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In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders concerned with air pollution. As the U.S. Environmental Protection Agency (EPA) was finalizing its most recent review of epidemiologic evidence on particulate matter air pollution (PM). statisticians and epidemiologists found that the S-PLUS implementation of generalized additive models (GAMs) can overestimate effects of air pollution and understate statistical uncertainty in time series studies of air pollution and health. This discovery delayed completion of the PM Criteria Document prepared as part of the review of the U.S. National Ambient Air Quality Standard, because the time series findings represented a critical component of the evidence. In addition, it raised concerns about the adequacy of current model formulations and their software implementations. In this article we provide improvements in semiparametric regression directly relevant to risk estimation in time series studies of air pollution. First, we introduce a closed-form estimate of the asymptotically exact covariance matrix of the linear component of a GAM. To ease the implementation of these calculations, we develop the S package gam.exact, an extended version of gam. Use of gam.exact allows a more robust assessment of the statistical uncertainty of the estimated pollution coefficients. Second, we develop a bandwidth selection method to reduce confounding bias in the pollution-mortality relationship due to unmeasured time-varying factors, such as season and influenza epidemics. Third, we introduce a conceptual framework lo fully explore the sensitivity of the air pollution risk estimates to model choice. We apply our methods to data of the National Mortality Morbidity Air Pollution Study, which includes lime series data from the 90 largest U.S. cities for the period 1987-1994. [ABSTRACT FROM AUTHOR]

In the national ambient air quality standards specified by the U.S. Environmental Protection Agency in the Code of Federal Regulations, new standards were established for particulate matter on July 18, 1997. The new particulate matter standards specify mass concentration as the indicator for fine particulate matter (aerodynamic diameter of 2.5 μm or less). Ambient measurements for the new particulate standard must be performed by a new federal reference method as specified in the Code of Federal Regulations or by an alternative measurement method that has been designated by the Environmental Protection Agency as an equivalent method. The new particulate reference method is a 24 h integrated sample collected from the ambient air and analyzed gravimetrically. The reference method is explicitly specified using a combination of design- and performance-based criteria. Additional requirements listed in the Code of Federal Regulations address conditioning, handling, and weighing of the sample filter, which are performed manually. For alternative measurement techniques that do not meet the qualifications of the reference method, the Environmental Protection Agency defines three classes of candidate PM[sub 2.5] equivalent methods based on the measurement technique used and its degree of similarity to the reference method specifications. [ABSTRACT FROM AUTHOR]

The article presents a reply to researcher Madhusudana N. Rao for his comments on a article by the authors. According to them they are familiar with most of the citations mentioned by Rao. as they were commissioned by the U.S. Environmental Protection Agency to develop a complete bibliography on climate/health relationships as part of the effort to evaluate the impact of a predicted global warming on the environment. In addition to that, the article presents various other information.