Abstract
In the catering industrytobacco smoke was the primary source of fine and ultrafine particles, which are well known for their health-damaging effects. As shown in studies, attempts to reduce passive smoking in the catering industry of Vienna, like separated smoking rooms, failed to reduce fine and ultrafine particle concentrations effectively. On November 1st 2019, an enlarged non-smoker s protection law was introduced, including a total smoking-ban in the catering industry. 40 hospitality venues with areas for smokers and non-smokers before the ban had been selected as typical Viennese cafes, pubs, bars and discotheques to be sampled unannounced. Concentrations of fine particle mass (PM10, PM2.5, PM1) and ultrafine particle number (PNC) and lung deposited surface area (LDSA) could be measured before and after the introduction of the smoking-ban in 39 venues at nearly identical locations and under comparable circumstances. Results showed a statistically significant decline in both fine and ultrafine particle concentrations in the former smoking areas for all parameters as well as in the former non-smoking areas for PM2.5, PM1 and LDSA. After the ban concentrations in former smoking areas and non-smoking areas showed no significant differences any more. From these results the smoking-ban successfully removed particles from breathing air of guests and staff, however, some outliers in the study after the ban point to the necessity of repeated controls in Vienna. Also, outside Vienna the compliance with the law should be controlled in the Austrian hospitality industry.
Author Contributions
Copyright© 2021
K. Sima Annika, et al.
License
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This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Competing interests The authors have declared that no competing interests exist.
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Introduction
Fine and ultrafine particles as atmospheric aerosols contribute to hazardous air pollution, mainly deriving from anthropogenic burning processes such as combustion engines, industry, heating and tobacco smoking. Studies have shown that fine and ultrafine particles cause multiple negative effects on human health. One of the most common sources of fine and ultrafine particles in closed spaces is tobacco smoke. Concerning the WHO’s suggestions, guidelines for ambient fine particle concentration limits were introduced in Austria. Thus, limited daily means of fine particle concentration were set for PM10 to 50 μg/m3, limited yearly means for PM10 to 40 μg/m3 and for PM2.5 to 25 μg/m3. For PM2.5, no daily mean concentration limit has been set yet. Also, there have neither been guidelines for ultrafine particle concentration or PM1 nor suggestions of concentration limits in closed spaces. To protect non-smokers from passive smoke in the catering industry, the Austrian legislation requested with 1st January 2009 among other things separated smoking and non-smoking areas in gastronomic facilities larger than 80 m2. Alongside, after years of debates, Austria’s legislation enlarged the so-called “Non-Smoker’s Protection Law” on November 1st 2019, introducing a smoking-ban regarding the whole catering industry. Through this law, all kinds of smoking got prohibited indoors. Furthermore, all gastronomic locations have to mark themselves visibly as smoke free. On account of this enlarged law, this study is rested. Therefore, its aim is to compare the concentrations of fine and ultrafine particulate matter before to after introducing the smoking ban into Austrian gastronomy, differentiated between formerly smoking and non-smoking areas. Thus, a repeated cross-sectional study on a sample of hospitality venues was created.
Materials And Methods
As to collect samples of fine and ultrafine particle concentration before introducing the smoking-ban, first study measurements were performed from April to October 2019 in 40 randomly chosen, well frequented catering facilities of different types, such as pubs, restaurants, bars, discotheques and cafeterias in Vienna. After collecting the data, the differences of concentrations between these two (formerly) areas were analysed and the differences of concentrations before to after introducing the smoking ban. The various mean concentrations of both studies were compared using statistics, including primarily paired t-testing as well as visual descriptions like boxplots via IBM SPSS Statistics Subscription®. The results were assessed to a confidence interval of 95%, therefore, contrasted against the significance level of p=0.05.
Results
Contrasted against p=0.05, statistics show statistically significant declines of fine particle concentrations of PM10, PM2.5 and PM1 in former smoking areas as well as of PM2.5 and PM1 in former non-smoking areas, as shown in Key: “Before” indicates samples before the introduction of the smoking-ban, “after” after the introduction. “S” codes the smoking area, “NS” the non-smoking area. PM10, PM2.5 and PM1 code the particular fine particle concentration. The hyphen represents the comparison. N = 39 Key: “Before” indicates samples before the introduction of the smoking-ban, “after” after the introduction. “S” codes the smoking area, “NS” the non-smoking area. PNC and LDSA code the particular ultrafine particle subsets. The hyphen represents the comparison. N = 39 Fine and ultrafine particle concentrations after introducing the smoking ban were not significantly different between the former smoking and former non-smoking areas. ( Key: “After” represents samples after the introduction of the smoking-ban. “S” codes the smoking area, “NS” codes the non-smoking area. PM10, PM2.5 and PM1 code the particular fine particle concentration. The hyphen represents the comparison. N = 35 Key: “After” represents samples after the introduction of the smoking-ban. “S” codes the smoking area, “NS” codes the non-smoking area. PM10, PM2.5 and PM1 code the particular fine particle concentration. The hyphen represents the comparison. N = 30 Overall, concerning the comparison before to after the introduction of the smoking-ban, in each area were found remarkable declines of fine as well as ultrafine particle concentrations, statistically significant in smoking areas for PM10, PM2.5, PM1, PNC and LDSA and in non-smoking areas for PM2.5, PM1 and LDSA. No statistically significant declines were registered in non-smoking areas for PM10 and PNC. After the ban, there were no significant differences of concentrations found anymore between former smoking and non-smoking areas.
95% confidence interval of differences
T
df
Sig. (2-sided)
Mean
Standard deviation
Standard error of mean
Lower value
Upper value
Pair 1
beforeSPM10- afterSPM10
119.034
149.816
24.303
69.791
168.278
4.898
37
0.000
Pair 2
beforeNSPM10 - afterNSPM10
22.411
68.427
11.566
-1.094
45.917
1.938
34
0.061
Pair 3
beforeSPM2.5 - afterSPM2.5
121.006
136.585
22.157
76.112
165.901
5.461
37
0.000
Pair 4
beforeNSPM2.5- afterNSPM2.5
29.557
70.819
11.971
5.230
53.885
2.469
34
0.019
Pair 5
beforeSPM1 - afterSPM1
106.264
122.758
20.181
65.335
147.195
5.265
36
0.000
Pair 6
beforeNSPM1- afterNSPM1
25.982
61.699
10.429
4.788
47.177
2.491
34
0.018
95% confidence interval of differences
T
df
Sig. (2-sided)
Mean
Standard deviation
Standard error of mean
Lower value
Upper value
Pair 1
beforeSPNC- afterSPNC
76724.690
84008.941
14850.823
46436.234
107013.140
5.166
31
0.000
Pair 2
beforeNSPNC - afterNSPNC
3518.939
49925.829
8207.756
-13127.161
20165.040
0.429
36
0.671
Pair 3
beforeSLDSA- afterSLDSA
384.810
332.852
58.841
264.804
504.816
6.540
31
0.000
Pair 4
beforeNSLDSA - afterNSLDSA
67.879
157.620
25.913
15.326
120.432
2.620
36
0.013
95% confidence interval of differences
T
df
Sig. (2-sided)
Mean
Standard deviation
Standard error of mean
Lower value
Upper value
Pair 1
afterSPM10 - afterNSPM10
7.444
40.982
7.028
-6.855
21.743
1.059
33
0.297
Pair 2
afterSPM2.5 - afterNSPM2.5
4.957
19.183
3.290
-1.736
11.651
1.507
33
0.141
Pair 3
afterSPM1 - afterNSPM1
3.210
11.528
1.977
-.8121
7.233
1.624
33
0.114
95% confidence interval of differences
T
df
Sig. (2-sided)
Mean
Standard deviation
Standard error of mean
Lower value
Upper value
Pair 1
afterNSPNC- afterSPNC
6167.783
28884.296
5273.527
-4617.790
16953.357
1.170
29
0.252
Pair 2
afterNSLDSA - afterSLDSA
-1.748
61.225
11.178
-24.610
21.114
-0.156
29
0.877
Discussion
In comparison to the smoking areas before the ban statistically significant declines of fine and ultrafine particle concentrations indicate reduced passive smoking in the Viennese hospitality industry, which is a successful development. Also, these results underline the effectiveness of the new legislation to protect the population against the harmful effects of fine and ultrafine particles from second-hand smoke. The decline of PM10 in former non-smoking areas was not significant, which might be due to renovation and other sources of PM10, stirred up and resuspended by walking of guests and waiters. The high variance of PNC in the non-smoking area might have been due to illegal smoking shortly before the air sample was taken, which could explain some very high concentrations at single venues, especially if concomitant with high LDSA and PM1 in the room. But the big variance of PNC in the non-smoking area could partly be explained also by other possible combustion (e.g. candles which have been excluded at the table of the researcher only) and condensation products, highly variable in time and space. Prior to the smoking ban indoor smoke exposures were highest in the smoking rooms, followed by adjacent rooms and lowest outdoors. There were no significant differences in concentrations between the smoking and non-smoking areas after the smoking ban entered into force. Therefore, one could diagnose that the indoor air quality was considerably improved.
Conclusion
To conclude, by this study’s statistics and interpretation the suggestion of the smoking-ban’s effectiveness on Viennese gastronomy is given. Additional controls are necessary to verify compliance with tobacco legislation in the Austrian catering industry.