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Inventories in practice: An example from New Zealand

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Presentation by Hazelle Tomlin, GRA, at the CLIFF-GRADS workshop on 6-7 October 2019 in Bali.

The two-day workshop was organized by the CCAFS Low Emissions Development Flagship and the Global Research Alliance on Agricultural Greenhouse Gases (GRA). Read more: https://ccafs.cgiar.org/cliff-grads-workshop

Published in: Environment
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Inventories in practice: An example from New Zealand

  1. 1. Inventories in Practice: An Example from New Zealand Hazelle Tomlin Reporting and Evidence Team
  2. 2. Agriculture and Energy are the largest contributors to New Zealand’s gross emissions, at 48.1 per cent and 40.7 per cent respectively NZ Emissions Profile
  3. 3. Institutional Arrangements • NZ Ministry for the Environment (MfE) is the centralized agency that compiles the national inventory submission (NIS) and submit to the UNFCCC • MPI compiles the agriculture sector inventory, chapter 5 of the NIS • Country specific (CS) emission factors (EF’s) are necessary for NZ because IPCC defaults do not accommodate NZ’s agricultural circumstances
  4. 4. 30,000 32,000 34,000 36,000 38,000 40,000 42,000 1990 1995 2000 2005 2010 2015 2017 Kilotonnesofcarbon-dioxideequivalent(KtCO2e) NZ Agriculture Emission Trends 1990-2017 13.5% increase since 1990 Since 2005, 2.5% decrease 0.1% decrease 2016-2017
  5. 5. • Livestock: • Major - Dairy cattle, Beef cattle, Sheep, Deer • Minor– Pigs, goats, horses, Alpaca and Llama, Mules and Asses, Poultry • Crops: • Barley, wheat, oats, potatoes, maize seed, other seed crops, onions, squash, and sweetcorn. • N-fixing – peas, lentils, forage legume seed, grass/clover pasture, lucerne. • Fertilisers: • N containing synthetic fertilisers, dolomite and lime • Mitigation practices: • Nitrification and Urease inhibitors NZ Agriculture Inventory - Source categories
  6. 6. 2017 Agricultural Emissions Profile by Livestock Industry • In 2017, agriculture emissions were 38.9 Mt CO2-e.
  7. 7. Contributors to the change in agricultural emissions between 1990 and 2017 Categories: • Dairy • Beef • Sheep • Other NB Emissions expressed in kilotonnes of carbon dioxide equivalent (kt CO2-e)
  8. 8. • Energy requirements model estimates feed intake and emissions for dairy cattle, sheep and deer • Production data and physiological characteristics used to estimate metabolisable energy (ME) requirements • This is combined with pasture quality data to estimate intake (DM) per animal • There is a linear relationship between intake and emissions NZ Ag Inventory - Livestock Model
  9. 9. • The APS is the most important data source for the inventory • Smaller data sets are sourced from other organisations NZ Ag Inventory - Data sources
  10. 10. • 92% of NZ’s agricultural emissions are calculated using a ‘tier 2’ method • Dairy and beef cattle, sheep and deer • Cropping emissions • The remaining proportion are calculated using tier 1 methods, but still use country-specific emission factors where available NZ’s Ag Inventory Methodology Tiers
  11. 11. Tier 1 Alpaca (D) Goats (CS) Horses (D) Mules and asses (D) Swine (CS, D) Poultry (CS, D) Direct N2O* (CS,D) Indirect N2O* (CS,D) Tier Increase % Change in Estimated Emissions Tier 2 / 3 (CS) Dairy cattle Beef cattle Sheep Deer Crops Where CS = Country Specific and D = Default Examples of country specific values
  12. 12. Impact of country specific values on N2O inventory
  13. 13. NZ Agriculture Inventory Mitigation Option Estimates
  14. 14. • Continual improvement of inventory estimates is required to account for new farming techniques and mitigation technologies • Comprehensive process for incorporating new science and technology into the inventory methodology and emission estimates • Any significant inclusion requires peer- reviewed published research and data Improving the agriculture inventory
  15. 15. • Gaps in our inventory data; some years of missing data (extrapolate and uncertainty). Other AD gaps limit tier 2. • Data sharing issues; cross agency, data privacy regulations • MfE as centralised inventory compiler: subject to their deadlines despite ag. complexity • Agriculture Inventory Model (AIM) Reprogram • Providing information at the right level of complexity to inform policy is also important, i.e. not too detailed or too aggregate. MRV Challenges faced in New Zealand’s Agricuture Inventory
  16. 16. Thank You! Questions?

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