IPCC 2019 Tier 1 Parameters — Editable Inputs
Corn — Baseline Fertilizer


Wheat — Baseline Fertilizer


N Reduction Rate (Project)


FracLEACH


Corn — N₂O Calculation Chain (IPCC Tier 1)
Step / ParameterBaselineABCUnit
Wheat — N₂O Calculation Chain (IPCC Tier 1)
Step / ParameterBaselineABCUnit
N₂O Emission Reductions — Scenario Comparison
N₂O Emissions (tCO₂e/ha/yr) — Corn & Wheat by Scenario
Emission Reduction vs Baseline (tCO₂e/ha/yr)
MetricCornWheatRotation Avg

IPCC 2019 Tier 1 Formula:
N₂O-N = N×EF₁ + N_urea×FracGASF_urea×EF₄ + N_dap×FracGASF_dap×EF₄ + N×FracLEACH×EF₅
N₂O (kg/ha) = N₂O-N × 44/28 · tCO₂e/ha = N₂O_kg × GWP/1000
EF₁=0.005 · EF₄=0.01 · EF₅=0.011 · FracGASF_urea=0.15 · FracGASF_dap=0.08 · GWP=273 (AR6)

N₂O Emission Modeling Methodology

Direct and indirect N₂O is modeled under different water and fertilization regimes, following Approach 3 in the VM0042 protocol. The transition from flood to drip reduces waterlogging frequency, shifting production from denitrification-dominated to nitrification-dominated pathways, generally lowering total emissions [1]. In this study, the switch from flood/furrow/sprinkler to surface drip irrigation and sub-surface drip irrigation (SDI) were modeled under various rotation scenarios.

Although the literature provides more precise emission factors (EFs) for flood-irrigated maize [2] and comparative analyses across irrigation systems and crop types [3], no study has explicitly evaluated EFs across comparable drip- and flood-irrigated maize scenarios. To ensure methodological consistency and avoid double counting, the IPCC default EF for all N inputs in dry climates [4], set at 0.005, is applied uniformly across all scenarios.

Indirect N₂O emission factors for atmospheric deposition (EF₄ = 0.010 kg N₂O-N kg⁻¹ NH₃-N) and leaching (EF₅ = 0.011 kg N₂O-N kg⁻¹ N leached) were adopted from IPCC (2019) Tier 1 defaults and held constant across all irrigation scenarios [4]. These factors represent biogeochemical processes occurring after reactive nitrogen leaves the field boundary — atmospheric redeposition and denitrification in receiving water bodies, respectively — and are therefore independent of on-farm irrigation management. Therefore, no scenario-specific adjustment was applied.

For the FracLEACH parameter, the IPCC default value of 0.24 [4] is applied in the baseline scenario. Empirical evidence from maize production systems under semi-arid conditions indicates that drip irrigation reduces nitrogen losses via leaching by approximately 33% compared to flood irrigation [5]. This reduction factor is therefore applied, resulting in an assumed FracLEACH value of 0.16 for drip irrigation. Due to the lack of differentiated data, the same value is also used for the SDI scenario. Furthermore, as the referenced study reports no significant difference in NH₃ volatilization between irrigation methods, FracGASF,urea and FracGASF,DAP are assumed to remain at their IPCC default values of 0.15 and 0.08, respectively, across all scenarios.

References

[1] Gültekin, R., Avağ, K., Görgiişen, C., Öztürk, Ö., Yeter, T. & Bahçeci Alsan, P. (2023). Effect of deficit irrigation practices on greenhouse gas emissions in drip irrigation. Scientia Horticulturae, 310, 111757.

[2] Franco-Luesma, S., Lafuente, V., Alonso-Ayuso, M., Bielsa, A., Kouchami-Sardoo, I., Arrúe, J.L. & Álvaro-Fuentes, J. (2022). Maize diversification and nitrogen fertilization effects on soil nitrous oxide emissions in irrigated Mediterranean conditions. Frontiers in Environmental Science, 10, 914851.

[3] Cayuela, M.L. et al. (2017). Direct nitrous oxide emissions in Mediterranean climate cropping systems: Emission factors based on a meta-analysis of available measurement data. Agriculture, Ecosystems & Environment, 238, 25–35.

[4] Baasansuren, J. et al. (2019). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. IPCC, Switzerland.

[5] Di, Y., Gao, Y., Yang, H., Yan, D., Tang, Y., Zhang, W., Hu, Y. & Li, F. (2024). Cutting carbon and nitrogen footprints of maize production by optimizing nitrogen management under different irrigation methods. Frontiers in Plant Science, 15, 1476710.

SOC Reference — SoilGrids (ISRIC) Data for Turkish Agricultural Regions

Click a region to set SOC_REF. Values = OCS 0–30 cm (t C/ha) from SoilGrids REST API (ISRIC, 2024).

Selected:  |  SOC_REF = 30 t C/ha  
IPCC 2006 Tier 1 — Land Management Factors
FactorValueNote
FLU — Land use (annual cropland)1.00Cropland remaining cropland [IPCC 2006, Table 5.4]
FI_baseline — Input factor (flood)1.00Medium residue, no manure [Table 5.6, warm dry]
FI_project — Input factor (drip)1.11High residue (optimised fertigation → better yield → more residue) [Table 5.6]
FMG_baseline — Full tillage (flood)1.00Full tillage = 1.00 [Table 5.5, warm dry]
FMG_ScenA — Surface drip1.00No tillage change with surface drip lines
FMG_ScenC — SDI (no-till)1.10SDI buried lines → no-till feasible → FMG_no-till [Table 5.5]
Transition period20 yrDefault: 20 years to new SOC equilibrium [IPCC 2006 §2.3.3.1]
C→CO₂ conversion44/12 = 3.667Molecular weight ratio CO₂/C
SOC Stock Calculation Results
ParameterBaselineABCUnit
SOC Accumulation Over 20-Year Transition Period
Cumulative SOC Stock (t C/ha) — IPCC Linear Accumulation
Annual ΔSOC Carbon Credit (tCO₂e/ha/yr)
NPV/ha — Scen A
Surface Drip + N₂O + SOC
NPV/ha — Scen B
Surface Drip + N₂O only
NPV/ha — Scen C
SDI + N₂O + SOC
Programme Carbon Revenue
Total USD (all farms, best scenario)
Annual Benefits & Costs Breakdown (USD/ha/yr)
Carbon Revenue Breakdown (per ha/yr)
ComponentScen AScen BScen CUnit
NPV Sensitivity to Carbon Price (per ha)
Cumulative Cash Flow per Farmer (full programme duration)
MRV Design Impact on Farmer Cash Flow — Surface Drip & SDI × All 4 MRV Designs
Her iki sulama senaryosu × 4 MRV tasarımı. App1 SOC = yıllık kredi; App2 = Y6/11/16/21 lump sum. App1 N₂O = ölçülen (×EF ratio×0.95); App3 = IPCC default. Solid = SDI, Dashed = Surface Drip.
Programme Totals (all farms × farm size × duration)
MetricScen AScen BScen CUnit
Carbon Credits Generated Over Programme Duration (tCO₂e/ha/yr)
Annual Credits per ha — corn/wheat year variation + SOC
Credits Summary
MetricScen AScen BScen C
Total Carbon Revenue — All Farms, Cumulative (USD)
Implementer / Programme Operator Revenue
Cumulative implementer net revenue (after costs)
Programme Operator Costs
Revenue Summary
Dynamic Enrollment Model — Growth Over Time
Starting from farms × ha. Each new cohort starts at base farm size and grows independently.
Total enrolled farms & area over time
Cumulative farmer carbon revenue — dynamic enrollment (Scenario A / B / C)
Implementer cumulative net revenue — dynamic enrollment (Scenario A / B / C)
Implementer Economics × MRV Design — SDI Programme · All 4 Designs
Cumulative implementer net revenue after full MRV costs (from MRV tab parameters) + annual expenses. Irrigation = SDI. Carbon = implementer's share per year. Verification lag applied.
Phased Regional Enrollment Simulator — Cohort SOC Clock

Her bölgenin SOC ölçüm saati kendi enrollment yılından başlar. Sonradan katılan çiftçiler mevcut SOC birikimini devralmaz — 20 yıllık SOC geçiş süreci sıfırdan başlar.

Bölge / Faz Başlangıç Yılı Başlangıç Çiftlik ha/çiftlik₀ +Çiftlik/yıl Max Çiftlik ha Büyüme %/yıl Max ha/çiftlik
Yıllara göre enrolled alan — bölgelere göre (ha)
Kohort bazlı SOC kredi çıkışı (tCO₂e/yıl) — her bölge kendi saatiyle
Implementer kümülatif net gelir — phased enrollment vs flat (MRV C, SDI)
MRV Cost & Measurement Parameters
SOC Sampling — VM0042 §8.2.1.3
N₂O Sampling
Costs
MRV Scenario Comparison — Total Program · 20-Year Horizon
Scenario A Scenario B Scenario C Scenario D
SOC / N₂O approach App 1 + App 1 App 2 + App 1 App 1 + App 3 App 2 + App 3
Cumulative Net Revenue After MRV Cost
SOC Sampling Optimisation — Net Value vs. Sample Size
Net SOC credit revenue minus SOC-specific sampling cost · total program
Year-by-Year MRV Cost — All 4 Scenarios