The impacts of rubber variations (clonal, seasonal, and pre-treatment) were investigated to assess changes in the composition of volatile organic compounds (VOCs) emitted during rubber processing. VOC emissions from 14 different rubber types were evaluated by headspace micro-chamber (μ-TEC) extraction coupled with gas chromatography-mass spectrometry (GC-MS). Headspace extracted at 120 °C, which is equivalent to the drying temperature during rubber processing, revealed a significant number of odorants in terms of concentrations as well as odorant type. Volatile fatty acids (VFAs) such as acetic, propanoic, butanoic, pentanoic and hexanoic acids, were frequently detected at concentrations greater than their odour detection thresholds. Other odorous compounds including trimethylamine, p-cresol, butanone, indole, and phenol, were also detected. Emissions collected at ambient conditions represent odorants released during material storage (or maturation) and were dominated by benzene derivatives followed by ketones, aldehydes, esters, and acids. Emission composition during storage appeared to be governed by specific rubber properties such as protein and rubber moisture content. Seasonal variations revealed greater impacts on the concentration of VOCs for all studied clones, compared to pre-treatment variations, suggesting that the VOCs composition was seasonally dependent and may represents the 'potential' emissions from rubber as they are processed. A combination of sensorial and analytical measurements were used to produce odour wheels which may be used as tool to identify key malodours in onsite rubber processing. The linking of odours and odorants can facilitate communication between receptors (the public) and plant operators inorder to minimise odour impact and develop effective abatement and on-site management practices.
The petrochemical wastewater (PCW) from acrylic acid plants possesses a very high chemical oxygen demand (COD) due to the presence of acrylic acid along with other organic acids. The treatment of PCW by conventional aerobic and anaerobic methods is energy intensive. Therefore, the treatment of PCW with concurrent power generation by employing microbial fuel cell (MFC) could be a potential alternative to solve the energy and environmental issues. This study demonstrates the potentiality of PCW from acrylic acid plant with an initial COD of 45,000 mg L-1 generating maximum power density of 850 mW m-2 at a current density of 1500 mA m-2 using acclimatized anaerobic sludge (AS) as biocatalyst. The predominant microbes present in acclimatized AS were identified using Biolog GEN III analysis, which include the electrogenic genera namely Pseudomonas spp. and Bacillus spp. along with methanogenic archea Methanobacterium spp. The mechanism of electron transfer was elucidated by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) which clearly demonstrated the natural metabolite-based electron transfer across the electrode/biofilm/solution interface. The abundance of the electron shuttle metabolites was increased with the microbial growth in the bulk solution as well as in the biofilm leading to a high power generation. The COD removal efficiency and the coulombic efficiency (CE) were found to be 40% and 21%, respectively after 11 days of operation using initial COD of 45,000 mg L-1. The low COD removal efficiency could drastically be increased to 82% when the initial COD of PCW was 5000 mg L-1 generating a power density of 150 mW m-2. The current work proves the feasibility of the MFC for the treatment of acrylic acid plant PCW using acclimatized anaerobic sludge (AS) as a biocatalyst.
Global patterns of biodiversity have emerged for soil microorganisms, plants and animals, and the extraordinary significance of microbial functions in ecosystems is also well established. Virtually unknown, however, are large-scale patterns of microbial diversity in freshwaters, although these aquatic ecosystems are hotspots of biodiversity and biogeochemical processes. Here we report on the first large-scale study of biodiversity of leaf-litter fungi in streams along a latitudinal gradient unravelled by Illumina sequencing. The study is based on fungal communities colonizing standardized plant litter in 19 globally distributed stream locations between 69°N and 44°S. Fungal richness suggests a hump-shaped distribution along the latitudinal gradient. Strikingly, community composition of fungi was more clearly related to thermal preferences than to biogeography. Our results suggest that identifying differences in key environmental drivers, such as temperature, among taxa and ecosystem types is critical to unravel the global patterns of aquatic fungal diversity.
In this paper, a facile synthesis method for CaFe2O4 is introduced that produces a catalyst capable of significant photocatalytic degradation of POME under visible light irradiation. The co-precipitation method was used to produce two catalysts at calcination temperatures of 550 °C and 700 °C dubbed CP550 and CP700. CP550 demonstrated the maximum COD removal of 69.0% at 0.75 g/L catalyst loading after 8 h of visible light irradiation which dropped to 61.0% after three consecutive cycles. SEM images indicated that the higher calcination temperature of CP700 led to annealing which reduced the pore volume (0.025 cm3/g) and pore diameter (10.3 nm) while simultaneously creating a smoother and more spherical surface with lower SBET (9.73 m2/g). In comparison, CP550 had a rough hair-like surface with higher SBET (27.28 m2/g) and pore volume (0.077 cm3/g) as evidenced by BET analysis. XRD data indicated the presence of CaFe5O7 in the CP550 composition which was not present in CP700. The presence of Wustite-like FeO structures in CaFe5O7 are likely the cause for lower photoluminescence intensity profile and hence better charge separation of CP550 as these structures in CaFe2O4 have been known to increase resistivity and electron localization. The COD removal of CP550 dropped from 69.0% to just 7.0% upon adding a small quantity of isopropanol into the reaction mixture indicating hydroxyl radicals as the primary reactive oxidative species.
Marine harbours are the focus of a diverse range of activities and subject to multiple anthropogenically induced pressures. Support for environmental management options aimed at improving degraded harbours depends on understanding the factors which influence people's perceptions of harbour environments. We used an online survey, across 12 harbours, to assess sources of variation people's perceptions of harbour health and ecological engineering. We tested the hypotheses: 1) people living near impacted harbours would consider their environment to be more unhealthy and degraded, be more concerned about the environment and supportive of and willing to pay for ecological engineering relative to those living by less impacted harbours, and 2) people with greater connectedness to the harbour would be more concerned about and have greater perceived knowledge of the environment, and be more supportive of, knowledgeable about and willing to pay for ecological engineering, than those with less connectedness. Across twelve locations, the levels of degradation and modification by artificial structures were lower and the concern and knowledge about the environment and ecological engineering were greater in the six Australasian and American than the six European and Asian harbours surveyed. We found that people's perception of harbours as healthy or degraded, but not their concern for the environment, reflected the degree to which harbours were impacted. There was a positive relationship between the percentage of shoreline modified and the extent of support for and people's willingness to pay indirect costs for ecological engineering. At the individual level, measures of connectedness to the harbour environment were good predictors of concern for and perceived knowledge about the environment but not support for and perceived knowledge about ecological engineering. To make informed decisions, it is important that people are empowered with sufficient knowledge of the environmental issues facing their harbour and ecological engineering options.
Fossil fuel depletion and the environmental concerns have been under discussion for energy production for many years and finding new and renewable energy sources became a must. Biomass is considered as a net zero CO2 energy source. Gasification of biomass for H2 and syngas production is an attractive process. The main target of this research is to improve the production of hydrogen and syngas from palm kernel shell (PKS) steam gasification through defining the optimal operating parameters' using a modern optimization algorithm. To predict the gaseous outputs, two PKS models were built using fuzzy logic based on the experimental data sets. A radial movement optimizer (RMO) was applied to determine the system's optimal operating parameters. During the optimization process, the decision variables were represented by four different operating parameters. These parameters include; temperature, particle size, CaO/biomass ratio and coal bottom ash (CBA) with their operating ranges of (650-750 °C), (0.5-1 mm), (0.5-2) and wt% (0.02-0.10), respectively. The individual and interactive effects of different combinations were investigated on the production of H2 and syngas yield. The optimized results were compared with experimental data and results obtained from Response Surface Methodology (RSM) reported in literature. The obtained optimal values of the operating parameters through RMO were found 722 °C, 0.92 mm, 1.72 and 0.06 wt% for the temperature, particle size, CaO/biomass ratio and coal bottom ash, respectively. The results showed that syngas production was significantly improved as it reached 65.44 vol% which was better than that obtained in earlier studies.
Chlorine radical plays an important role in the formation of ozone and secondary aerosols in the troposphere. It is hence important to develop comprehensive emissions inventory of chlorine precursors in order to enhance our understanding of the role of chlorine chemistry in ozone and secondary pollution issues. Based on a bottom-up methodology, this study presents a comprehensive emission inventory for major atomic chlorine precursors in the Yangtze River Delta (YRD) region of China for the year 2017. Four primary chlorine precursors are considered in this study: hydrogen chloride (HCl), fine particulate chloride (Cl-) (Cl- in PM2.5), chlorine gas (Cl2), and hypochlorous acid (HClO) with emissions estimated for twelve source categories. The total emissions of these four species in the YRD region are estimated to be 20,424 t, 15,719 t, 1556 and 9331 t, respectively. The emissions of HCl are substantial, with major emissions from biomass burning and coal combustion, together accounting for 68% of the total HCl emissions. Fine particulate Cl- is mainly emitted from industrial processing, biomass burning and waste incineration. The emissions of Cl2 and HClO are mainly associated with usage of chlorine-containing disinfectants, for example, water treatment, wastewater treatment, and swimming pools. Emissions of each chlorine precursor are spatially allocated based on the characteristics of individual source category. This study provides important basic dataset for further studies with respect to the effects of chlorine chemistry on the formation of air pollution complex in the YRD region.
In this research investigation, three microalgal species were screened (Pleurosigma sp., Amphora sp., and Amphiprora sp.) for lipid content before choosing the potential microalgae for biodiesel production. It was found that the lipid content of Amphiprora sp. was 41.48 ± 0.18%, which was higher than the Pleurosigma sp. (27.3 ± 0.8%) and Amphora sp. (22.49 ± 0.21%). The diatom microalga, Amphiprora sp. was isolated and exposed to a controlled environment. Two different media were prepared, and the main research was on the SiO2-NP medium as the cell wall of diatom was made up of silica. Essential growth parameters were studied such as dry cell weight and chlorophyll a content. The results revealed that Amphiprora sp. cultured in the modified medium showed a higher biomass yield and growth rate in all the analyses. In Soxhlet extraction method, biodiesel yield of Amphiprora sp. in modified medium under 24 μmol m-2 s-1 of light intensity was 81.47 ± 1.59% when using 2% of catalyst amount with 1.5:1 volume ratio of methanol/oil in 3 h reaction time at 65 °C. Results reveled that Amphiprora sp. diatom has a higher yield of oil 52.94 ± 0.42% and can be efficiently optimized with further studies with modified nanomaterial culture medium. The present research revealed the series of experiments on microalgal lipid transesterification and in future investigation different types of nanomaterials should be used in culture medium to identify the lipid production in microalgal cells.
Wide spread documentation of antibiotic pollution is becoming a threat to aquatic environment. Erythromycin (ERY), a macrolide belonging antibiotic is at the top of this list with its concentrations ranging between ng/L to a few μg/L in various global waterbodies giving rise to ERY-resistance genes (ERY-RGs) and ERY- resistance bacteria (ERY-RBs) posing serious threat to the aquatic organisms. ERY seems resistant to various conventional water treatments, remained intact and even increased in terms of mass loads after treatment. Enhanced oxidation potential, wide pH range, elevated selectivity, adaptability and greater efficiency makes advance oxidation processes (AOPs) top priority for degrading pollutants with aromatic rings and unsaturated bonds like ERY. In this manuscript, recent developments in AOPs for ERY degradation are reported along with the factors that affect the degradation mechanism. ERY, marked as a risk prioritized macrolide antibiotic by 2015 released European Union watch list, most probably due to its protein inhibition capability considered third most widely used antibiotic. The current review provides a complete ERY overview including the environmental entry sources, concentration in global waters, ERY status in STPs, as well as factors affecting their functionality. Along with that this study presents complete outlook regarding ERY-RGs and provides an in depth detail regarding ERY's potential threats to aquatic biota. This study helps in figuring out the best possible strategy to tackle antibiotic pollution keeping ERY as a model antibiotic because of extreme toxicity records.
Soil salinization is an extremely serious land degradation problem in arid and semi-arid regions that hinders the sustainable development of agriculture and food security. Information and research on soil salinity using remote sensing (RS) technology provide a quick and accurate assessment and solutions to address this problem. This study aims to compare the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction and exploration of the potential application of derivatives to RS prediction of salinized soils. It explores the ability of derivatives to be used in the Landsat-8 OLI and Sentinel-2A MSI multispectral data, and it was used as a data source as well as to address the adaptability of salinity prediction on a regional scale. The two-dimensional (2D) and three-dimensional (3D) optimal spectral indices are used to screen the bands that are most sensitive to soil salinity (0-10 cm), and RS data and topographic factors are combined with machine learning to construct a comprehensive soil salinity estimation model based on gray correlation analysis. The results are as follows: (1) The optimal spectral index (2D, 3D) can effectively consider possible combinations of the bands between the interaction effects and responding to sensitive bands of soil properties to circumvent the problem of applicability of spectral indices in different regions; (2) Both the Landsat-8 OLI and Sentinel-2A MSI multispectral RS data sources, after the first-order derivative techniques are all processed, show improvements in the prediction accuracy of the model; (3) The best performance/accuracy of the predictive model is for sentinel data under first-order derivatives. This study compared the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction in finding the potential application of derivatives to RS prediction of salinized soils, with the results providing some theoretical basis and technical guidance for salinized soil prediction and environmental management planning.
The Soil and Water Assessment Tool (SWAT) ecohydrological model was utilized to simulate fecal contamination in the 1937 km2 Selangor River Watershed in Malaysia. The watershed conditions posed considerable challenges owing to data scarcity and tropical climate conditions, which are very different from the original conditions that SWAT was developed and tested for. Insufficient data were compensated by publicly available data (e.g., land cover, soil, and weather) to run SWAT. In addition, field monitoring and interviews clarified representative situations of pollution sources and loads, which were used as input for the model. Model parameters determined by empirical analyses in the USA (e.g., surface runoff, evapotranspiration, and temperature adjustment for bacteria die-off) are thoroughly discussed. In particular, due consideration was given to tropical climate characteristics such as intense rainfall, high potential evapotranspiration, and high temperatures throughout the year. As a result, the developed SWAT successfully simulated fecal contamination ranging several orders of magnitude along with its spatial distribution (i.e., Nash-Sutcliffe Efficiency (NSE) = 0.64, Root Mean Square Error-Observations Standard Deviation Ratio (RSR) = 0.64 at six mainstem sites, and NSE = 0.67 and RSR = 0.57 at 12 major tributaries). Moreover, mitigation countermeasures for future worsening of fecal contamination (i.e., E.coli concentration > 20,000 CFU/100 mL for 690 days during nine years at a raw water intake point for Kuala Lumpur [KL] residents) were analyzed through scenario simulations, thereby contributing to discussing effective watershed management. The results propose improving decentralized sewage treatment systems and treating chicken manure with effective microorganisms in order to guarantee water safety for KL residents (i.e., E.coli concentrations <20,000 CFU/100 mL throughout the period, considering Malaysian standards). Accordingly, this study verified the applicability of SWAT to simulate fecal contamination in areas that are difficult to model and suggests solutions for watershed management based on quantitative evidence.
We explore the interplay between preventative risk management and regulatory style for the implementation of water safety plans in Malaysia and in England and Wales, two jurisdictions with distinct philosophies of approach. Semi-structured interviews were conducted with 32 water safety professionals in Malaysia, 23 in England and Wales, supported by 6 Focus Group Discussions (n = 53 participants). A grounded theory approach produced insights on the transition from drinking water quality surveillance to preventative risk management. Themes familiar to this type of regulatory transition emerged, including concerns about compliance policy; overseeing the risk management controls of regulatees with varied competencies and funds available to drive change; and the portfolio of interventions suited to a more facilitative regulatory style. Because the potential harm from waterborne illness is high where pathogen exposures occur, the transition to risk-informed regulation demands mature organisational cultures among water utilities and regulators, and a laser-like focus on ensuring risk management controls are delivered within water supply systems.
Recognizing and mainstreaming pertinent walkability elements into the university campus planning is crucial to materialise green mandates of the campus, while enhancing social and economic sustainability. In one of such attempts, this transverse study investigated the walking motivations, built environment factors associated with campus walkability and the relative importance of the studied built environment factors in reference to the sociodemographic attributes from the viewpoint of the campus community in a tropical university campus in Kuala Lumpur, Malaysia. An online survey using a structured questionnaire was conducted between May and September 2019. The built environment factors associated with campus walkability were expressed and ranked as adjusted scores (AS). Meanwhile, multivariable logistic regression was deployed to examine the relative importance of the studied built environment factors in reference to the sociodemographic attributes of the campus community. Among 504 total responses acquired, proximity between complementary land uses (90.7%) was reported as the main motivation for walking. On the other hand, street connectivity and accessibility (AS: 97.62%) was described as the most opted built environment factor, followed by land use (AS: 96.76%), pedestrian infrastructure (AS: 94.25%), walking experience (AS: 87.07%), traffic safety (AS: 85.28%) and campus neighbourhood (AS: 59.62%), respectively. Among the sociodemographic attributes, no regular monthly income (OR = 3.162; 95% CI = 1.165-8.379; p
Landslides are major hazards for human activities often causing great damage to human lives and infrastructure. Therefore, the main aim of the present study is to evaluate and compare three machine learning algorithms (MLAs) including Naïve Bayes (NB), radial basis function (RBF) Classifier, and RBF Network for landslide susceptibility mapping (LSM) at Longhai area in China. A total of 14 landslide conditioning factors were obtained from various data sources, then the frequency ratio (FR) and support vector machine (SVM) methods were used for the correlation and selection the most important factors for modelling process, respectively. Subsequently, the resulting three models were validated and compared using some statistical metrics including area under the receiver operating characteristics (AUROC) curve, and Friedman and Wilcoxon signed-rank tests The results indicated that the RBF Classifier model had the highest goodness-of-fit and performance based on the training and validation datasets. The results concluded that the RBF Classifier model outperformed and outclassed (AUROC = 0.881), the NB (AUROC = 0.872) and the RBF Network (AUROC = 0.854) models. The obtained results pointed out that the RBF Classifier model is a promising method for spatial prediction of landslide over the world.
Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic compounds, composed of benzene rings. The objective of this research was to identify the optimum condition for the degradation of PAHs contaminated water using photo-Fenton oxidation process via response surface methodology (RSM). Aqueous solution was prepared and potable water samples were collected from water treatment plants in Perak Tengah, Perak, Malaysia in September 2016. The reaction time, pH, molarity of H2O2 and FeSO4 were analyzed followed by RSM using aqueous solution. A five level central composite design with quadratic model was used to evaluate the effects and interactions of these parameters. The response variable was the percentage of total organic carbon (TOC) removal. PAHs quantification was done using gas chromatography mass spectrometry analysis. The regression line fitted well with the data with R2 value of 0.9757. The lack of fit test gives the highest value of Sum of Squares (15,666.64) with probability F value 0.0001 showing significant quadratic model. The optimum conditions were established corresponding to the percentage of TOC removal. The PAHs removal efficiency for potable water samples ranged from 76.4% to 91% following the first order of kinetic rates with R2 values of >0.95. Conventional water treatment techniques are not effective for PAHs removal. Thus, advanced oxidation processes may be considered as an alternative to conventional water treatment techniques in Malaysia and other developing countries.
Endocrine disrupting compounds (EDCs) are an emerging environmental concern and commonly occur as a mixture of compounds. The EDC mixture can be more toxic than any single compound. The present study analyses EDCs in surface water in the case of an urban tropical river, the Langat River, using the multiresidue analytical method of solid phase extraction and liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS). The Langat River is used as a drinking water source and is treated for Malaysian drinking water supply. A total of 14 EDCs i.e. five hormones, seven pharmaceuticals, one pesticide, and one plasticizer were detected. Caffeine was observed to be highest at 19.33 ng/L, followed by bisphenol A and diclofenac at 8.24 ng/L and 6.15 ng/L, respectively. Using a conservative risk quotient (RQ) method, EDCs were estimated for having negligible risks under acute and chronic exposure (RQ
Southeast Asian countries stand at a crossroads concerning their shared energy future and heavily rely on fossil fuels for transport and electricity. Within Asia, especially India and China lead the world renewable energy generation undergoing a period of energy transition and economic transformation. Southeast Asian countries have huge potentials for sustainable energy sources. However they are yet to perform globally in renewable energy deployment due to various challenges. The primary objective of the study is to examine the renewable energy growth and analyse the government policies to scale up the deployment of renewables for power generation substantially. The study also offers policy recommendations to accelerate renewable energy exploitation sustainably across the region. To achieve the ambitious target of 23% renewables in the primary energy mix by 2025, ASEAN Governments should take proactive measures like removal of subsidies of fossil fuels, regional market integration and rapid implementation of the existing project. Eventually, each of this strategy will necessitate sustained leadership, political determination, and concrete actions from stakeholders, in particular, increased cooperation across the region.
With the population growth, urbanization and industrialization, China has become a hotspot of atmospheric deposition nitrogen (ADN), which is a threat to ecosystem and food safety. However, the impacts of increased ADN on rice growth and grain metal content are little studied. Based on previous long-term ADN studies, greenhouse experiment was conducted with four simulated ADN rates of 0, 30, 60 and 90 kg N ha-1 yr-1 (CK, N1, N2 and N3 as δ15N, respectively) to assess rice growth and metal uptake in a red soil ecosystem of southeast China during 2016-2017. Results showed that simulated ADN could promote rice growth and increase yields by 15.68-24.41% (except N2) and accumulations of cadmium (Cd) or copper (Cu) in organs. However, there was no linear relationship between ADN rate and rice growth or Cd or Cu uptake. The 15N-ADN was mainly accumulated in roots (21.31-67.86%) and grains (25.26-49.35%), while Cd and Cu were primarily accumulated in roots (78.86-93.44% and 90.00-96.24%, respectively). 15N-ADN and Cd accumulations in roots were significantly different between the two growing seasons (p
Plastic debris is a worldwide problem. This is particularly acute in the Pacific region, where its scale is a reason for serious concerns. There is an obvious need for studies to assess the extent to which plastic debris affects the Pacific. Therefore, this research aims to address this need by undertaking a systematic assessment of the ecological and health impacts of plastic debris on Pacific islands. Using pertinent historical qualitative and quantitative data of the distribution of plastic debris in the region, this study identified pollution and contamination trends and risks to ecosystems, and suggests some measures which may be deployed to address the identified problems. The study illustrates the fact that Pacific Island States are being disproportionately affected by plastic, and reiterates that further studies and integrated strategies are needed, involving public education and empowerment, governmental action, as well as ecologically sustainable industry leadership. It is also clear that more research is needed in respect of developing alternatives to conventional plastic, by the production of bio-plastic, i.e. plastic which is produced from natural (e.g. non-fossil fuel-based sources) materials, and which can be fully biodegradable.
The primary biological treatment method for organic sludge is composting and/or anaerobic digestion, but their product (compost or biogas) is of little economic benefit; therefore, an improved process to produce a high-value product is required to make sludge management more sustainable. Maximizing NH3 gas recovery during composting processes has the potential benefit of producing high-value microalgal biomass. However, the majority of produced ammonia does not evaporate as NH3 gas but retains as NH4+-N in the compost after fermentation. The present study investigates the effects of the timing of Ca(OH)2 dosing (on days 2, 5, and 9), and the Ca(OH)2 dose (1.1-2.6 mmol/batch), on lab-scale thermophilic composting of anaerobic sludge. The effects on NH3 recovery, organic matter degradability, and microbial activity are evaluated. Ca(OH)2 dosing immediately improved the emission of NH3, with yields 50-69% higher than those under control conditions. The timing of the dosing did not influence NH3 recovery or organic matter degradability. Higher Ca(OH)2 doses resulted in higher NH3 recovery, while microbial activity was temporarily and marginally inhibited. The pH of the compost reached 10-11.5 but quickly dropped to 8-8.5 within a day, probably because of neutralization of Ca(OH)2 by the emitted CO2 and release of NH3, which maintained the microbial activity. The present study indicated that Ca(OH)2 dosing would be useful to apply during thermophilic composting for NH3 recovery to cultivate high-value microalgal biomass, which enables this process to obtain a more economic benefit.