Air quality and human health - Air Pollution Modeling and Its Application - page 487

Stratified analyses showed greater reductions in admissions in NYC, among
those aged 0-4 years old, and whites than among upstate, other age groups, and
other racial/ethnic groups (data not shown). In contrast, admissions for the control
diseases, gastroenteritis and accidental falls, were higher during the post-implement-
ation period compared to baseline (data not shown).
4. Conclusion
Preliminary findings show significant reductions in ozone concentrations during
the summer season after the NOx SIP Call went into effect. However temperatures
increased across these same time periods, indicating that the ozone reductions are
not related to temperature. Although not significant, analyses identified reductions
in admission rates during the fall and winter season in all NYS regions following
the NOx SIP call, after controlling for multiple confounding factors. The findings
also identified that the intervention effect has regional differences that may be
accounted for by the NOx implementation which reduced ozone transport from
neighboring states into the southern portions of NYS. Further studies will examine
the potential effects of NOx SIP call on sensitive sub-populations, effects by
urbanicity, and relationships based on meteorological and windflow patterns.
References
New York State Department of Health. National Asthma Surve y - New York State Summary
Report. 2007.
Lin S, Fitzgerald E, Hwang SA, Munsie JP, Stark A. Asthma hospitalization rates and
socioeconomic status in New York State (1987-1993). J Asthma. 1999 May;36(3):239-51.
Kampa M, Castanas E. Human health effects of air pollution . Environ Pollut. 2008
January;151(2):362-7.
5. Questions and Answers
D. Bert: Accountability studies are very important but also difficult to do when
changes in pollution as a result of regulatory actions are gradual?
Answer: The challenges can be overcome but they require careful thought and
very targeted study designs. We agree that determining the impact of a regulation
is extremely difficult. The signal associated with a change in emissions is
embedded within the overall health endpoint that is confounded by other
factors. We believe multiple approaches will be needed to discern this signal
using a “weight of evidence” approach. This paper presents one approach for
such an analysis.