MedElevator Войти в исследования
← Поиск публикаций
Journal of dairy science · 2026

Comparison of 4 calculators for milk carbon footprint assessment on dairy farms in eastern Canada.

СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Nadon F, Matteau J-P, Binggeli S, Delmotte S, Kroebel R, Charbonneau É

Аннотация

Assessing the milk carbon footprint (MCF) is essential for understanding greenhouse gas emissions associated with dairy production and for guiding mitigation strategies on dairy farms. The objective of this study was to compare 4 commonly used MCF calculators in Québec (Holos-ULaval, Agriclimat, Logiag, and the Cool Farm Tool) across 20 dairy farms. The average MCF values were 1.02 ± 0.15 kg CO2 equivalent/kg of fat- and protein-corrected milk (FPCM) for Holos-ULaval, 1.05 ± 0.16 for Agriclimat, 1.13 ± 0.14 for Logiag, and 1.16 ± 0.27 for the Cool Farm Tool. The comparison revealed differences in methodology, data requirements, and applicability to Canadian dairy systems. Enteric fermentation was consistently identified as the main source of emissions across all 4 calculators. Soil carbon sequestration, considered by 3 of the calculators, was treated differently, resulting in contrasting effects on the MCF: the inclusion of soil carbon sequestration reduced MCF in Holos-ULaval (-5.5% on average) and slightly decreased it in the Cool Farm Tool (-1.8%), while increasing it in Agriclimat (+10.2%). This highlights the uncertainty associated with soil carbon modeling and supports its separation from whole-farm MCF assessments. Overall, these results underscore the importance of carefully selecting an MCF calculator according to assessment objectives and highlight opportunities to harmonize methodological approaches, improving consistency and relevance for both research and on-farm decision-making.