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Annex 3: Detailed methodological information for other sectors

A3.1 Agriculture

A3.1.1 Uncertainty of animal population data

Details of the surveys and census are included to provide an understanding of the livestock statistics process and uncertainty values. The information documented is from Statistics New Zealand. Full details of the surveys are available from Statistics New Zealand’s website. For information about surveys and census see http://search.stats.govt.nz/nav/ct2/industrysectors_agriculture/ct1/indu....

Agricultural production surveys

The target population for the 2008 Agricultural Production Survey were all units that were engaged in agricultural production activity (including livestock, cropping, horticulture and forestry) or that owned land that was intended for agricultural activity during the year ended 30 June 2008. The response rate was 84 per cent. These businesses represent 85 per cent of the total estimated value of agricultural output. Statistics New Zealand imputes using a random ‘hot deck’ procedure for values for farmers and growers who did not return a completed questionnaire. The imputation levels for the 2008 Agricultural Production Survey are provided in Table A3.1.1.

The 2008 Agricultural Production Survey is subject to sampling error as it is a survey. Sampling error arises from selecting a sample of businesses and weighting the results, rather than taking a complete enumeration, and is not applicable when there is a census. Non-sampling error arises from biases in the patterns of response and non-response, inaccuracies in reporting by respondents, and errors in the recording and classification of data. Statistics New Zealand adopts procedures to detect and minimise these types of errors, but they may still occur and are not easy to quantify.

Table A3.1.1 Imputation levels and sample error for New Zealand’s 2008 Agricultural Production Survey
Statistic Proportion of total estimate imputed (%) Sample error (%)
Ewe hoggets put to ram 24 7
Breeding ewes, 2 tooth and over 18 2
Total number of sheep 19 2
Lamb born to ewe hoggets 18 6
Lambs born to ewes 18 2
Beef cows and heifers (in calf) 2 years and over 18 3
Beef cows and heifers (in calf) 1–2 years 20 5
Total number of beef cattle 19 2
Calves born alive to beef heifers/cows 18 2
Dairy cows and heifers, in milk or calf 23 3
Total number of dairy cattle 23 2
Calves born alive to dairy heifers/cows 24 3
Female deer mated 15 5
Total number of deer 16 4
Fawns born on farm and alive at 4 months 16 4
Area of wheat harvested 25 11
Area of barley harvested 21 8

A3.1.2 Key parameters and emission factors used in the agricultural sector

Table A3.1.2.1 Parameter values for New Zealand’s agriculture N2O emissions
Parameter (fraction) Fraction of the parameter Source Parameter value
FracBURN
(kg N/kg crop-N)
Crop residue burned in fields Ministry of Agriculture and Forestry (expert opinion) 0.3
FracBURNL
(kg N/kg legume-N)
Legume crop residue burned in fields Ministry of Agriculture and Forestry (expert opinion) 0
FracFUEL
(N/kg N excreted)
Livestock nitrogen excretion in excrements burned for fuel Practice does not occur in New Zealand 0
FracGASF
(kg NH3-N + NOx-N/kg of synthetic fertiliser N applied)
Total synthetic fertiliser emitted as NOx or NH3 Sherlock et al (2009) 0.1
FracGASM
(kg NH3-N + NOx-N/kg of N excreted by livestock)
Total nitrogen emitted as NOx or NH3 Sherlock et al (2009) 0.1
FracGRAZ
(kg N/kg N excreted)
Livestock nitrogen excreted and deposited onto soil during grazing See Table 6.3.1 Livestock specific
FracLEACH
(kg N/kg fertiliser or manure N)
Nitrogen input to soils that is lost through leaching and run-off Thomas et al (2005) 0.07
FracNCRBF
(kg N/kg of dry biomass)
Nitrogen in N-fixing crops IPCC (1996) Reference Manual Table 4.19 0.03
FracNCR0
(kg N/kg of dry biomass)
Nitrogen in non-N-fixing crops IPCC (1996) Reference Manual Table 4.19 0.015
FracR
(kg N/kg crop-N)
Crop residue removed from the field as crop IPCC (1996) Reference Manual Table 4.19 0.45
Table A3.1.2.2 Emission factors for New Zealand’s agriculture emissions N2O emissions
Emission factor Emissions Source Parameter value
EF1
(kg N2O-N/kg N)
Direct emissions from nitrogen input to soil Kelliher and de Klein (2006) 0.01
EF2
(kg N2O-N/ha-yr)
Direct emissions from organic soil mineralisation due to cultivation IPCC (2000) Table 4.17 8
EF3AL
(kg N2O-N/kg N excreted)
Direct emissions from waste in the anaerobic lagoons AWMS IPCC (2000) Table 4.12 0.001
EF3SSD
(kg N2O-N/kg N excreted)
Direct emissions from waste in the solid waste and drylot AWMS IPCC (2000) Table 4.12 0.02
EF3PRP
(kg N2O-N/kg N excreted)
Direct emissions from waste in the pasture range and paddock AWMS Carran et al (1995); Muller et al (1995); de Klein et al (2003) 0.01
EF3OTHER
(kg N2O-N/kg N excreted)
Direct emissions from waste in other AWMSs IPCC (2000) Table 4.13 0.005
EF4
(kg N2O-N/kg NHx-N)
Indirect emissions from volatising nitrogen IPCC (2000) Table 4.18 0.01
EF5
(kg N2O-N/kg N leached & runoff)
Indirect emissions from leaching nitrogen IPCC (2000) Table 4.18 0.025
Table A3.1.2.3 Emission factor for Tier 1 enteric fermentation livestock and manure management
Emission factor Emissions Source Parameter value (kg/head/yr)
EFGOATS Enteric fermentation – goats New Zealand-specific 9
EFHORSES Enteric fermentation – horses IPCC (1996) Table 4.3 18
EFSWINE Enteric fermentation – swine IPCC (1996) Table 4.3 1.5
EFALPACA Enteric fermentation – alpaca IPCC (2006) Table 10.10 8
MMGOATS Manure management – goats IPCC (1996) Table 4.5 0.18
MMHORSES Manure management – horses IPCC (1996) Table 4.5 2.1
MMSWINE Manure management – swine IPCC (1996) Table 4.6 20
MMPOULTRY Manure management – poultry IPCC (1996) Table 4.5 0.117
MMALPACA Manure management – alpaca New Zealand 1990 sheep value 0.091

A3.2 Supplementary information for the LULUCF sector: the Land Use and Carbon Analysis System (LUCAS)

Systems

The data collected as part of LUCAS is stored and manipulated within three systems: the Geospatial System, the Gateway and the Calculation and Reporting Application (CRA).

The key objectives of these systems are to:

  • provide a transparent system for data storage and carbon calculations
  • provide a repository for the versioning and validation of plot measurements and land-use data
  • calculate carbon stocks, emissions and removals per hectare for land uses and carbon pools based on the plot and spatial data collected
  • calculate biomass burning and liming emissions by land use based on spatial and emission factors stored in the Gateway
  • produce the outputs required for the LULUCF sector reporting under the Climate Change Convention and the Kyoto Protocol.
The Geospatial System

The Geospatial System consists of hardware and specific applications designed to meet LULUCF reporting requirements. The hardware largely comprises servers for spatial database storage, management, versioning and running web mapping applications. The core components of the Geospatial System are outlined below.

Figure A3.2.2.1 New Zealand’s Geospatial System Components

Figure A3.2.2.1 New Zealand’s Geospatial System Components

Figure A3.2.2.1 illustrates the components of New Zealand’s Geospatial System, as described by section A3.2. of the Inventory Submission. These components consist of:

  • External images, feeding into an image server
  • A land-use map (LUM) data supplier
  • A LUM Import/Export Application – Windows form and ARC object
  • A LUM Database (Arc SDE) and associated web-based QA/QC application
  • A LUM Attribute Tool Application
  • A Spatial Gateway Database (Arc SDE) (Staging)
  • Versioning and validation
  • A Core Geospatial Database, used to produce summary land-use tables, for use in the Calculations and Reporting Application (CRA)

These components can be accessed through a standard ArcGIS desktop.

The land-use mapping (LUM) functionality of the Geospatial System largely involves the editing and maintenance of time-stamped land-use mapping data. There are three components within the LUM functionality, as described below.

  • LUM Import/Export Application – provides functionality for managing the importing and exporting of land-use mapping information into and out of the database.
  • LUM Attribute Tool Application – an extension to the standard ArcGIS Desktop software that facilitates maintenance and updates to the land-use mapping data by external contractors.
  • LUM Database – a non-versioned GIS database for interim land-use mapping data and related quality assurance and control observation data.

Land-use mapping functionality

The Gateway

A key component of the LUCAS programme is the Gateway database. The Gateway enables the storage of field collected, land-use area, biomass burning, liming and other data, such as IPCC defaults, needed by the CRA.

The LUCAS Gateway provides a viewing, querying and editing interface to the source (plot, land-use area, carbon and non-carbon) data. The Gateway also stores any published or saved results from running the CRA.

All survey data is stored within the Gateway database and is broken down into layers (Figure A3.2.2.2).

  • A data layer contains all survey data (natural, planted forest, soils, default carbon, non-carbon, land-use areas, land-use change and reference tables). The user has the ability to create a ‘snapshot’ in time (a dataset archiving system) of the data held in the Gateway. This enables users of the CRA to select from a range of data snapshots and also ensures that past results can be replicated over time.
  • A secondary validation layer allows users to judge the suitability of data for use in the CRA calculations, subsequent to passing primary validation. Where records are deemed not acceptable for use within published reports they are tagged as ‘invalid’ in the LUCAS Gateway database.
  • An audit trail provides a history of any changes to the database tables within the Gateway.
  • Versioning at a number of levels ensures any changes to data, schema or the database itself are logged and versioned, while providing the user with the ability to track what changes have been applied, and roll back to a previous version if required. The results of saved or published reports within the CRA are also stored within the Gateway for repeatability and reference.
  • Primary data validation, both during data capture and during import of the data into the Gateway, ensures that only data that has passed acceptability criteria are available for a publishable CRA run.
  • Hosting and application support provides hosting services, system security, backup and restore, daily maintenance and monitoring for the Gateway and CRA.

Figure A3.2.2.2 The layers of New Zealand’s LUCAS Gateway database

Figure A3.2.2.2 The layers of New Zealand’s LUCAS Gateway database

Figure A3.2.2.2 illustrates the layers in which the data in New Zealand’s LUCAS Gateway database is stored. These layers, depicted in concentric rings and listed from the outside in, are:

  • hosting and application support
  • a data layer, containing all survey data
  • a secondary validation layer
  • an audit trail layer
  • versioning
  • primary data validation.
Calculation and Reporting Application

The Calculation and Reporting Application (CRA) enables users to import carbon and non-carbon data from the Gateway and, by running the various modules, determines emissions and removals by New Zealand’s forests, cropland, grassland and other land-use types. This information, combined with land-area data, enables New Zealand to meet its reporting requirements under the Climate Change Convention and Kyoto Protocol.

The CRA is built to have enough flexibility to allow for the inclusion of other datasets, models and calculations without the complete redesign of the applications. All models, data and results are versioned, and the CRA allows the user to alter specific key values within a model or calculation (parameters) without the intervention of a programmer or technical support officer. The CRA application is deployed as a client-based application that sources the required data from the Gateway.

Figure A3.2.2.3 Interaction between New Zealand’s Gateway and CRA

Figure A3.2.2.3 Interaction between New Zealand’s Gateway and CRA

Figure A3.2.2.3 illustrates the interaction between New Zealand’s LUCAS Gateway Database and the Calculation and Reporting Application (CRA). The Gateway Database is depicted as comprising data, land-use area and carbon look-up tables, and published results. The inputs to the Gateway comprise the soils, natural forest, planted forest (pre-1990 planted and post-1989) and non-carbon datasets, as well as IPCC default emission factors, which must all pass data acceptance rules before they enter the Gateway. The Gateway outputs snapshots of data and look-up tables, which provide the inputs for the CRA. The CRA is depicted as containing regression models, default parameters and outputs against each of the datasets, which in combination feed into the ‘joint calculations’ of final emission factors and land-use areas (tonnes C/ha multiplied by areas). The outputs of the CRA are the inputs used to populate the Common Reporting Format tables, which are required to meet UNFCCC LULUCF and Kyoto Protocol reporting obligations.

Note: Soils, NF, PF and NC refer to the soils, natural forest, planted forest (pre-1990 planted and post-1989) and non-carbon datasets. The IPCC default emission factors are also an input.

There are five modules that comprise the CRA: natural forest, planted forest, soils, non-carbon and joint calculations. Any of these modules can be run independently or as a group. The results are provided as ‘views’ to the user at the completion of the run.

To activate the module, the user selects the module to run within the CRA, the version of the dataset to be used, the model version and other calculation parameters. The natural forest and soil carbon modules use R statistical language as the base programme language, while the non-carbon module and joint calculations module are developed in C Sharp programming language (C#).

Within the joint calculations module, the user has the option of using the carbon results from running the modules, or using default carbon estimates (based on published reports) stored within the Gateway. The joint calculations module combines the carbon estimates with the land-use area to calculate carbon stock and change. The results represent carbon stock and change for every ‘from’ and ‘to’ land-use combination outlined by the IPCC since 1990.

On completion of running a module, the results can be saved or published back to the Gateway. This provides a versioned and auditable record of the results used for reporting. If the results are saved or published, other information such as the time created, the user’s identification and the module-particular parameters that were used are also saved for tracking and audit control.

Figure A3.2.2.4 How New Zealand used the CRA for entry into the common reporting format database

Figure A3.2.2.4 How New Zealand used the CRA for entry into the common reporting format database

Figure A3.2.2.4 illustrates the steps by New Zealand to use the LUCAS Calculations and Reporting Application (CRA) to produce the data for entry into the UNFCCC Common Reporting Format (CRF) database. These steps are:

  1. Create a new CRA run
  2. Select runtime parameters
  3. Run module
  4. View results
  5. Publish results to gateway
  6. Export results
  7. Enter into CRF

The CRA application is maintained and supported by Interpine Forestry Limited, a New Zealand-based company that specialises in forestry inventories and related IT development. Interpine is contracted to provide hosting of the Gateway and CRA application in a secure environment. Interpine also provides general support services such as back ups and system security (firewalls and virus control), day-to-day issue resolution and enhancement projects to the Gateway or the CRA as required.

Any changes to the data or table structure within the Gateway, or to people accessing the Gateway or CRA, are tracked via audit logs. For any changes to the data within the Gateway the person making the change, the date, reason for change and the version are logged and reports are made available to the users for review.