Human Footprint

While previous discussions relating to global demographics, both past and present, have provided some insight to the complexity of human interactions, which may go some way to explaining the existing global population and population growth in various regions of the world; the wider reasons behind resource usage has not necessarily been resolved. For while the previous discussion of ‘resource economics’ suggested that unchecked capitalism might be a cause of over-consumption, it did not address the question tabled at the end of this discussion:

What long-term consequences are being implied?

However, before the question above can be addressed, the idea of the ‘human footprint’, ‘biocapacity’ and ‘sustainability’ all need to be introduced. For based on such ideas, some have attempted to calculate the ‘Sustainability of the Human Population’.

Every human activity demands natural resources and produces waste. The measure of the impact on the environment is referred to as the ecological or human footprint.

In this context, the human footprint is a measure of the resources that humanity uses or takes from the bio-capacity of the Earth. Therefore, it might also be useful to provide a general definition of this term:

The Earth’s biocapacity refers to the biological capacity of planet Earth to produce an on-going supply of renewable resources and to absorb any pollution by-products .

In this respect, these two definitions provide the basis of an ecological ‘balance sheet’ of resource assets versus footprint liabilities. If we pursue this financial analogy, when your liabilities erode your assets, you end up in debt; likewise the human footprint can also grow to exceed the biocapacity of planet Earth, which then means the total biocapacity of the Earth can be exhausted. Essentially, this defines the difference between sustainability and unsustainability:

Basically, unsustainability occurs when the human footprint exceeds the biocapacity of planet Earth.

As a result of a debate between Barry Commoner and Paul Ehrlich, in the 1970’s, an equation called the ‘Commoner-Ehrlich equation’ attempted to quantify, albeit in 3 simple terms, the impact of human activity on the environment as follows:

Impact [I] = Population [P] * Affluence [A] * Technology [T]

In words, this equation suggests that the ‘human impact (I)’ on the environment equals the product of ‘population [P], affluence [A] and the technology [T]’. In the current context, we might assume that [P] equates to the global population at some point in time, e.g. now, while [A] is reflective of the average consumption within the population defined by [P]. The variable [T] is essentially an efficiency factor that attempts to quantify whether technology reduces or increases the overall impact on the environment. While it may be very difficult to assign [T] any meaningful value, it might be realised that if [P] increases exponentially, while [A] remains static, then [T] would have to decrease exponentially just to maintain the same impact [I]. However, ongoing data from the World Bank seems to show that while [T] may have decreased, [P] is still increasing faster, as is [A]. As such, the overall environmental impact [I] is still increasing, as all observations and analysis continue to suggest. While it is clear that this equation is too simplistic to represent the totality of the complexity outlined, it may still be useful as a general characterisation of the problem space under discussion. For, in practice, there are multiple dependencies between the variables [P,A,T], such that it would be more accurate to say that [I] has to be some complex function of [P,A,T]. For example, changing the value of [T] by some amount does not necessary change [I] by a corresponding amount, if either [P] or [A] are affected by the same change in [T].

So how might we estimate of the impact [I]?

The first academic publication introducing the idea of ‘ecological footprinting’ was published by William Rees in 1992, although the concept was actually developed as the PhD dissertation of Mathis Wackernagel. This type of analysis attempts to compare human demands for natural resources against the biosphere's ability to regenerate resources. As a generalisation, it does this by assessing the biologically productive land and marine areas required to produce the resources a population consumes and the ability to absorb its waste pollutants using known technology. The resulting ‘footprint’ value is calculated in terms of various factors, e.g. carbon, food, housing plus goods and services, but then often quantified in terms of the ‘number of Earths’ needed to sustain the global population at a given level of consumption. However, within this process, resource usage is equated to the consumption of energy, biomass, building material, water and other resource, which are then quantified in terms of a normalized measure of land area, i.e. global hectares (gha). In 2007, the ‘average’ biologically productive area per person worldwide was estimated to be 1.8 global hectares (gha) per capita.  However, as a comparison, the US footprint per capita was 9.0 gha, while China's was closer to the 1.8 gha average. As a net result, the WWF claimed that the human footprint was already exceeding the biocapacity of the planet by 20%. The Global Footprint Network summarised the current situation as follows:

Today humanity uses the equivalent of 1.5 planets to provide the resources we use and absorb our waste. This means it now takes the Earth one year and six months to regenerate what we use in a year. Moderate UN scenarios suggest that if current population and consumption trends continue, by the 2030s, we will need the equivalent of two Earths to support us. And of course, we only have one. Turning resources into waste faster than waste can be turned back into resources puts us in global ecological overshoot, depleting the very resources on which human life and biodiversity depend. The result is collapsing fisheries, diminishing forest cover, depletion of fresh water systems, and the build up of carbon dioxide emissions, which creates problems like global climate change. These are just a few of the most noticeable effects of overshoot. Overshoot also contributes to resource conflicts and wars, mass migrations, famine, disease and other human tragedies and tends to have a disproportionate impact on the poor, who cannot buy their way out of the problem by getting resources from somewhere else.

In 2008, it was estimated that Earth’s biocapacity equated to ~12 billion hectares of biologically productive land and water. Dividing by the number of people alive in that year, 6.7 billion, gives the 1.8 global hectares per capita figure quoted above, e.g.


However, it might be noted that the relationship inferred above can be reversed, such that we might estimated the global population based on the Earth’s biocapacity and resource footprint per capita, e.g.


If this relationship as any validity, we might be able to estimate the sustainable global population for a given level of consumption, i.e. the footprint/capita. For example, based on the quote above, we already require 1.5 Earth’s to provide our current resource, such that it implies the sustainable biocapacity of planet Earth would have to be revised down from 12 to 8 billion hectares. If so, using the average footprint per capita, a sustainable global population would also have to be revised down:


Clearly, reducing the global population from 6.7 billion to 4.4 billion is a worrying projection, especially in light of the fact that the global population is now estimated to approach 10 billion by 2050. Of course, some may rightly point out that technology could effectively increases the Earth’s overall biocapacity, while reducing the average footprint. Although anything is possible, it is unclear how realistic this assumption might be in light of the table showing the current overshoot between the required biocapacity and the current biocapacity for a few selected countries:

Country Population
 Singapore 4.5 5.34 24.0 0.1 267.00
 Israel 6.9 4.82 33.4 2.2 15.06
 South Korea 48.0 4.87 233.6 15.8 14.76
UAE 6.3 10.68 66.8 5.3 12.56
 Jordan 5.9 2.05 12.2 1.4 8.54
 Japan 127.4 4.73 602.6 76.4 7.88
 Lebanon 4.2 2.9 12.1 1.7 7.25
 Saudi Arabia 24.7 5.13 126.6 20.7 6.11
 Jamaica 2.7 1.93 5.2 1.0 5.08
 Italy 59.3 4.99 296.0 67.6 4.38
UK 61.1 4.89 298.9 81.9 3.65
 Greece 11.1 5.39 59.9 18.0 3.33
 Iran 72.4 2.68 194.1 58.7 3.31
 El Salvador 6.1 2.03 12.4 4.1 3.03
 Egypt 80.1 1.66 132.9 49.6 2.68
 Germany 82.3 5.08 418.3 158.1 2.65
 Cuba 11.2 1.85 20.7 8.3 2.50
 North Korea 23.7 1.32 31.3 13.8 2.28
 China 1336.6 2.21 2953.8 1309.8 2.26
 US 310.0 8 2480.0 1199.7 2.07
 India 1164.7 0.91 1059.8 594.0 1.78
 France 61.7 5.01 309.2 185.1 1.67
 Ethiopia 78.7 1.1 86.5 51.9 1.67
 Bangladesh 157.8 0.62 97.8 59.9 1.63

All the countries in the top table have a greater than unity overshoot figure compared to those in lower table. The data for North and South Korea is highlighted as, to some extent, it might reflect the divide between the extremes of a capitalist versus communist economic models.

Country Population
 Russia 141.9 4.41 626.0 816.2 0.77
 Argentina 39.5 2.6 102.7 296.2 0.35
 Brazil 190.1 2.91 553.2 1707.3 0.32
Congo 3.6 0.96 3.4 47.1 0.07
 Gabon 1.4 1.41 2.0 41.6 0.05
 Guyana 0.8 2.38 1.8 47.2 0.04

Of the 153 countries listed by Wikipedia, over 60% are already in overshoot based on their required and actual biocapacity. However, the following chart may provide some clearer overview of the global population implications for a range of biocapacities and footprints

So, the red curve shows the result for an estimated Earth biocapacity of 8 billion global hectares (12/1.5), which for a footprint of 1.8 gha/capita would only support a sustainable global population of 4.4 billion. However, the table above appears to suggest that a footprint of 1.8 gha/hectares is possibly optimistic, if developing countries aspire to a better standard of living. Of course, it may be possible for technology to offset some of the increases in the footprint by increasing the overall biocapacity of Earth. However, some caution may need at this point, as history suggests that technology has only resulted in greater resource usage and pollution, e.g. deforestation, soil erosion, salinity of the soil, waste disposal to landfill, desertification, declining fish stocks, global warming and rising sea levels and climate change. Clearly, it would seem that technology can be a two-edge sword, such that it cannot be simply assumed that further technology advances will lead to any net increase in Earth’s biocapacity. We may also have to reflect further on the implications of the following chart, which shows the consumption by percentiles (10%) in 2005:

Based on many of the arguments presented for over-consumption, it might appear that all that needs be done is for the top 10% of consumers to use less resources. However, we might still have to seriously question whether this is a realistic solution given that it also appears to be human nature to want to live a ‘better life’ . So the question we may now need to consider is:

How might the current consumption profile change as we approach 2050?

The shaded column in the table below reflects the 2005 consumption profile, but now adjusted for a global population of 10 billion in 2050. The subsequent columns then show the consumption weighted from the top 10%, i.e. a 60% consumption level, by 50%, 75% and 90% to reflect the pressure/desire to increase the standard of living for a larger percentage of the global population.

Population Consumption Consumption Weighting
% % 50% 75% 90%
10% 0.5% 0.1% 4.5% 23.2%
20% 1.0% 0.2% 6.0% 25.8%
30% 1.4% 0.5% 8.0% 28.7%
40% 1.9% 0.9% 10.7% 31.9%
50% 2.4% 1.9% 14.2% 35.4%
60% 3.3% 3.8% 19.0% 39.4%
70% 4.8% 7.5% 25.3% 43.7%
80% 8.1% 15.0% 33.8% 48.6%
90% 17.6% 30.0% 45.0% 54.0%
100% 59.0% 60.0% 60.0% 60.0%
% Totals 100.0% 119.9% 226.5% 390.8%
# Total 10,000 11,988 22,648 39,079
Equivalent Population

So, if the current top 10% resists any attempt to willingly reduce its current consumption (60%), while the consumption profile of a larger percentage of the global population is increased, it is clear this will result in an increased equivalent population demand for resources. For example, if the consumption profile for 10 billion is changed using a 50% weighting, its resource usage is equivalent to a global population of 11,988 billion, while the 75% weighting increases this figure to 22,648 billion. We shall not even think about the implications of a global population eqquivalent to 39,079 billion. However, if we accept the over-consumption argument then the problem is due to the 60% consumption of the top 10%, which conceptually might halved to 30% to assess the benefits.

In the chart above, we see that the consumption of the top 10% being halved with a small redistribution to the lower percentiles. While this redistribution of consumption may appear fair, it would only reduce the equivalent consumption by 5%. If you only halved the top 10% consumption without any change to the consumption of the remain 90%, it might help reduce the equivalent consumption to 70%. Of course, if we accept no change in the current footprint per capita profile, while accepting the biocapacity of Earth is already 1.5 times the current sustainable biocapacity of Earth, then something else MUST change, irrespective of whether humanity takes any action or not, as the global population progresses toward 10 billion by 2050.

Note: The traditional pessimist model derives from Rev. Thomas Malthus's Essay on the Principle of Population (1798). Malthus observed that population tend to grow exponentially, while the food production capacity of the land base is fixed, so it is only a matter of time before the human population outgrows the carrying capacity of the Earth. At that point, humans will be reduced to bare subsistence living. However, Malthus cited population figures from America to prove his point, but overlooked the fact that much of the American population increase was due to immigration rather than births. His prediction were therefore even more pessimistic than the 'Limit-to-Growth' model, as reflected in the chart below: