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.
The well-established emissions-growth debate relies on the symmetric nexus between CO2 emissions and economic growth, thereby ignoring a fundamental component of macro economy in the form of asymmetric relation. This paper considers how CO2 emissions respond asymmetrically to changes in economic growth. While utilizing both linear and nonlinear time series approaches for an environmentally exposed country, Pakistan over the period 1971-2018, we find convincing evidence that CO2 emissions rise more rapidly during negative shocks to economic growth than increase during economic expansions. Thus, contrary to what has previously been reported, the effect is strong as holds both at short run and long run. This is partly due to the increase in informal sector as GDP declines. Our estimated results show that accounting for the shadow economy results a higher magnitude of CO2 emissions due to decrease in economic growth, thus question the traditional symmetric decoupling of economic growth and CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and dynamic OLS (DOLS). Thus, the findings of this study call for a re-thinking on climate policy design that rarely pays attention to the aforementioned outcomes due to fall in economic growth.
This study empirically investigates the effect of meat consumption on greenhouse gas emissions (carbon dioxide, methane, and nitrous oxide) in the USA. The impact of meat consumption on greenhouse gas emissions is examined by controlling for economic growth and energy consumption. The empirical analysis finds that all these variables are cointegrated for the long run. Moreover, meat consumption aggravates greenhouse gas emissions. Specifically, meat consumption (except for beef) has a U-shaped relationship with carbon emissions and an inverted U-shaped relationship with methane and nitrous oxide emissions. The causality analysis indicates a unidirectional causality running from meat consumption to greenhouse gas emissions. These empirical findings indicate that the US livestock sector has the potential to become more environmentally friendly with careful policy formulation and implementation.
Being closely correlated with income and economic growth, trade openness impacts the environmental quality through different means. The study analyzes the robustness of the environmental Kuznets curve (EKC) hypothesis in OIC countries by examining the extent to which trade openness influence environmental quality through different environmental indicators for the period 1991 to 2018. A new methodology dynamic common correlated effects (DCCE) is applied to resolve the issue of cross-sectional dependence (CSD). We have used greenhouse gas (GHG) emissions, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) along with ecological footprint as indicators of environmental quality. Results of DCCE estimation identify a negative association of trade openness with CO2, N2O, and CH4, while the positive relationship with the ecological footprint in overall OIC countries and higher income OIC countries. On the other hand, trade openness has a positive association with all environmental indicators in lower income OIC countries. Our findings confirm that inverted-U-shaped EKC exists in all groups of OIC countries when CO2, CH4, and ecological footprint are used as environmental indicators. However, a U-shaped EKC exists in overall OIC countries and lower income OIC countries when N2O is used. Eventually, it is recommended that if OIC countries continue trade openness policies and energy sector reforms and maintain sustainable use of biocapacity; then, they will be able to combat environmental issues with the increase in income.
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.
Validity of the environmental Kuznets curve (EKC) hypothesis is consistently and widely debated among economists and environmentalists alike throughout time. In Malaysia, transport is one of the "dirtiest" sectors; it intensively consumes energy in powering engines by using fossil fuels and poses significant threats to environmental quality. Therefore, this study attempted an examination into the impact of corruption on transport carbon dioxide (CO2) emissions. By adopting the fully modified ordinary least squares, canonical cointegrating regression, and dynamic ordinary least squares in performing long-run estimations, the results obtained based on the annual data spanning from 1990 to 2017 yielded various notable findings. First, more corruption would be attributable towards increased transport CO2 emissions. Second, a monotonic increment of transport CO2 emission was seen with higher economic growth and thus invalidated the presence of EKC. Overall, this study suggests that Malaysia has yet to reach the level of economic growth synonymous with transport CO2 emission reduction due to the lack of high technology usage in the current system implemented. Therefore, this study could position policy recommendations of use to the Malaysian authorities in designing the appropriate economic and environmental policies, particularly for the transport sector.
Carbon dioxide (CO2) emission will increase due to the increasing global plastic demand. Statistical data shows that plastic production alone will contribute to at least 20% of the annual global carbon budget in the near future. Hence, several alternative methods are recommended to overcome this problem, such as bio-product synthesis. Algae consist of diverse species and have huge potential to be a promising biomass feedstock for a range of purposes, including bio-oil production. The convenient cultivation method of algae could be one of the main support for algal biomass utilization. The aim of this study is to forecast and outline the strategies in order to meet the future demand (year 2050) of plastic production and, at the same time, reduce CO2 emission by replacing the conventional plastic with bio-based plastic. In this paper, the analysis for 25%, 50% and 75% CO2 reduction has been done by using carbon emission pinch analysis. The strategies of biomass utilization in Malaysia are also enumerated in this study. This study suggested that the algal biomass found in Malaysia coastal areas should be utilized and cultivated on a larger scale in order to meet the increasing plastic demand and, at the same time, reduce carbon footprint. Some of the potential areas for macroalgae sea-farming cultivation in Sabah coastline (Malaysia), comprised of about 3885 km2 (388,500 ha) in total, have been highlighted. These potential areas have the potential to produce up to 14.5 million tonnes (Mt)/y of macroalgae in total, which can contribute 370 Mt of phenol for bioplastic production.
This paper presents a fresh understanding of the vigorous connection between inward FDI, renewable energy consumption, economic growth and carbon emission in the Chinese economy employing novel Morlet wavelet analysis. Wavelet correlation, continuous wavelet transform and partial and the multiple wavelet coherence analyses are applied on variables under study for data acquired during the period 1979 to 2017. The outcome of these analyses reveals that the connections among the variables progress over frequency and time. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages, although time domain reveals inconsistent associations among the considered variables. The wavelet analysis according to economic point of view supports that inward foreign direct investment (FDI) and renewable energy consumption help to enhance economic condition in Chinese economy. The results also suggested that inward FDI enhances the environmental degradation in medium and long run in China. The results emphasize the significance of having organized strategies by the policymakers to cope with huge environmental degradation occurred for a couple of decades in China.
Greenhouse gases (GHGs) carbon dioxide (CO2) and nitrous oxide (N2O), contribute significantly to global warming, and they have increased substantially over the years. Reforestation is considered as an important forestry application for carbon sequestration and GHGs emission reduction, however, it remains unknown whether reforestation may instead produce too much CO2 and N2O contibuting to GHGs pollution. This study was performed to characterize and examine the CO2 and N2O emissions and their controlling factors in different species and types of pure and mixture forest used for reforestation. Five soil layers from pure forest Platycladus orientalis (PO), Robinia pseudoacacia (RP), and their mixed forest P-R in the Taihang mountains of central China were sampled and incubated aerobically for 11 days. The P-R soil showed lower CO2 and N2O production potentials than those of the PO soils (P
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.
Tropical peatlands are vital ecosystems that play an important role in global carbon storage and cycles. Current estimates of greenhouse gases from these peatlands are uncertain as emissions vary with environmental conditions. This study provides the first comprehensive analysis of managed and natural tropical peatland GHG fluxes: heterotrophic (i.e. soil respiration without roots), total CO2 respiration rates, CH4 and N2 O fluxes. The study documents studies that measure GHG fluxes from the soil (n = 372) from various land uses, groundwater levels and environmental conditions. We found that total soil respiration was larger in managed peat ecosystems (median = 52.3 Mg CO2 ha-1 year-1 ) than in natural forest (median = 35.9 Mg CO2 ha-1 year-1 ). Groundwater level had a stronger effect on soil CO2 emission than land use. Every 100 mm drop of groundwater level caused an increase of 5.1 and 3.7 Mg CO2 ha-1 year-1 for plantation and cropping land use, respectively. Where groundwater is deep (≥0.5 m), heterotrophic respiration constituted 84% of the total emissions. N2 O emissions were significantly larger at deeper groundwater levels, where every drop in 100 mm of groundwater level resulted in an exponential emission increase (exp(0.7) kg N ha-1 year-1 ). Deeper groundwater levels induced high N2 O emissions, which constitute about 15% of total GHG emissions. CH4 emissions were large where groundwater is shallow; however, they were substantially smaller than other GHG emissions. When compared to temperate and boreal peatland soils, tropical peatlands had, on average, double the CO2 emissions. Surprisingly, the CO2 emission rates in tropical peatlands were in the same magnitude as tropical mineral soils. This comprehensive analysis provides a great understanding of the GHG dynamics within tropical peat soils that can be used as a guide for policymakers to create suitable programmes to manage the sustainability of peatlands effectively.
This study examines the association between transportation services (i.e., passenger and freight) and carbon emissions concerning the US economy. The monthly data for this study were collected for the period from 2000 M1 to 2019 M8. In this study, QARDL econometric approach as discussed by Cho et al. (2015) has been used to tests the relationship between transportation services and CO2 emissions. Due to the chaotic and nonlinear behavior of our concerning variables, it was quite difficult to gauge the principle properties of their variations. Therefore, we relied on QARDL, which has been missing in previous researches. By utilizing the QARDL method, this research assesses the long-term stability of the nexus across the quantiles to provide an econometric framework that is more flexible than the traditional ones. In particular, the authors have analyzed how the quantiles of transportation (i.e., passenger and freight) influence the quantiles of CO2 emissions (environmental degradation). The empirical evidence revealed the negative significant relationship of both the transportation system (i.e., passenger and freight) with carbon emissions; however, this relationship holds at low quantiles of freight transport, whereas the same relationship has been observed at the majority of quantiles of passenger transport. So, this depicts that the transportation system of the USA helps to reduce CO2 emissions. Therefore, to maintain this situation, the government shall introduce more technologies that are fuel-efficient and promote clean consumption, thus reducing CO2 emissions, boosting economic growth, and making green transportation services.
This novel research is an argumentative subject which was needed to be addressed and to fill this gap, the author examined the effect of financial development, information and communication technology, and institutional quality on CO2 emission in Pakistan by using quantile autoregressive distributed lag (QARDL) model. The data were obtained for the period from 1995Q1 to 2018Q4. In the long run, GDP and institutional quality have a positive impact on CO2 emission when this emission is already high, which shows that if the GDP and institutional quality increases, the CO2 emission also increases. Moreover, financial development and ICT has a negative impact on CO2 emission irrespective of emission level that whether it is high or low in the country, which shows that if financial enhancement and ICT increases, carbon emission decreases. The study also supported the EKC hypothesis in Pakistan.
This paper uses the quantile autoregressive distributed lag (QARDL) model to analyze the impact of economic growth, tourism, transportation, and globalization on carbon dioxide (CO2) emissions in the Malaysian economy. The QARDL model is employed utilizing quarterly data from 1995Q1 to 2018Q4. The results demonstrate that economic growth is significantly positive with CO2 emissions at lower to upper quantiles. Interestingly, tourism has a negative effect on CO2 emissions at higher quantiles. Moreover, globalization and transportation services are positive, with CO2 emissions at upper-middle to higher quantiles. Furthermore, we tested the environmental Kuznets curve, and the outcomes confirm the presence of the inverted U-shaped curve in the Malaysian economy. The results of this study suggest that ecotourism is beneficial for economic growth in underdeveloped areas; it increases employment opportunities and, thus, achieves a win-win situation for protection and development. The government should encourage the low-carbon development of ecotourism and achieve green development of both tourism and the economy.
The main objective of this paper is to estimate the interfuel substitution elasticities between hydropower and the fossil fuels of coal and natural gas used in the generation of electricity for Malaysia. Due to the violation of the assumption behind the ordinary least squares (OLS) method on account of the correlated error terms in the system of equations, the econometrics techniques of seemingly unrelated regression (SUR) was adopted to obtain the parameter estimates using dataset that covers the period 1988 to 2016. The main finding is that there exists substantial substitution possibility between hydropower and fossil fuels in the generation of electricity for Malaysia. CO2 emissions mitigation scenarios were also conducted to explore the possible effects of substituting fossil fuels for hydropower to generate electricity. The results show that switching from high carbon-emitting fuels to renewable energy such as hydropower will substantially reduce CO2 emission and assist the country towards achieving the carbon emissions reduction targets. Policy recommendations are offered in the body of the manuscript.
The developing world is facing pivotal challenges in recent times. Among these, global warming has ominous repercussions on every segment of society, thus tracing its underlying causes is imperative. This research attempts to investigate the impact of urbanization and energy consumption on carbon dioxide emissions (CO2) for a panel of 8 Asian countries (Bangladesh, China, India, Indonesia, Malaysia, Nepal, Pakistan, and Sri Lanka) over the period 1982 to 2017. The analyses are executed using panel co-integration and Granger causality techniques. The main findings of panel co-integration reveal a long-run relationship between urbanization, energy consumption, and CO2 emissions. Furthermore, the results indicate a positive and significant impact of urbanization and energy consumption on CO2 emissions, indicating that urban development and high energy consumptions are barriers to improve environmental quality in the long run. The results also highlight bi-directional causality between energy consumption and urbanization, while unidirectional causality exists between energy consumption and CO2 emissions. Based on the obtained results, this study offers useful policy implications for plummeting carbon emissions.
Pollution haven hypothesis (PHH) has been investigated extensively in the existing literature due to global environmental issues such as global warming and climate change. However, there is still no consensus on whether this hypothesis is valid. Therefore, the aim of this study is to examine the validity of the PHH in ASEAN-5 countries (Indonesia, Malaysia, Philippines, Singapore, and Thailand) covering the period of 1981-2014. It is utilized the up-to-date panel data techniques taking cross-sectional dependence and slope heterogeneity into account to test the relationship. According to the results of CCEMG and AMG estimators, the validity of the PHH is confirmed in ASEAN-5 countries. The increase in foreign direct investments (FDI) increases environmental degradation in these countries. Our additional findings show that the environmental Kuznets curve (EKC) hypothesis (EKC) is also valid in these countries. There is an inverted U shape between economic growth and CO2 emissions. In addition, energy consumption exacerbates CO2 emissions.
In this paper, we revisit the environmental Kuznets curve (EKC) hypothesis by using estimations that account for cross-sectional dependency (CSD) and asymmetry effect in 76 countries for the period 1971-2014. Our results lend moderate support to the EKC hypothesis. The country-specific results unfold that a total of 16 out of 76 countries support the EKC hypothesis using CCEMG estimator. Results from AMG reveal that the EKC hypothesis holds in 24 out of 76 countries. It is worth highlighting that 11 countries (Australia, China, Congo Dem. Rep., Costa Rica, Gabon, Hong Kong, India, Korea, Myanmar, Turkey, and Uruguay) exhibit an inverted U-shaped curve regardless of whether CCEMG or AMG is used. The asymmetry analysis using PMG is also able to support the EKC hypothesis. We conclude that the EKC hypothesis does not fit all countries. Policy implication and recommendation in designing appropriate energy and economic policies are provided.
This paper assesses the Environmental Kuznets curve based on quantile behavior of the relationship between economic growth, forest area, agriculture production, renewable energy, and environmental degradation. The current literature generally used a single indicator to address environmental issues; however single indicator neither measures overall environmental conditions nor does specify that the environment issue is generally diminishing. Our study is the first one that used ecological footprint (EF) as an indicator to test environmental Kuznets curve (EKC) hypothesis for Pakistan by employing recent approach of quantile autoregressive distributed lag (QARDL) initiated by Cho et al. (J Econ 188(1):281-300, 2015). The result of this study validates the EKC hypothesis for Pakistan and shows quantile-dependent relationship, and in that case, using the conventional methods may somewhat lead to biased results. Moreover, the rejection of the null hypothesis of parameter constancy is also confirmed by Wald test. In the long run, the findings of renewable energy consumption and forest area show significant negative effects on ecological footprints, which indicates that by increasing renewable energy usage and forest area, ecological footprints can be minimized. Interestingly, the short-term effects of agricultural production findings on EF show statistically negative results. This illustrates that EF can also be reduced in the agriculture sector by adopting environment-friendly technologies. In order to create efficient policies for environment deterioration, the empirical findings of the current analysis can be used as a guideline for policy implications.
Conversion of tropical peat swamp forest to drainage-based agriculture alters greenhouse gas (GHG) production, but the magnitude of these changes remains highly uncertain. Current emissions factors for oil palm grown on drained peat do not account for temporal variation over the plantation cycle and only consider CO2 emissions. Here, we present direct measurements of GHGs emitted during the conversion from peat swamp forest to oil palm plantation, accounting for CH4 and N2O as well as CO2. Our results demonstrate that emissions factors for converted peat swamp forest is in the range 70-117 t CO2 eq ha-1 yr-1 (95% confidence interval, CI), with CO2 and N2O responsible for ca. 60 and ca. 40% of this value, respectively. These GHG emissions suggest that conversion of Southeast Asian peat swamp forest is contributing between 16.6 and 27.9% (95% CI) of combined total national GHG emissions from Malaysia and Indonesia or 0.44 and 0.74% (95% CI) of annual global emissions.