Search

A well-resolved database of a small-scale heptane pool fire is analyzed to assess the assumptions of flamelet models in fire simulations. The pool fire database features well-resolved turbulence fields, finite-rate chemistry for heptane using a 33-species skeletal mechanism, and a coupled Monte Carlo ray-tracing radiation solver with a line-by-line spectral model. A budget analysis of the flamelet equation is performed by transforming temperature and species to the mixture fraction space and extracting instantaneous flamelet solutions along flame-aligned directions. Five flame-aligned budget terms and one unsteady term are identified through transformation of the temperature equation. Three conditions are examined, including an adiabatic case, a case involving only gas radiation, and a case involving both gas and soot radiation. The budget analysis shows that preferential diffusion is non-negligible near the base of the pool. Radiation is found to be appreciable in the transition region of the fire, resulting in a reduction of flame temperature by as much as 270 K due to radiative heat losses. The curvature of the flame surface is found to have a minor impact on the temperature dynamics near the flame front. The extracted flame structures deviate from those predicted from a steady-state adiabatic laminar flamelet model, particularly in the profiles of CO, CO 2 , and OH. A time scale analysis is performed, indicating that steady state assumptions for chemical species are reasonable for this flame, although radiation is much slower compared to chemistry and requires consideration to correctly capture the temperature evolution. The source terms from radiative absorption and emission show pronounced non-proportionality between the two, where absorption can exceed emission, thereby serving as a heating source for the fuel and oxidizer streams. The controlling factors for radiative absorption are analyzed, based on which a non-local model is proposed to approximate absorption in pool fires. A priori assessment of this model shows good agreement with the pool fire database, demonstrating the feasibility of enhancing the flamelet formulation to account for radiative emission and absorption effects.

The fractal geometry, anisotropy, discontinuity, and non-Darcy flow of tight reservoirs exert a significant effect on well production performance. In this study, the reservoir fractal geometry is represented by exponential functions on the basis of microseismic data, while the discontinuity of the fractures is presented as a nonequilibrium effect. The impact of the nonequilibrium effect and the low velocity non-Darcy flow on the temporal scale of the wellbore pressure is predicted herein. Results showed that the time scale analysis accurately simulates gas flow in a tight reservoir. The wellbore pressure gradually increases, whereas the pressure in the matrix lags when the nonequilibrium effect is considered. The wellbore pressure is affected in the early period by the nonequilibrium effect. However, at the later stage, the pressure in the matrix is mainly affected by the non-Darcy flow. When the non-Darcy flow is dominant, the pores without gas flowing through are better presented.

The charging and discharging times are some of the very important factors for the design of highly efficient hydrogen storage chambers with metal hydrides or activated carbon. However, experimental research or numerical simulations have to be performed to determine these factors, which could be time consuming and expensive. In this study, the possible existence of a general time scale for hydrogen storage chambers with large amount of sorption heat is discussed. By scale analysis of the energy equation and rapid heat generation and slow cooling assumption, it is found that there likely exists a general time scale for hydrogen charging and discharging. The time scale is determined as the thermal diffusion time scale of the porous storage bed. Its validity is demonstrated by comparing with the available metal hydrides and activated carbon data in previous literature. Furthermore, a minimum bed thickness scale for a specific charging time is also derived according to the developed general time scale. The proposed temporal and spatial scales may serve as a low cost and efficient tool for the design and optimization of hydrogen storage devices with metal hydrides or activated carbon.

Groundwater discharge generates streamflow and influences stream thermal regimes. However, the water quality and thermal buffering capacity of groundwater depends on the aquifer source-depth. Here, we pair multi-year air and stream temperature signals to categorize 1729 sites across the continental United States as having major dam influence, shallow or deep groundwater signatures, or lack of pronounced groundwater (atmospheric) signatures. Approximately 40% of non-dam stream sites have substantial groundwater contributions as indicated by characteristic paired air and stream temperature signal metrics. Streams with shallow groundwater signatures account for half of all groundwater signature sites and show reduced baseflow and a higher proportion of warming trends compared to sites with deep groundwater signatures. These findings align with theory that shallow groundwater is more vulnerable to temperature increase and depletion. Streams with atmospheric signatures tend to drain watersheds with low slope and greater human disturbance, indicating reduced stream-groundwater connectivity in populated valley settings., Groundwater discharge generates streamflow and influences stream thermal regimes. Classifying more than 1700 streams across the US by using an empirically-based approach the study shows that the vulnerability of streams to stressors depends on the aquifer source-depth of groundwater discharge

The occurrence of flow pattern can be predicted based on constructal law. Scale analysis is a method for deriving the essential information based on the basic principles of fluid flow and heat transfer. It provides order-of-magnitudes but also the form of the functions that describe the quantities understudy. In flow systems, patterns (configuration, design, architecture) arise from competition between competing trends, at least two modes of transport or locomotion: slow (diffusion, walk, etc.) and fast (streams, run, etc.). Optimal patterns mean the best flow access and the best balance between these trends. The study presented here follows from the scale analysis together with constructal and, is illustrated by examples from simple water heating to human locomotion.

This study characterizes potential soil lead (Pb) exposure risk at the household scale in Greensboro, North Carolina, using an innovative combination of field sampling, statistical analysis, and machine-learning techniques. Soil samples were collected at the dripline, yard, and street side at 462 households (total sample size = 2310). Samples were analyzed for Pb and then combined with publicly available data on potential historic Pb sources, soil properties, and household and neighborhood demographic characteristics. This curated data set was then analyzed with statistical and machine-learning techniques to identify the drivers of potential soil Pb exposure risks and to build predictive models. Among all samples, 43% exceeded current guidelines for Pb in residential gardens. There were significant racial disparities in potential soil Pb exposure risk; soil Pb at the dripline increased by 19% for every 25% increase in the neighborhood population identifying as Black. A machine-learned Bayesian network model was able to classify residential parcels by risk of exceeding residential gardening standards with excellent reproducibility in cross validation. These findings underscore the need for targeted outreach programs to prevent Pb exposure in residential areas and demonstrate an approach for prioritizing outreach locations.

While shifting electricity production to renewable sources is of critical importance in addressing global climate change, the costs of such development are often felt locally. This study explores w...

In the last decades, climatic changes in Mediterranean regions and frequent events of water resource scarcity in supply systems have required addressing the problem of increasing the inflows in storage reservoirs by connecting them to diversion dams. Usually, diversion dams do not have a large storage volume; consequently, these works are not able to regulate monthly flow, and they can divert to reservoirs only a part of river flow. In this field of research, this study aims to provide a procedure to evaluate water volumes withdrawn from diversion dams considering river flows and transfer flows. The procedure is founded by analysing 36 gauging stations in Sardinia (Italy), where a unique regional flow duration curve (FDC) can be defined. The effectiveness of regional evaluation of volume withdrawn, based on a monthly time scale analysis, has been investigated. The methodology allows finding optimal values of regional FDC parameters in order to better evaluate water resources withdrawn from diversion dams with respect to the current estimation used in the Sardinia Region Water Plan (SRWP). The current SRWP (RAS 2006) uses a fixed and extremely precautionary value of the FDC that underestimates withdrawal volumes. Moreover, a correlation analysis has been carried out in order to extend the evaluation of optimal FDC parameters for ungauged basins that allows to improve application of this procedure. Obtained results could allow to update the SRWP as highlighted in the final application to a real water system.

This study investigated the multifractal characteristics of fine resolution (0.25ox0.25°) daily gridded rainfall fields of India over the period 1901–2013 to examine their spatiotemporal variability. The scaling characterization using Multifractal Detrended Fluctuation Analysis (MFDFA) detected short-term persistency and strong multifractality in the majority of rainfall (over 81%) of the grid points. A detailed exploration on the spatial variability of multifractal properties such as Hurst exponent, spectral width, asymmetry index, Holder exponent are also performed for six rainfall homogenous regions and 34 meteorological subdivisions in India. The results showed that the highest persistence and complexity is noted in the mountainous terrains of northern and northeastern India. The sub-divisional scale analysis showed that the variability of persistence and complexity is the highest in Kerala and lowest at Vidarbha. Further, the evaluation of multifractal properties of rainfall series of pre- and post-1976/77 Pacific climate shift showed an increase in strength of multifractality in 62% grids after the shift. Changes in the status of persistence with respect to 1976/77 is the highest at Uttaranchal subdivision and changes from positive to negative asymmetry was the highest at northwestern (NW) region. Grid points of Peninsular India exhibited least reduction in complexity, multifractality and persistence in the post-1977 period when compared to pre-1977 period.

Currently, there are a large number of diverse climate datasets in existence, which differ, sometimes greatly, in terms of their data sources, quality control schemes, estimation procedures, and spatial and temporal resolutions. Choosing an appropriate dataset for a given application is therefore not a simple task. This study compares nine global/near-global precipitation datasets and three global temperature datasets over 3138 North American catchments. The chosen datasets all meet the minimum requirement of having at least 30 years of available data, so they could all potentially be used as reference datasets for climate change impact studies. The precipitation datasets include two gauged-only products (GPCC and CPC-Unified), two satellite products corrected using ground-based observations (CHIRPS V2.0 and PERSIANN-CDR V1R1), four reanalysis products (NCEP CFSR, JRA55, ERA-Interim, and ERA5), and one merged product (MSWEP V1.2). The temperature datasets include one gauge-based (CPC-Unified) and two reanalysis (ERA-Interim and ERA5) products. High-resolution gauge-based gridded precipitation and temperature datasets were combined as the reference dataset for this intercomparison study. To assess dataset performance, all combinations were used as inputs to a lumped hydrological model. The results showed that all temperature datasets performed similarly, albeit with the CPC performance being systematically inferior to that of the other three. Significant differences in performance were, however, observed between the precipitation datasets. The MSWEP dataset performed best, followed by the gauge-based, reanalysis, and satellite datasets categories. Results also showed that gauge-based datasets should be preferred in regions with good weather network density, but CHIRPS and ERA5 would be good alternatives in data-sparse regions.

This paper presents novel multi-scale modeling and failure analysis of hybrid carbon fiber reinforced polymer (CFRP) composites enhanced by zinc oxide (ZnO) nanowires. Vertically aligned ZnO nanowi...

Context Selective logging has been commonly mapped using binary maps, representing logged and unlogged forests. However, binary maps may fall short regarding the optimum representation of this type of disturbance, as tree harvest in tropical forests can be highly heterogeneous. Objectives The objective of this study is to map forest disturbance intensities in areas of selective logging located in the Brazilian Amazon. Methods Selective logging activities were mapped in ten forest management units using Sentinel-2 data at 10 m resolution. A spatial pattern analysis was applied to the logging map, using a moving window approach with different window sizes. Two landscape metrics were used to derive a forest disturbance intensity map. This map was then compared with actual disturbances using field data and a post-harvest forest recovery analysis. Results Disturbed areas were grouped into five distinct disturbance intensity classes, from very low to very high. Classes high and very high were found to be related to log landings and large felling gaps, while very low intensities were mainly related to isolated disturbance types. The post-harvest forest recovery analysis showed that the five classes can be clearly distinguished from one another, with the clearest differences in the year of logging and one year after it. Conclusions The approach described represents an important step towards a better mapping of selectively logged areas, when compared to the use of binary maps. The disturbance intensity classes could be used as indicators for forest monitoring as well as for further evaluation of areas under forest management.

The present study examines the spatial and temporal changes in extreme rainfall events (EREs) across the Godavari river basin to develop adaptation strategies for vulnerable regions by understanding opportunities and risks. Indices such as consecutive dry and wet days, daily intensity, one-day highest precipitation, days with rainfall > 10 mm and 20 mm have been computed over the Godavari basin for the time period 1901–2015, and changes are compared between the two time periods 1901–1976 and 1977–2015. This study examines long-term trends on monthly and seasonal scales and climatological characteristics of EREs to understand the observed spatiotemporal changes in EREs. Analysis of EREs in the monsoon months further indicates significant trends over both traditionally “high-rainfall regions” (Humid) and “low-rainfall regions” (semiarid). In low-rainfall region, an increase in mean and coefficient of variability of annual rainfall has been identified during 1977–2015 as compared to pre-1977 period. It is also found that the month of September experienced statistically significant increase in frequency and intensity of all wet extreme rain indices during the period 1977–2015. Extremes in high- and low-rainfall regions show significant increase during 1977–2015 as compared to 1901–1976. Century scale analysis of extreme events with reference to regional level changes would help in looking at the grass root reality for the estimation of water budget as well as for developing region-specific adaptation measures and crop contingency plans. These findings would feed into state action plan for climate change to take appropriate measures to combat changing and rapidly occurring EREs in different climate zones of Godavari basin.

Lake water levels fluctuate at time scales ranging from minutes to many years. While extensive research has been devoted to seasonal and multiannual time scales, we examined water level changes at ...

The effect of tank orientation on heat transfer of a typical roof-top water storage tank is examined in this paper. The theoretical study is based on scale analysis of the governing equation that is used to evaluate the comfort time of both vertical and horizontal water storage tanks. The scale analysis is validated numerically by solving the resulting energy equation using an explicit numerical technique based on two programs written in the MATLAB software for each tank orientation. Different water tank capacities are examined for both horizontal and vertical orientations. Data for commercially available water storage tanks are used in the calculations. Three parameters play an important role in the evaluation process of the comfort time ratio. These are (1) the tank capacity, (2) the tank characteristic length, and (3) the tank surface area. It is shown that the heat transfer coefficient associated with water inside the tank is much higher than the outside air heat transfer coefficient around the body of the tank. The simplicity of the proposed method will allow the user in quick decision making as to which water storage tank orientation would provide longer comfort time. For example, in a vertical tank with a capacity of 1000 L, the water will heat up slowly and from 11:00 AM onwards, it will approximately need 3.7 h to reach the temperature of the environment. On the other hand, in a horizontal tank of the same capacity, the water will heat up much quickly and it will take only about 0.9 h for water to reach the surrounding environment temperature. Eventually, this work will contribute to less water evaporation from these tanks, thus saving water that is essential to water starved desert climates such as in the Kingdom of Saudi Arabia.

International audience; For parasites, finding their hosts in vast and heterogeneous environments is a task that can be complex. Some parasite species rely on elaborate strategies to increase encounter rate with their hosts (e.g. behavioural modification of host), but others do not. For these parasites, a key issue is to reveal the processes that enable them to successfully find their hosts and complete their life cycles. Here, we tested the hypothesis that infective larvae of the freshwater ectoparasite Tracheliastes polycolpus are not homogeneously distributed along the river and preferentially occur in very specific microhabitats that maximize encounter rate, and hence infection rate, with their host fish. To do this, we combined an in situ experiment (caging) with an empirical survey carried out on the same sites to identify potential 'hotspots' of infection at the microgeographic scale and their environmental characteristics. Experimental and empirical results demonstrated that infections were not evenly distributed among microhabitats, and that infections were spatially aggregated in hotspots at a very fine spatial grain. We further found that certain combinations of environmental variables were consistently and nonlinearly associated with higher infection rate for both caged and wild-caught fish. Microhabitats characterized by very low or high stream velocities, associated with medium or very small substrate, respectively, and a deep water column were strongly and repeatedly associated with higher infection rates. These microhabitats could concentrate parasites and/or promote physical contact with the hosts. We conclude that the characteristics of some microhabitats could facilitate contact between hosts and parasites and explain how some parasites manage to find their hosts in complex environments.

The spatial structures of China’s Major Function Zoning are important constraining indicators in all types of spatial planning and key parameters for accurately downscaling major functions. Taking the proportion of urbanization zones, agricultural development zones and ecological security zones as the basic parameter, this paper explores the spatial structures of major function zoning at different scales using spatial statistics, spatial modeling and landscape metrics methods. The results show: First, major function zones have spatial gradient structures, which are prominently represented by latitudinal and longitudinal gradients, a coastal distance gradient, and an eastern-central-western gradient. Second, the pole-axis system structure and core-periphery structure exist at provincial scales. The general principle of the pole-axis structure is that as one moves along the distance axis, the proportion of urbanization zones decreases and the proportion of ecological security zones increases. This also means that the proportion of different function zones has a ring-shaped spatial differentiation principle with distance from the core. Third, there is a spatial mosaic structure at the city and county scale. This spatial mosaic structure has features of both spatial heterogeneity, such as agglomeration and dispersion, as well as of mutual, adjacent topological correlation and spatial proximity. The results of this study contribute to scientific knowledge on major function zones and the principles of spatial organization, and it acts as an important reference for China’s integrated geographical zoning.

Transient free convection from a heated surface immersed in a cold ambient is investigated using scale analysis. The heated plate is our model for the heat exchangers in a natural draft dry cooling tower. The scale analysis results led to a timescale for initiation of the plumes. Furthermore, a model is developed to study the near-wall free convection which allows the prediction of plume extension and merging process. Both the normal and lateral components of the fluid velocity are expressed as functions of the Prandtl and Rayleigh number. Expressions are proposed to predict the plume size and spacing in the lateral direction. Results are then successfully compared with independent experimental data available in the literature.

Existing studies regarding the impact of wind turbines on birds typically utilize data collected from a few wind facilities to estimate the impact at national level. This study examines the impact of wind turbines on breeding bird abundance by using a fine scale, spatial longitudinal dataset for 1,670 wind turbines and 86 bird observation routes located in 36 states in the United States over 2008–2014. We find that the establishment of one additional wind turbine, on average, leads to disappearance of about three breeding birds. The aggregate effect of the U.S. on-shore wind turbines on breeding bird count is 151,630, a magnitude at the lower end of existing estimates that range between 20,000 and 573,000. We also find that turbine size is a critical determinant of the magnitude of this impact, with turbine tower height positively, but blade length negatively, associated with aggregate breeding bird abundance. Grassland breeding bird abundance increases by up to 0.81 following the establishment of an additional wind turbine, although it is insensitive to tower height or blade length. Our findings provide important implications for policies related to wind facility siting and wind turbine development that can enhance the sustainability of wind energy.

A novel structure of woven composite pressure pipes (WCPP) is designed in this paper. Based on the overall geometry structure of woven preform, the representative volume unit (RVU) is estab...

In this paper, a theoretical and numerical study of melting process driven by natural convection inside a porous square cavity differentially heated in the presence of a magnetic field is carried out. The theoretical study based on the scale analysis method made it possible to determine correlations giving the Nusselt number and the average melting front as function of the different parameters that control melting process. A numerical study by lattice Boltzmann method is also performed to verify the accuracy of the proposed correlations.

A contactless, non-destructive approach to measure the geometrical parameters of the growth ridge, based on surface topography, is presented and established. It allows a systematic, large scale analysis of growth ridges of single crystals of almost any type. Here, it is applied to Czochralski-grown silicon crystals. Based on the measurement results, Voronkov’s theory of the shape of the growth ridge is verified. This theory is used to calculate the temperature gradient at the growth ridge from the geometrical parameters. The presented method gives an easy, direct experimental access to the thermal conditions, both qualitative and quantitative, at the solid-liquid interface during the growth process.

Spatial variability of available P, K, Ca and Mg, sampled along two short transects and determined by two different extraction methods, was characterized using multifractal and joint multifractal analysis. Sixty-six soil samples were collected every 0.8 m, both in a vineyard and in a polyculture field. Available nutrients were extracted with an ion exchange resin and the Mehlich 3 solution. Shape and width of singularity, f(α) versus α, and generalized dimension, Dq, spectra, showed that spatial distributions obtained by the two tests behaved as quasi-monofractals in the vineyard, but were fitted with multifractal models under polyculture. Joint multifractal analysis demonstrated positive correlations between the scaling indices of P, K, Ca and Mg, extracted by resin and Mehlich 3, which were stronger under polyculture. Pearson correlations between available nutrients determined by two tests at the single scale ranged from R2 = 0.54 to 0.95 and were weaker than those of the respective scaling indices across the range of scales studied, which varied from R2 = 0.63 to 0.97. The joint multifractal approach showed that single scale analysis may be insufficient to compare relationships between available nutrient tests. Moreover, multifractal analysis may be useful to upscaling/downscaling nutrient availability.

In this study, we investigated the scale sizes of equatorial plasma irregularities (EPIs) using measurements from the Swarm satellites during its early mission and final constellation phases. We found that with longitudinal separation between Swarm satellites larger than 0.4°, no significant correlation was found any more. This result suggests that EPI structures include plasma density scale sizes less than 44 km in the zonal direction. During the Swarm earlier mission phase, clearly better EPI correlations are obtained in the northern hemisphere, implying more fragmented irregularities in the southern hemisphere where the ambient magnetic field is low. The previously reported inverted-C shell structure of EPIs is generally confirmed by the Swarm observations in the northern hemisphere, but with various tilt angles. From the Swarm spacecrafts with zonal separations of about 150 km, we conclude that larger zonal scale sizes of irregularities exist during the early evening hours (around 1900 LT)., Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe; 1112

Pockets of open cells sometimes form within closed‐cell stratocumulus cloud decks but little is known about their statistical properties or prevalence. A convolutional neural network was used to detect occurrences of pockets of open cells (POCs). Trained on a small hand‐logged dataset and applied to 13 years of satellite imagery the neural network is able to classify 8,491 POCs. This extensive database allows the first robust analysis of the spatial and temporal prevalence of these phenomena, as well as a detailed analysis of their micro‐physical properties. We find a large (30%) increase in cloud effective radius inside POCs as compared to their surroundings and similarly large (20%) decrease in cloud fraction. This also allows their global radiative effect to be determined. Using simple radiative approximations we find that the instantaneous global annual mean top‐of‐atmosphere perturbation by all POCs is only 0.01 W/m2.

International audience; A time scale analysis of the homogeneous flame inhibition problem is carried out to identify the main param- eters controlling the gas phase chemical interaction of the alkali metal inhibitors with the flame chemistry. First, kinetic sub-models for the interaction of alkali metals with the flame are analyzed to show that a simplified 2-step inhibition cycle can capture the essential features of this interaction. Second, it is shown that this cycle is auto-catalytic, which explains the high efficiency of alkali metals in inhibiting flames even at low concentrations. Third, the time scales associated to this inhibition cycle are linked to the free flame termina- tion time scale via a non-dimensional parameter characterizing the efficiency of an inhibitor at promoting radical scavenging. It is shown that this parameter accounts for the main trends observed in the literature and can also be used to provide estimates for the chemical flame suppression limit.

Accurate (spatio-temporal) estimation of the crop yield relation to climate variables is essential in the densely populated Indus, Ganges, and Brahmaputra (IGB) river basins of South Asia for devising appropriate adaptation strategies to ensure regional food and water security. This study examines wheat (Triticum aestivum) and rice (Oryza sativa) crop yields&rsquo, sensitivity to primary climate variables (i.e., temperature and precipitation) and related changes in irrigation water demand at different spatial (i.e., province/state, districts and grid cell) and temporal (i.e., seasonal and crop growth phase) scales. To estimate the climate driven variations in crop yields, observed and modelled data applying the Lund-Potsdam-Jena managed Land (LPJmL) model are used for six selected study sites in the IGB river basins over the period 1981&ndash, 2010. Our statistical analysis underscores the importance of impacts assessments at higher spatio-temporal scales. Our grid cell (aggregated over study sites) scale analysis shows that 27&ndash, 72% variations in wheat and 17&ndash, 55% in rice crop yields are linked with temperature variations at a significance level of p &lt, 0.001. In the absence of irrigation application, up to 39% variations in wheat and up to 75% variations in rice crop yields are associated with precipitation changes in all study sites. Whereas, observed crop yields show weak correlations with temperature at a coarser resolution, i.e., up to 4% at province and up to 31% at district scales. Crop yields also showed stronger sensitivity to climate variables at higher temporal scale (i.e., vegetative and reproductive phases) having statistically strong negative relationship with temperature and positive with precipitation during the reproductive phase. Similarly, crop phase-specific variations in climate variables have considerable impacts (i.e., quantity and timing) on irrigation water demand. For improved crop water planning, we suggest integrated climate impact assessments at higher spatio-temporal scales which can help to devise appropriate adaptation strategies for sustaining future food demand.

Intensity of urban heat island (UHII) is a key indicator to quantify the magnitude of UHI effect. Change in UHII, however, can be affected by change in urban or rural temperature, or both. Numerous studies have investigated the change of UHII, but how it relates to change in urban and rural temperature is poorly understood. Here we present a continental scale analysis on the change in UHII from 2000 to 2015 in 31 major cities in China, and further explored whether such change was caused by urban warming. We used time series analysis based on MODIS land surface temperature product (MOD11A2) in summer. We found: (1) A majority of the cities (25 out of 31) had an increasing trend in UHII from 2000 to 2015, among which 44% were significant, suggesting a significantly intensified UHI effects. (2) Intensified UHII does not necessarily mean deterioration of urban thermal environment, and vice versa. For the 25 cities with an increasing trend in UHII, 11 cities had a decreasing trend of LST in both urban and rural areas. Meanwhile, for the 6 cities with a decreasing trend in UHII, three had warming trend in both urban and rural areas. (3) The attribution of changes in UHII to that of urban and rural LST indicated that it is necessary to quantify the change of LST in both urban and rural areas to fully quantify the impact of urbanization on UHI effect.

Fire serves as a successional initiation in jack pine (Pinus banksiana) forests of North America, as jack pine reproduce using seratonous cones that open only in intense heat. Jack pine seedling resilience after fire is characterized by high numbers of mortality. The estimation of sapling survivability and density is useful for understanding dynamics of carbon sequestration, forest structure and dynamic, and supporting management of the landscape. Most studies concerning the interaction of forest disturbances occurs at moderate spatial resolution. These moderate resolution data analyses do not adequately capture the fine scale spatial variation of the landscape after fire for understanding sapling survival. Thus, high-resolution data, such as aerial photography may provide more detailed information to support decision-making. A key to the types of spatial patterns that emerge in these early years is the pre-fire stand condition. In heavily managed areas, the mosaic of forest patches may include extensive variety in disturbance conditions. In this current research we address the problem of scale in relation to understanding the influence of pre-fire condition on post-fire early recovery patterns. To do this, we combine data output from the LandTrendr algorithm in Google Earth Engine with spectral data from aerial photography collected by airplane and Unmanned Aerial System to perform a random forest classification. The result is a finer scale resolution map of forest conditions of varying sapling density.

Changes in the amount and location of cropland areas may affect the potential crop production at different spatial scales. However, most studies ignore the impacts of cropland displacement on potential crop production. In many countries, cropland protection policies mainly aim for no loss in cropland area, while there is no restriction on change of cropland location. Taking China as the study area, we analyze the impacts of cropland displacement on potential crop production at four administrative levels during the period 2000 and 2018. At the national level, we find a net decrease in cropland area of 0.81 Mha, while another 19.63 Mha was displaced. The former led to a decrease of 4.20 Mton in potential crop production, while the latter resulted in a decrease of 43.26 Mton as a result of lower quality of the newly cultivated lands. In other words, cropland displacement explains 91% of the total loss in potential crop production at the national scale. However, the contribution of cropland displacement to total change in potential crop production is increasingly smaller at provincial level, municipal level, and county levels. These findings highlight the importance of geographic location on crop production and suggest that cropland policies should consider geographic location in addition to cropland area.

Terrain analysis is an important tool for modeling environmental systems. Aiming to use the cloud-based computing capabilities of Google Earth Engine (GEE), we customized an algorithm for calculating terrain attributes, such as slope, aspect, and curvatures, for different resolution and geographical extents. The calculation method is based on geometry and elevation values estimated within a 3 × 3 spheroidal window, and it does not rely on projected elevation data. Thus, partial derivatives of terrain are calculated considering the great circle distances of reference nodes of the topographic surface. The algorithm was developed using the JavaScript programming interface of the online code editor of GEE and can be loaded as a custom package. The algorithm also provides an additional feature for making the visualization of terrain maps with a dynamic legend scale, which is useful for mapping different extents: from local to global. We compared the consistency of the proposed method with an available but limited terrain analysis tool of GEE, which resulted in a correlation of 0.89 and 0.96 for aspect and slope over a near-global scale, respectively. In addition to this, we compared the slope, aspect, horizontal, and vertical curvature of a reference site (Mount Ararat) to their equivalent attributes estimated on the System for Automated Geospatial Analysis (SAGA), which achieved a correlation between 0.96 and 0.98. The visual correspondence of TAGEE and SAGA confirms its potential for terrain analysis. The proposed algorithm can be useful for making terrain analysis scalable and adapted to customized needs, benefiting from the high-performance interface of GEE.

Icebergs are ocean hazards which require extensive monitoring. Synthetic Aperture Radar (SAR) satellites can help with this, however, SAR backscattering is strongly influenced by the properties of icebergs, together with meteorological and environmental conditions. In this work, we used five images of quad-pol ALOS-2/PALSAR-2 SAR data to analyse 1332 icebergs in five locations in west and east Greenland. We investigate the backscatter and polarimetric behaviour, by using several observables and decompositions such as the Cloude&ndash, Pottier eigenvalue/eigenvector and Yamaguchi model-based decompositions. Our results show that those icebergs can contain a variety of scattering mechanisms at L-band. However, the most common scattering mechanism for icebergs is surface scattering, with the second most dominant volume scattering (or more generally, clouds of dipoles). In some cases, we observed a double bounce dominance, but this is not as common. Interestingly, we identified that different locations (e.g., glaciers) produce icebergs with different polarimetric characteristics. We also performed a multi-scale analysis using boxcar 5 &times, 5 and 11 &times, 11 window sizes and this revealed that depending on locations (and therefore, characteristics) icebergs can be a collection of strong scatterers that are packed in a denser or less dense way. This gives hope for using quad-pol polarimetry to provide some iceberg classifications in the future.

Sandy cobble stratum is a kind of heterogeneous geological body. A further study on the safety of wall rocks and underground structure demands developing suitable analysis method to simulate tunnel excavation in such a formation. Macro-scale simulations assume the sandy cobble soil to be homogeneous in numerical models. They get more efficient computing, but have difficulties in capturing enough information about the meso-scopic fields needed. Meso-scale simulations explicitly represent the individual components of the heterogeneous internal material structure in numerical models, e.g. the shape and the spatial distribution of rocks. They achieve high accuracy, but large computational cost would be needed. To reduce the numerical effort with the precision guaranteed, a multi-scale analysis method for simulating tunnel excavation in sandy cobble strata is proposed. In this method, the numerical model is divided into two regions, involving the meso-scale region and macro-scale region. The meso-scale region is a critical sub-domain disturbed by tunnel excavation, in it, the rocks and soil are considered as separate constituents. In the macro domain, the sand gravel soil was regarded as homogeneous materials whose effective material parameters were determined using an equivalent homogenization method. Three critical issues in the multi-scale method are explored, including: (i) the determination of meso domain and macro domain, (ii) the determination of rock maximum size that can be homogenized in the meso domain and iii) the determination of effective material parameters of soil-rock mixture during the equivalent process. By comparing with simulation results predicted by macro-scale and meso-scale simulation methods, the validation of the proposed multi-scale simulation method was carried out. The result indicates that the proposed multi-scale analysis method has a high efficiency without loosening accuracy on the simulation of tunnel excavation in sandy cobble stratum.

Since the development of Jiangsu Coast was proposed as a national strategy by the Chinese Government in 2009, Jiangsu Coast has been experiencing rapid and intensive development in industry and tidal flat reclamation, which has inevitably led to the accumulation of heavy metals in its soils. A total of 239 samples (0–20 cm) were collected from topsoils of Jiangsu Coast, and their concentrations of Cd, Cr, Cu, Hg, Ni, Pb, and Zn were determined. Factorial kriging was applied to examine the scale-dependent correlations between heavy metals and to generate the spatial components at multiple scales, and multivariate stepwise regression was used to explore the relationships between the spatial multi-scale components of heavy metals and environmental factors. Linear model of co-regionalization (LMC) fitting indicated that the multi-scale variation comprised a nugget effect, an exponential structure with a range of 15 km (local scale), and a spherical structure with a range of 135 km (regional scale). The spatial correlations of seven heavy metals depended on their spatial scales, and their correlations increased with the increasing scales. Spatial variations in Cr and Ni were associated with natural geochemical sources on both local and regional scales. Parent material influenced the basic spatial variations in Cd, Cu, Pb and Zn on both local and regional scales, but human activity also contributed to the spatial variations in these four metals. The human inputs of Cd, Cu, Pb, and Zn differed on these two scales. Hg was dominated by industrial emissions and agricultural practices on both scales.

Two phase flow between two fractures commonly exists around fractured wells. Due to the fracture network, the flow velocity is extremely variable in different regions and it can be described by the temporal scale analysis. The flow velocity also changes with time during the change in water saturation, but these changes cannot be captured by the conventional temporal scale analysis. The temporal scales are obtained based on a principal equation, so it is difficult to accurately estimate the formation properties and to determine the exploitation scheme. In this study, the two phase flow model between two fractures has been proposed for the temporal scale description. The impact of reservoir heterogeneity on the temporal scales is considered in the model. Due to the tortuous flow channel shape between the fractures, the flow pressure affects the fluid flow afterwards. This is explained by the time lag effect in the model. The temporal scales are obtained by using finite element method and Laplace transformation at all time points with these considerations. Moreover, the well is soaked intermittently. The soaking duration is chosen based on temporal scales, and then discussed in terms of efficiency and recovery factor. The results showed that the water saturation profile position is reflected by the temporal scales, the flow resistance and the flow velocity are represented by their zero status response contributions, while the initial flow pressure is described by their zero input contribution. The highest zero status response contribution is different for different properties. Moreover, the time lag effect promotes the initial pressure fluctuation, and also upscales the fluid flow in tortuous channels. Finally, the soaking duration is an approximation of the time required to reduce the fracture flow pressure.

In cities, vegetation temperature is important for quantifying water use, microclimates, and water and energy fluxes, as demonstrated by urban climate models and in situ studies. Remote sensing is capable of observing land surface temperatures (LST) across a city; however, its ability to quantify vegetation canopy temperatures is limited because of LST variability resulting from urban surface heterogeneity, differences in vegetation fraction and non-vegetated material, and the coarse resolution of available thermal imagery. This study is a large-scale analysis of urban surface composition and temperature variability across the Los Angeles, USA, metropolitan area (4466 km2). Sub-pixel fractions of two plant functional types (tree and turfgrass) and four urban materials (impervious surface, commercial roof, non-photosynthetic vegetation, and soil) were quantified using hyperspectral imagery (Airborne Visible/Infrared Imaging Spectrometer). Fractional cover gradients of plant types and non-vegetated materials were developed using 1.7 million pixels, from which we modeled LST changes using simultaneously collected thermal imagery (MODIS-ASTER Airborne Simulator). Vegetation LST variability was mapped by subtracting modeled LST from observed LST and investigated relative to building density and vegetation management. Overall, LST varied significantly among plant functional types and urban material types. Across heterogeneous mixtures, LST and vegetation fraction exhibited a negative, linear relationship, with the slopes of LST change showing significant differences between trees and turfgrass. The map of vegetation LST variability had a standard deviation of 3.5 °C, indicating significant variability across Los Angeles independent of vegetation type or fractional cover. Building density was observed to affect tree and turfgrass LST differently, while a negative relationship was observed between vegetation LST and irrigation (R2 = 0.55). Our results show that an LST signal of vegetation function, distinct from that of vegetation fractional cover, can be observed and modeled at city-scales in fractional mixture analysis, indicating potential for improved understanding of urban microclimates.

A set of new approaches and techniques of non-destructive testing is described and implemented within a unified computer analysis of the patterns of multi-scale dynamic thermography. Depending on the size of the inspected area, nature, location, orientation and size of the defects, various energy sources were used for probe dynamic heating of the controlled article: air flow, focused laser beam, and point contact. The non-stationary thermal picture of the monitored area was recorded with a high resolution thermal imaging device and then analyzed using original model approaches and developed software. A set of discussed approaches allows detecting and quantitative characterizing of the defects of various types, size (from fractions to tens of millimeters) and orientation, including cracks, coating delamination or degradation, welding and glue seams defects, deposits, etc., both at the outer and inner surfaces of tubes, tanks, and reactors, etc. The developed methods provides determination of the thermophysical characteristics of the material, i.e., the thermal diffusivity coefficient with an accuracy better than ±3%.

1H NMR pulsed gradient spin echo attenuation and water density profile analysis by magnetic resonance imaging are both used to determine the mobility of water molecules confined within a porous network of compacted kaolinite clay sample (total porosity of ∼50%). These two complementary experimental procedures efficiently probe molecular diffusion within time scales varying between milliseconds and few hours, filling the gap between the time scale of diffusion dynamics measured by traditional quasi elastic neutron scattering and through-diffusion methods. Furthermore, magnetic resonance imaging is a nondestructive investigation tool that is able to assess the effect of the local structure on the macroscopic mobility of the diffusing probe.

In this paper, we clustered and analyzed landslides and investigated their underlying driving forces at two levels, country and cluster, all over Iran. Considering 12 conditioning factors, the landslides were clustered into nine relatively homogeneous regions using the Contextual Neural Gas (CNG) algorithm. Next, their underlying driving forces were ranked using the Random Forest (RF) algorithm at country and cluster levels. Our results indicate that the mechanisms for landslide occurrence varied for each cluster and that driving forces of the landslides operated differently at a country level compared to the cluster level. Moreover, slope, altitude, average annual rainfall, and distance to the main roads were identified as the most important causes of landslides within all clusters. Thus, for effective management and modelling landslides on a large scale, the variation in the functionality of effective factors should be considered.

An evidence of a changing climate is already sensed in India where there is a large diversity from region to region and from season to season. The rainfall pattern in the pre-monsoon (March–April–May) season is important as it helps in determining many crop-related activities in many parts of the country. In the present study, an attempt is made to analyze the current trends in pre-monsoon season rainfall and temperatures over 34 meteorological subdivisions in India using the India Meteorological Department observed analysis datasets of rainfall (1951–2013) and temperatures (1981–2013). The results suggest that a significant decreasing trend in the pre-monsoon rainfall at all-India level and the maximum reduction is found in the month of March. From the regional scale analysis, the south peninsular India is found to have an increasing trend, whereas a decreasing trend is observed over Jammu and Kashmir, Himachal Pradesh and northeast parts of the country. The analyses reveal an association of pre-monsoon rainfall over India with precipitation over China and temperature over the South China Sea, which may act as a precursor for the pre-monsoon rainfall that ultimately could affect the Indian summer monsoon rainfall. The increase of rainfall activity over south peninsular India is attributed to increases in the meridional temperature gradient with an increase of specific humidity. The results of the study will be useful for a long-term risk management in various sectors and would aid in adapting new technologies for a sustainable development in the changing climate scenario.

Under global climate change, relationship between vegetation dynamics and climate change is vital for vegetation conservation and restoration in fragile ecological system. However, the relationships at multiple time scales are unclear. Based on the Ensemble empirical mode decomposition method (EEMD), we revealed the spatial heterogeneity of vegetation dynamics and its relationship with climate change at multiple time scales in Southwest China during 1982–2015. Vegetation dynamics can be divided into 3-, 6-, 14-, and 32-year time scale oscillations with an increasing trend. Hereinto, the 3-year time scale and the increasing trend are dominant. In Guangxi and north of Guizhou provinces, vegetation dynamics was dominated by the long-term trend, whereas in the other areas it was dominated by the 3-year time scale. With increasing time scale, the impact of climate change became more pronounced. The relationship between vegetation dynamics and temperature in growing season was determined by elevation and vegetation type at the 3- and 6-year time scales, but only by vegetation type over the long-term trend. The relationship between vegetation dynamics and precipitation was driven by karst landform and vegetation type at the 3-year time scale, by precipitation amount at the 6-year time scale, and by karst landform and elevation over the long-term trend. Based on multivariate regression analysis with multiple time scale analysis, climate change had a good and significant interpretation on vegetation dynamics in 54.1% of the study area. Specifically, in Guangxi and north of Guizhou provinces, the impact of climate change on vegetation dynamics was greater than that of human activities. Our findings showed that multiple time scale analysis might facilitate a better understanding of the mechanisms of vegetation dynamics, and provide scientific knowledge on vegetation restoration and conservation in fragile ecosystems.

The rapidly increased earthquake rate in the central United States has been linked with wastewater injection. While the overall understanding appears clear at large scales, the interaction between injection and faulting at smaller scales within individual sequences is still not clear. For an earthquake sequence in central Oklahoma, we conduct finer scale analysis of the spatiotemporal evolution of seismicity, and pore pressure modeling. The pore pressure modeling suggests that nearby wells show much stronger correlation with earthquake sequence evolution. Detailed temporal analysis found correlation between earthquake rate, seismic moment and injection rates from wells in close proximity. However, the observed maximum magnitude (Mmax) is about one order of magnitude smaller than expected based on a theoretical relationship between Mmax and cumulative volume. This discrepancy may point toward additional parameters, such as fault size and stress, which influence Mmax. The lower Mmax is consistent with the truncated Gutenberg-Richter distribution observed from matched-filter detected catalog. Overall, the detailed observations suggest that it is possible to resolve relationships between individual disposal wells and induced earthquake sequences.

This study describes a multi-scale nuclear safety analysis method for a main steam line break accident, which focuses on the 3-dimensional approach for the coolant temperature in the reactor pressure vessel related to the re-criticality and/or pressurizer thermal shock. The direct coupled code, CUPID/MARS, where CUPID is a 3-dimensional two-phase flow analysis code and MARS is a 1-dimensional nuclear system analysis code, was validated against a main steam line break test in the ATLAS facilities, which are a 1/2 scale integral test loop for a Korean APR1400 PWR. The calculation indicates that the suggested 4-step method, which expands the previous 2-step method of steady-state and transient calculations of a 1-dimensional system code, is valid for analyzing a direct 1-D/3-D coupled safety analysis, and the 3-dimensional temperature distribution in the downcomer agrees with the measured result.

In this work, we perform a combined experimental and numerical analysis of elastomer swelling dynamics upon impingement of a train of solvent droplets. We use time scale analysis to identify spatiotemporal regimes resulting in distinct boundary conditions that occur based on relative values of the absorption timescale and the droplet train period. We recognize that when either timescale is significantly larger than the other, two cases of quasi-uniform swelling occur. In contrast, when the two timescales are comparable, a variety of temporary geometrical features due to localized swelling are observed. We show that the swelling feature and its temporal evolution depends upon geometric scaling of polymer thickness and width relative to the droplet size. Based on this scaling, we identify six cases of localized swelling and experimentally demonstrate the swelling features for two cases representing limits of thickness and width. A finite element model of local swelling is developed and validated with experimental results for these two cases. The model is subsequently used to explore the swelling behavior in the rest of the identified cases. We show that depending upon the lateral dimension of the sample, swelling can locally exhibit mushroom, mesa, and cap like shapes. These deformations are magnified during the droplet-train impact but dissipate during post-train polymer equilibration. Our results also show that while swelling shape is a function of lateral dimensions of the sample, the extent of swelling increases with the elastomer sample thickness.

Reinforcement of hydroxyapatite (HA) particles into poly- l -lactic acid (PLLA) enhances the mechanical properties of PLLA and further makes it favorable to use in biomedical applications. A micro-scale computational model for predicting the effective elastic properties of HA-PLLA composites through 3D representative volume element was studied in the presented work. The influence of volume fraction of HA particles, the orientation of HA and voids, and interpenetration of voids were discussed in detail. With perfect bonding conditions, the fracture strength increased with an increase in the volume fraction of the HA particles. The computed longitudinal modulus was in good agreement with the experimental results. This work might help in determining the optimal configuration of the HA-PLLA composites for biomedical applications.

For better control of a lean premixed combustion system, it is necessary to understand the mechanism of unsteady cellular flame. The objective of the present study is to investigate how heat loss influences the cellular instability of lean premixed flame. The lean premixed CH4/H2/air cellular flames generated on a McKenna burner were studied, and heat loss was responsible for the manifestation of unsteady cellular structure. A method of applying proper orthogonal decomposition in scale analysis is presented, which has proven helpful in characterizing the cellular flame. The multiple scale nature of unstable cellular flame was identified, and the small scales were found to act in the random movement of cells. The contribution of each scale is obtained. The energy distribution on modes indicates that the energy on higher-order modes, equivalently the contribution of smaller scales, is decreased with decreasing heat loss. Through analyzing the principal modes and temporal coefficients, heat loss is f...

Understanding the relationship and spatial distribution of multiple ecosystem services (ES) in the context of underlying socio-environmental conditions is an essential element of national ecosystem assessments. Here, we use Germany as an example to present a reproducible blueprint approach for mapping and analysing ecosystem service bundles (ESB) and associated socio-environmental gradients. We synthesized spatial indicators of eleven provisioning, regulating and cultural ES in Germany and used the method of self-organizing maps (SOM) to define and map ESBs. Likewise, we collated data from 18 covariates to delineate socio-environmental clusters (SEC). Finally, we used an overlap analysis to characterise the relationship between the spatial configuration of ESBs and co-occurring SECs. We identified and mapped eight types of ESBs that were characterized to varying degrees by provisioning, cultural and regulating/maintenance services. While ESBs dominated by provisioning ES were linked to regions with distinct environmental characteristics, cultural ESBs were associated with areas where environmental and socio-economic gradients had similar importance. Furthermore, spatial stratification of ESBs indicated hot spots where more detailed analysis is needed within national assessments. Our approach can serve as a blueprint for ESB analysis that can be reproduced in other geographical and environmental settings.