| Emissions Source | Unit | kg CO₂–e/unit | Uncertainties |
|---|---|---|---|
| Forest Growth – Natural Forests | |||
| Post–1989 Regenerating natural forest | ha | –7973.151769 | 44.50% |
| Pre–1990 Regenerating natural forest | ha | –1566.381483 | 119.50% |
| Pre–1990 Tall natural forest | ha | 0 | |
| Forest Growth – Planted Forests – Approach One: Stock Change Accounting | |||
| All Planted forests | ha | –35140.43872 | 13.30% |
| All hardwoods | ha | –26256.37156 | 146.80% |
| Other softwoods | ha | –29956.33595 | 23.30% |
| Pinus radiata | ha | –36565.42587 | 13.30% |
| Forest Growth – Planted Forests – Approach Two: Averaging Accounting | |||
| All hardwoods – First rotation (Age 24 years and under) | ha | –26256.37156 | 146.80% |
| All planted forest above the long–term average age | ha | 0 | |
| All planted forests – First rotation (Age 23 years and under) | ha | –35140.43872 | 13.30% |
| Other Softwoods – First rotation (Age 29 years and under) | ha | –29956.33595 | 23.30% |
| Pinus radiata – First rotation (Age 23 years and under) | ha | –36565.42587 | 13.20% |
11 Agriculture, forestry and other land-use emission factors
This category covers emissions produced by land use, land-use change and forestry (LULUCF), livestock enteric fermentation, manure management, agricultural soils and fertiliser use.
We selected the emission factors below, based on appropriate available data and the professional opinions of the Ministry for Primary Industries (MPI) and the Ministry for the Environment.
- Land use, land-use change and forestry:
- forest growth
- forest harvest and deforestation.
- Agriculture:
- enteric fermentation from livestock
- manure management from livestock
- agricultural soils from livestock
- fertiliser and lime use.
Users should disclose in their inventories if they include animals grazing on land not owned by the entity.
Entities looking for a more accurate farm-based estimate of their agricultural emissions are encouraged to use the Ag Matters on-farm emissions calculator.
The list of tools approved by the He Waka Eke Noa programme can be found here: Know your number – Ag Matters.
11.1 Overview of changes since previous update
| Domain | Emission factors | Size of change | Explanation for change |
|---|---|---|---|
| Agriculture | Livestock factors | Between -10.5% to -36.2% for Deer and Swine and Non-dairy cattle +5.5% to +7% | The change is due to population, emissions calculation methodologies and how populations are accounted detailed in the New Zealand’s latest Greenhouse Gas Inventory (1990–2023). In summary: - Population decrease for deer - Revisions in how different populations of poultry have been accounted for - New methodolology to calculation emissions for deer and swine |
| Forestry | Land use growth and change | +40.6% (removals) +181.3% (land-use change) | Change is due to an update to the expected harvest age of hardwoods, based on new LUCAS research for the New Zealand’s latest Greenhouse Gas Inventory (1990–2023). The expected harvest age has changed as follows: - Pinus radiata from 22 years to 23 years - Other Softwoods from 28 years to 29 years - All hardwoods from 13 years to 24 years |
11.2 Land use, land-use change and forestry
11.2.1 Overview of the sector
GHG emissions from vegetation and soils due to human activities are reported in the LULUCF sector. This guide provides emission factors related to forest growth, forest harvest and deforestation only. The term LULUCF is used for consistency with New Zealand’s Greenhouse Gas Inventory 1990–2023.
The LULUCF sector is responsible for both emitting GHGs (primarily carbon dioxide) to the atmosphere (emissions; ie, through harvesting and deforestation) and removing GHG from the atmosphere (removals; ie, through vegetation growth). Most emissions reported in this sector are due to forestry activities such as harvest operations in production forests, and most removals are due to forest growth.
The basis for the methods given here is that the flux of carbon dioxide to and from the atmosphere is due to the changes in carbon stocks in vegetation and soils. When emissions exceed removals, LULUCF is a ‘net source’, and emissions are positive. When removals exceed emissions, LULUCF is a ‘net sink’, and emissions are negative.
The guide provides methods to estimate the carbon stock change (or flux) that occurs from forestry activities during the applicable measurement period. We do not include methods to estimate carbon stock changes in non-forest vegetation, soils, harvested wood products, or for the associated nitrous oxide and methane emissions. For more detail, see New Zealand’s Greenhouse Gas Inventory 1990–2023.
In line with ISO 14064-1:2018 and the GHG Protocol, entities should consider LULUCF emissions and removals if they have forest land within their measurement boundary, or own land that has been deforested during the measurement period.
Entities with LULUCF emissions should calculate and report these separately from direct and indirect (Scope 1, 2 and 3) emissions.
The emission factors in this guide are New Zealand-specific, derived from national averages.
Although the main aim of this section of the guide is to estimate stock changes from forestry activities, it can also be used to estimate the total carbon stored for a given forest type in a given area. This can help entities understand the potential impact of some forestry activities on emissions, and how to manage land use for carbon.
11.2.2 LULUCF emission factors
11.2.2.1 Planted forests
Two approaches are provided to calculate emissions and removals from planted forests. Only one approach can be used, a mixture of approaches is not permitted.
Approach one – Carbon stock change accounting
This approach estimates the net emissions and removals from forest growth and harvesting each year. The emission factors are based on the Land Use and Carbon Analysis System (LUCAS) national forest inventory.
Annual removals from forest growth (Table 11.2) are estimated as an average annual increment over the average duration of their harvesting cycle. Emission factors are provided for three species groups (Pinus radiata, other softwoods, and all hardwoods) and an ‘all planted forest category’ (this represents an average emission factor for New Zealand’s entire planted forest estate, regardless of species). The ‘all planted forest’ category may only be used when a species breakdown is not available. The emission factors for forest harvesting and deforestation are provided as the entire loss of carbon on the clearing of planted forest at the average harvest (Table 11.3).
Note, if species-specific emission factors for forest growth are used, the corresponding species-specific values must be used to account for land-use change emissions. Likewise, if the ‘all planted forest’ emission factor is used for forest growth, then it must also be used to account for land-use change emissions.
Approach two – Averaging accounting
The averaging approach estimates carbon dioxide removals from the planting of new forests (afforestation) up to the age when they reach their average long-term carbon stock. The long-term average carbon stock represents the average carbon that is estimated to be stored over successive rotations.
Once carbon dioxide removals have been measured up to the long-term average carbon stock, there are assumed to be no further emissions or removals (ie, no additional removals from growth nor emissions from harvest). The averaging approach requires information on forest plant date, so the age can be determined, and for the forest to be in its first rotation (forests that have been replanted following a harvesting event are beyond their long-term average carbon stock).
The age that the long-term average carbon stock is reached varies depending on species. Any forest that is over the age1 of the long-term average carbon stock is considered to have an emission factor of zero. The ‘all planted forest’ category may only be used when a species breakdown is not available (this represents an average emission factor for New Zealand’s planted forest estate, regardless of species).
This approach broadly aligns with the approach that New Zealand will take to account for emissions and removals in post-1989 planted forest under the Paris Agreement. The averaging approach can be appropriate for participants who can identify the plant date of their forests, or do not have data available on harvesting activity.
Deforestation emissions are still accounted in full, as in approach one (Table 11.3). If species-specific emission factors for forest growth are used, the corresponding species-specific values must be used to account for land-use change emissions. Likewise, if the ‘all planted forest’ emission factor is used for forest growth, then it must also be used to account for land-use change emissions.
11.2.2.2 AFFORESTATION, DEFORESTATION AND HARVESTING
Afforestation occurs when forest is established on previously unforested land.
Deforestation occurs when forest land is cleared for another land use.
Harvesting refers to the harvest of planted production forests for timber, which are then replanted.
11.2.2.3 Natural forests
The emission factors for natural forest growth (shown in Table 11.2) are based on the LUCAS national forest inventory. We provide separate emission factors if the forest is pre-1990 or post-1989. Post-1989 regenerating natural forest is regenerating natural forest that was established from 1 January 1990 onwards. Pre-1990 natural forest is natural forest that was established before 1 January 1990. Within pre-1990 natural forest we provide separate emission factors if the forest is tall or regenerating ie, recovering from conversion from another land use, logging, or other anthropogenic disturbance.
The emission factor for natural forest deforestation (shown in Table 11.3) is based on the average stock at the national level, calculated from the LUCAS national forest inventory.
| Emissions Source | Unit | kg CO₂–e/unit | Uncertainties |
|---|---|---|---|
| Land–Use Change – Natural Forests | |||
| Post–1989 Regenerating natural forest: Deforestation | ha | 141350 | 27% |
| Pre–1990 Regenerating natural forest: Deforestation | ha | 280293.6545 | 27.20% |
| Pre–1990 Tall natural forest: Deforestation | ha | 898577.3185 | 21% |
| Land–Use Change – Planted Forests – Approach One: Stock Change Accounting | |||
| All Planted forests: Harvest or Deforestation | ha | 983932.2842 | 21.80% |
| All hardwoods: Harvest or Deforestation | ha | 787691.1469 | 147.80% |
| Other Softwoods: Harvest or Deforestation | ha | 1198254.189 | 29.10% |
| Pinus radiata: Harvest or Deforestation | ha | 1023831.924 | 21.80% |
| Land–Use Change – Planted Forests – Approach Two: Averaging Accounting | |||
| All Planted forests: Deforestation | ha | 983932.2842 | 21.80% |
| All Planted forests: Harvest | ha | 0 | |
| All hardwoods: Deforestation | ha | 787691.1469 | 147.80% |
| All hardwoods: Harvest | ha | 0 | |
| Other Softwoods: Deforestation | ha | 1198254.189 | 29.10% |
| Other Softwoods: Harvest | ha | 0 | |
| Pinus radiata: Deforestation | ha | 1023831.924 | 21.80% |
| Pinus radiata: Harvest | ha | 0 | |
11.2.3 GHG inventory development
To calculate LULUCF emissions, entities need activity data on each forest type, the area harvested and any changes to forested land within the organisational boundary for the measurement period. Different forest types have different emission factors, while deforestation and harvest rates change over time.
First, determine the type of forest and the area it covers. The New Zealand parameters to define a forest are a minimum area of 1 hectare, the potential to reach a minimum height of 5 metres and a minimum crown cover of 30 per cent.
Forest types
1. Pre-1990 Tall natural forest: Areas, that on 1 January 1990, were and presently comprise of mature indigenous forest.
2. Pre-1990 Regenerating natural forest: Areas, that on 1 January 1990, were and presently comprise of indigenous and naturally occurring vegetation, including broadleaved hardwood shrubland, mānuka–kānuka and other woody shrubland, with potential to reach forest definition under its current management. This category represents mid-successional regenerating forest.
3. Post-1989 Regenerating natural forest: Areas of forest established from 1 January 1990 onwards that comprise of indigenous tree species arising from natural regeneration. This category represents early successional regenerating forest and may also have some exotic species present.
4. Planted forest: plantations of forest species mainly used for forestry, including:
- radiata pine (Pinus radiata)
- softwoods, such as Douglas fir (Pseudotsuga menziesii)
- hardwoods, such as eucalypts (Eucalyptus spp.)
- other planted species (with potential to reach ≥5 metre height at maturity in situ).
The following information can be used to determine natural forest types:
The LUCAS Land Use Map2 can provide area by vegetation type (pre-1990 and post-1989 natural forest) at 1990, 2008, 2012, 2016 and 2020. It requires geospatial expertise to analyse and extract the data by region. This is free to use and supports users in monitoring changes in their own land management practices.
The New Zealand Land Cover Database (LCDB)3 provides multi-temporal land cover. This can be used to differentiate between tall and regenerating pre-1990 natural forest. Two LCDB classes are classified as tall forest; indigenous forest and broadleaved indigenous hardwoods. All other categories are classified as regenerating forest. It requires geospatial expertise to analyse and extract the data for sub-national analysis.
Alternatively, if the age of the forest is known or can be estimated, this can be used to determine forest type:
- Planted from 1990 onwards: post-1989 regenerating natural forest
- Planted before 1990: pre-1990 regenerating natural forest
- Planted 100 or more years ago: pre-1990 tall natural forest
Entities will also need records of forest harvest and deforestation activities (including area in ha) to calculate the emissions from LULUCF. Sources of this information include:
- corporate or farm records for enterprises and entities
- geospatial analysis of the property or region
- the LUCAS Land Use Map
- the New Zealand Land Cover Database (LCDB)
- if Approach two (averaging) is used, the planting date (to calculate the age of the forest)will be required as well as evidence that the forest is in its first rotation.
Using the sources detailed above to gather information on the land use, forest type and size, entities can apply the equation E = Q x F:
- E = emissions from the emissions source in kg CO2-e per year
- Q = area of land (ha)
- F = appropriate emission factors (for land use) from Table 11.2 and Table 11.3.
LAND USE, LAND-USE CHANGE AND FORESTRY: EXAMPLE CALCULATIONS 1
Using Approach one for planted forest
An entity owns 4 ha of land: 3 ha are planted forest (Pinus radiata) and 1 ha is pre-1990 regenerating natural forest. During the reporting year the entity harvested the planted forest for timber.
3 ha of planted forest (Pinus radiata) were harvested, therefore:
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| Total CO₂-e emissions | 3 x 1023831.924 kg CO₂-e per ha | 3,070,000 kg CO₂-e |
The removals (expressed as a negative) for the regenerating pre-1990 natural forest are:
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| Total CO₂-e emissions | 1 x -1566.381483 kg CO₂-e per ha | -1,570 kg CO₂-e |
The sum of the above totals is the total emissions:
- -1,570 kg CO₂-e + 3,070,000 kg CO₂-e = 3,070,000 kg CO₂-e
Note: Negative emissions are a carbon sink. Numbers may not add due to rounding.
LAND USE, LAND-USE CHANGE AND FORESTRY: EXAMPLE CALCULATIONS 2
Using Approach two for planted forest:
An entity owns 40 ha of land: 10 ha are planted forest (Other softwoods) below the long-term average age (< 28 years since time of planting), 20 ha are planted forest (Pinus radiata) above the long-term average age (> 22 years since time of planting) and a further 10 ha of planted forest (Pinus radiata) were deforested during the reporting year.
The removals (expressed as negative) for the 10 ha of planted forest (Other softwoods) below the long-term average age (< 28 years) are:
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| Total CO₂-e emissions | 10 x -29956.33595 kg CO₂-e per ha | -300,000 kg CO₂-e |
The removals (expressed as a negative) for the 20 ha of planted forest (Pinus radiata) above the long-term average (> 22 years):
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| Total CO₂-e emissions | 20 x 0 kg CO₂-e per ha | 0 kg CO₂-e |
The emissions for the 10 ha of planted forest (Pinus radiata) that were deforested:
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| Total CO₂-e emissions | 10 x 1023831.924 kg CO₂-e per ha | 10,200,000 kg CO₂-e |
The sum of the above totals is the total emissions:
- 0 kg CO₂-e kg CO2-e + -300,000 kg CO₂-e kg CO2-e + 10,200,000 kg CO₂-e kg CO2-e = 9,940,000 kg CO₂-e kg CO2-e
Note: Negative emissions are a carbon sink. Numbers may not add due to rounding.
11.2.3.1 Activity data uncertainties
National mapping uncertainty for natural forest and pre-1990 planted forest land is ±5 per cent, and ±8 per cent for post-1989 forest land. As the guide combines planted forest types, we recommend applying the higher uncertainty of ±8 per cent.
11.2.4 Emission factor derivation methodology
As stated above, two approaches are provided to calculate emissions and removals from planted forests. Approach one (carbon stock change accounting) estimates the net emissions and removals from forest growth and harvesting each year. Approach two (averaging accounting) estimates carbon dioxide removals from the planting of new forests up to the age when they reach their average long-term carbon stock.
The approach to emissions estimation for Approach one (stock change accounting) follows this equation:
\[ \begin{aligned} \Delta C &= \sum_{i,j} \Big[ A_{ij} \cdot \big( C_I - C_L \big)_{ij} \Big] \end{aligned} \]
Where:
- ∆C = carbon stock change in the pool, kg C yr-1
- A = area of land, ha
- ij = corresponds to forest type, and whether harvested or deforested
- CI = rate of gain of carbon, kg C ha-1 yr-1
- CL = rate of loss of carbon, kg C ha-1 yr-1.
The area refers to the area of each forest type and whether harvested or deforested in the year of the inventory. The general approach is to multiply the area data by an emission factor to provide the source or sink estimates.
Quantities of carbon can be expressed in different ways: carbon (C), CO2 and CO2-e.
To convert carbon to carbon dioxide, multiply by 44/12 (ie, the molecular conversion of carbon to carbon dioxide).
The approach to emissions estimation for Approach two (averaging) follows this equation:
\[ \begin{aligned} \Delta C &= \sum \Big[ A_{a_i} \cdot C_I + A_b \cdot 0 \Big] \end{aligned} \]
Where:
- ∆C = carbon stock change in the pool, kg C yr-1
- i = corresponds to forest type
- Aa = area of planted forest land that is yet to reach its long-term average, ha
- Ab = area of planted forest land that has reached its long-term average, ha
- CI = rate of gain of carbon, kg C ha-1 yr-1.
11.2.5 Assumptions, limitations and uncertainties
The emission factors are based on national average data, therefore the uncertainties will not necessarily reflect sub-national circumstances.
For natural forests, deforestation and harvest loss, data are based on the national stock average, which comes from the most recent carbon stock inventory for these forests.
The emission factors for planted forest (Approach one) and natural forest in this guide are based on New Zealand’s Greenhouse Gas Inventory 1990–2023. These emission factors represent the most up-to-date forestry data available. ETS look-up tables are another source of emission factors; however, these are not updated as frequently. The emission factors are based on national average data and the uncertainties will not necessarily reflect sub-national circumstances and will not be exactly the same as the ETS estimates of carbon sequestration which differentiate based on tree age, region and to a limited extent, the species. Selection of the most appropriate emission factor should be guided by the requirements of the intended use and by the user’s inventory. The age at which the long-term average carbon stock is reached for planted forests (Approach two) are based on Wakelin et al.4
11.3 Agriculture
Emissions from agriculture are produced in several ways. This section includes emissions from enteric fermentation, manure management and fertiliser use, in more detail:
- Methane from enteric fermentation is a by-product of ruminant digestion. Cattle and sheep are the largest sources of methane in this sector.
- Storing and treating manure, including spreading it onto pasture, produces methane and nitrous oxide.
- Losses also occur from manure that is deposited by livestock directly onto pasture.
- Applying nitrogen (urea-sourced or synthetic) fertiliser onto land produces nitrous oxide and carbon dioxide (urea) emissions.
- Applying lime and dolomite fertilisers results in carbon dioxide emissions.
If an entity directly owns and manages livestock, agriculture emission sources are direct (Scope 1).
Note the livestock emissions you calculate using these implied emission factors are intended to be an approximate estimate of emissions only, and are based on the average per-animal biological emissions of New Zealand’s main farmed livestock categories. Implied emission factors are provided per head of livestock type per year.
Actual livestock emissions for an individual farm will differ depending on a number of factors, including live-weights, productivity, and feed quality. Entities looking for a more accurate farm-based estimate of their agricultural emissions are encouraged to use alternative GHG calculator tools. The list of tools approved by the He Waka Eke Noa programme can be found here: Know your number – Ag Matters.
11.3.1 Enteric fermentation
Enteric fermentation is the process by which ruminant animals produce methane through digesting feed. We provide emission factors for dairy cattle, non-dairy cattle, sheep and deer and other minor livestock categories in Table 11.4.
| Emissions Source | Unit | kg CO₂–e/unit | CO₂/unit (kg CO₂–e) | CH₄/unit (kg CO₂–e) | N₂O/unit (kg CO₂–e) | Uncertainties |
|---|---|---|---|---|---|---|
| Enteric fermentation | ||||||
| Alpaca and llama | per head | 224 | 0 | 224 | 0 | 15.5% |
| Dairy cattle | per head | 2649.341783 | 0 | 2649.341783 | 0 | 15.5% |
| Deer | per head | 547.67824 | 0 | 547.67824 | 0 | 15.5% |
| Goats | per head | 250.9684211 | 0 | 250.9684211 | 0 | 15.5% |
| Horses | per head | 504 | 0 | 504 | 0 | 15.5% |
| Mules and asses | per head | 280 | 0 | 280 | 0 | 15.5% |
| Non–dairy cattle | per head | 1950.136772 | 0 | 1950.136772 | 0 | 15.5% |
| Sheep | per head | 348.6860224 | 0 | 348.6860224 | 0 | 15.5% |
| Swine | per head | 25.58803376 | 0 | 25.58803376 | 0 | 15.5% |
Note: For enteric fermentation there is no estimation for poultry.
11.3.1.1 GHG inventory development
Entities should collect data on the number and type of livestock as at 30 June during the measurement period (regardless of whether the period is a calendar or financial year) to calculate emissions from enteric fermentation.
Applying the equation E = Q x F, this means:
- E = emissions from the emissions source in kg CO2-e per year
- Q = number of animals (per head per livestock type)
- F = appropriate emission factors from Table 11.4.
ENTERIC FERMENTATION: EXAMPLE CALCULATION
An entity owns 2,400 sheep and 210 dairy cows on 30 June during the reporting period. They graze on land owned by the entity.
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 210 x 2649.341783 kg CO₂-e per per head | 556,000 kg CO₂-e |
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 2,400 x 348.6860224 kg CO₂-e per per head | 837,000 kg CO₂-e |
The sum of the above totals is the total emissions:
- 556,000 kg CO₂-e kg CO2-e + 837,000 kg CO₂-e kg CO2-e = 1,390,000 kg CO₂-e kg CO2-e
Note: Numbers may not add due to rounding.
11.3.1.2 Emission factor derivation methodology
New Zealand’s Greenhouse Gas Inventory 1990–2023 publishes total emissions for enteric fermentation per livestock type, along with population numbers. The Ministry for Primary Industries (MPI) publishes total emissions for enteric fermentation per livestock type, along with population numbers. MPI supplied these same data for the creation of implied emission factors. We used this information to calculate the emission factors based on the following equation:
\[ \begin{aligned} \text{implied emission factor per animal} &= \frac{ \text{enteric fermentation} }{ \text{population} } \end{aligned} \]
Note that the emission factors are based on data supplied for New Zealand’s Greenhouse Gas Inventory 1990–2023.
To ensure consistency, entities should report their population of livestock as at 30 June, regardless of the measurement period.
MPI defines non-dairy cattle as beef breeds of cattle, including dairy-beef, as well as any beef breeding stock.
| Animal | 2023 Population | Total Emissions (kt CH4) |
|---|---|---|
| Dairy cattle | 5,884,628 | 556.799673 |
| Non-dairy cattle | 3,654,032 | 254.495078 |
| Sheep | 24,359,267 | 303.347711 |
| Deer | 741,599 | 14.50563 |
| Swine | 249,796 | 0.228278 |
| Goats | 78,055 | 0.699619 |
| Horses | 31,184 | 0.561312 |
| Alpaca and llama | 15,443 | 0.123546 |
| Mules and asses | 1,500 | 0.015 |
| Note: kt = kilotonne. Source: Based on figures from the Agricultural Inventory Model used in New Zealand’s Greenhouse Gas Inventory 1990–2023. |
||
Note: NE = Not Estimated
Alternative methods and tools
There are alternative calculating tools, such as AgMatters, OverseerFM, or the B+LNZ GHG calculator. The implied emission factors in this guide may differ from other tools because of the different in-built assumptions and limitations. It is up to the user to assess the appropriateness of alternative tools.
11.3.1.3 Assumptions, limitations and uncertainties
New Zealand’s Greenhouse Gas Inventory 1990–2023 details the uncertainties associated with the activity data used to calculate the emission factors.
The level of uncertainty with enteric fermentation emissions is ±15.5 per cent.
11.3.2 Manure management emission factors
Manure management refers to the process of managing the excretion of livestock, particularly when they are not on paddocks, but also covers losses from manure that is deposited by livestock directly onto pasture, and it is distinct from losses from agricultural soils. The storage and treatment of manure produces GHG emissions. We provide the manure management emission factors in Table 11.6
| Emissions Source | Unit | kg CO₂–e/unit | CO₂/unit (kg CO₂–e) | CH₄/unit (kg CO₂–e) | N₂O/unit (kg CO₂–e) | Uncertainties |
|---|---|---|---|---|---|---|
| Manure management | ||||||
| Alpaca and llama | per head | 2.768109758 | 0 | 2.768109758 | 0 | CH4 20% |
| Dairy cattle | per head | 270.5410534 | 0 | 258.1241169 | 12.41693647 | CH4 20% / N2O 100% |
| Deer | per head | 7.350482966 | 0 | 7.350482966 | 0 | CH4 20% |
| Goats | per head | 5.6 | 0 | 5.6 | 0 | CH4 20% |
| Horses | per head | 65.52 | 0 | 65.52 | 0 | CH4 20% |
| Mules and asses | per head | 30.8 | 0 | 30.8 | 0 | CH4 20% |
| Non–dairy cattle | per head | 26.77655214 | 0 | 26.77655214 | 0 | CH4 20% |
| Poultry | per head | 1.379144023 | 0 | 0.8043110825 | 0.5748329402 | CH4 20% / N2O 100% |
| Sheep | per head | 3.773736061 | 0 | 3.773736061 | 0 | CH4 20% |
| Swine | per head | 186.8957777 | 0 | 165.4103901 | 21.48538759 | CH4 20% / N2O 100% |
11.3.2.1 GHG inventory development
Entities should collect data on the number and type of livestock as at 30 June during the measurement period (regardless of whether the period is a calendar or financial year) to calculate emissions from manure management.
Applying the equation E = Q x F, this means:
- E = emissions from the emissions source in kg CO2-e per year
- Q = number of animals (per head per livestock type)
- F = appropriate emission factors from Table 11.6.
MANURE MANAGEMENT: EXAMPLE CALCULATION
An entity owns 2,400 sheep and 210 dairy cows on 30 June during the reporting period. They graze on land owned by the entity.
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 210 x 258.1241169 kg CO₂-e per per head | 54,200 kg CO₂-e |
| CO₂ emissions | 210 x 0 kg CO₂-e per per head | 0 kg CO₂-e |
| N₂O emissions | 210 x 12.41693647 kg CO₂-e per per head | 2,610 kg CO₂-e |
| Total CO₂-e emissions | 210 x 270.5410534 kg CO₂-e per per head | 56,800 kg CO₂-e |
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 2,400 x 3.773736061 kg CO₂-e per per head | 9,060 kg CO₂-e |
| CO₂ emissions | 2,400 x 0 kg CO₂-e per per head | 0 kg CO₂-e |
| N₂O emissions | 2,400 x 0 kg CO₂-e per per head | 0 kg CO₂-e |
| Total CO₂-e emissions | 2,400 x 3.773736061 kg CO₂-e per per head | 9,060 kg CO₂-e |
The sum of the above totals is the total emissions:
CH4 emissions: 54,200 kg CO₂-e + 9,060 kg CO₂-e = 63,300 kg CO₂-e
N2O emissions: 2,610 kg CO₂-e + 0 kg CO₂-e = 2,610 kg CO₂-e
Total kg CO2-e = 65,900 kg CO₂-e
Note: Numbers may not add due to rounding.
11.3.2.2 Emission factor derivation methodology
We calculated the implied emission factors from figures in the Agricultural Inventory Model, used in New Zealandʼs Greenhouse Gas Inventory 1990-2023. MPI provided the data in Table 11.7.
| Animal | 2023 Population | Methane from manure management (kt CH4) | Nitrous oxide from manure management (kt N2O) |
|---|---|---|---|
| Dairy cattle | 5,884,628 | 54.248729 | 0.275732 |
| Non-dairy cattle | 3,654,032 | 3.494371 | 0 |
| Sheep | 24,359,267 | 3.283052 | 0 |
| Deer | 741,599 | 0.194683 | 0 |
| Swine | 249,796 | 1.475673 | 0.020253 |
| Goats | 78,055 | 0.015611 | 0 |
| Horses | 31,184 | 0.072971 | 0 |
| Alpaca and llama | 15,443 | 0.001527 | 0 |
| Mules and asses | 1,500 | 0.00165 | 0 |
| Poultry | 18,100,783 | 0.519952 | 0.039264 |
Note: kt = kilotonne. Source: The Agricultural Inventory Model used in New Zealand’s Greenhouse Gas Inventory 1990-2023.
| Animal | 2023 Population | Methane from manure management (kg CH4) | Nitrous oxide from manure management (kg N2O) |
|---|---|---|---|
| Dairy cattle | 5,884,628 | 54,248,728.78 | 275,732.272 |
MANURE MANAGEMENT: EMISSION FACTORS CALCULATIONS FOR LIVESTOCK TYPE
We calculated the manure management emission factors for each type of livestock as follows:
- Convert the units to kg of GHG.
- Divide by population to generate kg of GHG per head (ie, per animal).
- Calculate kg CO2-e/animal by multiplying each GHG by the IPCC AR5 100-year GWP.
Emission factors for dairy cattle (Table 11.8) were calculated as follows
- Methane emissions = 54,248,728.78 ÷ 5,884,628 = 9.22 kg CH4 per head
- Nitrous oxide emissions = 275,732.27 ÷ 5,884,628 = 0.0469 kg N2O per head
- Total kg CO2 equivalent = (9.2187 x 28) + (0.0469 x 265) = 271 kg CO₂-e per head
Note: The final emission factor derived in this example calculation is marginally different to the emission factor in Table 11.6 due to rounding.
11.3.2.3 Assumptions, limitations and uncertainties
New Zealand’s Greenhouse Gas Inventory 1990–2023 states that the major sources of uncertainty in emissions from manure management are the accuracy of emission factors for manure management system distribution, the activity data on the livestock population and the use of the various manure management systems. Based on the IPCC methodologies5, the uncertainty factor for methane emissions is ±20 per cent and for nitrous oxide emissions ±100 per cent, although different uncertainty values are reported in the New Zealand Inventory. New Zealand’s Greenhouse Gas Inventory 1990–2023 details the assumptions and limitations of these data.
11.3.2.4 Alternative methods of calculation
11.3.3 Agricultural soils
Agricultural soils emit nitrous oxide due to the addition of nitrogen to soils through manure, dung and urine. The guide provides implied emission factors for the impact of common agricultural livestock categories on soil in Table 11.9.
| Emissions Source | Unit | kg CO₂–e/unit | CO₂/unit (kg CO₂–e) | CH₄/unit (kg CO₂–e) | N₂O/unit (kg CO₂–e) | Uncertainties |
|---|---|---|---|---|---|---|
| Agricultural soils (live stock) | ||||||
| Alpaca and llama | per head | 61.49372337 | 0 | 0 | 61.49372337 | 54.1% |
| Dairy cattle | per head | 413.1963493 | 0 | 0 | 413.1963493 | 54.1% |
| Deer | per head | 63.36053096 | 0 | 0 | 63.36053096 | 54.1% |
| Goats | per head | 61.5008015 | 0 | 0 | 61.5008015 | 54.1% |
| Horses | per head | 290.9211643 | 0 | 0 | 290.9211643 | 54.1% |
| Mules and asses | per head | 129.592155 | 0 | 0 | 129.592155 | 54.1% |
| Non–dairy cattle | per head | 260.4338891 | 0 | 0 | 260.4338891 | 54.1% |
| Poultry | per head | 1.525834657 | 0 | 0 | 1.525834657 | 54.1% |
| Sheep | per head | 29.00377682 | 0 | 0 | 29.00377682 | 54.1% |
| Swine | per head | 26.93509614 | 0 | 0 | 26.93509614 | 54.1% |
11.3.3.1 GHG inventory development
Entities should collect data on the number and type of livestock they had as at 30 June during the measurement period.
Applying the equation E = Q x F, this means:
- E = emissions from the emissions source in kg CO2-e per year
- Q = number of animals (per head per type)
- F = appropriate emission factors from Table 11.9.
AGRICULTURAL SOILS: EXAMPLE CALCULATION
An entity owns 2,400 sheep and 210 dairy cows on 30 June during the reporting period. They graze on land owned by the entity.
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 210 x 0 kg CO₂-e per per head | 0 kg CO₂-e |
| CO₂ emissions | 210 x 0 kg CO₂-e per per head | 0 kg CO₂-e |
| N₂O emissions | 210 x 413.1963493 kg CO₂-e per per head | 86,800 kg CO₂-e |
| Total CO₂-e emissions | 210 x 413.1963493 kg CO₂-e per per head | 86,800 kg CO₂-e |
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 2,400 x 0 kg CO₂-e per per head | 0 kg CO₂-e |
| CO₂ emissions | 2,400 x 0 kg CO₂-e per per head | 0 kg CO₂-e |
| N₂O emissions | 2,400 x 29.00377682 kg CO₂-e per per head | 69,600 kg CO₂-e |
| Total CO₂-e emissions | 2,400 x 29.00377682 kg CO₂-e per per head | 69,600 kg CO₂-e |
The sum of the above totals is the total emissions:
- 86,800 kg CO₂-e + 69,600 kg CO₂-e = 156,000 kg CO₂-e
Note: Numbers may not add due to rounding.
11.3.3.2 Emission factor derivation methodology
We calculated the emission factors from the Agricultural Inventory Model, used in New Zealand’s Greenhouse Gas Inventory 1990–2023. These data are in Table 11.10.
| Animal | 2023 Population | Agricultural soils emissions (kg N2O) |
|---|---|---|
| Dairy cattle | 5,884,628 | 9,175,497.382855 |
| Non-dairy cattle | 3,654,032 | 3,591,070.809994 |
| Sheep | 24,359,267 | 2,666,078.27735 |
| Deer | 741,599 | 177,313.609052 |
| Swine | 249,796 | 25,389.733111 |
| Goats | 78,055 | 18,114.887024 |
| Horses | 31,184 | 34,234.285234 |
| Alpaca and llama | 15,443 | 3,583.63164 |
| Mules and asses | 1,500 | 733.5405 |
| Poultry | 18,100,783 | 104,221.894431 |
11.3.3.3 Assumptions, limitations and uncertainties
New Zealand’s Greenhouse Gas Inventory 1990–2023 details the uncertainties associated with the activity data used to calculate the implied emission factors.
11.3.4 Fertiliser use
The use of fertiliser produces GHG emissions. Nitrogen fertiliser breaks down to produce nitrous oxide and carbon dioxide (urea). Limestone and dolomite fertilisers break down to produce carbon dioxide. New Zealand’s Greenhouse Gas Inventory 1990–2023 reports the total emissions from fertiliser using New Zealand-specific emission factors. We used emission factors supplied by MPI to develop emission factors for:
- the nitrogen content of non-urea nitrogen fertiliser
- the nitrogen content of urea nitrogen fertiliser not coated with urease inhibitor
- the nitrogen content of urea nitrogen fertiliser coated with urease inhibitor
- limestone
- dolomite.
In line with the reporting requirements of ISO 14064-1:2018 and the GHG Protocol, we provide implied emission factors to allow separate calculation of carbon dioxide, methane and nitrous oxide. Table 11.11 lists the nitrogen fertiliser, limestone and dolomite emission factors. Note for nitrogen fertilisers, the input amounts are expressed in terms of the nitrogen component of fertiliser only. Table 11.12 lists example products for the different fertiliser types.
| Emissions Source | Unit | kg CO₂–e/unit | CO₂/unit (kg CO₂–e) | CH₄/unit (kg CO₂–e) | N₂O/unit (kg CO₂–e) | Uncertainties |
|---|---|---|---|---|---|---|
| Fertiliser use | ||||||
| Dolomite | kg | 0.4766666667 | 0.4766666667 | 0 | 0 | CO2 –50% to 0% |
| Limestone | kg | 0.3608 | 0.3608 | 0 | 0 | CO2 –50% to 0% |
| Non–urea nitrogen fertiliser | kg N | 4.836817857 | 0 | 0 | 4.836817857 | 54% |
| Urea nitrogen fertiliser coated with urease inhibitor | kg N | 4.536270756 | 1.594202898 | 0 | 2.942067857 | CO2 –50% to 0% / N2O 54% |
| Urea nitrogen fertiliser not coated with urease inhibitor | kg N | 4.723663613 | 1.594202898 | 0 | 3.129460714 | CO2 –50% to 0% / N2O 54% |
Note: The emission factors for nitrogen fertilisers are expressed in terms of the nitrogen component of fertiliser only. For example, if an entity applies 100 kg of urea fertiliser, which contains 46 per cent nitrogen, the input amount for the calculation would be 46 kg of nitrogen.
| Fertiliser type | Example product |
|---|---|
| Non-urea nitrogen | Diammonium phosphate |
| Urea nitrogen not coated with urease inhibitor | Nrich urea |
| Urea nitrogen coated with urease inhibitor | Agrotain, SustaiN, N-Protect |
11.3.4.1 GHG inventory development - nitrogen
Entities should collect data on quantity of nitrogen (in kg) of fertiliser used in the reporting period by type. Applying the equation E = Q x F, this means:
- E = emissions from the emissions source in kg CO2-e per year
- Q = type of fertiliser used (in kg)
- F = appropriate emission factors from Table 11.11.
FERTILISER USE: EXAMPLE CALCULATION
An entity uses 80 kg of dolomite and 50 kg of nitrogen from non-urea nitrogen fertiliser in the reporting year.
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 80 x 0 kg CO₂-e per kg | 0 kg CO₂-e |
| CO₂ emissions | 80 x 0.4766666667 kg CO₂-e per kg | 38.1 kg CO₂-e |
| N₂O emissions | 80 x 0 kg CO₂-e per kg | 0 kg CO₂-e |
| Total CO₂-e emissions | 80 x 0.4766666667 kg CO₂-e per kg | 38.1 kg CO₂-e |
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 50 x 0 kg CO₂-e per kg N | 0 kg CO₂-e |
| CO₂ emissions | 50 x 0 kg CO₂-e per kg N | 0 kg CO₂-e |
| N₂O emissions | 50 x 4.836817857 kg CO₂-e per kg N | 242 kg CO₂-e |
| Total CO₂-e emissions | 50 x 4.836817857 kg CO₂-e per kg N | 242 kg CO₂-e |
The sum of the above totals is the total emissions:
- 38.1 kg CO₂-e + 242 kg CO₂-e = 280 kg CO₂-e
Note: Numbers may not add due to rounding.
LIME USE: EXAMPLE CALCULATION
An entity uses 1,600 kg of lime fertiliser in the reporting year.
| Gas | Calculation | Emissions (kg CO₂-e) |
|---|---|---|
| CH₄ emissions | 1,600 x 0 kg CO₂-e per kg | 0 kg CO₂-e |
| CO₂ emissions | 1,600 x 0.3608 kg CO₂-e per kg | 577 kg CO₂-e |
| N₂O emissions | 1,600 x 0 kg CO₂-e per kg | 0 kg CO₂-e |
| Total CO₂-e emissions | 1,600 x 0.3608 kg CO₂-e per kg | 577 kg CO₂-e |
Note: Numbers may not add due to rounding.
11.3.4.2 Emission factor derivation methodology
MPI provided data on the quantified direct and indirect GHG emissions produced per tonne of nitrogen in fertiliser in Table 11.13. The final emission factor is the sum of adding the three N2O columns and multiplying this by the global warming potential of N2O, which is 265. This sum is then added to the value in the CO2 column on the far right, to produce the final emission factors seen in Table 11.11.
| Fertiliser type | Direct emissions of N2O (kg N2O/kg of N in fertiliser) | Indirect emissions volatilisation (kg N2O/kg of N in fertiliser) | Indirect emissions– leaching (kg N2O/kg of N in fertiliser) | CO2 emissions from urea (kg CO2/kg of N in fertiliser) |
|---|---|---|---|---|
| Non-urea nitrogen | 0.015714 | 0.001571 | 0.000966 | |
| Urea nitrogen not coated with urease inhibitor | 0.009271 | 0.001571 | 0.000966 | 1.594203 |
| Urea nitrogen coated with urease inhibitor | 0.009271 | 0.000864 | 0.000966 | 1.594203 |
The input parameters used to calculate the limestone and dolomite emission factors are in Table 11.14, where the final emission factor is the product of multiplying these three inputs.
| Fertiliser type | Concentration factor | Emission factor | Molecular conversion CO2 |
|---|---|---|---|
| Limestone | 0.82 | 0.12 | 3.666667 |
| Dolomite | 1 | 0.13 | 3.666667 |
It is assumed that the lime applied to soils is 100 per cent pure calcium carbonate. The correction factor in the Table 11.14 accounts for the impurities of the lime, as well as its moisture content. No correction factor is required for dolomite.
Table 11.15 provides the full list of parameters used to calculate the emission factors for nitrogen fertiliser, lime and dolomite.
| Description | Value | Source | Reference |
|---|---|---|---|
| Current processor level emissions factor | 5.72 | Climate Change (Agriculture Sector) Regulations 2010 | |
| Direct emissions factor non-urea-N | 0.01 | Based on Kelliher and de Klein, 2006 | Landcare Research and AgResearch. Unpublished. 2006. Report prepared for the Ministry for the Environment. Review of New Zealand’s Fertiliser Nitrous Oxide Emission Factor (EF1) Data. |
| Direct emissions urea-N | 0.0059 | Based on van der Weerden et al 2016 (new in 2017 NIR) | van der Weerden T, Cox N, Luo J, Di HJ, Podolyan A, Phillips RL, Saggar S, de Klein CAM, Ettema P, Rys G. 2016. Refining the New Zealand nitrous oxide emission factor for urea fertiliser and farm dairy effluent. Agriculture Ecosystems & Environment 222: 133–137. |
| FracGASnfert (UI) | 0.055 | Saggar (2013) | Saggar S, Singh J, Giltrap DL, Zaman M, Luo J, Rollo M, Kim D-G, Rys G, van der Weerden TJ. 2013. Quantification of reductions in ammonia emissions from fertiliser urea and animal urine in grazed pastures with urease inhibitors for agriculture inventory: New Zealand as a case study. Science of the Total Environment 465: 136–146. |
| FracGASnfert (non-UI) | 0.1 | Sherlock et al (2008) | Sherlock RR, Jewell P, Clough T. 2008. Review of New Zealand Specific FracGASM and FracGASF Emissions Factors. Report prepared for the Ministry of Agriculture and Forestry by Landcare Research and AgResearch. Wellington: Ministry of Agriculture and Forestry. |
| Volatilsation emission factor (EF4) | 0.01 | 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, table 11.3 | IPCC. 2006c. Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K (eds). 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Volume 4. Agriculture, Forestry and Other Land Use. IPCC National Greenhouse Gas Inventories Programme. Japan: Institute for Global Environmental Strategies for IPCC. |
| FracLeach - Cropland | 0.1 | Welten et al. (2021) | |
| FracLeach - Grassland* | 0.08 | Welten et al. (2021) | Welten B, Mercer G, Smith C, Sprosen M, Ledgard S. 2021. Refining estimates of nitrogen leaching for the New Zealand agricultural greenhouse gas inventory. Report prepared for the Ministry for Primary Industries. |
| Leaching emission factor (EF5) | 0.0075 | 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, table 11.3 | |
| Urea emissions factor (CO2 component) | 0.2 | 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, section 11.4.2 | |
| Emissions factor for limestone | 0.12 | 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, section 11.3.2 | |
| Emissions factor for dolomite | 0.13 | 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, section 11.3.2 | |
| Lime purity (national default) | 0.82 | Thomson et al (2021) | Thomson BC, Ward KR, Muir PD. 2021. Purity of agricultural lime and dolomite used in New Zealand. Final report prepared for the Ministry for Primary Industries. Wellington: Ministry for Primary Industries. |
| Dolmite purity (national default) | 1 | 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, chapter 11 | |
| Correction factor for impurities | 0.82 | Thomson et al (2021) | |
| N content of urea | 0.46 | Agriculture inventory model | |
| Molecular conversion CO2 | 3.666667 | ||
| Molecular conversion N2O | 1.571429 | ||
| GWP100 N2O | 265 | IPCC (AR5) |
11.3.4.3 Assumptions, limitations and uncertainties
New Zealand’s Greenhouse Gas Inventory 1990–2023 uses the IPCC (2006) Tier 1 methodology when default emission factors are used, which assume conservatively that all carbon in the fertilisers is emitted as carbon dioxide into the atmosphere.
There is no country-specific methodology on carbon dioxide emissions from urea application for New Zealand. Emissions associated with the application of urea are estimated using a Tier 1 methodology (equation 11.13; IPCC, 2006) using the default emission factor for carbon conversion of 0.2.
Age is defined as the number of years since afforestation.↩︎
Wakelin SJ, Paul THS, West T, Dowling, LJ. Unpublished. Reporting New Zealand’s Nationally Determined Contribution under the Paris Agreement using Averaging Accounting for Post-1989 forests. Contract report prepared for the Ministry for the Environment by New Zealand Forest Research Institute Ltd (trading as Scion) in 2021.↩︎
See volume 4, chapter 10 of 2006 IPCC Guidelines for National Greenhouse Gas Inventories.↩︎