Exceptions to the scenario rules
Atmospheric emissions associated with production
The historical data used in this study are taken from the study World Agriculture: Towards 2010 (AT2010, first published as FAO ; and later in expanded form as Alexandratos ). The historical data are standardized to conform to the AT2010 commodity classification. The 2010 projections of this FAO study are at the country level. They are the result of an interdisciplinary analytical analysis described by Alexandratos (1995: 407-420). For this study the FAO data and projections were aggregated; projections were made in different steps.
Although much more simple, the method used is in general terms similar to the AT2010 methodology. The various steps will be discussed in more detail. The order of the various topics discussed below reflects the order by which the different segments of the scenarios were developed. For China the AT2010 study provides forecasts of consumption, total production, trade, other uses and self-sufficiency ratios, but it does not give predictions on future areas, crop yields and animal productivity. In the scenarios for China, therefore, the historical trends were used to develop scenarios of yields.
The population scenario used in this study is different from that used in AT2010. Although the global total and the total population in developing countries is not much different, there are important regional differences (see Alexandratos, 1995: 426). For that reason the 1990 and 2010 projections of this study for food consumption, domestic demand, crop and livestock production deviate slightly from the AT2010 estimates and forecasts. In addition, the projections deviate from AT2010 where adjustments made by FAO were omitted. These adjustments concern mainly crop area and yield estimates for the base year1. To comply with the requirement of reproducibility, only the unadjusted referenced data were used in this study.
1 The base year of AT2010 is the 3-year average 1988/1990. indicated as 1989BY, based on data as known in May 1992, but with adjustments. These adjustments are not fully documented, but their implications for regional arable land and harvested land are indicated in Tables 4.5 and 4.6 in Alexandratos (1995).
Three baseline production scenarios have been developed. The medium baseline scenario is an extrapolation of the AT2010 projection. The other two scenarios are identical regarding the general assumptions on demography, GDP and food demand. They are different with respect to the production and technology assumptions. These differences are reflected in the estimates from 1990 onwards to include uncertainty starting from the base year. A summary of the three scenarios is presented in Table 2.
TABLE 2 - Summary of the three scenarios
Analysis of country data is required to analyse and understand certain conditions specific to a country. For this study the country data and projections were aggregated to the level of regions and individual crops were aggregated to crop groups. Livestock products were not grouped. The classification of regions, crop groups and livestock products is listed in Appendix 1. For each group of crops projections were made for both irrigated and rainfed production. Rainfed crop production is the aggregate of seven land classes (see Alexandratos, 1995:151-178).
The AT2010 study is based on the UN (1990) population projections for individual countries. In this study the updated population projection from FAO is used, which is slightly adapted from the UN (1994) population projection for 1990-2050 (Appendix 2). For the period 2050-2100 the growth rates used by Alcamo et al. (1994), which were originally produced for the IPCC IS92 scenarios by Pepper et al. (1992), were taken.
For the period 1960-2010 the FAO estimates of the mean regional per capita food demand were used. Scenarios for the period 2010-2100 were based on the relative growth rates of the per capita food demand given by Zuidema et al. (1994). Since Zuidema et al. (1994) give a scenario for total Africa, some assumptions had to be made for the two African sub-regions. The relative growth rates for Sub-Saharan Africa were assumed to be equal to those assumed by Zuidema et al. (1994) for total Africa. The growth rate for North Africa was assumed to be equal to that of the region Near East in Asia. Finally, for some commodities additional adjustments of the regional demand scenarios had to be made (see Appendix 2).
Historical data on the feed use of the different commodities are much less reliable than those for food consumption. Generally, information on feed use is not directly available, but is inferred from the supply-utilization-accounts (SUAs). It is even more difficult to make projections of feed demand. Alexandratos (1995) gives a very simple approach based on the fact that in developing countries much of the beef, mutton and milk production comes from non-grainfed animals, while pigs and poultry are mainly from grainfed production systems. The feed intensity weighted livestock production (referred to as Livestock Production, L.P.), calculated as 0.3 (beef + mutton production) + 0.1 (milk production) + 1.0 (pork + poultry + egg production) was used for individual countries by Alexandratos (1995).
Three scenarios of cereal feed use have been developed. The medium scenario is based on the assumption that the feed conversion rates are constant, i.e., that a 1% increase in L.I. leads to a 1 % increase in feed demand. For the aggregated data this assumption proved to reproduce the historical data reasonably well, and was therefore also used to calculate the future feed requirements for cereals, starchy foods and oil crops. For the other products the use as animal feed was assumed to be proportional to the food demand of the particular commodity in that region. For cereal feed use two other scenarios were developed to illustrate the uncertainty and the effect of variation of the feed use for the crop areas required. Chapter 4 discusses the scenarios of feed intensity.
Other uses of the various commodities as given in the SUAs include industry, seeds and waste. The variability in the total of these other uses in the historical periods of the various regions is only small. Therefore, the total of other uses, calculated as a percentage of the food demand + use as feed, is assumed to remain constant in the period after 2010.
The domestic demand is calculated as food demand (= per capita food demand x total population) + use as animal feed + other uses. For most of the animal products the use as feed and other uses are not relevant. A minor part of the milk is currently converted to animal feed.
Self-sufficiency ratios and trade
Regional agricultural production
Crop yields and animal production
Irrigated and rainfed cropped areas
Animal populations and harvested areas
Alexandratos (1995) described the forecasts for import, export and self-sufficiency ratios for the year 2010. The regional self sufficiency ratios for the different commodities are assumed to remain constant beyond the year 2010. The resulting net trade for the various commodities is presented in Appendix 22. Exceptions were made for Near East and North Africa, where the expanding demand for feed cereals lead to a demand for land exceeding the land balance or irrigation potential. Analogous to AT2010, it is assumed in these cases that countries prefer to produce meat and import feed stuffs instead of importing meat.
The regional production is calculated as the product of domestic demand and self sufficiency ratio. For sugar and oil seeds an additional term is needed, i.e., the extraction rate. The extraction rate is the amount of sugar or vegetable oil extracted from the total harvested biomass. The extraction rate for vegetable oil is assumed to remain constant after 2010, and the extraction for sugar crops is assumed to increase to 13% between 2010 and 2050.
The regional production can be achieved in different ways. For the crop groups temperate cereals, rice, maize, sorghum/millet, pulses, sugar, and starchy foods three scenarios were developed for both irrigated and rainfed production. These scenarios consist of different projections of irrigated areas, and irrigated and rainfed yields. For the oil crops and other crop groups scenarios were made, reflecting the mean change in yields assumed for the other crop commodity groups. Similarly, three production scenarios were developed for beef, pork, mutton, poultry and meat from goats, as well as for milk and eggs. For meat production the scenarios consist of projections for the offtake rates and carcass weights. For milk and egg production scenarios were made for the yearly yield per animal.
In general, the medium scenario forms a continuation after 2010 of the AT2010 trend. Currently, region-specific limiting conditions and constraints determine the maximum attainable production level for crops and animals. In the medium scenario the yield ceilings express these current conditions and constraints. The level of the yield ceilings may be raised as a result of major research breakthroughs, as assumed in the high, or optimistic, scenarios.
In the low or pessimistic variant of the medium scenario the expected research breakthroughs will not occur and even the current maximum levels may not be reached as a consequence of, for instance, increased incidence of pests and diseases.
The irrigated crop areas for the three scenarios are calculated on the basis of the following rules:
· Medium scenario: annual growth between 1990 and 2010 is equal to that assumed in AT2010;
· High scenario: annual growth is 1.25 x that of the medium scenario;
· Low scenario: annual growth is 0.75 x that of the medium scenario.
In all three scenarios the growth rate decreases by a factor of 2 in each consecutive period (2010-2025, 2025-2050, 2050-2075, 2075-2100). The rainfed area is calculated by taking the difference between the required production of a crop group and the irrigated production, and dividing the result by the yield. Hence the rainfed crop areas arise from the irrigated areas and yields.
The number of animals required to produce a certain volume of product can be calculated from the production scenarios. Similarly, the harvested area results from total irrigated and rainfed production, and yield level for both irrigated and rainfed crops.
Cropping intensity and arable land
The cropping intensity is the fraction of the arable area that is harvested. The cropping intensity may exceed 100% where more than one crop is harvested each year. Unfortunately, data are not available to produce estimates by crop. Therefore, only country average intensities can be used. Cropping intensities used in AT2010 deviate strongly from those derived from the production yearbooks1. The AT2010 estimates for the years 1989 and 2010 are used to make the results of this study comparable.
1 For example, the intensity derived from the official data from Latin America is 83%, while the intensity assumed in AT2010 is 61% (Appendix 20). For Near East in Asia the official data (70%) are much lower than AT2010 data (90%).
In the periods after 2010 the intensity was assumed to decrease by a factor of 2 in every consecutive period. Hence in 2010-2025 the annual increase is half that in the period 1990-2010, and in 2025-2050 it is half that in the years 2010-2025. The medium scenario is a continuation of AT2010, and the increase rate of the high scenario is 1.25 x that of the medium scenario, while in the low scenario the annual increase is only 0.75 x that in the medium scenario.
The cropping intensity has a certain maximum value determined by the climatic and soil conditions, and the irrigation potential. Using rough estimates for the current maximum cropping intensities for irrigated and rainfed crops, and assuming that the maximum intensity for rainfed cropping will remain constant, future maximum cropping intensities can be estimated when the irrigated area is known (see Chapter 7). The regional total harvested area and the cropping intensity determine the arable land area. The maximum arable area is given in the land balances (Alexandratos, 1995: 161-168).
The method used in this study to produce scenarios of fertilizer use is different from Alexandratos (1995)1. The approach is based on the hypothesis that the intensity of fertilizer use increases along with intensity of crop production. The amount of nutrient inputs per unit area in the form of mineral fertilizers may increase with increasing crop yields, but the nutrient input per unit product is assumed to be stable after a certain level of technology is reached. This implies a tendency towards higher fertilizer use efficiencies. A simple relationship between the overall regional crop production level and the fertilizer intensity (the amount of mineral fertilizer applied per unit of total produce for all crops) has been devised, whereby improving efficiency in general nutrient use is expressed by the assumed constant fertilizer intensity above a certain overall crop yield level. The three scenarios differ in the point at which the fertilizer intensity levels off (Table 2). The method will be discussed in more detail in Chapter 6.
1 In AT2010 the fertilizer use is obtained for the projection to 2010 by multiplying fertilizer input coefficients per hectare by the projected harvested area; these coefficients are specific to each crop, land class and yield level (Alexandratos, 1995: 417). The coefficients are not country specific, but they are yield specific, and thus the method is equivalent to using yield-fertilizer response curves for each of the seven land classes. In this study only two land classes are distinguished, i.e. irrigated and rainfed. Another problem is that the fertilizer-yield response functions defined by Alexandratos (1995) refer to current ranges of crop yields. If the period to 2100 is considered, the yields may exceed the maximum possible yields in the curves. An attempt was made to develop more general yield response curves, but extreme adjustments were required to reproduce the 1990 fertilizer use.
A number of exceptions to the general rules had to be made.
1. Since no base year estimates and projections of areas and yields to 2010 are available for China, the general procedure to extrapolate the AT2010 growth rates to the period after 2010 could not be followed. The 1980-1990 annual increase rates were used instead of the 1990-2010 growth rates. For each period (1990-2010, 2010-2025, 2025-2050, 2050-2075 and 2075-2100) the growth rate was then halved until the target yields or ceilings were reached.
2. The self-sufficiency ratios for individual cereals for the Near East in Asia and North Africa are not constant in the period 2010-2100. In these regions the potential expansion of arable land is limited by the land balance (Alexandratos, 1995) and the irrigation potential. In the Near East a gradual decrease of the SSR for temperate cereals (the major cereal in this region) from ~ 70% in 2010 to ~ 50% in 2100 was assumed to prevent the projected total arable area from exceeding the upper limit set by the land balance and irrigation potential. Similarly, in North Africa the self-sufficiency ratios for temperate cereals and maize were assumed to decrease to achieve a decrease in the self-sufficiency ratios for total cereals from 51% in 2010 to 40% in 2100.
3. For cattle in South Asia the carcass weight and offtake rates were assumed to be constant at the 1990 level in the medium scenario, at the level predicted for 2010 in AT2010 in the high scenario and at the 1989 base year estimate of AT2010 in the low scenario.
4. In cases where the calculated irrigated production exceeded the required production in a certain year, with rainfed production being eliminated, the irrigated area was adjusted downwards to match the calculated production with the demand. This correction and other adjustments were necessary in:· East Asia: Sugar (high scenario from 1990 onwards) the rainfed area was assumed constant and the irrigated area calculated from (total - rainfed production)/irrigated yield.
· South Asia: Maize (medium scenario after 2050 and high scenario after 2025), pulses (medium + high after 2075), root and tuber crops (medium after 2075, high after 2025), sugar (high after 2025) and other crops (high after 2010). In addition, yields for other groups were assumed not to increase further after 2010 in the medium, high and low scenarios. For temperate cereals (medium + high scenario) the rainfed production was assumed to remain constant after 2010, and irrigated area is calculated as (total - rainfed production) / irrigated yield.
· Near East in Asia: Sugar (high scenario from 1990 onwards) and other crops (high scenario after 2050).
· North Africa: Maize (from 1990 onwards), roots and tuber crops (medium scenario from 2010, high from 1990, low from 2025 onwards).
· Latin America: Pulses (high scenario in 2100).
Agricultural production contributes directly to emissions of greenhouse gases and other atmospheric pollutants through a variety of different processes. These include:
· CH4 emissions from livestock production. Methane is produced in herbivores as a byproduct of enteric fermentation, a digestive process. Both ruminants (e.g. cattle and sheep) and non-ruminants (e.g. pigs, horses) produce CH4.
· CH4 from animal waste management. Methane is produced during anaerobic decomposition of animal waste, mostly from confined animals, where animal waste is stored or disposed of in lagoons.
· CH4 emission from rice cultivation. Methane is produced during anaerobic decomposition of organic material in wetland rice fields. The methane is transported through the rice plants.
· NH3 and N2O emission from animal waste and mineral fertilizers.
In general atmospheric emissions of a compound from a specific source are calculated as E = A x e.f., where E = emission, A = activity level, e.f. = emission factor (emission per unit of activity). For example, in the case of animal production, the activity level is the number of animals and the emission factor is the emission of a substance per head and per unit of time. In this study estimates will be generated for NH3, CH4 and N2O for the following sources:
- Animal waste
- Mineral fertilizers
- Enteric fermentation
- Animal waste
- Wetland rice fields
The procedures for estimating atmospheric emissions used in this study are based on the Intergovernmental Panel on Climate Change (IPCC) guidelines for national greenhouse gas inventories, the FAO Livestock Environment Study and procedures proposed by the Global Emissions Inventory Activity (GEIA, a project of the International Global Atmospheric Chemistry Programme of IGBP).