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Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM2.5, NO2) concentrations in the European EXPOLIS study
Atmospheric Environment 36 (2002) 4593–4602
Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM2.5, NO2) concentrations in the European EXPOLIS study b Tuulia Rotkoa,*, Lucy Oglesbyb, Nino Kunzli . , Paolo Carrerc, Mark J. Nieuwenhuijsend, Matti Jantunena a
Department of Environmental Health, KTL-National Public Health Institute, P.O. Box 95, FIN-70701 Kuopio, Finland b Institute of Social and Preventive Medicine, University of Basel, Steinengraben 49, CH-4051 Basel, Switzerland c Institute of Occupational Health, University of Milan, Via San Barnaba 8, IT-20122 Milan, Italy d Department of Environmental Science and Technology, Imperial College of Science, Technology and Medicine, London SW7 2BP, UK Received 11 February 2002; received in revised form 24 June 2002; accepted 28 June 2002
Abstract Apart from its traditionally considered objective impacts on health, air pollution can also have perceived effects, such as annoyance. The psychological effects of air pollution may often be more important to well-being than the biophysical effects. Health effects of perceived annoyance from air pollution are so far unknown. More knowledge of air pollution annoyance levels, determinants and also associations with different air pollution components is needed. In the European air pollution exposure study, EXPOLIS, the air pollution annoyance as perceived at home, workplace and in traffic were surveyed among other study objectives. Overall 1736 randomly drawn 25–55-yr-old subjects participated in six cities (Athens, Basel, Milan, Oxford, Prague and Helsinki). Levels and predictors of individual perceived annoyances from air pollution were assessed. Instead of the usual air pollution concentrations at fixed monitoring sites, this paper compares the measured microenvironment concentrations and personal exposures of PM2.5 and NO2 to the perceived annoyance levels. A considerable proportion of the adults surveyed was annoyed by air pollution. Female gender, self-reported respiratory symptoms, downtown living and self-reported sensitivity to air pollution were directly associated with high air pollution annoyance score while in traffic, but smoking status, age or education level were not significantly associated. Population level annoyance averages correlated with the city average exposure levels of PM2.5 and NO2. A high correlation was observed between the personal 48-h PM2.5 exposure and perceived annoyance at home as well as between the mean annoyance at work and both the average work indoor PM2.5 and the personal work time PM2.5 exposure. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM2.5) and 19% (NO2) of the variation in perceived air pollution annoyance in traffic. Compared to Helsinki, in Basel and Prague the adult participants were more annoyed by air pollution while in traffic even after taking the current home outdoor PM2.5 and NO2 levels into account. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Exposure; Fine particles; Nitrogen dioxide; Road traffic; Workplace
1. Introduction *Corresponding author. Department of Sociology, University of Helsinki, P.O Box 35, FIN-00014 Helsinki, Finland. Tel.: +358-9-19124700; fax: +358-9-191-24750. E-mail address: tuulia.rotko@helsinki.fi (T. Rotko).
Apart from its objective impacts on health (Committee of Environmental and Occupational Health Assembly of the American Thoracic Society, 1996), air
1352-2310/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 2 - 2 3 1 0 ( 0 2 ) 0 0 4 6 5 - X
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T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
pollution can also have perceived effects, such as annoyance, even at low concentrations. In addition to studies on perceived annoyance in association with psychosomatic symptoms and respiratory illnesses (Lercher et al., 1995) and startle reflex and breathing changes (Danuser, 2001), several studies have quantified the relations between the annoyance from environmental factors and the measured levels of these factors. Annoyance from environmental noise, odour and air pollution have been compared to levels of environmental noise (Klaeboe et al., 2000; Miedema and Vos, 1998; Lercher and Kofler, 1996), odours (Danuser, 2001; Miedema et al., 2000) and air pollution (Klaeboe et al., 2000; Oglesby et al., 2000a; Forsberg et al., 1997; Lercher et al., 1995; Evans et al., 1988). Oglesby et al. (2000a, b) investigated the validity of air pollution annoyance as an indirect and simplistic but inexpensive exposure assessment tool in air pollution epidemiology. Klaeboe et al. (2000) adopted an integrated approach to study the simultaneous effects of exposure, traffic noise and air pollution annoyance from traffic. Evans et al. (1988) investigated psychological reactions to air pollution and found that a large representative sample of Los Angeles residents were somewhat aware and concerned about air pollution, but not knowledgeable about its causes and that there were modest but significant relationships between ambient photochemical oxidants and anxiety symptoms. Meertens and Swaen (1997) suggested that the psychological effects of air pollution might often be of greater importance to well-being than the biophysical effects. Population level perceived air pollution annoyance has so far been compared mostly to ambient long-term (6-month, 1-yr averages) air pollution levels measured at fixed monitoring sites (Oglesby et al., 2000a; Forsberg et al., 1997; Lercher et al., 1995). Exposure indicators for air pollution have been produced for each respondent also by comprehensive environmental modelling (Klaeboe et al., 2000). More recent approaches, such as microenvironment and personal monitoring, give more accurate information of individual level short-term exposures to the selected pollutants. Oglesby et al. (2000a) performed individual level analysis of exposure– annoyance relationship based on residential outdoor NO2 measurements. However, annoyance also depends on individual characteristics, such as sensitivity, health status, and attitude towards traffic, tobacco smoke or other sources of air pollution. EXPOLIS (Air Pollution Exposure Distributions within Adult Urban Populations in Europe) is a European multi-city air pollution exposure study. Within the framework of the EXPOLIS study each participant reported the annoyance caused by air pollution after the 48-h participation period. Concurrently personal exposures and microenvironment concentrations of PM2.5 and NO2 were measured. Although the air
pollution annoyances have been compared to the levels of a few specific pollutants, it is important to keep in mind that the air pollutants which may cause most of the annoyance maybe other than those measured, and that the annoyance is most likely an aggregate effect of many different pollutants. In addition to the individual level analysis of the annoyance–exposure relationship, the average of the short-term EXPOLIS measurements, collected by randomly selected participants throughout 1 yr, yields an estimate of the long-term population value for each city. In former studies, population mean annoyance scores and exposure concentrations have been compared between cities within one country (Oglesby et al., 2000a; Forsberg et al., 1997). In the EXPOLIS study respective comparisons are made between six cities in six European countries. The next section briefly describes the EXPOLIS study design including population sampling, annoyance and air pollution measurements with the used methods. The objectives of this work are: *
*
to assess and compare the levels and determinants of air pollution annoyance among the adult populations of six European cities and to determine the correlation between the perceived air pollution annoyance and the measured fine particle (PM2.5) and nitrogen dioxide (NO2) exposures and microenvironment concentrations. PM2.5 represents the most hazardous air pollutant and NO2 is often used as a marker of ambient air pollution originating from combustion, especially traffic.
2. Material and methods The EXPOLIS study consisted of two randomly drawn population samples, the Exposure and Diary samples, of adults (25–55 yr) in each participating city (Athens, Greece; Basel, Switzerland; Helsinki, Finland; Milan, Italy; Oxford, United Kingdom and Prague, Czech Republic). A detailed description of the EXPOLIS study design, sampling, data and QA/QC is presented in Jantunen et al. (1998). The Exposure sample filled in questionnaires and time-activity-diaries with personal exposure monitoring and microenvironment measurements of PM2.5 and NO2. The Diary sample filled in the same questionnaires and time-activitydiaries without air pollution monitoring. Both the Exposure and Diary samples had somewhat more women and more educated adults compared to the general same-age population in these cities. These population samples are described and the representativity of them is evaluated in detail in Rotko et al. (2000) and Oglesby et al. (2000b). In addition, in Helsinki another Environment Attitude Questionnaire sample
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
(Heaq) participated by filling in the questionnaire 1 yr later without personal monitoring. The participants of EXPOLIS reported the perceived annoyance from air pollution at home, at work and in traffic on the annoyance scale which ranged from 0 (no annoyance at all) to 10 (unbearable annoyance) (the same as in Oglesby et al., 2000a). After the measurement period the participants were asked ‘‘To what degree did you feel annoyed about air pollution at home/at workplace/in traffic during the last 48-h?’’ (three different questions). Determinants of the perceived annoyances were searched from the EXPOLIS questionnaire data. In addition to the basic background questions (gender, age, education) the following questions were used: current smoking status, self-reported allergic symptoms (wheezing, nasal allergies, asthma), self-reported sensitivity to air pollution, having small children and home location (downtown/suburban). The fixed site monitoring data was received from each city’s urban air quality monitoring network and data of one urban background monitoring station was used from each city. Ambient fixed site PM2.5 concentrations were measured with high volume monitoring (Eberline or Digitel) (available from Helsinki and Basel only) and ambient air NO2 concentrations were monitored by the standard chemiluminesence method (ISO 7996, 1985). PM2.5 results are available from the Exposure samples in six EXPOLIS cities (Athens (A), Basel (B), Milan (M), Oxford (O), Prague (P), and Helsinki (H)). Personal PM2.5 exposures were collected on two different filters: one for the working hours including commuting (personal work) and the other for the remaining hours of 48-h measurement period (personal leisure time). In addition to personal exposure monitoring, PM2.5 concentrations were measured in each home (indoors and outdoors) and workplace (indoors). The PM2.5 concentration measured at work was the average of two consecutive workdays and at home of the remaining hours of the 48-h monitoring period. PM2.5 personal cyclones were used as pre-separators at flow rate of 4 l min1 and the EPA-WINS impactors were employed at 16.7 l min1 for the microenvironment measurements with Gelman Teflo filters (37- and 47-mm, respectively). Detailed methods and quality assurance results for the PM2.5 measurements in EXPOLIS are presented by Koistinen et al. (1999) and H.anninen et al. (2001). In the EXPOLIS study personal and microenvironment NO2 samples were collected from Helsinki, Basel, Oxford and Prague. The reported NO2 concentrations are 48-h averages collected by Palmes passive samplers. More detailed descriptions of the EXPOLIS NO2 measurements and results are presented in Rotko et al. (2001) and Kousa et al. (2001). The Exposure, Diary and Heaq samples are combined in the analyses of the annoyance levels and determi-
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nants. A time-weighted total mean annoyance was computed by weighting each of the three average annoyance scores (residential, workplace, traffic) by the average time used in each of these microenvironments. Analysis of the associations between perceived annoyance caused by air pollution and concurrently measured air pollution exposure levels to PM2.5 and NO2 include only the Exposure sample. All statistical tests were carried with a SPSS statistical package (SPSS Inc. 1998, version 9.0).
3. Results 3.1. Levels and determinants of perceived air pollution annoyance Air pollution in traffic annoyed the most. The average perceived annoyance scores in traffic ranged from 3.6 in Helsinki to 7.1 in Prague (Table 1). The average annoyance levels at the workplaces (from 1.8 in Oxford to 3.9 in Athens) were higher than at home (from 1.4 in Oxford to 2.0 in Milan), except in Prague (3.3 and 4.3, respectively). In Helsinki 15–22% and in Prague 62% of the participants were highly annoyed (annoyance score X7) by air pollution in traffic. At workplaces the share of highly annoyed ranged from 4% in Oxford to 22% in Athens and respectively at home from 3% in Basel to 25% in Prague. At home 8–53% of participants were not at all annoyed by air pollution, but in traffic only 1– 15%. A time-weighted total mean annoyance ranged between 2.1 in Helsinki and 3.9 in Prague. In the first univariate logistic regression analysis each possible determinant was evaluated one at a time, and a dichotomised annoyance (annoyance scores >7 versus p7) rating of traffic annoyance was used as the outcome measure. Significant individual determinants were the city, gender, self-reported allergic symptoms, selfreported sensitivity to air pollution, and home location. Women, Athens, Basel, Milan and Prague inhabitants (compared to Helsinki), those reporting respiratory symptoms, those reporting to be sensitive to air pollution and those living in downtown area were on average more annoyed about air pollution than the remaining population groups (Table 2). Age, education level, current smoking status or having children were not significant determinants of air pollution annoyance in traffic. In a second multivariate logistic regression model (the determinants were added into the model at the same time), excluding respiratory symptoms and self-reported sensitivity to air pollution, the effect of gender and city remained almost the same and the impact of downtown living decreased somewhat. When respiratory symptoms and self-reported sensitivity to air pollution were included in the adjusted model, Athens and Basel dropped out and the other values changed also. The
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T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
Table 1 Average levels of perceived air pollution annoyance in the EXPOLIS cities
Residential Home annoyance mean Home annoyance SD Proportion (%) Not annoyed (0) Slightly annoyed (1–2) Moderately annoyed (3–6) Highly annoyed (7–10) Workplace Work annoyance mean Work annoyance SD Proportion (%) Not annoyed (0) Slightly annoyed (1–2) Moderately annoyed (3–6) Highly annoyed (7–10) In traffic Mean annoyance in traffic Traffic annoyance SD Proportion (%) Not annoyed (0) Slightly annoyed (1–2) Moderately annoyed (3–6) Highly annoyed (7–10) Time-weighted mean total annoyance
Helsinki
Heaq
Athens
Basel
Milan
Oxford
Prague
n ¼ 428 1.73 2.18
n ¼ 421 1.94 2.30
n ¼ 100 1.87 2.31
n ¼ 330 1.98 2.00
n ¼ 299 2.03 2.18
n ¼ 55 1.44 2.23
n ¼ 83 4.30 2.83
40.4 33.9 19.4 6.3
36.6 34.2 22.1 7.1
42.0 27.0 24.0 7.0
34.8 30.9 31.5 2.7
38.1 25.4 32.4 4.0
52.7 27.3 14.5 5.5
8.4 22.9 43.4 25.3
n ¼ 384 2.60 2.58
n ¼ 361 3.26 2.85
n ¼ 72 3.85 2.81
n ¼ 273 2.64 2.39
n ¼ 274 3.80 2.74
n ¼ 46 1.78 2.35
n ¼ 72 3.29 2.86
30.5 26.3 33.3 9.9
24.4 22.4 35.2 18.0
19.4 16.7 41.7 22.2
28.2 23.8 41.0 7.0
20.1 13.1 48.5 18.2
50.0 17.4 28.3 4.3
25.0 20.8 38.9 15.3
n ¼ 425 3.58 2.50
n ¼ 422 3.90 2.84
n ¼ 92 4.93 3.08
n ¼ 327 5.01 2.63
n ¼ 299 5.94 2.65
na na
n ¼ 84 7.08 2.41
14.6 20.9 49.6 14.8
13.7 22.7 41.5 22.0
14.1 8.7 43.5 33.7
7.0 11.0 51.4 30.6
4.7 7.0 41.1 47.2
na na na
1.2 3.6 33.3 61.9
2.14
na
2.54
2.45
2.91
na
3.94
na=not available, Heaq=Helsinki Environmental Attitude Questionnaire sample (7 December 1998–5 June 1999).
effect of respiratory symptoms and self-reported sensitivity to air pollution (and also female gender) on high traffic annoyance decreased somewhat compared to the unadjusted model. 3.2. Air pollution concentration levels Fixed site 24-h mean PM2.5 values from the whole EXPOLIS study period were 9 mg m3 in Helsinki and 22 mg m3 in Basel (Table 3). The mean ambient NO2 for the whole study period ranged from 27 mg m3 in Helsinki to 97 mg m3 in Athens. The NO2 means for the actual measurement periods and the time-activity diary filling periods (no weekends) were usually somewhat higher than means over the whole study period. Among the EXPOLIS PM2.5 measurements the workplace indoor concentrations were usually the highest (from 16 mg m3 in Helsinki to 90 mg m3 in Athens), except in Oxford and Basel, followed by personal exposure and home indoor levels (Table 3). Home outdoor PM2.5 concentrations (from 10 mg m3 in Helsinki to 41 mg m3 in Milan) were the lowest. The average residential outdoor PM2.5 concentrations measured in EXPOLIS were almost the same as the fixed site levels in
Helsinki and Basel and the Pearson correlation between the values was high; r ¼ 0:84 in Helsinki and r ¼ 0:96 in Basel. The fixed site NO2 averages were higher in Helsinki but lower in Basel and Prague than the residential outdoor EXPOLIS levels. Pearson correlation between the fixed site NO2 and the residential outdoor EXPOLIS measurements was r ¼ 0:45 in Helsinki, r ¼ 0:84 in Basel and r ¼ 0:36 in Prague. The residential outdoor levels of NO2 in Basel (36 mg m3) and Prague (61 mg m3) and work indoor levels in Helsinki (27 mg m3) and Oxford (31 mg m3) were the highest among the measured exposures and microenvironments in these cities. 3.3. Correlation between perceived air pollution annoyance and measured PM2.5 and NO2 concentrations The perceived annoyance variation was large and the individual annoyance scores at home, at work or in traffic did not correlate with the corresponding EXPOLIS measurements in any of the EXPOLIS cities. The Pearson correlation coefficients between individual annoyance scores and the measured PM2.5 and NO2 exposures and concentrations (annoyance at home versus personal exposures and residential indoor
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
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Table 2 Determinants of perceived air pollution annoyance in traffic: unadjusteda and adjustedb odds ratios and 95% confidence intervals of the highly annoyed (>7 versus p7 at annoyance scale, n ¼ 336)
City (Helsinki) Athens Basel Milan Prague Female Age (25–34 yr) 35–44 yr 45–55 yr Education X14 yr Current smoker Respiratory symptoms Sensitive to air pollution Having children Downtown living
N
% of highly annoyed
847 92 327 299 84 914 505 534 603 981 406 401 294 669 505
11 26 24 32 54 24 22 20 19 20 20 31c 32e 19 30
OR Unadjusteda
95% CI (n ¼ 1649)
OR Adjustedb
95% CI (n ¼ 1586)
2.86nn 2.58nn 3.78nn 9.35nn 1.61nn
(1.71; (1.85; (2.73; (5.79; (1.25;
4.78) 3.60) 5.23) 15.12) 2.06)
2.90nn 2.60nn 3.74nn 8.15nn 1.65nn
(1.70; (1.84; (2.65; (4.83; (1.27;
0.88 0.85 0.92 0.92 1.95nn 2.50nn 0.83 2.14nn
(0.65; (0.63; (0.72; (0.69; (1.46; (1.86; (0.65; (1.67;
1.19) 1.13) 1.18) 1.22) 2.60) 3.37) 1.07) 2.74)
0.96 1.04 0.98 0.97 1.82d 1.63d 0.96 1.39n
(0.69; 1.34) (0.75; 1.43) (0.75; 1.28) (0.71; 1.31) (1.21; 2.74) (1.03; 2.57) (0.73; 1.28) (1.04; 1.84)
nn n
4.93) 3.68) 5.29) 13.75) 2.15)
a
Unadjusted=each variable at a time. Adjusted=with the other determinants. c Symptoms not asked in Athens. d If included in the adjusted model Athens and Basel will drop out of it, and other values would change also. e Sensitivity not asked in Basel and Oxford. n po0:05: nn po0:001: b
concentrations, annoyance at work versus personal working time exposure and work indoor concentrations as well as annoyance in traffic versus residential outdoor concentrations) ranged between 0:19oro0:36 and no correlation was significant. As an example individual perceived air pollution annoyance at work versus PM2.5 levels at work indoors for EXPOLIS cities is presented in Fig. 1. In contrast, at population level the mean annoyance scores and mean PM2.5 and NO2 concentrations of the EXPOLIS measurements across cities did correlate and some of these correlations were high. However, the correlations were not significant due to the small number of observations (cities). The mean annoyance at home did not correlate with the average home indoor PM2.5 or the personal leisure time PM2.5 exposure, but the correlation was higher between the annoyance at home and personal 48-h PM2.5 exposure (Fig. 2). The mean annoyance in traffic correlated weakly with the average home outdoor PM2.5. The mean annoyance at work correlated strongly with both the average work indoor PM2.5 and the personal work time PM2.5 exposure. The correlations between the mean annoyance scores at home and the mean NO2 exposure and residential indoor NO2 concentration were high. Likewise, the correlation between the mean annoyance in traffic and the residential outdoor concentration (with small number of observations) was also high (Fig. 3).
3.4. Regression models of perceived air pollution annoyance in traffic Crude estimates of the linear regression models showed that 10 mg m3 change in the NO2 home outdoor level increased annoyance level in traffic more than the same change in the PM2.5 home outdoor level, and both were significant (Table 4). However, home outdoor levels explained only 4% (PM2.5) and 13% (NO2) of the variation in individual perceived air pollution annoyance scores in traffic. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM2.5) and 19% (NO2) of the variation in perceived air pollution annoyance in traffic. In the multivariate models, however, home outdoor PM2.5 and NO2 levels no longer significantly affected the perceived annoyances. Even after adjusting for the different PM2.5 outdoor concentrations in the EXPOLIS cities, the participants scored 1.5 points higher in Athens and Basel and 2.5 points higher in Milan and Prague on the air pollution annoyance scale while in traffic compared to Helsinki. After adjusting for the level of outdoor NO2 concentration in the different EXPOLIS cities participants in Basel scored 1.2 points higher and in Prague 1.5 points higher on the perceived annoyance scale compared to Helsinki. Similar results were obtained with multivariate logistic regression models using
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
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Table 3 Levels of air pollution (mg m3) in fixed site stations during measurement periods in EXPOLIS cities and mean values of EXPOLIS PM2.5 and NO2 measurements (mg m3)
PM2.5 Fixed site Mean1a Rangeb Mean2c EXPOLIS N Personal 48-hd Home, indoor Home, out Work, indoor NO2 Fixed site Mean1a Rangeb Mean2c EXPOLIS N Personal 48-hd Home, indoor Home, out Work, indoor
Helsinki1
Athens2
Basel3
Milan4
Oxford5
Prague6
9.1 (1.1–32.3) 9.9
— — —
21.4 (4.0–96.8) 21.9
— — —
— — —
— — —
201 15.1 12.1 9.7 15.9
50 28.6 35.5 36.6 90.3
50 27.8 20.8 19.4 26.7
50 na 42.7 41.3 59.0
60 16.5 17.0 10.6 11.8
50 35.2 35.9 26.9 42.9
26.6 (4.7–71.6) 30.2
97.0 (35.5–190.3) 94.6
28.9 (6.5–65.0) 29.3
82.9 (25.8–196.0) 84.1
na na na
39.0 (13.1–84.3) 42.2
176 25.0 17.7 23.9 27.0
— — — — —
50 33.2 30.1 36.2 35.0
— — — — —
60 28.3 25.4 24.5 31.1
50 44.4 43.1 60.5 30.7
Measurement periods: 1Helsinki (26 September 1996–10 December 1997); 2Athens (26 January 1997–4 June 1998); 3Basel (3 February 1997–23 January 1998); 4Milan (10 March 1997–23 May 1998); 5Oxford (4 November 1998–7 October 1999); 6Prague (3 June 1997–4 June 1998). —not measured, na=not available. a Fixed mean over the whole study period. b Range of 24-h means. c Fixed mean from the EXPOLIS 48-h measurement periods. d Personal 48-h exposure.
4. Discussion
Annoyance at work
R 2 = 0.06
10 9 8 7 6 5 4 3 2 1 0 0
50 100 150 200 250 Work indoor PM2.5 concentration (µg m-3)
300
Fig. 1. Individual perceived work annoyance scale scores versus PM2.5 levels at work indoors in the EXPOLIS cities (Helsinki, Basel, Athens, Milan and Prague).
high annoyance (annoyance scores >7) rating of air pollution annoyance in traffic as the outcome measure (Table 4).
Although the PM2.5 and NO2 levels were usually below the guidelines in the EXPOLIS cities, a considerable proportion of the adults surveyed was annoyed by air pollution. On average 29% of respondents in the EXPOLIS cities were highly annoyed (X7 at annoyance scale) by air pollution in traffic and 14% at workplace. Because women were over-represented among the respondents of the EXPOLIS study (Rotko et al., 2000) and women seem to be more annoyed by air pollution than men, probably somewhat higher annoyance levels were reached compared to other same age city populations. In Switzerland where annoyance was measured with a similar method, the average proportion of those highly annoyed (>7 at annoyance scale) by ambient air pollution was 18% in eight Swiss cities (Oglesby et al., 2000a). In Sweden (Forsberg et al., 1997) the proportion of adults that were daily or almost daily annoyed by air pollution varied from 5% to 17% in the selected 55 urban areas. In Austria 40% of the
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602 8.0
R 2 = 0.63
3.5
P Annoyance in traffic
Annoyance at home
4.0
3.0 2.5 B A
2.0 O
1.5
H
1.0 0.5 0
10
20
30
Personal 48h PM2.5 (µg
P
6.0
M B
5.0 4.0
A
H
3.0 2.0 1.0 0
40
A
3.0 H B
2.0 O
1.5
30
40
R2 = 0.15
3.5 Annoyance at home
P
2.5
20
50
4.0
R 2 = 0.79
3.5
10
Home outdoor PM2.5 (µg m-3)
m-3)
4.0 Annoyance at work
R 2 = 0.32
7.0
0.0
0.0
1.0 0.5 0.0
P
3.0 2.5 2.0
B
H
1.5
A O
1.0 0.5 0.0
0
20
40
60
80
0
Personal work time PM2.5 (µg m-3)
10
20
30
Personal leisure time PM2.5 (µg
40 m-3)
4.0 R 2 = 0.74
3.5
A
M P
3.0 H
2.5
B
2.0 O
1.5 1.0 0.5 0.0
R 2 = 0.23
3.5 Annoyance at home
4.0 Annoyance at work
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P
3.0 2.5 B
2.0
M
H
1.5
A
O
1.0 0.5 0.0
0
20
40
60
80
100
Work indoor PM2.5 (µg m-3)
0
10
20
30
40
50
Home indoor PM2.5 (µg m-3)
Fig. 2. Associations between mean air pollution annoyance scores and average personal (48-h, work and leisure time) and microenvironment PM2.5 levels in the EXPOLIS cities (H=Helsinki, A=Athens, B=Basel, M=Milan, O=Oxford, P=Prague).
respondents were annoyed by car fumes and 27% by visible dust/soot (Lercher et al., 1995). Like in the previous studies, female gender (Oglesby et al., 2000a, Klaeboe et al., 2000; Forsberg et al., 1997), self-reported respiratory symptoms (Oglesby et al., 2000a; Forsberg et al., 1997) and downtown living indicating high traffic volume near home (Forsberg et al., 1997) were shown to be determinants of perceived air pollution annoyance. In addition, self-reported sensitivity to air pollution, as well as sensitivity to noise and odours (Lercher et al., 1995), increased the probability of being highly annoyed. In some earlier studies also current smoking status (Oglesby et al., 2000a; Lercher
et al., 1995), older age and low education level (Klaeboe et al., 2000) were found to be determinants of perceived annoyance by air pollution. However, in the present study current smoking status (as in Forsberg et al., 1997), older age within the age range of 25–55 yr (as in Oglesby et al., 2000a) or low education level were not significant determinants of perceived air pollution annoyance. There is no EU standard for PM2.5, but the USNAAQS (USEPA, 1997) for annual average ambient PM2.5 is 15 mg m3. The average PM2.5 levels—for fixed site and EXPOLIS outdoor air measurements—were below this US standard in Helsinki and Oxford, but
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Annoyance at home
4.0 R2 = 0.95
P
3.0 2.0
B
H O
1.0 0.0 0
10
20 30 40 Personal 48-hour NO2 (µg m-3)
50
Annoyance at home
4.0
R2 = 0.87
P
3.0 2.0
B
H
O
1.0 0.0 0
10
20
30
40
50
Annoyance in traffic
Home indoor NO2 (µg m-3)
8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0
R 2 = 0.99
P B
H
0
20
40
60
80
Home outdoor NO2 (µg m-3)
Fig. 3. Associations between mean air pollution annoyance scores and average personal (48-h) and microenvironment NO2 levels in the EXPOLIS cities (H=Helsinki, B=Basel, O=Oxford, P=Prague).
above it in Basel, Prague, Athens and Milan. The NO2 levels were below the EU standard for annual average level, 40 mg m3 (Council of the European Union, 1999) in Helsinki, Basel and Oxford, but exceeded the EU standard in Prague, Athens and Milan. In a Swiss study the annual mean NO2 levels in some of the cities exceeded the EU guideline (Oglesby et al., 2000a). In Helsinki and Basel the individual EXPOLIS residential PM2.5 outdoor levels correlated highly with the fixed site PM2.5 values. The residential outdoor NO2 levels, however, correlated with the fixed site NO2 levels only in Basel and the ambient levels were lower than any outdoor, indoor or personal EXPOLIS measurements of NO2 in Basel and Prague. Fixed site NO2 monitoring is most useful for following the day-to-day variation in concentration and longer-term trends. They may, however, be less valuable for assessing spatial NO2 variation (Kousa et al., 2001), which is relevant for
assessing the differences in personal exposures of individuals. Although the individual perceived air pollution annoyance scores at home, at work or in traffic did not correlate with the corresponding individual EXPOLIS concentrations of PM2.5 and NO2, the population level average values appeared to be useful in exposure–annoyance assessments. In the Swiss study (Oglesby et al., 2000a) the correlation between population level perceived annoyance based on ambient air and fixed site annual average NO2 level was higher among those who lived close to the fixed monitoring site (r ¼ 0:93) than for all participants (r ¼ 0:88) in eight Swiss cities. Population level correlations between the averages of perceived annoyance (daily or almost daily) and 6-month average fixed site NO2 levels ranged from r ¼ 0:52 (smelly outdoor air in the residential area) to r ¼ 0:66 (irritating outdoor air in the town centre) in 55 Swedish cities (Forsberg et al., 1997). Evans et al. (1988) noted modest but significant relationships between ambient ozone concentrations and anxiety symptoms in a large representative sample of Los Angeles residents. Among the EXPOLIS measurements the mean annoyance at work correlated highly with both the average work indoor PM2.5 level (r ¼ 0:86) and the personal work time PM2.5 exposure (r ¼ 0:89). Generalisation of the high correlation between air pollution annoyance and NO2 exposure in the EXPOLIS study should be done with caution only due to the small number of observations (number of cities=4). Both PM2.5 and NO2 levels increased the air pollution annoyance level in traffic. When other determinants were included in the model, variable ‘city’—which contains different air pollution levels—removes a lot pollution related variance and therefore the association with these air pollutants and perceived annoyance was no more significant. Besides from the different pollution levels, the variable ‘city’ indicated an additional community related factor of perceived annoyance. Yet, the measured outdoor PM2.5 and NO2 concentrations explained only a small fraction of the perceived traffic pollution annoyance variation in the studied cities. ‘Dirty and sooty’ air has been shown to annoy people more easily than ‘smelly’ or ‘irritating’ air (Forsberg et al., 1997). Yet, black smoke or SO2 did not correlate with population level annoyance scores, but NO2 did (Forsberg et al., 1997). In the present study residential outdoor NO2 contributed stronger to annoyance and explained more of air pollution annoyance variation in traffic than residential outdoor PM2.5. NO2 levels are probably associated with traffic volume and perceivable traffic (i.e. number of cars) may be crucial for annoyance scores. The higher the road traffic noise levels people are exposed to, the more likely they are to be annoyed by exhaust smell at a specific air pollution level (Klaeboe et al., 2000). Air quality is a complex mixture of air
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
4601
Table 4 Coefficients of linear (annoyance scale score) and logistic (high levels >7 of annoyance versus p7 of annoyance) regression models of traffic pollution annoyance in association with PM2.5 (n ¼ 296) and NO2 (n ¼ 238) concentrations and main annoyance determinants in the EXPOLIS cities Annoyance scale score
Highly annoyed >7
B
95% CI
OR
95% CI
2
Crude estimate Intercept PM2.5 level at home outdoors (per 10 mg m3)1,2,3,4,6 Multivariate model Intercept PM2.5 level at home outdoors (per 10 mg m3)1,2,3,4,6 Female City (Helsinki) Athens Basel Milan Prague Downtown living
(R ¼ 0:04) 3.74 0.32nn (R2 ¼ 0:14) 3.11 0.01 0.55
(3.29; 4.20) (0.14; 0.50)
1.16n
(1.00; 1.35)
(2.54; 3.68) (0.23; 0.22) (0.05; 1.15)
1.04 1.09
(0.84; 1.28) (0.58; 2.08)
1.50nn 1.47nn 2.52nn 2.38nn 0.62
(0.43; 2.57) (0.58; 2.35) (1.10; 3.94) (0.95; 3.81) (0.16; 1.41)
2.47 3.93nn 1.58 6.05nn 1.77
(0.84; (1.68; (0.35; (1.77; (0.81;
Crude estimate Intercept NO2 level at home outdoors (per 10 mg m3)1,3,6 Multivariate model Intercept NO2 level at home outdoors (per 10 mg m3)1,3,6 Female City (Helsinki) Basel Prague Downtown living
(R2 ¼ 0:13) 2.44 0.55nn (R2 ¼ 0:19) 2.37 0.25 0.66
(1.77; 3.12) (0.37; 0.74)
1.36nn
(1.15; 1.62)
(1.56; 3.16) (0.00; 0.50) (0.01; 1.32)
1.08 1.43
(0.85; 1.36) (0.69; 2.95)
1.21nn 1.50n 0.72
(0.33; 2.10) (0.07; 2.92) (1.15; 1.58)
3.50nn 2.97 2.41n
(1.49; 8.23) (0.83; 10.56) (1.06; 5.51)
7.28) 9.21) 7.09) 20.65) 3.86)
n
po0:05: po0:001: Note: 1Helsinki, 2Athens, 3Basel, 4Milan, 5Oxford, 6Prague. nn
pollutants and therefore difficult to compare to levels of one pollutant at a time. The psychological effects of air pollution may often be of greater importance to well-being than the biophysical effects, since it seems that people often worry far more about air pollution than is defensible from a medical point of view. Moreover, it is argued that since psychological research reveals more and more results that indicate clinically relevant effects of psychological processes on somatic functioning and health-related behaviour, air pollution may affect human somatic functioning both by psychological and somatic means (Meertens and Swaen, 1997). Besides, health effects of perceived annoyance from air pollution are so far unknown. Now the air pollution annoyance scores have been compared to the levels of a few specific pollutants only. The air pollutants, which may cause most of the annoyance, however, maybe other than those measured, and the annoyance is most likely an aggregate effect of many different pollutants. Therefore further research of air pollution annoyance levels, determinants and also
associations with different air pollution components is needed.
5. Conclusions *
*
*
*
There was a large variation in the levels of air pollution annoyance between the six studied cities. The highest annoyance levels were experienced while in traffic. The significant determinants of air pollution annoyance were the city, self-reported sensitivity to air pollution and respiratory symptoms, downtown residence and gender of the subject. No consistent or significant correlations were seen between the individual levels of annoyance and exposure concentrations to either PM2.5 or NO2. High air pollution annoyance in traffic, however, was significantly associated with home outdoor concentrations of both PM2.5 and NO2 and downtown living (NO2-model).
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T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
When average annoyance levels and concentrations were averaged for each city, the perceived annoyance levels at home correlated highly with the measured personal 48-h PM2.5 and NO2 exposures and home indoor NO2 concentration, annoyance at work correlated with personal workday exposure and workplace PM2.5 concentrations, and annoyance in traffic with home outdoor NO2 concentration.
Acknowledgements This work has been supported by EU (Contracts: ENV4-CT96-0202 (DG12–DTEE) and ERBIC20CT960061), Academy of Finland (Contracts: N36586 and N42610), Swiss Ministry for Education and Science (Contract BBW 95.0894) and intramural funding by KTL-National Public Health Institute of Finland.
References Committee of Environmental and Occupational Health Assembly of the American Thoracic Society, 1996. Health effects of outdoor air pollution. American Journal of Respiratory and Critical Care Medicine 153, 3–50. Council of the European Union, 1999. Directive (399L0030) 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air. http://europa.eu.int/eur-lex/en/lif/reg/en register 15102030.html Danuser, B., 2001. Candidate physiological measures of annoyance from airborne chemicals. Chemical Senses 26 (3), 333–337. Evans, G.W., Colome, D.S., Shearer, F., 1988. Psychological reactions to air pollution. Environmental Research 45, 1–15. Forsberg, B., Stjernberg, N., Wall, S., 1997. People can detect poor air quality well below guideline concentrations: a prevalence study of annoyance reactions and air pollution from traffic. Occupational and Environmental Medicine 54 (1), 44–48. H.anninen, O., Koistinen, K., Kousa, A., Keski-Karhu, J., Jantunen, M., 2001. Quantitative analysis of environmental factors in differential weighing of blank Teflon filters. Journal of Air and Waste Management Association 52, 134–139. ISO 7996, 1985. Amibient Air—Determination of the Mass Concentration of Nitrogen Oxides—Chemiluminescence Method, 1st Edition, pp. 12–15. . Jantunen, M.J., H.anninen, O., Katsouyanni, K., Knoppel, H., Kunzli, . N., Lebret, E., Maroni, M., Saarela, K., Sr!am, R., Zmirou, D., 1998. Air pollution exposure in European cities: the ‘‘EXPOLIS’’ study. Journal of Exposure Analysis and Environmental Epidemiology 8 (4), 495–518. Klaeboe, R., Kolbenstvedt, M., Clench-Aas, J., Bartonova, A., 2000. Oslo traffic study—part 1: an integrated approach
to assess the combined effects of noise and air pollution on annoyance. Atmospheric Environment 34 (27), 4727–4736. Koistinen, K., Kousa, A., Tenhola, V., H.anninen, O., Jantunen, M., Oglesby, L., Kunzli, . N., Georgoulis, L., 1999. Fine particle (PM2.5) measurement methodology, quality assurance procedures and pilot results of the ‘‘EXPOLIS’’ study. Journal of Air and Waste Management Association 49, 1212–1220. Kousa, A., Monn, C., Rotko, T., Alm, S., Oglesby, L., Jantunen, M., 2001. Personal exposures to NO2 in the EXPOLIS-study: relation to residential indoor, outdoor and workplace concentrations in Basel, Helsinki and Prague. Atmospheric Environment 35 (20), 3405–3412. Lercher, P., Kofler, W.W., 1996. Behavioral and health responses associated with road traffic noise exposure along alpine through-traffic routes. Science of the Total Environment 190, 85–89. Lercher, P., Schmitzberger, R., Kofler, W., 1995. Perceived traffic air pollution, associated behavior and health in an alpine area. Science of the Total Environment 169 (1–3), 71–74. Meertens, R., Swaen, G., 1997. Psychological factors in air pollution epidemiology. In: Jantunen, M.J., Viegi, G., Nolan, C. (Eds.), Socioeconomic and Cultural Factors in Air Pollution Epidemiology. EC Air Pollution Epidemiology Report Series 8, pp. 105–112. Miedema, H.M.E., Vos, H., 1998. Exposure–response relationships for transportation noise. Journal of the Acoustical Society of America 104 (6), 3432–3445. Miedema, H.M.E., Walpot, J.I., Vos, H., Steunenberg, C.F., 2000. Exposure–annoyance relationships for odour from industrial sources. Atmospheric Environment 34 (18), 2927–2936. Oglesby, L., Kunzli, . N., Monn, C., Schindler, C., AckermannLiebrich, U., Leuenberger, P., the SAPALDIA Team, 2000a. Validity of annoyance scores for estimation of long-term air pollution exposure in epidemiological studies. American Journal of Epidemiology 152 (1), 75–83. . Oglesby, L., Rotko, T., Krutli, P., Boudet, C., Kruize, H., Jantunen, M.J., Kunzli, . N., 2000b. Personal exposure assessment studies may suffer from exposure relevant selection bias. Journal of Exposure Analysis and Environmental Epidemiology 10 (3), 251–266. Rotko, T., Oglesby, L., Kunzli, . N., Jantunen, M.J., 2000. Population sampling in European air pollution exposure study, EXPOLIS: comparisons between the cities and representativity of the samples. Journal of Exposure Analysis and Environmental Epidemiology 10 (4), 355–364. Rotko, T., Kousa, A., Alm, S., Jantunen, M., 2001. Exposures to nitrogen dioxide (NO2) in EXPOLIS-Helsinki: microenvironment, behavioral and sociodemographic factors. Journal of Exposure Analysis and Environmental Epidemiology 11 (3), 216–223. USEPA, 1997. National Ambient Air Quality Standards (NAAQS). US Environmental Protection Agency. http:// www.epa.gov/airs/criteria.html
Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM2.5, NO2) concentrations in the European EXPOLIS study b Tuulia Rotkoa,*, Lucy Oglesbyb, Nino Kunzli . , Paolo Carrerc, Mark J. Nieuwenhuijsend, Matti Jantunena a
Department of Environmental Health, KTL-National Public Health Institute, P.O. Box 95, FIN-70701 Kuopio, Finland b Institute of Social and Preventive Medicine, University of Basel, Steinengraben 49, CH-4051 Basel, Switzerland c Institute of Occupational Health, University of Milan, Via San Barnaba 8, IT-20122 Milan, Italy d Department of Environmental Science and Technology, Imperial College of Science, Technology and Medicine, London SW7 2BP, UK Received 11 February 2002; received in revised form 24 June 2002; accepted 28 June 2002
Abstract Apart from its traditionally considered objective impacts on health, air pollution can also have perceived effects, such as annoyance. The psychological effects of air pollution may often be more important to well-being than the biophysical effects. Health effects of perceived annoyance from air pollution are so far unknown. More knowledge of air pollution annoyance levels, determinants and also associations with different air pollution components is needed. In the European air pollution exposure study, EXPOLIS, the air pollution annoyance as perceived at home, workplace and in traffic were surveyed among other study objectives. Overall 1736 randomly drawn 25–55-yr-old subjects participated in six cities (Athens, Basel, Milan, Oxford, Prague and Helsinki). Levels and predictors of individual perceived annoyances from air pollution were assessed. Instead of the usual air pollution concentrations at fixed monitoring sites, this paper compares the measured microenvironment concentrations and personal exposures of PM2.5 and NO2 to the perceived annoyance levels. A considerable proportion of the adults surveyed was annoyed by air pollution. Female gender, self-reported respiratory symptoms, downtown living and self-reported sensitivity to air pollution were directly associated with high air pollution annoyance score while in traffic, but smoking status, age or education level were not significantly associated. Population level annoyance averages correlated with the city average exposure levels of PM2.5 and NO2. A high correlation was observed between the personal 48-h PM2.5 exposure and perceived annoyance at home as well as between the mean annoyance at work and both the average work indoor PM2.5 and the personal work time PM2.5 exposure. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM2.5) and 19% (NO2) of the variation in perceived air pollution annoyance in traffic. Compared to Helsinki, in Basel and Prague the adult participants were more annoyed by air pollution while in traffic even after taking the current home outdoor PM2.5 and NO2 levels into account. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Exposure; Fine particles; Nitrogen dioxide; Road traffic; Workplace
1. Introduction *Corresponding author. Department of Sociology, University of Helsinki, P.O Box 35, FIN-00014 Helsinki, Finland. Tel.: +358-9-19124700; fax: +358-9-191-24750. E-mail address: tuulia.rotko@helsinki.fi (T. Rotko).
Apart from its objective impacts on health (Committee of Environmental and Occupational Health Assembly of the American Thoracic Society, 1996), air
1352-2310/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 2 - 2 3 1 0 ( 0 2 ) 0 0 4 6 5 - X
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pollution can also have perceived effects, such as annoyance, even at low concentrations. In addition to studies on perceived annoyance in association with psychosomatic symptoms and respiratory illnesses (Lercher et al., 1995) and startle reflex and breathing changes (Danuser, 2001), several studies have quantified the relations between the annoyance from environmental factors and the measured levels of these factors. Annoyance from environmental noise, odour and air pollution have been compared to levels of environmental noise (Klaeboe et al., 2000; Miedema and Vos, 1998; Lercher and Kofler, 1996), odours (Danuser, 2001; Miedema et al., 2000) and air pollution (Klaeboe et al., 2000; Oglesby et al., 2000a; Forsberg et al., 1997; Lercher et al., 1995; Evans et al., 1988). Oglesby et al. (2000a, b) investigated the validity of air pollution annoyance as an indirect and simplistic but inexpensive exposure assessment tool in air pollution epidemiology. Klaeboe et al. (2000) adopted an integrated approach to study the simultaneous effects of exposure, traffic noise and air pollution annoyance from traffic. Evans et al. (1988) investigated psychological reactions to air pollution and found that a large representative sample of Los Angeles residents were somewhat aware and concerned about air pollution, but not knowledgeable about its causes and that there were modest but significant relationships between ambient photochemical oxidants and anxiety symptoms. Meertens and Swaen (1997) suggested that the psychological effects of air pollution might often be of greater importance to well-being than the biophysical effects. Population level perceived air pollution annoyance has so far been compared mostly to ambient long-term (6-month, 1-yr averages) air pollution levels measured at fixed monitoring sites (Oglesby et al., 2000a; Forsberg et al., 1997; Lercher et al., 1995). Exposure indicators for air pollution have been produced for each respondent also by comprehensive environmental modelling (Klaeboe et al., 2000). More recent approaches, such as microenvironment and personal monitoring, give more accurate information of individual level short-term exposures to the selected pollutants. Oglesby et al. (2000a) performed individual level analysis of exposure– annoyance relationship based on residential outdoor NO2 measurements. However, annoyance also depends on individual characteristics, such as sensitivity, health status, and attitude towards traffic, tobacco smoke or other sources of air pollution. EXPOLIS (Air Pollution Exposure Distributions within Adult Urban Populations in Europe) is a European multi-city air pollution exposure study. Within the framework of the EXPOLIS study each participant reported the annoyance caused by air pollution after the 48-h participation period. Concurrently personal exposures and microenvironment concentrations of PM2.5 and NO2 were measured. Although the air
pollution annoyances have been compared to the levels of a few specific pollutants, it is important to keep in mind that the air pollutants which may cause most of the annoyance maybe other than those measured, and that the annoyance is most likely an aggregate effect of many different pollutants. In addition to the individual level analysis of the annoyance–exposure relationship, the average of the short-term EXPOLIS measurements, collected by randomly selected participants throughout 1 yr, yields an estimate of the long-term population value for each city. In former studies, population mean annoyance scores and exposure concentrations have been compared between cities within one country (Oglesby et al., 2000a; Forsberg et al., 1997). In the EXPOLIS study respective comparisons are made between six cities in six European countries. The next section briefly describes the EXPOLIS study design including population sampling, annoyance and air pollution measurements with the used methods. The objectives of this work are: *
*
to assess and compare the levels and determinants of air pollution annoyance among the adult populations of six European cities and to determine the correlation between the perceived air pollution annoyance and the measured fine particle (PM2.5) and nitrogen dioxide (NO2) exposures and microenvironment concentrations. PM2.5 represents the most hazardous air pollutant and NO2 is often used as a marker of ambient air pollution originating from combustion, especially traffic.
2. Material and methods The EXPOLIS study consisted of two randomly drawn population samples, the Exposure and Diary samples, of adults (25–55 yr) in each participating city (Athens, Greece; Basel, Switzerland; Helsinki, Finland; Milan, Italy; Oxford, United Kingdom and Prague, Czech Republic). A detailed description of the EXPOLIS study design, sampling, data and QA/QC is presented in Jantunen et al. (1998). The Exposure sample filled in questionnaires and time-activity-diaries with personal exposure monitoring and microenvironment measurements of PM2.5 and NO2. The Diary sample filled in the same questionnaires and time-activitydiaries without air pollution monitoring. Both the Exposure and Diary samples had somewhat more women and more educated adults compared to the general same-age population in these cities. These population samples are described and the representativity of them is evaluated in detail in Rotko et al. (2000) and Oglesby et al. (2000b). In addition, in Helsinki another Environment Attitude Questionnaire sample
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
(Heaq) participated by filling in the questionnaire 1 yr later without personal monitoring. The participants of EXPOLIS reported the perceived annoyance from air pollution at home, at work and in traffic on the annoyance scale which ranged from 0 (no annoyance at all) to 10 (unbearable annoyance) (the same as in Oglesby et al., 2000a). After the measurement period the participants were asked ‘‘To what degree did you feel annoyed about air pollution at home/at workplace/in traffic during the last 48-h?’’ (three different questions). Determinants of the perceived annoyances were searched from the EXPOLIS questionnaire data. In addition to the basic background questions (gender, age, education) the following questions were used: current smoking status, self-reported allergic symptoms (wheezing, nasal allergies, asthma), self-reported sensitivity to air pollution, having small children and home location (downtown/suburban). The fixed site monitoring data was received from each city’s urban air quality monitoring network and data of one urban background monitoring station was used from each city. Ambient fixed site PM2.5 concentrations were measured with high volume monitoring (Eberline or Digitel) (available from Helsinki and Basel only) and ambient air NO2 concentrations were monitored by the standard chemiluminesence method (ISO 7996, 1985). PM2.5 results are available from the Exposure samples in six EXPOLIS cities (Athens (A), Basel (B), Milan (M), Oxford (O), Prague (P), and Helsinki (H)). Personal PM2.5 exposures were collected on two different filters: one for the working hours including commuting (personal work) and the other for the remaining hours of 48-h measurement period (personal leisure time). In addition to personal exposure monitoring, PM2.5 concentrations were measured in each home (indoors and outdoors) and workplace (indoors). The PM2.5 concentration measured at work was the average of two consecutive workdays and at home of the remaining hours of the 48-h monitoring period. PM2.5 personal cyclones were used as pre-separators at flow rate of 4 l min1 and the EPA-WINS impactors were employed at 16.7 l min1 for the microenvironment measurements with Gelman Teflo filters (37- and 47-mm, respectively). Detailed methods and quality assurance results for the PM2.5 measurements in EXPOLIS are presented by Koistinen et al. (1999) and H.anninen et al. (2001). In the EXPOLIS study personal and microenvironment NO2 samples were collected from Helsinki, Basel, Oxford and Prague. The reported NO2 concentrations are 48-h averages collected by Palmes passive samplers. More detailed descriptions of the EXPOLIS NO2 measurements and results are presented in Rotko et al. (2001) and Kousa et al. (2001). The Exposure, Diary and Heaq samples are combined in the analyses of the annoyance levels and determi-
4595
nants. A time-weighted total mean annoyance was computed by weighting each of the three average annoyance scores (residential, workplace, traffic) by the average time used in each of these microenvironments. Analysis of the associations between perceived annoyance caused by air pollution and concurrently measured air pollution exposure levels to PM2.5 and NO2 include only the Exposure sample. All statistical tests were carried with a SPSS statistical package (SPSS Inc. 1998, version 9.0).
3. Results 3.1. Levels and determinants of perceived air pollution annoyance Air pollution in traffic annoyed the most. The average perceived annoyance scores in traffic ranged from 3.6 in Helsinki to 7.1 in Prague (Table 1). The average annoyance levels at the workplaces (from 1.8 in Oxford to 3.9 in Athens) were higher than at home (from 1.4 in Oxford to 2.0 in Milan), except in Prague (3.3 and 4.3, respectively). In Helsinki 15–22% and in Prague 62% of the participants were highly annoyed (annoyance score X7) by air pollution in traffic. At workplaces the share of highly annoyed ranged from 4% in Oxford to 22% in Athens and respectively at home from 3% in Basel to 25% in Prague. At home 8–53% of participants were not at all annoyed by air pollution, but in traffic only 1– 15%. A time-weighted total mean annoyance ranged between 2.1 in Helsinki and 3.9 in Prague. In the first univariate logistic regression analysis each possible determinant was evaluated one at a time, and a dichotomised annoyance (annoyance scores >7 versus p7) rating of traffic annoyance was used as the outcome measure. Significant individual determinants were the city, gender, self-reported allergic symptoms, selfreported sensitivity to air pollution, and home location. Women, Athens, Basel, Milan and Prague inhabitants (compared to Helsinki), those reporting respiratory symptoms, those reporting to be sensitive to air pollution and those living in downtown area were on average more annoyed about air pollution than the remaining population groups (Table 2). Age, education level, current smoking status or having children were not significant determinants of air pollution annoyance in traffic. In a second multivariate logistic regression model (the determinants were added into the model at the same time), excluding respiratory symptoms and self-reported sensitivity to air pollution, the effect of gender and city remained almost the same and the impact of downtown living decreased somewhat. When respiratory symptoms and self-reported sensitivity to air pollution were included in the adjusted model, Athens and Basel dropped out and the other values changed also. The
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T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
Table 1 Average levels of perceived air pollution annoyance in the EXPOLIS cities
Residential Home annoyance mean Home annoyance SD Proportion (%) Not annoyed (0) Slightly annoyed (1–2) Moderately annoyed (3–6) Highly annoyed (7–10) Workplace Work annoyance mean Work annoyance SD Proportion (%) Not annoyed (0) Slightly annoyed (1–2) Moderately annoyed (3–6) Highly annoyed (7–10) In traffic Mean annoyance in traffic Traffic annoyance SD Proportion (%) Not annoyed (0) Slightly annoyed (1–2) Moderately annoyed (3–6) Highly annoyed (7–10) Time-weighted mean total annoyance
Helsinki
Heaq
Athens
Basel
Milan
Oxford
Prague
n ¼ 428 1.73 2.18
n ¼ 421 1.94 2.30
n ¼ 100 1.87 2.31
n ¼ 330 1.98 2.00
n ¼ 299 2.03 2.18
n ¼ 55 1.44 2.23
n ¼ 83 4.30 2.83
40.4 33.9 19.4 6.3
36.6 34.2 22.1 7.1
42.0 27.0 24.0 7.0
34.8 30.9 31.5 2.7
38.1 25.4 32.4 4.0
52.7 27.3 14.5 5.5
8.4 22.9 43.4 25.3
n ¼ 384 2.60 2.58
n ¼ 361 3.26 2.85
n ¼ 72 3.85 2.81
n ¼ 273 2.64 2.39
n ¼ 274 3.80 2.74
n ¼ 46 1.78 2.35
n ¼ 72 3.29 2.86
30.5 26.3 33.3 9.9
24.4 22.4 35.2 18.0
19.4 16.7 41.7 22.2
28.2 23.8 41.0 7.0
20.1 13.1 48.5 18.2
50.0 17.4 28.3 4.3
25.0 20.8 38.9 15.3
n ¼ 425 3.58 2.50
n ¼ 422 3.90 2.84
n ¼ 92 4.93 3.08
n ¼ 327 5.01 2.63
n ¼ 299 5.94 2.65
na na
n ¼ 84 7.08 2.41
14.6 20.9 49.6 14.8
13.7 22.7 41.5 22.0
14.1 8.7 43.5 33.7
7.0 11.0 51.4 30.6
4.7 7.0 41.1 47.2
na na na
1.2 3.6 33.3 61.9
2.14
na
2.54
2.45
2.91
na
3.94
na=not available, Heaq=Helsinki Environmental Attitude Questionnaire sample (7 December 1998–5 June 1999).
effect of respiratory symptoms and self-reported sensitivity to air pollution (and also female gender) on high traffic annoyance decreased somewhat compared to the unadjusted model. 3.2. Air pollution concentration levels Fixed site 24-h mean PM2.5 values from the whole EXPOLIS study period were 9 mg m3 in Helsinki and 22 mg m3 in Basel (Table 3). The mean ambient NO2 for the whole study period ranged from 27 mg m3 in Helsinki to 97 mg m3 in Athens. The NO2 means for the actual measurement periods and the time-activity diary filling periods (no weekends) were usually somewhat higher than means over the whole study period. Among the EXPOLIS PM2.5 measurements the workplace indoor concentrations were usually the highest (from 16 mg m3 in Helsinki to 90 mg m3 in Athens), except in Oxford and Basel, followed by personal exposure and home indoor levels (Table 3). Home outdoor PM2.5 concentrations (from 10 mg m3 in Helsinki to 41 mg m3 in Milan) were the lowest. The average residential outdoor PM2.5 concentrations measured in EXPOLIS were almost the same as the fixed site levels in
Helsinki and Basel and the Pearson correlation between the values was high; r ¼ 0:84 in Helsinki and r ¼ 0:96 in Basel. The fixed site NO2 averages were higher in Helsinki but lower in Basel and Prague than the residential outdoor EXPOLIS levels. Pearson correlation between the fixed site NO2 and the residential outdoor EXPOLIS measurements was r ¼ 0:45 in Helsinki, r ¼ 0:84 in Basel and r ¼ 0:36 in Prague. The residential outdoor levels of NO2 in Basel (36 mg m3) and Prague (61 mg m3) and work indoor levels in Helsinki (27 mg m3) and Oxford (31 mg m3) were the highest among the measured exposures and microenvironments in these cities. 3.3. Correlation between perceived air pollution annoyance and measured PM2.5 and NO2 concentrations The perceived annoyance variation was large and the individual annoyance scores at home, at work or in traffic did not correlate with the corresponding EXPOLIS measurements in any of the EXPOLIS cities. The Pearson correlation coefficients between individual annoyance scores and the measured PM2.5 and NO2 exposures and concentrations (annoyance at home versus personal exposures and residential indoor
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
4597
Table 2 Determinants of perceived air pollution annoyance in traffic: unadjusteda and adjustedb odds ratios and 95% confidence intervals of the highly annoyed (>7 versus p7 at annoyance scale, n ¼ 336)
City (Helsinki) Athens Basel Milan Prague Female Age (25–34 yr) 35–44 yr 45–55 yr Education X14 yr Current smoker Respiratory symptoms Sensitive to air pollution Having children Downtown living
N
% of highly annoyed
847 92 327 299 84 914 505 534 603 981 406 401 294 669 505
11 26 24 32 54 24 22 20 19 20 20 31c 32e 19 30
OR Unadjusteda
95% CI (n ¼ 1649)
OR Adjustedb
95% CI (n ¼ 1586)
2.86nn 2.58nn 3.78nn 9.35nn 1.61nn
(1.71; (1.85; (2.73; (5.79; (1.25;
4.78) 3.60) 5.23) 15.12) 2.06)
2.90nn 2.60nn 3.74nn 8.15nn 1.65nn
(1.70; (1.84; (2.65; (4.83; (1.27;
0.88 0.85 0.92 0.92 1.95nn 2.50nn 0.83 2.14nn
(0.65; (0.63; (0.72; (0.69; (1.46; (1.86; (0.65; (1.67;
1.19) 1.13) 1.18) 1.22) 2.60) 3.37) 1.07) 2.74)
0.96 1.04 0.98 0.97 1.82d 1.63d 0.96 1.39n
(0.69; 1.34) (0.75; 1.43) (0.75; 1.28) (0.71; 1.31) (1.21; 2.74) (1.03; 2.57) (0.73; 1.28) (1.04; 1.84)
nn n
4.93) 3.68) 5.29) 13.75) 2.15)
a
Unadjusted=each variable at a time. Adjusted=with the other determinants. c Symptoms not asked in Athens. d If included in the adjusted model Athens and Basel will drop out of it, and other values would change also. e Sensitivity not asked in Basel and Oxford. n po0:05: nn po0:001: b
concentrations, annoyance at work versus personal working time exposure and work indoor concentrations as well as annoyance in traffic versus residential outdoor concentrations) ranged between 0:19oro0:36 and no correlation was significant. As an example individual perceived air pollution annoyance at work versus PM2.5 levels at work indoors for EXPOLIS cities is presented in Fig. 1. In contrast, at population level the mean annoyance scores and mean PM2.5 and NO2 concentrations of the EXPOLIS measurements across cities did correlate and some of these correlations were high. However, the correlations were not significant due to the small number of observations (cities). The mean annoyance at home did not correlate with the average home indoor PM2.5 or the personal leisure time PM2.5 exposure, but the correlation was higher between the annoyance at home and personal 48-h PM2.5 exposure (Fig. 2). The mean annoyance in traffic correlated weakly with the average home outdoor PM2.5. The mean annoyance at work correlated strongly with both the average work indoor PM2.5 and the personal work time PM2.5 exposure. The correlations between the mean annoyance scores at home and the mean NO2 exposure and residential indoor NO2 concentration were high. Likewise, the correlation between the mean annoyance in traffic and the residential outdoor concentration (with small number of observations) was also high (Fig. 3).
3.4. Regression models of perceived air pollution annoyance in traffic Crude estimates of the linear regression models showed that 10 mg m3 change in the NO2 home outdoor level increased annoyance level in traffic more than the same change in the PM2.5 home outdoor level, and both were significant (Table 4). However, home outdoor levels explained only 4% (PM2.5) and 13% (NO2) of the variation in individual perceived air pollution annoyance scores in traffic. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM2.5) and 19% (NO2) of the variation in perceived air pollution annoyance in traffic. In the multivariate models, however, home outdoor PM2.5 and NO2 levels no longer significantly affected the perceived annoyances. Even after adjusting for the different PM2.5 outdoor concentrations in the EXPOLIS cities, the participants scored 1.5 points higher in Athens and Basel and 2.5 points higher in Milan and Prague on the air pollution annoyance scale while in traffic compared to Helsinki. After adjusting for the level of outdoor NO2 concentration in the different EXPOLIS cities participants in Basel scored 1.2 points higher and in Prague 1.5 points higher on the perceived annoyance scale compared to Helsinki. Similar results were obtained with multivariate logistic regression models using
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
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Table 3 Levels of air pollution (mg m3) in fixed site stations during measurement periods in EXPOLIS cities and mean values of EXPOLIS PM2.5 and NO2 measurements (mg m3)
PM2.5 Fixed site Mean1a Rangeb Mean2c EXPOLIS N Personal 48-hd Home, indoor Home, out Work, indoor NO2 Fixed site Mean1a Rangeb Mean2c EXPOLIS N Personal 48-hd Home, indoor Home, out Work, indoor
Helsinki1
Athens2
Basel3
Milan4
Oxford5
Prague6
9.1 (1.1–32.3) 9.9
— — —
21.4 (4.0–96.8) 21.9
— — —
— — —
— — —
201 15.1 12.1 9.7 15.9
50 28.6 35.5 36.6 90.3
50 27.8 20.8 19.4 26.7
50 na 42.7 41.3 59.0
60 16.5 17.0 10.6 11.8
50 35.2 35.9 26.9 42.9
26.6 (4.7–71.6) 30.2
97.0 (35.5–190.3) 94.6
28.9 (6.5–65.0) 29.3
82.9 (25.8–196.0) 84.1
na na na
39.0 (13.1–84.3) 42.2
176 25.0 17.7 23.9 27.0
— — — — —
50 33.2 30.1 36.2 35.0
— — — — —
60 28.3 25.4 24.5 31.1
50 44.4 43.1 60.5 30.7
Measurement periods: 1Helsinki (26 September 1996–10 December 1997); 2Athens (26 January 1997–4 June 1998); 3Basel (3 February 1997–23 January 1998); 4Milan (10 March 1997–23 May 1998); 5Oxford (4 November 1998–7 October 1999); 6Prague (3 June 1997–4 June 1998). —not measured, na=not available. a Fixed mean over the whole study period. b Range of 24-h means. c Fixed mean from the EXPOLIS 48-h measurement periods. d Personal 48-h exposure.
4. Discussion
Annoyance at work
R 2 = 0.06
10 9 8 7 6 5 4 3 2 1 0 0
50 100 150 200 250 Work indoor PM2.5 concentration (µg m-3)
300
Fig. 1. Individual perceived work annoyance scale scores versus PM2.5 levels at work indoors in the EXPOLIS cities (Helsinki, Basel, Athens, Milan and Prague).
high annoyance (annoyance scores >7) rating of air pollution annoyance in traffic as the outcome measure (Table 4).
Although the PM2.5 and NO2 levels were usually below the guidelines in the EXPOLIS cities, a considerable proportion of the adults surveyed was annoyed by air pollution. On average 29% of respondents in the EXPOLIS cities were highly annoyed (X7 at annoyance scale) by air pollution in traffic and 14% at workplace. Because women were over-represented among the respondents of the EXPOLIS study (Rotko et al., 2000) and women seem to be more annoyed by air pollution than men, probably somewhat higher annoyance levels were reached compared to other same age city populations. In Switzerland where annoyance was measured with a similar method, the average proportion of those highly annoyed (>7 at annoyance scale) by ambient air pollution was 18% in eight Swiss cities (Oglesby et al., 2000a). In Sweden (Forsberg et al., 1997) the proportion of adults that were daily or almost daily annoyed by air pollution varied from 5% to 17% in the selected 55 urban areas. In Austria 40% of the
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602 8.0
R 2 = 0.63
3.5
P Annoyance in traffic
Annoyance at home
4.0
3.0 2.5 B A
2.0 O
1.5
H
1.0 0.5 0
10
20
30
Personal 48h PM2.5 (µg
P
6.0
M B
5.0 4.0
A
H
3.0 2.0 1.0 0
40
A
3.0 H B
2.0 O
1.5
30
40
R2 = 0.15
3.5 Annoyance at home
P
2.5
20
50
4.0
R 2 = 0.79
3.5
10
Home outdoor PM2.5 (µg m-3)
m-3)
4.0 Annoyance at work
R 2 = 0.32
7.0
0.0
0.0
1.0 0.5 0.0
P
3.0 2.5 2.0
B
H
1.5
A O
1.0 0.5 0.0
0
20
40
60
80
0
Personal work time PM2.5 (µg m-3)
10
20
30
Personal leisure time PM2.5 (µg
40 m-3)
4.0 R 2 = 0.74
3.5
A
M P
3.0 H
2.5
B
2.0 O
1.5 1.0 0.5 0.0
R 2 = 0.23
3.5 Annoyance at home
4.0 Annoyance at work
4599
P
3.0 2.5 B
2.0
M
H
1.5
A
O
1.0 0.5 0.0
0
20
40
60
80
100
Work indoor PM2.5 (µg m-3)
0
10
20
30
40
50
Home indoor PM2.5 (µg m-3)
Fig. 2. Associations between mean air pollution annoyance scores and average personal (48-h, work and leisure time) and microenvironment PM2.5 levels in the EXPOLIS cities (H=Helsinki, A=Athens, B=Basel, M=Milan, O=Oxford, P=Prague).
respondents were annoyed by car fumes and 27% by visible dust/soot (Lercher et al., 1995). Like in the previous studies, female gender (Oglesby et al., 2000a, Klaeboe et al., 2000; Forsberg et al., 1997), self-reported respiratory symptoms (Oglesby et al., 2000a; Forsberg et al., 1997) and downtown living indicating high traffic volume near home (Forsberg et al., 1997) were shown to be determinants of perceived air pollution annoyance. In addition, self-reported sensitivity to air pollution, as well as sensitivity to noise and odours (Lercher et al., 1995), increased the probability of being highly annoyed. In some earlier studies also current smoking status (Oglesby et al., 2000a; Lercher
et al., 1995), older age and low education level (Klaeboe et al., 2000) were found to be determinants of perceived annoyance by air pollution. However, in the present study current smoking status (as in Forsberg et al., 1997), older age within the age range of 25–55 yr (as in Oglesby et al., 2000a) or low education level were not significant determinants of perceived air pollution annoyance. There is no EU standard for PM2.5, but the USNAAQS (USEPA, 1997) for annual average ambient PM2.5 is 15 mg m3. The average PM2.5 levels—for fixed site and EXPOLIS outdoor air measurements—were below this US standard in Helsinki and Oxford, but
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
4600
Annoyance at home
4.0 R2 = 0.95
P
3.0 2.0
B
H O
1.0 0.0 0
10
20 30 40 Personal 48-hour NO2 (µg m-3)
50
Annoyance at home
4.0
R2 = 0.87
P
3.0 2.0
B
H
O
1.0 0.0 0
10
20
30
40
50
Annoyance in traffic
Home indoor NO2 (µg m-3)
8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0
R 2 = 0.99
P B
H
0
20
40
60
80
Home outdoor NO2 (µg m-3)
Fig. 3. Associations between mean air pollution annoyance scores and average personal (48-h) and microenvironment NO2 levels in the EXPOLIS cities (H=Helsinki, B=Basel, O=Oxford, P=Prague).
above it in Basel, Prague, Athens and Milan. The NO2 levels were below the EU standard for annual average level, 40 mg m3 (Council of the European Union, 1999) in Helsinki, Basel and Oxford, but exceeded the EU standard in Prague, Athens and Milan. In a Swiss study the annual mean NO2 levels in some of the cities exceeded the EU guideline (Oglesby et al., 2000a). In Helsinki and Basel the individual EXPOLIS residential PM2.5 outdoor levels correlated highly with the fixed site PM2.5 values. The residential outdoor NO2 levels, however, correlated with the fixed site NO2 levels only in Basel and the ambient levels were lower than any outdoor, indoor or personal EXPOLIS measurements of NO2 in Basel and Prague. Fixed site NO2 monitoring is most useful for following the day-to-day variation in concentration and longer-term trends. They may, however, be less valuable for assessing spatial NO2 variation (Kousa et al., 2001), which is relevant for
assessing the differences in personal exposures of individuals. Although the individual perceived air pollution annoyance scores at home, at work or in traffic did not correlate with the corresponding individual EXPOLIS concentrations of PM2.5 and NO2, the population level average values appeared to be useful in exposure–annoyance assessments. In the Swiss study (Oglesby et al., 2000a) the correlation between population level perceived annoyance based on ambient air and fixed site annual average NO2 level was higher among those who lived close to the fixed monitoring site (r ¼ 0:93) than for all participants (r ¼ 0:88) in eight Swiss cities. Population level correlations between the averages of perceived annoyance (daily or almost daily) and 6-month average fixed site NO2 levels ranged from r ¼ 0:52 (smelly outdoor air in the residential area) to r ¼ 0:66 (irritating outdoor air in the town centre) in 55 Swedish cities (Forsberg et al., 1997). Evans et al. (1988) noted modest but significant relationships between ambient ozone concentrations and anxiety symptoms in a large representative sample of Los Angeles residents. Among the EXPOLIS measurements the mean annoyance at work correlated highly with both the average work indoor PM2.5 level (r ¼ 0:86) and the personal work time PM2.5 exposure (r ¼ 0:89). Generalisation of the high correlation between air pollution annoyance and NO2 exposure in the EXPOLIS study should be done with caution only due to the small number of observations (number of cities=4). Both PM2.5 and NO2 levels increased the air pollution annoyance level in traffic. When other determinants were included in the model, variable ‘city’—which contains different air pollution levels—removes a lot pollution related variance and therefore the association with these air pollutants and perceived annoyance was no more significant. Besides from the different pollution levels, the variable ‘city’ indicated an additional community related factor of perceived annoyance. Yet, the measured outdoor PM2.5 and NO2 concentrations explained only a small fraction of the perceived traffic pollution annoyance variation in the studied cities. ‘Dirty and sooty’ air has been shown to annoy people more easily than ‘smelly’ or ‘irritating’ air (Forsberg et al., 1997). Yet, black smoke or SO2 did not correlate with population level annoyance scores, but NO2 did (Forsberg et al., 1997). In the present study residential outdoor NO2 contributed stronger to annoyance and explained more of air pollution annoyance variation in traffic than residential outdoor PM2.5. NO2 levels are probably associated with traffic volume and perceivable traffic (i.e. number of cars) may be crucial for annoyance scores. The higher the road traffic noise levels people are exposed to, the more likely they are to be annoyed by exhaust smell at a specific air pollution level (Klaeboe et al., 2000). Air quality is a complex mixture of air
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
4601
Table 4 Coefficients of linear (annoyance scale score) and logistic (high levels >7 of annoyance versus p7 of annoyance) regression models of traffic pollution annoyance in association with PM2.5 (n ¼ 296) and NO2 (n ¼ 238) concentrations and main annoyance determinants in the EXPOLIS cities Annoyance scale score
Highly annoyed >7
B
95% CI
OR
95% CI
2
Crude estimate Intercept PM2.5 level at home outdoors (per 10 mg m3)1,2,3,4,6 Multivariate model Intercept PM2.5 level at home outdoors (per 10 mg m3)1,2,3,4,6 Female City (Helsinki) Athens Basel Milan Prague Downtown living
(R ¼ 0:04) 3.74 0.32nn (R2 ¼ 0:14) 3.11 0.01 0.55
(3.29; 4.20) (0.14; 0.50)
1.16n
(1.00; 1.35)
(2.54; 3.68) (0.23; 0.22) (0.05; 1.15)
1.04 1.09
(0.84; 1.28) (0.58; 2.08)
1.50nn 1.47nn 2.52nn 2.38nn 0.62
(0.43; 2.57) (0.58; 2.35) (1.10; 3.94) (0.95; 3.81) (0.16; 1.41)
2.47 3.93nn 1.58 6.05nn 1.77
(0.84; (1.68; (0.35; (1.77; (0.81;
Crude estimate Intercept NO2 level at home outdoors (per 10 mg m3)1,3,6 Multivariate model Intercept NO2 level at home outdoors (per 10 mg m3)1,3,6 Female City (Helsinki) Basel Prague Downtown living
(R2 ¼ 0:13) 2.44 0.55nn (R2 ¼ 0:19) 2.37 0.25 0.66
(1.77; 3.12) (0.37; 0.74)
1.36nn
(1.15; 1.62)
(1.56; 3.16) (0.00; 0.50) (0.01; 1.32)
1.08 1.43
(0.85; 1.36) (0.69; 2.95)
1.21nn 1.50n 0.72
(0.33; 2.10) (0.07; 2.92) (1.15; 1.58)
3.50nn 2.97 2.41n
(1.49; 8.23) (0.83; 10.56) (1.06; 5.51)
7.28) 9.21) 7.09) 20.65) 3.86)
n
po0:05: po0:001: Note: 1Helsinki, 2Athens, 3Basel, 4Milan, 5Oxford, 6Prague. nn
pollutants and therefore difficult to compare to levels of one pollutant at a time. The psychological effects of air pollution may often be of greater importance to well-being than the biophysical effects, since it seems that people often worry far more about air pollution than is defensible from a medical point of view. Moreover, it is argued that since psychological research reveals more and more results that indicate clinically relevant effects of psychological processes on somatic functioning and health-related behaviour, air pollution may affect human somatic functioning both by psychological and somatic means (Meertens and Swaen, 1997). Besides, health effects of perceived annoyance from air pollution are so far unknown. Now the air pollution annoyance scores have been compared to the levels of a few specific pollutants only. The air pollutants, which may cause most of the annoyance, however, maybe other than those measured, and the annoyance is most likely an aggregate effect of many different pollutants. Therefore further research of air pollution annoyance levels, determinants and also
associations with different air pollution components is needed.
5. Conclusions *
*
*
*
There was a large variation in the levels of air pollution annoyance between the six studied cities. The highest annoyance levels were experienced while in traffic. The significant determinants of air pollution annoyance were the city, self-reported sensitivity to air pollution and respiratory symptoms, downtown residence and gender of the subject. No consistent or significant correlations were seen between the individual levels of annoyance and exposure concentrations to either PM2.5 or NO2. High air pollution annoyance in traffic, however, was significantly associated with home outdoor concentrations of both PM2.5 and NO2 and downtown living (NO2-model).
4602 *
T. Rotko et al. / Atmospheric Environment 36 (2002) 4593–4602
When average annoyance levels and concentrations were averaged for each city, the perceived annoyance levels at home correlated highly with the measured personal 48-h PM2.5 and NO2 exposures and home indoor NO2 concentration, annoyance at work correlated with personal workday exposure and workplace PM2.5 concentrations, and annoyance in traffic with home outdoor NO2 concentration.
Acknowledgements This work has been supported by EU (Contracts: ENV4-CT96-0202 (DG12–DTEE) and ERBIC20CT960061), Academy of Finland (Contracts: N36586 and N42610), Swiss Ministry for Education and Science (Contract BBW 95.0894) and intramural funding by KTL-National Public Health Institute of Finland.
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