Application of Dynamically Constrained Interpolation Methodology to the Surface Nitrogen Concentration in the Bohai Sea

Zheng, Quanxin; Li, Xiaona; Lv, Xianqing

doi:10.3390/ijerph16132400

Cited by 8 publications

(4 citation statements)

References 29 publications

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“…where C denotes the concentration of pollutants; t and x, y, z are the time and Cartesian coordinates, respectively; u and v represent the horizontal velocities (in the x and y directions, respectively); w represents the vertical velocity (in the z direction); K H and K V denote the horizontal and vertical diffusion coefficients, which are set as 100 m 2 s −1 and 10 −5 m 2 s −1 , respectively; and r denotes the degradation coefficient of petroleum hydrocarbon pollutants. Compared with previous research in which the degradation coefficient is generally determined to be zero [12,16], this article defines the degradation coefficient r as a time-space-varying parameter in consideration of the degradation of newly injected terrestrial petroleum hydrocarbons.…”

Section: Model Equationmentioning

confidence: 99%

Inversion of the Degradation Coefficient of Petroleum Hydrocarbon Pollutants in Laizhou Bay

Huang

Han

et al. 2021

JMSE

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When petroleum hydrocarbon pollutants enter the ocean, besides the migration under hydrodynamic constraints, their degradation due to environmental conditions also occurs. However, available observations are usually spatiotemporally disperse, which makes it difficult to study the degradation characteristics of pollutants. In this paper, a model of transport and degradation is used to estimate the degradation coefficient of petroleum hydrocarbon pollutants with the adjoint method. Firstly, the results of a comprehensive physical–chemical–biological test of the degradation of petroleum hydrocarbon pollutants in Laizhou Bay provide a reference for setting the degradation coefficient on the time scale. In ideal twin experiments, the mean absolute errors between observations and simulation results obtain an obvious reduction, and the given distributions can be inverted effectively, demonstrating the feasibility of the model. In a practical experiment, the actual distribution of petroleum hydrocarbon pollutants in Laizhou Bay is simulated, and the simulation results are in good agreement with the observed ones. Meanwhile, the spatial distribution of the degradation coefficient is inverted, making the simulation results closer to the actual observations.

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Section: Model Equationmentioning

confidence: 99%

Inversion of the Degradation Coefficient of Petroleum Hydrocarbon Pollutants in Laizhou Bay

Huang

Han

et al. 2021

JMSE

Self Cite

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“…is the diffusion term. The transport model has been used in previous studies and proven to be stable and reliable [21][22][23]. The region of the model is the Bohai Sea (37~41…”

Section: Modelmentioning

confidence: 99%

Study on Total Control of Total Nitrogen in the Laizhou Bay

Peng

Geng

Mao

et al. 2021

Water

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Human activity imposes a stronger and increasing impact on the coastal environment by land-based discharge and run-off pollution inputs. Land-based total nitrogen (TN) pollution, as the main cause of eutrophication in the Laizhou Bay, China, should be controlled effectively. Based on a three-dimensional pollution transport model, 20 groups of allocation schemes were designed under the requirement that the allocations of three estuaries in the inner bay were adjusted properly, while the two estuaries in the outer bay, i.e., the Yellow River and the Jiehe River, were kept unchanged. The statistical results show that the area ratio of heavily polluted seawater to the entire Laizhou Bay reached the maximum (35.14%) when the load allocation of the Xiaoqinghe River accounted for a high proportion (65%), and the Yuhe River and the Jiaolaihe River accounted for 15% and 20%, respectively. Overall, the pollution levels of the Laizhou Bay were positively associated with the allocation of the Xiaoqinghe River. Reducing pollutant allocation in the Xiaoqinghe River contributed most to the improvement of the seawater quality of the entire Laizhou Bay, and it was followed by a reduction in the Yuhe River and the Jiaolaihe River.

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“…Wang et al [35] established a three-dimensional viscous sediment transport model with the adjoint assimilation method, and obtained good numerical simulation results. In addition, the adjoint assimilation method has also been applied in numerous other ecosystem dynamics and pollutant simulation studies [36][37][38][39].…”

Section: Adjoint Modelmentioning

confidence: 99%

Inversion of Initial Field Based on a Temperature Transport Adjoint

Jiao

Huang

Wang

et al. 2021

JMSE

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The setting of initial values is one of the key problems in ocean numerical prediction, with the accuracy of sea water temperature (SWT) simulation and prediction greatly affected by the initial field quality. In this paper, we describe the development of an adjoint assimilation model of temperature transport used to invert the initial temperature field by assimilating the observed data of sea surface temperature (SST) and vertical temperature. Two ideal experiments were conducted to verify the feasibility and validity of this method. By assimilating the “observed data”, the mean absolute error (MAE) between the simulated temperature data and the “observed data” decreased from 1.74 °C and 1.87 °C to 0.13 °C and 0.14 °C, respectively. The spatial distribution of SST difference and the comparison of vertical data also indicate that the regional error of vertical data assimilation is smaller. In the practical experiment, the monthly average temperature field provided by World Ocean Atlas 2018 was selected as background filed and optimized by assimilating the SST data and Argo vertical temperature observation data, to invert the temperature field at 0 a.m. on 1 December 2014 in the South China Sea. Through data assimilation, MAE was reduced from 1.29 °C to 0.65 °C. In terms of vertical observations data comparison and SST spatial distribution, the temperature field obtained by inversion is in good agreement with SST and Argo observations.

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Application of Dynamically Constrained Interpolation Methodology to the Surface Nitrogen Concentration in the Bohai Sea

Cited by 8 publications

References 29 publications

Inversion of the Degradation Coefficient of Petroleum Hydrocarbon Pollutants in Laizhou Bay

Inversion of the Degradation Coefficient of Petroleum Hydrocarbon Pollutants in Laizhou Bay

Study on Total Control of Total Nitrogen in the Laizhou Bay

Inversion of Initial Field Based on a Temperature Transport Adjoint

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