PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

A critical review of the basis for WHO's new recommendations forlimiting annoyance due to environmental noise
Truls GJESTLAND
1

SINTEF DIGITAL, Norway
truls.gjestland@sintef.no

ABSTRACTThe new WHO Environmental Noise Guidelines for the European Region include recommendations forlimiting noise exposure to levels without adverse health effects. This paper reviews WHO’s evidence withrespect to aircraft and road traffic noise annoyance. It demonstrates that WHO’s new guidelines are basedon a non-representative selection of existing studies whose findings cannot be generalized to the residential
population at large. The new WHO recommendations are unwarranted and unsupported by the reported
evidence.
Keywords: Aircraft noise, road traffic noise, WHO recommendations

1. INTRODUCTION
The European Regional Office of the World Health Organization (1) recently dramatically lowered
its former (2) recommendations for cumulative aircraft noise exposure levels associated with risks ofadverse public health effects. Similarly, the recommendations for road traffic noise were also reduced
to a lesser degree.
WHO’s recommendations, although lacking the force of law, are nonetheless of interest to national
regulatory bodies and to the public at large. It is therefore important that WHO’s recent
recommendations receive and withstand careful scrutiny.
WHO (2018) strongly recommends decreasing permissible noise exposure levels produced byaircraft to below L den = 45 dB to prevent adverse public health consequences. WHO’s newly
identified noise exposure levels are an order of magnitude lower than those identified by WHO in 2000.
WHO’s 2000 recommendations were not source-specific recommendations, but suggested a limit of
L pA,16h = 55 dB to avoid health effects mediated by serious annoyance. The corresponding L den value
would have been higher for a full 24- (rather than 16-hour) day period. A source-specific correction
for aircraft, however, would have moved WHO’s recommendation in the opposite direction. WHO’snew (2018) recommendation thus represents a shift of about 10 dB from its former recommendation.
A 10 dB reduction in the duration-corrected loudness of cumulative noise exposure (to Lden = 45 dB
from L pA,16h = 55 dB) represents a halving of loudness as WHO’s prior recommendation. This is adramatic shift in the recommended "safe" limit on aircraft noise exposure, for which strong andreliable evidence is essential.
WHO also recommends reducing exposure to road traffic noise to less than L den = 53 dB to avoid
adverse health effects. This is a less drastic reduction, but still represents a lowering of the "safe"
exposure level by 3 to 5 dB compared with WHO's former 2000 recommendation.

2. BASIS FOR NEW RECOMMENDATIONS
WHO commissioned different groups of noise experts to provide a basis for the newrecommendations. Three researchers, R Guski, D Schreckenberg and R Schuemer, were given the taskof reviewing the connection between environmental noise and annoyance. Their review was published
as a separate report (3).

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2.1 Road traffic noise
Guski et al. identified 25 studies of road traffic noise annoyance for their analysis. A scatterplot of
the calculated percentage highly annoyed (%HA) for these studies is shown in Figure 1, together withthe exposure-response function (ERF) for the complete dataset (black curve), and the ERF presented
by Miedema and Oudshoorn (red curve) that is currently being used as a reference curve by EU.

Figure 1. Scatterplot and quadratic regression functions for the relation between Lden and thecalculated %HA for 25 road traffic noise studies reported by Guski et al.(3).
The most striking feature of the proposed ERF is the U-shape with a minimum at L den 45.5 dB andincreasing values for %HA for decreasing exposure levels below this point. This result is presented
despite the observation made by Guski et al. : It should be noted that 20 of 21 road traffic noise studies
reporting a correlation show a statistically significant correlation between noise levels and raw s cores,
and they all show a clear increase of %HA with increasing noise levels, too (3) (Supplement S14). The
shape of the derived ERF is, of course, just an artifact of the curve-fitting methods that Guski et al.
employed. Response data from only five studies are available at L den 40 dB, of which four wereconducted in the Austrian Alpine region. The latter studies yielded exceptionally high annoyancescores.
2.1.1 Alpine surveys
The dataset compiled by Guski et al. included five surveys from the Austrian Alpine region.
According to Guski et al. three of these surveys used a cut-off at 60 % for "highly annoyed" while theother two used a cut-off at 73 %. This is incorrect, however. A closer reading of the report by Lercher
et al. (4) reveals that they used the upper four categories of the 11-point scale (not the usual three) toclassify respondents as highly annoyed in two of the studies. This corresponds to a cut-off at 64 %. The
main reason for the high annoyance scores for the Alpine surveys (black plotting symbols in Figure 1)
is thus different definitions of highly annoyed. Lercher et al. (4) also offer response data for the Alpine
studies based on the usual cut-off at 73 %. The ERF curve for these data is shifted about 5 dB comparedto the cut-off used by Guski et al. It is, however, not possible to validly compare data that has been
derived using different definitions of highly annoyed. The five Alpine studies should therefore nothave been included in the WHO dataset with a cut-off at 60-64 %.

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In addition, Lercher et al. comment in their report that the noise prediction model they used may not
be applicable to the special topography found in the narrow Alpine valleys. This is yet another reason
for not including the results in the WHO dataset.
2.1.2 The Hyena study - roadSix of the surveys in the WHO dataset were part of the HYENA study (5). Respondents in the
HYENA study were limited to residents aged 45 – 70 because it was designed primarily to study
prevalence of hypertension. Noise annoyance has been shown to vary with age (6), with a maximum
noise sensitivity around 45 years of age. The prevalence of highly annoyed residents in the HYENA
study thus over-estimates the prevalence of annoyance in the general population in a more
representative group aged 18 – 80 (as is commonplace in such surveys). Guski et al. comment on thisfact but cite other studies that show only weak links between annoyance and age.
Social surveys on noise annoyance nowadays are usually carried out according to the ICBEN
recommendations that specifies standard survey questions and response scales (7). This facilitatesinter-survey comparisons. The HYENA study used a modified annoyance question. Instead of asking
about annoyance in general, as is recommended by ICBEN, the participants were asked about theannoyance during the day and during the night. Guski et al. assumed, without documentation thatannoyance during the day is no different from annoyance in general.
The assumptions that modification of the annoyance question and limitation of the age range makeno difference to the response can be tested by comparing the average ERF for the HYENA study withthe average ERF for the other surveys. The HYENA response is shifted 3.5 dB toward higher
annoyance. The results of the HYENA study cannot therefore be compared directly with results fromsurveys conducted strictly according to the ICBEN recommendations and should not have been
included in the WHO dataset.
2.1.3 Discussion - road traffic noise
The response data for all of the road traffic noise studies shown in Figure 1 have been analyzed by
the CTL method defined in ISO 1996-1 (8). Original data reported from the surveys (pairs of noise
exposure levels and % HA values) were used, rather than a secondary dataset calculated fromindividual, regression-derived exposure-response functions. Each survey was analyzed separately
with no weighting of sample size differences. As Guski et al. (9) note, the influence of sample-size
weighting is relatively small. Three ERFs were constructed: results from the five Alpine surveys,
results from the six HYENA surveys, and the results from the remaining surveys. These curves areshown in Figure 2 together with the Miedema & Ooudshorn curve which is currently used by the EU asa reference for road traffic noise annoyance.

percentage highly annoyed

50
40
EU
30

Hyena
Alps

20

Rest
10

ex Alps
All, Alps73

0
40

45

50

55

60

65

70

75

road traffic noise, Lden [dB]

Figure 2. Exposure-response curves for road traffic noise annoyancecalculated for the surveys presented in Figure 1.

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The ERF based on the surveys that were conducted according to the ICBEN recommendations andusing a cut-off of 73 % for highly annoyed (red curve) lies below the EU reference curve for most of
the exposure range. The ERF for the HYENA surveys (green curve) displays higher annoyanceequivalent to a shift in exposure level of 3.5 dB. It may be argued that the difference between the
HYENA surveys and the rest is not severe enough to warrant exclusion of the whole study. The ERF"ex Alps" (light blue curve) shows slightly higher annoyance but still lies below the EU reference for
exposure levels below L den 65 dB.
The ERF for the Alpine studies (black curve) indicates a much higher prevalence of annoyance.
This is due to a different definition of highly annoyed. It is evident from Figure 2 that the results fromthe Alpine surveys should not have been included in the manner elected by Guski et al. However,Lercher et al. (4) have provided alternative results for the Alpine studies based on the standard cut -offdefinition 73 %. An ERF based on all the surveys in the WHO dataset but with a comparable cut -off for
the Alpine surveys is also shown in Figure 2 (yellow curve). Although based on some surveys ofquestionable quality, this curve also lies below the EU reference at low exposure levels but displays
annoyance prevalence rates above the EU reference at higher levels.
An analysis of 47 surveys on annoyance from road traffic noise conducted between 1969 and 2015
yields an average CTL value of 78.7 dB (8). The ERF associated with this value is very similar to the
EU reference curve. If the selection is limited to studies conducted after 1996, similar to the WHO
dataset, the average CTL value for 19 post-1996 studies is 1 dB higher, L ct 79.7 dB, indicating thatpeople are slightly less annoyed.
A survey on noise annoyance in Switzerland has recently been reported by Brink et al.(9). This wasa large-scale survey comprising more than 5400 respondents. The results reported by Brink et al. forroad traffic noise have a CTL value of 78.3 dB (r 2=0.98), which is practically identical to the average
CTL value for the 47 surveys analyzed by Gjestland (8). Actual response data reported by Brink et al.
have been plotted in Figure 3 together with the ERF associated with L ct 78.7 dB, the ERF proposed by
Guski et al. (3), and the EU reference curve.

percentage highly annoyed

50

40

30

EU
CTL 78.7

20

Guski
Brink

10

0
40

45

50

55

60

65

70

75

road traffic noise, Lden [dB]

Figure 3. Exposure-response curves for road traffic noise annoyance as proposed by Guski et al.(3),the average of 47 surveys analyzed by Gjestland (8) (CTL 78.7 dB), and the EU reference curve. Red
dots are results reported by Brink et al.

2.1.4. Conclusions – road traffic noise
The WHO recommendation for limiting road traffic noise annoyance deals with exposure at low
levels. The yellow curve in Figure 2 shows that an exposure-response curve based on comparable
results from available post-2000 surveys on road traffic noise annoyance displays annoyance7132

prevalence rates below the current EU reference curve at exposure levels below L den = 60 dB. Similarly,
a comprehensive study, recently conducted in Switzerland with more than 5400 respondents, reported
by Brink et al. shows results comparable to the current EU reference curve for low exposure levels.
The lowering of the recommended guideline value to L den = 53 dB to avoid adverse health effects
therefore seems unwarranted and unsupported by existing evidence. At this noise level the average
prevalence of highly annoyance is about 2 percent, a prevalence rate that cannot plausibly beconsidered evidence of a serious public health hazard.
2.2 Aircraft noise
Guski et al. included 12 studies of aircraft noise annoyance in their analysis (3). Figure 4 is ascatterplot of the calculated %HA for these studies, together with the exposure-response function forthe complete dataset (black curve) and the ERF presented by Miedema and Oudshoorn that currently
serves as a reference curve by EU (red curve).

Figure 4. Scatterplot and quadratic regression functions for the relation between L den and thecalculated %HA for 12 aircraft noise studies reported by Guski et al.(3).
The data points in Figure 4 do not represent aggregated empirical observations as is usual in suchplots. Instead, they represent predicted values estimated from regression curves developed for each of
the studies. Inconsistent regression methods have been used in the various studies, and the regressions
have been developed over different exposure ranges. Further, the results for the WHO full dataset were
derived using a quadratic regression model that weighted studies by sample size.
A procedure based on combining all responses from different surveys in this manner does not take
into account the fact that only about one third of the variance in the response data is explained by the
cumulative noise exposure (12) while the rest of the variance is accounted for by so-called
non-acoustic factors. As is evident from the very large spread in response data, such non-acoustic
factors are especially prominent in aircraft noise surveys. Simple visual inspection of the data in
Figure 4 shows that for the noise exposure range of most practical interest fo r regulatory purposes,
Lden = 50 dB to Lden = 60 dB, the prevalence of highly annoyed residents varies between about 5 % and
70 %. This enormous spread is not necessarily fully attributable to personal or situational attitudes
toward the cumulative noise exposure. A more plausible explanation would be that there must be otherfactors that also play an important role.
2.2.1 The HYENA study - aircraft
As in section 2.1.2 above, the HYENA study was designed to investigate the prevalence ofhypertension among residents of neighborhoods near airports. The questionnaire did not follow the
ICBEN recommendations. The selection of residents was limited to people aged 45 – 70 years.
According to Guski et al. the respondents were selected at random from available registries, but atleast at one airport, (Heathrow), some respondents may have been self-selected. A letter was

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distributed to members of a noise interests group urging them to pa rticipate in the survey and tellingthem that if you "would be interested in taking part, please telephone NN" at Imperial College, even if
they did not belong to the randomly selected group.
Likewise, there is reason to question the adequacy of the exposure estimates at several of the
HYENA airports. Babisch et al. (5) cite aircraft noise levels as low as L Aeq 24h = 11 dB (Stockholm)and L Aeq 24h = 22 dB (Milan). Such aircraft noise levels are not credible as modeling estimates, muchless as acoustic measurements. Referring to Brink (13), Guski et al. (3) convert these estimates to
L den values by applying a correction factor of 2.6414 dB. These values suggest that the researchers
relied heavily on software modeling to describe the aircraft noise exposure, with little evident concern
for the limitations of aircraft noise modeling software, nor for the reasonableness of predicted
exposure levels. No existing aircraft noise prediction programs can yield credible exposure predictions
at such low levels (indicating a very long distance from the source). Applying a n adjustment with a
precision of "one ten-thousandth of a decibel", to a number that has been predicted by a model thatyields output values with a standard error of at least 1-2 dB (14) , makes no sense.
Visual inspection of the annoyance data from the HYENA study reveals that two airports, Athens(ATH) and Milan (MXP) have an exceptionally high prevalence of highly annoyed neighbors, (seeupper six surveys in Figure 4). The field work for the Athens study was conducted in 2003, but this
airport was not opened until March 2001. Someone who has endured a noisy construction period of
perhaps 3-4 years and then suddenly has been exposed to unfamiliar aircraft noise for two years, can
not be considered a typical airport neighbor.
In a report on the results of the HYENA study its authors comment on the very high annoyancescoring of the Athens and Milan airports. They discuss several reasons for this including a bias in theselection of respondents and conclude that the data from these two airports is not representative for
airports in general. They therefore exclude the data from their subsequent pooled analyses (5) (p.1175).
Guski et al. nevertheless included both airports in the WHO full dataset.
Likewise, Babisch et al. state that “Our results may not be fully comparable to the EU curve,
because the HYENA study annoyance was assessed in the limited age range of 45 -70-year-old
subjects" (5) (page 1175). The original researchers’ concerns were not shared by Guski et al. (11).
All in all, the HYENA study design deviates so much from standard survey procedures that theresults should not have been included in the WHO dataset.
2.2.2

High-rate and low-rate airport change situation

Most airports experience growth in traffic over time. This increase usually occurs gradually overmany years. Other airports are characterized by large abrupt changes due to the opening of a new
runway, introduction of new flight paths, an abrupt increase in number of aircraft movements, etc.
Janssen and Guski (15) classify airports low-rate change airports if there is no indication of asustained abrupt change of aircraft movements, or the intention of the airport to change the number ofmovements within three years before and after the annoyance study. They offer the following
definition: "An abrupt change is defined here as a significant deviation in the trend of aircraft
movements from the trend typical for the airport. If the typical trend is disrupted significantly andpermanent, we call this a ‘high-rate change airport’. We also classify this airport in the latter category
if there has been public discussion about operational plans within [three] years before and after the
study". Low-rate change is the default characterization.
Gelderblom et al. (16) have applied this "high-rate/low-rate" classification to 62 aircraft noise
annoyance studies conducted over the past half century. They show that there is a difference in theannoyance response between the two types amounting to about 9 dB. To express a certain degree ofannoyance people at a high-rate change (HRC) airport on average "tolerate" 9 dB less noise thanpeople at a low-rate change (LRC) airport Any attempt to develop an average dose -response curvefrom at set of studies will therefore be highly sensitive to the types of airports that are included. A highpercentage of HRC airports will increase the average prevalence of highly annoyed people.
The WHO dataset includes 8 out of 12 HRC airports and about 83 % of the respondents. In contrast,in the dataset presented by Gelderblom et al., 17 out of 62 airports and about 35 % of the respondents
are HRC airports. In the original dataset used by Miedema and Vos for their dose-response curve (17),only 2 out of 20 airports or about 10 % of the respondents were categorized as HRC.

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2.2.3

Discussion - aircraft noise

The response data for all of the aircraft noise studies shown in Figure 4 were analyzed according to
the CTL method as defined by ISO 1996-1 (10). Original data reported from the surveys (pairs of noise
exposure and % HA) were used, rather than a secondary dataset calculated from individual
exposure-response curves, except for the Amsterdam-2002 study for which original data could not be
obtained. Each survey was analyzed separately, without any sample size weighting. The red curve in
Figure 5 shows an average exposure-response function based on CTL analysis together with the ERF
derived by Guski et al. (black curve) and the current EU reference curve for aircraft noise annoyance(dashed blue curve). As noted above some of the surveys included in WHO dataset are of a dubious
quality (conducted in a non-standardized manner). These results cannot therefore be considered
representative for the noise situation around airports in general.

percentage highly annoyed

80

60

WHO
WHO-CTL

40

EU
post-2000

20

Brink
0
40

45

50

55

60

65

70

75

aircraft noise, Lden [dB]

Figure 5. Exposure-response curves for aircraft noise annoyance
Gjestland (18) has compiled a different selection of post-2000 aircraft noise surveys that adhere to
the inclusion protocol defined by Guski et al. (3) and for which sufficient data were available to do acomparative analysis. His dataset includes 18 surveys with 16,047 individual respondents. Half of the
airports were characterized as HRC airports. The average exposure-response curve for these airports
has also been plotted in Figure 5 (yellow curve). This curve lies above the EU reference curve,
indicating a higher prevalence of highly annoyed people, but lies substantially below the ERF based on
the WHO dataset. The difference between the EU reference and the ERF based on the alternative
dataset by Gjestland is less than 1σ (one standard deviation) so they cannot be considered significantly
different. This ERF shows 10 % highly annoyed at an exposure level L den = 53 dB.
Brink et al.(9) have recently published results from a large Swiss study on annoyance fromenvironmental noise. Data for aircraft noise annoyance have been compiled on the basis of the
response from 2664 participants. Data from this study has also been plotted in Figure 5 (red dots). The
results presented by Brink et al. confirm that the ERF suggested by Guski et al. overestimates theannoyance at low exposure levels. According to Brink et al. a prevalence rate of 10 % highly annoyed
can be found for an exposure level L den = 51 dB.
2.2.4 Conclusions aircraft noise
Even if all the surveys analyzed by Guski et al. (3), the WHO dataset, had been conducted byirreproachable methods, the fact that a similar analysis of a different and larger set of survey data (1 8)yields a very different result clearly indicates that the findings of Guski et al. (3) are not representative,
and cannot be generalized to community response to aircraft noise around airports.

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As has been shown by Gjestland (18) in his original critical remarks on the new WHO
recommendations, and further documented in (19) and in the current paper, WHO's newrecommendations for limiting aircraft noise are based on questionable evidence.
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