The COVID-19 pandemic has plunged the world into uncharted territory, leaving people feeling helpless in the face of an invisible threat of unknown duration that could adversely impact the national economic growths. According to the World Health Organization (WHO), the SARS-CoV-2 spreads primarily through droplets of saliva or discharge from the mouth or nose when an infected person coughs or sneezes. However, the transmission of the SARS-CoV-2 through aerosols remains unclear. In this study, computational fluid dynamic (CFD) is used to complement the investigation of the SARS-CoV-2 transmission through aerosol. The Lagrangian particle tracking method was used to analyze the dispersion of the exhaled particles from a SARS-CoV-2-positive patient under different exhale activities and different flow rates of chilled (cooling) air supply. Air sampling of the SARS-CoV-2 patient ward was conducted for 48-h measurement intervals to collect the indoor air sample for particulate with diameter less than 2.5 μm. Then, the reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was conducted to analyze the collected air sample. The simulation demonstrated that the aerosol transmission of the SARS-CoV-2 virus in an enclosed room (such as a hospital ward) is highly possible.
Despite a profound evidence of the human unsustainable behaviours' impact on the environment, stark disparities prevail on this narrative especially in the context of the current epidemiological situation ushered by the COVID-19. The ongoing pandemic is a global public health concern due to its sagacious impacts on environmental sustainability, social responsibility and people's quality of life. This study primarily focuses on analysing the impact of COVID-19 (COV) on the environmental awareness (EA), sustainable consumption (SC) and social responsibility (SR). Additionally, we aspire to investigate the impact of demographics of generations and religion on the proposed nexus in this study. The data was collected from 700 participants of different age groups and religious backgrounds in Malaysia, and structural equation modelling (SEM) was used to analyse this data and test the hypotheses. The findings indicate that COVID-19 has a significantly positive impact on EA, SC and SR, and the generations and religiosity moderate the relationship between COVID-19 and its impact on sustainable behaviours. This study contributes to analyse the difference in the perception of EA, SC and SR among the people that eventually will stimulate the scientific reasoning among the governments, policymakers and scientists to develop a holistic framework to combat unprecedented event such as COVID-19 and ensure the authentication of sustainable environment and exceptional quality of life. The policymakers in Malaysia may use the findings of this study to inspect the social and environmental aspects of the people during the transformation events.
Air pollution has a serious and adverse effect on human health, and it has become a risk to human welfare and health throughout the globe. One of the major effects of air pollution on health is hospitalizations associated with air pollution. Recently, the estimation and prediction of air pollution-based hospitalization is carried out using artificial intelligence (AI) and machine learning (ML) techniques, i.e., deep learning and long short-term memory (LSTM). However, there is ample room for improvement in the available applied methodologies to estimate and predict air pollution-based hospital admissions. In this paper, we present the modeling and analysis of air pollution and cardiorespiratory hospitalization. This study aims to investigate the association between cardiorespiratory hospitalization and air pollution, and predict cardiorespiratory hospitalization based on air pollution using the artificial intelligence (AI) techniques. We propose the enhanced long short-term memory (ELSTM) model and provide a comparison with other AI techniques, i.e., LSTM, DL, and vector autoregressive (VAR). This study was conducted at seven study locations in Klang Valley, Malaysia. The utilized dataset contains the data from January 2006 to December 2016 for five study locations, i.e., Klang (KLN), Shah Alam (SA), Putrajaya (PUJ), Petaling Jaya (PJ), and Cheras, Kuala Lumpur (CKL). The dataset for Banting contains data from April 2010 to December 2016, and the data for Batu Muda, Kuala Lumpur, contains data from January 2009 to December 2016. The prediction results show that the ELSTM model performed significantly better than other models in all study locations, with the best RMSE scores in Klang study location (ELSTM: 0.002, LSTM: 0.013, DL: 0.006, VAR: 0.066). The results also indicated that the proposed ELSTM model was able to detect and predict the trends of monthly hospitalization significantly better than the LSTM and other models in the study. Hence, we can conclude that we can utilize AI techniques to accurately predict cardiorespiratory hospitalization based on air pollution in Klang Valley, Malaysia.
Proposals have been made by several researchers to conduct the sequestration of carbon dioxide (CO2) through calcium and magnesium-rich materials. From these materials, ground granulated blast furnace slag (GGBS) containing 5% magnesium and 45% calcium is seen to be a good candidate and is available to sequester CO2. This study intends to ascertain the ability to absorb CO2, sequester it, and increase treated kaolin strength with different content of GGBS under various carbonation periods with varying CO2 pressure. The impacts of carbonated GGBS on the mechanical attributes of soil were examined by conducting the unconfined compressive strength (UCS) test, and microstructure analysis was conducted to identify the changes in the structure and Crestline phase. Stationary carbonation in a triaxial test with pure CO2 was conducted to accelerate the carbonation process. The outcome indicates that the strength rises as the carbonation period rises. Likewise, UCS rises as the CO2 pressure rises from 100 to 200 kPa. It could be concluded that augmentation of the strength is because of carbonated calcium and magnesium products which stuff the soil voids. Changes occur on the microstructure level due to carbonation as well.
A key objective of renewable energy development in the USA is to reduce CO2 emissions by decreasing reliance on fossil fuels in the coming decades. Using quantile-on-quantile regressions, this research examines the relationship between disaggregated sources of renewable energy (biomass, biofuel, geothermal, hydroelectric, solar, wind, wood, and waste) and CO2 emissions in the USA during the period from 1995 to 2017. Our findings support the deployment of various types of renewables in combating CO2 emissions for each quantile. In particular, a negative effect of renewable energy consumption on CO2 emissions is observed for the lower quantiles in almost all types of renewables. The effect of all the renewable energy sources taken together is significant for the lower and upper quantiles of the provisional distribution of CO2 emissions. The effect of renewable energy becomes stronger and more significant in the middle quantiles, where a pronounced causal effect of return and volatility is detected for the lower and upper middle quantiles. At the same time, heterogeneity in the findings across various types of renewable energy sources reveals differences in the relative importance of each type within the energy sector taken as a whole. Future US initiatives in renewable energy deployment at both the federal and the state levels should take into consideration the relative importance of each type, so as to maximize the efficacy of renewable energy policies in combating CO2 emissions.
The presence of conventional and emerging pollutants infiltrating into our water bodies is a course of concern as they have seriously threatened water security. Established techniques such as photocatalysis and membrane technology have proven to be promising in removing various persistent organic pollutants (POP) from wastewaters. The emergence of hybrid photocatalytic membrane which incorporates both photocatalysis and membrane technology has shown greater potential in treating POP laden wastewater based on their synergistic effects. This article provides an in-depth review on the roles of both photocatalysis and membrane technology in hybrid photocatalytic membranes for the treatment of POP containing wastewaters. A concise introduction on POP's in terms of examples, their origins and their effect on a multitude of organisms are critically reviewed. The fundamentals of photocatalytic mechanism, current directions in photocatalyst design and their employment to treat POP's are also discussed. Finally, the challenges and future direction in this field are presented.
The production of cement contributes to 10% of global carbon dioxide (CO2) pollution and 74 to 81% towards the total CO2 pollution by concrete. In addition to that, its low strength-to-weight ratio, high density and thermal conductivity are among the few limitations of heavy weight concrete. Therefore, this study was carried out to provide a solution to these limitations by developing innovative eco-friendly lightweight foamed concrete (LFC) of 1800 kg/m3 density incorporating 20-25% palm oil fuel ash (POFA) and 5-15% eggshell powder (ESP) by weight of total binder as supplementary cementitious material (SCM). The influence of combined utilization of POFA and ESP on the fresh state properties of eco-friendly LFC was determined using the J-ring test. To determine the mechanical properties, a total of 48 cubes and 24 cylinders were prepared for compressive strength, splitting tensile strength and modulus of elasticity each. A total of 24 panels were prepared to determine the thermal properties in terms of surface temperature and thermal conductivity. Furthermore, to assess the environmental impact and eco-friendliness of the developed LFC, the embodied carbon and eco-strength efficiency was calculated. It was determined that the utilization of POFA and ESP reduced the workability slightly but enhanced the mechanical properties of LFC (17.05 to 22.60 MPa compressive strength and 1.43 to 2.61 MPa tensile strength), thus satisfies the ACI213R requirements for structural lightweight concrete and that it can be used for structural applications. Additionally, the thermal conductivity reduced ranging from 0.55 to 0.63 W/mK compared to 0.82 W/mK achieved by control sample. Furthermore, the developed LFC showed a 16.96 to 33.55% reduction in embodied carbon and exhibited higher eco-strength efficiency between 47.82 and 76.97%. Overall, the combined utilization of POFA and ESP as SCMs not only enhanced the thermo-mechanical performance, makes the sustainable LFC as structural lightweight concrete, but also has reduced the environmental impacts caused by the disposal of POFA and ESP in landfills as well as reducing the total CO2 emissions during the production of eco-friendly LFC.
This work aims to assess multidimensional energy poverty and energy efficiency for environmental policy measures using data envelopment analysis (DEA), a DEA-Like mathematical composite indicator applied on a dataset based on multiple sets of variables from South Asian economies. The multidimensional energy poverty index (MEPI) is computed to analyze the combining effects and energy poverty in these countries. Simultaneously, South Asia's metropolitan areas' population rose by 130 million between 2001 and 2011 and is projected to expand by approximately 250 million by 2030. The findings reveal that endogenous increasing population shocks account for about 72% of energy use. In contrast, the long-term effects of remittance revenue, economic growth, and urbanization on energy use are approximately 20%, 8.25%, and 0.03%, respectively. This work advocates more coordinated and innovative policies to eliminate energy poverty. It can act as a base for policymakers and government officials to make efficient policies and enforce them properly in the regional power sector. Policies should be designed around a smarter use of biomass for cooking, alternate sources for domestic energy production, increased programs for biomass-based cookstoves, and periodic regional-level energy database development.
The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975-2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high-technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country's economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.
Studies that associate environmental parameters with aquatic organisms in man-made lakes remain limited by accessibility and interest particularly in many Asian countries. With missed opportunities to monitor environmental transitions at Lake Kenyir, our knowledge of lake transition is restricted to the non-mixing shallow waters only. Triplicate monthly benthic invertebrate samples were collected concurrently with various environmental parameters at three locations (zones A-C) of Kenyir Lake, Malaysia. Our results affirmed that the northeast part of Lake Kenyir is oligotrophic. Abundance of phytoplankton, total suspended solids, phosphate, nitrite and nitrate drive the abundance of various groups of benthic invertebrates. All of these extrinsic variables (except phosphate) negatively influenced the density of Trichoptera and positively influenced (P<0.05) the densities of Polychaeta, Oligochaeta, Bivalvia, Gastropod, Isopoda and Copepod in all zones. Phosphate negatively influenced the density of Trichoptera and positively influenced (P<0.05) the densities of Oligochaeta, Bivalvia and Copepod. Its influences on the Polychaeta, Gastropod and Isopoda densities were zone-specific. Overall, seasons equally influenced the relationships between extrinsic and response variables in all zones. The results of this study are useful to evaluate the lake's environmental quality, in conservation and in similar projects involving environmental handling, monitoring and recovery.
This research sought to develop and validate the "Workplace Second-hand Smoke: Perception on the SHS Knowledge, Attitude, and Practice" (WSHS: PAP) instrument, which targets non-smoking employees. A cross-sectional study was conducted between April and June 2018 to validate WSHS: PAP among non-smoking employees at Universiti Malaya Medical Centre (UMMC). Experts were invited to validate the instrument. Then, for exploratory factor analysis, a cross-sectional study was conducted among 336 UMMC non-smoking employees who were recruited by convenience sampling. A total of 28 items on KAP, rated on five-point Likert scales, underwent exploratory factor analysis and were tested for internal consistency (Cronbach's alpha). Participants were approached after 2 weeks for the assessment of test-retest reliability. Cronbach's alpha was 0.828, 0.743 and 0.837, respectively, for the domains of perception of the knowledge, attitude and practice, indicating acceptable internal consistency (above 0.7). Exploratory factor analysis identified a one-factor solution for each of the KAP domains. Therefore, the Malay version of the WSHS: PAP instrument demonstrated satisfactory psychometric properties for the assessment of non-smoking employees in workplaces with a smoking ban.
Within a framework that includes economic activity, real interest rate, grants, and subsidies, we aim to explore the role of renewable energy, technological innovation, and particularly the environmentally damaging militarization in driving green growth, which fosters sustainable economic growth by ensuring the values of natural assets, considering OECD countries. Our examination affirms a positive proposition between the development of renewable energy, technological innovation, and green growth in the long run by implementing the cross-sectional dependency panel autoregressive-distributed lags (CS-ARDL) framework in a dynamic heterogeneous panel setting. The findings also suggest that militarization is antagonistic to green growth. Our decomposed analysis is compatible with our premier analysis, indicating a conducive impact of both biomass and non-biomass types of renewable energy on green growth. We also document a negative association between the real interest rate (RIR) and green growth, while income muddles the results. The robustness tests confirm the sensitivity of our main findings to the magnitude of the subsidies and grants provided to renewable energy. The paper concludes with several policy recommendations.
Red mud as industrial waste from bauxite was utilized as a precursor for the synthesis of mesoporous ZSM-5. A high concentration of iron oxide in red mud was successfully removed using alkali fusion treatment. Mesoporous ZSM-5 was synthesized using cetyltrimethylammonium bromide (CTABr) as a template via dual-hydrothermal method, and the effect of crystallization time was investigated towards the formation of mesopores. Characterization using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), N2 adsorption-desorption, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) indicated the formation of cubic crystallite ZSM-5 with high surface area and mesopore volume within 6 h of crystallization. Increasing the crystallization time revealed the evolution of highly crystalline ZSM-5; however, the surface area and mesoporosity were significantly reduced. The effect of mesoporosity was investigated on the adsorption of methylene blue (MB). Kinetic and thermodynamic analysis of MB adsorption on mesoporous ZSM-5 was carried out at a variation of adsorption parameters such as the concentration of MB solution, the temperatures of solution, and the amount of adsorbent. Finally, methanol, 1-butanol, acetone, hydrochloric acid (HCl), and acetonitrile were used as desorbing agents to investigate the reusability and stability of mesoporous ZSM-5 as an adsorbent for MB removal.
This research aims to assess the sustainability of the most common earth-retaining walls (Gravity Walls and Cantilever Walls) in terms of environmental impacts, economic issues, and their combination. Gravity walls observed in this study consist of Gabion Wall, Crib Wall, and Rubble Masonry Wall, while Cantilever Walls include Reinforced Concrete Wall. Six different criteria were taken into account, including global warming potential, fossil depletion potential, eutrophication potential, acidification potential, human toxicity potential, and cost. To achieve the aim of this study, life cycle assessments, life cycle costs, and multi-criteria decision-making methods were implemented. The results showed that the most environmental-friendly option among all alternatives was the Gabion Wall, followed by the Rubble Masonry Wall. However, in terms of economic aspects, the Cantilever Concrete Wall was the best option, costing about 17% less than the Gabion Wall. On the other hand, the results of multi-criteria decision-making showed that the Gabion Wall was the most sustainable choice. This study addressed the research gap by carrying out a sustainability assessment of different retaining walls while considering cost and environmental impacts at the same time.
Growing environmental deterioration has caused many countries to tighten their environmental regulations across the globe. Recent studies show that most developed countries enforced stricter environmental regulations creating a pollution haven to developing countries such as Nigeria. Studies show the non-availability of an environmental regulation compliance scale in the energy sectors. The aim of this paper is to validate the effects of environmental regulation compliance scale for oil and gas companies' operations in the Nigerian oil and gas industry. Hence, an adapted questionnaire comprising 11 items was administered to 300 local and multinational oil and gas companies in Nigeria. All the items were subjected to evaluations and validations by eight expert reviewers with cognate experience in oil and gas activities. Evaluation of the reliability and validity of the measures of the environmental regulation scale was performed through confirmatory factor analysis (CFA) using SPSS version 25 and PLS-SEM version 3.8. The results provide evidence that the environmental regulation compliance scale has met the reliability and validity criteria. Consequently, policymakers, practitioners, and researchers can adapt this scale to assess the effects of environmental regulation compliance by companies in different jurisdictions across the globe. This study undoubtedly builds the existing literature and contributes to the subject area; by implication, the validated scale will assist host oil and gas countries with stringent environmental regulations to come up with policies in such a way as to ensure not chasing away the current investors or discouraging prospective ones from investing in their countries.
Obesity is a worldwide concern as it leads to adverse effects on human health. This study uses a panel of 165 countries and annual data from 2000 to 2014 to examine the obesity Kuznets curve (OKC) hypothesis. By using tests and estimators that are robust to cross-section dependence (CSD), our results support the OKC hypothesis. This indicates that obesity increases at the initial stage of economic development and eventually would decrease once the threshold is reached. In addition, we find that the role of global warming on obesity is not significant. Food production is found to be a contributing factor to obesity. Besides, one-way and two-way causalities are identified between the variables. This study provides important insights particularly about the relationship between (i) economic growth and obesity and (ii) environmental degradation and obesity. Implication of the results and policy recommendations are also provided to policymakers and health personnel in finding solutions to the obesity epidemic around the world.
Along with the growing utilization of zinc (Zn) and Zn-containing nanoparticles in various industries, Zn ecotoxicological evaluation on human food supply is necessary even though Zn is generally considered safe and rarely concentrated ecotoxicologically. This study aimed to investigate the bioaccumulation of Zn in 18 species of vegetables (seven leafy, nine fruity vegetables and one species each of tuber and legume) collected from two farming sites in the west coast of Peninsular Malaysia. A human health risk assessment (HHRA) was also conducted. In addition to HHRA based on the general population, HHRA based on each major ethnic group of the Malaysian society was also determined considering that the food consumption pattern would definitely be varied across ethnicities and age groups (children and adults). The study results showed that Zn concentrations were significantly higher (p < 0.05) in leafy vegetables than in other types of vegetables. However, the target hazard quotient (THQ) values were all found to be < 1.0. Therefore, based on the Malaysian ethnicities and age groups with their respective vegetable consumption patterns, the results indicated insignificant noncarcinogenic human health risk of Zn via oral consumption of vegetables by the Malaysian population. As a metric of measurement of HHRA, a comparison of THQ values could yield previously unreported insights into HHRA differences among the compared populations. A comparison of THQ values among the consumer groups indicated higher HHR for Chinese Malaysians and children due to their higher vegetable consumption and lower body weight, respectively. A comparison the Zn intakes of all the consumer groups with the recommended nutrient intakes indicated that the oral consumption of the vegetable species collected in this study would not result in Zn-related hazards and would not be able to fulfil the Zn dietary need of the individual consumer.
Drought is considered one of the costliest natural disasters that result in water scarcity and crop damage almost every year. Drought monitoring and forecasting are essential for the efficient management of water resources and sustainability in agriculture. However, the design of a consistent drought prediction model based on the dynamic relationship of the drought index with its antecedent values remains a challenging task. In the present research, the SVR (support vector regression) model was hybridized with two different optimization algorithms namely; Particle Swarm Optimization (PSO) and Harris Hawks Optimization (HHO) for reliable prediction of effective drought index (EDI) 1 month ahead, at different locations of Uttarakhand State of India. The inputs of the models were selected through partial autocorrelation function (PACF) analysis. The output produced by the SVR-HHO and SVR-PSO models was compared with the EDI estimated from observed data using five statistical indicators, i.e., RMSE (Root Mean Square Error), MAE (Mean Absolute Error), COC (Coefficient of Correlation), NSE (Nash-Sutcliffe Efficiency), WI (Willmott Index), and graphical inspection of radar-chart, time-variation plot, box-whisker plot, and Taylor diagram. Appraisal of results indicates that the SVR-HHO model (RMSE = 0.535-0.965, MAE = 0.363-0.622, NSE = 0.558-0.860, COC = 0.760-0.930, and WI = 0.862-0.959) outperformed the SVR-PSO model (RMSE = 0.546-0.967, MAE = 0.372-0.625, NSE = 0.556-0.855, COC = 0.758-0.929, and WI = 0.861-0.956) in predicting EDI. Visual inspection of model performances also showed a better performance of SVR-HHO compared to SVR-PSO in replicating the median, inter-quartile range, spread, and pattern of the EDI estimated from observed rainfall. The results indicate that the hybrid SVR-HHO approach can be utilized for reliable EDI predictions in the study area.
This study proposes a set of GuFSyADD guidelines on steps for developing suggestions that enhance of its rigor in systematic literature review (SLR) for studies related to climate change adaptation. The prescribed guidelines are based on the following six steps, (1) guided by review of protocol/publication standard/established guidelines/related published articles, (2) formulation of review questions, (3) systematic searching strategies, (4) appraisal of quality, (5) data extraction and analysis, and (6) data demonstration. Essentially, this set of proposed guidelines enables researchers to develop an SLR pertaining to climate change adaptation in an organised, transparent, and replicable manner.