Aquaponics and the crossroads of profitability and sustainability viewed through sensitivity and risk modeling

Aquaponics integrates aquaculture effluent with hydroponic crop production, offering a resource- and water-efficient alternative to conventional agriculture. However, its economic viability remains contested, with many commercial operations having short lifespans. This study develops a financial modelling framework to evaluate aquaponics profitability and sustainability by analyzing the sensitivity of Net Present Value (NPV) and Internal Rate of Return (IRR) to variations in aquaculture, hydroponics, and facility operational parameters. A 73-parameter financial model was built. Sensitivity and elasticity analyses ranked parameters by their influence on NPV and IRR over realistic ranges. Monte Carlo simulations estimated the likelihood of positive returns, while Latin Hypercube Sampling of truncated normal distributions identified parameter combinations yielding optimal outcomes. Life Cycle Analysis (LCA) and Green Asset Ratio (GAR) were applied to assess environmental impacts and eligibility for sustainable financing. Labor, managerial efficiency, production yield and market price were dominant profitability drivers; plant revenues influenced profitability more than fish. The mean five-year NPV was −21,991 ± 54,800 $USD; IRR was 4.8 ± 12.2 %, with only ∼25 % of simulations yielding positive values. The high variability suggests persistent operational vulnerability. LCA showed electricity as the largest contributor to GWP (∼20,000 kg CO 2 -eq y −1 median) followed by infrastructure maintenance. Moreover, the profile of profitable scenarios diverged from non-profitable ones. GAR scores ranged from 46 to 94 %, indicating suitability for EU green-finance instruments to buffer risk. This stochastic modelling approach enables researchers to target parameters for optimization, operators to address process constraints, and investors to assess risk–return trade-offs. Applied here to aquaponics, the methodology is transferable to other circular systems as a risk assessment tool.