Costs and effects of measures to reduce ammonia emissions from dairy cattle and pig production: A comparison of country-specific estimations and model calculations.

Understanding the costs of emission abatement measures is essential for devising reduction efforts. It allows to identify cost-effective solutions to achieve target values set by international agreements or national policies. This work aims to summarize and discuss the current knowledge on costs and effects associated with selected ammonia (NH3) mitigation measures in livestock production through comparison of country-specific and model-estimated values. Often, large differences appear between the results of individual countries, also in comparison with model results that are generally better harmonized between countries. It seems that different system boundaries in cost assessments, but also different geographic and structural conditions create perceived as well as real cost differences, also caused by the variability of individual situations. Our results are robust with respect to identifying feeding strategies as the most cost-effective, but results for other mitigation options do not show any clear trends, thus making it difficult to distinguish further cost-effective solutions. We point out and discuss some key aspects which may affect estimates of national costs, leading to challenges with the interpretation of final results. Our study concludes that further and more consistent assessments (e.g. standardized protocols) are needed to improve the evaluation base for other individual abatement options, including options that are under development.

Improved accuracy and reduced uncertainty in greenhouse gas inventories by refining the IPCC emission factor for direct N2 O emissions from nitrogen inputs to managed soils.

Most national GHG inventories estimating direct N2 O emissions from managed soils rely on a default Tier 1 emission factor (EF1 ) amounting to 1% of nitrogen inputs. Recent research has, however, demonstrated the potential for refining the EF1 considering variables that are readily available at national scales. Building on existing reviews, we produced a large dataset (n = 848) enriched in dry and low latitude tropical climate observations as compared to former global efforts and disaggregated the EF1 according to most meaningful controlling factors. Using spatially explicit N fertilizer and manure inputs, we also investigated the implications of using the EF1 developed as part of this research and adopted by the 2019 IPCC refinement report. Our results demonstrated that climate is a major driver of emission, with an EF1 three times higher in wet climates (0.014, 95% CI 0.011-0.017) than in dry climates (0.005, 95% CI 0.000-0.011). Likewise, the form of the fertilizer markedly modulated the EF1 in wet climates, where the EF1 for synthetic and mixed forms (0.016, 95% CI 0.013-0.019) was also almost three times larger than the EF1 for organic forms (0.006; 95% CI 0.001-0.011). Other factors such as land cover and soil texture, C content, and pH were also important regulators of the EF1 . The uncertainty associated with the disaggregated EF1 was considerably reduced as compared to the range in the 2006 IPCC guidelines. Compared to estimates from the 2006 IPCC EF1 , emissions based on the 2019 IPCC EF1 range from 15% to 46% lower in countries dominated by dry climates to 7%-37% higher in countries with wet climates and high synthetic N fertilizer consumption. The adoption of the 2019 IPCC EF1 will allow parties to improve the accuracy of emissions' inventories and to better target areas for implementing mitigation strategies.

Effects of climate change on the delivery of soil-mediated ecosystem services within the primary sector in temperate ecosystems: a review and New Zealand case study.

Future human well-being under climate change depends on the ongoing delivery of food, fibre and wood from the land-based primary sector. The ability to deliver these provisioning services depends on soil-based ecosystem services (e.g. carbon, nutrient and water cycling and storage), yet we lack an in-depth understanding of the likely response of soil-based ecosystem services to climate change. We review the current knowledge on this topic for temperate ecosystems, focusing on mechanisms that are likely to underpin differences in climate change responses between four primary sector systems: cropping, intensive grazing, extensive grazing and plantation forestry. We then illustrate how our findings can be applied to assess service delivery under climate change in a specific region, using New Zealand as an example system. Differences in the climate change responses of carbon and nutrient-related services between systems will largely be driven by whether they are reliant on externally added or internally cycled nutrients, the extent to which plant communities could influence responses, and variation in vulnerability to erosion. The ability of soils to regulate water under climate change will mostly be driven by changes in rainfall, but can be influenced by different primary sector systems' vulnerability to soil water repellency and differences in evapotranspiration rates. These changes in regulating services resulted in different potentials for increased biomass production across systems, with intensively managed systems being the most likely to benefit from climate change. Quantitative prediction of net effects of climate change on soil ecosystem services remains a challenge, in part due to knowledge gaps, but also due to the complex interactions between different aspects of climate change. Despite this challenge, it is critical to gain the information required to make such predictions as robust as possible given the fundamental role of soils in supporting human well-being.

Addition of straw or sawdust to mitigate greenhouse gas emissions from slurry produced by housed cattle: a field incubation study.

The use of housed wintering systems (e.g., barns) associated with dairy cattle farming is increasing in southern New Zealand. Typically, these wintering systems use straw or a woodmix as bedding material. Ammonia (NH) and greenhouse gas (GHG) emissions (nitrous oxide [NO] and methane [CH]) associated with storage of slurry + bedding material from wintering systems is poorly understood. A field incubation study was conducted to determine such emissions from stored slurry where bedding material (straw and sawdust) was added at two rates and stored for 7 mo. During the first 4 mo of storage, compared with untreated slurry, the addition of sawdust significantly reduced NH and CH emissions from 29 to 3% of the initial slurry nitrogen (N) content and from 0.5 to <0.01% of the initial slurry carbon (C) content. However, sawdust enhanced NO emissions to 0.7% of the initial slurry-N content, compared with <0.01% for untreated slurry. Straw generally had an intermediate effect. Extending the storage period to 7 mo increased emissions from all treatments. Ammonia emissions were inversely related to the slurry C:N ratio and total solid (TS) content, and CH emissions were inversely related to slurry TS content. Mitigation of GHG emissions from stored slurry can be achieved by reducing the storage period as much as possible after winter slurry collection, providing ground conditions allow access for land spreading and nutrient inputs match pasture requirements. Although adding bedding material can reduce GHG emissions during storage, increased manure volumes for carting and spreading need to be considered.

Effects of environmental and housing system factors on ammonia and greenhouse gas emissions from cattle barns: A meta-analysis of a global data collation.

This study provides a meta-analysis on the relationships between cattle barn CH4, NH3 and N2O emission rates and their key drivers (i.e., housing type, floor type, environmental conditions). Understanding these relationships is essential to reduce uncertainties in emission inventories and suggest targeted mitigation measures. The total number of daily emission rates included in the analysis was 139 for CH4, 293 for NH3 and 100 for N2O emissions. Emission rates in the database showed a large variation with 45-803.5 g/LU d-1 for CH4, 0.036-146.7 gN LU-1 d-1 for NH3, and 0.002-18 gN LU-1 d-1 for N2O emissions. Despite the high emission variability, significant effects were identified·NH3 showed positive correlation with air temperature; NH3 emissions differed between housing types but not between floor types·NH3 emissions from tied stalls were lower than the ones from cubicle housing regardless of the floor type. Additionally, NH3 emissions from loose housings were lower than the ones from cubicle housing·NH3 and N2O emission rates from temperate wet zones were lower than the ones from temperate dry zones. CH4 emission rates were affected by environmental factors only and not by housing and floor type, showing negative correlation with air temperature and humidity. The factors investigated can be suggested as ancillary variables and descriptors when cattle barn emissions are measured, in order to make best use of emission data. Country-specific data of these key drivers can be included into national inventories to adapt them to different agroecosystems and support targeted policies.

DATAMAN: A global database of methane, nitrous oxide, and ammonia emission factors for livestock housing and outdoor storage of manure.

Livestock manure management systems can be significant sources of nitrous oxide (N2 O), methane (CH4 ), and ammonia (NH3 ) emissions. Many studies have been conducted to improve our understanding of the emission processes and to identify influential variables in order to develop mitigation techniques adapted to each manure management step (animal housing, outdoor storage, and manure spreading to land). The international project DATAMAN (http://www.dataman.co.nz) aims to develop a global database on greenhouse gases (N2 O, CH4 ) and NH3 emissions from the manure management chain to refine emission factors (EFs) for national greenhouse gas and NH3 inventories. This paper describes the housing and outdoor storage components of this database. Relevant information for different animal categories, manure types, livestock buildings, outdoor storage, and climatic conditions was collated from published peer reviewed research, conference papers, and existing databases published between 1995 and 2021. In the housing database, 2024 EFs were collated (63% for NH3 , 19.5% for CH4 , and 17.5% for N2 O). The storage database contains 654 NH3 EFs from 16 countries, 243 CH4 EFs from 13 countries, and 421 N2 O EFs from 17 countries. Across all gases, dairy cattle and swine production in temperate climate zones are the most represented animal and climate categories. As for the housing database, the number of EFs for the tropical climate zone is under-represented. The DATAMAN database can be used for the refinement of national inventories and better assessment of the cost-effectiveness of a range of mitigation strategies.

Challenges and opportunities to capture dietary effects in on-farm greenhouse gas emissions models of ruminant systems.

This paper reviews existing on-farm GHG accounting models for dairy cattle systems and their ability to capture the effect of dietary strategies in GHG abatement. The focus is on methane (CH4) emissions from enteric and manure (animal excreta) sources and nitrous oxide (N2O) emissions from animal excreta. We identified three generic modelling approaches, based on the degree to which models capture diet-related characteristics: from 'none' (Type 1) to 'some' by combining key diet parameters with emission factors (EF) (Type 2) to 'many' by using process-based modelling (Type 3). Most of the selected on-farm GHG models have adopted a Type 2 approach, but a few hybrid Type 2 / Type 3 approaches have been developed recently that combine empirical modelling (through the use of CH4 and/or N2O emission factors; EF) and process-based modelling (mostly through rumen and whole tract fermentation and digestion). Empirical models comprising key dietary inputs (i.e., dry matter intake and organic matter digestibility) can predict CH4 and N2O emissions with reasonable accuracy. However, the impact of GHG mitigation strategies often needs to be assessed in a more integrated way, and Type 1 and Type 2 models frequently lack the biological foundation to do this. Only Type 3 models represent underlying mechanisms such as ruminal and total-tract digestive processes and excreta composition that can capture dietary effects on GHG emissions in a more biological manner. Overall, the better a model can simulate rumen function, the greater the opportunity to include diet characteristics in addition to commonly used variables, and thus the greater the opportunity to capture dietary mitigation strategies. The value of capturing the effect of additional animal feed characteristics on the prediction of on-farm GHG emissions needs to be carefully balanced against gains in accuracy, the need for additional input and activity data, and the variability encountered on-farm.

DATAMAN: A global database of nitrous oxide and ammonia emission factors for excreta deposited by livestock and land-applied manure.

Nitrous oxide (N2 O), ammonia (NH3 ), and methane (CH4 ) emissions from the manure management chain of livestock production systems are important contributors to greenhouse gases (GHGs) and NH3 emitted by human activities. Several studies have evaluated manure-related emissions and associated key variables at regional, national, or continental scales. However, there have been few studies focusing on the drivers of these emissions using a global dataset. An international project was created (DATAMAN) to develop a global database on GHG and NH3 emissions from the manure management chain (housing, storage, and field) to identify key variables influencing emissions and ultimately to refine emission factors (EFs) for future national GHG inventories and NH3 emission reporting. This paper describes the "field" database that focuses on N2 O and NH3 EFs from land-applied manure and excreta deposited by grazing livestock. We collated relevant information (EFs, manure characteristics, soil properties, and climatic conditions) from published peer-reviewed research, conference papers, and existing databases. The database, containing 5,632 observations compiled from 184 studies, was relatively evenly split between N2 O and NH3 (56 and 44% of the EF values, respectively). The N2 O data were derived from studies conducted in 21 countries on five continents, with New Zealand, the United Kingdom, Kenya, and Brazil representing 86% of the data. The NH3 data originated from studies conducted in 17 countries on four continents, with the United Kingdom, Denmark, Canada, and The Netherlands representing 79% of the data. Wet temperate climates represented 90% of the total database. The DATAMAN field database is available at http://www.dataman.co.nz.

Ammonia and nitrous oxide emission factors for excreta deposited by livestock and land-applied manure.

Manure application to land and deposition of urine and dung by grazing animals are major sources of ammonia (NH3 ) and nitrous oxide (N2 O) emissions. Using data on NH3 and N2 O emissions following land-applied manures and excreta deposited during grazing, emission factors (EFs) disaggregated by climate zone were developed, and the effects of mitigation strategies were evaluated. The NH3 data represent emissions from cattle and swine manures in temperate wet climates, and the N2 O data include cattle, sheep, and swine manure emissions in temperate wet/dry and tropical wet/dry climates. The NH3 EFs for broadcast cattle solid manure and slurry were 0.03 and 0.24 kg NH3 -N kg-1 total N (TN), respectively, whereas the NH3 EF of broadcast swine slurry was 0.29. Emissions from both cattle and swine slurry were reduced between 46 and 62% with low-emissions application methods. Land application of cattle and swine manure in wet climates had EFs of 0.005 and 0.011 kg N2 O-N kg-1 TN, respectively, whereas in dry climates the EF for cattle manure was 0.0031. The N2 O EFs for cattle urine and dung in wet climates were 0.0095 and 0.002 kg N2 O-N kg-1 TN, respectively, which were three times greater than for dry climates. The N2 O EFs for sheep urine and dung in wet climates were 0.0043 and 0.0005, respectively. The use of nitrification inhibitors reduced emissions in swine manure, cattle urine/dung, and sheep urine by 45-63%. These enhanced EFs can improve national inventories; however, more data from poorly represented regions (e.g., Asia, Africa, South America) are needed.

Global Research Alliance N2 O chamber methodology guidelines: Considerations for automated flux measurement.

Nitrous oxide (N2 O) emissions are highly episodic in response to nitrogen additions and changes in soil moisture. Automated gas sampling provides the necessary high temporal frequency to capture these emission events in real time, ensuring the development of accurate N2 O inventories and effective mitigation strategies to reduce global warming. This paper outlines the design and operational considerations of automated chamber systems including chamber design and deployment, frequency of gas sampling, and options in terms of the analysis of gas samples. The basic hardware and software requirements for automated chambers are described, including the major challenges and obstacles in their implementation and operation in a wide range of environments. Detailed descriptions are provided of automated systems that have been deployed to assess the impacts of agronomy on the emissions of N2 O and other significant greenhouse gases. This information will assist researchers across the world in the successful deployment and operation of automated N2 O chamber systems.

Global Research Alliance N2 O chamber methodology guidelines: Statistical considerations, emission factor calculation, and data reporting.

Static chambers are often used for measuring nitrous oxide (N2 O) fluxes from soils, but statistical analysis of chamber data is challenged by the inherently heterogeneous nature of N2 O fluxes. Because N2 O chamber measurements are commonly used to assess N2 O mitigation strategies or to determine country-specific emission factors (EFs) for calculating national greenhouse gas inventories, it is important that statistical analysis of the data is sound and that EFs are robustly estimated. This paper is one of a series of articles that provide guidance on different aspects of N2 O chamber methodologies. Here, we discuss the challenges associated with statistical analysis of heterogeneous data, by summarizing statistical approaches used in recent publications and providing guidance on assessing normality and options for transforming data that follow a non-normal distribution. We also recommend minimum requirements for reporting of experimental and metadata of N2 O studies to ensure that the robustness of the results can be reliably evaluated. This includes detailed information on the experimental site, methodology and measurement procedures, gas analysis, data and statistical analyses, and approaches to generate EFs, as well as results of ancillary measurements. The reliability, robustness, and comparability of soil N2 O emissions data will be improved through (a) application, and reporting, of more rigorous methodological standards by researchers and (b) greater vigilance by reviewers and scientific editors to ensure that all necessary information is reported in scientific publications.

Does Brachiaria humidicola and dicyandiamide reduce nitrous oxide and ammonia emissions from cattle urine patches in the subtropics?

Nitrous oxide (N2O) emissions from pasture-based livestock systems represent 34% of Brazil's agricultural greenhouse gas emissions. The forage species Brachiaria humidicola is known for its biological nitrification inhibition (BNI) capacity and N2O emissions reduction ability from urine patches under tropical conditions. However, there is little information about the effect of BNI on N2O emission and ammonia (NH3) volatilisation in the subtropics. This study aimed to: (i) evaluate the potential of Brachiaria humidicola, compared with Panicum maximum (Jacq. cv. Áries; guinea grass), a broadly used grass (with no BNI capacity), to reduce N2O emissions under subtropical conditions; (ii) determine the efficacy of nitrification inhibitor dicyandiamide (DCD) to decrease N2O emissions; and (iii) determine the effect of brachiaria and DCD application on NH3 volatilisation. A field experiment was carried out using a Cambisol, where cattle urine ± DCD was applied to brachiaria and guinea grass. Over the 67-day measurement period, cumulative N2O emissions were 20% lower from urine patches in the brachiaria treatment (1138 mg N m-2, Emission factor = 1.06%) compared to guinea grass (1436 mg N m-2, Emission factor = 1.33%) (P < .10). A greenhouse experiment, using pots with the same treatments as in the field experiment, suggested that this could have been due to lower soil nitrate levels under brachiaria forage compared to guinea grass, indicating that BNI could be a possible mechanism for lower N2O emissions from brachiaria. The DCD application was effective in both forage species, decreasing N2O emissions by 40-50% (P < .10) compared with the urine only treatment. Approximately 25% of the urine applied N was lost via NH3 volatilisation, however the NH3 loss was not affected by forage species or DCD application (P > .10). Overall, the results demonstrated that brachiaria and DCD use are strategies that can reduce N2O emissions from urine patches.

Benefits and Trade-Offs of Dairy System Changes Aimed at Reducing Nitrate Leaching.

Between 2011 and 2016, small-scale farm trials were run across three dairy regions of New Zealand (Waikato, Canterbury, Otago) to compare the performance of typical regional farm systems with farm systems implementing a combination of mitigation options most suitable to the region. The trials ran for at least three consecutive years with detailed recording of milk production and input costs. Nitrate leaching per hectare of the milking platform (where lactating cows are kept) was estimated using either measurements (suction cups), models, or soil mineral nitrogen measurements. Post-trial, detailed farm information was used in the New Zealand greenhouse gas inventory methodology to calculate the emissions from all sources; dairy platform, dairy support land used for wintering non-lactating cows (where applicable) and replacement stock, and imported supplements. Nitrate leaching was also estimated for the support land and growing of supplements imported from off-farm using the same methods as for the platform. Operating profit (NZ$/ha/year), nitrate leaching (kg N/ha/year), and greenhouse gas emissions (t CO2-equivalent/ha/year) were all expressed per hectare of milking platform to enable comparisons across regions. Nitrate leaching mitigations adopted in lower-input (less purchased feed and nitrogen fertiliser) farm systems reduced leaching by 22 to 30 per cent, and greenhouse gas emissions by between nine and 24 per cent. The exception was the wintering barn system in Otago, where nitrate leaching was reduced by 45 per cent, but greenhouse gas emissions were unchanged due to greater manure storage and handling. Important drivers of a lower environmental footprint are reducing nitrogen fertiliser and purchased feed. Their effect is to reduce feed flow through the herd and drive down both greenhouse gas emissions and nitrate leaching. Emission reductions in the lower-input systems of Waikato and Canterbury came at an average loss of profit of approximately NZ$100/t CO2-equivalent (three to five per cent of industry-average profit per hectare).

The Effects of System Changes in Grazed Dairy Farmlet Trials on Greenhouse Gas Emissions.

An important challenge facing the New Zealand (NZ) dairy industry is development of production systems that can maintain or increase production and profitability, while reducing impacts on receiving environments including water and air. Using research 'farmlets' in Waikato, Canterbury, and Otago (32⁻200 animals per herd), we assessed if system changes aimed at reducing nitrate leaching can also reduce total greenhouse gas (GHG) emissions (methane and nitrous oxide) and emissions intensity (kg GHG per unit of product) by comparing current and potential 'improved' dairy systems. Annual average GHG emissions for each system were estimated for three or four years using calculations based on the New Zealand Agricultural Inventory Methodology, but included key farmlet-specific emission factors determined from regional experiments. Total annual GHG footprints ranged between 10,800 kg and 20,600 kg CO2e/ha, with emissions strongly related to the amount of feed eaten. Methane (CH4) represented 75% to 84% of the total GHG footprint across all modelled systems, with enteric CH4 from lactating cows grazing pasture being the major source. Excreta deposition onto paddocks was the largest source of nitrous oxide (N2O) emissions, representing 7⁻12% of the total GHG footprint for all systems. When total emissions were represented on an intensity basis, 'improved' systems are predicted to generally result in lower emissions intensity. The 'improved' systems had lower GHG footprints than the 'current' system, except for one of the 'improved' systems in Canterbury, which had a higher stocking rate. The lower feed supplies and associated lower stocking rates of the 'improved' systems were the key drivers of lower total GHG emissions in all three regions. 'Improved' systems designed to reduced N leaching generally also reduced GHG emissions.