Forma correcta de citar este articulo: E. GONZÁLEZ and L.G. RUIZ-SUÁREZ 1995. METHANE EMISSIONS FROM CATTLE IN MEXICO: METHODOLOGY AND MITIGATION ISSUES. INTERCIENCIA 20(6): 370-372. URL: http://www.interciencia.org.ve

METHANE EMISSIONS FROM CATTLE IN MEXICO: METHODOLOGY AND MITIGATION ISSUES

E. GONZÁLEZ and L.G. RUIZ-SUÁREZ

SUMMARY

In Mexico, agriculture is the largest source of methane. In the 1990 National Greenhouse Gas Emissions Inventory (INE, 1995), Mexico's methane emissions are reported to be 1.89 teragrams (Tg); of these, 1.85 Tg come from livestock. Enteric fermentation from cattle is the source of 1.62 Tg and cattle manure is the source of 0.025 Tg. Methane emissions from enteric fermentation have been calculated using the Tier 1 approach of the 1994 Intergovernmental Panel on Climate Change (IPCC) methodologies (IPCC, 1994), which is based on continental means for cattle weight and emission factors. Methane from manure was calculated using a Tier 2 approach based on detailed information about cattle weight, food, and food digestibility. Tier 1 was used for emissions from enteric fermentation because the amount of detailed data required for a Tier 2 calculation is more demanding for emissions from enteric fermentation than from manure. In this paper, we show how Tier 1 approaches represent an upper bound for methane emissions from cattle. This is true because of the default values that are used for the average weight of cattle. We also show how an innovative but simple use of the some data given for the Tier 1 approach may enable us to better calculate emissions.

Because cattle ranching competes with other land uses, emissions from cattle ranching need to be considered together with emissions from other land uses. In this paper, we show the strong link between methane emissions from cattle and carbon dioxide emissions by land use change. Forecasts of methane emissions from cattle are useful for estimating future emissions, mitigation opportunities, and connections to sources and sinks of other greenhouse gases. One simple model for herd size has been proposed by Anastasi and Simpson (1993). In the model, herd size depends on the country population; this relationship is evident if we recognize that people raise cattle to feed themselves. We attempt to model herd size in Mexico up to the year 2025. Conclusions about mitigation options are given.

METHOD

Agriculture and population censuses and macroeconomic data dating back to 1950 were used. Herd structure was obtained from an extensive search in agriculture censuses and other government reports (INEGI, 1988, SIC 1975, 1965, SE 1955). Population data and growth rates were obtained from the National Council for Population (CONAPO, 1988). Economic data, GNP, and growth rates were obtained from NAFINSA (1991) and INEGI (1985). Land use data were obtained from UNAM (1990), SARH (1980), and INEGI (1988-1992). Linear regressions and trend forecasts were obtained using basic statistics available in commercial spreadsheet software.

Methane synthesis by enteric fermentation implies the use of energy that would otherwise be available for other purposes. Therefore, emissions from any given bovine depend on its size; the amount, digestibility, and energy content of its food; the energy it spends feeding itself-, the work it does; how much milk it produces, if it is a cow; the energy required for growth; and the fraction of energy wasted in methane synthesis. If all this information is available, then we calculate country- specific emission factors using a Tier 2 approach. Otherwise, we need to apply the Tier 1 approach, which is based on gross continental mean values for relevant parameters such as mean cattle weight and emission factors.

RESULTS

Analysis of Table B-1 in the Agriculture Appendix and of Table 4.4 in IPCC (1994) did show that simple linear relationships can be used to make better use of the data provided (see Table II). These linear relationships were obtained by a first-order fitting of energy intake (EI) to typical animal mass (TAM) and, later, a first order fitting of emission factors (EF) to El for values given in those tables for all regions of the developing world. Knowledge of country-specific TAM or, even better, average animal mass by age stratum, enabled us to do better methane emissions calculations. These calculations are more detailed than the oversimplified Tier 1 calculations and less burdensome than Tier 2 procedures. These relationships need to be improved, especially for dairy cattle where less data is available. However, this Procedure may enable a country to improve its methane inventory if at least TAM values are available.

Herd size depends on the country population. We have modeled herd size in Mexico using two models. In the first model, we base herd size only on human population (P) (see Figure 1, Curve B, Equation 1):

(1) heads = a + b * P

This model uses census data on human population for the decades spanning 1950 to 1990; for each decade, the actual growth rate was applied. Expected growth rates up to year 2000 were applied up to year 2025 (CONAPO, 1988).

The second model also includes per capita gross national product (GNP). This inclusion is based on the assumption that a more affluent society consumes more cattle on a per capita base than a poorer one (see Figure 1, Curve C. Equation 2):

(2) heads = a + b * P + c(P/G)

where G is the gross national product. This model takes GNP at 1970 constant prices. Currently, data at 1970 prices is available only to 1985. The model can detect the actual increase of real income that occurred in the 1970s. Declines in herd population due to economic crises such as the debt crisis of the 1980s or the current devaluation crisis cannot be detected by the model. To do so, the model would need a correction term including growth rates of per capita GNP or available income.

For this work, we have modeled herd size up to year 2025 using Equation 1. Because of the current uncertainty regarding economic growth, we assumed in the forecast that there were no changes in herd structure, management practices, or land-use intensity, and that available land was not a limiting factor. Our calculations are based on a cattle population of about 72 million heads; we estimate that the methane emissions associated with these cattle would be 2.71 Tg.

In contrast, if the current types of herd management (feedlot, grazing with supplement, and grazing) are extrapolated into the future, and the current expansion rate of the area dedicated to cattle ranching is assumed ( Toledo et al, 1989) through 2025, 141 million hectares would be needed for cattle ranching (Table III).

On the other hand, if current distribution of the herd by managing practices (feedlot, grazing with supplement, and grazing) is extrapolated into the future, and if, current expansion rate of the area dedicated to cattle rising applies (Toledo et al, 1989), then, this would be equivalent to 75% of the national land surface. Certainly cattle rising will face stronger competition for available land. Most of the increase on the land used for this activity has been at the expense of some type of forest (Cairns et al 1995, Massera 1995). Cattle rising will face stronger competition from farming activities and urban expansion. It will also face stronger challenges from forest protection policies. Indeed, increase in methane emissions from growing herd size is associated with land use change rated as the second largest source of carbon dioxide (25.8%) in Mexico, (Gay et al, 1995). Mitigation options on this activity should be associated with a shift from land-extensive cattle rising to land-intensive. Most of the methane emissions (Fig 2) are from range (43%) and grassing (46%). Part of the land used for these forms of cattle rising could be diverted to high energy cattle crops, allowing for an increase of the herd without further use of current forest land.

Into the future, mitigation on methane emissions from waste or even enteric fermentation could be dealt by energy recovery schemes.

CONCLUSIONS

A very simple new procedure for calculating methane emissions from enteric fermentation in cattle has been developed. The new method shows that Tier I procedures using default values overestimate methane emissions by varying amounts depending on actual herd structure and country specific TAM (in this case, by 6%). Connections between methane emissions from cattle ranching and other competing land uses are shown and mitigation options based on a shift to intensive cattle ranching are envisioned.

ACKNOWLEDGMENTS

This work was carried out under the INE-UNAM Collaborative agreement to support the Mexico Country Study, thanks to funding support from UNEP to the 1990 National Inventory of Greenhouse Gas Emissions. Additional funding for the inventory was provided by the US CSSP. Authors wish to thank B. Mar for all of her help in handling the large volumes of information obtained during the inventory work.

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