Energy, Air Pollution, and Climate Change
Although a large number of the inhabitants are connected to the electric grid, some two billion poor people in the developing world still largely rely on biomass to meet their energy needs.
That leaves approximately 4.7 billion people with more energy-intensive lifestyles who consume, with little help from the world’s poorest, the energy equivalent of 77 trillion barrels of oil a year (Energy Information Annual 2004).
More than 80% of global energy consumption is derived from fossil fuels (IEA 2006), and it is this dependence on fossil energy that is responsible for the release of the greenhouse gases and other pollutants that are altering atmospheric composition and processes on a global scale.
Despite the global concerns over the health impacts of urban air quality and the potential adverse effects of climate change, population-environment researchers have paid particular attention to understanding the demographic drivers of energy consumption.
Although it is clear that there are vast differences in consumption levels (per capita energy consumption in the United States is 48 times what it is in Bangladesh and 4.7 times the world average), it would be wrong to suggest that population variables are not a contributing factor.
Selden et al. (1999), analyzed the reduction of U.S. major air pollution emissions from 1970 to 1990 and found that changes in economic scale, economic composition, energy, energy intensity, and emissions intensity all played important roles.
In quantifying the impacts of population on air pollution, researchers have reached different conclusions depending on which pollutants are under study, in which locations, at what scale, and for which time periods.
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For instance, a study of California shows that population size significantly contributes to the increase of the reactive organic gases NOx and CO and has little impact on PM10 and SOx, which are derived more from production activities (Cramer, 1998).
Population size shows no significant relation to ground-level ozone because ozone is very difficult to measure at specific sites owing to its nature as a diffuse secondary pollutant (Cramer and Cheney, 2000).
In research using national-level data, researchers found an almost linear positive correlation between population size and CO2 emissions (Cole and Neumayer, 2004).
The same inconsistencies in the relationship between population size and emissions of various pollutants are in evidence when examining other population-related variables.
Cramer (1998) in his study of California counties and Cole and Neumayer (2004) in their cross-national studies found that other variables such as the percent of population that are migrants, age composition, household size, and level of urbanization have the same basic relationship as overall population size on emission levels of each of the pollutants they studied.
However, caution should be used in interpreting these results because the studies only cover short time periods (10 to 20 years) in which there were only small changes in the demographic variables.
As a result of the complexity of population interactions as well as political issues, population issues were not considered in formulation of the Kyoto Protocol (Mayerson, 1998) and have also been largely excluded from the Intergovernmental Panel on Climate Change (IPCC) assessment reports (Bongaarts, O‟Neill and Graffin, 1997).
Although the 1996 scenarios continue to serve as a primary basis for assessing future climate change and possible response strategies, the Fourth Assessment Report of the IPCC is based on slightly lower population projections than the Third Assessment Report under the A2 scenario, which describes an economically divided world with slow technological advancement and high population growth.
Consideration of demographic factors beyond population size, such as changes in age structure, urbanization, and living arrangements, which as discussed above are important in modelling future energy use, are not accounted in the SRES population assumptions.
Making progress in this area requires a better understanding of the scope for future demographic change as well as methods for including demographic heterogeneity within energy-economic growth models used for emissions scenario development (Mayerson 1998).
