Search Results (25)

Monitoring turbidity is essential for sustainable coastal management because an increase in turbidity leading to diminishing water clarity has a detrimental ecological impact. Turbidity in coastal waters is strongly dependent on the concentration and physical properties of particles in the water column. In the Belgian part of the North Sea, turbidity and suspended particulate matter (SPM) concentrations have been monitored for decades by satellite remote sensing, but this technique only focuses on the surface layer of the water column. Within the water column, turbidity and SPM concentrations are measured in stations or transects with a suite of optical and acoustic sensors. However, the dynamic nature of SPM variability in coastal areas and the recent construction of offshore windmill parks and dredging and dumping activities justifies the need to monitor natural and human-induced SPM variability in 3D instead. A possible solution lies in modern multibeam echosounders (MBES), which, in addition to seafloor bathymetry data, are also able to deliver acoustic backscatter data from the water column. This study investigates the potential of MBES as a 3D turbidity and SPM monitoring tool. For this purpose, a novel empirical approach is developed, in which 3D MBES water column and in-situ optical sensor datasets were collected during ship transects to yield an empirical relation using linear regression modeling. This relationship was then used to predict SPM volume concentrations from the 3D acoustic measurements, which were further converted to SPM mass concentrations using calculated densities. Our results show that these converted mean mass concentrations at the Kwinte and Westdiep swale areas are within the limits of the reported yearly averages. Moreover, they are in the same order of magnitude as the measured mass concentrations from Niskin water samples during each campaign. While there is still need for further improvement of acquisition and processing workflows, this study presents a promising approach for converting MBES water column data to turbidity and SPM measurements. This opens possibilities for improving future monitoring tools, both in scientific and industrial sectors. Full article

The Pomeranian lakes in Northern Poland and the nearby coastal waters of the Baltic Sea belong to optically complex water bodies characterised by high eutrophication levels. These water types require a local approach when developing bio-optical algorithms that combine the inherent and the apparent properties of seawater. Well-established local algorithms are of great value for understanding and addressing rapid changes in water quality related mostly to human activities in coastal and near-shore zones, as well as in optically similar lakes. Our research analyses the possibility of using the multi-parameter algorithms of absorption a(λ), backscattering b_b(λ) and remote sensing reflectance R_rs(λ), originally developed for the coastal waters of the Southern Baltic Sea, for three selected Pomeranian lakes. Our multi-parameter algorithms are based on the input concentrations of the biogeochemical components measured in the lake waters, i.e., chlorophyll a (Chl a), suspended particulate matter (SPM), inorganic suspended particulate matter (SPM_inorg), the sum of the surface concentrations of accessory pigments (ΣC) and coloured dissolved organic matter with a wavelength of 400 nm (a_CDOM(400)). R_rs(λ) and a(λ) output values were compared with independent measurements of these parameters conducted in the lake waters at 20 sampling stations. Our algorithm output values of b_b(λ) were compared to the values obtained based on the algorithm provided by Ficek, previously developed and validated for Pomeranian lakes, at the same stations. The statistical analyses conducted afterwards showed that the multi-parameter algorithms of R_rs(λ) and a(λ) for the Southern Baltic Sea are sufficient to be used for the stations investigated in the aforementioned three lakes. Specifically, the correlations between the b_b(λ) values obtained based on the Ficek algorithm and the b_b(λ) values obtained using our multi-parameter algorithm reveal a statistical error rate of less than 20%. Full article

The bidirectional reflectance distribution function (BRDF) factor ƒ′ provides a bridge between the inherent and apparent optical properties (IOPs and AOPs) of inland waters. The previous BRDF studies focused on ocean waters, while few studies examine inland waters. It is meaningful to improve the theory of remote sensing of water surface and the accuracy of image derivation in inland waters. In this study, radiative transfer simulation was applied to calculate the ƒ′ values using appropriate IOPs based on in situ combined with realistic boundary conditions (N = 11,232). This study shows that ƒ′ factor varied over the range of 0.33–16.64 in Lake Nansihu, a finite depth water, higher than the range observed for the ocean (0.3–0.6). Our results demonstrate that the factor ƒ′ depends on not only solar zenith angle (${\theta }_s$) but also the average number of collisions ($\stackrel{-}{n}$) and particulate backscattering ratio (${\tilde{b}}_{bp}$). The ƒ′ factor shows a continuous geometric increase as the solar zenith angle increases at 400–650 nm but is relatively insensitive to solar angle in the 650–750 nm range in which ƒ′ increases as ${\tilde{b}}_{bp}$ and $\stackrel{-}{n}$ decreases. To account for these findings, two empirical models for ƒ′ factor as a function of ${\theta }_s$, $\stackrel{-}{n}$ and ${\tilde{b}}_{bp}$ are proposed in various spectral wavelengths for Lake Nansihu waters. Our results are crucial for obtaining Hyperspectral normalized reflectance or normalized water-leaving radiance and improving the accuracy of satellite products. Full article

Observations of mixing layer height (MLH), its dynamics and the extent of homogeneity of the mixing layer are important in the study of air pollution as well as meteorological and air quality model validation. They can contribute to improvements in the application of satellite aerosol optical depth (AOD) products to ground fine particulate matter (PM2.5) estimation that can potentially provide synoptic-scale monitoring of fine particulate matter. Ceilometers have shown great potential for continuous monitoring of MLH and aerosol profiles within the boundary layer. In this study, we report an automated quality control/quality assurance (QC/QA) method that improves the consistency of MLH retrievals from ceilometer measurements and present measurements of MLH variation in New York City (NYC) as observed by ceilometers in summer and winter seasons. Distinct issues due to SNR and quality of overlap correction are addressed within the QC/QA method. We also analyze the diurnal and seasonal correlations between ceilometer-attenuated backscatter and ground-level PM2.5 as a function of height, time of day, and season, to shed light on the homogeneity of aerosol vertical mixing within the MLH, as well as the correlation between aerosol optical properties and PM2.5. The results show that the overall correlation in summer is better than in winter. This correlation decreases with increasing height but the degradation is less severe in summer than in winter, which is qualitatively consistent with urban heating models of convective mixing. However, no significant diurnal variation of the correlation coefficient was observed for both seasons. We also found that the linear regression slope between ceilometer-attenuated backscatter coefficients and ground PM2.5 shows seasonal variation, which can be partially explained by the difference in aerosol size distribution and aerosol species between summer and winter. Finally, we investigated the homogeneity of aerosol vertical distribution within the mixing layer (ML) during the daytime. The results indicate that the aerosols are well-mixed within the lower part of ML up to 500 m. Full article

Northwest China is significantly affected by sandstorm disasters. To mitigate the negative impacts of sandstorm events, it is critical to understand the spatio-temporal variations in typical sand and dust storms and their influencing factors. In this work, using ground-based measurements of particulate matter and remote sensing data such as MODIS, OMI, and CALIPSO data, the sources of aerosol pollution and aerosol optical properties of a typical sandstorm event that occurred in Northwest China in 2018 was studied. In addition, the HYSPLIT model was used to explore the air mass trajectories in order to analyze the sand and dust migration process during the sandstorm event. Furthermore, the wind erosion sensitivity of Northwest China was analyzed via single factor analysis and multi-factor superposition of wind field intensity, soil drought index, vegetation coverage, and relief amplitude. Finally, the region of the study area having a high comprehensive wind erosion sensitivity was identified. The results showed that the PM₁₀ concentrations exceeded 400 µg/m³ and the PM_2.5/PM₁₀ ratio did not exceeded 0.6 during the sandstorm event, indicating that natural particulate matter was dominant in the ambient air. At the epicenter of pollution, the aerosol optical depth (AOD) at 550 nm was 0.75–1. By combining AOD data with wind speed and direction data from field observation stations, it was found that the sandstorm event in 2018 mainly occurred between 1 April and 3 April, and affected all of Northwest China on 2 April and 3 April. The absorbed aerosol index (AAI) ranged between 2.5 and 4, indicating that the Taklimakan Desert was the main source of sandstorm events in Northwest China. The CALIPSO total attenuated backscatter coefficient at 532 nm indicated that the main component of tropospheric aerosol in this region was distributed in the range of 0–12.5 km. The simulated airflow track showed that it had the same dust source regions as AAI index studies. Moreover, investigation of wind erosion sensitivity in the study areas indicated that the Taklimakan Desert and other desert regions were the main ecologically sensitive areas. These conclusions can provide references and suggestions for the mitigation of damage caused by sandstorm events, in addition to the enhancement of ecological governance. Full article

Water transparency (or Secchi disk depth:$Z_{SD}$) is a key parameter of water quality; thus, it is very important to routinely monitor. In this study, we made four efforts to improve a state-of-the-art $Z_{SD}$ estimation algorithm that was developed in 2019 on the basis of a new underwater visibility theory proposed in 2015. The four efforts were: (1) classifying all water into clear (Type I), moderately turbid (Type II), highly turbid (Type III), or extremely turbid (Type IV) water types; (2) selecting different reference wavelengths and corresponding semianalytical models for each water type; (3) employing an estimation model to represent reasonable shapes for particulate backscattering coefficients based on the water type classification; and (4) constraining likely wavelength range at which the minimum diffuse attenuation coefficient (K_d(λ)) will occur for each water type. The performance of the proposed $Z_{SD}$ estimation algorithm was compared to that of the original state-of-the-art algorithm using a simulated dataset (N = 91,287, $Z_{SD}$ values 0.01 to 44.68 m) and an in situ measured dataset (N = 305, $Z_{SD}$ values 0.3 to 16.4 m). The results showed a significant improvement with a reduced mean absolute percentage error (MAPE) from 116% to 65% for simulated data and from 32% to 27% for in situ data. Outliers in the previous algorithm were well addressed in the new algorithm. We further evaluated the developed $Z_{SD}$ estimation algorithm using medium resolution imaging spectrometer (MERIS) images acquired from Lake Kasumigaura, Japan. The results obtained from 19 matchups revealed that the estimated $Z_{SD}$ matched well with the in situ measured $Z_{SD}$, with a MAPE of 15%. The developed $Z_{SD}$ estimation algorithm can probably be applied to different optical water types due to its semianalytical features. Full article

Particulate volume scattering function (VSF), especially at angles larger than 170°, is of particular importance for interpreting ocean optical remote sensing signals and underwater imagery. In this study, a laboratory-based VSF instrument (VSFlab) adopting the periscopic optical system was developed to obtain VSF measurements from 1°–178.5°. In the VSFlab, a new prism design that simply combines a single prism and a neutral density filter was proposed to more efficiently reduce the stray light in the backward direction, while a detailed calibration procedure was given. A full validation based on standard beads of various sizes and a comparison with the results from LISST-VSF and POLVSM indicated that the VSFlab can provide reliable results from 1° to 178.5°. VSFlab measurements in the East China Sea (ECS) exhibited a moderate increase (not more than 5 times) in VSF from 170° to 178.5° rather than a sharp increase of more than one order of magnitude presented in other instrument results measured in other coastal regions. The estimates of the particulate backscattering coefficient using single angle scattering measurements near 120° or 140° and suitable χ_p were justified. Two types of the VSFs with different size distribution and shape parameters in the ECS can be distinguished based on the variability of χ_p after 155°. The measured VSF could provide a basis for the parameterization of VSF in the radiative transfer model and the variability of χ_p in the backward direction had the potential to be used to characterize the particles in the coastal region of the ECS. Full article

We introduce a new instrument for sampling the airborne particulate matter (PM) while monitoring the black carbon (BC) atmospheric concentration. The concentration of PM and BC are usually measured by separate instruments with possible systematics differences even in the collecting inlets. The new equipment is based on a low-volume sequential PM sampler, fully compliant with the EU-CEN and US-EPA regulatory standards, with a built-in optical BC monitor. The BC concentration is continuously measured during the sampling in the PM accumulated on the filter while the PM concentration can be obtained off-line by a standard gravimetric analysis. The optical set-up, upstream the collecting filter, is composed by a single wavelength light source (λ = 635 nm) and a photodiode, placed in way to receive the light backscattered by the filter surface at a fixed angle. The mechanical arrangement does not introduce any perturbation to the PM sampling. Thanks to an original calibration curve, the sample absorbance is deduced from the output signal of the photodiode. Finally, the BC concentration is obtained through the Mass Absorption Coefficient (MAC). After the sampling and the PM gravimetric determination, the same filter can be sent to other compositional analyses. Thermo-optical quantification of the Elemental and Organic Carbon (EC and OC) in the filter sample can thus be exploited to tune the MAC value to the PM composition of a particular site. The main features of the new instrument and the set of validation tests against other PM samplers and BC monitors of widespread use (i.e.,: Multi Angle Absorption Photometer and aethalometer) are detailed and discussed. Full article

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. Full article

A multispectral backscattering LiDAR (Light detection and range) system (hereafter Oculus) was integrated into a wave glider and used to estimate the scattering order (i.e., single vs multiple collisions) of LIDAR backscattering, the water inherent optical properties (IOPs), the biogeo-chemical characteristics of particulate scatterers (i.e., relative size, composition) and their motion) on shelf waters of South East Florida. Oculus has a dual-wavelength configuration (473 and 532 nm) and two detection geometries (off- and on-axis). Characteristics of scatterers were investigated based on two complementary LiDAR-derived proxies (the Structural Dissimilarity Index and the spectral slope of LiDAR backscattering). In March 2017, field measurements showed a covariation between direct and diffuse backscattering contributions during morning hours and away from shore. LiDAR attenuation coefficients explained up to 57% of IOPs variability. The analysis of LiDAR-derived proxies suggested higher turbidity and larger particulates near the coast Full article

The recent integration of Acoustic Doppler Current Profilers (ADCPs) onto underwater gliders changes the way current and sediment dynamics in the coastal zone can be monitored. Their endurance and ability to measure in all weather conditions increases the probability of capturing sporadic meteorological events, such as storms and floods, which are key elements of sediment dynamics. We used a Slocum glider equipped with a CTD (Conductivity, Temperature, Depth), an optical payload, and an RDI 600 kHz phased array ADCP. Two deployments were carried out during two contrasting periods of the year in the Rhone River region of freshwater influence (ROFI). Coastal absolute currents were reconstructed using the shear method and bottom tracking measurements, and generally appear to be in geostrophic balance. The responses of the acoustic backscatter index and optical turbidity signals appear to be linked to changes of the particle size distribution in the water column. Significantly, this study shows the interest of using a glider-ADCP for coastal zone monitoring. However, the comparison between suspended particulate matter dynamics from satellites and gliders also suggests that a synoptic view of the processes involved requires a multiplatform approach, especially in systems with high spatial and temporal variability, such as the Rhone ROFI area. Full article

The paper presents the modelling results of selected characteristics of water-leaving light in an optically complex nearshore marine environment. The modelled quantities include the spectra of the remote-sensing reflectance R_rs(λ) and the hue angle α, which quantitatively describes the colour of water visible to the unaided human eye. Based on the latter value, it is also possible to match water-leaving light spectra to classes on the traditional Forel-Ule water colour scale. We applied a simple model that assumes that seawater is made up of chemically pure water and three types of additional optically significant components: particulate organic matter (POM) (which includes living phytoplankton), particulate inorganic matter (PIM), and chromophoric dissolved organic matter (CDOM). We also utilised the specific inherent optical properties (SIOPs) of these components, determined from measurements made at a nearshore location on the Gulf of Gdańsk. To a first approximation, the simple model assumes that the R_rs spectrum can be described by a simple function of the ratio of the light backscattering coefficient to the sum of the light absorption and backscattering coefficients (u = b_b/(a + b_b)). The model calculations illustrate the complexity of possible relationships between the seawater composition and the optical characteristics of an environment in which the concentrations of individual optically significant components may be mutually uncorrelated. The calculations permit a quantitative interpretation of the Forel-Ule scale. The following parameters were determined for the several classes on this scale: typical spectral shapes of the u ratio, possible ranges of the total light absorption coefficient in the blue band (a(440)), as well as upper limits for concentrations of total and organic and inorganic fractions of suspended particles (SPM, POM and PIM concentrations). The paper gives examples of practical algorithms that, based on a given R_rs spectrum or some of its features, and using lookup tables containing the modelling results, enable to estimate the approximate composition of seawater. Full article

Optical complexity and various properties of Case 2 waters make it essential to derive inherent optical properties (IOPs) through an appropriate method. Based on field measured data of Lake Chaohu between 2009 and 2018, the quasi-analytical algorithm (QAA) was modified for the particular scenario of that lake to derive absorption coefficients based on the moderate-resolution imaging spectroradiometer (MODIS) bands. By changing the reference wavelength to longer ones and building a relationship between the value of spectral power for particle backscattering coefficient (Y), suspended particulate matter (SPM), and above-surface remote-sensing reflectance (R_rs), we improved the accuracy of the retrieval of total absorption coefficients. The absorption coefficients of gelbstoff and non-algal particulates (a_dg) and absorption coefficients of phytoplankton (a_ph) in Lake Chaohu were also derived by changing important parameters according to Lake Chaohu. The derived a_ph tend to be bigger than measured a_ph in this study, while derived a_dg tend to be smaller than measured data. We also used the corrected MODIS surface reflectance product (MOD09/MYD09) to calculate the a_ph(443), a_ph(645), and a_ph(678) by the model proposed in this study. It shows that in summer and autumn, a_ph tended to be higher in the northwestern part of Lake Chaohu, and were relatively lower in the spring and winter, which is similar to previous studies. Overall, our study provides an algorithm that is effectively used in the case of Lake Chaohu and applicable to the data obtained by MODIS, which can be used for further study to investigate the change law of absorption coefficients in long time series by applying MODIS data. Full article

Haze is an atmospheric phenomenon in which different types of particulates obscure the sky, and hence affect almost all human activities. Over a couple of recent decades, China has witnessed increasingly worse air quality as well as atmospheric haziness in its cities. There are various haze contributing factors including the rapid industrialization, excessive biomass burning, and an increase in the number of vehicles. This study proposes a methodology based on the aerosols scattering and absorption properties, to predict the likelihood of an episode of hazy days. This case study employs the aerosol optical properties data from integrated nephelometer and aethalometer sensors from December 2009 to September 2014 over Wuhan. The role and contribution of each aerosol optical parameter (e.g., aerosol scattering and absorption coefficients, single scattering albedo, scattering, and absorption Ångström exponents, backscatter ratio, and asymmetry factor) in distinguishing haze and haze-free conditions has been quantitatively determined based on a machine learning approach. Each aerosol optical parameter was classified independently by the support vector machine (SVM) algorithm, and the aerosol scattering (85.37%) and absorption (74.53%) coefficients were found to be primary potential indicators. Through the Kolmogorov-Smirnov test and traditional statistical analysis, the aerosol scattering and absorption coefficients were then verified as important indicators in distinguishing haze and haze-free days. Finally, through a probability density diagram and frequency histogram, we propose a simple quantitative standard to distinguish between haze and haze-free conditions based on the aerosol scattering coefficient and absorption coefficient in Wuhan City. The accuracy of the standard was determined to be 81.49% after testing, which indicates an accurate result. An error in aerosol optical properties may lead to an error in the calculation of aerosol radiative forcing, the earth’s energy budget, and climate prediction. Therefore, understanding of the aerosol properties during haze-free and haze-days will help policymakers to make new policies to control urban pollution and their effects on human health. Full article

Particulate optical backscattering (b_bp) is a crucial parameter for the study of ocean biology and oceanic carbon estimations. In this work, b_bp retrieval, by the quasi-analytical algorithm (QAA), is assessed using a large in situ database of matched b_bp and remote-sensing reflectance (R_rs). The QAA is also applied to satellite R_rs (ESA OC-CCI project) as well, after their validation against in situ R_rs. Additionally, the effect of Raman Scattering on QAA retrievals is studied. Results show negligible biases above random noise when QAA-derived b_bp is compared to in situ b_bp. In addition, R_rs from the CCI archive shows good agreement with in situ data. The QAA’s functional form of spectral backscattering slope, as derived from in situ radiometry, is validated. Finally, we show the importance of correcting for Raman Scattering over clear waters prior to semi-analytical retrieval. Overall, this work demonstrates the high efficiency of QAA in the b_bp detection in case of both in situ and ocean color data, but it also highlights the necessity to increase the number of observations that are severely under-sampled in respect to others environmental parameters. Full article