1. Computational Modelling of Aerosol Cycle An Integrated Environmental Modelling System and Its Applications Dr. Yaping Shao CEMAP, School of Mathematics The University of New South Wales Sydney, Australia Tel: 61 2 9385 5746; Fax: 61 2 9386 7123 email: y.shao@unsw.edu.au

2. Aerosols –Aerosols are small particles suspended in air. The sizes of aerosols range between 0.1 - 20 microns; –Aerosol sources include natural and human induced ones.

3. Aerosol Research: Climate and Weather Directly, aerosols affect atmospheric radiation budget through scattering and absorbing; Indirectly, aerosols modify the optical properties and lifetimes of clouds; Dust (global emission): ~ 3000 Mt/yr. Sea salt: ~ 1300 Mt/yr. Dust (mean column load): ~ 65 mg m -2 Sea salt: ~ 7 mg m -2

4. Dust storm in Africa: 27 July 1998, Algeria and Mali

5. A severe dust storm over China (16 April 1998)

6. Dust clouds seen from satellite picture (14 April 1998)

7. Aerosols cause air-quality hazards in populated areas, e.g., Beijing; Many contaminants which pose significant risks to human health and the environment are found or associated with dust, including metal, pesticides, dioxins and radionuclides. Aerosol Research: Air quality

8. A severe dust storm (acknowledgement)

9. In agricultural areas, soil erosion depletes fine particles which are rich in organic matters and soil nutrients. This leads to land degradation; Wind erosion also reduces water, resulting in desertification. Land-Use Sustainability

10. A dust storm in an agricultural area

11. Soil Erosion

12. Melbourne 08-02-1983 dust storm: Nutrient content in soil particles < 44 microns

13. Melbourne 08-02-1983 dust storm

14. Mineral Aerosol Cycle –Entrainment: atmosphere and land-surface interactions; multi-disciplinary; –Transport: atmospheric circulation; atmospheric boundary layers; turbulence; two phase flow problem –Deposition: turbulent diffusion; clouds and precipitation.

15. Integrated Environmental Modelling –How can such complex environmental problems be simulated and predicted? –Computational environmental modelling: the integration of dynamic models with spatially distributed data –Atmosphere-land surface interactions –Air quality –Aerosol cycle –Land surface hydrology and salinity

16. Framework I

17. Computational Environmental Modelling System (CEMSYS_3) –Atmospheric prediction model (HIRES): high- resolution limited-area; nested in GCM, self- nested; 3rd order upwinding and semi- lagrangian schemes; clouds and radiation. –Land surface (ALSIS): Soil moisture, temperature; fluxes of energy, mass and momentum; –Aerosol cycle: entrainment, transport and deposition. –Air quality, etc

18. Framework of CEMSYS_3 (partial)

19. Physical processes involved in wind erosion

20. Particle Motion –Saltation: hop motion of sand particles; –Suspension: small particles can remain suspended once airborne.

21. The capability of wind to cause erosion is quantified by surface friction velocity, u *, depending on wind speed and surface roughness The ability of the surface to resist erosion is quantified by threshold friction velocity u *t, depending on soil texture, compactness, moisture content and surface coverage Modeling u *t is difficult Friction velocity & threshold friction velocity

22. Entrainment of Coarse Particles Balance of aerodynamic, gravity and cohesive forces, f a, f g and f i, determines the entrainment; For coarse particles, f a overcome f g and f i ; Friction velocity u * measures aerodynamic forces; Threshold friction velocity u *t measures retarding forces. Shao-Lu model for u *t is

23. Entrainment of Fine Particles The Entrainment mechanisms for coarse and fine particles differ as the importance of forces change. f g  d 3, f a  d 2 and f i  d; f i dominates.

24. Dust Emission Mechanisms F a, aerodynamic lift. Particles can be lifted directly by f a, but emission is weak; F b, saltation bombardment. Striking particles cause local impacts, overcome f i, result in strong emission; F c, aggregates disintegration. Fine particles exist as aggregates. Weak events, they behave as grains. Strong events, they disintegrate. Dust-emission rate: F = F a + F b + F c

25. Soil particle size ranges: 0.1  m - 2 m Gravel: 2000  m < d  2m Sand: 63 < d  2000  m Silt: 4 < d  63  m Clay: d  4  m Silt and clay particles are dust. Particle-size Distribution

26. Particle-size Distributions p s (d): sediment particle-size distribution (psd); p m (d): in-situ soil psd; minimally dispersed analysis; p f (d): fully-disturbed soil psd; fully-dispersed analysis.

27. Model for p s (d) Limiting cases

28. Example of p s (d)

29. Fractions of Fine Particles  m : free dust, lower limit for dust emission from unit soil mass;  f : not free dust, released through saltation impact and aggregates disintegration, upper limit for dust emission from unit soil mass;  s : aerosol in suspension

30. Theory of Saltation Saltation plays a critical role in the process of dust emission. Two quantities are of particular importance, namely, the streamwise saltation flux, Q, and the number flux of striking particles, n s

31. Volume Based Model for F b Particle trajectory is (X T, Y T ) in soil, forms a crater of volume 

32. Volume Based Model for F b Trajectory from equation of particle motion; c b  f : fraction released; (1-c b )  f : fraction retained;

33. Volume Based Model for F b Particle trajectory is (X T, Y T ) in soil, forms a crater of volume  ; Trajectory from equation of particle motion; c b  f : fraction released; (1-c b )  f : fraction retained;

34. Aggregates Disintegration: F c Aggregates disintegration occurs as they strike surface. Corresponding to n s, the mass flux of particles striking surface is mn s. F c (d s ) = c c f c m n s c c : a coefficient

35. Total Dust Emission: F Divide particles into I size groups, mean d i, increment  d i ; Consider emission of i group

36. Model of Particle Size Distribution Emission model requires p m (d) and p f (d). Express as sum of J log-normal pdfs with parameters w j, D j and  j; both for p m (d) and p f (d) for sand, loam and silty clay.

37. c c Model requires  ; c   E  fi /  : fraction of release; c Y = 1/7 c o, order 0.1.

38. Quantities Required u * : friction velocity; u *t : threshold friction velocity for surface; p m (d): minimally-dispersed psd; p f (d): fully-dispersed psd;  b,  p : bulk soil and particle density; s: soil drag coefficient; p ys :vertical component of plastic pressure.

39. Results

40. Conclusions for Emission Model Concept: F is related to Q; Mechanisms: saltation bombardment and aggregates disintegration; Models for F b and F c ; Soft soils, F b dominates;Hard soils, F c dominates; psds are used to eliminate empirical parameters; psds modeled using log-normal pdfs; Emission rates compare well with observations.

41. Transport: Lagrangian Particles are individuals; Trajectories are determined by integrating equations of motion; Isentropic trajectories on surface of constant potential temperature; Fluid parcel and particle are at height z f t-1 = z p t-1 at t-1, fluid moves to z f t, particle to z p t =z f t +w t  t.

42. Transport: Eulerian Particulate phase is a continuum; Particle concentration obeys advection-diffusion type of conservation equation; K px : particle eddy diffusivity; S r : wet and dry removal; S c : dry and wet convection; F 0 : dust flux at surface

43. Inertial and Trajectory Crossing

44. Particle Eddy Diffusivity

45. Deposition Dry-deposition flux F d = -  w d [c(z)-c(0)] c(0), c(z): concentration at surface and reference level; w d : dry-deposition velocity. Single-layer dry-deposition model w d =-w t +g bb +g bm g bb: molecular conductance; g bm : impaction conductance; f r : ratio of pressure drag to total drag; w d =-w t +g a [f r a p e m +(1-f r )a v S c -2/3 ]

46. Wet Deposition Wet deposition is the removal of aerosols by precipitation. The processes is extremely complicated, but is commonly calculated using F w =  w p r0 s 0 c 0 s 0 : scavenging ratio is a function of many parameters, but ranges from 100 to 2000. p r0 : rain received at the surface; c 0 : concentration in rain water.

47. Example 1: How does the Scheme Work

48. Comparison with Field Measurements

49. Land Surface Data

50. Weather pattern

51. Feb. 1996

52. Soil Erosion

53. Threshold Friction Velocity

54. Friction Velocity

55. Concentration Cross Section

56. Total Suspended Dust Time Series

57. Comparison with Satellite Image

58. Aerosol Concentration

59. Surface Concentration: Birdsvill, Feb. 1996

60. Higher Resolution

62. A comprehensively integrated system has been developed for the simulation and prediction of the entire mineral dust cycle, from entrainment, transport to deposition. CEMSYS_3 has a much wider range of applications; I have illustrated how the entire cycle can be modeled. Each of the modeling components constitutes an interesting research area. I have concentrated on dust emission in this talk; Coupling dynamic models with spatially distributed data has enabled the predictions of dust storm events. Summary