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Publications

2021
Shabtai, I. A. ; Lynch, L. M. ; Mishael, Y. G. Designing clay-polymer nanocomposite sorbents for water treatment: A review and meta-analysis of the past decade. WATER RESEARCH 2021, 188.Abstract
{{Clay-polymer nanocomposites (CPNs) have been studied for two decades as sorbents for water pollutants, but their applicability remains limited. Our aim in this review is to present the latest progress in CPN research using a meta-analysis approach and identify key steps necessary to bridge the gap between basic research and CPN application. Based on results extracted from 99 research articles on CPNs and 8 review articles on other widely studies sorbents, CPNs had higher adsorption capacities for several inorganic and organic pollutant classes (including heavy metals, oxyanions, and dyes
Hochman, D. ; Dor, M. ; Mishael, Y. G. Diverse effects of wetting and drying cycles on soil aggregation: Implications on pesticide leaching. CHEMOSPHERE 2021, 263.Abstract
The important effect of soil wetting and drying cycle (WDC) on soil structure, and the consequent effect on pollutant fate is underexplored. We thoroughly investigated the changes in soil structure and in leaching of Alion (indaziflam) and Express (tribenuron methyl), pre and post WDC, from two clayey soils and two loamy soils under different land uses (uncultivated, field crops, and orchards). Soil stability was quantified by an aggregate durability index we recently developed. WDC did not affect the stability of the sandy-loam soils, as expected. However, for the sandy-clay-loam with high CaCO3 content aggregation was observed. For the clayey soils with similar CaCO3, aggregation and disaggregation were obtained, for a soil with relatively low and high SOM, respectively. The stability trends are reflected by the ratio between the contents of inorganic carbon and soil organic matter (SOM), CaCO3/SOM, normalized to the clay content. Aggregation was explained by CaCO3 cementation, while disaggregation was attributed to high clay content and to alterations in SOM conformation post WDC. These opposite trends, obtained for the two clayey soils, were confirmed by analyzing changes in soil packing employing X-ray tomography (micro-CT). Our results clearly demonstrated that soil aggregation and disaggregation, induced by a WDC, suppresses and enhances herbicide mobility, respectively. However, the effect of WDC on herbicide leaching was not noticeable for Alion upon its high adsorption to a clayey soil, indicating that herbicide physical-chemical properties may dominate. Finally, WDC induces micron-scale changes in aggregate structure, which have a notable effect on pollutant mobility and fate in the environment. (C) 2020 Elsevier Ltd. All rights reserved.
Zusman, O. B. ; Perez, A. ; Mishael, Y. G. Multi-site nanocomposite sorbent for simultaneous removal of diverse micropollutants from treated wastewater. APPLIED CLAY SCIENCE 2021, 215.Abstract
Despite the advantages of maximizing treated wastewater (TWW) reuse, this practice brought upon the presence of micropollutants in edible plants, animals, and even humans, since many micropollutants are not completely removed by conventional treatment plants. Clay polymer nanocomposites (CPNs) have been proposed and widely studied in recent years as a promising sorbent for micropollutant removal. However, most of these studies report the development of a single CPN for the removal of specific micropollutants in batch experiments, usually from synthetic water, and do not compare to the removal by commercial sorbents. Here, we thoroughly investigated the adsorption mechanism of three chemically-diverse micropollutants; cationic, anionic, and non-ionic (metoprolol, diclofenac, and lamotrigine, respectively) from TWW by a CPN with a `loopy' polymer configuration. The results suggest that both cation and anion exchange sites coexist on the CPN, and therefore anionic and cationic micropollutants adsorb simultaneously, and they do not compromise the adsorption of each other. The adsorption of the non-ionic micropollutant enhanced in the presence of the charged micropollutants due to a synergistic effect. These adsorption trends were also obtained for micropollutant filtration by CPN columns. Finally, we demonstrated the simultaneous filtration of effluent organic matter and an array of micropollutants from TWW by the CPN columns and compared it to the filtration by granular activated carbon (GAC). A costeffective comparison indicates that the filtration by the CPN column is more efficient (ng pollutants/ sorbent cost) than by the GAC column.
Chaudhary, N. ; Bonfil, D. J. ; Tas, E. Physiological and Yield Responses of Spring Wheat Cultivars under Realistic and Acute Levels of Ozone. Atmosphere 2021, 12. Publisher's VersionAbstract
Tropospheric ozone (O3) is widely recognized as the cause of substantial yield and quality reduction in crops. Most of the previous studies focused on the exposure of wheat cultivars to elevated O3 levels. Our main objectives were to: (i) investigate the consistency of wheat cultivars’ physiological responses across two different realistic O3 levels; and (ii) compare these physiological responses with those under short acute O3 exposure. Three commercially available hard spring wheat cultivars bred under semiarid and Eastern Mediterranean conditions were exposed to two different O3 levels during two consecutive seasons (2016–2018)—36 and 71 ppbv 7 h mean O3 mixing ratios in open-top chambers. The results were compared to those following short acute O3 exposure (102.8 ppbv, 7 h mean for 10 days) in a greenhouse. Non-stomatal responses were significantly more pronounced than stomatal responses in all cultivars under different levels of O3. The specific cultivar was observed as the most O3-tolerant under all experiments. The fact that the same cultivar was found remarkably tolerant to the local semiarid ambient conditions according to other studies and to O3 exposure based on the present study supports a link between cultivar resistance to drought conditions and O3.
Xue, B. ; Helman, D. ; Wang, G. ; Xu, C. - Y. ; Xiao, J. ; Liu, T. ; Wang, L. ; Li, X. ; Duan, L. ; Lei, H. The low hydrologic resilience of Asian Water Tower basins to adverse climatic changes. 2021, 155, 103996. Publisher's VersionAbstract
Climate change has a significant impact on the runoff of basins in cold, dry areas. The quantification of regional ecohydrological responses to climate change such as warming and drought is essential for establishing proper water resource management schemes. We propose a simple and novel method based on the Budyko framework to evaluate the hydrologic resilience of 16 basins that conform the Asian Water Tower in the Tibetan Plateau (TP). Our method defines two metrics within the Budyko domain – tolerance (ψ) and plasticity (φ) – that characterize the hydrologic resilience of a basin. Based on an ecohydrological point of view, a basin is considered hydrologically resilient if ψ and φ are both greater than 1 or its φ is negative and ψ is greater than 1. Our results show that ψ varies between 0.27 and 0.74, with an average value of 0.45 and φ varies between 2 and 16.33, with an average value of 6.90, for 14 out of the 16 basins. Only two basins – Taohe and Datonghe – had negative φ (-11.67 and -8.11, respectively) and ψ greater than 1 (2.26 and 19.58, respectively), suggesting that these two are the only basins with a hydrologic resilience to climatic warming/drying in the TP. Within the non-resilient basins, we found vegetation to play a key role in the level of tolerance and plasticity indicating that basins with a larger vegetation cover display a lower capability to adapt to adverse climatic changes. Following these results, we call for afforestation efforts to be carefully considered in cold, dry areas. The proposed method and conclusions drawn by this study may help predict the hydrologic responses to future adverse climatic conditions.
Saadon, T. ; Lazarovitch, N. ; Jerszurki, D. ; Tas, E. Predicting net radiation in naturally ventilated greenhouses based on outside global solar radiation for reference evapotranspiration estimation. Agricultural Water Management 2021, 257, 107102. Publisher's VersionAbstract
A reliable prediction of net radiation (Rn) inside naturally ventilated greenhouses is critical for accurate evapotranspiration evaluation and thus for water saving, considering that previous studies have indicated that evapotranspiration in such relatively decoupled greenhouses is predominantly controlled by greenhouse Rn (Rn-GH). We hypothesized here that Rn-GH in naturally ventilated greenhouses can be accurately predicted using global solar radiation in the vicinity of the greenhouse (Rs-out) as the only measured parameter, together with the calculated position of the sun, defined by the solar elevation angle and solar azimuth. To test this hypothesis, we performed experiments in two adjacent greenhouses in the Southern Negev, Israel (30.96° N, 34.69° E) under arid climate. In one of the greenhouses, tomato was grown during winter 2017–2018, while in the other, melon was grown during winter and spring 2018–2019. Our analyses demonstrated that Rn-GH can be accurately predicted (r2 = 0.982) using Rs-out as the only measured parameter, while the global solar radiation inside the greenhouse (Rs-GH), and the ratio between Rn-GH and Rs-GH are predominantly dependent on solar elevation angle and solar azimuth, as well as the greenhouse structure and cloud cover. This paper shows that the impact of these properties on the association between Rs-out and Rn-GH can be accurately resolved using multivariate regression by the k-nearest neighbors approach. This suggests that computerized modeling of the greenhouse structure and light transmission can potentially enable precise evaluation of Rn-GH and therefore also reference evapotranspiration in naturally ventilated greenhouses, using Rs-out as the only measured parameter. A calculation-based factor for the cloud effect on Rs-out transmittance into the greenhouse significantly improved the Rn-GH prediction under cloudy conditions.
Jerszurki, D. ; Saadon, T. ; Zhen, J. ; Agam, N. ; Tas, E. ; Rachmilevitch, S. ; Lazarovitch, N. Vertical microclimate heterogeneity and dew formation in semi-closed and naturally ventilated tomato greenhouses. Scientia Horticulturae 2021, 288, 110271. Publisher's VersionAbstract
The extent of the vertical microclimate heterogeneity inside a greenhouse is mostly unknown, and it can strongly affect plant production and yield quality. Tomato crop was grown in a semi-closed greenhouse equipped with horizontal ventilation and sidewall curtains, which were only opened depending on microclimate conditions; and a naturally ventilated greenhouse equipped with sidewalls curtains that were kept open. Both greenhouses had a 1,000-m2 area and a net size of 50-mesh, and were located in an arid climate zone in Israel. Vertical profiles of CO2 concentration, actual vapor pressure, air, leaf and soil temperature, net CO2 assimilation rates, stomatal conductance, and total fruit yield, fresh mass, and quality were monitored in both greenhouses for 13 days, in January 2018; CO2 concentration, actual vapor pressure, and air and soil temperature were additionally monitored in the semi-closed greenhouse for seven days in December 2016, when the ventilation was inoperative, and in December 2017, with ventilation. The vertical air temperature gradient, along with the colder microclimate inside the naturally ventilated greenhouse, led to a lack of plant uniformity and yield loss. Closing the side curtains in the fanned semi-closed greenhouse had a beneficial effect on yield, however, with mixed results for quality, due to the higher air temperature and lower carbon dioxide levels at the upper canopy. Horizontal air circulation in the semi-closed greenhouse increased transpiration and assimilation, and increased dew occurrence at night, but did not reduce the vertical heterogeneity. Significant vertical gradients affect plant physiology, and closing the curtains in winter cultivation in semi-arid/arid climates has the potential to improve fruit yield and quality. However, it must be coupled with proper air circulation and, preferably, with CO2 enrichment, or careful management of natural ventilation through side curtains, in order to maximize CO2 replenishment while minimizing heat losses.
Klausner, Z. ; Ben-Efraim, M. ; Arav, Y. ; Tas, E. ; Fattal, E. The Micrometeorology of the Haifa Bay Area and Mount Carmel during the Summer. Atmosphere 2021, 12. Publisher's VersionAbstract
The Haifa bay area (HBA), which includes Mount Carmel and the Zevulun valley is the third largest metropolitan area in Israel. It is also a centre of heavy industry and an important transportation hub which serve as sources of local anthropogenic pollution. Such sources are associated with adverse health effects. In order to estimate the possible exposure of the inhabitants in such heterogeneous orographic area, a detailed atmospheric transport and dispersion modelling study is required, which in turn must take into account the local micrometeorology. The aim of this study is to conduct a spatio-temporal analysis of the flow field in the HBA in order to identify the common patterns of the average wind and characterize the statistical parameters of turbulence in this area, essential for detailed pollutants dispersion modelling. This study analyses data collected during four months of summer in a network of 16 weather stations which extend across Mount Carmel and the Zevulun valley. It was found that, during the evening and night time on Mount Carmel, different flow patterns may develop on each side, separated by the watershed line. When such conditions do not develop, as well as during the daytime, the wind field, both on Mount Carmel and the Zevulun valley is approximately homogenous. The analysis of the Monin–Obukhov similarity theory functions for the velocity standard deviations show a distinct difference between Mount Carmel and the Zevulun valley, as well as between strong and weak winds. This difference can be clearly seen also in the diurnal hourly distribution of atmospheric stabilities which exhibit higher proportions of unstable conditions in the Zevulun valley during day time and higher proportion of stable stratifications at the Mount Carmel during night-time.
Hendel, E. ; Bacher, H. ; Oksenberg, A. ; Walia, H. ; Schwartz, N. ; Peleg, Z. Deciphering the genetic basis of wheat seminal root anatomy uncovers ancestral axial conductance alleles. Plant, Cell & EnvironmentPlant, Cell & EnvironmentPlant Cell Environ 2021, n/a. Publisher's VersionAbstract
ABSTRACT Root axial conductance which describes the ability of water to move through the xylem, contributes to the rate of water uptake from the soil throughout the whole plant lifecycle. Under the rainfed wheat agro-system, grain-filling is typically occurring during declining water availability (i.e. terminal drought). Therefore, preserving soil water moisture during grain filling could serve as a key adaptive trait. We hypothesized that lower wheat root axial conductance can promote higher yields under terminal drought. A segregating population derived from a cross between durum wheat and its direct progenitor wild emmer wheat was used to underpin the genetic basis of seminal root architectural and functional traits. We detected 75 QTL associated with seminal roots morphological, anatomical, and physiological traits, with several hotspots harboring co-localized QTL. We further validated the axial conductance and central metaxylem QTL using wild introgression lines. Field-based characterization of genotypes with contrasting axial conductance suggested the contribution of low axial conductance as a mechanism for water conservation during grain filling and consequent increase in grain size and yield. Our findings underscore the potential of harnessing wild alleles to reshape the wheat root system architecture and associated hydraulic properties for greater adaptability under changing climate. This article is protected by copyright. All rights reserved.
Shiff, S. ; Helman, D. ; Lensky, I. M. Worldwide continuous gap-filled MODIS land surface temperature dataset. Scientific Data 2021, 8 74 - 74. Publisher's VersionAbstract
Satellite land surface temperature (LST) is vital for climatological and environmental studies. However, LST datasets are not continuous in time and space mainly due to cloud cover. Here we combine LST with Climate Forecast System Version 2 (CFSv2) modeled temperatures to derive a continuous gap filled global LST dataset at a spatial resolution of 1 km. Temporal Fourier analysis is used to derive the seasonality (climatology) on a pixel-by-pixel basis, for LST and CFSv2 temperatures. Gaps are filled by adding the CFSv2 temperature anomaly to climatological LST. The accuracy is evaluated in nine regions across the globe using cloud-free LST (mean values: R2 = 0.93, Root Mean Square Error (RMSE) = 2.7 °C, Mean Absolute Error (MAE) = 2.1 °C). The provided dataset contains day, night, and daily mean LST for the Eastern Mediterranean. We provide a Google Earth Engine code and a web app that generates gap filled LST in any part of the world, alongside a pixel-based evaluation of the data in terms of MAE, RMSE and Pearson’s r.
Michael, Y. ; Helman, D. ; Glickman, O. ; Gabay, D. ; Brenner, S. ; Lensky, I. M. Forecasting fire risk with machine learning and dynamic information derived from satellite vegetation index time-series. 2021, 764, 142844. Publisher's VersionAbstract
Fire risk mapping – mapping the probability of fire occurrence and spread – is essential for pre-fire management as well as for efficient firefighting efforts. Most fire risk maps are generated using static information on variables such as topography, vegetation density, and fuel instantaneous wetness. Satellites are often used to provide such information. However, long-term vegetation dynamics and the cumulative dryness status of the woody vegetation, which may affect fire occurrence and spread, are rarely considered in fire risk mapping. Here, we investigate the impact of two satellite-derived metrics that represent long-term vegetation status and dynamics on fire risk mapping – the long-term mean normalized difference vegetation index (NDVI) of the woody vegetation (NDVIW) and its trend (NDVIT). NDVIW represents the mean woody density at the grid cell, while NDVIT is the 5-year trend of the woody NDVI representing the long-term dryness status of the vegetation. To produce these metrics, we decompose time-series of satellite-derived NDVI following a method adjusted for Mediterranean woodlands and forests. We tested whether these metrics improve fire risk mapping using three machine learning (ML) algorithms (Logistic Regression, Random Forest, and XGBoost). We chose the 2007 wildfires in Greece for the analysis. Our results indicate that XGBoost, which accounts for variable interactions and non-linear effects, was the ML model that produced the best results. NDVIW improved the model performance, while NDVIT was significant only when NDVIW was high. This NDVIW–NDVIT interaction means that the long-term dryness effect is meaningful only in places of dense woody vegetation. The proposed method can produce more accurate fire risk maps than conventional methods and can supply important dynamic information that may be used in fire behavior models.
Weksler, S. ; Rozenstein, O. ; Haish, N. ; Moshelion, M. ; Wallach, R. ; Ben-Dor, E. Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting. Sensors 2021, 21. Publisher's VersionAbstract
Potassium is a macro element in plants that is typically supplied to crops in excess throughout the season to avoid a deficit leading to reduced crop yield. Transpiration rate is a momentary physiological attribute that is indicative of soil water content, the plant’s water requirements, and abiotic stress factors. In this study, two systems were combined to create a hyperspectral–physiological plant database for classification of potassium treatments (low, medium, and high) and estimation of momentary transpiration rate from hyperspectral images. PlantArray 3.0 was used to control fertigation, log ambient conditions, and calculate transpiration rates. In addition, a semi-automated platform carrying a hyperspectral camera was triggered every hour to capture images of a large array of pepper plants. The combined attributes and spectral information on an hourly basis were used to classify plants into their given potassium treatments (average accuracy = 80%) and to estimate transpiration rate