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.
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
This study is a scholarly effort to broaden the existing literature on the impact of transportation services, urbanization, and financial development on ecological footprints in Pakistan. Data used in this study covers the period of 39 years from 1980 to 2018. This study adopted the QARDL model to tackle the non-linear association of variables and test their long-run stability across the different quantiles. The findings of this study indicated a significant negative association of transportation services and financial development with ecological footprints in Pakistan at almost all quantiles whereas, the urban population was found to be positively associated with the ecological footprint in Pakistan. Results also justify the existence of the EKC hypothesis in the scenario of Pakistan. Policymakers are advised to frame strategies for investors to invest more in eco-friendly projects to curtail the ecological footprints in Pakistan. Minimizing the dependency of the transportation sector on fossil fuel, and increased use of energy-efficient appliances in the urban population would be beneficial to control the negative influence on ecological footprints in Pakistan.
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.
The objective of this paper is to examine the dynamic impact of urbanization, economic growth, energy consumption, and trade openness on CO 2 emissions in Nigeria based on autoregressive distributed lags (ARDL) approach for the period of 1971-2011. The result shows that variables were cointegrated as null hypothesis was rejected at 1 % level of significance. The coefficients of long-run result reveal that urbanization does not have any significant impact on CO 2 emissions in Nigeria, economic growth, and energy consumption has a positive and significant impact on CO 2 emissions. However, trade openness has negative and significant impact on CO 2 emissions. Consumption of energy is among the main determinant of CO 2 emissions which is directly linked to the level of income. Despite the high level of urbanization in the country, consumption of energy still remains low due to lower income of the majority populace and this might be among the reasons why urbanization does not influence emissions of CO 2 in the country. Initiating more open economy policies will be welcoming in the Nigerian economy as the openness leads to the reduction of pollutants from the environment particularly CO 2 emissions which is the major gases that deteriorate physical environment.
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.
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.
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.
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 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.
The disastrous consequences of climate change for human life and environmental sustainability have drawn worldwide attention. Increased global warming is attributed to anthropogenic greenhouse gas (GHG) emissions, biodiversity loss, and deforestation due to industrial output and huge consumption of fossil fuels. Financial inclusion can be acted as an adaptation or a mitigation measure for environmental degradation. This study analyzed the impact of financial inclusion on environmental degradation in OIC countries for the period 2004-2018. A novel approach, "Dynamic Common Correlated Effects (DCCE)" is used to tackle the problem of heterogeneity and cross-sectional dependence (CSD). Various GHG emissions along with deforestation and ecological footprint are used as indicators of environmental degradation. Long-run estimation confirms that financial inclusion is positively and significantly linked with CO2 emission, CH4 emission, and deforestation while negatively correlated with ecological footprint and N2O emission in overall and higher-income OIC economies. An inverted U-shaped environmental Kuznets curve (EKC) is validated when ecological footprint, CO2, and CH4 are used in all panels of OIC countries. An inverted U-shaped EKC is also observed for deforestation in lower-income and overall OIC countries. In the case of N2O emission, however, a U-shaped EKC appears in lower-income and overall OIC countries. It is suggested that the governments of OIC countries should continue to have easy access to financial services and maintain sustainable use of forests and biocapacity management to address environmental challenges.
To boost the stability of economic and financial aspects along with the apprehensions for sustainability, it is important to promote the development of clean energy stocks around the globe. In the current research, the researchers have examined the impact of oil prices, coal prices, natural gas prices, and gold prices on clean energy stock using the autoregressive distribution lag (ARDL) approach from the year 2011 to the year 2020. The result of daily data analysis specifies that in the long as well as in the short run, gold prices, oil prices, and coal prices have a positive and significant effect on clean energy stock. On the other side, natural gas prices in the long as well as in the short run have a negative and significant effect on clean energy stock. So, the empirical analysis of our study is of interest to investors at an institutional level who aim at detecting the risk associated with the clean energy market through proper financial modeling. Besides, this study opens up a new domain to sustain financial as well as economic prospects by protecting the environment through clean energy stock as the investment in clean energy stocks results in producing a substantial effect on the economy and the environment as well.
There are many advantages of geothermal energy as an environmentally friendly resource; however, there are quite a several challenges that need to be overcome to completely harness sustainable and renewable energy that is also natural. The primary aim of this study is to examine what influence geothermal energy will have on land use changes among the considered 27 states in the European Union from the time being 1990 to 2021. The study adopts the auto-regressive distributed lag (ARDL); the findings show that geothermal energy growth could be leveraged to achieve remarkable growth in land use change among the 13 European developing economies than among the 14 EU developed economies. On the other hand, results from analysis further show that a remarkable decrease in land use change could be better attained among the 14 EU developed economies that among the 13 EU developing economies as a result of institutional quality. Furthermore, the result suggests that through economic growth, there could be a remarkable increase in land use change among the 14 EU developed economies than among the 13 EU developing economies. It was further revealed by the study that the level of land use change among the 27 EU nations could be remarkably increased, boosting the level of geothermal energy production that will assist in attaining the aims behind the 2030 energy union. This will eventually help in curbing the incidence of climate change and pollution in the environment; the projected calculations are observed to be valid, as confirmed through the chosen three estimators for this research. The chosen estimators are the pooled mean group, mean group, and dynamic fixed effect. The regulations and governors in 27 European Union countries should give priority to using geothermal in their renewable energy mix to reduce the incidence of changes in land structures. Also, an increased level of efficiency and effectiveness should be made to the generation of geothermal energy by state actors and investors to prompt sustainability and attainability with no further depreciation in agricultural and forest natural states.
This study examines the impact of energy consumption, urbanization, and globalization on environmental degradation proxied by carbon emissions (CO2) in the South Asian Association for Regional Cooperation (SAARC) countries, namely Sri Lanka, Pakistan, Maldives, Nepal, Bhutan, Bangladesh, and India using data over the period 1990-2018. The cross-sectional autoregressive distributed lag (CS-ARDL), pooled mean group (PMG), and Dumitrescu and Hurlin (D-H) Granger causality techniques are employed for the empirical analysis. First and second-generation panel unit root tests are used to determine the stationary level of all data series which reveals mixed order of integration. The empirical findings show that urbanization, gross domestic product (GDP) per capita income, energy consumption, industrial growth, globalization, and financial development cause CO2 emissions, while the other variables, namely arable land and innovation, put negative effects on CO2 emissions. Moreover, the D-H heterogeneous test results exhibit that bi-directional relationship exists between CO2 and arable land, urbanization, industrial growth, and financial development, while a unidirectional causality exists between CO2 emissions and GDP per head income. These findings suggest that planned urbanization, investment in renewable energy sources, and effective strategies regarding the economic and financial integration with the global economies are required for a clean and green environment.
Prior studies on environmental standards have highlighted the significance of urbanization and transportation in affecting environmental sustainability worldwide. As the empirical and theoretical debates are still unresolved and divisive, the argument of whether urbanization, transportation and economic growth in Association of Southeast Asian Nations (ASEAN) countries cause greenhouse gas (GHG) emissions remains unclear. This study aim is to examine dynamic linkage between transportation, urbanization, economic growth and GHG emissions, as well as the impact of environmental regulations on GHG emission reduction in ASEAN countries over the years 1995-2018. On methodological aspects, the study accompanies a few environmental studies that check the cross-sectional dependence and slope heterogeneity issues. Moreover, the new cross-sectionally augmented autoregressive distributed lags (CS-ARDL) methodology is also applied in the study to estimate the short-run and long-run effects of the factors on GHG emissions. Substantial evidence is provided that GHG emissions increase with transportation, urbanization and economic growth but decrease with the imposition of environmental-related taxations. Augmented mean group (AMG) and common correlated effect mean group (CCEMG) also support the findings of CS-ARDL estimates. Finally, the study calls for drastic actions in ASEAN countries to reduce GHG emissions, including environmentally friendly transportation services and environmental regulation taxes. This study also provides the guidelines to the regulators while developing policies related to control the GHG emission in the country.
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.
The current study examines sustainable electricity consumption for economic growth in a small open and tourist economy. The energy-tourism nexus is evaluated for the relationship between sustainable electricity consumption and the international tourist arrival for the South African economy. The present study leverages on annual frequency data for South Africa from 1995 to 2019 for empirical analysis using the ARDL technique. Accordingly, empirical findings indicate a significant direct connection between the sustainable electricity consumption and the international tourism arrival; the study affirms that tourism-induced energy hypothesis is valid in South Africa. However, from a policy standpoint, alternative energy efficiency mechanisms such as renewable energy systems and emancipation of current energy management capabilities are recommended in South Africa. This is necessary for sustainable eco-friendly tourism that engenders clean energy consumption for the study area. More insights into policy caveats are presented in the concluding section.
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.
Information on temporal and spatial variations in soil greenhouse gas (GHG) fluxes from tropical peat forests is essential to predict the influence of climate change and estimate the effects of land use on global warming and the carbon (C) cycle. To obtain such basic information, soil carbon dioxide (CO2) and methane (CH4) fluxes, together with soil physicochemical properties and environmental variables, were measured at three major forest types in the Maludam National Park, Sarawak, Malaysia, for eight years, and their relationships were analyzed. Annual soil CO2 fluxes ranged from 860 to 1450 g C m⁻2 yr⁻1 without overall significant differences between the three forest sites, while soil CH4 fluxes, 1.2-10.8 g C m⁻2 yr⁻1, differed. Differences in GHG fluxes between dry and rainy seasons were not necessarily significant, corresponding to the extent of seasonal variation in groundwater level (GWL). The lack of significant differences in soil CO2 fluxes between the three sites could be attributed to set-off between the negative and positive effects of the decomposability of soil organic matter as estimated by pyrophosphate solubility index (PSI) and GWL. The impact of El-Niño on annual CO2 flux also varied between the sites. The variation in soil CH4 fluxes from the three sites was enhanced by variations in temperature, GWL, PSI, and soil iron (Fe) content. A positive correlation was observed between the annual CH4 flux and GWL at only one site, and the influence of soil properties was more pronounced at the site with the lowest GWL and the highest PSI. Variation in annual CH4 fluxes was controlled more strongly by temperature where GWL was the highest and GWL and plant growth fluctuations were the least. Inter-annual variations in soil CO2 and CH4 fluxes confirmed the importance of long-term monitoring of these at multiple sites supporting different forest types.