Carcinoscorpius rotundicauda and Tachypleus gigas may co-exist and share common spawning grounds elsewhere but at Balok (East Coast of Peninsular Malaysia), C. rotundicauda is an understudied species. Neglected as research candidate because of inaccessible spawning grounds, smaller size and less commercial value than T. gigas and also, difficulty to attain from the wild has made C. rotundicauda population status remaining unidentified at Balok. This standpoint drove the present attempt because anthropic activities like structure placement and mining are point-source for runoffs that load sediments into Balok River. While erosion-accretion events have altered Balok River width, the shore sediments in Balok Beach were transitioned between medium-fine and fine sand between years 2012 and 2016. Eventually by year 2016, the C. rotundicauda were depositing 5117 eggs in 91 nests from 200 to 1000 m range along this corridor facing South China Sea. From this yield, C. rotundicauda released 2880 eggs in 56 nests during the Southwest monsoon, 1254 eggs in 19 nests during the Northeast monsoon and 983 eggs in 16 nests during the Inter-monsoon seasons. Though female C. rotundicauda opted to lay their eggs in shallow burrows at lower shorelines, the absence of erosion and substantial silt and clay (>20%) deposition facilitates C. rotundicauda embryogenesis with brief periods of temperature and salinity shocks during day-time falling tides. This encourages C. rotundicauda to emerge with increasing abundance and carry out bi-monthly spawning at Balok Beach. In short, shore restoration initiatives like systematic boat docking, proper disposal of nets and waste and, periodic fish-catching operations were effectively led by the Balok fisher citizen scientist. This successful community joint-cooperation proves that citizen-led caretaking of degraded beaches offers marine life protection and are practical for coastal area management especially at areas where other oviparous animals such as turtles and crocodiles are harboured.
The water reservoirs are getting polluted due to increasing amounts of micropollutants such as pharmaceuticals, organic polymers and suspended solids. Powdered activated carbon (PAC) has been proved to be a promising solution for the purification of water without having harmful impacts on the environment. Parameters such as PAC dosing, wastewater hardness, the effect of coagulant and flocculant were evaluated in a batch scale study. These parameters were further applied on a pilot plant scale for the performance evaluation of PAC based removal of micropollutants concerning the contact time and PAC dosing with main focus on recirculation of PAC sludge. The obtained optimum dose was 10-20 mg/L providing 84.40-91.30% removal efficiency of suspended solid micropollutants (MPs) and this efficiency increased to 88.90-93.00% along with coagulant which further raised by the addition of polymer and recirculation process at batch scale. On pilot plant scale, the concentration in contact reactor and PAC removal effectiveness of dissolved air flotation, lamella separator and sedimentation tank were compared. Constant optimisation resulted in a concentration ranging from 2.70 to 3.40 g/L at dosing of PAC 10 mg/L, coagulant 2.00 mg/L and polymer 0.50 mg/L. PAC doses of 10-20 mg/L with 15-30 min contact time proved best for above 70-80% elimination. The recirculation system has also proved an efficient technique because the PAC's adsorption capacity was practically completely used. Small PAC dosages yielded high micropollutants elimination.
The emergence of the aluminium recycling industry has led to an increase in aluminium-containing wastewater discharge to the environment. Biological treatment of metal is one of the solutions that can be provided as green technology. Screening tests showed that Brochothrix thermosphacta and Vibrio alginolyticus have the potential to remove aluminium from wastewater. Brochothrix thermosphacta removed up to 49.60%, while Vibrio alginolyticus was capable of removing up to 59.72% of 100 mg/L aluminium in acidic conditions. The removal of aluminium by V. alginolyticus was well fitted with pseudo-first-order kinetics (k1 = 0.01796/min), while B. thermosphacta showed pseudo-second-order kinetics (k2 = 0.125612 mg substrate/g adsorbent. hr) in the process of aluminium removal. V. alginolyticus had a higher rate constant under acidic conditions, while B. thermosphacta had a higher rate constant under neutral pH conditions.
The exponential growth of waste generation is posing serious environmental issues and thus requires urgent management and recycling action to achieve green sustainable development. Controlled low-strength material (CLSM) is a highly flowable cementitious backfill material with self-consolidating properties. The CLSM efficiency during construction and final performance at the site depends on its plastic properties. Plastic properties are responsible for workability, pumpability, stability, and lateral pressure on adjacent soils. This paper presents a critical review to date on the use of waste materials and/or by-products and their impacts on the plastic properties of the CLSM. Extensive previous studies demonstrated that the basic properties and content of waste materials as well as the amount of water in the mix design, play a dominant role in determining the plastic properties of CLSM. The discussed plastic properties of CLSM include flowability, bleeding, segregation, and hardening time, which are found to be inter-related. Proper mix design adjustment to accommodate the use of waste materials is possible to produce sustainable CLSM with acceptable plastic properties. Additionally, the discussion and analysis presented in this paper could provide a basis for future research advances and the development of sustainable CLSM prepared with waste materials.
A continuous increase in the amount of greenhouse gases (GHGs) is causing serious threats to the environment and life on the earth, and CO2 is one of the major candidates. Reducing the excess CO2 by converting into industrial products could be beneficial for the environment and also boost up industrial growth. In particular, the conversion of CO2 into methanol is very beneficial as it is cheaper to produce from biomass, less inflammable, and advantageous to many industries. Application of various plants, algae, and microbial enzymes to recycle the CO2 and using these enzymes separately along with CO2-phillic materials and chemicals can be a sustainable solution to reduce the global carbon footprint. Materials such as MOFs, porphyrins, and nanomaterials are also used widely for CO2 absorption and conversion into methanol. Thus, a combination of enzymes and materials which convert the CO2 into methanol could energize the CO2 utilization. The CO2 to methanol conversion utilizes carbon better than the conventional syngas and the reaction yields fewer by-products. The methanol produced can further be utilized as a clean-burning fuel, in pharmaceuticals, automobiles and as a general solvent in various industries etc. This makes methanol an ideal fuel in comparison to the conventional petroleum-based ones and it is advantageous for a safer and cleaner environment. In this review article, various aspects of the circular economy with the present scenario of environmental crisis will also be considered for large-scale sustainable biorefinery of methanol production from atmospheric CO2.
Climate extremes have a significant impact on vegetation. However, little is known about vegetation response to climatic extremes in Bangladesh. The association of Normalized Difference Vegetation Index (NDVI) with nine extreme precipitation and temperature indices was evaluated to identify the nexus between vegetation and climatic extremes and their associations in Bangladesh for the period 1986-2017. Moreover, detrended fluctuation analysis (DFA) and Morlet wavelet analysis (MWA) were employed to evaluate the possible future trends and decipher the existing periodic cycles, respectively in the time series of NDVI and climate extremes. Besides, atmospheric variables of ECMWF ERA5 were used to examine the casual circulation mechanism responsible for climatic extremes of Bangladesh. The results revealed that the monthly NDVI is positively associated with extreme rainfall with spatiotemporal heterogeneity. Warm temperature indices showed a significant negative association with NDVI on the seasonal scale, while precipitation and cold temperature extremes showed a positive association with yearly NDVI. The DEA revealed a continuous increase in temperature extreme in the future, while no change in precipitation extremes. NDVI also revealed a significant association with extreme temperature indices with a time lag of one month and with precipitation extreme without time lag. Spatial analysis indicated insensitivity of marshy vegetation type to climate extremes in winter. The study revealed that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and low solar radiation with higher humidity contributed to climatic extremes in Bangladesh. The nexus between NDVI and climatic extremes established in this study indicated that increasing warm temperature extremes due to global warming might have severe implications on Bangladesh's ecology and the environment in the future.
Polyelectrolyte composite nanospheres are relatively new adsorbents which have attracted much attention for their efficient pollutant removal and reuse performance. A novel polyelectrolyte nanosphere with magnetic function (SA@AM) was synthesized via the electrostatic reaction between the polyanionic sodium alginate (SA) and the surface of a prepared terminal amino-based magnetic nanoparticles (AMs). SA@AM showed a size of 15-22 nm with 6.85 emu·g-1 of magnetization value, exhibiting a high adsorption capacity on Pb(II) ions representing a common heavy metal pollutant, with a maximum adsorption capacity of 105.8 mg g-1. The Langmuir isotherm adsorption fits the adsorption curve, indicating uniform adsorption of Pb(II) on the SA@AM surfaces. Repeated adsorption desorption experiments showed that the removal ratio of Pb(II) by SA@AM was more than 76%, illustrating improved regeneration performance. These results provide useful information for the production of bio-based green magnetic nano scale adsorption materials for environmental remediation applications.
Community-based monitoring is increasingly recognised as one solution to sustainable environmental management. However, the development of community-based monitoring has led to confusion or misconceptions regarding other similar initiatives. Through a review of the characteristics and synthesising criteria of effective community-based monitoring, this article addresses how to distinguish community-based monitoring from other forms of community engagement research. A review of relevant community-based monitoring literature identifies the characteristics of and knowledge gaps in procedures and governance structures. Additionally, evidence of common benefits, challenges and lessons learned for successful community-based monitoring are deliberated. As an outcome of the review, the article synthesises a set of community-based monitoring criteria as follows: (1) efficacy of initiatives, (2) technicality aspects, (3) feedback mechanisms and (4) sustainability. These synthesised criteria will be instrumental in designing customised community-based monitoring initiatives for environmental sustainability.
We aim at fabricating a ternary magnetic recyclable Bi2WO6/BiOI@Fe3O4 composite that could be applied for photodegradation of tetracycline (TC) from synthetic wastewater. To identify any changes with respect to the composite's morphology and crystal structure properties, ΧRD, FTIR, FESEM-EDS, PL and VSM analyses are carried out. The effects of Fe3O4 loading ratio on the Bi2WO6/BiOI for TC photodegradation are evaluated, while operational parameters such as pH, reaction time, TC concentration, and photocatalyst's dose are optimized. Removal mechanisms of the TC by the composite and its photodegradation pathways are elaborated. With respect to its performance, under the same optimized conditions (1 g/L of dose; 5 mg/L of TC; pH 7; 3 h of reaction time), the Bi2WO6/BiOI@5%Fe3O4 composite has the highest TC removal (97%), as compared to the Bi2WO6 (63%). After being saturated, the spent photocatalyst could be magnetically separated from solution for subsequent use. In spite of three consecutive cycles with 71% of efficiency, the spent composite still has reasonable photocatalytic activities for reuse. Overall, this suggests that the composite is a promising photocatalyst for TC removal from aqueous solutions.
To maximize the employment of sustainable solar energy in treating the recalcitrant pollutant and hydrogen energy production, the development of a highly efficient photocatalyst is desirable. Herein, a Z-scheme Ag/AgVO3/g-C3N4 photocatalyst was synthesized via a wet-impregnation method. The amount of Ag/AgVO3 deposited onto g-C3N4 has a significant effect on the photocharge carrier separation and migration of the as-developed Z-scheme photocatalyst. It was found that 0.5 wt % Ag/AgVO3/g-C3N4 photocatalyst exhibited a profound photocatalytic degradation performance with 82.6% ciprofloxacin removal and 3.57 mmol/h of hydrogen produced from natural rainwater under visible-light irradiation. Additionally, the apparent quantum efficiency (AQE) of this sample was 9.95% at 420 nm which is four times higher than the pure sample. The remarkable photocatalytic performance was attributed to the enhanced crystallographic structure, evidently from the XRD and XPS analysis. Moreover, the intimate contact between Ag/AgVO3 and g-C3N4 nanoparticles allows the smooth photocharge carrier separation and migrations, resulting in superior photocatalytic performance in comparison to the pure samples. Interestingly, the profound photocatalytic activity demonstrated here was achieved without the addition of any sacrificial reagents. This work demonstrates the feasibility of utilizing visible-light-driven photocatalysts in treating the recalcitrant antibiotic pollutants and producing hydrogen from natural rainwater.
Methylene blue is a refractory pollutant commonly present in textile wastewater. This study tests the feasibility of TiO2/graphene oxide (GO) composite in enhancing photocatalytic degradation of MB in synthetic wastewater with respect to scientific and engineering aspects. To enhance its removal, we vary the composition of the composite based on the TiO2 weight. Under UV-vis irradiation, the effects of photocatalyst's dose, pH, and reaction time on MB removal by the composites are evaluated under optimum conditions, while any changes in their physico-chemical properties before and after treatment are analyzed by using TEM, SEM, XRD, FTIR and BET. The photodegradation pathways of the target pollutant by the composite and its removal mechanisms are also elaborated. It is found that the same composite with a 1:2 wt ratio of GO/TiO2 has the largest surface area of 104.51 m2/g. Under optimum reactions (0.2 g/L of dose, pH 10, and 5 mg/L of pollutant's concentration), an almost complete MB removal could be attained within 4 h. This result is higher than that of the TiO2 alone (30%) under the same conditions. Since the treated effluents could meet the strict discharge standard limit of ≤0.2 μg/L set by China's regulation, subsequent biological treatments are unnecessary for completing biodegradation of remaining oxidation by-products in the wastewater effluents.
A simplified modelling approach for illustrating the fate of emerging pollutants can improve risk assessment of these chemicals. Once released into aquatic environments, these pollutants will interact with various substances including suspended particles, colloidal or nano particles, which will greatly influence their distribution and ultimate fate. Understanding these interactions in aquatic environments continues to be an important issue because of their possible risk. In this study, bisphenol A (BPA) in the water column of Bentong River, Malaysia, was investigated in both its soluble and colloidal phase. A spatially explicit hydrological model was established to illustrate the associated dispersion processes of colloidal-bound BPA. Modelling results demonstrated the significance of spatial detail in predicting hot spots or peak concentrations of colloidal-bound BPA in the sediment and water columns as well. The magnitude and setting of such spots were system based and depended mainly on flow conditions. The results highlighted the effects of colloidal particles' concentration and density on BPA's removal from the water column. It also demonstrated the tendency of colloidal particles to aggregate and the impact all these processes had on BPA's transport potential and fate in a river water. All scenarios showed that after 7.5-10 km mark BPA's concentration started to reach a steady state with very low concentrations which indicated that a downstream transport of colloidal-bound BPA was less likely due to minute BPA levels.
This study investigated the engine performance and emission characteristics of biodiesel blends with combined Graphene oxide nanoplatelets (GNPs) and 10% v/v dimethyl carbonate (DMC) as fuel additives as well as analysed the tribological characteristics of those blends. 10% by volume DMC was mixed with 30% palm oil biodiesel blends with diesel. Three different concentrations (40, 80 and 120 ppm) of GNPs were added to these blends via the ultrasonication process to prepare the nanofuels. Sodium dodecyl sulphate (SDS) surfactant was added to improve the stability of these blends. GNPs were characterised using Scanning Electron Microscope (SEM) and Fourier Transform Infrared (FTIR), while the viscosity of nanofuels was investigated by rheometer. UV-spectrometry was used to determine the stability of these nanoplatelets. A ratio of 1:4 GNP: SDS was found to produce maximum stability in biodiesel. Performance and emissions characteristics of these nanofuels have been investigated in a four-stroke compression ignition engine. The maximum reduction in BSFC of 5.05% and the maximum BTE of 22.80% was for B30GNP40DMC10 compared to all other tested blends. A reduction in HC (25%) and CO (4.41%) were observed for B30DMC10, while a reduction in NOx of 3.65% was observed for B30GNP40DMC10. The diesel-biodiesel fuel blends with the addition of GNP exhibited a promising reduction in the average coefficient of friction 15.05%, 8.68% and 3.61% for 120, 80 and 40 ppm concentrations compared to B30. Thus, combined GNP and DMC showed excellent potential for utilisation in diesel engine operation.
Landfill has become an underlying source of surface and groundwater pollution if not efficiently managed, due to the risk of leachate infiltration into to land and aquifers. The generated leachate is considered a serious environmental threat for the public health, because of the toxic and recalcitrant nature of its constituents. Thus, it must be collected and appropriately treated before being discharged into the environment. At present, there is no single unit process available for proper leachate treatment as conventional wastewater treatment processes cannot achieve a satisfactory level for degrading toxic substances present. Therefore, there is a growing interest in examination of different leachate treatment processes for maximum operational flexibility. Based on leachate characteristics, discharge requirements, technical possibilities, regulatory requirements and financial considerations, several techniques have been applied for its degradation, presenting varying degrees of efficiency. Therefore, this article presents a comprehensive review of existing research articles on the pros and cons of various leachate degradation methods. In line with environmental sustainability, the article stressed on the application and efficiency of sequencing batch reactor (SBR) system treating landfill leachate due to its operational flexibility, resistance to shock loads and high biomass retention. Contributions of integrated leachate treatment technologies with SBR were also discussed. The article further analyzed the effect of different adopted materials, processes, strategies and configurations on leachate treatment. Environmental and operational parameters that affect SBR system were critically discussed. It is believed that information contained in this review will increase readers fundamental knowledge, guide future researchers and be incorporated into future works on experimentally-based SBR studies for leachate treatment.
Droughts are slow-moving natural hazards that gradually spread over large areas and capable of extending to continental scales, leading to severe socio-economic damage. A key challenge is developing accurate drought forecast model and understanding a models' capability to examine different drought characteristics. Traditionally, forecasting techniques have used various time-series approaches and machine learning models. However, the use of deep learning methods have not been tested extensively despite its potential to improve our understanding of drought characteristics. The present study uses a deep learning approach, specifically the Long Short-Term Memory (LSTM) to predict a commonly used drought measure, the Standard Precipitation Evaporation Index (SPEI) at two different time scales (SPEI 1, SPEI 3). The model was compared with other common machine learning method, Random Forests, Artificial Neural Networks and applied over the New South Wales (NSW) region of Australia, using hydro-meteorological variables as predictors. The drought index and predictor data were collected from the Climatic Research Unit (CRU) dataset spanning from 1901 to 2018. We analysed the LSTM forecasted results in terms of several drought characteristics (drought intensity, drought category, or spatial variation) to better understand how drought forecasting was improved. Evaluation of the drought intensity forecasting capabilities of the model were based on three different statistical metrics, Coefficient of Determination (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The model achieved R2 value of more than 0.99 for both SPEI 1 and SPEI 3 cases. The variation in drought category forecasted results were studied using a multi-class Receiver Operating Characteristic based Area under Curves (ROC-AUC) approach. The analysis revealed an AUC value of 0.83 and 0.82 for SPEI 1 and SPEI 3 respectively. The spatial variation between observed and forecasted values were analysed for the summer months of 2016-2018. The findings from the study show an improvement relative to machine learning models for a lead time of 1 month in terms of different drought characteristics. The results from this work can be used for drought mitigation purposes and different models need to be tested to further enhance our capabilities.
The vast amount of oily wastewater released to the environment through industrialization has worsened the water quality in recent years, posing adverse impacts on general human health. Oil emulsified in water is one of the most difficult mixtures to be treated, making it imperative for new technology to be explored to address this issue. The use of conventional water treatment such as flotation, coagulation, precipitation, adsorption, and chemical treatment have low separation efficiencies and high energy costs, and are not applicable to the separation of oil/water emulsions. Therefore, there is a demand for more efficient methods and materials for the separations of immiscible oil/water mixtures and emulsions. Superwetting materials that can repel oil, while letting water pass through have been widely explored to fit into this concern. These materials usually make use of simultaneous hydrophilic/oleophobic mechanisms to allow a solid surface to separate oily emulsion with little to no use of energy. Also, by integrating specific wettability concepts with appropriate pore scale, solid surfaces may achieve separation of multifarious oil/water mixtures namely immiscible oil/water blends and consolidated emulsions. In this review, materials used to impart superwetting in solid surfaces by focusing on superhydrophilic/superoleophobic wetting properties of the materials categorized into fluorinated and non-fluorinated surface modification are summarized. In each material, its background, mechanism, fabricating processes, and their effects on solid surface's wetting capability are elaborated in detail. The materials reviewed in this paper are mainly organic and green, suggesting the alternative material to replace the fluorine group that is widely used to achieve oleophobicity in oily wastewater treatment.
China is the world's largest fossil fuel consumer and carbon emitter country. In September 2020, China pledged to reduce carbon emissions, and achieve carbon neutrality by 2060. Therefore, this study aimed to contribute to the literature and show the pictorial nexus of bioenergy and fossil fuel consumption, carbon emission, and agricultural bioeconomic growth, a new pathway towards carbon neutrality. For this study, time-series data from 1971 to 2019 were used to analyze the autoregressive distributed lag (ARDL) bound testing and novel dynamic autoregressive distributed lag (DYNARDL) simulation models. Initially, the unit root tests results showed that all variables were stationarity at the level and first difference. The presence of cointegration between selected variables was confirmed by the results from ARDL bound test. In addition, the results of long-run and short-run nexus show an increase in bioenergy consumption that caused an increase in agricultural bioeconomic growth both in the long and short-run nexus. A decrease in fossil fuel consumption was shown to result in increased agricultural bioeconomic growth with respect to both long- and short-term effects. Furthermore, the results of the novel dynamic ARDL simulation model demonstrated that a 10% positive shock from bioenergy consumption caused an increase in agricultural bioeconomic growth, while at the same time, a 10% negative shock in bioenergy consumption led to a decrease. A 10% negative shock from fossil fuels caused an increase in agricultural bioeconomic growth, whereas a 10% positive shock from fossil fuels led to a decrease. Therefore, this study suggests that China needs to switch from fossil fuel and other non-renewable energy consumption to sources of bioenergy and other renewable energy consumption to achieve carbon neutrality by 2060.
Biomass co-firing with coal can be adopted in the electricity sector to promote greenhouse gas reduction, renewable energy production, and resource efficiency improvement toward environmental sustainability. This realization, however, requires effective management of supply chain issues, such as the collection of biomass feedstock, the transportation of biomass, and the localization of biomass processing plants to deliver the co-firing scales needed. This work addresses these issues by providing a techno-economic assessment conducted in a spatially-explicit manner to investigate the opportunity for scaling up the co-firing deployment at the national scale. The modeling approach is applied to the case of Malaysia's coal and palm oil biomass industries. The number of cases involving the impact of energy decarbonization targets, economic policy instrument, and supply chain cost parameter variations on the co-firing scales deployed are assessed. The findings show that densified biomass feedstock can substitute significant shares of coal capacities to deliver up to 29 MtCO2/year of carbon dioxide reduction. Nevertheless, this would cause a surge in the electricity system cost by up to 2 billion USD/year due to the substitution of up to 40% of the coal plant capacities. In facilitating the maximal deployment of co-firing at the national scale, more than 100 solid biofuel production plants would need to be built to support a maximum of 41 TWh/year of co-firing capacity. Actions to minimize the specific cost elements of the biomass co-firing supply chain are thus needed in the near term to increase the effectiveness of economic policy instrument to promote co-firing and reduce environmental emissions.
Eco-industrial parks promise to reduce environmental and social impacts and improve the economic performance of industrial parks. However, the transition from industrial parks to eco-industrial parks is still not well understood. This study contributes to developing valid hierarchical eco-industrial park transition attribute sets with qualitative information, as prior studies lack an exploration of the attributes in the transition of eco-industrial parks in Hungary. In nature, eco-industrial park transition attributes have causal and hierarchical interrelationships and are described with qualitative information. The assessment involves an analysis of the industrial symbiosis principles by using linguistic preferences. However, multiple attributes are involved in the assessment; therefore, this study proposes the Delphi method to develop a valid attribute set and applies fuzzy set theory to translate qualitative information into crisp values. The fuzzy decision-making trial evaluation laboratory method is used to visualize the attributes' causal interrelationships under uncertainties. The results indicate that the policy and regulatory framework leads to collaboration among firms in the eco-industrial park transition model. In practice, price reforms, management commitment, strategic planning, cognitive barriers and the integration of external information are the practical criteria for improvement. Theoretical and practical implications are also discussed.
Striving to achieve the Sustainable Development Goals (SDGs), countries are increasingly embracing a sustainable financing mechanism via green bond financing. Green bonds have attracted the attention of the industrial sector and policymakers, however, the impact of green bond financing on environmental and social sustainability has not been confirmed. There is no empirical evidence on how this financial product can contribute to achieving the goals set out in Agenda 2030. In this study, we empirically analyze the impact of green bond financing on environmental and social sustainability by considering the S&P 500 Global Green Bond Index and S&P 500 Environmental and Social Responsibility Index, from October 1, 2010 to 31st July 2020 using a combination of Quantile-on-Quantile Regression and Wavelet Multiscale Decomposition approaches. Our results reveal that green financing mechanisms might have gradual negative transformational impacts on environmental and social responsibility. Furthermore, we attempt to design a policy framework to address the relevant SDG objectives.