Evaluation of electric vehicle response capability in power grid.

In recent years, frequent and substantial area-wide power outages have underscored the critical need for cities to possess robust backup power sources capable of swift response to prevent prolonged power system disruptions. Electric vehicles can contribute electricity to the power grid using vehicle-to-grid technology. The power delivered by electric vehicles in this context is termed as response capability. However, existing studies have overlooked response capability dynamics during transitions between electric vehicle states-such as the shift from charging or discharging to an idle state, thereby hindering a comprehensive understanding of this aspect. Hence, this paper introduces a multi-timescale response capability prediction model that evaluates the electric vehicle's state of charge to ensure users' requirements are met for upcoming trips. To better assess users' travel demand, the gravity model is employed as a precursor to response capability prediction to further enhance the validity of the prediction outcomes. Three neighborhoods in Los Angeles have been chosen for analysis: Downtown, Lincoln Heights, and Silver Lake. Predictions indicate that neglecting the response capability when electric vehicles undergo state transformation can lead to a differential response capability ranging from 2000 kWh to 4000 kWh, resulting in a loss of prediction accuracy by 20 % to 25 %.•The response capability of EV is non-zero during state transformations•Users' travel demand assessment•Seamless integration of vehicle-to-grid technology into the power grid.

Optimizing hybrid energy systems for remote communities in Asia's least developed countries.

In least-developed countries (LDCs), electricity shortages are the primary barrier to economic and social growth. Some remote areas in LDC rely on diesel-based systems. However, renewable energy must be taken into account for generating electricity because of the uncertainty of diesel fuel prices and the emissions of carbon dioxide. Hybrid energy systems (HES) are becoming increasingly popular, which is unsurprising given the rapid advancement of renewable energy technologies, which have made them the preferred method to respond to the current unreliable electricity supply, reduce the impact of global warming that occurs from electricity production, and contribute to cost reduction. This study explores the feasibility of utilizing a combination of solar PV, wind energy, and battery systems with the existing diesel generator in four different locations in Cambodia, Laos, Myanmar, and Bangladesh. Hybrid optimization multiples for electric renewables (HOMER) is used as a tool for techno-economic analysis and finding the possible combination of solar PV, wind, diesel, and battery. The multi-criteria decision-making (MCDM) technique was used to verify all configurations obtained from HOMER's results. This approach considers environmental, economic, and technological factors by utilizing the AHP, TOPSIS, EDAS, and PROMETHEEE II techniques. The results show that PV/diesel with batteries is the optimum solution. This hybrid system comprises 89% PV penetration, a cost of electricity (COE) of 0.257 $/kWh, an initial capital cost (IC) of $244,277, and a net present cost (NPC) of $476,216 for a case study in Cambodia. Furthermore, this system can reduce almost 51,005 kg/year of carbon dioxide compared to a diesel-only system, while the cost of electricity is reduced.

UV-blocking and photocatalytic properties of Ag-coated cotton fabrics with Si binders for photo-degradation of recalcitrant dyes in aqueous solutions under sunlight.

Textile wastewater laden with dyes has emerged as a source of water pollution. This possesses a challenge in its effective treatment using a single functional material. In respond to this technological constraint, this work presents multifunctional cotton fabrics (CFs) within a single, streamlined preparation process. This approach utilizes the adherence of Ag NPs (nanoparticles) using Si binder on the surface of CFs, resulting in Ag-coated CFs through a pad dry method. The prepared samples were characterized using scanning electron microscope-energy dispersive X-ray electroscopy (SEM-EDS), thermal gravimetric analysis (TGA), Fourier transformation infrared (FT-IR). It was found that the FT-IR spectra of Ag NPs-coated CFs had peaks appear at 3400, 2900, and 1200 cm-1, implying the stretching vibrations of O-H, C-H, and C-O, respectively. Based on the EDX analysis, the presence of C, O, and Ag related to the coated CFs were detected. After coating the CFs with varying concentrations of Ag NPs (1%, 2% and 3% (w/w)), they were used to remove dyes. Under the same concentration of 10 mg/L and optimized pH 7.5 and 2 h of reaction time, 3% (w/w) Ag-coated CFs exhibited a substantial MB degradation of 98 %, while removing 95% of methyl orange, 85% of rhodamine B, and 96% of Congo red, respectively, following 2 h of Vis exposure. Ag NPs had a strong absorption at 420 nm with 2.51 eV of energy band gap. Under UV irradiation, electrons excited and produced free radicals that promoted dyes photodegradation. The oxidation by-products included p-dihydroxybenzene and succinic acid. Spent Ag-coated CFs attained 98% of regeneration efficiency. The utilization of Ag-coated CFs as a photocatalyst facilitated treated effluents to meet the required discharge standard of lower than 1 mg/L mandated by national legislation. The integration of multifunctional CFs in the treatment system presents a new option for tackling water pollution due to dyes.

Leveraging food waste for electricity: A low-carbon approach in energy sector for mitigating climate change and achieving net zero emission in Hong Kong (China).

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.

WeedNet-R: a sugar beet field weed detection algorithm based on enhanced RetinaNet and context semantic fusion.

Accurate and dependable weed detection technology is a prerequisite for weed control robots to do autonomous weeding. Due to the complexity of the farmland environment and the resemblance between crops and weeds, detecting weeds in the field under natural settings is a difficult task. Existing deep learning-based weed detection approaches often suffer from issues such as monotonous detection scene, lack of picture samples and location information for detected items, low detection accuracy, etc. as compared to conventional weed detection methods. To address these issues, WeedNet-R, a vision-based network for weed identification and localization in sugar beet fields, is proposed. WeedNet-R adds numerous context modules to RetinaNet's neck in order to combine context information from many feature maps and so expand the effective receptive fields of the entire network. During model training, meantime, a learning rate adjustment method combining an untuned exponential warmup schedule and cosine annealing technique is implemented. As a result, the suggested method for weed detection is more accurate without requiring a considerable increase in model parameters. The WeedNet-R was trained and assessed using the OD-SugarBeets dataset, which is enhanced by manually adding the bounding box labels based on the publicly available agricultural dataset, i.e. SugarBeet2016. Compared to the original RetinaNet, the mAP of the proposed WeedNet-R increased in the weed detection job in sugar beet fields by 4.65% to 92.30%. WeedNet-R's average precision for weed and sugar beet is 85.70% and 98.89%, respectively. WeedNet-R outperforms other sophisticated object detection algorithms in terms of detection accuracy while matching other single-stage detectors in terms of detection speed.

Source, occurrence, distribution, fate, and implications of microplastic pollutants in freshwater on environment: A critical review and way forward.

The generation of microplastics (MPs) has increased recently and become an emerging issue globally. Due to their long-term durability and capability of traveling between different habitats in air, water, and soil, MPs presence in freshwater ecosystem threatens the environment with respect to its quality, biotic life, and sustainability. Although many previous works have been undertaken on the MPs pollution in the marine system recently, none of the study has covered the scope of MPs pollution in the freshwater. To consolidate scattered knowledge in the literature body into one place, this work identifies the sources, fate, occurrence, transport pathways, and distribution of MPs pollution in the aquatic system with respect to their impacts on biotic life, degradation, and detection techniques. This article also discusses the environmental implications of MPs pollution in the freshwater ecosystems. Certain techniques for identifying MPs and their limitations in applications are presented. Through a literature survey of over 276 published articles (2000-2023), this study presents an overview of solutions to the MP pollution, while identifying research gaps in the body of knowledge for further work. It is conclusive from this review that the MPs exist in the freshwater due to an improper littering of plastic waste and its degradation into smaller particles. Approximately 15-51 trillion MP particles have accumulated in the oceans with their weight ranging between 93,000 and 236,000 metric ton (Mt), while about 19-23 Mt of plastic waste was released into rivers in 2016, which was projected to increase up to 53 Mt by 2030. A subsequent degradation of MPs in the aquatic environment results in the generation of NPs with size ranging from 1 to 1000 nm. It is expected that this work facilitates stakeholders to understand the multi-aspects of MPs pollution in the freshwater and recommends policy actions to implement sustainable solutions to this environmental problem.

Decarbonization in waste recycling industry using digitalization to promote net-zero emissions and its implications on sustainability.

Digitalization and sustainability have been considered as critical elements in tackling a growing problem of solid waste in the framework of circular economy (CE). Although digitalization can enhance time-efficiency and/or cost-efficiency, their end-results do not always lead to sustainability. So far, the literatures still lack of a holistic view in understanding the development trends and key roles of digitalization in waste recycling industry to benefit stakeholders and to protect the environment. To bridge this knowledge gap, this work systematically investigates how leveraging digitalization in waste recycling industry could address these research questions: (1) What are the key problems of solid waste recycling? (2) How the trends of digitalization in waste management could benefit a CE? (3) How digitalization could strengthen waste recycling industry in a post-pandemic era? While digitalization boosts material flows in a CE, it is evident that utilizing digital solutions to strengthen waste recycling business could reinforce a resource-efficient, low-carbon, and a CE. In the Industry 4.0 era, digitalization can add 15% (about USD 15.7 trillion) to global economy by 2030. As digitalization grows, making the waste sector shift to a CE could save between 30% and 35% of municipalities' waste management budget. With digitalization, a cost reduction of 3.6% and a revenue increase of 4.1% are projected annually. This would contribute to USD 493 billion in an increasing revenue yearly in the next decade. As digitalization enables tasks to be completed shortly with less manpower, this could save USD 421 billion annually for the next decade. With respect to environmental impacts, digitalization in the waste sector could reduce global CO2 emissions by 15% by 2030 through technological solutions. Overall, this work suggests that digitalization in the waste sector contributes net-zero emission to a digital economy, while transitioning to a sustainable world as its social impacts.

Challenges and opportunities for biochar to promote circular economy and carbon neutrality.

Biochar, derived from unused biomass, is widely considered for its potential to deal with climate change problems. Global interest in biochar is attributed to its ability to sequester carbon in soil and to remediate aquatic environment from water pollution. As soil conditioner and/or adsorbent, biochar offers opportunity through a circular economy (CE) paradigm. While energy transition continues, progress toward low-emissions materials accelerates their advance towards net-zero emissions. However, none of existing works addresses CE-based biochar management to achieve carbon neutrality. To reflect its novelty, this work provides a critical overview of challenges and opportunities for biochar to promote CE and carbon neutrality. This article also offers seminal perspectives about strengthening biomass management through CE and resource recovery paradigms, while exploring how the unused biomass can promote net zero emissions in its applications. By consolidating scattered knowledge in the body of literature into one place, this work uncovers new research directions to close the loops by implementing the circularity of biomass resources in various fields. It is conclusive from a literature survey of 113 articles (2003-2023) that biomass conversion into biochar can promote net zero emissions and CE in the framework of the UN Sustainable Development Goals (SDGs). Depending on their physico-chemical properties, biochar can become a suitable feedstock for CE. Biochar application as soil enrichment offsets 12% of CO2 emissions by land use annually. Adding biochar to soil can improve its health and agricultural productivity, while minimizing about 1/8 of CO2 emissions. Biochar can also sequester CO2 in the long-term and prevent the release of carbon back into the atmosphere after its decomposition. This practice could sequester 2.5 gigatons (Gt) of CO2 annually. With the global biochar market reaching USD 368.85 million by 2028, this work facilitates biochar with its versatile characteristics to promote carbon neutrality and CE applications.

Influence of Fe2O3 and bacterial biofilms on Cu(II) distribution in a simulated aqueous solution: A feasibility study to sediments in the Pearl River Estuary (PR China).

This study investigated physico-chemical interactions among Cu(II), biogenic materials, and Fe2O3 in a continuous-flow biofilm reactor system under a well-controlled environment. The effects of Fe2O3 and bacterial biofilms on the distribution of Cu(II) in a simulated aquatic environment were studied. To control biological and abiotic elements in the marine environment, a biofilm reactor was designed to understand the metal speciation of Cu(II) and its distribution. The reactor consisted of a biofilm chamber equipped with glass slides for biofilms attachment. Due to its ability to grow as biofilm in the medium, Pseudomonas atlantica was cultivated to adsorb trace Cu(II) to attached and suspended cells. It was found that biofilms with 170-285 mequiv chemical oxygen demand (COD) concentration/m2 of total oxidizable materials accelerated the Cu(II) adsorption to the surface of the reactor significantly by a factor of five. A significant inhibition to the bacterial growth took place (p ≤ 0.05; t-test) when Cu(II) concentration was higher than 0.5 mg/L. In the absence of Cu(II), bacterial cells grew normally to 0.075 of optical density (OD). However, at the Cu(II) concentration of 0.2 mg/L, the cells grew to a lower OD of 0.58. The presence of glycine and EDTA substantially reduced the toxicity of Cu(II) on bacterial growth (p ≤ 0.05; paired t-test). Their complexation with Cu(II) rendered the metal ions less available to bacterial cells. This implies that the Fe2O3 and bacterial biofilm affected Cu(II) distribution and speciation in the aquatic environment.

Biosorption of heavy metals from aqueous solutions using activated sludge, Aeromasss hydrophyla, and Branhamella spp based on modeling with GEOCHEM.

This work tests the technical applicability of sewage sludge and isolated dead cells of Aeromasss hydrophyla and Branhamella spp for the elimination of inorganic pollutants such as Zn(II), Pb(II), Cd(II), and/or Cu(II) using synthetic wastewater with their initial concentrations of 100 mg/L, respectively. The sludge samples were collected from local sewage treatment plants. The effects of dose and pH on heavy metals removal were evaluated in batch studies and their removal performances were compared to those of previous studies. Both the Freundlich and the Langmuir models were plotted to study their biosorption using activated sludge and the bacteria. Isotherm data, resulting from the batch studies, were compared to the modeling results of Geochem. It was evident that the activated sludge could achieve 99% of Zn(II), Cd(II), Cu(II) and Pb(II) removal with 100 mg/L of concentration at pH 6.0 and 3 g/L of dose. Under the same conditions, 97% of Cd(II), Cu(II) and/or Pb(II) was removed by Aeromasss hydrophyla and Branhamella spp, as indicated by their adsorption capacities (activated sludge: 99.07 mg Pb2+/g; dewatered sludge: 57.15 mg Pb2+/g; digested sludge: 83.58 mg Pb2+/g; 24.47 mg Cd2+/g; Aeromasss hydrophylla: 71.91 mg Pb2+/g; Branhamella spp: 37.52 mg Cu2+/g). Of the four heavy metals studied, Pb(II) had the highest metal adsorption capacity for all adsorbents studied (Pb2+>Cu2+> Cd2+>Zn2+). The modeling results of the Geochem fitted well with the isotherm data of the batch studies at varying concentrations from 20 to 100 mg/L. The thermodynamic constant at pH 4 were comparable to those obtained from previous works. This indicates a reliable prediction over varying metal concentrations and pHs of the batch studies. In spite of the promising results, the treated effluents still could not meet the required effluent limits set by local legislation. Therefore, it is necessary to subsequently treat the samples using biological processes such as activated sludge.

Application of choosing by advantages to determine the optimal site for solar power plants.

Solar energy is a critical component of the energy development strategy. The site selection for solar power plants has a significant impact on the cost of energy production. A favorable situation would result in significant cost savings and increased electricity generation efficiency. California is located in the southwest region of the United States of America and is blessed with an abundance of sunlight. In recent years, the state's economy and population have expanded quickly, resulting in an increased need for power. This study examines the south of California as a possibly well-suited site for the constructing large solar power plants to meet the local electricity needs. To begin, this article imposed some limits on the selection of three potential sites for constructing solar power plants (S1, S2, and S3). Then, a systematic approach for solar power plant site selection was presented, focusing on five major factors (economic, technological, social, geographical, and environmental). This is the first time that the choosing by advantages (CBA) method has been used to determine the optimal sites for solar power plant construction, with the possible sites ranked as S2 > S1 > S3. The results were then compared with traditional methods such as the multi-criteria decision-making method. The findings of this study suggest that the CBA method not only streamlines the solar power plant site selection process but also closely aligns with the objectives and desires of the investors.

Harnessing landfill gas (LFG) for electricity: A strategy to mitigate greenhouse gas (GHG) emissions in Jakarta (Indonesia).

Due to its increasing demands for fossil fuels, Indonesia needs an alternative energy to diversify its energy supply. Landfill gas (LFG), which key component is methane (CH4), has become one of the most attractive options to sustain its continued economic development. This exploratory study seeks to demonstrate the added value of landfilled municipal solid waste (MSW) in generating sustainable energy, resulting from CH4 emissions in the Bantargebang landfill (Jakarta). The power generation capacity of a waste-to-energy (WTE) plant based on a mathematical modeling was investigated. This article critically evaluated the production of electricity and potential income from its sale in the market. The project's environmental impact assessment and its socio-economic and environmental benefits in terms of quantitative and qualitative aspects were discussed. It was found that the emitted CH4 from the landfill could be reduced by 25,000 Mt annually, while its electricity generation could reach one million kW â‹…h annually, savings on equivalent electricity charge worth US$ 112 million/year (based on US' 8/kW ⋅ h). An equivalent CO2 mitigation of 3.4 × 106 Mt/year was obtained. The income from its power sale were US$ 1.2 ×106 in the 1st year and 7.7 ×107US$ in the 15th year, respectively, based on the projected CH4 and power generation. The modeling study on the Bantargebang landfill using the LFG extraction data indicated that the LFG production ranged from 0.05 to 0.40 m3 per kg of the landfilled MSW. The LFG could generate electricity as low as US' 8 per kW ⋅ h. With respect to the implications of this study, the revenue not only defrays the cost of landfill's operations and maintenance (O&M), but also provides an incentive and means to further improve its design and operations. Overall, this work not only leads to a diversification of primary energy, but also improves environmental protection and the living standard of the people surrounding the plant.