Atmospheric_deposition

ModelingToolkit implementation of the aerodynamic resistance to dry deposition from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 19 (Dry Deposition), Eq. 19.14. Computes the aerodynamic resistance r_a [s/m] -- the resistance to turbulent transport of a depositing species through the surface layer, from the reference height z down to the roughness height z_0 -- under neutral atmospheric stability. Eq. 19.14, r_a = ln(z/z_0)/(kappa*u_star), is the integral of the neutral-stability logarithmic wind profile: r_a falls inversely with the friction velocity u_star (stronger turbulence carries the species down faster) and with the logarithm of the height ratio z/z_0 (a rougher surface, larger z_0, is more efficiently coupled to the atmosphere and presents less aerodynamic resistance). Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_ch19.jl:106 (the AerodynamicResistance @component). Purely algebraic: no differential states, a single explicit equation.

Air refreshing limitation on wet scavenging from Luo & Yu (2023), Eqs. 2, 5, 10, 11. The air refreshing limited removal rate R_A accounts for the finite time needed for species in subgrid cloud-free (rain-free) air to mix into cloudy (rainy) air before being subject to wet scavenging; the standard well-mixed assumption overestimates wet scavenging when the subgrid air mixing time scale is comparable to the model time step. When turbulent mixing is strong (large TKE) the grid refreshing time goes to zero and R_A approaches f*Rᵢ (the standard model); when mixing is weak R_A falls below f*Rᵢ. Migrated from AtmosphericDeposition.jl@e4468c79 src/luo2023.jl:210 (`AirRefreshingLimitation` @component). Observed-only algebraic system: cloud fraction f, in-cloud removal rate Rᵢ, turbulence kinetic energy TKE, and the grid spacings Δx/Δy/Δz are input parameters; Kᵢ, τ_A, and R_A are the algebraic outputs fixed by three explicit equations.

Irreversible below-cloud (washout) scavenging of a gas-phase species by falling raindrops, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 20 (Wet Deposition), Eqs. 20.22, 20.24, 20.25. The gas scavenging coefficient Λ_gas = 6·p₀·K_c/(D_p·U_t) (Eq. 20.25) for monodisperse drops is constant in time, so the below-cloud gas concentration decays exponentially via dC_g/dt = −Λ_gas·C_g (Eq. 20.24) and the below-cloud scavenging flux is F_bc = Λ_gas·h·C_g (Eq. 20.22). 'Irreversible' means the gas is assumed to be taken up and not re-released — the limiting case opposite to the reversible (Henry's-law-equilibrium) treatment of the sibling ReversibleGasScavenging component. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_2006_ch20.jl:234 (`BelowCloudGasScavenging` @component). ODE system: C_g is the single differential state; Λ_gas and F_bc are algebraic outputs (upstream `@variables`, serialized as type `state` with explicit algebraic equations); K_c, U_t, D_p, h, p₀ are input parameters.

Cloud ice uptake limitation on cold-cloud wet scavenging from Luo & Yu (2023), Eqs. 12-15. In cold clouds, water-soluble aerosols are captured by ice crystals via coagulation and then removed by precipitation; this component computes the cold-cloud rainout efficiency F_I from ice-crystal properties, turbulence, grid geometry, and temperature. The cloud ice uptake rate R_U is approximated by the HNO3 uptake rate of Jacob (2000) (Eq. 14); the temperature-dependent uptake efficiency gamma follows Hudson et al. (2002) (Eq. 15: gamma = 0.003 at T >= 220 K rising linearly to 0.007 at T <= 209 K); the cloudy-air refreshing rate Ki comes from turbulence kinetic energy and grid spacing (Eq. 11); the air-refreshing limited uptake rate R_AU applies the Eq. 2 refreshing-limit structure to R_U (Eq. 13); and F_I = 1 - exp(-R_AU*dt) (Eq. 12). Migrated from AtmosphericDeposition.jl@e4468c79 src/luo2023.jl:260 (`CloudIceUptakeLimitation` @component). Observed-only: the 5 equations are algebraic, so gamma, R_U, Ki, R_AU, F_I are the algebraic outputs while the 12 ice/turbulence/grid inputs and 9 module constants are parameters.

ModelingToolkit implementation of particle (aerosol) dry deposition from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 19 (Dry Deposition), Eq. 19.7. Computes the particle dry deposition velocity v [m/s] for a single aerosol size and the corresponding first-order deposition rate k = v/z [1/s], as a resistance network: v = 1/(R_a + R_b + R_a*R_b*V_s) + V_s, where R_a is the aerodynamic resistance (Eqs. 19.13-19.14), R_b is the quasi-laminar sublayer resistance (Eq. 19.27), and V_s is the gravitational settling velocity (Eq. 9.42). R_b combines Brownian diffusion (Schmidt number), inertial impaction (Stokes number) and interception, with land-use-dependent collector geometry from the Seinfeld & Pandis Table 19.2 characteristic-radius table. Migrated from AtmosphericDeposition.jl@e4468c79 src/dry_deposition.jl:1040 (the DryDepositionAerosol builder); its DryDepParticle kernel (src/dry_deposition.jl:272) and the whole helper chain (ra, mu, mfp, cc, vs, dParticle, sc, stSmooth/stVeg, RbParticle) are inlined. Purely algebraic: no differential states -- the 27 computed quantities are observed variables defined by inline expressions.

Wesley (1989) gas-phase dry deposition model. Computes dry deposition velocities v_* [m/s] and rates k_* [1/s] for 132 atmospheric trace gas species. Each species is characterized by its GasData (Dh2oPerDx, Hstar, Fo) constants from Wesely (1989) Table 2 and extended GEOS-Chem species data. The deposition velocity v_i = ifelse(lev==1,1,0) / (Ra + Rb_i + Rc_i) where Ra is the aerodynamic resistance (shared), Rb_i = 5*Sc_i^(2/3)/u_star is the quasi-laminar sublayer resistance, and Rc_i is the Wesley (1989) surface resistance computed inline with species constants substituted. Rain and dew are hardcoded false in the upstream DryDepositionGas builder. Migrated from AtmosphericDeposition.jl@e4468c79 src/dry_deposition.jl:323.

ModelingToolkit implementation of the complete gas dry-deposition velocity model from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 19 (Dry Deposition), Eq. 19.2 (deposition velocity) and Eq. 19.1 (deposition flux). The gas dry-deposition velocity follows the resistance-in-series model: a depositing gas crosses three resistances stacked in series between the reference height and the surface -- the aerodynamic resistance r_a (turbulent transport through the surface layer, Eq. 19.14), the quasi-laminar resistance r_b (molecular diffusion across the thin stagnant sublayer in contact with the surface, Eq. 19.17), and the surface resistance r_c (uptake by the canopy along four parallel pathways, Wesely 1989, Eq. 19.50). The deposition velocity is the reciprocal of their sum, v_d = 1/(r_a + r_b + r_c), and the downward deposition flux is F = -v_d*C for a gas concentration C at the reference height. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_ch19.jl:416 (`DryDepositionGas` @component), which composes three MTK subsystems via `System(eqs, t; systems=[aero, qlam, surf])` plus its own coupling equations. Represented here as a subsystem-composed ESS model (spec section 4.7): the `aero` subsystem inlines the already-migrated AerodynamicResistance component (aerodynamic_resistance.esm, esm-x8pg), `qlam` inlines QuasiLaminarResistanceGas (quasi_laminar_gas.esm, esm-t3wp), and `surf` inlines SurfaceResistance (surface_resistance.esm, esm-ug1i), wired together by seven top-level coupling equations. Algebraic (no time derivative): u_star, C, G and T_s are input parameters; r_t, v_d and F are algebraic state outputs.

Composite particle dry-deposition model from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 19 (Dry Deposition). Given the surface-layer friction velocity and an aerosol particle's properties it computes the particle dry deposition velocity v_d (Eq. 19.7) and the resulting downward deposition flux F (Eq. 19.1). Eq. 19.7, v_d = 1/(r_a + r_b + r_a*r_b*v_s) + v_s, combines the resistance-network pathway -- turbulent transport through the aerodynamic resistance r_a and the quasi-laminar boundary-layer resistance r_b, with the r_a*r_b*v_s cross term capturing gravitational settling acting inside the resistance network -- with a direct gravitational-settling term v_s; the flux F = -v_d*C (Eq. 19.1) is negative for downward transport. The competition between Brownian diffusion (efficient for sub-0.1 um particles) and inertial impaction (efficient for super-um particles) leaves a deposition-velocity minimum at accumulation-mode sizes. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_ch19.jl:479 (the DryDepositionParticle @component), which composes three MTK subsystems via System(eqs, t; systems=[aero, settling, qlam]). Represented here as a subsystem-composed ESS model (spec §4.7): the aero subsystem inlines the already-migrated AerodynamicResistance component (aerodynamic_resistance.esm, esm-x8pg), settling inlines ParticleSettling (particle_settling.esm, esm-egwt) and qlam inlines QuasiLaminarResistanceParticle (quasi_laminar_particle.esm, esm-brbr), wired by six top-level coupling equations. Purely algebraic (no D() time-derivative anywhere): u_star and C are input parameters; v_d and F are algebraic state outputs.

Below-cloud gas scavenging coefficient for irreversible uptake of a gas-phase species by falling monodisperse raindrops, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 20 (Wet Deposition), Eq. 20.25. The scavenging coefficient Λ_gas = 6·p₀·K_c/(D_p·U_t) sets the first-order loss rate (s⁻¹) of a soluble gas to rain: it rises linearly with the precipitation rate p₀ and the gas-phase mass transfer coefficient K_c, and falls inversely with the raindrop diameter D_p and terminal velocity U_t. 'Irreversible' uptake assumes the gas is captured and not re-released — the limiting case opposite to the Henry's-law-equilibrium treatment of the sibling ReversibleGasScavenging component. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_2006_ch20.jl:116 (`GasScavengingCoeff` @component). Observed-only algebraic model: K_c, U_t, D_p, p₀ are input parameters and Λ_gas is the single algebraic output, fixed by one equation with no time derivative.

Gas-phase mass transfer coefficient K_c to a falling raindrop, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 20 (Wet Deposition), Eq. 20.12. K_c is computed from a Sherwood-number correlation K_c = (D_g/D_p)·[2 + 0.6·Re^(1/2)·Sc^(1/3)], where the drop Reynolds number Re = ρ_air·U_t·D_p/μ_air measures the convective flow past the falling drop and the gas Schmidt number Sc = μ_air/(ρ_air·D_g) is the ratio of the momentum to the mass boundary-layer thickness. The leading 2 is the still-air diffusive limit (Sh→2 for an isolated sphere); the 0.6·Re^(1/2)·Sc^(1/3) term is the ventilation enhancement from the drop's fall. K_c sets the gas-uptake rate at the raindrop surface and feeds the below-cloud gas scavenging coefficient computed by the sibling GasScavengingCoeff / BelowCloudGasScavenging components. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_2006_ch20.jl:60 (`MassTransferCoeff` @component). Algebraic (observed-only) system: K_c is the single algebraic output (the upstream component's lone `@variable`); D_g, D_p, U_t are input parameters and ρ_air_sp, μ_air_sp are the migrated upstream module `@constants`.

Slinn (1983) semi-empirical collision (collection) efficiency E between a falling raindrop and an aerosol particle, the kernel of below-cloud particle scavenging (Eqs. 20.53-20.54, Seinfeld & Pandis, 2006). E is the sum of three collection mechanisms — Brownian diffusion (E_diff, important for sub-0.1 µm particles), interception (E_int), and inertial impaction (E_imp, important for super-µm particles, switched on only when the Stokes number exceeds the critical Stokes number S* of Eq. 20.54) — and is clamped to a maximum of 1. The competition between the diffusion and impaction mechanisms produces the Greenfield gap: a collection-efficiency minimum at accumulation-mode (~0.1-1 µm) particle sizes. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_2006_ch20.jl:365 (`ParticleCollectionEfficiency` @component). The upstream component carries the single equation E ~ slinn_collection_efficiency(D_p, U_t, d_p, ρ_p, T); the helper function and its sub-helpers (particle_diffusivity, particle_relaxation_time, particle_terminal_velocity) are decomposed here into 18 named intermediate algebraic states (Re, D_diff, Sc, τ, St, S_star, E_diff, E_int, E_imp, ...) mirroring the helper's local variables, so each equation maps to one source line. Observed-only: all 18 equations are algebraic — the five raindrop/aerosol/thermodynamic inputs and six physical constants are parameters, and Re through E are the algebraic outputs.

Below-cloud scavenging coefficient Λ_particle for an aerosol particle collected by monodisperse raindrops (Seinfeld & Pandis 2006, Chapter 20, Eq. 20.57): Λ_particle = (3/2)·E·p₀/D_p, where E is the Slinn (1983) raindrop-aerosol collision (collection) efficiency of Eqs. 20.53-20.54, p₀ the precipitation rate and D_p the raindrop diameter. E sums three collection mechanisms — Brownian diffusion, interception, and inertial impaction (switched on only when the Stokes number exceeds the critical Stokes number S*) — and is clamped to a maximum of 1; their competition produces the Greenfield gap, a scavenging minimum at accumulation-mode (~0.1-1 µm) particle sizes. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_2006_ch20.jl:414 (`ParticleScavengingCoeff` @component). The upstream slinn_collection_efficiency helper and its diffusivity / relaxation-time / settling-velocity sub-helpers are decomposed into 18 named intermediate algebraic states (Re, D_diff, Sc, τ, St, S_star, E_diff, E_int, E_imp, ...) — identical to the sibling component particle_collection_eff.esm — and a 19th equation applies Eq. 20.57. The five raindrop/aerosol/thermodynamic inputs, the precipitation rate, and six physical constants are parameters; Re through E and Λ_particle are the algebraic outputs.

Gravitational settling velocity and Brownian diffusivity of an aerosol particle, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 19 (Dry Deposition). Two algebraic outputs are computed from the particle and air properties. The settling (terminal) velocity v_s = rho_p*D_p^2*g*C_c/(18*mu) (Eq. 19.18) is the steady gravitational drift speed of a particle in the Stokes (low-Reynolds-number) regime, where aerodynamic drag balances gravity; the Cunningham slip correction factor C_c (>= 1) accounts for the non-continuum reduction in drag when the particle diameter approaches the mean free path of air. The Brownian diffusivity D_diff = k_B*T*C_c/(3*pi*mu*D_p) (Eq. 19.20) is the Stokes-Einstein diffusion coefficient describing the particle's thermal random walk. The two quantities have opposite size dependence -- v_s grows as D_p^2 while D_diff falls as 1/D_p -- which is the physical origin of the dry-deposition-velocity minimum for accumulation-mode (~0.1-1 um) aerosol: such particles settle too slowly to deposit gravitationally yet are too large to diffuse efficiently to the surface. Both quantities feed the Zhang et al. (2001) quasi-laminar resistance and the overall particle dry deposition velocity computed by the sibling sp_ch19 components. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_ch19.jl:182 (`ParticleSettling` @component). Observed-only algebraic model: rho_p, D_p, mu, T, C_c are input parameters, g/k_B/pi_val are physical-constant parameters, and v_s and D_diff are the two algebraic outputs, each fixed by one equation with no time derivative.

ModelingToolkit implementation of the quasi-laminar (boundary-layer) resistance to gaseous dry deposition from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 19 (Dry Deposition), Eq. 19.17. The quasi-laminar resistance r_b [s/m] is the second of the three series resistances of the gas dry-deposition resistance model (r_a aerodynamic + r_b quasi-laminar + r_c surface) and represents molecular diffusion of the depositing gas across the thin, quasi-laminar sublayer of stagnant air in direct contact with the surface. It is computed as r_b = 5*Sc^(2/3)/u_star, where the Schmidt number Sc = nu/D_g is the ratio of the kinematic viscosity of air nu to the molecular diffusivity D_g of the gas, and u_star is the friction velocity. Slower-diffusing (higher-Sc) gases face a larger boundary-layer resistance, and stronger surface turbulence (higher u_star) thins the sublayer and lowers r_b. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_ch19.jl:143 (`QuasiLaminarResistanceGas` @component). Algebraic (no time derivative) two-equation system: Sc and r_b are the algebraic outputs (the upstream component's computed @variables, migrated as type:state); nu and D_g are the input @parameters and u_star is the upstream input @variable (migrated as type:parameter -- it carries no defining equation and the upstream test suite compiles the component with u_star declared as an input).

Zhang et al. (2001) quasi-laminar (boundary-layer) resistance r_b for particle dry deposition, Seinfeld & Pandis (2006) Ch. 19 Eq. 19.27. r_b = 1/(3*u_star*(E_B+E_IM+E_IN)*R_1) sums three size-dependent collection mechanisms — Brownian diffusion E_B (Eq. 19.21), inertial impaction E_IM (Eq. 19.22), and interception E_IN (Eq. 19.25) — scaled by the friction velocity u_star and the rebound-correction sticking fraction R_1 (Eq. 19.26). The competition between diffusion (efficient for sub-0.1 um particles) and impaction (efficient for super-um particles) leaves a deposition minimum at accumulation-mode sizes. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_ch19.jl:234 (`QuasiLaminarResistanceParticle` @component). The seven upstream equations are migrated verbatim and one-to-one; the five input @parameters, the @constant g, and the three externally-supplied input @variables (u_star, v_s, D_diff) are all parameters, and the seven equation-defined quantities (Sc, St, E_B, E_IM, E_IN, R_1, r_b) are the algebraic outputs.

Below-cloud scavenging of a reversibly-absorbed (Henry's-law) trace gas by falling raindrops, from Chapter 20 (Wet Deposition) of Seinfeld & Pandis (2006). Unlike the irreversible-uptake parameterizations used for highly soluble species such as HNO3, this component retains the equilibrium (Henry's law) ceiling: a raindrop falling through polluted air relaxes toward -- but cannot exceed -- the aqueous concentration in equilibrium with the local gas phase, and a drop entering the layer already overloaded (C_aq0 above equilibrium) instead desorbs gas back to the air. Two algebraic outputs: C_aq_ground (Eq. 20.33, which is Eq. 20.28 evaluated at the cloud-base fall distance h) is the aqueous-phase concentration in a drop arriving at the ground; F_bc (Eq. 20.35) is the total below-cloud scavenging flux. Both are governed by the single dimensionless exponent alpha = 6*K_c*h/(D_p*U_t*HRT): the drop relaxes from its initial aqueous concentration C_aq0 toward the Henry's-law equilibrium C_eq = C_g*HRT, and (1 - exp(-alpha)) is the fraction of that equilibrium uptake realised over the fall. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_2006_ch20.jl:194 (`ReversibleGasScavenging` @component). The upstream component is a flat MTK System whose two equations call the module helper functions reversible_drop_conc (Eq. 20.28) and reversible_scavenging_flux (Eq. 20.35); both helpers are inlined into the equation ASTs here. The eight upstream @parameters (C_g, HRT, K_c, D_p, U_t, h, C_aq0, p0) map directly to type:parameter and the two upstream @variables(t) (C_aq_ground, F_bc) to type:state, each fixed by one explicit algebraic equation. HRT is the dimensionless product H* x R x T x 1000 (effective Henry's law coefficient x gas constant x temperature x unit conversion); for HNO3 at 298 K, HRT = 2.1e5 x 8.206e-5 x 298 x 1000 is approximately 5.14e6 (the declared default). Observed-only algebraic system: both equations are algebraic (no D operator), so the two outputs are the algebraic solution while the gas-phase, drop, and precipitation inputs are parameters; system_kind is left unset.

Operator model that turns first-order dry + wet deposition loss-rate coefficients into additive sink terms on a SuperFast-family gas-phase mechanism. Each equation is D(<X>) ~ -(k_dry + k_wet)*<X> over the model's OWN species unknowns; when this model is merged with a SuperFast reaction system via an `operator_compose` coupling (systems: [<Chem>, SuperFastDepositionSink]), the flattener matches each sink equation's dependent variable to the chemistry system's state of the same species name and sums the two right-hand sides (dc/dt += -k*c), then retires the sink's own declaration of that name (esm-spec 10.1/10.2 — direct match, else the bare-name match). The deposition rate coefficients are exposed as parameters so they can be driven from the full DryDepositionGas (Wesley 1989) and WetDeposition (EMEP) components via param_to_var edges in an assembly. Species->rate mapping mirrors AtmosphericDeposition.jl/ext/GasChemExt.jl couple2(SuperFastCoupler, DryDepositionGasCoupler / WetDepositionCoupler): NO reuses NO2's dry-dep rate; CH2O uses the formaldehyde (HCHO) dry-dep rate; the wet rate k_wet is the lumped soluble-gas WetDeposition.k_othergas applied to HNO3, H2O2, CH2O, CH3OOH.

ModelingToolkit implementation of the surface (canopy) resistance to gaseous dry deposition from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 19 (Dry Deposition), Eqs. 19.50-19.52 -- the Wesely (1989) resistance model. Computes the total surface resistance r_c [s/m] as four parallel deposition pathways (Eq. 19.50): the combined stomatal+mesophyll pathway, the cuticular/outer-surface pathway r_lu, the lower-canopy pathway r_dc+r_cl, and the ground pathway r_ac+r_gs. The stomatal resistance r_st (Eq. 19.51) responds to solar irradiance G and surface temperature T_s through dimensionless light and temperature factors; the mesophyll resistance r_m (Eq. 19.52) is set by the gas's effective Henry's-law solubility H_star and reactivity f_0. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_ch19.jl:311 (the SurfaceResistance @component). Purely algebraic: no differential states, six explicit equations evaluated as a triangular cascade.

Wesely (1989) bulk surface (canopy) resistance to gaseous dry deposition. Computes the total surface resistance r_c [s/m] along Wesely's three parallel mass-transfer pathways — the upper-canopy leaf cuticles, the lower-canopy structures, and the ground — from the gas species' Henry's-law solubility and reactivity, solar irradiation, surface air temperature, terrain slope, season, land-use category, and surface wetness (rain/dew). Migrated from AtmosphericDeposition.jl@e4468c79 src/wesley1989.jl:360 (the `WesleySurfaceResistance` builder function); implements Wesely (1989) Eq. 2 with the stomatal, mesophyll, cuticle, lower-canopy and ground sub-resistances of Eqs. 3-14 and the Walmsley & Wesely (1996) corrections.

EMEP-formulation wet deposition model for PM2.5, SO2, and other gases. Computes three first-order wet deposition rate coefficients (k_particle, k_SO2, k_othergas [1/s]) from cloud fraction (cloudFrac), rain mixing ratio (qrain), air density (rho_air), and the atmospheric level index (lev). Subcloud scavenging rates scale as qrain*rho_air/Dz times a species-specific washout coefficient; in-cloud scavenging additionally scales with cloudFrac; the particle subcloud term uses A_wd*E*qrain*rho_air without the 1/Dz factor. The layer depth Dz is looked up from a 72-entry constant table (GEOS-Chem-derived model-level thicknesses in metres) indexed by lev. The gt-p3ep blocking gap (get_lev_depth is @register_symbolic) is resolved by expressing the lookup as an interp.linear AST composition over the 72-entry integer-axis table — matching the FastJX_interpolation_troposphere precedent. Migrated from AtmosphericDeposition.jl@e4468c79 src/wet_deposition.jl:147 (the WetDeposition builder) and src/wet_deposition.jl:82 (_WetDeposition helper). Purely algebraic: no differential states; k_particle, k_SO2, k_othergas are observed variables.

Net wet deposition diagnostics — wet deposition flux, washout ratio, and wet deposition velocity — for a trace species removed from the atmosphere by falling rain, from Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 20 (Wet Deposition), Eqs. 20.6-20.9. Given the species concentration in ground-level rainwater (C_rain), its gas-phase concentration in air (C_air), and the precipitation rate (p₀), the component evaluates three quantities: the wet deposition flux F_w = C_rain·p₀ (Eq. 20.7) — the downward species mass flux carried to the surface by rain; the dimensionless washout ratio w_r = C_rain/C_air (Eq. 20.6) — a measure of how strongly the species partitions into rainwater; and the wet deposition velocity u_w = F_w/C_air (Eq. 20.8), equivalently w_r·p₀ (Eq. 20.9) — the flux normalized by the air-phase concentration. Migrated from AtmosphericDeposition.jl@e4468c79 src/seinfeld_pandis_2006_ch20.jl:451 (`WetDepositionFlux` @component). Flat observed-only algebraic model: C_rain, C_air and p₀ are the input parameters and F_w, w_r, u_w are the algebraic outputs, each fixed by one equation with no time derivative. The upstream @component is a single flat System with no subsystems; the migration-tracker `coupling.couple` feature tag and `depends_on: ParticleScavengingCoeff, GasScavengingCoeff` describe a conceptual relationship that the source code does not implement, so this is migrated as a standalone flat model.

Combined air refreshing and cloud ice uptake limitations on wet scavenging from Luo & Yu (2023). This component unifies the two novel parameterizations of the paper into a single algebraic system: (1) the air refreshing limitation (Section 2.1, Eqs. 2/5/10/11), which reduces the wet-scavenging removal rate R_A when subgrid cloud-free (rain-free) air mixes into cloudy (rainy) air slower than the model time step; and (2) the cloud ice uptake limitation (Section 2.2, Eqs. 12-15), which limits the cold-cloud rainout efficiency F_I by the rate R_U at which water-soluble aerosols are captured by ice crystals -- the HNO3 ice uptake rate of Jacob (2000), with the temperature-dependent uptake efficiency gamma of Hudson et al. (2002). Migrated from AtmosphericDeposition.jl@e4468c79 src/luo2023.jl:326 (`WetScavengingLimitations` @component). The upstream component is a flat MTK System that inlines the equations of both AirRefreshingLimitation and CloudIceUptakeLimitation -- it does not `couple` them -- so this migration is the union of air_refreshing.esm (esm-1i3m) and cloud_ice_uptake.esm (esm-3hh9): 13 input parameters, 9 module constants, and 7 algebraic state variables (Kᵢ, τ_A, R_A, gamma, R_U, R_AU, F_I) fixed by 7 explicit equations. Observed-only: every equation is algebraic, so the 7 outputs are the algebraic solution while the ice/turbulence/grid/temperature inputs and module constants are parameters.