Interactions between nutritional interventions and dual mitigation of methane and ammonia emissions in dairy cows: a Bayesian meta-analysis

Livestock agriculture is a major contributor to both climate change and air pollution, through emissions of methane and ammonia. Despite their shared origins, mitigation policies for greenhouse gases and air pollutants are usually developed independently, creating a risk that interventions targeting one emission may have an unintended impact (cross-effect) on the others. Here, we present a meta-analysis quantifying the cross-effects of nutritional interventions in dairy cows intended to reduce methane and ammonia emissions. Because few studies measure both gases directly, two proxies were also considered: milk urea nitrogen (MUN) for ammonia and volatile fatty acid profiles for methane, although after exploratory analysis only MUN was used. Data from 51 peer-reviewed studies (117 treatments) were synthesised using a hierarchical Bayesian model to estimate correlated treatment effects across studies targeting methane or ammonia mitigation. Although significant uncertainties remain, interventions designed to reduce either gas on average decreased both: studies intending to reduce methane reduced methane by 5.1% and MUN by 2.2%. Studies focused on ammonia reduced methane by 4.8% and MUN by 25%. The probability of achieving simultaneous reductions in both was 0.63 for ammonia reduction studies and 0.41 for methane reduction studies, indicating that positive cross-effects (co-benefits) are more common than trade-offs. When the correlation between methane and ammonia responses could be estimated, it was weak and more likely positive than negative (ρ = 0.096 for the more accurately estimated methane mitigation studies, with 90% credible interval [-0.173, 0.357]), suggesting biological and management linkages that favour joint mitigation. Studies with more rigorous experimental designs appeared to provide greater efficiency in estimating treatment effects, underscoring the value of robust methodology. Overall, our results demonstrate that coordinated nutritional strategies can deliver co-reductions in methane and ammonia emissions from dairy systems, supporting the development of integrated policies at the interface of climate and air-quality goals.

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Journal
Journal of Dairy Research
Published
2026-11-05
DOI
https://doi.org/10.1017/s0022029926102696
Primary Topic
Ruminant Nutrition and Digestive Physiology
Type
article
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article

Interactions between nutritional interventions and dual mitigation of methane and ammonia emissions in dairy cows: a Bayesian meta-analysis

Gemma A. Miller, Zhou Fang, Sarah Brocklehurst, John R. Newbold
Journal of Dairy Research
Ruminant Nutrition and Digestive Physiology
article

Interactions between nutritional interventions and dual mitigation of methane and ammonia emissions in dairy cows: a Bayesian meta-analysis

Gemma A. Miller, Zhou Fang, Sarah Brocklehurst, John R. Newbold
article en

Abstract

Livestock agriculture is a major contributor to both climate change and air pollution, through emissions of methane and ammonia. Despite their shared origins, mitigation policies for greenhouse gases and air pollutants are usually developed independently, creating a risk that interventions targeting one emission may have an unintended impact (cross-effect) on the others. Here, we present a meta-analysis quantifying the cross-effects of nutritional interventions in dairy cows intended to reduce methane and ammonia emissions. Because few studies measure both gases directly, two proxies were also considered: milk urea nitrogen (MUN) for ammonia and volatile fatty acid profiles for methane, although after exploratory analysis only MUN was used. Data from 51 peer-reviewed studies (117 treatments) were synthesised using a hierarchical Bayesian model to estimate correlated treatment effects across studies targeting methane or ammonia mitigation. Although significant uncertainties remain, interventions designed to reduce either gas on average decreased both: studies intending to reduce methane reduced methane by 5.1% and MUN by 2.2%. Studies focused on ammonia reduced methane by 4.8% and MUN by 25%. The probability of achieving simultaneous reductions in both was 0.63 for ammonia reduction studies and 0.41 for methane reduction studies, indicating that positive cross-effects (co-benefits) are more common than trade-offs. When the correlation between methane and ammonia responses could be estimated, it was weak and more likely positive than negative (ρ = 0.096 for the more accurately estimated methane mitigation studies, with 90% credible interval [-0.173, 0.357]), suggesting biological and management linkages that favour joint mitigation. Studies with more rigorous experimental designs appeared to provide greater efficiency in estimating treatment effects, underscoring the value of robust methodology. Overall, our results demonstrate that coordinated nutritional strategies can deliver co-reductions in methane and ammonia emissions from dairy systems, supporting the development of integrated policies at the interface of climate and air-quality goals.

Journal of Dairy Research
Scotland's Rural College (GB), Biomathematics and Statistics Scotland (GB)
Openalex Percentile: Top 14%
Ruminant Nutrition and Digestive Physiology
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