The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.
As the negative repercussions of environmental devastation, such as global warming and climate change, become more apparent, environmental consciousness is growing across the world, forcing nations to take steps to mitigate the damage. Thus, the current study assesses the effect of green investments, institutional quality, and political stability on air quality in the G-20 countries for the period 2004-2020. The stationarity of the variables was examined with the Pesaran (J Appl Econ 22:265-312, 2007) CADF, the long-term relationship between the variables by Westerlund (Oxf Bull Econ Stat 69(6):709-748, 2007), the long-run relationship coefficients with the MMQR method proposed by Machado and Silva (Econ 213(1):145-173, 2019), and the causality relationship between the variables by Dumitrescu and Hurlin (Econ Model 29(4):1450-1460, 2012) panel causality. The study findings revealed that green finance investments, institutional quality and political stability increased the air quality, while total output and energy consumption decreased air quality. The panel causality reveals a unidirectional causality from green finance investments, total output, energy consumption and political stability to air quality, and a bidirectional causality between institutional quality and air quality. According to these findings, it has been found that in the long term, green finance investments, total output, energy consumption, political stability, and institutional quality affect air quality. Based on these results, policies implications were proposed.
The objective of the study is to examine the impact of environmental indicators and air pollution on "health" and "wealth" for the low-income countries. The study used a number of promising variables including arable land, fossil fuel energy consumption, population density, and carbon dioxide emissions that simultaneously affect the health (i.e., health expenditures per capita) and wealth (i.e., GDP per capita) of the low-income countries. The general representation for low-income countries has shown by aggregate data that consist of 39 observations from the period of 1975-2013. The study decomposes the data set from different econometric tests for managing robust inferences. The study uses temporal forecasting for the health and wealth model by a vector error correction model (VECM) and an innovation accounting technique. The results show that environment and air pollution is the menace for low-income countries' health and wealth. Among environmental indicators, arable land has the largest variance to affect health and wealth for the next 10-year period, while air pollution exerts the least contribution to change health and wealth of low-income countries. These results indicate the prevalence of war situation, where environment and air pollution become visible like "gun" and "bullet" for low-income countries. There are required sound and effective macroeconomic policies to combat with the environmental evils that affect the health and wealth of the low-income countries.
The foremost purpose of the study is to establish a point that an economy of G-7 countries has an abundance of resources to tackle the environmental changes that occur in the world, but these countries are still behind the line because in this modern era, environmental performance changes their shape, dimension, and nature very frequently and create a huge impact on globalization of world economy. To fill this gap, we use green investment, institutional quality, and economic growth on environmental performance for this, we use four proxies for green investment and three proxies for greenhouse gas, and we also use six proxies of institutional quality to do this using period of 1997 to 2021. Moreover, we have used the panel nonlinear autoregressive distributed lag method to evaluate the long-run and short-run asymmetric effects of green investment, institutional quality, and economic growth on greenhouse gas emissions. The findings of the study affirm that the positive change of green investment has a positive and significant relationship with environmental performance, while the negative change of green investment has a significant and positive influence with environmental performance in the long run. Furthermore, the outcomes demonstrate that the positive shock of institutional quality has a positive and significant relationship with environmental performance, while the negative shock of intuitional quality has a significant and positive association with environmental performance in the long run, whereas positive change in economic growth has a positive and significant with the environmental performance, while the negative change of economic growth has a positive effect with environmental performance in the long run. This study finds future precautions that institutional quality has to perform exceptionally and shows results very rapidly, while green investment with economic growth has also made a deadly combination to control greenhouse gas emission, so the role of G-7 countries is pretty clear and straight. Furthermore, it is suggested that governments and policymakers take a proactive stance to promote resource acquisition and investment across all industries. To reduce gas emissions, public interest might also be complementary to private ones. So, economic policymakers, specifically in G-7 countries, should consider strategies that support sustainable economic growth.
The present paper implements the quantile autoregressive lagged (QARDL) approach of Cho et al. (2015) and the Granger causality in quantiles tests of Troster et al. (2018) to explore the nonlinear effects of US energy consumption, economic growth, and tourist arrivals on carbon dioxide (CO2) emission. Our results unveil the existence of substantial reversion to the long-run equilibrium connectedness between the variables of interest and CO2 emissions. The outcomes show that tourist arrivals decrease CO2 emissions in the long term for each quantile. In addition, we found that the output growth positively influences the carbon emissions at lower quantiles but negatively influences the carbon emissions at upper quantiles. Moreover, our findings of short-term dynamics validate an asymmetric short-run effect of tourist arrivals and economic growth on CO2 emissions in the US economy. Further results and their corresponding policy implications are discussed.
Over the last three decades, the world has been facing the phenomenon of the ecological deficit as the ecological footprint is continuously rising due to the persistent decline of the per-capita bio-capacity. Moreover, there is a substantial increase in globalization and electricity consumption for the same period, and transportation is contributing to economic prosperity at the cost of environmental sustainability. Understanding the determinants of ecological footprint is thus critical for suggesting appropriate policies for environmental sustainability. As a result, this study analyzes the impacts of economic globalization, transportation, coal rents, and electricity consumption in ecological footprint in the context of the USA over the period 1995 to 2018. The data have been extracted from "Global Footprint Network," "Swiss Economic Institute," and "World Development Indicators." The current study has also applied the flexible Fourier form nonlinear unit root test to examine the stationarity among variables. For the empirical estimation, a novel technique, the "quantile auto-regressive distributive lag model," is applied in the study to deal with the nonlinear associations of the variables and to evaluate the long-term stability of variables across quantiles. The study's findings indicate that coal rents, transportation, and globalization significantly and positively contribute to the deterioration of ecological footprints at different quantile ranges in the short and long run. Electricity consumption is found to have a positive and significant impact at lower quantile ranges in the long run but not have a significant impact in the short run. The study suggested that lowering the dependence of the transport sector on fossil fuels, more use of hydroelectricity, and stringent strategies to curb coal consumption would be helpful to reduce the positive influence of these variables on ecological footprints in the USA.
Agricultural production is sensitive to climate variability, so climate change-agriculture sector nexus is topical in developing countries. To this end, this study examines the impact of climate change variables-rainfall and temperature-and non-climatic factors on maize production in Somalia for the period between 1980 and 2018 using the autoregressive distributed lag (ARDL) bound test, dynamic ordinary least square (DOLS), variance decomposition(VD), and impulse response function (IRF). The empirical results of the ARDL bound test confirmed the presence of long-run cointegration between the dependent variable and the explanatory variables. Furthermore, the long-run results revealed that average temperature, average rainfall, and political instability significantly inhibit maize production in the long and short runs, but rainfall has a favorable effect on maize production in the short run. Furthermore, rural population and land area under maize cultivation have negative and positive effects on maize production in the long run, respectively-albeit they are statistically insignificant. The empirical results of the study are robust to different econometric methods. Based on these findings, the study emphasizes the importance of the de-escalation of conflicts and the implementation of irrigation facilities which will enhance the productivity of maize crop production.
Extensive contamination of soils by highly recalcitrant contaminants such as polycyclic aromatic hydrocarbons (PAHs) is an environmental problem arising from rapid industrialisation. This work focusses on the remediation of soil contaminated with 3- and 4-aromatic ring PAHs (phenanthrene (PHE) and fluoranthene (FLUT)) through catalysed hydrogen peroxide propagation (CHP). In the present work, the operating parameters of the CHP treatment in packed soil column was optimised with central composite design (H2O2/soil 0.081, Fe(3+)/soil 0.024, sodium pyrophosphate (SP)/soil 0.024, pH of SP solution 7.73). The effect of contaminant aging on PAH removals was also investigated. Remarkable oxidative PAH removals were observed for the short aging and extended aging period (up to 86.73 and 70.61 % for PHE and FLUT, respectively). The impacts of CHP on soil biological, chemical and physical properties were studied for both spiked and aged soils. Overall, the soil functionality analyses after the proposed operating condition demonstrated that the values for soil respiration, electrical conductivity, pH and iron precipitation fell within acceptable limits, indicating the compatibility of the CHP process with land restoration.
The increasing level of greenhouse gas carbon emission currently exacerbates the devastating effect of global warming on the Earth's ecosystem. Energy usage is one of the most important determinants that is increasing the amount of carbon gases being released. Simultaneously, the level of energy usage is derived by the price, and therefore, this study examines the contribution of energy price to carbon gas emissions in thirteen African nations for the period spanning 1990 to 2017. It does this by utilising the cross-sectional dependence (CD), augmented mean group (AMG) and pooled mean group (PMG) panel modelling methods. The findings of the AMG model suggest that a 1% increase in energy price leads to a 0.02% decrease in carbon emission. The results further reveal that a 1% increase in energy intensity and technological innovation leads to 0.04% and 3.65% increase in carbon emission, respectively, in the selected African countries. Findings will help policymakers to implement effective energy price policies to reduce carbon emissions and achieve sustainable development goals especially in the emerging economies of Africa.
Empirical studies pertaining to the effects of fiscal policy instruments on environmental quality have provided mixed evidence. We consider the asymmetric effects of fiscal policy instruments on environmental quality for the top ten Asian carbon emitters over the period 1981-2018. We go beyond the literature and claim that the effects could be asymmetric. More specifically, we found that a positive shock in government expenditure will worsen environmental quality in Malaysia, UAE, Thailand, Indonesia, Turkey, Iran, India, and China, and improve it in Japan. On the other hand, we found that cutting government expenditure will improve environmental quality in these economies and will worsen only in Japan. Moreover, a higher government income tax revenue uniquely increases the government's spending that increases the carbon emissions in Malaysia, UAE, Thailand, Indonesia, Turkey, Iran, India, and China, and decrease in Japan. The negative shock of government revenue has adverse results on carbon emissions in these economies. However, short-run asymmetric effects translate to long-run effects in most Asian economies.
The relationship between national income growth and the environment of 14 Asian economies over a 50 year period is examined using the Environmental Kuznets Curve (EKC) hypothesis. Ecological Footprint (EF) measures environmental impacts and gross domestic product (GDP) measures economic growth. It is hypothesised that increased rates of economic growth come at a cost to the natural environment. The EKC hypothesis has been mainly tested in the literature by cross-sectional or panel data methods. In this study, it is tested using time series analysis through initially examining the relationship between EF and GDP using linear, quadratic and cubic estimating OLS regression functions. In the second stage, the long-run relationship between EF and GDP is investigated using an augmented error correction trend model. There is a statistically significant cointegrated long-run relationship between the variables in most of the countries. The EKC hypothesis is supported in the case of India, Nepal, Malaysia and Pakistan with the other countries exhibiting a positive linear relationship between the two variables. Almost all error correction terms are correct in sign and significance that implies that some percentage of disequilibria in EF in the previous year adjusts back to the long-run equilibrium in the current year. Based on the long-run relationship, it is apparent that rapid economic growth has had an impact on the environment and the ecosystems of these countries over the last 50 years. Despite that, until now, not many of them have taken sufficient steps to reduce their EF or to improve their bioproductive capacity.
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.
Ocean acidification, due to increased levels of anthropogenic carbon dioxide, is known to affect the physiology and growth of marine phytoplankton, especially in polar regions. However, the effect of acidification or carbonation on cellular metabolism in polar marine phytoplankton still remains an open question. There is some evidence that small chlorophytes may benefit more than other taxa of phytoplankton. To understand further how green polar picoplankton could acclimate to high oceanic CO2, studies were conducted on an Antarctic Chlorella sp. Chlorella sp. maintained its growth rate (∼0.180 d-1), photosynthetic quantum yield (Fv/Fm = ∼0.69) and chlorophyll a (0.145 fg cell-1) and carotenoid (0.06 fg cell-1) contents under high CO2, while maximum rates of electron transport decreased and non-photochemical quenching increased under elevated CO2. GCMS-based metabolomic analysis reveal that this polar Chlorella strain modulated the levels of metabolites associated with energy, amino acid, fatty acid and carbohydrate production, which could favour its survival in an increasingly acidified ocean.
Human emissions of carbon dioxide are causing irreversible changes in our oceans and impacting marine phytoplankton, including a group of small green algae known as picochlorophytes. Picochlorophytes grown in natural phytoplankton communities under future predicted levels of carbon dioxide have been demonstrated to thrive, along with redistribution of the cellular metabolome that enhances growth rate and photosynthesis. Here, using next-generation sequencing technology, we measured levels of transcripts in a picochlorophyte Chlorella, isolated from the sub-Antarctic and acclimated under high and current ambient CO2 levels, to better understand the molecular mechanisms involved with its ability to acclimate to elevated CO2. Compared to other phytoplankton taxa that induce broad transcriptomic responses involving multiple parts of their cellular metabolism, the changes observed in Chlorella focused on activating gene regulation involved in different sets of pathways such as light harvesting complex binding proteins, amino acid synthesis and RNA modification, while carbon metabolism was largely unaffected. Triggering a specific set of genes could be a unique strategy of small green phytoplankton under high CO2 in polar oceans.
This study aimed to predict monthly columnar ozone (O3) in Peninsular Malaysia by using data on the concentration of environmental pollutants. Data (2003-2008) on five atmospheric pollutant gases (CO2, O3, CH4, NO2, and H2O vapor) retrieved from the satellite Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) were employed to develop a model that predicts columnar ozone through multiple linear regression. In the entire period, the pollutants were highly correlated (R = 0.811 for the southwest monsoon, R = 0.803 for the northeast monsoon) with predicted columnar ozone. The results of the validation of columnar ozone with column ozone from SCIAMACHY showed a high correlation coefficient (R = 0.752-0.802), indicating the model's accuracy and efficiency. Statistical analysis was utilized to determine the effects of each atmospheric pollutant on columnar ozone. A model that can retrieve columnar ozone in Peninsular Malaysia was developed to provide air quality information. These results are encouraging and accurate and can be used in early warning of the population to comply with air quality standards.
China is responsible for the biggest shellfish and macroalgae production in the world. In this study, comprehensive methods were used to assess the CO2 release and sequestration by maricultured shellfish and macroalgae in China. Through considering CaCO3 production and CO2 release coefficient (Φ, moles of CO2 released per mole of CaCO3 formed) in different waters, we find that cultured shellfish released 0.741 ± 0.008 Tg C yr-1 through calcification based on the data of 2016-2020. In addition to calcification, maricultured shellfish released 0.580 ± 0.004 Tg C yr-1 by respiration. Meanwhile, shellfish sequestered 0.145 ± 0.001 and 0.0387 ± 0.0004 Tg C yr-1 organic carbon in sediments and shells, respectively. Therefore, the net released CO2 by maricultured shellfish was 1.136 ± 0.011 Tg C yr-1, which is about four times higher than that maricultured macroalgae could sequester (0.280 ± 0.010 Tg C yr-1). To achieve carbon neutrality within the mariculture system, shellfish culture may need to be restricted and meanwhile the expansion of macroalgae cultivation should be carried out. The mean carbon sequestration rate of seven kinds of macroalgae was 174 ± 6 g m-2 yr-1 while some cultivated macroalgae had higher CO2 sequestration rates, e.g. 356 ± 24 g C m-2 yr-1 for Gracilariopsis lemaneiformis and 331 ± 17 g C m-2 yr-1 for Undaria pinnatifida. In scenario 0.5 (CCUS (Carbon Capture, Utilization and Storage) sequesters 0.5 Gt CO2 per year), using macroalgae culture cannot achieve China's carbon neutrality by 2060 but in scenarios 1.0 and 1.5 (CCUS sequesters 1.0 and 1.5 Gt CO2 per year, respectively) it is feasible to achieve carbon neutrality using some macroalgae species with high carbon sequestration rates. This study provides important insights into how to develop mariculture in the context of carbon-neutrality and climate change mitigation.
The aim of this research is to explore the effect of biomass energy consumption on CO2 emissions in 80 developed and developing countries. To achieve robustness, the system generalised method of moment was used and several control variables were incorporated into the model including real GDP, fossil fuel consumption, hydroelectricity production, urbanisation, population, foreign direct investment, financial development, institutional quality and the Kyoto protocol. Relying on the classification of the World Bank, the countries were categorised to developed and developing countries. We also used a dynamic common correlated effects estimator. The results consistently show that biomass energy as well as fossil fuel consumption generate more CO2 emissions. A closer look at the results show that a 100% increase in biomass consumption (tonnes per capita) will increase CO2 emissions (metric tons per capita) within the range of 2 to 47%. An increase of biomass energy intensity (biomass consumption in tonnes divided by real gross domestic product) of 100% will increase CO2 emissions (metric tons per capita) within the range of 4 to 47%. An increase of fossil fuel consumption (tonnes of oil equivalent per capita) by 100% will increase CO2 emissions (metric tons per capita) within the range of 35 to 55%. The results further show that real GDP urbanisation and population increase CO2 emissions. However, hydroelectricity and institutional quality decrease CO2 emissions. It is further observed that financial development, foreign direct investment and openness decrease CO2 emissions in the developed countries, but the opposite results are found for the developing nations. The results also show that the Kyoto Protocol reduces emission and that Environmental Kuznets Curve exists. Among the policy implications of the foregoing results is the necessity of substituting fossil fuels with other types of renewable energy (such as hydropower) rather than biomass energy for reduction of emission to be achieved.
We investigate the role of military expenditure on emission in USA during the period 1960-2015. To achieve the objectives of this study, two measures of military expenditure are utilised, while several timeseries models are constructed with the gross domestic product (GDP) per capita, population, energy consumption per capita, non-renewable energy consumption per capita, renewable energy consumption per capita, urbanisation, trade openness and financial development serving as additional determinants of air pollution. We also use ecological indicator as an alternative measure of pollution. Moreover, different timeseries methods are utilised including a likelihood-based approach with two structural breaks. The output of this research concluded that all the variables are cointegrated. It is found that military expenditure has mixed impact on CO2 emissions. Real GDP per capita, energy consumption per capita, non-renewable energy consumption per capita, population and urbanisation increase CO2 emissions per capita in the long-run, while renewable energy consumption, financial development and trade openness reduce it. There is also evidence for the mixed role of military expenditure, when ecological footprint is utilised as the environmental degradation index. From the output of this research, few policy recommendations are offered for the examined country.
The main objective of this study is to investigate the influence of the globalisation (Trans-Pacific Partnership (TPP) agreement in particular) on air pollution in Malaysia. To achieve this goal, the Autoregressive Distributed Lag (ARDL) model, Johansen cointegration test and fully modified ordinary least square (FMOLS) methods are utilised. CO2 emission is used as an indicator of pollution while GDP per capita and urbanisation serve as its other determinants. In addition, this study uses Malaysia's total trade with 10 TPP members as an indicator of globalisation and analyse its effect on CO2 emission in Malaysia. The outcome of this research shows that the variables are cointegrated. Additionally, GDP per capita, urbanisation and trade between Malaysia and its 10 TPP partners have a positive impact on CO2 emissions in general. Based on the outcome of this research, important policy implications are provided for the investigated country.
The objective of this study is to examine the impact of natural gas consumption, output, and urbanization on CO2 emission in China and India for the period, 1965-2013. A cointegraton test, which provides for endogenously determined structural breaks, has been applied to examine the long-run relationship and to investigate the presence of environmental Kuznets curve (EKC) in the two countries. The presence of causal relationship between the variables is also investigated. The findings show that there is a long-run relationship in the variables and natural gas, real GDP, and urbanization have long-run positive impact on emission in both countries. There is no evidence for EKC in China and India. The findings further suggest that there is a long-run feedback relationship between the variables. The policy inferences of these findings are discussed.