Where do the data come from?

Estimating air pollution levels around the world

Air quality monitoring

Many high-income countries of the world operate extensive networks of air quality monitoring stations in urban areas, providing continuous hourly measurements of pollution levels each day. Areas that more often lack extensive air monitoring include the many rapidly developing urban areas of low- and middle-income countries. Air quality data for large rural and suburban areas of high-income countries are also lacking, because most air quality monitoring occurs in major cities.

The Global Burden of Disease (GBD) project takes advantage of the monitoring data available from the World Health Organization Global Urban Ambient Air Pollution Database. This database is updated every two years; the last update was in 2016. Official air quality providers at the country or city level can submit data for inclusion in the database and are encouraged to do so, using the data template provided on the site.

Using satellite data when there are no monitors

Scientists have relied on ground-level measurements of air quality for most site-specific studies of air pollution health effects and for air quality management. However, in areas that do not have extensive air quality monitoring, they need to use other approaches to provide a consistent view of air pollution levels throughout the world.

To accomplish this, scientists rely on air quality observations from satellites and combine them with information from global chemical transport models  and available ground measurements. They then estimate global exposure to PM2.5 systematically, beginning in blocks or grid cells covering 0.1° x 0.1° of longitude and latitude (approximately 11 km x 11 km at the equator).

Taking into account the population in each block within a country, scientists then aggregate the estimated exposure concentrations to national-level population-weighted averages for a given year. The Global Burden of Disease analysis was conducted in 2017 using data in five-year intervals from 1990 to 2016, the most recent year for which the necessary data were available.

Estimating ozone levels around the world

For ozone, a global chemical transport model was used to calculate a seasonal average concentration (summer, when temperatuires are warmest). Scientists accounted for variation in the timing of the ozone (summer) season in different parts of the world. The process for estimating national-level population-weighted mean ozone exposures was the same as that for fine particulate matter exposures.

Estimating exposures to household air pollution

In the Global Burden of Disease project, estimation of exposure to household air pollution begins with surveys of the proportion of households in each country using solid fuels of any kind for cooking or heating. This information is then combined with data on the numbers, ages, and sex of people living in households in each country to estimate the proportion, or fraction, of the population exposed to household air pollution. This proportion is the measure of household air pollution exposure used in the State of Global Air report. For more details on how this proportion is translated into estimates of exposure to particulate matter, see the report.

Estimating the burden of disease

Deaths and disability adjusted life-years (DALYs)

The burden of disease due to air pollution or any other risk factor is calculated using estimates of the numbers of deaths and disability-adjusted life-years (DALYs). The numbers of deaths attributable to air pollution in a given year includes deaths that have likely occurred months or even years earlier than might be expected in the absence of air pollution (as in the case of a child dying from a lower-respiratory infection). DALYs provide an overall measure of the loss of healthy life expectancy and are calculated as the sum of the years of life lost from a premature death and the years lived with disability (e.g., shortness of breath) caused by a disease attributable to air pollution (e.g., chronic-obstructive pulmonary disease).

An important insight gained by using DALYs rather than just the numbers of deaths is that DALYs account for the age at which disease or death occurs. For example, air pollution contributes to lower-respiratory infections in children, but the number of deaths from such infections is small relative to the number of air pollution–related deaths from heart disease, a major cause of death in older adults. However, because children who die from such infections have lost many more years of healthy life, their burden is appropriately reflected in a larger number of DALYs.

Age-standardized death rates and DALY rates

Burden is also measured in terms of age-standardized death rates and DALY rates (i.e., the number of deaths or DALYs per 100,000 people). Age-standardized rates are important because they adjust for population size and the age structure of each country’s population. This means that the standardized rates in two countries can be compared as if the countries had the same population characteristics. Otherwise, in a country with a large and older population, the total number of deaths attributable to air pollution would be larger than that in a country with a smaller or younger population, even if exposure levels were the same.

Further details

Details on the complete Global Burden of Disease study, as well as more information on the methods used to estimate particulate matter and ozone exposures, mortality, and DALYs for the GBD 2016 analyses can be found in the following studies and their related references:

GBD 2016 Risk Factors Collaborators. 2017. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet 390:1345–1422.

Shaddick G, Thomas ML, Jobling A, Brauer M, van Donkelaar A, Burnett R, et al. 2016. Data integration model for air quality: A hierarchical approach to the global estimation of exposures to ambient air pollution. Available: https://arxiv.org/abs/1609.00141 [accessed  March 21, 2018].

Cohen AJ, Brauer M, Burnett R, Anderson HR, Frostad J, Estep K, Balakrishnan K, et al. 2017. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: An analysis of data from the Global Burden of Diseases Study 2015. Lancet 389: 1907–1918