In pursuit of reliable data

In the ongoing international climate debate, there is a need for increased data-based monitoring of the change that is happening and of its consequences. That became evident in reactions to the report of economist Nicolas Stern, who, two years ago, published scientific predictions and concrete figures on the economic dimensions of climate change. Applying the report’s findings to Germany, Sigmar Gabriel, the Federal Republic’s environment minister, said that every euro invested in climate protection today would result in saving twenty times that amount in future.
A diverse range of data is relevant to climate matters – from greenhouse emissions to a country’s forest inventory. But the quality of such data varies depending on regions and countries, not least because different methods are used to collect and analyse data. There are consequences in terms of just how binding data are.

A distinction is generally made between primary and secondary data: primary or raw data is measured or collected through observation and interviews or surveys. Once these data are assessed in relation to a particular aspect, they are referred to as secondary data. It is, of course, also of interest whether the data are collected by government officials or by independent researchers.

Secondary data about the future impacts of climate change – such as the Stern Report or analyses of global warming and rising sea levels – are often generated outside the official statistics system. Such studies are highly relevant, but not binding in a political sense. Analyses of human influence on the climate, for example, may well be scientifically substantiated, but they are not officially recognised, which has made it easy to downplay or even deny them. Climate policy, nonetheless, has to rely on future scenarios and predictions.

In many developing countries – south of the Sahara, for example – this general problem is exacerbated by another one: statistical offices are often still weak. They are not really in a position to produce environmental data for international reporting systems like the one of the UN Framework Convention on Climate Change (UNFCCC) in the same way as well-equipped national systems of rich nations do.

Germany, for example, has undertaken to set up a greenhouse reporting system for forests vis-à-vis the UNFCCC. The Federal Environment Agency has a close-knit institutional network at its disposal for doing so: local forestry offices, state statistical offices and the Federal Statistics Office all produce reports on forest area, composition and condition. In addition, there is the National Forest Inventory with approximately 50,000 samples and other supplementary surveys, which make it possible to obtain a very accurate greenhouse-emission balance.

Satellite images won’t do

Such closely interwoven data-collection systems do not exist in developing countries, but their forests change even faster than German ones. Therefore, satellite pictures are often used to get a rough overview. However, these images are often not particularly good, and they are certainly not suitable for closing gaps in data collection.

New methods have been developed under the UNFCCC for reports to be prepared all the same. The UNFCCC is an international framework for action. Its scientific body is the Intergovernmental Panel on Climate Change (IPCC). The IPCC became well-known through its scenarios on the effects of climate change. It also concerns itself with ways in which developing countries can produce reports. The UNFCCC secretariat collects and analyses the data.

With respect to organisation and structure, this international data-management initiative is comparable to other reporting systems – for instance the one of the Millennium Development Goals. Developing countries get support in terms of finance and capacity building for collecting the data. From 1997 to 2007, 134 countries took part in reporting. Six countries so far have supplied data for the second cycle, which has been running since 2008. It is expected that 67 countries will submit statistics by 2010.

Despite accompanying measures by the UNFCCC and IPCC, it is a challenge to implement the ambitious guidelines for the production of climate-related data. This is so, in part, because greenhouse emissions should be broken down and analysed according to human activities. In other words, precise data is needed on diverse, but overlapping sectors such as cattle breeding, cereal growing, energy consumption, industrial production, transport and so on.

Who has what information?

The heterogeneity of climate-relevant data means that it has to be sourced from different authorities. That is easier said than done in view of institutionally fragmented environment-statistics systems in sub-Saharan Africa.

Michael Pappoe works for Ghana’s environmental protection agency, his job is to make sense of data from different institutions. He mentions typical difficulties: “Different institutions use different methods to collect data, often the data does not tally, and it is difficult to tell who has what information and whose information is more reliable.”

To solve such problems, most developing countries have drawn up National Strategies for the Development of Statistics (NSDS). InWEnt supports partners in implementing these strategies. However, they are still in the early stages and, as a rule, the main focus is on economic and social statistics, not on environmental statistics. International climate policy would benefit from better global statistics – which have to be based on national data. Therefore, it is important that climate protectors cooperate with the institutions that are engaged in the NSDS.

In April, the United Nations Statistics Division held a conference on “Climate Change and Official Statistics”. One of the items on the agenda was how official statistics can record data better to create politically binding principles. Two approaches with different outcomes for environmental statistics are conceivable in Africa: the indicator-based approach and integrated environmental and economic accounting.
– The indicator-based approach conforms to the status quo. Environmental data is collected within internationally recognised frameworks, which facilitates data standardisation. The corresponding weaknesses have already been mentioned.
– The system of integrated environmental and economic accounting (SEEA), on the other hand, is derived from the system of national accounts. It incorporates the factor of nature into the calculation of key economic data. However, factors such as the economic costs of land use are relatively complex to determine. For that reason, the approach is applied with reservations, even in industrialised countries. It does, however, have the advantage of making climate change processes clear by means of economic figures, which has great political impact. In view of the fact that the official statistics system in Africa is weak overall, it seems doubtful whether this approach can quickly become established.

The two approaches do not exclude one another. On the contrary, integrated environmental and economic accounting is not possible without basic data. Therefore, a stronger interconnection of the two approaches would be desirable for better climate-related information management.

A reliable database would make it easier for developing countries to benefit from climate-related opportunities like the Clean Development Mechanism (CDM). The CDM basically makes it possible to credit emission reductions in poor countries against the industrialised countries’ obligation to reduce emissions. Obviously, such complex trade relations require a sound data base, including precise evidence of the trends in forestry.