Mass Transfer-based Models Research Articles

Selection of best wavelet functions and decomposition levels for coupling with soft computing methods in estimating ETo in coastal and island regions

ABSTRACT Mass transfer-based models are among the extensively applied reference evapotranspiration (ET o ) estimation approaches that have been proven to provide reliable estimates under certain climatic and geographical conditions. A major issue with such approaches is the high variations in wind speed time series, which is a governing meteorological parameter in mass transfer-based models. few studies have focused on applying wavelet transform as a robust pre-processing technique for ETo estimation. A major question with coupling wavelet transforms with soft computing methods would be the proper choice of the wavelet function, vanishing moments and the decomposition levels. The present study aims at assessing different wavelet functions coupled with boosted regression tree (BT) models, i.e. wavelet-BT (WBT), in estimating ET o values (through mass transfer parameters) in both coastal and island regions, where it is supposed that wind speed variations are affected by sea–inland interactions and so has the sharp variations (unlike ET o ). The obtained results showed that the coupled WBT model could improve the single BT model results to a great extent, and meanwhile, the Daubechies wavelet function with six vanishing moments provided the most accurate results in all the locations. Further, the best simulation outcomes with each wavelet function were obtained when the maximum possible decomposition level was used with each function.

Effect of etching and reduction time on the structure, performance, and stability of GO-based membrane for water purification

Holey graphene oxide (HGO) and reduced HGO membranes (rHGO) can overcome high tortuosity and poor stability of GO-based membranes, respectively. In this study, HGO and rHGO membranes were fabricated to try to quantitatively elucidate the etching and reduction time on structure, stability and rejection performance for slat and pharmaceuticals. Water flux of HGO membrane linearly increased (Jv=2.07t + 1.02, R2=0.9931) and Na2SO4 rejection linearly decreased (RNa2SO4=−4.37t + 88.26, R2=0.9511), while the membranes stability substantially increased with etching time from 1 to 5 h (water flux variation from 22% to 5% and rejection ratio variation from 17% to 7%) under long-term vibration . Subsequently, water flux of rHGO membranes exponentially decreased (Jv=exp(2.89–0.12t + 0.0039t2), R2= 0.9996) with reduction time, while slightly improved salt rejection (RNa2SO4=exp(2.89–0.12t + 0.0039t2), R2= 0.9971) were observed. Effective length of actual pathways for GO, HGO4 and rHGO4–5 membranes calculated by the mass transfer-based model was 7.37 ± 0.47, 4.48 ± 0.68 and 7.23 ± 1.29 µm, respectively, which were much higher than that geometric thickness of the GO membranes. These results indicated that d-spacing, tortuosity and porosity should be comprehensively considered for membrane design and fabrication. With a series of saccharides as probes, average pore size slightly decreased for HGO4 (rp=0.36 nm, Sp=0.34) and rHGO4–5 (rp=0.33 nm, Sp=0.28) membrane compared with GO membranes (rp=0.38 nm, Sp=0.3), demonstrating that etching and following reduction marginally affected the pore size distribution. H2O2 etching increased both water permeability (A) and its selectivity (A/B) for three pharmaceuticals, while the thermal reduction substantially decreased the water flux. Moderate and low rejection ratios for the three pharmaceuticals also demonstrated the importance of trade-off between etching and reduction time and the urgent need for narrowing pore-size distribution for GO-based membranes for water purification.

Ranking of Empirical Evapotranspiration Models in Different Climate Zones of Pakistan

Accurate estimation of evapotranspiration (ET) is vital for water resource development, planning and management, particularly in the present global warming context. A large number of empirical ET models have been developed for estimating ET. The main limitations of this method are that it requires several meteorological variables and an extensive data span to comprehend the ET pattern accurately, which is not available in most developing countries. The efficiency of 30 empirical ET models has been evaluated in this study to rank them for Pakistan to facilitate the selection of suitable models according to data availability. Princeton Global Meteorological Forcing daily climate data with a 0.25° × 0.25° resolution for 1948–2016 were utilized. The ET estimated using Penman–Monteith (PM) was considered as the reference. Multi-criteria group decision making (MCGDM) was used to rank the models for Pakistan. The results showed the temperature-based Hamon as the best model for most of Pakistan, followed by Hargreaves–Samani and Penman models. Hamon also showed the best performance in terms of different statistical metrics used in the study with a mean bias (PBias) of −50.2%, mean error (ME) of −1.62 mm and correlation coefficient (R2) of 0.65. Ivan showed the best performance among the humidity-based models, Irmak-RS and Ritch among the radiation-based models and Penman among the mass transfer-based models. Northern Pakistan was the most heterogeneous region in the relative performance of different ET models.

High-resolution thermography and modelling allows for improved characterization of drying sessile single droplets

Single droplet drying experiments help to understand droplet drying behavior during spray drying. In this study, high-resolution thermography and high-speed camera monitoring were used to characterize drying behavior of sessile single droplets containing solutes. Selected solutes were maltodextrin with a dextrose equivalent of 6, 21, and 38, whey protein isolate and galacto-oligosaccharide. A heat and mass transfer-based model was developed to describe the drying kinetics of the sessile droplets, assuming ideal shrinkage. This model accurately predicted the drying behavior of the droplets, including the droplet temperature during the constant rate period, the duration of this period, and the final droplet temperature. Remaining differences between measured and predicted droplet temperature are explained by skin formation and subsequent morphological development. Tracking temperature with thermography allows to more accurately follow and understand drying behavior, including morphology development of sessile droplets. It makes it possible to develop better models to translate the obtained insights to spray drying behavior.

Supercritical CO2 Extraction of High-Added Value Compounds from Chlorella vulgaris: Experimental Design, Modelling and Optimization.

Microalgae are well-known for their high-added value compounds and their recovery is currently of great interest. The aim of this work is the recovery of such components from Chlorella vulgaris through supercritical fluid extraction (SFE) with CO2. The effect of the extraction temperature (40–60 °C), pressure (110–250 bar), and solvent flow rate (20–40 g/min) was tested on yield, the extract’s antioxidant activity, and the phenolic, chlorophyll and carotenoid content. Thus, data analysis indicated that the yield was mainly affected by temperature, carotenoids by pressure, while the extract’s phenolics and antioxidant activity were affected by the synergy of temperature and pressure. Moreover, SFE’s kinetic study was performed and experimental data were correlated using Sovová’s mass transfer-based model. SFE optimization (60 °C, 250 bar, 40 g/min) led to 3.37% w/w yield, 44.35 mgextr/mgDPPH antioxidant activity (IC50), 18.29 mgGA/gextr total phenolic content, 35.55, 21.14 and 10.00 mg/gextr total chlorophyll, carotenoid and selected carotenoid content (astaxanthin, lutein and β-carotene), respectively. A comparison of SFE with conventional aq. ethanol (90% v/v) extraction proved SFE’s superiority regarding extraction duration, carotenoids, antioxidant activity and organoleptic characteristics of color and odor despite the lower yield. Finally, cosolvent addition (ethanol 10% w/w) at optimum SFE conditions improved the extract’s antioxidant activity (19.46%) as well as yield (101.81%).

Methods to estimate evapotranspiration in humid and subtropical climate conditions

Selecting appropriate reference evapotranspiration (ETo) methods is crucial for managing water resources efficiently. Statistical criteria commonly used to assess the performance of empirical ETo models on a station level may produce inconsistent results, making ranking approaches a complex process. This study was conducted in India's Humid and Subtropical region, considering 11 years of mean daily data from 2009 to 2019. We evaluated thirty empirical ETo models, which were categorized into four groups based on the input parameters, namely, temperature-based (10), radiation-based (10), mass transfer-based (9), and combination model (1). The results show that the observed ETo reached maximum magnitude during Monsoon followed by Spring, Summer, Autumn, Winter, and pre-Winter season; the average observed ETo from 2009 to 2019 was ≈ 1163 mm. Among temperature-based and radiation-based models, the Hargreaves model with RMSE of 1.45 mm/day and the Turc model with RMSE of 1.01 mm/day yielded the best ETo predictions under the humid, sub-tropical climate conditions. The radiation-based models demonstrate higher accuracy in the prediction of ETo than the temperature-based and mass transfer-based models. The FAO56-PM technique, Turc model, Hargreaves model, Makkink model, and Papadakis model were ranked as the five best models among all 30 tested models. Overall, the FAO56-PM method outperformed among all 30 selected models. Thus, the exact calculation of ETo is essential for many agricultural water engineering applications, particularly in developing countries with a lack of meteorological data records and limited resources to conduct long-term in-situ observation of evapotranspiration. The methodological approach proposed in this work applies to any other location for a simple yet rigorous evaluation of evapotranspiration empirically.

Hybrid particle swarm optimization with extreme learning machine for daily reference evapotranspiration prediction from limited climatic data

Accurate prediction of reference evapotranspiration (ETo) is pivotal to the determination of crop water requirement and irrigation scheduling in agriculture as well as water resources management in hydrology. In the present study, the particle swarm optimization (PSO) algorithm was utilized to optimally determine the parameters of the extreme learning machine (ELM) model, and a novel hybrid PSO-ELM model was thus proposed for estimating daily ETo in the arid region of Northwest China with limited input data. The PSO-ELM model was compared with the original ELM, artificial neural networks (ANN) and random forests (RF) models as along with six empirical models (including radiation-, temperature- and mass transfer-based empirical models). Three input combinations were utilized to develop the data-driven models, which corresponded to the radiation-, temperature- and mass transfer-based models, respectively. The results indicated that machine learning models provided more accurate ETo estimates, compared with the corresponding empirical models with the same inputs. The hybrid PSO-ELM model exhibited better performance than the other models for daily ETo estimation as indicated by the statistical results. Although radiation-based machine learning models outperformed temperature- and mass transfer-based machine learning models, the temperature-based PSO-ELM model obtained reasonable results when only air temperature data were available, which was considered as a promising model for forecasting future ETo with temperature data. Overall, the PSO-ELM model was superior to the other machine learning and empirical models, which was thus recommended to predict daily ETo with limited inputs in the arid region of Northwest China.

Assessment of different reference evapotranspiration models to estimate the actual evapotranspiration of corn (Zea mays L.) in a semiarid region (case study, Karaj, Iran)

In this study, an experiment was performed to assess and rank different evapotranspiration models. This was done to estimate the daily actual evapotranspiration of corn using a single (Kc-single) and dual (Kc-dual) crop coefficients in the semiarid climate of Karaj, Iran, in 2014. Daily evapotranspiration calculations using one combination-based model, one pan evaporation-based model, nine temperature-based models, ten radiation-based models, and seven mass transfer-based models were compared to the lysimeter measurements. Considering the single-crop coefficient, the Hargreaves-M3 model (RMSE = 1.89 mm/day) in the temperature-based models, the Caprio (1974) model (RMSE = 1.99 mm/day) in the radiation-based models, and the Albrecht (1950) model (RMSE = 4.33 mm/day) in the mass transfer-based models were ranked first place. Moreover, the Hargreaves-M2 model (RMSE = 0.88 mm/day) in the temperature-based models, the Caprio (1974) model (RMSE = 1.17 mm/day) in the radiation-based models, as well as the Albrecht (1950) model (RMSE = 3.76 mm/day) in the mass transfer-based models using the dual-crop coefficient, provided the most accurate estimation of daily corn evapotranspiration as compared to the lysimeter measurements.

Implementation of Spiegler⁻Kedem and Steric Hindrance Pore Models for Analyzing Nanofiltration Membrane Performance for Smart Water Production.

A predictive model correlating the parameters in the mass transfer-based model Spiegler–Kedem to the pure water permeability is presented in this research, which helps to select porous polyamide membranes for enhanced oil recovery (EOR) applications. Using the experimentally obtained values of flux and rejection, the reflection coefficient σ and solute permeability Ps have been estimated as the mass transfer-based model parameters for individual ions in seawater. The reflection coefficient and solute permeability determined were correlated with the pure water permeability of a membrane, which is related to the structural parameters of a membrane. The novelty of this research is the development of a model that consolidates the various complex mechanisms in the mass transfer of ions through the membrane to an empirical correlation for a given feed concentration and membrane type. These correlations were later used to predict ion rejections of any polyamide membrane with a known pure water permeability and flux with seawater as a feed that aids in the selection of suitable nanofiltration (NF) for smart water production.

Reference Evapotranspiration Variation Analysis and Its Approaches Evaluation of 13 Empirical Models in Sub-Humid and Humid Regions: A Case Study of the Huai River Basin, Eastern China

Accurate and reliable estimations of reference evapotranspiration (ET0) are imperative in irrigation scheduling and water resource planning. This study aims to analyze the spatiotemporal trends of the monthly ET0 calculated by the Penman–Monteith FAO-56 (PMF-56) model in the Huai River Basin (HRB), eastern China. However, the use of the PMF-56 model is limited by the insufficiency of climatic input parameters in various sites, and the alternative is to employ simple empirical models. In this study, the performances of 13 empirical models were evaluated against the PMF-56 model by using three common statistical approaches: relative root-mean-square error (RRMSE), mean absolute error (MAE), and the Nash–Sutcliffe coefficient (NS). Additionally, a linear regression model was adopted to calibrate and validate the performances of the empirical models during the 1961–2000 and 2001–2014 time periods, respectively. The results showed that the ETPMF increased initially and then decreased on a monthly timescale. On a daily timescale, the Valiantzas3 (VA3) was the best alternative model for estimating the ET0, while the Penman (PEN), WMO, Trabert (TRA), and Jensen-Haise (JH) models showed poor results with large errors. Before calibration, the determination coefficients of the temperature-based, radiation-based, and combined models showed the opposite changing trends compared to the mass transfer-based models. After calibration, the performance of each empirical model in each month improved greatly except for the PEN model. If the comprehensive climatic datasets were available, the VA3 would be the recommended model because it had a simple computation procedure and was also very well correlated linearly to the PMF-56 model. Given the data availability, the temperature-based, radiation-based, Valiantzas1 (VA1) and Valiantzas2 (VA2) models were recommended during April–October in the HRB and other similar regions, and also, the mass transfer-based models were applicable in other months.

Modelling Evapotranspiration to Increase the Accuracy of the Estimations Based on the Climatic Parameters

The potential evapotranspiration was estimated using different mass transfer-based models and was compared with the Food and Agriculture Organization Penman–Monteith model. The results showed that the Albrecht model estimates the potential evapotranspiration better than the other models in the most provinces of Iran (23 provinces). The best values of R 2 were 0.9854 and 0.9826 for the Brockamp–Wenner and Albrecht models in Bushehr (BU) and Tehran provinces, respectively. Finally, a list of the best performance of each model has been presented. The best weather conditions (not only for Iran but also for all countries) to use mass transfer-based equations are 23.6–24.6 MJ m−2 day−1, 12–26 °C, 18–30 °C, 5–21 °C, and 2.50–3.25 m s−1 (with the exception of Penman) for solar radiation, mean temperature, maximum temperature, minimum temperature, and wind speed, respectively. The results are also useful for selecting the best model when researchers must apply mass transfer (humidity)-based models on the basis of available data. In addition, the designed maps and categories are applicable for considering the role of climatic parameters in architectural evaluations over Iran.

Removal of pyridine from dilute aqueous streams using hollow fiber supported liquid membranes

The removal of pyridine from aqueous phase using hollow fiber supported liquid membranes has been investigated. Effect of several parameters such as feed concentration, extractant concentration, type of extractants, etc. has been studied. Organic solvents such as, 2-nonyl phenol (2-NP), 4-nonyl phenol (4-NP), stearic acid (SA), and di-(2-ethylhexyl) phosphoric acid (D2EHPA) were used as extractants. It was observed that the initial flux of pyridine increased with an increase in extractant concentration. The investigations showed that phenolic-based extractants (4-NP or 2-NP) were better for pyridine removal as compared to other extractants. The equilibrium experiments have been carried out by varying stirring speed and time in order to find the reaction kinetics and equilibrium time. Mass transfer-based model was used to explain the removal of pyridine for three different modules. Scale-up experiment shows nearly similar flux values of pyridine at both the scales. The model results were found to be in good agreement with the experimental observations. The results have been explained on the basis of steric effects, acidity of the extractant molecules along with the overall mass transfer resistance for the transport of pyridine.

Methyl Oleate Production in a Supported Sol–Gel Immobilized Lipase Packed Bed Reactor

A supported immobilized lipase was investigated as a suitable biocatalyst for the transesterification of triolein to methyl oleate in a packed bed reactor (PBR). The packing material for the bioreactor was comprised of lipase immobilized in sol–gel and supported on Celite (CSG). A kinetic- and mass transfer-based model was developed, incorporating a novel efficiency correlation to account for the effect of glycerol on the immobilized enzyme. Comparing the CSG PBR performance to that using a commercial lipase preparation (Novozym 435 (N435)), higher product conversion was achievable using CSG over a shorter time period, indicating the superior performance of CSG for enzymatic transesterification. A rate equation accounting for alcohol inhibition was used to compare the kinetics of the CSG and N435 PBRs. It was found that CSG exhibited a higher maximum reaction rate and was less prone to inhibition by methanol relative to N435. The resulting model showed good agreement with the experimental data, and CSG exhibited good stability without loss of activity over a five day period. This biocatalyst shows significant potential for the efficient production of biodiesel, and the mechanistic model developed has broader applications for similar enzyme and reaction systems.

Calibration of mass transfer-based models to predict reference crop evapotranspiration

The present study aims to compare mass transfer-based models to determine the best model under different weather conditions. The results showed that the Penman model estimates reference crop evapotranspiration better than other models in most provinces of Iran (15 provinces). However, the values of R2 were less than 0.90 for 24 provinces of Iran. Therefore, the models were calibrated, and precision of estimation was increased (the values of R2 were less than 0.90 for only ten provinces in the modified models). The mass transfer-based models estimated reference crop evapotranspiration in the northern (near the Caspian Sea) and southern (near the Persian Gulf) Iran (annual relative humidity more than 65 %) better than other provinces. The best values of R2 were 0.96 and 0.98 for the Trabert and Rohwer models in Ardabil (AR) and Mazandaran (MZ) provinces before and after calibration, respectively. Finally, a list of the best performances of each model was presented to use other regions and next studies according to values of mean, maximum, and minimum temperature, relative humidity, and wind speed. The best weather conditions to use mass transfer-based equations are 8–18 °C (with the exception of Ivanov), <25.5 °C, <15 °C, >55 % for mean, maximum, and minimum temperature, and relative humidity, respectively.

Application of new mass transfer formulae for computation of evapotranspiration

This study aims to compare mass transfer-based models to detect the best model under different weather conditions. For this purpose, weather data were gathered from 181 synoptic stations in 31 provinces of Iran. The reference crop evapotranspiration was estimated using 11 mass transfer-based models and was compared with the FAO Penman–Monteith model. The results showed that the Penman model estimates the reference crop evapotranspiration better than other models in the most provinces of Iran. However, the values of R2 were less than 0.90 for 24 provinces of Iran. Therefore, the models were calibrated using new formulae and preciseness of estimation was increased. The mass transfer-based models estimated the reference crop evapotranspiration in the eastern provinces (desert regions) of Iran better than other provinces. The best values of R2 were 0.96 and 1.00 for Trabert and Penman models in AR and TE, KE, and YA provinces before and after calibration, respectively.

A mass transfer model for predicting emission of the volatile organic compounds in wet building materials

A new mass transfer model is developped to predict the volatile organic compounds (VOCs) from fresh wet building materials. The dry section of wet materials during the process of VOC emission from wet building materials is considered in this new model, differing from the mass transfer-based models in other literatures. The mechanism of effect of saturated vapor pressure on the surface of wet building materials in the process of VOC emission is discussed. The concentration of total volatile organic compounds (TVOC) in the building materials gradually decreases as the emission of VOCs begins, and the vapor pressure of VOCs on the surface of wet building materials decreases in the case of newly wet building materials. To ensure the partial pressure of VOCs on the surface of wet building materials to be saturated vapor pressure, the interface of gas-wet layer is lowered, and a dry layer of no-volatile gases in the material is formed. Compared with the results obtained by VB model, CFD model and the experiment data, the results obtained by the present model agree well with the results obtained by CFD model and the experiment data. The present model is more accurate in predicting emission of VOC from wet building materials than VB model.

A general model for analyzing single surface VOC emission characteristics from building materials and its application

A new and generally applicable model for calculating the surface emissions of volatile organic compounds (VOCs) from single-layered, dry building materials and the VOC instantaneous distributions in the materials is developed. Different from the mass transfer-based models in the literature, the new model does not neglect the mass transfer resistance through the air phase boundary layer and does not assume that the initial VOC concentration distribution (C0) in the building materials is uniform. And this paper provides an analytical solution for this model. For the specific case that C0 is uniform, the proposed model is validated with experimental data. Using different distribution of initial VOC concentration in building materials, the influence of initial VOC concentration on VOC emission characteristics is clarified: the influence of initial distribution on emission characteristics decreases with increasing time. When time is less than tc (critical time of early stage), the influence is strong and should be considered. After that period, such influence can be neglected. tc is mainly influenced by L and D. For the long-term emission prediction cases that the material thickness is relatively small and the diffusion coefficient is relatively large (larger than 10−11 m2/s), it would be justified to neglect the effect of initial VOC concentration distribution on emission characteristics. The model would be useful to estimate the emission characteristics of building materials.

Bioavailability of Mixtures of PAHs Partitioned into the Micellar Phase of a Nonionic Surfactant

Recent work has shown that a fraction of a contaminant solubilized in the micellar phase of some nonionic surfactants is directly available for biodegradation, meaning that the contaminant can be transferred directly from the core of the micelle to cell without having to transfer to the water phase first. This study extends the understanding of the bioavailability of the micellar phase for a single compound to a multicomponent system of contaminants. Biodegradation experiments were conducted with binary and ternary mixtures of naphthalene, phenanthrene, and pyrene in the presence of a nonionic surfactant, Triton X-100. A mixed bacterial culture, isolated and enriched from a PAH-contaminated soil at the Wurstsmith Air Force Base, MI, was used for the biodegradation experiments. In the absence of the surfactant and at surfactant concentrations below cmc, the multisubstrate Monod kinetics adequately simulated the biodegradation kinetics of the binary and ternary mixtures. In the multicomponent systems, as in single solute systems, the solutes in the micelle were found to be directly bioavailable, and the bioavailability of each compound in the micellar phase decreased with increasing surfactant concentration. For a given surfactant concentration, the bioavailability was higher for the lower molecular weight PAHs. There was little difference in the bioavailability of the same compound as a single solute or in different binary and ternary mixtures. To predict the bioavailability of the micellar phase substrates, a mass transfer-based model was formulated that describes the transfer of substrate from the micellar phase to the microorganisms. The predictions matched the experimental observations well, indicating the validity of the model and its potential for applications in remediation designs.