Livestock country inventory: Bulgaria

Sadie S

Overview of Bulgaria’s current Tier 2 approach

Methane from enteric fermentation and N2O from animal sources have consistently been identified as key sources in Bulgaria’s GHG inventory. Together, cattle and sheep have accounted for 80-90% of enteric fermentation emissions in each inventory year since the late 1980s. Bulgaria began to use the IPCC Tier 2 approach for cattle in 2010, and for sheep in 2011. Inventories since 2003 have reported using a Tier 2 approach for methane emissions manure management, but no technical description of the approach used is given in the inventory reports.

Table 1: Overview of Tiers used for livestock methane emissions in Bulgaria’s national GHG inventories

Livestock typesTier used for enteric fermentation (CH4)Year adopted*Tier used for manure management (CH4)Year adopted*
Dairy cattleT22010T22003
Non-dairy cattleT22010T22003
SheepT22011T1-
PigsT1-T22003
OtherT1-T1-

*Year refers to the year of NIR submission

Enteric fermentation

Description of approach: Bulgaria implements the IPCC Tier 2 model for both cattle and sheep. The approach estimates daily gross energy (GE) intake on the basis of animal performance, management practices and environmental factors. GE is converted to methane using a methane conversion factor (Ym), and estimated daily emissions are multiplied by number of days to make an estimate of annual emissions per head. Activity data on the population of livestock of each category are multiplied by the EF to estimate total annual emissions from enteric fermentation for that category of livestock.
Implementation of the approach:

Activity data: Livestock population data is provided each year by the Ministry of Agriculture. Emissions are separately estimated for mature dairy cattle and four other types of cattle (Table 2). For the period 1988-2000, livestock population data came from the Yearbooks of the National Statistics Institute. Since 2000, there has been an agreement between the Executive Environment Agency the centralized unit responsible for inventory compilation with the Agrostatistics Department of the Ministry of Agriculture and Food (MAF) to provide activity data for the inventory. MAF collects the agricultural statistics through surveys conducted in accordance with European regulations(1).

Table 2: Livestock categorization in Bulgaria’s Tier 2 approach

Dairy cattleNon-dairy cattleSheep
1 category (mature dairy cattle)4 categories defined by age and sex (mature male, mature female, young male, young female)4 categories defined by:
Age, physiological status (female, male intact, male castrates) and purpose (meat/wool, milk)

Estimation of emission factors: Tables 3 and 4 show the sources of data used when Bulgaria first applied the Tier 2 approach (2010) to dairy and other cattle and in its most recent inventory submission (2017). For dairy cattle, Bulgaria uses country specific data for live weight, calf birth weight, annual milk yield and fat content of milk.

Since NIR 2017, a country specific value for feed digestibility from a published paper has been used for dairy cattle. All other parameters use IPCC default values. For non-dairy cattle, Bulgaria uses country specific data for live weight and mature weight, and IPCC default values for all other parameters. For sheep, national data on live weight and weight at weaning, milk yield and fat content of milk are used. All other parameters use IPCC default values.

With the exception of digestibility for dairy cattle, country specific values are updated annually. Estimated GE and EFs thus vary year to year. For mature dairy and non-dairy cattle, live weight estimates remain constant over the time series. For young growing cattle and sheep, live weight estimates vary year to year. The live weight estimates reported by the Ministry of Agriculture are not published data but are reportedly based on measurements. No detail is given in NIRs on how the measurements are conducted. The main drivers of change in emission factors have been an increase in milk yields, change in live weight of young cattle and a decline in the dairy cattle herd, causing a change in the population structure of animals in the ‘non-dairy cow’ category.

Table 3: Data sources used for Tier 2 estimate of enteric fermentation emissions from mature dairy cattle

Model parameterData source in 2010Data source in 2017
Average live weightMinistry of AgricultureLivestock Breeding Agency
Calf birth weight (kg)Eq. 7 IPCC 1996 Ref ManualMinistry of Agriculture
Coefficient for maintenance (Cfi)IPCC defaultIPCC default
% of time spent on pasture
Coeff. for feeding situation (Ca)IPCC defaultIPCC default
Annual milk yield (kg)Ministry of AgricultureMinistry of Agriculture
Average fat content (% fat)Ministry of AgricultureMinistry of Agriculture
% pregnant in the year
Coefficient for pregnancy (Cpreg)IPCC defaultIPCC default
DigestibilityTable 10.2 IPCC 2006 Ref ManualScientific publication
Gross energy (GE)CalculatedCalculated
Methane conversion factor (Ym)Table 4.8 GPG 2000IPCC 2006 GL
Emission factorCalculatedCalculated

Table 4: Data sources used for Tier 2 estimate of enteric fermentation emissions from non-dairy cattle

Model parameterData source in 2010Data source in 2017
Average weightMinistry of AgricultureLivestock Breeding Agency
Calf birth weight (kg)Eq. 7 IPCC 1996 Ref ManualMinistry of Agriculture
Daily weight gain (kg/day)IPCC default‘Default’
Coefficient for maintenance (Cfi)IPCC defaultIPCC default
% of time spent on pasture
Coeff. for feeding situation (Ca)IPCC defaultIPCC default
Annual milk yield (kg)Ministry of Agriculture
Average fat content (% fat)Ministry of Agriculture
% pregnant in the year
Coefficient for pregnancy (Cpreg)IPCC defaultIPCC default
DigestibilityTable 10.2 IPCC 2006 Ref ManualIPCC default
Gross energy (GE)CalculatedCalculated
Methane conversion factor (Ym)Table 4.8 GPG 2000
Emission factorCalculatedCalculated

The country specific data on milk production and live weight come from surveys conducted by the Agrostatistics Department of MAF. Data on the fat content of milk is obtained from EUROSTAT. Data on live weight is provided by the Agrostatistics Department of MAF. For mature cattle, the data are informed by measurements, but are not formally published data and NIR 2017 notes that the data can be considered ‘expert judgement’. These weights are constant over time. For calves and heifers, the data are based on measurements, which change from year to year.

Inventory improvements: Bulgaria’s initial application of the Tier 2 model used a mix of country-specific and default data. Over time, the default values used have changed, and the number of parameters using country specific data has increased (Table 5).

Table 5: Cattle enteric fermentation emission inventory improvements in Bulgaria (2011-2017)

 ImprovementYear*
Activity data-
Livestock characterization-
Emission factorsUsed revised country specific values for milk fat content2017
Revision of live weight estimation method for young cattle2014
Adoption of IPCC 2006 GL Ym default value2015
Used country specific value for feed digestibility for dairy cattle2017
Uncertainty estimationUNCAD recalculated by Ministry of Agriculture2017

*Year refers to the year of NIR submission

Revision of live weight data: Until NIR 2014, the inventory used the slaughter body weight of young cattle, but this led to overestimation of the IEF for young cattle. Following an EU Effort Sharing Decision (ESD) review, Bulgaria changed to using average live weight rather than slaughter weight, and recalculated previous inventory estimates.

Revision of country specific value for milk fat content (2017): Before 2017, data for milk fat content was provided by the Agrostatistics Department at MAF. In 2017, an official time series from 2006 onwards became available from EUROSTAT, and the emissions time series for dairy cattle was recalculated in 2017 using the new dataset.

Adoption of IPCC 2006 GL Ym value: Prior to NIR 2015, the IPCC GPG 2000 Ym values were used. In 2015, the IPCC 2006 GL values were adopted.

Used country specific value for digestibility for dairy cattle (2017): In NIR 2017, a new country-specific value for %DE was used for dairy cattle. This value derived from a scientific publication that used acid insoluble ash as a marker in fresh herbage and feces to determine digestibility (2).

Revised UNCAD estimate (2017): For the uncertainty of emission factors, Bulgaria’s inventory uses a default uncertainty estimates from IPCC 2006 GL. For activity data, until 2017, the country-specific estimate of activity data uncertainty was 2%, but in 2017 a new estimate of 0.64% was provided by MAF based on examination of whether the livestock population survey precision requirements in EU regulations had been met.

Manure management (Methane)

Approach used: IPCC approach (T2 for cattle and swine), T1 for other livestock.

Implementation of the approach:

  • Activity data are taken from national statistics.
  • VS excretion rates for the different types of cattle are based on the digestibility and other input values used to estimate GE for enteric fermentation (see above). IPCC default values are used for other parameters required for estimation of VS. For pigs, country-specific VS estimates are based on a scientific publication, which in turn relied on a combination of published and unpublished literature (Penkov et al. 2014).
  • Values for Bo and MCF use IPCC default values.
  • The fraction of manure handled in different management systems is based on a survey conducted every 5 years by the Agrostatistics Department at MAF. This survey documents the number of animals per species and category; the quantity fresh manure and nitrogen per animal category; and the nitrogen emitted into different parts of the ecosystem. The data collection methodology is based on the methodologies used by EUROSTAT. The distribution of manure management systems in the intervening years is estimated by extrapolation. This requires recalculation of emission estimates for the years prior to a year with new survey data.

Inventory improvements:

 ImprovementYear*
Activity dataRecategorization of pig manure AWMS2017
Manure management systemsRevision of MCF for anaerobic lagoons2015
Emission factorsRe-estimation of young cattle weights based on ESD review2014
Uncertainty estimationUNCAD recalculated by Ministry of Agriculture2017

*Year refers to the year of NIR submission

Bulgaria has made a number of recalculations of manure management emissions in recent years. Among the few that are transparently documented are:

Revision of MCF value for anaerobic lagoons (2015): Prior to 2015, an MCF of 90% was used for anaerobic lagoons. In NIR 2015 this was revised to 70% on the basis of recommendations from expert review.

Recategorization of pig manure AWMS from anaerobic lagoons to liquid storage systems (2017): Prior to 2017, about 90% of pig manure was assigned to anaerobic lagoons. Review of the 2006 IPCC GL definition of anaerobic lagoons at the request of the expert review found that environmental and management factors in Bulgaria are not consistent with this definition. These AWMS were recategorized as liquid storage systems, which have a lower MCF (20%).

Uncertainty management

Prior to NIR 2017, UNCAD was estimated at 2% for all livestock types. In NIR, a new estimate of UNCAD was used. The new UNCAD estimate is based on the official statistical data in the country. It is country specific and based on the Regulation (EC) No 1165/2008 of the European Parliament and of the Council concerning livestock and meat statistics and repealing Council Directives 93/23/EEC, 93/24/EEC and 93/25/EEC. The estimate was made using statistical samples representative of level 6 statistical areas (NUTS2). As a result, UNCAD has been revised in NIR 2017 to 0.64% for cattle, 0.51% for swine and 1.63% for sheep. Total uncertainty for livestock sources has decreased. UNCEF estimates use IPCC defaults.


(1) Regulation (EC) No 1165/2008 of the European Parliament.

(2) Todorov & Ali, 2009


Resources

Penkov D, Gerzilov V, Despotov HHP. 2014. Methods for Determining the Release of Greenhouse Gas Emissions from Pig and Poultry Production in the Republic of Bulgaria. Global Journal of Science Frontier Research: Department of Agriculture and Veterinary, 14(5).