Environmental Analysis Research Articles

Machine learning, mathematical modeling and 4E (energy, exergy, environmental, and economic) analysis of an indirect solar dryer for drying sweet potato

A developed indirect solar dryer is built and operated to dry sweet potato cubes. Since, numerous instruments have gathered experimental data to comprehensively evaluate the system's energy, exergy, environmental, and economical aspects. Additionally, four machine learning algorithms, namely Decision Trees (DT), Gradient Boosting Regression (GBR), Multiple Linear Regression (MLR), and Random Forest (RF), are evolved to forecast the solar collector's energy (RSAH,η) and exergy efficiency (RSAH,ηEX) as well as the drying chamber's mean drying temperature and exergy efficiency (DC,ηEx). In addition, ten drying kinetics mathematical models were employed to fit with sweet potato moisture ratio variation over the experiment. Also, Color and bioactive compounds were analyzed. Results show that, RSAH,η and RSAH,ηEX was 72.9 %, and 5.6 %, respectively. Storage unit thermal (ηTh.,SUPCM)and exergy efficiency (ηEx,SUPCM) were 43.4 %, and 18.4 %, respectively, the discharging lasted around 5.5 h. Theoretical drying chamber thermal efficiency (DC,ηth) was from 21.9 to 97.2 %. And av. DC,ηEx was 46.1 %. RF algorithm achieved the best results for RSAH,η, RSAH,ηEX , DC,Tmean, and DC,ηEx forecasting, because of its superior adaptability and generalization. The overall dryer efficiency was 15 % with a specific energy consumption of 4.509 kWh/kg moisture. The Page model showed the best fitting with sweet potato moisture ratio data. In addition, CO2 mitigation reached 20.2 with earned carbon credit is 56771 RMB. The economic payback period is 29.24 months, the annual total revenue is 8464 RMB and 0.7 RMB as a Return on investment.

Analysis of market environment for smart grid technology investments via facial action coding system-enhanced hybrid decision-making model

Analysis of market environment for smart grid technology investments via facial action coding system-enhanced hybrid decision-making model

Environmental performance analysis of textile envelope integrated flexible photovoltaic using life cycle assessment approach

The textile envelope integrated flexible photovoltaic (TE-FPV) system is an emerging technology to promote building sustainability due to its lightweight structure, textile recovery easily, and renewable energy production. We develop six novel TE-FPV prototypes to determine their advantages of environmental performance. Especially, the systems with the solar cells directly printed on the textile are designed to show the promising sustainability prospect. Their environmental performances are conducted by a cradle-to-cradle life cycle assessment, and the results are compared to traditional building integrated photovoltaic (BIPV) technologies. The life cycle inventories of some textiles and solar cells are the first time to be developed. Based on the inventories, life cycle impact assessment is implemented to figure out environmental impacts in various categories. Furthermore, uncertainty analyses and sensitivity analyses are performed to unmask the effects of parameters on the fluctuation of environmental indicators. The results present that most of TE-FPV systems perform more sustainable and more recyclable over the traditional BIPV systems. The organic solar cell is unfavorable for the TE-FPV systems due to its low power conversion efficiency and short lifespan. ETFE facade integrated perovskite solar cell systems can refund the investment of greenhouse gas emission even on the north orientation, showing vast prospective potential in environmental performances. This work contributes significantly required environmental quantifications to promote the advancement of TE-FPV systems.

Investigation of a novel scheme utilizing solar and geothermal energies, generating power and ammonia: Exergoeconomic and exergoenvironmental analyses and cuckoo search optimization

The integration of solar and geothermal energy sources presents a promising avenue for enhancing the efficiency and output of energy systems. This research introduces a novel hybrid system combining solar and geothermal energy for the co-generation of power, cooling, and ammonia. The proposed system integrates several cycles and technologies, including an organic Rankine cycle, an ejector refrigeration cycle, an organic flash cycle, a proton exchange membrane electrolyzer, and an ammonia synthesis reactor. Through a comprehensive 4E (energy, exergy, economic, and environmental) analysis, utilizing thermodynamic, exergoeconomic, and exergoenvironmental methodologies, this study evaluates the system's performance. The findings reveal that solar collectors are the primary contributors to system irreversibility, accounting for 78 % of the total. Notably, an increase in the condenser outlet temperature significantly decreases the cooling load, whereas elevating the turbine 1 exit pressure enhances overall power production. At optimal operating conditions, the system generates a net power of 104 kW, provides 26.07 kW of cooling capacity, and produces 3.55 kg/h of ammonia. This performance translates into a product cost of 1.193 USD/h and an exergoenvironmental impact rate of 25.31 mPts/h, alongside achieving an exergy efficiency of 9.34 %. Financially, the system promises a payback period of 2.34 years and a net present value of 1.259 million USD, highlighting its economic viability and environmental benefits.

Energy, exergy, environmental and exergoeconomic (4E) analysis of an ultra-low temperature cascade refrigeration system with environmental-friendly refrigerants

To ensure the efficacy of some special vaccines, the ultra-low temperature storage below −80 °C is strictly required and the classical cascade refrigeration system has a good application prospect in the production, storage, transportation and distribution of COVID-19 vaccines. Previous investigations are mainly focused on the thermodynamic performance of cascade refrigeration cycles (CRSs) to generate low temperature, and the impact of cascade refrigeration cycles on environmental and exergoeconomic aspects is few involved. In this paper, an energy-exergy-environmental-exergoeconomic (4E) analysis model was built to investigate the comprehensive performance of an ultra-low temperature cascade refrigeration system. Eight environmental-friendly refrigerant pairs, including R290-R170, R290-R1150, R717-R170, R717-R1150, R1270-R170, R1234yf-R170 and R1234yf-R1150, were chosen and the associated refrigeration performance was compared. The results show that the optimal refrigerant pair is propane-ethane (R290-R170). Compared with HFC refrigerant pair R404A-R508B CRS, R290-R170 CRS could improve the COP by 5.94%, save 5.68% power consumption, reduce 29.67% carbon dioxide emission and decrease 5% exergy economic cost. This work is significant to select environmental-friendly nature refrigerants, enrich understanding of comprehensive performance of cascade refrigeration system and enhance depth research on ultra-low temperature refrigeration.

Genetic mapping reveals the complex genetic architecture controlling slow canopy wilting in soybean

In soybean [Glycine max (L.) Merr.], drought stress is the leading cause of yield loss from abiotic stress in rain-fed US growing areas. Only 10% of the US soybean production is irrigated; therefore, plants must possess physiological mechanisms to tolerate drought stress. Slow canopy wilting is a physiological trait that is observed in a few exotic plant introductions (PIs) and may lead to yield improvement under drought stress. Canopy wilting of 130 recombinant inbred lines (RILs) derived from Hutcheson × PI 471938 grown under drought stress was visually evaluated and genotyped with the SoySNP6K BeadChip. Over four years, field evaluations of canopy wilting were conducted under rainfed conditions at three locations across the US (Georgia, Kansas, and North Carolina). Due to the variation in weather among locations and years, the phenotypic data were collected from seven environments. Substantial variation in canopy wilting was observed among the genotypes in the RIL population across environments. Three QTLs were identified for canopy wilting from the RIL population using composite interval mapping on chromosomes (Chrs) 2, 8, and 9 based on combined environmental analyses. These QTLs inherited the favorable alleles from PI 471938 and accounted for 11, 10, and 14% of phenotypic variation, respectively. A list of 106 candidate genes were narrowed down for these three QTLs based on the published information. The QTLs identified through this research can be used as targets for further investigation to understand the mechanisms of slow canopy wilting. These QTLs could be deployed to improve drought tolerance through a targeted selection of the genomic regions from PI 471938.

Techno-Economic and Environmental Analysis of a Hybrid Power System Formed From Solid Oxide Fuel Cell, Gas Turbine, and Organic Rankine Cycle

Abstract Distributed energy technology is an essential pathway for future advancements in the field of energy technology. In the present study, organic Rankine cycle (ORC) is integrated with solid oxide fuel cell (SOFC)-gas turbine (GT) hybrid power system. The conventional metrics employed for assessing the performance of SOFCs, gas turbines, and organic Rankine cycles, such as voltage and gross real efficiencies, have some limitations as indices of merit. Contemporary second law concepts and economic and environmental analysis have been used to enhance hybrid power system evaluation. R1233zd(E) has been selected as the ORC working fluid. The outcomes reveal that, under certain conditions, the present configuration may reach 55.67% energy efficiency and 53.55% exergy efficiency. Economic and environmental analysis shows that the hybrid system's total cost rate and Emissions of CO2 gas (EMI) under design conditions are 36.09 $/h and 355.8 kg/MWh, respectively. Thermodynamic evaluation of present SOFC-GT-ORC configuration shows 11.72% improvement in exergy efficiency compared to hybrid SOFC-GT cycle. Consequently, the hybrid SOFC-GT-ORC system is far better than the hybrid SOFC-GT system. In the future, other ORC fluids like R123, R601a, and R245fa can be used as ORC fluids.

Microbe and bioprocess performances for sustainable production of biobased 2,3-butanediol in a sugarcane biorefinery; a technoeconomic and environmental analysis

AbstractIndustrial production of bio-based 2,3-butanediol via microbial conversion of sugars is intended to provide viable investment opportunities accompanied by reduced greenhouse gas emissions, compared to current fossil-based products. The potential impacts on the product minimum selling price and life cycle greenhouse gas emissions of further technology developments resulting in enhanced product yield, volumetric productivity and/or titres were assessed though a 33 full-factorial design. Aspen Plus® was employed to simulate multiple scenarios for 2,3-butanediol production from A-molasses in a biorefinery annexed to an existing sugarcane mill for subsequent techno-economic analysis. A 10% singular improvement in product yield, titre and volumetric productivity reduced the minimum selling price by 3.6%, 1.4% and 0.1%, whereas titre improvements reduced greenhouse gas emissions twice as much as product yield for a 10% step change. At the current state of technology, biobased 2,3-butanediol can achieve the minimum performance required to be a feasible alternative to fossil-based 2,3-butanediol with an estimated best minimum selling price of 1434$ t−12,3-BDO and greenhouse gas emissions 6.5 times less than those recorded for fossil-derived 1,4-butanediol. The minimum selling price and greenhouse gas emissions values can be reduced further by at least 16% and 14%, respectively, warranting further investment in strain and bioprocess performance enhancement. Overall, the research demonstrated that technological efforts intended to enhance the viability of biobased 2,3-butanediol production also minimized greenhouse gas emissions, integrating environmental and economic objectives for a sustainable bioeconomy. Graphical abstract

The Capacity of Alkali‐Activated Industrial Wastes in Novel Sustainable Ceramic Membranes

AbstractNovel ceramic membranes present unquestionable potential in wastewater treatment among the emerging technologies, while a few challenges such as cost, energy consumption, durability, and resistance in harsh mediums still limit their commercialization. Here, we review the capability of available industrial aluminosilicate waste materials in the fabrication of novel ceramic membranes using green and economical alkali‐activation synthesis method. The different sources of alkali‐activated aluminosilicate wastes including ashes, mining wastes, glass and ceramic wastes, slags, construction wastes, industrial byproducts, and agricultural wastes are introduced and the chemistry of geopolymers is reviewed. In this review, the major points are the following. 1) The alkali‐activated structures present reasonable chemical, frost, carbonation, and mechanical resistance as well as the ability to immobilize the toxic materials. 2) The synthesis aspects of porous and nonporous alkali‐activated ceramic membranes are explored by characterization methods. Furthermore, the durability analysis in harsh environments reveals that alkali‐activated ceramic membranes possess high resistance against acidic, alkaline, and other antifouling chemical washing methods. In summary, it is demonstrated that the studied membranes have an undeniable capability in the separation of organic solvents in the pervaporation process as well as toxic material removal from water with high ion‐exchange capacity.

A novel zero emission combined power and cooling system for concentrating solar power: Thermodynamic and economic assessments and optimization

This study aims to develop a zero-emission multi-generation system based on concentrated solar power to reduce solar thermal power cost and improve the efficiency of power generation. The multi-generation system mainly includes concentrated solar power system, supercritical carbon dioxide recompression Brayton cycle, organic flash cycle and absorption refrigeration cycle. A comprehensive energy, exergy, environment and economic analysis is carried out. Five key parameters are considered to assess the effect of decision parameters on system performance. An optimization method combining genetic algorithm and machine learning is used to accelerate the optimization process. Results display that compared with the stand-alone supercritical carbon dioxide recompression Brayton cycle, the energy utilization factor and exergy efficiency of the multi-generation system can improve 18.7 % and 6.4 %, respectively, and the decrement of levelized cost of electricity is reduced by 4 %. A higher turbine-Ⅰ inlet temperature can improve the exergy efficiency and reduce the levelized cost of electricity. Using the proposed optimization method, the long optimization time of complex multi-generation system is overcome. Comparing the exergy efficiency optimization case with the basic case and the cost optimization case, the exergy efficiency optimization case has the highest net power output and exergy efficiency. This work exhibits great potential in utilizing solar energy for power and cooling.

Wasted Food, Wasted Resources? A Critical Review of Environmental Impact Analysis of Food Loss and Waste Generation and Treatment.

Food loss and waste (FLW) comes with significant environmental impacts and thus prevents a sustainable food system transition. Here we conducted a systematic review of 174 screened studies that assessed the environmental impacts of FLW generation and treatment. We found that the embodied impacts of FLW along the supply chain and impacts from FLW treatment received equal attention, but few studies have included both. The reviewed studies show narrow geographical (mostly conducted in industrialized countries) and food supply chain (mostly focused on the consumption stage) coverage. Life cycle analysis (LCA), material flow analysis (MFA), or their combination are the most commonly used to quantify FLW related environmental impacts. More method standardization, integration, and innovation and better FLW data with regional and stage resolution from a first-hand source are badly needed. Among the various proposed mitigation strategies covering technology, economy, behavior, and policy aspects, process optimization and waste management options are the most discussed. Our review calls for a more holistic environmental impact assessment of FLW generation and treatment and analysis of the trade-offs among different environmental impact categories and between supply chain stages, which would better inform relevant policy on effective environmental impact mitigation strategies toward sustainable food systems.

An eco-friendly colorimetric strategy based on gold nanoparticles modified with 3-pyridinylboronic acid for detecting copper ions

Copper is an essential element in the human body. Excess accumulations of copper, however, would become a potential threat. Therefore, it is of great significance to detect copper ions. Owing to their controllable morphology, dispersal characteristics, high extinction coefficient, and easily functionalized surfaces, gold nanoparticles (AuNPs) have been highly employed as attractive sensing probes for environmental and biological analyses. We herein propose an eco-friendly colorimetric strategy based on AuNPs modified with 3-pyridinylboronic acid (PA) for sensitive and selective detection of copper ions (Cu2+) in water at trace level. The color changes of the system from wine-red to gray-blue with increasing amounts of copper ions is due to the binding of AuNPs modified with 3-pyridinylboronic acid to copper ions, which in turn leads to the aggregation of AuNPs with fine anti-interference. Strengths of the work: 1) rapid response time without complex pre-treatment; 2) high sensitivity with low limit of detection (LOD) and the good linear relationship (R2 = 0.98, LOD = 3.0 μM by the naked eye and 72 nM by ultraviolet-visible spectroscopy); 3) high selectivity under other interfering ions. In addition, the detection mechanism of this work has been successfully confirmed by density functional theory (DFT), transmission electron microscopy (TEM), dynamic light scattering (DLS), X-ray diffraction (XRD), Zeta potential analysis and ultraviolet-visible spectroscopy (UV–vis).

The integration of solar-hydrogen hybrid renewable energy systems in oil and gas industries for energy efficiency: Optimal sizing using Fick's Law optimisation Algorithm

The global demand for sustainable energy solutions in the oil and gas industry has stimulated interest in the integration of renewable energy sources. This paper investigates the techno-economic and environmental aspects of incorporating a solar-hydrogen-based hybrid renewable energy system (SHRES) into oil and gas processing facilities.The proposed SHRES, comprising Solar PV modules, hydrogen production and storage systems, and a gas turbine generator (PV-FC-EL-Tank-GT), aims to enhance energy efficiency and reduce the carbon footprint of energy-intensive operations. The study utilises a multidisciplinary approach, encompassing engineering, economics, and environmental analysis. The techno-economic evaluation employs detailed modelling and optimisation using Fick's Law Algorithm, ensuring efficient energy production and cost-effectiveness. Ecological assessments quantify potential reductions in greenhouse gas emissions and other environmental impacts.The technical and economic evaluation identifies the electrolyser system as the most significant cost contributor (57%). The optimised system balances energy sources with 45% from PV modules, 35% from fuel cells, and 20% from gas turbines, showcasing substantial reliance on renewable energy while maintaining required power generation.Addressing the urgent need for sustainable energy solutions in the oil and gas industry, the study highlights the potential of SHRES integration. By employing Fick's Law Algorithm, alongside with 80 % of renewable energy integration, the research optimises system components to optimise the annualised cost to be $57,539.85, decrease to zero the Loss of Power Supply Probability (LPSP), and mitigate CO2 emissions to a lowest value of 0.147 gCO2eq/kWh (by 80 %). The electrolyser system's pivotal role and the distribution of power generation sources are emphasised.This study presents a novel approach to integrating solar-hydrogen systems into oil and gas processing facilities, aiming for sustainability. The findings underscore the significance of the electrolyser system and the distribution of power generation sources in optimising the SHRES. Recommendations for renewable energy integration and potential reductions in CO2 emissions and costs are discussed, providing valuable insights for future energy policies.

Development of a Multichannel Organics In situ enviRonmental Analyzer (MOIRA) for mobile measurements of volatile organic compounds

Abstract. Volatile organic compounds (VOCs) have diverse functionality, emission sources, and environmental fates. Speciated measurements of their spatiotemporal variability are thus key to understanding their impacts on air quality, health, and climate. Networks of passive samplers can be used to map VOC concentrations, or in situ instruments can be deployed on mobile platforms. Limitations of existing in situ instruments include high cost, identification of non-target species, differentiation of isomeric species, and low time resolution, which limits how quickly an area can be spatially mapped with mobile measurements. This work describes the development of the Multichannel Organics In situ enviRonmental Analyzer (MOIRA), which has been designed for in situ mobile measurements of target and non-target VOCs from the cargo area of a hybrid hatchback wagon vehicle. Staggered sample collection and analysis by four thermal desorption collectors, four miniature gas chromatography (GC) heaters, and two compact residual gas analyzer (RGA) mass spectrometer (MS) detectors enable continuous measurements at a 10 min time resolution. Non-target species and structural isomers can be identified with electron ionization (EI), and species detected include alkanes (from pentane to pentadecane) and aromatics, as well as more oxidized species such as aldehydes, esters, and carboxylic acids. The instrument is characterized in the laboratory under different environmental conditions and in two pilot field studies of indoor air in a single-family residence and of ambient air during a mobile deployment.

A novel albumin-based supramolecular biosensor for ratiometric on-site determination of buprofezin

Buprofezin (BUP) is an effective insecticide against Homopteran and Thysanoptera pests. However, exposure to BUP may result in several harmful effects on the non-target organism including human body, such as hepatotoxicity and DNA damage. Therefore, development of a reliable analytical method for BUP holds paramount importance. This study presents a novel albumin-based supramolecular biosensor, DPP@ALB, designed for the sensitive detection of BUP in environmental matrices, including water, soil, and real food samples. The features of this biosensor include a fast response, high sensitivity, and visually detectable fluorescence color change, enabling on-site detection of BUP based on the portable paper strips and 3D-printed miniaturized testing system. Overcoming challenges associated with the low chemical reactivity of BUP, this supramolecular biosensor emerges as the very first fluorescent sensor for efficient and reliable monitoring of BUP with applications in broader areas of environmental analysis and food safety.

The Predictability of Naturalistic Evaluation of All-Day Recordings for Speech and Language Development.

The study aimed to investigate the predictive potential of language environment and vocal development status measures obtained through integrated analysis of Language ENvironment Analysis (LENA) recordings during the prelinguistic stage for subsequent speech and language development in Korean-acquiring children. Specifically, this study explored whether measures from both LENA-automated analysis and human coding at 6-8 months and 12-14 months of age predict vocabulary and phonological development at 18-20 months. One-day home recordings from 20 children were collected using a LENA recorder at 6-8 months, 12-14 months, and 18-20 months. Both LENA-automated measures and measures from human coding were obtained from recordings at 6-8 months and 12-14 months. The number of different words, consonant inventory, and utterance structure inventory were identified from recordings of 18-20 months. Correlation and multiple regression analyses were performed to investigate whether measures related to early language environment and child vocalization at 6-8 months and 12-14 months were predictive of vocabulary and phonological measures at 18-20 months. The results showed that the two main LENA-automated measures, conversational turn count (CTC) and child vocalization count, were positively correlated with all vocabulary and phonological measures at 18-20 months. Multiple regression analysis revealed that CTC during the prelinguistic stages was the most significant predictor of a number of different words, consonant inventory, and utterance structure inventory at 18-20 months. Also, adult word count in LENA-automated measures, child-directed speech ratio, and canonical babbling ratio measured by human coding significantly predicted some vocabulary and phonological measures at 18-20 months. This study highlights the multifaceted nature of language acquisition and collectively emphasizes the value of considering both quantitative and qualitative aspects of language input to understand early language development in children.

Immersive Emotion Analysis in VR Environments: A Sensor-Based Approach to Prevent Distortion

As virtual reality (VR) technology advances, research has focused on enhancing VR content for a more realistic user experience. Traditional emotion analysis relies on surveys, but they suffer from delayed responses and decreased immersion, leading to distorted results. To overcome these limitations, we propose an emotion analysis method using sensor data in the VR environment. Our approach can take advantage of the user’s immediate response and not reduce immersion. Linear regression, classification analysis, and tree-based methods were applied to electrocardiogram and galvanic skin response (GSR) sensor data to measure valence and arousal values. We introduced a novel emotional dimension model by analyzing correlations between emotions and the valence and arousal values. Experimental results demonstrated the highest accuracy of 77% and 92.3% for valence and arousal prediction, respectively, using GSR sensor data. Furthermore, an accuracy of 80.25% was achieved in predicting valence and arousal using nine emotions. Our proposed model improves VR content through more accurate emotion analysis in a VR environment, which can be useful for targeting customers in various industries, such as marketing, gaming, education, and healthcare.

Novel (2,6-difluorobenzoyl)urea-activated fluorescent probe for fluorine-containing-pesticide detection

Fluorine-containing pesticides (FCPs) are widely employed in modern agriculture because of their good bioactivity. However, their harmful impacts on humans and the ecosystem are increasing persistently owing to their overcommitment and bioconcentration in water and the soil. Concurrently, as the molecular probes for detecting FCPs are extremely rare, a multifunctional probe, N-(purinyl)-2-chromene-3-carbohydrazide (PCC), was designed and synthesized in this study to simultaneously detect two FCPs, teflubenzuron and fluazuron. PCC exhibited good sensitivity and selectivity toward both substances based on the supramolecular interaction driven by intermolecular hydrogen bonding. Furthermore, the detection limits for teflubenzuron and fluazuron were as low as 91.6 and 43.2 nM, respectively. Additionally, PCC could detect teflubenzuron in real water samples and detect ferric ions (Fe3+) in living cells, with low cytotoxicity. This method for detecting FCP and Fe3+ exhibited great potential for its mild conditions and facile operation; moreover, it did not require any pretreatment and large instruments. Thus, this study presents a novel probe and a convenient method for detecting teflubenzuron and fluazuron with good sensitivity and via a facile operation, which are conducive and may be employed in environmental analysis.

Effect of waste clay brick powder on microstructure and properties in blended oil well cement pastes at HTHP conditions

The use of waste materials to improve the thermal stability of oil well cement (OWC) at high temperature and high pressure (HTHP) conditions has received increasing attention. This study investigated the performance of sustainable blended OWC pastes by recycling waste clay brick powder (CBP) as a partial substitute for commercial high temperature resistant additives (silica flour, SF). The main objective was to assess the impact of these substitutions on the hydration, microstructure and mechanical properties of blended OWC. CBP was incorporated at substitution rates of 25 wt%, 50 wt%, 75 wt% and 100 wt% by weight of SF. These pastes were firstly precured at 50 °C for 7 days (to simulate the primary cementing operation prior to steam injection), and then thermally cycling cured at 300 °C/13.0 MPa (to simulate the steam injection process). The study conducted comprehensive tests and analyses, including compressive strength, gas permeability, hydration products and microstructural analyses. The results showed that the suitable substitution rate of CBP in this study was 25 wt%-50 wt%. At these substitution levels, the blended OWC pastes had good compressive strength (18.5 MPa and 17.9 MPa) and low gas permeability (3.1 × 10−3 mD and 4.51 × 10−3 mD). From the environmental and economic analyses, the energy intensity and CO2 emissions of all blended OWCs were significantly lower compared to those of conventional OWC. Meanwhile, the cost of blended OWC in this study was significantly lower compared to that of the commercial SF-OWC system. Overall, this study highlighted the potential of recycling waste materials to promote raw material sustainability and improve the performance of OWC pastes at HTHP conditions.

Comparative environmental analysis of sugar beet production using a solar-driven robot and conventional systems from a sustainability perspective

In the context of rapid global population growth and climate change, balancing agricultural productivity with environmental sustainability has never been more important. Precision farming technologies, including robotics, are touted as having huge potential to increase farm productivity, reduce energy and resource use and compact soil, while reducing the overall environmental impact of on-farm production. This comprehensive study presents, for the first time, a detailed analysis and environmental benchmarking of two organic sugar beet production (SBP) systems, conventional (CONV) and robotic (RBT), based on field experiments in Lithuanian conditions where a solar-powered robot is integrated into the production system to carry out sowing and weeding operations. In order to reduce the potential environmental impact and to understand the consequences of using the robot in agriculture, a Life Cycle Assessment (LCA) of the entire SBP process up to the factory gate was carried out. The results of the analysis show that the conventional system has higher total GHG emissions than the robotic system, 36.98 and 27.18 kg CO2eq t−1, respectively, with poultry manure being the largest contributor. The higher beet yield in the RBT system, mainly due to effective weed control, resulted in a higher GHG emissions ratio (14.72) and a higher sustainability index (13.72). The LCA results showed that the CONV system had a higher negative environmental impact than the RBT in all eleven environmental impact categories assessed, with the most pronounced difference in the Ozone Depletion (OD) category. Diesel fuel was identified as the most important environmental factor for organically growing sugar beet in all considered impact categories, with the most notable environmental impact (about 94%) in the terrestrial ecotoxicity category in both systems. Normalization of the results showed that marine aquatic ecotoxicity (ME) had the greatest (78%) influence of all exposure categories for both cultivation systems, CONV – 22079.82, and RBT 18121.61 kg 1.4-DBeq per ton of produced sugar beet. The study found that increasing yields and reducing fossil fuel use in organic farming are the two most promising strategies for achieving sustainability and efficiency in food production.