Dr. Yiwen Zhou

Measurements have been made at P-band (0.707 GHz) to construct a model for the dielectric constant of sea water and extend the model for the dielectric constant to high salinity (S > 50 pss). The measurements are part of research to develop a model for the dielectric constant suitable for future wide-bandwidth remote sensing of salinity and for application to water bodies such as the Great Salt Lake with salinity significantly above that found in the open ocean. Measurements have been made at temperatures from 2 to 30 °C and salinity from 0 to 138 pss. The data have been fit to a Debye model for the dielectric constant with a single relaxation mode as has been employed at L-band (1.413 GHz) where remote sensing of salinity is currently done. Comparison with contemporary models developed from data at L-band indicates that the L-band model and new P-band model do well at both frequencies for salinity less than 50 pss but at higher values of salinity the L-band models diverge from the data. The data has also been used to test at high salinity the mathematical relationship between salinity and conductivity which is the basis for the practical salinity scale pss.

The dependence of L-band Vegetation Optical Depth (L-VOD, τ) on Vegetation temperature T_V is investigated for 1165 boreal forest grid cells selected for latitudes > 55° and high radiometric forest fraction FFO ≥ 90%. SMOS Level-3 Brightness Temperatures (BT) at ascending orbits acquired from 2011 to 2022 are used. This is a spatio-temporal extension of our previous study on τ(T_V) made over the "Sodankylä grid cell" (Finland) in 2019. It demonstrated the Electromagnetic (EM) reasons for τ(T_V) reaching maximum at 0°C and decreasing when T_V is moving away from 0°C. The parameterisation of the "L-VOD model" developed in the previous study is simplified and updated to take into account the conservation of salt in sap-water during freezing. The "forward operator" based on the Two-Stream Microwave Emission Model (2S-MEM) is inverted to retrieve τ_SMOS(T_V) together with effective Ground permittivities ε_G during seasonal Warming Periods (WPs) determined from ERA-interim air temperatures. The "L-VOD model" parameters (T_meltWC_wood) are estimated for the boreal forest grid cells by minimizing squared differences between τ_SMOS(T_V) and simulated τ_sim(T_V). The vegetation melt-parameter T_melt represents the "number of degrees below 0°C" at which sap-water melts, and WC_wood is the gravimetric wood-Water Content of branches. Reasonable values of T_meltWC_wood are achieved for a majority of the boreal forest grid cells. It is found that T_melt tends to be too high over Northern Europe, a region with longer WP durations compared to other regions of the boreal forest belt. By optimising the scattering albedo used to retrieve τ_SMOS(T_V), the correlations between τ_sim(T_V) and τ_SMOS(T_V) can be increased, thereby improving the reliability of T_meltWC_wood. The results raise the possibility of an alternative method to parameterise the scattering albedo of boreal forests by means of the reality-based nature of τ_SMOS(T_V) associated with the consistency of T_melt with expected values. The study also shows that estimating the Above-Ground Biomass (AGB) of boreal forests using L-VOD must take into account the reduction in L-VOD due to the EM-reasons resulting from freezing sap-water in wooden branches, which dominate the radiative transfer at L-band.

The range of salinity and temperature measurements used to develop models for the dielectric constant of sea water have in the past been limited to values appropriate for the open ocean. But there are important water bodies such as the Great Salt Lake in Utah with salinities much larger than those encountered in the open ocean. Extrapolating existing models to values of salinity beyond the limits of the data used to create the model can result in unrealistic predictions in remote sensing applications. This can be prevented by using a model for conductivity based on the definition of salinity and ensuring that polynomials used to model the other unknown parameters result in bounded behavior at high salinity. New laboratory measurements with high salinity (up to 150 pss) are reported and used to test a model with these adjustments.

Numerous adsorbents have been applied for Heavy Metals (HMs) removal from contaminated water. The aim of this review was to critically analyze the status of research in HMs detection and adsorption, focusing on the adsorption approaches for better defining the corresponding future challenges and their potential solutions. Present research demonstrates the promising outlook for using remote sensing technology in the preliminary selection of contaminated areas before final HMs detection using spectrometry, microwave or electrochemical sensors. Adsorption can then be applied in treating HMs contaminated water due to its high effectiveness and low-cost. Natural zeolites showed 90 %–100 % Pb²⁺, 95 % Cd²⁺ and 100 % Cu²⁺ removal from water, their effectiveness is affected by initial pH, and adsorbent dosage and size. As synthesized zeolites, zeolitized pumice waste showed 100–500 mg/g of HMs adsorption at pH 4.0–5.0, 57 mg/g Zn²⁺ by oxalate-loaded zeolites and 682 mg/g Pb²⁺ and 122 mg/g Ni²⁺ by zeolite nanoparticle impregnated polysulfone membrane from wastewater. Activated carbon exhibited 99 %–100 % Hg²⁺, 93 % Cu²⁺ and 99 % Co²⁺ removal from water under acidic environment. Biochar is more ecofriendly and demonstrated its effectiveness in removing up to 98 % Cd²⁺, 97 % Cu²⁺, 99 % Pb and 94 % Zn²⁺ from water. Chitosan showed 755 mg/g Pb²⁺, 979 mg/g Cd²⁺ and 877 mg/g Cu²⁺ removal at pH 2.0–6.0 from wastewater. Peat moss exhibited 96 % Cu²⁺ and 50 % Cr⁶⁺ removal from wastewater at lower pH. Similarly, bioremoval showed 143 mg/g Zn²⁺ (algae) adsorption at pH 6.0 in, and 90 % Cr⁶⁺ and 98 % Cu²⁺ removal by biomass ash. Recently, carbon, magnetic and titanium nanotubes/composites have shown high efficiency and selectivity in HMs removal, but their preparation is often more expensive than their counterparts. In addition, adding enhancement solutions promoted HMs adsorption and reduced treatment time. Chemical precipitation demonstrated feasibility to recycle and recover extracted HMs and spent adsorbent. This review demonstrates the need for highly selective and efficient adsorbent, and guides the future researchers to make funtionalized and organic-inorganic composite HMs adsorbents.

A physics-based microwave emission model for layered vegetation (MEMLV) is developed to simulate the vegetation optical depth (VOD) and scattering albedo of coniferous forests from P- to Ka-band (0.4 GHz-37 GHz). This theoretical study aims to use physics-based forward modelling to guide and support multi-frequency VOD retrieval. The MEMLV consists of three major components: (i) the single-layer discrete scatter model (SL-DSM) that calculates the VOD and single scattering albedo of a single layer, (ii) a new Tree Structure Model (TSM) that represents forests by stratified multi-layer media, and (iii) the Two-Stream microwave emission model (2S-MEM) that combines SL-DSM and TSM to calculate the brightness temperature of forests and their corresponding effective VOD, τ_eff, and effective scattering albedo, ω_eff. Simulation of an exemplary coniferous forest shows that τ_eff increases as frequency increases until reaching saturation at K-band. Meanwhile, ω_eff increases rapidly at low frequencies until reaching a peak at S-band, then decreases until at X-band, and finally increases monotonically as frequency increases. Notably, ω_eff is negligible at P-band for most cases. Sensitivity analyses demonstrate the saturation of τ_eff when canopy height is substantial, and the decreasing trend of ω_eff as canopy height or the areal fraction of canopy gap increases. The MEMLV has the potential to improve the parameterization of retrieval algorithms and to enhance the understanding of the retrieved VOD over a wide frequency range.

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the reliability of the dielectric constant model. Two new parametrizations were recently developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements by Boutin et al. (2021) (BV), and on the other hand, on new George Washington University laboratory measurements by Zhou et al. (2021) (GW2020). These two approaches are fully independent. For most SSS and Sea Surface Temperature (SST) conditions commonly observed over the open ocean, the relative variations of brightness temperatures Tb simulated through the BV and GW2020 parametrizations agree particularly well, and better than with earlier parametrizations previously used in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Nevertheless, uncertainty remains, especially below 10 °C where a ∼ 0.1 K relative difference between the two models is observed. This motivates the development of a revised parameterization, BVZ, based on a methodology similar to that used to derive BV but using GW2020 instead of SMOS measurements. Compared to the GW2020 parameterization, BVZ is derived with a reduced number of degrees of freedom, it relies on the TEOS10 PSS78 conductivity-salinity relationship, and on the previously derived static permittivity of fresh water. One month per season of SMOS data have been reprocessed in 2018 using BV, GW2020, and BVZ. We find the best overall agreement between SMOS SSS and Argo SSS with BVZ parametrization, with noticeable improvement in the 5 °C-15 °C SST range.

This paper is concerned with the accurate measurement of the dielectric constant of seawater at P band. The measurement of seawater salinity at L band (1.414 GHz) by satellite becomes less accurate as the seawater temperature decreases. At lower frequencies such as 707 MHz, the sensitivity to salinity of the radiometer measurements increases. Designers of P band radiometers for ocean sensing will need to know how the dielectric constant of seawater varies with salinity (S) and temperature (T). To determine this relationship, a P band cavity, based on an L band design, has been constructed. Initial measurements are made at S=35 psu and T= 10°, 20°, 30°C. The results are compared with the values obtained from L band models evaluated at P band (f=707MHz.). The model predictions are close to the measurement results.

Accurate knowledge of the dielectric constant of sea water is important for remote sensing of surface parameters such as sea surface temperature (SST) and sea surface salinity (SSS). The advent of sensors in space, SMOS [1] , Aquarius [2] and SMAP [3] capable of measuring SSS motivated modern measurements [4] , [5] and modelling [5] , [6] of the dielectric constant at L-band (1.4 GHz). In the past, the range of salinity included in the data used to create these models has been restricted to values typically encountered in the open ocean (e.g., less than 40 psu). However, there are many smaller water bodies with much higher salinity. Notable examples are the Great Salt Lake in Utah with salinity on the order of 180 psu and Garabogazköl lagoon in Turkmenistan with even higher salinity. Unfortunately, existing models for the dielectric constant can't necessarily just be extended to higher values of salinity. The problem is that the polynomials in salinity and temperature used to represent the unknown parameters in the models are not constrained outside the range of SSS and SST used to determine their coefficients. While the models for the dielectric constant may be very good within that range, outside that range they can lead to unrealistic behavior. Research is underway to develop a model that represents the dielectric constant well over the ocean and behaves well at high salinity. In preparation for possible wideband remote sensing of salinity [7] , [8] , [9] , the laboratory measurements made at 1.413 GHz [4] , [5] are being repeated at 0.707 GHz (P-band) and the plan is to include values of high salinity (50, 100, 150 psu).

This study focuses on modelling the scattering albedo of a vegetation canopy, which can be used in vegetation opacity depth (VOD) retrieval, over a wide frequency range (1-37 GHz). In this study, boreal tree canopy has been used as an example. A discrete scatter model has been implemented to calculate single scattering albedo and vegetation opacity depth (VOD) of a single-layer canopy consisting of a variety type of scatterers. For a more realistic parameterization, a novel tree structure model has been developed to quantify the vertical structure of a forest. For the first time, we combined the discrete scatter model with the multi-layer 2Stream model to calculate the brightness temperature of the tree canopy based on its vertical structure. This research provides a comprehensive forward modelling tool that can be parameterized with different vegetation types (e.g. tree, crops and grass) and parameters (e.g. height, density, soil condition and vertical water content distribution). The model can be used in retrieval algorithm to find effective scattering albedo and VOD over a wide range of frequencies.

This manuscript reports an improvement in the model for the dielectric constant of seawater used to fit laboratory measurements of the dielectric constant at L-band. The new model (dielectric constant as a function of salinity, temperature and frequency) is based on the response of a polar molecule proposed by Debye and fits the same measurement as reported in earlier work, but uses a functional form for conductivity, σ(S,T), that is given by the definition of salinity. The new version of this model fits the data well and has the advantages that the relaxation time constant is allowed to be a function of temperature and salinity and is well behaved when extrapolated to high salinities.

The model expressing the dielectric constant of sea water at microwave frequencies as a function of salinity and temperature is an important element in remote sensing of sea surface salinity. It is also important independently as a description of the physical properties of salt water. A major milestone was the development in the late 1970’s by Klein and Swift of a model based on laboratory measurements at L- and S-band and a functional form supported by theory for polar molecules and previous work on freshwater. Much of the subsequent work has focused on measurements at higher frequency and determining model parameters tuned to apply for applications such as remote sensing of sea surface temperature. Interest in the dielectric constant at 1.4 GHz (L-band) increased again with the development of SMOS and Aquarius to measure salinity from space. But there have been few new measurements at L-band and often confusion regarding the applicability of new models at 1.4 GHz. The objective of this manuscript is to compare available models in the context of how well they represent the dielectric constant of sea water at 1.4 GHz. Among the criteria applied will be the recent measurements at the George Washington University of the dielectric constant at 1.4 GHz.