We call the pressures in question a geobiosphere load (GBLoad). Despite the fact that the term load might imply "impact," we concentrate merely on pressures exerted on the environment by social and economic developments (e.g., resource extraction, resource transformation into products and services, and subsequent emissions). To put it clearly, the pressure from a ton of coal equals the pressure from a ton of biomass.
Referring to our previous research (Moldan and Billharz 1997; Hak 2002), we focus on the geobiosphere load in three categories: material and energy flows and land requirements. Material flow analysis, energy flow accounting, and ecological footprints are useful points of departure for the development of the specific indicators in these three categories.
The GBLoad index is calculated in three forms (subindices related to either area, population, or GDP) in a transparent way following a straightforward formula. By proposing a single index based on three clearly defined indicators only, we fulfill the first of the fundamental prerequisites: a small number of individual indicators. Formally, our proposed GBLoad resembles the UNDP's Human Development Index based on three fundamental, rather obvious components of dignified human lives: health, education, and income. These three items are characterized by comprehensible indicators that are then joined by a simple and transparent mathematical formula. Our index is constructed in a similar fashion and is based on three indicators that, in our opinion, capture the most important factors of environmental sustainability.
Energy, materials, and land can be regarded as the essential components and prerequisites of nature's services (Daily 1997). The idea of ecosystem services is well established and is being developed as a fundamental concept by the ongoing Millennium Ecosystem Assessment program (MA 2003). Provision of energy and materials basically equals the provisioning services of ecosystems (e.g., food, fiber, energy resources, bio-chemicals, or freshwater). Land, in relation to other environmental media, is a prerequisite for all kinds of ecosystem services (beyond the provisions mentioned, land provides further supporting services such as primary production, regulating services such as climate regulation, and cultural services such as recreation).
The material component of the GBLoad index is based on data and indicators of economy-wide material flow analysis (MFA). MFA was developed in the 1990s with the cooperation of many research institutes and organizations, including the World Resources Institute; the Wuppertal Institute for Climate, Environment and Energy; the Institute for Interdisciplinary Studies of Austrian Universities (Department of Social Ecology), and Eurostat. In 2001, these methods were standardized in a methodological guide (Eurostat 2001a). The aim of the method is to quantify the physical exchange between the national economy, the environment, and foreign economies on the basis of total material mass flowing across the boundaries of the national economy. These flows consist of material inputs to and material outputs from the national economy. Material inputs are all mined raw materials and consumed biomass. Material outputs are air and water emissions, solid waste, and so-called dissipative use of products, such as are fertilizers, pesticides, and winter filling. The difference between inputs and outputs is the quantity of materials accumulated in the economic system in the form of construction, transport infrastructure, durable products, and so on (net addition to stock [NAS]). It is also important to include so-called unused extractions or hidden flows. Unused extractions are material flows that have taken place as the result of resource extraction but do not directly enter the economic system. Examples include biomass left in forests after logging, overburden from extraction of raw materials (as in open cast coal mining), earth movements resulting from the building of infrastructure, and dredged deposits from rivers. Foreign trade and related indirect flows (such as overburden in coal mined abroad and subsequently imported) also play an important role in the analysis because they also represent an important flow of material across the boundary of the economic system.
MFA provides an important database to infer series of environmental pressure indicators. The most commonly used material flow indicators can be divided into several groups:
Input indicators: Direct material input (DMI) equals domestic used extraction (excavated raw material, harvested biomass) plus imports; total material requirement (TMR) includes domestic used and unused extractions, imports, and their indirect flows. Output indicators: Domestic processed output (DPO) comprises emissions to air, land-filled wastes from industrial processes and households, the material load in wastewater, and dissipative uses and losses of products; total domestic output (TDO) includes DPO and unused domestic extractions. Consumption indicators: Domestic material consumption (DMC) is calculated as DMI minus exports; total material consumption (TMC) is TMR minus exports and their indirect flows; NAS measures the physical growth rate of the economy. Each year new materials are added to economic stocks, such as new buildings and durable goods, and old materials are removed from this stock and become wastes.
All these robust indicators have been developed into a fixed methodological framework, and they are characterized by a transparent method of data aggregation. Because all components of MFA indicators (e.g., extracted minerals, mined fossil fuels, or harvested biomass in case of DMI) are measured in tons, there is no limitation with regard to aggregation of data in different physical units (this applies for direct and used flows; indirect and unused flows usually are calculated by means of conversion coefficients). MFA indicators meet common policy relevance criteria. They relate directly to human pressure on the environment. They are designed to cover all material flows, so they are representative and comprehensive. Moreover, they are comparable because they are constructed on the basis of a standardized method. For these reasons, material flow indicators currently appear more often in official results of many organizations such as Eurostat, the European Environment Agency, and UN agencies (Eurostat 2001a; EEA 2004; UN 2001), even though some of MFA-related issues have not yet been addressed (e.g., linkage of pressures expressed by material flow indicators to specific impacts). The developing research in this field focuses on the fact that some enormous flows are not necessarily very harmful (e.g., overburdens from mines), whereas smaller highly toxic ones can be much more damaging to humans and nature (Steurer 1996; Van der Voet et al. 2004).
One of the aforementioned indicators will be selected or a new indicator (a combination of the existing ones) will be developed for the GBLoad index. One must keep in mind that all of these indicators are highly correlated. At present, the TMC indica tor seems to best fulfill the requirements of a suitable indicator for the GBLoad concept; it is a subject of our current research.
Energy flow accounting (EFA) aims at establishing a complete balance of energy inputs, internal transformations, and energy outputs of a society, or of a defined socioeconomic unit. On a macroeconomic level, EFA uses a similar concept as MFA (Haberl 2001). Its aim is to assess all inputs and outputs of a socioeconomic system in energy units (joules). EFA uses existing notions and methods of conventional energy balance as far as possible in order to trace energy flows through an economy and obtain indicators for the amount of energy a society is able to harness for its purposes (Krausmann and Haberl 2002; Schandl et al. 2004). Contrary to the conventional energy balances (IEA 2000; UN 2000), EFA includes inputs of energy-rich materials not directly used for energy conversion (e.g., wood for furniture, construction, or the paper industry) and also includes inputs of domestic animal and human work. These have a crucial impact on energy balances in preindustrial societies or small localities, where human and animal work can be significant components. EFA also includes inputs of nonmaterial energy carriers such as wind power, hydropower, heat, and electricity. EFA provides an important database for the derivation of a number of energy indicators. These quality-adjusted measures of energy flows are very useful in understanding the biophysical inputs needed for economic growth (Ayres et al. 2002). As with material flow indicators, it is possible to use EFA to assess changes or trends of crucial importance for the sustainability of national systems: intensity of energy use, energy consumption patterns, or energy use of regions.
EFA provides conceptually similar environmental pressure indicators as MFA does. The most important energy flow indicators can be grouped as follows:
Input indicators: Direct energy input (DEI) is the total amount of energy entering the socioeconomic component (either by domestic extraction or by imports); total primary energy input (TPEI) is defined as direct energy input and hidden flows (HFs), which can be classified as domestic hidden flows (DHFs) and imported hidden flows (IHFs). Output indicators: Useful energy (UE) means total energy benefit, connected with the end use of energy. This is counted as final energy use (FEU) multiplied by energy efficiency of end-use devices; FEU is a commonly used indicator (not only in EFA) and is the energy sold to end users. Against widely used FEU, EFA also counts biomass as an energy-rich material that results in higher values. Consumption indicators: Domestic energy consumption (DEC) is calculated as DEI minus exports; total energy consumption (TEC) is TPEI minus exports and their hidden flows; NAS measures the growth rate of the economy. Each year some energy-rich materials are added to economic stocks (e.g., new wooden buildings, energy carriers, and food in tins), and old materials are removed from this stock (e.g., eaten, burned) and become wastes.
Each of these aggregated indicators is compiled through a transparent method of data aggregation. At the end, all components of EFA indicators (e.g., electricity, fuels, or harvested biomass) are expressed in the same energy unit (joules). However, before the aggregation, some conversion factors must be used. EFA indicators also meet other criteria, such as being meaningful (EFA indicators relate directly to human pressure on the environment), representative (they are designed to cover all anthropogenic energy flows), and comparable (they are constructed on the basis of a standardized methodology).
Similarly to material flow indicators, the selection of the most appropriate indicator in this case is not finished. Analogously to TMC, the best candidate for the suitable indicator in the GBLoad context seems to be TEC. Again, research activities to resolve this question are under way. In general, the EFA method is less developed than its MFA counterpart, but research in this field is extensive and includes our own.
Together with energy and material flows, land and land area requirements are the third important category of resource input for economic activities. There is no doubt about the importance of land use for ecological processes. Land provides the spatial context (i.e., source function) for and bears the impacts of (i.e., sink function) human activities. Land-based trade balances illustrate the nondomestic land areas appropriated for the production of goods and services abroad (i.e., imports) and the domestic land area needed to produce the goods and services exported to the rest of the world (Hubacek and Giljum 2003). Several approaches or concepts try to assess human use of land, linking land use and socioeconomic data. The most popular ones include the Ecological Footprint (EF), which assesses land needs for individual consumption of goods and services (Wackernagel and Rees 1996). The EF concept is not based on actual land use or land cover data, and its results are hypothetical area units. EF will be taken as a point of departure (as a proxy for the "land requirements" indicator to provide results for pilot calculations). We have recently done research for a suitable indicator and its adaptation to provide the "land (area) requirement subindex" for GBLoad. We are considering tying the land pressure indicator to the degree of "naturalness." It will combine several variables (e.g., land cover, fragmentation, biodiversity) and will use approaches for evaluating anthropogenic influence on productive land and sea area. There are several examples to be modified and used: an assessment of land types based on their "naturalness" (Míchal 1994), the concept of human appropriation of the net primary production (Vitousek et al. 1986; Krausmann 2001; Haberl et al. 2004), and the classification developed by Daly (1996) for the hierar-chization of capital stocks.
Although some degree of subjectivity is inherent in the GBLoad construction (selection and definition of the main realms of human-induced pressure on the environment), there are advantages that outweigh it: All three component indicators (subindices) of the GBLoad are expressed in clearly defined physical units, and they are not subject to any weighting or assumptions affecting the mathematical calculation. Such steps in the index method always jeopardize the credibility of results. We simply count tons, joules, and hectares or any other units of matter, energy, and surface area.
The resulting index, called GBLoad, is constructed as an average of the individual indicators or subindices (material flow, energy flow, and pressure on land resources). A similar approach has been used for some other indices, such as the Human Development Index, the Environmental Sustainability Index (ESI), and the Index of Environmental Friendliness (Puolama et al. 1996; Global Leaders for Tomorrow Environment Task Force 2002; UNDP 2003). The GBLoad index is constructed as an average of the three cumulative standard normal distributions of z scores of subindices, which were first related to a chosen reference scale (area, population, or GDP). A similar approach is used for calculation of ESI. The construction of the subindices from variables follows standard statistical methods and is shown in Box 14.1.
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