m. morán, j.a. gonzález, m. diosharmo.isac.cnr.it/.../ppt/h16-053-moran-pr.pdf · ghgs emissions...
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1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
M. Morán, J.A. González, M. Dios
Department of Chemical Engineering University of Santiago de Compostela (Spain)
Overview
• Methodology and EFs estimation
• GHGs emissions estimation CH4 emission from enteric fermentation
CH4 emission from manure management
N2O emission from manure management
• Ammonia and NMVOC emissions
• Geographical distribution
• Comparison to standard emissions inventories
• Concluding remarks
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Introduction
In Spain, livestock contributes over 35% of CH4 emissions, of which 60% are from cattle
Cattle sector
Greenhouse Gases
(GHGs)
Contribution
of Livestock
Carbon Dioxide (CO2) 9%
Methane (CH4) 35 - 40%
Nitrous oxide (N2O) 65%
Ammonia (NH3) 64%
Emissions of pollutants in the cattle sector
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Overview Animal husbandry and manure management Description of sources
Livestock Feeding
Livestock Housing and Holding areas
Manure Storage
Field Applied Manure
Excreta deposited while grazing
PM
PM NMVOC NH3
NO
NMVOC
NH3
NO
NMVOC
NH3
NO
NMVOC
NH3
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Atlantic coastal region in the NW of Iberian Peninsula:
Half of Spanish cattle are located in Galicia
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100.000
200.000
300.000
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Nu
mb
er o
f a
nim
al
per
fa
rm
Nu
mb
er o
f a
nim
al
Number of animal and number of animal per farm in Galicia (Spain)
Number of
animal
Animal per
farm
Study region - Galicia
Methodology and EFs estimation
EMEP inventory and E-PRTR
Specific information to each activity,
calculation models and emission factors
Activity definition
Review: Emissions inventories and methodologies
Simplified methodology (Tier1)
EMISSIONS COMPUTATION EMISSIONS
Detailed methodology (Tier 2) information: EMEP
Methodology, IPCC Methodology and data collection for Galicia
Comparison comparison
Dataset compilation: Regional data, EMEP, IPCC
GHGs emissions estimation
GHGs emissions (IPCC, 2006) are calculated by multiplying the number of animals (N) in each category (i) by an appropriate emission factor (EF).
Tier 1 EFs are based in constant values Tier 2 EFs depend on the different direct and indirect processes involved in a typical cattle farm, that is, enteric fermentation and manure management and other specific parameters are required: the animal type, the animal productivity, the quality of diet, and the management conditions; particularly, in order to support a more accurate food intake value applied to the estimation of methane production resulting from enteric fermentation.
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Universidade de Santiago de CompostelaUniversidade de Santiago de Compostela
Ammonia and NMVOC emissions estimation
NH3 and NMVOC emissions were calculated using the methodology and algorithm provided by the EMEP/CORINAIR Atmospheric Emission Inventory Guidebook Mass-flow approach was developed to quantify ammonia NMVOC emissions are calculated by using a single default EF value (Hobbs et al., 2004)
LEVEL 2
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Universidade de Santiago de CompostelaUniversidade de Santiago de Compostela
Results – GHGs (2009)
Tier 1 Tier 2
Livestock
category EF ef EF mm Emissions EF ef EF mm Emissions
kgCH4
hd-1yr-1
kgCH4
hd-1yr-1
Gg CH4
yr-1
kgCH4
hd-1yr-1
kgCH4
hd-1yr-1
Gg CH4
yr-1
Mature
Dairy Cow 109 27 50.69 82.65 45.59 47.80
Other
Mature
Cattle
57 8 22.28 65.18 28.99 32.29
Growing
Cattle 57 8 14.8 52.75 33.94 22.04
TOTAL 89.50 102.12
CH4 emissions
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Results – GHGs (2009)
N2O emissions Tier 1 Tier 2
Livestock category Nint(T) Nint (T)
kg N hd-1yr-1 kg N hd-1yr-1
Mature Dairy Cow 79.72 69.62
Other Mature Cattle 84.65 54.01
Growing Cattle 22.89 65.56
Tier 1 Tier 2
Livestock category Emissions EF mm Emissions EF mm
Gg N2O yr-1 kg N2O hd-1yr-1 Gg N2O yr-1 kg N2O hd-1yr-1
Mature Dairy Cow 8.25 22.13 0.969 2.6
Other Mature Cattle 33.56 97.90 17.22 50.2
Growing Cattle 6.73 26.47 15.50 61.0
TOTAL 48.54 44.82
Results – GHGs annual series
0
20000
40000
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2007 2008 2009 t
CH
4 h
ead
-1 y
ear
-1
Enteric Fermentation
Manure Manegement
CH4 emissions
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2007 2008 2009
t N
2O
he
ad-1
ye
ar-1
N2O D
N2O G N2O emissions
Tier
1 2
Tier
1 2
Tier
1 2
Tier
1 2
Tier
1 2
Tier
1 2
Universidade de Santiago de CompostelaUniversidade de Santiago de Compostela
Results – Tropospheric gases (2009)
NMVOC and NH3 emissions
NFR NFR Name
EF
(kg hd-1yr-1)
for
NMVOC
NMVOC
emissions
(Gg NMVOC
yr-1)
EF
(kg hd-1yr-1)
for NH3
NH3
emissions
(Gg NH3yr-1)
Tier 1
NH3
emissions
(Gg NH3 yr-1)
Tier 2
4.B.01.a Dairy cattle 13.6 5.07 39.3 14.6 13.0
4.B.01.d Non-dairy
cattle 7.4 4.42 13.4 8.0 6.47
TOTAL 9.50 22.65 19.50
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Results - Geographical distribution (2009)
Dairy cows
Beef cows
1 point = 100 head
Universidade de Santiago de CompostelaUniversidade de Santiago de Compostela
Comparison to standard inventories (2009)
EMEP emissions of NH3 and NMVOC in tons (t) in 2009 S10 – Agriculture sector (CEIP, 2012)
NH3 NMVOC
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Comparison of calculated and EMEP S10 sector NH3 emissions at Galicia region, considering both original and updated EMEP (June-2012) inventories.
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1998 2000 2002 2004 2006 2008 2010
Em
iss
ion
s (
t N
H3yr-
1)
Year
NH3 inventories comparison
EMEP original inventory
Calculated emissions
EMEP inventory 2012 update
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1998 2000 2002 2004 2006 2008 2010 Em
iss
ion
s (t
NM
VO
Cyr-
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Year
NMVOC Inventories comparison
Comparison to std. emissions inventories
Comparison to standard inventories (2009)
Comparison of E-PRTR emissions (Cathegory 7) with those calculated for cattle in Galicia for the year 2009
E-PRTR emissions Calculated emissions
(Tier 2)
(t·yr-1) (t·yr-1)
CH4 108 102120
NH3 2290.9 19500
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Universidade de Santiago de CompostelaUniversidade de Santiago de Compostela
Conclusions
Cattle activities produce significant both GHGs and tropospheric pollutants
emissions
CH4 emission estimated using Tier 2 (IPCC, 2006) is higher than using Tier 1
(IPCC, 2006). Tier 2 results show that more CH4 livestock emissions come from
enteric fermentation than using Tier 1.
About N2O emissions, direct contribution (89%) is the largest component
Considering GHGs emissions, Global Warming Potential (GWP) from CH4 and
N2O cattle emissions represents 56% of the total GWP in this region
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Universidade de Santiago de CompostelaUniversidade de Santiago de Compostela
Conclusions
Compared to EMEP inventory, NH3 emissions value is twice the updated S10
EMEP sector emissions, even though S10 sector not only includes cattle
Differences are even higher when NMVOC emissions are considered, with
extremely low S10 EMEP values respect to the calculated NMVOC emissions
Cattle activities must be included in E-PRTR
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
Universidade de Santiago de CompostelaUniversidade de Santiago de Compostela
Future work
An extension of these results to Europe depends on the availability and accuracy of
data input, specially for Tier 2 method and NH3 emissions calculation
A sensitivity analysis of these emissions estimation methods to the different data
input should be useful to define the uncertainties associated to these emissions.
Also, in order to reduce the required data input
Currently, we are in collaboration with the GEMAC group, University of Aveiro, to
extend these cattle emissions calculations and, also, new S10 EMEP emissions
estimations, to Portugal and Galicia: In order to estimate the impact of those
emissions in the ozone episodes observed in rural areas
.
1616thth International Conference on International Conference on HarmonisationHarmonisation within Atmospheric Dispersion within Atmospheric Dispersion ModellingModelling for Regulatory Purposesfor Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
M. Morán J.A. González ja.souto@usc.es M. Dios
1616thth International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory PurposesInternational Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes 88--11 11 SeptemberSeptember 2014 Varna, Bulgaria 2014 Varna, Bulgaria
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