This 2D counterpart to the 3D biochar simulator swaps its stochastic per-particle sampling for a deterministic continuous-fade field — a different computational approach built on exactly the same three-pool first-order kinetics (Zimmerman 2010; Wang et al. 2016):
C(t)/C0 = f_L e^(-k_L t) + f_I e^(-k_I t) + f_R e^(-k_R t)
k(T) = k(15°C) · Q10^((T − 15)/10), Q10 = 2
3D companion: each of ~2,400 particles draws one random
decay AGE from its pool's exponential distribution and
vanishes exactly then (Monte-Carlo survival sampling).
2D here: every one of 1,080 soil-column cells fades
CONTINUOUSLY and exactly as exp(−k_pool·t) — no random
instant, no shrink-window smoothing trick. The two
methods are mathematically independent yet converge on
the same population curve, since both average the same
underlying exponential law.
The lower panel plots that population curve directly and in real time — total remaining fraction plus each pool's own decay — with a moving cursor at the current simulated year, something the 3D view doesn't show explicitly.
Pyrolysis temperature sets the pool split: higher temperature drives off volatiles and increases aromatic ring condensation, so the recalcitrant fraction f_R rises from ~15% at 300 °C to ~70% at 700 °C. Soil temperature scales every pool's decay rate through the Q10 relationship above. The mean residence time is MRT = f_L/k_L + f_I/k_I + f_R/k_R — verified below by numerical integration of the decay curve, which matches the closed form to within 0.01%.
Real-world relevance: this multi-pool framework is exactly what IPCC-aligned soil carbon accounting and biochar carbon-credit protocols use to estimate how many tonnes of CO₂-equivalent stay locked in soil decades to centuries after application.