Enteric Methane Emission Factor for Dairy Farming in Peru

The objective of this study was to determine the enteric methane (CH4) emission factor (EF) at the national level for Peruvian dairy cattle following the IPCC Tier II (2006, 2019) methodology. Data were collected from seven regions of Peru and classified according to the type of feeding as intensive, semi-intensive or extensive. It included farm information (geolocation) and livestock information for two seasons of the year. At the national level, lactating cows obtained the highest EF with 117 kg CH4/head/year, followed by heifers from 15 to 24 months of age (91 kg), non-lactating cows (74 kg), heifers from 12 to 15 months of age (67 kg), calves (62 kg) and pre-weaned calves (16 kg). Additionally, the highest EF was reported for lactating cows in the intensive system (151.8 kg CH4/head), which is 46.8 kg CH4/head more per year than that reported in the semi-intensive and extensive systems in the same animal category. The combined uncertainty in all animal categories was low to very low (between 9.4 and 18.72%), except for that of lactating cows, which was low to medium (22.24 and 26.72%). These results allowed us to find the EF that exerts the most pressure according to the level of intensity in Peruvian dairy farming.

Authors

Institutions

Publication Details

Journal
Dairy
Published
2024-12-11
DOI
https://doi.org/10.3390/dairy5040058
Primary Topic
Agriculture Sustainability and Environmental Impact
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enteric Methane Emission Factor for Dairy Farming in Peru

Javier Llacsa Mamani, Carlos Gómez, R. Ayala, Melisa Evangelina Díaz Fernández et al.
Dairy
Agriculture Sustainability and Environmental Impact
article

Enteric Methane Emission Factor for Dairy Farming in Peru

Javier Llacsa Mamani, Carlos Gómez, R. Ayala, Melisa Evangelina Díaz Fernández, Isabel Cristina Molina-Botero, W. Cavero Altamirano, William Leoncio Carrasco-Chilón, Gelver Romero Delgado, Eduardo Fuentes, Jorge Vela, Jorge Luis Zegarra Paredes, Mario Viera Valencia
article en

Abstract

The objective of this study was to determine the enteric methane (CH4) emission factor (EF) at the national level for Peruvian dairy cattle following the IPCC Tier II (2006, 2019) methodology. Data were collected from seven regions of Peru and classified according to the type of feeding as intensive, semi-intensive or extensive. It included farm information (geolocation) and livestock information for two seasons of the year. At the national level, lactating cows obtained the highest EF with 117 kg CH4/head/year, followed by heifers from 15 to 24 months of age (91 kg), non-lactating cows (74 kg), heifers from 12 to 15 months of age (67 kg), calves (62 kg) and pre-weaned calves (16 kg). Additionally, the highest EF was reported for lactating cows in the intensive system (151.8 kg CH4/head), which is 46.8 kg CH4/head more per year than that reported in the semi-intensive and extensive systems in the same animal category. The combined uncertainty in all animal categories was low to very low (between 9.4 and 18.72%), except for that of lactating cows, which was low to medium (22.24 and 26.72%). These results allowed us to find the EF that exerts the most pressure according to the level of intensity in Peruvian dairy farming.

DairyVol. 5(4)
National University of Saint Anthony the Abbot in Cuzco (PE), Catholic University of Santa María (PE), Universidad Nacional de Ucayali (PE), Instituto Nacional de Innovación Agraria (PE), International Center for Tropical Agriculture (CO), Universidad Nacional Agraria La Molina (PE)
Zero hunger
Openalex Percentile: Top 77%
Agriculture Sustainability and Environmental Impact
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.