In addition to human health, air pollution affects ecosystem vitality. Small reactive compounds such as ozone (O3), benzene (C6H6), sulfur dioxide (SO2), nitrogen oxides (NOx) and volatile organic compounds (VOCs) have a range of negative environmental impacts. For example, ozone degrades plant cuticles through oxidation, inhibiting plant development and growth. SO2 and NOx both react with other atmospheric compounds, resulting in acid rain. Prolonged ecosystem exposure to acid rain can diminish fish stocks, decrease biological diversity in acid-sensitive lakes, degrade forests and soils, and diminish agricultural productivity.
Air pollutants are difficult to track and measure. They diffuse freely through the atmosphere and frequently react with other atmospheric chemicals. These features often obscure the sources of air emissions, which can lead to inappropriate policy recommendations. Because many of the ecosystem effects of air pollution are particularly damaging during certain seasons, policymakers must consider the seasonal patterns of air pollution.
Ideally, data for the 2008 EPI air quality metrics should come from representative sources that take both spatial and temporal variations into account and have been collected using well-documented, scientific methods.
Existing data sources for global air emissions are either incomplete or difficult to use in global comparisons. Air quality monitoring systems vary significantly between countries, often producing fundamentally dissimilar data. Additionally, some countries do not have sufficient monitoring stations to produce representative data samples.
In comparison with monitoring data, air quality models are relatively easy to access. However, these models are sometimes based on contentious algorithms and lack empirical support. Uncertainty is inherent to models, making it unadvisable to rely on them exclusively. These problems can be somewhat ameliorated by utilizing models in conjunction with empirically collected data. The models simplify trends in large-scale air flows, and the results can be confirmed with empirical data in smaller-scale environments.
The 2005 World Health Organization (WHO) Air Quality Guidelines include updated data and criteria for four important air pollutants: particulate matter, ozone, nitrogen dioxide, and sulfur dioxide (WHO 2005). The US EPA has National Ambient Air Quality Standards (NAAQS) for six principal pollutants: carbon monoxide, lead, nitrogen dioxide, ozone, particulate matter, and sulfur dioxide. A complete Air Quality index for the EPI would contain a metric for each of these compounds, in addition to other pollutants such as benzene.
However, due to data gaps, the 2008 EPI features only two of these pollutants as air quality metrics: ground-level ozone and sulfur dioxide. Others will be incorporated when better datasets become available.
Small and lesser-developed countries received the highest scores in this category, which is correlated with their low levels of industrial pollution. However, proximity to target was generally high in this category, with 130 nations scoring above 80 points. High performance overall magnifies the low performance of countries at the bottom of the ranking, such as China and the United States, which both received scores below 45.
One of the primary conclusions that can be drawn from the sulfur dioxide ranking is that among developed nations, the European Union has set and kept much more ambitious sulfur dioxide reduction targets than its economic peers. The United States hasn’t revised its sulfur dioxide targets since 1990, which is consistent with its poor score.
The ecological ozone rankings are much less straightforward than the sulfur dioxide rankings. Ground-level ozone concentrations are a function of various factors including elevation, meteorological conditions, industrial emissions, and biomass burning. One example of how this complexity can impact rank is the performance of countries in Central Africa. These countries perform poorly despite having low industrial emissions because of their high levels of biomass burning. Furthermore, certain regions may accumulate high ozone levels if they’re located in geologic basins that collect emissions from neighboring regions.
Both indicators in this section have methodological issues that need to be resolved. For example, the question of whether to use daily averages or hourly maximums of pollutant concentrations is still unresolved, and may vary depending on the pollutant in question. Whether or not to weight data by population is another question debated in the community that lacks a definitive answer. In terms of sulfur dioxide emissions specifically, in future editions of the EPI we would prefer to look at concentrations relative to the buffering capacity of specific ecosystems. Different environments have varying degrees of ecological resistance to sulfur dioxide, but there is no data currently available that reflects this.
Ecological ozone and sulfur dioxide emissions are important indicators of air quality but do not give a complete picture of the ecosystem effects of air pollution. Several other hazardous pollutants such as nitrogen oxides should ideally be tracked using similar global metrics. Like sulfur dioxide, they are known to react with volatile atmospheric compounds to produce smog and acid rain. However, they were excluded in the 2008 EPI due to insufficient data.
In addition to the need for global datasets on a wider range of air pollutants, modeling systems and methods for integrating empirical and modeled data need improvement. The benefit of models is that they are able to generate values for large spatial domains. Due to the lack of empirical backing, however, the use of purely modeled values is still controversial. More research on effectively combining empirically collected data from air monitoring facilities with model-generated data is needed within the field.
An ideal performance measure for air pollution would include emissions quantities, the mapping of pollutant movement, the ecological sensitivity to pollutants by area, and clear policy commitments to emissions reduction. The European Union can be upheld as a model in this regard because it actually meets all of these monitoring goals. However, there are no global datasets with all of these measures, so it is currently impossible to be as precise as we would like.
