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
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.
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.
This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions.
The objective of the study is to establish the link between air pollution, fossil fuel energy consumption, industrialization, alternative and nuclear energy, combustible renewable and wastes, urbanization, and resulting impact on health services in Malaysia. The study employed two-stage least square regression technique on the time series data from 1975 to 2012 to possibly minimize the problem of endogeniety in the health services model. The results in general show that air pollution and environmental indicators act as a strong contributor to influence Malaysian health services. Urbanization and nuclear energy consumption both significantly increases the life expectancy in Malaysia, while fertility rate decreases along with the increasing urbanization in a country. Fossil fuel energy consumption and industrialization both have an indirect relationship with the infant mortality rate, whereas, carbon dioxide emissions have a direct relationship with the sanitation facility in a country. The results conclude that balancing the air pollution, environment, and health services needs strong policy vistas on the end of the government officials.
Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.
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.
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.
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.
In light of a slow buildup in CO2 emissions since the recovery, this paper revisits the relationship between CO2 emissions and the US economy using a nonlinear autoregressive distributed lag model, in which the determinants are identified through an expanded real business cycle model. We find convincing evidence that CO2 emissions decline more rapidly during recessions than increase during expansions over the long run. Of all determinants considered, long-run asymmetry is fostered once vehicle miles traveled is controlled. This calls for a greater attention to public transportation development and vehicle miles traveled tax for slowing down stock buildup of CO2 emissions during good times.
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.
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.
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.
The medium-chain-length polyhydroxyalkanoate (PHA(MCL)) produced by Pseudomonas putida PGA1 using saponified palm kernel oil as the carbon source could degrade readily in water taken from Kayu Ara River in Selangor, Malaysia. A weight loss of 71.3% of the PHA film occurred in 86 d. The pH of the river water medium fell from 7.5 (at d 0) to 4.7 (at d 86), and there was a net release of CO2. In sterilized river water, the PHA film also lost weight and the pH of the water fell, but to lesser extents. The C8 monomer of the PHA was completely removed after 6 d of immersion in the river water, while the proportions of the other monomers (C10, C12, and C14) were reversed from that of the undegraded PHA. By contrast, the monomer composition of the PHA immersed in sterilized river water did not change significantly from that of the undegraded PHA. Scanning electron microscopy showed physical signs of degradation on the PHA film immersed in the river water, but the film immersed in sterilized river water was relatively unblemished. The results thus indicate that the PHA(MCL) was degraded in tropical river water by biologic as well as nonbiologic means. A significant finding is that shorter-chain monomers were selectively removed throughout the entire PHA molecule, and this suggests enzymatic action.
As the world's second largest palm oil producer and exporter, Malaysia could capitalize on its oil palm biomass waste for power generation. The emission factors from this renewable energy source are far lower than that of fossil fuels. This study applies an integrated carbon accounting and mitigation (INCAM) model to calculate the amount of CO2 emissions from two biomass thermal power plants. The CO2 emissions released from biomass plants utilizing empty fruit bunch (EFB) and palm oil mill effluent (POME), as alternative fuels for powering steam and gas turbines, were determined using the INCAM model. Each section emitting CO2 in the power plant, known as the carbon accounting center (CAC), was measured for its carbon profile (CP) and carbon index (CI). The carbon performance indicator (CPI) included electricity, fuel and water consumption, solid waste and waste-water generation. The carbon emission index (CEI) and carbon emission profile (CEP), based on the total monthly carbon production, were determined across the CPI. Various innovative strategies resulted in a 20%-90% reduction of CO2 emissions. The implementation of reduction strategies significantly reduced the CO2 emission levels. Based on the model, utilization of EFB and POME in the facilities could significantly reduce the CO2 emissions and increase the potential for waste to energy initiatives.
In this era of globalization, various products and technologies are being developed by the industries. While resources and energy are utilized from processes, wastes are being excreted through water streams, air, and ground. Without realizing it, environmental pollutions increase as the country develops. Effective technology is desired to create green factories that are able to overcome these issues. Wastewater is classified as the water coming from domestic or industrial sources. Wastewater treatment includes physical, chemical, and biological treatment processes. Aerobic and anaerobic processes are utilized in biological treatment approach. However, the current biological approaches emit greenhouse gases (GHGs), methane, and carbon dioxide that contribute to global warming. Microalgae can be the alternative to treating wastewater as it is able to consume nutrients from wastewater loading and fix CO2 as it undergoes photosynthesis. The utilization of microalgae in the system will directly reduce GHG emissions with low operating cost within a short period of time. The aim of this review is to discuss the uses of native microalgae species in palm oil mill effluent (POME) and flue gas remediation. In addition, the discussion on the optimal microalgae cultivation parameter selection is included as this is significant for effective microalgae-based treatment operations.
This paper investigates the non-linear impacts of the agricultural, industrial, financial, and service sectors on environmental pollution in Malaysia during the 1980-2018 period. It employs the extended STIRPAT model and two indicators of environmental pollution (carbon dioxide emissions and ecological footprints). It uses the autoregressive distributed lag (ARDL) technique to estimate the parameters. Evidence from the study indicate that the agricultural, industrial, and service sectors have inverted U-shaped non-linear impacts on carbon dioxide emissions and ecological footprints, while the financial sector has a U-shaped non-linear relationship with carbon dioxide emissions and ecological footprint. These empirical outcomes are robust to diagnostic tests, structural breaks, and alternative estimation technique and proxies. The economic implication of this paper is that, at the early stage of sectoral growth, the pollution intensity of sectoral output increases, but after a certain turning point, a further increase in sectoral output will reduce environmental pollution. Precisely, environmental pollution will reduce if the agricultural, industrial, and service sectors exceed threshold levels of 11%, 44%, and 49% of GDP, respectively, while environmental pollution will be aggravated if financial sector exceeds a threshold level of 94%. Therefore, efforts to mitigate environmental pollution in Malaysia should integrate sectoral growth to attain sustainable development.
The aim of this study was to optimize the antioxidant activity of Piper nigrum L. essential oil extracted using the supercritical carbon dioxide (SC-CO₂) technique. Response surface methodology was applied using a three-factor central composite design to evaluate the effects of three independent extraction variables: pressure of 15-30 MPa, temperature of 40-50 °C and dynamic extraction time of 40-80 min. The DPPH radical scavenging method was used to evaluate the antioxidant activity of the extracts. The results showed that the best antioxidant activity was achieved at 30 MPa, 40 °C and 40 min. The extracts were analyzed by GC-FID and GC-MS. The main components extracted using SC-CO₂ extraction in optimum conditions were β-caryophyllene (25.38 ± 0.62%), limonene (15.64 ± 0.15%), sabinene (13.63 ± 0.21%), 3-carene (9.34 ± 0.04%), β-pinene (7.27 ± 0.05%), and α-pinene (4.25 ± 0.06%). The essential oil obtained through this technique was compared with the essential oil obtained using hydro-distillation. For the essential oil obtained by hydro-distillation, the most abundant compounds were β-caryophyllene (18.64 ± 0.84%), limonene (14.95 ± 0.13%), sabinene (13.19 ± 0.17%), 3-carene (8.56 ± 0.11%), β-pinene (9.71 ± 0.12%), and α-pinene (7.96 ± 0.14%). Radical scavenging activity of the extracts obtained by SC-CO₂ and hydro-distillation showed an EC₅₀ of 103.28 and 316.27 µg mL(-1) respectively.
Tropical peatlands are globally important ecosystems with high C storage and are endangered by anthropogenic disturbances. Microbes in peatlands play an important role in sustaining the functions of peatlands as a C sink, yet their characteristics in these habitats are poorly understood. This research aimed to elucidate the responses of these complex ecosystems to disturbance by exploring greenhouse gas (GHG) emissions, nutrient contents, soil microbial communities and the functional interactions between these components in a primary and secondary peat swamp forest in Peninsular Malaysia. GHG measurements using closed chambers, and peat sampling were carried out in both wet and dry seasons. Microbial community phenotypes and nutrient content were determined using phospholipid fatty acid (PLFA) and inductively-coupled plasma mass spectrometry (ICP-MS) analyses respectively. CO2 emissions in the secondary peat swamp forest were > 50% higher than in the primary forest. CH4 emission rates were ca. 2 mg m-2 h-1 in the primary forest but the secondary forest was a CH4 sink, showing no seasonal variations in GHG emissions. Almost all the nutrient concentrations were significantly lower in the secondary forest, postulated to be due to nutrient leaching via drainage and higher rates of decomposition. Cu and Mo concentrations were negatively correlated with CO2 and CH4 emissions respectively. Microbial community structure was overwhelmingly dominated by bacteria in both forest types, however it was highly sensitive to land-use change and season. Gram-positive and Gram-negative relative abundance were positively correlated with CO2 and CH4 emissions respectively. Drainage related disturbances increased CO2 emissions, by reducing the nutrient content including some with known antimicrobial properties (Cu & Na) and by favouring Gram-positive bacteria over Gram-negative bacteria. These results suggest that the biogeochemistry of secondary peat swamp forest is fundamentally different from that of primary peat swamp forest, and these differences have significant functional impacts on their respective environments.
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.