Loading presentation...

Present Remotely

Send the link below via email or IM


Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.


Copy of Copy of Soil Horizons

Soil horizons, why and how they form

mahmood fazeli

on 1 August 2014

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of Copy of Copy of Soil Horizons

Fate, Spatial distribution and Transport Modelling of Engineered Nano Particles in Soil
Andres Herrera
our Team
Dr. Amir Fotovat
specialty and interests:
Soil chemistry
Nanomaterials in soil
Dr. Alireza Astaraei
specialty and interests:
Soil Salinity
plant nutrition
solute behavior
Soil Physics
solute transport in soil
Soil Physics
Engineered nanomaterials (ENMs)1 are being incorporated into new commercial products at an increasing rate (Wiesner et al., 2006).
There are many unknowns regarding the ecological or human health risk associated with exposure to nanoscale materials.
To determine the nature and extent of possible exposure to ENMs in the environment, methods will be needed to predict their fate and transport in environmental media, understand the biologically relevant forms of ENMs that persist in the environment and, ultimately, confirm their occurrence in media (e.g., drinking water and foods) to which humans and animals may be exposed
At the nano scale, chemicals can exhibit behaviors that are unique when compared to behaviors of materials in a larger scale,
predictive modeling will be required to represent the relationships among: (1) the manner in which ENMs are released into the environment, (2) the behavior, fate, and transport of ENMs in various environmental compartments, (3) the exposure of human and ecological receptors to ENMs, and (4) the adverse effects to ENMs as exposures occur over time and space.
the information that predictive models provide will be an essential component of the decision-making process regarding safe management, use, and disposal of ENMs.
A predictive modeling strategy to evaluate ENM risks.
source-to-outcome framework to operationalize the purposes of exposure assessment.
Source-to-outcome framework for ecological exposure research (US EPA, 2009)
Key Question.
What are the major processes and/or properties that govern the environmental fate, transport, and transformation of manufactured nanomaterials, and how are these related to the physical and chemical properties of those materials?
it is widely recognized that there are many obstacles to model development and, in general, to conducting environmental risk assessments of ENMs that provide meaningful information for risk managers (e.g., Greiger et al., 2009, 2010; Wiesner et al., 2009).
Engineered Nanomaterials

having at least one dimension less than 100 nm and exhibiting properties that are in some way unique relative to the same materials in larger, conventional forms.
Classification (based on the chemical composition)

1- Carbonaceous ENMs
fullerenes known as buckyballs
carbon nanotubes (CNTs)
Common applications include plastics, catalysts, battery and fuel cell electrodes, super-capacitors, water purification, orthopedic implants, conductive coatings, adhesives and composites, sensors, and as components in electronics, aircraft, aerospace and automotive industries.

2- Metal ENMs
include metal oxides as well as zero-valent metals.
Titanium dioxide
zinc oxide
zero-valent iron

3- Semiconductor Materials, Including Quantum Dots

4- Nanopolymers/Dendrimers
Proporties of ENMs that Influence Environmental Behavior
Key Processes Influencing Environmental Behavior
Challenges to Modeling Nanomaterials

Complexity of ENM transport characteristics and associated data gaps
Variability in nanomaterial types and properties
Limitations of current modeling approaches
Need for near term risk management decisions.
About ENMs
Literature review
Purpose and Scope of this study
Experimental Design

Comparing the efficacy of MNM and Hydrus models for prediction the transport of TiO2 and Ag Nanoparticles in different soils.

MNM model is developed specifically for the simulation of nanparticle transport in porous media and does account for some of the key processes for nanomaterial behavior (attachment/detachment, blocking, and ionic strength effects). Therefor it can produce more accurate estimation of transport model parameters tha Hudrus for column experiment.

Transport and deposition of functionalized CdTe nanoparticles in saturated porous media (Torkzaban et al. 2010)

Accusand, ultrapure quartz, and iron-coated sand

The observed transport behavior in ultrapure quartz and iron-coated sand was consistent with conventional colloid deposition theories.

The effluent breakthrough occurred with a delay

they proposed that nanoscale charge heterogeneities on clay particles on Accusand surface played a key role in QD deposition
stability of TiO2 nanoparticles in soil suspensions and their transport behavior through saturated soil columns were studied (Fang et al. 2008)

Twelve surface (0–20 cm) soils

The suspended TiO2 contents in soil suspensions after 24 h were positively correlated with the
dissolved organic
carbon and
clay content
of the soils, but were negatively correlated with
ionic strength, pH and zeta potential

In soils containing soil particles of relatively large diameters and lower solution ionic strengths, a significant portion of the TiO2 (18.8–83.0%) readily passed through the soils columns,
TiO2 was significantly retained by soils with higher clay contents and salinity.

TiO2 aggregate sizes in the column outflow significantly increased after passing through the soil columns.

The estimated transport distances of TiO2 in some soils ranged from 41.3 to 370 cm, indicating potential environmental risk of TiO2 nanoparticles to deep soil layers.
The subsurface mobility of two carbon nanoparticles: nano-fullerenes (nC60) and multi-walled carbon nanotubes (MWCNTs) (Cullen etal. 2009)

Numerical model is based on colloid filtration theory (CFT)

nanoparticles were predicted to be less mobile in heterogeneous systems compared to the homogeneous systems with the same average hydraulic properties.
The transport of Fe3O4, TiO2, CuO, and ZnO was measured in a series of column experiments (Ben-Moshe et al. 2010)

uniform, spherical glass beads

breakthrough curves at the outlet were measured

Different factors affecting the mobility of the nanoparticles such as
ionic strength,
organic matter (humic acid),
flow rate

demonstrating the highest mobility
Transport of functionalized carbon nanotubes or CNTs (Tian et al. 2011).

water-saturatedsand columns

acid-cleaned, baked, and natural sand

The CNTs were highly mobile in the acid-cleaned sand columns
showed little transport in the both natural and baked sand columns

irreversible retention

Results suggest that the retention and transport of the functionalized CNTs in natural sand porous media were
mainly controlled
by strong
surface deposition
through the electrostatic and/or hydrogen-bonding attractions between surface function groups of the CNTs and metal oxyhydroxide impurities on the sand surfaces.
C is the particle concentration in solution,
t is time
x is the travel distance,
D is the dispersion coefficient
vp is the average travel velocity of particles,
k is the particle deposition rate coefficient.
L is the column length,
C0 is the initial effluent particleconcentration,
Cf is the final effluent particle concentration after the breakthrough curve has reached a plateau
(Simunek et al. 2006)
simulates the movement of water, heat, multiple solutes, and particulates in variably saturated porous media (unsaturated and saturated zones).

In addition to key processes relevant to transport in porous media, the model utilizes colloid filtration theory to describe the attachment/detachment behavior of particulates in porous media systems.

The model has been extensively used, verified, and peer reviewed.

A graphical user interface is available.
HYDRUS considers advection, diffusion and dispersion, sorption, and degradation of up to 15 solutes.

In addition, HYDRUS can evaluate non-equilibrium mass transfer through two-region, dual porosity sorption formulation, which considers mobile and immobile regions of the pore space.

Filtration theory is used to describe attachment/detachment behavior of particulates (viruses, colloids, or bacteria).
The flow model is based on a finite element solution to Richard’s equation for variably saturated flow.

The transport model is based on a finite element solution to the advection-dispersion equation.
(Tosco and Sethi 2009)

The model simulates one-dimensional transport of nanoparticles in porous media.

The model accounts for key nanoparticle behaviors, including attachment, detachment, and blocking, as well as transient ionic strength effects.

The authors have developed a unique empirical relationship for attachment, detachment, and blocking coefficients as a function of ionic strength.
The model considers potentially transient ionic strength conditions, which can impact the stability of nanoparticle suspensions. The model accounts for particle attachment and detachment using one or two linear and/or langmuirian sorption sites and first-order kinetic attachment coefficients. The model also considers potential blocking phenomena, whereby all sorption sites become occupied.
Input parameters include: inlet colloid concentration, solid bulk density, dispersion coefficient, Darcy velocity, porosity, attachment and detachment coefficients, maximum attached particle concentration (for blocking), inlet salt concentration (for ionic strength effects).
Corn plant
Our Project needs your accurate advices!

I hear your !!!

Thank You
The development of modeling nanomaterial behavior in the environment is in its infancy.
Because of different characteristics, TiO2 and Ag Nanoparticles show different type of behavior and transport in soil.
Porious media characteristics and its variations affect the transport of TiO2 and Ag Nanoparticles and therefore different fate and transport .
The Transport of , TiO2 and Ag Nanoparticles in soil is similar to other solute and colloids
Numerical solution of Convection-Dispersion Equation (CDE), using breakthrough curves in hydrus and MNM models can estimate the transport model parameters of TiO2 and Ag Nanoparticle.
There is a correlation between water retention curve and hydraulic characteristics and transport model parameters.
TIO2 Nanoparticles
Ag Nanoparticles
Solute and colloids transport in soil
Convection-Dispersion Equation
Mahmood Fazeli (Ph.D student)
Dr. Hojat Emami
What is the fate of ENMs in soil systems?
Determination breakthrough curves of TiO2 and Ag Nanoparticles in saturated condition in columns including different porous media as clean beads, acid washed sand, sandy soil, loamy and clayey soil.

Investigation the effect of ion strength and organic matter on TiO2 and Ag Nanoparticles transport in clean porious media.
Determination of the transport model parameters of TiO2 and Ag Nanoparticle using breakthrough curves and particle concentration data in different time and soil depth.
Investigation of the correlation between water retention curve, hydraulic characteristics and transport model parameters of TiO2 and Ag Nanoparticle.
Comparing the transport of TiO2 and Ag Nanoparticle in different porous media.
Using determined parameters of transport model for prediction of the concentration of TiO2 and Ag Nanoparticles in different soil depth at different time at the presence of corn plant.
Investihation of the process and factors affecting the retention of TiO2 and Ag Nanoparticles in soils.
Full transcript