Recent Submissions

  • Desalination at ambient temperature and pressure by a novel class of biporous anisotropic membrane

    Qtaishat, Mohammed Rasool; Obaid, Mohammed; Matsuura, Takeshi; Al-Samhouri, Areej; Lee, Jung-Gil; Soukane, Sofiane; Ghaffour, NorEddine (Scientific reports, Springer Science and Business Media LLC, 2022-08-09) [Article]
    Recent scientific advances have made headway in addressing pertinient issues in climate change and the sustainability of our natural environment. This study makes use of a novel approach to desalination that is environment friendly, naturally sustainable and energy efficient, meaning that it is also cost efficient. Evaporation is a key phenomenon in the natural environment and used in many industrial applications including desalination. For a liquid droplet, the vapor pressure changes due to the curved liquid-vapor interface at the droplet surface. The vapor pressure at a convex surface in a pore is, therefore, higher than that at a flat surface due to the capillary effect, and this effect is enhanced as the pore radius decreases. This concept inspired us to design a novel biporous anisotropic membrane for membrane distillation (MD), which enables to desalinate water at ambient temperature and pressure by applying only a small transmembrane temperature gradient. The novel membrane is described as a super-hydrophobic nano-porous/micro-porous composite membrane. A laboratory-made membrane with specifications determined by the theoretical model was prepared for model validation and tested for desalination at different feed inlet temperatures by direct contact MD. A water vapor flux as high as 39.94 ± 8.3 L m-2 h-1 was achieved by the novel membrane at low feed temperature (25 °C, permeate temperature = 20 °C), while the commercial PTFE membrane, which is widely used in MD research, had zero flux under the same operating conditions. As well, the fluxes of the fabricated membrane were much higher than the commercial membrane at various inlet feed temperatures.
  • Coverage Enhancement of Underwater Internet of Things Using Multi-Level Acoustic Communication Networks

    Xu, Jiajie; Kishk, Mustafa Abdelsalam; Alouini, Mohamed-Slim (IEEE Internet of Things Journal, Institute of Electrical and Electronics Engineers (IEEE), 2022-08-03) [Article]
    Underwater acoustic communication networks (UACNs) are considered a key-enabler to the underwater internet of things (UIoT). UACN is regarded as essential for various marine applications such as monitoring, exploration, and trading. However, a large part of existing literature disregards the 3-dimensional (3D) nature of the underwater communication system. In this paper, we propose a K-tier UACN that acts as a gateway that connects the UIoT with the Space-Air-Ground-Sea Integrated System (SAGSIS). The proposed network architecture consists of several tiers along the vertical direction with adjustable depths. On the horizontal dimension, the best coverage probability (CP) is computed and maximized by optimizing the densities of surface stations (SSs) in each tier. On the vertical dimension, the depth of each tier is also optimized to minimize inter-tier interference and maximize overall system performance. Using tools from stochastic geometry, the total CP of the proposed K-tier network is analyzed. For given spatial distribution of UIoT device’s depth, the best CP can be achieved by optimizing the depths of the transceivers connected to the SSs through a tether. We verify the accuracy of the analysis using Monte-Carlo simulations. In addition, we draw multiple useful system-level insights that help optimize the design of underwater 3D networks based on the given distribution of UIoT device’s depths.
  • Investigation of Antibiotic Resistome in Hospital Wastewater during the COVID-19 Pandemic: Is the Initial Phase of the Pandemic Contributing to Antimicrobial Resistance?

    Wang, Changzhi; Mantilla Calderon, David; Xiong, Yanghui; Alkahtani, Mohsen; Bashawri, Yasir M.; Al Qarni, Hamed; Hong, Pei-Ying (Environmental Science & Technology, American Chemical Society (ACS), 2022-08-02) [Article]
    Since the COVID-19 pandemic started, there has been much speculation about how COVID-19 and antimicrobial resistance may be interconnected. In this study, untreated wastewater was sampled from Hospital A designated to treat COVID-19 patients during the first wave of the COVID-19 pandemic alongside Hospital B that did not receive any COVID-19 patients. Metagenomics was used to determine the relative abundance and mobile potential of antibiotic resistant genes (ARGs), prior to determining the correlation of ARGs with time/incidence of COVID-19. Our findings showed that ARGs resistant to macrolides, sulfonamides, and tetracyclines were positively correlated with time in Hospital A but not in Hospital B. Likewise, minor extended spectrum beta-lactamases (ESBLs) and carbapenemases of classes B and D were positively correlated with time, suggesting the selection of rare and/or carbapenem-resistant genes in Hospital A. Non-carbapenemase blaVEB also positively correlated with both time and intI1 and was copresent with other ARGs including carbapenem-resistant genes in 6 metagenome-assembled genomes (MAGs). This study highlighted concerns related to the dissemination of antimicrobial resistance (AMR) during the COVID-19 pandemic that may arise from antibiotic use and untreated hospital wastewater.
  • Nickel-Coated ceramic hollow fiber cathode for fast enrichment of chemolithoautotrophs and efficient reduction of CO2 in microbial electrosynthesis

    Bian, Bin; Singh, Yogesh Balwant; Rabaey, Korneel; Saikaly, Pascal (Chemical Engineering Journal, Elsevier BV, 2022-07-30) [Article]
    Microbial electrosynthesis (MES) explores the potential of chemolithoautotrophs for the production of value-added products from CO2. However, the enrichment of chemolithoautotrophs on a cathode is relatively slow and the separation of the products is energy intensive. In this study, a novel and multifunctional cathode configuration, enabling the simultaneous enrichment of chemolithoautotrophs and separation of acetate from MES, was developed through one-step electroless nickel plating on ceramic hollow fiber (CHF) membrane. A thick layer of chemolithoautotrophs with 5.2 times higher cell density, which was dominated by Sporomusa (68 % of the total sequence reads in biocathode), was enriched on the membrane cathode surface through suspended biomass microfiltration compared to MES reactors operated without filtration. Simultaneously, >87 % of acetate (31 mM) per batch could be harvested after catholyte microfiltration. The Ni content was > 80 % on the CHF surface after long-term operation in the two-chamber MES system, which exhibited 78 % lower charge transfer resistance compared to three-chamber MES system (∼110 vs 510 Ω) for acetate separation/extraction. The ease of product separation in two-chamber MES systems and the fast establishment of chemolithoautotrophs on the cathode are a step forward in realizing MES systems as a promising platform for CO2 reduction and biochemical production in a circular carbon bioeconomy.
  • Are commercial polyamide seawater and brackish water membranes effectively charged?

    Blankert, Bastiaan; Huisman, Kees Theo; Martinez, Fernan David; Vrouwenvelder, Johannes Simon; Picioreanu, Cristian (Journal of Membrane Science Letters, Elsevier BV, 2022-07-30) [Article]
    New developments in modeling solute transport in reverse osmosis (RO) membranes are based on the mechanistic description of solution friction and electromigration. In these models, the membrane charge significantly impacts the separation that occurs in the membrane through Donnan partitioning. One implication of membrane charge is that the salt permeability strongly depends on the ion concentration in the feedwater. In this study, we experimentally evaluate the effect of salinity, varied over almost two orders of magnitude (ca. 10–650mM), on four commercially available polyamide seawater RO and brackish water RO membranes. We found no significant effect of feed concentration on observed salt permeability, while the membrane performance closely resembled the specification by the manufacturers. We also demonstrate that a minor leak in the membrane provides a plausible alternative explanation to trend between concentration and salt permeability reported in other studies. The standard solution diffusion model provides a satisfactory description of our data for the membranes and feedwater conditions that we tested.
  • Unraveling the role of feed temperature and cross-flow velocity on organic fouling in membrane distillation using response surface methodology

    Ricceri, Francesco; Blankert, Bastiaan; Ghaffour, NorEddine; Vrouwenvelder, Johannes S.; Tiraferri, Alberto; Fortunato, Luca (Desalination, Elsevier BV, 2022-07-28) [Article]
    Understanding the role of operating condition on fouling development in membrane distillation (MD) is critical for the further optimization of MD technology. In this study, organic fouling development in MD was investigated varying the feed inlet temperature from 35 to 65 °C and the cross-flow velocity from 0.21 to 0.42 m/s. The fouling layer thickness was estimated at the end of each experiment non-invasively with optical coherence tomography. The set of experiments was mined to model the initial flux decline, the near-stable flux, and the final foulant thickness responses by central composite design, a useful response surface methodology (RSM) tool. The results indicated a linear increment of the fouling thickness by increasing the feed inlet temperatures. Overall, the feed inlet temperature governed both the initial flux decline and the fouling deposition. The benefits in water productivity obtained by increasing the feed temperature were always offset by higher fouling deposition. Higher cross-flow velocities showed a positive effect on the initial flux, which however translated in larger values of the initial flux decline rate. On the other hand, the higher shear stress contributed to a decrease of the final steady-state fouling layer thickness. The proposed approach was proven to be a valuable tool to assess the role of the operating conditions on fouling and process performance in MD.
  • A novel anaerobic fluidized membrane bioreactor system: Improving process performance and fouling control

    Issa, L.; Kik, O. El; Katuri, Krishna; Saikaly, Pascal; Alameddine, I.; El-Fadel, Mutasem (Environmental Technology and Innovation, Elsevier BV, 2022-07-27) [Article]
    In this study, the effectiveness of a novel system of an anaerobic fluidized membrane bioreactor (AnFMBR) in treating wastewater was demonstrated and the results were validated by testing duplicate systems in parallel under similar operating conditions. In this novel system, an outer loop performs as an anaerobic reactor while an inner loop serves as an AnFMBR with granular activated carbon (GAC) used as a carrier and for fouling control. The GAC fluidization is restricted to the inner loop to minimize operational energy while ensuring membrane scouring. Fluidized GAC was a key factor in maintaining low TMP by attracting biofilm formation thus reducing attachment to the membrane surface and by removing deposits from membrane surface via abrasion. The new system improved fouling control as reflected in a slower buildup in transmembrane pressure (TMP) resulting in a 1.5 to 3.8 folds increase in typically reported operating periods for anaerobic membrane bioreactors (AnMBRs) and AnFMBRs. Similarly, energy requirements were estimated at 52 and 94% lower than those reported for typical AnMBRs and aerobic MBRs, respectively. At a validation level, both AnFMBR systems exhibited a similar performance with respect to several indicators including the microbial community composition, methane yield, chemical oxygen demand removal, TMP, and energy savings.
  • Exploring the use of synthetic aperture radar data for irrigation management in super high-density olive orchards

    El Hajj, Marcel Mohamad; Almashharawi, Samer K.; Johansen, Kasper; El Farkh, Jamal; McCabe, Matthew (International Journal of Applied Earth Observation and Geoinformation, Elsevier BV, 2022-07-06) [Article]
    Understanding the plant water-uptake dynamics and behavior in olive orchards is an area of much interest, particularly for efforts to optimize the use and application of water resources. However, plant water-uptake information is rarely available or consistently monitored for large agricultural areas, especially in developing countries. Here we evaluate the potential of using synthetic aperture radar (SAR) images to monitor the water-uptake rate in super high-density olive orchards located in the hot and arid desert climate of Saudi Arabia. The experiment was performed using Sentinel-1 data acquired between 2019 and 2020 in concert with in situ sap flow measurements. To date, no study has explored the potential of Sentinel-1 SAR data to assess the water-uptake rate in olive orchards. The results demonstrate that the SAR backscatter increased between January and July/August, and then decreased during the remainder of the year, following a broadly Gaussian distribution. Of key interest is the strength of the relationship between the increasing and decreasing trends of SAR backscatter and the variation in the coincident water-uptake rate measured in situ, producing a coefficient of determination of 0.81 in the VV polarization. As the relationship between the SAR backscatter and water-uptake rate was established for plots with similar tree type and planting density, further exploration of orchards with different characteristics and planting densities is needed to fully understand the potential of SAR data to estimate plant water-uptake. Overall, the study demonstrates that SAR data can track variation in locally measured water-uptake and illustrates the potential to assist with enhancing irrigation management.
  • Mangrove distribution and afforestation potential in the Red Sea

    Blanco Sacristan, Javier; Johansen, Kasper; Duarte, Carlos M.; Daffonchio, Daniele; Hoteit, Ibrahim; McCabe, Matthew (Science of The Total Environment, Elsevier BV, 2022-06-30) [Article]
    Mangrove ecosystems represent one of the most effective natural environments for fixing and storing carbon (C). Mangroves also offer significant co-benefits, serving as nurseries for marine species, providing nutrients and food to support marine ecosystems, and stabilizing coastlines from erosion and extreme events. Given these considerations, mangrove afforestation and associated C sequestration has gained considerable attention as a nature-based solution to climate adaptation (e.g., protect against more frequent storm surges) and mitigation (e.g. offsetting other C-producing activities). To advance our understanding and description of these important ecosystems, we leverage Landsat-8 and Sentinel-2 satellite data to provide a current assessment of mangrove extent within the Red Sea region and also explore the effect of spatial resolution on mapping accuracy. We establish that Sentinel-2 provides a more precise spatial record of extent and subsequently use these data together with a maximum entropy (MaxEnt) modeling approach to: i) map the distribution of Red Sea mangrove systems, and ii) identify potential areas for future afforestation. From these current and potential mangrove distribution maps, we then estimate the carbon sequestration rate for the Red Sea (as well as for each bordering country) using a meta-analysis of sequestration values surveyed from the available literature. For the mangrove classification, we obtained mapping accuracies of 98 %, with a total Red Sea mangrove extent estimated at approximately 175 km2. Based on the MaxEnt approach, which used soil physical and environmental variables to identify the key factors limiting mangrove growth and distribution, an area of nearly 410 km2 was identified for potential mangrove afforestation expansion. The factors constraining the potential distribution of mangroves were related to soil physical properties, likely reflecting the low sediment load and limited nutrient input of the Red Sea. The current rate of carbon sequestration was calculated as 1034.09 ± 180.53 Mg C yr-1, and the potential sequestration rate as 2424.49 ± 423.26 Mg C yr-1. While our results confirm the maintenance of a positive trend in mangrove growth over the last few decades, they also provide the upper bounds on above ground carbon sequestration potential for the Red Sea mangroves.
  • Parametric Analysis of a Universal Isotherm Model to Tailor Characteristics of Solid Desiccants for Dehumidification

    Burhan, Muhammad; Chen, Qian; Shahzad, Muhammad Wakil; Ja, M. Kum; Ng, Kim Choon (Frontiers in Energy Research, Frontiers Media SA, 2022-06-28) [Article]
    Cooling has a significant share in energy consumption, especially in hot tropical regions. The conventional mechanical vapor compression (MVC) cycle, widely used for air-conditioning needs, has high energy consumption as air is cooled down to a dew point to remove the moisture. Decoupling the latent cooling load through dehumidification from the sensible cooling load can significantly improve the energy requirement for air-conditioning applications. Solid desiccants have shown safe and reliable operation against liquid desiccants, and several configurations of solid desiccants dehumidifiers are studied to improve their performance. However, the characteristics of solid desiccants are critical for the performance and overall operation of the dehumidifier. The properties of every desiccant depend upon its porous adsorbing surface characteristics. Hence, it has an optimum performance for certain humid conditions. Therefore, for a better dehumidification performance in a specific tropical region, the solid desiccant must have the best performance, according to the humidity range of that region. In this article, a theoretical methodology has been discussed to help the industry and chemists to understand the porous structural properties of adsorbent surfaces needed to tune the material performance for a particular humidity value before material synthesis.
  • Experimental study of a sustainable cooling process hybridizing indirect evaporative cooling and mechanical vapor compression

    Chen, Qian; Ja, M. Kum; Burhan, Muhammad; Shahzad, Muhammad Wakil; Ybyraiymkul, Doskhan; Zheng, Hongfei; Ng, Kim Choon (Energy Reports, Elsevier BV, 2022-06-27) [Article]
    The hybrid indirect evaporative cooling-mechanical vapor compression (IEC-MVC) process is an emerging cooling technology that combines the advantages of IEC and MVC, i.e., effective temperature and humidity control, high energy efficiency, and low water consumption. This paper presents an experimental study of the hybrid IEC-MVC process. A 1-Rton pilot is fabricated by connecting IEC and MVC in series, and its performance is evaluated under different operating conditions (outdoor air temperature and humidity, air flowrate, compressor frequency). Results revealed that the outdoor air temperature and humidity could be lowered to 5–15 °C and 5–10 g/kg, respectively. The IEC handles 35%–50% of the total cooling load, and the energy consumption can be reduced by 15%–35% as compared to standalone MVC. Moreover, the condensate collected from the evaporator can compensate for >70% of water consumption in IEC, making the system applicable in arid regions. Based on the derived results, a simplified empirical model is developed for rapid evaluation of the IEC-MVC process, and the energy-saving potential in major cities of Saudi Arabia is estimated.
  • Spatial Variation of the Microbial Community Structure of On-Site Soil Treatment Units in a Temperate Climate, and the Role of Pre-treatment of Domestic Effluent in the Development of the Biomat Community

    Criado Monleon, Alejandro Javier; Knappe, Jan; Somlai, Celia; Betancourth, Carolina Ospina; Ali, Muhammad; Curtis, Thomas P; Gill, Laurence William (Frontiers in microbiology, Frontiers Media SA, 2022-06-24) [Article]
    The growth of microbial mats or “biomats” has been identified as an essential component in the attenuation of pollutants within the soil treatment unit (STU) of conventional on-site wastewater treatment systems (OWTSs). This study aimed to characterize the microbial community which colonizes these niches and to determine the influence of the pre-treatment of raw-domestic wastewater on these communities. This was achieved through a detailed sampling campaign of two OWTSs. At each site, the STU areas were split whereby half received effluent directly from septic tanks, and half received more highly treated effluents from packaged aerobic treatment systems [a coconut husk media filter on one site, and a rotating biodisc contactor (RBC) on the other site]. Effluents from the RBC had a higher level of pre-treatment [~90% Total Organic Carbon (TOC) removal], compared to the media filter (~60% TOC removal). A total of 92 samples were obtained from both STU locations and characterized by 16S rRNA gene sequencing analysis. The fully treated effluent from the RBC resulted in greater microbial community richness and diversity within the STUs compared to the STUs receiving partially treated effluents. The microbial community structure found within the STU receiving fully treated effluents was significantly different from its septic tank, primary effluent counterpart. Moreover, the distance along each STU appears to have a greater impact on the community structure than the depth in each STU. Our findings highlight the spatial variability of diversity, Phylum- and Genus-level taxa, and functional groups within the STUs, which supports the assumption that specialized biomes develop around the application of effluents under different degrees of treatment and distance from the source. This research indicates that the application of pre-treated effluents infers significant changes in the microbial community structure, which in turn has important implications for the functionality of the STU, and consequently the potential risks to public health and the environment.
  • Combining multi-indicators with machine-learning algorithms for maize yield early prediction at the county-level in China

    Cheng, Minghan; Penuelas, Josep; McCabe, Matthew; Atzberger, Clement; Jiao, Xiyun; Wu, Wenbin; Jin, Xiuliang (Agricultural and Forest Meteorology, Elsevier BV, 2022-06-18) [Article]
    The accurate and timely prediction of crop yield at a large scale is important for food security and the development of agricultural policy. An adaptable and robust method for estimating maize yield for the entire territory of China, however, is currently not available. The inherent trade-off between early estimates of yield and the accuracy of yield prediction also remains a confounding issue. To explore these challenges, we employ indicators such as GPP, ET, surface temperature (Ts), LAI, soil properties and maize phenological information with random forest regression (RFR) and gradient boosting decision tree (GBDT) machine learning approaches to provide maize yield estimates within China. The aims were to: (1) evaluate the accuracy of maize yield prediction obtained from multimodal data analysis using machine-learning; (2) identify the optimal period for estimating yield; and (3) determine the spatial robustness and adaptability of the proposed method. The results can be summarized as: (1) RFR estimated maize yield more accurately than GBDT; (2) Ts was the best single indicator for estimating yield, while the combination of GPP, Ts, ET and LAI proved best when multi-indicators were used (R2 = 0.77 and rRMSE = 16.15% for the RFR); (3) the prediction accuracy was lower with earlier lead time but remained relatively high within at least 24 days before maturity (R2 > 0.77 and rRMSE <16.92%); and (4) combining machine-learning algorithms with multi-indicators demonstrated a capacity to cope with the spatial heterogeneity. Overall, this study provides a reliable reference for managing agricultural production.
  • Alleviating mass transfer limitations in industrial external-loop syngas-to-ethanol fermentation

    Puiman, Lars; Abrahamson, Britt; Lans, Rob G.J.M.van der; Haringa, Cees; Noorman, Henk J.; Picioreanu, Cristian (Chemical Engineering Science, Elsevier BV, 2022-06-17) [Article]
    Mass transfer limitations in syngas fermentation processes are mostly attributed to poor solubility of CO and H2 in water. Despite these assumed limitations, a syngas fermentation process has recently been commercialized. Using large-sale external-loop gas-lift reactors (EL-GLR), CO-rich off-gases are converted into ethanol, with high mass transfer performance (7–8.5 g.L-1.h−1). However, when applying established mass transfer correlations, a much poorer performance is predicted (0.3–2.7 g.L-1.h−1). We developed a CFD model, validated on pilot-scale data, to provide detailed insights on hydrodynamics and mass transfer in a large-scale EL-GLR. As produced ethanol could increase gas hold-up (+30%) and decrease the bubble diameter (≤2 mm) compared to air–water mixtures, we found with our model that a high volumetric mass transfer coefficient (650–750 h−1) and mass transfer capacity (7.5–8 g.L-1.h−1) for CO are feasible. Thus, the typical mass transfer limitations encountered in air–water systems can be alleviated in the syngas-to-ethanol fermentation process.
  • Materials for energy conversion in membrane distillation localized heating: Review, analysis and future perspectives of a paradigm shift

    Soukane, Sofiane; Son, Hyuk Soo; Mustakeem, Mustakeem; Obaid, M.; Alpatova, Alla; Qamar, Adnan; Jin, Yong; Ghaffour, NorEddine (Renewable and Sustainable Energy Reviews, Elsevier BV, 2022-06-16) [Article]
    Despite its ability to treat high salinity feeds and its integration readiness with renewable energy, membrane distillation (MD) is still facing many challenges. Intrinsically, the process suffers from low water fluxes and high thermal energy input, further aggravated by the temperature polarization phenomenon. Recent progress in MD design to improve its efficiency has taken the process to the heart of the materials-energy nexus. The use of advanced materials for efficient heat delivery has led to the concept of localized heating. Here, after emphasizing the main challenges that still hinder MD from reaching the industry arena, a compilation of the energy sources used in localized heating with concomitant materials is presented. Whether by coating, or incorporation, or brought close to the membrane, materials are grouped following the energy sources they respond to and their level of integration in the MD system is discussed accordingly. An energy analysis is carried out for cases reported in the literature. Results are assembled following different criteria to highlight the performance achieved with each energy source, the material integration strategy and the MD variant used with an adjustment if photovoltaics research cells are to power these energy sources in the future. Particular emphasis is put on process scale-up opportunities when localized heating is used compared to classical MD configurations. It is shown that, although localized heating provides a significant improvement, process and module design need to be included in the material energy development loop for MD to fully penetrate the desalination and water treatment industry.
  • Application of a smart dosing pump algorithm in identifying real-time optimum dose of antiscalant in reverse osmosis systems

    Mangal, Muhammad Nasir; Yangali-Quintanilla, Victor A.; Salinas-Rodriguez, Sergio G.; Dusseldorp, Jos; Blankert, Bastiaan; Kemperman, Antoine J. B.; Schippers, Jan C.; Kennedy, Maria D.; van der Meer, Walter G. J. (JOURNAL OF MEMBRANE SCIENCE, Elsevier BV, 2022-06-14) [Article]
    The potential of membrane scaling control by a real-time optimization algorithm was investigated. The effect of antiscalant dosing was evaluated from the induction time measured in glass batch-reactors, and from the operational performance of a lab-scale reverse osmosis (RO) unit and two pilot-scale RO units. Step changes in the antiscalant dosing demonstrated that the accumulation of scaling is ‘paused’ during periods when the optimum dose is applied. This is paramount for the application of a dynamic dosing strategy that may briefly underdose, while searching for the optimum dose. It was found that antiscalant underdose and overdose were both detrimental to RO operation since underdose resulted in membrane scaling, while overdose led to membrane fouling due to calcium-antiscalant deposits. The dosing algorithm was used to minimize antiscalant consumption in two pilot RO units. The algorithm was able to lower the antiscalant doses to 0.2 mg/L and 0.6 mg/L, while the supplier's recommended antiscalant doses were 2.0 mg/L and 4.5 mg/L, respectively. As a result, the algorithm could reduce antiscalant consumption by up to 85–90% for the plants mentioned.
  • Multi-sensor and multi-platform consistency and interoperability between UAV, Planet CubeSat, Sentinel-2, and Landsat reflectance data

    Jiang, Jiale; Johansen, Kasper; Tu, Yu-Hsuan; McCabe, Matthew (GIScience & Remote Sensing, Informa UK Limited, 2022-06-06) [Article]
    Unmanned aerial vehicle (UAV) and satellite data have considerable complementarity for platform inter-operability, data fusion studies, calibration and validation efforts, and various multiscale analyses. To optimize cross-platform synergies between field-deployable UAV and space-based satellite systems, an understanding of spectral characteristics and compatibility is required. Here, we present the assessment of spectral consistency, undertaking a pixel-to-pixel similarity assessment of co-registered reflectance maps using corresponding spectral bands from UAV and satellite multispectral imagery. A high-resolution centimeter-scale UAV-mounted MicaSense RedEdge-MX sensor is intercompared against variable-resolution multi-spectral sensors on-board PlanetScope, Sentinel-2 and Landsat 8 platforms. Sampling from within an urban environment that covers a range of both natural and man-made surfaces, we employ ground-based spectroradiometer data to evaluate pixel-level responses, using regression analysis and measurements of relative root mean square error (rRMSE) to assess for factors such as spatial and spectral misalignment. Using two radiometric correction approaches for the UAV data, we found that a vicarious radiometric correction was more accurate than a linear empirical line method, with the former improving rRMSE by between 1.6% and 20.11% when assessed against spectroradiometer measurements. Spectral band misalignment between the UAV and satellite sensors affected their spectral consistency, causing different reflectance values for the same object in the corresponding UAV and satellite bands, with the issue amplified over specific land-cover classes (e.g. grass in the red edge part of the spectrum). Using the standard deviation of a UAV-derived normalized difference vegetation index (NDVI) as a metric of spatial heterogeneity, larger differences between the UAV and satellite-based NDVI were observed for different ground features in response to both land-cover boundary and shadow effects. Interestingly, higher spatial heterogeneity did not necessarily lead to higher spectral inconsistencies. It was also determined that as spatial scale differences between the UAV and satellite platforms increased, the lower was the impact of geometric misregistration on their consistency. Indeed, the rRMSE between the reflectance values of the UAV-based spectral bands and the corresponding satellite imagery was smaller at lower resolution (e.g. Landsat 8) than higher resolution (e.g. PlanetScope). Overall, the study provides insight into the collective effect of spectral and spatial misalignments on the degree of spectral consistency that can be expected between UAV and satellite data, guiding robust radiometric intercalibration efforts and the potential for improved synergy and interoperability between UAV and satellite data.
  • Periodic fouling control strategies in gravity-driven membrane bioreactors (GD-MBRs): Impact on treatment performance and membrane fouling properties

    Ranieri, Luigi; Johannes, S; Vrouwenvelder; Fortunato, Luca (The Science of the total environment, Elsevier BV, 2022-05-31) [Article]
    This study aims to assess the effects of periodic membrane fouling control strategies in Gravity-Driven Membrane Bioreactor (GD-MBR) treating primary wastewater. The impact of each control strategy on the reactor performance (permeate flux and water quality), biomass morphology, and fouling composition were evaluated. The application of air scouring coupled with intermittent filtration resulted in the highest permeate flux (4 LMH) compared to only intermittent filtration (i.e., relaxation) (1 LMH) and air scouring under continuous filtration (2.5 LMH). Air scouring coupled with relaxation led to a thin (~50 μm) but with more porous fouling layer and low hydraulic resistance, presenting the lowest concentration of extracellular polymeric substance (EPS) in the biomass. Air scouring under continuous filtration led to a thin (~50 μm), dense, compact, and less porous fouling layer with the highest specific hydraulic resistance. The employment of only relaxation led to the highest fouling formation (~280 μm) on the membrane surface. The highest TN removal (~62%) was achieved in the reactor with only relaxation (no aeration) due to the anoxic condition in the filtration tank, while the highest COD removal (~ 60%) was achieved with air scouring under continuous filtration due to the longer aeration time and the denser fouling layer. The results highlighted the importance of performing in-depth fouling characterization to link the membrane fouling properties to the hydraulic resistance and membrane bioreactor performances (i.e., water quality and water production). Moreover, this work proven the versatility of the GD-MBR, where the choice of the appropriate operation and fouling control strategy relies on the eventual discharge or reuse of the treated effluent.
  • Evapotranspiration estimates in a traditional irrigated area in semi-arid Mediterranean. Comparison of four remote sensing-based models

    El Farkh, Jamal; Simonneaux, Vincent; Jarlan, Lionel; Ezzahar, Jamal; Boulet, Gilles; Chakir, Adnane; Er-Raki, Salah (Agricultural Water Management, Elsevier BV, 2022-05-31) [Article]
    Quantification of actual crop evapotranspiration (ETa) over large areas is a critical issue to manage water resources, particularly in semi-arid regions. In this study, four models driven by high resolution remote sensing data were intercompared and evaluated over an heterogeneous and complex traditional irrigated area located in the piedmont of the High Atlas mountain, Morocco, during the 2017 and 2018 seasons: (1) SAtellite Monitoring of IRrigation (SAMIR) which is a software-based on the FAO-56 dual crop coefficient water balance model fed with Sentinel-2 high-resolution Normalized Difference Vegetation Index (NDVI) to derive the basal crop coefficient (Kcb); (2) Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) which is a surface energy balance model fed with land surface temperature (LST) derived from thermal data provided from Landsat 7 and 8; (3) a modified version of the Shuttleworth–Wallace (SW) model which uses the LST to compute surface resistances and (4) METRIC-GEE which is a version of METRIC model (“Mapping Evapotranspiration at high Resolution with Internalized Calibration”) that operates on the Google Earth Engine platform, also driven by LST. Actual evapotranspiration (ETa) measurements from two Eddy-Covariance (EC) systems and a Large Aperture Scintillometer (LAS) were used to evaluate the four models. One EC was used to calibrate SAMIR and SPARSE (EC1) which were validated using the second one (EC2), providing a Root Mean Square Error (RMSE) and a determination coefficient (R) of 0.53 mm/day (R=0.82) and 0.66 mm/day (R=0.74), respectively. SW and METRIC-GEE simulations were obtained respectively from a previous study and Google Earth Engine (GEE), therefore no calibration was performed in this study. The four models predict well the seasonal course of ETa during two successive growing seasons (2017 and 2018). However, their performances were contrasted and varied depending on the seasons, the water stress conditions and the vegetation development. By comparing the statistical results between the simulation and the measurements of ETa it has been shown that SAMIR and METRIC-GEE are the less scattered and the better in agreement with the LAS measurements (RMSE equal to 0.73 and 0.68 mm/day and R equal to 0.74 and 0.82, respectively). On the other hand, SPARSE is less scattered (RMSE = 0.90 mm/day, R = 0.54) than SW which is slightly better correlated (RMSE = 0.98 mm/day, R = 0.60) with the observations. This study contributes to explore the complementarities between these approaches in order to improve the evapotranspiration mapping monitored with high-resolution remote sensing data.
  • INTRA-FIELD CROP YIELD VARIABILITY BY ASSIMILATING CUBESAT LAI IN THE APSIM CROP MODEL

    Ziliani, M. G.; Altaf, Muhammad; Aragon, B.; Houborg, Rasmus; Franz, Trenton; Lu, Y.; Sheffield, Justin; Hoteit, Ibrahim; McCabe, Matthew (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Copernicus GmbH, 2022-05-30) [Article]
    Predicting within-field crop yield early in the season can help address crop production challenges to improve farmers’ economic return. While yield prediction with remote sensing has been a research aim for years, it is only recently that observations with the suited spatial and temporal resolutions have become accessible to improve crop yield predictions.Here we developed a yield prediction framework that integrates daily high-resolution (3 m) CubeSat imagery into the APSIM crop model. The approach trains a regression model that correlates simulated yield to simulated leaf area index (LAI) from APSIM. That relationship is then employed to determine the optimum date at which the regression best predicts yield from the LAI. Additionally, our approach can forecast crop yield by utilizing a particle filter to assimilate CubeSat-based LAI in the model APSIM to generate yield maps at 3 m several weeks before the optimum regression date. Our method was evaluated for a rainfed site located in the US Corn belt, using a collection of spatially varying yield data. The proposed approach does not need in situ data to rain the regression, with outcomes reporting that even with a single assimilation step, accurate yield predictions were provided up to 21 days before the optimum regression date. The spatial variability of crop yield was reproduced fairly well, with a good correlation against in situ measurements (R2 = 0.73 and RMSE = 1.69), demonstrating that high-resolution yield predictions early in the season have great potential to meet and improve upon digital agricultural goals.

View more