Biogeochemical Process-Based Modeling of Nutrients · PDF filePresented at the Dairy Emissions...

Presented at the Dairy Emissions Research Symposium, Davis, CA, Oct 11, 2006

Biogeochemical Process-Based Modeling of Nutrients and Greenhouse Gas Emissions from California Dairies(A on-going project supported by California Energy Commission PIER and USDA NRI programs)

William Salas*, Applied Geosolutions, LLC

Changsheng Li, University of New Hampshire, Durham

Frank Mitloehner, University of California, Davis

Charles Krauter, California State University, Fresno

John Pisano, University of California, Riverside

* [email protected], ph: 603-292-5747


California Dairy Industry

Source: CDFA 2004


1999 California CH4 Emissions31.65 MMTCO2eq

Energy13%

Waste47%

Agriculture40%

Manure Management41%

Enteric Fermentation

55%

Rice Paddies4% Burning Ag.

Residues0%~

Source: CEC 2002 GHG Inventory


Agricultural Soils62%

Manure Management

5%

Manure appliedsoils32%

Burning Ag. Residues

1%

1999 California N2O Emissions 23.55 MMTCO2eq

Agriculture65%

Energy29%

Waste5%

Industrial Processes

1%

Source: CEC 2002 GHG Inventory


Modify an existing “process-based”biogeochemical model (DNDC) for estimating CH4, NH3, NO, N2O emissions from dairy systems in California.Collect field data to calibrate and validate this modelBuild GIS databases on soils, climate, dairy locations, and manure management.Apply the model to estimate emissions across California. Note: model is designed for both regional and single farm simulations.

Project Goals


What are Process-based Models?

Process-based modeling refers to biochemical and geochemical reactions or processes

Process modeling, in this case, does not refer to AFO practices or components (e.g. dairy drylots or manure lagoons) per se, but

Biogeochemical processes… like decomposition, hydrolysis, nitrification, denitrification, etc…True process-based models do not rely on constant emission factors. They simulate and track the impact on emissions of varying conditions within components of the dairies (e.g., climate, flush lanes, storage facility, soils).


Role of Process-based ModelsAccurate assessment of air emissions from dairies with emission factors is difficult due to:

1. high variability in the quality and quantity of animal waste, and2. numerous factors affecting the biogeochemical transformations

of manure during collection, storage and field application. Measurement programs are essential but expensive and thus not feasible for monitoring, emission inventories, mitigation analyses and “what if” scenario analyses. Therefore, process-based models that incorporate mass balance constraints are needed to extrapolate air emissions in both space and time (NRC, 2003).


Nitrogen Biogeochemistry of Manure

Manure production Manure organic pools N tranformation in manure

Dung

Bedding

Urine

Very labile litter N

Labile litter N

Resistant litter N

Labile microbial N

Resistant microbial N

Labile humad N

Resistant humad N

Passive humus NNH4+

NO3-

NH3

Clay-NH4+

NO2-

NO

N2O

N2

Atmospheric N deposit or fertilization

NH3N2NO N2O

Nitrification

Denitrification

Assimilation

Decomposition

Chemical equilibrium

HydrolysisLitter fall

Atmospheric deposition and fertilization

Gas emission

Chemodenitrification

Leaching

Urea

Fresh manure


ecologicaldrivers

Climate Soil Vegetation Human activity

soil environmentalfactors

Temperature Moisture pH Substrates: NH4+, NO3

-, DOCEh

Denitrification:• NO3

- consumption• net NO, N2O production• N2 production

Nitrification:• NH4

+ consumption • NO3

- production• Net NO, N2O production

Fermentation:• CH4 production• CH4 consumption• CH4 transport• net CH4 flux

Decomposition:• SOM decay• N-mineralization• CO2 production• DOC production

Plant growth:• water use• C accumulation• C allocation• root respiration• litter production

Soil climate:• temperature profiles• water profiles• water drainage• redox potential profiles

ecologicaldrivers

Climate Soil Vegetation Human activity

soil environmentalfactors

Temperature Moisture pH Substrates: NH4+, NO3

-, DOCEh

Denitrification:• NO3

- consumption• net NO, N2O production• N2 production

Nitrification:• NH4

+ consumption • NO3

- production• Net NO, N2O production

Fermentation:• CH4 production• CH4 consumption• CH4 transport• net CH4 flux

Decomposition:• SOM decay• N-mineralization• CO2 production• DOC production

Plant growth:• water use• C accumulation• C allocation• root respiration• litter production

Soil climate:• temperature profiles• water profiles• water drainage• redox potential profiles

The DNDC Model


DOC

Electron acceptor

O2

NO3

H2

CO2 N2O CH4

Trace gas production is induced by microbial activity based on…

Gain energy

Release electrons

Eh-driven microbial activity:

- Decomposers

- Denitrifiers

- Methanogens


Soil Trace Gas Evolution Driven by Redox Potential (Eh)Soil CO2, N2O and CH4 production is driven by the microbes

demanding electron acceptors


Why DNDC Model?• Contains algorithms for both anaerobic and aerobic

soil environments• Simulates full range of biogeochemical processes:

decomposition, hydrolysis, nitrification, denitrification, ammonium adsorption, chemical equilibriums of ammonium/ammonia, fermentation, and gas diffusion

• Well validated across a wide range of agroecosystems and is currently being used for national GHG emission inventories and mitigation studies worldwide.


Observed and DNDC-Modeled N2O Fluxes from Agricultural Soils in the U.S., Canada, the U.K., Germany, New Zealand, China, Japan, and Costa Rica

0.1

1

10

100

1000

0.1 1 10 100 1000

Observed N2O flux, kg N/ha/year

Mod

eled

N2O

flux

, kg

N/h

a/ye

ar

0.4

0.

0. 0.4

0.032

0.37

0.

0.

0.033

0.05

0.037

0.340.41

0.43

0.032

0.032

0.032

0.035

0.015

0.0350.029

0.035

0.028

0.011

0.031

0.05

0.0290.029

0.006

0.01

0.0190.019

0.02 0.025 0.025

0.010.015

R2 = 0.84


Structure of Manure-DNDC

Milk or meat production

Intake of C, N and water

Quantity and quality of fresh manure: dung

and urine

Temperature, moisture, pH, bedding and ventilation

Decomposition, hydrolysis, nitrification,

denitrification, fermentation

Emissions of CO2, NH3, CH4,

N2O, NO

Quantity and quality of manure

Aerobic storage or compost,

lagoon, slurry tank, digester




N2O, NO

Quantity and quality of

residue manure

Climate, soil, farming

management




N2O, NO

Soil C and N storage

Manure production Housing Storage Field application


Model Status


Easy to Use Input Interface for Defining Climate, Housing, Storage, Processing, Soil, and Field Application Conditions


Manure-DNDC will be validated with datasets observed in housing, storage, treatment and

field application.

Sampling and measurement are conducted at feed-lot, housing, storage, lagoon and field in 3-5 dairy farms in CA in 2006-2007


GIS Soils: NRCS Soil Surveys• STATSGO (1:250K) and SSURGO (1:12k-1:63K)

Organic CarbonSoil pHSoil Texture, andBulk Density


Environmental Factors: Climate Data

• DAYMET: Gridded (1kmx1km) daily min/max T, precipitation, relative humidity, and solar radiation. Available from 1980.

• CIMIS (California Irrigation Management Information System): station data with hourly Temp, Precip, Radiation, Rel Hum, Wind Speed, …).

• Built automated routines for data mining, QA/QC and pre-processing into Manure-DNDC format.


GIS and Site Specificity:Dairy Locations: Aerial Photos

GIS Data on:

Dairy Locations

Soils (soil propertiespH, SOC, texture,Bulk density)

Climate (daily/hr T,Precip, rel humidty,Wind, solar radiation)Merced 429Stanislaus 409Tulare 338Kings 199San Joaquin 199


Manure Management Statistics• Objective: build spatially explicit database

on Type of dairy: flush, scrape, vacuum, etcType of housing: free stalls, open corals, etcManure handling: anaerobic lagoon, aerobic lagoon, anaerobic digester, composting, setting basin, land application, etc.Specifics on storage, treatment, and land application practices, etc.

Source: Permits and surveys


Expected Project Outcomes:

• Biogeochemical process modeling tool for estimating air emissions (CH4, NH3, N2O, NO) and N leaching from California dairies;

• GIS databases on dairies (location, types, herd sizes, manure management, local soils, climate, etc);

• Improved understanding of manure management practices impact on GHGs.

• Regional estimates of NH3 and GHG emissions from California dairies;

• Emission inventory tool for emission inventories ranging from project or facility level up to air-district and state level


AB 32• Establishes statewide greenhouse gas

emissions caps• Animal feeding operations are an important

source of non-CO2 greenhouse gases (CH4and N2O)

• Climate Action Team Report: changes in manure management may be an important GHG mitigation strategy - anaerobic digesters may be a viable reduction strategy…


Low decomposition

Low CO2, CH4, N2O

Low N leaching

High C sequestration

High decomposition

High CO2, CH4, N2O

High N leaching

Low C sequestration

Manure

Labile organic matter

Resistant organic matter

Digester

CH4 for energySoil

By tracking changes in quantity and quality of manure in its life cycle, process-based model can assess impacts of digester or other treatment on

environment in a comprehensive way

Emission Factors cannot capture this dynamic…need process models


Thank you!

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Biogeochemical Process-Based Modeling of Nutrients · PDF filePresented at the Dairy Emissions...

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