Strengthening air pollution standards in the USA
Submitting InstitutionUniversity of Bath
Unit of AssessmentMathematical Sciences
Summary Impact TypeHealth
Research Subject Area(s)
Mathematical Sciences: Statistics
Medical and Health Sciences: Public Health and Health Services
Economics: Applied Economics
Summary of the impact
Air pollution poses significant threats to both the environment and to
human health and the World Health Organization estimates that 800,000
deaths per year could be related to ambient air pollution. Formulating air
quality legislation and understanding its effect on human health requires
accurate information on ambient concentrations of air pollution and how
these translate into exposures actually experienced by individuals
Our research provides a framework for estimating personal exposures for
specific susceptible sub-populations, such as the elderly and those
suffering from respiratory diseases. This framework also provides novel
means of assessing uncertainty associated with the estimates of exposures.
Furthermore, it allows changes in exposures to be assessed under
hypothetical scenarios reflecting potential regulatory changes.
These models were used in the US Environmental Protection Agency's (EPA)
recent review of ozone standards that resulted in a reduction in the
statutory limits of ozone in the United States. The EPA stated that "These
changes will improve both public health protection and the protection of
sensitive trees and plants" [C].
Direct measurement of personal exposures requires an exposure monitor to
be worn. Whilst accurate, this is extremely costly and time-consuming. As
a consequence, in studies using this approach, sample sizes are small and
the information provided may therefore be limited. In order to provide
accurate data for larger samples, an indirect method has been developed in
which concentrations of pollutants in specific micro-environments, such as
the home, workplace or car, are modelled. When combined with models of
human behaviour that estimate the time spent in the different
microenvironments, these provide an integrated framework for estimating
Early approaches to combining micro-environments and time activity were
deterministic and did not have means of assessing the uncertainty
associated with the resulting estimated exposures. In , we provide a
theoretical model framework for estimating personal exposures
stochastically with full integration of the uncertainties inherent in the
Based on this framework, stochastic models, known as `exposure
simulators', have been developed which predict the exposures to a
pollutant experienced by individuals together with quantification of the
associated uncertainties. These individual exposures may then be
aggregated over demographic groups. Estimating individual personal
exposures is performed by sampling individuals from each demographic group
and randomly associating to each individual a time activity pattern that
matches the subject in terms of personal characteristics, day of the week,
temperature, season, etc.
In  we describe pCNEM (Personal Computer National Exposure Model), a
specific computational implementation of the framework developed in .
pCNEM comprises a large-scale computer simulation model that provides a
flexible platform for developing a wide variety of models and produces
distributions of predicted exposures. It can be formulated to produce
estimates for a range of pollutants, and has been used for both
particulate matter and ozone. For registered users, pCNEM can be accessed
via the internet . This allows users to define their own models for the
levels of pollution in individual micro-environments and incorporate data
on ambient levels of pollution from specific areas.
The US Environmental Protection Agency (EPA) has commissioned two
implementations based on the framework in [1, 2]: SHEDS (Stochastic Human
Exposure and Dose Simulation) and APEX (Air Pollution EXposure model).
An important application of the personal exposure simulation framework is
to help quantify the possible effects of abatement strategies, e.g.,
regulations and mandatory surveillance, by running them before and after
the hypothetical change. For example, the effects of a potential decrease
in ambient concentrations of a pollutant due to a new law, known as
`rollbacks', can be assessed in terms of the changes in exposures actually
experienced by individuals. In  it is shown how the effects of such
`rollbacks' can be assessed.
The underpinning research was carried out by Shaddick at Bath where he
has been Lecturer, Senior Lecturer and Reader in Statistics since 2001.
The work was produced in collaboration with Professor Jim Zidek of the
University of British Columbia (UBC) and colleagues within the departments
of Mathematical Sciences at Bath (Chatfield) and Statistics at UBC. Large
parts of the work have been performed during long-term visits by Prof.
Zidek to Bath which have been funded by an EPSRC travel grant (2002/3),
the EPSRC funded Bath Institute for Complex Systems (2005, 2007) and the
Canadian National Science and Engineering Research Council (2004-2013).
Work has also been performed during visits by Shaddick to UBC with funding
including a Peter Wall Institute for Advanced Studies Personal Fellowship
References to the research
References that best indicate the quality of the underpinning research
* Zidek, J. V., Shaddick, G., Meloche, J., Chatfield, C. and White,
R., 2007. A framework for predicting personal exposures to environmental
hazards. Environmental and Ecological Statistics, 14 (4), pp.
411-431. DOI 10.1007/s10651-007-0028-x
* Zidek, J. V., Shaddick, G., White, R., Meloche, J. and Chatfield,
C., 2005. Using a probabilistic model (pCNEM) to estimate personal
exposure to air pollution. Environmetrics, 16 (5), pp. 481-493.
Both papers contain developments of work which first appeared in a
technical report: Zidek, J.V., Meloche, J., Shaddick, G., Chatfield, C.
and White, R.A., 2003. A Computational Model for Estimating Personal
Exposure to Air Pollutants with Application to London's PM10 in 1997,
Technical Report TR#2003-3, Statistical and Applied Mathematical
Sciences Institute, Research Triangle Park, NC.
Details of the impact
Regulation of air pollution has important effects on human health and it
has recently been estimated that the 1990 Clean Air Act in the US
prevented 160,000 premature deaths, 1.7 million asthma attacks and 13
million lost work days per year — with these figures set to increase over
The Clean Air Act requires the Environmental Protection Agency (EPA) to
set national ambient air quality standards (NAAQS) for ozone and five
other pollutants considered harmful to public health and the environment
(the other pollutants are particulate matter, nitrogen oxides, carbon
monoxide, sulfur dioxide and lead). As mandated by the Clean Air Act, the
EPA must periodically review the scientific bases (or criteria) for the
various NAAQS by assessing newly available scientific information for each
of the pollutants listed above. This process occurs every ten years for
Models for estimating personal exposures based on  and  were used
extensively as part of the scientific basis for the most recent changes in
the NAAQS for ozone. The goal was to determine the effect of ambient
regulatory strategies on human exposure by observing how different ambient
concentration scenarios changed the predicted personal exposure for
different demographic groups.
The review of the standards for ozone was announced in 2008 and resulted
in a reduction of the primary standard level (8-hour average) for ozone
from 0.08 to 0.075 parts per billion [B, C, D]. This reduction
"significantly strengthened its national ambient air quality standards
(NAAQS) for ground-level ozone, the primary component of smog. These
changes will improve both public health protection and the protection of
sensitive trees and plants" [C]. After a series of petitions and
legislation, the final stage in the implementation of the new limits,
which refers to methods for designating areas as either in accordance or
in non-attainment was passed in 2012 [D, E].
During the process of formulating the new limits for ozone, three volumes
of scientific background information were released for consultation, "Air
Quality Criteria for Ozone and Related Photochemical Oxidants" [F]. These
linked the underpinning research to the subsequent formulation of the
legislation. Over 20 pages of the summary (Volume 1) are related to
estimating personal exposures together with a 70 page technical appendix
(Volume 2). The methods derived in  provide "the underpinning
theoretical probabilistic framework underlying these exposure simulators"
as referenced in [G] (in which 3rd and 4th authors
are members of the EPA). Our work [1,2], in particular pCNEM, is
extensively discussed in Section 3, Vol.1 and Chapter 3, Vol. 2 of [F],
with its advantages noted specifically in terms of its ability, in
contrast to other methods, to provide a coherent approach to incorporating
"uncertainties in the predicted distributions" and "its ability to
estimate the effects of reductions in ambient levels of pollutants"
(Section 3, Vol.1, pages 3-61 and 3-62).
- Detailed information is required on the potential exposures
experienced by individual members of the population to provide
scientific support for potential changes in air quality standards. The
research developed in [1,2] provides a convenient framework that can be
used to generate this information.
- Our work had impact on public policy and changes to legislation and
regulations. Models for estimating personal exposures based on  and
 were used extensively as part of the scientific basis for the most
recent changes in air quality standards for ozone.
- Our research has impact on the management of environmental risk. The
result of the 2008 EPA review was to make the standards for ozone more
rigorous. Areas classified "nonattainment" may have to impose more
stringent emission controls.
- According to the EPA these changes "will improve both public health
protection and the protection of sensitive trees and plants." [C]
Sources to corroborate the impact
[A] U.S. EPA. The Benefits and Costs of the Clean Air Act from 1990 to
[B] Federal Register. http://www.gpo.gov/fdsys/pkg/FR-2008-03-27/pdf/E8-5645.pdf
[C] FACT SHEET FINAL REVISIONS TO THE NATIONAL AMBIENT AIR QUALITY
STANDARDS FOR OZONE (http://www.epa.gov/glo/pdfs/2008_03_factsheet.pdf)
[D] March 2008 Final National Ambient Air Quality Standards for
Ground-level Ozone. http://www.epa.gov/glo/pdfs/2008_03_text_slides.pdf
[E] EPA Final Area Designations for 2008 Ground-level Ozone Standards
(issued May 2012).
[F] U.S. EPA Report "Air Quality Criteria for Ozone and Related
Photochemical Oxidants, Volumes 1 and 2, EPA/600/R-05/004aF and
EPA/600/R-05/004bF, 2006. http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_cd.html
[G] Berrocal, V. J., Gelfand, A. E., Holland, D. M., Burke, J. and
Miranda, M. L., 2011. On the use of a PM2.5
exposure simulator to explain birthweight. Environmetrics, 22, pp.
553-571. DOI 10.1002/env.1086