Although evidence of mosquito coils' impact on disease epidemiology is limited, they are popularized as mosquito-borne disease prevention devices. Their usage affects the environment, human and mosquito health. This study investigated the perception, usage pattern and efficacy of coils in a predominantly poor malaria-endemic Ghanaian peri-urban area. Information on protection methods, perception and usage pattern was garnered using questionnaires. The efficacy of commonly used coils in the area was then assessed on the malaria vector, Anopheles gambiae, in a glass chamber. Sole or co-application of mosquito control methods and risky usage practices were reported. Coils were deemed harmful to humans and mosquitoes, and their perceived effectiveness varied, with several factors influencing their purchase. High d-allethrin concentration coils induced quicker mosquito knockdown; however, mortality was less than 85%. The coil usage pattern compromises users' health and can enhance mosquito tolerance to d-allethrin. The coils were ineffective against the vector, outlining a dichotomy between the users' perception of efficacy and the observed efficacy. Hence, the usage of other safer and more effective vector control methods should be encouraged to protect households.
Yearly, huge amounts of sock refuse are discarded into the environment. Socks contain many molecules, and worn ones, which are rich in smell-causing bacteria, have a strong influence on animals' behaviors. But the impacts of sock odor on the oviposition behavior of dengue vectors are unknown. We assessed whether Aedes albopictus changes its oviposition activity in response to the presence of used socks extract (USEx) in potential breeding grounds, using choice and no-choice bioassays (NCB). When furnished even chances to oviposit in two sites holding USEx and two others containing water (control), Ae. albopictus deposited significantly less eggs in USEx than in water sites. A similar pattern of oviposition preference was also observed when there were more oviposition options in water. When there were greater oviposition opportunities in USEx sites, Ae. albopictus oviposited preferentially in water. Females laid significantly more eggs during the NCB involving water than USEx. Also, significantly more mature eggs were retained by females in the NCB with USEx than in that with water. These observations strongly suggest the presence of molecules with either repellent or deterrent activities against Ae. albopictus females and provide an impetus to advocate the integration of used socks in dengue control programs. Such applications could be a realistic end-of-life recourse to reroute this waste from landfills.
The rapid spread of highly aggressive arboviruses, parasites, and bacteria along with the development of resistance in the pathogens and parasites, as well as in their arthropod vectors, represents a huge challenge in modern parasitology and tropical medicine. Eco-friendly vector control programs are crucial to fight, besides malaria, the spread of dengue, West Nile, chikungunya, and Zika virus, as well as other arboviruses such as St. Louis encephalitis and Japanese encephalitis. However, research efforts on the control of mosquito vectors are experiencing a serious lack of eco-friendly and highly effective pesticides, as well as the limited success of most biocontrol tools currently applied. Most importantly, a cooperative interface between the two disciplines is still lacking. To face this challenge, we have reviewed a wide number of promising results in the field of green-fabricated pesticides tested against mosquito vectors, outlining several examples of synergy with classic biological control tools. The non-target effects of green-fabricated nanopesticides, including acute toxicity, genotoxicity, and impact on behavioral traits of mosquito predators, have been critically discussed. In the final section, we have identified several key challenges at the interface between "green" nanotechnology and classic biological control, which deserve further research attention.
The present work describes the successful functionalization/magnetization of bio-polymeric spores of Lycopodium clavatum (sporopollenin) with 1-(2-hydroxyethyl) piperazine. Analytical techniques, i.e., Fourier transform infrared (FT-IR), field emission scanning electron microscope (FESEM), energy-dispersive X-ray spectroscopy (EDS), and vibrating sample magnetometer (VSM), were used to confirm the formation of 1-(2-hydroxyethyl) piperazine-functionalized magnetic sporopollenin (MNPs-Sp-HEP). The proposed adsorbent (MNPs-Sp-HEP) was used for the removal of noxious Pb(II) and As(III) metal ions from aqueous media through a batch-wise method. Different experimental parameters were optimized for the effective removal of selected noxious metal ions. Maximum adsorption capacity (q m ) 13.36 and 69.85 mg g-1 for Pb(II) and As(III), respectively, were obtained. Thermodynamic parameters such as free energy (ΔG°), entropy (ΔS°), and enthalpy (ΔH°) were also studied from the adsorption results and were used to elaborate the mechanism of their confiscation. The obtained results indicated that newly adsorbent can be successfully applied for the decontamination of noxious Pb(II) and As(III) from the aqueous environment.
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.
The devastating health effects of particulate matter (PM10) exposure by susceptible populace has made it necessary to evaluate PM10 pollution. Meteorological parameters and seasonal variation increases PM10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM10 concentration levels. The analyses were carried out using daily average PM10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM10 concentration levels having coefficient of determination (R 2) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.
One of the most critical parameters in concrete design is compressive strength. As the compressive strength of concrete is correctly measured, time and cost can be decreased. Concrete strength is relatively resilient to impacts on the environment. The production of concrete compressive strength is greatly influenced by severe weather conditions and increases in humidity rates. In this research, a model has been developed to predict concrete compressive strength utilizing a detailed dataset obtained from previously published studies based on a deep learning method, namely, long short-term memory (LSTM), and a conventional machine learning (ML) algorithm, namely, support vector machine (SVM). The input variables of the model include cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate, and age of specimens. To demonstrate the efficiency of the proposed models, three statistical indices, namely, the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE), were used. Findings shows that LSTM outperformed SVM with R2=0.98, R2= 0.78, MAE=1.861, MAE=6.152, and RMSE=2.36, RMSE=7.93, respectively. The results of this study suggest that high-performance concrete (HPC) compressive strength can be reliably measured using the proposed LSTM model.
Regional estimates of VOC fluxes focus largely on emissions from the canopy and omit potential contributions from the forest floor including soil, litter and understorey vegetation. Here, we measured monoterpene emissions every 2 months over 2 years from logged tropical forest and oil palm plantation floor in Malaysian Borneo using static flux chambers. The main emitted monoterpenes were α-pinene, β-pinene and d-limonene. The amount of litter present was the strongest indicator for higher monoterpene fluxes. Mean α-pinene fluxes were around 2.5-3.5 μg C m-2 h-1 from the forest floor with occasional fluxes exceeding 100 μg C m-2 h-1. Fluxes from the oil palm plantation, where hardly any litter was present, were lower (on average 0.5-2.9 μg C m-2 h-1) and only higher when litter was present. All other measured monoterpenes were emitted at lower rates. No seasonal trends could be identified for all monoterpenes and mean fluxes from both forest and plantation floor were ~ 100 times smaller than canopy emission rates reported in the literature. Occasional spikes of higher emissions from the forest floor, however, warrant further investigation in terms of underlying processes and their contribution to regional scale atmospheric fluxes.
Peat fires in tropical peatland release a substantial amount of carbon into the environment and cause significant harm to peatlands and the ecology, resulting in climate change, biodiversity loss, and the alteration of the ecosystem. It is essential to understand peat fires and to develop more effective methods for controlling them. To estimate carbon emissions and monitor fires, the depth of burning can measure the overall burnt down the volume, which is proportional to the carbon emissions that are emitted to the environment. The first step is to understand the technique of measuring the depth of the burn. However, there is a lack of integrated information regarding the burning depth for peat fires. This review paper discusses the techniques used to measure the burning depth, with particular attention given to quantifying carbon emissions. The article also provides information on the types of methods used to determine the burning depths. This research contributes to the field of peat fire by providing a readily available reference for practitioners and researchers on the current state of knowledge on peat fire monitoring systems.
Rainwater harvesting is an effective alternative practice, particularly within urban regions, during periods of water scarcity and dry weather. The collected water is mostly utilized for non-potable household purposes and irrigation. However, due to the increase in atmospheric pollutants, the quality of rainwater has gradually decreased. This atmospheric pollution can damage the climate, natural resources, biodiversity, and human health. In this study, the characteristics and physicochemical properties of rainfall were assessed using a qualitative approach. The three-year (2017-2019) data on rainfall in Peninsular Malaysia were analysed via multivariate techniques. The physicochemical properties of the rainfall yielded six significant factors, which encompassed 61.39% of the total variance as a result of industrialization, agriculture, transportation, and marine factors. The purity of rainfall index (PRI) was developed based on subjective factor scores of the six factors within three categories: good, moderate, and bad. Of the 23 variables measured, 17 were found to be the most significant, based on the classification matrix of 98.04%. Overall, three different groups of similarities that reflected the physicochemical characteristics were discovered among the rain gauge stations: cluster 1 (good PRI), cluster 2 (moderate PRI), and cluster 3 (bad PRI). These findings indicate that rainwater in Peninsular Malaysia was suitable for non-potable purposes.
This paper investigates the efficiency and total factor productivity (TFP) growth of the Pakistani banking industry and determines the impact of risk and competition on the efficiency and TFP growth. The data envelopment analysis (DEA)-based Malmquist productivity index is used to measure efficiency and TFP growth of the Pakistani banking industry. The generalized method of moments (GMM) model is applied to observe the impact of risk and competition on efficiency and TFP growth. The motivation behind the use of GMM model is its ability to overcome unobserved heterogeneity, autocorrelation, and endogeneity issues. The results of the study show that the credit and liquidity risks have positive while insolvency risk has negative effect on the efficiency and TFP growth. The competition leads to improve technological efficiency but declines the technical efficiency growth. Among other explanatory variables, operational cost management, banking sector development, GDP growth rate, and infrastructure development show significant relationships with various efficiencies and TFP growth. The banks also facilitate for the purchase of carbon-intensive products in order to reduce carbon emissions. Strong banking development successfully allocate their financial resources for the development of energy-efficient technology while banking sector development is found to be negatively related with environmental sustainability. The strong banking sector possesses a significant negative influence on carbon reduction and environmental degradation.
This study investigated the coagulation performance of titanium tetrachloride (TiCl4) for leachate treatment and preparation of titanium oxide (TiO2) from generated sludge through calcination process at different temperatures and times. TiCl4 with chitosan as coagulant aid employed to perform coagulation process on Alor Ponhsu Landfill leachate. Further calcination process was done to synthesize TiO2 from produced sludge for photocatalytic applications. The studied factors included pH, TiCl4 dosage, and chitosan dosage. The results indicated that maximum reduction in suspended solids was 92.02% at pH 4, 1200 mg/L TiCl4, and 250 mg/L chitosan addition, and maximum reduction in chemical oxygen demand was 71.92% at experimental condition of 1200 mg/L TiCl4 and 500 mg/L chitosan with pH 10. The maximum and minimum band gaps of prepared TiO2 achieved at 3.35 eV and 2.75 eV, respectively. Morphology and phase analysis of prepared TiO2 characterized using scanning electron microscope (SEM) and X-ray diffraction (XRD). The XRD spectrums showed the anatase phase at lower calcination temperature and the rutile phase at elevated temperature. The photocatalysis activity of produced TiO2 investigated under UV irradiation and showed almost fast degradation similar to commercial TiO2. The results indicated that TiO2 powder was successfully prepared from generated sludge from TiCl4 coagulation for photocatalytic applications.
Most of the existing studies on stochastic convergence of emission have not adequately considered smooth structural changes. The primary purpose of this paper is to examine the validity of stochastic convergence at different income levels by recently proposed Fourier-based wavelet augmented Dickey-Fuller test with smooth shifts. Empirical results can be summed up as follows: (i) carbon emission per capita follows the stationarity process in 35 high-income countries, while carbon emission per capita follows the stationarity process in 27 upper-middle-income countries; (ii) besides, carbon emission per capita follows stationarity process in 30 lower-middle-income countries, while carbon emission per capita follows stationarity process in 13 low-income countries; (iii) in light of these findings, it can be said that stochastic convergence among different income groups is valid. The implications of the empirical findings for environmental planning and management are discussed in the body of the paper.
This study examined the impacts of the Coronavirus disease 2019 (COVID-19) on the environment in the Southeast Asia region using qualitative content analysis to analyze the textual data of published studies and other online references such as the organizational reports. Besides, the materiality assessment particularly the Global Reporting Initiative was conducted by analyzing short- and long-term impacts from the stakeholders' (local and regional policymakers) perspective. The positive effects of COVID-19 lockdown and movement restriction on the regional environment identified in this study included a reduction in air pollution, improvement of air and water quality, lower noise levels, and reduced land surface temperature. In contrast, the negative effects encompassed a rise in the use of plastics and the generation of medical waste in Indonesia, Malaysia, Thailand, the Philippines, and Vietnam. Materiality assessment findings have offered insights on the need of stakeholders' importance for further to deal with huge amount of waste, inadequate waste management facilities and system, explore the effectiveness of such sustainable work and lifestyle changes, utilize real-time monitoring air quality data and future prediction responses for climate change mitigation and adaptation policies as well as consideration towards new green technologies for clean energy in each Southeast Asian country and at regional level. It is anticipated that this study will contribute towards a better understanding of the impacts of COVID-19 on environmental sustainability in the Southeast Asia region, particularly from the perspective of the stakeholders.
Studies have shown that factors like trade, urbanization, and economic growth may increase the ecological footprint (EFP) since ecological distortions are mainly human-induced. Therefore, this study explores the effect of economic growth and urbanization on the EFP, accounting for foreign direct investment and trade in Nigeria, using data from 1977 to 2016. This study used the EFP variable as against the CO2 emissions used in the previous studies since the former is a more comprehensive and extensive measure of environmental quality. We apply the novel dynamic autoregressive distributed lag (ARDL) simulations for model estimation, the Bayer and Hanck J Time Ser Anal 34: 83-95, (2013) combined cointegration, and the ARDL bounds test for cointegration. Although the results affirmed the presence of long-run relationship among the variables, economic growth deteriorates the environment in the short run, while urbanization exacts no harmful impact. In the long run, FDI and trade deteriorate the environment while economic growth adds to environmental quality. It is recommended that policymakers strengthen the existing environmental regulations to curtail harmful trade and provide rural infrastructures to abate urban anomaly.
Palms are highly significant tropical plants. Oil palms produce palm oil, the basic commodity of a highly important industry. Climate change from greenhouse gasses is likely to decrease the ability of palms to survive, irrespective of them providing ecosystem services to communities. Little information about species survival in tropical regions under climate change is available and data on species migration under climate change is important. Palms are particularly significant in Africa: a palm oil industry already exists with Nigeria being the largest producer. Previous work using CLIMEX modelling indicated that Africa will have reduced suitable climate for oil palm in Africa. The current paper employs this modelling to assess how suitable climate for growing oil palm changed in Africa from current time to 2100. An increasing trend in suitable climate from west to east was observed indicating that refuges could be obtained along the African tropical belt. Most countries had reduced suitable climates but others had increased, with Uganda being particularly high. There may be a case for developing future oil palm plantations towards the east of Africa. The information may be usefully applied to other palms. However, it is crucial that any developments will fully adhere to environmental regulations. Future climate change will have severe consequences to oil palm cultivation but there may be scope for eastwards mitigation in Africa.
The study tries to discover the impact of financial and social indicators' growth towards environmental considerations to understand the drivers of economic growth and carbon dioxide emissions change in G7 countries. The DEA-like composite index has been used to examine the tradeoff between financial and social indicator matters in environmental consideration by using a multi-objective goal programming approach. The data from 2008 to 2018 is collected from G-7 countries. The results from the DEA-like composite index reveals that there is a mixed condition of environmental sustainability in G-7 countries where the USA is performing better and Japan is performing worse among the set of other countries. The further result shows that the energy and fiscal indicators help to decrease the dangerous gas emissions. Divergent to that, the human and financial index positively contributes to greenhouse gas emissions. Fostering sustainable development is essential to successfully reduce emissions, meet established objectives, and ensure steady development. The study provides valuable information for policymakers.
Since developing countries experience economic and environmental sustainability challenges, it is desirable digging into the linkages between economic and environmental parameters. The purpose of this work is to evaluate the existence of the environmental Kuznets curve (EKC) theory (i.e., the inverse U-shape connection between real GDP per capita and per capita carbon dioxide emissions) in the sample of 11 developing countries. By using balanced annual panel data in the period between 1992 and 2014 and two alternative estimation techniques, we explored the potential inverted U-shaped linkage between carbon dioxide emissions and real GDP per capita in the sample of interest. For analysis purposes, Pedroni and Westerlund co-integration techniques are employed. Then, fully modified ordinary least squares, pooled mean group methods are applied for long-run parameter estimations. And, the Dumitrescu-Hurlin causality approach is employed for causal directions. Firstly, this work's findings provide the supportive evidence to the inverse U-shaped linkage in the long-run, indicating that an increase in real GDP per capita and electricity consumption tends to mitigate long-run carbon dioxide emissions in the developing countries, for the whole sample. Secondly, the country-specific findings suggested the presence of EKC theory for Brazil, China, India, Malaysia, the Russian Federation, Thailand, and Turkey. It implicated that these countries are on the path of attaining environmental sustainability in the long-run. However, Mexico, Philippines, Indonesia, and South Africa failed to lend credence to the EKC theory. It manifested that these countries need to design strategies directed to reduce carbon dioxide emissions from economic activity and electricity generation through efficiency improvement or promotion of renewables. Finally, bidirectional causal links are observed among all the variables of interest. The findings suggest that country-specific targeted action plans should be implemented to ensure the environmental sustainability in the developing world.
Artemisia arborescens, Artemisia abyssinica, Pulicaria jaubertii, and Pulicaria petiolaris are fragrant herbs traditionally used in medication and as a food seasoning. To date, there are no studies on the use of supercritical fluids extraction with carbon dioxide (SFE-CO2) on these plants. This study evaluates and compares total phenolic content (TPC), antioxidant activity by DPPH• and ABTS•+, antibacterial, and anti-biofilm activities of SFE-CO2 extracts. Extraction was done by SFE-CO2 with 10% ethanol as a co-solvent. A. abyssinica extract had the highest extraction yield (8.9% ± 0.41). The GC/MS analysis of volatile compounds identified 307, 265, 213, and 201compounds in A. abyssinica, A. arborescens, P. jaubertii, and P. petiolaris, respectively. The P. jaubertii extract had the highest TPC (662.46 ± 50.93 mg gallic acid equivalent/g dry extract), antioxidant activity (58.98% ± 0.20), and antioxidant capacity (71.78 ± 1.84 mg Trolox equivalent/g dry extract). The A. abyssinica and P. jaubertii extracts had significantly higher antimicrobial activity and were more effective against Gram-positive bacteria. B. subtilis was the most sensitive bacterium. P. aeruginosa was the most resistant bacterium. P. jaubertii extract had the optimum MIC and MBC (0.4 mg/ml) against B. subtilis. All SFE-CO2 extracts were effective as an anti-biofilm formation for all tested bacteria at 1/2 MIC. Meanwhile, P. jaubertii and P. petiolaris extracts were effective anti-biofilm for most tested bacteria at 1/16 MIC. Overall, the results indicated that the SFE-CO2 extracts of these plants are good sources of TPC, antioxidants, and antibacterial, and they have promising applications in the industrial fields.
One of humanity's most significant problems in the twenty-first century revolves around how to balance the mitigation of environmental pollution while achieving sustainable economic development. Despite increased awareness and dedication to climate change, the planet is still seeing a drastic decrease in the volume of pollutant emissions. This study explores the long-run and causal impact of economic growth, financial development, urbanization, and gross capital formation on Malaysia's CO2 emissions based on the STIRPAT framework. The current paper employs recently developed econometric techniques such as Maki co-integration, auto-regressive distribution lag (ARDL), fully modified OLS (FMOLS), dynamic ordinary least square (DOLS), and wavelet coherence and gradual shift causality tests to investigate these interconnections. The advantage of the gradual shift causality test is that it can capture the causality in the presence of a structural break(s). The findings from the Maki co-integration and ARDL bounds tests reveal evidence of cointegration among the variables. The ARDL test reveals that economic growth, gross capital formation, and urbanization exert a positive impact on CO2 emissions. Furthermore, the wavelet coherence test reveals that there is a significant dependency between CO2 emissions and economic growth, gross capital formation, and urbanization. The Toda Yamamoto and Gradual shift causality tests reveal that there is a (a) unidirectional causality from urbanization to CO2 emissions, (b) unidirectional causality from economic growth to CO2 emissions, and (c) unidirectional causality from gross capital formation to CO2 emissions.