Optical Properties Of Water Research Articles

Decline of suspended particulate matter concentrations in Lake Taihu from 1984 to 2020: observations from Landsat TM and OLI.

Suspended particulate matter (SPM) affects the optical properties of water, which can be used as a marker of water quality. The water quality of Lake Taihu has changed immensely since the 1980's. However, despite the link between water quality and SPM, long-term systematic studies on SPM have not been conducted in this lake. Here, we used Landsat-5 TM and Landsat-8 OLI data to model changes in the SPM concentration of Lake Taihu from 1984 to 2020. Various models were generated, calibrated, and finally validated using in situ SPM, remote sensing reflectance (Rrs) data, and synchronous satellite data. After comparing various commonly used models, it was found that the exponential model based on band combination [Rrs(red) + Rrs(NIR)/Rrs(green)] had the highest accuracy, with an average unbiased relative error greater than 35%. Subsequently, the SPM products of Lake Taihu during 1984-2020 were generated. Overall, the SPM concentration showed a downward trend over the study period, which might be primarily attributable to a decline in wind speed. These findings may assist in the conservation of Lake Taihu and its associated water resources.

Investigation on Reinforcement Effects of Nanocellulose on the Mechanical Properties, Water Absorption Capacity, Biodegradability, Optical Properties, and Thermal Stability of a Polyvinyl Alcohol Nanocomposite Film

This paper presents the reinforcement of nanocellulose (NC) in polyvinyl alcohol (PVA) to examine the effect of the amount of reinforcement on the properties of PVA. The nanocellulose was successfully extracted by sulfuric acid hydrolysis method and ultrasonication, and successively reinforced with polyvinyl alcohol by the solvent-casting method. After incorporating nanocellulose into the PVA matrix, the effect of nanocellulose on the tensile strength, elongation at break, water absorption capacity, transmittance, thermal stability, and biodegradability of PVA was investigated. The tensile strength increased from 24.5 ± 0.53 MPa to 35.5 ± 0.55 MPa and 40.6 ± 0.73 MPa with the addition of 2%NC and 5%NC, respectively. The elongation at break increased from 40 ± 0.53 % to 45.7 ± 0.53 % with 2%NC, and after the reinforcement of 7%NC, it decreased to 32.2 ± 0.75 % . The water absorption capacity result reveals that neat PVA absorbs the highest amount of water which is 84.6 ± 0.56 % and is reduced to 73 ± 0.78 % by adding 2%NC. By increasing the nanocellulose loading to 7%, the water intake capacity was reduced to 61 ± 0.59 % which illustrates the water intake was reduced linearly with the increment of NC. The ultraviolet-visible (UV-Vis) result implies that the transmittance of neat PVA and PVA-2%NC composite film was 85.4% and 78.2% at 600 nm, respectively, which indicates the decrement in transmittance. The thermogravimetry analysis (TGA) reveals that the thermal stability of polyvinyl alcohol after incorporating nanocellulose particles was reduced. The weight loss of neat PVA is 70.7 ± 1.7 % after 90 days while the weight loss of the PVA composite films reinforced with 1%, 3%, 5%, 7%, and 9% was 65 ± 1.85 % , 57 ± 1.57 % , 55.6 ± 0.64 % , 52 ± 1.73 % , and 53.1 ± 1.72 % , respectively. The scanning electron microscopy micrograph for the PVA-6%NC nanocomposite film reveals a dispersion of nanocellulose in a matrix.

An optical water classification and quality control model (OC_QC model) for spectral diffuse attenuation coefficient

Spectral diffuse attenuation coefficient of down-welling irradiance (Kd(λ)) is a fundamental optical parameter for water color and of significance for heat budget calculation, photosynthesis modeling and carbon sequestration. Uncertainties exist in both in situ measured and satellite derived Kd(λ), therefore, evaluation of its data quality is essential. In addition, optical water classification of Kd(λ) is still limited. To address these issues, we proposed an optical water classification and quality control model (OC_QC model) based on a globally collected high-quality in situ Kd(λ) data. The model consists of the reference Kd(λ) spectra for 7 optical water types (OWT, ranging from clear open ocean water to highly turbid water) and a scoring system. An individual Kd(λ) spectrum can be assigned an OWT and quality control score (QC score) with this model. The performance of the OC_QC model is tested with independent in situ Kd(λ) spectra from the turbid coastal water (Bohai Sea) and clear oceanic water (Indian Ocean). Questionable or erroneous Kd(λ) spectra can be identified, suggesting the model’s robustness. The model was also evaluated with the Medium Resolution Imaging Spectrometer (MERIS) Level-2 and the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-3 Kd(λ) data in the Bohai Sea, Yellow Sea, East China Sea and South China Sea. Satellite derived maps clearly showed the spatial and temporal variations of OWTs and QC scores, and the regions of low-quality Kd(λ) were reasonably extracted. Global maps of Kd(λ)-based optical water types and corresponding QC scores were also obtained with OC_QC model. With the quality controlled Kd(λ) data, the retrieval accuracy of Secchi disk depth was improved. The retrieval accuracies of Chlorophyll-a concentration and total seawater absorption coefficient were also improved with the Kd(λ) optical water classification based algorithms. The OC_QC model would be valuable for evaluating Kd(λ) data (especially the operational global Kd(λ) products), investigation of water optical properties, and development and merging of bio-optical algorithms.

Identification of the best model to predict optical properties of water

Identification of the best model to predict optical properties of water

Measurement of in-vivo spectral reflectance of bottom types: Implications for remote sensing of shallow waters

Field spectroscopy data serve as a standard for the inter-comparisons, calibration and validation of remote sensing data. It also greatly assists in the detection, characterization and mapping of the earth features from the satellite imagery. Strategies and methods for field-based spectro-radiometric measurements are well-established for land and deep ocean applications, however, there are certain challenges and limitations with respect to the shallow water coastal ecosystems. This paper focuses on the background theory, concepts, and measurement techniques of in-vivo sensing of benthic reflectance in shallow water environment. We investigated various measurement methods, influences of water column, air–water interface, sources of errors (introduced by experimental and environmental factors), and the correction methods that are involved in the determination of benthic substrate reflectance. Special emphasis is provided using in-vivo measurements made in the estuarine and shelf regions, illustrating the benthic substrate reflectance at various platforms, i.e., within the water column, above the water surface, at the top-of-atmosphere, in the air, and in a controlled (laboratory) environment. As part of the correction procedure, a new water column correction method is theoretically formulated and examined for varying water optical properties and water depth. A new step correction method is also developed (based on the additive approach) to correct the spectral reflectance measured by a full range spectroradiometer (350–2500 nm) that is in-built with two or more detectors. This study will have direct implications for improving the data quality of field-based spectro-radiometric measurements that are essential for shallow water remote sensing applications.

Leveraging DOM UV absorbance and fluorescence to accurately predict and monitor short-chain PFAS removal by fixed-bed carbon adsorbers

Carbon adsorbent fouling by dissolved organic matter (DOM) inhibits the ability of the widely-used rapid small-scale column test (RSSCT) to accurately predict the removal of organic micropollutants (OMP) from water by full-scale carbon adsorbers. Here, the adsorption of 11 short-chain per-/poly-fluoroalkyl substances (PFAS) from groundwater, surface water, and wastewater was examined in pilot columns as well as RSSCTs using constant diffusivity (CD) and proportional diffusivity (PD) designs. Neither the CD- or PD-RSSCT accurately predicted pilot adsorber breakthrough of PFAS using standard diffusional mass transfer models. However, PFAS breakthrough relative to optical property (e.g., peak C, UV absorbance at 254 nm) breakthrough remained constant between pilot column, CD-RSSCT, and PD-RSSCT designs. This finding permitted accurate breakthrough predictions for the sum of PFAS and for 9 of the 11 PFAS on an individual basis in pilot columns using RSSCTs. Multiple linear regressions incorporating influent and treated water optical parameters enabled the modeling approach to be applied to water sources with heterogeneous DOM characteristics. It is hypothesized that this methodology was successful because (i) optical parameters adequately quantified the competitive nature of DOM and their adsorption behaved similar to OMP and (ii) competitive adsorption by low-molecular weight DOM was the predominant fouling mechanism. An OMP monitoring approach was developed for waters containing DOM with heterogenous characteristics that also relied on raw and treated water optical properties. UVA254 and fluorescence monitoring could therefore enable water treatment to remove PFAS in a variety of scenarios that face inhibitory cost and analytical limitations, such as decentralized and low-resource settings.

Evaluation of radiometric calibration of drone-based imagery for improving shallow bathymetry retrieval

ABSTRACT Extracting high resolution, shallow bathymetry from drone-based imagery using empirical methods is a novel approach that gains increasing interest. However, due to the rapidly expanding character of this field, there are not sufficient guidelines for optimal pre-processing of drone-based imagery regarding bathymetry retrieval. This study explores the suitability of imagery resulted from commonly used drone cameras in terms of producing good correlation with ground-truth depth measurements obtained from an unmanned surface vehicle (USV). Thus, imagery with similar spectral responses, from two commercial sensors (DJI Phantom 4 Pro and MicaSense-RedEdge multispectral camera), is examined along with and without radiometric corrections applied, using proprietary software. The results show that radiometric image corrections using a reference reflectance panel, greatly enhance the correlation coefficient between bathymetry data and single-band or band-ratio reflectance mosaics at two study areas with mixed seafloor types. However, it was observed that the Red band and its associated logarithmic band ratios (Blue/Red, Green/Red) from both sensors show good correlation with depth as well, regardless of radiometric corrections. This result applies mainly to areas with favourable optical properties of water. This study suggests that radiometric calibration is crucial in empirical bathymetry retrieval from drone-based imagery. Furthermore, radiometric corrections applied on common Red, Green, Blue (RGB) cameras provide useful reflectance mosaics at lower costs compared to multispectral cameras.

Range Difference Between Shallow and Deep Channels of Airborne Bathymetry LiDAR With Segmented Field-of-View Receivers

Significant range differences were identified between shallow and deep channels of Mapper5000 bathymetry LiDAR system with segmented field-of-view (FOV) receivers. Range difference varied with depth and water optical properties. The main feature was the maximum value in range difference curves, which ranged from 0.3 to 0.6 m and usually exceeded the International Hydrographic Organization (IHO) accuracy standards. Sensitivity analyses based on a semi-analytical Monte Carlo simulation model revealed that the scattering phase function and laser beam divergence angle played more important roles in causing pulse dispersion and determining the amplitude and position of maximum range difference than absorption and scattering coefficients. A range difference correction method by fitting existing shallow and deep channel data in the overlapping range with a cubic polynomial was proposed to correct the deep channel data in the entire depth range that LiDAR can detect. Depth discontinuity at the junction of shallow channel and deep channel measurements was successfully removed, and the mean and standard deviation of corrected range difference were within 0.01 m and 0.1 m, respectively. Combination of range difference correction and mean bias corrector can be an alternative method for depth bias correction of segmented-FOV LiDAR when referenced sonar data is not available.

Spatio-temporal variations in the water quality of the Doorndraai Dam, South Africa: An assessment of sustainable water resource management

The problem of water scarcity and clean water in sub-Saharan Africa is a growing concern. This study aims to quantify the water quality on a temporal scale in the Doorndraai dam site in sub-Saharan Africa to design possible management options. Here, an integrated approach using both in-situ measurements of water quality parameters and remote sensing data was used to derive the water quality index (WQI) and inherent optical properties of water to deduce the factors governing seasonal and annual variability. The results show that all the water quality parameters analyzed fall under the permissible limit of the World Health Organization (WHO) for drinking water, except turbidity. The average value of turbidity for the dry and wet periods was 12.52 and 3.39 NTU, respectively. WQI value ranges from good to excellent during the wet season, and poor in the dry season owing to the high values of turbidity in the water samples. Both in-situ and remote sensing-based analysis shows that during the last five years, the value of suspended particulate matter (SPM) based on Landsat-8 increased gradually in the study area. The Sentinel-2 derived modified normalized difference water index (MNDWI) shows a decreasing trend in the water area due to encroachment. The strong correlation between in-situ and remote sensing data supports the usefulness of remote sensing techniques for water resource management, especially in data-scarce regions. Looking at the spatio-temporal trend of water quality evolution, the findings of this study will help local decision-makers design sustainable plans for water resource management of Doorndraai dam.

Optical Properties of Water for Prediction of Wastewater Contamination, Human-Associated Bacteria, and Fecal Indicator Bacteria in Surface Water at Three Watershed Scales.

Relations between spectral absorbance and fluorescence properties of water and human-associated and fecal indicator bacteria were developed for facilitating field sensor applications to estimate wastewater contamination in waterways. Leaking wastewater conveyance infrastructure commonly contaminates receiving waters. Methods to quantify such contamination can be time consuming, expensive, and often nonspecific. Human-associated bacteria are wastewater specific but require discrete sampling and laboratory analyses, introducing latency. Human sewage has fluorescence and absorbance properties different than those of natural waters. To assist real-time field sensor development, this study investigated optical properties for use as surrogates for human-associated bacteria to estimate wastewater prevalence in environmental waters. Three spatial scales were studied: Eight watershed-scale sites, five subwatershed-scale sites, and 213 storm sewers and open channels within three small watersheds (small-scale sites) were sampled (996 total samples) for optical properties, human-associated bacteria, fecal indicator bacteria, and, for selected samples, human viruses. Regression analysis indicated that bacteria concentrations could be estimated by optical properties used in existing field sensors for watershed and subwatershed scales. Human virus occurrence increased with modeled human-associated bacteria concentration, providing confidence in these regressions as surrogates for wastewater contamination. Adequate regressions were not found for small-scale sites to reliably estimate bacteria concentrations likely due to inconsistent local sanitary sewer inputs.

The Imprint of Primary Production on High-Frequency Profiles of Lake Optical Properties.

Water inherent optical properties (IOPs) contain integrative information on the optical constituents of surface waters. In lakes, IOP measurements have not been traditionally collected. This study describes how high-frequency IOP profiles can be used to document short-term physical and biogeochemical processes that ultimately influence the long-term trajectory of lake ecosystems. Between October 2018 and May 2020, we collected 1373 high-resolution hyperspectral IOP profiles in the uppermost 50 m of the large mesotrophic Lake Geneva (Switzerland-France), using an autonomous profiler. A data set of this size and content does not exist for any other lake. Results showed seasonal variations in the IOPs, following the expected dynamic of phytoplankton. We found systematic diel patterns in the IOPs. Phases of these diel cycles were consistent year-round, and amplitudes correlated to the diurnal variations of dissolved oxygen, clarifying the link between IOPs and phytoplankton metabolism. Diel amplitudes were largest in spring and summer under low wind condition. Wind-driven changes in thermal stratification impacted the dynamic of the IOPs, illustrating the potential of high-frequency profiles of water optical properties to increase our understanding of carbon cycling in lake ecosystems.

Underwater image recovery utilizing polarimetric imaging based on neural networks.

Underwater imaging faces challenges due to complex optical properties in water. Our purpose is to explore the application of polarimetric imaging in image recovery under turbid water based on deep learning. A polarization camera is used to capture the polarization images of objects under water as datasets. The method used in our study aims to explore a structure and loss function that is suitable for the model. In terms of the model structure, four pairs of models consisting of polarized version and gray version based on the idea of dense U-Net and information flow were proposed. In the aspect of loss function, the method of combining weighted mean squared error with perceptual loss was proposed and a proper set of loss weights was selected through comparison experiments. Comparing the model outputs, it is found that adding polarized information along with the light intensity information to the model at the very front of the model structure brings about better recovering image. The model structure proposed can be used for image recovery in turbid water or other scattering environments. Since the polarization characteristics are considered, the recovered image has more detailed features than that where only intensity is considered. The results of comparison with other methods show the effectiveness of the proposed method.

A Novel Fast Multiple-Scattering Approximate Model for Oceanographic Lidar

An effective lidar simulator is vital for its system design and processing algorithms. However, laser transmission is a complex process due to the effects of sea surface and various interactions in seawater such as absorption, scattering, and so on. It is sophisticated and difficult for multiple scattering to accurately simulate. In this study, a multiple-scattering lidar model based on multiple-forward-scattering-single-backscattering approximation for oceanic lidar was proposed. Compared with previous analytic models, this model can work without assuming a homogeneous water and fixed scattering phase function. Besides, it takes consideration of lidar system and environmental parameters including receiver field of view, different scattering phase functions, particulate sizes, stratified water, and rough sea surface. One should note that because the scattering phase function is difficult to determine accurately, the simulation accuracy may be reduced in a complex oceanic environment. The Cox–Munk model used in our method simulates capillarity waves but ignores gravity waves, and the pulse stretching is not included. The wide-angle scattering occurs in the dense subsurface phytoplankton, which sometimes makes it hard to use this model. In this study, we firstly derived this method based on an analytical solution by convolving Gaussians of the forward-scattering contribution of layer dr and the energy density at R in the small-angle-scattering approximation. Then, the effects of multiple scattering and water optical properties were analyzed using the model. Meanwhile, the validation with Monte Carlo model was implemented. Their coefficient of determination is beyond 0.9, the RMSE is within 0.02, the MAD is within 0.02, and the MAPD is within 8%, which indicates that our model is efficient for oceanographic lidar simulation. Finally, we studied the effects of FOV, SPF, rough sea surface, stratified water, and particle size. These results can provide reference for the design of the oceanic lidar system and contribute to the processing of lidar echo signals.

An Extensive Literature Review on Underwater Image Colour Correction.

The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined.

Effect of scattering phase function on underwater visible light communication channel models

Non-sequential ray tracing simulations are commonly employed to model underwater visible light communication (VLC) channels. The accuracy of such simulations highly depends on how well the optical properties of water (i.e., absorption and scattering) as well as scattering phase function (SPF) are modeled in the simulation. Existing empirical models are only a function of chlorophyll concentration and particle composition and are independent of refractive index, size and concentration of particles. In this paper, we carry out an underwater VLC channel modeling study using the Mie SPF which provides a full description of the scattering from phytoplankton particles which dominate the optical properties of most oceanic waters. We obtain the channel impulse response (CIR) based on an extensive non-sequential ray tracing study and calculate the fundamental channel parameters such as channel gain and delay spread. Comparison of CIRs reveals out that deployment of simplified SPF models results in the overestimation of path loss with respect to Mie SPF. Our results clearly demonstrate the importance of selecting realistic SPF models for an accurate underwater VLC channel modeling. While highlighting the channel models, we discuss adaptive modulation technique to maximize the data rate under the constraint of a targeted bit error rate. Besides, the maximum achievable distance is also determined both in terms of analytical guarantees and computer simulations. The results reveal that larger transmission distances can be achieved through Mie SPF channel model.

Physiological and ecological consequences of the water optical properties degradation on reef corals

Degradation of water optical properties due to anthropogenic disturbances is a common phenomenon in coastal waters globally. Although this condition is associated with multiple drivers that affect corals health in multiple ways, its effect on light availability and photosynthetic energy acquisition has been largely neglected. Here, we describe how declining the water optical quality in a coastal reef exposed to a turbid plume of water originating from a man-made channel compromises the functionality of the keystone coral species Orbicella faveolata. We found highly variable water optical conditions with significant effects on the light quantity and quality available for corals. Low-light phenotypes close to theoretical limits of photoacclimation were found at shallow depths as a result of reduced light penetration. The estimated photosynthetically fixed energy depletion with increasing depth was associated with patterns of colony mortality and vertical habitat compression. A numerical model illustrates the potential effect of the progressive water quality degradation on coral mortality and population decline along the depth gradient. Collectively, our findings suggest that preserving the water properties seeking to maximize light penetration through the water column is essential for maintaining the coral reef structure and associated ecosystem services.

The sensory impacts of climate change: bathymetric shifts and visually mediated interactions in aquatic species.

Visual perception is, in part, a function of the ambient illumination spectrum. In aquatic environments, illumination depends upon the water's optical properties and depth, both of which can change due to anthropogenic impacts: turbidity is increasing in many aquatic habitats, and many species have shifted deeper in response to warming surface waters (known as bathymetric shifts). Although increasing turbidity and bathymetric shifts can result in similarly large changes to a species' optical environment, no studies have yet examined the impact of the latter on visually mediated interactions. Here, we examine a potential link between climate change and visual perception, with a focus on colour. We discuss (i) what is known about bathymetric shifts; (ii) how the impacts of bathymetric shifts on visual interactions may be distributed across species; (iii) which interactions might be affected; and (iv) the ways that animals have to respond to these changes. As warming continues and temperature fluctuations grow more extreme, many species may move into even deeper waters. There is thus a need for studies that examine how such shifts can affect an organism's visual world, interfere with behaviour, and impact fitness, population dynamics, and community structure.

Water Optical Property of High-Altitude Lakes in the Tibetan Plateau

Measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) from 2012 to 2019 are used to derive the normalized water-leaving radiance spectra nLw(λ ) in high-altitude lakes over the Tibetan Plateau (TP) (elevation of ~4 km). nLw(λ ) spectra in various lakes in the TP show a significant water optical property diversity in terms of nLw(λ ) spectral shapes, their magnitudes, and their spatial and temporal variations. In the TP major lakes, nLw(λ ) spectra in Lake Namtso and Siling Lake show enhancements at the blue wavelengths of 410 and 443 nm [nLw(410) and nLw(443)], and peak at the wavelength of 486 nm [nLw(486)]. In Lake Ngangze, the nLw(λ ) spectrum shows the optical feature of typical eutrophic waters. Its nLw(λ ) peaks at the green wavelength of 551 nm [nLw(551)] with its value ~2.5 mW cm⁻² μ m⁻¹ sr⁻¹. In Dogai Coring Lake, the typical nLw(λ ) spectrum is similar to those of many smaller and medium size lakes in the TP, and nLw(λ ) spectra are featured with the peak at the green band nLw(551) with another notable red band nLw(671) over ~1.0 mW cm⁻² μ m⁻¹ sr⁻¹, as well as a nonnegligible contribution at the near-infrared (NIR) band nLw(745). This implies that the suspended particle matter (SPM) in the lake plays a significant role in water nLw(λ ) spectra in Dogai Coring Lake and other similar lakes in the TP. The diversity of water optical property in the TP lakes reflects the fact of the regional diversification of processes in various TP lakes and poses potential challenges to the development of remote sensing algorithms for water biological and biogeochemical products in the TP lakes.

Evaluation of regions suitable for vicarious calibration of ocean color satellite sensors in the South China Sea.

Accurate retrieval of biogeochemical components of the ocean at a global scale from space requires accurately calibrated top-of-atmosphere (TOA) radiance, which is usually achieved by deriving a vicarious gain coefficient (g-factor) through a process called system vicarious calibration (SVC). Currently, only two SVC sites, Marine Optical Buoy (MOBY) and BOUée pour l'acquiSition d'une Série Optique à Long termE (BOUSSOLE), are routinely operated to support the SVC process for all on-orbit ocean color satellite payloads. However, high-quality matchups between satellite observations and in situ measurements are rare because of the strict requirements of the SVC process. Meanwhile, a stable g-factor is usually computed by averaging sufficient gain measurements. Therefore, more SVC sites are required to derive a stable g-factor in a short duration, particularly for the initial calibration of newly launched satellite sensors. In this study, nearly twenty years of well-calibrated ocean color satellite data were used to calculate the mean and standard deviation of physical and optical properties of waters and the atmosphere in the South China Sea (SCS) to evaluate the feasibility of establishing a SVC site. A region was identified that meets all requirements that were used to evaluate the MOBY and BOUSSOLE sites. Two in situ measurements within this region were used to derive a g-factor for MODIS-Terra and MODIS-Aqua and were compared with the g-factor derived using MOBY data. The consistence of the two g-factors indicates that the identified region in the SCS could be a potential area for establishing a long-term moored SVC site.

Monodispersed CsPb2Br5@SiO2 Core-Shell Nanoparticles as Luminescent Labels for Biosensing.

Despite the rising advances in the field of metal halide perovskite nanocrystals (NCs), the exploitation of such nanoparticles as luminescent labels for ex vivo imaging and biosensing is still unclear and in the early stages of investigation. One of the major challenges toward the implementation of metal halide perovskite NCs in biosensing applications is to produce monodispersed nanoparticles with desired surface characteristics and compatible with aqueous environments. Here, we report the synthesis of monodispersed spherical CsPb2Br5@SiO2 core–shell nanoparticles by post-synthetic chemical transformation of 3D CsPbBr3 NCs in the presence of tetraethyl orthosilicate and a critical water/ammonia ratio. This method involves an ammonia-mediated and ammonia-induced “top-down” transformation of as-synthesized 3D CsPbBr3 NCs to smaller CsPb2Br5 nanoclusters (ca. 2–3 nm), which trigger a seed-mediated silica growth, yielding monodispersed spherical blue luminescent (λemission = 432 nm) CsPb2Br5@SiO2 perovskite nanoparticles. By adjusting the reaction conditions, core–shell nanoparticles of a 36.1 ± 4.5 nm diameter, which preserve their optical properties in water, were obtained. Besides that, the viability of the developed nanoparticles as a luminescent label for biosensing has been proven by specific biorecognition of the IgG protein in a direct immunoassay. Our work sheds light on the chemical processes and transformations involved in the silica nucleation mechanism in the presence of perovskite nanoparticles and opens the way for the future rational design of the next generation of semiconductor NC luminescent biological labels.