompts traction among researchers to examine these influence factors. The aim of this study is to scrutinize the factors affecting consumers' intention to adopt RE for household use in Pakistan. The current research has contributed through expanding the structural framework of the theory of planned behavior by incorporating three novel factors (perception of self-effectiveness, perception of neighbor's participation, and belief about RE benefits) to have a deep insight into the factors that motivate or inhibit consumers to adopt RE. Outcomes are based on the primary data compiled from 353 households in the five main cities of Pakistan accompanying an inclusive survey. The state-of-the-art structural equation modeling was utilized to test and analyze the proposed hypotheses. The results signify that the influencing factors such as perception of self-effectiveness, awareness of RE, and perception of neighbor's participation impart a positive effect on consumers' intention to adopt RE, whereas cost of RE generation has an opposite effect. Interestingly, environmental concern and belief about RE benefits found to have neutral effects. Research results emphasize the need to enhance public awareness, reform policy structure, transform social norms, and highlight the benefits that RE provides, all through an integrative and coherent way.

This study employs dynamic panel data for 34 Sub Saharan Africa (SSA) countries for the period 1984-2016 to estimate the effects of renewable energy on environmental quality measured by three indicators, namely, per capita CO 2 emissions, energy intensity (EI) and Aggregate National Savings (ANS). The study leveraged a battery of second-generation econometric tests and estimation and causality methods to obtain the coefficients between the regressed and the regressors. Results reveal that use of renewable energy reduces CO 2 emissions and energy intensity while it enhances ANS. Economic growth still seems to be expensive for the region as it stimulates CO 2 emissions. However, it has a positive effect on ANS. As expected, fossil fuels exacerbate CO 2 emissions and energy intensity. FDI is found to be detrimental for the environment of SSA region with its positive significant coefficient on CO 2 emissions. Financial development is reported to reduce CO 2 emissions. Some causal links between variables are also noted., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The purpose of this study is to observe the effects of stock markets and exchange rate volatility on environmental pollution in Pakistan during the period 1985-2018. A nonlinear autoregressive distributed lag (ARDL) model is applied to get this objective. In general, the short-term results revealed that the positive and negative shocks in stock markets reducing the carbon emissions. In adverse, positive shocks in exchange rate volatility reduces the carbon emissions while negative shocks in exchange rate volatility have a positive significant effect on carbon emissions in Pakistan. Moreover, the positive and negative shocks in the stock market have a positive significant effect on Pakistan's carbon emissions but positive and negative shocks in exchange rate volatility negative influence on carbon emissions in the long run. The findings further show that positive and negative shocks of the stock markets and exchange rate volatility have the same effects in sign but different in magnitude in the long run. Based on these findings, some policy recommendations proposed in the context of Pakistan as well as for other developing countries.

The asymmetrical impacts of globalization and tourism on pollution emissions of 5 South Asian countries for the period from 1980 to 2018 are examined through a non-linear autoregressive distributed lag (NARDL) technique, which shows that both short and long-run coefficients are asymmetric. The findings suggest that positive and negative shocks in globalization affect carbon emissions differently in the case of Bangladesh, India, and Pakistan, while similar results are found in the case of Nepal and Sri Lanka in the long run. Furthermore, positive tourism shock, in the long run, ameliorates the environmental quality by reducing carbon emissions in Nepal and Sri Lanka, however, increases the carbon emissions in Bangladesh, India, and Pakistan. While negative tourism shock has an adverse effect on positive shock on carbon emissions in South Asia. The phenomena of globalization and tourism can exert a severe impact in aggravating the pollution emissions that policymakers should forecast and oppose. Based on these findings, some policy suggestions are proposed for South Asian economies.

In recent times, there has been increase in climate change protest across the globe. However, whether decrease in emissions is connected with climate change protest or not is yet to be documented in the literature. Consequently, the aim of this study is to fill this gap by examining ex-post detection of how climate change protests and its interconnectedness with CO2 emissions. Using the Bai and Perron (1998) structural break test, we estimate the number of breaks as well as the date of such structural breaks in CO2 emissions series for 41 countries. Our aim is to match the date of the climate change protests to those of the structural breaks. We observe that climate change protests are fairly consistent with the dates of breaks in Europe and Asia, but not in BRICS economies or US, Canada and other countries. Therefore, this method allows us to solve a gap in the energy industry related to the modelling and correct allocation of positive shocks in CO2 emissions to climate change protests., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

This study examines the short-run and long-run asymmetric effects of clean energy consumption on carbon emission in Pakistan, over the annual time period 1975-2018, by using a non-linear ARDL approach. The findings of the study confirm the existence of asymmetries, in the nexus between the clean energy consumption and carbon emission in the short and long run. The findings of non-linear model confirm that carbon emission responded contrary to positive shocks of energy variables as compared with their negative shocks. Asymmetric findings recommend that positive and negative shocks of the alternative and nuclear energy and combustible and waste energy have affected differently. Although, short- and long-run results suggest an insignificant positive and negative relationship between electric power consumption and carbon emissions. Therefore, more taxation of non-renewable energy and clean energy supports are suggested for the Pakistan economy. We concluded that Pakistan has potential in clean energy which will improve environmental quality in the near future.

The main objective of this study is to examine the impacts of globalization, financial development, government expenditures, and institutional quality on CO 2 emissions, incorporating energy consumption, and GDP per capita in the Environmental Kuznets Curve (EKC) model for 47 Emerging Market and Developing Economies (EMDEs) between 1990 and 2014. Owing to the presence of cross-sectional dependence and slope heterogeneity in the panel data, CADF and CIPS unit root tests are employed to validate the stationarity of the variables. Westerlund (Oxf Bull Econ Stat 69:709-748, 2007) and Banerjee and Carrion-i-Silvestre (J Time Ser Anal 38:610-636, 2017) cointegration tests denote the occurrence of cointegration among the variables. We employed CCEMG, AMG, and DCCE estimators to estimate heterogeneous parameters. The findings demonstrate that globalization, financial development, and energy consumption increase CO 2 emissions. Besides, the EKC hypothesis is affirmed in EMDEs. The accrual of governments' financial and governance activities also boosts carbon dioxide emissions. Moreover, the analysis of Dumitrescu and Hurlin causality provides evidences for the feedbacks among the variables and CO 2 emissions. From the aforementioned results, there exists the trade-off effect between economic growth and environmental quality in EMDE countries. Finally, the empirical findings of this study indicate profound implications for policy makers, which recommend governments to consider the role of finance and governance in order to ensure that energy consumption, financial development, and sustainable economic growth are in harmony with the environment in the globalization era.

China's carbon-embedded growth trajectory is gradually becoming a burden to environmental sustainability, hence, requires much attention. The complexity of human capital attributed emissions coupled with fossil fuel inclined energy utilization for industrialization underscores the failure of China to meet its mitigation target. We developed a policy-driven conceptual tool based on disaggregate energy utilization, human capital, trade, income level and natural resource exploitation in a carbon and environmental degradation function. Using a battery of statistics and econometric techniques such as neural network, SIMPLS, U test, dynamic ARDL Simulations, and Prais-Winsten first-order autoregressive [AR(1)] regression with robust standard errors, we examined the theme based on a data spanning 1961-2016. The study demonstrates that fossil fuel energy consumption and human capital are conducive catalysts for climate change. The instantaneous increase in renewable energy, environmental sustainability and income level has a diminishing effect on emissions and environmental degradation. The environmental Kuznets curve (EKC) hypothesis is validated in both emissions and degradation function - at a turning point of US$ 5469.79 and US$ 5863.70, respectively. The study highlights that the over-dependence on fossil fuel energy and natural resources for economic development, carbon-intensive trade and carbon-embedded human capital, thwart efforts to mitigating climate change and its impacts. Thus, the onus of responsibility for achieving a cleaner environment in China depends majorly on governmental policies that favour or dampens environmental sustainability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

This study investigates the relationship between environmental degradation and population health using a global panel data of 180 countries from 1990 to 2016. The empirical analysis is conducted using fixed-effects approach based on Hausman test. Moreover, two-stage least squares (2SLS) and system-generalized method of moments (SGMM) are used to deal with the endogenous nature of environmental degradation. The indicators of life expectancy and infant mortality are used to measure population health, whereas environmental degradation is measured by CO 2 emissions. The empirical findings show that environmental degradation negatively influences population health outcomes. It implies that countries having a high level of environmental degradation experience low life expectancy and high infant mortality rates. Findings of the study suggest that health-related reforms need to be aligned with policies which ensure lower environmental degradation.

This article revisits the nexus between financial development and environmental degradation by incorporating economic growth, electricity consumption and economic globalization in the CO 2 emissions function for the period 1975Q I -2014Q IV in the United Arab Emirates. We apply structural break and cointegration tests to examine unit root and cointegration between the variables. Further, the article also uses the Toda-Yamamoto causality test to investigate the causal relationship between the variables and tests the linkages of the robustness of causality by following the innovative accounting approach. Our empirical analysis shows cointegration between the series. Financial development increases CO 2 emissions. Economic growth is positively linked with environmental degradation. Electricity consumption improves environmental quality. Economic globalization affects CO 2 emissions negatively. The relationship between financial development and CO 2 emissions is U-shaped and inverted N-shaped. Further, financial development leads to environmental degradation, and environmental degradation in turn leads to financial development in the Granger sense.

In this modern era, environmental pollution is the biggest problem attached to industrialization. This study tries to ensure the relationship between industrialization and CO2 emissions in Pakistan for the time period 1980-2018 by using nonlinear ARDL model while controlling for urbanization, GDP, and human capital variables as a likely factor of CO2 emissions. Our foremost study objective is to examine whether or not the outcome of industrialization on CO2 emissions is symmetric or asymmetric for Pakistan that is one of the core suppliers to CO2 in South Asia, as the emissions were 0.82 million tons in 2018. Our result approves the presence of an asymmetric effect of industrialization shocks on CO2 emissions both in the short run and long run. The results reveal that industrialization increases emissions and deindustrialization decrease emissions, in short as well as long run, in Pakistan. Moreover, our finding also advises that urbanization and GDP variables have exerted a positive impact on CO2 emissions. Based on the findings, some policy suggestions are proposed for Pakistan.

This research has examined the dynamic linkages among climate change factors, such as CO 2 emissions, temperature, rainfall, and cereal yield in Turkey from 1968 to 2014. At first step, we tested stationary properties of the climatic factors and crop yield by using both traditional and breakpoint unit root tests. After the confirmation of given properties, we used the autoregressive distributed lag (ARDL) model to capture the dynamic relationship among the variables in the given span of time. The empirical results show that there is a long-run equilibrium relationship that exists between climate change factors and cereal yield. CO 2 emissions and average temperature have a diverse effect on the cereal yield, whereas average rainfall has a positive effect on the cereal yield in both the long run and short run. To check the causality, we use the Granger causality test that reveals a significant effect of climate change variables on the cereal yield. The unidirectional causal link is significant among temperature and rainfall factors. The results show that the cereal yield is affected by more climate factors like rain fall and temperature due to CO 2 emissions as compared to land and labor use. Based on the findings of the study, few suggestions have been made to address the climate change factors. Devise agriculture-specific adaptation policy for the farmers to build their capacity and resilience to tackle climate changes, for example, farm practices. Agriculture research and development should work on cereal crop varieties that can tolerate the high temperature and precipitation. These policies could help the agriculture sector to sustain production and allocation efficiency in the long run.

This study investigated the causal linkage between environmental pollution by carbon dioxide (CO 2 ) emissions and net foreign direct investment (FDI), along with some other variables, namely economic growth by real per capita income and trade openness, using balanced annual data of 17 countries from Asia for the period from 1980 to 2014. Panel cointegration tests confirm the long-run association among the variables. After checking the panel data for stationarity properties, the method panel fully modified ordinary least squares (FMOLS) is implemented. The FMOLS estimates on CO 2 emission model reveal that inward FDI has a significantly positive impact on environmental pollution, supporting the pollution haven hypothesis (PHH). Likewise, FDI model results imply that CO 2 emissions represent environmental pollution; economic growth and trade openness are the pivotal determinants of FDI. Panel causality results suggest bidirectional linkages between CO 2 emissions and inward FDI. Empirical findings suggest that economic policy reforms are required to channelise foreign capital inflows to a more environmentally healthy direction. The governments of Asian countries should chalk out policies on FDI inflows and the environment in order to achieve sustainable economic growth and development.

The current empirical study explores the linkage between carbon dioxide (CO 2 ) emissions, average temperature, cultivated area, consumption of fertilizer, and rice production in Pakistan. For this research, the annual time series data from 1968 to 2014 were used to enhance the validity of the empirical outcomes. The cointegration analysis with the auto-regressive distributed lag (ARDL) bounds testing approach is applied to explore the effects of climate change on rice production. Additionally, the estimated long-run outcomes are verified by employing fully modified ordinary least squared (FMOLS) and canonical cointegrating regression (CCR) approaches. The empirical outcomes revealed that the selected important study variables are cointegrated demonstrating the existence of long-run linkages among them. The main fruitful outcomes of this study are that rice production in Pakistan is positively affected by the carbon dioxide (CO 2 ) emissions in both long-run and short-run.

Sustainable development inculcates the process of preserving the environment for future generations while maintaining existing human needs. This study attempts to empirically investigate the relationship between CO 2 emissions, GDP, energy consumption, and imports and exports using yearly data between 1980 and 2014 for the panel of eight developing countries (i.e., Bangladesh, Egypt, Iran, Indonesia, Malaysia, Nigeria, Pakistan, and Turkey). All the tests for cointegration establish the long-run association among the variables and confirm the environmental Kuznets curve (EKC) hypothesis for the panel of eight countries. GDP and energy consumption remained significant factors for emission intensity both in the long and short run. However, exports found to be positive factor for emissions in the long run only and imports spur emissions in the short run. The country-specific results validate EKC hypothesis for Bangladesh, Iran, Nigeria, Pakistan, and Turkey. The findings are policy oriented and suggest that the countries' economic growth along with energy consumption and exports are highly emission intensive which require necessary adjustments at sustainable development policy front.