The APM Project Calculator is a comprehensive planning tool for aquaponics systems. It combines biological growth models, technical calculations, and financial analyses to generate a realistic feasibility study from just a handful of user inputs.
This document explains what happens behind the scenes when you click Calculate.
From input to result, the “Big Picture”
The calculator takes your basic project parameters—location, greenhouse size, building type, operating mode, and production focus—and routes them through a chain of interconnected models:
- Location & Climate — Your postal code is linked to local climate data (temperature, solar irradiance, wind), which governs all subsequent calculations.
- Facility Layout — The gross area is divided into functional zones: hydroponic areas, an aquaculture area, social/logistics areas, and infrastructure.
- Crop Production — A dynamic growth model simulates crop yields based on local light and temperature conditions in the greenhouse throughout the year.
- Fish Production — A temperature-controlled growth model calculates fish yields, feed requirements, and the nutrient link between fish and plants.
- Energy & Heating — A greenhouse heating demand model determines how much energy is needed to maintain growing conditions throughout the year.
- Equipment & Capital Expenditure (CAPEX) — A detailed CAPEX model maps your configuration to the specific equipment required, including economies of scale in pricing. Operating Expenses (OPEX) — Annual operating costs are calculated from actual consumption data (energy, water, feed, seeds, labor, etc.) and adjusted for inflation.
- Financial Analysis — Revenue, costs, and investments are summarized into standardized financial KPIs (Key Performance Indicators): net present value, internal rate of return, return on investment, and payback period.
Each step feeds into the next, creating a coherent picture of the technical and financial viability of your project.
Location-based climate data
The calculator uses climate data from the German Meteorological Service (DWD). When you enter a postal code, the system retrieves the local monthly average values for that specific area:
- Air temperature — minimum, average, and maximum values. One of the main factors for plant growth and heat loss.
- Global radiation — the total solar energy received, used for passive heating calculations.
- Wind speed — affects convective heat loss through the greenhouse envelope.
- Daily light integral (DLI) — the total photosynthetically active radiation available to plants each day, calculated from the global radiation in mol/m²/day. This is another key factor for plant growth.
- Standard outdoor temperature (DIN EN 12831) — the coldest expected winter temperature (5th percentile), used for sizing heating systems.
All these values vary considerably across Germany. A plant near Freiburg will have completely different energy costs and crop yields than one near Hamburg — the calculator automatically takes these differences into account.
The plant growth model
Plant yields aren’t simply looked up in a table. The calculator uses a dynamic biomass accumulation model that simulates daily plant growth based on actual environmental conditions. The calculation of crop cycles also takes into account that the plants are typically started on the facility’s own propagation shelves.
How it works
- Each day of the growing season, the model calculates how much biomass a plant gains. This depends on three interacting factors:
- Available light (DLI) — Plants convert light into biomass through photosynthesis. The model uses crop-specific values for light use efficiency (LUE) — that is, how many grams of dry mass a plant produces per mole of light received. Lettuce, for example, is photosynthetically more efficient than basil.
- Temperature response — Every crop has a base temperature (below which growth stops), an optimum temperature (at which growth is fastest), and a maximum temperature (above which growth stops again). The model uses a section-defined function that captures the asymmetric way in which plants respond to heat stress compared to cold stress.
- Developmental stage — Young seedlings cannot use light as efficiently as mature plants simply because their leaf area is still small. The model takes this into account with a sigmoid function that gradually increases the photosynthetic capacity as the plant develops.
Supported plant cultures
The model contains calibrated parameters for:
| Kultur | temperature | growth cycle | typical yield |
|---|---|---|---|
| Lettuce | 22 °C | 54–75 days | 0,2 kg/plant |
| Basil | 29 °C | 32–52 days | 0,04 kg/plant |
| Tomato | 24 °C | ~270 days | 0,5 kg/plant/week |
Assimilation lighting
In year-round operation, the calculator takes into account additional assimilation lighting during the winter months when the natural DLI value falls below the crop’s minimum requirement. This increases both the yield (by extending the effective growing season) and electricity costs—both of which are factored into the model.
The fish growth model
The aquaculture component uses a temperature-dependent allometric growth model to simulate fish production in a recirculating aquaculture system (RAS).
How it works
Fish growth is driven by two biological relationships:
- Size-dependent feeding—Smaller fish eat proportionally more (relative to their body weight) than larger fish. The model uses a power function where the feeding rate decreases as the fish grows. Each species has its own calibrated parameters for this relationship.
- Temperature response—Fish have an optimal water temperature at which growth and feed conversion are most efficient. The model uses a Gaussian response curve centered on the species‘ preferred temperature. Deviations in either direction decrease growth efficiency.
The combination of these two factors, along with the feed conversion ratio (FCR—how efficiently the fish converts food into body mass), determines daily growth.
Supported fish species
| Species | Optimal temperature | Feed conversion rate (FCR) | Characteristics |
|---|---|---|---|
| Tilapia | 28 °C | 1.15 | Warm water, fast growth, robust |
| Trout | 16 °C | 1.25 | Kaltwasser, hohe Anforderungen an WaCold water, high water quality requirements |
| European Catfish | 26 °C | 1.20 | Warm water, robust, excellent fillet quality |
The choice of species not only influences the fish yields, but also the heating requirements (warm water species require more energy in the German climate) and the nutrient profile of the aquaculture wastewater.
The nutrient cycle — The connection between fish and plants
Aquaponics is fundamentally about the nutrient cycle between fish and plants. The calculator explicitly models this:
- Fish produce nutrients — Fish excrete nitrogen (N) and phosphorus (P) as metabolic waste products. The model calculates how much of each nutrient is produced based on the feed volume and species-specific excretion rates. Not all excreted nutrients are available to plants: Only some of the excreted nitrogen and phosphorus dissolve (the rest is bound in the solid waste). The model only considers the dissolved excretions. It is potentially possible to optimize the nutrient balance by using additional methods to make nutrients available from the solid waste. However, this is not considered in the potential analysis.
- Plants consume nutrients — Each crop species has a specific nitrogen and phosphorus requirement per kilogram of yield. The model sums the total nutrient requirement across all hydroponic sections.
- The system is balanced — The calculator sizes the aquaculture component so that the nutrient production of the fish matches the nutrient requirements of the plants. This can be optimized for either nitrogen or phosphorus balancing (configurable in the system design). In seasonal operating modes, the fish feed requirement follows the nutrient demand curve of the hydroponics system—less feed during the transitional seasons, none during the off-season.
This coupling means that changing your plant production focus directly impacts how many fish need to be stocked, how much feed is consumed, and consequently, the project’s cost structure.
Heat requirements of the greenhouse
Maintaining the correct temperature in a greenhouse requires a lot of energy in the German climate—often the single largest operating cost factor. The calculator uses a parametric heat demand model that takes the following into account:
Components of heat loss
- Ventilation losses — Heat lost through air exchange, whether through intentional ventilation or unintentional infiltration.
- Transmission losses — Heat flowing through walls and roof, determined by the greenhouse’s design and its thermal properties (U-values). A double-glazed Venlo greenhouse loses significantly less heat than a PE film tunnel.
- Soil losses — Heat conducted through the soil into the underlying earth (assuming a soil temperature of approximately 10 °C).
What reduces heating requirements
- Solar Gains — Direct sunlight provides free heating. The model uses site-specific monthly solar irradiance data to account for passive solar heating.
- Energy Screens — Optional energy screens that can be closed at night drastically reduce the effective U-value of the roof (for example, from 4.5 to 2.5 W/m²K).
- Improved Insulation — The choice between PE film and double glazing has a significant impact on annual heating costs.
The operating mode is crucial
In year-round operation, the greenhouse is heated throughout the winter to maintain optimal growing conditions—this is the most energy-intensive configuration. Seasonal operation completely avoids winter heating and is only used during the warmer months. Extended season operation includes the transitional seasons of spring and autumn with moderate heating.
It is important to understand that the chosen operating mode also influences the greenhouse’s features. For example, greenhouses selected for year-round operation are automatically equipped with multiple high-efficiency energy screens on the roof and side walls. In extended season operation, only a single energy screen is assigned to the roof, and in pure seasonal operation, only a less energy-efficient shade screen is used.
This should also be considered when selecting a greenhouse. For example, a single-glazed Venlo greenhouse is significantly less energy-efficient in extended season operation than a PE greenhouse with air cushions.
The heat demand model provides both a peak heating load (kW, for dimensioning the heating system) and the annual energy consumption (kWh/year, for operating cost calculations).
Financial indicators
Investment costs, operating costs, sales and debt service – this encompasses all financial calculations.
Capital expenditures (CAPEX)
The calculator generates a detailed equipment and construction cost list tailored to your specific configuration. It doesn’t use simple average values per square meter—instead, it allocates your input across 30 individual cost categories:
What’s included
- Greenhouse structures — price per m² by type (PE film or Venlo glass, including ventilation option).
- Ancillary buildings — office space, sanitary facilities, cold storage rooms — each calculated separately and only included if „new construction required“ is selected.
- Heating systems — dimensioned for the calculated peak heating load: burners, pipe systems, buffer tanks, vegetation heating.
- Aquaculture systems — RAS equipment (tanks, biofilters, pumps, aeration), priced per m³ of production volume.
- Hydroponic equipment — media beds, DWC (Deep Water Culture) tanks, floating rafts, propagation racks, nanobubble aeration — each tailored to the production focus.
- Environmental control — climate control systems, assimilation lighting (if applicable), roof screens, UV disinfection.
- Irrigation & utilities — piping, water treatment, electrical infrastructure.
Economies of scale
Larger systems benefit from lower unit costs. The calculator applies a power-law scaling function to each cost category—as the system area increases, the cost per square meter decreases. The effect varies depending on the category: greenhouse structures, for example, exhibit moderate scaling, while heating systems show strong scaling, reflecting the real-world advantage of central heating.
Inflation adjustment
All basic cost data is stored with its respective reference year. The calculator applies industry-specific inflation indices (construction price, agricultural, and labor cost indices) to adjust all costs to a uniform price level for the current year.
Operational costs
The annual running costs are composed of actual consumption quantities multiplied by unit prices, not simplified percentages:
Cost categories
- Water — Additional water to compensate for evapotranspiration losses and system wastewater.
- Fish feed — Derived from the nutrient balance model; the required feed quantity is a calculated result, not an assumption.
- Seeds & Planting Material — Crop-specific costs: lettuce seeds, basil seeds, tomato seedlings — each with very different unit costs.
- Consumables — Substrate, mineral fertilizers (to supplement fish nutrients as needed), plant protection products.
- Aquaculture Consumables — Seedlings (fingerlings), disinfectant, fish transport.
- Packaging & Distribution — Crates, pallets, cold chain logistics.
- Waste Disposal — Plant waste, packaging recycling.
- Lease — Configurable annual costs per square meter.
Labor
Personnel costs are calculated based on task-based working hours:
- Each work step (sowing, transplanting, harvesting, fish management, cleaning) has a defined time requirement per unit.
- Working hours are divided between permanent staff (40%) and seasonal workers (60%), each at different hourly rates based on German agricultural tariffs.
- Each configuration includes at least one facility manager.
Maintenance
An annual maintenance budget is calculated as a percentage of CAPEX and reflects the ongoing costs of maintaining and replacing equipment.
Financial analysis
All technical results — revenues, costs, income — are incorporated into a sound financial model:
Revenue
The annual income is calculated from:
- Plant sales — Yield (kg/year) × Selling price (€/kg), broken down by crop category. You can override the default prices for fruiting vegetables, leafy vegetables, herbs, and fish in the optional fields.
- Fish sales — Yield (kg/year) × Selling price (€/kg), taking into account the product mix (ready-to-cook, fillets, smoked fish, live stocking fish) and their varying weight proportions.
Key Performance Indicators (KPIs)
The calculator generates four standard financial ratios:
| KPI | What it tells you |
|---|---|
| Net Present Value (NPV) | The total value your project creates over its lifetime, discounted to today’s money. A positive NPV means the project is financially viable at the assumed discount rate. |
| Internal Rate of Return (IRR) | The effective annual return on your investment. Compare this to your cost of capital or alternative investments. |
| Return on Investment (ROI) | Average annual profit as a percentage of total invested capital. A quick profitability indicator. |
| Payback period | How many years it takes for the cumulative cash flow to become positive — i.e., when you have recouped your initial investment. |
Cash Flow Forecast
The model generates an annual cash flow over the project duration:
- Year 0: Initial CAPEX expenditures.
- Years 1–N: Annual revenues less annual OPEX, with appropriate discounting.
The cash flow waterfall diagram in the results illustrates how revenues, operating expenses, and the initial investment are related to each other.
What the results will show you
After the calculation, the dashboard displays:
- KPI Cards — The four most important financial metrics at a glance, color-coded for quick assessment.
- Facility Area Breakdown — How the total area is divided between aquaculture, hydroponics areas, and ancillary spaces.
- Labor Breakdown — Labor hours and costs broken down by aquaculture and hydroponics areas.
- Revenue by Category — Contribution of each plant and fish product to total revenue.
- Capacity Expenses (CAPEX) — Breakdown of initial investment by category.
- Annual Operating Expenses (OPEX) — The seven OPEX categories: energy, water, waste disposal, consumables, maintenance, lease, and labor.
- Cash Flow Waterfall — Visual representation of how costs and revenues contribute to net income.
- Production Tables — Detailed output per section, showing section type, crop/species, area allocation, and annual production.
Data quality and sources
The calculator is based on:
- Climate data from the German Meteorological Service (DWD), providing location-specific monthly averages at the county level.
- Cost models maintained with over 70 individual cost items (34 CAPEX, 40+ OPEX), each with reference year, unit, and scaling parameters.
- Biological parameters calibrated from aquaponics research literature and practical experience, covering three fish species and three crop categories.
- Inflation indices from the Federal Statistical Office (construction, agriculture, and labor sectors), keeping all cost forecasts up to date.
- Labor costs based on collective bargaining agreements for agriculture in Germany.
The system designs (equipment configurations) reflect real aquaponics plant layouts and are continuously refined based on operational data.
Limitations of the calculator
Like any planning tool, the calculator also works with models and assumptions:
- Climate data uses monthly averages—extreme weather events or unusual years are not included.
- Growth models are simplified — real plant and fish growth is influenced by many factors beyond light, temperature, and feed (diseases, water quality fluctuations, management quality).
- Costs are estimates — actual equipment prices, construction costs, and raw material prices vary depending on the supplier, region, and market conditions at the time of purchase.
- The model assumes competent management — mortality rates, crop losses, and utilization efficiencies reflect well-managed operations.
The calculator is designed for pre-feasibility studies and project planning — it provides a solid foundation for understanding whether a project concept is worth pursuing and how different configuration decisions affect the outcome. Detailed technical designs and precise cost calculations require additional site-specific analysis.