The aim of the study is to estimate the nexus between energy insecurity and energy poverty with the role of climate change and other environmental concerns. We used DEA like WP methods and properties of MCDA, a most common form of data envelopment analysis (DEA) to estimate the nexus between constructs. This paper presents a measurement and analysis of G7 countries' energy, economic, social, and environmental performance associated with energy poverty indexes. The study used the multiple, comprehensive, and relevant set of indicators, including energy economics and environmental consideration of energy poverty. The net energy consumption of al G7 economies is equal to 34 percent of the entire world along with the net estimate GDP score of around 50 percent. Using DEA modelling and estimation technique, our research presented valuable insights for readers, theorists and policy makers on energy, environment, energy poverty and climate change mitigation. For this reasons, all these indicators combined in a mathematical composite indicator to measure energy, economic, social, and environmental performance index (EPI). Results show that Canada has the highest EPII score, which shows that Canada's capacity to deal with energy self-sufficiency, economic development, and environmental performance is greater than the other G7 countries. France and Italy rank second and third. Japan comes next with 0.50 EPI scores, while the USA has the lowest average EPI score environment vulnerable even though have higher economic development among the G7 group countries. We suggest a policy framework to strengthen the subject matter of the study.
Without enhancing the quality of the environment, the goals of sustainable development remain unachievable. In order to minimize the damage to the planet, sustainable practices need to be considered. This study is conducted to identify some of the drivers behind the increasing sustainability issues and tried to investigate the impact of natural resources, financial development, and economic growth on the ecological footprint in Malaysia from the year 1980-2019 by utilizing the dynamic simulated autoregressive distribution lag approach. It was identified that financial development, economic growth, and natural resources are the determinants behind the upsurge of the ecological footprint as all three show a positive and significant effect on ecological footprint. However, in the long run, the presence of the Environmental Kuznets Curve hypothesis was also validated in Malaysia. Therefore, it is recommended to increase awareness among the public regarding the adoption of sustainable practices in everyday life and to use green technologies that offer maximum efficiency and minimum damage to the environment in commercial and domestic activities. Finally, based on the research results, a comprehensive policy framework was proposed which could allow the Malaysian economy to attain the objectives of Sustainable Development Goals (SDGs) 7, 8, and 13.
The atmosphere security and regulation of climate change are being continuously highlighted as a pressing issue. The crisis of climate change owing to the anthropogenic carbon dioxide emission has led many governments at federal and provincial levels to promulgate policies to address this concern. Among them is regulating the carbon dioxide emission from major industrial sources such as power plants, petrochemical industries, cement plants, and other industries that depend on the combustion of fossil fuels for energy to operate. In view of this, various CO2 capture and sequestration technologies have been investigated and presented. From this review, adsorption of CO2 on porous solid materials has been gaining increasing attention due to its cost-effectiveness, ease of application, and comparably low energy demand. Despite the myriad of advanced materials such as zeolites, carbons-based, metal-organic frameworks, mesoporous silicas, and polymers being researched, research on activated carbons (ACs) continue to be in the mainstream. Therefore, this review is endeavored to elucidate the adsorption properties of CO2 on activated carbons derived from different sources. Selective adsorption based on pore size/shape and surface chemistry is investigated. Accordingly, the effect of surface modifications of the ACs with NH3, amines, and metal oxides on adsorption performance toward CO2 is evaluated. The adsorption performance of the activated carbons under humid conditions is also reviewed. Finally, activated carbon-based composite has been surveyed and recommended as a feasible strategy to improve AC adsorption properties toward CO2. The activated carbon surface in the graphical abstract is nitrogen rich modified using ammonia through thermal treatment. The values of CO2 emissions by sources are taken from (Yoro and Daramola 2020).
Bamboo is the fastest-growing plant and is abundant in Malaysia. It is employed as a starting material for activated carbon production and evaluated for its potential in CO2 capture. A single-stage phosphoric acid (H3PO4) activation is adopted by varying the concentrations of H3PO4 between 50 and 70 wt.% at a constant temperature and holding time of 500°C and 120 min, respectively. The bamboo-based activated carbons are characterized in terms of product yield, surface area, and porosity, as well as surface chemistry properties. Referring to the experimental findings, the prepared activated carbons have BET surface area of >1000 m2 g-1, which implies the effectiveness of the single-stage H3PO4 activation. Furthermore, the prepared activated carbon via 50 wt.% H3PO4 activation shows the highest BET surface area and carbon dioxide (CO2) adsorption capacity of 1.45 mmol g-1 at 25°C/1 bar and 9.0 mmol g-1 at 25°C/30 bar. With respect to both the characterization analysis and CO2 adsorption performance, it is concluded that bamboo waste conversion to activated carbon through H3PO4 activation method is indeed promising.
Microbial fuel cells (MFCs) are the efficient and sustainable approach for the removal of toxic metals and generate energy concurrently. This article highlighted the effective use of rotten rice as an organic source for bacterial species to generate electricity and decrease the metal concentrations from wastewater. The obtained results were corresponding to the unique MFCs operation where the 510 mV voltage was produced within 14-day operation with 1000 Ω external resistance. The maximum power density and current density were found to be 2.9 mW/m2 and 168.42 mA/m2 with 363.6 Ω internal resistance. Similarly, the maximum metal removal efficiency was found to be 82.2% (Cd), 95.71% (Pb), 96.13% (Cr), 89.50% (Ni), 89.82 (Co), 99.50% (Ag), and 99.88% (Cu). In the biological test, it was found that Lysinibacillus strains, Chryseobacterium strains, Escherichia strains, Bacillus strains are responsible for energy generation and metal removal. Furthermore, a multiparameter optimization revealed that MFCs are the best approach for a natural environment with no special requirements. Lastly, the working mechanism of MFCs and future recommendations are enclosed.
We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals' use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. However, the accuracy of such prediction models has always been one of the major concerns for the researchers working in this area. The mutagenicity prediction models were developed using deep neural network (DNN), support vector machine, k-nearest neighbor, and random forest. The developed classifiers were based on 3039 compounds and validated on 1014 compounds; each of them encoded with 1597 molecular feature vectors. DNN-based prediction model yielded highest prediction accuracy of 92.95% and 83.81% with the training and test data, respectively. The area under the receiver's operating curve and precision-recall curve values were found to be 0.894 and 0.838, respectively. The DNN-based classifier not only fits the data with better performance as compared to traditional machine learning algorithms, viz., support vector machine, k-nearest neighbor, and random forest (with and without feature reduction) but also yields better performance metrics. In current work, we propose a DNN-based model to predict mutagenicity of compounds.
China's green growth has shown a trend of fluctuation year by year. Simultaneously, Chinese local governments have pursued simple economic growth driven by the interests of "political competition" for a long time, while the supervision of the ecological environment has been loosened and tightened. In this environment, financial development and technological innovation may easily become the accelerator of this phenomenon, thus exacerbating the fluctuation of green growth. To deeply excavate the key factors to achieve stable and sustained growth of green economy, based on the annual panel data of 30 provinces in China from 2011 to 2018, this paper studies the impact of financial development and technological innovation on the volatility of green growth using dynamic system GMM method. The findings of this paper are shown as follows: First, the expansion of financial institutions' scale will significantly enhance the volatility of green growth. Second, the increase in the scale of the stock market will also significantly cause green growth fluctuations. Third, the interaction between financial development and technological innovation can significantly weaken the volatility of green growth. Fourth, financial development measured by stock market indicators is more efficient than financial development measured by financial institutions indicators to curb the volatility of green growth. Fifth, the fluctuation of green growth in the previous period will reduce the volatility of green growth in the current period. This study provides new evidence for exploring the power source to promote the stability and sustainable growth of the green economy in the special stage of financial and technological integration. Controlling the development scale of financial institutions and removing their state preferences, expanding the development of capital markets, and deepening the integration of financial development and technological innovation are conducive to achieve stable green growth.
The demand for primary energy resources has increased significantly due to the rapid growth of the global economy and increasing greenhouse gas (GHG) emissions. Therefore, improving energy efficiency levels is essential for global energy, energy security, and environmental sustainability. In the context of the Asia-Pacific region, the study of energy efficiency among different countries can play a role in better energy utilization. These countries also provide a policy for the Asia-Pacific region to improve its energy utilization. This study's primary focus is to investigate the optimal efficiency score of 15 areas of the Asia-Pacific region, and the analysis is based on super-efficiency (radical) and super slacks-based measure (SBM) data in a nonparametric DEA model. Three areas in the Asia-Pacific are selected for energy efficiency measures: South Asia, East Asia, and Australasia. The results suggest that Bangladesh, Pakistan, China, Singapore, New Zealand, the Philippines, Japan, India, Indonesia, Malaysia, Thailand, and Vietnam obtain the most efficient score of 1 in both DEA models throughout the study period. Australia and Sri Lanka receive a low score during all study periods, while Hong Kong does not have data for all study years. The results of the study will help improve energy performance, cost-effectiveness, and environmental sustainability, increasing the competitiveness and scalability of efficient energy sources.
Research for alternative binders has become a necessity due to cement's embodied carbon, climate change, and depletion of natural resources. These binders could potentially reduce our reliance on cement as the sole binder for concrete while simultaneously enhancing the functional characteristics of concrete. Theoretically, the use of finer particles in the cement matrix densifies the pore structure of concrete and results in improved properties. To validate this hypothesis, current research was designed to investigate how the value-added benefits of nano-silica (NS) and metakaolin (MK) in fly ash (FA)-blended cement affect the mechanical and durability characteristics of concrete when used as ternary and quaternary blends. Additionally, the cost-benefit analysis and environmental impact assessment were conducted. It was observed that the synergy of MK and NS used in FA-blended cement had a greater impact on enhancing the functional characteristics of concrete, while 10% MK as ordinary Portland cement (OPC) replacement and 1% NS as an additive in FA-blended OPC concrete was the optimum combination which achieved 94-MPa compressive strength at the age of 91 days and showed more than 25% increment in the flexural and splitting tensile strengths compared to the control mix (MS00). The ultrasonic pulse velocity and dynamic modulus of elasticity were significantly improved, while a significant reduction in chloride migration of 50% was observed. In terms of environmental impact, MS100 (30% FA and 10% MK) exhibited the least embodied CO2 emissions of 319.89 kgCO2/m3, while the highest eco-strength efficiency of 0.268 MPa/kgCO2·m-3 with respect to 28-day compressive strength was exhibited by MS101. In terms of cost-benefit, MS00 was determined the cheapest, while the addition of MK and NS increased the cost. The lowest cost of producing 1 MPa was exhibited by MS01 with a merely 0.04-$/MPa/m3 reduction compared to MS00.
At the end of 2019, a novel coronavirus COVID-19 emerged in Wuhan, China, and later spread throughout the world, including Iraq. To control the rapid dispersion of the virus, Iraq, like other countries, has imposed national lockdown measures, such as social distancing, restriction of automobile traffic, and industrial enterprises. This has led to reduced human activities and air pollutant emissions, which caused improvement in air quality. This study focused on the analysis of the impact of the six partial, total, and post-lockdown periods (1st partial lockdown from March 1 to16, 2020, 1st total lockdown from March 17 to April 21, 2nd partial lockdown from April 22 to May 23, 2nd total lockdown from May 24 to June 13, 3rd partial lockdown from June 14 to August 19, and end partial lockdown from August 20 to 31) on the average of daily NO2, O3, PM2.5, and PM10 concentrations, as well as air quality index (AQI) in 18 Iraqi provinces during these periods (from March 1st to August 31st, 2020). The analysis showed a decline in the average of daily PM2.5, PM10, and NO2 concentrations by 24%, 15%, and 8%, respectively from March 17 to April 21, 2020 (first phase of total lockdown) in comparison to the 1st phase of partial lockdown (March 1 to March 16, 2020). Furthermore, the O3 increased by 10% over the same period. The 2nd phase of total lockdown, the 3rd partial lockdown, and the post-lockdown periods witnessed declines in PM2.5 by 8%, 11%, and 21%, respectively, while the PM10 increases over the same period. Iraqi also witnessed improvement in the AQI by 8% during the 1st phase of total lockdown compared to the 1st phase of partial lockdown. The level of air pollutants in Iraq declined significantly during the six lockdown periods as a result of reduced human activities. This study gives confidence that when strict measures are implemented, air quality can improve.
This study analyzes the relationship between globalization, energy consumption, and economic growth among selected South Asian countries to promote the green economy and environment. This study also finds causal association between energy growth and nexus of CO2 emissions and employed the premises of the EKC framework. The study used annual time series analysis, starting from 1985 to 2019. The data set has been collected from the World Development Indicator (WDI). The result of a fully modified ordinary least square (FMOLS) method describes a significantly worse quality environment in the South Asian region. The individual country as Bangladesh shows a positively significant impact on the CO2 emissions and destroys the level of environment regarding non-renewable energy and globalization index. However, negative and positive growth levels (GDP) and square of GDP confirm the EKC hypothesis in this region. This study has identified the causality between GDP growth and carbon emission and found bidirectional causality between economic growth and energy use.
The Southeast Asian countries have experienced significant degrees of economic growth over the years but have not managed to safeguard their environmental attributes in tandem. As a result, the aggravation of the environmental indicators across this region casts a shadow of doubt on the sustainability of the economic growth achievements of the Southeast Asian countries. Against this milieu, this study specifically explores the influence of renewable electricity generation capacity, technological innovation, financial development, and economic growth on the ecological footprints in five Southeast Asian countries namely Indonesia, Malaysia, the Philippines, Thailand, and Vietnam during the period 1985-2016. One of the major novelties of this study is in terms of its approach to assess the renewable energy use-ecological footprint nexus using the renewable electricity generation capacity as an indicator of renewable energy use in the selected Southeast Asian nations. The econometric analysis involves methods that are robust to handling cross-sectional dependency and slope heterogeneity issues in the data. Accordingly, the recently developed Cross-sectional Augmented Autoregressive Distributed Lag estimator is used to predict the short- and long-run impacts on ecological footprints. The major findings suggest that higher renewable electricity generation capacity and technological innovation reduce ecological footprints, while higher financial development and economic growth increase the ecological footprints. Therefore, these findings imply that in forthcoming years, the selected Southeast Asian countries will need to tackle the environmental adversities by enhancing their renewable electricity generation capacities, increasing investment in technological development, greening the financial sector, and adopting environmentally-friendly growth policies. Hence, the implementation of relevant policies, in this regard, can be expected to ensure complementarity between economic growth and environmental welfare across Southeast Asia.
Irgarol 1051 and diuron are photosystem II inhibitors in agricultural activities and antifouling paints in the shipping sector. This study focused on three major ports (western, southern, and eastern) surrounding Peninsular Malaysia to construct the distribution of both biocides on the basis of the seasonal and geographical changes. Surface seawater samples were collected from November 2011 to April 2012 and pretreated using the solid-phase extraction technique followed by quantification with GC-MS and LC-MS-MS for Irgarol 1051 and diuron, respectively. Generally, the distribution of Irgarol 1051 was lowest during November 2011 and highest during April 2012, and similar patterns were observed at all ports, whereas the distribution of diuron was rather vague. The increasing pattern of Irgarol 1051 from time to time is probably related to its accumulation in the seawater as a result of its half-life and consistent utilization. On the basis of the discriminant analysis, the temporal distribution of Irgarol 1051 varied at Klang North Port, Klang South Port, and Pasir Gudang Port, whereas diuron was temporally varied only at Kemaman Port. Furthermore, Irgarol 1051 was spatially varied during November 2011, whereas diuron did not show any significant changes throughout all sampling periods. Ecological risk assessment exhibited a high risk for diuron and Irgarol 1051, but Irgarol 1051 should be of greater concern because of its higher risk compared to that of diuron. Thus, it is recommended that the current Malaysian guidelines and regulations of biocide application should be reevaluated and improved to protect the ecosystem, as well as to prevent ecological risks to the aquatic environment.
Despite the potential shown by previous investigations on the use of ultrasound for the remediation of oil-contaminated sand, the influence and interactions among ultrasonic parameters and oily sand are unclear, leading to possible ineffective treatment and high-power consumption. In order to improve the process efficiency, this work analyzes the effects of ultrasonic power, frequency, and load toward the cleaning of crude oil-contaminated sand, using two different sample positions and sand types. Crude oil-contaminated beach sand and produced sand from offshore oil well were used as samples. They were cleaned in custom-made ultrasonic bath reactor for 10 min with power from 30 to 120 W, frequency covering 25-60 kHz, and sand load of 10-100 g. With experimental design consisting multiple factors and levels, the interactions between factors in all possible combinations were determined using ANOVA (n = 210). From p-value based at 95% confidence interval and extensive F test, the three most significant factors were the sand type, the ultrasonic frequency, and the interaction between sand type and frequency. The best setting for suspended samples involved high frequency of 60 kHz, whereas bottom samples preferred low frequency at 28 kHz. This finding was justified when the acoustic pressure attenuation, standing wave pattern, and surface pitting/cracking were found in correlation with the cleaning results. Overall, the maximum treatment under ultrasonic bath solely gained around 60%, improvable by hybrid cleaning with other techniques such as chemical, biological, mechanical, and thermal.
A study was carried out to determine the level of rare earth elements (REEs) in water and sediment samples from ex-mining lakes and River in Kinta Valley, Perak, Malaysia. Surface water and sediments from an ex-mining lake and Kinta River water samples were analyzed for REEs by inductively coupled plasma mass spectrometry. The total concentration of REEs in the ex-mining lake water samples and sediments were found to be 3685 mg/l and 14159 mg/kg, respectively, while the total concentration of REEs in Kinta River water sample was found to be 1224 mg/l. REEs in mining lake water were found to be within 2.42 mg/l (Tb) to 46.50 mg/l (Ce), while for the Kinta River, it was 1.33 mg/l (Ho) to 29.95 mg/l (Ce). Sediment samples were also found with REEs from 9.81 mg/kg (Ho) to 765.84 mg/kg (Ce). Ce showed the highest average concentrations for mining lake (3.88 to 49.08 mg/l) and Kinta River (4.44 to 33.15 mg/l) water samples, while the concentration of La was the highest (11.59 to 771.61 mg/kg) in the mining lake sediment. Lu was shown to have the highest enrichment of REEs in ex-mining lake sediments (107.3). Multivariate statistical analyses such as factor analysis and principal component analysis indicated that REEs were associated and controlled by mixed origin, with similar contributions from anthropogenic and geogenic sources. The speciation study of REEs in ex-tin mining sediments using a modified five-stage sequential extraction procedure indicated that yttrium (Y), gadolinium (Gd), and lanthanum (La) were obtained at higher percentages from the adsorbed/exchanged/carbonate fraction. The average potential mobility of the REEs was arranged in a descending order: Yb > Gd > Y = Dy > Pr > Er > Tm > Eu > Nd > Tb > Sc > Lu > Ce > La, implying that under favorable conditions, these REEs could be released and subsequently pollute the environment.
Rare earths (RE), chemically uniform group of elements due to similar physicochemical behavior, are termed as lanthanides. Natural occurrence depends on the geological circumstances and has been of long interest for geologist as tools for further scientific research into the region of ores, rocks, and oceanic water. The review paper mainly focuses to provide scientific literature about rare earth elements (REEs) with potential environmental and health effects in understanding the research. This is the initial review of RE speciation and bioavailability with current initiative toward development needs and research perceptive. In this paper, we have also discussed mineralogy, extraction, geochemistry, analytical methods of rare earth elements. In this study, REEs with their transformation and vertical distribution in different environments such as fresh and seawater, sediments, soil, weathering, transport, and solubility have been reported with most recent literature along key methods of findings. Speciation and bioavailability have been discussed in detail with special emphasis on soil, plant, and aquatic ecosystems and their impacts on the environment. This review shows that REE gained more importance in last few years due to their detrimental effects on living organisms, so their speciation, bioavailability, and composition are much more important to evaluate their health risks and are discussed thoroughly as well.
Recent bauxite mining activities in the vicinity of Kuantan, Pahang, have been associated with apparent environmental quality degradation and have raised environmental concerns among the public. This study was carried out to evaluate the overall ecological impacts on water and sediment quality from the bauxite mining activities. Water and sediment samples were collected at seven sampling locations within the bauxite mining areas between June and December 2015. The water samples were analyzed for water quality index (WQI) and distribution of major and trace element geochemistry. Sediment samples were evaluated based on geochemical indices, i.e., the enrichment factor (EF) and geoaccumulation index (I geo). Potential ecological risk index was estimated to assess the degree to which sediments of the mine-impacted areas have been contaminated with heavy metals. The results showed that WQIs of some locations were classified as slightly polluted and contained metal contents exceeding the recommended guideline values. The EFs indicated minimal to moderate enrichment of metals (Pb, Cu, Zn, Mn, As, Cd, Cr, Ni, Co, and Sr) in the sediments. I geo showed slightly to partially polluted sediments with respect to As at some locations. The potential ecological risk index (RI) showed that As posed the highest potential ecological risk with RI of 52.35-60.92 at two locations, while other locations indicated low risk. The findings from this study have demonstrated the impact of recent bauxite mining activities, which might be of importance to the local communities and relevant authorities to initiate immediate rehabilitation phase of the impacted area.
The main aim of this article is to examine empirically the impact of urbanization on carbon dioxide emissions in Singapore from 1970 to 2015. The autoregressive distributed lags (ARDL) approach is applied within the analysis. The main finding reveals a negative and significant impact of urbanization on carbon emissions in Singapore, which means that urban development in Singapore is not a barrier to the improvement of environmental quality. Thus, urbanization enhances environmental quality by reducing carbon emissions in the sample country. The result also highlighted that economic growth has a positive and significant impact on carbon emissions, which suggests that economic growth reduces environmental quality through its direct effect of increasing carbon emissions in the country. Despite the high level of urbanization in Singapore, which shows that 100 % of the populace is living in the urban center, it does not lead to more environmental degradation. Hence, urbanization will not be considered an obstacle when initiating policies that will be used to reduce environmental degradation in the country. Policy makers should consider the country's level of economic growth instead of urbanization when formulating policies to reduce environmental degradation, due to its direct impact on increasing carbon dioxide emissions.
The paper examines the impacts of financial development on sectoral carbon emissions (CO2) for environmental quality in Malaysia. Since the financial sector is considered as one of the sectors that will contribute to Malaysian economy to become a developed country by 2020, we utilize a cointegration method to investigate how financial development affects sectoral CO2 emissions. The long-run results reveal that financial development increases CO2 emissions from the transportation and oil and gas sector and reduces CO2 emissions from manufacturing and construction sectors. However, the elasticity of financial development is not significant in explaining CO2 emissions from the agricultural sector. The results for short-run elasticities were also consistent with the long-run results. We conclude that generally, financial development increases CO2 emissions and reduces environmental quality in Malaysia.
Sulfadimidine (SM2) is commonly used in the swine industry and enters the environment via faeces. In recent years, advances in the ecotoxicology of SM2 have become a popular research interest with two common research methods including swine manure collection from swine fed with a diet containing SM2 and directly adding SM2. The purpose of this experiment was to compare SM2 degradation behaviour in pig manure with two different SM2 addition methods. The results showed that the degradation half-lives of SM2 in manure from SM2-fed swine treatment were 33.2 and 32.0 days at the initial addition level of SM2 at 32.1 and 64.3 mg/kg, respectively. This was significantly longer than that in manure directly adding SM2 treatment with the half-lives of 21.4 and 14.8 days. The metabolite of SM2 N(4)-acetyl-sulfamethazine occurred in manure from SM2-fed swine treatment but was not detected in directly adding SM2 treatment. The pH in manure from SM2-fed swine treatment was significantly lower than that in directly adding SM2 treatment, but the values of organic carbon, total nitrogen, and electrical conductivity in manure from SM2-fed swine treatment were significantly higher than those in manure directly adding SM2 treatment. Meanwhile, although the copy number of bacteria had no significant difference between two treatments, there was a significant difference in bacteria diversity. Results of the present study demonstrated that the presence of the metabolites, chemical property, and microbial diversity might be the reason for different SM2 degradation behaviours on different addition methods. Thus, the method using manure with SM2 collected from swine could obtain more accurate results for the ecotoxicological study of SM2.