8.2.1.3 Country Studies for Developing Countries

Several recent studies have been carried out as part of internationally co-ordinated country study programs conducted by the United Nation Environment Programme (UNEP) Collaborating Centre of Energy and Environment (UNEP, 1999a–1999g), and by the Asian Development Bank, United Nations Development Programme (UNDP), and the Global Environment Facility (ALGAS, 1999c–h). Summaries and analyses appear in Halsnaes and Markandia (1999). These recent studies supplement a number of earlier ALGAS studies of Egypt, Senegal, Thailand, Venezuela, Brazil, and Zimbabwe. The relevant results on aggregate cost are presented as individual country reports and summarized in ALGAS (1999) and in Sathaye et al. (1998). National study teams undertook the UNEP and ALGAS studies, using a variety of modelling approaches. The study results reported in Table 8.2 are based primarily on energy sector options, which are supplemented with a number of options in the transportation sector, waste management, and from the land-use sectors. The GHG emissions reductions are defined as percentage reductions below baseline emissions in 2020 or 2030, or as accumulated GHG emission reductions over the timeframe of the analysis. These analyses are very useful to indicate the extent and cost of clean development mechanism (CDM) potentials in all countries studied.

Table 8.2: Emission reduction potentials achievable at or less than US$25/tCO2 for developing countries and two economies in transition
Annual reduction relative to reference case
Country	MtCO2/yr	%
Argentina (UNEP, 1999a)	-	11.5
Botswana (UNEP, 1999c)	2.87	15.4
China (ALGAS, 1999c)	606	12.7
Ecuador (UNEP, 1999b)	12.7	21.3
Estonia (UNEP, 1999g)	9.6	58.3
Hungary (UNEP, 1999f)	7.3	7.6
Philippines (ALGAS, 1999h)	15	6.2
South Korea(ALGAS, 1999d)	5.3	5.7
Zambia (UNEP, 1999d)	6.09	17.5
Brazil (UNEP, 1994)	-	29
Egypt (UNEP, 1994)	-	52
Senegal (UNEP, 1994)	-	50
Thailand (UNEP, 1994)	-	29
Venezuela (UNEP, 1994)	-	24
Zimbabwe (UNEP, 1994)	-	34
Cumulative reduction relative to reference case
Country	MtCO2/yr	%
Myanmar (ALGAS, 1999e)	44	23
Pakistan (ALGAS, 1999f)	1120	23.7
Thailand (ALGAS, 1999g)	431	4.2
Vietnam (UNEP, 1999e)	1016	13.4

The ALGAS cost curves show a total accumulated CO₂ emission reduction potential of between 10% and 25% of total emissions in the period 2000 to 2020. The marginal reduction cost is below US$25/tCO₂ (see Table 8.2) for a major part of this potential, and a large part of the potentials in many of the country studies are associated with very low costs which even in some cases are assessed to be negative. The magnitude of the potential for low cost options in the individual country cost curves depends on the number of options that have been included in the studies. Countries like Pakistan and Myanmar have included relatively many options and have also assessed a relatively large potential for low-cost emission reductions.

Most of the country studies have concluded that options like end-use energy efficiency improvements, electricity saving options in the residential and service sectors, and introduction of more efficient motors and boilers are among the most cost-effective GHG emission reduction options. The studies have included relatively few GHG emission reduction options related to conventional power supply.

The UNEP cost curves exhibit a number of interesting similarities across countries. All country cost curves have a large potential for low cost emission reductions in 2030, where 25% (and in some cases up to 30%) of the emission reduction can be achieved at a cost below US$ 25/tCO₂ (See Table 8.2). The magnitude of this “low cost potential” is like in the ALGAS studies, influenced by the number of climate change mitigation options included in the study. Individual studies indicate that some of the countries like Ecuador and Botswana experience a very steep increase in GHG emission reduction costs when the reduction target approaches 25%. It must be noted that these country studies primarily have assessed end use energy efficiency options and a few renewable options and have not included major reduction options related to power supply which probably could have extended the low cost emission reduction area. The studies for Hungary and Vietnam estimate a relatively small emission reduction potential, which primarily can be explained by the specific focus in the studies on end use efficiency improvements and electricity savings that do not include all potential reduction areas in the countries.

The options in the low-cost part of the UNEP cost curves typically include energy efficiency improvements in household and industry, and a number of efficiency or fuel switching options for the transportation sector. The household options include electricity savings such as compact fluorescent lightbulbs (CFLs) and efficient electric appliances and, for Zambia, improved cooking stoves. A large number of end-use efficiency options have been assessed for electricity savings, transport efficiency improvements, and household cooking devices, but very few large scale power production facilities.

There are a number of similarities in the low cost GHG emission reduction options identified in the ALGAS and UNEP studies. Almost all studies have assessed efficient industrial boilers and motors to be attractive climate change mitigation options and this conclusion is in line with the conclusions of earlier UNEP studies (UNEP 1994b). A number of transportation options, in particular vehicle maintenance programmes and other efficiency improvement options, are also included in the low-cost options. Most of the studies have included a number of renewable energy technologies such as wind turbines, solar water thermal systems, photovoltaics, and bioelectricity. The more advanced of these technologies tend to have medium to high costs in relation to the above mentioned low-cost options. A detailed overview of the country study results is given in the individual country study reports (UNEP 1999a-g; ALGAS a-h, 1999).

Apart from the UNEP and ALGAS studies presented above, several additional independent studies were carried out for large countries with the help of equilibrium models. Examples are the ETO optimization model (for India, China, and Brazil), the MARKAL model for India, Nigeria, and Indonesia, and the AIM model for China. Table 8.3 reports the marginal costs (or other cost in some cases) for the abatement levels considered in the studies (relative to baseline). Marginal costs vary from moderate to negative, depending on the country and model used, for emission reductions that are quite large in absolute terms compared to the baseline emissions.

Table 8.3: Abatement costs for five large less-developed countries
Country	China	India	Brazil	China	India	Nigeria	Indonesia
Reference	Wu et al. (1994)	Mongia et al. (1994)	La Rovere et al.,(1994)	Jiang et al.(1998)	Shukla(1996)	Adegbulugbe et al.(1997)	Adi et al.(1997)
Span of study	1990–2020	1990–2025	1990–2025	1990–2010	1990–2020	1990–2030	1990–2020
Emissions in 1990 (MtCO2)	2411	422	264
Emissions in final year, baseline (MtCO2)	6133	3523	1446
% change	154%	735%	447%	130%	650%
Emissions in final year, mitigation (MtCO2)	4632	2393	495
% change	92%	467%	88%	53%	520%
% change: mitigation versus baseline, final year	–40%	–36%	–80%	–59%	–20%	–20%	–20%
Marginal cost in final year (US$/tCO2)	32	–16	–7	28	28	<30
Average cost in final year (US$/tCO2)						<5
Annual cost in final year (billion US$/yr)							47

These studies point out the interest of the same set of technologies for most of the countries, such as efficient lighting, efficient heating or air-conditioning (depending upon the region), transmission and distribution losses, and industrial boilers.

Importantly, it should be emphasized that in the way these studies are conducted, the potential for cheap abatement increases in proportion the baselines. In reality, this may not be the case because, in cases of rapid growth, an acceleration of the diffusion of efficient technologies is expected, which would lower the magnitude of the negative cost potentials. A second caveat to be placed is that an increase of the GDP per capita is consistent with the increase of wages and purchasing power parities which would increase the cost of carbon imported from these countries through CDM projects.

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