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Modeling 234 Th in the ocean from scavenging to export flux

Modeling 234 Th in the ocean from scavenging to export flux. Nicolas SAVOYE Vrije Universiteit Brussel. Photo: C. Beucher. Modeling 234 Th in the ocean from scavenging to export flux. Th scavenging models. Estimating 234 Th export flux Steady vs non-steady state models

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Modeling 234 Th in the ocean from scavenging to export flux

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  1. Modeling 234Th in the ocean from scavenging to export flux Nicolas SAVOYE Vrije Universiteit Brussel Photo: C. Beucher

  2. Modeling 234Th in the ocean from scavenging to export flux Th scavenging models Estimating 234Th export flux Steady vs non-steady state models Toward 3D-models Photo: C. Beucher

  3. Modeling 234Th in the ocean from scavenging to export flux Th scavenging models Estimating 234Th export flux Steady vs non-steady state models Toward 3D-models Photo: C. Beucher

  4. Th scavenging models estimating Th (total, dissolved, particulate, colloidal) residence time and extrapolating the result to contaminant residence time (Th as contaminant analogous) understanding particle dynamics: adsorption / desorption aggregation / disaggregation remineralization sinking determining Th fluxes and estimating biogenic fluxes (POC, PON, BSi) in ocean

  5. k l U Tht l One-box models k l U Tht l f P = (l + k) [234Th] Broecker et al (1973) P + ([234Th]I – [234Th]) / f = (l + k) [234Th] Matsumoto et al (1975) P: production rate of 234Th from 238U [234Th]I: 234Th concentration in the input water from the deeper layer f: fluid residence time of the surface layer l: decay constants k: first-order removal rate constant

  6. k l U Tht l One-box models k l U Tht l f P = (l + k) [234Th] P + ([234Th]I – [234Th]) / f = (l + k) [234Th] Broecker et al (1973) 228Th/228Ra t = 0.7 year open ocean Matsumoto et al (1975) 234Th/238U t = 0.38 year open ocean Knauss et al (1978) 228Th/228Ra t = 0.52, 0.30 year shelf water t = 0.19 year shelf break Knauss et al (1978) 228Th/228Ra, 234Th/238U t = 0.03 year coastal water t = 1 / k

  7. k l U Tht l One-box models k l U Tht l f P = (l + k) [234Th] P + ([234Th]I – [234Th]) / f = (l + k) [234Th] Assumptions: • k: first order • steady state • diffusion, advection negligible

  8. lU k lTh U Thd Thp lTh S d[Thp] d[Thp] – = S + k [Thd] – [Thp] lTh dt dz two-box irreversible models Krishnaswami et al (1976) [Ud] lU = – [Thd] (lTh + k) d: dissolved; p: particulate; l: decay constants; k: first-order rate constant for the transfer from dissolved to particulate phases; S: settling velocity of particles

  9. lU k lTh U Thd Thp lTh S k [Ud] lU z lTh [Thp] lTh = 1 – exp S k + lTh two-box irreversible models Krishnaswami et al (1976) Steady state: t = 0.40 year (from 234Th/238U) S = 0.03 – 0.2 m/s (from 230Th/234U)

  10. dATh,d dATh,p AUlTh- ATh,dlTh - JTh JTh - ATh,plTh - PTh = = dt dt two-box irreversible models l kd l U Thd Thp l kp Coale and Bruland (1985, 1987) PTh = 0 = 0 d: dissolved; p: particulate; l: decay constant; kd, kp: first-order scavenging and suspended particulate removal rate constants, respectively; A: radioisotope activity; JTh: rate of removal of 234Th from dissolved to particulate form; PTh: rate at which 234Th is transported out of the surface layer by the particle flux.

  11. two-box irreversible models l kd l U Thd Thp l kp Coale and Bruland (1985, 1987) PTh Assumptions: • U is dissolved only • kd, kp: first order • steady state • diffusion, advection negligible • all particles have the same comportment • irreversible scavenging

  12. k-1 k1 two-box reversible models k1 l l U Thd Thp k-1 l S Nozaki et al (1981) P z [230Thd] + [230Thp] = 1 + S d: dissolved; p: particulate; l: decay constant; k1: first-order adsorption/scavenging rate constant; k-1: first-orderrate constantfor the transfer of 230Th from particles to solution; S: settling velocity of particulate 230Th; P: production rate of 230Th from 234U.

  13. two-box reversible models k1 l l U Thd Thp k-1 l S Bacon and Anderson (1982) Steady state: k1 P l (l + k1 +k-1) [Thp] = 1 – exp – z S (l + k1) l (l + k1 + k-1) P + k-1 [Thp] [Thd] = l + k1 d: dissolved; p: particulate; l: decay constant; z: depth; k1, k-1: first-order adsorption and desorption rate constants; S: settling velocity of particulate 230Th; P: production rate of Th from its parent.

  14. 1.4 1.2 1.0 0.8 k1 (yr-1) 0.6 0.4 0.2 0 0 5 10 15 20 25 [SPM] (µg/l) two-box reversible models k1 l l U Thd Thp k-1 l S Bacon and Anderson (1982) Assumptions: • U is dissolved only • k1, k-1: first order • steady state • diffusion, advection negligible • all particles have the same comportment

  15. three-box irreversible models r1 l l k1 U Thd Thsp Thlp r-1 l l Tsunogai and Minagawa (1978) cited by Moore and Hunter (1985) and Moore and Millward (1988) d: dissolved; sp, lp: small and large particles, respectively; l: decay constant; k1: first-order scavenging rate constant; r1, r-1: aggregation, disaggragationrate constants, respectively.

  16. modeling Th adsorption/desorption on mineral particles k1 k2 k3 Th ThX ThX’ ThX’’ k-1 k-2 k-3 Moore and Millward (1988): in vitro experiments X: surface binding site for Th; ThX: weakly-bound Th on the particle surface; ThX’: more strongly bound form or form held within the structure of particle; ThX’’: most strongly bound form of particulate Th; k: first-order adsorption/desorption rate constants. k-1 >> l The extent to which Th can desorb from the particle decreases as the particle ages

  17. three-box reversible models k1 k2 l l U Thd Thsp Thlp k-1 k-2 S l l Bacon et al (1985), Nozaki et al (1987) d: dissolved; sp, lp: small and large particles, respectively; l: decay constant; k1, k-1: adsorption and desorption rate constants, respectively; k2, k-2: aggregation and disaggragationrate constants, respectively; S: sinking speed.

  18. three-box reversible models g k1 r1 l l U Thd Thsp Thlp k-1 r-1 l l S Clegg and Whitfield (1991) d: dissolved; sp, lp: small and large particles, respectively; l: decay constant; k1, k-1: adsorption and desorption rate constants, respecitvely; r1, r-1: aggregation, disaggragationrate constants, respectively; g: remineralization rate constant; S: sinking.

  19. three-box reversible models b-1 k1 b2 l l U Thd Thsp Thlp k-1 b-2 l l w Murnane et al (1994) d: dissolved; sp, lp: small and large particles, respectively; l: decay constant; k1, k-1: second order adsorption and first order desorption rate constants, respecitvely; b2, b-2: first order aggregation and disaggragationrate constants, respectively; b-1: first order remineralization rate constant; w: sinking velocity.

  20. three-box reversible models: the Brownian pumping model k1 k-1 k1 k2 l l U Thd Thc Thfp k-1 k-2 S l l Honeyman and Santschi (1989) d: dissolved; c: colloids; fp: flitrable particles; l: decay constant; k1, k-1: adsorption and desorption rate constants, respectively; fast equilibrium; k2, k-2: aggregation and disaggragationrate constants, respectively; slow step S: sinking.

  21. four-box reversible model R k1 k2 k3 l l U Thd Thc Thsp Thlp k-1 k-2 k-3 l l l S Honeyman and Santschi (1992) cited by Baskaran et al (1992) d: dissolved; c: colloids; sp, lp: small and large particles, respectively; l: decay constant; k1, k-1: adsorption and desorption rate constants, respectively; k2, k-2: coagulation and repeptizationrate constants, respectively; k2, k-2: aggregation and disaggregationrate constants, respectively; S: sinking; R: remineralization

  22. l l l l four (or more)-box irreversible model h2 h3 l U Thd Thc Thsp Thlp k-1 k1 S1 k-2 k2 S2 k-3 k3 S3 Burd et al (2000) l: decay constant; d: dissolved; c: colloids; sp, lp: small (0.5 < < 56 µm) and large (> 56 µm) particles, respectively; k: adsorption or desorption rate constants; h: aggregation rate constants; S: settling loss.

  23. five-box (ir)reversible model Fd Fp1 Fp2 Fp4 Fp3 l Th Thsp Thlp Thlp U Thd 0.5-1µm 1-10µm 10-53µm >53µm l l l l l Guo et al (2002) d: dissolved; p: particulate; l: decay constant; F: flux.

  24. Th scavenging models: usual main assumptions k1 k2 b1 l l U Thd Thc Thsp Thlp k-1 k-2 b-1 l l l S • U is dissolved only • rate constants are (pseudo) first-order • steady state conditions • diffusion, advection negligible • remineralization negligible • adsorption on colloids or small particles only

  25. Th scavenging models: ideas for future directions • increasing the number of particle size classes (i.e. of boxes); • including biology (e.g. food web) -including physical properties of particles like density and stickiness

  26. [Thp] Thd Thp Kd = Partitioning coefficient: [Thd] Th scavenging models: importance of the chemistry of the particles from 230Th sediment trap data: Kd,CaCO3 = 9.0 x 106 > Kd,BSi = 3.9 x 105; no influence of lithogenics Chase et al (2002), Chase and Anderson (2004) Kd,lithogenics = 2.3 x 108 >Kd,CaCO3 = 1.0 x 106 > Kd,BSi = 2.5 x 105 Kuo et al (2004a, b)

  27. Importance of acid polysaccharides for 234Th complexation Polysaccharides: -highly surface-reactive exudates excreted by phytoplankton and bacteria -composed of deoxysugars, galactose and polyuronic acids - main component of transparent exopolymer particles (TEP)

  28. Importance of acid polysaccharides for 234Th complexation Quigley et al (2002)

  29. 3 4 y = 0.577x-0.788 y = 1.70x-0.192 3 R2 = 0.66 R2= 0.07 2 234Th residence time (day) 2 1 1 >53µm 0 0 0 0.5 1 1.5 2 2.5 0 2 4 6 8 10-53µm y = 53.9x-1.94 y = 528x-2.31 1-10µm 5 5 R2= 0.63 R2= 0.85 4 y = 37.9x-1.37 4 R2= 0.47 3 3 234Th residence time (day) 2 2 1 1 0 0 0 10 20 30 0 10 20 30 [uronic acid] (nM) [uronic acid] (nM) Importance of uronic acid for 234Th scavenging from Guo et al (2002) y = 0.577x-0.788 R2= 0.66

  30. Th scavenging models: ideas for future directions • increasing the number of particle size classes (i.e. of boxes) • including biology (e.g. food web) -including physical properties of particles like density and stickiness • including the chemistry of the ‘particles’

  31. k1 k-1 Th scavenging models: usual main assumptions k2 b1 l l U Thd Thc Thsp Thlp k-2 b-1 l l l S • U is dissolved only • rate constants are (pseudo) first-order • steady state conditions • diffusion, advection, horizontal transport negligible • remineralization negligible • adsorption on colloids or small particles only

  32. Th scavenging models: reversibility / irreversibilty of Th adsorption k1 k2 b1 l l U Thd Thc Thsp Thlp k-1 k-2 b-1 l l l S Quigley et al (2001)

  33. Th scavenging models: reversibility / irreversibilty of Th adsorption k1 k2 b1 l l U Thd Thc Thsp Thlp k-1 k-2 b-1 l l l S Quingley et al (2001)

  34. Modeling 234Th in the ocean from scavenging to export flux Th scavenging models Estimating 234Th export flux Steady vs non-steady state models Toward 3D-models Photo: C. Beucher

  35. k l U Th l Tanaka et al (1983) dATh AUl- AThl - ATh k = dt l AU l AU ATh2 = ATh1 - e-(l + k)T l + k l + k estimating 234Th export flux: steady vs non-steady state models 0.3 < tNSS/tSS < 3.8 (data from the Funka Bay, Japan) l: decay constant; k: removal rate constant; A: radioisotope activity; 1, 2: first and second samplings; T: time interval between 1 and 2; t: residence time SS, NSS: steady and non-steady state models.

  36. k l U Th l Tanaka et al (1983) dATh AUl- AThl - ATh k = dt l AU l AU ATh2 = ATh1 - e-(l + k)T l + k l + k estimating 234Th export flux: steady vs non-steady state models 0.3 < tNSS/tSS < 3.8 (data from the Funka Bay, Japan) Assumptions: • k is first order • removal and input rates of 234Th are constant within the observational period • diffusion and advection are negligible

  37. k l U Th l dATh AUl- AThl - ATh k = dt l AU l AU ATh2 = ATh1 - e-(l + k)T l + k l + k estimating 234Th export flux: steady vs non-steady state models Tanaka et al (1983) 20 1:1 15 Wei and Murray (1992); data from Dabob Bay, USA 10 SS residence time (day) 5 0 0 5 10 15 20 NSS residence time (day)

  38. l J1 U Thd Thp Layer 1 (surface) l l P1 l J2 U Thd Thp Layer 2 l l P2 Pi-1 l Ji U Thd Thp Layer i l l Pi estimating 234Th export flux: steady vs non-steady state models Buesseler et al (1992)

  39. ∂AiTh,d AiUl- AiTh,dl - Ji = ∂t ∂AiTh,p Ji + Pi-1 - AiTh,pl - Pi = ∂t ∂AiTh,t AiUl + Pi-1 - AiTh,tl - Pi = ∂t estimating 234Th export flux: steady vs non-steady state models Pi-1 Buesseler et al (1992) l Ji U Thd Thp l l Pi d: dissolved; p: particulate; t: total; l: decay constant; A: radioisotope activity; J: net flux of all forward and reverse exchange reactions; P: particulate 234Th flux.

  40. ∂AiTh,t AiUl + Pi-1 - AiTh,tl - Pi = ∂t AiU (1- e-l(t2-t1)) + Ai,t1Th,t e-l(t2-t1) – Ai,t2Th,t Pi = Pi-1 + l 1- e-l(t2-t1) estimating 234Th export flux: steady vs non-steady state models Pi-1 Buesseler et al (1992) l Ji U Thd Thp l l Pi d: dissolved; p: particulate; t: total; l: decay constant; A: radioisotope activity; t1, t2: time of the first and second sampling, respectively; i: layer of interest; J: net flux of all forward and reverse exchange reactions; P: particulate 234Th flux.

  41. AiU (1- e-l(t2-t1)) + Ai,t1Th,t e-l(t2-t1) – Ai,t2Th,t Pi = Pi-1 + l 1- e-l(t2-t1) estimating 234Th export flux: steady vs non-steady state models Pi-1 Pi-1 l l Ji U Tht U Thd Thp l l l Pi Pi Buesseler et al (1992) Assumptions: • - Pi is constant within the period t2-t1 • diffusion and advection are negligible

  42. 5000 SS NSS 4000 3000 234Th flux (dpm/m2/d) 2000 1000 0 16-Jan 02-Jan 30-Jan 13-Mar 13-Feb 27-Feb 24-Oct 19-Dec 05-Dec 21-Nov 07-Nov estimating 234Th export flux: steady vs non-steady state models Buesseler et al (2001), Southern Ocean

  43. 2500 SS NSS 2000 1500 234Th flux (dpm/m2/d) 1000 500 0 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 estimating 234Th export flux: steady vs non-steady state models Benitez-Nelson et al (2001), Aloha station, Pacific Ocean

  44. 2000 1500 NSS 234Th flux (dpm/m2/d) 1000 SS 500 0 7 mai 9 mai 11 mai 13 mai 15 mai 17 mai 19 mai 21 mai 23 mai 25 mai 27 mai 29 mai estimating 234Th export flux: steady vs non-steady state models Schmidt et al (2002), Dyfamed, Mediterranean Sea

  45. inpatch 234Th, 238U (dpm/l) out patch 234Th, 238U (dpm/l) 1.0 1.5 2.0 2.5 1.0 1.5 2.0 2.5 0 0 50 50 100 Depth (m) 100 150 150 238U 200 200 day -1 day -1 day 20 day 5 day 4 day 23 day 10 day 9 day 28 day 16 day 11 day 25 day 15 day 32 day 36 day 34 day 18 estimating 234Th export flux: steady vs non-steady state models Savoye et al (preliminary data), EIFEX, Southern Ocean

  46. 15000 10000 NSS in-patch SS 5 10 -1 15 20 25 30 36 NSS 234Th flux (dpm/m2/d) 5000 0 5 10 -1 15 20 25 30 36 4000 in-patch out-patch -5000 3000 SS 234Th flux (dpm/m2/d) 2000 10000 NSS out-patch SS 1000 NSS 234Th flux (dpm/m2/d) 5000 0 0 days after infusion 5 10 -1 15 20 25 30 36 -5000 days after infusion estimating 234Th export flux: steady vs non-steady state models Savoye et al (preliminary data), EIFEX, Southern Ocean

  47. 234Th, 238U (dpm/l) 234Th, 238U (dpm/l) 0 1 2 3 0 1 2 3 234Th 51°S 65°S 0 0 238U 50 50 100 100 150 150 200 200 Depth (m) Depth (m) 250 250 300 300 350 350 400 400 450 450 500 500 estimating 234Th export flux: steady vs non-steady state models Checking the validity of the steady state assumption -49 +/- 216 dpm/m2/d -2001 +/- 264 dpm/m2/d Savoye et al (2004), Southern Ocean

  48. 234Th, 238U (dpm/l) SS 'true' fluxes SS '+/-' fluxes NSS 'true' fluxes NSS '+/-' fluxes 1.5 2.0 2.5 0 6000 5000 238U 4000 day 1 50 3000 day 3 234Thflux (dpm/m2/d) 2000 day 5 1000 Depth (m) 100 0 1 2 3 4 5 -1000 -2000 days 150 200 estimating 234Th export flux: steady vs non-steady state models Limit of the non-steady state model +/- 0.02dpm/l

  49. steady vs non-steady state models: some remaining questions • To what extent the actual steady and non-steady state models • can be used? • How to test the validity of these models (especially the SS • model)? • To what extent the assumption of constant Pi over the • observation period is valid? Need to use a Pi = f(t) • relationship?

  50. Modeling 234Th in the ocean from scavenging to export flux Th scavenging models Estimating 234Th export flux Steady vs non-steady state models Toward 3D-models Photo: C. Beucher

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