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 evaluated the total carbon stock of mangrove ecosystems in two contrasting sites: a fishing village in Delta Kelantan (DK) and Ramsar sites in Johor Park (JP). In both sites, aboveground carbon was significantly higher than belowground carbon, and stems contained more carbon than leaf and root partitions. The average carbon concentration of individual mangrove species (44.9-48.1%) was not significantly different but the larger biomass of the DK samples resulted in vegetation carbon stock that was higher than that in JP. Season played an important role in soil carbon stock-a pronounced wet season in DK coincided with the dry season in JP. The total carbon pool was estimated to be 427.88 t ha-1 in JP and 512.51 t ha-1 in DK, where at least 80% was contributed by soil carbon. The carbon dioxide equivalent was 1570.32 t ha-1 CO2e (JP) and 1880.91 t ha-1 CO2e (DK).
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.
This study aims to determine an interactive environmental model for economic growth that would be supported by the "sustainability principles" across the globe. The study examines the relationship between environmental pollutants (i.e., carbon dioxide emission, sulfur dioxide emission, mono-nitrogen oxide, and nitrous oxide emission); population growth; energy use; trade openness; per capita food production; and it's resulting impact on the real per capita GDP and sectoral growth (i.e., share of agriculture, industry, and services in GDP) in a panel of 34 high-income OECD, high-income non-OECD, and Europe and Central Asian countries, for the period of 1995-2014. The results of the panel fixed effect regression show that per capita GDP are influenced by sulfur dioxide emission, population growth, and per capita food production variability, while energy and trade openness significantly increases per capita income of the region. The results of the panel Seemingly Unrelated Regression (SUR) show that carbon dioxide emission significantly decreases the share of agriculture and industry in GDP, while it further supports the share of services sector to GDP. Both the sulfur dioxide and mono-nitrogen oxide emission decreases the share of services in GDP; nitrous oxide decreases the share of industry in GDP; while mono-nitrogen oxide supports the industrial activities. The following key growth-specific results has been obtained from the panel SUR estimation, i.e., (i) Both the food production per capita and trade openness significantly associated with the increasing share of agriculture, (ii) food production and energy use significantly increases the service sectors' productivity; (iii) food production decreases the industrial activities; (iv) trade openness decreases the share of services to GDP while it supports the industrial share to GDP; and finally, (v) energy demand decreases along with the increase agricultural share in the region. The results emphasize the need for an interactive environmental model that facilitates the process of sustainable development across the globe.
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.
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.
The CO2 capture capacity and cyclic stability of calcium oxide (CaO) prepared from cockle shells (CS) were enhanced by incorporating rice husk (RH) and binder through wet-mixing method. The cyclic reaction of calcination and carbonation was demonstrated using thermal gravimetric analyzer (TGA) which the calcination was performed in a pure N2 environment at 850 °C for 20 min and carbonation at 650 °C for 30 min in 20 vol% of CO2 in N2. The analysis using x-ray fluorescence (XRF) identified silica (Si) as the major elements in the sorbents. The RH-added sorbents also contained several types of metal elements such as which was a key factor to minimize the sintering of the sorbent during the cyclic reaction and contributed to higher CO2 capture capacity. The presence of various morphologies also associated with the improvement of the synthesized sorbents performance. The highest initial CO2 capture capacity was exhibited by CS+10%RH sorbent, which was 12% higher than the RH-free sorbent (CS). However, sorbents with the higher RH loading amount such as 40 and 50 wt% were preferred to maintain high capture capacity when the sorbents were regenerated and extended to the cyclic reaction. The sorbents also demonstrated the lowest average sorption decay, which suggested the most stable sorbent for cyclic-reaction. Once regenerated, the capture capacity of the RH-added sorbent was further increased by 12% when clay was added into the sorbent. Overall, the metal elements in RH and clay were possibly the key factor that enhances the performance of CaO prepared from CS, particularly for cyclic CO2 capture. Graphical abstract Cyclic calcination and carbonation reaction.
China is the world's largest fossil fuel consumer and carbon emitter country. In September 2020, China pledged to reduce carbon emissions, and achieve carbon neutrality by 2060. Therefore, this study aimed to contribute to the literature and show the pictorial nexus of bioenergy and fossil fuel consumption, carbon emission, and agricultural bioeconomic growth, a new pathway towards carbon neutrality. For this study, time-series data from 1971 to 2019 were used to analyze the autoregressive distributed lag (ARDL) bound testing and novel dynamic autoregressive distributed lag (DYNARDL) simulation models. Initially, the unit root tests results showed that all variables were stationarity at the level and first difference. The presence of cointegration between selected variables was confirmed by the results from ARDL bound test. In addition, the results of long-run and short-run nexus show an increase in bioenergy consumption that caused an increase in agricultural bioeconomic growth both in the long and short-run nexus. A decrease in fossil fuel consumption was shown to result in increased agricultural bioeconomic growth with respect to both long- and short-term effects. Furthermore, the results of the novel dynamic ARDL simulation model demonstrated that a 10% positive shock from bioenergy consumption caused an increase in agricultural bioeconomic growth, while at the same time, a 10% negative shock in bioenergy consumption led to a decrease. A 10% negative shock from fossil fuels caused an increase in agricultural bioeconomic growth, whereas a 10% positive shock from fossil fuels led to a decrease. Therefore, this study suggests that China needs to switch from fossil fuel and other non-renewable energy consumption to sources of bioenergy and other renewable energy consumption to achieve carbon neutrality by 2060.
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.
Environmental degradation is significantly studied both in the past and the current literature; however, steps towards reducing the environmental pollution in carbon emission and haze pollution like PM2.5 are not under rational attention. This study tries to cover this gap while considering the carbon emission and PM2.5 through observing the role of renewable energy, non-renewable energy, environmental taxes, and ecological innovation for the top Asian economies from 1990 to 2017. For analysis purposes, this research considers cross-sectional dependence analysis, unit root test with and without structural break (Pesaran, 2007), slope heterogeneity analysis, Westerlund and Edgerton (2008) panel cointegration analysis, Banerjee and Carrion-i-Silvestre (2017) cointegration analysis, long-short run CS-ARDL results, as well as AMG and CCEMG for robustness check. The empirical evidence in both the short- and long-run has confirmed the negative and significant effect of renewable energy sources, ecological innovation, and environmental taxes on carbon emissions and PM2.5. Whereas, non-renewable energy sources are causing environmental degradation in the targeted economies. Finally, various policy implications related to carbon emission and haze pollution like PM2.5 are also provided to control their harmful effect on the natural environment.
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.
This article aims to investigate the relationship among renewable energy consumption, carbon dioxide (CO2) emissions, and GDP using panel data for 24 Asian countries between 1990 and 2012. Panel cross-sectional dependence tests and unit root test, which considers cross-sectional dependence across countries, are used to ensure that the empirical results are correct. Using the panel cointegration model, the vector error correction model, and the Granger causality test, this paper finds that a long-run equilibrium exists among renewable energy consumption, carbon emission, and GDP. CO2 emissions have a positive effect on renewable energy consumption in the Philippines, Pakistan, China, Iraq, Yemen, and Saudi Arabia. A 1% increase in GDP will increase renewable energy by 0.64%. Renewable energy is significantly determined by GDP in India, Sri Lanka, the Philippines, Thailand, Turkey, Malaysia, Jordan, United Arab Emirates, Saudi Arabia, and Mongolia. A unidirectional causality runs from GDP to CO2 emissions, and two bidirectional causal relationships were found between CO2 emissions and renewable energy consumption and between renewable energy consumption and GDP. The findings can assist governments in curbing pollution from air pollutants, execute energy conservation policy, and reduce unnecessary wastage of energy.
BACKGROUND: Assessment of asthma outside of the hospital using a patient independent device is highly in demand due to the limitation of existing devices, which are manual and unreliable if patients are not cooperative.
OBJECTIVE: The study aims to verify the use of newly developed human respiration, carbon dioxide (CO2) measurement device for the management of asthma outside of the hospital.
METHOD: The data were collected from 60 subjects aged between 18-35 years via convenience sampling method reported in UTM Health Center using the device. Furthermore, the data were normalized and analyzed using descriptive statistics, t-test, and area (Az) under receiver operating characteristic curve (ROC).
RESULT: Findings revealed that the normalized mean values of end-tidal carbon dioxide (EtCO2), Hjorth Activity (HA), and respiratory rate (RR) were lower in asthmatic compared with healthy subjects with minimum deviation from the mean. In addition, each parameter was found to significantly differ statistically for asthma and non-asthma with p< 0.05. Furthermore, the Az shows the strong association for the screening of asthma and non-asthma with an average of 0.71 (95% CI: 0.57-0.83), 0.77 (95% CI: 0.64-0.90), and 0.83 (95% CI: 0.73-0.94) for RR, EtCO2, and HA, respectively.
CONCLUSIONS: This study demonstrates that the newly developed handheld human respiration CO2 measurement device may possibly be used as an effort-independent asthma management method outside of the hospital.
The development of a human respiration carbon dioxide (CO2) measurement device to evaluate cardiorespiratory status inside and outside a hospital setting has proven to be a challenging area of research over the few last decades. Hence, we report a real-time, user operable CO2 measurement device using an infrared CO2 sensor (Arduino Mega2560) and a thin film transistor (TFT, 3.5″), incorporated with low pass (cut-off frequency, 10 Hz) and moving average (span, 8) filters. The proposed device measures features such as partial end-tidal carbon dioxide (EtCO2), respiratory rate (RR), inspired carbon dioxide (ICO2), and a newly proposed feature-Hjorth activity-that annotates data with the date and time from a real-time clock, and is stored onto a secure digital (SD) card. Further, it was tested on 22 healthy subjects and the performance (reliability, validity and relationship) of each feature was established using (1) an intraclass correlation coefficient (ICC), (2) standard error measurement (SEM), (3) smallest detectable difference (SDD), (4) Bland-Altman plot, and (5) Pearson's correlation (r). The SEM, SDD, and ICC values for inter- and intra-rater reliability were less than 5% and more than 0.8, respectively. Further, the Bland-Altman plot demonstrates that mean differences ± standard deviations for a set limit were 0.30 ± 0.77 mmHg, -0.34 ± 1.41 mmHg and 0.21 ± 0.64 breath per minute (bpm) for CO2, EtCO2 and RR. The findings revealed that the developed device is highly reliable, providing valid measurements for CO2, EtCO2, ICO2 and RR, and can be used in clinical settings for cardiorespiratory assessment. This research also demonstrates that EtCO2 and RR (r, -0.696) are negatively correlated while EtCO2 and activity (r, 0.846) are positively correlated. Thus, simultaneous measurement of these features may possibly assist physicians in understanding the subject's cardiopulmonary status. In future, the proposed device will be tested with asthmatic patients for use as an early screening tool outside a hospital setting.
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.
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.
The purpose of this paper is to investigate the links between renewable energy (RE), non-renewable energy (NRE), capital, labour and economic growth, using the nonlinear autoregressive distributive lag (NARDL) model in Malaysia for the period of 1980-2018. The results of NARDL confirm the asymmetric effect of RE and NRE consumption on the economic growth in the long run as well as the short run in Malaysia. The findings also show that in the long and short run, positive shocks of NRE are greater than the positive shocks of RE. It indicates that Malaysia's economic growth is highly dependent on NRE which is not a good indication as NRE consumption increases carbon dioxide (CO2) emission in the country. Moreover, the empirical results of this study demonstrated that RE consumption reduction accelerates economic growth, whereas NRE consumption reduction decreases economic growth. It can have claimed that in Malaysia, RE is still more expensive than NRE. In conclusion, this study offered a variety of measures to develop RE to reduce the dependency on NRE consumption.
Sustainable development inculcates the process of preserving the environment for future generations while maintaining existing human needs. This study attempts to empirically investigate the relationship between CO2 emissions, GDP, energy consumption, and imports and exports using yearly data between 1980 and 2014 for the panel of eight developing countries (i.e., Bangladesh, Egypt, Iran, Indonesia, Malaysia, Nigeria, Pakistan, and Turkey). All the tests for cointegration establish the long-run association among the variables and confirm the environmental Kuznets curve (EKC) hypothesis for the panel of eight countries. GDP and energy consumption remained significant factors for emission intensity both in the long and short run. However, exports found to be positive factor for emissions in the long run only and imports spur emissions in the short run. The country-specific results validate EKC hypothesis for Bangladesh, Iran, Nigeria, Pakistan, and Turkey. The findings are policy oriented and suggest that the countries' economic growth along with energy consumption and exports are highly emission intensive which require necessary adjustments at sustainable development policy front.
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.