Contamination of toxic metals in P. viridis mussels has been prevalently reported; hence, health risk assessment for consuming this aquaculture product as well as the surrounding surface seawater at its harvesting sites appears relevant. Since Kampung Pasir Puteh, Pasir Gudang is the major harvesting site in Malaysia, and because the last heavy metal assessment was done in 2009, its current status remains unclear. Herein, flame atomic absorption spectrometry and flow injection mercury/hydride system were used to determine the concentrations of Pb, Cd, Cu and total Hg in P. viridis mussels and surface seawater (January-March 2015), respectively. Significantly higher concentrations of these metals were found in P. viridis mussels (p
We investigate the role of military expenditure on emission in USA during the period 1960-2015. To achieve the objectives of this study, two measures of military expenditure are utilised, while several timeseries models are constructed with the gross domestic product (GDP) per capita, population, energy consumption per capita, non-renewable energy consumption per capita, renewable energy consumption per capita, urbanisation, trade openness and financial development serving as additional determinants of air pollution. We also use ecological indicator as an alternative measure of pollution. Moreover, different timeseries methods are utilised including a likelihood-based approach with two structural breaks. The output of this research concluded that all the variables are cointegrated. It is found that military expenditure has mixed impact on CO2 emissions. Real GDP per capita, energy consumption per capita, non-renewable energy consumption per capita, population and urbanisation increase CO2 emissions per capita in the long-run, while renewable energy consumption, financial development and trade openness reduce it. There is also evidence for the mixed role of military expenditure, when ecological footprint is utilised as the environmental degradation index. From the output of this research, few policy recommendations are offered for the examined country.
Earthworms are commonly referred as environmental engineers and their guts are often compared with chemical reactors. However, modeling experiments to substantiate it are lacking. The aim of this study was to use established reactor models, particularly PFR, on the gut of the vermicomposting earthworm Eudrilus eugeniae to understand more on its digestion. To achieve the objective, a mathematical model based on first-order kinetics was framed and used to determine the pattern of digestion rates of nutrient indicators, namely total carbon (%), total nitrogen (%), C/N ratio, 13C (‰), and 15N (‰) at five intersections (pre-intestine, foregut, midgut A, midgut B, and hindgut) along the gut of E. eugeniae. The experimental results revealed that the concentrations of TC, TN, 13C, and 15N decreased during gut transit, whereas C/N ratio increased. The first-order model demonstrated that all the nutrients exhibit a linear pattern of digestion during gut transit, which supports the PFR model. On this basis, the present study concludes that the gut of E. eugeniae functions as PFR.
Economic losses due to health-related implications of air pollution were huge and incurred significant burdens towards healthcare providers. The objective of this study is to systematically review published literature on the financial implications of air pollution on health in Asia. Four databases: PubMed, Scopus, NHS Economic Evaluation Database (NHS EED), and Web of Science (WoS) were used to identify all the relevant articles. It was limited to all articles that had been published in the respected databases from January 2007 until March 2017. Twenty-four articles were included in this review. Five of the 24 studies (20.8%) reported financial implications of air pollution-related disease through value of statistical life (VOSL) which ranged from USD180 million to USD2.2 billion, six (25%) studies used cost of illness (COI) to evaluate air pollution-related morbidity and found that the cost ranged from USD5.4 million to USD9.1 billion. Another six studies (25%) used a combination of VOSL and COI for both mortality and morbidity valuation and found that the financial implications ranging from USD253 million to USD2.9 billion. Thirteen (54.2%) studies reported healthcare cost associated with both hospital admission and outpatient visit, five (20.1%) on hospital admission only, and one (4.2%) on outpatient visit only. Economic impacts of air pollution can be huge with significant deterioration of health among the Asians.
This paper examines the pattern of convergence in electricity intensity in a sample of 79 countries. We apply the residual augmented least squares regression to the convergence of energy intensity. This method has been used in the convergence of per capita energy consumption but not convergence of energy intensity. Furthermore, in contrast to the previous studies which mainly used the conventional beta convergence approach to examine conditional convergence, we use a beta convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma and gamma convergences of electricity intensity are also examined. In addition to the full sample of countries, we also examine convergence in African countries, Asian and Oceanic countries, American countries and European countries, separately. Convergences in OECD and non-OECD countries are also examined, separately. In the full sample, the results show convergence exists in 54% of the countries in the total sample. There is convergence in 65% of the African countries, 61% of the American countries, 43% of the Asian and Oceanic countries and 33% of the European countries. In terms of the regional classification, it is also observed that convergence exists for 58% of the non-OECD countries and 31% of the OECD countries. There is evidence for sigma convergence in all the blocs with the exception of European and non-OECD countries. With the exception of African countries, there is evidence for gamma convergence in all the countries and the various blocs. The policy implications of the results are discussed.
Although plastic induces environmental damages, almost the consumption of poly(vinyl chloride) never stops increasing. Therefore, this work abstracted by two parts, first, synthesis of Schiff bases 1-4 compounds through the reaction of amino group with appropriate aromatic aldehyde, reaction of PVC with Schiff bases compounds 1-4 in THF to form a new modified PVC-1, PVC-2, PVC-3, and PVC-4. The structures of Schiff bases 1-4 and the modified PVC-1, PVC-2, PVC-3, and PVC-4 have been characterized by different spectroscopic analyses. Second, the influence of introducing 4-amino-1,2,4-triazole as a pendent groups into PVC chain investigated on photostability rules of tests. The modified polymers photostability investigated by observing indices (ICO, Ipo, and IOH), weight loss, UV and morphological studies, and all results obtained indicated that PVC-1, PVC-2, PVC-3 and PVC-4 gave lower growth rate of ICO, IPO, and IOH through UV exposure time. The photostability are given as PVC-4
Visible light-responsive Pt-loaded coral-like BiFeO3 (Pt-BFO) nanocomposite at different Pt loadings was synthesized via a two-step hydrothermal synthesis method. The as-synthesized photocatalyst was characterized using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), UV-vis diffuse reflectance spectroscopy (UV-vis DRS), photoluminescence (PL) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, and magnetic hysteresis loop (M-H loop) analyses. The FESEM images revealed that Pt nanoparticles were evenly distributed on the coral-like BFO. The UV-vis DRS results indicated that the addition of Pt dopant modified the optical properties of the BFO. The as-synthesized Pt-BFO nanocomposite was effectively applied for the photodegradation of malachite green (MG) dye under visible light irradiation. Specifically, 0.5 wt% Pt-BFO nanocomposite presented boosted photocatalytic performance than those of the pure BFO and commercial TiO2. Such a remarkably improved photoactivity could be mainly attributed to the formation of good interface between Pt and BFO, which not only boosted the separation efficiency of charge carriers but also possessed great redox ability for significant photocatalytic reaction. Moreover, the strong magnetic property of the Pt-BFO nanocomposite was helpful in the particle separation along with its great recyclability. The radical scavenger test indicated that hole (h+), hydroxyl (·OH) radical, and hydrogen peroxide (H2O2) were the main oxidative species for the Pt-BFO photodegradation of MG. Finally, the Pt-BFO nanocomposite was revealed high antibacterial activity towards Bacillus cereus (B. cereus) and Escherichia coli (E. coli) microorganisms, highlighting its potential photocatalytic and antibacterial properties at different industrial and biomedical applications.
Poor removal of many pharmaceuticals and personal care products in sewage treatment plants leads to their discharge into the receiving waters, where they may cause negative effects for aquatic environment and organisms. In this study, electrochemical removal process has been used as alternative method for removal of mefenamic acid (MEF). For our knowledge, removal of MEF using electrochemical process has not been reported yet. Effects of initial concentration of mefenamic acid, sodium chloride (NaCl), and applied voltage were evaluated for improvement of the efficiency of electrochemical treatment process and to understand how much electric energy was consumed in this process. Removal percentage (R%) was ranged between 44 and 97%, depending on the operating parameters except for 0.1 g NaCl which was 9.1%. Consumption energy was 0.224 Wh/mg after 50 min at 2 mg/L of mefenamic acid, 0.5 g NaCl, and 5 V. High consumption energy (0.433 Wh/mg) was observed using high applied voltage of 7 V. Investigation and elucidation of the transformation products were provided by Bruker software dataAnalysis using liquid chromatography-time of flight mass spectrometry. Seven chlorinated and two non-chlorinated transformation products were investigated after 20 min of electrochemical treatment. However, all transformation products (TPs) were eliminated after 140 min. For the assessment of the toxicity, it was impacted by the formation of transformation products especially between 20 and 60 min then the inhibition percentage of E. coli bacteria was decreased after 80 min to be the lowest value.
Despite being a key Malaysian economic contributor, the oil palm industry generates a large quantity of environmental pollutant known as palm oil mill effluent (POME). Therefore, the need to remediate POME has drawn a mounting interest among environmental scientists. This study has pioneered the application of Meyerozyma guilliermondii with accession number (MH 374161) that was isolated indigenously in accessing its potential to degrade POME. This strain was able to treat POME in shake flask experiments under aerobic condition by utilising POME as a sole source of carbon. However, it has also been shown that the addition of suitable carbon and nitrogen sources has significantly improved the degradation potential of M. guilliermondii. The remediation of POME using this strain resulted in a substantial reduction of chemical oxygen demand (COD) of 72%, total nitrogen of 49.2% removal, ammonical nitrogen of 45.1% removal, total organic carbon of 46.6% removal, phosphate of 60.6% removal, and 92.4% removal of oil and grease after 7 days of treatment period. The strain also exhibited an extracellular lipase activity which promotes better wastewater treatment. Additionally, Fourier transform infrared spectroscopy (FTIR) and gas chromatography-mass spectrometry (GC-MS) analyses have specifically shown that M. guilliermondii strain can degrade hydrocarbons, fatty acids, and phenolic compounds present in the POME. Ultimately, this study has demonstrated that M. guilliermondii which was isolated indigenously exhibits an excellent degrading ability. Therefore, this strain is suitable to be employed in the remediation of POME, contributing to a safe discharge of the effluent into the environment.
Globalization persists the tendency to alter numerous aspects of today's world including religion, transport, language, living styles, and international relations; however, its potential to influence quality of environment is the prime concern for trade and environmental policies guidelines (Audi and Ali 2018). In response to the growing interest for identifying the dynamic relationship between globalization and environmental performance, the present study seeks to investigate the critical link between globalization and ecological footprints in top 15 globalized countries between 1970 and 2016. Applying the novel methods of quantile-on-quantile regression (QQ) and Granger causality in quantiles, the findings examine the manners in which quantiles of globalization affect the quantiles of ecological footprints and vice versa. The empirical results suggest that globalization has a long-term positive effect on ecological footprint and vice versa in case of Belgium, the Netherlands, Sweden, Switzerland, Denmark, Norway, Canada, and Portugal. On the other hand, the estimated results indicate a negative effect between globalization and ecological footprint in the case of France, Germany, the UK, and Hungary. These results extend the recent findings on the globalization-environment nexus implying that the magnitude of relationship among both variables varies with countries demanding individual focus and cautions for postulating environmental and trade policies.
The aim of this work is to convert agroforestry residue to a novel adsorbent (M-1CTA-SDS-BT) used for adsorptive benzene sequestration from aqueous solution. In this study, the anionic surfactant-coated-cationized banana trunk was synthesized and characterized for batch adsorption of benzene from aqueous solution. The surface morphology, surface chemistry, surface area, and pore properties of the synthesized adsorbents were examined. It was proven that surface cationization successfully increased the benzene adsorption capacity of sodium dodecyl sulfate-coated adsorbents. The Langmuir isotherm model satisfactorily described the equilibrium adsorption data. The maximum benzene adsorption capacity (qmax) of 468.19 μmol/g was attained. The kinetic data followed the pseudo-second-order kinetic model in which the rate-limiting step was proven to be the film diffusion. The batch-adsorbent regeneration results indicated that the M-1CTA-SDS-BT could withstand at least five adsorption/desorption cycles without drastic adsorption capacity reduction. The findings demonstrated the adsorptive potential of agroforestry-based adsorbent as a natural and cheap material for benzene removal from contaminated water.
Sustainable urban development has been a popular subject in urban studies and related disciplines. Owing to the challenges faced by cities worldwide to accommodate the growing urban populations, it is becoming ever more important for innovative research on sustainable urban development to be performed to help cities achieve sustainability. This study develops and tests an integrated approach to sustainable city assessment, which is a combination of importance-performance analysis (IPA) and modified analytic hierarchy process (AHP). Questionnaires designed following the IPA concept were distributed to residents of three cities. The importance scores from the collected data were factorized and the factors' relative scores were then calculated using a formula developed in this study to represent pairwise comparisons. The derived criteria weights were applied to the performance scores to evaluate the cities' relative overall sustainability performance. This approach replaces the AHP's 1-9 scale with the IPA's importance rating scale, which is a Likert scale, in the questionnaire. Based on the findings, implications and future research suggestions were provided.
Groundwater is a primary natural water source in the absence of surface water bodies. Groundwater in urban environments experiences unprecedented stress from urban growth, population increase, and industrial activities. This study assessed groundwater quality in terms of arsenic and heavy metal contamination in three industrial areas (Shahdara, Jhilmil, and Patparganj), Delhi, India. The water quality was assessed over a 3-year time interval (i.e., 2015 and 2018). The groundwater constituents investigated were As, Fe, Cr, Cd, Ni, Zn, Mn, Cu, and Pb. Metal index and heavy metal pollution indexes were estimated to assess groundwater pollution. The health risk was evaluated in terms of non-carcinogenic and carcinogenic risk assessment. Patparganj industrial area saw increment in concentration for Cu 0.23 mg/L (2015)-0.85 mg/L (2018), Zn 0.51 mg/L (2015)-7.2 mg/L (2018), Fe 0.32 mg/L (2015)-0.9 mg/L (2018), Cr 0.21 mg/L (2015)-0.26 mg/L (2018), Mn 0.14 mg/L (2015)-0.25 mg/L (2018), Ni 0.04 mg/L (2015)-0.34 mg/L (2018), and As 0.01 mg/L (2015)-0.18 mg/L (2018). Cd and Pb concentrations were observed to decrease by 40-90 % and 85-99% for all the three industrial areas. Metal index and heavy metal index values were found to be >1 for all locations. The risk quotient value > 1 was observed for all locations in the year 2015 but was found to increase further to a range of RQ 10-62 in the year 2018, inferring increased non-carcinogenic risk to consumers. The carcinogenic risk was significant with respect to Fe (0.2-0.7), Zn (0.001-0.007), and As (0.002-0.003) for all locations in the year 2015. This study concludes that groundwater in the three industrial areas is highly polluted and is not fit for human consumption. Further studies are required to explore possible control measures and develop methods to mitigate groundwater pollution, sustainable management, and optimized use to conserve it for future generations.
The study estimates the long-run dynamics of a cleaner environment in promoting the gross domestic product of E7 and G7 countries. The recent study intends to estimate the climate change mitigation factor for a cleaner environment with the GDP of E7 countries and G7 countries from 2010 to 2018. For long-run estimation, second-generation panel data techniques including augmented Dickey-Fuller (ADF), Phillip-Peron technique and fully modified ordinary least square (FMOLS) techniques are applied to draw the long-run inference. The results of the study are robust with VECM technique. The outcomes of the study revealed that climate change mitigation indicators significantly affect the GDP of G7 countries than that of E7 countries. The GDP of both E7 and G7 countries is found depleting due to less clean environment. However, green financing techniques helps to clean the environment and reinforce the confidence of policymakers on the elevation of green economic growth in G7 and E7 countries. Furthermore, study results shown that a 1% rise in green financing index improves the environmental quality by 0.375% in G7 countries, while it purifies 0.3920% environment in E7 countries. There is a need to reduce environmental pollution, shift energy generation sources towards alternative, innovative and green sources.The study also provides different policy implications for the stakeholders guiding to actively promote financial hedging for green financing. So that climate change and envoirnmental pollution reduction could be achieved effectively. The novelty of the study lies in study framework.
Researchers have broadly studied textile waste, but the research topics development and performance trends in this study area are still unclear. A bibliometric analysis was conducted to explore the global scientific literature to determine state of the art on textile waste over the past 16 years. Data of publications output are identified based on the Web of Science (from 2015 to 2020). This study used VOSviewer to analyse collaboration networks among authors, countries, institutions, and author's keywords in identifying five main clusters. A total of 3296 papers in textile waste research were identified. In this study, a total of 10451 authors were involved in textile waste research, and 36 authors among them published more than ten research publications in the period of this study. China has been in a top position in textile waste research moving from 3 output publications in 2005 to 91 output publications in 2020. Indian Institute of Technology System IIT System was ranked first in terms of the total publication number (85 publications, 2.45%). Textile wastewater and adsorption are the most commonly used keywords that reflect the current main research direction in this field and received more attention in recent years. Based on keyword cluster analysis outputs, textile waste research can be categorized into five types of clusters, namely (1) pollutant compositions, (2) component of textile wastewater, (3) treatment methods for textile wastewater, (4) effect mechanism of textile wastewater, and (5) recyclability of textile waste.
The performance of Cu/TiO2/FA composite, a hybrid adsorbent-photocatalyst consisting of copper-doped titania particles supported on fly ash, was optimized, under visible light irradiation, for the removal of the model dye pollutant methyl orange (MO) by using a response surface methodology and Box-Behnken experimental design. Three independent variables were considered for the optimization study: catalyst/solvent dosage (0.5 - 2.0 g/L), irradiation time (30-120 min), and the initial concentration (5- 25 ppm) of the dye. A 99.91% rate of removal was achieved using 2 g/L dosage, 5 ppm initial concentration, and 100 min of irradiation time as the optimal operating conditions. The recorded trends support the hypothesis of a combined and synergic adsorption-photocatalytic degradation process which fully exploits the "capture and destroy" approach for pollutant removal.
Climate change caused by different anthropogenic activities is a subject of attention globally. There is a concern on how to maintain a clean environment and at the same time achieve optimal use of land. To this end, this study examines the causal effects of land use including agricultural, forestry, and other land categories on greenhouse gas (GHG) emissions. The data for China is collected over the period 1990 to 2012 for the empirical examination. By employing vector error correction model (VECM), it is found that there is significant long-run causality among variables. However, in the short run expectedly, only land under agriculture has strong causality with the GHG emissions. The results in case of variance decomposition analysis highlight that land under agriculture and other use significantly causes the GHG emissions in the long run. Further, impulse responses of variables are also measured with the Cholesky one standard deviation. The results are robust and support the argument that different land uses cause GHG emissions in China. The study provides insights for policy makers to improve the activities occurring on agricultural and other land uses. Assessment of overall potential, including bio energy, needs to include analysis of trade-offs and feedbacks with land-use competition. Many positive linkages with sustainable development and with adaptation exist but are case and site specific as they depend on scale, scope, and pace of implementation.
The aim of this review is to highlight and provide an update on the current development of pesticide remediation methods, focusing on the utilization of different cyclodextrin (CD) molecules. Because of less environmental impact and non-toxic nature, CDs are beneficial for pesticide remediation, reducing environmental risk and health hazards. They are advantageous for the removal of pesticides from contaminated areas, as well as for better pesticide formulation and, posing significant effects on the hydrolysis or degradation of pesticides. The review focuses on the current trend and innovations regarding the methods and strategies employed for using CDs in designing pesticide remediation. Nowadays, in addition to the conventional experimental techniques, molecular simulation approaches are significantly contributing to the study of such phenomena and hence are recognized as a widely used tool.
Energy efficiency (EE) is an evolving research aspect for researchers, businesses, and policymakers for its undeniable role in meeting increasing energy demand, reducing CO2 emissions, and tackling climate change. This paper provides a review of the current state of EE research by mapping the research landscape in business and economics to understand the socioeconomic dimensions within these research areas. To identify key information, we examine the trends and characteristics of 2935 relevant scientific publications over a 30-year period from 1990 to 2019 in the Social Science Citation Index of the Web of Science database using bibliometric analysis with a R language package called 'bibliometrix'. Our analysis shows an increasing trend in publications from 2006 onwards; the period remarkably coincides with the implementation phase of the Kyoto protocol in 2005. Accordingly, we observe that EE research has a strong association with issues like CO2 emissions, climate change, sustainability, and the growing importance of these issues in recent years. Thus, our findings provide crucial understandings by incorporating a wide array of scientific outputs in response to calls for greater theoretical clarification of EE research. These findings provide insights into the current state of the art of, and identify crucial areas for future, research. Hence, our research assists in formulating environmentally sustainable policies to tackle the adverse effects of CO2 emissions and related climate change through providing critical grasps on the scholarly development related to EE.
The investigation of sediment transport in tropical rivers is essential for planning effective integrated river basin management to predict the changes in rivers. The characteristics of rivers and sediment in the tropical region are different compared to those of the rivers in Europe and the USA, where the median sediment size tends to be much more refined. The origins of the rivers are mainly tropical forests. Due to the complexity of determining sediment transport, many sediment transport equations were recommended in the literature. However, the accuracy of the prediction results remains low, particularly for the tropical rivers. The majority of the existing equations were developed using multiple non-linear regression (MNLR). Machine learning has recently been the method of choice to increase model prediction accuracy in complex hydrological problems. Compared to the conventional MNLR method, machine learning algorithms have advanced and can produce a useful prediction model. In this research, three machine learning models, namely evolutionary polynomial regression (EPR), multi-gene genetic programming (MGGP) and M5 tree model (M5P), were implemented to model sediment transport for rivers in Malaysia. The formulated variables for the prediction model were originated from the revised equations reported in the relevant literature for Malaysian rivers. Among the three machine learning models, in terms of different statistical measurement criteria, EPR gives the best prediction model, followed by MGGP and M5P. Machine learning is excellent at improving the prediction distribution of high data values but lacks accuracy compared to observations of lower data values. These results indicate that further study needs to be done to improve the machine learning model's accuracy to predict sediment transport.