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

Community response to high-speed railway noise in Tianjin, China
Lan ZHANG1; Hui MA1
1

Tianjin University, China

ABSTRACT
Adverse effects of noise from high-speed railway have become more and more serious and widespread withthe rapid development of high-speed rail in China. A social survey on community response to high-speed
railway noise was carried out in Tianjin, China from March to July, 2018 along the Beijing-Tianjin intercity
high-speed rail line and Beijing-Shanghai high-speed rail line. 674 residents were interviewed byquestionnaires to explore their noise annoyance, activity interference caused by high-speed railway noise,sensitivity to noise, and satisfaction with living environment. The exposure of high-speed railway noise wasmeasured for 24h at each site, and standardized questions and scales suggested by ICBEN Team 6 were usedin the social survey. As a result, the dose-response relationship curve for high-speed railway noise of Chinese
residents was established, and it showed that with the increasing of noise level (Ldn), annoyance increased
exponentially. Compared with Japanese and French people, Chinese residents showed more annoyed tohigh-speed railway noise. It also suggested background noise had important impact on noise annoyanceevaluation to high-speed railway. Furthermore, annoyance caused by high-speed railway noise was also
greatly influenced by subjective characteristics such as noise sensitivity, satisfaction of living environment
and attitudes towards high-speed rail.
Keywords: Community response, High-speed rail noise, Annoyance

1. INTRODUCTION
Since the opening of the Tokaido Shinkansen Line in 1964, rapid transit railway networks had been
constructed in European countries such as France, Spain, and Germany and in Asian countries such as
China and Korea. The high-speed rail emitted much noise because of its high speed (1). Noiseproblems caused by high-speed rail had grown from a local to a global issue.
The research on conventional railway noise was relatively mature (2-5), but the research on
high-speed railway noise was still in its infancy (6-8). Japanese scholars conducted a series of social
surveys on impact of Shinkansen noise. Sato T (9) carried out a social survey on community responses
to Shinkansen noise in Kyushu. The result indicated that people living along the Shinkansen weremore annoyed by the same amount of noise than those living along the ordinary railways.
Yokoshima S et al. (10) compared the exposure-response relationships for transportation noise using
datasets accumulated in Japan and showed that Shinkansen railway noise was equally as annoying ascommercial aircraft noise and more annoying than conventional railway and road traffic nois e. The
research on community response to high-speed railway noise was mainly concentrated in developed
countries such as Japan and France(11). In the research comparing community response to road traffic
noise between Japan and Sweden, Sato T et al. (12) found the difference in lifestyles might result in
the different response. Hence, a question arose as to whether the findings of previous studies, whichwere obtained mainly for developed countries, were applicable to the rest of the word, especiallydeveloping countries. China, as a populous country, had the highest amount of high-speed rail
construction. The involvement of China would contribute to the knowledge of the situation ofdeveloping countries in terms of environmental noise in the word.
Even in a country with the same cultural background, the percentage of highly annoyed residents
was found to vary greatly among different regions. In the research on community response to roadtraffic noise in Vietnam, Phan HYT(13) found inhabitants lived in residential areas with relatively
narrow roads and high levels of traffic density would initiate higher annoyance. Gjestland T (14)
1
1

374

zhanglan@tju.edu.cn
muhui@tju.edu.cn

conducted a second analysis of data from previous community response social survey. He found that
residents in detached house were more annoyed to Shinkansen noise than residents in apartments.
However, different settlements in China had their own characteristics. It remained to be explored
what features of sites in Tianjin of China would cause differences in annoyance.
In previous studies, noise annoyance was not only affected by acoustic factors, but non -acoustic
factors also played an important role. In the investigation of community response to aircraft noise in
Vietnam (15), it found that the frequency of use of airplanes and time to go to bed seemed to affectannoyance. To assess the factors on road traffic annoyance in Vietnam, Nguyen T (16) developed
five structural equation models for five cities. The result showed that sensitivity would become
greater modifier of road traffic noise annoyance if residents didn’t satisfy with their living area.
Different non-acoustics factors might be involved in different noise sources. The impact of
non-acoustic factors on high-speed railway noise needed further research.
This paper conducted a social survey on the response of Chinese residents to high -speed railway
noise. The objectives of this study were to propose a representative dose-response relationship curvefor high-speed rail noise in China and to assess how acoustic and non-acoustic factors moderated
response differences among different sites.

2. METHOD
2.1

Survey Sites
A social survey on community response to high-speed railway noise was carried out in Tianjin,
China from March to July, 2018 along the Beijing-Tianjin intercity high-speed rail line (BTL) andBeijing-Shanghai high-speed rail line (BSL). The two lines represented the form of short-distance andlong-distance lines in China, respectively. The BTL is the first intercity high-speed railway inmainland of China with a line length of 120 kilometers which opened in 2008. The BSL from Beijing
to Shanghai with a total length of 1318 kilometers went into service in 2011. The total number of trains
per day running on BTL was 200-230, and there were 229-239 trains a day on BSL (see Figure 1).
In our investigation, the sites with only high-speed trains passing though were selected in order toeliminate the interference of conventional railway noise. The high-speed trains passed through bothrural and urban areas in China. Therefore, four rural residential areas and three urban residential areas
along BSL, as well as three rural residential areas and three urban residential areas along BTL wereselected in this survey. According to the type of settlements and railway lines, investigation sites weredivided into four sub-areas: four rural residential areas along BSL in sub-area 1, three urban
residential areas along BSL in sub-area 2, three urban residential areas along BTL in sub-area 3 andthree rural residential areas along BTL in sub-area 4, as shown in Figure 2.

Average traffic volume

30
BSL
25

BTL

20
15
10
5
0
5 6 7 8 9 1011121314151617181920212223

Time˄h˅Figure 1 – Average traffic volume in BSL and BTL

Figure 2 – Map of survey sites in Tianjin.

2.2

Questionnaire Design
The questionnaire was labeled as “Survey on living environment”. It was not only on noise but
also on various components of living environment. There were 33 questions in five aspects:
annoyance, activities disturbance caused by high-speed railway noises, living environment
evaluations, housing factors and demographic variables, as summarized in Table 1.General annoyance375

and activity interferences were measured with an 11-point numeric scale constructed by ICBEN Team
6 (17) ,with end points of 10= “extremely annoyed” and 0= “not at all annoyed”. Other items such as
self-reported noise sensitivity to noise source were gauged using five-point verbal scale.

Residential environment
Housing factors anddetails of the house

Table 1 – Questionnaire item of surveys
Quiet, comfort, preference
Quality of residential environment (soundproof, ventilation, sunshine,
insulation, area of house), Housing type, the number of glass layers,
frame type of windows, direction of facing or not facing railways

Annoyance

Annoyance due to high-speed railway noise, Annoyance due tovibration caused by high-speed railway, the influence time

Interference on daily
activities

Sleeping disturbance, listening to TV or radio, talking, disturbance inoutdoor or balcony, reading or working, opening windows, emotion ormood
Noise sensitivity, attitudes to the transportation (using frequency,
comments on safety, support for its construction)

Sensitivities, attitudes,etcLife style

The time of getting up and going to sleep, length of period to stay athome, the frequency of opening widows in summer

Socio-demographic
variables

Occupation, age, gender, education, the number of family, income,health states(whether heart disease and headache occur˅

2.3

Social Surveys
Since the most high-speed railway lines passing though residential areas were in the form of
viaducts and most of the residential buildings were perpendicular to the railway lines, the high -speed
railway noise spread far. Thus, questionnaires were delivered to people living in houses within 500
meters of the railway, as an investigation rule. Respondents were interviewed face to face on a
one-person-per-family basis. Totally, 674 responses were obtained and the response rate was 85%
shown in Table 2. The socio-demographic factors of this survey were presented in Table 3. Employed
respondents constituted 45% in the surveys. 65.9% respondents were in the age from 20 to 60. The
proportions of these demographic characteristics were balanced, except that the ratio of females was ahigher than that of males. Because housewives who spent the longest time at home in settlements
accounted for a large proportion of respondents.
Table 2 – Outlines of social surveys
Sub-areas 1

Sub-areas 2

Sub-areas 3

Sub-areas 4

BSL

BSL

BTL

BTL

Rural areas

Urban areas

Urban areas

Rural areas

DH

AH

AH

DH

Survey sites

4

3

3

3

Sample

190

265

120

210

785

Respondents

164

252

99

159

674

Response rate

86%

95%

82.5%

75%

85%

Type of railaResidential typeType of house

376

b

Total

a

Beijing-Tianjin intercity high-speed rail line (BTL) ;Beijing-Shanghai high-speed rail line (BSL);b

Detached house(DH); Apartment house(AH);Table 3 – Demographic factors of the survey.
Items

Category

Proportion

Gender

Male

37.5%

Female62.5%

Under 20s

3.9%

20-39s31.8%

40-59s34.1%

Older than 60s

29.6%

Employed

45%

Students, housewives, retired, and unemployed

55%

Age

Occupation

2.4

Noise Measurements
After the social survey, noise measurements were made. The specific measurement method was asfollows. At reference points close to the railway, noise levels were measured with an integrating soundlevel meter for 24 hours. LAeq.24h and Ldn were both calculated from these noise measurement data.
Then the distance reduction measurements were conducted at each site. The noise levels of at least
three pass-by trains were measured at points 0, 10, 20, 40, 80 and 160m from the reference points
simultaneously. L AE values were calculated from noise level data recorded every 20 ms within 10 dB
from the maximum noise levels of noise events. Equations for estimating the distance reductions of
L AE were formulated. The noise exposure to each house was calculated using LAeq.24h and Ldn at thereference point and the distance reduction equations.

3. RESULTS AND DISCUSSION
Dose-response Relationships
Dose-response relationships were established with the indicators of Ldn and L Aeq.24h, commonlyused in noise evaluation. And the percentage of highly annoyed respondents was taken from the top
three points of the 11-point numeric scale. Figure 3 showed that with the increase of Ldn, theproportion of residents with high annoyance increased exponentially. And an approximate linear
relationship was found between L Aeq.24h and annoyance.
100
90
80
70
60
50
40
30
20
10
0

% Highly annoyed% Highly annoyed

3.1

33-37 38-42 43-47 48-52 53-57 58-62 62-67

Ldn(dB)

100
90
80
70
60
50
40
30
20
10
0
31-35 36-40 41-45 46-50 51-55 56-60 60-65

LAeq.24h(dB)(a)(b)
Figure 3 – Dose-response relationships for general annoyance
Figure 4 showed the comparison of dose-response curves among China, Japan and France. The
individual datasets of Japan analyzed in this paper were derived from five social surveys: Kanagawa(KNG01), Fukuoka (FKO), Nagoya (NGY), Kumamoto (KMM), and Nagano surveys (NGN) (10). The
dataset of France came from a social survey on annoyance from TGV traffic noise in 1996(11). The
result indicated that respondents in China were more annoyed by high -speed rail noise than those in377

Japan and France at the same noise level. Such differences might be attributed to the differences inacoustic characteristics of high-speed railway noise among countries. The maximum operating speedsof high-speed trains in China, Japan and France were 350km/h, 200-250km/h and 300km/h
respectively, resulting in a different perception of suddenness of noise.
This hypothesis could be supported by a previous laboratory study on exploration of high -speed
rail noise indicators (18). It suggested that “shock-effects” caused by the sudden increasing of noiselevel of the aerodynamic noise might lead to higher degree of noise annoyance. The noise ofhigh-speed train caused much more annoyance than that of conventional train at the same L Aeq ,partially was a result of the “shock-effects” value. According to this explanation, it could be inferred
why the annoyance of high-speed rail noise in China was higher than those of Japan and France
might be the different “shock-effects” caused by high-speed trains with different maximum speeds.

% Highly annoyed

90
80
70

100

Tianjin in China
FKO(2003)

60

NGY(2004)50

KMM(2011-2012)40

KGN(2013)

Tianjin in China90

KNG01(2001-2003)% Highly annoyed

100

30
20
10

France(1996)

80
70
60
50
40
30
20
10

0

0

33-37 38-42 43-47 48-52 53-57 58-62 62-67

31-35 36-40 41-45 46-50 51-55 56-60 60-65

Ldn(dB)

LAeq.24h(dB)(a)(b)
Figure 4 – Comparison of dose-response relationships between China and Japan or France
3.2

Differences in Response among Sites
L dn and L Aeq were highly correlated variables, thus, the differences in annoyance among different
sites obtained by using these two variables as indicators were similar. Since the correlation between
L dn and annoyance score was slightly higher than L Aeq, L dn was used in the next analysis. Residential
type and railway line were the main different factors in these sites. The dose-response relationshipcurves in each sub-area were plotted, shown in Figure 5. Because the residents in sub-area 3 were also
affected by military aircraft noise, the result in this area was excluded in next analysis in order toavoid the bias on the response to high-speed rail noise. Table 4 compared the percentage of highly
annoyed respondents between sub-areas at each range of Ldn by Chi-square test. It showed that there
was no difference between sub-area 1 and sub-area 4 at the range of 48-62dBA. And there wassignificant difference in annoyance between sub-area 1 and sub-area 2 at each range of L dn. The
result suggested that respondents in rural areas were more annoyed by high-speed railway noise thanthose in urban areas at the same noise levels.
100

Sub-area 1
Sub-area 2
Sub-area 3
Sub-area 4% Highly annoyed

90
80
70
60
50
40
30
20
10
0
43-47

48-52

53-57

58-62

63+

Ldn(dB)

Figure 5 – Comparison of dose-response relationships among sub-areas in Tianjin, China(sub-area 1: rural areas along BSL; sub-area 2: urban areas along BSL; sub-area 3: urban areas along
BTL; sub-area 4: rural areas along BTL)

378

Table 4 – Chi-square test of the percentage of highly annoyed respondents between urban-rural areas andbetween BTL-BSL at each range of Ldn.
Type 1

Type 2

43-47

48-52

53-57

58-62

Sub-area 1 (rural areas)

Sub-area 2 (urban areas)

0.042

0.013

0.002

0.033

Sub-area 1 (BSL)

Sub-area 4 (BTL)

0.039

0.292

0.127

0.877

On average, the background noise levels in urban areas were approximately 5dB higher than thosein rural areas. The background noise level defined as the 95th percentile level (L95 ) in this study.
Multiple regression analysis were conducted to examine the effect of background noiselevel(L 95 ).The results indicated that there was a significant effect of background noise level(p˘0.01)
on annoyance. When the difference value between Ldn and L95 was used as an indicator of exposure,the percentage of highly annoyed respondents was raised with the increase of this indicator value,
and the difference of community response between rural and urban residents didn’t exist at the rangeof 10-20, as seen in Figure 6 and Table 5. It could be speculated that noise of high-speed railway
events might be generally more noticeable in rural areas because of the lower noise level in those areas.
This finding was consistent with the result of another study on community response to aircraft noise
in Vietnam(15),which also proved that the areas affected by a single aircraft noise with a lower
background noise level yielded more annoyance.

% Highly annoyed

100
90

Sub-area 1

80

Sub-area 2

70Sub-area 4

60
50
40
30
20
10
0
5-

5-10 10-15 15-20 20-25

25+

Ldn-L95(dB)Figure 6 – Comparison of dose-response relationships among sub-areas at each range of Ldn-L95 in
Tianjin, China
Table 5 – Chi-square test of the percentage of highly annoyed respondents between urban-rural areas andbetween BTL-BSL at each range of Ldn-L95
Type 1
Type 2
5-10
10-15
15-20
Sub-area 1 (rural areas)

Sub-area 2 (urban areas)

0.012

0.211

0.353

Sub-area 1 (BSL)

Sub-area 4 (BTL)

0.039

0.404

0.116

It remained significant difference between rural and urban areas at range of 5-10 for the L dn-L 95
value. It seemed that background noise didn’t work when high-speed rail noise events were notprominent. In this case, such difference might be result from the difference in the type of house.
Residential buildings in rural areas were dominated by detached house with single -story windows,
while residential buildings in urban areas were mainly apartments with double glazed windows.
Compared to rural residents, urban residents had more opportunitie s to choose a quiet environment
when closing the windows at home.
3.3

Non-acoustic Factors Affecting Response
In order to find out the factor that affected annoyance of high-speed railway noise, a logistic
regression model was fitted with high annoyance as the dependent variable and various factors

379

displayed in Table 6 as independent variables. The result showed that non-acoustic factor contained
noise sensitivity, health state (whether suffering from heart disease), house satisfaction, satisfaction ofliving environment and attitudes towards high-speed rails. As the levels of the first two factors
increased, the proportion of residents with high annoyance would raise. It indicated that residents
who were sensitive to noise or suffered from heart diseases were more susceptible to high-speed rail
noise. And noise sensitive had the greatest effect on annoyance cause by high-speed rail noise among
non-acoustic factors. Furthermore, with increasing of the last three factors, the percentage of highly
annoyed respondents would reduce. The annoyance caused by high-speed rail noise would bedecreased by improving the satisfaction of living environment and house. And residents who
considered high-speed railway more safety had relatively lower annoyance of high-speed rail noise.
These factors were somewhat consistent with previous research on community response to roadtraffic noise in Vietnam (16). However, the result was different from the research on community
response to Shinkansen noise (19), a second analysis of data from social surveys in Kanagawa andFukuoka. It found that only gender provided a significant effect on noise annoyance among
demographic factors and the responses to living environments had no significant effects on theannoyance reaction.
It should be emphasized was that there might be an interaction between palpitations andannoyance. Not only residents with heart diseases were more annoyed by high-speed rail noise, but
high-speed rail noise could also cause heart palpitations to some extent though this conclusion needs
more support of further research.
Table 6 – Results of logistic regression analysis for general noise annoyance a.
Items

B

Odds radio

95% CI

p

Ldn

0.375

1.455b

1.170-1.810

0.001-0.1550.856

c0.774-0.947

0.003

0.600

d

0.478-0.755

0.000

0.714

d

0.574-0.889

0.003

0.565

d

0.410-0.780

0.001

2.369

d

1.855-3.026

0.000

d

1.169-3.235

0.010

L95
Satisfaction of living environment
House satisfaction
Attitudes towards high-speed rails
Noise sensitivitya-0.510-0.336-0.5700.863

Heart disease

0.665

1.945

Constant

3.454

-

0.092

Dependent variable: high level of noise annoyance, represented by the top three points of the 11 -point
numeric scale; b Increase of risk per 5dBA; c Increase of risk per 1dBA; d Increase of risk per unit scale.

4. CONCLUSIONS
The results from the social survey on community response to high-speed railway noise conducted in
Tianjin provided a broader knowledge on high-speed railway noise situation in China. The
dose-response relationship curve between noise levels and % highly annoyed was established in
Tianjin, China. With the increasing of noise level (L dn), annoyance of high-speed rail noise increased
exponentially. Compared to Japan and France, Chinese residents were more annoyed by high -speed
railway noise at the same equivalent sound pressure levels probably due to different maximum speedof high-speed train. The response to high-speed railway noise of rural residents was significantly more
serious than that of urban residents at the same noise levels, possibly because of the different
background noise level in urban and rural areas. It was also recommended that background noise had
important impact on noise annoyance evaluation of high-speed railway noise. In addition to acoustic
factors, non-acoustic factors such as noise sensitivity, satisfaction of living environment, attitudes
towards high-speed rails, and health status should be considered when evaluating annoyance causedby high-speed railway noise.

ACKNOWLEDGEMENTS
This study was supported by the National Natural Science Foundation of China (Project380

No.51678401). The authors would like to thank every member of Acoustics team at Tianjin University
for conducting noise measurement. We would also like to express our appreciation to each respondent
for completing the questionnaire.

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