Contributions of meteorology and nutrient to the surface cyanobacterial blooms at different timescales in the shallow eutrophic Lake Taihu.

Quantitative assessments of the contributions of various environmental factors to cyanobacterial blooms at different timescales are lacking. Here, the hourly cyanobacterial bloom intensity (CBI) index, a proxy for the intensity of surface cyanobacterial biomass, was obtained from the geostationary satellite sensor Geostationary Ocean Color Imager (GOCI) over the years 2011-2018. Generalized additive model was applied to determine the responses of monthly and hourly CBI to the perturbations of meteorological factors, water stability and nutrients, with variation partitioning analysis used to analyze the relative importance of the three groups of variables to the inter-monthly variation of diurnal CBI in each season. The effects of environmental factors on surface cyanobacterial blooms varied at different timescales. Hourly CBI increased with increasing air temperature up to 18 °C but decreased sharply above 18 °C, whereas monthly CBI increased with increasing air temperature up to 30 °C and stabilized thereafter. Among all the environmental factors, air temperature had the largest contribution to the intra-daily variation in CBI; water stability had the highest explanation rate for the inter-monthly variation of diurnal CBI during summer (42.3 %) and autumn (56.9 %); total phosphorus explained the most variation in monthly CBI (18.5 %). Compared with cyanobacterial biomass (CB) in the water column, high light and low wind speed caused significantly lower CBI in July and higher CBI in November respectively. Interestingly, cyanobacterial blooms at the hourly scale were aggravated by climate warming during winter and spring but inhibited during summer and autumn. Collectively, this study reveals the effects of environmental factors on surface cyanobacterial blooms at different timescales and suggests the consideration of the hourly effect of air temperature in short-term predictions of cyanobacterial blooms.

Transfer model to determine the above-water remote-sensing reflectance from the underwater remote-sensing ratio.

Remote-sensing reflectance, Rrs(λ, θ, Δϕ, θs), contains the spectral color information of the water body below the sea surface and is a fundamental parameter to derive satellite ocean color products such as chlorophyll-a, diffuse light attenuation, or inherent optical properties. Water reflectance, i.e., spectral upwelling radiance, normalized by the downwelling irradiance, can be measured under- or above-water. Several models to extrapolate this ratio from underwater "remote-sensing ratio", rrs(λ), to the above-water Rrs, have been proposed in previous studies, in which the spectral dependency of water refractive index and off-nadir viewing directions have not been considered in detail. Based on measured inherent optical properties of natural waters and radiative transfer simulations, this study proposes a new transfer model to spectrally determine Rrs from rrs for different sun-viewing geometries and environmental conditions. It is shown that, compared to previous models, ignoring spectral dependency leads to a bias of ∼2.4% at shorter wavelengths (∼400 nm), which is avoidable. If nadir-viewing models are used, the typical 40°-off nadir viewing geometry will introduce a difference of ∼5% in Rrs estimation. When the solar zenith angle is higher than 60°, these differences of Rrs have implications for the downstream retrievals of ocean color products, e.g., > 8% difference for phytoplankton absorption at 440 nm and >4% difference for backward particle scattering at 440 nm by the quasi-analytical algorithm (QAA). These findings demonstrate that the proposed rrs-to-Rrs model is applicable to a wide range of measurement conditions and provides more accurate estimates of Rrs than previous models.

Oxidative C-O bond cleavage of dihydroxybenzenes and conversion of coordinated cyanide to carbon monoxide using a luminescent Os(VI) cyanonitrido complex.

The photoreactions of a luminescent osmium(VI) nitrido complex, [OsVI(N)(L)(CN)3]- (OsN, HL = 2-(2-hydroxy-5-nitrophenyl)benzoxazole), with catechol (H2Cat) and hydroquinone (H2Q) lead to the cleavage of strong C-OH bonds (ca. 120 kcal mol-1) of the dihydroxybenzenes with concomitant conversion of the coordinated cyanide to carbon monoxide.

Ultrasound and clinical findings of hyalinizing trabecular tumor of the thyroid.

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Utilization of GOCI data to evaluate the diurnal vertical migration of Microcystis aeruginosa and the underlying driving factors.

Cyanobacterial blooms are one of the most severe ecological problems affecting lakes. The vertical migration of cyanobacteria in the water column increases the uncertainty in the formation and disappearance of blooms, which may be closely associated with light, temperature, and wind speed. However, it is difficult to quantitatively evaluate the influencing factors of cyanobacteria vertical movement in natural environment compared to the laboratory experimental environment. Besides, both field survey and laboratory experiment method have the difficulties in determining the diurnal vertical migration of cyanobacteria at the synoptic lake scale. In this study, based on the diurnal dynamics of cyanobacterial bloom intensity (CBI) observed by the Geostationary Ocean Color Imager (GOCI) from 2011 to 2019, the daily variations, floating rate, and sinking rate of Microcystis aeruginosa were calculated in the natural environment. Then, the effects of light, temperature, and wind speed on the vertical migration of M. aeruginosa were analysed from the perspectives of day, night, and season. The results are as follows: the records of three typical patterns of diurnal CBI exhibited strong seasonal variability from the 9-year statistics; at night, the buoyancy recovery rate of cyanobacterial colonies increased with temperature, so that at temperature >15 °C and wind speed <3 m s-1, CBI reached the maximum of the whole day at 08:16; the sinking rate of M. aeruginosa was positively correlated with the cumulated light energy at both synoptic and pixel scale; the upward migration speed of M. aeruginosa was positively correlated with the maximum wind speed of the day before cyanobacterial bloom. Therefore, the severer cyanobacterial blooms were often observed by satellite images after strong winds. The analysis of diurnal variation, floating rate, and sinking rate of M. aeruginosa will expand our knowledge for further understanding the formation mechanism of cyanobacterial blooms and for improving the accuracy of model simulation to predict the hourly changes in cyanobacterial blooms in Lake Taihu.

[Comprehensive Classification Method of Urban Water by Remote Sensing Based on High-Resolution Images].

Urban water is a significant part of the urban ecosystem. Therefore, a comprehensive evaluation method of the water environment was proposed based on domestic high-resolution images. The relationships between the spectral characteristics and water quality parameters of urban water were analyzed based on sampling in Nanjing, Wuxi, Changzhou, and Yangzhou from 2017 to 2019. An index named the U-FUI (urban Forel-Ule index) suitable for urban water based on GF-2 images was proposed to achieve the classification of urban water on the basis of the international standard chroma conversion model and the Forel-Ule index. Independent verification data showed that the recognition accuracy of the classification model could reach 72%. The results indicated that urban water can be classified into six classes from Ⅰ to Ⅵ, which represent water colors of blue, light green, dark green, yellow, yellowish brown, and dark grey, respectively, according to the U-FUI. Among them, the water quality of U-FUI Ⅰ water is good, but is rarely distributed in urban water. The concentrations of chlorophyll-a in U-FUI Ⅱ-Ⅲ water are higher than those of the other classes; the concentrations of total suspended solids, particularly inorganic suspended solids, of U-FUI Ⅳ-Ⅴ water are higher than those of the other classes; and the water quality of U-FUI Ⅵ water is poor and the water quality parameters are different from those of the other classes. Meanwhile, the method was successfully applied to the GF-2 image of Nanjing on April 9, 2018. The results showed that the urban water in Nanjing is mainly composed of U-FUI Ⅱ-Ⅳ water, whereas the distribution of U-FUI Ⅰ, Ⅴ, and Ⅵ water is lower in the city. The spatial distribution characteristics were consistent with the results of in-situ sampling in the same period.

Simultaneous inversion of concentrations of POC and its endmembers in lakes: A novel remote sensing strategy.

Data on the concentration of particulate organic carbon (POC) and its endmembers provide a basis for the characterisation of lake biogeochemical cycles. Here, a novel remote sensing strategy (the SCPOC algorithm) was developed to determine total POC concentrations, as well as terrestrial and endogenous POC concentrations in lakes. This strategy provides a successful example for the combination of isotope tracer and remote sensing technology. First, we obtained the terrestrial and endogenous POC concentration at the sampling point based on isotope tracing technology. Afterwards, we established a relationship between the phytoplankton absorption coefficient and the endogenous POC concentration (Cend), and applied a semi-analytical algorithm to invert the Cend value. Finally, the POC source ratio model and Cend value were combined to obtain the POC concentration (CPOC) and terrestrial POC (Cter). The results of synchronisation verification based on ocean and land colour instrument (OLCI) images show that the SCPOC algorithm has high Cend, Cter, and CPOC inversion accuracy, with MAPE values of 26.07%, 30.43%, and 42.28%, respectively. In fact, the SCPOC algorithm not only improved the accuracy of lake POC mapping, but also fills the gap of optical retrieval of POC endmember concentrations. Additionally, data from the OLCI images indicated that the studied lakes were dominated by external POC. However, because of the greater contribution of algal blooms to POC, this dominant advantage weakens in summer, although the terrestrial organic carbon carried by rainfall runoff also affects lake POC composition. Different POC sources have different ecological roles in lakes, and the superior POC end-element estimation capability of the SCPOC algorithm can not only be used as a supplement to traditional tracing methods, but also provides accurate spatial data for lake management.

Characteristics of the chromophoric dissolved organic matter of urban black-odor rivers using fluorescence and UV-visible spectroscopy.

Urban black-odor water (BOW) is a typical phenomenon seen in the urban water environment; it is caused by excessive pollution by organic matter and other pollutants, such as nitrogen and phosphorous. Chromophoric dissolved organic matter (CDOM) is a major optical fraction of dissolved organic matter. In this study, optical properties and components of CDOM were obtained from 178 river samples collected from five cities in China, the sample were investigated using absorption and fluorescence spectroscopy. The collected included 89 ordinary water (OW) samples, 63 mild BOW (MBOW), and 26 heavy BOW (HBOW) samples. Significant differences were found in the absorption spectra of the HBOW, MBOW, and OW samples, particularly in their optical parameters (the slope of the spectrum (S275-295), and the ratio of two absorption coefficients of CDOM (E2:E3)). Additionally, the fluorescence intensity of the humic acid-like component (F5) and soluble microbial by product-like component (F4) obtained via the fluorescence regional integration (FRI) method were 3 and 4.2 times higher in HBOW than in OW, respectively; this could be used as an indicator to distinguish OW from BOW in urban rivers. The results obtained using the redundancy method and the strong negative correlation between F4 and dissolved oxygen (DO) (r = - 0.56) suggested that the composition of CDOM could change significantly under different urban water environments (p < 0.01). Different correlations were also found between F5, and a355, E2:E3, S275-295 in different BOW levels, suggesting that the optical parameters of CDOM were mainly determined by the polluted organic matter originating from terrestrial sources with large molecular humic acid-like compounds; optical parameter a355 could distinguish BOW from OW. These findings are conducive in understanding the dynamics of organic matter pollution and to discover the composition and optical properties of the CDOM in urban BOW and OW, thereby providing an effective method for tracking the spatial characteristics of BOW in urban rivers using remote sensing technologies in areas with multiple sources of pollution.

[Remote Sensing Classification of Urban Black-odor Water Based on Decision Tree].

Remote sensing monitoring of black-odor water is an important method for understanding the current status of urban water quality, and comprehensively evaluating the effect of urban water environment treatment. A total of 171 samples were collected in Nanjing, Changzhou, Wuxi, and Yangzhou cities and water quality parameters and optical parameters were measured simultaneously. Based on the analysis of the water color and optical characteristics of the black-odor water and non-black-odor water (denoted as general water), a decision tree was constructed to identify the severe, mild black-odor water, and general water as green and yellow water. The results found that:①According to the water color, the water bodies can be divided into six types. Among them, type 1 to 4 water bodies are black-odor water, which are gray black, dark gray, gray, and light gray water, respectively, and type 5 and 6 water bodies are general water, which are green and yellow water, respectively; ②Type 1 water body contains high contents of non-pigmented particulate matter and colored dissolved organic matter(CDOM), however, the absorption of pigmented particulate matter is not dominant. Type 2 and 5 water bodies are dominated by pigmented particulate matter. Type 3, 4, and 6 water bodies are dominated by non-pigmented particulate matter; ③After water color classification, and according to the differences of the reflection spectrums of the six types of water bodies, the difference of black-odorous water index (DBWI), green-red-nir area water index (G-R-NIR AWI), the green band reflectance and the normalized difference black-odorous water index (NDBWI) were used to construct a decision tree to identify the severe, mild black-odor water, and general water; ④The decision tree was applied to the PlanetScope satellite image of Yangzhou City on April 9, 2019, and 10 synchronous sampling points were used for verification. The overall recognition accuracy reached 80.00%, and the K value reached 0.67. The urban water classification model, after water color classification, can be applied to other similar water bodies, and provides a technical method for the supervision of black-odor water bodies.

Tracking spatio-temporal dynamics of POC sources in eutrophic lakes by remote sensing.

Estimating the proportions of particulate organic carbon (POC) endmembers is essential to fully understand the carbon cycle, the function of aquatic ecosystems, and the migration of contaminants in eutrophic lakes. There is currently no effective remote sensing optical algorithm in the literature to solve this problem. In this study, a POC-source color index (SPOC) was constructed based on the terrestrial and endogenous POC ratios calculated from field-measured stable isotope (δ13CPOC) values. The SPOC algorithm traces the sources of POC by utilizing three spectral bands centered approximately at 560 nm, 674 nm, and 709 nm, covering the intrinsic optical information of different POC sources. At the same time, the SPOC algorithm shows good applicability to Ocean and Land Color Instrument (OLCI), Medium-Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Geostationary Ocean Color Imager (GOCI) image data. The POC sources estimated using the algorithm and monthly OLCI data showed that from March 2018 to January 2019, the POC at the surface of Lake Taihu was mainly terrigenous. In addition, due to multiple factors such as algal blooms, plant physiology, river transport, regional rainfall, and carbon cycling, the distribution of POC sources exhibited strong spatial and temporal heterogeneity. Compared with other methods, it is more convenient to use remote sensing to identify the proportion of POC in different endmembers, which offers a more comprehensive understanding of the energy flows and material circulation in lakes.

Optical classification of inland waters based on an improved Fuzzy C-Means method.

Water optical clustering based on water color information is important for many ecological and environmental application studies, both regionally and globally. The fuzzy clustering method avoids the sharp boundaries in type-memberships produced by hard clustering methods, and thus presents its advantages. However, to make good use of the fuzzy clustering methods on water color spectra data sets, the determination of the fuzzifier parameter (m) of FCM (fuzzy c-means) is the key factor. Usually, the m is set to 2 by default. Unfortunately, this method assigned some membership degrees to non-belonging water type, failing to obtain the unitarity of cluster structure in some cases, especially in inland eutrophic water. To overcome this shortcoming, we proposed an improved FCM method (namely FCM-m) for water color spectra classification by optimizing the fuzzifier parameter. We collected an inland data set containing 1280 in situ spectral data and co-measured water quality parameters with a wide range of biogeochemical variability in China. Using FCM-m, seven spectrally distinct water optical clusters on Sentinel-3 OLCI (Ocean and Land Colour Imager) bands were obtained with the optimized fuzzifier (m=1.36), and the well-performed clustering result is assessed by the validated index (Fuzzy Silhouette Index=0.513). Also, the FCM-m-based soft classification framework was successfully applied to the atmospherically corrected OLCI images, which was evaluated by previous case studies. Besides, by testing FCM-m on three coastal and oceanic data sets, we verified that the optimized m should be adjusted based on the data set itself, and in general, the value gradually approaches 1 with the increase of the band number (or dimension). Finally, the effect of the improved method was tested by Chlorophyll-a concentration estimation. The results show that the algorithm------- blending by FCM-m performs better than that by original FCM, which is mainly because the FCM-m reduces the estimation error from non-belonging clusters by a stricter membership value assignation. To sum up, we believe that FCM-m is an adaptive algorithm, whose R codes are available at https://github.com/bishun945, and needs to be tested by more public data sets.

Long-term observation of cyanobacteria blooms using multi-source satellite images: a case study on a cloudy and rainy lake.

High-frequency and reliable data on cyanobacteria blooming over a long time period is crucial to identify the outbreak mechanism of blooms and to forecast future trends. However, in cloudy and rainy areas, it is difficult to retrieve useful satellite images, especially in the rainy season. To address this problem, we used data from the HJ-1/CCD (Chinese environment and disaster monitoring and forecasting satellite/charge coupled device), GF-1/WFV (Chinese high-resolution satellite/wide field of view), and Landsat-8/OLI (Operational Land Imager) satellites to generate a time series of the bloom area from 2009 to 2016 in Dianchi Lake, China. We then correlated the responses of bloom dynamics to meteorological factors. Several findings can be drawn: (1) a higher bloom frequency and a larger bloom area occurred in 2011, 2013, and 2016, compared to the other years; (2) the frequency of blooms peaked in April, August, and November each year and expanded from north to south starting in July; (3) air temperature in spring and sunshine hours in summer greatly correlated to the yearly bloom area; (4) wind speed and sunshine hours strongly affected the short-term expansion of blooms and thereafter influenced the monthly bloom scale; and (5) rainfall had a strong short-term influence on the occurrence of blooms. Cyanobacteria blooms often occurred when wind speeds were less than 2.35 ± 0.78 m/s in the dry season and 2.01 ± 0.75 m/s in the rainy season, when there were 48 to 72 h of sunshine in the dry season and 35 to 57 h of sunshine in the rainy season, and when there was more than 10 mm of daily precipitation.

Remote observation of water clarity patterns in Three Gorges Reservoir and Dongting Lake of China and their probable linkage to the Three Gorges Dam based on Landsat 8 imagery.

The Secchi disk depth (ZSD) plays a critical role in describing water clarity. Several studies have shown linkages between Three Gorges Dam (TGD) and the downstream lacustrine ecosystem in the middle and lower Yangtze River basin. However, the potential influence on the ZSD fluctuation in the entire anthropogenic reservoirs of Three Gorges (ER) and Dongting Lake (DTL) has not been reported, possibly due to technical obstacles in obtaining statistically significant spatial and temporal results. We addressed this challenge by using remote sensing technology: the Landsat 8 Operational Land Imager (OLI). We proposed a new, robust remote-sensing algorithm to estimate ZSD from OLI imagery using red and green band-ratio, leading to MAPE of 21.68% and RMSE of 0.076m for ZSD ranging from 0.1m to 1.05m. After satisfactory image-based validation, the algorithm was implemented on OLI data to derive ZSD patterns over ER and DTL from 2013 to 2017. Several crucial findings can be drawn: 1) Spatial-temporal patterns of ZSD exhibited notable fluctuations over both ER and DTL, and they also demonstrated a significant correlation with each other because of the opposite temporal cycle of ZSD fluctuations between ER and DTL; 2) Temporally, monthly fluctuations of ZSD between ER and DTL had opposite temporal cycles, which was mainly attributed to the surface runoff and sediment discharge driven by the outbound runoff variations of TGD. Spatially, the heterogeneity of the ZSD pattern in ER might have resulted from the different geographical regions being divided by large anthropologic hydrological facilities, such as TGD; 3) The relationship between ZSD and total suspended matter (TSM) showed a significant negative correlation, as did the relationship between ZSD and Kd(490). These findings demonstrate that TSM often plays a principal role in light attenuation of extremely turbid inland waters; 4) An inversed phenomenon of water clarity was observed at the intersection of DTL and the Yangtze River around Chenglingji site (YRAC), which was due to the opposite temporal cycle of ZSD fluctuations between DTL and ER after the impoundment of TGD; and 5) Owing to the analysis of noise-equivalent ZSD, OLI data can be used to derive ZSD, since the imagery uncertainty is 0.07m by means of our band-ratio algorithm, which demonstrates similar results to MODIS. The proposed ZSD-derived algorithm in this study could be suitable for other turbid lakes or reservoirs to formulate related strategies of water quality management in the middle and lower Yangtze River basin, and the unveiled findings here improve our understanding of ZSD spatiotemporal fluctuations in large river-connected lakes, such as Poyang Lake.

[Remote Sensing of Chlorophyll-a Concentrations in Lake Hongze Using Long Time Series MERIS Observations].

Chlorophyll-a (Chl-a) concentrations are usually measured as the proxy of phytoplankton biomass and used to evaluate the trophic status of inland waters. Based on 49 in situ samples taken from two measurement campaigns in Lake Hongze in 2016, we evaluate the performance of five Chl-a estimation algorithms (including the band ratio, three-band, FLH algorithm, MCI, and UMOC algorithms). The results showed that the UMOC model was the most suitable model for the estimation of Chl-a in Lake Hongze. The mean relative error (MRE) of UMOC was 32.30%, much lower than the band ratio algorithm (75.17%), three-band algorithm (62.44%), FLH algorithm (45.87%), and MCI algorithm (56.95%). The best-performing UMOC model was applied to the atmospherically corrected 689 MERIS images between 2002-2012 and long time series MERIS Chl-a concentration estimation products were acquired. Between 2002 and 2012, the mean Chl-a concentration in Lake Hongze was 19.560 mg·m-3 with substantial spatial and temporal variability. Based on the variability of monthly mean Chl-a concentrations in each pixel, the Lake Hongze waterbody was divided into three water types, Region A, Region B, and Region C. The annual mean Chl-a concentrations of Region B and Region C showed no significant changes, while the concentrations in Region A increased markedly. The analysis of the meteorological factors showed that the fluctuations of the annual mean Chl-a concentrations in Region B and Region C were mainly affected by annual precipitation, suggesting that the Chl-a concentrations of these two regions are dominated by the intensity of the lake flow. The annual mean Chl-a concentrations of Region A showed a strong negative correlation with the annual mean wind speed. The descending trend of the annual wind speed may enhance the eutrophication degree of this region, threatening the safety of the water quality of the South-North Water Transfer Project. The Chl-a concentrations showed a strong positive correlation with the distance from the Huaihe Estuary in the wet season suggesting that the Huaihe River has an obvious inhibitory effect on algal biomass in Lake Hongze during this period.

Enantioselective Syntheses of Heteroyohimbine Natural Products: A Unified Approach through Cooperative Catalysis.

Alstonine and serpentine are pentacyclic indoloquinolizidine alkaloids (referred to as "anhydronium bases") containing three contiguous stereocenters. Each possesses interesting biological activity, with alstonine being the major component of a plant-based remedy to treat psychosis and other nervous system disorders. This work describes the enantioselective total syntheses of these natural products with a cooperative hydrogen bonding/enamine-catalyzed Michael addition as the key step.

Catalytic enantioselective synthesis of 2-aryl-chromenes.

An enantioselective Pd-catalyzed 6-endo-trig reaction for the synthesis of 2-aryl-chromenes has been developed. A systematic optimization of a TADDOL-derived ligand set resulted in the identification of a novel monodentate phosphoramidite-palladium catalyst that accesses 2-aryl-2H-chromenes with high yield and enantioselectivity under mild conditions. The products obtained from this method can be transformed into biologically active compounds through functionalization of the chromene alkene.

Ligand-elaboration as a strategy for engendering structural diversity in porous metal-organic framework compounds.

A series of 4,4'-ethynylenedibenzoic acids were synthesized and used in the construction of Zn-based, mixed-ligand metal-organic frameworks; through variation of functionality in the 3- and 3'-positions of these linkers, a collection of MOFs with differing connectivities and varying levels of interpenetration was obtained.

Efficient and selective Al-catalyzed alcohol oxidation via Oppenauer chemistry.

A highly active and selective Al-based catalytic Oppenauer (O) oxidation is reported. Quantitative and selective oxidations of a variety of benzylic, propargylic, allylic, and aliphatic primary and secondary alcohols were achieved using nitrobenzaldehyde derivatives as the oxidant and simple aluminum compounds as precatalysts.