1 D steady state diffusion equation in the atmosphere

In summary, to solve your 1-D steady state differential equation numerically in MATLAB, you will need to replace each derivative with a finite difference and then solve the resulting system of linear equations using MATLAB's built-in functions or numerical solvers.
  • #1
Juliousceasor
25
0
Hello,

I have a 1-D steady state (dc/dt=0) differential equation in the atmosphere. It looks like follows,

K*C'' + (K'+K/H)*C' + (1/H*K'- (K/H^2)*H'- (L+Si))C + S = 0

where,
C = concentration of the contaminant in the atmosphere at different heights z
K = vertical diffusion coefficient
H = scale height
L = decay constant
Si= constant
S = source term

C'' = double derivative of C w.r.t. z
C',K',H'= derivative of C,K,H w.r.t. z

K,H,Si,S,L are all known values.

I am trying to solve the above differential equation numerically by means of finite differences of 1st order with boundary conditions,

At the top boundary: C = S/L
at the bottom boundary k*dc/dx = 0



Can anyone tell me how to write this routine in matlab?

help would be greatly appricieted! :)
 
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  • #2
Thanks in advance!The first step is to convert the equation into a system of linear equations. To do this, you will need to replace each of the derivatives with finite differences. For example, if you have a grid of points z_i for i=1,...,n then the derivative of C with respect to z can be approximated by the finite difference C'(z_i) ~ (C_(i+1)-C_(i-1))/(2*dz). Here, dz is the spacing between two consecutive grid points. Using this approach, you can rewrite the differential equation as a system of linear equations. Once you have the system of linear equations, you can solve it using the MATLAB function "solve" or any other numerical method. You can also use MATLAB's built-in numerical solvers, such as ode45, to solve the differential equation directly. This is generally more accurate than using finite differences.
 

What is the 1 D steady state diffusion equation in the atmosphere?

The 1 D steady state diffusion equation in the atmosphere is a mathematical model that describes the movement of particles through the air over time. It takes into account factors such as concentration gradients, diffusion coefficients, and wind speed to predict the distribution of particles in the atmosphere.

How is the 1 D steady state diffusion equation used in atmospheric science?

The 1 D steady state diffusion equation is used in atmospheric science to study the transport and dispersion of pollutants, aerosols, and other particles in the atmosphere. It helps scientists understand how these particles move and spread, and can be used to make predictions about air quality and the impact of different emissions.

What are the assumptions made in the 1 D steady state diffusion equation?

The 1 D steady state diffusion equation assumes that the concentration of particles in the atmosphere is only affected by diffusion and advection (transport by wind), and that there are no sources or sinks of particles. It also assumes that the diffusion coefficient is constant and that the atmosphere is well-mixed, meaning particles are evenly distributed.

How is the 1 D steady state diffusion equation solved?

The 1 D steady state diffusion equation is typically solved using numerical methods, such as finite difference or finite element methods. These methods break the equation down into smaller parts and approximate the solution at each point in space and time. The solutions can then be combined to create a model of the overall particle distribution in the atmosphere.

What are the limitations of the 1 D steady state diffusion equation?

The 1 D steady state diffusion equation has several limitations, including the assumption of a well-mixed atmosphere and constant diffusion coefficient. It also does not take into account other factors that can affect particle movement, such as chemical reactions and variations in terrain. Additionally, it is a simplified model and may not accurately capture all the complexities of atmospheric diffusion in real-world scenarios.

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