A Model to Determine the Location of Heavy Metal Contaminant Source

We conducted a tracing model which was based on the process of dopamine diffusion in human brains, taking the diffusion coefficients and absorption coefficients into consideration. By combining with the spatial distributions of heavy metals plotted by ArcGIS, we can determine the contaminant sources and the results have high accuracy. Besides, we made an improvement in consideration of different transmission modes of heavy metal contaminants and the corresponding dilution factors.

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Magnetic properties of airborne particulate matter in Shanghai during dust storm events and the implications for heavy metal contaminant sources

Environmental Earth Sciences ◽

10.1007/s12665-014-3313-7 ◽

2014 ◽

Vol 72 (10) ◽

pp. 4167-4178 ◽

Cited By ~ 6

Author(s):

Peng Qian ◽

Limin Zhou ◽

Xiangmin Zheng ◽

Yan Dong ◽

Yongjie Wang

Keyword(s):

Heavy Metal ◽

Magnetic Properties ◽

Particulate Matter ◽

Dust Storm ◽

Airborne Particulate Matter ◽

Storm Events ◽

Airborne Particulate ◽

Contaminant Sources ◽

Metal Contaminant

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Heavy metal contaminant remediation study of western Xiamen Bay sediment, China: Laboratory bench scale testing results

Journal of Hazardous Materials ◽

10.1016/j.jhazmat.2009.06.138 ◽

2009 ◽

Vol 172 (1) ◽

pp. 108-116 ◽

Cited By ~ 5

Author(s):

Luoping Zhang ◽

Huan Feng ◽

Xiaoxia Li ◽

Xin Ye ◽

Youhai Jing ◽

...

Keyword(s):

Heavy Metal ◽

Xiamen Bay ◽

Bench Scale ◽

Laboratory Bench ◽

Contaminant Remediation ◽

Metal Contaminant

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Measurement of particle diffusion coefficients with high accuracy by dynamic light scattering

Progress in Colloid & Polymer Science - Optical Methods and Physics of Colloidal Dispersions ◽

10.1007/bfb0110753 ◽

2007 ◽

pp. 110-112

Author(s):

S. Will ◽

A. Leipertz

Keyword(s):

Light Scattering ◽

Dynamic Light Scattering ◽

Diffusion Coefficients ◽

High Accuracy ◽

Particle Diffusion

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Solving Inverse Problems of Unknown Contaminant Source in Groundwater-River Integrated Systems Using a Surrogate Transport Model Based Optimization

Water ◽

10.3390/w12092415 ◽

2020 ◽

Vol 12 (9) ◽

pp. 2415

Author(s):

Azade Jamshidi ◽

Jamal Mohammad Vali Samani ◽

Hossein Mohammad Vali Samani ◽

Andrea Zanini ◽

Maria Giovanna Tanda ◽

...

Keyword(s):

Inverse Method ◽

Transport Model ◽

Computation Time ◽

Forward Model ◽

New Approach ◽

Contaminant Source ◽

Contaminant Sources ◽

Speed Up ◽

River Cross Section

The paper presents a new approach to identify the unknown characteristics (release history and location) of contaminant sources in groundwater, starting from a few concentration observations at monitoring points. An inverse method that combines the forward model and an optimization algorithm is presented. To speed up the computation, the transfer function theory is applied to create a surrogate transport forward model. The performance of the developed approach is evaluated on two case studies (literature and a new one) under different scenarios and measurement error conditions. The literature case study regards a heterogeneous confined aquifer, while the proposed case study was never investigated before, it involves an aquifer-river integrated flow and transport system. In this case, the groundwater contaminant originated from a damaged tank, migrates to a river through the aquifer. The approach, starting from few concentration observations monitored at a downstream river cross-section, accurately estimates the release history at a groundwater contaminant source, even in presence of noise on observations. Moreover, the results show that the methodology is very fast, and can solve the inverse problem in much less computation time in comparison with other existing approaches.

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