WHAT IS HUMAN MORTALITY? Part 1

Human mortality

Projecting the concentrations of trace species in the

troposphere over the next several decades is important

for projecting climate change, as well as for under-

standing the effects of air pollutants on human health,

agricultural productivity, and natural ecosystems.

Projecting future emissions of primary particulate

matter (PM), and of the precursors of ozone and

secondary PM, is likewise important when considering

the long-range transport of air pollutants and, for

example, the effect of growing emissions in emerging

countries on air quality in industrialized nations.

In this study, we address the effects of future ozone

concentrations on premature human mortality, in several

scenarios for 2030. Ozone is an atmospheric oxidant that

has been associated with adverse health effects including

hospital admissions and chronic respiratory conditions.

In addition, a substantial epidemiological literature

documents an association between ozone and premature

human mortality through daily time-series studies

[1–5,9,12–15,19,22,26].

PM is another major air pollutant that has also been

associated with premature mortality, in both daily time

series studies and long-term cohort studies [20].

Because PM has been demonstrated to have long-term

chronic effects on mortality, while chronic effects have

not been demonstrated for ozone, future changes in PM

concentrations are likely the most important component

of changes in mortalities due to air pollution in future

scenarios. While this study focuses on future mortality

associated with changes in ozone, an assessment of the

total mortality effects of air pollutants would also need

to account for changes in PM mortality.

Here we evaluate human mortality globally due to

changes in surface ozone concentrations under three

scenarios for 2030. We use the results of global

atmospheric modeling studies performed by Szopa et al.

[24] and Szopa and Hauglustaine [25] to give surface

ozone changes. The next section describes these

atmospheric modeling simulations and our methods

of estimating global human mortality effects associated

with these changes in ozone. We then present our

We estimate effects of changes in ozone on

premature human mortality for several scenarios,

following the methods used by West et al. [27]. We

use the results of an epidemiological daily time-series

study that relates ozone with daily mortalities, using a

distributed lag method and a large database for 95 cities

in the United States [2]. The equation for a change in

human mortalities (DMort) due to a change in ozone

concentration (DO3) used in the epidemiological study

and in this study is:

DMort ¼ -

y0ðe-

bDO3 -

1ÞPo p (1)

where y0 is the baseline mortality rate for a given

population, b is the mortality coefficient (fraction

excess mortalities per ppbv of ozone), and Pop is the

total population. We use the total non-accident baseline

mortality rates (y0) for the whole population in each of

14 world regions, obtained from the World Health

Organization [28], and we assume that these baseline

mortality rates are constant to 2030.

The b that we have selected from Bell et al. [2] is

consistent with, but generally smaller than, meta-

analyses of ozone mortality that have been published

since 2001 [1,3,12,14,15,22,26]. We selected this b

because it is not subject to publication bias (the possible

tendency to selectively publish positive results), which

may bias meta-analyses high. While this value of b was

estimated in the US, we assume that this ozone–

mortality relationship is valid globally, as similar results

have been demonstrated in Europe [9] and in some

locations in the less industrialized world [5,13,19]. We

use a value of b that was derived for the daily maximum

8-h ozone. While some studies have tried to distinguish

the ozone–mortality relationship for different popu-

lations, such as by age or by the proximate cause of

death, these attempts generally do not find significant

differences from the whole population [2]. Conse-

quently, we use a value of b derived for the whole

population, and apply it to the whole population. Since

long-term effects of ozone on mortality have not been

demonstrated [20], we do not consider possible chronic

effects of ozone on mortality, nor the years of life lost

due to premature mortality.

The growth in global population and its spatial

distribution is modeled in four world regions, according

to the SRES A2 scenario [17], totaling 6.17 billion in

2000 and 9.17 billion in 2030. The spatial distribution of

population within each region is based on the 2003

population from the LandScan database [18], which

provides population data at very fine resolution, and

which we then map onto the atmospheric modeling grid.

Equation (1) is applied in each grid cell and on each

day, using the change in the daily maximum 8-h ozone

concentration on that day, the population of that grid

cell, and the value of y0 corresponding to the appropriate

world region. Since it is applied on each day, b is divided

by 365.25 days per year. Equation (1) is prescribed for a

change in ozone concentration, and epidemiological

studies can effectively evaluate b over the range of ozone

concentrations for which there are observations. While

most ozone measurements in these studies are in the

range of modest ozone, some studies show evidence that

a similar ozone–mortality relationship holds at low

concentrations, well below current national standards,

and question whether a low-concentration threshold

exists [4,9]. Estimating the total mortality burden due to

ozone would require one to specify a reference ozone

concentration or field against which current levels would

be compared. Because the ozone–mortality relationship

has not been firmly established at low concentration, and

because specifying a reference case is beyond the scope

of this study, we do not estimate the total mortality burden

of ozone. Rather, we estimate ozone mortality due to

differences in ozone concentration between the different

scenarios considered.

We evaluate ozone mortality assuming a low-

concentration threshold of 25 ppbv, below which

changes in ozone are assumed to have no effect on

human mortality. Using such a threshold replaces

estimating mortality in particular seasons; epidemiolo-

gical studies in temperate regions have often segregated

results by season, but these seasons do not have the

same relevance in tropical nations [27]. We choose a

threshold at roughly the current background concentra-

tion, as the effect of ozone on mortality is uncertain at

low concentrations. Since this choice of a threshold is

fairly arbitrary, we test the sensitivity of the results to

this threshold level.

3. Results

Szopa et al. [24] and Szopa and Hauglustaine [25]

present global results for the set of scenarios that

we consider; here we present population-weighted

concentrations, as indicators which are relevant for

human health. Table 1 shows the population-weighted

annual average 8-h daily maximum surface ozone

concentration, globally and in each of ten world regions.

Definitions of these ten regions are shown in Fig. 1.

The results in Table 1 indicate a very substantial

increase in ozone globally in 2030 under the A2 scenario,

relative to the 2000 simulation, with the global

population-weighted 8-h ozone increasing by 9.4 ppbv.

estimates of human mortality globally and in ten world

regions.

2. Methods

We use results from a global atmospheric modeling

exercise performed using a coupled general circulation

model with interactive chemistry, the LMDz-INCA

chemistry–climate model [8,10,11]. Modeled ozone

concentrations for present conditions using this model

are shown to agree reasonably well with surface ozone

measurements [8,10].

The global simulations used in this study are

described fully by Szopa et al. [24] and Szopa and

Hauglustaine [25], and these simulations were shown

previously to be within the range of several other

models in the Photocomp experiment [7,23]. While

Szopa et al. [24] and Szopa and Hauglustaine [25] also

present results for a regional model imbedded over

Europe, and consider climate change scenarios in the

future, we consider here only the results of the global

model using present-day meteorology (for 2000 from

the ECMWF ERA40 reanalysis).

Four scenarios are considered in this study: a

simulation for 2000, and projected 2030 emissions

under the SRES A2 scenario, the CLE (current

legislation) scenario, and the MFR (maximum feasible

reduction) scenario. The SRES A2 scenario [17] is a

high-growth scenario with rapid increases in emissions

of air pollutants. The CLE scenario takes into

consideration recently-enacted legislation to improve

air quality in nations around the world, and the MFR

scenario assumes that currently available emission

control technologies are aggressively employed glob-

ally [6]. LMDz-INCA is run with a horizontal resolution

of 3.758 in longitude and 2.58 in latitude, and mortality

effects are calculated on this grid also. Using hourly

surface ozone concentrations, we calculate the daily

maximum 8-h average ozone concentration on each day

and at each grid cell, and use these 8-h m