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Endocrine disrupting compounds (EDCs) need to be removed by efficient treatment methods as they are a major concern for both human and environmental health. To reduce the impact of EDCs in water, this review examines the use of ultrasonic degradation processes. Following an overview of EDCs and their origins, the basic concepts of sonochemistry are examined, highlighting the potential of ultrasound in chemical reactions. An in-depth analysis of the variables that affect the ultrasonic degradation of EDCs, such as frequency, intensity/power, temperature and solution chemistry, prepares the reader for a case study investigation focusing on specific EDCs. The study also looks at synergistic methods, emphasizing how hybrid ultrasonic systems can improve removal efficiency. The study provides a comprehensive overview of the use of sonochemistry in the treatment of EDCs by addressing current issues and suggesting future research directions. The aim of this review paper is to provide insightful analysis and useful suggestions for scientists working on EDC remediation projects.

It is a well-known fact that water bodies are crucial for human life, ecosystems and biodiversity. Therefore, they are subject to regulatory monitoring in terms of water quality. However, land-use intensification, such as open-cast mining activities, can have a direct impact on water quality. Unfortunately, in situ measurements of water quality parameters are spatially limited, costly and time-consuming, which is why we proposed a combination of hyperspectral data, in situ data and simple regression models in this study to estimate and thus monitor various water quality parameters. We focused on the variables of total iron, ferrous iron, ferric iron, sulphate and chlorophyll-a. Unlike other studies, we used a combination of airborne hyperspectral and RGB data to ensure a very high spatial resolution of the data. To investigate the potential of our approach, we conducted simultaneous in situ measurements and airborne hyperspectral/RGB aircraft campaigns at different sites of the Spree River in Germany to monitor the impact of pyrite weathering on water bodies after open-cast mining activities. Appropriate regression models were developed to estimate the five variables mentioned above. The model with the best performance for each variable gave a coefficient of determination R2 of 64% to 79%. This clearly shows the potential of airborne hyperspectral/RGB data for water quality monitoring. In further investigations, we focused on the use of machine learning techniques, as well as transferability to other water bodies. The approach presented here has great potential for the development of a monitoring method for the continuous monitoring of still waters and large watercourses, especially given the freely available space-based hyperspectral missions via EnMAP. [ABSTRACT FROM AUTHOR]

A growing coastal population is leading to increased anthropogenic pollution that greatly affects coastal and inland water bodies, especially in the tropics. The Sustainable Development Goal-14, 'Life below water' emphasises the importance of conservation and sustainable use of the ocean and its resources. Pollution management practices often include monitoring of water quality using in situ observations of chlorophyll-a (chl-a) and total suspended matter (TSM). Satellite technology, including the MultiSpectral Instrument (MSI) sensor onboard Sentinel-2, enables the continuous monitoring of these variables in inland waters at high spatial and temporal resolutions. To improve the monitoring of water quality in the tropical Vembanad-Kol-Wetland (VKW) system, situated on the southwest coast of India, we present two regionally tuned satellite algorithms developed to estimate chl-a and TSM concentrations. The new algorithms estimate the chl-a and TSM concentrations from the simulated reflectance values as a function of the inherent optical properties using a forward modelling approach. The model was parameterised using the National Aeronautics and Space Administration (NASA) bio-Optical Marine Algorithm Dataset (NOMAD) and in situ measurements collected in the VKW system. To assess model performance, results were compared with in situ measurements of chl-a and TSM and other existing satellite-based models of chl-a and TSM. For satellite application, two different atmospheric correction methods (ACOLITE and POLYMER) were tested and satellite matchups were used to validate the new chl-a and TSM algorithms following standard validation procedures. The results demonstrated that the new algorithms were in good agreement with in situ observations and outperform existing chl-a and TSM algorithms. The new regional satellite algorithms can be used to monitor water quality within the VKW system to support the sustainable management under natural (cyclones, floods, rainfall, and tsunami) and anthropogenic pressures (industrial effluents, agricultural practices, recreational activities, construction, and demolishing concrete structures) and help achieve Sustainable Development Goal 14. [ABSTRACT FROM AUTHOR]

The Landsat data archive provides a unique opportunity to investigate the long-term evolution of coastal ecosystems at fine spatial scales that cannot be resolved by ocean colour (OC) satellite sensors. Recognizing Landsat's limitations in applications over coastal waters, we have launched a series of field campaigns in Boston Harbor and Massachusetts Bay (MA, USA) to validate OC products derived from Landsat-8. We will provide a preliminary demonstration on the calibration/validation of the existing OC algorithms (atmospheric correction and in-water optical properties) to enhance monitoring efforts in Boston Harbor. To do so, Landsat optical images were first compared against ocean colour products over high-latitude regions. The in situ cruise data, including optical data (remote sensing reflectance) and water samples were analyzed to obtain insights into the optical and biogeochemical properties of near-surface waters. Along with the cruise data, three buoys were deployed in three locations across the Harbor to complement our database of concentrations of chlorophyll a, total suspended solids (TSS), and absorption of colour dissolved organic matter (CDOM). The data collected during the first year of the project are used to develop and/or tune OC algorithms. The data will be combined with historic field data to map in-water constituents back to the early 1990's. This paper presents preliminary analysis of some of the data collected under Landsat-8 overpasses. [ABSTRACT FROM AUTHOR]

Obtaining and analyzing the specific inherent optical properties (SIOPs) of water bodies is necessary for bio-optical model development and remote sensing-based water quality retrievals and, further, for related ecological studies of aquatic ecosystems. This study aimed to measure and analyze the specific absorption and backscattering coefficients of the main water constituents in Poyang Lake, China. The specific absorption and/or backscattering coefficients of the main water constituents at 85 sampling sites (47 in 2010 and 38 in 2011) were measured and analyzed as follows: (1) the concentrations of chlorophyll a ( C), suspended particulate matter ( C) (including suspended particulate inorganic matter ( C) and suspended particulate organic matter ( C)), and the absorption coefficients of total particulate ( a), phytoplankton ( a), and non-pigment particulate ( a) were measured in the laboratory; (2) the total backscattering coefficients at six wavelengths of 420, 442, 470, 510, 590, and 700 nm, including the contribution of pure water, were measured in the field with a HydroScat-6 backscattering sensor, and the backscattering coefficients without the contribution of pure water ( b) were then derived by subtracting the backscattering coefficients of pure water from the total backscattering coefficients; (3) the specific absorption coefficients of total particulate ( $$ a_{\mathrm{p}}^{ * } $$), phytoplankton ( $$ {a_{{\mathrm{ph}}}}^{ * } $$), and non-pigment particulate ( $$ a_{\mathrm{d}}^{ * } $$) were calculated by dividing a, a, and a by C, C, and C, respectively, while the specific backscattering coefficients of total suspended particulate matter ( $$ b_{\mathrm{b}}^{ * } $$) were calculated by dividing b by C; and (4) the $$ {a_{{\mathrm{ph}}}}^{ * } $$, $$ a_{\mathrm{d}}^{ * } $$, $$ a_{\mathrm{p}}^{ * } $$ and $$ b_{\mathrm{b}}^{ * } $$ of the remaining samples (46 in 2010 and 36 in 2011) were visualized and analyzed, and their relations to C, C or C were studied, respectively. The main results are summarized as follows: (1) the $$ {a_{{\mathrm{ph}}}}^{ * } $$ values at 440 nm were 0.0367-0.7203 m mg with a mean of 0.1623 ± 0.1426 m mg in 2010 and 0.0319-0.7735 m mg with a mean of 0.3145 ± 0.1961 m mg in 2011; there existed significant, negative, and moderate correlations between $$ {a_{{\mathrm{ph}}}}^{ * } $$ and C at 400-700 nm in 2010 and 2011 ( p < 0.05); (2) The $$ a_{\mathrm{d}}^{ * } $$ values at 440 nm were 0.0672-0.2043 m g with a mean of 0.1022 ± 0.0326 m g in 2010 and 0.0559-0.1347 m g with a mean of 0.0953 ± 0.0196 m g in 2011; there existed negative correlations between $$ a_{\mathrm{d}}^{ * } $$ and C, while the correlations showed overall decreasing and increasing trends before and after around 575 nm with increasing wavelengths, respectively; (3) The $$ a_{\mathrm{p}}^{ * } $$ values at 440 nm were 0.0690-0.1929 m g with a mean of 0.1036 ± 0.0298 m g in 2010 and 0.0571-0.1321 m g with a mean of 0.1014 ± 0.0191 m g in 2011, and the negative correlations between $$ a_{\mathrm{p}}^{ * } $$ and C were found in both years; (4) The $$ b_{\mathrm{b}}^{ * } $$ at the six wavelengths generally decreased with increasing wavelengths, while the $$ b_{\mathrm{b}}^{ * } $$ values at 420 nm were lower than those at 442 nm for some samples; the correlation between $$ b_{\mathrm{b}}^{ * } $$ and C increased with increasing wavelength. Such results can only represent the SIOPs during the sampling time periods, and more measurements and analyses considering different seasons need to be carried out in the future to comprehensively understand the SIOPs of Poyang Lake. [ABSTRACT FROM AUTHOR]

Monitoring coastal and inland waters, recognized as case II waters, using the existing Landsat technology is somewhat restricted because of its low signal-to-noise ratio (SNR) and its relatively poor radiometric resolution. The new generation of Landsat, Landsat Data Continuity Mission (LDCM) carrying the Operational Land Imager (OLI), has enhanced features allowing for a more lucid characterization of water constituents in either coastal or inland waters with respect to Landsat-7 (ETM+). This paper applies a physics-based approach to fully examine the potential of OLI in terms of its enhanced features in a water constituent retrieval framework. An EO-1 dataset, including Hyperion and the Advanced Land Imager (ALI), together with nearly coincident ETM+ imagery were atmospherically corrected using a data-driven approach. An in-water radiative transfer model, i.e., Hydrolight, was applied to generate a Look-Up-Table (LUT) of simulated surface reflectances for various combinations of water constituents. Using the Hyperion-derived concentration maps as validation sources, it was found that the simulated OLI imagery is superior to ETM+ on the order of 40%, 20%, and 28% when retrieving the concentrations of chlorophyll-a and total suspended solids (TSS), as well as the absorption of the colored dissolved organic matter (CDOM), respectively. It was also demonstrated that the simulated OLI imagery outperforms the simulated ALI and the recorded ALI datasets in the retrieval of chlorophyll-a and CDOM absorption. It is concluded that the new generation of Landsat enables mapping and monitoring of case II waters with accuracies not achieved with the previous Landsat satellite series. [ABSTRACT FROM PUBLISHER]