Air pollution risk model for three pollutants combined (4500357984)

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Tender Award


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CAD 67 800.00
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Health Canada
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Health Canada

Customer info

Merrick, Robert
200 Eglantine Driveway, Tunney's Pasture
Ottawa  ON
K1A 0K9


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Supplier Information

Glen Takahara
Department of Mathematics & Statistics
Queen's University
Kingston, Ontario
K7L 3N6



Solicitation #: 1000184801a Closing Date: November 8, 2016 Time: 2 p.m. EST

This requirement is for the department of Health Canada. This is the second attempt to find a qualified supplier. The evaluation criteria have been softened by changing it from the project leader’s knowledge and experience to that of the bidder’s proposed team.

Title: Air pollution risk model for three pollutants combined


Until recently, studies of the health risks associated with day-to-day exposure to air pollution have looked at each pollutant individually. Health Canada combines these data in calculations of the Air Quality Health Index (AQHI) – a communication tool that sums the individual risks associated with three major components of pollution: ozone, nitrogen dioxide (NO2) and fine particulate matter up to 2.5 micrometers in size (PM2.5). This method is understood to be only an approximation, because the formula used in the calculations does not fully represent the effect of the combined exposures on health due to interactions among the three air pollutants.

The Air Health Indicator (AHI) tracks trends in the short-term (acute) health risks of air pollution, and currently reports results from PM2.5 and ozone individually. This study seeks to develop statistical methods and models to combine the health risks associated with the air pollution mixture of the three main pollutants, taking into consideration that the calculated risk is more accurate if it is determined from the combined impacts of the three chemicals simultaneously, rather than the sum of the estimates of their individual impacts. It is anticipated that this 3-pollutant model will eventually be used to propose adjustments to calculation of the AQHI and AHI, which will improve the accuracy of these two departmental programs.

This project will examine air pollution data for 2000-2012, as both PM2.5 data and health outcome data are available for these years. The health outcomes that will be investigated include cause-specific mortality (deaths) and morbidity (illnesses) related to heart, circulatory and respiratory diseases.

Objectives of the Requirement

This project would support three major objectives:

1) to provide the general public with information reflecting the combined health risks associated with Canada’s three major air pollutants (ozone, NO2 and PM2.5)

2) to develop advanced statistical models to review and revise AQHI

3) to provide epidemiologic evidence and air pollutant-induced population risks for review and revision of the Canadian Ambient Air Quality Standards (CAAQS).

Currently, public health risks due to attributable air pollution are estimated for single pollutants; however, arithmetic sum of the individual risk estimates from these models do not reflect a combined health risk from multiple air pollutants because the multiple air pollutants are usually correlated. For example, ozone and NO2 are known to be correlated, and thus these two pollutants would have some structure in common, which is to be identified.

The 3-pollutant combined risk will certainly improve not only AQHI (Canada’s major hourly communication tool reporting on air quality at the community level) but also CAAQS (Canada’s regulations on air quality at the national level).

This work is supposed to provide information on the following questions:

(1) What models/methods have been done for 3 pollutants, ozone, NO2 & PM2.5, together in the same model?

(2) Interpolations are necessary for each of the 3 pollutants? If so, what methods? Need other air pollutants?

(3) Are there considerable correlations among the 3 pollutants?

(4) How to separate signals of individual single air pollutants only from those in common between the 3 pollutants

(5) Are there considerable correlations among the 3 pollutants & temperature? If so, how to handle the temperature? Temperature should be considered as another air pollutants?

(6) How best to model the interaction between temperature and pollutants based on (5)?

(7) How to best model three pollutant risk estimates based on (1) - (5) above?

a. What is the 1st pollutant specific risk?

b. What is the 2nd pollutant specific risk?

c. What is the 3rd pollutant specific risk?

d. What is the risk in common between the three pollutants, which cannot separate one pollutant from the others?

(8) How to best model multiple pollutant models and short temporal (single- or several-year) blocks for mortality?

(9) How to best model multiple pollutant models and short temporal (single- or several-year) blocks for morbidity?

Estimated Value:

The contract will be awarded to the bidder with the highest technical score within the budget of $60,000 for each fiscal year (one year contract with two option years, taxes not included).

Ownership of Intellectual Property:

The Contractor will own the Intellectual Property, while the Crown will have an irrevocable, royalty-free licence to use the IP.

Security Requirement:

There is no security requirement.

Mandatory Requirements:

M1. The bidder’s proposed team must include a resource with a PhD from a recognized university with specialization in Statistics and/or with experiences in Spectral analysis and Smoother functions.

M2. The bidder’s proposed team must demonstrate that within the last 5 years, they have undertaken at least three (3) projects with Canadian environmental data or population health issues.

M3 The bidder’s proposed team must have at least two peer-reviewed publications on environmental data or population health in scientific journals listed in the Science Citation Index Expanded (within the last 5 years).

M4. The bidder’s proposed team must show that they have experience working with Canadian environmental databases on air pollutant, climate and solar activities.

M5. The bidder’s proposed team must show that they have experience working with statistical software such as R, Fortran or C.

Selection Methodology

The contract will be awarded to the bidder with the highest technical score within the budget of $60,000 for each fiscal year (one year contract with two option years, taxes not included).

Enquiries regarding this Request for Proposals are to be submitted in writing to:

Robert Merrick

Contracting Authority


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