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Incoherent scatter radars (ISRs) represent the only instrument (both ground and space based) capable of making high temporal and spatial resolution measurements of multiple atmospheric parameters—such as densities, temperatures, particle velocities, mass flux—over an altitude range covering the entire mesosphere/lower thermosphere/ionosphere (MLTI) system on a quasi-continuous basis. The EISCAT Svalbard incoherent scatter radar (ESR), located just outside Longyearbyen (78.15 ∘ N) on Svalbard, is the only currently operating facility capable of making such measurements inside the polar cusp—an area of significant energy input into the atmosphere and characterized by heating instabilities and turbulence. The ESR was built in the mid-1990s and has provided valuable data for the international experimental and modelling communities. New radar technologies are now available, in the form of phased array systems, which offer new data products and operational flexibility. This paper outlines the achievements and current research focus of the ESR and provides scientific arguments, compiled from inputs across the international scientific community, for a new phased array ISR facility on Svalbard. In addition to the fundamental scientific arguments, the paper discusses additional benefits of continued ISR observations on Svalbard, building on the key findings of the ESR. Svalbard has a large network of complementary instrumentation both focused on the MLTI system (e.g. the Kjell Henriksen auroral Observatory, the Svalbard SuperDARN radar and the Svalrak sounding rocket launch facility) with synergies to other research fields, such as meteorology and oceanography. As a further holistic system science view of the Earth becomes more important, a new ISR on Svalbard will be important also in this respect with its ability to provide datasets with a wide range of scientific applications. Increased activity in space has highlighted problematic issues such as space debris. A changing Arctic has also seen increased human activity via the opening up of new shipping routes, which are reliant on GNSS technology that is effected by severe turbulence in the MLTI system. As such, societal applications of a future ISR are also presented. The accessibility and logistical support for such a facility is also briefly discussed. [ABSTRACT FROM AUTHOR]

Incoherent scatter radars (ISRs) represent the only instrument (both ground and space based) capable of making high temporal and spatial resolution measurements of multiple atmospheric parameters—such as densities, temperatures, particle velocities, mass flux—over an altitude range covering the entire mesosphere/lower thermosphere/ionosphere (MLTI) system on a quasi-continuous basis. The EISCAT Svalbard incoherent scatter radar (ESR), located just outside Longyearbyen (78.15 ∘ N) on Svalbard, is the only currently operating facility capable of making such measurements inside the polar cusp—an area of significant energy input into the atmosphere and characterized by heating instabilities and turbulence. The ESR was built in the mid-1990s and has provided valuable data for the international experimental and modelling communities. New radar technologies are now available, in the form of phased array systems, which offer new data products and operational flexibility. This paper outlines the achievements and current research focus of the ESR and provides scientific arguments, compiled from inputs across the international scientific community, for a new phased array ISR facility on Svalbard. In addition to the fundamental scientific arguments, the paper discusses additional benefits of continued ISR observations on Svalbard, building on the key findings of the ESR. Svalbard has a large network of complementary instrumentation both focused on the MLTI system (e.g. the Kjell Henriksen auroral Observatory, the Svalbard SuperDARN radar and the Svalrak sounding rocket launch facility) with synergies to other research fields, such as meteorology and oceanography. As a further holistic system science view of the Earth becomes more important, a new ISR on Svalbard will be important also in this respect with its ability to provide datasets with a wide range of scientific applications. Increased activity in space has highlighted problematic issues such as space debris. A changing Arctic has also seen increased human activity via the opening up of new shipping routes, which are reliant on GNSS technology that is effected by severe turbulence in the MLTI system. As such, societal applications of a future ISR are also presented. The accessibility and logistical support for such a facility is also briefly discussed. [ABSTRACT FROM AUTHOR]

Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud‐SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi‐decadal SST variability. A heat‐budget analysis reveals coupling between cloud‐radiative effects, circulation, and SST gradients in driving multi‐decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ∼ ${\sim} $56% on average. If models underestimate climate "noise," as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate. Plain Language Summary: In recent decades, observed sea surface temperatures (SSTs) have cooled in the eastern tropical Pacific and warmed in the western tropical Pacific. Historical simulations using state‐of‐the‐art climate models fail to reproduce this pattern. We find that the feedback between low‐lying clouds and SSTs is related to the magnitude of naturally occurring SST variability in the Southeast Pacific. On average, climate models that have too weak a cloud‐SST feedback in the Southeast Pacific underestimate the likelihood of multi‐decadal cooling in the eastern Pacific in preindustrial simulations. Our results suggest that biases in cloud feedbacks may be causing models to underestimate internal SST variability. Key Points: Multi‐decadal Southeast Pacific sea surface temperature trends are related to the strength of the subtropical cloud feedbackCloud radiative effects amplify multi‐decadal Pacific sea surface temperature trends by impacting circulation and surface energy fluxesCorrecting model biases in cloud feedback raises the likelihood of internally producing Southeast Pacific cooling as large as observations [ABSTRACT FROM AUTHOR]

Aircraft observations of high-energy rays emitted by thunderstorms reveal that they are both intense and dynamic. Long-lasting glows that switch to rapidly flickering flashes could offer clues to how lightning forms.Aircraft observations of γ-rays emitted by thunderstorms. [ABSTRACT FROM AUTHOR]

Shallow water waves are seen in oceanography, atmospheric science, and other fields. In this paper, we investigate an extended (3+1)-dimensional shallow water wave equation. We get the travelling-wave solutions via the polynomial-expansion method. Applying the Hirota method and symbolic computation, we derive some mixed-lump-kink and mixed-rogue-wave-kink solutions. Based on the mixed-lump-kink solutions, we graphically show the interaction between a lump and a kink soliton, and find two different cases: (1) the lump merges into the kink soliton; (2) the lump separates from the kink soliton. Based on the mixed-rogue-wave-kink solutions, we graphically analyze the interaction between the rogue wave and two-kink solitons, and find that the rogue wave emerges from the one kink soliton and merges into the other kink soliton. [ABSTRACT FROM AUTHOR]

Recovering additional historical weather observations from known archival sources will improve the understanding of how the climate is changing and enable detailed examination of unusual events within the historical record. The UK National Meteorological Archive recently scanned more than 66,000 paper sheets containing 5.28 million hand‐written monthly rainfall observations taken across the UK and Ireland between 1677 and 1960. Only a small fraction of these observations were previously digitally available for climate scientists to analyse. More than 16,000 volunteer citizen scientists completed the transcription of these sheets of observations during early 2020 using the RainfallRescue.org website, built using the Zooniverse platform. A total of 3.34 million observations from more than 6000 locations have so far been quality controlled and made openly available. This has increased the total number of monthly rainfall observations that are available for this time period and region by a factor of six. The newly rescued observations will enable longer and much improved reconstructions of past variations in rainfall across the British and Irish Isles, including for periods of significant flooding and drought. Specifically, this data should allow the official gridded monthly rainfall reconstructions for the UK to be extended back to 1836, and even earlier for some regions. [ABSTRACT FROM AUTHOR]

High‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over‐entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present‐day climate, limiting their scientific utility. We report new results showing that this over‐entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small‐scale momentum fluctuations associated with the formulation of the momentum solver of the embedded large eddy simulation. By considering the sedimentation process adjacent to default one‐moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that can produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub‐cloud eddy spectrum are observed. We report these sensitivities in multi‐week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5° exterior resolution. The result is a new HR having desired improvements in the baseline present‐day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation. Plain Language Summary: Stratocumulus clouds cover a large fraction of the globe but are very challenging to reproduce in computer simulations of Earth's atmosphere because of their unique complexity. Previous studies find the model produces too few Stratocumulus clouds as we increase the model resolution, which, in theory, should improve the simulation of important motions for the clouds. This is because the clouds are exposed to more conditions that make them evaporate away. On Earth, stratocumulus clouds reflect a lot of sunlight. In the computer model of Earth, too much sunlight reaches the surface because of too few stratocumulus clouds, which makes it warmer. This study tests two methods to thicken Stratocumulus clouds in the computer model Earth. The first method smooths out some winds, which helps reduce the exposure of clouds to the conditions that make them evaporate. The second method moves water droplets in the cloud away from the conditions that would otherwise make them evaporate. In long simulations, combining these methods helps the model produce thicker stratocumulus clouds with more water. Key Points: We improve a long‐standing stratocumulus (Sc) dim bias in a high‐resolution Multiscale Modeling FrameworkIncorporating intra‐CRM hyperviscosity hedges against the numerics of its momentum solver, reducing entrainment vicinityFurther adding sedimentation boosts Sc brightness close to observed, opening path to more faithful low cloud feedback analysis [ABSTRACT FROM AUTHOR]

This bibliometric study of a large publication set dealing with research on climate change aims at mapping the relevant literature from a bibliometric perspective and presents a multitude of quantitative data: (1) The growth of the overall publication output as well as (2) of some major subfields, (3) the contributing journals and countries as well as their citation impact, and (4) a title word analysis aiming to illustrate the time evolution and relative importance of specific research topics. The study is based on 222,060 papers (articles and reviews only) published between 1980 and 2014. The total number of papers shows a strong increase with a doubling every 5–6 years. Continental biomass related research is the major subfield, closely followed by climate modeling. Research dealing with adaptation, mitigation, risks, and vulnerability of global warming is comparatively small, but their share of papers increased exponentially since 2005. Research on vulnerability and on adaptation published the largest proportion of very important papers (in terms of citation impact). Climate change research has become an issue also for disciplines beyond the natural sciences. The categories Engineering and Social Sciences show the strongest field-specific relative increase. The Journal of Geophysical Research, the Journal of Climate, the Geophysical Research Letters, and Climatic Change appear at the top positions in terms of the total number of papers published. Research on climate change is quantitatively dominated by the USA, followed by the UK, Germany, and Canada. The citation-based indicators exhibit consistently that the UK has produced the largest proportion of high impact papers compared to the other countries (having published more than 10,000 papers). Also, Switzerland, Denmark and also The Netherlands (with a publication output between around 3,000 and 6,000 papers) perform top—the impact of their contributions is on a high level. The title word analysis shows that the term climate change comes forward with time. Furthermore, the term impact arises and points to research dealing with the various effects of climate change. The discussion of the question of human induced climate change towards a clear fact (for the majority of the scientific community) stimulated research on future pathways for adaptation and mitigation. Finally, the term model and related terms prominently appear independent of time, indicating the high relevance of climate modeling. [ABSTRACT FROM AUTHOR]

The action required to stem the environmental and social implications of climate change depends crucially on how humankind shapes technology, economy, lifestyle and policy. With transport CO2 emissions accounting for about a quarter of the total, we examine the contribution of CO2 output by scientific travel. Thankfully for the reputation of the scientific community, CO2 emissions associated with the trips required to present a paper at a scientific conference account for just 0.003% of the yearly total. However, with CO2 emissions for a single conference trip amounting to 7% of an average individual’s total CO2 emissions, scientists should lead by example by demonstrating leadership in addressing the issue. [ABSTRACT FROM AUTHOR]

Atmospheric science research has seen significant advances in facilitating the generation of knowledge and promoting a scientific understanding of global meteorological issues and concerns with the advent of technological progress across many disciplines, including the physical and biological sciences and the breakthroughs in computational and modeling methodologies. This has resulted in a rich library of scientific literature showcasing knowledge creation and a deeper understanding of natural phenomena and their linkages to the sustenance of life embodied by the extensive systems of the hydrosphere, biosphere, and even the frontiers of outer space. This article outlines how primary research in atmospheric science can be integrated into chemical education by furnishing connections and synchronicity with chemistry, bridging the concepts, discoveries, innovations, and their immediate importance to science and society. A general overview is given on how topics or themes in general chemistry courses can utilize the power of scientific research articles on atmospheric science, fostering students' interest in meteorological concepts and related fields. A non-exhaustive list of primary research literature highlighting breakthroughs related to a specific chemistry theme serving as templates for chemical educators is provided to enable the students to see real-world applications. Integrating research into science education is an effective strategy to promote scientific thinking and literacy and should be a catalyst for the global drive for sustainability. [ABSTRACT FROM AUTHOR]

An unprecedented glimpse of a distant planet reveals clues about how it might have formed. Scientists explain why it's a win for atmospheric chemistry, and celebrate the technology that made it possible. Two viewpoints on data from a distant world. [ABSTRACT FROM AUTHOR]

A cutting-edge global model of the atmosphere combines machine learning with a numerical model based on the laws of physics. This 'hybrid' system accurately predicts the weather — and even shows promise for climate simulations. Numerical modelling and machine learning unite to emulate the atmosphere. [ABSTRACT FROM AUTHOR]

Unexpected smoke-particle chemistry is shown to be the link between intense wildfires and stratospheric ozone loss. As the climate changes, more-frequent and more-intense fires might delay the recovery of the stratospheric ozone layer.Smoke particles promote ozone depletion more than was thought. [ABSTRACT FROM AUTHOR]

Dryland ecosystems cover nearly 45% of the Earth’s land area and account for large proportions of terrestrial net primary production and carbon pools. However, predicting rates of plant litter decomposition in these vast ecosystems has proven challenging due to their distinctly dry and often hot climate regimes, and potentially unique physical drivers of decomposition. In this study, we elucidated the role of photopriming, i.e. exposure of standing dead leaf litter to solar radiation prior to litter drop that would chemically change litter and enhance biotic decay of fallen litter. We exposed litter substrates to three different UV radiation treatments simulating three-months of UV radiation exposure in southern New Mexico: no light, UVA+UVB+Visible, and UVA+Visible. There were three litter types: mesquite leaflets (Prosopis glandulosa, litter with high nitrogen (N) concentration), filter paper (pure cellulose), and basswood (Tilia spp, high lignin concentration). We deployed the photoprimed litter in the field within a large scale precipitation manipulation experiment: ∼50% precipitation reduction, ∼150% precipitation addition, and ambient control. Our results revealed the importance of litter substrate, particularly N content, for overall decomposition in drylands, as neither filter paper nor basswood exhibited measurable mass loss over the course of the year-long study, while high N-containing mesquite litter exhibited potential mass loss. We saw no effect of photopriming on subsequent microbial decay. We did observe a precipitation effect on mesquite where the rate of decay was more rapid in ambient and precipitation addition treatments than in the drought treatment. Overall, we found that precipitation and N played a critical role in litter mass loss. In contrast, photopriming had no detected effects on mass loss over the course of our year-long study. These results underpin the importance of biotic-driven decomposition, even in the presence of photopriming, for understanding litter decomposition and biogeochemical cycles in drylands. [ABSTRACT FROM AUTHOR]

Most lidars used for cloud observations have the range resolution of about 10 m, so they are incapable of resolving submeter-scale processes that are crucial to cloud evolution. This article describes a prototype of a ground-based, vertically pointing, time-gated, time-correlated single-photon-counting lidar (referred to as the T2 lidar) developed to explore atmospheric clouds at range resolution two orders of magnitude finer than traditional atmospheric lidars. The T2 lidar emits green-light pulses (532 nm) at a repetition rate of 20.6 kHz and a pulse width of ∼650 ps, which enables the observation of aerosol and cloud layers at heights from a few hundred meters to 7.28 km above the ground level at range resolution down to 10 cm. In addition, a digital delay pulse generator controls the detector to only receive photons for a short period after each laser pulse. This time-gated technique blocks photons arriving from regions outside the target zone, thus significantly reducing the noise level and allowing observation even inside clouds. Initial observations show that the T2 lidar can detect sharp cloud boundaries and fine structures near the cloud base. Such refined measurements of cloud structure could lead to an improved understanding of microphysical processes such as droplet activation, entrainment and mixing, and precipitation. [ABSTRACT FROM AUTHOR]

Individual paintings by artists including Vincent van Gogh and Edvard Munch have been shown to depict specific atmospheric phenomena, raising the question of whether longer-term environmental change influences stylistic trends in painting. Anthropogenic aerosol emissions increased to unprecedented levels during the 19th century as a consequence of the Industrial Revolution, particularly in Western European cities, leading to an optical environment having less contrast and more intensity. Here, we show that trends from more figurative to impressionistic representations in J.M.W. Turner and Claude Monet's paintings in London and Paris over the 19th century accurately render physical changes in their local optical environment. In particular, we demonstrate that changes in local sulfur dioxide emissions are a highly statistically significant explanatory variable for trends in the contrast and intensity of Turner, Monet, and others' works, including after controlling for time trends and subject matter. Industrialization altered the environmental context in which Turner and Monet painted, and our results indicate that their paintings capture changes in the optical environment associated with increasingly polluted atmospheres during the Industrial Revolution. [ABSTRACT FROM AUTHOR]

This paper studies the heterogeneous effects of exchange rate and stock market on carbon emission allowance price in four emissions trading scheme pilots in China. We employ a panel quantile regression model, which can describe both individual and distributional heterogeneity. The empirical results illustrate that the effects of explanatory variables on carbon emission allowance price is heterogeneous along the whole quantiles. Specifically, exchange rate has a negative effect on carbon emission allowance price at lower quantiles, while becomes a positive effect at higher quantiles. In addition, a negative effect exists between domestic stock market and carbon emission allowance price, and the intensity decreasing along with the increase of quantile. By contrast, an increasing positive effect is discovered between European stock market and domestic carbon emission allowance prices. Finally, heterogeneous effects on carbon emission allowance price can also be proved in European Union Emission Trading Scheme (EU-ETS). [ABSTRACT FROM AUTHOR]

This paper constructed a stacked-autoencoder neural network model (SAE model) to estimate sea state bias (SSB) based on radar altimeter data. Six cycles of the geophysical data record (GDR) from Jason-1/2 radar altimeters were used as a training dataset, and the other 2 cycles of the GDR from Jason-1/2 were used for testing. The inputs to this SAE model include the significant wave height (SWH), wind speed (U), sea surface height (SSH), backscatter coefficient (σ0) and automatic gain control (AGC), and the model outputs the SSB. The model includes one input layer, three hidden layers and one output layer. The SSBs in the GDR of Jason-1/2 were obtained from a nonparametric model based on the SWH and U as input variables; thus, the model has high accuracy but low efficiency. The SSBs in the GDR of HY-2A were computed using a four-parameter parametric model that uses the SWH and U as input variables; therefore, this model’s computational speed is high but its accuracy is low. Thus, we used the HY-2A radar altimeter as an unseen validation dataset to evaluate the performance of the SAE model. Then, we analyzed the contrasting results of these methods, including the differences in the SSB, explained variance, residual error and operational efficiency. The results demonstrate not only that the accuracy of the SAE model is superior to that of the conventional parametric model but also that its operational efficiency is better than that of the nonparametric model. [ABSTRACT FROM AUTHOR]

This paper proposes a method based on a local weather type classification approach to facilitate analysis and communication of climate information in local climate studies. Presented herein is an application to urban climatology in Toulouse, France, but the method can be used in other applied fields of climatology as well. To describe the climatic context of this urbanized area, the local weather types that explain the plurality of weather situations Toulouse faces are presented in depth. In order to show the potential for use of this approach, this information is applied to the study of changes in local weather types in terms of frequency and intensity within a series of future climate projections, a classic urban canopy and a series of atmospheric boundary layer analyses, and as a support for communication aimed to initiate urban climate awareness in urban planning practices. The proposed classification method has been coded in an R script and is provided as a supporting information file. The paper concludes that a systematic pre-study using this kind of climatic analysis is a good practice for performing climatic contextualization in local scale applied studies, both for scientific analysis and communication. [ABSTRACT FROM AUTHOR]

The space telescope has helped to determine the atmospheric composition of an exoplanet using the light spectrum of its host star. Spectral changes as the planet orbits the star reveal the long-sought presence of exoplanetary methane.Methane detected in an exoplanet’s atmosphere. [ABSTRACT FROM AUTHOR]

Wind and temperature data are important parameters in aircraft performance studies. The lack of accurate measurements of these parameters forces researchers to rely on numerical weather prediction models, which are often filtered for a larger area with decreased local accuracy. Aircraft, however, also transmit information related to weather conditions, in response to interrogation by air traffic controller surveillance radars. Although not intended for this purpose, aircraft surveillance data contains information that can be used for weather models. This paper presents a method that can be used to reconstruct a weather field from surveillance data that can be received with a simple 1090 MHz receiver. Throughout the paper, we answer two main research questions: how to accurately infer wind and temperature from aircraft surveillance data, and how to reconstruct a real-time weather grid efficiently. We consider aircraft as moving sensors that measure wind and temperature conditions indirectly at different locations and flight levels. To address the first question, aircraft barometric altitude, ground velocity, and airspeed are decoded from down-linked surveillance data. Then, temperature and wind observations are computed based on aeronautical speed conversion equations. To address the second question, we propose a novel Meteo-Particle (MP) model for constructing the wind and temperature fields. Short-term local prediction is also possible by employing a predictor layer. Using an unseen observation test dataset, we are able to validate that the mean absolute errors of inferred wind and temperature using MP model are 67% and 26% less than using the interpolated model based on GFS reanalysis data. [ABSTRACT FROM AUTHOR]

This paper investigates the consequences of ignoring the clustered data structure on allometric models. Clustered data, in the form of multiple trees sampled from multiple forest stands is commonly used to develop biomass allometric models. Of 102 reviewed papers published between 2012 and 2016 that reported biomass allometric models, 84 (82%) have used a clustered sampling design. However, in as many as 80% of these, the clustered data structure was ignored, potentially violating the independence assumption in ordinary least squares methods. The consequences of ignoring clustered data structure were empirically validated using two clustered biomass datasets (of 110 and 220 trees, with the cluster size of 5 and 10 trees respectively). We showed that when Intraclass Correlation Coefficient (ICC) was higher than zero, ignoring the clustered data structure returned underestimated standard errors, affecting further the confidence interval and t-test results. The underestimation level depended on ICC (which shows the variance proportion that was caused by the forest stand) and on cluster size (the number of trees sampled from one forest stand). We also showed that using first-order autocorrelation tests, such as the traditional Durbin-Watson statistic, to detect the autocorrelation due to clustered structure could be misleading as the test may show lack of autocorrelation even though ICC is different from zero. In conclusion, when ICC is higher than zero, ignoring the clustered data structure yields over-confident biomass predictions (due to underestimated confidence interval) and/or incorrect research conclusions (due to overestimated evidence against null hypothesis in t-test). Therefore, using a modelling approach that accounts for the hierarchical structure of the data is highly recommended when any form of clustering can be identified, even if the autocorrelation is not significant. [ABSTRACT FROM AUTHOR]

Local and indigenous knowledge is being transformed globally, particularly being eroded when pertaining to ecology. In many parts of the world, rural and indigenous communities are facing tremendous cultural, economic and environmental changes, which contribute to weaken their local knowledge base. In the face of profound and ongoing environmental changes, both cultural and biological diversity are likely to be severely impacted as well as local resilience capacities from this loss. In this global literature review, we analyse the drivers of various types of local and indigenous ecological knowledge transformation and assess the directionality of the reported change. Results of this analysis show a global impoverishment of local and indigenous knowledge with 77% of papers reporting the loss of knowledge driven by globalization, modernization, and market integration. The recording of this loss, however, is not symmetrical, with losses being recorded more strongly in medicinal and ethnobotanical knowledge. Persistence of knowledge (15% of the studies) occurred in studies where traditional practices were being maintained consiously and where hybrid knowledge was being produced as a resut of certain types of incentives created by economic development. This review provides some insights into local and indigenous ecological knowledge change, its causes and implications, and recommends venues for the development of replicable and comparative research. The larger implication of these results is that because of the interconnection between cultural and biological diversity, the loss of local and indigenous knowledge is likely to critically threaten effective conservation of biodiversity, particularly in community-based conservation local efforts. [ABSTRACT FROM AUTHOR]

Over recent years, several visualization tools that offer advanced threedimensional (3D) rendering techniques, while still showing good performance for large data sets, have been developed. However, how to provide an intuitive way to combine traditional two-dimensional (2D) methods essential in operational weather forecasting and new 3D techniques welcomed in atmospheric research is not fully investigated, if not overlooked, in these tools. The paper presents MeteoExplorer: a software tool designed to analyse and visualize atmospheric and geoscience data. It consists of a developer-orientedcrossplatform foundation framework and several applications built upon the framework. The framework is developed with C++ on the central processing unit side and shader languages on the graphics processing unit (GPU) side. Modules in the framework are loosely coupled with minimum interdependencies to facilitate code reuse and improve code efficiency. Compared with other software tools, the framework provides distinctive features, including a unified framework that integrates both 2D and 3D rendering context, comprehensive support of popular data formats and computing platforms, decent rendition quality via the export of vector graphics and page layout customization, and interactive composition of synoptic charts. Based on the foundation libraries, the software can develop web, desktop and mobile applications for meteorological purposes. These applications support the analysis and visualization of numerous data set types, as well as the interactive content creation. MeteoExplorer is an exploratory project that provides forecasters with new techniques for climate diagnosis and forecasts. [ABSTRACT FROM AUTHOR]

This paper reviews some of the challenges posed by the huge growth of experimental data generated by the new generation of large-scale experiments at UK national facilities at the Rutherford Appleton Laboratory (RAL) site at Harwell near Oxford. Such 'Big Scientific Data' comes from the Diamond Light Source and Electron Microscopy Facilities, the ISIS Neutron and Muon Facility and the UK's Central Laser Facility. Increasingly, scientists are now required to use advanced machine learning and other AI technologies both to automate parts of the data pipeline and to help find new scientific discoveries in the analysis of their data. For commercially important applications, such as object recognition, natural language processing and automatic translation, deep learning has made dramatic breakthroughs. Google's DeepMind has now used the deep learning technology to develop their AlphaFold tool to make predictions for protein folding. Remarkably, it has been able to achieve some spectacular results for this specific scientific problem. Can deep learning be similarly transformative for other scientific problems? After a brief review of some initial applications of machine learning at the RAL, we focus on challenges and opportunities for AI in advancing materials science. Finally, we discuss the importance of developing some realistic machine learning benchmarks using Big Scientific Data coming from several different scientific domains. We conclude with some initial examples of our 'scientific machine learning' benchmark suite and of the research challenges these benchmarks will enable. [ABSTRACT FROM AUTHOR]

Significant progress has been made in the past few years in the development of recommendations, policies, and procedures for creating and promoting citations to data sets, software, and other research infrastructures like computing facilities. Open questions remain, however, about the extent to which referencing practices of authors of scholarly publications are changing in ways desired by these initiatives. This paper uses four focused case studies to evaluate whether research infrastructures are being increasingly identified and referenced in the research literature via persistent citable identifiers. The findings of the case studies show that references to such resources are increasing, but that the patterns of these increases are variable. In addition, the study suggests that citation practices for data sets may change more slowly than citation practices for software and research facilities, due to the inertia of existing practices for referencing the use of data. Similarly, existing practices for acknowledging computing support may slow the adoption of formal citations for computing resources. [ABSTRACT FROM AUTHOR]

Dispersal knowledge is essential for conservation management, and demand is growing. But are we accumulating dispersal knowledge at a pace that can meet the demand? To answer this question we tested for changes in dispersal data collection and use over time. Our systematic review of 655 conservation-related publications compared five topics: climate change, habitat restoration, population viability analysis, land planning (systematic conservation planning) and invasive species. We analysed temporal changes in the: (i) questions asked by dispersal-related research; (ii) methods used to study dispersal; (iii) the quality of dispersal data; (iv) extent that dispersal knowledge is lacking, and; (v) likely consequences of limited dispersal knowledge. Research questions have changed little over time; the same problems examined in the 1990s are still being addressed. The most common methods used to study dispersal were occupancy data, expert opinion and modelling, which often provided indirect, low quality information about dispersal. Although use of genetics for estimating dispersal has increased, new ecological and genetic methods for measuring dispersal are not yet widely adopted. Almost half of the papers identified knowledge gaps related to dispersal. Limited dispersal knowledge often made it impossible to discover ecological processes or compromised conservation outcomes. The quality of dispersal data used in climate change research has increased since the 1990s. In comparison, restoration ecology inadequately addresses large-scale process, whilst the gap between knowledge accumulation and growth in applications may be increasing in land planning. To overcome apparent stagnation in collection and use of dispersal knowledge, researchers need to: (i) improve the quality of available data using new approaches; (ii) understand the complementarities of different methods and; (iii) define the value of different kinds of dispersal information for supporting management decisions. Ambitious, multi-disciplinary research programs studying many species are critical for advancing dispersal research. [ABSTRACT FROM AUTHOR]

Today's moon is vastly different from what it was 3 billion years ago. At that time, it was home to a collisional atmosphere formed through massive amounts of volcanism, releasing enough subsurface gas to sustain surface pressures of up to 1 kPa. Observations of our solar system have taught us that all dense atmospheres are host to clouds and aerosols, and we expect the Moon's to be no different. Knowing when, where, and under what conditions cloud particles form is important for understanding the evolution of the lunar atmosphere, how it reacted to temperature gradients, and how it cycled volatiles. To study this, I investigated the immersion freezing properties of three aerosols: JSC- 1A lunar simulant, which is similar in composition and properties to lunar sample #14163 returned by the Apollo 14 Mission; Exolith LMS- 1D Lunar Mare simulant, which simulates volcanic deposits on the Moon's surface; and Arizona Test Dust (ATD), a standard for Earth atmospheric studies. A Peltier thermoelectric cooler and droplet freezing array were used to isolate Millipore water droplets with aerosols cooled to temperatures as low as - 18 ° C. Aerosol type, aerosol concentration, and droplet size was varied across these experiments. Both lunar simulants were found to nucleate ice less frequently than ATD, with JSC- 1A nucleating more droplets than LMS- 1D, which exhibited freezing properties similar to pure water. The results indicate that water ice nucleation is possible but highly variable on lunar regolith aerosols, and cloud formation on volcanic dust may have been possible in the ancient lunar atmosphere. [ABSTRACT FROM AUTHOR]

Introduction: In connection to food insecurity, adaptation of new techniques or alteration of regular behavior is executed that translates to coping strategies. This paper has used data from food security and nutrition surveillance project (FSNSP), which collects information from a nationally representative sample in Bangladesh on coping behaviors associated with household food insecurity. To complement the current understanding of different coping strategies implemented by the Bangladeshi households, the objective of this paper has been set to examine the demographic and socio-economic characteristics of the food insecure households which define their propensity towards adaptation of different types of coping strategies. Methodology: FSNSP follows a repeated cross-sectional survey design. Information of 23,374 food insecure households available from February 2011 to November 2013 was selected for the analyses. Coping strategies were categorized as financial, food compromised and both. Multinomial logistic regression was employed to draw inference. Results: Majority of the households were significantly more inclined to adopt both multiple financial and food compromisation coping strategies. Post-aman season, educational status of the household head and household women, occupation of the household’s main earner, household income, food insecurity status, asset, size and possession of agricultural land were found to be independently and significantly associated with adaptation of both financial and food compromisation coping strategies relative to only financial coping strategies. The relative risk ratio of adopting food compromisation coping relative to financial coping strategies when compared to mildly food insecure households, was 4.54 times higher for households with moderate food insecurity but 0.3 times lower when the households were severely food insecure. Whereas, households were 8.04 times and 4.98 times more likely to adopt both food compromisation and financial relative to only financial coping strategies if moderately and severely food insecure respectively when compared to being mildly food insecure. Conclusion: Households suffering from moderate and severe food insecurity, are more likely to adopt both financial and food compromisation coping strategies. [ABSTRACT FROM AUTHOR]

Peer-reviewed publications focusing on climate change are growing exponentially with the consequence that the uptake and influence of individual papers varies greatly. Here, we derive metrics of narrativity from psychology and literary theory, and use these metrics to test the hypothesis that more narrative climate change writing is more likely to be influential, using citation frequency as a proxy for influence. From a sample of 732 scientific abstracts drawn from the climate change literature, we find that articles with more narrative abstracts are cited more often. This effect is closely associated with journal identity: higher-impact journals tend to feature more narrative articles, and these articles tend to be cited more often. These results suggest that writing in a more narrative style increases the uptake and influence of articles in climate literature, and perhaps in scientific literature more broadly. [ABSTRACT FROM AUTHOR]

Although substantial attention has focused on efforts by the new Administration to block environmental policies, climate politics have been contentious in the US since well before the election of Donald Trump. In this paper, we extend previous work on empirical examinations of echo chambers in US climate politics using new data collected on the federal climate policy network in summer 2016. We test for the similarity and differences at two points in time in homophily and echo chambers using Exponential Random Graph Models (ERGM) to compare new findings from 2016 to previous work on data from 2010. We show that echo chambers continue to play a significant role in the network of information exchange among policy elites working on the issue of climate change. In contrast to previous findings where echo chambers centered on a binding international commitment to emission reductions, we find that the pre-existing echo chambers have almost completely disappeared and new structures have formed around one of the main components of the Obama Administration’s national climate policy: the Clean Power Plan. These results provide empirical evidence that science communication and policymaking at the elite level shift in relation to the policy instruments under consideration. [ABSTRACT FROM AUTHOR]

Accurate reporting and forecasting of PM2.5 concentration are important for improving public health. In this paper, we propose a partial differential equation (PDE) model, specially, a linear diffusive equation, to describe the spatial-temporal characteristics of PM2.5 in order to make short-term prediction. We analyze the temporal and spatial patterns of a real dataset from China’s National Environmental Monitoring and validate the PDE-based model in terms of predicting the PM2.5 concentration of the next day by the former days’ history data. Our experiment results show that the PDE model is able to characterize and predict the process of PM2.5 transport. For example, for 300 continuous days of 2016, the average prediction accuracy of the PDE model over all city-regions is 93% or 83% based on different accuracy definitions. To our knowledge, this is the first attempt to use PDE-based model to study PM2.5 prediction in both temporal and spatial dimensions. [ABSTRACT FROM AUTHOR]

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

Background: There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species’ responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Objectives: Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. Data sources and study eligibility criteria: We systematically reviewed SDM studies published from 2003–2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. Synthesis methods and limitations: We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. Results: There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. Conclusions: We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis. [ABSTRACT FROM AUTHOR]

The selection of seismic attributes is a key process in reservoir prediction because the prediction accuracy relies on the reliability and credibility of the seismic attributes. However, effective selection method for useful seismic attributes is still a challenge. This paper presents a novel selection method of seismic attributes for reservoir prediction based on the gray relational degree (GRD) and support vector machine (SVM). The proposed method has a two-hierarchical structure. In the first hierarchy, the primary selection of seismic attributes is achieved by calculating the GRD between seismic attributes and reservoir parameters, and the GRD between the seismic attributes. The principle of the primary selection is that these seismic attributes with higher GRD to the reservoir parameters will have smaller GRD between themselves as compared to those with lower GRD to the reservoir parameters. Then the SVM is employed in the second hierarchy to perform an interactive error verification using training samples for the purpose of determining the final seismic attributes. A real-world case study was conducted to evaluate the proposed GRD-SVM method. Reliable seismic attributes were selected to predict the coalbed methane (CBM) content in southern Qinshui basin, China. In the analysis, the instantaneous amplitude, instantaneous bandwidth, instantaneous frequency, and minimum negative curvature were selected, and the predicted CBM content was fundamentally consistent with the measured CBM content. This real-world case study demonstrates that the proposed method is able to effectively select seismic attributes, and improve the prediction accuracy. Thus, the proposed GRD-SVM method can be used for the selection of seismic attributes in practice. [ABSTRACT FROM AUTHOR]

This paper introduces an optimal sizing algorithm for a hybrid renewable energy system using smart grid load management application based on the available generation. This algorithm aims to maximize the system energy production and meet the load demand with minimum cost and highest reliability. This system is formed by photovoltaic array, wind turbines, storage batteries, and diesel generator as a backup source of energy. Demand profile shaping as one of the smart grid applications is introduced in this paper using load shifting-based load priority. Particle swarm optimization is used in this algorithm to determine the optimum size of the system components. The results obtained from this algorithm are compared with those from the iterative optimization technique to assess the adequacy of the proposed algorithm. The study in this paper is performed in some of the remote areas in Saudi Arabia and can be expanded to any similar regions around the world. Numerous valuable results are extracted from this study that could help researchers and decision makers. [ABSTRACT FROM AUTHOR]

The body of science evaluating the potential impacts of unconventional natural gas development (UNGD) has grown significantly in recent years, although many data gaps remain. Still, a broad empirical understanding of the impacts is beginning to emerge amidst a swell of research. The present categorical assessment provides an overview of the peer-reviewed scientific literature from 2009–2015 as it relates to the potential impacts of UNGD on public health, water quality, and air quality. We have categorized all available original research during this time period in an attempt to understand the weight and direction of the scientific literature. Our results indicate that at least 685 papers have been published in peer-reviewed scientific journals that are relevant to assessing the impacts of UNGD. 84% of public health studies contain findings that indicate public health hazards, elevated risks, or adverse health outcomes; 69% of water quality studies contain findings that indicate potential, positive association, or actual incidence of water contamination; and 87% of air quality studies contain findings that indicate elevated air pollutant emissions and/or atmospheric concentrations. This paper demonstrates that the weight of the findings in the scientific literature indicates hazards and elevated risks to human health as well as possible adverse health outcomes associated with UNGD. There are limitations to this type of assessment and it is only intended to provide a snapshot of the scientific knowledge based on the available literature. However, this work can be used to identify themes that lie in or across studies, to prioritize future research, and to provide an empirical foundation for policy decisions. [ABSTRACT FROM AUTHOR]

The global tsunami and atmospheric waves that followed the eruption of the Tongan volcano Hunga Tonga–Hunga Ha’apai were observed around the world. Analysing the data could reshape our understanding of such events.Volcanic eruption caused a meteotsunami. [ABSTRACT FROM AUTHOR]

This paper brings advances in weather data collection and modeling, and developments in socioeconomic climate microsimulations to bear on the analysis of the implications of climate change (CC) in the design of public policies to combat food insecurity. It uses new downscaled predictions of future climate in 2050, derived from three Earth System Models calibrated with a new historical weather station dataset for Peru. This climate data is used in a three-stage socioeconomic microsimulation model that includes climate risk, and deals with the endogeneity of incomes and simultaneity of expected food consumption and its variability. We estimate the impact of CC on agricultural yields, and find results consistent and fully bounded within what the global simulations literature has found, with yields falling up to 13% in some regions. However, we show that these drops (and increases) in yields translate to much smaller changes in food consumption, and also surprisingly, to very minor impacts on vulnerability to food insecurity. The document explores what explains this surprising result, showing that in addition to characteristics that are specific to Peru, there are household and market mediating mechanisms that are available in all countries, which explain how changes in yields, and corresponding farm incomes have a reduced impact in vulnerability to food insecurity. Finally, in light of these findings, we explore which policies might have greater impact in reducing food insecurity in contexts of hunger prevalence. [ABSTRACT FROM AUTHOR]

Regulating ecosystem services provided by urban forests are of great importance for the quality of life among city dwellers. To reach a maximum contribution to well-being in cities, the urban regulating ecosystem services (URES) must match with the demands in terms of space and time. If we understand the matches or mismatches between the current urban dwellers’ desired quality conditions (demand) and the supply of URES by urban forests (UF) in the cities, this will facilitate integrating the concepts of ecosystem services in urban planning and management, but such an assessment has suffered from major knowledge limitations. Since it is complex and problematic to identify the direct demands for URES and the spatiotemporal patterns therein, improving the demand indicators can help to determine the actual requirements. In this paper, a methodological approach based on indicators is presented and demonstrated for two important URES: air quality improvement and global climate change mitigation provided by urban trees and shrubs. Four air quality standards and greenhouse gas reduction targets were used and compared to supplies of the URES in Tabriz, Iran. Our results show that the mean contribution of the URES supply to air quality standards and greenhouse gas reduction targets is modest. Hence, in Tabriz, there is a strong mismatch between demand and supply. Mismatches at the city scale will have to be reduced by both a reduction in pollutant emissions and an increased provisioning of URES supply through urban greenery. The presented assessment approach and the results for Tabriz make it explicit how different the demands and supplies of the two studied URES are, and we expect similar mismatches in many other cities. Therefore, our approach, relatively simple but still realistic and easy-to-apply, can raise awareness about, and the utility of, the ecosystem services concepts for urban planning and policymaking. [ABSTRACT FROM AUTHOR]

Artificial smokes focusing on macroscopic or fluid properties of smoke have been available for a long time. This paper presents a simple method to generate fully customizable smoke-like atmospheres at microscopic scale (i.e. considering their constituent particles as discrete elements) using a different approach. Synthetic, reproducible media can be generated combining monodisperse microspheres with known geometrical and optical properties conveniently parameterized. The method is presented as a proof-of-concept, highlighting the design decisions along with their implications. Practical issues such as aerosol nebulization, particle carrier selection or the features of the medium chamber where the smoke-like atmosphere is to be tested are analyzed. A comparison between methanol and ethanol as carriers for polystyrene microsphere nebulization is also made. The method could be the seed for the obtention of standard reference media for calibration or standardized characterization of not only smoke detectors and exhaust smoke sensors but also other instruments relying on optical properties of dispersive media (dust in PV panels, public lighting, etc.). [ABSTRACT FROM AUTHOR]

Plant cell walls development is an integrated process during which several components are deposited successively. In the cell walls in grass, the accessibility of structural polysaccharides is limited by the cell walls structure and composition mainly as a result of phenolic compounds. Here, we studied the patterns of cell walls establishment in the internode supporting the ear in three distinct maize genotypes. The developmental patterns observed in the internode cell walls in terms of its composition are reported with an emphasis on lignification, p-coumaroylation and feruloylation. We combined biochemical and histological approaches and revealed that internode cell walls development in maize before flowering is characterized by the rapid deposition of secondary cell walls components and robust lignification in both the pith and the rind. After flowering and until silage maturity, the slow deposition of secondary walls components occurs in the cortical region, and the deposited lignins are rich in β-O-4 bonds and are highly p-coumaroylated. We conclude the paper by proposing a revised spatiotemporal model based on that proposed by Terashima et al. (1993) for cell walls development in grass. [ABSTRACT FROM AUTHOR]

When the unmanned aerial vehicle (UAV) is used for aerial spraying, the downwash airflow generated by the UAV rotor will interact with the crop canopy and form a conical vortex shape in the crop plant. The size of the vortex will directly affect the outcome of the spraying operation. Six one-way spraying were performed by the UAV in a rice field with different but random flying altitude and velocities within the optimal operational range to form different vortex patterns. The spraying reagent was clear water, which was collected by water sensitive paper (WSP), and then the WSP was analyzed to study the droplets deposition effects in different vortex states. The results showed that the formation of the vortex significantly influenced the droplet deposition. To be specific, the droplet deposition amount in the obvious-vortex (OV) state was about 1.5 times of that in the small-scale (SV) vortex state, and 7 times of that in the non-vortex (NV) state. In the OV state, the droplets mainly deposited directly below and on both sides of the route. The deposition amount, coverage rate and droplet size increased from top to bottom of the crops with the deposition amount, coverage rate, and volume median diameter (VMD) ranging 0.204–0.470 μL/cm2, 3.31%-7.41%, and 306–367μm, respectively. In the SV state, droplets mainly deposited in the vortex area directly below the route. The deposition amount in the downwind direction was bigger than that in the upwind direction. The maximum of deposition amount, coverage rate and droplet size were found in the middle layer of the crops, the range are 0.177–0.334μL/cm2, 2.71%-5.30%, 295–370μm, respectively. In the NV state, the droplet mainly performed drifting motion, and the average droplet deposition amount in the downwind non-effective region was 29.4 times of that in the upwind non-effective region and 8.7 times of the effective vortex region directly below the route. The maximum of deposition amount, coverage rate and droplet size appeared in the upper layer of the crop, the range are 0.006–0.132μL/cm2, 0.17%-1.82%, 120–309μm, respectively, and almost no droplet deposited in the middle and lower part of the crop. The coefficient of variation (CV) of the droplet deposition amount was less than 40% in the state of obvious-vortex and small-scale vortex, and the worst penetration appeared in the non-vortex amounting to 65.97%. This work offers a basis for improving the spraying performance of UAV. [ABSTRACT FROM AUTHOR]

This paper investigates how former hunter-gatherers living along the southern North Sea coast in NW Europe adapted to long-term and short-term climatic and environmental changes at the beginning of the Holocene. It is argued that contemporaneous hunter-gatherers repeatedly changed their hunting equipment in response to changing climate and environment, not just for functional reasons but mainly driven by socio-territorial considerations. Based on a Bayesian analysis of 122 critically selected radiocarbon dates a broad chronological correlation is demonstrated between rapid changes in the design and technology of stone projectiles and short but abrupt cooling events, occurring at 10.3, 9.3 and 8.2 ka cal BP. Combined with the rapid sea level rises and increased wildfires these climatic events probably impacted the lifeways of hunter-gatherers in such a way that they increasingly faced resource stress and competition, forcing them to invest in the symbolic defense of their social territories. [ABSTRACT FROM AUTHOR]

Compared with the idealized isotropic coal seam, the effectively cracking distances of deep-hole pre-splitting blasting in different directions have significant difference in the structural anisotropy of coal seam. In this paper, based on the test results of coal mechanical parameters in different coring directions, the blasting crack distances in these coring directions of coal seam are theoretically calculated and analyzed, and then a new method of blasthole layout in coal seam is designed and the blasting crack effect is investigated according to the test data of gas drainage. The research results show that both compressive strength and tensile strength of the direction of perpendicular to bedding are larger than that in other directions, especially parallel to bedding. The blasting crack distances of calculation results are in great agreement with that of underground in-situ measurement, so the blasting crack zone caused by the differences of mechanical properties in different directions can be approximately treated as an ellipse. Comparing the conventional method of blasthole layout, the blasting crack effect with new method has greatly enhanced the methane concentration and gas drainage quantity. Pure methane quantities with the new method and conventional method are about 2.8 times and 1.67 times as large as that before blasting, and pure methane quantity with the new method is about 1.46 times that with the conventional method. Therefore, considering the anisotropic characteristics of coal seams, the reasonable blasthole layout plays an important role for enhancing gas drainage in low permeability and outburst working face. [ABSTRACT FROM AUTHOR]

Artificial surfaces are routinely used instead of leaves to enable a reductionist approach in phyllosphere microbiology, the study of microorganisms residing on plant leaf surfaces. Commonly used artificial surfaces include, flat surfaces, such as metal and nutrient agar, and microstructured surfaces, such as isolate leaf cuticles or reconstituted leaf waxes. However, interest in replica leaf surfaces as an artificial surface is growing, as replica surfaces provide an improved representation of the complex topography of leaf surfaces. To date, leaf surfaces have predominantly been replicated for their superhydrophobic properties. In contrast, in this paper we investigated the potential of agarose, the elastomer polydimethylsiloxane (PDMS), and gelatin as replica leaf surface materials for phyllosphere microbiology studies. Using a test pattern of pillars, we investigated the ability to replicate microstructures into the materials, as well as the degradation characteristics of the materials in environmental conditions. Pillars produced in PDMS were measured to be within 10% of the mold master and remained stable throughout the degradation experiments. In agarose and gelatin the pillars deviated by more than 10% and degraded considerably within 48 hours in environmental conditions. Furthermore, we investigated the surface energy of the materials, an important property of a leaf surface, which influences resource availability and microorganism attachment. We found that the surface energy and bacterial viability on PDMS was comparable to isolated Citrus × aurantium and Populus × canescens leaf cuticles. Hence indicating that PDMS is the most suitable material for replica leaf surfaces. In summary, our experiments highlight the importance of considering the inherent material properties when selecting a replica leaf surface for phyllosphere microbiology studies. As demonstrated, a PDMS replica leaf offers a control surface that can be used for investigating microbe-microbe and microbe-plant interactions in the phyllosphere, which will enable mitigation strategies against pathogens to be developed. [ABSTRACT FROM AUTHOR]

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

This paper aims to develop a novel computational technique for the detection of the transit through the anaerobic threshold. This technique uses only cardiac intervals derived from the electrocardiogram and is based on algebraic relationships between RR and QRS intervals. Electrocardiograms are measured during the load and the recovery processes. Algebraic relationships between cardiac intervals are used not only to identify the anaerobic threshold but also to characterise individual features of the person during the transit through the threshold. The ratio between carbon dioxide and oxygen in the exhaled air is used to validate the results. The algebraic relationship between cardiac intervals serves as a stand-alone indicator for both the determination of the anaerobic threshold and the characterization of the performance of the person during the load and the recovery processes. [ABSTRACT FROM AUTHOR]

Cities are major drivers of environmental change at all scales and are especially at risk from the ensuing effects, which include poor air quality, flooding and heat waves. Typically, these issues are studied on a city-by-city basis owing to the spatial complexity of built landscapes, local topography and emission patterns. However, to ensure knowledge sharing and to integrate local-scale processes with regional and global scale modelling initiatives, there is a pressing need for a world-wide database on cities that is suited for environmental studies. In this paper we present a European database that has a particular focus on characterising urbanised landscapes. It has been derived using tools and techniques developed as part of the World Urban Database and Access Portal Tools (WUDAPT) project, which has the goal of acquiring and disseminating climate-relevant information on cities worldwide. The European map is the first major step toward creating a global database on cities that can be integrated with existing topographic and natural land-cover databases to support modelling initiatives. [ABSTRACT FROM AUTHOR]

The production of concrete for construction purposes is a major source of anthropogenic CO2 emissions. One promising avenue towards a more sustainable construction industry is to make use of naturally occurring mineral-microbe interactions, such as microbial-induced carbonate precipitation (MICP), to produce solid materials. In this paper, we present a new process where calcium carbonate in the form of powdered limestone is transformed to a binder material (termed BioZEment) through microbial dissolution and recrystallization. For the dissolution step, a suitable bacterial strain, closely related to Bacillus pumilus, was isolated from soil near a limestone quarry. We show that this strain produces organic acids from glucose, inducing the dissolution of calcium carbonate in an aqueous slurry of powdered limestone. In the second step, the dissolved limestone solution is used as the calcium source for MICP in sand packed syringe moulds. The amounts of acid produced and calcium carbonate dissolved are shown to depend on the amount of available oxygen as well as the degree of mixing. Precipitation is induced through the pH increase caused by the hydrolysis of urea, mediated by the enzyme urease, which is produced in situ by the bacterium Sporosarcina pasteurii DSM33. The degree of successful consolidation of sand by BioZEment was found to depend on both the amount of urea and the amount of glucose available in the dissolution reaction. [ABSTRACT FROM AUTHOR]