Hasil untuk "Environmental Science"

Zhe Yang, Chao Hu

Enhancing carbon emission efficiency is a critical pathway for advancing global climate governance and achieving the “Dual Carbon” goals. Precisely mapping the spatiotemporal evolution patterns of carbon emission efficiency in urban agglomerations and thoroughly analyzing the underlying driving mechanisms are of paramount importance for optimizing the nation’s overall carbon neutrality pathway. This study examines 26 cities within the Yangtze River Delta urban agglomeration from 2005 to 2023. Employing methods such as the Super-EBM model, exploratory spatiotemporal data analysis, and the Tobit model, it delves into the spatiotemporal evolution of carbon emission efficiency and its influencing factors. Key findings include: (1) Overall carbon emission efficiency remained stable at approximately 0.85 during the study period, with minor fluctuations. (2) Significant spatial disparities in carbon emission efficiency emerged, exhibiting gradually increasing convergence. (3) Local spatial structures of carbon emission efficiency were relatively dynamic yet demonstrated strong spatial dependence, while overall spatial structures remained stable with pronounced spatial cohesion. (4) Urbanization level, economic development level, population density, degree of openness, and technological innovation have a significant impact on improving carbon emission efficiencye, whereas industrial structure and environmental regulation showed no significant promotional impact.

Xin Guan, Yang Liu, Lianwei Li et al.

Abstract Particle assembly at liquid–liquid interfaces presents a promising bottom‐up strategy for creating supramolecular materials with advanced functionalities. However, the significantly lower interfacial tension observed in immiscible organic phases compared to traditional oil–water systems has hindered the effective adsorption and assembly of particles at oil–oil interfaces. In this work, a versatile and effective strategy is presented that utilizes the assembly and jamming of microgels and polymer ligands at non‐aqueous liquid–liquid interfaces to create non‐aqueous Pickering emulsions and reconfigurable droplet networks. The resulting microgel‐polymer complexes form an asymmetric interfacial bilayer with high surface coverage, which effectively minimizes interfacial energy and improves interfacial elasticity. Through a combination of systematic interfacial measurements and molecular dynamics simulations, the underlying mechanisms governing interfacial self‐assembly are elucidated. Notably, the stimuli‐responsive nature of the microgel‐polymer complexes allows for precise control over the interfacial assembly and disassembly by introducing competitive molecules. Furthermore, it is demonstrated that these non‐aqueous Pickering emulsions serve as excellent templates for the fabrication of heterogeneous organogels and microgel‐based colloidosomes through both covalent and non‐covalent crosslinking strategies. This work underscores the potential of non‐aqueous interfaces in advancing materials science and opens new avenues for developing multifunctional materials.

Niels Taubert

This paper reviews research literature on Diamond Open Access (DOA) journals - sometimes also called Platinum Open Access - that was produced after this journal segment started to become a priority in European research policy around 2020. It contextualizes the current science policy debate, critically examines different understandings of DOA, and reviews studies on the role of such journals in scholarly communication. Most existing research consists of quantitative studies focusing on aspects such as the number of DOA journals, their publication output, the diversity of the landscape in terms of subject areas, languages, publishing entities, indexing in major databases, awareness and perception among scholars, cost analyses, as well as insights into the internal operations of DOA journals. The review shows that research on DOA journals is partly influenced by the science policy discourse in at least two ways: first, through the normativity inherent in that discourse, and second, through the temporality of policy-driven research of practical relevance, which leaves important aspects of the phenomenon understudied. Moreover, research on the DOA journal landscape has implications beyond understanding this particular journal segment, as it also challenges established views of the global system of scholarly communication.

Hang Jiang, Tal August, Luca Soldaini et al.

The field of Computer science (CS) has rapidly evolved over the past few decades, providing computational tools and methodologies to various fields and forming new interdisciplinary communities. This growth in CS has significantly impacted institutional practices and relevant research communities. Therefore, it is crucial to explore what specific research values, known as basic and fundamental beliefs that guide or motivate research attitudes or actions, CS-related research communities promote. Prior research has manually analyzed research values from a small sample of machine learning papers. No prior work has studied the automatic detection of research values in CS from large-scale scientific texts across different research subfields. This paper introduces a detailed annotation scheme featuring ten research values that guide CS-related research. Based on the scheme, we build value classifiers to scale up the analysis and present a systematic study over 226,600 paper abstracts from 32 CS-related subfields and 86 popular publishing venues over ten years.

Nahshon Mokua Obiri, Kristof Van Laerhoven

This paper presents a comprehensive dataset of LoRaWAN technology path loss measurements collected in an indoor office environment, focusing on quantifying the effects of environmental factors on signal propagation. Utilizing a network of six strategically placed LoRaWAN end devices (EDs) and a single indoor gateway (GW) at the University of Siegen, City of Siegen, Germany, we systematically measured signal strength indicators such as the Received Signal Strength Indicator (RSSI) and the Signal-to-Noise Ratio (SNR) under various environmental conditions, including temperature, relative humidity, carbon dioxide (CO$_2$) concentration, barometric pressure, and particulate matter levels (PM$_{2.5}$). Our empirical analysis confirms that transient phenomena such as reflections, scattering, interference, occupancy patterns (induced by environmental parameter variations), and furniture rearrangements can alter signal attenuation by as much as 10.58 dB, highlighting the dynamic nature of indoor propagation. As an example of how this dataset can be utilized, we tested and evaluated a refined Log-Distance Path Loss and Shadowing Model that integrates both structural obstructions (Multiple Walls) and Environmental Parameters (LDPLSM-MW-EP). Compared to a baseline model that considers only Multiple Walls (LDPLSM-MW), the enhanced approach reduced the root mean square error (RMSE) from 10.58 dB to 8.04 dB and increased the coefficient of determination (R$^2$) from 0.6917 to 0.8222. By capturing the extra effects of environmental conditions and occupancy dynamics, this improved model provides valuable insights for optimizing power usage and prolonging device battery life, enhancing network reliability in indoor Internet of Things (IoT) deployments, among other applications. This dataset offers a solid foundation for future research and development in indoor wireless communication.

Grace Wolf-Chase, Charles Kerton, Kathryn Devine et al.

We review participatory science programs that have contributed to the understanding of star formation. The Milky Way Project (MWP), one of the earliest participatory science projects launched on the Zooniverse platform, produced the largest catalog of ``bubbles'' associated with feedback from hot young stars to date, and enabled the identification of a new class of compact star-forming regions (SFRs) known as ``yellowballs'' (YBs). The analysis of YBs through their infrared colors and catalog cross-matching led to discovering that YBs are compact photodissociation regions generated by intermediate- and high-mass young stellar objects embedded in clumps that range in mass from 10 - 10,000 solar masses and luminosity from 10 - 1,000,000 solar luminosities. The MIRION catalog, assembled from 6176 YBs identified by citizen scientists, increases the number of candidate intermediate-mass SFRs by nearly two orders of magnitude. Ongoing work utilizing data from the Spitzer, Herschel and WISE missions involves analyzing infrared color trends to predict physical properties and ages of YB environments. Methods include applying summary statistics to histograms and color-color plots as well as SED fitting. Students in introductory astronomy classes contribute toward continued efforts refining photometric measurements of YBs while learning fundamental concepts in astronomy through a classroom-based participatory science experience, the PERYSCOPE project. We also describe an initiative that engaged seminaries, family groups, and interfaith communities in a wide variety of science projects on the Zooniverse platform. This initiative produced important guidance on attracting audiences that are underserved, underrepresented, or apprehensive about science.

M.I. Sayyed, Abdelmoneim Saleh, Anjan Kumar et al.

Investigations were conducted on the addition of barium's impact on the radiation shielding and physical attributes of five different glasses, designated S1–S5, with varying BaO contents. Using two point sources namely Co60 and Cs137 along with a scintillation detector [NaI(TL)], experimental measurements were made of the shielding parameters of γ-rays, namely the effective atomic number (Zeff), electron density (Nel), half-value layer (HVL), linear attenuation coefficient (μ), mass attenuation coefficient (μm), mean free path (λ), and radiation protection effectiveness at the energies of 0.664, 1.177, and 1.334 MeV, and comparisons made with recently considered glasses as well as frequently employed materials for γ-ray shielding. The results show that the examined glasses' physical and radiation shielding qualities are improved by the addition of BaO. The μ values increased from 0.245 to 0.275 cm−1 (0.662 MeV), from 0.174 to 0.198 cm−1 (1.173 MeV), and from 0.161 to 0.189 (1.332 MeV). The observed values of HVL decreased from 2.83, 3.98, and 4.3 cm to 2.5, 3.5, and 3.62 cm at 0.662, 1.173, and 1.332 MeV, respectively, for the samples S1 and S5. In addition, the S5 glass sample was determined to have the best protection against photon among all the samples that were evaluated, as well as against recently considered glasses and those materials often utilized for gamma-ray shielding purposes.

Xiaoxuan Su, Xinrong Huang, Yiyue Zhang et al.

Abstract The estuarine plastisphere, a novel ecological habitat in the Anthropocene, has garnered global concerns. Recent geochemical evidence has pointed out its potential role in influencing nitrogen biogeochemistry. However, the biogeochemical significance of the plastisphere and its mechanisms regulating nitrogen cycling remain elusive. Using 15N- and 13C-labelling coupled with metagenomics and metatranscriptomics, here we unveil that the plastisphere likely acts as an underappreciated nitrifying niche in estuarine ecosystems, exhibiting a 0.9 ~ 12-fold higher activity of bacteria-mediated nitrification compared to surrounding seawater and other biofilms (stone, wood and glass biofilms). The shift of active nitrifiers from O2-sensitive nitrifiers in the seawater to nitrifiers with versatile metabolisms in the plastisphere, combined with the potential interspecific cooperation of nitrifying substrate exchange observed among the plastisphere nitrifiers, collectively results in the unique nitrifying niche. Our findings highlight the plastisphere as an emerging nitrifying niche in estuarine environment, and deepen the mechanistic understanding of its contribution to marine biogeochemistry.

Thenmozhi D, M. Eswara Rao, Ch. Nagalakshmi et al.

The current study presents a novel examination of heat transfer properties in a magnetohydrodynamic (MHD) flow of Casson fluid across a porous stretching sheet, uniquely incorporating the effects of heat source and variable viscosity. Unlike previous studies, this research employs the Lie similarity transformation to convert the governing equations into a dimensionless form. These transformed equations are then solved using advanced numerical techniques, specifically the fourth-order Runge-Kutta (RK) along with shooting method. The findings reveal that the velocity decreases with the adjustment of significant parameters such as the Casson fluid properties, variable viscosity, heat source, magnetic field, and porosity, leading to an inverse increase in temperature within the convection system. As the Prandtl number increases, the temperature gradient and thermal boundary layer thickness decrease, resulting in reduced heat transfer rates within the convection system. Likewise, an increase in the Schmidt number decreases the concentration gradient and mass transfer rate within the fluid. This novel approach provides new insights into the behavior of Casson fluids, with significant applications in industrial processes, energy systems, environmental engineering, material science, and aerospace and automotive industries, where understanding heat transfer mechanisms in complex systems can enhance efficiency, performance, and safety.

Manish Parashar

Emerging data-driven scientific workflows are seeking to leverage distributed data sources to understand end-to-end phenomena, drive experimentation, and facilitate important decision-making. Despite the exponential growth of available digital data sources at the edge, and the ubiquity of non trivial computational power for processing this data, realizing such science workflows remains challenging. This paper explores a computing continuum that is everywhere and nowhere -- one spanning resources at the edges, in the core and in between, and providing abstractions that can be harnessed to support science. It also introduces recent research in programming abstractions that can express what data should be processed and when and where it should be processed, and autonomic middleware services that automate the discovery of resources and the orchestration of computations across these resources.

Mike Diessner, Kevin J. Wilson, Richard D. Whalley

Experiments in engineering are typically conducted in controlled environments where parameters can be set to any desired value. This assumes that the same applies in a real-world setting -- an assumption that is often incorrect as many experiments are influenced by uncontrollable environmental conditions such as temperature, humidity and wind speed. When optimising such experiments, the focus should lie on finding optimal values conditionally on these uncontrollable variables. This article extends Bayesian optimisation to the optimisation of systems in changing environments that include controllable and uncontrollable parameters. The extension fits a global surrogate model over all controllable and environmental variables but optimises only the controllable parameters conditional on measurements of the uncontrollable variables. The method is validated on two synthetic test functions and the effects of the noise level, the number of the environmental parameters, the parameter fluctuation, the variability of the uncontrollable parameters, and the effective domain size are investigated. ENVBO, the proposed algorithm resulting from this investigation, is applied to a wind farm simulator with eight controllable and one environmental parameter. ENVBO finds solutions for the full domain of the environmental variable that outperforms results from optimisation algorithms that only focus on a fixed environmental value in all but one case while using a fraction of their evaluation budget. This makes the proposed approach very sample-efficient and cost-effective. An off-the-shelf open-source version of ENVBO is available via the NUBO Python package.

U. Nanni, U. Nanni, D. Scherler et al.

<p>Accurate measurements of ice flow are essential to predict future changes in glaciers and ice caps. Glacier displacement can in principle be measured on the large scale by cross-correlation of satellite images. At weekly to monthly scales, the expected displacement is often of the same order as the noise for the commonly used satellite images, complicating the retrieval of accurate glacier velocity. Assessments of velocity changes on short timescales and over complex areas such as mountain ranges are therefore still lacking but are essential to better understand how glacier dynamics are driven by internal and external factors. In this study, we take advantage of the wide availability and redundancy of satellite imagery over the western Pamirs to retrieve glacier velocity changes over 10 d intervals for 7 years and for a wide range of glacier geometry and dynamics. Our results reveal strong seasonal trends. In spring/summer, we observe velocity increases of up to 300 % compared to a slow winter period. These accelerations clearly migrate upglacier throughout the melt season, which we link to changes in subglacial hydrology efficiency. In autumn, we observe glacier accelerations that have rarely been observed before. These episodes are primarily confined to the upper ablation zone with a clear downglacier migration. We suggest that they result from glacier instabilities caused by sudden subglacial pressurization in response to (1) supraglacial pond drainage and/or (2) gradual closure of the hydrological system. Our 10 d resolved measurements allow us to characterize the short-term response of glaciers to changing meteorological and climatic conditions.</p>

E. I. Burt, E. I. Burt, G. R. Goldsmith et al.

<p>Determining the sources of water provisioning streams, soils, and vegetation can provide important insights into the water that sustains critical ecosystem functions now and how those functions may be expected to respond given projected changes in the global hydrologic cycle. We developed multi-year time series of water isotope ratios (<span class="inline-formula"><i>δ</i>¹⁸</span>O and <span class="inline-formula"><i>δ</i>²</span>H) based on twice-monthly collections of precipitation, lysimeter, and tree branch xylem waters from a seasonally dry tropical montane cloud forest in the southeastern Andes mountains of Peru. We then used this information to determine indices of the seasonal origins, the young water fractions (<span class="inline-formula"><i>F</i>_yw</span>), and the new water fractions (<span class="inline-formula"><i>F</i>_new</span>) of soil, stream, and tree water. There was no evidence for intra-annual variation in the seasonal origins of stream water and lysimeter water from 1 m depth, both of which were predominantly comprised of wet-season precipitation even during the dry seasons. However, branch xylem waters demonstrated an intra-annual shift in seasonal origin: xylem waters were comprised of wet-season precipitation during the wet season and dry-season precipitation during the dry season. The young water fractions of lysimeter (<span class="inline-formula">&lt;</span> 15 %) and stream (5 %) waters were lower than the young water fraction (37 %) in branch xylem waters. The new water fraction (an indicator of water <span class="inline-formula">≤</span> 2 weeks old in this study) was estimated to be 12 % for branch xylem waters, while there was no significant evidence for new water in stream or lysimeter waters from 1 m depth. Our results indicate that the source of water for trees in this system varied seasonally, such that recent precipitation may be more immediately taken up by shallow tree roots. In comparison, the source of water for soils and streams did not vary seasonally, such that precipitation may mix and reside in soils and take longer to transit into the stream. Our insights into the seasonal origins and ages of water in soils, streams, and vegetation in this humid tropical montane cloud forest add to understanding of the mechanisms that govern the partitioning of water moving through different ecosystems.</p>

Emilio Vital Brazil, Eduardo Soares, Lucas Villa Real et al.

Data is a critical element in any discovery process. In the last decades, we observed exponential growth in the volume of available data and the technology to manipulate it. However, data is only practical when one can structure it for a well-defined task. For instance, we need a corpus of text broken into sentences to train a natural language machine-learning model. In this work, we will use the token \textit{dataset} to designate a structured set of data built to perform a well-defined task. Moreover, the dataset will be used in most cases as a blueprint of an entity that at any moment can be stored as a table. Specifically, in science, each area has unique forms to organize, gather and handle its datasets. We believe that datasets must be a first-class entity in any knowledge-intensive process, and all workflows should have exceptional attention to datasets' lifecycle, from their gathering to uses and evolution. We advocate that science and engineering discovery processes are extreme instances of the need for such organization on datasets, claiming for new approaches and tooling. Furthermore, these requirements are more evident when the discovery workflow uses artificial intelligence methods to empower the subject-matter expert. In this work, we discuss an approach to bringing datasets as a critical entity in the discovery process in science. We illustrate some concepts using material discovery as a use case. We chose this domain because it leverages many significant problems that can be generalized to other science fields.

Angelo Salatino, Simone Angioni, Francesco Osborne et al.

Understanding the relationship between the composition of a research team and the potential impact of their research papers is crucial as it can steer the development of new science policies for improving the research enterprise. Numerous studies assess how the characteristics and diversity of research teams can influence their performance across several dimensions: ethnicity, internationality, size, and others. In this paper, we explore the impact of diversity in terms of the authors' expertise. To this purpose, we retrieved 114K papers in the field of Computer Science and analysed how the diversity of research fields within a research team relates to the number of citations their papers received in the upcoming 5 years. The results show that two different metrics we defined, reflecting the diversity of expertise, are significantly associated with the number of citations. This suggests that, at least in Computer Science, diversity of expertise is key to scientific impact.

Jan-Christoph Klie, Ji-Ung Lee, Kevin Stowe et al.

Many Natural Language Processing (NLP) systems use annotated corpora for training and evaluation. However, labeled data is often costly to obtain and scaling annotation projects is difficult, which is why annotation tasks are often outsourced to paid crowdworkers. Citizen Science is an alternative to crowdsourcing that is relatively unexplored in the context of NLP. To investigate whether and how well Citizen Science can be applied in this setting, we conduct an exploratory study into engaging different groups of volunteers in Citizen Science for NLP by re-annotating parts of a pre-existing crowdsourced dataset. Our results show that this can yield high-quality annotations and attract motivated volunteers, but also requires considering factors such as scalability, participation over time, and legal and ethical issues. We summarize lessons learned in the form of guidelines and provide our code and data to aid future work on Citizen Science.

Shasha Zhao, Liuqingqing Liu, Chenguang Li et al.

IntroductionBiobased polymer blends have been recommended as an eco-friendly solution to abate plastic pollution in the environment. However, the formation of microplastics (MPs) by photodegradation of biobased polymer blends in the marine environment is still not well understood. In this study, we investigated the formation of MPs and the changes in the physicochemical properties of three types of biobased polymer blends after photodegradation in seawater.MethodsThe investigated materials included non-biodegradable polyethylene/ thermoplastic starch blends (PE/TPS) and polypropylene/thermoplastic starch blends (PP/TPS), as well as biodegradable polylactic acid/poly (butylene adipate-co-terephthalate)/thermoplastic starch blends (PLA/PBAT/TPS). The control groups were the corresponding neat polymers, including polyethylene (PE), polypropylene (PP), and polylactic acid (PLA).ResultsThe size distribution of the pristine and aged MPs indicated that the polymer blends were more likely to produce small-sized particles after photodegradation due to their poorer mechanical properties and lower resistance to UV irradiation than the neat polymers. Noticeable surface morphology alterations, including cracks, holes, and pits, were observed for polymer blends after photodegradation, while neat polymers were relatively resistant. After photodegradation, the attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR) spectrum of the polymer blends showed a significant decrease in the characteristic bands of thermoplastic starch (TPS), indicating depletion of their starch fractions. The C1s spectra of the polymer blends demonstrated that the aged MPs contained fewer -OH groups than the pristine MPs, further confirming the photodegradation of TPS. The molecular weight distribution curve of the polymer blends shifted significantly towards low molecular weight, suggesting the occurrence of chain scission during photodegradation. These results indicate that the polymer blends have a higher degree of photodegradation than neat polymers, and thereby generate more small-sized MPs than neat polymers. Photodegradation caused changes in the contact angle and surface charge of MPs derived from biobased polymer blends, which may affect the vector effects of MPs on any coexisting pollutants.DiscussionIn summary, polymer blends may pose a higher risk to the marine environment than neat polymers, and caution should be taken in promoting biobased polymer blends.

Gaolei Jiang, Nai'ang Wang, Dayou Zhai et al.

Limnocythere inopinata (Baird, 1843) is a widely distributed ostracod in modern non-marine waters and Quaternary sediments. Based on its morphological variation (the number and position of its nodes), different phenotypes have been identified. However, the factors controlling its morphological variation are currently open to debate, which hinders palaeoecological reconstructions based on this species. In this study, ostracod distribution and hydrochemical analyses of the ambient environment of 21 lakes in the Badain Jaran Desert were carried out. Three ostracod species belonging to two genera are identified as Limnocyhtere inopinata, Cypris cf. granulate and Cypris sp. with the dominant species L. inopinata represented by six phenotypes. The distribution features of these ostracods in the lakes and related ecological information are reported. In addition, the factors controlling the morphological variations of L. inopinata were analysed. Our data indicate that the noded individuals of L. inopinata prefer water with appropriate Ca2+ content (30–40 mg L−1) and low salinities (below 4.60 g L−1). The percentage of noded individuals of L. inopinata increases with increasing salinity only within a certain salinity range. Hence, caution should be exercised in reconstructions of palaeosalinity based on the morphological variability of L. inopinata.

Marcelo O. Soares, Marcelo O. Soares, Luis Ernesto Arruda Bezerra et al.

In this article, we discuss knowledge and gaps regarding blue carbon ecosystems (BCEs) in Brazil, considering the urgency to apply protection actions and policies to safeguard their biodiversity and associated ecosystem services. We also indicate areas of further research to improve carbon stocks and sequestration rate estimates. We call attention to the shortage of studies on Brazilian BCEs relative to the growing knowledge on the Blue Carbon Framework accumulated worldwide over the last decade. Considering the extensive Brazilian Economic Exclusive Zone (known as “Blue Amazon”), knowledge concerning blue carbon stocks is vital at regional and global scales for mitigating global increases in atmospheric carbon dioxide (CO2). The Blue Amazon has at least 1,100,000 ha of vegetated and non-vegetated coastal ecosystems (mangroves, salt marshes, seagrass meadows, and hypersaline tidal flats) that collectively contain vast amounts of stored carbon, making Brazil an ideal place to test mechanisms for evaluating, conserving, and restoring BCEs. Other poorly understood potential sinks and sources of carbon are macroalgal and rhodolith beds, mudflats, continental shelf sediments, and marine animal forests in shallow, mesophotic, and deep waters. The carbon fluxes between diverse environmental compartments, such as soil–air, soil–water, groundwater–water–surface water, air–water, and land–ocean, in BCEs across the Blue Amazon must be studied. We emphasize the importance of assessing the total carbon stock and the recent dismantling of environmental laws that pose great risks to these important BCEs. The conservation and recovery of these areas would enhance the carbon sequestration capacity of the entire country. Furthermore, we highlight priorities to improve knowledge concerning BCEs and their biogeochemical cycles in the Blue Amazon and to provide information to assist in the reduction of atmospheric levels of CO2 for the United Nations Decade of Ocean Science (2021–2030).

Michael A. Heroux

Software plays a central role in scientific discovery. Improving how we develop and use software for research can have both broad and deep impacts on a spectrum of challenges and opportunities society faces today. The emergence of Research Software Engineer (RSE) as a role correlates with the growing complexity of scientific challenges and diversity of software team skills. In this paper, we describe research software science (RSS), an idea related to RSE, and particularly suited to research software teams. RSS promotes the use of scientific methodologies to explore and establish broadly applicable knowledge. Using RSS, we can pursue sustainable, repeatable, and reproducible software improvements that positively impact research software toward improved scientific discovery.