Composed

Full cloud chemistry system with pH computed from the electroneutrality condition — Seinfeld & Pandis (2006), Ch. 7. The model composes AqueousEquilibria (quadratic charge-balance H⁺ from dissolved CO2, SO2, NH3, HNO3, H2O2, and O3 equilibria) with SulfateFormation (S(IV) oxidation kinetics via O3, H2O2, and Fe/Mn pathways). Unlike CloudChemistryFixedpH, which prescribes H⁺ from an external pH_input, this model self-consistently solves for the cloud-water pH from the trace-gas composition. Migrated from Aerosol.jl@c8c640bb src/cloud_chemistry.jl:73.

Simplified cloud chemistry system with pH as an externally prescribed input parameter — Seinfeld & Pandis (2006), Ch. 7. Instead of computing pH from the electroneutrality condition (as in the full CloudChemistry model), this variant takes pH_input as an input and derives H_plus = C_ref × 10^(-pH_input). This is useful for sensitivity studies that vary pH, for cases where unmeasured ions affect pH, or for quick calculations that bypass the full equilibrium solve. The model composes seven aqueous-equilibrium subsystems (WaterEquilibrium, CO2Equilibria, SO2Equilibria, NH3Equilibria, HNO3Equilibria, H2O2Equilibria, O3Equilibria) and the SulfateFormation oxidation kinetics module (O3, H2O2, and Fe/Mn-synergism pathways). All equilibria use van't Hoff temperature dependence from Table 7.4. Migrated from Aerosol.jl@c8c640bb src/cloud_chemistry.jl:269.

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.

Combined aqueous-phase S(IV)->S(VI) oxidation kinetics — Seinfeld & Pandis (2006), Atmospheric Chemistry and Physics, 2nd ed., Chapter 7, Section 7.5, with the Section 7.4 rate conversions. The model composes five S(IV)-oxidation pathway subsystems — O3 (Eqs. 7.79-7.80), H2O2 (Eq. 7.84), Fe(III)-catalyzed (Eq. 7.92), Mn(II)-catalyzed (Eq. 7.101), and Fe/Mn synergism (Eq. 7.102) — wired to shared cloud-droplet inputs by coupling equations. The total oxidation rate R_total sums the O3, H2O2 and Fe/Mn-synergism rates (the femn_ox subsystem already carries Fe-only and Mn-only terms, so the standalone fe_ox/mn_ox rates are excluded to avoid double-counting). It also reports sulfate production S_VI_production = R_total and three Section 7.4 diagnostics: the rate in ppb/hr (Eq. 7.75) and %/hr (Eq. 7.76) and the SO2 lifetime tau_SO2 (Eq. 7.78). Migrated from Aerosol.jl SulfateFormation as a subsystem-composed model (ESS spec §4.7).

Top-level composed diagnostic urban canopy model following the Community Land Model Urban (CLMU) parameterization of Oleson et al. (2010). Wires four CLMU subsystems — OfflineModeForcing (raw met → derived forcing), CLMUAtmosphere (atmospheric interface diagnostics), UrbanRadiation (solar/longwave radiation), and HeatMomentumFluxes (Monin-Obukhov surface fluxes) — via top-level coupling equations. All subsystems are inlined (ESS spec §4.7 composed-model pattern). Surface temperatures are prescribed as parameters (diagnostic mode). Migrated from UrbanCanopy.jl@9200edd4 src/urban_canopy_model.jl:41.

Composite water-vapor thermodynamics system from Seinfeld & Pandis (2006) Chapter 1: given air temperature and water-vapor partial pressure it computes the saturation vapor pressure of water over liquid water (Eq. 1.10) and the relative humidity (Eq. 1.9). Migrated from AtmosphericDynamics.jl@816cc391 src/seinfeld_pandis_ch1.jl:433 (`WaterVaporThermodynamics` @component), which composes two MTK subsystems via `System(eqs, t; systems=[sat, rh])`. Represented here as a subsystem-composed ESS model (spec §4.7): the `sat` subsystem inlines the already-migrated SaturationVaporPressure component (sat_vapor_pressure.esm, esm-zuku) and the `rh` subsystem inlines RelativeHumidity (relative_humidity.esm, esm-vann), wired together by five top-level coupling equations. Algebraic (observed-only): T and p_H2O are input parameters; p_sat and RH are algebraic state outputs. The flattened chain T -> sat.a -> sat.p_sat -> rh.p_sat -> rh.RH is fully explicit and triangular.