been largely attained. Monitoring networks have also documented a reduction in sulfate deposition in the eastern United States.
Economic assessments of the overall costs and benefits of AQM in the United States conclude that, even recognizing the considerable uncertainties, implementation of the CAA has had net economic benefits.
With regard to the three broad activities in AQM (Figure ES-1), the committee found the following:
Standard setting, planning and control strategies for criteria pollutants and hazardous air pollutants have largely focused on single pollutants instead of potentially more protective and more cost-effective multipollutant strategies. Integrated assessments that consider multiple pollutants (ozone, particulate matter, and hazardous air pollutants) and multiple effects (health, ecosystem, visibility, and global climate change) in a single approach are needed.
Current risk assessment and standard-setting programs do not account sufficiently for all the hazardous air pollutants that may pose a significant risk to human health and ecosystems or for the complete range of human exposures both outdoors and indoors.
EPA’s current practice for setting secondary standards5 for most criteria pollutants does not appear to be sufficiently protective of sensitive crops and ecosystems.
Although pollutant concentrations have decreased, the federal, regional, and state emission-control programs implemented under the SIP process have not resulted in NAAQS attainment for ozone and particulate matter in many areas. In addition, the SIP process has become overly bureaucratic, places too much emphasis on uncertain emission-based modeling simulations of future air pollution episodes, and has become a barrier to technological and programmatic innovation.
Air quality models have often played a major role in designing air pollution control strategies. Much effort has gone into the development and improvement of these models; as a result, they are highly sophisticated. Limitations remain, however, in large part due to a lack of data to adequately evaluate their performance in specific applications for specific locations and an inability to rigorously quantify their uncertainty.