Hasil untuk "Environmental effects of industries and plants"

K. Kathiresan, B. Bingham

J. A. Kumar, T. Krithiga, S. Manigandan et al.

Abstract Nanomaterial synthesis using a greener route has received massive attention as a sustainable, feasible, reliable, cost-effective, wealthy and environmentally friendly paradigm. Perhaps, synthesis via a greener route is considered as a sophisticated tool to minimize the toxic effects agglomerated with the conventional procedures of synthesis adapted for nanomaterials generally preferable in industry and laboratory. This work outlines the basic processes on the advanced patterns of the eco-friendly and various approaches involved in the green synthesis and its mechanism particularly accounted to metal and metal-based oxides like silver (Ag), gold (Au), zinc oxide (ZnO) and copper oxide (CuO) nanoparticles with the aid of plant extracts. This review article encompasses the essential purpose of biological approaches, green roue for nanoparticle synthesis, the impact of various operating parameters, and solvent-based techniques. The toxicity/stability of nanomaterials and the occluded surface engineering protocols for deriving biocompatibility along with various solvent systems have also been outlined. Various mechanisms involved for green synthesis, merits of greener chemistry and its application in various fields are emphasized. Finally, the prospects of green route strategies for metal/metal oxide nanomaterials synthesis are proposed for further development. The challenges in utilizing the green synthesized metal/metal oxide nanoparticles are discussed. The recommendations of the green chemistry towards the cleaner production are emphasized.

Ayşe Lisa Allison, Abbie Curtis O'Reilly, Alicia Abicht et al.

Disposable absorbent hygiene products, particularly diapers, are a major contributor to global plastic waste. Focusing on high-priority strategies within the EU's waste hierarchy, waste prevention and reuse, we examine two behaviours that reduce reliance on single-use diapers: earlier toilet training and reusable diaper use. We identified behavioural patterning, influencing factors and support for interventions using a mixed-methods study of UK parents (surveys: n = 624; interviews: n = 35), underpinned by behavioural science frameworks (COM-B model, Behaviour Change Wheel). Reusable diapering remains a minority practice, with few users using them exclusively (10% of reusable users) and most combining with disposable diapers. Reusable diaper use was associated with earlier toilet training (χ2(1, N = 322) = 4.05, p = .044). While parents intend to begin toilet training by 30 months, our findings show that completion often occurs significantly later, highlighting a gap between intended and actual timelines (χ2(18, N = 624) = 72.80, p < .001). Barriers and enablers to both behaviours were identified across Capability (e.g., laundry demands, identifying readiness), Opportunity (e.g., product access, childcare support), and Motivation (e.g., environmental values, competing priorities). Recommended interventions include expert-led training, public awareness campaigns, reusable diaper provision and laundering schemes, and flexible work policies. Regulatory measures (e.g., diaper taxes, nursery admission policies) were less favoured. Creating supportive, resource-rich settings at key parenting stages, such as ante- and postnatal periods and early toddlerhood, can empower parents to adopt reusable diapers and earlier toilet training, aligning caregiving with broader sustainability goals of reducing plastic waste.

Lizzie Neumann, Philipp Wittenberg, Jan Gertheiss

System outputs such as eigenfrequencies or strain data, often used in structural health monitoring (SHM), not only react to damage but also depend on environmental conditions. When trying to correct for these confounding effects, it is often (at least implicitly) assumed that only the expected, i.e., mean, output values are affected by environmental conditions. However, the evaluation of real-world SHM data indicates that environmental conditions may influence not only the mean output but also higher-order statistical moments, particularly the variances of and the covariances and correlations between the output quantities, such as eigenfrequencies of different modes or strain sensors at different locations. To address these issues, we discuss two approaches for identifying and quantifying multivariate confounding effects on output covariances and correlations: a random forest and a nonparametric, kernel-based approach. We compare the two competing methods on both artificial and real-world SHM data, finding that the kernel-based approach achieves higher accuracy, but the random forest produces estimates that are more robust and sometimes easier to interpret.

Stelian Alexandru Borz, Salvatore Papandrea, Michele Zoli et al.

Wood chip production from short-rotation coppice (SRC) can be an interesting opportunity for farmers and for the environment. SRC cultivation in fertile arable land, with full mechanisation of the operations, results in higher yields. However, the establishment of SRC is more rational in marginal areas where the conventional crops cannot provide suitable results. In this context, the mechanisation of SRC plays a relevant role, and the availability of small machinery is a key element.In this study, two different willow SRC management regimes, characterised by the adoption of small mechanisation solutions for crop management and harvesting, were compared. The life cycle assessment (LCA) was applied considering 1 cubic metre of wood chips as the functional unit (FU) and a ‘from cradle to gate’ perspective regarding the system boundary. Primary data were directly collected via field trials and interviews with the farmers.The results highlighted how the mechanisation of different field operations is the main cause of environmental impact, which is primarily due to the felling and chipping of stems. The 3-year SRC harvesting regime, despite lower productivity, presents better environmental performance compared to the 2-year one for all the evaluated impact categories, owing to a reduction of the environmental impact related to harvesting.

Erina Riak Asie, Nyahu Rumbang, Hastin E.N.C. Chotimah et al.

Degraded peatlands are natural resources that must be managed properly. The unique characteristics of degraded peatlands, such as high acidity and low availability of macro and micronutrients, are the main challenges in soybean cultivation. The pot experiment was conducted using a completely randomized design consisting of four dolomite dosage levels, namely 0, 3, 6, and 9 t/ha, with five replications. The research objective was to assess the effect of dolomite application on the chemical properties of degraded peatland, physiological characteristics, and soybean yield. The results showed that dolomite application significantly improved the chemical properties of degraded peatlands and increased the physiological characteristics and yield of soybeans. Dolomite at a dose of 6 or 9 t/ha achieved the highest pH, exchangeable Ca, and exchangeable Mg after incubation and after harvest. The highest total chlorophyll and average net assimilation rate were obtained at 9 t/ha dolomite application of 3.95 mg/g and 0.048 g/cm2/day, respectively. The relationship between dolomite and the total chlorophyll content of soybean plants was very strong (r = 0.94) with the equation y = 0.35 + 0.37x. The highest soybean seed weight was observed when dolomite was applied at a dose of 9 t/ha, resulting in 9.72 g/plant, an increase of 219.70% compared to the control. These findings suggest that optimal dolomite application can enhance the fertility of degraded peatlands and improve soybean productivity while supporting the sustainable management and rehabilitation of these ecosystems.

Mohamed H. Abdullah, Nouran E. Abdelhamid, Rasha M. Samir et al.

We present a comprehensive study of the galaxy size-stellar mass relation (SMR) at low redshift (z <= 0.125), using a large spectroscopic sample from the SDSS-DR13 survey. Our goal is to investigate how environment affects galaxy structural properties across multiple spatial scales. Galaxies are classified by specific star formation rate, optical color, and bulge-to-total light ratio, allowing us to disentangle environmental effects from intrinsic galaxy properties. We examine the SMR in three contexts: (1) comparing galaxy sizes in two extreme environments-dense clusters versus cosmic voids; (2) analyzing cluster galaxies across a range of cluster masses; and (3) studying member galaxies located in different cluster regions, from the core to the infall zone. In all three cases, we find no significant dependence of the SMR on environment at fixed stellar mass and galaxy type. Cluster and void galaxies follow consistent SMR trends, and no measurable variation is observed with cluster mass or cluster-centric distance. We also confirm that early-type galaxies exhibit steeper SMR slopes than late types. Notably, this consistent lack of environmental dependence on the SMR persists even when accounting for the differing galaxy number densities in voids, supporting the universality of this SMR scaling relation across diverse environments.

Xinxin Li, Yifan Wei, Lijun Wang et al.

Direct land application of conventional compost may cause ecological risks due to the presence of heavy metals. To effectively reduce heavy metal bioavailability in compost, a multi-component passivator comprising Candida utilis, sodium humate, zeolite and attapulgite was developed, which showed passivation rates of 59.28%, 86.93% and 38.95% for zinc (Zn), copper (Cu), and ferrum (Fe), respectively, in compost. The addition of customized multi-component passivator in compost not only reduced the mobility of heavy metals, but also improved the quality of the compost and further increased the abundance of lignocellulose-degrading beneficial microorganisms in compost. Subsequent fertilization results showed that the compost product fermented with customized multi-component passivator greatly improved the growth of Chinese cabbage, with significant increases in height, weight, root length, and total chlorophyll contents of 97.63%, 210.13%, 20.42%, and 40.38%, respectively. It can be concluded that the custom-made multi-component passivator is expected to be a good additive for heavy metal passivation, high-quality compost, and plant growth.

Hao Yin, Bhavna Sharma, Howard Hu et al.

Health care accounts for 9–10% of greenhouse gas (GHG) emissions in the United States. Strategies for monitoring these emissions at the hospital level are needed to decarbonize the sector. However, data collection to estimate emissions is challenging. We explored the potential of gradient boosting machines (GBM) to impute missing data on resource consumption in the 2020 survey of a consortium of 283 hospitals participating in Practice Greenhealth. GBM imputed missing values for selected variables in order to predict electricity use (R2 = 0.82) and beef consumption (R2 = 0.82) and anesthetic gas desflurane use (R2 = 0.51), using administrative and financial data readily available for most hospitals. After imputing missing consumption data, estimated GHG emissions associated with these three examples totaled over 3 million metric tons of CO2 equivalent emissions (MTCO2e). Specifically, electricity consumption had the largest total carbon footprint (2.4 MTCO2e), followed by beef (0.6 million MTCO2e) and desflurane consumption (0.03 million MTCO2e) across the 283 hospitals. The approach should be applicable to other sources of hospital GHGs in order to estimate total emissions of individual hospitals and to refine survey questions to help develop better intervention strategies.

Mohammad Fazle Rabbi, Mohammad Bin Amin

The United Nation's Sustainable Development Goals (SDGs) prioritize halving global per capita food waste at retail, consumer, production, and food supply chain by 2030. This aligns with promoting circular economy principles for enhanced sustainability. The circular economy offers a transformative approach to the food industry by promoting environmental health, human well-being, and economic prosperity. This bibliometric analysis examines how circular economy principles can drive sustainability in food businesses, which closely aligning with SDGs 12.3 (food waste reduction), 12.5 (waste reduction), 13.2 (climate policy integration), and 13.3 (climate adaptation). Through a bibliometric analysis of 1000 relevant articles sourced from the Web of Science (spanning from 2005 to 2023), we evaluated the progress, challenges, and opportunities in this field. Utilizing analytical tools such as Biblioshiny (Bibliometrix) package of R-Studio and VOSviewer, the researchers identify key trends and research hotspots through thematic maps, co-occurrence networks, co-citation analysis, keyword analysis, and collaboration networks. This research highlights that the circular economy can transform the food industry by implementing sustainable waste management practices, optimizing supply chains and resource utilization to minimize environmental impact. Furthermore, research findings indicate that adopting circular economy principles in the food industry can significantly reduce waste and enhance resource efficiency by transforming food waste into valuable products such as biogas and bio-based materials. This study provides valuable insights for researchers, practitioners, policymakers, and government officials to improve sustainable food production systems. It enhances understanding in a vital area for guiding future endeavours to promote circular economy strategies for a more sustainable and efficient food industry.

Yu Huang, Liang Guo, Wanqian Guo et al.

In the field of environmental science, it is crucial to have robust evaluation metrics for large language models to ensure their efficacy and accuracy. We propose EnviroExam, a comprehensive evaluation method designed to assess the knowledge of large language models in the field of environmental science. EnviroExam is based on the curricula of top international universities, covering undergraduate, master's, and doctoral courses, and includes 936 questions across 42 core courses. By conducting 0-shot and 5-shot tests on 31 open-source large language models, EnviroExam reveals the performance differences among these models in the domain of environmental science and provides detailed evaluation standards. The results show that 61.3% of the models passed the 5-shot tests, while 48.39% passed the 0-shot tests. By introducing the coefficient of variation as an indicator, we evaluate the performance of mainstream open-source large language models in environmental science from multiple perspectives, providing effective criteria for selecting and fine-tuning language models in this field. Future research will involve constructing more domain-specific test sets using specialized environmental science textbooks to further enhance the accuracy and specificity of the evaluation.

Xiuqiang He, Josué Duarte, Verena Häberle et al.

This article explores a flexible and coordinated control design for an aggregation of heterogeneous distributed energy resources (DERs) in a dynamic virtual power plant (DVPP). The control design aims to provide a desired aggregate grid-forming (GFM) response based on the coordination of power contributions between different DERs. Compared to existing DVPP designs with an AC-coupled AC-output configuration, a more generic modular DVPP design is proposed in this article, which comprises four types of basic DVPP modules, involving AC- or DC-coupling and AC- or DC-output, adequately accommodating diverse DER integration setups, such as AC, DC, AC/DC hybrid microgrids and renewable power plants. The control design is first developed for the four basic modules by the aggregation of DERs and the disaggregation of the control objectives, and then extended to modular DVPPs through a systematic top-down approach. The control performance is comprehensively validated through simulation. The modular DVPP design offers scalable and standardizable advanced grid interfaces (AGIs) for building and operating AC/DC hybrid power grids.

Shilpa Borehalli Mayegowda, Gitartha Sarma, Manjula Nagalapur Gadilingappa et al.

Abstract Antibiotic-resistant microorganisms are a rising issue when it comes to human health. Microbial pathogens that cause harmful infections are quickly becoming resistant to the antimicrobial action of traditional antibiotics. Nanotechnology, an innovative sector being an indispensable part of healthcare and research, has in-depth and extensive applications. Nano-compounds have been promising antimicrobial agents, anti-cancerous mediators, vehicles for drug delivery, formulations for functional foods, identification of pathogens, food and drug packaging industry, and many more. However, the chemical synthesis of nanoparticles (NPs) has certain drawbacks such as causing toxicity and other adverse effects. For more than a decade, the use of NPs that are conjugated or green-synthesized has gained popularity due to the two-fold action of metallic NPs mixed with biological sources. In contrast, NPs synthesized using plant or microbial extracts, conjugated with biologically active components, appear to be a safe alternative approach as they are environmentally friendly and cost-effective. Such environmentally safe techniques are referred to as “green nanotechnology” or “clean technology” and are feasible alternatives to chemical methods. Furthermore, NPs conjugated with natural biomolecules have improved bioavailability and have minimal side effects, as they are smaller in size and have higher permeability in addition to being reducing and stabilizing agents possessing excellent antioxidant activity. NPs serve as potential antimicrobial agents due to their affinity towards sulphur-rich amino acids, adhere to microbial cell walls by means of electrostatic attraction, and disrupt the cytoplasmic membrane along with the nucleic acid of microbes. They possess anticancer activity owing to oxidative stress, damage to cellular DNA, and lipid peroxidation. The green-synthesized NPs are thus a promising and safe alternative for healthcare therapeutic applications.

B. Saravanan, R. Divahar, S. P. Sangeetha and M. Bhuvaneshwari

Climate change and global warming are two of the world’s most pressing environmental issues. With CO2 being one of the most significant greenhouse gases released into the atmosphere, and cement and concrete manufacturing accounting for roughly 10% of worldwide CO2 emissions, the construction sector must employ an environmentally sustainable substance as a substitute for cement. The CO2 emissions, energy factor, and strength qualities of concrete were investigated. Those negative reaction of conventional cementitious substances is reduced by the development of binary and ternary cementitious systems. In this study, two mineral admixtures obtained from industrial waste substances, red mud (RM) and silica fume (SF), had been used as the alternatives for cement and fine aggregate was fully replaced by manufactured sand (M-sand). An experimental examination of the compressive strength, water absorption, density of concrete, equivalent CO2 emission, and energy factor for environmental benefits with the comparison of RM on SF-based eco-friendly concrete mix of M30 grade was used. A binary and ternary blended cementitious system with RM and SM was created with twelve various mix proportions, varying from 0-20% by 5% increases. From the binary blended cementitious system (BBS), based on the observed mechanical characteristic of concrete it was found that the optimum level of RM was 15% and SF was 10 % by the volume of cement. Similarly, for the ternary blended cementitious system (TBS), the level of 10% RM and 10% SF in the cement mixture provides a much higher improvement in compression strength compared to the alternative trials. The negative sign implies that replacing cement with RM and SF reduces energy consumption (-1.91% to -6.97%) and CO2 emissions (-4.52% to -16.16%). The use of mineral admixtures such as RM and SM in supplementary cementitious materials results in a significant outcome and potential impact on the production of sustainable concrete that addresses environmental issues.

K. Kiran Kumar, Ratnakaram Venkata Nadh, Kaza Somasekhara Rao and G. Krishnaveni

Human beings experience adversative effects due to the large fluoride concentrations present in potable water. Because of the low cost and simple operation, the extensively acknowledged process is adsorption. The objective of this study is to investigate the performance of some of the prepared carbons from bio-waste materials viz., Citrus limon, Citrus nobilis, Pithecellobium dulce, and Bombax malabaricum sheaths in defluoridation. Initial concentration, particle size, agitation time, adsorbent dose, and pH were the different parameters chosen to study their effect on adsorption. Studied the adsorption kinetics. Further suitability to adsorption isotherms was reviewed.

Nan Hu, Daobilige Su, Shuo Wang et al.

With the increasing deployment of agricultural robots, the traditional manual spray of liquid fertilizer and pesticide is gradually being replaced by agricultural robots. For robotic precision spray application in vegetable farms, accurate plant phenotyping through instance segmentation and robust plant tracking are of great importance and a prerequisite for the following spray action. Regarding the robust tracking of vegetable plants, to solve the challenging problem of associating vegetables with similar color and texture in consecutive images, in this paper, a novel method of Multiple Object Tracking and Segmentation (MOTS) is proposed for instance segmentation and tracking of multiple vegetable plants. In our approach, contour and blob features are extracted to describe unique feature of each individual vegetable, and associate the same vegetables in different images. By assigning a unique ID for each vegetable, it ensures the robot to spray each vegetable exactly once, while traversing along the farm rows. Comprehensive experiments including ablation studies are conducted, which prove its superior performance over two State-Of-The-Art (SOTA) MOTS methods. Compared to the conventional MOTS methods, the proposed method is able to re-identify objects which have gone out of the camera field of view and re-appear again using the proposed data association strategy, which is important to ensure each vegetable be sprayed only once when the robot travels back and forth. Although the method is tested on lettuce farm, it can be applied to other similar vegetables such as broccoli and canola. Both code and the dataset of this paper is publicly released for the benefit of the community: https://github.com/NanH5837/LettuceMOTS.

Yuzi Zhang, Howard H. Chang, Joshua L. Warren et al.

Environmental epidemiologic studies routinely utilize aggregate health outcomes to estimate effects of short-term (e.g., daily) exposures that are available at increasingly fine spatial resolutions. However, areal averages are typically used to derive population-level exposure, which cannot capture the spatial variation and individual heterogeneity in exposures that may occur within the spatial and temporal unit of interest (e.g., within day or ZIP code). We propose a general modeling approach to incorporate within-unit exposure heterogeneity in health analyses via exposure quantile functions. Furthermore, by viewing the exposure quantile function as a functional covariate, our approach provides additional flexibility in characterizing associations at different quantile levels. We apply the proposed approach to an analysis of air pollution and emergency department (ED) visits in Atlanta over four years. The analysis utilizes daily ZIP code-level distributions of personal exposures to four traffic-related ambient air pollutants simulated from the Stochastic Human Exposure and Dose Simulator. Our analyses find that effects of carbon monoxide on respiratory and cardiovascular disease ED visits are more pronounced with changes in lower quantiles of the population-level exposure. Software for implement is provided in the R package nbRegQF.

Marcus Olofsson, André Berg Niklas L. P. Lundström

We use a dynamic programming approach to construct management strategies for a hydropower plant with a dam and a continuously adjustable unit. Along the way, we estimate unknown variables via simple models using historical data and forecasts. Our suggested scheme achieves on average 97.1 % of the theoretical maximum using small computational effort. We also apply our scheme to a Run-of-River hydropower plant and compare the strategies and results to the much more involved PDE-based optimal switching method studied earlier by the authors in (Optimization and Engineering (2021): 1-25); this comparison shows that our simple approach may be preferable if the underlying data is sufficiently rich.

Dr. R. Premsudha, A. Vasareddy, B. Saiteja et al.

The menace of environmental pollution due to improper municipal solid waste management (MSWM) has been enduring the human world still it is growing due to enormous growth of industries in the developing countries. Currently 2.0 billion tonnes per year of MSW is generating. Solid Waste Management process includes the collection, conveyance, segregation, treatment and disposal. Various municipal Solid waste treatment (landfilling, incineration, open burning) processes which emits the hazardous Greenhouse gases &affects Environment and Human health. This study has made an attempt on collection of data about various process involved in treatment of Hyderabad Integrated Municipal Solid Waste Management (HIMSWM) done by Ramky group PvtLtd and its impact on air. During 2018 national cleanliness survey was conducted in that Hyderabad ranked first out of 4,203 cities in Solid Waste Management. GHMC, the Greater Hyderabad Municipal Corporation, is responsible for the city's Solid Waste Management function. Hyderabad ranks among the top 5 cities in India in Solid Waste generation. In these processes Landfilling is one of the major municipal solid wastes (MSW) disposal methods practiced all over the world. Although it is considered as the most cost-effective means of waste disposal, but there are poor management practices specially in developing countries like India are the major causes of environmental pollution. Recently several studies has been carried out for the better understanding of the effects of landfill pollution on human health as well on the environment. Toxic gas emissions from landfills like Methane, NOx, SO2, VOC’s, CO2, PM, HC, pose a serious threat to both the environment and human health. Some studies has shown that the toxic gases released from landfill sites are even responsible for the lung and heart diseases in humans beings. Landfills also generate a toxic soup known as leachate, formed when the waste is subjected to biological and physiochemical transformation process. Leachate is highly toxic and causes the land and groundwater pollution. This study focus the impact on air due to landfills, and the challenges faced in the current scenario, and the possible measures that can be taken to deal with the problem of municipal solid waste management treatment

Rohan Jeffry Robert and C. R. Girish

The present work introduces a new methodology in the production of biodiesel from pork-lard waste having high cholesterol content and discusses its improved performance and emissions in a diesel engine. The traditional method of transesterification does not work with cholesterol due to the absence of triglycerides, therefore, the new improved method oxidizes cholesterol to fatty acids and then converts it to biodiesel ester. The procedure includes an acid reagent to break cholesterol and a renewable basic catalyst from seashells, for catalyzing the production. The acid-base system maintains the overall pH while yielding 95.6% conversion at the optimized conditions. The morphology of the produced catalyst was analyzed through FESEM and confirmed through XRD and EDX analyses. The physicochemical and ASTM properties were determined and the calorific value of the 20% biodiesel blend was found to be comparable with that of diesel. From the engine performance analysis, the thermal efficiency of the engine was observed to be higher and the exhaust emissions showed a maximum of 75% reduction in CO and 42.2% reduction in CO2 emissions, proving it to be an environment-friendly fuel. Additionally, a 32.7% reduction in smoke opacity was also observed, thus decreasing the concentration of particulate matter in the atmosphere.