Analysis of the marginal abatement cost curve for ammonia emissions: addressing farm system heterogeneity

Abstract

Agriculture is responsible for 99.4% of ammonia (NH₃) emissions in the Republic of Ireland and the country has failed to comply with limits set down by the European Union National Emissions Ceiling Directive (NECD) for 9 of the last 11 reporting years. Hence, there exists an urgent need to reduce NH₃ emissions to control air pollution and moderate other related environmental and health hazards. This study carries out farm-level marginal abatement cost curve analysis across different farm typologies in the Republic of Ireland. The study also addresses the interactions amongst the considered abatement options and explores the presence of farm system heterogeneity. This allows an assessment as to whether it is sub-optimal to adopt a mitigation measure across different farm systems. Findings indicate that the measures examined in this study are effective in abating NH₃ emissions at varying levels across the different farm typologies. Ammonia mitigation measures such as liming, switching to protected urea and a crude protein reduction in livestock diets were primarily cost-saving while the increased clover measure moved between cost-saving and cost-positive depending on the farm system type. The presence of heterogeneity across the farm typologies was generally supported in this study, highlighting that optimal policy design should be tailored to reflect farms’ characteristics. Furthermore, a lower abatement potential was reported for the combined implementation of selected mitigation measures compared to the sum of individual measures due to interaction effects.

Main article text

Introduction

Sustainable food production encompasses the “shared responsibility for the production, supply, and consumption of safe and nutritious food while simultaneously protecting the natural environment and quality of life now and into the future” (Bord Bia, 2020). The quest to achieve sustainable food production is the central aim of many national and global communities. However, improving food production to attain food security and providing an acceptable welfare status for farmers sometimes come at the detriment of the environment as agricultural activities may lead to environmental degradation (Buckley & Donnellan, 2020). Actions are therefore sometimes required to minimise the negative environmental influences, such as greenhouse gas (GHG) and ammonia (NH₃) emissions, water pollution and biodiversity loss associated with agricultural production.

Agriculture is an important source of gaseous emissions accounting for approximately 85% of all NH₃ emissions globally (Bouwman et al., 1997; Zhang et al., 2011; Xu et al., 2018). In the Republic of Ireland (henceforth called Ireland), agriculture accounts for 99.4% (shown in Figure 1) of total NH₃ emissions (Hyde et al., 2021). The European Environmental Agency (EEA, 2020) indicated that the poor air quality in Ireland results in >1,300 premature deaths/yr. Other negative consequences of NH₃ emissions include the destruction of aquatic, plant and forest ecosystems through increased acidification of land and waterbodies (EEA, 2019a,b).

Figure 1.

Trend of ammonia (NH₃) emissions in the Republic of Ireland between 1990 and 2021. Source: EPA Ireland’s Air Pollutant Emissions 1990–2030 report (EPA, 2020, 2021, 2022, 2023), EPA Ireland’s Informative Inventory Report (Hyde et al., 2021, 2023) and Central Statistics Office Environmental Indicators Ireland Data (CSO, 2021, 2023). EPA = Environmental Protection Agency; NEC = National Emissions Ceilings.

The European Union (EU) National Emissions Ceilings (NEC) Directive sets limits for NH₃ emissions at the Member State level. Ireland was initially allocated a fixed annual emissions ceiling of 116 kilotonnes (kt) of NH₃ (NEC Directive 2001/81 EC) which continued to be applied until 31 December 2019. Beginning in 2020, Article 4(1) of Directive 2016/2284 set down new national emission ceilings for each EU Member State for the years 2020–2029, and from 2030 onwards. These new targets have to be achieved relative to the levels of emissions in the base year of 2005. For Ireland, these reduction commitments currently equate to a limit of 118.95 kt NH₃/yr (1% reduction)¹ to be achieved in the 2020 commitment period and a 114.14 kt NH₃/yr (5% reduction)¹ to be achieved in the 2030 commitment period. Thus, there is an urgent need to reduce NH₃ emissions from agriculture since it is the predominant emission source. Figure 1 below shows the trends in national NH₃ emissions from 1990 to 2021. According to the Irish Environmental Protection Agency (EPA, 2022), Ireland has failed to achieve its NEC Directive target for NH₃ in 9 of the last 11 yr.

The research question being investigated in this study is whether both environmental and farm-level economic models can be combined to generate a cost-effectiveness estimate of abatement options for NH₃ emissions across the different farm system types. The marginal abatement cost curve (MACC) methodology is a technique used to assess the abatement potential of different abatement options and the relative cost associated with implementing a measure. It can potentially suggest an economically optimal mitigation level (Bockel et al., 2012).

Another function of the MACC is to rank abatement options from those measures that are cost-saving, cost-neutral, cost-effective to cost-prohibited. Cost-saving measures reduce emissions and costs; cost-neutral measures reduce emissions but are cost-neutral; cost-effective measures reduce emissions but are cost-positive but effective to adopt based on the shadow price of the emissions; and cost-prohibited measures reduce emissions but are not cost-effective to implement based on the shadow price of emissions.

Many studies (MacLeod et al., 2010; Moran et al., 2011; Bockel et al., 2012; Hou et al., 2019) have adopted the use of the MACC methodology to study the abatement of gaseous emissions. However, the focus has principally been on GHG and not NH₃. In Ireland, a few studies (Lanigan et al., 2015; Buckley et al., 2020) investigated the abatement of NH₃ emissions using the MACC methodology, but these studies were at the national aggregate scale and may not provide a nuanced understanding of marginal costs for particular farm system types. Other studies (Holly et al., 2017; Wang et al., 2017) assessed the farm-level abatement of NH₃ emissions in the USA and China but focused only on dairy and swine farms, respectively. In contrast, this study examines the effect of measures across a number of farm system types simultaneously.

This paper hypothesises that NH₃ mitigation measures will impact farm systems differently and efficient public policy dictates that any measures that are promoted must be cost-effective. Policies that fail to recognise heterogeneity in costs and effects are unlikely to be efficient. Therefore, this research assesses the cost-effectiveness of potential NH₃ mitigation measures across all of the dominant land-based farm system types in Ireland. In this context, this paper seeks to address the following research questions: (1) Is the ranking of mitigation measures consistent across farm system types?, (2) Is the cost-effectiveness of mitigation measures significantly different across different farm system types?, and (3) Is the abatement potential from the sum of individual mitigation measures significantly different from that when all measures are implemented simultaneously?

Methodology

Nitrogen flow framework

The nitrogen (N) in manure tends to be converted to NH₃ through bacterial degradation, primarily through urease, an enzyme produced by microorganisms in faeces that reacts with urinary urea to form NH₃ (Ishler, 2016).

Following the N flow model proposed in the EMEP/EEA Emission Inventory (EEA, 2019a,b, 2023), Figure 2 illustrates where NH₃ emissions occur at different stages of the manure management chain. In this study, these stages are broadly classified as the manure management measures and chemical fertiliser-based measures.

Figure 2.

Framework of nitrogen (N) flow adopted in the MACC analysis. Source: adapted from Buckley et al. (2020). LESS = low emission slurry spreading; MACC = marginal abatement cost curve; NUE = nitrogen use efficiency.

Along the manure management chain, NH₃ is emitted through the animal housing, slurry storage and slurry spreading stages. Abatement measures thus work by reducing NH₃ emissions at a specific stage of the N flow chain. The implementation of abatement measures can occur at different stages of the production chain; for instance, the reduction of crude protein in the diets of dairy cows is applied during feed intake to reduce the N excreted by livestock. In this case, the abatement measure is classified as an individual abatement measure, referred to here as a “standalone measure”. Alternatively, the reduction of NH₃ can occur at multiple stages of the manure management chain and/or the fertiliser point simultaneously.

The combined implementation of two or more measures such as reducing crude protein in diets and using protected urea may result in a reduction of NH₃ emissions at the manure management chain and at the fertiliser point; this is referred to as a combined measure. It is noteworthy that the implementations of the abatement strategies at the different stages are interdependent and are not strictly additive (Webb et al., 2005). Webb et al. (2005) emphasised the importance of reducing NH₃ emissions at each stage of manure management, due to the loss of NH₃ emissions at the housing, storage and spreading stages of the manure management chain.

In addition, abatement of NH₃ emissions along the manure management chain is increased because of increased nutrient use efficiency/recovery associated with the manure based measures, thus reducing the requirement for chemical fertilisers.

Data

Following the Environmental Protection Agency (EPA) national inventory accounting-based methodology (Duffy et al., 2020), the total farm NH₃ emissions across different farm activities are calculated as a vector of the activity data (A) on a farm (i) multiplied by an emission factor (E) for the particular source (e.g., housing, storage and land spreading for manure management, shown in Appendix Table A1) as set out below.

(1) $${\text{Total}\hspace{0.17em}\text{NH}}_{\text{3}}\hspace{0.17em}\text{Emissions}={\displaystyle \sum _{i=1}^n(A_i\ast {\text{NH}}_{\text{3}}E)}$$

Data on emission factors were obtained from the Irish National Inventory Report (Hyde et al., 2021, 2022, 2023) and farm-level activity data were obtained from Teagasc (Irish Agricultural and Food Development Authority) National Farm Survey (NFS) 2020 dataset which is part of the EU Farm Accountancy Data Network (FADN). The EU FADN obtains data relating to business and farm incomes of agricultural enterprises from farms across the EU.

This involves sampling about 80,000 farm holdings, out of a population of approximately 5 million farms across the EU. Physical and structural (e.g., livestock number) data are also collected which are increasingly used to create sustainability indicators (Hennessy et al., 2013). The data collected in the FADN sample, when population-weighted, reflect about 90% of the total cultivated agricultural area and approximately 90% of the total agricultural production of the EU (DG AGRI and Eurostat, 2020). The Teagasc NFS data are nationally representative and generally report results across five farm systems: specialist dairy, cattle production, specialist sheep, specialist tillage and mixed livestock systems. Pig, poultry and very small farms are not included in the NFS. The NFS represents approximately 90% of the agricultural area in Ireland (DAFM, 2023).

For a detailed explanation of the different farm types, see Table 1. Farms are randomly selected into the sample by the Central Statistics Office of Ireland based on farm size and system to be representative of farms across the population. Each farm attracts a population weight, which indicates the number of farms across the population that it is selected to represent. Activity data are collected on NFS farms across a range of areas including animal inventories, land and cropping area, manure management practices, chemical fertilisation practices and technology adoption.

Table 1:

Description of farm typologies

Farm type	Description
Specialist dairying	Dominant enterprise is milk production
Cattle	Involves both cattle rearing and cattle other systems of production Cattle rearing: ≥50% of the standard output is derived from suckler cow-based activity Cattle other systems: ≥50% of the standard output is derived from the rearing and fattening of livestock (non-suckler cows)
Sheep	Dominant enterprise is sheep
Tillage	Dominant enterprise is cereals or root crops
Mixed livestock	Some combination of grazing livestock (dairy, cattle, sheep) or grazing livestock combined with a crop enterprise Dairying tends to be the main livestock enterprise

Source: Buckley et al. (2015).

Table 2 provides summary statistics for farms within the sample. It shows that the farm size of the cattle and sheep farm types is smaller relative to the other farm types. The farms are categorised based on the dominant enterprise practised based on gross output and need not exclusively be the only activity being carried out on the farm (Buckley et al., 2015; DAFM, 2023).

Table 2:

Profile of farms from the National Farm Survey 2020 data

Parameters	Farm types
	Specialist dairy	Cattle	Specialist sheep	Tillage	Mixed livestock	All farms
	Farm size (ha)	60.8	33.9	44.3	61.2	64.4	42.6
Livestock units	139.4	54.0	68.5	41.40	159.8	86.2
Sample size	290	341	108	59	14	812
Sample size (weighted to population)	16,146	54,020	14,322	6,879	1,877	93,244

MACC methodology

The MACC methodology involves estimating the cost and abatement potential of implementing mitigation measures relative to a business-as-usual (BAU) scenario (baseline scenario). The cost of a measure is estimated as the difference between implementing the mitigation measures versus the baseline, including taking into account of any financial benefits (e.g., reduced chemical N fertiliser use) or income foregone that may arise all expressed in monetary terms.

The cost-effectiveness is calculated as the cost or cost-savings from the implementation of mitigation measures relative to the BAU scenario divided by the abatement potential of the measures compared to the baseline as set out in Equation 2. Costs are discounted (D = discount factor) where applicable over more than 1 yr. It is noteworthy that the discount factor varies across the measures. For each measure the discount rates and time horizon are indicated under the cost assumption in the Appendix Table A2.

(2) $$\begin{array}{l}{\text{MAC\hspace{0.17em}(€/kg\hspace{0.17em}of\hspace{0.17em}NH}}_{\text{3\hspace{0.17em}}}\text{\hspace{0.17em}abated)\hspace{0.17em}}\\ \text{=\hspace{0.17em}}\frac{\begin{array}{l}\Delta \text{\hspace{0.17em}Cost\hspace{0.17em}(Mitigation\hspace{0.17em}measure\hspace{0.17em}}\\ \text{implementation}\hspace{0.17em}–\hspace{0.17em}\text{Baseline)}\ast D\end{array}}{\begin{array}{l}\Delta {\text{\hspace{0.17em}NH}}_{\text{3}}\text{\hspace{0.17em}emissions\hspace{0.17em}(Mitigation\hspace{0.17em}measure\hspace{0.17em}}\\ \text{implementation}\hspace{0.17em}–\hspace{0.17em}\text{Baseline)}\end{array}}\end{array}$$

Selection of abatement measures

The mitigation measures selected here follow those of Lanigan et al. (2018) and Buckley et al. (2020). The justification for using these measures is that these options have been evidenced to apply to Irish agriculture. These studies also suggested adoption rates for mitigation measures. The abatement measures selected for investigation here include the following:

1. Use of protected urea chemical N fertiliser formulation

2. Achieving optimal soil pH through liming

3. Introduction of white clover into grass swards

4. Use of low emission slurry spreading (LESS) equipment

5. Addition of chemical amendments to bovine manure during slurry storage

6. Reduction in the crude protein of animal feeds

7. Covering of slurry stores.

It is noteworthy that there are other NH₃ abatement measures applicable to Irish agriculture and studied by Lanigan et al. (2015) and Buckley et al. (2020) but not considered in this study as they were deemed to lie outside the scope of the farm system level examination employed here.² The seven strategies considered in this study are those that are most applicable to land-based farm systems in Ireland. The assumptions underpinning the selection of the abatement measures are shown in Appendix Table A2.

Results

As indicated above, seven abatement measures were considered in this study across five different farm types. A baseline of NH₃ emissions was established for each farm system typology from which all the abatement measures were assessed.

Baseline level of farm emissions

The baseline year of analysis is 2020. Table 3 describes the baseline level of total farm-level NH₃ emissions across the five farm system types as well as the baseline level of adoption of the measures under investigation. Dairy farms exhibit higher NH₃ emissions compared to other farm systems, about four times higher than the cattle and five times higher than specialist sheep and tillage farms.

Table 3:

Baseline emissions and percentage adoption of abatement measures by farm type

	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
Baseline emissions (kg NH3/farm)	2,867	744	525	595	1,802	1,070
Baseline adoption of abatement measures
1. % of chemical N fertiliser applied as protected urea	16	3	8	2	3	6
2. % of soils at optimum pH	54	50	50	78	66	53
3. Grass-clover swards (%)	0	0	0	0	0	0
4. % of slurry applied by low emission slurry spreading equipment	50	15	9	17	25	20
5. Use of slurry amendments (%)	0	0	0	0	0	0
6. % of farmers at the optimum level of crude protein in dairy cow diet	0	0	0	0	0	0
7. % of slurry stores that are covered	85	93	95	91	98	92

Source: Authors’ computation of 2020 National Farm Survey and assumption data.

Table 3 also shows the baseline level of adoption across the measures examined. Results indicate that most of the farmers are already adopting covered stores with varying levels of uptake of other abatement measures. The use of LESS and protected urea measures appears to be more popular amongst dairy farms compared to other farm systems. It is noteworthy that some measures such as LESS are already adopted by a significant number of farms in the baseline period.

Farm-level NH₃ abatement potential

This section first reports on the NH₃ abatement potential of the different mitigation measures. For the average farm in the NFS, as reported in Table 4 (last column), results for the sum of individual measures indicated that 281 kg of NH₃ could be abated by adopting the seven measures examined. The LESS measure accounted for the largest share (33%) of this abatement. This implies that an average Irish farm will abate 92 kg of NH₃ emissions if they use LESS as against the more common splash plate method of application.

Table 4:

Farm-level NH₃ abatement potentials

Abatement potential (kg NH3/farm)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
	(N = 16,146)	(N = 54,020)	(N = 14,322)	(N = 6,879)	(N = 1,877)	(N = 92,264)
1. Protected urea	287	14	20	32	64	62
2. Liming	86	17	21	15	32	29
3. Clover	174	29	33	11	81	53
4. Low emission slurry spreading	184	83	50	21	196	92
5. Slurry amendments	91	17	9	10	52	28
6. Reduction in crude protein	33	10	5	7	22	13
7. Covering of slurry stores	16	1	0	0	4	3
Total	873	170	138	95	451	281
*Combined measure – when accounting for interactions	744	150	110	101	410	243

*It is not simply a summation of the 7 measures.

For the average farm, the use of protected urea recorded the second-highest level of abatement potential (62 kg NH₃). Results also indicate that the use of white clover as an abatement measure will reduce NH₃ emissions by 53 kg. The reduction in crude protein and covering of slurry stores measures accounted for the lowest levels of NH₃ emissions abatement compared to other measures considered in this study as outlined in Table 4.

However, when examining results by farm system type the abatement potential of the measures can differ. Contrary to the results of the other farm categories, the LESS measure did not account for the highest abatement potential for specialist dairy and tillage farms. In the case of specialist dairying, this was due to the fact that half of these farms had already adopted this measure by the year 2020. Results show that on average 184 kg of additional NH₃ emission reduction can be achieved on the average dairy farm by full adoption of the LESS measure as against the baseline scenario of using a splash plate. The LESS measure has the highest abatement potential on the mixed livestock farm system at 196 kg of NH₃ reduced. The average cattle and sheep farms indicated abatement potentials of 83 kg NH₃ and 50 kg NH₃, respectively, when implementing the LESS measure.

Introducing grass-clover swards across all the grassland area of an average specialist dairy farm resulted in a per annum reduction of NH₃ of 175 kg, while applying lime to all sub-optimal soils within a dairy farm led to an abatement of 86 kg of NH₃. Other abatement measures such as the addition of slurry amendment, lowering crude protein in diets and covering of slurry stores indicated NH₃ reduction of 109, 30 and 29 kg, respectively.

The specialist dairy farm type had the highest level of abatement potential across all the measures; generally between five and seven times higher than for the cattle and sheep systems, nine times higher than tillage and double that of mixed livestock. The LESS measure delivered the highest level of NH₃ mitigation across all farm enterprises except for dairy and tillage where the protected urea measure was highest. The use of protected urea indicates a reduction of NH₃ emissions of 287 kg (32.9% of the total average abatement potential) for an average Irish dairy farm. The average of all farm’s abatement potential is significantly lower than that of dairy and mixed livestock farms and higher than the other farm categories for all the abatement measures.

The result of the combined measure approach (i.e., the implementation of all measures together taking account of interaction effects) leads to a lower overall abatement potential across the different farm types compared to the total abatement potentials when summing individual measures. This implies that the interactions are not additive. The overall impact of interacting the abatement measures allows for crowding out of the measures’ impacts. The abatement potential for the combined implementation of all measures ranges from 101 kg NH₃ for the tillage farm to 744 kg NH₃ for the specialist dairy farm with the all farm average being 243 kg NH₃. The combined interactive scenario leads to between a 6% and 15% reduction in abatement potential compared to adding the impact of the individual measures depending on the farm system.

Cost of farm-level abatement

In addition to the potential mitigation impact of a measure, the cost of adopting a measure needs to be considered to develop cost-effectiveness metrics. This section first reports on the cost of implementing the different mitigation measures. A negative value in Table 5 represents a benefit (cost-saving), and a positive value represents an increase in cost (cost-positive).

Table 5:

Cost of abatement measures/farm

Cost/farm (€)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
	(N = 16,146, 60.8/ha)	(N = 54,020, 33.9/ha)	(N = 14,322, 44.3/ha)	(N = 6,879, 61.2/ha)	(N = 1,877, 64.4/ha)	(N = 92,264, 42.6/ha)
1. Protected urea	−€24	−€1	−€2	−€3	−€5	−€5
2. Liming	−€1,337	−€399	−€337	−€517	−€687	−€558
3. Clover	−€1,550	−€102	€137	€166	−€466	−€291
4. Low emission slurry spreading	€127	€102	€68	€33	€202	€98
5. Slurry amendments	€1,410	€767	€460	€394	€1,527	€813
6. Reduction in crude protein	−€745	−€106	−€60	−€68	−€386	−€207
7. Covering of slurry stores	€8	€1	€0	€0	€2	€2
Combined measure – when accounting for interactions	−€6,255	−€758	−1,074	−€1,956	−€2,633	−€1,840

From the results obtained (Table 5), there are monetary benefits associated with implementing the fertiliser-based measures across the five farm system types. On average across all farms, the liming measure led to the highest benefit (€558), followed by the white clover measure (€291) and then by the crude protein measure (€207). However, when considering the heterogeneity across the farm system types, disparities exist in terms of the relative ranking of the cost of the specific measures. Therefore, the results further justify the need to consider farm-heterogeneity and also the biophysical environment in constructing a MACC.

Overall, the cumulative cost implication of all the abatement measures for the dairy farm is cost-saving, and this largely influences the results for the average across all farms (Table 5, last column). The cost-savings associated with the implementation of the average specialist dairy farm is about three times higher than the all farm average.

For the average specialist dairy farm in the NFS, the white clover measure is the cheapest measure with an average per farm saving of €1,550 associated with this measure. The mixed livestock and the cattle farms also incurred a benefit in the implementation of the white clover option. The average tillage and sheep farm on the other hand incur a cost of €166 and €137, respectively, from the white clover measure. For all other farm types except the dairy farm, the liming measure is the cheapest abatement option.

Unlike the fertiliser-based strategies, farmers will incur some level of cost should they adopt the bovine measures (except for the crude protein measure). The slurry amendment option is the most expensive strategy to implement across all farm system types. It is projected to cost €813 across the average farm and ranges from €1,410 for a specialist dairy farm to €394 for a tillage farm with livestock.

Farm-level MACC

The marginal abatement cost of NH₃ emissions (expressed as €/kg of NH₃ abated) can be compared across different farm typologies, and mitigation measures can be ranked in terms of their cost-effectiveness.

A negative sign implies a measure that reduces NH₃ emissions and saves money for the farmer, while a positive sign indicates that, although the measure reduces NH₃ emissions, there are net costs associated with its implementation. As detailed in Table 6 (and in Figure 3A–F) the cost-saving measures across all farm systems are liming, crude protein, white clover and protected urea. On an average farm basis, liming is the most cost-saving measure with a marginal abatement cost of −€27.35/kg of NH₃ abated, followed by the crude protein reduction in diets (−€11.85/kg of NH₃) and white clover (−€2.40/kg of NH₃). Other measures indicate results that are cost-positive, these include covered stores (€0.03/kg of NH₃), LESS (€0.8/kg of NH₃) and slurry amendments (€34.85/kg of NH₃).

Figure 3.

Diagram showing the MACC for different farm systems. (A) All farms, (B) Dairy farms, (C) Cattle farms, (D) Sheep farms, (E) Tillage farms, and (F) Mixed livestock farms. LESS = low emission slurry spreading; MACC = marginal abatement cost curve.

Table 6:

NH₃ farm-level marginal abatement cost across different farm typologies

Cost-effectiveness NH3 (€/kg abated)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	−€0.04	−€0.01	−€0.02	−€0.01	−€0.02	−€0.02
2. Liming	−€30.03	−€26.91	−€19.47	−€43.48	−€17.31	−€27.35
3. Clover	−€22.59	−€6.16	€16.44	€31.69	€2.85	−€2.40
4. Low emission slurry spreading	€0.48	€0.94	€0.83	€0.27	€1.07	€0.80
5. Slurry amendments	€16.57	€41.83	€36.36	€15.66	€41.23	€34.85
6. Reduction in crude protein	−€21.55	−€10.62	−€8.96	−€5.91	−€12.48	−€11.85
7. Covering of slurry stores	€0.12	€0.03	€0.02	−€0.10	€0.01	€0.03
*Combined measure – when accounting for interactions	−€11.64	−€10.05	−€21.84	−€43.66	−€3.85	−€14.52

*It is not simply a summation of the 7 measures.

Following de Bruyn et al. (2018), the price of NH₃ emissions was set at €17.5/kg of NH₃. The price is quantified by the CE-Delft as the damage cost of NH₃ emissions to the EU’s ecosystem and human health as a result of environmental damage from acidification, eutrophication and human deaths (UNECE, 2021).

The MACC diagrams for all farm system types are illustrated in Figure 3A–F. The figures show the cost-effectiveness of the mitigation measures by farm system type ordered from the most cost-saving measures to the most cost-positive measures. Results indicate that the cost-effectiveness varies across farm system types and that the sign (positive or negative) can be different for a mitigation measure depending on the farm system. For example, the clover measure is cost-saving for dairy and cattle farms, cost-effective for sheep and mixed livestock farms but cost-prohibited for the tillage farm. These variations in cost-effectiveness and the ranking of abatement options may be attributed to the presence of heterogeneity across the farm system types. Farm system heterogeneity is most evident in the clover measure and, as indicated in Figure 3A–F, no two farm types have the same MACC. To further buttress the existence and importance of accounting for farm heterogeneity when constructing MACCs, variations also exist in the categorisation of the covered stores. While this option is generally cost-effective for other farm systems, it is cost-saving for tillage. Similarly, the slurry amendments option is cost-effective for the diary and tillage farms but cost-prohibited for all other farm types.

The average cost-effectiveness of the measure across “all farm” ranges from −€27.35/kg of NH₃ to €34.85/kg of NH₃. All fertiliser options and the crude protein reduction in diet measures are cost-saving while slurry amendments are cost-prohibited. The LESS and the covered stores are cost-effective for all farm system types. In contrast to the all farm average that ranks the inclusion of crude protein in diets as the second most cost-effective option, the clover measure is ranked as the second most cost-effective option for the dairy farm system. This again indicates the presence of farm system heterogeneity.

For the dairy farm MACC (Figure 3B), the diagram shows the cost-saving measures as liming, clover, crude protein and protected urea. The cost-effective measures are covered stores, LESS and slurry amendments. All of the abatement options considered in this study can be implemented on the dairy farm to reduce NH₃ emissions since no abatement measure is cost-prohibited (i.e., below the price of NH₃) with the marginal abatement cost ranging from −€30.03/kg of NH₃ to €16.57/kg of NH₃.

The ranking of abatement measures for the cattle farm follows closely that of the all farm average. The cost-effectiveness of the mitigation measures on cattle farms ranges between −€26.91/kg of NH₃ and €41.83/kg of NH₃. The sheep and the mixed livestock farms systems ranked the abatement measures invariance to the other farm types. For both of these farm types, only three measures (liming, crude protein and protected urea) are cost-saving and clover ranked sixth (as a cost-effective measure).

As shown in Table 6, the combined effect of implementing all measures examined is cost-saving with the effect of the cost-negative measures outweighing the cost-positive measures. Adoption of all mitigation measures across the average of all farms indicates cost-effectiveness of −€14.52/kg of NH₃.

It should be noted that results here represent the average result by farm system type; however, there is also heterogeneity within the five farm systems. Table 7 details this within-farm system heterogeneity. Results do indicate that on a farm system basis measures tend to be largely either cost-positive/neutral or cost-negative/neutral. The clover measure was the exception for the non-dairy system where the measure was equally likely to be cost positively or negatively distributed.

Table 7:

MAC distribution across different farm systems

Cost-effectiveness NH3 (€/kg abated)	Specialist dairy			Cattle			Specialist sheep			Specialist tillage			Mixed livestock			All farms
	% Cost-negative	% Cost-neutral	% Cost-positive	% Cost-negative	% Cost-neutral	% Cost-positive	% Cost-negative	% Cost-neutral	% Cost-positive	% Cost-negative	% Cost-neutral	% Cost-positive	% Cost-negative	% Cost-neutral	% Cost-positive	% Cost-negative	% Cost-neutral	% Cost-positive
1. Protected urea	52	48	0	9	91	0	21	79	0	12	88	0	22	78	0	18	82	0
2. Liming	99	1	0	85	8	8	77	13	10	92	8	0	65	0	35	86	7	7
3. Clover	99	1	0	72	7	21	54	13	34	44	24	33	48	0	52	71	8	21
4. LESS	0	36	63	0	27	73	0	42	58	0	82	18	0	13	87	0	35	65
5. Slurry amendments	2	0	98	8	7	84	7	29	64	19	48	33	0	0	100	8	12	80
6. Reduction in crude protein	100	0	0	99	1	0	71	29	0	56	44	0	100	0	0	92	8	2
7. Covering of slurry stores	2	73	25	10	83	7	6	92	2	18	81	1	0	98	2	9	83	9

LESS = low emission slurry spreading; MAC = marginal abatement cost.

Sensitivity analysis

A sensitivity analysis around the cost of abatement and the cost-effectiveness of the measures was undertaken. This was first based on a 50% increase in the price of chemical fertiliser. As shown in Appendix Table A3, for most of the abatement measures (except crude protein and protected urea) a 50% increase in fertiliser prices at the constant abatement potential resulted in a higher cost and higher cost-effectiveness (Appendix Table A4) values, respectively, as N recovered under the mitigation measures has a higher relative chemical N fertiliser replacement value under this scenario.

For a reduction in the cost of chemical N fertiliser, the results are explained in the opposite direction. A 50% reduction in the price of chemical N fertiliser (Appendix Table A5) resulted in a lower cost (except for the use of protected urea and the reduction of crude protein in the diets) and lower cost-effectiveness (Appendix Table A6) with the abatement potentials held constant. This is because the N recovered under the various mitigation measures has a lower relative chemical N fertiliser replacement value under this scenario.

The sensitivity analysis around mitigation measure adoption rates was also undertaken. This sensitivity analysis was based on assuming adoption rates at 50% and 75% (as opposed to 100%). Results (presented in Appendix Tables A7–A12) indicate that at a 50% adoption rate, there is a proportionate decrease of about 40–50% (Appendix Table A7) in the abatement potentials of the measures except for the white clover where about 75% proportionate decrease is reported. Similarly at a 75% adoption rate, the abatement potentials reduced by approximately 20–30% (Appendix Table A10) except for the white clover measure.

Regarding the cost-effectiveness at these different adoption rates, the ranking of the measures remains unchanged except for the use of the white clover measure. At 50% and 75% adoption rates (Appendix Tables A9 and A12, respectively), the white clover measure is cost-effective for dairy farms but cost-prohibitive for the other farms. In addition the result of the abatement potentials, cost and cost-effectiveness on hectare basis are presented in Tables A13 to A15 in the Appendix.

Discussion

Results from this analysis suggest that LESS delivered the highest level of NH₃ mitigation across all farm system types except specialist dairy and tillage where the protected urea measure was the highest. However, the LESS measure remains a crucial measure in abating NH₃ emissions (Lalor et al., 2014; Wagner et al., 2017). The findings here are consistent with that of Buckley et al. (2020) who reported that the LESS measure has the highest abatement potential for NH₃ emissions in Irish agriculture. In the study by Buckley et al. (2020), the LESS measure was responsible for about 65% of the total NH₃ abatement. On the other hand, contrary to Buckley et al. (2020), our study found that LESS reduced NH₃ emissions by approximately 33% for the average farm and about 45% for the cattle and mixed livestock farms. The contrast in these findings may be due to different levels of analysis used across both studies and different baseline assumptions. Also, the results for the abatement potential of dairy and tillage farms show that the LESS measure accounts for the second-highest abatement potential. This is because some farmers, especially dairy farmers, have already implemented the LESS measure in the baseline scenario in our analysis. While for the specialist tillage farm, the higher concentration of arable to livestock production makes the protected urea measure more suitable than the LESS measure. Farm system disaggregation provides additional insights into NH₃ MACC analysis. For example, for the LESS measure, the average farm results may overestimate the influence of LESS across different farm systems, especially tillage, and underestimate it on others (cattle and mixed livestock).

The findings here confirm the use of protected urea as an important strategy for reducing NH₃ emissions (Hristov et al., 2011; Klimczyk et al., 2021). Results here suggest that the protected urea measure is more cost-effective on dairy farms compared to some other farm system categories. While Hristov et al. (2011) report the importance of protected urea (urease inhibitors) as a manure treatment in abating NH₃ emissions from both dairy and cattle feedlots, our results indicate far greater cost-effectiveness of protected urea as a chemical N fertiliser in NH₃ abatement in the dairy farm system in contrast to the cattle system. The high abatement potential reported for dairy farms is attributable to the grass-based characteristics of Irish dairy farms; that is, the grass is used as the chief source of food for the dairy cows (Läpple et al., 2012; Läpple & Thorne, 2019). Thus, replacing the chemical N fertiliser necessary for the growth of grass on dairy farms away from straight urea with protected urea has a significant impact. Collectively, the LESS and protected urea measures account for more than half (>50%) of the NH₃ reductions on an average all farm basis.

The use of white clover was also found to have a relatively high abatement potential. This result corroborates the report of Spink et al. (2019) who shared the importance of implementing white clover as an NH₃ abatement strategy. However, taking account of farm system heterogeneity, the white clover measure also exhibits varying levels of abatement potential, with the abatement potential for the average dairy farm about 16 times that of the average tillage farm.

While Colmenero and Broderick (2006) and Spink et al. (2019) posited that a 1% reduction in the N excretion rate results in about 3–6% NH₃ reduction, results from this study found that a 1% reduction in dairy N excretion leads to a decrease of approximately 1% in NH₃ emissions at the farm-level.

The results of the study contrast with those of Kavanagh et al. (2019) who reported that slurry amendments are more favourable than slurry spreading techniques and covering of slurry stores. The difference in these findings could be a result of conceptualisation. For instance, their study involved the use of splash plate as a land spreading technique while our study focused essentially on LESS techniques. Also while their study encompassed ferric chloride, aluminium sulphate (alum), sulphuric acid and acetic acid as slurry amendments, this study focused essentially on the use of aluminium sulphate as a slurry amendment strategy under this pathway due to the ease and safe use and application of the substance (Buckley et al., 2020).

The MACC analysis here for all measures combined produced a different ranking for the abatement strategies compared to that of Lanigan et al. (2015) and Buckley et al. (2020). Buckley et al. (2020) ranked crude protein in diets as the most cost-saving measure (first measure) whereas this study ranked liming as the most beneficial measure. Liming in Buckley et al. (2020) was ranked in fourth place. Low emissions slurry spreading was ranked as a more cost-effective measure by Buckley et al. (2020) with covered stores the least cost-effective, which is in contrast to the findings of this study. The difference in the outcome of this study was due to the assumptions made and the timeline for implementation. For example, liming in Buckley et al. (2020) was assumed to be implemented on 20% of the sub-optimal area. The protected urea measure was assumed to replace calcium ammonium nitrate (CAN) and straight urea fertiliser in that study. White clover was also only assumed to be applied to 25% of dairy farms – significantly, different assumptions are used here. For instance, in this study, we assumed the replacement of all straight urea by protected urea, and all grassland areas were reseeded by white clover swards across the different farm systems.

Lanigan et al. (2015) ranked protected urea as a cost-effective measure as against this study or Buckley et al. (2015) who ranked protected urea as a cost-saving measure. Our result shared a similar view with Zhang et al. (2019) who reported crude protein in diets as a cost-saving measure under dairy production in China. Sajeev et al. (2018) also point out the importance of reducing crude protein in diets in abating NH₃ emissions from cattle.

Wagner et al. (2017) firmly support the presence and importance of farm system heterogeneity in explaining the potential abatement values of different strategies. Similar to our study, a lower marginal abatement cost was recorded for the LESS measure in Wagner et al. (2017) for cattle and dairy systems compared to the mixed livestock and all farms. Additionally, results here report a higher marginal abatement cost of covered stores for the dairy and cattle farms in contrast to the mixed livestock and all farms. The point of this discussion is that variation exists in the abatement potentials, cost of abatement and the marginal cost of abatement across different farm types; therefore, it is very important to consider farm heterogeneity in policy recommendations. Despite the variations across the farm typologies, some similarities can also be found. For instance, liming, protected urea and the crude protein option are all cost-saving across the system types. Consequently, these measures are highly appropriate for implementation across all the different farm systems.

Assessing the interactions among abatement measures is also important in order to understand the synergistic and antagonistic effects among these measures. Interactions can occur between two or more measures and amongst measures in abating NH₃ emissions. This study focused on the interactions across all the seven abatement measures but did not go into specific details about the potential interactions between any two measures. Unlike Pellerin et al. (2017) we also did not assume an additive nature of the abatement potentials, as interaction among abatement measures was accounted for and assessed through the simultaneous adoption of the abatement measures in the manure management chain.

As explained by Webb et al. (2005), abatement measures tend to have some level of interaction and interdependence among them. Hence, accounting for the interactions and not assuming additive figures for the abatement potentials and cost-effectiveness gives a truer estimate of the NH₃ emissions reduced across the manure management chain starting from the crude protein to the land spreading stage. Eory et al. (2018) buttress the importance of accounting for interactions amongst abatement measures rather than cumulating the abatement potentials of measures. Elsewhere, Wagner et al. (2015) and Röder et al. (2015) report on the importance and the existence of interactions amongst abatement measures. Röder et al. (2015) in their study on GHG abatement support our findings that combining abatement measures leads to higher abatement potentials than that of each individual measure but not necessarily at a lower cost as argued in their study. Whether assuming an additive nature or not, studies have shown that accounting for interactions (combining measures) for MACC analysis has an added advantage compared to the analysis of each individual measure separately.

While this research focused on farm heterogeneity through the different farm typologies, regional differentials were not accounted for, thus further research could account for farm location as well as typology in constructing farm-level MACC. Although this study accounted for heterogeneity and inter-relationships among the abatement measures through interactions within the measures, it did not account for dynamic relationships through time and uncertainties due to the lack of a farm-level model that can project activity data into the future.

Even though the aforementioned research has shown that abatement measures are effective in reducing NH₃ emissions, previous work has shown that they may also be effective in abating GHG emissions; thus, the full impact of these measures in mitigating both NH₃ and GHG emissions simultaneously represents an avenue for future research.

Conclusions

While an extensive literature on GHG MACC analysis exists, studies focusing on NH₃ are more limited, particularly when it comes to studies investigating the distribution of NH₃ emissions across different farm systems. This is an important knowledge gap since not accounting for farm system heterogeneity could lead to inefficient policy decisions and a sub-optimal level of emission reduction. This research addresses this knowledge gap by assessing the cost-effectiveness of measures to abate NH₃ emissions across different farm system types rather than at an aggregate national level.

This study showed that one type of MACC for all the different farm types may not necessarily represent the optimum abatement potential or MAC required by the farms. Furthermore, this study points toward the existence of an interdependent relationship among the abatement measures as evidenced by the abatement potential and overall cost-saving associated with the combined interaction-based scenario.

The cumulative impact of all the abatement measures is cost-saving for all five farm types. This gives rise to the question of why farmers are not already applying such cost-saving measures out of self-interest which may suggest that other parameters outside profit maximisation motivate farmers’ choice of adoption. Unawareness of the potential profit inherent in combining these measures may also be responsible for the non-implementation of these measures at optimal capacity. Therefore, efforts are required in the form of extension services to involve and educate the farmers on the importance of implementing these combined measures at the farm level and also work with them to address the factors and barriers influencing abatement measure adoption.

Footnotes

1

As the EPA inventory re-calculates historical emission levels based on the best/newest available data, absolute numbers can change.

2

Lanigan et al. (2015) and Buckley et al. (2020) considered pigs and poultry-based measures as well as measures for the farm types considered in this study.

Acknowledgements

This research was funded by the Teagasc Walsh Scholarship Programme.

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Appendices

Appendix

Appendix Table A1:

NH₃ emission factors of farm activities

Pollutant	Unit	Reference	2020
Manure management – cattle
NH3	Proportion of TAN	Housing, slurry	0.28
NH3	Proportion of TAN	Housing, solid	0.17
NH3	Proportion of TAN	Housing, solid – calves	0.04
NH3	Proportion of TAN	Yard, dairy cows	0.23
NH3	Proportion of TAN	Storage covered, slurry	0.05
NH3	Proportion of TAN	Storage uncovered, slurry	0.10
NH3	Proportion of TAN	Storage, solid	0.26
NH3	Proportion of TAN	Grass spread, slurry, summer	0.48
NH3	Proportion of TAN	Grass spread, slurry, autumn-spring	0.26
NH3	Proportion of TAN	Arable spread, slurry, summer	0.36
NH3	Proportion of TAN	Arable spread, slurry, autumn-spring	0.19
NH3	Proportion of TAN	Spread, solid	0.68
NH3	Proportion of TAN	Grazing, dairy cows)	0.06
NH3	Proportion of TAN	Grazing, other cattle	0.06
Manure management – sheep
NH3	Proportion of TAN	Housing, solid	0.216
NH3	Proportion of TAN	Storage, solid	0.263
NH3	Proportion of TAN	Spread	0.683
NH3	Proportion of TAN	Grazing	0.060
Inorganic N-fertilisers, includes also urea application
NH3	g/kg	Anhydrous ammonia	19.0
NH3	g/kg	Ammonium nitrate	15.0
NH3	g/kg	Ammonium phosphate	50.0
NH3	g/kg	Ammonium sulphate	90.0
NH3	g/kg	Calcium ammonium nitrate	8.0
NH3	g/kg	NK mixtures	15.0
NH3	g/kg	NPK mixtures	15.0
NH3	g/kg	NP mixtures	15.0
NH3	g/kg	N solutions	98.0
NH3	g/kg	Other N compounds	10.0
NH3	g/kg	Urea	155.0
NH3	g/kg	Protected urea	155.0

TAN = total ammonia nitrogen. Source: Hyde et al. (2023).

Appendix Table A2:

Assumptions applied to modelling mitigation

Abatement measure	Intervention	Abatement potential assumptions	Cost assumptions	References
Protected urea	Switch from straight urea to protected urea.	It was assumed that all straight urea used on farms was replaced fully by protected urea. Emission factors of straight urea is 155 (NH3 g/kg) compared to 33 NH3 g/kg for protected urea (Environmental Protection Agency, national inventory).	Cost/kg of straight urea = €0.73 (Irish Central Statistics Office, 2021). The market price of protected urea was assumed to be €0.8 based on prevailing market conditions at the time.	CSO (2021) Buckley et al. (2020)
Liming: the application of lime on soils with a sub-optimal pH	Based on a Teagasc (2019) soil analysis, only 54% of dairy farm area, 50% of cattle and sheep farm area and 78% of tillage farm area have an optimum soil pH (>6.2). 22%, 19% and 5% of dairy farm area have a soil pH of 5.9–6.2, 5.5–5.9 and <5.5, respectively. 1%, 9% and 12% of tillage farms have a soil pH of 5.9–6.2, 5.5–5.9 and <5.5, respectively. 8%, 21% and 21% of cattle and sheep farms have a soil pH of 5.9–6.2, 5.5–5.9 and <5.5, respectively.	This research assumes that all sub-optimal soils are treated with lime. Based on Teagasc long-term soil experiments, the pH response rate is 1 t/ha = 0.15 pH units for mineral soils (i.e., soil pH < 5.5) and 1 t/ha = 0.2 pH units for soils with pH between 5.5 and 6.2. The soil pH and the pH response rate were used to estimate the quantity of lime required for each category of soil sub-optimality and across different farm types. 80 kg of N/ha was assumed to be released from liming thus reducing the need for chemical fertiliser application.	In line with the recommended guidelines (Teagasc, 2020), a soil sample is assumed to be taken for every 3 ha of land targeted under this pathway at a cost of €25/sample to be tested in the laboratory. Following Buckley et al. (2020), the cost of lime, including the cost of application to the field, is assumed to be €25/t. As against the studies by Lanigan et al. (2018) and Buckley et al. (2020) which assumed a dynamic abatement of gaseous emissions and cost of abatement, this research assumes a one-off implementation of abatement measures, thus the cost of liming and sampling were discounted at a rate of 20% for 5 yr. The number of years used in discounting the amount of liming was based on the Teagasc (2021) advice on liming which stated that a replacement of lime is required approximately every 5 yr.	Teagasc (2019) Teagasc (2020) Buckley et al. (2020) Teagasc (2021)
Clover	The importance of using clover as an abatement practice can be attributed to its natural fixation of nitrogen which reduces the need for chemical fertilisation, thus reducing emissions from chemical fertiliser application. The study assumes that all grassland area is reseeded with clover over a 10-yr time horizon. The study also assumes that 10% of the land area is over sown with clover annually.	The nitrogen fixation of clover was fixed to a maximum of 80 kg N/ha per yr. All chemical N savings are captured through reduced protected urea fertiliser applications.	€121/ha was assumed as the contractor’s rate for a full reseed of grassland with clover (FCI, 2020). €22/ha was assumed as the contractor rates for over sowing with clover (FCI, 2020). The cost of clover seed is €50/ha.	FCI (2020) Buckley et al. (2020) Lanigan et al. (2018) Teagasc (2017)
Low emission slurry spreading (LESS)	The splash plate method which is the most popular method broadcasts the slurry over a wide area. Alternative application methods exist under the broad label of LESS. LESS consists of the use of slurry injection, trailing hose and trailing shoe, which reduces ammonia emissions compared to the splash plate method. LESS is based on the principle of reducing the area of the ammonia emitting surface, in this case of soil/plant surface that is covered by the applied liquid manure and can reduce ammonia emissions by >60% when compared to emissions associated with the use of the splash plate method.	The new scenario was developed based on the assumption that 100% of slurry applied by splash plate in the base year was substituted to LESS, with a 50/50 split between the trailing shoe and trial hose methods. The use of trailing hose results in a 30% reduction of NH3 emissions as against splash plate (Bittman et al., 2014; Buckley et al., 2020). The use of trailing shoe results in a 60% reduction of NH3 emissions as against splash plate (Bittman et al., 2014; Buckley et al., 2020). Increased nitrogen recovery associated with LESS is assumed to be realised through a reduction in chemical N fertiliser. It is assumed that this reduction is realised in the form of reduced protected urea use that is costed at market rates.	Costs were estimated based on relative contractor rates for application which suggests that, using an 11,500-L tanker, the cost of slurry spreading by splash plate and LESS methods is €65/h and €85/h, respectively. The volume of slurry spread by LESS and splash plate per hour for an 11,500-L tanker is assumed to be 28.4 m3 and 34 m3, respectively.	Buckley et al. (2020) Lanigan et al. (2018) Bittman et al. (2014)
Slurry Amendments	The emissions of NH3 during the slurry storage stage can be offset by the inclusion of chemical amendments (Kavanagh et al., 2019). These amendments may include chemicals such as alum, ferric acid, sulphuric acid and acetic acids.	This mitigation scenario is based on the assumption that compound alum is the treatment added to the bovine slurry and that this reduces NH3 emissions at the slurry storage stage by 70% with a 100% adoption rate assumed among farmers. The adoption rate is assumed to be 100%. The adoption of the slurry amendment leads to a reduced requirement for chemical fertiliser due to the increased quantity of nitrogen captured in the slurry and later returned to the soil at the land spreading stage of the manure management chain.	The treatment cost per volume of slurry treated is assumed to be €2.34/m3 and €4.40/m3 for dairy and cattle slurry, respectively (Kavanagh et al., 2019). The extra N retained over the baseline level represents a benefit and is accounted for as the cost-saving of protected urea fertiliser.	Kavanagh et al. (2019) Buckley et al. (2020) Lanigan et al. (2018) Teagasc (2017)
Covering of slurry stores	NH3 reduction at the slurry storage stage leads to higher nitrogen retention for use within the farm system. This in turn reduces the requirement for chemical nitrogen fertiliser for a given level of agricultural production. All cover types were posited to reduce NH3 emissions (Kupper et al., 2020).	The assumptions behind the adoption of the covering of slurry stores are based on the use of a flexible floating cover and an implementation rate of 100% (i.e., it involves moving all uncovered stores to covered stores). The emission factors for covered stores is 50% lower than for uncovered slurry stores (Misselbrook et al., 2016). Reduction in chemical N fertiliser is assumed to be realised in the form of reduced protected urea use that is costed at market rates per tonne of protected urea.	On the cost side, the assumption was based on the report of Reis et al. (2015) which assumes a cost of €1.5/m3 of slurry to replace an open slurry store with a covered slurry type. The total cost of replacing an open slurry to a covered type was discounted over a period of 10 yr.	Buckley et al. (2020) Reis et al. (2015) Misselbrook et al. (2016)
Crude protein	Excess crude protein (over requirement) in the diet of livestock leads to higher N excretion rates and ultimately higher ammonia emissions (Sajeev et al., 2018; Buckley et al., 2020). This abatement measure works by influencing the amount of nitrogen excreted by livestock and by extension the amount entering the manure management chain (Buckley et al., 2020).	It is assumed that the average dairy cow was fed 1,045 kg of concentrates (Buckley et al., 2020). Furthermore, it is assumed that a 1% decrease in the crude protein composition of dairy concentrates leads to a decrease of 1.5 kg in the N excretion rate of dairy. The N excretion rate for the non-dairy animals considered in this study was reduced by a percentage reduction obtained by the ratio of the new dairy N excretion rate to the old dairy N excretion rate.	A 1 percentage point crude protein reduction results in a €6/t reduction in the price of dairy concentrates, based on the market price differential between the two protein ingredients in 2020 (Buckley et al., 2020).	Shalloo et al. (2018) O’Brien et al. (2018) O’Brien and Shalloo (2019)

Appendix Table A3:

Sensitivity analysis for the cost of abatement (increase in the cost of fertiliser by 50%)

Cost/farm (€)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
	(N = 16,146, 60.8/ha)	(N = 54,020, 33.9/ha)	(N = 14,322, 44.3/ha)	(N = 6,879, 61.2/ha)	(N = 1,877, 64.4/ha)	(N = 92,264, 42.6/ha)
1. Protected urea	€1,048	€55	€76	€90	€283	€229
2. Liming	−€2,200	−€723	−€669	−€887	−€1,191	−€979
3. Clover	−€3,782	−€943	−€718	−€338	−€2,217	−€1,356
4. Low emission slurry spreading	€68	€76	€53	€27	€139	€69
5. Slurry amendments	€1,381	€762	€457	€392	€1,510	€804
6. Reduction in crude protein	−€745	−€106	−€60	−€68	−€386	−€207
7. Covering of slurry stores	€3	€1	€0	€0	€1	€1

Appendix Table A4:

Sensitivity analysis of NH₃ farm-level marginal abatement cost (increase in price of fertiliser by 50%)

Cost-effectiveness NH3 (€/kg abated)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	€2.04	€0.28	€0.64	€0.34	€0.72	€0.64
2. Liming	−€49.48	−€52.45	−€30.14	−€73.90	−€42.17	−€49.89
3. Clover	−€41.27	−€30.21	−€3.11	€10.73	−€19.51	−€24.61
4. Low emission slurry spreading	€0.28	€0.72	€0.66	€0.22	€0.79	€0.60
5. Slurry amendments	€16.25	€41.54	€36.16	€15.50	€40.90	€34.59
6. Reduction in crude protein	21.55	−10.62	−8.96	−5.91	−12.48	−11.85
7. Covering of slurry stores	€0.04	−€0.03	−€0.01	−€0.16	€0.01	−€0.02

Appendix Table A5:

Sensitivity analysis for cost of abatement (decrease in the cost of fertiliser by 50%)

Cost/farm (€)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
	(N = 16,146, 60.8/ha)	(N = 54,020, 33.9/ha)	(N = 14,322, 44.3/ha)	(N = 6,879, 61.2/ha)	(N = 1,877, 64.4/ha)	(N = 92,264, 42.6/ha)
1. Protected urea	−€1,095	−€57	−€80	−€95	−€294	−€239
2. Liming	−€474	−€75	−€6	−€147	−€182	−€137
3. Clover	−€335	€188	€348	€260	€226	€132
4. Low emission slurry spreading	€186	€128	€83	€39	€266	€127
5. Slurry amendments	€1,439	€772	€463	€397	€1,543	€822
6. Reduction in crude protein	−€745	−€106	−€60	−€68	−€386	−€207
7. Covering of slurry stores	€13	€1	€0	€0	€3	€3

Appendix Table A6:

Sensitivity analysis of NH₃ farm-level marginal abatement cost (decrease in price of fertiliser by 50%)

Cost-effectiveness NH3 (€/kg abated)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	−€2.12	−€0.29	−€0.67	−€0.36	−€0.76	−€0.67
2. Liming	−€10.57	€0.05	€14.91	−€13.05	€7.54	−€0.22
3. Clover	−€2.36	€22.29	€41.80	€60.36	€30.20	€24.21
4. Low emission slurry spreading	€0.68	€1.16	€1.00	€0.31	€1.35	€1.00
5. Slurry amendments	€16.89	€42.11	€36.57	€15.82	€41.55	€35.12
6. Reduction in crude protein	€21.55	−€10.62	−€8.96	−€5.91	−€12.48	−€11.85
7. Covering of slurry stores	€0.21	€0.09	€0.04	−€0.04	€0.02	€0.09

Appendix Table A7:

Farm-level NH₃ abatement potentials at a 50% adoption rate

Abatement potential (kg NH3)/farm	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	144	7	10	16	32	31
2. Liming	43	8	10	7	16	14
3. Clover	44	7	8	3	20	13
4. Low emission slurry spreading	92	42	25	11	98	46
5. Slurry amendments	46	8	4	5	26	14
6. Reduction in crude protein	17	5	3	3	11	6
7. Covering of slurry stores	9	1	0	0	2	2
Total	394	78	61	45	205	128

Appendix Table A8:

Cost of abatement measures per farm at a 50% adoption rate

Cost/farm (€)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	−€848	−€41	−€60	−€95	−€188	−€184
2. Liming	−€668	−€199	−€169	−€259	−€343	−€279
3. Clover	€87	€232	€335	€232	€378	€227
4. Low emission slurry spreading	€63	€51	€34	€17	€101	€49
5. Slurry amendments	€1,439	€772	€463	€397	€1,543	€822
6. Reduction in crude protein	−€373	−€53	−€30	−€34	−€193	−€103
7. Covering of slurry stores	€107	€41	€25	€22	€98	€49

Appendix Table A9:

NH₃ farm-level marginal abatement cost across different farm typologies at a 50% adoption rate

Cost-effectiveness NH3 (€/kg abated)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	−€3.09	−€0.53	−€1.23	−€0.72	−€1.27	−€1.09
2. Liming	−€30.03	−€26.91	−€19.47	−€43.48	−€17.31	−€27.35
3. Clover	€7.82	€80.13	€130.67	€183.10	€100.72	€84.03
4. Low emission slurry spreading	€0.48	€0.94	€0.83	€0.27	€1.07	€0.80
5. Slurry amendments	€33.77	€84.22	€73.13	€31.64	€83.11	€70.24
6. Reduction in crude protein	−€21.55	−€10.62	−€8.96	−€5.91	−€12.48	−€11.85
7. Covering of slurry stores	€1.30	€0.33	€0.52	€0.10	€0.00	€0.49

Appendix Table A10:

Farm-level NH₃ abatement potentials at a 75% adoption rate

Abatement potential (kg NH3)/farm	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	221	11	16	24	50	48
2. Liming	65	13	15	11	24	22
3. Clover	98	16	19	6	46	30
4. Low emission slurry spreading	138	62	37	16	147	69
5. Slurry amendments	68	13	7	7	39	21
6. Reduction in crude protein	25	7	4	5	17	10
7. Covering of slurry stores	14	1	0	0	3	3
Total	628	123	98	70	325	202

Appendix Table A11:

Cost of abatement measures per farm at a 75% adoption rate

Cost/farm (€)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	−€563	−€29	−€41	−€49	−€151	−€123
2. Liming	−€1,003	−€299	−€253	−€388	−€515	−€419
3. Clover	−€516	€135	€303	€236	€109	€61
4. Low emission slurry spreading	€95	€77	€51	€25	€152	€73
5. Slurry amendments	€1,424	€770	€462	€396	€1,535	€817
6. Reduction in crude protein	−€373	−€53	−€30	−€34	−€193	−€103
7. Covering of slurry stores	€113	€41	€25	€22	€100	€50

Appendix Table A12:

NH₃ farm-level marginal abatement cost across different farm typologies at a 75% adoption rate

Cost-effectiveness NH3 (€/kg abated)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
1. Protected urea	−€3.00	−€0.97	−€0.84	−€0.25	−€0.50	−€1.22
2. Liming	−€30.03	−€26.91	−€19.47	−€43.48	−€17.31	−€27.35
3. Clover	−€7.76	€35.92	€72.14	€105.53	€50.58	€39.75
4. Low emission slurry spreading	€0.48	€0.94	€0.83	€0.27	€1.07	€0.80
5. Slurry amendments	€22.30	€55.96	€48.62	€20.99	€55.19	€46.65
6. Reduction in crude protein	−€21.55	−€10.62	−€8.96	−€5.91	−€12.48	−€11.85
7. Covering of slurry stores	€0.99	€0.23	€0.36	€0.03	€0.01	€0.35

Appendix Table A13:

Farm-level NH₃ abatement potentials (/ha)

Abatement potential (kg NH3)/farm	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
Protected urea	4.33	0.30	0.48	0.35	0.52	1.00
Liming	1.33	0.44	0.51	0.22	0.34	0.58
Clover	2.72	0.80	0.91	0.21	0.85	1.09
Low emission slurry spreading	3.49	2.61	1.40	0.34	3.22	2.41
Slurry amendments	1.51	0.51	0.22	0.13	0.69	0.60
Reduction in crude protein	0.56	0.30	0.13	0.10	0.33	0.30
Covering of slurry stores	0.27	0.03	0.00	0.00	0.03	0.06
*Combined measure – when accounting for interactions	12.28	4.52	2.85	1.46	5.68	5.33

*It is not simply a summation of the 7 measures.

Appendix Table A14:

Cost of abatement measures per hectare basis

Cost/farm (€)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
Protected urea	−€0.36	−€0.02	−€0.04	−€0.03	−€0.04	−€0.08
Liming	−€22.23	−€12.22	−€8.84	−€8.58	−€8.03	−€12.99
Clover	−€35.74	−€13.96	−€7.65	−€2.33	−€9.58	−€15.62
Low emission slurry spreading	€2.46	€3.15	€1.87	€0.47	€3.66	€2.64
Slurry amendments	€23.46	€23.08	€11.79	€5.32	€25.02	€20.10
Reduction in crude protein	−€12.25	−€3.05	−€1.43	−€1.00	−€4.68	−€4.19
Covering of slurry stores	€0.13	€0.03	€0.00	€0.00	€0.01	€0.04
Combined measure – when accounting for interactions	−€65.00	€16.05	€13.07	−€17.76	€10.50	−€0.40

Appendix Table A15:

NH₃ hectare-level marginal abatement cost across different farm typologies

Cost-effectiveness NH3 (€/kg abated)	Specialist dairy	Cattle	Specialist sheep	Specialist tillage	Mixed livestock	All farms
Protected urea	€0.00	€0.00	€0.00	€0.00	€0.00	€0.00
Liming	−€0.76	−€1.21	−€0.62	−€1.35	−€0.28	−€1.03
Clover	−€0.59	−€0.51	€0.11	€1.05	€0.26	−€0.29
Low emission slurry spreading	€0.01	€0.04	€0.03	€0.01	€0.03	€0.03
Slurry amendments	€0.37	€1.64	€1.33	€0.33	€1.20	€1.27
Reduction in crude protein	−€0.47	−€0.42	−€0.32	−€0.15	−€0.21	−€0.39
Covering of slurry stores	€0.00	€0.00	€0.00	€0.00	€0.00	€0.00
*Combined measure – when accounting for interactions	−€0.16	€0.43	€0.82	−€0.97	€0.20	€0.28

*It is not simply a summation of the 7 measures.