Very little work has determined the relative importance of uncontrolled environmental factors for affecting fish biology, and how these might influence gillnet catches. This study addresses this deficit for an important Southeast Asian cyprinid (Barbonymus schwanenfeldii). Fish were caught monthly for 12 months using gillnets of three different mesh sizes, each of which was deployed in duplicate at the surface of one of three randomly selected sites in Lake Kenyir, Malaysia, concurrent with determining various environmental parameters and the abundance of phytoplankton (chlorophyll-a). Results indicated that growth co-efficient of B. schwanenfeldii was positively influenced by dissolved oxygen and negatively influenced by total inorganic nitrogen, whereas an opposite result was observed in case of the hepatosomatic index of fish. Water turbidity was a limiting factor only for small fish (mean total length: 15.74±1.10 cm). B. schwanenfeldii could best be caught during the period of high phytoplankton abundance or at the location of high phytoplankton density in the water. Water temperature negatively influenced the gillnet catches of the fish. The remaining environmental factors such as water depth, pH, and phosphate had a weak and insignificant influence (P >0.05) on the biology and gillnet catches of fish. The observed results can be very useful for the ecological monitoring and conservation plans for this species in relation to climate change. Furthermore, the utility of the similar data for other species would be useful not only for regional but also for international fishery by optimizing catches considering environmental conditions.
The aim of this paper is to examine immigration and environmental degradation using bibliometric analysis. This paper also analyzes sources of publication, authorship, citations, distributions publications and other bibliometric indicators. The study focuses on a total of 1372 articles published from 2000 to 2020. These articles were collected through an automated process from the Scopus database and later analyzed using techniques such as bibliometric indicators analysis, VOSviewer, and Perish or Publish. The research identified 991 articles from varieties of published sources. The topic of immigrants and environmental degradation has been an emerging topic since 1981. Starting in 2000, most of the scholars actively producing an articles pertinent to this topic. Most of the articles were published in journals, and English is the primary language of research. United States is the leading country in contributing the publications. Meanwhile, the most significant fields in which the sources were produced were environmental science, agricultural and biological sciences, arts and humanities and earth and planetary sciences. However, some limitations has been found. It has been suggested for future research, to lengthen this work to other databases, as well as bibliometric analyses of immigration and environmental degradation in developed and developing countries by adding a new keyword such as energy consumption and climate change. This paper aims to assess recent trends in the expansion of academic literature on immigration and environmental degradation using the bibliometric analysis method. Network visualization and bibliometric indicators are used in this paper to present the results.
Roads play a pivotal role in the overall economic growth of any country. Developed countries allocated sufficient budget to make new roads and to maintain the existing roads. They also have a proper pavement management system (PMS) in practice to manage roads, whereas developing countries suffer from budgetary issues to make new roads and maintain the existing road network. Therefore, this paper explores the awareness of PMS via direct and indirect methods in Pakistan with a proposed framework of the low-cost model and pavement maintenance indicators for developing countries. This paper also performs a scientometric assessment of PMS. A detailed literature review has been carried out for this study, followed by a quantitative study from experienced professionals. The scientometric data is collected from the Scopus database from 1975 to 2020, whereas the data for PMS awareness assessment has been collected using questionnaires from different experts working directly and indirectly in the road management sector. The data has been analyzed using the arithmetic mean because of the nature of the questions and scope of the study. The direct method results show that experts are aware of PMS for a new road, but they have no PMS to rehabilitate roads. The indirect method results show that the authorities are applying various components of PMS, but there is no proper PMS in practice. This paper helps decision-makers to make better decisions and policies for improved road maintenance and rehabilitation. The proposed framework in the study can significantly assist the UN-SDG 9 (Facilitate Sustainable Infrastructure in Developing Countries) and 11 (Affordable and Sustainable Transport System).
Cellulosic fiber (CF) in nanoform is emergingly finding its way for COVID-19 solution for instance via nanocomposite/nanoparticle from various abundant biopolymeric waste materials, which may not be widely commercialized when the pandemic strikes recently. The possibility is wide open but needs proper collection of knowledge and research data. Thus, this article firstly reviews CF produced from various lignocellulosic or biomass feedstocks' pretreatment methods in various nanoforms or nanocomposites, also serving together with metal oxide (MeO) antimicrobial agents having certain analytical reporting. CF-MeO hybrid product can be a great option for COVID-19 antimicrobial resistant environment to be proposed considering the long-established CF and MeO laboratory investigations. Secondly, a preliminary pH investigation of 7 to 12 on zinc oxide synthesis discussing on Fouriertransform infrared spectroscopy (FTIR) functional groups and scanning electron microscope (SEM) images are also presented, justifying the knowledge requirement for future stable nanocomposite formulation. In addition to that, recent precursors suitable for zinc oxide nanoparticle synthesis with emergingly prediction to serve as COVID-19 purposes via different products, aligning with CFs or nanocellulose for industrial applications are also reviewed.
In this study, palm oil mill effluent (POME) treated by ultrasonication at optimum conditions (sonication power: 0.88 W/mL, sonication duration: 16.2 min and total solids: 6% w/v) obtained from a previous study was anaerobically digested at different hydraulic retention times (HRTs). The reactor biomass was subjected to metagenomic study to investigate the impact on the anaerobic community dynamics. Experiments were conducted in two 5 L continuously stirred fill-and-draw reactors R1 and R2 operated at 30 ± 2 °C. Reactor R1 serving as control reactor was fed with unsonicated POME with HRT of 15 and 20 days (R1-15 and R1-20), whereas reactor R2 was fed with sonicated POME with the same HRTs (R2-15 and R2-20). The most distinct archaea community shift was observed among Methanosaeta (R1-15: 26.6%, R2-15: 34.4%) and Methanobacterium (R1-15: 7.4%, R2-15: 3.2%). The genus Methanosaeta was identified from all reactors with the highest abundance from the reactors R2. Mean daily biogas production was 6.79 L from R2-15 and 4.5 L from R1-15, with relative methane gas abundance of 85% and 73%, respectively. Knowledge of anaerobic community dynamics allows process optimization for maximum biogas production.
Rapid progress of industrial development, urbanization and traffic has caused air quality reduction that negatively affects human health and environmental sustainability, especially among developed countries. Numerous studies on the development of air quality forecasting model using machine learning have been conducted to control air pollution. As such, there are significant numbers of reviews on the application of machine learning in air quality forecasting. Shallow architectures of machine learning exhibit several limitations and yield lower forecasting accuracy than deep learning architecture. Deep learning is a new technology in computational intelligence; thus, its application in air quality forecasting is still limited. This study aims to investigate the deep learning applications in time series air quality forecasting. Owing to this, literature search is conducted thoroughly from all scientific databases to avoid unnecessary clutter. This study summarizes and discusses different types of deep learning algorithms applied in air quality forecasting, including the theoretical backgrounds, hyperparameters, applications and limitations. Hybrid deep learning with data decomposition, optimization algorithm and spatiotemporal models are also presented to highlight those techniques' effectiveness in tackling the drawbacks of individual deep learning models. It is clearly stated that hybrid deep learning was able to forecast future air quality with higher accuracy than individual models. At the end of the study, some possible research directions are suggested for future model development. The main objective of this review study is to provide a comprehensive literature summary of deep learning applications in time series air quality forecasting that may benefit interested researchers for subsequent research.
Non-point source (NPS) pollution has become a vital contaminant source affecting the water environment because of its wide distribution, hydrodynamic complexity, and difficulty in prevention and control. In this study, the identification and evaluation of NPS pollution risk based on landscape pattern were carried out in the Hanjiang River basin above Ankang hydrological section, Shaanxi province, China. Landscape distribution information was obtained through land use data, analyzing the contribution of "source-sink" landscape to NPS pollution through the location-weighted landscape contrast index. Using the NPS pollution risk index to identify and evaluate the regional NPS pollution risk considering the slope, cost distance, soil erosion, and precipitation erosion affect migration of pollutants. The results showed that (i) the pollution risk was generally high in the whole watershed, and the sub-watersheds dominated by "source" landscapes account for 74.61% of the whole basin; (ii) the high-risk areas were distributed in the central, eastern, and western regions of the river basin; the extremely high-risk areas accounted for 12.7% of the whole watershed; and the southern and northern regions were dominated by forestland and grassland with little pollution risk; (iii) "source" landscapes were mostly distributed in areas close to the river course, which had a great impact on environment, and the landscape pattern units near the water body needed to be further adjusted to reduce the influence of NPS pollution.
Many advanced technologies have shown encouraging results in removing antibiotics from domestic wastewater. However, as activated sludge treatment is the most common sewage treatment system employed worldwide, improving its effect on antibiotic removal would be more desirable. Understanding the removal mechanisms, kinetics and factors that affect antibiotic removal in the activated sludge process is important as it would allow us to improve the treatment performance. Although these have been discussed in various literature covering different types of antibiotics and wastewater, a specific review on antibiotics and domestic wastewater is clearly missing. This review paper collates, discusses and analyses the removal of antibiotics from sewage in the activated sludge process along with the removal mechanisms and kinetics. The antibiotics are categorised into six classes: β-lactam, dihydrofolate reductase inhibitor, fluoroquinolone, macrolide, sulfonamides and tetracycline. Furthermore, the factors affecting the system performance with regard to antibiotic removal are examined.
Despite the nutritional benefits, bivalves like mussels are also an excellent aquatic heavy metal biomonitoring agent due to their high tolerance to varying levels of temperature, salinity and oxygen, as well as pollutants. Although the accumulated toxic heavy metals may not exert direct negative impacts on the mussels, such toxicants in mussel tissues can give harmful effects on human body when consumed in toxic quantities and/or over prolonged period. The booming of urban and industrial activities, and consequently the increment of runoffs, as well as wastewater effluents and leaching, further exacerbated the magnitude of this issue. Hence, continuous monitoring of heavy metal contents in mussels is vital to ensure its compliance with food safety regulations, protecting consumers at large. This review paper discusses the occurrence of heavy metals in mussels especially that of Perna viridis in Malaysia and other parts of the world since year 2000 until 2021. Heavy metal concentration data and patterns from various coastal and/or estuaries were compared. Where applicable, statistical data that indicate variations between sampling sites, sampling months or years and chemical treatments for heavy metal removal were critically reviewed. Health risk assessment findings were also discussed. More importantly, related chemical-based interventions to minimize and/or eliminate toxic heavy metals from mussels are also reviewed.
Although firms increasingly publish sustainability reports, assuring such reports is relatively new. This study reviews the literature of sustainability assurance to evaluate the intellectual development of the field and provide recommendations for future studies. It also demonstrates the role of assurance to enhance the credibility of sustainability reports and corporate reputation. This paper systematically reviews 94 papers obtained from the Scopus database between 1993 and August 2021. Our study shows that there is an increase in the number of studies published in recent years. We also found that some countries have received limited attention, such as the USA. The scant literature examining sustainability assurance in private institutions and non-profit organisations should be reinforced. Likewise, the sustainability research also provides limited evidence on the governance debate. The vast majority of research is not based on theoretical grounds. The need for assurance of sustainability reports not only enhances the reputation but also adds more value to the organisation's planning, monitoring, and accountability. We highlight several new research suggestions that may enhance the understanding of sustainability assurance practices.
In exploring the application of natural coagulants in industrial wastewater treatment, plant-based coagulants have been gaining more interests due to their potential such as biodegradability and easy availability. Hylocereus undatus foliage as a plant-based coagulant has been proven to be efficient during the coagulation-flocculation process; however, limited research has been reported focusing only on palm oil mill effluent (POME) and latex concentrate wastewater. In addition, no previous study has been carried out to determine the performance evaluation of Hylocereus undatus foliage in treating different types of wastewater incorporating different operating conditions using optimization techniques. Hence, this study employed response surface methodology (RSM) in an attempt to determine the performance evaluation of the coagulant in paint wastewater treatment. Four independent factors such as the pH value, coagulant dosage, rapid mixing speed and temperature were chosen as the operating conditions. Three water parameters such as turbidity, chemical oxygen demand (COD) and suspended solids (SS) were chosen as responses in this study. Results revealed that through central composite design (CCD) via Design Expert software, the optimum conditions were achieved at pH 5, coagulant dosage of 300 mg/L, rapid mixing speed of 120 rpm and temperature at 30 °C. The experimental data was observed to be close to the model predictions with the optimum turbidity, COD and SS removal efficiencies found to be at 62.81%, 59.57% and 57.23%, respectively.
This paper investigates the effect of different categories of essential COVID-19 data from 2020 to 2021 towards stock price dynamics and options markets. It applied the hypothetical method in which investors develop depression based on the understanding suggested by various green finance divisions. Furthermore, additional elements like panic, sentiment, and social networking sites may impact the attitude, size, and direction of green finance, subsequently impacting the security prices. We created new emotion proxies based on five groups of information, namely COVID-19, marketplace, lockdown, banking sector, and government relief using Google search data. The results show that (1) if the proportional number of traders' conduct exceeds the stock market, the effect of sentimentality indexes on jump volatility is expected to change; (2) the volatility index component jump radically increases with the COVID-19 index, city and market lockdown index, and banking index; and (3) expanding the COVID-19 index gives rise to the stock market index. Moreover, all indexes decreased in jump volatility but only after 5 days. These findings comply with the hypotheses proposed by our model.
Bioretention systems are among the most popular stormwater best management practices (BMPs) for urban runoff treatment. Studies on plant performance using bioretention systems have been conducted, especially in developed countries with a temperate climate, such as the USA and Australia. However, these results might not be applicable in developing countries with tropical climates due to the different rainfall regimes and the strength of runoff pollutants. Thus, this study focuses on the performance of tropical plants in treating urban runoff polluted with greywater using a bioretention system. Ten different tropical plant species were triplicated and planted in 30 mesocosms with two control mesocosms without vegetation. One-way ANOVA was used to analyze the performance of plants, which were then ranked based on their performance in removing pollutants using the total score obtained for each water quality test. Results showed that vetiver topped the table with 86.4% of total nitrogen (TN) removal, 93.5% of total phosphorus (TP) removal, 89.8% of biological oxygen demand (BOD) removal, 90% of total suspended solids (TSS) removal, and 92.5% of chemical oxygen demand (COD) removal followed by blue porterweed, Hibiscus, golden trumpet, and tall sedge which can be recommended to be employed in future bioretention studies.
There are many advantages of geothermal energy, as an environmental friend resource. This heat radiation emanating from beneath the earth's surface presents man with good opportunities to harness it and makes a good level of agricultural food production and its processing in the EU region. The primary objective of this research is to examine the impact of geothermal energy on agri-food supply among the 27 European countries (EU27), within the time frame 1990 to 2021. The study adopted the autoregressive distributed lag (ARDL), and the findings from this study revealed that agri-food supply can increase significantly among the 13 European countries (EU13 emerging economies), leveraging on geothermal energy and economic growth variables than in the EU14 emerged economies. Furthermore, the outcome of this study showed that there could be a significant decrease in the food products coming from agricultural practices among the 13 European countries (EU13 emerging economies), due to an ineffective population density than in EU14 emerged economies. Furthermore, fossil fuel and institutional quality contribute more positively to the agri-food supply in the EU14 emerged economies than in the EU13 emerging economies. This results in an outcome that means that the agri-food supply among the EU13 emerging economies could be greatly boosted by replacing fossil fuel consumption with geothermal energy, and this facilitates the attainment of the European energy goals by the year 2030. Substituting fossil fuels with geothermal will also assist in minimizing the risks of environmental pollution and climate change. All projected calculations were seen as valid in this study, and this was confirmed by the three estimators adopted which are the pooled mean group, the mean group, and the dynamic fixed effect. This study, therefore, recommends that the 27 European countries should lay more emphasis on geothermal energy production as this will help in ensuring food security in the region. Policymakers and other government authorities as well as local and foreign investors should make more investments in geothermal energy resources as this study has proven that this will lead to agri-food security and sustainability. Not only this, it will as well curb the incidence of climate change and environmental pollution.
Businesses are becoming more conscious of operational risk management practices due to the COVID-19 pandemic. However, some firms practice risk management without fully comprehending how it might help them and their needs. As a result, companies that practice risk management without realizing it are being controlled by the discipline itself. The goal of this study is to look into the epistemic process of risk management practice in the workplace. This phenomenological study interviewed 39 risk management officers, executives, and employees. Data are thematically analyzed. This study discovered five epistemic processes of risk mapping using Foucault's governmentality paradigm. This phenomenological study, interestingly, revealed the black box of risk management practices, as well as the behavior of risk management officers, executives, and risk owners who preferred to monitor the compliance aspects of risk management practices rather than comprehend the capabilities of risk management that could be used within their strategic planning process. Unaware of this black box, organizational actors were blanketed by the organization's culture of fear, which created the impression that the authority was always watching every word said and every action taken. Practically, this study contributes an improved understanding of the real function of risk management that helps them justify the practice and reduce unnecessary fear. The paper concludes with limitations and research recommendations.
This paper empirically examines the effects of energy, natural resources, agriculture, political constraint and regional integration on CO2 emissions in four ASEAN (Association of Southeast Asian Nations) countries of Cambodia, Malaysia, Indonesia and Thailand. We distinguish between renewable and fossil fuel energy consumption to see their individual impacts on CO2 emissions. The study employed a panel data from 1990 to 2019 derived from sources such as World Development Indicators, which were then analysed using Common-Correlated Effect Mean Group (CCEMG) and Augmented Mean Group (AMG) estimates. The findings show that renewable energy consumption has a negative impact on CO2 emissions while fossil fuel energy degrades the environment. The role of natural resources was found to be favourable for environmental quality with the impact of agriculture being found to be detrimental. For regional trade integration, its influence was not significant enough to offset CO2 emission. Furthermore, we discovered that political constraint induces CO2 emission. Based on the result, it is recommended that the selected ASEAN countries promote the use of renewable energy and clean technologies in their manufacturing processes, conserve natural resources, adopt eco-friendly political policies and intensify regional integration to accelerate the achievement of the SDGs.
Solar cells are considered one of the most important and widespread solar applications in the world. However, the performance of the PV modules is significantly affected by the dust in the air. This paper, therefore, presents a comparison of an outdoor experimental study of dust effect on monocrystalline, and polycrystalline photovoltaic (PV) modules. For analysis, four 100 W PVs were installed horizontally in Sohar, Oman. For each pair of PV modules, one was left dusty due to environmental impact, and the second was cleaned daily. PV performance and environmental parameter measurements were conducted every 30 min for 35 days. The effects of dust on current, voltage, power, and energy were discussed in terms of time and normalized values. Also, cleaning methods were tested to determine the optimum one. It is found that power degradation of monocrystalline (20%) is higher compared with polycrystalline (12%) due to dust accumulation. For monocrystalline, the current, voltage, and power losses ranged between 10.0-24.0%, 2.0-3.5%, and 14.0-31.0%, respectively. However, for polycrystalline, the degradation rates were 16.88-27.92%, 0.455-0.455%, and 17.14-28.1% for current, voltage, and power losses after exposure to outdoor conditions for the same period, respectively. The dust accumulation on the PV surface found after 5 weeks is 0.493 mg/cm2, which can be considered the lowest accumulation rate compared to other Gulf countries, but which, however, leads to less energy degradation as well. It is found that water is sufficient to clean PV in the study area. However, sodium detergent as a cleaner introduced better results compared to water, especially when there is high pollution in the location.
Mostly, the product manufacturer and activities related to transportation have a greater influence on the supply chain and the environment. Hence, the green investment in water, biodiversity protection, waste treatment, resources, and climate change alleviation help in enhancing industrial production. Thus, for the enhancement of green growth, the industries must adopt green financing by making investments in ecology, climate change, and carbon reduction. Despite having the greatest growth in green supply chain management, still, the implementations of greening the product and processes have not been seen properly in many industries. A bibliometric analysis was conducted through VOS viewer version 1.6.7. of last twenty years (2001-2021). A total of 2385 articles were retrieved from the Scopus database. The results revealed that China, India, Iran, and Taiwan have a vast collection of articles and have very strong international collaborations. The most cited authors were Sarkis, J., Zhu, Q., and Khan, S.A.R. The results also suggest that green supply chain management research was related to the field of engineering, environmental science, energy sciences, social sciences, and business management. Some new areas are discovered like green innovation, green information technology, green productivity, corporate environmental responsibility, green investments, green credit, and green credit policy. As evidenced from our bibliographic database search, it is observed that integrated work on green supply chain management and green finance is limited, and this makes this research work to be novel. This study is beneficial for credit managers and policymakers.
COVID-19 has affected the pursuit of sustainable development in multifaceted ways; this study investigates Malaysian Gen Z perceptions of the COVID-19 pandemics' disruptions to sustainable development. The exploratory research began with brainstorming from Malaysian Gen Z individuals with the following excerpt, 'The COVID-19 pandemic has disrupted the world and led to unprecedented change. How do you believe this has impacted either positively or negatively, the global pursuit of sustainable development?' Ninety-eight unique statements were generated with subsequent participants sorting these statements into thematic groups before rating each of them on impact and duration. Subsequently, multi-dimensional scaling and cluster analysis was performed with eight-cluster solution being proposed. This study suggests that the pandemic has contributed both positively and negatively to sustainable development, while also highlighting the duration of these impacts. This community-based participatory research provides a guide for policy to mitigate negative impacts whilst also attempting to fully realise the positive impacts in response to managing the unprecedented effects of the pandemic.