GBLoad was calculated in three forms relating subindices to either GDP, population, or area. Each form brings different information: GBLoadGDp points at the economy's efficiency of resource transformation into economic outputs, GBLoadpop captures the environmental justice aspects (equity and equal resource sharing) because all people should have equal rights to consume natural resources, and the results related to the area seem the most suitable from an environmental point of view because that index (GBLoadAREA) shows pressure exerted on the geobiosphere, which should not exceed the carrying capacity of a given area.
Using the GBLoadAREA form, the best results (i.e., lowest GBLoad values) are achieved by countries with low population density (Figure 14.1). They differ in consumption: Brazil and Venezuela have low consumption per capita (expressed by material, energy, and area needs). On the other hand, Finland, Norway, and Sweden have high per capita consumption. The worst results (i.e., the highest GBLoad values) are achieved by countries with both high per capita consumption and population density (the Netherlands, Belgium and Luxembourg). The highest values for GBLoadpop are attained by countries with high consumption per capita but low population density (Figure 14.2). Concerning this group of countries, the way in which results are expressed has great impact. Although these countries achieved the lowest GBLoad values from the viewpoint of pressure on the environment, they are the black sheep from the viewpoint of equality of resource use. Quite a different situation applies to the Czech Republic, where GBLoad equaled 50 in both cases. Greece and Spain are also rather balanced, whereas Hungary achieved very different results for each GBLoad form, as did the Scandinavian countries, even though the absolute values of the indices are much lower in Hungary's case. As regards the last form, GBLoadGDp, the lowest values (best results) were achieved by the economically developed European Union (EU) countries, Japan, and Norway, and countries such as Venezuela and Brazil placed much worse (Figure 14.3). Significantly worse results were also achieved by the countries that recently joined the EU (Czech Republic, Hungary). The authors did not investigate the reasons further, but the obvious reason for these disparities is the differences in the use of modern technologies and in labor productivity. Results of all three types of GBLoad presentation are shown in Figure 14.4.
Obviously, the core of our proposal is the three indicators (subindexes), selected as fundamental components of the entire human pressure on the environment. The GBLoad certainly does not capture all environmental problems caused by human activity (e.g., all the harmful effects of transport, dispersal of chemicals, and direct influence on climate and biodiversity). However, given the high correlation between selected indicators and such
phenomena as production and consumption of chemicals (correlated with material indicators), greenhouse gas emissions (correlation with energy indicators), and loss of habitats (correlation with land indicators), these factors are captured to some extent. We are conducting research on these and other correlations and relationships. We believe that the overall human-induced environmental pressure is captured in a fairly comprehensive way.
The proposed materials, energy, and land indicators are readily understandable by a broad public because no special environmental education is needed. Both their absolute values and the rank of entities being compared (townships, regions, countries) could be highly policy relevant when used for naming and faming or shaming. Local or national targets can be set. The analysis of time series may be revealing. The selected indicators can be complemented by a plethora of derived indicators (e.g., normalized by surface area or capturing the so-called decoupling phenomenon, i.e., links to GDP or other economically or socially critical variables).
GBLoad includes a challenge that will be addressed in future research: a possible double-counting (or even triple-counting) of some variables into the index. As an example we can take the pressure exerted by biomass harvesting: It is currently counted by material flow indicators in the form of matter of the biomass, by energy flow indicators in the form of biomass energetic content, and by Ecological Footprint in the form of the area needed to grow the biomass. Apart from this possible conceptual shortcoming, this multiple counting can be misleading for international comparison because a country that is more dependent on nonrenewable resources might have a lower GBLoad. This distortion occurs because biomass is counted three times, whereas nonrenewables are counted just once (e.g., minerals by material flow indicators) or twice (e.g., fossil fuels by material and energy flow indicators). The multiple counting might be justified on the basis of linking flows with impacts: The more impacts the particular flow would have, the greater weight would be given to it. However, the pressure impact analysis using material, energy, or land use data has not yet provided sufficient foundation.
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