Suitable extraction technique and the least cost while reducing the environmental impact is the primary concern in timber transportation planning in undulate topography. Two types of extraction machines with unique characteristics to be applied in timber harvest area in Malaysia is combined for timber harvesting with the aim each machine will extract timber suitable to their ability. A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. The result shows the log fisher (1351 timbers) as a preferable extraction technique with total cost of RM 86,551.73 than the crawler tractor (206 timbers); the timber extraction route is 2630 m for the log fisher and 9860 m for the crawler tractor with total cost of RM 10,453.03. The model finds a suitable timber extraction technique and estimates the extraction costs. Further studies are required to compare the BA with other optimization methods for better results.
Palm oil sludge (POS) is an organic waste generated from the palm oil industry. POS causes environmental pollution if it is improperly disposed. In this study, the potential of activated POS biochar, as an adsorbent for the removal of SO2 gas was tested. POS biochar was physically activated using CO2 gas. The effects of activation preparation variables i.e. activation temperature (300-700 °C), activation time (30-150 min) and CO2 flow rate (100-500 ml/min) were investigated using design expert version 8.0.7.1 software. Central Composite Design (CCD) was used to develop a quadratic model to correlate the operating variables with the activated biochar adsorption capacity. Analysis of variance (ANOVA) was performed to identify the significant factors on the experimental design response. The optimum preparation conditions of activated POS biochar were found to be at activation temperature of 442 °C, activation time of 63 min and CO2 flow rate of 397 ml/min. The maximum adsorption capacity at the optimum conditions was recorded as 16.65 mg/g. The adsorption capacity increased significantly after the activation process. Characteristics of the activated POS biochar proposed that SO2 was physically adsorbed. Furthermore, it was found that the adsorption capacity can be further enhanced by increasing the reaction temperature to 100 °C or with 15% of relative humidity in the inlet gas. The prepared adsorbents can be regenerated by thermal treatment.
The effective reduction of hazardous organic pollutants in wastewater is a pressing global concern, necessitating the development of advanced treatment technologies. Pollutants such as nitrophenols and dyes, which pose significant risks to both human and aquatic health, making their reduction particularly crucial. Despite the existence of various methods to eliminate these pollutants, they are not without limitations. The utilization of nanomaterials as catalysts for chemical reduction exhibits a promising alternative owing to their distinguished catalytic activity and substantial surface area. For catalytically reducing the pollutants NaBH4 has been utilized as a useful source for it because it reduces the pollutants quiet efficiently and it also releases hydrogen gas as well which can be used as a source of energy. This paper provides a comprehensive review of recent research on different types of nanomaterials that function as catalysts to reduce organic pollutants and also generating hydrogen from NaBH4 methanolysis while also evaluating the positive and negative aspects of nanocatalyst. Additionally, this paper examines the features effecting the process and the mechanism of catalysis. The comparison of different catalysts is based on size of catalyst, reaction time, rate of reaction, hydrogen generation rate, activation energy, and durability. The information obtained from this paper can be used to steer the development of new catalysts for reducing organic pollutants and generation hydrogen by NaBH4 methanolysis.
In this work, the influence of pyrolysis temperature on the physicochemical properties of palm oil mill sludge biochar (POSB) and its adsorption properties towards cadmium (Cd) and copper (Cu) was investigated. Characterization experiments suggested that POSBs' surface functional groups play the major role in the adsorption process. POSB pyrolyzed at 400 °C showed the best characteristics for Cu and Cd removal. Adsorption study indicated that contact time and shaking speed enhances the adsorption capacity of POSB. It was affirmed that pH adjustment is not necessary for POSB to adsorb Cu and Cd. Mechanism studies fitted well with Langmuir and Pseudo-Second Order model. Thermodynamic parameters indicated that the adsorption was spontaneous, endothermic and correspond to chemical adsorption. The highest uptakes of Cu and Cd were recorded at 48.8 mg/g and 46.2 mg/g respectively. This work verifies that the temperature used for palm oil mill sludge (POS) pyrolysis and adsorption condition played the most prominent role in Cu and Cd removal from aqueous solutions.
In this study two deep eutectic solvents (DESs) were prepared using ethylene glycol (EG) and two different ammonium-based salts. The potential of these DESs as novel agents for CNTs functionalization was examined by performing a comprehensive characterization study to identify the changes developing after the functionalization process. The impact of DESs was obvious by increasing the surface area of CNTs to reach 197.8 (m2/g), and by adding new functional groups to CNTs surface without causing any damage to the unique structure of CNTs. Moreover, CNTs functionalized with DESs were applied as new adsorbents for the removal of methyl orange (MO) from water. The adsorption conditions were optimized using RSM-CCD experimental design. The kinetics and the equilibrium adsorption data were analyzed using different kinetic and isotherm models. According to the regression results, adsorption kinetics data were well described by pseudo-second order model, whereas adsorption isotherm data were best represented by Langmuir isotherm model. The highest recorded maximum adsorption capacity (qmax) value was found to be 310.2 mg/g.
Acetaminophen (Ace) is a trace pollutant widely found in sewage treatment plant (STP) wastewater. We test the feasibility of coconut shell waste, a low cost adsorbent from coconut industry, for removing Ace from synthetic solution in a fixed-bed column adsorption. To enhance its performance, the surface of granular activated carbon (GAC) was pre-treated with NaOH, HNO3, ozone, and/or chitosan respectively. The results show that the chemical modification of the GAC's surface with various chemicals has enhanced its Ace removal during the column operations. Among the modified adsorbents, the ozone-treated GAC stands out for the highest Ace adsorption capacity (38.2 mg/g) under the following conditions: 40 mg/L of Ace concentration, 2 mL/min of flow rate, 45 cm of bed depth. Both the Thomas and the Yoon-Nelson models are applicable to simulate the experimental results of the column operations with their adsorption capacities: ozone-treated GAC (20.88 mg/g) > chitosan-coated GAC (16.67 mg/g) > HNO3-treated GAC (11.09 mg/g) > NaOH-treated GAC (7.57 mg/g) > as-received GAC (2.84 mg/g). This suggests that the ozone-treated GAC is promising and suitable for Ace removal in a fixed-bed reactor.
Microplastic pollution is a serious environmental problem that affects both aquatic and terrestrial ecosystems. Small particles with size of less than 5 mm, known as microplastics (MPs), persist in the environment and pose serious threats to various species from micro-organisms to humans. However, terrestrial environment has received less attention than the aquatic environment, despite being a major source of MPs that eventually reaches water body. To reflect its novelty, this work aims at providing a comprehensive overview of the current state of MPs pollution in the global environment and various solutions to address MP pollution by integrating applied technology, policy instruments, and legislation. This review critically evaluates and compares the existing technologies for MPs detection, removal, and degradation, and a variety of policy instruments and legislation that can support the prevention and management of MPs pollution scientifically. Furthermore, this review identifies the gaps and challenges in addressing the complex and diverse nature of MPs and calls for joint actions and collaboration from stakeholders to contain MPs. As water pollution by MPs is complex, managing it effectively requires their responses through the utilization of technology, policy instruments, and legislation. It is evident from a literature survey of 228 published articles (1961-2023) that existing water technologies are promising to remove MPs pollution. Membrane bioreactors and ultrafiltration achieved 90% of MPs removal, while magnetic separation was effective at extracting 88% of target MPs from wastewater. In biological process, one kg of wax worms could consume about 80 g of plastic/day. This means that 100 kg of wax worms can eat about 8 kg of plastic daily, or about 2.9 tons of plastic annually. Overall, the integration of technology, policy instrument, and legislation is crucial to deal with the MPs issues.
In recent years, food waste has been a global concern that contributes to climate change. To deal with the rising impacts of climate change, in Hong Kong, food waste is converted into electricity in the framework of low-carbon approach. This work provides an overview of the conversion of food waste into electricity to achieve carbon neutrality. The production of methane and electricity from waste-to-energy (WTE) conversion are determined. Potential income from its sale and environmental benefits are also assessed quantitatively and qualitatively. It was found that the electricity generation from the food waste could reach 4.33 × 109 kWh annually, avoiding equivalent electricity charge worth USD 3.46 × 109 annually (based on US' 8/kWh). An equivalent CO2 mitigation of 9.9 × 108 kg annually was attained. The revenue from its electricity sale in market was USD 1.44×109 in the 1st year and USD 4.24 ×109 in the 15th year, respectively, according to the projected CH4 and electricity generation. The modelling study indicated that the electricity production is 0.8 kWh/kg of landfilled waste. The food waste could produce electricity as low as US' 8 per kW ∙ h. In spite of its promising results, there are techno-economic bottlenecks in commercial scale production and its application at comparable costs to conventional fossil fuels. Issues such as high GHG emissions and high production costs have been determined to be resolved later. Overall, this work not only leads to GHG avoidance, but also diversifies energy supply in providing power for homes in the future.
Corporate real estate management holds the tent that risk which is not understood cannot be measured or managed. The effect of global warming on real estate investment and need for climate change mitigation through disclosures by companies of carbon emission information has becomes a sine-qua-non for the management of companies' carbon footprint and reducing its overall effect on global warming. This study applied the structural equation modeling technique to determine the determinants influencing Carbon Disclosure in Real Estate Companies in a developing economy. The analysis was based on 2013 annual reports of 126 property sector companies listed in Malaysia stock exchange market. The model was validated through convergent validity, discriminant validity, composite reliability and goodness of fit. The result reveals that social and financial market were critical determinant factors for carbon disclosure while the economic and institutional factors did not achieve significant effect on voluntary carbon disclosure. The result is consistent with legitimacy theory and agency theories. The implication of this finding is that increase in public education and awareness will enhance community demand for disclosure from companies and they will increase level of disclosure; also as financial institutions consider sustainability practice as a viable investment and term for credit financing, companies will be motivated to increase disclosure.
Haze has been a major issue afflicting Southeast Asian countries, including Malaysia, for the past few decades. Hierarchical agglomerative cluster analysis (HACA) is commonly used to evaluate the spatial behavior between areas in which pollutants interact. Typically, using HACA, the Euclidean distance acts as the dissimilarity measure and air quality monitoring stations are grouped according to this measure, thus revealing the most polluted areas. In this study, a framework for the hybridization of the HACA technique is proposed by considering the topological similarity (Wasserstein distance) between stations to evaluate the spatial patterns of the affected areas by haze episodes. For this, a tool in the topological data analysis (TDA), namely, persistent homology, is used to extract essential topological features hidden in the dataset. The performance of the proposed method is compared with that of traditional HACA and evaluated based on its ability to categorize areas according to the exceedance level of the particulate matter (PM10). Results show that additional topological features have yielded better accuracy compared to without the case that does not consider topological features. The cluster validity indices are computed to verify the results, and the proposed method outperforms the traditional method, suggesting a practical alternative approach for assessing the similarity in air pollution behaviors based on topological characterizations.
Constructed wetland (CW) is a low-cost alternative technology to treat wastewater. This study was conducted to co-treat landfill leachate and municipal wastewater by using a CW system. Typha domingensis was transplanted to CW, which contains two substrate layers of adsorbents, namely, ZELIAC and zeolite. Response surface methodology and central composite design have been utilized to analyze experimental data. Contact time (h) and leachate-to-wastewater mixing ratio (%; v/v) were considered as independent variables. Colour, COD, ammonia, nickel, and cadmium contents were used as dependent variables. At optimum contact time (50.2 h) and leachate-to-wastewater mixing ratio (20.0%), removal efficiencies of colour, COD, ammonia, nickel, and cadmium contents were 90.3%, 86.7%, 99.2%, 86.0%, and 87.1%, respectively. The accumulation of Ni and Cd in the roots and shoots of T. domingensis was also monitored. Translocation factor (TF) was >1 in several runs; thus, Typha is classified as a hyper-accumulator plant.
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.
Palm oil production is one of the major industries in Malaysia and this country ranks one of the largest productions in the world. In Malaysia, the total production of crude palm oil in 2008 was 17,734,441 tonnes. However, the production of this amount of crude palm oil results in even larger amounts of palm oil mill effluent (POME). In the year 2008 alone, at least 44 million tonnes of POME was generated in Malaysia. Currently, the ponding system is the most common treatment method for POME but other processes such as aerobic and anaerobic digestion, physicochemical treatment and membrane filtration may also provide the palm oil industries with possible insights into the improvement of POME treatment processes. Generally, open ponding offers low capital and operating costs but this conventional method is becoming less attractive because the methane produced is wasted to the atmosphere and the system can not be certified for Carbon Emission Reduction trading. On the other hand, anaerobic digestion of POME provides the fastest payback of investment because the treatment enables biogas recovery for heat generation and treated effluent for land application. Lastly, it is proposed herewith that wastewater management based on the promotion of cleaner production and environmentally sound biotechnologies should be prioritized and included as a part of the POME management in Malaysia for attaining sustainable development. This paper thus discusses and compares state-of-the-art POME treatment methods as well as their individual performances.
A combination of persulfate and hydrogen peroxide (S2O8(2-)/H2O2) was used to oxidizelandfill leachate. The reaction was performed under varying S2O8(2-)/H2O2 ratio (g/g), S2O8(2-)/H2O2 dosages (g/g), pH, and reaction time (minutes), so as to determine the optimum operational conditions. Results indicated that under optimum operational conditions (i.e. 120 min of oxidation using a S2O8(2-)/H2O2 ratio of 1 g/1.47 g at a persulfate and hydrogen peroxide dosage of 5.88 g/50 ml and8.63 g/50 ml respectively, at pH 11) removal of 81% COD and 83% NH3-N was achieved. In addition, the biodegradability (BOD5/COD ratio) of the leachate was improved from 0.09 to 0.17. The results obtained from the combined use of (S2O8(2-)/H2O2) were compared with those obtained with sodium persulfate only, hydrogen peroxide only and sodium persulfate followed by hydrogen peroxide. The combined method (S2O8(2-)/H2O2) achieved higher removal efficiencies for COD and NH3-N compared with the other methods using a single oxidizing agent. Additionally, the study has proved that the combination of S2O8(2-)/H2O2 is more efficient than the sequential use of sodium persulfate followed by hydrogen peroxide in advanced oxidation processes aiming at treatingstabilizedlandfill leachate.
The construction industry generates a substantial volume of solid waste, often destinated for landfills, causing significant environmental pollution. Waste recycling is decisive in managing waste yet challenging due to labor-intensive sorting processes and the diverse forms of waste. Deep learning (DL) models have made remarkable strides in automating domestic waste recognition and sorting. However, the application of DL models to recognize the waste derived from construction, renovation, and demolition (CRD) activities remains limited due to the context-specific studies conducted in previous research. This paper aims to realistically capture the complexity of waste streams in the CRD context. The study encompasses collecting and annotating CRD waste images in real-world, uncontrolled environments. It then evaluates the performance of state-of-the-art DL models for automatically recognizing CRD waste in-the-wild. Several pre-trained networks are utilized to perform effectual feature extraction and transfer learning during DL model training. The results demonstrated that DL models, whether integrated with larger or lightweight backbone networks can recognize the composition of CRD waste streams in-the-wild which is useful for automated waste sorting. The outcome of the study emphasized the applicability of DL models in recognizing and sorting solid waste across various industrial domains, thereby contributing to resource recovery and encouraging environmental management efforts.
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.
The extensive amount of available information on global warming suggests that this issue has become prevalent worldwide. Majority of countries have issued laws and policies in response to this concern by requiring their industrial sectors to reduce greenhouse gas emissions, such as CO2. Thus, introducing new and more effective treatment methods, such as biological techniques, is crucial to control the emission of greenhouse gases. Many studies have demonstrated CO2 fixation using photo-bioreactors and raceway ponds, but a comprehensive review is yet to be published on biological CO2 fixation. A comprehensive review of CO2 fixation through biological process is presented in this paper as biological processes are ideal to control both organic and inorganic pollutants. This process can also cover the classification of methods, functional mechanisms, designs, and their operational parameters, which are crucial for efficient CO2 fixation. This review also suggests the bio-trickling filter process as an appropriate approach in CO2 fixation to assist in creating a pollution-free environment. Finally, this paper introduces optimum designs, growth rate models, and CO2 fixation of microalgae, functions, and operations in biological CO2 fixation.
Integrated fixed-film activated sludge (IFAS) process is considered as one of the leading-edge processes that provides a sustainable solution for wastewater treatment. IFAS was introduced as an advancement of the moving bed biofilm reactor by integrating the attached and the suspended growth systems. IFAS offers advantages over the conventional activated sludge process such as reduced footprint, enhanced nutrient removal, complete nitrification, longer solids retention time and better removal of anthropogenic composites. IFAS has been recognized as an attractive option as stated from the results of many pilot and full scales studies. Generally, IFAS achieves >90% removals for combined chemical oxygen demand and ammonia, improves sludge settling properties and enhances operational stability. Recently developed IFAS reactors incorporate frameworks for either methane production, energy generation through algae, or microbial fuel cells. This review details the recent development in IFAS with the focus on the pilot and full-scale applications. The microbial community analyses of IFAS biofilm and floc are underlined along with the special emphasis on organics and nitrogen removals, as well as the future research perspectives.
Based on the panel data of 22 inland provinces in China from 2010 to 2020, this study constructs and measures the level of rural ecological environment in China. The impact of the financial performance of green-listed companies on the rural ecological environment and its moderating and threshold effects are analyzed. The following conclusions are drawn: (1) During 2010-2020, China's rural ecological environment shows a trend of "fluctuating-decreasing-rising" with significant regional non-equilibrium characteristics. (2) The financial performance of green-listed companies has a significantly negative impact on rural ecology. This negative impact has a crucial heterogeneous feature, with a more significant negative impact in areas with a higher rural ecological environment index and less substantial performance in regions with a lower rural ecological environment index. (3) There is a significant positive moderating effect of education level and digitalization on the relationship between the financial performance of green-listed companies on the level of rural ecological development. As moderating variables, the digitalization and education level weakens the negative impact of green-listed companies' performance on the ecological environment. The positive impact of the financial performance of green-listed companies on the development level of the rural ecological environment is more vital in areas with higher per capita education levels and digitalization in rural areas. (4) There is a significant threshold effect on the financial performance of green-listed companies on the level of rural ecological development. When the financial performance of green-listed companies exceeds a particular threshold value, the impact of the financial performance of green-listed companies on the development level of the rural ecological environment is significantly positive. Based on the above findings, this paper puts forward corresponding countermeasure suggestions.
The world water resources are contaminated due to discharge of a large number of pollutants from industrial and domestic sources. A variety of a single and multiple units of physical, chemical, and biological processes are employed for pollutants removal from wastewater. Adsorption is the most widely utilized process due to high efficiency, simple procedure and cost effectiveness. This paper reviews the research work carried out on the use of geopolymer materials for the adsorption of heavy metals and dyes. Geopolymers possess good surface properties, heterogeneous microstructure and amorphous structure. The performance of geopolymers in the removal of heavy metals and dyes is reported comparable to other materials. The pseudo-second order kinetics and Langmuir isotherm models mostly fit to the adsorption data suggesting homogeneous distribution of adsorption sites with the formation of monolayer adsorbate on the surface of geopolymers. Adsorption of heavy metals and dyes onto geopolymers is spontaneous, endothermic and entropy driven process. Future research should focus on the enhancement of geopolymer performance, testing on pollutants other than heavy metals and dyes, and verification on real wastewater in continuous operation.