Vertical distribution of suspended particulate matter and its response to river discharge and seawater intrusion: a case study in the Pearl River Estuary during the 2020 dry season

The vertical distribution of suspended particulate matter (SPM) in the Pearl River Estuary (PRE) during winter has not been widely reported. The aim of this paper is to describe the high-resolution vertical distribution of SPM along the transect based on the in-situ observations (including SPM, attenuation coefficient, and particle backscattering coefficient) from three transects of the winter cruise in the northern South China Sea in 2020. The empirical relationship between SPM and bio-optical parameters with correlation coefficients greater than 0.7 is also established and combined with model data to further discuss the mechanism of river discharge and seawater intrusion effects on the vertical distribution of SPM. In the horizontal distribution, the mass concentration of SPM was high in the nearshore region and was low in the offshore region. In the vertical direction, the mass concentration of SPM in the offshore region was more homogeneous, while the mass concentration of SPM in the nearshore region varied greatly, showing a pattern of high bottom and middle layer or high bottom and surface layer. The difference in the vertical distribution of SPM in the nearshore area is the combined effect of river discharge and seawater intrusion on the resuspension of sediment and the inhibition of the spread of high SPM

Existence of Solutions to Elliptic Problem with Convection Term and Lower-Order Term

In this paper, we establish the existence of solutions to the following noncoercivity Dirichlet problem −divMx∇u+up−1u=−divuEx+fx,x∈Ω,ux=0,x∈∂Ω, where Ω⊂ℝNN>2 is a bounded smooth domain with 0∈Ω, f belongs to the Lebesgue space LmΩ with m≥1,p>0. The main innovation point of this paper is the combined effects of the convection terms and lower-order terms in elliptic equations

Culture Clash in the Boardroom (HBR CASE STUDY)

The article presents a case study about a fictional chemical-manufacturing joint venture in China that involves a German parent firm and its Chinese partner. The German firm has insisted upon scrupulous compliance with Western standards regarding industrial safety, business ethics, and the environment. However, its Chinese partners are annoyed that they cannot use gifts, commissions, and other favors said to be frequently used in China in order to secure business. Disagreement has arisen over whether the joint venture should pay a commission to a potential customer's purchasing agent in order to clinch a very large sale

Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea

Ocean colour remote sensing is used as a tool to detect phytoplankton size classes (PSCs). In this study, the Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) phytoplankton size classes (PSCs) products were compared with in-situ High Performance Liquid Chromatography (HPLC) data for the South China Sea (SCS), collected from August 2006 to September 2011. Four algorithms were evaluated to determine their ability to detect three phytoplankton size classes. Chlorophyll-a (Chl-a) and absorption spectra of phytoplankton (aph(λ)) were also measured to help understand PSC’s algorithm performance. Results show that the three abundance-based approaches performed better than the inherent optical property (IOP)-based approach in the SCS. The size detection of microplankton and picoplankton was generally better than that of nanoplankton. A three-component model was recommended to produce maps of surface PSCs in the SCS. For the IOP-based approach, satellite retrievals of inherent optical properties and the PSCs algorithm both have impacts on inversion accuracy. However, for abundance-based approaches, the selection of the PSCs algorithm seems to be more critical, owing to low uncertainty in satellite Chl-a input dat

Retrieving Phytoplankton Size Class from the Absorption Coefficient and Chlorophyll A Concentration Based on Support Vector Machine

The phytoplankton size class (PSC) plays an important role in biogeochemical processes in the ocean. In this study, a regional model of PSCs is proposed to retrieve vertical PSCs from the total minus water absorption coefficient (at-w(λ)) and Chlorophyll a concentration (Chla). The PSC model is developed by first reconstructing phytoplankton absorption and Chla from at-w(λ), and then extracting PSC from them using the support vector machine (SVM). In situ bio-optical data collected in the South China Sea from 2006 to 2013 were used to train the SVM. The proposed PSC model was subsequently validated using an independent PSC dataset from the Northeast South China Sea Cruise in 2015. The results indicate that the PSC model performed better than the three components model, with a value of r2 between 0.35 and 0.66, and the absolute percentage difference between 56% and 181%. On the whole, our PSC model shows a remarkable utility in terms of inferring vertical PSCs from the South China Sea