Technology For Environmentally Friendly Livestock Production Thomas Bartzanas

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Smart Animal Production 1
Technology for
Environmentally
Friendly Livestock
Production
Thomas Bartzanas
Editor

Smart Animal Production
Volume 1
Series Editors
Daniel Berckmans, M3-BIORES Department of BioSystems, Katholieke
Universiteit Leuven, Leuven, Belgium
Tomas Nor ton,Research &Developm ent,Katholi ekeUniversiteit Leuven, Leuven,
Belgiu m

Thisnew book series wishes to contribute to the discussion by looking at various
aspects of modern livestock production. This includes the acceptability of how this is
done in relation to the ethics and animal welfare, the practicality of the role of
technology and the economics of animal-based food production.
The increasing demand for cheap animal products, for higher animal welfare and
healthier animals while heavily reducing environmental load and energy use with an
ever smaller suitable workforce is putting livestock farming world-wide under
pressure. Previous research has shown that modern technology has a high potential
to address these issues by using sensors and sensing systems to automatically capture
quantitative information directly from the animal; this is referred to as Precision
Livestock Farming (PLF).
However , ithasalsobeenshown thatimportant issuesremaintobesolved:
(i)lackofcoopera tionbetween animalscientists,veterinari ans,bio-andother
engine ersandeconom ists,(ii)lackofimplemen tablesystemswhichrelatesensor s,
image andsound analysis tokeyindicators onfarms, (iii)lackofunders tandinghow
PLFcreatesvalueforthedifferent stakeholder sand(iv)suitablebusiness models to
further adoption ofPLF.Furthermor e,thedivide between consumer understandi ng
andthereality ofmoder nlivestockproduct ioniswidenin gwiththeurbanisati onof
thepopula tionandtheincreased useofintensiv efarming systems.

Thomas Bartzanas
Editor
Technology
forEnvironmentally
FriendlyLivestock
Production

Editor
Thomas Bartzanas
Laboratory of Farm Structures
Department of Natural Resources
Development and Agricultural
Engineering, School of Environment
and Agricultural Engineering
Agricultural University of Athens
Athens, Greece
ISSN2731-7382 ISSN2731-7390 (electronic)
Smart Animal Production
ISBN 978-3-031-19729-1 ISBN 978-3-031-19730-7 (eBook)
https://doi.org/10.1007/978-3-031-19730-7
#Theditor(s)ifpplicable)ndheuthor(s)nderxclusiveicenseopringeraturewitzerlan
AG023
Thisorksubjectoopyright.llightsreolelyndxclusivelyicensedyheublisher,hether
theholerartfheaterialsoncerned,peci ﬁcallyheightsfranslation,eprinting,eusef
illustrations, recitation, broadcasting, reproduction onmicroﬁlmsorinanyotherphysical way,and
transmission orinformation storage andretrieval, electronic adaptation, computer software, orby
similar ordissimilar methodo logynowknown orhereafter developed .
Theuseofgeneral descriptive names, registered names, trademarks, service marks, etc.inthispublication
doesnotimply, evenintheabsence ofaspeciﬁcstatement, thatsuchnames areexempt fromtherelevant
protective lawsandregulations andtherefore freeforgeneral use.
Thepublishe r,theauthors, andtheeditors aresafetoassumethattheadvice andinformation inthis
bookarebelieved tobetrueandaccurate atthedateofpublication. Neither thepublisher northeauthors or
theeditors giveawarranty, expressed orimplied, withrespect tothematerial contained herein orforany
errors oromissions thatmayhavebeenmade. Thepublishe rremains neutral withregard tojurisdictiona l
claims inpublished mapsandinstitutional afﬁliations.
ThisSpringer imprint ispublished bytheregistered company Springer Nature Switzerlan dAG
Theregistered company address is:Gewerbestra sse11,6330Cham, Switzerlan d

Acknowledgment
This book is based upon work from COST Action LivAge (CA16106), supported by
COST (European Cooperation in Science and Technology).
COST (European Cooperation in Science and Technology) is a funding agency
for research and innovation networks. Our actions help connect research initiatives
across Europe and enable scientists to grow their ideas by sharing them with their
peers. This boosts their research, career, and innovation.
www.

v

7
Contents
1Technology for Environmentally Friendly Livestock Production...1
Thomas Bartzanas, Salva Calvet, and Guoqiang Zhang
2A Simple Model as Design Tool for Low-Ammonia Emission
Pig Housing........................................... 11
André J. A. Aarnink, P. Demeyer, and L. Rong
3Measuring Techniques for Ammonia and Greenhouse Gas
Emissions from Naturally Ventilated Housings................ 23
M. Hassouna, T. Amon, C. Arcidiacono, M. Bühler, S. Calvet,
P. Demeyer, P. R. D’Urso, F. Estellés, C. Häni, S. Hempel, D. Janke,
M. Kjosevski, T. Kupper, J. Mohn, J. Mosquera, T. Norton,
C. Scheutz, N. Thygesen Vechi, P. Van Overbeke, and S. Schrade
4Nutritional Approaches to Reduce Enteric Methane Emission
from Ruminants....................................... 65
Vibeke Lind, Angela Schwarm, Marcello Mele, Alice Cappucci,
Giulia Foggi, Özge Sizmaz, Eleni Tsiplakou, Alberto Stanislao Atzori,
Joni Van Mullem, and Nico Peiren
5The Implications of Animal Manure Management
on Ammonia and Greenhouse Gas Emissions................. 99
David Fangueiro, Pilar Merino, Athanasios Pantelopoulos,
José L. S. Pereira, Barbara Amon, and David R. Chadwick
6Modelling Methane Emission from Manure.................. 137
Salva Calvet, Fernando Estellés, Agustín del Prado,
and Karin Groenestein
7Available Technical Options for Manure Management in
Environmentally Friendly and Circular Livestock Production.... 14
C. Marques-dos-Santos, J. Serra, G. Attard, U. Marchaim, S. Calvet,
and B. Amon
viivii

viii Contents
8Legal Requirements on Ammonia Emissions from Animal
Production Buildings in European Countries and in Countries
at the Eastern Mediterranean............................. 177
Bjarne Bjerg, Peter Demeyer, Julien Hoyaux, Mislav Didara,
Juha Grönroos, Mélynda Hassouna, Barbara Amon,
Thomas Bartzanas, Renáta Sándor, Micheal Fogarty, Sivan Klas,
Stefano Schiavon, Violeta Juskiene, Miroslav Kjosevski,
George Attard, André Aarnink, Vibeke Lind, Tadeusz Kuczyński,
David Fangueiro, Monica Paula Marin, Stefan Mihina, Jože Verbič,
Salvador Calvet, Knut-Håkan Jeppsson, Harald Menzi, Ozge Sizmaz,
Tomas Norton, Biljana Rogic, Stepan Nosek, Olga Frolova,
Günther Schauberger, and Nigel Penlington
9The Use of Renewable Energy Sources as a Driver to Reduce
the Carbon Footprint of the Livestock Sector.................217
Andrea Costantino, Salvador Calvet, and Enrico Fabrizio
10Sensors and Instrumentation in Management
and Online Control..................................... 251
Sang-Yeon Lee, In-Bok Lee, and Jun-gyu Kim
11E
mental Impact Assessment of Emission Reduction
Technologies.......................................... 279
Vasileios Anesti s,AnnaVatsanidou ,andThomas Bartzanas

Technology for Environmentally Friendly
Livestock Production
1
Thomas Bartzanas, Salva Calvet, and Guoqiang Zhang
Abstract
The global livestock sector is growing faster than any other agricultural subsector.
It provides livelihoods to about 1.3 billion people and contributes about 40% to
global agricultural output. While livestock production forms one of the pillars of
the EU food industry, it faces many societal challenges, not least from the rising
demand for meat protein, increasingly stringent environmental regulations, cou-
pled with the falling numbers of young farmers entering the industry. Modern
farm animal production is increasingly regarded as a source of solid, liquid and
gaseous and dusts emissions which can be both a nuisance and environmentally
harmful. The global livestock sector, particularly ruminants, contributes approxi-
mately 18% of total anthropogenic GHG emissions. In the EU, the livestock
sector accounts for about 13% of total GHG emissions. As regulations and social
pressure harden, there is a growing interest in scientiﬁc research in air pollution
and emissions from livestock operations in Europe (Heidecke et al., International
conference on agricultural GHG emissions and food security–connecting
research to policy and practice–10–13 September 2018. Berlin. Volume of
abstracts, Thünen working paper, no. 103. Johann Heinrich von Thünen-Institut,
Braunschweig.https://doi.org/10.3220/WP1535709029000, 2018).
T. Bartzanas (✉)
Laboratory of Farm Structures, Department of Natural Resources Development and Agricultural
Engineering, School of Environment and Agricultural Engineering, Agricultural University of
Athens, Athens, Greece
e-mail:[email protected]
S. Calvet
Institute of Animal Science and Technology, Universitat Politècnica de València, València, Spain
G. Zhang
Department of Civil and Architectural Engineering–Design and Construction, Aarhus University,
Aarhus, Denmark
#The
Author(s), underexclusive license to Springer Nature Switzerland AG 2023
T. Bartzanas (ed.),Technology for Environmentally Friendly Livestock Production,
Smart Animal Production 1,https://doi.org/10.1007/978-3-031-19730-7_1
1

2 T. Bartzanas et al.
1.1 Rational of the Book
Along with an increasing population, the world faces climate change, rising fossil
fuel prices, ecosystem degradation and water and land scarcity, all of which are
making today’s food production methods increasingly unsustainable. The EU energy
strategy (EU,2013) calls for a 40% cut in greenhouse gas (GHG) emissions
compared to 1990 levels and at least a 27% share of renewable sources in total
energy consumption (EU (COM15),2014). The EU directive 406/2009/EC for GHG
emissions forces for at least 50% reduction below 1990 levels by 2050 (EU,2019a).
The approaches of the past simply cannot meet the challenges ahead. Building on
already successful techniques, there is a need to boost production in a more environ-
mental and sustainable way with the least use of natural resources.
The Food Agriculture Organisation (FAO) estimates that there are currently
12 million EU farms with in the livestock sector, accounting for nearly half of EU
agricultural activity and production value (FAO,2017).
The livestock sector contributes up to 50% of the global agricultural gross
domestic product (Herrero et al.,2016) and supports the livelihoods and food
security of almost 1.3 billion people in developing countries. FAO projected a
need for 60–70% increase in agricultural production by 2050 compared to 2007.
This means 1.1% annual average increase, against past 2,2% per year during
1961–2007, while 80% of that increase must come from the intensiﬁcation of
agricultural production (EU,2012). The global livestock sector is growing faster
than any other agricultural subsector. Livestock production has been called the next
food revolution, addressing the massive increase in world demand for food of animal
origin. Although this increase is seen especially in developing countries, it also has a
major inﬂuence in the industrialized world through the global economy (Wright
et al.,2012).
The EU is currently the world’s leading milk producer, accounting for one third
of the world cheese and whole milk powder markets each, and the second largest
beef producer in the world. The EU is also the second largest pork producer in the
world after China. The value of livestock production in the EU is almost 125 billion
Euro per annum, and the contribution of animal production to the gross indigenous
production is at least twice as high if the whole agribusiness sector is considered.
Global meat production is projected to become more than double (from 229 million
tonnes in 1999/2001 to 465 million tonnes in 2050), while milk output is set to climb
from 580 to 1043 million tonnes (Steinfeld et al.,2006).
The r
ncrease in livestock production gives prominence to potential and
growing negative impact this can have on the global ecosystem. Intensive animal
agricultural methods are the norm in Europe and North America and are increasingly
common in Asia and Latin America. Therefore, the extensive knowledge on the
optimisation of these systems with minimal environmental impacts must be lever-
aged for increasing production levels while preserving resources and decreasing
emissions (Animal Task Force,2016)

TheEuropean deman dforanimalproduct smight decrease slightlyinthecoming
decades ,buttheworldwide deman dforanimal product sispredicted todouble till

2050 due to population growth and increasing prosperity (Alexandratos &
Bruinsma,2012). This creates a huge responsibility for global livestock sector and
food chainsin
terms of export opportunities of (i) animal products for a growing
middle class in areas/countries with high population growth (Africa) that often are
not able to produce the necessary livestock products and (ii) scientiﬁc knowledge
and know-how enabling these countries to increase their local production capacities.
European standards are extremely high compared to those from otherparts of the
world interms
of animal welfare, safety, healthiness, environment, etc. The livestock
sector is contributing substantially to the European economy in terms of national
income, employment and contribution to the trade balance.
1 Technology for Environmentally Friendly Livestock Production 3
Nevertheless, the past has also highlighted the drawbacks of continuous growth
of the animal sector despite huge efforts and progresses have been achieved by
farmers to tackle these drawbacks. These include challenges to the environment
(gaseous emissions, water and soil pollution and ecosystem damage), animal and
human health (zoonotic diseases and inappropriate use of antimicrobials and
anthelmintics). Therefore, while livestock production forms one of the pillars of
the worldwide food industry, it faces societal challenges, such as increasingly
stringent environmental regulations, coupled with the falling numbers of young
farmers entering the industry. Environmental degradation because of the releases
of livestock waste and emissions can ultimately lead to regional tensions and
violence, affecting economic policies and farmers’income.
Enhancing the resilience to climate change and food security requires investment
in a low-carbon economy that promotes energy efﬁciency and the update of green
products (EU,2013). This is one of the key objectives of the European Economic
Recovery Plan, which outlines the EU’s response to the economic crisis, leading us
to a creative, knowledge-based economy. The agricultural sector is core contributor
to this vision. In fact, the recent proliferation of technical innovations in agriculture
and emergence of the Agri-Tech Industry (JRC,2014) demonstrates how socioeco-
nomic beneﬁts to EU citizens can be derived from tackling food production
problems linked with GHG emissions, over consumption of energy and water.European Gre enDealsetsouthowtomake Europetheﬁrstclimate -neutral
continentby2050(European Comm ission, 2019b ).Itmapsanew,sustainabl eand
inclusiv egrowth strategy toboosttheeconomy,improvepeople ’shealth andquality
oflife,carefornature andleave noonebehind .TheClimateLawsetsoutthe
objectiveforaclimate neutral Union in2050.TheCommission cameforward on
Septem ber2020witha2030climatetargetplan,toincreasetheGHG emission
reductiontargettowards55%compa redto1990levels.TheFarm-to-For kStrat-
egy(EU,2020b )laysdownanewapproac htoensurethatagriculture, ﬁsheries and
aquacul tureandthefoodvaluechaincontribut eappropr iatelytothisproces s.More
recently,theCOVID-19 pandem ichasunderl inedtheimportanceofarobust and
resilien tfoodsystem thatfunctions inallcircumstances andiscapableofensuring
access toasufﬁcientsupply ofaffordable foodforcitizens. Ithasalsomade us
acutely aware oftheinterrel ations betweenourhealth, ecosys tems,supply chains,
consum ptionpatterns andplanetary boundar ies.Itisclearthatweneedtodomuch
moretokeepourselvesandtheplanet healthy.Thecurren tpandemic isjustone

example. The increasing recurrence of droughts,ﬂoods, forestﬁres and new pests are
a constant reminder that our food system is under threat and must become more
sustainable and resilient.
4 T. Bartzanas et al.
The agricultural sector is responsible for 24% of the emissions of atmospheric
pollutants. According to recent EU report (EEA Report No 5/2020), 94% of ammo-
nia emissions into the environment originate from agriculture, while its contribution
to the primary PM
2.5
and PM
10
emissions is estimated to be over 5% and 25%,
respectively. Moreover, as the effects of climate change intensify, biodiversity is
becoming more endangered. Ammonia from livestock production contributes con-
siderably to the formation of secondaryﬁne dust, as well. The livestock sector
contributes to 14.5% of total GHG emissions (EEA Report No 5/2020).Τhisﬁgure
is in line with FAO’s assessment (Livestock’s Long Shadow), published in 2006,
although it is based on a much more detailed analysis and improved data sets. Cattle
(raised for both beef and milk, as well as for inedible outputs like manure and draft
power) are the animal species responsible for the most emissions, representing about
65% of the livestock sector’s emissions. In terms of activities, feed production and
processing (this includes land use change) and enteric fermentation from ruminants
are the two main sources of emissions, representing 45% and 39% of total emissions,
respectively. Manure storage and processing represent 10%. The remainder is
attributable to the processing and transportation of animal products. Fossil fuel
consumption along the supply chain accounts for about 20% of the livestock sector’s
GHG emissions. On commodity basis, beef and cattle milk are responsible for the
most emissions, respectively, contributing 41% and 20% of the sector’s overall
GHG outputs (FAOSTAT,2016).
Emissions intensities currently vary widely within and across geographic regions
and production systems, by a factor of two to more than four, especially for products
from ruminant animals (meat and milk) but also for pork and poultry. Intensive
animal production systems tend to have higher overall GHG emissions, but their
emissions intensity is lower than in low-yield extensive systems. The gap between
high and low emissions intensity producers itself signals signiﬁcant mitigation
opportunities.
Over r
ecades, efforts have been made to reduce emissions from livestock.
As a result, combined with reductions in livestock numbers, GHG emissions were
reduced by 23% from 1990 to 2014 (EEA Report No 5/2020) and ammonia
emissions by 27% from 1990 to 2013 (EEA Report No 5/2020). But more needs
to be done to further improve air quality and combat global warming. Politically, the
EU states have been committed to reduce both GHG and ammonia emissions further
that requires efforts by all sectors–including agriculture.
Reducing emi ssionintensity on-farm willnotnecessarily translat eintolower
absoluteemissi ons,asthesedepend ontotalproduction andrespon sesoffarmers to
wider market andpolicy signals.Nonethel ess,sinceoverallfooddeman dislargely
outofthecontrolofindividual farmers andevenmajor individual businesses,afocus
onemissi onsintensityon-farmpresen tsarealisticapproac htoreduce supply -side
emissi onswithoutprecluding otheractions tomanagethedeman dforlivestock
product s.Foralllivestock product ionsystems,opport unities existandarebeing

developed to decrease GHG emissions per unit of animal product further. Some of
these options require novel technological interventions; others are‘simple’
principles that can be applied already in most production systems.
1 Technology for Environmentally Friendly Livestock Production 5
Mitigation options can be targeted towards the supply of livestock products.
These include technical and management interventions and practices for increasing
crop and livestock productivity. Another group of options could target reductions in
the consumption of livestock products. Mitigation options can be found in the
production of feed, enteric methane production, manure production, energy con-
sumption and carbon sequestration in soils. In addition, shortcomings in the man-
agement of animal productions lead to other harmful emissions and losses in the
nutrient cycle (carbon, nitrates, phosphorus–C, N, P) with negative impacts on soil,
water and air quality. Apart from GHG, air pollutants include ammonia and other
nitrogen compounds (NO
X), dust particles, sediments and odours. Water pollutants
include nitrates, P and pesticides. Soil pollutants include trace elements, pesticides
and antibiotics residues. Improvements in managing environmental impacts will
beneﬁt animal health (dysbiosis), farmers (mainly economically), the society and
the environment. Research is needed to reduce GHG emission without negative
effect on other emissions (risk of pollution swapping) and on livestock productivity.
A w
ange of measures can be applied at livestock farms to reduce emissions.
There are also major challenges in implementing these measures. The challenge of
reducing emissions from livestock can be solved at different stages in the production
chain and with tools of varying complexity. The success and fail factors for
implementing these tools are therefore also diverse. One parameter, which was
repeatedly mentioned as a major challenge for increased implementation of emission
reducing measures, is the difﬁculty of showing the bene ﬁts to farmers (Bartzanas
et al.,2017). Emissions are invisible, and many of the environmental effects are only
visible over long time spans and take place a long way from the source of the
emissions. The emission reduction itself is therefore not a good incentive for the
farmer. In theory, several of the measures have beneﬁts such as increased production
efﬁciency which could be an incentive for the farmers (e.g. improved health and
husbandry). This must however be shown clearly during demonstration projects if
the measures are to spread by themselves. Another problem is that production
efﬁciency is not valued in environmental policies. On a national scale, reduction
targets are absolute; little emphasis is put on how reductions are achieved. This
leaves a gap between overall targets and the measures which can be used to achieve
them. It also means that one of the few clear economic incentives for emission
reductions–production efﬁciency–is not valued and accounted for by the social,
economic and political systems.
Thepost-2 013Comm onAgricul turePolicy(CAP)reformshaverecognised such
challen gesbyfocusing attentiononthetranslat ionofscience andtechno logical
develo pments intoeveryda yfarmpractice, sothatEUfarms canimprovetheir
product ionefﬁciency while maintai ningahighecological status.RecentRIS3
strategi esdevelo pedinregional andnational levelshighlight alsothisapproac h.
Resource manag ement andfoodsecurity inachangingenvironmen tduetoclimate
change isthereforeanissuethatagriculture musttakeveryseriously.Livestock

production in the EU can only remain competitive by ensuring the highest standard
of both product quality and safety, and by efﬁcient production methods that are both
animal and environmentally friendly. Although there are a lot of existing techniques
and technologies that can be used for a more sustainable and environmentally
friendly livestock production, there is a severe gap between the development of
new and innovative technologies/solutions and the proper implementation of these
solutionsin
the production chain. A real innovation aspect in sustainable livestock
production will be the proper and wide implementation of innovative technologies
by the farmers. There needs to be a focus on practice innovation, supported by
knowledge transfer,ﬁnancial incentives, regulations and awareness rising. Particu-
larly important, better policies are needed to facilitate the transfer and use of efﬁcient
practices and technologies already adopted by a minority of producers and to
encouragethe
development of new solutions. Using a‘life cycle’approach can
help policymakers target emission hot spots along the livestock sectors supply
chains, identifying clear opportunities for cuts and facilitating situation-tailored
actions.
6 T. Bartzanas et al.
Transfer of knowledge is an important action and a clear challenge for European
agriculture, including the livestock sector. Networking and cooperation between
research and extension services on the one hand and farmers groups and other actors
in the livestock sector on the other are crucial for maintaining competitiveness,
innovation and sustainability. This collaboration must be supported, and, in order to
do this, exchange and uptake of knowledge is a key requirement that has to be
promoted. The EU is an SME-based economy in which the agricultural sector plays a
vital role in maintaining sustainable economic growth. However, agricultural actors
face severe common problems and challenges across the EU livestock sector in
maintaining their competitiveness and sustainability.
In t
espect, there is a growing interest in scientiﬁ c research in air pollution and
emissions from livestock operations in Europe. This area is inherently multidisci-
plinary. Several research groups in Europe are engaged in the areas related to the
proposed action, but the information and knowledge obtained is dispersed. A
considerable part of the work is hidden in‘grey’literature. Furthermore, there is
currently no reliable and standard methodology for emission measurements, espe-
cially from naturally ventilated buildings. Moreover, considerable work was carried
out in other countries outside Europe which faced similar or even more extended
problems probably long time ago before the problems became evident in Europe.
However, more needs to be done to further improve air quality and combat global
warming. Even if EU policy framework has been committed to reduce both GHG
and ammonia emissions further, this target requires combined efforts by all sectors,
with livestock being in the core.
Thepresent booktriedtoﬁllthisgapandcombin estheoutcomes andactivities of
a4yearnetworkactionfunded under theCOST initiativeentitled:‘Greenhouse
gasesandammonia emissions fromlivestockbuildings’.Themainobjective ofthe
action wastoenhance international discipli necoopera tionforexchangi ngideasand
knowledge, sharing good practices;toassesstechno logies thatcould resultin
reducingtheemissions ofGHGsandammonia fromlivestockbuildingsandthus

to lead to a more environmental friendly and sustainable livestock production. Focus
was given on methodology improvement and harmonization of measurements and
modelling aspects. An effort has been made that the project results will be made
readily available to signiﬁcantly enhance awareness in the livestock sector of the
current hazard level and the perspectives related to the future. Some secondary
objectives include the estimation of emission factors, the impact of the applied
diets,prevai
ling microclimate and ventilation schemes on emissions and the assess-
ment of mitigation techniques and the environmental analysis of the proposed
techniques and solution.
1 Technology for Environmentally Friendly Livestock Production 7
The participant teams and research groups tried to promote (experimentally and
numerically) the development of low-emission building design and environmental
friendly technologies to reduce livestock framing impacts on the environment.
Developments of innovative measurement methodology and protocols was aiming
at accurate measurements and documentation of gaseous emissions from livestock
farming operation. This will included innovation and identiﬁcation of most reliable
sensors and instrumentations for gaseous monitoring, establishing validated mea-
surement protocols for emission evaluation at varied farm levels, regions and for
different animal species. Combining process level ammonia release models with
CFD methods provided obvious potential for modelling spatially distributed aerial
conditions above the release surface. Integration of process level models in CFD
simulations made it feasible to model how gaseous release is inﬂuenced by turbu-
lence intensity/turbulent scales above the release surface. Finally, it is envisaged that
the identiﬁcation and developments of effective emission reduction techniques will
greatly improve the environmental behaviour of livestock buildings. The establish-
ment and assessment of abatement techniques, whose application can result in the
improvement of air quality inside and outside livestock buildings, will enable a
wider adoption by the farmers and will create improvements by the supplying
industry.
Asimple ammoniaemission model thatcanbeusedasadesigntoolfor
low-am monia housingsystems forpigshasbeendescribedbyA.Aarnink etal.
Themodel canbeusedtoestimate ammonia emissions fromdifferent housing
farming systems forpigsbutalsototestdifferent low-am monia emissi onhousing
systems .Different emissions measurementapproac hesandanalyticalinstruments
togetherwithinformation relatedtodatapreparation ,analys is,reporting anduncer-
taintyassessmen tarepresen tedbyM.Hassouna etal.Authors alsodescribehow
measurements andmodelli ngarecombined andwhichmodelscould beusedfor
severa lscientiﬁcandapplied.Dietarymeasures tomitiga temethane atanimal level
aresumma rizedbyV.Lind.Thechaptercoversmaindietaryingredient ssuchas
forage quality,inclusio nofconcentrate, grazingmanag ement andinclusion of
primary andseconda ryplantcompo undsaswellaschemical inhibitors tothediet
andcanbeusedasaguidan ceonwhattouseandatwhich concentrations inthediets
levels (farmers )andhowtoquantifytheeffect (researcher s).Thecontribution of
manur emanag ement toNH3andGHG emissions withfocus onbovine ,pigand
poultry manur eisanalys edbyD.Fanguei roetal.Different mitiga tionoptionsfor
reducinggaseous emissions along themanur emanag ement chaininterms oftheir

efﬁciency to decrease NH3 and GHG emissions and their applicability are presented.
At the end two case studies of integrated manure management strategies to reduce
gaseous emissions are presented. A detail approach for modelling methane emission
from manure is presented and analysed by S. Calvet et al., whereas the role of
manure management in environmentally friendly and circular livestock production is
detailed analysed by C. Cordovil et al. B. Bjerg et al. review the current legal
requirements related to the emission of ammoniafrom
animal housing in 24 out of
the 27 EU countries and in 7 non-EU countries. The analysis presented in this
chapter can be considered as an introduction to the substantial initiatives and
decisions taken by the EU in relation to ammonia emission from animal housing
and as a notiﬁcation on the absence of corresponding initiatives and decisions in
relation to greenhouse gases. The contribution of renewable energy sources in
decreasingthegreenhousegasemissionsfromanim
al farms is presented by
A. Constantino et al. After initial general concepts about the relations between the
energy use and the related greenhouse gas emissions, an overview about the energy
consumption in animal farms is provided and different solutions based on the use of
renewable energy sources are presented to show their potentialities in decreasing the
greenhouse gas emissions. Sensors that can quantitatively measure NH3, odour and
GHG in livestock houses are presented anddescri
bed by in Bok Lee at al. The
principles of sensor measurements areﬁrst analysed according to measurement
parameters, and then issues related to the used sensors in livestock houses, sensors
development of durability, ICT control systems and optimal sensor placement were
analysed. Finally the different techniques and tools that can be used for assessing the
environmental impact assessment of emissions in livestock farming systems are
presentedandanalysedbyAnestisetal.
8 T. Bartzanas et al.
References
Alexandratos, N., & Bruinsma, J. (2012).World agriculture towards 2030/2050: The 2012 revision
(ESA working paper no. 12–03). FAO.
Animal Task Force (ATF). (2016).A strategic research and innovation agenda for a sustainable
livestock sector in Europe(Second White Paper). Animal Task Force.
Bartzanas, T., Amon, B., Calvet, S., Mele, M., Morgavi, D., Norton, T., Ruiz, D. Y., & van Dongen,
C. (2017). Mini-paper–Precision livestock farming. EIP-AGRI Focus Group (2017). Reducing
emissions from Cattle farming (Final Report).
EU. (2012).Rural developmentﬁnancial instruments: New opportunities to tackle the economic
crisis(EU Rural review, no 13). Also available athttps://enrd.ec.europa.eu/sites/default/ﬁles/
69D9962A-A9D5-5298-0AB7-C4B02470D0B5_0.pdf
EU. (2013).Green paper: A 2030 framework for climate and energy policies. Also available at
https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2013:0169:FIN:en:PDF
EU. (2019a).Decision No 406/2009/EC of the European parliament and of the council.
EU. (2019b).Communication
from the commission. The European Green Deal, COM(2019)
640ﬁnal
EU. (
EEA R eport No 5/2020.
EU.(2020 b,May20).Communication fromtheCommission totheEuropean Parliament, the
Council, theEuropean Economic andSocial Committee oftheRegions: AFarm toFork
Strategy forafair, healthy andenvironmentally-friendly food system (Document
52020DC0381. COM(2020) 381ﬁnal).

1 Technology for Environmentally Friendly Livestock Production 9
EU (COM 15). (2014).A policy framework for climateand
energy in the period from 2020 to 2030.
FAO. (2017).The state of food and agriculture. Leveraging Food Systems for Inclusive Rural
Transition. Also available athttps://www.fao.org/3/I7658e/I7658e.pdf
FAOSTAT. (2016).FAOSTAT emissions database, agriculture, agriculture total.
Heidecke, C., Montgomery, H., Stalb, H., & Wollenberg, L. (Eds.). (2018, September 10–13).
International conference on agricultural GHG emissions and food security–Connecting
research to policy and practice. Volume of abstracts (Thünen working paper, no. 103). Johann
Heinrich von Thünen-Institut.https://doi.org/10.3220/WP1535709029000
Herrero, et al. (2016). Greenhouse gas mitigation potentials in the livestock sector.Nature Climate
Change, 6, 452.
JRC. (2014).Precision agriculture–An opportunity for EU farmers–Potential support with the
CAP 2014-2020.
Steinfeld, e
l. (2006).Livestock’s long shadow: Environmental issues and options. FAO.
Wright, et al.(2012). Integrating cropsandlivestock insubtropical agricultural systems. Journal of
theScience ofFoodandAgriculture, 92,1010.

A Simple Model as Design Tool
for Low-Ammonia Emission Pig Housing
2
André J. A. Aarnink, P. Demeyer, and L. Rong
Abstract
Within this chapter, a simple ammonia emission model is described that can be
used as a design tool for low-ammonia housing systems for pigs. Within this
model, ammonia emission is calculated by summation of the ammonia emissions
of the different sources that can be distinguished within a pig pen: manure
channel(s), slattedﬂoor, and solidﬂoor (including fouled pigs and pen partitions).
The emission from each source is calculated by multiplying the ammonia emis-
sion per m
2
emitting area with the emitting area of each source. A general
equation is given to calculate the ammonia emission per m
2
emitting area. An
example of a design study is given for a partially slattedﬂoor housing system for
growing-ﬁnishing pigs. Ammonia emissions are calculated in kg/y per pig place,
in which a certain inoccupation period is discounted. From this study, it is
concluded that a simple ammonia emission model can be very useful for design-
ing low-ammonia emission housing systems. Different low-ammonia emission
housing systems are now tested in practice. Estimations of the ammonia
emissions from these systems have been performed with the simple model
described in this chapter. Results from the practical studies can be used to further
develop and improve the model.
A. J. A. Aarnink (✉)
Wageningen University and Research, Wageningen, The Netherlands
e-mail:[email protected]
P. Demeyer
Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Merelbeke, Belgium
L. Rong
Aarhus University, Aarhus, Denmark
#The
Author(s), underexclusive license to Springer Nature Switzerland AG 2023
T. Bartzanas (ed.),Technology for Environmentally Friendly Livestock Production,
Smart Animal Production 1,https://doi.org/10.1007/978-3-031-19730-7_2
11

12 A. J. A. Aarnink et al.
2.1 Introduction
Ammonia emitted from livestock production largely contributes to nitrogen deposi-
tion in nature areas, causing loss of biodiversity and negative consequences for
ecosystem services (Sutton & Bleeker,2013; Payne et al.,2017; Guthrie et al.,
2018). Furthermore, ammonia contributes to the formation of secondary aerosols
consisting of ammonium sulphate and ammonium nitrate, which make up a large
fraction ofﬁne particles, posing a threat to human health (Backes et al.,2016). In the
period from 2014 to 2017, ammonia emissions within the EU still increased by
approx. 2.5%. This increase was mainly caused by the agricultural sector (NEC
Directive reporting status 2019). In the Netherlands 88% of emitted ammonia
originate from livestock production of which approx. 20% from pig production
(CBS et al.,2020). In pig production, a signiﬁcant part of ammonia emits from
housing, and there are different options to reduce these emissions (Bittman et al.,
2014). Various models have been developed to simulate and predict ammonia
emissions from pig houses (e.g., Zhang et al.,1994; Aarnink & Elzing,1998;
Sommer et al.,2006; Cortus et al.,2008; Ye et al.,2008). These models, however,
generally have a mechanistic approach, and generally numerous input values are
needed, and those input values often are not easy to obtain. For developing new
concepts of low-ammonia emission pig housing systems, there is a need for a simple
design tool. Within this chapter, such a design tool is described, and an example is
given to use this tool to develop a low-ammonia emission housing system for
growing-ﬁnishing pigs.
In Sect.2.2, the model approach and a description of the design tool are given. In
Sect.2.3, an example of the development of a new housing design with
low-ammonia emission for growing-ﬁnishing pigs is described. In Sect.2.4, the
modelling tool is discussed with its potential and limitations.
2.2 Description of the Ammonia Model
According to Elzing and Monteny (1996), ammonia emission from the different
sources in livestock houses can be described with the following general formula:
E
NH3=
k×A×f×TAN?
H
ð2:1Þ
where
1.E
NH3=ammonia emission (mol/s)
2.k=mass transfer coefﬁcient (m/s)
3.A=emitting area (m
2
) ~ size manure pit,ﬂoor fouling
4.f
=fractionf NH
3insolution (-)~pH,T

2 A Simple Model as Design Tool for Low-Ammonia Emission Pig Housing 13
5. [TAN] =NH 3+NH4
+in solution (mol/m
3
) ~ nutrition, growth, and urease
activity
6.H=Henry constant (-)~T
kis the mass transfer coefﬁcient, and this is related to the air velocity and
temperature of the emitting surface.Ais the emitting area of each source of ammonia
inside the house. f is the fraction of unionized ammonia in the solution, and [TAN] is
the total ammoniacal concentration in the solution.His the Henry constant, and this
gives the relationship between the ammonia concentration in the solution and the
ammonia concentration in the boundary layer above the emission source. The Henry
constant is related to the temperature of the emitting surface.
In the Netherlands and in Flanders, Belgium, a lot of houses for growing-ﬁnishing
are designed as given in Fig.2.1(cross-section) and Fig.2.2(layout). In a lot of other
European countries, very similar pens with manuring systems are used. Often,
however, the solidﬂoor area is smaller, or the pens are fully slatted. In the pen as
given in Figs.2.1and2.2, four emission sources can be distinguished. S1 and S2 are
the two manure channels, one in the back of the pen (S1), opposite to the feeders,
where most excreta are deposited, and one in front of the pen, near the feeders, where
only little excreta are deposited (Aarnink et al.,1996). S3 are the concrete-slatted
ﬂoors, in front and in the back of the pen. While there is almost no excretion in front
of the pen, the emission from this slattedﬂoor can almost be ignored. S4 is the fouled
solidﬂoor, including the fouled pigs and pen partitions. In a well-designed pen, as in
Fig.2.1, with temperatures within the comfort zone of the pigs, almost no pen
fouling will occur. At temperatures above the comfort zone, however, pigs will
prefer to lie on an uninsulatedﬂoor, i.e., the slattedﬂoor, and consequently, they will
Fig.2.1Differentourcesfmmonianross-sectionfeferenceigouseithartially
slatted ﬂoors.1nd2:anureits;3:oncrete-slatted ﬂoor;4:ouledolid ﬂoorincluding
fouledigsndenartitions)

2
excrete on the solidﬂoor. When the ambient temperature is exceeding the comfort
zone considerably, the pigs will even start to lie in their own urine and feces
(Aarnink et al.,2006) to wet themselves for evaporative cooling like in a mud
pool (Bracke,2011).
14 A. J. A. Aarnink et al.
Fig. 2.2Layout of a reference pig house with partially slattedﬂoors. The pen contains 12 pigs with
a total area of 0.83 m
2
/pig. The manure is stored inside the room for at least one fattening round
With the simple modelling tool, ammonia emission is estimated with the follow-
ing two equations:
E
NH3=
X
E S i ð2:2Þ
where
7.E
NH3=ammonia emission
8.E_S
i=ammonia emission from sourcei(i=1...4)
E S
i=Ai∙E m
i
ð2:3Þ
where
9.E_S
i=ammonia emission from sourcei
10.A
i=emitting area of sourcei
11.E_m
2
i
=ammonia emission per m
2
of sourcei
Theammonia emissionperm
2
emitting areadepends ontheNH4-N concentra-
tionandthepHofthesource solution andonthetemperat ureofthesurfaceofthe
emissi onsource andontheairvelocity abovetheemitting area.Thedifferent

Parameter
a
20202222
equations to calculate the ammonia emission per m
2
emitting area are described in
detail by Aarnink and Elzing (1998).
2 A Simple Model as Design Tool for Low-Ammonia Emission Pig Housing 15
Table 2.1Reference values for calculation of the ammonia emission per m
2
emitting area and per
pig place per year for sources S1, S2, S3, and S4 (see Fig.2.1
)
Source
S1
Source S2 Source S3 Source S4
Tsurface manure/urine puddle,°C
v above manure/urine puddle, m/s 0.045 0.045 0.14 0.14
pH surface manure/urine puddle,- 8.5 8.5 8.5 8.5
[TAN] surface manure/urine puddle, mol/m
3
320 320 105
b
105
b
Estimated ammonia emission, kg/y per m
2
emitting area
4.2 4.2 4.3 4.3
A of manure/urine puddles, m
2
/pig 0.333 0.167 0.175
c
0.035
Estimated ammonia emission, kg/y per pig
place
d
1.40 0.70 0.75 0.15
a
Ttemperature,vair velocity, [TAN] total ammoniacal nitrogen concentration,Aemitting area
b
In a study by Aarnink et al. (2018), it was found that the TAN concentration of a urine puddle,
randomly sampled from theﬂoor, is about one-third of the concentration in the manure
c
This is the total emitting area of the slattedﬂoor, so not only the top area but also the emitting areas
at the sides and the bottom of the slats
d
To calculate ammonia emission on a yearly basis, it is assumed that the pig house is unoccupied for
3% of the year, and during this inoccupation period, it is assumed that ammonia emission is negligible
In Table2.1, the reference values for calculation of the ammonia emissions per
m
2
emitting area and per pig place per year are given for sources S1, S2, S3, and S4
for the reference house shown in Figs.2.1and2.2. The total yearly ammonia
emission for this type of pig house is estimated to be 3.0 kg per pig place. This
value equals the emission value as included in the list of ammonia emission factors
for the reference housing system for growing-ﬁnishing pigs in the Netherlands
(www.infomil.nl).
2.3 New Housing Designs with Low-Ammonia Emissions
There are different buttons to turn to lower the ammonia emission from the pens
shown in Figs.2.1and2.2. In this design study, we want to reduce ammonia
emission by the following means:
Reducing the emitting area
Lowering the manure temperature
Lowering the TAN concentration by dilution with water
In F
2.3, t he effects of the abovementioned variables, including the effect of air
velocity above the emitting area, on the ammonia emission are given, as relative
values compared with the reference emission from that source. Theseﬁgures show

that ammonia emission from a source is linearly related to the area and the TAN
concentration, while it is exponentially related to the temperature and logarithmi-
cally related to the air velocity above that source.
16 A. J. A. Aarnink et al.
Fig. 2.3Effects of emitting area, surface temperature, dilution (TAN concentration), and air
velocity on the relative ammonia emission from a source. The red lines give the values for the
sources S1 and S2 in the reference pen as shown in Figs.2.1and2.2and Table2.1
Theemittingmanure areainthepitscanbereduced bydecreas ingtheslatted ﬂoor
area,andatthesametimeincreasingthesolidﬂoorarea,andbyplacing slanted walls
inside themanur echannel where mostofthefecesandurineareexcreted (source
S1).Theestimated ammonia emissio nsfromeachsource aregiveninFig.2.4.This
ﬁgure showsthatthesemeasu resreduce theemissi onfromS1from1.40to0.30kg/
y.However ,theincreaseintheareaofsolidﬂoorwillincreasetheemissi onfromthis
source (S4)from0.15to0.20kg/y.Furthe rmore, anextrasource iscreatedwiththe
slanted walls.InthestudyofAarnink etal.(2018),itwasshown thatapprox. 17%of
theslantedwallatthesolidﬂoorsidewasfouledwithurineandapprox. 33%ofthe
slanted wallatthewallside.Undertheassumptionthattheammoniaemissionper
m
2
fouledslantedwallissimilarastheemissio nfromthemanur epit,itwas
estimat edthattheammoniaemissi onfromtheslantedwallsis0.15kg/yperpig
place. Thetotalammoniaemissi onfromthishousing system wasestimate dtobe
2.1kg/yperpigplace, equaling areductionof30
%.Byreplacingtheconcret e-
slatted ﬂoorbyametal-slatted ﬂoortheammoniaemissi onfromthissource canbe
reduced by68%(estimated fromtheresults ofAarnink etal.(1997)), giving anextra
ammoniareduction of0.51kg/yperpigplace. Bydiluting thesmall amoun tof
manur ethatendsupinthemanure channel infrontofthepen(under neath the
feeders )withafactor 5(1partmanur eand4partswater), theemission fromthis
manur echannel canbereduced withafactor5from0.70to0.14kg/yperpigplace.

Finally, by cooling the manure channel with the slanted walls to a temperature of
14°C the ammonia emission from this manure and from the fouled slanted walls can
be reduced with approx. 50% (see Fig.2.3). When also the solidﬂoor is cooled
during summertime, it is expected that fouling can be reduced by approx. 50%,
giving a reduction in ammonia emission from this source from 0.20 to 0.10 kg/y per
pig place. In Fig.2.5, theﬁnal design of the low-ammonia emission system is given
with the estimated emissions for each source. It is expected that the overall ammonia
emission of this system will be 0.72 kg/y per pig please, meaning a 76% reduction
from the reference system.
2 A Simple Model as Design Tool for Low-Ammonia Emission Pig Housing 17
Fig. 2.4Estimated ammonia emission when reducing the emitting area of the manure pit (source
S1). Total ammonia emission of this housing system is estimated to be 2.1 kg/year per pig place
2.4 Discussion
Asimple ammonia emissi onmodel waspresen tedtoserveasadesigntooltolower
ammoniaemissions frompighouses .Different assumptions havebeenmade for
creatingthismodel.Mostassumpti ons,however, aresuppor tedbymeasurement
data.Calculatio nwiththismodel showsthat70%ofammonia emissi oninthe
referencepenoriginate fromthemanur echannels and30%fromtheﬂoor.Thisis
inagreem entwithmeasuredresultsfromHoeksmaetal.(1992),whofound asimilar
percent ageinpenswithasimilar percent ageofslatted ﬂoor.Effects ofmanur e
coolingsystemshavealsobeenproven indifferentstudies(Brok&Verdoes, 1996;
Groen
estein &Huisin‘tVeld,1996;DenBrok, 1997).Depending onthedecreas e
inmanur etemperature, higher -orlower-ammon iareductionshavebeenmeasured.
Bycombiningtwostudies (Hoeksm aetal.,1993;Aarnink etal.,1996),almosta
linear relations hipbetween theslattedﬂoorareaandtheammonia emissionwas

found, with an ammonia emission per pig place from pens with fully slattedﬂoors of
approx. 3.6 kg/y and of pens with 25% slattedﬂoor of 1.8 kg/y. It is important to
notice that with decreasing slattedﬂoor area, the risk of pen fouling increases,
especially during the summer period. Therefore it is important to optimize indoor
climate when the solidﬂoor area is enlarged. Studies have shown that heavy
growing-ﬁnishing pigs already change their lying behavior above ambient
temperatures of 20°C(Huynh
et al.,2005; Aarnink et al.,2006). The refore also in
temperate climate zones like the Netherlands, Belgium, and Denmark, cooling in the
summertime is needed to prevent pen fouling.
18 A. J. A. Aarnink et al.
Fig. 2.5Estimated ammonia emission when taking the following reduction measures: reduced
emitting area of source S1; metal instead of concrete-slattedﬂoor; dilution of manure in manure
channel near feeder; cooling of manure channel with slanted walls and of the solidﬂoor during
summertime. Total ammonia emission of this housing system is estimated to be 0.72 kg/year per pig
place
When looking atthereference values given inTable 2.1,thetemperat ureofthe
emittin gsurfacesandtheairvelocity above theemittin gsurfacesismainly
dependi ngontheindoor climate control. Thisclimate controlislargelyinﬂuenced
bytheoutdoor condition s,especiallytheoutdoor temperat ure.Thetemperat ureof
theemittingsurfacesdepends onthisoutdoo rtemperat ure,ontheventilat ionrateand
inside airﬂowpattern, onindoor heating and/or cooling systems ,andontheheat
product ionofthepigs(mainly dependingonthesizeoftheanimals) .Theairvelocity
above theemitting areasmainly depends ontheventilation rateandtheairﬂow
pattern. Airﬂowpatterns canhavealargeeffect onairvelocity above theemitting
areasandthereby ontheammoniaemission(Rong etal.,2018; Tabaseetal.,2020).
Inthestudiesmentionedbefore ,airﬂowpatternsweresimulated withCFDmodels.
These modelscanbeveryuseful topredicttemperature andairvelocityofthe
emittin gareas.

2 A Simple Model as Design Tool for Low-Ammonia Emission Pig Housing 19
The pH and the TAN concentration of the manure and urine puddles can mainly
be inﬂuenced by the diet of the pigs (Canh et al.,1998a,b,c; Portejoie et al.,2004;
Le et al.,2009). The pH can also be inﬂuenced by acidifying the manure as is done in
Denmark in different cow and pig houses (Kai et al.,2008; Petersen et al.,2012). The
TAN concentration can also be inﬂuenced by dilution, as shown in this design study.
The emitting area is determined by the manure pit area that is in open connection
with the ambient air and by the fouledﬂoor areas (solid and slatted) and fouled pigs
and pen partitions. The emitting manure pit area is quiteﬁxed. That is not true,
however, for the emittingﬂoor areas. Especially the fouled solidﬂoor areas can vary
a lot, and this has a large effect on variations in ammonia emission. Fouled solid
ﬂoor areas are often an important reason for high emissions during the summertime,
besides the direct effect of raised temperatures on the ammonia emission. Therefore,
reducing the emitting manure pit area by increasing the solidﬂoor area is only
effective when the pen and the climate control system are well designed, so pen
fouling can be kept at a minimum level.
From this study, it can be concluded that a simple ammonia emission model can
be very useful for designing low-ammonia emission housing systems. In the
Netherlands different low-ammonia emission housing systems are now tested in
practice. Estimations of the ammonia emissions from these systems have been
performed with the simple model described in this chapter. Results from these
studies can be used to further develop and improve the model.
References
Aarnink, A. J. A., & Elzing, A. (1998). Dynamic model for ammonia volatilization in housing with
partially slattedﬂoors, for fattening pigs.Livestock Production Science, 53, 153– 169.
Aarnink, A. J. A., Berg, A. J. V. D., Keen, A., Hoeksma, P., & Verstegen, M. W. A. (1996). Effect
of slattedﬂoor area on ammonia emission and on the excretory and lying behaviour of growing
pigs.Journal of Agricultural Engineering Research, 1996(64), 299–310.
Aarnink, A. J. A., Swierstra, D., Van den Berg, A. J., & Speelman, L. (1997). Effect of type of
slattedﬂoor and degree of fouling of solidﬂoor on ammonia emission rates from fattening
piggeries.Journal of Agricultural Engineering Research, 1997(66), 93–102.
Aarnink, A. J. A., Schrama, J. W., Heetkamp, M. J. W., Stefanowska, J., & Huynh, T. T. T. (2006).
Temperature and body weight affect fouling of pig pens.Journal of Animal Science, 84,
2224–2231.
Aarnink, A. J. A., Van de Pas, P. A., Van der Peet-Schwering, C. M. C., Hol, A., Binnendijk, G. P.,
Le Dinh, P., Hafner, S. D., & Ogink, N. W. M. (2018).Rekentool voor het bepalen van de
effecten van voer- en management-maatregelen op de ammoniakemissie bij varkens:
ontwikkeling en validatie[Calculation tool to estimate the effects of feeding and management
measures on ammonia emission in pigs] (Report 1086, 118 p.). Wageningen Livestock
Research.
Backes, A
., Aulinger, A., Bieser, J., Matthias, V., & Quante, M. (2016). Ammonia emissions in
Europe, part II: How ammonia emission abatement strategies affect secondary aerosols.Atmo-
spheric Environment, 126, 153– 161.https://doi.org/10.1016/j.atmosenv.2015.11.039
Bittman, S., Dedina, M.,Howard, C.,Oenema, O.,&Sutton, M.(2014). Options forammonia
mitigation: Guidance fromtheUNECE TaskForce onReactive Nitrogen. NERC/Centre for
Ecology &Hydrology.

20 A. J. A. Aarnink et al.
Bracke, M. (2011). Review of wallowing in pigs: Description of the behaviour and its motivational
basis.Applied Animal Behaviour Science, 132(1), 1 –13.
Brok, G. M. D., & Verdoes, N. (1996).Effect vanmestkoeling
op de ammoniakemissie uit een
vleesvarkensstal(Proefverslag P 1.155, 28 pp.). Praktijkonderzoek Varkenshouderij.
Canh, T. T., Aarnink, A. J. A., Mroz, Z., Jongbloed, A. W., Schrama, J. W., & Verstegen,
M. W. A. (1998a). Inﬂuence of electrolyte balance and acidifying calcium salts in the diet of
growing-ﬁnishing pigs on urinary pH, slurry pH and ammonia volatilisation from slurry.
Livestock Production Science, 56,1–13.
Canh, T. T., Aarnink, A. J. A., Schutte, J. B., Sutton, A. L., Langhout, D. J., Verstegen, M. W. A., &
Schrama, J. W. (1998b). Dietary protein affects nitrogen excretion and ammonia emission from
slurry of growing-ﬁnishing pigs.Livestock Production Science, 56, 181– 191.
Canh, T. T., Sutton, A. L., Aarnink, A. J. A., Verstegen, M. W. A., Schrama, J. W., & Bakker,
G. C. M. (1998c). Dietary carbohydrates alter the faecal composition and pH and ammonia
emission from slurry of growing pigs.Journal of Animal Science, 76, 1887–1895.
CBS, PBL, RIVM, WUR. (2020).Ammoniakemissie door de land- en tuinbouw, 1990–2018
(indicator 0101, versie 17, 8 oktober 2020).www.clo.nl. Centraal Bureau voor de Statistiek
(CBS), Den Haag; PBL Planbureau voor de Leefomgeving, Den Haag; RIVM Rijksinstituut
voor Volksgezondheid en Milieu, Bilthoven; en Wageningen University and Research,
Wageningen.https://www.clo.nl/indicatoren/nl0101-ammoniakemissie-door-de-land%2D%2
Den-tuinbouw, 2021.
Cortus, E. L., Lemay, S. P., Barber, E. M., Hill, G. A., & Godbout, S. (2008). A dynamic model of
ammonia emission from urine puddles.Biosystems Engineering, 99(3), 390– 402.
Den Brok, G. M. (1997).Mestkoeling bij kraamzeugen en gespeende biggen(Proefverslag P 4.12,
pp. 9–11). Research Institute for Pig Husbandry, Oktober 1995.
Elzing, A., & Monteny, G. J. (1996).Model to predict the ammonia emission from a scale model of
a dairy-cow house. Submitted to Trans. ASAE.
Groenestein, C. M., & Huis in‘t Veld, J. H. W. (1996).Praktijkonderzoek naar de
ammoniakemissie van stallen XIX. Vleesvarkensstal met koeling van mestoppervlak in de kelder
(DLO-rapport 96-1003).
Guthrie, S., Giles, S., Dunkerley, F., Tabaqchali, H., Harshﬁeld, A., Ioppolo, B., & Manville,
C. (2018).The impact of ammonia emissions from agriculture on biodiversity. RAND Corpo-
ration and The Royal Society.
Hoeksma, P., Verdoes, N., Oosthoek, J., & Voermans, J. A. M. (1992). Reduction of ammonia
volatilization from pig houses using aerated slurry as recirculation liquid.Livestock Production
Science, 31, 121– 132.
Hoeksma, P., Oosthoek, J., Verdoes, N., & Voermans, J. A. M. (1993).Reductie van
ammoniakemissie uit varkensstallen door mestspoelen met beluchte spoelvloeistof(Rapport
93-23, 56 pp.). IMAG-DLO Wageningen.
Huynh, T. T. T., Aarnink, A. J. A., Gerrits, W. J. J., Heetkamp, M. J. H., Canh, T. T., Spoolder,
H. A. M., Verstegen, M. W. A., & Kemp, B. (2005). Thermal behaviour of growing pigs in
response to high ambient temperature and humidity.Applied Animal Behaviour Science, 91,
1–16.
Kai, P., Pedersen, P., Jensen, J., Hansen, M. N., & Sommer, S. G. (2008). A whole-farm assessment
of the efﬁcacy of slurry acidiﬁcation in reducing ammonia emissions.European Journal of
Agronomy, 28(2), 148– 154.
Le, D. P., Aarnink, A. J. A., & Jongbloed, A. W. (2009). Odour and ammonia emission from pig
manure as affected by dietary crude protein level.Livestock Science, 121, 267– 274.
Payne, R
., Dise, N. B., Field, C. D., Dore, A. J., Caporn, S. J., & Stevens, C. J. (2017). Nitrogen
deposition and plant biodiversity: Past, present, and future.Frontiers in Ecology and the
Environment, 15(8), 431–436.
Petersen, S. O.,Andersen, A.J.,&Eriksen, J.(2012). Effects ofcattle slurry acidiﬁcation on
ammonia andmethane evolution during storage. Journal ofEnvironmental Quality, 41(1),
88–94.

2 A Simple Model as Design Tool for Low-Ammonia Emission Pig Housing 21
Portejoie, S., Dourmad, J., Martinez, J., & Lebreton, Y. (2004). Effect of lowering dietary crude
protein on nitrogen excretion,manure
composition and ammonia emission from fattening pigs.
Livestock Production Science, 91(1), 45–55.
Rong, L., Aarnink, A., & Zhang, G. (2018).Challenges of predicting ammonia mass transfer
coefﬁcient in pig houses. AgEng 2018. Book of Abstracts.https://ageng2018.com/sites/default/
ﬁles/ageng2018_book_of_abstracts_-_draft_version.pdf, Wageningen, The Netherlands.http://
dx.doi.org/https://ageng2018.com/sites/default/ﬁles/ageng2018_book_of_abstracts_-_draft_
version.pdf
Sommer, S., Zhang, G., Bannink, A., Chadwick, D., Misselbrook, T., Harrison, R., Hutchings, N.,
Menzi, H., Monteny, G., & Ni, J. (2006). Algorithms determining ammonia emission from
buildings housing cattle and pigs and from manure stores.Advances in Agronomy, 89, 261–335.
Sutton, M. A., & Bleeker, A. (2013). The shape of nitrogen to come.Nature, 494(7438), 435– 437.
https://doi.org/10.1038/nature11954
Tabase, R. K., Bagci, O., De Paepe, M., Aarnink, A. J., & Demeyer, P. (2020). CFD simulation of
airﬂows and ammonia emissions in a pig compartment with underﬂoor air distribution system:
Model validation at different ventilation rates.Computers and Electronics in Agriculture, 171,
105297.
Ye, Z
hang, G., Li, B., Strøm, J., & Dahl, P. (2008). Ammonia emissions affected by airﬂow in a
model pig house: Effects of ventilation rate,ﬂoor slat opening, and headspace height in a
manure storage pit.Transactions of the ASABE, 51(6), 2113–2122.
Zhang, R. H.,Day,D.L.,Christianson, L.L.,&Jepson, W.P.(1994). Acomputer model for
predicting ammonia release ratesfromswine manure pits.Journal ofAgricultural Engineering
Research, 58,223–229.

Measuring Techniques for Ammonia
and Greenhouse Gas Emissions from
Naturally Ventilated Housings
3
M. Hassouna, T. Amon, C. Arcidiacono, M. Bühler, S. Calvet,
P. Demeyer, P. R. D’Urso, F. Estellés, C. Häni, S. Hempel, D. Janke,
M. Kjosevski, T. Kupper, J. Mohn, J. Mosquera, T. Norton, C. Scheutz,
N. Thygesen Vechi, P. Van Overbeke, and S. Schrade
Abstract
The quantiﬁcation of gas emissions from livestock housings is a complex and
challenging measurement task because performing emission measurements under
practice conditions requires a high level of expertise and poses signiﬁcant
M. Hassouna (✉)
INRAE, Institut Agro Rennes Angers, UMR SAS, Rennes, France
e-mail:[email protected]
T. Amon
Leibniz Institute for Air Pollution & Agricultural Engineering and Bioeconomy (ATB), Department
Livestock Engineering, Potsdam, Germany
Free University Berlin (FUB), Department of Veterinary Medicine, Institute of Animal Hygiene and
Environmental Technology and Health, Berlin, Germany
C. Arcidiacono · P. R. D’Urso
University of Catania, Department of Agriculture, Food and Environment (Di3A), Building and
Land Engineering Section, Catania, Italy
M. Bühler
School of Agricultural, Forest and Food Sciences HAFL, Bern University of Applied Sciences,
Zollikofen, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Institute of Geography, University of Bern, Bern, Switzerland
S. Calvet · F. Estellés
Institute of Animal Science and Technology. Universitat Politècnica de València, Valencia, Spain
P. Demeyer · P. Van Overbeke
Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Merelbeke, Belgium
C. Häni · T. Kupper
School of Agricultural, Forest and Food Sciences HAFL, Bern University of Applied Sciences,
Zollikofen, Switzerland
#The
Author(s), underexclusive license to Springer Nature Switzerland AG 2023
T. Bartzanas (ed.),Technology for Environmentally Friendly Livestock Production,
Smart Animal Production 1,https://doi.org/10.1007/978-3-031-19730-7_3
23

challenges to obtaining a careful evaluation and a reliable validation. Many
measurement methods have been developed in recent decades to improve the
knowledge on emissions from livestock housings, to such an extent that it
becomes difﬁcult to choose the most suitable method for the system under
study and especially for the measurement objectives. The aim of this chapter is
to present and discuss different measurement approaches as well as analytical
instruments. Additional information is given concerning data preparation,
analysisand
reporting and uncertainty assessment. Further it is shown how
measurements and modelling are combined and which models could be used
for several scientiﬁc and applied.
24 M. Hassouna et al.
3.1 Introduction
The quantiﬁcation of gas emissions from livestock housings is a complex and
challenging measurement task because it involves measurements on an evolving
biological system with emission processes subject to more or less rapid dynamics
and inﬂuenced by a large number of biotic and abiotic factors. Performing emission
measurements under practice conditions requires a high level of expertise and poses
signiﬁcant challenges since the involved complexities lead to large inherent mea-
surement uncertainties (Calvet et al.,2013) that require careful evaluation and
validation. These complexities are mainly related to (1) highly diverse production
techniques and management practices (e.g. housing, feeding, manure management);
(2) a wide range of biological, chemical and physical reactions inherent to the
S.Hempel ·D.Janke
Leibniz Institute forAirPollution &Agricultural Engineering andBioeconomy (ATB), Department
Livestock Engineering, Potsdam, Germany
M.Kjosevski
University “Ss.CyrilandMethodius ”Skopje, Faculty ofVeterinary Medicine, Department for
Animal Hygiene andEnvironmental Protect ion,Animal Welfare Center, Skopje, Republic of
Macedonia
J.Mohn
Empa, Laboratory forAirPollution &Environmental Technology, Dübendorf, Switzerland
J.Mosquera
Wageningen URLivestock Research, PO,Wageningen, Netherlands
T.Norton
Animal andHuman Health Engineering, KULeuven, Leuven, Belgium
C.Scheutz ·N.Thygesen Vechi
Department ofEnvironmental Engineering, Technical University ofDenmark, Kgs.Lyngby,
Denmark S.Schrade
Agroscope, Ruminant Nutrition andEmissions Research Group,Ettenhausen, Switzerland

respective emission (reduction) processes and (3) application of sampling and
measurement techniques under a large variation of farm practice conditions.
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 25
Many measurement methods have been developed in recent decades to improve
the knowledge on emissions from livestock housings, to such an extent that it
becomes difﬁcult to choose the most suitable method for the system under study
and especially for the measurement objectives (Hassouna et al.,2016; Hassouna
et al.,2021a,b). In this context, a good knowledge of available measurement
methods, theirﬁeld of applicability and the required conditions for their implemen-
tation appear essential.
The aim of this chapter is to present and discuss different measurement
approaches as well as analytical instruments. Additional information is given
concerning data preparation, analysis and reporting and uncertainty assessment.
Further it is shown how measurements and modelling are combined and which
models could be used for several scientiﬁc and applied.
Within the framework of the working group for monitoring indoor climate and
gaseous emissions from animal housings, part of the COST Action CA16106 (http://
cost-livage.eu/), a survey on the current measuring approaches for emissions from
animal buildings in Europe and beyond was conducted. Fifteen research groups from
14 different European countries and Canada replied to the survey (Fig.3.1).
The results of this survey were cross-referenced and complemented with information
Fig.3.1Europeanountriesnvolvednheurvey.anadaaslsoarticipating

collated in the ELFE database, which contains emission values published in the
international literature and numerous metadata associated with these values (Vigan
et al.,2019, Hassouna et al.,2019).
26 M. Hassouna et al.
The analysis of the information collected shows that the main reasons for
emissions measurements are (i) mitigation techniques development and evaluation
followed by (ii) studying emission processes, (iii) quantiﬁcation of emission factors
and (iv) emission monitoring and control (Table3.1). Emission measurements are
mainly related to dairy cattle followed by fattening pigs and poultry (broilers, laying
hens) which means that the measurements are carried out on housing systems with
natural but also mechanical ventilation. Considering the target parameter, methane
(CH
4), ammonia (NH3) and carbon dioxide (CO2) are the gases measured by most of
the groups. Although other substances were likewise recorded as hydrogen sulphide
or particulate matters, the number of the groups that focus on further gases are
considerably lower (Fig.3.2). Concerning concentration measurements, optical and
continuous measurement techniques are the most frequently used. In the survey, the
Table 3.1The aim of the emission measurement from animal systems/housings (more than one
answer per respondent/participant was possible)
Aim of measurements
Response (%)
Mitigationtechnique development 80
Studying emission processes 67
Quantiﬁcation of emission factors 60
Emissions monitoring and control 60
Indoor air quality monitoring for animal health
and welfare 53
Indoor air
quality monitoring for workers’safety 33
Other (breeding for low emissions) 70
2
4
6
8
10
12
14
Number of reponses [n]
Substances
Fig. 3.2Responses [n] that measure a particular target substance in an animal housing system
(more than one answer per respondent was possible)

most used gas analysers are infrared photoacoustic gas monitors, followed by cavity
ring down spectrometers, which is in good agreement with information included in
the ELFE database. For determining the airﬂow for calculating the emissions, in the
survey, the most mentioned method was direct measurement by using anemometers
(only for mechanical ventilation) followed by the CO
2balance and external tracer
gas methods. In the ELFE database, heat balance methods and micrometeorological
methods are alsocited
for the assessment of airﬂow rate and emissions. The
additional parameters monitored along with the emission measurements were very
similar between different research groups: outdoor climate, housing climate, feed
data, numbers of animals, zoo technical data, housing/building dimensions, housing
speciﬁcations and design (ﬂoors, facades, lying area, etc.), area’s soiling and manure
management.
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 27
3.2 Description of the Measurement Approaches
The most common approaches to quantify emissions from livestock farming under
natural ventilation can be divided as follows: (i) local and disruptive: chamber
methods for comparison of surfaces, (ii) local and nondisruptive: determination of
ventilation rates (VR) and concentration gradients in housings and (iii) global and
nondisruptive: tracer gas dispersion, dispersion modelling of single emission sources
or whole farms. Individual approaches are brieﬂy described in the next paragraphs,
and their most important advantages and disadvantages as well as their area of
application are listed in Table3.2.
These measurement approaches are then translated into methodologies adapted to
the measurement objectives and the types of sources. These methodologies are
implemented and adapted in protocols. A methodology is not always linked to the
same type of sensor or analyser, even if the quantity to be measured isﬁxed by the
methodological framework and the model used (Fig.3.3).
3.2.1 Measurement of Surface Emissions with Chamber Techniques
Chamber techniques (static ordynam ic)arewidelyapplicatedforlandﬁeldmanur e
applicationbecause theyareadapte dtoinsitumeasurementsofsurface-atmosp here
gasexchanges. Furthe rtheycanbeimplemented toassess emissi onsfrommanur eor
ﬂoorsurfacesinside theanimal housings. Thestaticoraccumulate dchamb ermethod
(noairrenewalinside thechamb erandnoairvelocity ontheemitting surfaceinthe
chamb er)isusedinpractisetoquantify GHG emissi ons(Sommeretal.,2004).
Gases
areaccum ulated overashortperiodoftime(i.e.15to30min)inside the
chamb ertominimize theeffect onemission proces sesinside thechamb er
(Woodb uryetal.,2018).Theincreaseofgasconcent ration ismeasuredduring the
closuretime,i.e.untiltheconcent ration remains constant throughout. Accordingto
Barrancos etal.(2013),theconcentration increaseversus timeisclosely relatedto
thegasemissi onfromthesurface .Gasconcent rations canbemeasureddirectlywith

Approach
(continued)
28 M. Hassouna et al.
Table 3.2Overview of common measuring approaches for naturally ventilated housings
Area of application, principle
and
description
Evaluation (pros, cons,
important aspects)
Local anddisruptive: Measurements of surface emissions
(A) Chamber techniques
Static chamber (closed
chamber)
Dynamic chamber
(wind channel,ﬂux
chamber,
open dynamic
chamber)
Partial
areas (ﬂoors)
Chamber placed airtight on the
emitting surface; calculation of
the emissions via the temporal
increase in gas concentration in
relation to the covered surface
area
Air is sucked through the
chamber at a deﬁ ned airﬂow;
emission calculation from the
difference in concentration
between incoming and outgoing
air and the airﬂow rate in
relation to the covered surface
area
+ Cost-effective
+ Handling easy
–Only partial areas.
–Intervention in the system and
thus inﬂ uence on emission
processes.
–Animal activity affected or
excluded.
→No transfer to practice and
calculation of absolute
emissions level
→Short-term measurements to
compare variants feasibly
Local and nondisruptive: Direct measurement of ventilation rate and concentration gradients
(B) Direct
measurements of the
airﬂow rate using
anemometers
The ventilation openings are
divided into equal areas. In the
centre of each area, an
anemometer measures the
normal velocity vector.
Multiplying this vector with the
opening area results in the
airﬂow rate. Adding all inﬂ ows
or outﬂows results in the total
airﬂow rate through the building.
Target gas analysis in the inﬂ ow/
outﬂow air provides a
concentration gradient
+ High-frequency info on the
airﬂow rate
+ Does not require the release of
gases
+ Able to measure in strong
crossﬂows
+ Self-check: in- and outﬂows
should be equal, indicates the
precision/accuracy of the
measurement
+ As it is clear where the air
leaves the barn, target gas
concentrations can be measured
at these locations, effectively
measuring emissions.
–Many expensive anemometers
are necessary to account for
heterogeneous velocity
distributions.
–Measuring ridge ventilation is
practically impossible.
–More research necessary to
determine ideal sampling
locations.

Approach
(continued)
Table 3.2(continued)
Area of application, principle
and description
Evaluation (pros, cons,
important aspects)
(C) Balancing methods
(internal tracer methods)
CO
2balance
Heat balance
Moisture balance
Housing (building)
Calculation of the air exchange
rate based on the concentration
gradient of CO
2, heat or
moisture inside versus outside
the housing and its theoretical
output by the animals, taking
into account climatic conditions
Target gas analysis along with
CO2, heat or moisture
+ Quickly applicable
+ Inexpensive
–In cases of very high air
exchange rates (e.g. high wind
speeds or large openings) or very
low wind velocities, the gradient
between inside and outside air
might not be sufﬁcient or
inaccurate.
–Complete CO
2, heat, moisture
sources and sinks must be
included in the model.
–High inaccuracy under certain
wind and/or housing situations.
→Suitable for housings without
an outdoor exercise area and
with a sufﬁcient gradient
between inside and outside
D) External tracer
methods
Tracer decay
Constant dosing
Area sources: housing, outdoor
exercise areas, slurry and/or
manure storage
Emission source is mimicked by
the means of a dosed tracer gas;
calculation of the emission based
on
Tracer decay: decrease of the
tracer gas concentration
Constant dosing: the massﬂow
of the dosed tracer gas and the
concentration ratio of tracer gas
to target substance
+ Practical conditions
+ Real-time measurements
+ Established for natural
ventilation, tracer dosing can be
adapted based on the ventilation
rate
–High costs and high workload.
→Suitable for naturally
ventilated housing systems with
outdoor exercise area
Global and nondisruptive: Dispersion modelling
(E) Tracer gas
dispersion method
Whole farm, including housing
and manure storages, or single
units depending on source
spatial distribution
Simultaneous measurements of
target gas and tracer gas across
the downwind plumes. Use of
tracer gas to simulate the
emission sources. Calculating
the plume-integrated ratio and
knowing the massﬂow of tracer,
the target gas emission can be
calculated
+ Does not rely on
measurements or modelling of
atmospheric conditions
+ Source simulation of farm is
not difﬁ cult if sources are known
+ Quick setup
+ Application under most
meteorological conditions
–Requires available road at
suitable distance
–Nearby sources might interfere
measurements
–Separation of individual
sources (manure storage,
housing and others) within farm
not feasible
→Suitable for whole farm
emission measurements, relies
on source simulation and road
availability

Approach
online analysers connected to the chamber (Vac et al.,2013; Barrancos et al.,2013),
or air samples are collected and stored in vials for subsequent laboratory analysis, for
example with a GC analyser (Powers & Capelari,2016; Hao et al.,2001).
30 M. Hassouna et al.
Table 3.2(continued)
Area of application, principle
and description
Evaluation (pros,cons,
important
aspects)
(F) Inverse
dispersion
method
Total farm including housing,
outdoor exercise area, slurry and
manure storages, etc.
Measurement of concentration
of the target gas upwind/
downwind of the source and
turbulence characteristics
Emission determination based
on a dispersion model and
concentration measurements
+ Farm scale
+ Cost-effective,ﬂexible
–Not suitable for complex
topography/surrounding area
and with low wind speed.
–No distinction between
individual sources within farm
or livestock building:
e.g. housing, outdoor exercise
area, manure/slurry storage, feed
storage, etc. possible.
→Suitable for whole farm
assessments or farm buildings
separated from other sources, if
requirements concerning
weather conditions and
topography are fulﬁlled
3measurement
approaches:
Chambers
Direct/indirect
measurements
Micrometeorological
methods
For each approach,
different
methodologies
adapted to the
measurement
purposes and
emitting source
Each methodology
can be implemented
in different protocols
in function of the
context and
measurement
purposes
For each protocol,
different
measurement
devices/sensors can
be implemented
(measurement range,
budget, operator's
skills etc.)
Fig. 3.3From the main measurement approaches to the protocols
ForNH 3emissionmeasurement,theimplementat ionofstaticchamb erisnot
recommende dbecause ofadsorp tion’slossesandstrong effects ofenvironmen tal
conditions(e.g.windspeed, temperat ure)onthevolatil ization process. Windtunnels

with a relatively uniform, horizontal airﬂow over the enclosed surface like environ-
mental wind speeds are recommended. The concentration increase of NH
3between
the inlet and outlet air along with airﬂow rate through the wind tunnel provides the
ﬂux rate.
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 31
Emissions of some pollutants, such as NH
3, are spatially very heterogeneous
(i.e. urine spots), and therefore many repetitions (>100) over the total emitting
surface are required to determine a robust average (Cole et al.,2008). Moreover,
most emission estimates based onﬂux chambers must be viewed with caution as the
temporal variability of emissions has also to be considered.
Advantages of chamber measurements are, among others, the low costs, ease of
use and theﬂexibility in application. Disadvantages are that climatic conditions are
affected and do not correspond to housing conditions. In addition, in the case of
surfaces in livestock housings, animal activity is excluded. Therefore, the results of
chamber measurements can only be treated as comparative values. Scaling up and
extrapolation to the entire housing is not permissible.
3.2.2 Direct Measurements of the Velocity by Anemometers
A naturally ventilated housing is characterized by large ventilation openings, which
are, depending on the continuously changing wind direction, acting as in- or outlets
or even both simultaneously. By installing anemometers measuring wind speed and
direction across those vents, the airﬂow rate can be determined in a direct way.
Multiplying the velocity vector perpendicular to the ventilation-opening plane with
the area of that plane results in the airﬂow rate. Knowing theﬂow directions across
the ventilation openings enables to differentiate between inﬂows and outﬂows.
Integrating across all outﬂows (or inﬂows) results in the total airﬂow rate through
the building. As in- and outﬂow should be equal, their difference is an indication of
the measurement accuracy. This possibility to‘self-check’is one of the method’s
biggest advantages compared to other, indirect methods. Although it is estimated
that with such setups a standard uncertainty of 25% can be achieved (Calvet et al.,
2013), the actual accuracy of the method cannot be determined as the true value of
the ventilation rate remains unknown.
Some s
s have already applied this seemingly straightforward technique with
satisfying results (Joo et al.,2014,2015). However, many questions remain to be
solved before such a method can be put into aﬁxed and clear protocol applicable to
the large diversity of housing geometries.
Practical and econom icconstraintslimittheamount ofanemo meters thatcanbe
deploy ed.Awell-thought -outdistrib utionofsensor sisthereforecrucial.However ,
thereisnoruleofthumbthatdictates these sample locations.Ingeneral ,the
ventilat ionopenin gsaredivided intoequal partswiththeanemometer splaced in
theircentres.Thenumbe rofpartsisdependen tontheamoun tofavailable sensor s.
Thisoftenresults inverylargesample areaswhere theairvelocitydistributio nis
assumedhomog enous andequaltothevelocitymeasuredinitscentres (Fig.3.4).

32 M. Hassouna et al.
Fig. 3.4The red circles show the locations of the ultrasonic anemometers; the green rectangles
represent the area of which the sensor is deemed representative. In this case, the focus lies on
measuring the horizontalﬂow distribution. Depending on barn geometry and windscreens, focusing
more on the verticalﬂow distribution might be a more correct approach
Considering only large openings (i.e. those found in most dairy farms) and a wind
direction perpendicular to these, some practice experiments and simulations have
proven this simpliﬁcation to be adequate (Janke et al.,2020a,b). However, wind
directions other than perpendicular increase the air velocity heterogeneity along the
length of the opening, resulting in a need for an increased sampling density (Van
Overbeke et al.,2016). Furthermore, such vents are often equipped with ventilation
screens allowing the farmer to effectively change the opening size. As measurements
should be taken as close as possible to the centre of the remaining opening, ideal
sampling heights could change throughout the day.
For future application in a wide range of practical circumstances, this method will
need to rely partly on airﬂow models. Based on building geometry and meteorologi-
cal conditions, those models will provide a conversion factor accounting for the
heterogeneous velocity distribution in the vents. For prototype applications, com-
parison of inﬂow and outﬂow as the self-check will be able toﬁlter out the most
unreliable measurements.
3.2.3 Balancing Methods (Internal Tracer Methods)
TheCO
2balanc eapproac hisanaffordablealternative methodtoestimat etheVRof
animalhouses, inparticula runder naturalventilat ion.Themethodhasbeenwidely
presen ted(Blanes &Pedersen ,2005;Liuetal.,2016;Samer etal.,2012)andhas
been implem ented forthequantiﬁcationofemissi onsfrom different animal
catego ries(Estelles etal.,2011;Pereira andTrindad e,2014).

Total heat per house×Ventilation flow per hpu
Þ
Þ
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 33
The method relies on the hypothesis that the ventilation rate determines the
relationship between CO
2production in the housing and the difference in CO2
concentrations between the inside and outside of the housing.
The ventilation rate is calculated as follows:
Ventilation rate=
1000
where
Total heat per house=total heat producedfor
the entire house, hpu.
Ventilationﬂow per hpu=Ventilationﬂow per heat production unit and 1hpu is
1 kW in total animal heat production at 20°C.
Ventilationﬂow per hpu will vary in function of animal activity at different times
of the day and CO
2concentrations difference between indoor and outdoor:
Ventilation flow per hpu=
c×Relative animal activityð
CO
2,indoors-CO2,outdoorsð ×10
-6
where
c=CO
2production, (m
3
h
-1
hpu
-1
); this factor varies in function of animal type
(Pedersen and Sällvik,2002; Pedersen et al.,2008).
CO
2,indoorsandCO 2,outdoors=Measured indoor and outdoor carbon dioxide
concentrations at time h (in ppm).
The accuracy of this method relies on the accuracy of the metabolic rate data of
the animals and the amount of CO
2released by other sources inside the housing
(e.g. soiled areas, slurry storage, solid manure). Pedersen and Sällvik (2002) propose
models to calculate total heat production for different animal categories. Liu et al.
(2016) compared modelled and measured CO
2production rates and concluded that
values were generally in agreement for different animal species, and the standard
deviation of model residuals was about 20% to 30% of the average measured CO
2
production rate except dairy cows. When using the carbon dioxide balance method
to estimate the hourly ventilation rate, it is necessary to correct for the animal
activity.
The C
2balance method has its application limits with very large air exchange
rates and high wind speeds occur or when the required gradient of CO
2concentration
between inside and outside is not fulﬁlled. An in-depth analysis of concentration
variability in time and at sampling locations in dependence on the variables affecting
emissions (e.g. microclimatic conditions, barn management and animals’routine) is
needed prior to proceeding with emission computation, especially for open buildings
(D’Urso et al.,2021i
ress).
Another appli cation limitistheneedtoconsider CO
2fromsolidmanur eand
gas/fuelheatingsystems inthecalculations. TheCO
2product ionfromsolidmanur e

is not well documented, and a huge variability can be observed in the function of the
characteristics (biological, chemical and physical) of the solid manure. Concerning
the CO
2production of gas/fuel heating systems, it’s unusual to have gas counters
with aﬁne time step in an animal house or an individual gas counter for a house. The
CO
2due to the use of gas/fuel for heating at the beginning of the batch is signiﬁcant
compared to animal CO
2production.
34 M. Hassouna et al.
Moreover, it is not possible to rely on the concentration measurements without
using a limitation method for concentrations. For example, Wang et al. (2016)
neglected CO
2concentration differences lower than 70 ppm, whereas Van
Ouwerkerk and Pedersen (1994) suggested that CO
2concentration gradients should
not be lower than 200 ppm for the method to yield reliable results.
Currently, several (governmental) measuring campaigns mainly on dairy
housings are running using the CO2 balance method (e.g. in the Netherlands,
Germany, Denmark), but it should be noted that this method is not accepted as a
reference method in all countries as, for instance, in Flanders where the Flemish
Scientiﬁc Team deemed this method insufﬁciently reliable to establish representative
data for a yearlong emission behaviour of dairy housings.
3.2.4 External Tracer Ratio Methods
External tracer methods are established to quantify ventilation rates or emissions
from naturally ventilated livestock housings with or without an outdoor exercise area
as well as from other areal or point sources (e.g. Greatorex,2000; Schneider et al.,
2005; Schrade et al.,2012; Mohn et al.,2018; Ogink et al.,2013). According to
Ogink et al. (2013), three tracer gas release techniques can be distinguished:
(i) constant injection method, (ii) concentration decay method and (iii) constant
concentration method. The constant injection (e.g. Schrade et al.,2012; Mohn et al.,
2018; Edouard et al.,2016; Van Duinkerken et al.,2011) and the concentration
decay method (e.g. Schieﬂer,2013; Schneider et al.,2005) are common for
measurements in livestock housings.
For t
onstant dosing method, a known massﬂow of an artiﬁcial tracer gas is
dosed into a ventilated building or more generally close to an emitting areal/point
source. This tracer gas mimics the dynamicﬂow and the dilution of the target gas
(es). The underlying principle for the tracer gas method is the law of conservation of
mass of both target and tracer gases. The ventilation rate is thus calculated using the
known massﬂow of the injected tracer gas and the concentration ratio of the tracer
gases to the target gas (e.g. NH
3). For the tracer decay method, a dose of tracer gas is
injected and mixed into the housing until a set and uniform distribution of the tracer
gas is reached. Then the injection is stopped, and the decrease of tracer gas
concentration is recorded during a given period to calculate the ventilation rate.
Theba sicrequirementsfortheexternaltracermethodsareagoodrepresentation
oftheemissi onsource bythetracergasrelease aswellasagoodmixing oftracergas
andtargetgas,which enable sacompa rabletransfer ofboth,tracergasandtargetgas
fromtheemissi onsource tothesamplingpoints(Fig.3.5).Anartiﬁcialtracer gas

should be safe, inert (in relevant time-scales), perfectly mix with air (similar density),
easily measurable, not available in ambient air at high concentrations or emitted
close to the housing and inexpensive (Phillips et al.,2001). The most common tracer
gas used in livestock housings is sulphur hexaﬂuoride (SF
6) (e.g. Snell et al.,2003;
Berry et al.,2005; Van Duinkerken et al.,2011; Edouard et al.,2016). In addition, a
second tracer gas (e.g. triﬂuoromethyl sulphur pentaﬂuoride, SF
5CF3) has been
applied (e.g. Mohn et al.,2018; Schrade et al.,2012) to quantify emissions
in a
separated compartment or outdoor exercise area.
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 35
Fig. 3.5Schematic drawing of the‘constant dosing’tracer gas method, with tracer dosing close to
area source of the target gas and integrative sampling of tracer/target gas in well-mixed air
Advantages of the external tracer gas method compared to the CO
2balance are
that it is more robust at very low and high wind speeds and can also be used for housings with high ventilation rates, for example very large air exchange openings
and housings with outdoor exercise areas.
3.2.5 Tracer Gas Dispersion Method
Thetracergasdispersionmethod(TDM) hasbeenusedtomeasurefugitive methane
emissi onsfromareasource ssuchaslandﬁlls(Galleetal.,2001;Mønster etal.,2015;
Scheutz etal.,2011),compo stingplants (Andersen etal.,2010),wastewater treat-
mentplants (Delre etal.,2017)andbiogas plants (Scheut z&Fredens lund,2019)
andtoalowerextend fromfarms(Arndt etal.,2018).Themethodreliesonthe
continuousreleaseofagaseous tracer ataknown,contro lledrelease ratecombined
withcross-plume measurements ofCH
4andtracer gasesusingamobileanalytical
platform (Fig.
3.6).Theuseofagaseous tracer removesthedepend enceonatmo-
sphericdispersionmodels andmeasurementsofwindspeed, etc.,andthetracergas
canprovideaconﬁrmation thattheobserv edmeasuredplume originate sfromthe
targetsource andnotanother, nearby source .Thetracergasneeds tobereleasedat
thelocationwhere CH
4isemittedfromthefarm, forexamp lefromtheanimal
housingandmanur estorages.Anexact CH
4source simulation becom esofless
importan cewithi
ncreasing measuring distances (~1km).Anymisalignme nt
between farmmethaneemissions andtracergasreleasewillbevisible fromthe
real-tim eplumemonitoring, andthelocation ofthetracergasreleasepointscanbe
adjustedduring themeasurements.

36 M. Hassouna et al.
Fig. 3.6Example of plume measurement at a pig farm with acetylene used as tracer gas. The red
arrow indicates the wind direction. The peak concentrations above background were 27 ppb for CH
4
and 6.6 ppb for C
2H
2. The measurements included both the animal housing and the external manure
storage on this example
The use of TDM requires a trained operator capable of adjusting to conditions at
each measurement location according to observed nearby CH
4sources, wind speed
and direction, available measurement locations and more. A correct use of the
method has been proven to provide determination of release rates with errors
generally below 10–15% in controlled release experiments (Fredenslund et al.,
2019). The guideline for best practices consists of three steps: area screening for
target gas concentrations; screening of atmospheric target gas concentrations at the
farms surrounding, in order to identify external sources, andﬁnally, tracer gas
release and plume traverse measurements (Scheutz & Kjeldsen,2019)
cetylene
and ethane can be used as tracer gas for this type of target sources, considering that
there will not be other sources at the farm emitting them. N
2O, another common
tracer gas, is not suitable, as it is produced in livestock housings (Samuelsson et al.,
2018).
Differe ntly fromtheexternal tracermethod,thetracerdispersionmethodisused
tomeasurethetotalfarmemission, andthemeasurements aretaken atahigher
distance fromthefarmtoallowforsufﬁcient mixingbetweentracerandtargetgases.
Applica tionoftheTDMforanimalhousing arelesscomplex, andsimulation ofthe
source sismorestraight forward incompa risontofacilitiessuchaslandﬁllsbecause
source sareknown.There areafewstudiesusingTDMtomeasureemissi onsfrom
livestock operation (Arndtetal.,2018; Daubeetal.,2018),andthesestudies were
focuse donCH
4quantiﬁcation,venhough,nrincipleheethodanequally

C-C
applied to NH3or N2O emissions. Individual target gas sources can be quantiﬁed as
long as located at an appropriate distance from other sources or with the help of two
different tracer gases (Arndt et al.,2018; Scheutz et al.,2011). Additionally, access
to the farm is necessary to place the tracer gas close to the sources; however, the
technique does not affect activities at the farm. Longer-term measurements are more
labour-intensive; hence, short-term measurements might be more practical.
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 37
3.2.6 Inverse Dispersion Method (IDM)
The inverse dispersion method (IDM) for emission quantiﬁcation from stationary
emission sources related to livestock production such as housings, feedlots, pastures
and manure stores has attracted increasing interest in recent years (Flesch et al.,
2005; Claußet al.,2019) due to high accuracy, simplicity andﬂexibility in the
application ofﬁeld measurements (Ro et al.,2013). IDM is based on a dispersion
model which relates the concentration within the dispersion plume to the simulated
emission. The determination of the emissionﬂuxQis achieved by relating the
difference between the measured concentrations upwind (C
UW, background concen-
tration) and downwind (C
DW) of the emission source to a modelled dispersion factor
D(following equation, Fig.3.7).
Q=
DW UW
D
The most often used dispersion model for IDM to determine D is a backward
Lagrangian stochastic (bLS) model described by Flesch et al. (2004). Free available
software/code of the bLS model are‘WindTrax’(Thunder Beach Scientiﬁc, Halifax,
Canada;www.thunderbeachscientiﬁc.com) or bLSmodelR (Häni et al.,2018,https://
github.com/ChHaeni/bLSmodelR).
Fig.3.7Schematic overview oftheprinciple oftheinverse dispersion method (IDM). Given isan
emission plumefromaspatial limited source withconcentration measurements up-/downwind of
thesource andmeasurements oftheturbulence characteristics

38 M. Hassouna et al.
The dispersion factor D is determined as a function of the measured near-ground
turbulence characteristics and the precise spatial determination of the emission
source and of the positions of the concentration measuring devises. For the concen-
tration measurements, it is advised to use open-path line integrated devices instead of
point sensors (Flesch et al.,2004). A common temporal resolution of the IDM results
is 30-min averages.
The applicability of the IDM depends on the speciﬁc settings of the emission
source, for example farm buildings (Flesch et al.,2005). Sites with complex terrain
with slopes and obstacles like trees and important emission sources of the target gas
in the surrounding area must be avoided. A situation with a prevailing wind direction
is advantageous. Sufﬁcient open terrain in the surroundings is required allowing to
set up the devices for concentration and turbulence measurements in a distance of at
least ten times the maximum source height (e.g. housing) downwind of the emission
source (Harper et al.,2011) to ensure that the measuring devices are outside the
disturbed turbulenceﬁeld. The height of the instruments above ground must be at
least three times the canopy height. The surface between the emission source and the
measuring devices needs to be homogeneous, for example crops with different
heights must be avoided.
Given that these requirements are fulﬁlled, IDM can be easily employed with
relatively inexpensive equipment. Access to livestock buildings or the farmyard is
not necessary. Total emissions from various sources, for example housings of
different livestock animals, outside yards and manure stores are captured. Distinc-
tion between individual sources (e.g. housing, manure store) is difﬁcult or impossi-
ble, however. Sticky gases like NH
3are deposited between the emission source and
the concentration measurement device which requires a correction by, for example
using a bLS model which includes a correction for deposition (Häni et al.,2018).
IDM implies substantial data loss due to excluding data from measuring intervals,
where the micrometeorological requirements are not fulﬁlled. To compensate for
this, measurement periods of sufﬁcient lengths are needed, i.e. in the order of 5 to
20 consecutive days.
3.3 Adapting Measurement Methods and Approaches
to the Measurement Purpose
As already indicated above, the quantiﬁcation of animal housing gas emissions
meets various objectives:
Studying formation and release processes (e.g. NH
3from surface areas, CH4from
ruminants).
Devel
r veriﬁcation of mitigation measures and strategies (e.g. to certify the
effectiveness of emission reduction technologies).
Compar ative quantiﬁcationofemissions fordifferent systems ,processes or
product s.

Providing emission factors for environmental assessment and emission inventories
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 39
(e.g. to comply with nationalemission ceiling and with IPPC regulations) and
environmental assessment.
Monitoring and veriﬁcation compliance with emissions threshold (e.g. to permit
regulation purposes at farm level, including compliancy with restrictions
linked with local impacts for example nature sensitive areas as identiﬁed by
NATURA2000).
Each measurement objective does not require the same level of uncertainty on the
results, the same measuring concept, the same measurement conditions and the same
number of measurement campaigns. The measurement concept may include the
setup (location of sampling points, type of analytics, uncertainties, etc.), duration
and temporal resolution of the measurement(s), the number of farms, documentation
of accompanying parameters, etc. Moreover, depending on the objectives, the
protocol implementers will have different levels of skills, more or less high budgets
to devote to the measurement. All these elements must be considered when choosing
a measurement method.
If the aim of a study is to understand the emission processes and to identify the
inﬂuencing parameters (Aarnink et al.,1995) or to develop mitigation techniques
and practices (Jeppsson et al.,2021), the implemented instruments should have
acquisition frequencies, detection thresholds, detection range in adequacy with the
dynamics and intensity of the emission processes. The associated costs related to
measurement equipment, consumables and time spent can be quite high. In addition,
the measurement approaches and methods for relative comparisons may differ from
those aiming at absolute values. Moreover, different kind of methods could be
implemented simultaneously (for instance, CO
2balance and external tracer gas for
ventilation rate quantiﬁcation) for cross validation of the emissions measurements.
In the same idea, different types of sensors are generally used simultaneously to
validate observations and for the interpolation in the case of missing or biased
measurement.
The d
m ination of accurate emission factors representative of a class of
animal housing or production systems requires to multiply emission measure-
ments in a large number of farms/housings in the same class to appreciate the
intra-class variability (e.g.‘farm effect’), to ensure the relevance of the different
classes and to cover seasonal effects (e.g. Aarnink & Ogink,2006; Schrade et al.,
2012; VERA,2018). It requires emission measurements on several farms in different
seasons.
Methods thatrelyonintermitt entmeasurements areparticula rlyadapte dtothis
objective.Dekocketal.(2009),Guingand etal.(2011)andHassouna etal.
(2010)develo pedsuchmethodstoreduce costsandenable largemeasurem ent
campa igns.Theyﬁrstidentiﬁedthemostsuitable daysandtheminim umnumbe r
ofmeasurementdaysoverthebreedingperiodbyevalua tingthedifference between
emissi onscalculated fromintermittent measu rement withcontinuous measurement
(Table3.3).

40 M. Hassouna et al.
Table3.3Differences (in %) of cumulated emissions between continuous measurements (CE) and
intermittent measurements (2 or 3 days during the rearing period) in a fattening pig room
CO
2_C
CH
4_C NH
3_N N
2O_N H
2O
CE(kg/breeding room)3514 44.9 41.2 1.0 15325
With 2 measurement days
D15,95 5.7 -8.5 -24.1 -9,2 27.0
D25,60 5.9 -24.2 -15.5 -16.3 -8.8
D25,80 5.8 -12.2 -15.0 -5,1 -16.6
With 3 measurement days
D25, 60, 95 5.6 1.0 -9.7 -5.1 16.4
D25, 80, 95 5.5 10.6 -9.3 3.1 10.8
D25, 60, 80 5.7 -9.4 -15.3 -2.0 -10.4
D25, 80,110 5.3 25.2 32.3 7.1 -17.2
Guingand et al. (2011 )
Intermittent measurements can also be recommended to test the environmental
efﬁciency and operational stability of a range of environmental technologies to
mitigate gas emissions for livestock production. The VERA cooperation proposes
protocols for housing (https://www.vera-veriﬁcation.eu/test-protocols/) that
recommended six independent measurement periods of at least 24 h distributed
over 1 year, depending on the emission pattern.
In any case, the measurement methods and concepts have to be adapted to the
respective housing system (ventilation rate, with/without outdoor exercise area, etc.)
or system boundaries (partial areas, housing, whole farm). Particularly in the case of
growing animals, the measurement periods have to be selected to ensure the repre-
sentativeness of the measurements (VERA,2018). Of course, the measurement
method and concept have to be adapted to the target substance(s), the emission
source (soiledﬂoors, animals, feed, etc.) andﬁnally comply with the available
resources (ﬁnancial, personnel, equipment, skills, experience, etc.).
3.4 Coupling Measurement and Modelling
As implied in the description of the main measurement methods, the selection and
adaption of methods for emission monitoring from livestock houses involve to some
extent model assumptions. When emissions are measured, usually one is limited in
temporal and spatial resolution and boundary conditions dependent on the speciﬁc
housing system. This results in signiﬁcant uncertainties. Modelling of airﬂow and
emission processes can add valuable knowledge for the assessment of measured
concentrations and volumeﬂows. Moreover, it can support a suitable selection of
measurement resolution and distribution (both in time and space), and it permits to
ﬁll gaps in measurement data. On the other hand, accurate measurements are the
basic requirement for the development and validation of meaningful models. Obvi-
ously, the synergy works here in both directions (Fig.3.8)

3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 41
Fig. 3.8Synergy works
between modellingand
measurement
3.5 Information Gaps to be Addressed by Different Modelling
Approaches
There is a huge variety of models with different degree of complexity that are used in
the context of emissions from livestock housing: from simple empirical relations to
complex systems of chemical and/or physical equations. Usually, the applied models
are deterministic (i.e. given initial and boundary conditions, the model output will
always be the same). However, there is also a possibility to include stochastic
(i.e. random) elements in the models to mimicﬂuctuations that cannot be explained
by the model. Moreover, models can be empirical (i.e. data-driven) or mechanistic
(i.e. process-oriented). Often, particularly complex models are a mixture of both–
the so-called semi-mechanistic models. Depending on the information gap in the
measurement that should beﬁlled, different types of models and modelling
approaches are suitable (Table3.4).
A l
tion in temporal resolution means that the measurements are not carried
out continuously over a long period that reﬂects all possible climate conditions and
production stages. In most cases, the measurements are carried out in some shorter
campaigns with a duration of several days spread over a period of, for example one
production cycle for pigs or 1 year for dairy cattle. Models based on the measure-
ment data can help to reconstruct the missing data and toﬁll the temporal gaps (Saha
et al.,2014)
n this context, particularly empirical models are employed.
Alimitati oninspatial resolutionmeans that,duetoeconom icorpractical reason s,
therepresentat ivesamplingofgasconcent rations andother accom panyin g
parametersisnotoronlywithgreateffort possib le.Thisconcern s,forexamp le,
measurements innaturallyventilated barns, where gasconcent rations aredistributed
highly heterogeneous lyandthedispersio npatternchanges rapidly intime.Theuse
ofmodelswithgreatspatial depth ofdetailcanhelpinthesecasestopredeﬁnethe
mostrepresentat iveposition sforsensor s.These modelscanalsobeusedfor
situations,where ameasurementistechnicallynotpossible,forexample inthe
manur estorage under slatted ﬂoors orintheanimal-occupied zone.

Model type Principle
(continued)
42 M. Hassouna et al.
Table3.4Models and modelling approaches suitable for gapﬁlling in measurements
Modelling
approach
Area of
application
Pros, cons and
crucial aspects
Mathematical
empirical
model
Interpolation
m
odel
Purely data-
driven toﬁll gaps
in time and/or
space (e.g. gas
concentrations,
emission values)
Based on value of
the variable at
adjacentlocations
or
time points
intermediate
values are
estimated
Measured values
are exactly kept;
no
additional
variables needed;
should not
be
used for
extrapolation; for
temporal and
spatial gaps, not
for missing
boundary
conditions; very
fast
Regression
modelling
Purely data-
driven; e.g. air
exchange, gas
concentrations,
emission values
Based on some
explanatory
variables that are
monitored with
higher resolution
values of the
response variable
are
estimated
Measured values
are
approximated;
explanatory
variables are
employed; should
not be used for
extrapolation; for
temporal and
spatial gaps, not
for missing
boundary
conditions; rather
fast
Mathematical
mechanistical
model (see
Chap. 2 for
further details
and examples)
Biochemical
modelling
Process-based,
usually with data-
driven submodels
derived by
regression;
e.g. NH
3from
urine puddle or
manure storage,
CH
4from
rumination or
manure storage
(Differential)
equation system
built up on basic
chemical
relations, time
courses
dependent on
explanatory
variables
Speciﬁ c for an
emission source
and a gas;
bottom-up
approach,
upscaling to
on-farm
conditions tricky;
for missing
boundary
conditions and
temporal gaps;
rather fast
Numerical
ﬂuid-
dynamics
modelling
Process-based,
with partly data-
driven
submodels; for
airﬂow, air
exchange and gas
orparticle
transport
processes
(steady
state ortransient)
(Differential)
equati
on system
built up on basic
physical relations,
spatial
distribution
(partly with
temporal
ﬂuctuation) for
given initial and
boundary
conditions
Focus on airﬂow;
top-down
approach, local
emission strength
must be a priory
speciﬁ ed; time-
consuming

Model type Principle
3 Measuring Techniques for Ammonia and Greenhouse Gas Emissions... 43
Table 3.4(continued)
Modelling
approach
Area of
application
Pros, cons and
crucial aspects
Physical
model
Wind tunnelPurely process-
based;
e.g. airﬂow
pattern or
dispersion of gas
withina
particular
geometry
Based
onﬂuid
dynamical laws of
similarity scaled
models are
measured
Lab-scale,
upscaling to
on-farm
conditions tricky;
for
missing
boundary
conditions and
spatial
gaps; time-
consuming
A limitation in boundary conditions dependent on the speciﬁc housing system
means that measurements are usually carried out in one or a few more examples of a
housing system. The variability among the respective housing system (building
envelope, climatic conditions, ridge or cross ventilation, etc.) and operational man-
agement (variable screen openings, scraping frequency, etc.) cannot be represented
during this procedure. Here, models can be used to compare different building
designs or management options. Moreover, the potential of speciﬁc emission reduc-
tion measures can be tested before setting up on-farm trials.
3.5.1 Example Applications
3.5.1.1 CFD Modelling for Sample Point Selection
Theemissionrateofabarnisoftendeterminedastheproduct ofairexchange rate
andgasconcent ration difference between indoor andoutdoor. Theairexchange rate
ofhousingcanbedetermined directly bymeasuringairvelocitiesatallinletand
outletopening sorindirectlybyusingatracergasmethod. Because ofthespatialand
temporalvariation sofairﬂows aswellasnon-per fectmixing oftargetgaswith
indoor air,themainproblem thatoccurs whenplanning measurementsisthedensity
andposition sofsamplingpoints.Itisimpracti caltoinstall numer oussensors overall
theopenin gsorinside thebuilding. Therefore,direct andindirectmethods to
estimat eairexchange ratesrequirerepresentative samplingposition sforairvelocity
orgasconcentrati on.Thoseshouldrepresentmeanvalues attheopeningareasorof
thebuildingvolum e.CFDmodellingprovides analternative approac htocalculate
thewhole airﬂowandgasconcentration ﬁelddatainandaround buildings ,i.e.data
ontherelevantparametersinallpoints ofthecomputation aldomain(Arcidiacono &
D’Emilio,2006; Tomase lloetal.,2021).Insome researchintheﬁeld,thebest
ventilat ionandthelowest temperatures attheanimallevelinopen-s idedbarnswere
describ edbyusingCFDsimulations andin-barnassessment throughspeciﬁcexper-
imental tests(Arcidiacono &D’Emilio,2006;Tomase lloetal.,2021).Moreo ver,
CFD-ba sedengine eredsolutionsreported instudies concerning thereductionofheat
stressinhotclimate condition swerereviewed(Arcidiacono,2018). CFDprovides

possibilities of determining the representative sampling positions for laboratory or
ﬁeld measurements by analysing spatial and temporal distributions of airﬂow and
gas (Tabase et al.,2020a). Furthermore, this distribution pattern depends on the
amount and locationof
fresh air entering the barn as well as the source strength of
emissions. CFD modelling is then able to perform parametric study toﬁnd out
inﬂuencing factors of the airﬂow and gas concentration distributions and therefore
contribute to the selection of representative measurement positions. Firstly, the
indoor spatial distribution of the target gas is predicted by a validated CFD model.
Secondly, the average concentration inside the barn is calculated, and the tolerance
levelaroundaverageisdeﬁ
ned. Then, the representative sampling positions/area
within the barn is identiﬁed by analysing the velocity/concentration at, for example,
the horizontal sections of the whole space at certain distances along the building
height. Finally, a common spatial representative sampling area which applies to
different barn designs or weather conditions might beobtained by incorporating all
results of the parametric
study.
44 M. Hassouna et al.
3.5.1.2 Regression to Fill Data Gaps
Based on observations of explanatory variables, regression models predict, for
example, the dynamics of greenhouse gas or ammonia emissions (Fig.3.9). This
permits toﬁll gaps in emission values in the course of time as a consequence of
temporally spare measurement strategies or device failures.
While gas concentration and airﬂow measurements in housings are mainly
monitored during a few interim measurement campaigns, other variables, which
affect the emission value, are monitored continuously at farms. These potential
Fig.3.9Example ofdatagapﬁllingbased onamultilinear regression model withoutdoor
temperature (T),outdoor winddirect (WDasacyclic variable), outdoor windspeed andmilk
yield. (From Willink etal.,2020)

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Technology For Environmentally Friendly Livestock Production Thomas Bartzanas

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