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Modeling 234Th in the ocean from scavenging to export flux Nicolas SAVOYE Vrije Universiteit Brussel Photo: C. Beucher 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 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 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 One-box models U l k Tht l U P = (l + k) [234Th] Broecker et al (1973) l k Tht l f 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 One-box models U l k Tht l U l k Tht l f P = (l + k) [234Th] P + ([234Th]I – [234Th]) / f = (l + k) [234Th] 228Th/228Ra t = 0.7 year open ocean 234Th/238U t = 0.38 year open ocean Knauss et al (1978) 228Th/228Ra t = 0.52, 0.30 year shelf water Knauss et al (1978) 228Th/228Ra, 234Th/238U t = 0.19 year t = 0.03 year Broecker et al (1973) Matsumoto et al (1975) t=1/k shelf break coastal water One-box models U l k Tht l U P = (l + k) [234Th] l k Tht l f P + ([234Th]I – [234Th]) / f = (l + k) [234Th] Assumptions: -k: first order -steady state -diffusion, advection negligible two-box irreversible models U lU Thd lTh Krishnaswami et al (1976) d[Thp] dt k =– S d[Thp] dz lTh Thp S + k [Thd] – [Thp] lTh [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 two-box irreversible models U lU Thd [Thp] lTh = t = 0.40 year (from 234Th/238U) S = 0.03 – 0.2 m/s (from 230Th/234U) lTh Thp lTh Krishnaswami et al (1976) Steady state: k S k [Ud] lU k + lTh 1 – exp z lTh S two-box irreversible models U l Coale and Bruland (1985, 1987) kd Thd l Thp l kp PTh dATh,d dt = AU lTh- ATh,d lTh - JTh =0 dATh,p dt = JTh - ATh,p lTh - PTh =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. two-box irreversible models U l Coale and Bruland (1985, 1987) kd Thd l Thp kp PTh Assumptions: - U is dissolved only - kd, kp: first order - steady state - diffusion, advection negligible - all particles have the same comportment - irreversible scavenging l two-box reversible models U l k1 Thd l Thp k-1 l Nozaki et al (1981) [230Thd] + [230Thp] = S 1+ k-1 P k1 S d: dissolved; p: particulate; l: decay constant; k1: first-order adsorption/scavenging rate constant; k-1: first-order rate constant for the transfer of 230Th from particles to solution; S: settling velocity of particulate 230Th; P: production rate of 230Th from 234U. z two-box reversible models U k1 l Thd l Thp k-1 l Bacon and Anderson (1982) S Steady state: [Thp] = [Thd] = k1 P l (l + k1 + k-1) 1 – exp – l (l + k1 +k-1) S (l + k1) P + k-1 [Thp] 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. z two-box reversible models U l k1 Thd l Thp k-1 Bacon and Anderson (1982) l S 1.4 1.2 Assumptions: - U is dissolved only k1 (yr-1) 1.0 0.8 0.6 0.4 - k1, k-1: first order - steady state - diffusion, advection negligible - all particles have the same comportment 0.2 0 0 5 10 15 [SPM] (µg/l) 20 25 three-box irreversible models U l k1 Thd r1 Thsp Thlp l 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, disaggragation rate constants, respectively. modeling Th adsorption/desorption on mineral particles Th k1 k-1 ThX k2 k-2 ThX’ k3 k-3 ThX’’ 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 three-box reversible models U l k1 Thd k2 Thsp k-1 l Thlp l k-2 l S 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 disaggragation rate constants, respectively; S: sinking speed. three-box reversible models g U l k1 Thd r1 Thsp k-1 l Thlp l r-1 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, disaggragation rate constants, respectively; g: remineralization rate constant; S: sinking. three-box reversible models b-1 U l b2 k1 Thd Thsp k-1 l l b-2 Thlp 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 disaggragation rate constants, respectively; b-1: first order remineralization rate constant; w: sinking velocity. three-box reversible models: the Brownian pumping model k1 k-1 U l k1 Thd k2 Thc Thfp k-1 l l k-2 l S 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 disaggragation rate constants, respectively; slow step S: sinking. four-box reversible model R U l k1 Thd k2 Thc Thsp k-1 l k3 k-2 l Thlp l k-3 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 repeptization rate constants, respectively; k2, k-2: aggregation and disaggregation rate constants, respectively; S: sinking; R: remineralization four (or more)-box irreversible model h2 U l Thd Thc l k-1 k1 S1 Thsp l k-2 k2 S2 h3 Thlp l k-3 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. k3 S3 l five-box (ir)reversible model U l Thd Fd Th 0.5-1µm l Guo et al (2002) d: dissolved; p: particulate; l: decay constant; F: flux. l Fp1 Thsp 1-10µm l Fp2 Thlp 10-53µm l Fp3 Thlp >53µm l Fp4 U Th scavenging models: usual main assumptions l k1 Thd b1 k2 Thc Thsp k-1 l k-2 l - 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 l b-1 Thlp S l 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 Th scavenging models: importance of the chemistry of the particles Thd Thp Partitioning coefficient: Kd = [Thp] [Thd] 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) 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) Importance of acid polysaccharides for 234Th complexation Quigley et al (2002) Importance of uronic acid for 234Th scavenging from Guo et al (2002) 4 y = 0.577x-0.788 R2 y = 1.70x-0.192 3 = 0.66 R2= 0.07 2 2 1 1 234Th residence time (day) 3 0 >53µm 0 0 0.5 1 1.5 2 2.5 0 2 4 y = 0.577x-0.788 5 234Th residence time (day) 5 R2= 0.47 3 2 1 1 0 0 10 20 [uronic acid] (nM) R2= 0.85 y = 528x-2.31 R2= 0.63 3 2 0 y = 53.9x-1.94 8 4 y = 37.9x-1.37 4 R2= 0.66 6 30 0 10 20 [uronic acid] (nM) 30 10-53µm 1-10µm 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’ U Th scavenging models: usual main assumptions l k1 Thd Thc Thsp k-1 l b1 k2 k-2 l - 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 l b-1 Thlp S l Th scavenging models: reversibility / irreversibilty of Th adsorption U l k1 Thd Thc Thsp k-1 l b1 k2 k-2 l l b-1 Thlp l S Quigley et al (2001) Th scavenging models: reversibility / irreversibilty of Th adsorption U l k1 Thd Thc Thsp k-1 l b1 k2 k-2 l l b-1 Thlp l S Quingley et al (2001) 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 estimating 234Th export flux: steady vs non-steady state models U l Th k dATh l dt Tanaka et al (1983) 0.3 < tNSS/tSS < 3.8 ATh2 = l AU l+k = AU l - ATh l - ATh k ATh1 - l AU l+k (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. e-(l + k)T estimating 234Th export flux: steady vs non-steady state models U l Th k dATh l dt Tanaka et al (1983) 0.3 < tNSS/tSS < 3.8 ATh2 = l AU l+k = AU l - ATh l - ATh k ATh1 - l AU l+k e-(l + k)T (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 estimating 234Th export flux: steady vs non-steady state models l U Th k dATh l dt Tanaka et al (1983) ATh2 = SS residence time (day) 20 l AU l+k = AU l - ATh l - ATh k ATh1 - l AU l+k e-(l + k)T 1:1 15 10 Wei and Murray (1992); data from Dabob Bay, USA 5 0 0 5 10 15 NSS residence time (day) 20 estimating 234Th export flux: steady vs non-steady state models Layer 1 (surface) U l Thd J1 l Layer 2 U l Thd J2 l Thp P1 l Thp P2 l Pi-1 Layer i Buesseler et al (1992) U l Thd Ji l Thp Pi l estimating 234Th export flux: steady vs non-steady state models Pi-1 Buesseler et al (1992) U ∂AiTh,d ∂t ∂AiTh,p ∂t ∂AiTh,t ∂t = Ai U l- Ai Th,d l- l Thd Ji Ji l Thp Pi i i-1 i i = J + P - A Th,p l - P i i-1 i i = A U l + P - A Th,t l - P 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. l estimating 234Th export flux: steady vs non-steady state models Pi-1 Buesseler et al (1992) U ∂AiTh,t ∂t = Ai U l+ Pi = Pi-1 + l Pi-1 - Ai Th,t l- l Thd Ji Thp l Pi Pi AiU (1- e-l(t2-t1)) + Ai,t1Th,t e-l(t2-t1) – Ai,t2Th,t 1- e-l(t2-t1) 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. l estimating 234Th export flux: steady vs non-steady state models Pi-1 U l Pi-1 Tht Pi Pi = Pi-1 + l U l Thd l Ji Thp l Pi l AiU (1- e-l(t2-t1)) + Ai,t1Th,t e-l(t2-t1) – Ai,t2Th,t 1- e-l(t2-t1) Buesseler et al (1992) Assumptions: - Pi is constant within the period t2-t1 - diffusion and advection are negligible estimating 234Th export flux: steady vs non-steady state models Buesseler et al (2001), Southern Ocean SS NSS 4000 3000 2000 13-Mar 27-Feb 13-Feb 30-Jan 16-Jan 02-Jan 19-Dec 05-Dec 21-Nov 0 07-Nov 1000 24-Oct 234Th flux (dpm/m2/d) 5000 estimating 234Th export flux: steady vs non-steady state models Benitez-Nelson et al (2001), Aloha station, Pacific Ocean SS NSS 2000 1500 1000 Mar-00 Feb-00 Jan-00 Dec-99 Nov-99 Oct-99 Sep-99 Aug-99 Jul-99 Jun-99 0 May-99 500 Apr-99 234Th flux (dpm/m2/d) 2500 estimating 234Th export flux: steady vs non-steady state models Schmidt et al (2002), Dyfamed, Mediterranean Sea 1500 NSS 1000 SS 500 29 mai 27 mai 25 mai 23 mai 21 mai 19 mai 17 mai 15 mai 13 mai 11 mai 9 mai 0 7 mai 234Th flux (dpm/m2/d) 2000 estimating 234Th export flux: steady vs non-steady state models Savoye et al (preliminary data), EIFEX, Southern Ocean inpatch 234Th, 238U (dpm/l) Depth (m) 1.0 1.5 2.0 out patch 234Th, 238U (dpm/l) 2.5 1.0 0 0 50 50 100 100 150 238U 200 1.5 2.0 150 200 day -1 day 20 day -1 day 4 day 23 day 5 day 9 day 28 day 10 day 11 day 32 day 16 day 15 day 18 day 36 day 25 day 34 2.5 estimating 234Th export flux: steady vs non-steady state models Savoye et al (preliminary data), EIFEX, Southern Ocean in-patch NSS 234Th flux (dpm/m2/d) 4000 out-patch 3000 2000 10000 SS NSS in-patch 5000 0 -1 5 10 15 20 25 30 36 30 36 -5000 1000 0 -1 5 10 15 20 25 days after infusion 30 36 NSS 234Th flux (dpm/m2/d) SS 234Th flux (dpm/m2/d) 15000 10000 SS NSS out-patch 5000 0 -1 -5000 5 10 15 20 25 days after infusion estimating 234Th export flux: steady vs non-steady state models Checking the validity of the steady state assumption 234Th, 238U 0 1 234Th, 238U (dpm/l) 2 0 3 51°S 100 50 234Th 150 Depth (m) Depth (m) 65°S 100 238U 150 200 250 300 200 250 300 350 350 400 400 450 2 0 0 50 1 (dpm/l) -49 +/- 216 dpm/m2/d 500 450 500 -2001 +/- 264 dpm/m2/d Savoye et al (2004), Southern Ocean 3 estimating 234Th export flux: steady vs non-steady state models Limit of the non-steady state model 234Th, 238U 1.5 (dpm/l) 2.0 2.5 0 SS '+/-' fluxes NSS 'true' fluxes NSS '+/-' fluxes 2 4 6000 +/- 0.02dpm/l 234Thflux 100 (dpm/m2/d) 50 Depth (m) SS 'true' fluxes 150 5000 4000 3000 2000 1000 0 -1000 -2000 200 238U day 1 day 3 day 5 1 3 days 5 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? 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 estimating 234Th export flux: toward 3D-models 1D model U l l Tht (Thd + Thp) S d: dissolved; p: particulate; t: total; l: decay constant; S: sinking. estimating 234Th export flux: toward 3D-models 3D model v Ky l U l u Tht Kx (Thd + Thp) Kz w S d: dissolved; p: particulate; t: total; l: decay constant; S: sinking velocity; u, v, w: advection velocities; Kx, Ky, Kz: diffusion constants. estimating 234Th export flux: toward 3D-models 3D model – steady state conditions ∂ATh ∂t = 0 = AU l – ATh l – P + V V=–u + Kx ∂ATh ∂x ∂2ATh ∂x2 –v ∂ATh ∂y + Ky –w ∂2ATh ∂y2 ∂ATh advection term ∂z + Kz ∂2ATh ∂z2 diffusion term estimating 234Th export flux: toward 3D-models importance of advection and diffusion in coastal area McKee et al (1984) Gustafsson et al (1998) Santschi et al (1999) Benitez-Nelson et al (2000) Charette et al (2001) estimating 234Th export flux: toward 3D-models importance of advection and diffusion in coastal area Charette et al (2001) Gulf of Maine, USA estimating 234Th export flux: toward 3D-models U l k Tht f Matsumoto et al (1975) l P + ([234Th]I – [234Th]) / f = (l + k) [234Th] l + (RI – R) / f = (l + k) R 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 R: ATh / AU = l [234Th] / P A: radioisotope activity estimating 234Th export flux: toward 3D-models U l k Tht f l Matsumoto et al (1975) P + ([234Th]I – [234Th]) / f = (l + k) [234Th] l + (RI – R) / f = (l + k) R R = 0.8; RI = 1.0; f = 5 yr (RI – R) / f = 0.04 yr-1 << l = 10.5 yr-1 estimating 234Th export flux: toward 3D-models Pi-1 wi-1 U l wi – wi-1 Tht Bacon et al (1996) l wi Pi Steady state conditions: Pi = Pi-1 + l (AU – AiTh) + wi (Ai+1 – Ai) t: total; l: decay constant; A: radioisotope activity; i: layer of interest; P: particulate 234Th flux; w: upwelling velocity. estimating 234Th export flux: toward 3D-models Bacon et al (1996), equatorial Pacific El Niño conditions non-El Niño conditions estimating 234Th export flux: toward 3D-models v Ky v Ky U Dunne and Murray (1999) l l k’1 Thd Kz w k-1 Thp Kz w S Zonal (W-E) advection and diffusion negligible d: dissolved; p: particulate; l: decay constant; k’1, k-1: adsorption and desorption constants S: sinking velocity; v, w: advection velocities; Ky, Kz: diffusion constants. l Dunne and Murray (1999), equatorial Pacific estimating 234Th export flux: toward 3D-models estimating 234Th export flux: toward 3D-models Advection and/or diffusion are not negligible: in coastal areas and continental marges in upwelling systems What about frontal systems (cf Coppola et al, accepted), eddies, etc?... Need to identify peculiar regions and/or physical conditions where advection and diffusion processes are not negligible (model simulation may be useful) summary: toward 5D-models? ∂ATh ∂t ∂ATh ∂t = Sc + V Sc: scavenging; V: physic : non-steady state term (t) Sc: adsorption/desorption, aggregation/disaggregation (s), remineralization V = diffusion (x, y, z) + advection (x, y, z) t: time dimension s: particle size dimension x, y, z: longitude, latitude and depth dimensions, respectively summary: toward 5D-models? v Ky l U l u v Ky l R k1 Thd Kx Kz w k-1 u Kx Ths1 Kz w S v Ky l k2 ki k-2 k-i u Kx ki+1 Thsi Kz w S k-i+1 What, when, where? Do we need complex models? how many boxes (dissolved phase, colloids, particle spectrum)? what fluxes (remineralization, advection, diffusion, desorption)? including particle composition (chemistry, biology)? including the physical properties of particles (density, stickiness)? Depends on scientific questions scales (time, space) conditions (physic, biology) What, when, where? What do we need to improve models? peculiar experiment to better parameterize models? development of new techniques? Need of model simulations to check the validity of the assumptions to design the sampling strategy Need to identify ocean regions and physical and biological conditions where some assumption can be made