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Tools for quantifying GHG emissions from Agroecosystems E. Pattey, R.L. Desjardins and W. Smith Agriculture and Agri-Food Canada, Research Branch, Ottawa.

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Presentation on theme: "Tools for quantifying GHG emissions from Agroecosystems E. Pattey, R.L. Desjardins and W. Smith Agriculture and Agri-Food Canada, Research Branch, Ottawa."— Presentation transcript:

1 Tools for quantifying GHG emissions from Agroecosystems E. Pattey, R.L. Desjardins and W. Smith Agriculture and Agri-Food Canada, Research Branch, Ottawa CAgM Expert Team Meeting on the Contribution of Agriculture to the State of Climate Ottawa, Canada, September 2004

2 INTRODUCTION Goals: Develop a set of reliable Models for estimating net GHG emissions from agricultural sources/sinks and for deriving emissions factors relevant of a given country situation. Establish a series of databases of the various agricultural activities for integrating the GHG emissions over space and time domains (land use, mgt practices, animal production, climate…).

3 INTRODUCTION (Cont’d) A “reliable” Model is:  sensitive to input conditions such as management practices;  adapted to the geographical and climatic conditions under which it will be used;  based on sound scientific knowledge.  …Ideally it requires a set of input descriptors easily available. Framework: Any national GHG emission accounting system needs to be transparent (well-documented), verifiable (pilot test sites, scaling-up experiments etc.) and consistent with the Kyoto Protocol.

4 OUTLINE Speaker more familiar with Canadian situation Example of Canada… GHG emission estimates from agricultural sources in Canada, CO 2, CH 4, N 2 O Tools for developing models (chamber, tower) Tools for verifying temporal dynamic and top-down constraints (tower, aircraft) Results from tower- aircraft-based measuring systems Modeling results from Ecosys, DNDC and Daycent Summary

5 Greenhouse Gas Emissions from Canada’s Agroecosystems (100 Year Time Horizon - Tg of CO 2 equivalents) CO CH N2ON2O Total

6 GHG flux measuring techniques only cover a limited portion of the space and time domains Aircraft Atmospheric Inversion Tower Chamber Area m 2 Time h Soil Cores Mass Balance BLS & Tracer Regional and sub- continental estimates using tall towers and CBL budgets Satellite

7 Auditing/ Monitoring Long Term Experimental Sites: Flux, Meteorological and Ancillary Measurements F GHG Regional/ National Estimates Regional (Spatial) databases “Ecosystem Models” Benchmark Sites Inventory/ Monitoring Sites  C s Regional Flux and Surface Feature Measurements Process Studies climate soils topography land use land management Data collection Driving variables Verification Research Needs Model Refinement Scaling Up Verification Model Refinement Proposed Framework for a Accounting/Verification System

8 How do we improve and verify models? ModelingModeling Measuring chambers, towers Virtual Farm (with uncertainty estimates) Virtual Farm (with uncertainty estimates) timetime Verifying temporal dynamic Top-Down constraint Regional & Nat’l GHG budget (with uncertainty estimates) Regional & Nat’l GHG budget (with uncertainty estimates) Measuring towers, blimps aircraft Developing new knowledge on mgt practices

9 F g = dC V M w dt A M v Non-Flow Through, Non-Steady State Chamber Measurements Experimental design for comparing management practices and environmental conditions

10 Tower-based Measurements Closed-path Tunable Diode Laser Air Intakes Sonic anemometer

11 Setup for quantifying N 2 O fluxes for two management practices 1 TDL connected to 2 micromet. towers

12 ECOSYS Grant, R. and Pattey, E., Modelling variability in N 2 O emissions from fertilized agricultural fields. Soil Biology and Biochemistry:35(2): Urea applied at the following rates: Meas. model Non-linear increase of N 2 O emissions with fertilizer application rate

13 Flux Towers are the only suitable measuring approach … during Snow melt (Permanent Site, Ottawa)

14 Harvested corn field - Snow melt

15 global Fluxnet The global Fluxnet project features towers tracking the movement of carbon dioxide between various ecosystems and the air with emphasis on forest Ameriflux Euroflux Japanflux Establish a network of towers for measuring N 2 O fluxes to verify temporal dynamics of models and assist in scaling up from individual agricultural fields to region Biocap

16 Aircraft-Based Measurements

17 The REA sampling system and TDL Laser Aircraft REA system Laboratory TDL Laser

18 Canada Casselman Flight Track Morewood Flight Track km Tower Site AC/Tower Study Sites, Spring 2001, 2003 and 2004

19 Casselman Flight Track 12 km 13km Casselman Highway 417 N soy cereals pasture/grass alfalfa forest corn town LEGEND

20 Morewood Flight Track N

21 Mean Crop Cover in 2000 within Footprint of Aircraft Transects HayAlfalfaCornSoybeanForestPastureCereals Percentage (%) Casselman Morewood

22 Aircraft Results, 2001

23 Combining Tower and Aircraft N 2 O Fluxes FN 2 O by AC kg N 2 O-N ha day FN 2 O by Tower kg N 2 O-N ha day FN 2 O by AC (1130 to 1430) ng N 2 O-N m 2 s FN 2 O by Tower (1130 to 1430) ng N 2 O-N m 2 s = Unknown

24 Tower and Aircraft Results, 2004

25 Modeling and Aircraft Results, 2004

26 Ecological drivers ClimateSoilVegetation Anthropogenic activity Decomposition Crop Growth Soil Climate Soil environmental factors TemperatureMoisturepH Anaerobic balloon Substrates (NH4+, NO3- and DOC) DenitrificationNitrification N Gas Emissions Fluxes of NO, N 2 O, N 2 and NH 3 Exchange of NO and N 2 O Effect of temperature and moisture on decomposition Schematic of the major components of the DNDC model

27 Using models for obtaining regional and national estimates ModelingModeling timetime Regional & Nat’l GHG budget (with uncertainty estimates) Regional & Nat’l GHG budget (with uncertainty estimates) MeasuringMeasuring

28 Time (years) Cumulative C (T ha -1 ) Cumulative CO 2 -C from N fertilizer (50 kg N ha -1 ) Soil C gain Net gain Challenge: The net impact of management practices changes with timetime Cumulative net GHG emissions 0 Option A Option B Option C Option A

29 Year Gg N 2 O-N Estimated direct annual N 2 O-N emissions Estimated direct spring N 2 O-N emissions Estimated Direct N 2 O-N Emissions from Agriculture Soils in Canada Using DNDC ( )

30 “Model” province region SLC polygon “Situations” defined by: Soil Climate Land use Management National C and GHG Accounting and Verification System country SOC & GHG Emissions for each “situation”

31 Verification by direct measurement of national GHG estimates best done through holistic top-down national, continental, or global scale GHG budgets N 2 O emissions?

32 Scientific uncertainty CH 4 N2ON2O GHG emission (Mt CO 2 equiv. per year) CO 2 Relative uncertainty (estimated)

33 Scientific uncertainty Uncertainty Understanding 0

34 Tools to quantify uncertainties Sensitivity tests of models Monte-Carlo approach for evaluating uncertainty Sensitivity tests of models Monte-Carlo approach for evaluating uncertainty

35 Summary Tools for measuring GHG fluxes only cover a limited portion of the space and time domains The combination of tower and aircraft-based GHG flux measurements provide valuable information to estimate regional fluxes on a daily basis Models are essential for deriving national estimates of GHG emissions Models still require lots of verification and improvement to provide more accurate estimates Tools for measuring GHG fluxes only cover a limited portion of the space and time domains The combination of tower and aircraft-based GHG flux measurements provide valuable information to estimate regional fluxes on a daily basis Models are essential for deriving national estimates of GHG emissions Models still require lots of verification and improvement to provide more accurate estimates


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