• Gambo Apagu Thliza
• Coker, A.O
• Adefisoye, S.A

Abstract Airports in Sub-Saharan Africa (SSA) are emerging as urban-scale hubs where wastewater generation closely follows passenger growth. Yet, forecasting tools to guide capacity planning remain limited. This study develops a deterministic–stochastic framework to forecast sanitary sewage generation and design treatment capacity under uncertainty. Using a 2025 baseline of 275.04 m³/day (passenger-driven 255.04 m³/day; fixed/service 20.00 m³/day; passenger share α = 0.927), flows were projected to 2035 under low (5%), baseline (8.31%), and high (10%) annual passenger growth. Forecasted average daily flows reach 435, 587, and 682 m³/day, respectively. Applying conservative peak and safety factors (PF95 = 1.5; SF = 1.2) yields design capacities of ~784, ~1,056, and ~1,227 m³/day. An efficiency drift of δ = 0.5% per annum reduces the 2035 baseline design to ~1,006 m³/day. A stochastic layer—incorporating Beta, Normal, Triangular, and Lognormal distributions—was defined for Monte Carlo simulations to produce confidence bands. Using Murtala Muhammed International Airport (MMIA; 6°34′22.79″ N, 3°19′9.60″ E) as a calibration exemplar, the framework shows that even modest growth rapidly erodes capacity margins. Staged expansion to ~1,050–1,100 m³/day by 2035 under baseline growth, with modular scalability to ~1,200–1,250 m³/day, is recommended. This framework provides resilient, data-light forecasting applicable across SSA airports, enabling alignment with ICAO and WHO sanitation standards and advancing SDG 6. Keywords: Airport Sanitation; Forecasting; Design Capacity; Sub-Saharan Africa; Uncertainty Analysis; Wastewater Treatment Highlights  Deterministic–stochastic model links passenger growth to wastewater generation.  2025 baseline: Q₀ = 275.04 m³/day with passenger share α = 0.927.  2035 flows: 435 (5%), 587 (8.31%), 682 m³/day (10%).  2035 design capacities: ~784, ~1,056, ~1,227 m³/day (PF95 = 1.5; SF = 1.2).  Efficiency drift δ = 0.5%/yr lowers baseline 2035 design to ~1,006 m³/day.  Uncertainty inputs support Monte Carlo bands (median, P5–P95).

"Predictive Modelling of Airport Sanitary Sewage in Sub-Saharan Africa: Deterministic–Stochastic Framework, Scenario Forecasts (2025–2035) and Design-Capacity Implications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.f440-f449, August-2025, Available :http://www.jetir.org/papers/JETIR2508559.pdf

"Predictive Modelling of Airport Sanitary Sewage in Sub-Saharan Africa: Deterministic–Stochastic Framework, Scenario Forecasts (2025–2035) and Design-Capacity Implications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. ppf440-f449, August-2025, Available at : http://www.jetir.org/papers/JETIR2508559.pdf