On the use of air quality analysis for health impact studies

Richard Ménard, Alain Robichaud, Martin Deshaies-Jacques Air Quality Research Division, Environment and Climate Change Canada

Yulia Zaitseva, and the AQMAS teamCanadian Meteorological Center

with contribution from Francois Reeves (MD)Cardiologist, University of Montréal

Dan Crouse, Rick BurnettEnvironmental Health Science and Research Bureau, Health Canada

Jeffrey R. BrookDalla Lana School of Public Health, University of Toronto

and Jacek KaminskiInstitute of Geophysics, Polish Academy of Sciences

CAMS Second General Assembly, Warsaw, Poland, May 2017

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• In terms of mass, we breathe-in 10 times more mass of air in a day than liquid or solid

• The surface of the lungs are lot more permeable to contaminants than are the colon

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Sun et al., JAMA 2005

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Mean 15 µg/m3

Sun et al., JAMA 2005

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Air Quality Models : GEM-MACH (Government) , GEM-AQ (University)

Global Environmental Multi-scale (GEM) model –Modeling Air Quality and Chemistry (MACH)Coupled meteorology-chemistry model 10km grid Run twice per day (initialization at 00 and 12 UTC) and produces 48-hour forecasts

History of AQ models atEnvironment Canada

2001 – CHRONOS (CTM 21 km)2009 – GEM_MACH (15 km)2012 – GEM-MACH (10 km)

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Operational objective analysis

experimental since 2002, operational since Feb 2013

ozonefine particles

Analysis of O3, NO2, SO2, PM2.5, PM10 each hour

• 2D Optimum Interpolation, offline FOAR correlation functions error stat in obs. space only chi2 adjusted statistics 3-month diurnal bias correction Ménard and Robichaud 2005

ECMWF ProceedingsHistory• O3, PM2.5 – using CHRONOS

2002-2009• O3, PM2.5 – using GEM-MACH

2009-2015• O3, PM2.5 , NO2, SO2, PM10

since April 2015(Robichaud et al. 2015,

Air Qual Atmos Health)• Multi-year data set (2002-2012)

Robichaud and Ménard 2014, ACP)

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Canadian Air Quality Health Index (Stieb et al. 2008, JA&WMA)•Ten year old program that has evolved from an O3-only forecast in Eastern Canada to a Canada-wide O3, NO2, PM2.5 forecast program

•A map of AQHI is delivered operationally (each hour)

AQHI = 10/10.4×100×[(exp(0.000871[NO2])-1)+(exp(0.000537[O3]) -1)+(exp(0.000487[PM2.5]) -1)]

Near real-time mapping of the Air Quality Health Index

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• A cohort is a group of people that have been followed for a long period of time in order to examine the association between cause and effect

• CanCHEC (Canadian Census Health and Environment Cohort) is a database of 2.5 million Canadians followed for a period of 16 years and which has been used to study the impact on mortality from long term exposure to ambient air pollution

Individual level data• Followed address of 2.5 million Canadians each year using tax

reports• Canadian mortality database: date and cause of death

Epidemiologic studies based on cohorts

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Neighborhood level data – grouped by postal code (~ 500 individuals)• Socio-economy data. Census long form 1991 – grouped by census

tracts (size of a neighborhood)• Medical history data. Canadian Community Health Survey (CCHS)

Survey done each two years and collect information of about 120,000 Canadians– Diseases and heath conditions– Health care services– Lifestyle and social conditions– Mental health and well-being

• Ambient air pollution by postal code, yearly basis– Satellite observations for PM2.5

– Land-use regression models for NO2

– Objective analysis for O3

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• The survival function S(t) is the probability of survival

up to time t where T is the time of death

• The hazard rate λ(t) is the conditional probabilitydying in the next short time t+Δt given to be alive at time t

• Epidemiology studies uses the Cox proportional hazard model specifies the hazard ratio (HR) for an individual i is modelled as

is the baseline hazard rate and are covariatespollution levels, socio-economic, health, etc …

Cox proportional hazard model

)(P)( tTtS >=

−= ∫

t

dtttS0

)(exp)( λ

)exp()(/)(HR 22110 pipiii XXXtt βββλλ +++==

)(0 tλ pii XX ,,1

Area under the curve is the life expectancy

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• HR > 1 hazard rate of an exposed person (or treated patient) is larger than for an unexposed (or untreated patient) person

• HR < 1 hazard rate of an exposed person (or treated patient) is smaller than for an unexposed (or untreated patient) person

• Examples– Atorvastatin (Lipitor) 10 mg as a HR = 0.64 for heart attack– Cigarette smoking 10 cigarette/day as a HR = 1.8 for heart

disease (HR = 1.2 for 2 cigarette/day)

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Ambient PM2.5, O3, and NO2 Exposures and Associations with Mortality over 16 Years of Follow-Up in the Canadian Census Health and Environment Cohort (CanCHEC)Crouse et al. (2015), Environ. Health Perspect., 123, 1180-1186

For an increase of 5 µg/m3 of PM2.5, or 9.5 ppb of O3, or 8 ppb of NO2

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Having polynomials of concentration (i.e. cubic splines) as covariates we can obtain a fitted concentration response

Concentration response

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• The Canadian Urban Environmental (CANUE) Health Research Consortium Jeff Brook (PI) (ECCC and U of T) with 15 Canadian Universities and Governments. Develop an easy access geospatial data server (e.g. Google Earth) to support quantitative research on the effect urban environment on health. Data linked to postal codes will contain information on numerous metrics, NDVI, local climatic zones, building density, land use, noise level, air pollution, greenspace, walkability. Data from 1980’s up to now

• Reforecast of GEM-MACH 15 km from 1991 until now with objective analysis of surface observation

Future plans: Assessment over Canada

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• Use an ensemble of model forecast valid at a given time (over 2 months)• Use a similar procedure to EnKF on ensemble members:

localization + spatial smoothing of model outputWe get terrain-dependent (land/water, mountain) error correlations

OAv2 OAv1

Impact of an observationO3 – 21 UTC

No additional forecast needed Seem to address known problems with OA in costal areas and close to mountainsMénard, R. and M. Deshaies-Jacques, 2017: The use of a time-serie air quality forecast to

develop an ensemble error covariance. (document in preparation, Atmosphere ?)

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• We propose do undertake surface analysis of air pollutants over Poland using:

– Initial conditions from CAMS ensemble and C-IFS– Meteorological forcing from IFS– O3 and PM10 observations from Polish stations

• The assessment will determine population exposure for health impact studies

• The proposed assessment will be done for 2010 – 2017

Assessment over Poland

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