Hasil untuk "Environmental Science"

Chaiti Saha, Shova Pandit, Md Motaher Hossain et al.

Rice blast caused by Pyricularia oryzae (syn. Magnaporthe oryzae ) is one of the most devastating diseases in rice, resulting in substantial yield loss. Currently, the control of rice blast relies significantly on chemical fungicides, which raise numerous environmental concerns. However, silver nanoparticles (AgNPs) are emerging as innovative, non-resistant substitutes for conventional fungicides. This study aimed to synthesize AgNPs from banana flowers via a green approach and assess their antifungal activity against Pyricularia oryzae strain SP2 in vitro . The pathogen Pyricularia oryzae strain SP2 was identified by morphological features and study of the internal transcribed spacer (ITS) sequence. The AgNPs were characterized via UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), x-ray diffraction (XRD), transmission electron microscopy (TEM) and energy-dispersive x-ray analysis (EDX). The optimal reaction conditions for the green synthesis of the AgNPs resulted in a rapid color change from light yellow to dark brown when the floral extract (15 ml) was added. A surface plasmon resonance peak was observed in the UV-visible spectrum at approximately 433 cm ^−1 , which was correlated with the synthesis of the AgNPs. The biogenic AgNPs had a spherical form with an average particle size of 47.63 nm, according to TEM and SEM examination. The greatest mycelial growth inhibition of P. oryzae (87.25%) was observed when it was exposed to biofabricated AgNPs at 40 μg ml ^−1 . The AgNPs successfully suppressed spore germination and germ tube development of P. oryzae , with increased doses demonstrating enhanced antifungal efficacy. Additionally, the appressorium formation rates decreased from 78.34% in the control to 41.67%, 16.45%, and 4% at increasing concentrations (20, 30, 40 μg ml ^−1 ). Overall, this study demonstrated that bioinspired AgNPs have antifungal activity against the rice blast pathogen P. oryzae and can be used to control blast diseases in rice.

M. Paglione, Y. Hao, S. Decesari et al.

<p>Understanding the chemical composition and sources of organic aerosol (OA) in the Arctic is critical given its importance for particle climate-relevant properties. This study presents a year-long analysis (May 2019–June 2020) of PM<span class="inline-formula">₁</span> filter samples collected in Ny-Ålesund, Svalbard. A multi-instrumental approach is employed to characterize the comprehensive chemical composition of PM<span class="inline-formula">₁</span>, with a specific focus on its water-soluble organic fraction depicted combining proton nuclear magnetic resonance spectroscopy (H-NMR) and high-resolution time-of-flight aerosol mass spectrometry (HR-TOF-AMS), which provide complementary insights into the nature and structure of the organic aerosol classes characterizing the bulk OA mixture. Positive matrix factorization (PMF) source apportionment identifies consistent OA sources from the H-NMR and AMS datasets, showing a pronounced seasonality in their relative contributions to total OA mass. Winter–spring aerosol is dominated by long-range transport of Eurasian anthropogenic pollution (up to 70 %), while summer is characterized by biogenic aerosols from marine sources (up to 44 %), including sulfur compounds, amines, and fatty acids. Occasional summertime high OA loadings are associated with wildfire aerosols enriched in levoglucosan and humic-like substances (HULIS; averagely 27 %–28 %). Eventually, about 28 %–40 % of the OA mass is attributed to an unresolved mixture of extremely oxidized compounds of difficult specific source attribution. This integrated approach provides valuable insights into the seasonal dynamics of OA sources in the Arctic.</p>

Michail Bachras, Hans-Arno Jacobsen

The exponential growth of data is making query processing increasingly critical for modern computing infrastructure, yet the environmental impact of database operations remains poorly understood and largely overlooked. This paper presents ATLAS, a comprehensive methodology for measuring and quantifying the environmental footprint of analytical database systems, considering both operational impacts and manufacturing costs of hardware components. Through extensive empirical evaluation of four distinct database architectures (DuckDB, MonetDB, Hyper, and StarRocks), we uncover how fundamental architectural decisions affect environmental efficiency. Our findings reveal that environmental considerations in database operations are multifaceted, encompassing both immediate operational impacts and long-term sustainability implications. We demonstrate that architectural choices can significantly influence both power consumption and environmental sustainability, while deployment location emerges as a critical factor that can amplify or diminish these architectural advantages.

Junying Wang, Zicheng Zhang, Yijin Guo et al.

As foundation models grow rapidly in capability and deployment, evaluating their scientific understanding becomes increasingly critical. Existing science benchmarks have made progress towards broad Range, wide Reach, and high Rigor, yet they often face two major challenges: data leakage risks that compromise benchmarking validity, and evaluation inefficiency due to large-scale testing. To address these issues, we introduce the Ever-Evolving Science Exam (EESE), a dynamic benchmark designed to reliably assess scientific capabilities in foundation models. Our approach consists of two components: 1) a non-public EESE-Pool with over 100K expertly constructed science instances (question-answer pairs) across 5 disciplines and 500+ subfields, built through a multi-stage pipeline ensuring Range, Reach, and Rigor, 2) a periodically updated 500-instance subset EESE, sampled and validated to enable leakage-resilient, low-overhead evaluations. Experiments on 32 open- and closed-source models demonstrate that EESE effectively differentiates the strengths and weaknesses of models in scientific fields and cognitive dimensions. Overall, EESE provides a robust, scalable, and forward-compatible solution for science benchmark design, offering a realistic measure of how well foundation models handle science questions. The project page is at: https://github.com/aiben-ch/EESE.

Claire Hughson, Vasily I. Ponomarev, Boris M. Kondratenok et al.

Abstract Fish and fish tissue are effective bioindicators due to their sensitivity to pollution and are frequently used for assessing aquatic ecosystem health. Establishing baseline metal concentrations in freshwater fish tissues within aquatic ecosystems is important prior to establishing industrial activities to help determine potential future industrial impacts. Historically, North-Eastern European Russia has been an area with relatively low levels of industrial development and is still in pristine condition. In this region, the noise-to-background ratio for industrial contaminants may be disproportionately high. This study measured baseline metal concentrations in freshwater fish tissues collected from three study sites (the Bolshoi Patok, Maly Patok and Kara Rivers) in northeastern European Russia as bioindicators of overall aquatic ecosystem health. Seven fish species, namely, European Grayling, Arctic Char, Whitefish, Perch, Pike, Roach, and Peled, were studied over a three-year period between 2000 and 2003. The copper (Cu), lead (Pb), cadmium (Cd), and zinc (Zn) concentrations were analysed in fish tissue samples. Metal concentrations measured in fish tissues in this study were comparable to those measured at remote sites in Alaska, the United States and Slovenia. Despite the small variation between the sampling sites, the metal concentrations were relatively low and considered to be in pristine condition. Metal concentrations measured in fish tissues in this study represent baseline conditions, which will be important for comparison against monitoring programmes should the region experience future industrial development.

Toke Emil Panduro, Doan Nainggolan, Marianne Zandersen

Despite increasing interest in Nature-based Solutions (NbS), there is still a lack of comprehensive understanding regarding the costs of different types of NbS and their variations. Cost information is crucial for economic assessments of the viability of NbS compared to other alternatives. In this paper, we provide an overview of NbS costs in urban settings, drawing primarily from a literature review of both gray and scientific literature. We present cost estimates for establishing green and blue spaces in urban and peri-urban areas, street trees, green roofs, and green walls. Our findings show that median costs are 56 EUR/m² for green spaces, 73 EUR/m³ for blue spaces, and 201 EUR/m² for green roofs.Furthermore, we demonstrate how an economic assessment can be carried out utilizing the calculated cost estimates while providing a systematic procedure to handle the multiple potential benefits provided by NbS. We argue that a step-wise ranked cost-effectiveness analysis, based on ranking local policy objectives, is a feasible approach for making informed choices on competing solutions relative to conventional cost-effectiveness analysis and cost-benefit analysis. The proposed approach could prove useful due to its relatively straightforward application and the fact that it does not require the aggregation of multiple benefits into one common measurement or valuation unit.

O. Ndletyana, B. S. Madonsela and T. Maphanga

Fixed air quality monitoring stations generally monitor the air quality in developing countries. However, this practice, in addition to being costly, inherently contains drawbacks associated with the inability to capture the spatial distribution of air pollutants. Against this limitation, it is necessary to employ flexible and dynamic monitoring techniques that are fundamental and influential in comprehending the spatial distribution of pollutants. Because of this, in recent times, the application of GIS as a monitoring technique has proved to be more efficient than using fixed monitoring stations. Therefore, to this end, the current study mapped the spatial distribution of PM10 and NO2 pollutants in Cape Town CBD using the GIS technique. Subsequently, the GIS monitoring technique revealed that both pollutants had high spatial distribution between 2017 and 2018, irrespective of the season. Furthermore, high exposure concentrations of PM10 were generally observed across the CBD in contrast to NO2 exposure levels, which were relatively low. To contextualize the findings, compared with other studies, the current research discovered that spatial distribution of air pollution is associated with meteorological conditions, such as wind speed and temperature, that traditional techniques of monitoring exposure can’t capture.

Pooja Singh, R. C. Tiwari, Rakesh Bhutiani et al.

According to the world Summit of sustainable Development, the major reason for lack of safe water is either scarcity of water or contamination of water sources. Therefore this study eye on developing nations, seeks to find sustainable, yet economically and socially practical solution to the problems associated with polluted water. To fulfil the objectives of the present study, two medicinal value plants Dhav (Anogeissuslatifolia wall.) and Aragvadha (Cassia fistula Linn.) were selected and absorbents were prepared from the bark of both the plants. Then the reactors were prepared using the different compositions of sand, gravel, absorbents of Dhavand Aragvadha and cotton.In this way four filter reactors were prepared. The feeding rate of raw water is maintained at 0.5 litre per hour. The results revealed that Dhav plant absorbent was found more effective thanAragvadha. All reactors shows different efficiencies for different parameters suggesting that reactors should be prepared based on need or targeted parameters. Over all reactor 4 shows better efficiency for all the parameters. The main exclusivity of the present reactor is low cost with no electricity demand. The prepared reactors are environment friendly and easily implementable but further study is required to prove it on large scale.

Changmei Liang, Changmei Liang, Changmei Liang et al.

The cost-benefit is a key factor when selecting an appropriate sponge city construction scheme. The research of applying intelligent technology to find cost-benefit efficient planning and construction of sponge city is urgently required. This paper established a multi-objective simulation optimization framework of sponge city construction which considered minimization of runoff control rate, pollutant control rate and life-cycle cost Non-dominated sorting genetic algorithm (NSGA-II) was successfully coupled to Storm water management model to complete the simulation-optimization process. A case study in Xining, China, was conducted to demonstrate the proposed framework. The results of this research suggested that 1) different sponge city construction schemes lead to different runoff control rates and pollutant control rates although under the same investment; 2) the runoff control rate and pollutant control rate total suspended solids decreased with the increase of the rainfall return period, while the cost of sponge city construction increased with the increase of rainfall return period. Furthermore, for T = 2-year, the sponge facility exhibited the most stable control effect on runoff and pollutants among the three different return periods (T = 2-year, 5-year, 10-year); 3) sponge city construction exhibited a “cost-benefit” efficient interval. For T = 2-year, the cost-benefit high efficiency interval of sponge city construction is calculated between 1.2 billion and 1.8 billion; for T = 5-year, the interval is between 1.2 billion and 1.8 billion, while for T = 10-year, the interval is between 1.3 billion and 2.1 billion. The above observations provide reference for reasonable and effective sponge city construction in Xining, China.

Steven Kutarna, Wanzhen Chen, Ying Xiong et al.

Andrew R Kampfschulte, Rebecca K Miller

Community-wide wildfire mitigation can effectively protect homes from structure ignition. The Firewise USA program provides a framework for grassroots wildfire preparedness. Here, we examine the 500 Firewise USA sites in California to understand participation and demographic trends. We find important regional differences regarding the influence of underlying fire hazard, fire history, and other Firewise sites on new site formation. Sites in the Bay Area and Sierras respond strongly to fire history and proximity to other Firewise sites, while Northern and Southern California have few Firewise sites despite underlying hazardous conditions and large fire history. Firewise sites are often whiter, older, and more well-educated than California’s median population, potentially leaving out many communities that do not meet this demographic profile but face severe risks from wildfires. These findings offer important insights into the factors motivating communities to pursue wildfire protection, particularly important given recent severe and destructive wildfire seasons.

Jiang Yuqi, Yang Yikang, Tian Wenbo et al.

[Objective] The spatial differences and dynamic evolution of carbon ecological security level were analyzed to optimize the overall plan of carbon ecological security in the Yellow River basin (an important “energy basin” in China) in order to objectively reflect the current status and evolution trend of carbon ecological security, and to provide a reference for optimizing the carbon ecological security pattern. [Methods] An evaluation index system for carbon ecological security in the Yellow River basin was constructed under the framework of driving-pressure-state-impact-response (DPSIR) analysis. The technique for order preference by similarity to ideal solution (TOPSIS) model was used to evaluate the level of carbon ecological security, and the spatial-temporal evolution characteristics were analyzed by the kernel density estimation method. [Results] ① Carbon sinks and carbon emissions increased from 2012 to 2021 in the Yellow River basin, and the growth rate of carbon emissions was faster than that of carbon sinks. Carbon sinks were spatially characterized as “higher in the west and lower in the east”, while carbon emissions were “lower in the west and higher in the east”. ② The carbon ecological security level in the Yellow River basin increased over time, from 0.356 in 2012 to 0.639 in 2021. In terms of spatial distribution, the carbon ecological security level in the upstream region was higher than in the middle and downstream regions, and was characterized as “upstream leading, midstream catching up, and downstream surpassing”. In addition, the level of carbon ecological security tended to be good. ③ Based on the kernel density estimation results, the differences in carbon security levels among different regions in the Yellow River basin were gradually narrowing, and were decreasing in the upstream region faster than in the middle and downstream regions. [Conclusion] Based on the current status of carbon ecological security in the Yellow River basin, carbon sink capacity in the upstream region is expected to increase over time, while clean energy industries and technology-intensive industries with high added value should be developed to promote green GDP growth in the middle and downstream regions. In addition, a carbon ecological compensation mechanism should be established to coordinate and resolve cross-regional security issues, and to improve the carbon ecological security level of the entire basin.

Zhenyu Gao, Dimitri N. Mavris

Accurate modeling of aircraft environmental impact is pivotal to the design of operational procedures and policies to mitigate negative aviation environmental impact. Aircraft environmental impact segmentation is a process which clusters aircraft types that have similar environmental impact characteristics based on a set of aircraft features. This practice helps model a large population of aircraft types with insufficient aircraft noise and performance models and contributes to better understanding of aviation environmental impact. Through measuring the similarity between aircraft types, distance metric is the kernel of aircraft segmentation. Traditional ways of aircraft segmentation use plain distance metrics and assign equal weight to all features in an unsupervised clustering process. In this work, we utilize weakly-supervised metric learning and partial information on aircraft fuel burn, emissions, and noise to learn weighted distance metrics for aircraft environmental impact segmentation. We show in a comprehensive case study that the tailored distance metrics can indeed make aircraft segmentation better reflect the actual environmental impact of aircraft. The metric learning approach can help refine a number of similar data-driven analytical studies in aviation.

M. Kadler, D. A. Riechers, J. Agarwal et al.

The Next Generation Very Large Array (ngVLA) is a planned radio interferometer providing unprecedented sensitivity at wavelengths between 21 cm and 3 mm. Its 263 antenna element array will be spatially distributed across North America to enable both superb low surface brightness recovery and sub-milliarcsecond angular resolution imaging. The project was developed by the international astronomy community under the lead of the National Radio Astronomy Observatory (NRAO), and is anticipated to be built between 2027 and 2037. Two workshops have been held in 2022 and 2023 with the goal to discuss and consolidate the scientific interests in the ngVLA within the German astronomical community. This community paper constitutes a collection of 48 science ideas which the German community aims to pursue with the ngVLA in the 2030s. This is not a complete list and the ideas are not developed at the level of a "Science Book", such that the present document is mainly meant provide a basis for further discussion within the community. As such, additional contributions are welcome, and will be considered for inclusion in future revisions.

Lars Möckel, Karen Meusemann, Bernhard Misof et al.

The Entomophthoromycotina, a subphylum close to the root of terrestrial fungi with a bias toward insects as their primary hosts, has been notoriously difficult to categorize taxonomically for decades. Here, we reassess the phylogeny of this group based on conserved genes encoding ribosomal RNA and RNA polymerase II subunits, confirming their general monophyly, but challenging previously assumed taxonomic relationships within and between particular clades. Furthermore, for the prominent, partially human-pathogenic taxon <i>Conidiobolus</i>, a new type species <i>C. coronatus</i> is proposed in order to compensate for the unclear, presumably lost previous type species <i>C. utriculosus</i> Brefeld 1884. We also performed an exhaustive survey of the broad host spectrum of the Entomophthoromycotina, which is not restricted to insects alone, and investigated potential patterns of co-evolution across their megadiverse host range. Our results suggest multiple independent origins of parasitism within this subphylum and no apparent co-evolutionary events with any particular host lineage. However, Pterygota (i.e., winged insects) clearly constitute the most dominantly parasitized superordinate host group. This appears to be in accordance with an increased dispersal capacity mediated by the radiation of the Pterygota during insect evolution, which has likely greatly facilitated the spread, infection opportunities, and evolutionary divergence of the Entomophthoromycotina as well.

Kondwani Luwe, Rebecca C Sindall, Flor Y Garcia-Becerra et al.

Citywide Inclusive Sanitation (CWIS) calls for sustainable urban sanitation services for all, but the definitions of “inclusion” and “sustainability” within the framework leave room for interpretation. This study aims to provide an initial understanding of how these terms are currently interpreted by a range of sanitation actors in six cities of the Global South. Urban sanitation professionals from private (n = 16), public (n = 28), non-governmental (n = 43), and academic (n = 10) institutions were interviewed using a standardized tool, and data was analyzed to identify themes and trends. Terms such as “everyone” or “for all” shed little light on how to ensure inclusion, though disabled people, women, children, and the poor were all highlighted when probed. Greater specificity of beneficiary groups in policy is likely to enhance their visibility within sanitation service provision. All three pillars of sustainability identified within CWIS were referenced, with different stakeholders focusing more closely on environmental, social, or economic sustainability, based on their organizational goals and interests. Greater collaboration may foster a balanced view across the pillars, with different organizations acting as champions for each one. The findings can facilitate discussions on a shared understanding of multi-stakeholder engagement in achieving inclusive and sustainable sanitation service provision.

Ivana R. Sequeira, Ivana R. Sequeira, Wilson C. Yip et al.

ObjectivePrevalence of type 2 diabetes (T2D) is disproportionately higher in younger outwardly lean Asian Chinese compared to matched Caucasians. Susceptibility to T2D is hypothesised due to dysfunctional adipose tissue expansion resulting in adverse abdominal visceral and organ fat accumulation. Impact on early risk, particularly in individuals characterised by the thin-on-the-outside-fat-on-the-inside (TOFI) phenotype, is undetermined.MethodsSixty-eight women [34 Chinese, 34 Caucasian; 18–70 years; body mass index (BMI), 20–45 kg/m2] from the TOFI_Asia study underwent magnetic resonance imaging and spectroscopy to quantify visceral, pancreas, and liver fat. Total body fat was (TBF) assessed by dual-energy x-ray absorptiometry, and fasting blood biomarkers were measured. Ethnic comparisons, conducted using two-sample tests and multivariate regressions adjusted for age, % TBF and ethnicity, identified relationships between abdominal ectopic fat depots with fasting plasma glucose (FPG), insulin resistance (HOMA2-IR), and related metabolic clinical risk markers in all, and within ethnic groups.ResultsDespite being younger and of lower bodyweight, Chinese women in the cohort had similar BMI and % TBF compared to their Caucasian counterparts. Protective high-density lipoprotein cholesterol, total- and high-molecular weight adiponectin were significantly lower, while glucoregulatory glucagon-like peptide-1 and glucagon significantly higher, in Chinese. There were no ethnic differences between % pancreas fat and % liver fat. However, at low BMI, % pancreas and % liver fat were ∼1 and ∼2% higher in Chinese compared to Caucasian women. In all women, % pancreas and visceral adipose tissue had the strongest correlation with FPG, independent of age and % TBF. Percentage (%) pancreas fat and age positively contributed to variance in FPG, whereas % TBF, amylin and C-peptide contributed to IR which was 0.3 units higher in Chinese.ConclusionPancreas fat accumulation may be an early adverse event, in TOFI individuals, with peptides highlighting pancreatic dysfunction as drivers of T2D susceptibility. Follow-up is warranted to explore causality.

Melissa Chapman, Caleb Scoville, Marcus Lapeyrolerie et al.

Machine learning (ML) methods already permeate environmental decision-making, from processing high-dimensional data on earth systems to monitoring compliance with environmental regulations. Of the ML techniques available to address pressing environmental problems (e.g., climate change, biodiversity loss), Reinforcement Learning (RL) may both hold the greatest promise and present the most pressing perils. This paper explores how RL-driven policy refracts existing power relations in the environmental domain while also creating unique challenges to ensuring equitable and accountable environmental decision processes. We leverage examples from RL applications to climate change mitigation and fisheries management to explore how RL technologies shift the distribution of power between resource users, governing bodies, and private industry.