Air quality index and its significance in environmental health risk communication

Abstract

Air Quality Index (AQI) is a standardized summary measure of ambient air quality used to express the level of health risk related to particulate and gaseous air pollution. The index, first introduced by US EPA in 1998 classified ambient air quality according to concentrations of such principal air pollutants as PM10, PM2.5, ozone, SO2, NO2, and CO. Subsequently similar, index-based approach to express health risk was developed in France, Great Britain and Germany. No such environmental warning system exists in Poland, although some test-trials took place in Katowice area and the city of Gdańsk. However, the operational value of AQI under environmental circumstances in Poland remains unknown. The aim of the study was to examine current air pollution levels in Katowice area and to confront AQI categories with local air quality, also in terms of health impact on the population as expressed by daily total and specific mortality. The data on daily average PM10 and sulphur dioxide concentrations available in regional network (PIOŚ in Katowice) and data on daily number of total deaths and deaths due to cardiorespiratory diseases from the Central Statistical Office in Warsaw were collected. The data covered the period 2001-2002. The percentage of days with individual Air Quality Index, created by American, French, British and German method of indexation was calculated. Then, the relationship between values of air quality indexes and daily total and specific mortality according to Spearman correlation coefficients was assessed. Finally, the obtained results were verified according to ANOVA Kruskal-Wallis test. The obtained results suggest significant discrepancy in the range of air quality categories depending on applied system of classification. Percentage of days with "unhealthy" air quality (in the period 2001-2002) was running from 0.1% (American method of indexation) to 11.2% (British method) and usually referred to winter season. Statistically significant Spearman correlation coefficients were obtained for the relationship between air quality and total number of deaths, as well as the number of deaths due to cardiovascular and respiratory diseases in elderly population (aged 65 and more). The observed values of correlation coefficients are very low and do not exceed value 0.2 for each chosen method of indexation. © Copyright by Institute of Envionmental Engineering of the Polish Academy of Sciences, Zabrze, Poland 2009.

Full text

1
AIR QUALITY INDEX AND ITS SIGNIFICANCE IN
ENVIRONMENTAL HEALTH RISK COMMUNICATION.
Małgorzata Kowalska
1
, Leszek Ośródka
2
, Krzysztof Klejnowski
3
, Jan E.Zejda
1
,
Ewa Krajny
2
, Marek Wojtylak
4
1
Department of Epidemiology, Medical University of Silesia, Medyków Str.18, 40-752
Katowice, Poland
2
Institute of Meteorology and Water Management, Bratków Str. 10, 40-045 Katowice,
Poland
3
Institute of Environmental Engineering Bases of Polish Academy of Science,
Department of Air Protection, M.Skłodowskiej-Curie Str. 34, 41-819 Zabrze, Poland
4
Uniwersytet Śląski, 40-007 Katowice, ul. Bankowa 14
Key words: air quality index, daily mortality, environmental epidemiology
INDEKS JAKOŚCI POWIETRZA I JEGO ZNACZENIE DLA
KOMUNIKOWANIA ŚRODOWISKOWEGO RYZYKA ZDROWOTNEGO.
Indeks jakości powietrza (AQI) jest wskaźnikiem określającym jakość powietrza
atmosferycznego i jednocześnie wskazującym potencjalne ryzyko zdrowotne ponoszone
przez populację wskutek naraŜenia na standardowo mierzone stęŜenia zanieczyszczeń
pyłowych i gazowych w danym regionie. Po raz pierwszy został uŜyty przez US EPA w
1998 roku i klasyfikował jakość powietrza atmosferycznego w oparciu o stęŜenia
podstawowych zanieczyszczeń: PM
10
, PM
2,5
, ozon, SO
2
, NO
2
oraz CO. Podobne
wskaźniki, oparte na danych regionalnych opracowano równieŜ we Francji, Wielkiej
Brytanii i Niemczech. Właściwie w naszym kraju nie funkcjonuje spójny system
komunikowania ryzyka zdrowotnego, który byłby oparty na własnym indeksie jakości
powietrza, chociaŜ pewne próby podejmowane są w Katowicach i Gdańsku.
Celem prezentowanej pracy była ocena jakości powietrza atmosferycznego w
Katowicach na podstawie przyjętych kategorii AQI oraz porównanie uzyskanych
danych z danymi opisującymi potencjalne ryzyko zdrowotnego wyraŜone w postaci
dobowej umieralności całkowitej lub specyficznej.
Zebrano dane dotyczące śrdniodobowych stęŜeń pyłu PM10 oraz dwutlenku
siarki dostępne w ramach regionalnego monitoringu środowiska (PIOŚ w Katowicach)
oraz dane dotyczące dobowej liczby zgonów ogółem i zgonów z powodu chorób układu
oddechowego i krąŜenia pochodzące z bazy Głównego Urzędu Statystycznego w
Warszawie. Wszystkie dane dotyczyły okresu 2001-2002. Obliczono odsetki dni z

2
właściwym dla nich indeksem jakości powietrza, stosując amerykański, francuski,
brytyjski i niemiecki sposób indeksowania. Następnie oceniono zaleŜność pomiędzy
przyjętą kategorią jakości powietrza a dobową umieralnością ogólną i specyficzną z
zastosowaniem współczynników korelacji Spearmana. Ostatecznie uzyskane wyniki
zweryfikowano przy uŜyciu testu ANOVA Kruskal-Wallis.
Uzyskane wyniki sugerują występowanie istotnego zróŜnicowania w zakresie
kategorii jakości powietrza atmosferycznego, zaleŜnie od przyjętego sposobu
klasyfikacji. Procent dni z tzw. ‘niezdrową’ jakością powietrza kształtował się w
badanym okresie (2001-2002) w zakresie od 0.1% (amerykański sposób indeksowania)
do 11.2% (brytyjski sposób indeksowania) i zazwyczaj kategoria dotyczyła okresu
zimy. Statystycznie znamienne wartości współczynników korelacji Spearmana
uzyskano jedynie dla zaleŜności pomiędzy jakością powietrza a dobową liczbą zgonów
ogółem oraz zgonów z powodu chorób układu oddechowego i krąŜenia w grupie osób
po 65 roku Ŝycia. JednakŜe zaobserwowane wartości współczynników były niewielkie i
nie przekraczały wartości 0.2 dla kaŜdej z przyjętych metod klasyfikacji.
Summary
Air Quality Index (AQI) is a standardized summary measure of ambient air
quality used
to express the level of health risk related to particulate and gaseous air pollution
.
The index, first introduced by US EPA in 1998 classified ambient air quality according
to concentrations of such principal air pollutants as PM
10
, PM
2,5
, ozone, SO
2
, NO
2
and
CO. Subsequently similar, index-based approach to express health risk, was developed
in France, Great Britain and Germany. No such environmental warning system exists in
Poland, although some test-trials took place in Katowice area and the city of Gdańsk.
However, the operational value of AQI under environmental circumstances in Poland
remains unknown.
The aim of study was to examine current air pollution levels in Katowice area
and to confront AQI categories with local air quality, also in terms of health impact on
the population as expressed by daily total and specific mortality.
It was collected data of daily average PM
10
and sulphur dioxide concentrations
available in regional network (PIOŚ in Katowice) and data of daily number of total
deaths and deaths due to cordiorespiratory diseases from the Central Statistical Office in
Warsaw, interesting data was concerned the period 2001-2002. It was calculated
percentage of days with individual Air Quality Index, created by American, French,

3
British and German method of indexation. Then it was assessed the relationship
between values of air quality indexes and daily total and specific mortality according to
Spearman correlation coefficients. Finally, obtained results were verified according to
ANOVA Kruskal-Wallis test.
Obtained results suggest significant discrepancy in range of air quality
categories depending on applied system of classification. Percent of days with
‘unhealthy’ air quality (in the period 2001-2002) was running from 0.1% (American
method of indexation) to 11.2% (British method) and usually applied winter season.
Statistically significant Spearman correlation coefficients was obtained for relationship
between air quality and total number of deaths, as well as number of deaths due to
cardiovascular and respiratory diseases in elder population (aged 65 and more).
Observed values of correlation coefficients are very low and don’t exceed value 0.2 for
each chosen method of indexation.
Background
The impact of ambient air pollution on the human health has been subject to many
epidemiological investigations performed worldwide and targeting morbidity and
mortality, both total and specific mostly due to respiratory and circulatory diseases. The
accumulated epidemiologic evidence provided scientific background for regular
assessment of air pollution-related health risk, summarized in the reports published
under the auspices of World Health Organization [15]. A wide spectrum of health risk
estimates and their presentation are commonly used by public health professionals;
however their meaning is less clear to the public, more and more interested in
environmental health hazards. A need to communicate the results and inform the public
about potential health impacts of the measured and/or projected ambient air pollution
levels prompted the effort to develop an easily understood information, of every-day use
by the public, including administrative authorities [6,13]. The concept was addressed as
early as in 1970 the European level and followed by initiatives taken by the
Environmental Protection Agency in the USA in 1998 [2, 5]. As a result summary
index, known as the Air Quality Index (AQI) was introduced in order to express an
increasing health risk to the public in response to an increasing ambient air pollution, an
a daily basis. The construction of AQI allows distinction between “good” and “bad” air
quality.

4
The Air Quality Index developed in the USA is based on the combined effects of
five criteria pollutants: suspended particulate matter – aerodynamic diameter below 10
and 2.5 µm (PM
10
, PM
2.5
), sulphur dioxide (SO
2
), carbon monoxide (CO), ozone (O
3
)
and nitrogen dioxide (NO
2
) [1]. Concentrations of the pollutants are recorded by
automatic air monitoring stations permitting prompt data analysis and transformation of
the readings into the AQI scale. The range of AQI values includes seven categories
grouped into “good”, “moderate” and “dangerous” air quality zones [1]. The “good” air
quality zone is defined if the AQI is in the range 0 to 50. The “moderate” air quality
zone is defined if the AQI is between 51 and 100. The “dangerous” air quality zone is
defined if the AQI values over 100. A similar three-level approach has been adopted in
the European countries. Table 1 shows the cut-of values for the specific air quality
zones used in France, Great Britain and Germany, compared to the US standards
[12,18-19].
In addition to the between-country differences in the decisive cut-of values of air
pollution the country-specific AQIs differ in the internal composition, as shown in
Table 2 [12,18-19]. Moreover, in each country the AQI is calculated on the daily basis.
The presentation of AQIs implies their practical application, both in
environmental health risk communication to the public (via media) and as an evidence-
based support for preventive measures. Because of its simplicity the AQI serves as a
convenient early warning tool. No such environmental warning system exists in Poland,
although some test-trials took place in Katowice area and the city of Gdańsk [4,16].
However, the operational value of AQI under environmental circumstances in Poland
remains unknown. Because of poor ambient air quality in our country it is essential to
examine the potential for AQI application and to explore the system’s functioning given
ambient air quality in Poland. For a number of reasons relevant findings could be
provided by a pilot study implemented under the “worst case scenario”, in terms of
ambient air pollution. Hence, the aim of the study was to examine current air pollution
levels in Katowice area and to confront local air quality with AQI categories, also in
terms of health impact on the population as expressed by daily total and specific
(cardiovascular and respiratory mortality)
mortality.
Material and methods. Data concerning ambient air pollution, such as particulate
mater PM10 and sulphur dioxide, and meteorological conditions were obtained from
regional network providing on-line measurements by the State Environmental Agency

5
in Silesia voivodeship. There were calculated as 24-hour area averages and applied to
measurements in 14 regional stations. Mortality data (total and specific mortality) were
obtained from the registry at the Central Statistical Office in Warsaw. The records were
analyzed according to the classification scheme of the International Classification of
Diseases – 10
th
Edition (ICD-10) [11] and included the number of daily deaths in
population living in the urban area of Katowice from January 01 to December 31 in the
period 2001-2002. Daily mortality was arranged in three categories: all deaths, deaths
due to cardiovascular causes (ICD-10 codes: I00-I99) and deaths due to respiratory
causes (ICD-10 codes: J00-J99). Moreover, analysis was taken for the two aged groups:
inhabitants aged 0-64 years and aged 65 and more. It was calculated the percentage of
days with selected AQI categories according to available method (American, French,
British and German), but established way of indexation concern only 24-hourly PM10
concentrations. Next, it was calculated mean value of daily number of deaths
characteristic for days with particular categories quality of air, expressed by 33th and
66th percentile of PM10 concentration or specific AQI value. The association between
air quality and daily number of deaths was calculated by ANOVA Kruskal-Wallis
procedure. Moreover the relationship between daily number of deaths and value of AQI
was estimated by means of Spearman correlation analysis. Finally, the obtained results
were verified by ANOVA Kruskal –Wallis procedure. Interpretation of statistical
significance of the results was based on the criterion p<0.05. Statistica 7.1 statistical
software was used for all of the calculations.
Results. Values of daily particulate matter (PM10) and sulphur dioxide (SO2)
concentrations measured in the urban area of Katowice, in the study period (year 2001-
2002), are presented in the Table 3. Mean value was below the acceptable limit value
for both pollution, but observed maximum concentrations exceeded the established
norms only in the winter time.
Percentage of days with selected value of AQI calculated for PM10
concentrations, defined such as “dangerous air quality” depends of chosen indexation
method and amounted from 0.1% (American method, AQI in the range 4-7) and 6.1%
(German - AQI in the range 6, and French method- AQI in the range 8-10) to over 11%
(British method, AQI in the range 7-10) and usually concerned winter season.
The observed number of total deaths, deaths due to cardiovascular and
respiratory diseases, their average values and number of deaths during days with low,

6
medium or high concentration of particulate matter (PM10) are presented in the Table 4.
The most of total deaths (about 47% from 39 222 cases) concerned deaths due to
cardiovascular diseases, and most of them appeared in the older population (people aged
65 year or more). Deaths due to respiratory diseases represent near 4.1% of total
mortality in the study period, but it is significant that most of them (78.2%) concerned
elderly. Moreover it was observed, that the number of total deaths and deaths due to
cardiorespiratory diseases in total and old population depends on chosen level of PM
concentration, defined by value of 33.33 and 66.66 percentile. The highest mortality
concerned days with high level of air pollution, exceeding the concentration 49.3 µg/m
3
.
Moreover it was calculated mean value of daily total and specific mortality
characteristic for days with particular AQI defined as: good, moderate and dangerous
category of air quality, determine by particular methods of indexation. It was observed
that the highest mortality concerned days with dangerous quality of air. Detailed results
are presented in Table 5. The association between mortality and quality of air was
similar for German, British and French method of indexation, but finally the obtained
results confirm that the highest mortality concerned days with dangerous quality of air
and the lowest concerned days with good quality of air. The observed variability was
statistically significant in each AQI categories.
The relationship between daily number of deaths, separately for total and
specific mortality, and value of particular AQI was estimated by means of Spearman
correlation analysis. The obtained results are presented in Table 6 and confirm existence
statistically significant correlation for each chosen air quality index and daily count of
deaths in total and elderly population, although values of correlation coefficients were
below 0.20. It was observed that particular values of correlation coefficient were similar
in each applied method of AQI indexation. It was documented that the higher level of
AQI is associated with the increase of daily mortality.
Finally, the obtained results were verified by ANOVA Kruskal –Wallis
procedure and additionally by median test. Table 7 presents particularly data
(statistically significance expressed by ‘p’ value) in both tests for separate air quality
indexes. The results suggest that the difference between medians of compared groups is
not statistically significant only in population aged 0-64 years.

7
Discussion.
The obtained results suggest disagreement on the range of air quality according
to selected classification method. Percent of days with ‘unhealthy’ air quality (in the
period 2001-2002) was between 0.1% (American method of indexation) and 11.2%
(British method). The frequency of days with air quality dangerous for health (PM10
concentrations) calculated by French and German AQI were similar and amounted near
6%. Moreover, it was observed that the highest number of daily mortality was
characteristic for days with the highest level of PM10 concentration expressed by
percentile value of PM10 concentration or by AQI value. The association between
mortality and quality of air was similar for German, British and French method of
indexation, the course of relationship for American AQI was quite different, but finally
the highest mortality was assigned to dangerous air quality. We noted statistically
significant relationship between daily number of total deaths and deaths due to
cardiovascular/respiratory diseases and air quality index in the elderly (population aged
65+ years) and in total population. These results confirm that older people are the most
sensitive group of population in environmental health and our data are comparable with
well-known published data [3, 8-10,14].
According to poor ambient air quality in Silesia region, especially during the
winter time, it is essential to inform inhabitants about environmental health hazard.
Confrontation data of local air quality with AQI categories and with daily total and
specific (cardiovascular and respiratory)
mortality confirm, that British and French
method of AQI indexation are the best way to risk communication in Poland. Probably,
similar climate conditions and specific of air pollution are comparable in all described
countries, so the association between air quality index and health effect is similar too.
Despite existence of very interesting handbooks prepared for older people [7,17]
the information is not enough clear and available to protect person with cardiovascular
or respiratory problems before undesirable health effects. It is necessary to disclose the
knowledge about air quality index and their association with health effect. Very
important source of this information are medical doctors, especially general practitioner.
Moreover well known websites or regional televisions are very useful sources to
transmit important information about environmental health risk.

8
References
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191-198 (2007).
6. Communicating air quality. A guidebook on communication with the public about air
quality. Environmental Protection Agency Rijnmond, Nethrlands 2006. Available:
www.citeair.rec.org
7. Dbaj o zdrowie w starszym wieku i oddychaj łatwiej. [in Polish]. Available
www.epa.aging/resources/factsheets
8. Fischer P., Hoek G., Brunekreef B., Verhoeff A., van Wijnen J. Air pollution and
mortality in The Netherlands: are the elderly more at risk? Eur Respir J Suppl. 40,34-
38 (2003).
9. Franklin M., Zeka A., Schwartz J. Association between PM2.5 and all-cause and
specific-cause mortality in 27 US communities. Journal of Exposure Science and
Environmental Epidemiology, 17 (3), 279-287 (2007)
10. Goldberg M.S., Burnet R.T., Bailar J.C.III., TamblynR., Ernst P., Flegel K. at all.
Identification of person with cardiorespiratory conditions who are at risk of dying from
the acute effects of ambient air particles. Environ Health Perspect, 109, Supll 4, 487-
494 (2001).
11. International Classification of Diseases.ICD-10. Vesalius, Kraków 1996
12. Klassifizierung der Luftqualität. Available: www.eurad.uni-koeln.de
13. Kyrkilis G, Chaloulakou A, Kassomenos PA. Development of an aggregate Air
Quality Index for an urban Mediterranean agglomeration: relation to potential health
effects. Environ Int, 33(5), 670-676 (2007).

9
14.Ostro B., Broadwin R., Green S., Feng W.Y., Lipsett M. Fine particulate air
pollution and mortality in nine California counties: results from CALFINE. Environ
Health Perspect, 114 (1), 29-33 (2006).
15. Report of WHO: Meta-analysis of time-series studies and panel studies of
Particulate Matter (PM) and Ozon (O
3
). WHO, Kopenhagen 2004
16. System prognoz jakości powietrza w strefach i aglomeracjach województwa
śląskiego (In polish). Available: www.spjp.katowice.pios.gov.pl
17. Środowiskowe czynniki ryzyka obciąŜają w znacznym stopniu pracę serca. [in
Polish]. Available www.epa.aging/resources/factsheets
18. The French Air Quality Index ATMO. Available: www.airparif.asso.fr
19. UK Air Quality Archive. Available: www.airquality.co.uk/archive/index.php

10
Table 1.
Cut-of values for daily PM10 concentration [µg/m
3
]
Category of air
quality USA France Great Britain Germany
Good 0-54 0-39 0-49 0-34
Moderate 55-154 40-79 50-74 35-99
Dangerous 155 and more 80 and more 75 and more 100 and more

11
Table 2.
AQI
USA France Great Britain Germany
1 good air quality good air quality good air quality good air quality
2 moderate air quality good air quality good air quality good air quality
3 moderate air quality good air quality good air quality good air quality
4 dangerous air
quality good air quality moderate air quality moderate air quality
5 dangerous air
quality moderate air quality moderate air quality moderate air quality
6 dangerous air
quality moderate air quality moderate air quality dangerous air
quality
7 dangerous air
quality moderate air quality dangerous air
quality
8 dangerous air
quality dangerous air
quality
9 dangerous air
quality dangerous air
quality
10 dangerous air
quality dangerous air
quality

12
Table 3.
Sulphur dioxide SO2 [µg/m
3
] Particulate matter PM10 [µg/m
3
]
Mean value ± SD 35.21 ± 24.18 48.98 ± 34.26
Median 27.10 39.45
Minimum 10.50 11.20
Maximum 239.80 421.30
33.3 percentile 21.90 31.80
66.6 percentile 36.50 49.30

13
Table 4.
Number of deaths during days with
selected concentrations of PM10
Deaths due to Age Total
number
of
deaths
Average
± SD Low
(<31,8 µg/m
3
)
Medium
(31,8-49,3
µg/m
3
)
High
(>49,3µg/m
3
)
0-64 years 4391 6.0 ±
2.4 6.2±2,4 5.7±2.3 6.0±2.5
65 and more
14065 19.2 ±
4.8 18.7±4.4 18.8±4.7 20.2±5.0
Cardiovascular
diseases
total 18456 25.2 ±
5.5 24.9±5.3 24.6±5.4 26.2±5.8
0-64 years 348 0.4 ±
0.7 0.4±0.7 0.4±0.6 0.5±0.7
65 and more
1246 1.7 ±
1.3 1.5±1.2 1.7±1.4 1.8±1.4
Respiratory
diseases
total 1594 2.1 ±
1.6 1.9±1.4 2.1±1.6 2.4±1.6
0-64 years 14220 19.4 ±
4.7 19.4±4.8 19.2±4.6 19.6±4.6
65 and more
25002 34.2 ±
6.3 33.1±5.8 34.2±6.5 35.5±6.4
Total
total 39222 53.7 ±
8.2 52.6±8.3 53.4±8.4 55.1±8.0

14
Table 5.
Number of deaths during days with selected AQI (mean value ± SD) Deaths due
to Great Britain France USA Germany
Age
g m d g m d g m d g m d
<65
6.0±2.4 5.7±2.3 6.3±2.8 6.0±2.4 5.9±2.4 6.2±2.8 5.9±2.4 6.1±2.6 9.0±0 6.1±2.4 5.9±2.5 6.0±2.7
+65
18.8±4.6
19.9±4.7
20.6±5.3
18.8±4.6
19.5±4.9
20.5±5.2
18.8±4.6
20.3±5.0
25.0±0
18.7±4.6
19.5±4.9
20.7±5.1
Cardio-
vascular
diseases total
24.8±5.4
25.6±5.3
26.9±6.1
24.8±5.4
25.5±5.6
26.7±5.9
24.8±5.4
26.4±5.7
34.0±0
24.9±5.5
25.4±5.5
26.7±5.8
<65
0.4±0.7 0.5±0.8 0.6±0.8 0.4±0.7 0.5±0.7 0.6±0.8 0.4±0.7 0.5±0.7 1.0±0 0.4±0.7 0.5±0.7 0.7±0.9
+65
1.6±1.3 1.7±1.4 2.0±1.5 1.6±1.3 1.8±1.4 2.0±1.4 1.6±1.3 1.9±1.4 2.0±0 1.6±1.3 1.8±1.4 2.0±1.5
Respiratory
diseases total
2.1±1.6 2.3±1.5 2.6±1.7 2.0±1.6 2.3±1.6 2.6±1.6 2.1±1.5 2.5±1.6 3.0±0 2.0±1.5 2.3±1.6 2.7±1.7
<65
19.4±4.7
19.5±4.8
19.7±4.5
19.3±4.7
19.5±4.8
19.9±4.3
19.4±4.8
19.6±4.5
29±0 19.3±4.9
19.5±4.6
20.4±4.4
+65
33.6±6.2
34.9±6.3
36.0±6.4
33.4±6.2
34.8±6.3
36.1±6.7
33.8±6.3
35.4±6.3
40.0±0
33.4±6.2
34.6±6.4
36.7±5.6
Total
total
53.0±8.3
54.5±8.0
55.9±7.9
52.7±8.5
54.3±7.8
56.1±7.9
53.2±8.5
55.0±7.6
69.0±0
52.7±8.8
54.1±7.8
57.1±7.7

Table 6.
Daily mortality Population
aged AQI
Great Britain AQI
France AQI
USA AQI
Germany
0-64 0.00 (NS)
0.01 (NS)
0.04 (NS)
0.00 (NS)
65 + 0.15 (p<0.05)
0.15 (p<0.05)
0.16 (p<0.05)
0.14 (p<0.05)
Cardiorespiratory
diseases Total 0.13 (p<0.05)
0.13 (p<0.05)
0.16 (p<0.05)
0.12 (p<0.05)
0-64 -0.02 (NS)
-0.01(NS)
0.03 (NS)
-0.01(NS)
65 + 0.13 (p<0.05)
0.14 (p<0.05)
0.14 (p<0.05)
0.13 (p<0.05)
Cardiovascular
diseases Total 0.11 (p<0.05)
0.11 (p<0.05)
0.14 (p<0.05)
0.10 (p<0.05)
0-64 0.07(NS)
0.08 (NS)
0.08 (NS)
0.07 (NS)
65 + 0.10 (p<0.05)
0.11 (p<0.05)
0.10 (p<0.05)
0.10 (p<0.05)
Respiratory
diseases Total 0.12 (p<0.05)
0.13 (p<0.05)
0.13 (p<0.05)
0.12 (p<0.05)
0-64 0.03 (NS)
0.03 (NS)
0.04 (NS)
0.04 (NS)
65 + 0.17 (p<0.05)
0.17 (p<0.05)
0.13 (p<0.05)
0.16 (p<0.05)
Total number of
deaths Total 0.15 (p<0.05)
0.15 (p<0.05)
0.11 (p<0.05)
0.14 (p<0.05)

16
Table 7.
AQI
Great Britain AQI
France AQI
USA AQI
Germany
Mortality Population
aged K-W M K-W M K-W M K-W M
Total 0.0009
0.009 0.0005
0.01 0.0001
0.0009
0.004 0.01
0-64 0.1 0.3 0.07 0.1 0.3 0.5 0.4 0.5
Cardio-
respiratory
diseases 65 + 0.001 0.007 0.0007
0.001 0.0001
0.0001
0.001 0.001
Total 0.004 0.02 0.004 0.01 0.004 0.03 0.0001
0.01
0-64 0.8 0.7 0.7 0.8 0.1 0.2 0.5 0.4
Total
number of
deaths 65 + 0.001 0.0009
0.0005
0.0003
0.002 0.0005
0.0007
0.001

17
Tables
Table 1. Comparison of the definition of three categories of ambient air quality (“good”,
“moderate”, “dangerous”) used in Air Quality Indices in the USA, France, Great Britain and
Germany – example for 24 hours PM10 concentration.
Table 2. Composition of Air Quality Index in selected countries.
Table 3. Daily means concentrations of PM10 and SO2 in ambient air in urban area of
Katowice, in the period 2001-2002.
Table 4. Total and daily number of deaths in the Urban Area of Katowice, in the study period
2001-2002.
Table 5. Total and daily number of deaths in the Urban Area of Katowice, in the study period
2001-2002.
Legend: g – good; m – moderate; d – dangerous
Table 6. Spearman correlation coefficients for relationship between daily count of deaths and
air quality index by different method of indexation, p value in the bracket.
Legend: NS – not statistically significant
Table 7. Results of ANOVA Kruskal-Wallis and median procedure (p values) in relationship
between AQI and daily mortality, urban area of Katowice in the period 2001-2002.
Legend: K-W – Kruskal-Wallis procedure; M- median test