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Many cities around the world have claimed that the enforcement of lockdown measures to contain the spread of COVID-19 and the corresponding limitations of human activities led to reduced environmental noise levels. However, noise complaints reported by many local authorities were on the rise soon after the local lockdowns came into force. This research took Greater London in the UK as a case study. The overall aim was examining how noise complaints changed during the first stages of the lockdown implementation, during Spring 2020, both locally and at city scale, and how urban factors may have been influencing them. Noise complaint and urban factor datasets from the Government’s publicly available data warehouse were used. The results show that during the COVID-19 lockdown the number of noise complaints increased by 48%, compared with the same period during Spring 2019. In terms of noise sources, complaints about construction (36%) and neighbourhood (50%) noise showed significant increases. Urban factors, including housing and demographic factors, played a more significant role than the actual noise exposure to road and rail traffic noise, as derived from the London noise maps. In detail, the change rate of noise complaints is higher in areas with higher unemployment rates, more residents with no qualifications, and lower house price. It is expected that this study could help government with allocating resources more effectively and achieve a better urban environment.
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Increases in noise complaints during the COVID-19
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lockdown in Spring 2020: a case study in Greater
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London, UK.
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Huan Tong, Francesco Aletta, Andrew Mitchell, Tin Oberman, Jian Kang
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University College London, The Bartlett, Institute for Environmental Design and Engineering
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Abstract
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Many cities around the world have claimed that the enforcement of lockdown measures to contain
9
the spread of COVID-19 and the corresponding limitations of human activities led to reduced
10
environmental noise levels. However, noise complaints reported by many local authorities were on
11
the rise soon after the local lockdowns came into force. This research took Greater London in the
12
UK as a case study. The overall aim was examining how noise complaints changed during the first
13
stages of the lockdown implementation, during Spring 2020, both locally and at city scale, and
14
how urban factors may have been influencing them. Noise complaint and urban factor datasets
15
from the Government’s publicly available data warehouse were used. The results show that during
16
the COVID-19 lockdown the number of noise complaints increased by 48%, compared with the
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same period during Spring 2019. In terms of noise sources, complaints about construction (36%)
18
and neighbourhood (50%) noise showed significant increases. Urban factors, including housing
19
and demographic factors, played a more significant role than the actual noise exposure to road and
20
rail traffic noise, as derived from the London noise maps. In detail, the change rate of noise
21
complaints is higher in areas with higher unemployment rates, more residents with no qualifications,
22
and lower house price. It is expected that this study could help government with allocating resources
23
more effectively and achieve a better urban environment.
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Keywords: noise complaint; COVID-19; housing factors; demographic factors, transport factors,
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noise level band.
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1. INTRODUCTION
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The coronavirus disease 2019 (COVID-19) was first identified in December 2019 and quickly
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started to affect many regions of the world in the following months. In January 2020, the World
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Health Organization declared the outbreak a Public Health Emergency of International Concern,
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and subsequently escalated it to a pandemic in March 2020 (Brown & Horton, 2020). In order to
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prevent and slow down the spread of the virus, many countries adopted a series of policies and
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actions, which in the most restrictive scenarios were commonly identified as national
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lockdowns.
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In general, lockdown measures involved staying at homerecommendations, social distancing,
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stopping non-essential commercial activities, banning public gatherings, limiting traffic mobility
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and alike. Specifically, the UK Government passed the Health Protection (Coronavirus,
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Restrictions) (England) Regulations 2020, which were put into force at 1:00 pm on 26th March
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2020 (Public Health England, 2020). Under these restrictions, the public were only allowed to
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leave their homes once per day for essential activities and exercise. All offices and shops selling
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non-essential goods were told to close, gatherings of more than two people in public were banned,
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and individuals were advised to only interact with members of their own household. These
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restrictions were set to be reviewed by the Secretary of State at least once every 21 days and
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would continue indefinitely until they were no longer necessary to prevent the spread of infection
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in England. In practice the lockdown continued through the spring of 2020 and was first partially
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eased on 1st of June, with school children in England returning to school, but the broader
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lockdown continued throughout the summer.
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Such measures at global scale were unprecedented and suddenly changed human behaviours and
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communities life around the world, with considerable impacts on society. For instance, from
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psychological perspectives, acute panic, anxiety, obsessive behaviours, paranoia, and depression
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can be produced (Ausín, González-Sanguino, Castellanos & Muñoz, 2021; Dubey, et al., 2020;
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Dzhambov, et al., 2021). The socio-economical condition can also be impacted, where financial
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uncertainty, decrease in income, fear of job loss, and food insecurity are some major challenges
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(Ali, Ahmed & Hassan, 2020; Rasheed, Rizwan, Javed, Sharif & Zaidi, 2021). Yet, in spite of the
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adverse societal and economic implications, the lockdown implementations to contain the
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COVID-19 outbreak led to some improvements in the urban environment, particularly in terms of
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air quality and noise pollution. For instance, In the United States, NO2 levels declined by 25.5%
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during the COVID-19 pandemic compared to historical data, and PM2.5 levels declined in urban
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counties and those instituting early business closures (Berman & Ebisu, 2020). In China, because
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of the lockdown, NO2 emissions dropped by 30%; CO2 emissions decreased by 25% (Dutheil,
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Baker & Navel, 2020). Furthermore, early reports in China show that the improved air quality
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avoided a total of 12,125 NO2 and PM2.5 -related deaths during the lockdown period (Chen, Wang,
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Huang, Kinney & Anastas, 2020).
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Noise pollution followed similar decreasing trends, with environmental noise levels dropping
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particularly in urban contexts, due to the lack of human activities in public spaces and overall
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reduction of traffic volumes. In Paris (France), since the lockdown measures were implemented,
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the noise levels from road traffic reduced by 7.6 dB(A) (Lden) on average, and aircraft noise
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reduced by 21.5 dB(A) (Lden) (Bruitparif, 2020). In Barcelona, the noise pollution levels dropped
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by 9 dB(A) (Lday) after one week of lockdown, and an additional 2dB reduction after two weeks
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was observed (Ajuntament de Barcelona, 2020). In Athens (Greece), noise levels (Lden) reductions
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of up to 6 dB(A) and 8 dB(A) were measured on road networks and in proximity of the Athens
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International Airport, accordingly, as a consequence of the lockdown restrictions (Vogiatzis, et al.,
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2020). In London (UK), an average reduction of 5.4 dB (LAeq) was observed across 11 sampled
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locations by comparing a dataset of noise measurements from Spring 2019 and one from Spring
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2020, during the UK lockdown (Aletta, Oberman, Mitchell, Tong & Kang, 2020).
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The cases mentioned above are just examples: the reduction in environmental noise levels
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observed in these cities is likely to be common also to other urbanized areas of the world, for
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which monitoring data is not yet available. Consequently, one could reasonably expect that since
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there was a reduction in noise pollution levels, the general attitude of the public towards the urban
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acoustic environments would have improved during the lockdown confinements. However,
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focusing merely on the physical acoustic environment rather than how it is experienced and
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perceived by people is a major issue that needs further discussion, for the manifold implications
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that noise annoyance can have on people’s lives. Indeed, focusing on the UK context, soon after
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the national lockdown was implemented on March 26th 2020, reports started to appear in news
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outlets claiming that noise complaints were on the rise in many UK councils (BBC, 2020). The
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underlying reasons seemed to be that since people were spending more time at home to comply
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with lockdown restrictions, they would become more sensitive to neighbourhood-related noise
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sources. Some city councils had to release specific guidance on possible coping strategies and/or
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special “noise advice” (Royal Borough of Greenwich, 2020). An excerpt from the Gateshead
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Council website on the “Neighbour noise advice during the Coronavirus (COVID-19) pandemic”
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page stated:
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A considerable number of people will need to work from home and children will be doing
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school work at home […] that means we will probably be seeing and hearing more of our
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neighbours than we are used to. In some situations, this may lead to frustrations or annoyance
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with noise we do not want to hear. With this in mind, we urge everyone to be considerate of
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their neighbours by thinking about how noise from your home could be causing problems and
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upset to others. For the same reason, we urge everyone to be more tolerant and patient with
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noise and activity that they won't be used to hearing (Gateshead Council, 2020).
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The rationale for this study is ascertaining whether such informal claims were indeed supported by
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noise complaints data, using Greater London as a case study.
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2. AIM AND SCOPE
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Greater London has approximately an 8.9M population and a population density of 64.16/ha.
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There are 32 boroughs divided into Inner London and Outer London (Butler, Hamnett & Ramsden,
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2008). There are three reasons that London is well-suited as a case study: the noise complaint,
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noise level and urban factors datasets are all available in London; the lockdown measures were
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consistent across all London boroughs; and it includes areas with various urban factors (such as
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housing, transport, demographics, and noise sources). In England, reporting noise complaints is
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carried out under environmental legislation and managed by the local authority. This noise
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complaint dataset can provide a basis for the government decision-making. In this context, if
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residents have a problem with noise, they can report through service hotlines, websites, or
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in-person to the local council, which can then seek to address this problem.
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Noise complaints typically dominate the amount of environment-related complaints that local
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authorities have to deal with (Kang, 2006). The topic has received increased research attention
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across several disciplines, such as psychology, sociology, and urban studies (Kang & Aletta, 2018;
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Tong & Kang, 2020). For instance, Nieuwenhuis et al. (2013) examined negative relationships
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between neighbours and proposed that property ownership is not correlated to neighbour conflicts,
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involving noise annoyance complaints. Legewie and Schaeffer (2016) examining 311 noise
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complaints datasets in New York City, found that ethno-racial diversity is positively associated
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with the number of complaint calls. Hong, Kim and Widener (2019) created heat maps using a
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kernel density estimation to examine clustering patterns of the major construction and noise
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complaints. This study found that construction activities were associated with higher volumes of
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noise complaints. The results suggest that a one-unit increase in construction activity was
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associated with an approximately 6% higher incidence rate of noise complaints. Tong and Kang
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(2020, 2021a) investigated the effects of urban development patterns and socio-economic factors on
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noise complaints across different local authorities in England. The results suggested that the rate of
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noise complaints is generally significantly related to urban morphology, road network, demographic,
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and housing factors. The rate of noise complaints is always higher in large, centralised or compact
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cities. Specifically, the noise complaint rates are positively related to population density, primary
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road density, and unemployment rates, but negatively related to mean age and average number of
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cars owned. For housing factors, noise complaint has a negative relationship with home ownership,
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while it has a positive relationship with the percentage of rented homes.
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Noise complaints depend on individual attitudes, perceptions, and objective noise levels (Hong,
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Kim & Widener, 2019; Public Health England, 2018). It seems apparent that the amount of noise
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complaints would be related to noise level, particularly road traffic and rail sources. However, the
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perception of noise and the act of filing a complaint might also be affected by a number of urban
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planning parameters involving demographic, transport, housing factors. For instance, the road
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network is the main source of noise, primarily affecting the sound pressure level, which can be
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characterised through urban planning factors such as road density and the mode for commuting
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(Calixto, Diniz & Zannin, 2003; Tong & Kang, 2020). Secondly, the influence of demographic
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factors such as population density, age, occupation, education level, and health states on sound
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evaluation have been broadly studied (Aletta, et al., 2018; Licitra et al., 2016; Miedema & Vos,
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1999; Rey et al., 2018; Yu & Kang 2008). Finally, housing factors such as price, housing size,
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house type, and ownership have been proved to have a relation to the sound environment and
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evaluation (Fields, 1993; Tong & Kang, 2021a). However, the changing patterns of noise
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complaints during the lockdown and the effect of such urban factors have not been investigated in
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detail yet.
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The aim of this study is to examine how noise complaints changed during the first stages of the
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lockdown implementation during Spring 2020, both locally and at city scale, and how urban
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factors, including housing, demographic, transport, and traffic noise level band, may have been
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influencing them. More specifically, the research questions are:
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(1) How did the noise complaints received by local authorities in London change because of
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the lockdown measures?
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(2) Did this change in noise complaints during the lockdown vary depending on the noise
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complaint type (i.e., categories of noise sources)?
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(3) To what degree are these changes mediated by other factors related to urban and
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socio-economic characteristics of the local environment, including housing, demographic,
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transport, and traffic noise level band?
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For this purpose, a case study in Greater London was considered. Noise complaint datasets were
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requested from London’s Borough Councils for the years 2019 and 2020 in order to compare the
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noise complaints received during the lockdown in Spring 2020 and the noise complaints received
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during the same period from the previous year.
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3. METHODS
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3.1. London noise complaint dataset
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The noise complaint dataset was applied for from the local Borough authorities under the Freedom
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of Information Act 2000 (FOI), which provides public access to information held by public
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authorities (UK Government, 2000). As of the 16th of July 2020, noise complaint datasets from 24
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boroughs were received by the researchers: 22 datasets without missing data or a crucial missing
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field (e.g. date) were used for this analysis. The data includes received date, complaint type, and
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location information for the single complaint record. The geographic location information of noise
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complaints is based on the coordinate points, postcode, or ward, depending on the reporting
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policies of the various boroughs. Amongst them, ward level was selected to get the same level of
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geographic labelling across all of the provided data (i.e., if postcode and coordinate points
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information were available, these were assigned to the corresponding ward) (Figure S1 in the
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Supplementary File). Wards are the administrative level below boroughs, which are the local
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government areas within Greater London (Figure 1).
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Figure 1. Borough and ward boundary in London
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The datasets received from some local authorities include other environmental complaints in
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addition to noise complaints. These include complaints related to odours, anti-social behaviours,
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dust, etc. These complaints were identified based on the type label and were excluded from this
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analysis in order to focus solely on noise complaints.
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The classification for the “type of noise complaint” was not consistent among the London
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boroughs: some would use multiple-answer options with pre-defined categories, others a free-text
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field for users to fill; thus, a further categorization step was necessary to handle the complaints
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type variable in a meaningful way. From the original database, a set of 484 unique labels used to
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characterize the type of noise complaint was extracted. These were then manually screened and
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sorted into 4 categories: Industry (36 labels), Construction (29 labels), Neighbourhood (373
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labels), and Undefined (46 labels) (Table S1 in the Supplementary Files). The rationale for
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clustering the labels in this way was being aligned as much as possible with the World Health
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Organization categorization for community noise, defined as “noise emitted from all sources
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except noise at the industrial workplace […] including: road, rail and air traffic, industries (i.e.,
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“Industry” label in this study), construction and public work (i.e., “Construction” label in this
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study), and the neighbourhood (i.e., “Neighbourhood” label in this study). […] Typical
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neighbourhood noise comes from premises and installations related to the catering trade
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(restaurant, cafeterias, discotheques, etc.); from live or recorded music; sport events including
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motor sports; playgrounds; car parks; and domestic animals such as barking dogs” (World Health
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Organization, 1999). So the first category would essentially cover transportation and industries;
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the second category have a connotation of “public” works, as opposed to construction noise from a
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neighbour’s flat for instance ( as that would fall into the following category); the third category is
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possibly the broadest in scope, yet, from the perspective of the person complaining, the main
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difference between category 1-2 and category 3 is whether the complaint is directed towards an
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“infrastructural element” (for which local authority is accountable most likely) or towards a
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clearly identifiable person/group/premises generating the noise (thus the conflict is between to
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private subjects). The fourth category (“Undefined”) does not indicate missing data, but rather
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lack of clear category, as sometimes the labels in the database did not allow classification (e.g.
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“other noise”; “noise”; or alike). Unique labels for the noise complaints with the category to which
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they were assigned were presented in Table S2 in the Supplementary Files.
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3.2. The Spring 2020 Lockdown period
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For the purpose of analysing the data, it was decided to compare the same period of the year in
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2019 and 2020; that is: 27th March 2019-31st May 2019 (Spring 2019), and 27th March 2020-31st
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May 2020 (Spring 2020), the latter capturing the start and development of the UK lockdown
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period. This resulted in 43,186 complaints being analysed. Only for the analysis of the temporal
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variations in noise complaints, the periods considered range from 1st January to 31st May, both in
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2019 and 2020, because of the need to detect potentially sudden changes (i.e., transitioning from a
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non-lockdown to a lockdown scenario).
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3.3. Urban factors
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To explore affecting urban factors causing the difference in noise complaints changing among
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London boroughs, housing, demographics, transport, and traffic noise level bands were discussed.
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Generally, (high) noise levels are expected to lead to increased noise complaints in any given area,
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therefore the possible influences of the exposure to road and rail traffic noise sources on the noise
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complaints change rate were explored. To test this, Lden (day-evening-night sound level) values
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were extracted at a ward level from the noise pollution datasets obtained from the Department of
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Environment, Food and Rural Affairs (2018) for Greater London. The two indicators, namely road
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Lden and rail Lden, were selected as they are the main parameters represented in noise maps
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(Figures S2&S3 in the Supplementary File). Using ArcGIS 10.3, Lden data at ward level was
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extracted and each ward was assigned a rank (0 5) automatically based on the percentage of its
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area covered by a certain noise level band (split by 5 dB). Amongst 383 wards covered by noise
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complaint data, 373 wards were covered by the road Lden data and 295 were covered by the rail
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Lden data. They received ranks from 0 to 2 for road and from 0 to 1 for rail noise, with rank 0
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representing a ward ranked to a noise level band below 55 dB(A), and rank 2 representing a ward
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ranked in the noise level band of 60-64.9 dB(A) (Figures S4&S5 in the Supplementary File). For
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instance, the ward of Barnsbury in the borough of Islington features a total area of 83 ha, with 7.1
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ha (8.5%) of which is covered by data modelled for road Lden above 55 dB(A). The amount of area
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covered by each noise level band in Barnsbury is as follows: 3% in the 55-59.9 dB(A), 1.6% in the
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60-64.9 dB(A), 1% in the 65-69.9 dB(A), 1.9% in the 70-74.9 dB(A), 1% in the area covered by
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the noise level band above 75 dB(A) and 91.5% of the area left uncovered by any noise level band,
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meaning the Lden exposure was modelled below 55 dB(A) for the most of the ward’s footprint.
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Therefore, Barnsbury was assigned the rank of 0 for road noise.
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In addition, according to previous studies, the decrease in noise levels during the enforcement of
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lockdown measures varies in different types of areas (Aletta, Oberman, Mitchell, Tong & Kang,
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2020). However, the noise complaint or perception might be also affected by other factors like a
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number of urban planning parameters involving housing, demographic, and transport factors as
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mentioned in the introduction. Apart from considering factors mentioned above, the data
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availability is also considered when selecting the urban planning parameters. London Ward Profile
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is the main data source used, downloaded from the London Datastore (Greater London Authority,
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2015). In this dataset, all the indicators have been aggregated to the ward level. For instance, the
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mean age is the average age for all residents in the ward; ‘cars per household’ means the average
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number of cars per household in the Ward. Meanwhile, in this dataset, the tax band codes from A
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to H, were categorised into three groups (A or B; C, D or E; F, G or H) by Department for
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Communities and Local Government and indicate the tax rate from lowest to highest (UK
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Government, 2020). Finally, 18 indicators were selected and grouped into four categories -
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housing, demographics, transport, and noise level bands (detailed parameters are in Table 1).
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It is worth noting that some urban factors show significant inter-correlations. Significant
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correlations exist both within and between categories, such as between qualification and
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household income. This multicollinearity should be paid attention to when building and selecting a
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regression model. However, as this study focuses on the correlation between each individual urban
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factor and noise complaints, rather than the inter-relationship between the factors this is not
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considered a primary concern. The coefficient values given are the Spearman correlation strength
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between noise complaint change rate and each individual urban factor.
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3.4. Statistical analysis
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In order to characterise how the noise complaints changed across the boroughs and wards
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investigated, the rate by which noise complaints changed from Spring 2019 to Spring 2020 was
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calculated. The equation for this change rate is shown as follows:
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R=(NSpring 2020 - NSpring 2019)/NSpring 2019*100 (1)
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where R is the change rate of noise complaints in percentage; NSpring 2019 is total number of
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noise complaints during spring 2019; NSpring 2020 is total number of noise complaints during spring
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2020. The results return to positive and negative values. Negative values mean the number of
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noise complaints decreased, while the positive values mean increase (Kenton & Mansa, 2020).
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The change rate of noise complaints in three wards were extremely high and identified as outliers,
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namely Gospel Oak and Highgate in the borough of Camden and Heathfield Ward in the London
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borough of Richmond upon Thames. These were considered outliers due to their very low number
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of noise complaints in Spring 2019 (which may itself be an anomaly for year-over-year numbers
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in that borough), meaning a relatively small increase in absolute numbers of complaints results in
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a very high percentage change. They were not considered in further analyses.
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The variables in this study are not normally distributed, according to the Shapiro-Wilk test
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(Ghasemi & Zahediasl, 2012; Yap & Sim, 2011). Therefore, Spearman's rho, as a nonparametric
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test which does not assume normal distributions (Hauke & Kossowski, 2011), was applied to
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measure the correlations between the urban factors and noise complaints. This process was
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conducted using SPSS software (version 25) (Landau & Everitt, 2003). The correlation analysis
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was conducted at ward level, as all indicators are available at ward level (Kendall's Tau was also
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examined. The results were similar to Spearman correlation and those are presented in Table S3 in
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the Supplementary File). Meanwhile, the Mann-Whitney U test, as a non-parametric test, was used
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to compare differences in the number of noise complaints between Spring 2020 and Spring 2019
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for each borough and source breakdown individually.
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In order to further investigate how the factors interact with each other as well as with the noise
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complaint outcome, a Random Forest (RF) regression model was built, which can better handle
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multicollinearity and non-linear relationships than multivariate linear regression. As a widely used
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ensemble learning method, the core idea of this model is to construct a series of decision trees to
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obtain scores of variable (urban factors) importance in determining the dependent variable (noise
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complaints). The higher the score, the more important the indicator is, and vice versa. Only the
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variables with significant Spearman correlation coefficients were included for analysis. The whole
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process was implemented using the sci-kit learn 0.19.1 in Python 3.7.0 (Pedregosa, et al., 2011).
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4. RESULTS
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During the Spring 2020 lockdown period (27th March 31st May), local authorities experienced a
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significant increase of noise complaints compared to the same time period in the previous year
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(p<0.001 via Mann-Whitney U test). In total during the lockdown, there were 25,740 noise
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complaints reported, with approximately 4.29 complaints per 1,000 people. During the same
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period in 2019, there were 17,446 and 2.97, respectively.
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To investigate the effects of the containment measures on the amount of noise complaints received,
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the time series of total daily noise complaints for the first half-year of 2019 and 2020 is shown in
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Figure 2. To better demonstrate the general trends, a seven-day rolling average window is applied,
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accounting for observed weekly patterns in received noise complaints. In general, 2019 exhibits a
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relatively stationary pattern with small fluctuations above and below 250 daily noise complaints,
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showing no clear increasing or decreasing pattern during this period. Likewise, the pre-lockdown
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period of 2020 also exhibits a stationary trend with fluctuations around 250 daily noise complaints.
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However, shortly after the imposition of a national lockdown on 26th of March, there is a marked
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increase of the 2020 trend. Within two weeks the number of daily noise complaints has nearly
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doubled compared to the same time period in 2019 and continues to grow throughout the
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lockdown period.
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Figure 2 Time series of the number of noise complaints in the first half year in 2019 and 2020. A
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7-day rolling average window is applied to account for weekly patterns in noise complaint
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reporting.
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In the month before the start of the lockdown, local authorities received an average of 282 new
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complaints per day and 8,454 individual noise complaints in total. In the first month after the start
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of the lockdown, these numbers had increased significantly with 402 new cases every day and
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12,071 reports in total, representing an increase of 42.55% for the whole of London. For the
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second month since enforcing lockdown, this rate of increase began to slow, with local authorities
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receiving 442 reports per day, an increase of 10% compared to the first month.
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4.1. Variations in noise complaints at borough level
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To explore more characteristics of the variation in noise complaints due to the implementation of
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lockdown measures among boroughs, the spatial distribution of the change rate of noise
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complaints during the lockdown compared with Spring 2019 was mapped, as shown in Figure 3
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and Figure 4. This figure shows the change rate of noise complaints between Spring 2020 and
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Spring 2019, by borough. In 21 of the 22 boroughs for which data of noise complaint numbers
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were available, the rate of complaints increased during the lockdown. The increases were
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significant in 15 of the 21 boroughs (the details were shown in Table S4 in the Supplementary
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File). Contrary to the rest of the boroughs, Barnet experienced a decrease (-20.92%) in noise
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complaints during the lockdown period.
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On the other hand, Haringey, which is adjacent to Barnet, has the highest increase in noise
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complaints (+175.36%), followed by Barking and Dagenham (+104.2%), Hounslow (+84.46%),
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and Bexley (+84.32%), all located in Outer London. Apart from Barnet, the lowest change rate
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was observed in Waltham Forest (+6.31%), followed by Kensington and Chelsea (+11.23%),
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Greenwich (+15.59%), and Croydon (+18.08%). The change rate was substantially lower across
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Inner London (+38.67%) compared to Outer London (+66.37%). Indeed, the difference in change
335
rate is also more dramatic for the first month of the lockdown. Overall, it can be observed that the
336
number of noise complaints increased significantly after the lockdown measures were
337
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implemented and the change rate of noise complaints was distributed unevenly across London.
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Figure 3 Change rate of noise complaints by boroughs
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* Difference is significant at the 0.05 level as per the Mann-Whitney U test
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** Difference is significant at the 0.01 level as per the Mann-Whitney U test
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Figure 4 Differences in the number of noise complaints between Spring 2019 and Spring 2020 by
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borough.
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4.2. Variation by types of noise complaints
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15
In order to further investigate the driving factors in the general increase in noise complaints during
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the lockdown period, the data are analysed according to the type of noise complaint. Figure 5
348
shows the number of complaints received during the lockdown period and the same period in 2019,
349
across all boroughs, for the four types of noise source (Industry, Construction, Neighbourhood,
350
and Undefined). These categories were aggregated from the various tags provided by the borough
351
data, as described in Section 2.1.
352
The most common noise complaints category in both 2020 and 2019 is Neighbourhood, followed
353
by Undefined, then Construction and Industry. Interestingly, in this last category, which includes
354
transportation noise, complaints remained at approximately the same level with only a slight
355
decrease (ca. -9%), despite road traffic and other noise-generating industrial activities being
356
dramatically reduced during the lockdown. Indeed, the decrease in Industry noise complaints did
357
not show significance (p=0.126). All other categories reported significant increases: Construction
358
(+36%), Neighbourhood +50%, Undefined +59% (p values<0.001 via Mann-Whitney U test).
359
360
** Difference is significant at the 0.01 level as per the Mann-Whitney U test. Figure 5 Differences in the number of
361
noise complaints between Spring 2019 and Spring 2020 by Noise source category
362
4.3. The effect of urban factors on noise complaint increase
363
From the previous results (Figure 2), it can be concluded that the change rate of noise complaints
364
varies across Greater London. Hence, urban planning factors such as housing, demographic,
365
transport, and traffic noise level bands may be contributing factors to this variation. The Spearman
366
16
correlation coefficients between these urban planning factors and the change rate across wards are
367
shown in Table 1. Regarding housing factors, several significant relationships are revealed with
368
noise complaints. Median house price and median household income, which reflect the economic
369
status of the family, are negatively related to the change rate of noise complaints, with coefficient
370
values of -0.108 and -0.140, respectively. This result means that the number of noise complaints in
371
rich areas had increased less since the lockdown was enforced. As for property ownership, the
372
change rate of noise complaints was positively related to the percentage of households that social
373
rented. For instance, the noise complaints in Westbourne ward with a relatively high social rented
374
housing rate (48.5%) has increased by 118%. Secondly, for the dwelling in council tax bands,
375
bands C, D or E had positive relationships with noise complaints, while F, G or H were negatively
376
related. No significant difference was found for bands A or B. For instance, In Kilburn ward,
377
where 55.5% of houses are in council tax band C, D or E, while 8.1% are in F, G or H, the change
378
rate of noise complaints is 125%. Therefore, the results of dwellings in council tax bands further
379
support, as previously mentioned, that noise complaints from residents living in expensive housing
380
had increased less during the lockdown period. In a word, the noise complaints increased less in
381
areas with a higher proportion of expensive houses.
382
Table 1 Spearman correlation coefficients between the change rate of noise complaints and urban
383
planning factors
384
Factors
Indicators
Housing
Median House Price (£)
Median Household income estimate
% Households Owned
% Households Social Rented
% Households Private Rented
% dwellings in council tax bands A or B
% dwellings in council tax bands C, D or E
% dwellings in council tax bands F, G or H
Demographic
Population density
Mean Age
Unemployment rate
% with no qualifications
Life Expectancy
Subjective well-being average score
Transport
Road density
Cars per household
Average Public Transport Accessibility score
% travel by bicycle to work
Noise level band
Road Lden rank
Rail Lden rank
% in the highest noise level band (road Lden≥75dBA)
% in the highest noise level band (rail Lden≥75dBA)
17
* Correlation is significant at the 0.05 level.
385
** Correlation is significant at the 0.01 level.
386
In terms of demographic factors, no significant relationships were found with population density,
387
mean age, or subjective well-being average score. The change rate of noise complaints was
388
positively related to unemployment rate, and the percentage of residents with no qualifications. In
389
contrast, it is negatively related to life expectancy. For transport factors, no significant
390
relationships were found with road density, cars per household, and average public transport
391
accessibility score. Noise complaints were positively correlated with the percentage of residents
392
who travel by bicycle to work.
393
In particular, it seems fair to assume that actual noise exposure should be an important factor
394
causing noise complaints and negative noise perception; however, significant correlation
395
(ρ=-0.114, p=0.05) was observed only between the noise complaint growth rate and road Lden
396
noise level band. No statistically significant correlations were observed between the other data
397
derived from noise level bands and complaints (Table 1). Furthermore, Figure 6 shows that the
398
median value of the complaint change rate does not increase with the noise rank, i.e. the median
399
value of the noise complaint change rate for wards ranked in the noise level band Lden 55-59.9
400
dB(A) (rank 1) is the lowest. The noise complaints have increased significantly during the
401
lockdown unrelated to whether an area is quiet or noisy, to some extent. These findings also
402
reinforce the results discussed above, which shows no relationship between noise from road and
403
noise complaints.
404
405
Figure 6 Boxplots showing the change rate of noise complaints (in percentage) per noise level
406
band ranks for road Lden (left) and rail Lden (right). For the purpose of this study, noise level band
407
ranks were defined at ward level as follows: 0 ≤54.9 dB(A), 1=55-59.9 dB(A), 2=60-64.9 dB(A).
408
18
Apart from the correlation analysis, multivariate regression analysis between noise complaints and
409
urban factors was also conducted. Comparing with multivariate linear regression, the RF has better
410
performance with a mean absolute error value of 0.8, suggesting the regressions are non-linear.
411
Correspondingly the variable importance to determine the contribution of urban factors to noise
412
complaints was identified using RF models. The results are presented in Table S5 as a
413
Supplementary File. the results suggest that the percentage of households social rented and the
414
percentage of residents who travel by bicycle to work contribute more in determining noise
415
complaint change rate, followed by unemployment rate and the percentage of residents with no
416
qualifications. Such findings can help the government organisations to prioritise resources for
417
dealing with noise complaint issues from the urban factors, and to informing more effective noise
418
management strategies.
419
5. DISCUSSION
420
This study investigated the variation of noise complaints in London during the COVID-19
421
lockdown period and tried to explore affecting factors causing the difference in noise complaints
422
changing across London boroughs. Having so many people staying home because of the
423
lockdown-related restrictions created unprecedented scenarios and forced people to adjust to their
424
new surrounding (indoor) acoustic environment, raising questions on how they relate to it and to its
425
sound sources (e.g., neighbours, construction noise, etc.). Recent literature on the topic is
426
identifying some emerging trends. Lee and Jeong (2021) conducted an online survey about noise
427
annoyance in London in May 2020, with 183 participants, before the lockdown eased. They
428
reported that neighbour noise was more annoying than outdoor noises during the lockdown,
429
suggesting that this type of noise source is more problematic than other typical sources of
430
community noise, when considered in the context of an enforced “stay home” policy. This brought
431
other researchers to question what the positive role of indoor soundscape could be to promote
432
well-being in times of social distancing (Andargie, Touchie & O’Brien, 2021; Dzhambov, et al.,
433
2021).
434
5.1. Changes in noise complaints by numbers, types and affecting factors
435
19
5.1.1 The number of noise complaints increase during lockdown
436
Overall, it can be observed that the number of noise complaints increased significantly after the
437
lockdown measures were implemented, indicating that residents have been more annoyed with
438
noise during the lockdown, hence the negative impact on psychology well-being could be more
439
serious. This impact is not one-directional the Covid-19 pandemic has caused a crucial effect
440
psychologically, such as anxiety, depression, and annoyance as mentioned in the introduction. In
441
turn, these negative psychological states could make residents more annoyed with noise and trigger
442
them to report a noise complaint. On the other hand, during lockdown, more family members could
443
stay in the house, hence more noise could be produced, particularly with children kept at home due
444
to school closures. These results are in line with a previous study, where Miedema and Vos (1999)
445
suggested that residents living in a large family are more annoyed by noise than residents living
446
alone. However, during the lockdown period, noise-inducing human activities reduced dramatically,
447
as did the traffic volumes. Therefore, the urban environmental noise levels decreased in several
448
cities worldwide, as reported by studies on environmental noise levels during the COVID-19
449
lockdowns which show decreases in the 5-15 dB range (Arenas, 2020; Aletta, Oberman, Mitchell,
450
Tong & Kang, 2020; Asensio, Pavón & de Arcas, 2020; Bartalucci, Borchi & Carfagni, 2020).
451
Thus, combining these results with the previous research, it can be pointed out that, noise
452
complaints are not only driven by noise events, there should be other factors impacting the noise
453
complaints/perception.
454
The 2020 lockdown has sparked further discussion on future patterns of people working from home
455
for a higher percentage of time. The results of this study indicate that large proportions of the
456
population permanently working from home could result in a considerable and lasting increase in
457
noise disturbance, even as urban noise levels decrease. In new dwelling developments, sound
458
insulation is more important and need to be increased, such as soundproof window and materials.
459
However, it is unclear to what extent this effect would remain under a non-lockdown scenario when
460
people have more options for managing and changing their environment.
461
5.1.2 Results from type of noise complaints
462
The increase in absolute numbers of complaints across London by type shows patterns that are
463
20
expected when considering the experiences of people spending more time at home. The results
464
seem to confirm that neighbourhood noise is the main trigger for complaints and the one that
465
witnessed a dramatic increase during lockdown. This could be a direct consequence of people
466
spending more time at home, thus being exposed to noises they would not normally experience if
467
they were at the workplace. It is also likely that Neighbourhood noise sources are perceived as
468
being closer and/or more easily identifiable (e.g., a neighbour, a domestic animal, catering
469
premises, etc.), so that a complaint would be meaningful, as from the perspective of the person
470
complaining it would be easier for a local authority to enforce compliance (compared, for instance,
471
with road traffic noise from a highway). Indeed, neighbourhood is the most common noise
472
complaints category in both 2020 and 2019. This result is in line with Tong and Kang (2021b):
473
they found the proportion of residential/neighbourhood noise complaints was approximately 50%
474
in New York City.
475
Construction noise complaints, which here include public works or perceived-to-be public works
476
(i.e., excluding DIY and small construction/refurbishment noises coming from neighbouring flats),
477
show a significant increase. The construction industry did not fully stop during the lockdown
478
measures as UK Government policy was to assimilate it to critical activities” and prioritize its
479
re-start (Mayor of London, 2020). So, in a relatively quieter background noise (less traffic, fewer
480
people on the streets, etc.) it is likely that construction noises became more salient also because of
481
their spectral and temporal features (e.g., very different sound sources, unsteady, often impulsive
482
noises, etc.).
483
In the Industry category (which included transportation noise sources) the slight, and possibly
484
negligible decrease, in noise complaints contrasts with considerable decreases in traffic noise
485
levels seen in other studies. In new dwelling developments, sound insulation is more important
486
and need to be increased, such as soundproof window and materials. The lack of an observable
487
impact of the lockdown measures and the low absolute numbers of transportation-related noise
488
complaints compared to other categories, indicates that traffic noise is not a major driver of
489
community noise complaints, when considering aggregated data at ward level or higher. This is
490
further confirmed by the lack of any relationship between the relative level of traffic noise within a
491
21
ward (as derived from the DEFRA noise map) and the change rate of noise complaints. However,
492
this does not necessarily indicate a complete decoupling between traffic noise levels and
493
complaints. It may be that transportation-related complaints are driven by cases and locations of
494
extremely disturbing traffic noise (e.g., only at major intersections and exposure to major
495
motorways). Aletta, Oberman, Mitchell, Tong, and Kang (2020) showed that traffic-dominated
496
locations in London (Camden Town and Euston Road intersection) experienced only a limited
497
decrease in noise levels (4.5 dB, LAeq) during the lockdown period, which may not be enough to
498
drive a noticeable decrease in noise complaints.
499
5.1.3 The effect of urban planning factors on noise complaint increase
500
By examining potential affecting factors on the change of noise complaints, (high) noise levels are
501
expected to lead to increased noise complaints in any given area. However, the noise level (as
502
characterised by noise bands derived from noise maps) did not show significant correlations with
503
change rate of noise complaints. Especially, according to Aletta, Oberman, Mitchell, Tong and
504
Kang (2020) during the lockdown, it is highly likely that the road Lden values across Greater London
505
were lower than presented in the noise maps. The observed lack of correlation between the increase
506
in noise complaints and the noise ranks assigned to wards could be explained by hypothesising that
507
noise complaints are driven more by single noise events than the overall levels represented by Lden.
508
Furthermore, housing factors show a significant relationship with noise complaints. The result that
509
noise complaints increased less in the area with expensive houses could be explained that the
510
expensive houses could have more bedrooms and yards. Hence, the residents are able to choose a
511
quiet room to stay and the green space in the yard could reduce noise annoyance (Bodin, Björk,
512
Ardö & Albin, 2015). As for property ownership, in this study, the change rate of noise complaints
513
was positively related to the percentage of households that social rented. This result contradicts
514
Nieuwenhuis et al. (2013), who proposed that ownership is not correlated to neighbour complaints.
515
However, it is supported by other previous studies. For instance, Gillen and Levesque (1994)
516
suggested complaint probabilities appear to be higher in the areas with high tenancy rate. Michaud
517
et al.(2016) also indicated that ownership can contribute to differences in high noise annoyance.
518
Indeed, housing policy and target are a key difference between Inner and Outer London (Butler,
519
22
Hamnett & Ramsden, 2008). For instance, density of dwellings in outer London is lower than in
520
inner London (the detailed density of dwellings was shown in Table S6 in the Supplementary File).
521
These results could support the finding that the change rate of noise complaints was distributed
522
unevenly in London; in detail, the four boroughs with the highest change rates were located in
523
Outer London area. This difference could be correlated with the base value before the lockdown.
524
Boroughs in inner London have relatively high number of noise complaints in Spring 2019, which
525
means an increase in absolute numbers of complaints results in a relatively low percentage change.
526
In addition, the high complaint levels of Inner London in 2019 could be explained by the density
527
and diversity. Legewie and Schaeffer (2016) found that residents living between racial enclaves
528
tend to complain more about noise than those who live within clearly defined racial boundaries.
529
Nieuwenhuis et al. (2013) also indicated religious diversity lead to a higher likelihood for negative
530
relationships between neighbours. In addition, during normal periods, high density areas have
531
more noise complaints or higher noise annoyance level (Liu et al., 2019; Zheng et al., 2014).
532
Compared with previous study findings, we found that the effect of several urban planning factors
533
on change rate of noise complaints during lockdown is different from its effect on noise
534
complaint/annoyance at normal times. For instance, normally, population density and road density
535
have strong positive correlations with the rate of noise complaints (Tong & Kang, 2020). While
536
population density didn’t prove to be a significant factor, another explanation behind this
537
phenomenon might simply be the number of residents who were spending more of their time in their
538
homes during the lockdown, as Outer London has higher population than the Inner. In terms of the
539
positive correlations between noise complaints and the percentage of residents who travel by
540
bicycle to work, it could be explained that cyclists are especially strongly exposed to noise in
541
urban environments, particularly because of their proximity to road traffic (Jérémy & Apparicio,
542
2019). To some extent, this finding is consistent with Tong and Kang (2020), where they found
543
that cities/regions with higher percentages of residents taking energy-efficient transport modes to
544
work tend to have more noise complaints. From a demographic perspective, the positive
545
relationships between residents with no qualification and the change rate of noise complaint rate is
546
supported by Gillen and Levesque (1994), who found that areas with high education level are less
547
likely to exhibit complaint activity. Indeed, the results from the housing and demographic factors
548
23
are consistent; higher unemployment rate and low qualification are always related to low quality
549
of house and income. All these factors are likely to increase the change rate of noise complaints.
550
This finding is also in line with previous studies; in normal time, cities/regions with higher
551
unemployment rates are also likely to receive more noise complaints (Tong & Kang, 2021a).
552
Overall, it can be concluded that in such extraordinary circumstances, such as a nation-wide
553
lockdown, contextual urban factors proved to be more significant for the increase in noise
554
complaints than the actual noise exposure to road and rail traffic noise. Even though the noise level
555
decreased during lockdown, the number of noise complaints increased significantly. It is expected
556
that the findings can inform policymakers from the perspective of acoustic impacts and urban
557
factors, allocating resources more effectively and leading to noise management strategies during the
558
lockdown. For instance, a number of actions have been carried out to prevent noise pollution from
559
road noise, such as noise barriers and noise level limitations for trucks. However, from the finding of
560
housing factors impacting on noise complaints, the noise abatement for housing which focus on
561
more than road noise and simultaneously prevent transfer from out-to-in could be paid more
562
attention, such as the use of sustainable sound absorbing material. During the lockdown, the house
563
is the main place where residents live, work and sleep, and it appears that increased working from
564
home will continue to be a trend in the future. Therefore, the home environment will likely play an
565
increasingly important role in human wellbeing. From previous studies, green spaces have been
566
proven to have relationships with noise perception, applying an absorption or scattering effect on
567
noise propagation and influencing individual perception of noise (Hao, Kang & Krijnders, 2015;
568
Margaritis & Kang, 2017). From an urban planning perspective, the accessibility and visibility of
569
green space from houses could be emphasised, such as utilising fragmented parks/yards.
570
5.2. Limitations of the study
571
The first aspect to consider is certainly related to the noise complaints dataset. The goal was to
572
provide an overview for the Greater London area, by aggregating data from its boroughs since they
573
are the local authorities responsible for handling such complaints. However, there could be some
574
inconsistencies and/or deviations due to how single boroughs gather and process noise complaints
575
records. For instance, sudden peaks or lows in numbers of complaints may be due to how easy (or
576
24
difficult) it is to approach the local authority (e.g., via an app, a dedicated telephone line, etc.). The
577
pandemic itself is likely to have affected the borough environmental departments’ operations and
578
ability to react to complaints (e.g., reduced staffing, increased remote working, etc.). Taking the
579
Borough of Barnet as an example, where a 21% decrease in noise complaints rate was observed
580
between 2019 and 2020, the information provided on its website states that during the lockdown
581
The council will continue to run a Noise Line Service, but with a reduced response capacity. You
582
can still call to report ongoing noise by calling [telephone number] (Barnet Council, 2021).
583
Information is not explicitly available on this matter for all boroughs, but it is fair to assume similar
584
circumstances apply. On the other hand, in boroughs where particularly high increase rates were
585
observed, it could be that complaints could be filed via different channels (thus streamlining the
586
process for the user), like in the case of Haringey, which accepted complaints both online and via
587
telephone (Haringey Council, 2021; Havering Council, 2021). While this is certainly a possible
588
limitation, we consider that, in the aggregate, such issues are averaged out and the trends are
589
observed are still representative of the 2019-2020 variations.
590
Related to this, is the fact that this analysis is based on a comparison to only one year of past data. It
591
is therefore potentially impacted by anomalous or random fluctuations in the noise complaints
592
received during the investigated period in 2019. This, as well as year-to-year changes in boroughs
593
complaint collection methods, could be addressed in future studies by comparing to an average of
594
multiple years of previous noise complaint data. This issue is also common to other studies being
595
conducted on similar topics, but different context. For instance, Yildirim and Arefi (2021) compared
596
the noise complaints in Dallas (USA) after the COVID-19 outbreak, from March to December
597
2020 and the same period in 2019. The authors in this case surprisingly observed reduced noise
598
complaints during the COVID-19 period by about 14% compared to the pre-COVID-19 period. It
599
seems reasonable to assume that there could be a lag to the effect that lockdown policies have on
600
noise complaints, and this lag time can be difficult to distinguish from normal levels of
601
week-to-week variations. In the Dallas case, it appears there was not enough time for the lockdown
602
effect to show up, at least when compared to 2019 levels alone, before regulations were changing
603
again. Thus, it is generally difficult to observe these patterns with such recent data, yet it is worth to
604
extract preliminary information to inform possible future policies.
605
25
The analysis is of course affected by the categorization of noise complaints performed in Section
606
2.1. While we tried to adhere to the framework provided by the World Health Organization about
607
community noise to define the categories in this study, we still have the Undefined category
608
showing the highest increase proportionally, and, in absolute numbers, being larger than two other
609
categories (i.e., Industry and Construction). During the categorization it was not possible to
610
allocate these items with certainty to any other category; many occurrences refer to complaints
611
where the type was inputted manually as a free-text by the complainant and the label was too
612
generic (e.g., “noise” or “other noise”). Following a statistical approach, we could allocate the
613
Undefined complaints either proportionally or evenly to the remaining three categories. In both
614
cases, this would not change the patterns we have observed, so we consider it to be a minor
615
methodological limitation.
616
For the other data types (i.e., non-noise complaint data), this study only considered basic housing,
617
demographic, and transportation factors. Therefore, if datasets are available. more indicators could
618
be explored. In addition, the sampling strategy at the ward level resulted in the low effect of the
619
highest noise level bands on the analyses as most of the wards were ranked in the low bands. The
620
ward area covered in the noise level band above 75 dBA is typically below 1% and the ward
621
coverage of the noise map data (above 55 dBA) for road Lden is typically below 50% and 30% for
622
rail noise. Hence, no ward received a rank above 2. This approach was used as it was not possible to
623
acquire the representative number of noise complaints at a level more detailed than a ward.
624
6. CONCLUDING REMARKS
625
Taking Greater London as a case study, this study investigated the change of noise complaints in
626
terms of their spatial and temporal distributions in London during the lockdown period and tried to
627
explore affecting factors causing the difference in noise complaints changing across London
628
boroughs. The results are shown as following:
629
(1) During the COVID-19 lockdown the number of noise complaints increased significantly after
630
the lockdown was implemented, with an overall increase of 47.54%. This change rate of noise
631
complaints was distributed unevenly across the Greater London area, with the top four boroughs
632
26
with the highest change rates located in Outer London. Outer London in general experienced a
633
higher change rate compared to Inner London.
634
(2) In terms of noise sources, complaints about construction and neighbourhood reported significant
635
increases, with the value of 36% and 50%, respectively.
636
(3) Finally, the change rate of noise complaints is higher in areas with higher unemployment rates,
637
more residents with no qualifications, and low house price. Meanwhile, no significant difference in
638
the change rate was observed across traffic and rail noise level bands as derived from the DEFRA
639
noise map. It can be inferred that in such extraordinary circumstances, such as a nation-wide
640
lockdown, contextual urban factors proved to be more significant for the increase in noise
641
complaints than the actual noise exposure to road and rail traffic noise.
642
While this study has focused on the first lockdown in Spring 2020, at the time of writing the
643
pandemic (unfortunately) continues, and lockdown measures are still being frequently enforced.
644
This work provided a cross-sectional dataset, but it would be interesting to examine the effect of
645
longer-term lockdown policy on noise complaints. Meanwhile, to get a comprehensive picture of
646
environmental noise complaints, other types of complaints such as odours, air pollution, and dust, as
647
well as inter-relationships among them need to be further investigated. In addition, the specific
648
lockdown measures vary from country to country, so it would be worth comparing noise complaint
649
variations across regions, if the data is available.
650
Despite the contingent lockdown measures, the dramatic events of 2020 did change the way people
651
look at working from home, probably for good, and it is likely this will become an increasingly
652
common practice in the future. Noise complaints (and particularly from neighbourhood sources)
653
will then be an even more crucial factor in the context of public health and people’s well-being. It is
654
expected that this study could inform government about the pattern of noise complaints and help
655
with allocating resources more effectively and achieve a better urban environment.
656
7. Acknowledgements
657
This research was supported from the UKRI (EP/X123456/1) and European Research Council
658
(ERC) Advanced Grant (no. 740696) on “Soundscape Indices” (SSID).
659
27
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660
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828
829
31
830
Figure S1. Change rate of noise complaints by wards
831
832
Figure S2. Road noise level in London
833
32
834
Figure S3. Rail noise level in London
835
836
Figure S4. Road noise ranks at ward level in London
837
33
838
Figure S5. Rail noise ranks at ward level in London
839
Table S1. Summary of the unique labels for noise complaints, grouped according to the five main
840
categories used in this study.
841
cat_num
Category
N
%
1
Industry
36
7.4%
2
Construction
29
6.0%
3
Neighbourhood
373
77.1%
4
Undefined
46
9.5%
5
Non-noise
246
50.8%
Total
484
100.0%
Table S2. Unique labels for the noise complaints extracted from the aggregated database of the 22
842
London boroughs that returned data, with the category to which they were assigned.
843
Unique noise complaint label
cat_num
Category
Building site
2
Construction
Residential noise
3
Neighbourhood
Smoke and fumes
5
Non-noise
Birds
3
Neighbourhood
Noise in the street
3
Neighbourhood
Noise from commercial premises
1
Industry
Street works
2
Construction
Basement construction - noise and dust
3
Neighbourhood
Busker complaint
3
Neighbourhood
Dog
3
Neighbourhood
34
OOH requests - street works
2
Construction
Odours and smoke
5
Non-noise
Burglar/fire alarm
3
Neighbourhood
Grit and dust
5
Non-noise
Crossrail complaint
1
Industry
Complaint Stage 1 (Noise Team Only)
4
Undefined
Proactive Noise Team Job
4
Undefined
Car alarm
3
Neighbourhood
Insects
5
Non-noise
People Noise
3
Neighbourhood
Barking Dogs
3
Neighbourhood
Music and Voices
3
Neighbourhood
Machinery and Equipment
3
Neighbourhood
Section 61 Building Site Prior Consent
2
Construction
Noisy Neighbours-Music
3
Neighbourhood
Parties/Raves
3
Neighbourhood
Noisy Neighbours-People
3
Neighbourhood
ASB Crime and Policing Act 2014
4
Undefined
Domestic - Loud Amplified Music
3
Neighbourhood
Domestic - Construction and Demolition
3
Neighbourhood
Construction/Roadworks
2
Construction
Licensed Prem Noise-People
3
Neighbourhood
Domestic noise DIY
3
Neighbourhood
Dog Barking/Other Animal Noise
3
Neighbourhood
DIY
3
Neighbourhood
Domestic noise other
3
Neighbourhood
Domestic noise music
3
Neighbourhood
Alarm Noise
3
Neighbourhood
Smoke / Bonfire
5
Non-noise
Noisy party
3
Neighbourhood
Service REQUEST Noise and Nuisance
4
Undefined
Party
3
Neighbourhood
Noise Pollution Case
4
Undefined
Domestic - Voices, Singing, Banging etc
3
Neighbourhood
Highways - In Car Entertainment stereo
3
Neighbourhood
Commercial - Construction and Demolition
3
Neighbourhood
Commercial - Fixed Air Handling Units
3
Neighbourhood
RS - Domestic - Bonfires, vehicle, etc
5
Non-noise
Commerical noise
3
Neighbourhood
TV / Radio
3
Neighbourhood
Premises alarm
3
Neighbourhood
Building works noise
2
Construction
Miscellaneous Noise
4
Undefined
Construction site
2
Construction
ENVIRONMENTAL PROTECTION ACT 1990
4
Undefined
Nuisance other
4
Undefined
Machinery Fixed
3
Neighbourhood
Other / Unidentified
4
Undefined
Domestic - Misc (Anything Else)
3
Neighbourhood
Mobile plant
3
Neighbourhood
Dust nuisance
5
Non-noise
Vehicle Noise (Deliv/Collect)
3
Neighbourhood
Construction/demolition
2
Construction
OOH other EH
5
Non-noise
35
Domestic - Generators
3
Neighbourhood
Noise - Planning Application
3
Neighbourhood
NAMP - Noise from amplified music
3
Neighbourhood
NBUI - Building Site Noise
2
Construction
NVME - Vehicle, Machine & Equip Noise
3
Neighbourhood
Odour/smoke nuisance
5
Non-noise
Plant (Mobile)
3
Neighbourhood
Amplified Music
3
Neighbourhood
N01 Domestic Noise - Music
3
Neighbourhood
N02 Domestic Noise - Other
3
Neighbourhood
Highways - Misc (Anything Else)
1
Industry
NOTH - Noise - Other
4
Undefined
Barking Dog
3
Neighbourhood
Alarm
3
Neighbourhood
Other
4
Undefined
Fixed machinery
3
Neighbourhood
Streetworks
2
Construction
N99 Noise advice
4
Undefined
Commercial - Loud Amplified Music
3
Neighbourhood
Domestic - Barking Dog
3
Neighbourhood
Noise in Street Car Alarms
3
Neighbourhood
Vehicle Repairs
3
Neighbourhood
N03 Animal Noise
3
Neighbourhood
(NSE) CIEH - People Noise (e.g. footsteps, talking, shouting etc)
3
Neighbourhood
(NSE) Noise (CIEH stats)
4
Undefined
Domestic - Non amplified musical instr
3
Neighbourhood
Noise Other
4
Undefined
Noise Domestic Music
3
Neighbourhood
N22 Vehicle Alarm
3
Neighbourhood
RS - Domestic Pol - Misc (Anything Else)
5
Non-noise
Licensed Premises Noise-Music
3
Neighbourhood
TV/Radio
3
Neighbourhood
(NSE) CIEH - TV / Radio
3
Neighbourhood
(NSE) CIEH - DIY
3
Neighbourhood
Domestic - Do it Yourself
3
Neighbourhood
RS - Domestic - Odours, fumes and gas
5
Non-noise
Commercial - Industrial Noise
1
Industry
NDOG - Noise from barking dog(s)
3
Neighbourhood
Buskers
3
Neighbourhood
Noise - domestic,neighbours
3
Neighbourhood
Vip Complaint (Noise Team Only)
4
Undefined
N20 Intruder alarm
3
Neighbourhood
Highways - Roadworks
2
Construction
Noise - barking dogs
3
Neighbourhood
Noise In the Street - NOT ALARMS
3
Neighbourhood
Noise commerical - deliveries
3
Neighbourhood
Noise - building sites
2
Construction
NNH Noise-People
3
Neighbourhood
NNT LA2003 Consultation - Public Nuisance
4
Undefined
E17 Fly-tipping - private land
5
Non-noise
N11 DIY On Premises - Domestic
3
Neighbourhood
A20 Smell nuisance - other
5
Non-noise
D01 Bonfires - Domestic
5
Non-noise
N09 Licensing Enquiry
5
Non-noise
36
N10 Industrial / Commercial Noise
1
Industry
N14 Construction Site Noise
2
Construction
Oth Invalid code
5
Non-noise
N08 Car Alarms on Street-Dom
3
Neighbourhood
E10 Accumulation - domestic
5
Non-noise
062 Private Land
5
Non-noise
E01 Blocked/Defective Drain
5
Non-noise
5
Non-noise
C57 Abandoned Vehicles
5
Non-noise
A15 Pollution Enquiry
5
Non-noise
(NSE) CIEH - Music
3
Neighbourhood
(NSE) CIEH - Barking Dogs
3
Neighbourhood
Highways Street Speakers,buskers etc
3
Neighbourhood
Domestic - Car Alarms all vehicles
3
Neighbourhood
N01 Construction
2
Construction
N47 Equipment/ Plant - Domestic
3
Neighbourhood
Dog barking
3
Neighbourhood
Commercial noise -other
3
Neighbourhood
Noise - commercial,shops,clubs,pubs
3
Neighbourhood
N13 Human Noise - Domestic
3
Neighbourhood
E26 Covid-19
5
Non-noise
N38 Planning App. Consultation
5
Non-noise
NNI Noise-Music
3
Neighbourhood
054 Other
5
Non-noise
C23 Fly Tipping
5
Non-noise
E11 Accumulation - commercial
5
Non-noise
C65 Trees
5
Non-noise
E25 Domestic Waste On Landings
5
Non-noise
A17 Fumes - Commercial
5
Non-noise
NALA - Noise from a burglar alarm
3
Neighbourhood
NNG Noise-Plant/machinery (mobile) e.g. construction site
2
Construction
NNB Noise-Barking Dog
3
Neighbourhood
NNF Noise-Machinery (fixed) e.g. fans, boiler
3
Neighbourhood
N16 Music - Domestic
3
Neighbourhood
601 Homelessness
5
Non-noise
N10 Road Works
2
Construction
L07 Out of hours noise - domestic music
3
Neighbourhood
N02 Domestic noise (banging/shouting)
3
Neighbourhood
I01 Rats
5
Non-noise
E12 Accumulation - private land (
5
Non-noise
(NSE) CIEH - Alarm (e.g. House, Car, Fire etc)
3
Neighbourhood
Commercial - Aircraft Noise
1
Industry
Domestic - Audible Intruder Alarm etc
3
Neighbourhood
Noise Pollution Street Record
4
Undefined
N18 Equipment/Plant - Commercial
5
Non-noise
Noise Construction Demolition
2
Construction
N50 Human Noise - Street
3
Neighbourhood
UA0 Drug / substance misuse & dea
5
Non-noise
ASBIT Noise
4
Undefined
N51 Human Noise - Commercial
3
Neighbourhood
N19 Light Motor Vehic./Street-Com
5
Non-noise
N15 Parties - Domestic
3
Neighbourhood
UP0 Intimidation / harassment
5
Non-noise
A09 Odour from Mogden
5
Non-noise
37
N17 Music - Commercial
3
Neighbourhood
(NSE) CIEH - Party
3
Neighbourhood
N35 Railway Noise-Engineering Wor
1
Industry
Extractor Fan/Airconditioning Unit
3
Neighbourhood
A16 Fumes - Domestic
5
Non-noise
L02 Out of Hours noise - domestic (banging/shouting)
3
Neighbourhood
N20 Noise in street
3
Neighbourhood
N46 Noise - commercial (other)
3
Neighbourhood
N25 Noise adv/info
3
Neighbourhood
N13 Noise - commercial construction/demolition
2
Construction
N07 Domestic noise (music from stereo)
3
Neighbourhood
N05 Domestic noise (other)
3
Neighbourhood
N12 Commercial and domestic alarm
3
Neighbourhood
N14 Domestic noise (DIY)
3
Neighbourhood
UIT Illegal Traveller Incursions
5
Non-noise
(NSE) CIEH - Mechanical (fixed) e.g. fan, pump, boiler
3
Neighbourhood
(NSE) CIEH - Vehicle Noise
3
Neighbourhood
Commercial - Misc (Anything Else)
5
Non-noise
Noise Domestic Other
3
Neighbourhood
NN NOISE COMPLAINTS
4
Undefined
N59 Licensing Consultation
5
Non-noise
Res - Asb Impact Noise (alleged Deliberate Banging)
3
Neighbourhood
Res - Loud Music / Tv / Entertainment /games Console/radio
3
Neighbourhood
E08 Light Nuisance - Domestic
3
Neighbourhood
N55 Jumping/Stamping on Floor
3
Neighbourhood
Res - Raised Voices, Shouting, Screaming
3
Neighbourhood
N33 Noise Non S61 street works for TFL/Highways decision
2
Construction
N26 Noise from vehicle/property alarm
3
Neighbourhood
N21 Noise from aircraft
1
Industry
L13 Out of Hours Noise - construction/demolition sites
3
Neighbourhood
UA3 Discarding needles / drug par
5
Non-noise
(NSE) CIEH - Vehicle Repairs
3
Neighbourhood
(NSE) CIEH - Plant (mobile) (e.g. construction equipment)
3
Neighbourhood
RS - Domestic - Security Flood lights
5
Non-noise
NCDN - Noise - Domestic
3
Neighbourhood
MUSC Music
3
Neighbourhood
PNSA Shouting / Arguing
3
Neighbourhood
BPLA Building Services Plant Noise
1
Industry
MISC Miscellaneous
5
Non-noise
SMLN Smell Nuisance
5
Non-noise
BSIT Building Site Noise
2
Construction
TVRD TV / Radio
3
Neighbourhood
BUSK Buskers in Street
3
Neighbourhood
ACON Air Conditioning
3
Neighbourhood
DIY D.I.Y.
3
Neighbourhood
SMOK Smoke
5
Non-noise
ALAR Alarm (burglar,car,fire)
3
Neighbourhood
Construction Bond Building Site
3
Neighbourhood
PNFT Footsteps / Talking
3
Neighbourhood
PART Party
3
Neighbourhood
Cmls - Commercial Unlicenced Premises (machinery, Refridg, Air Con)
3
Neighbourhood
Ph Noise Complaint
4
Undefined
NNO Noise-Vehicles
3
Neighbourhood
Res - House Party
3
Neighbourhood
38
Res - Household Appliances (eg Hoover)
3
Neighbourhood
N21 Noise on street
3
Neighbourhood
N34 Noise Non S61 site works application
2
Construction
N42 Noise - residential constuction/renovation
3
Neighbourhood
N23 Noise from river/water activity
3
Neighbourhood
A19 Dust - Commercial
5
Non-noise
RS - Commercial - Bonfires, vehicle, etc
5
Non-noise
PA system
3
Neighbourhood
Noise Commercial Intruder Alarms
3
Neighbourhood
Underground (tube/station)
1
Industry
Bonfire
3
Neighbourhood
COVID Corona Virus
5
Non-noise
BONF Bonfires
3
Neighbourhood
Noise - Premises Alarm
3
Neighbourhood
Devliveries
3
Neighbourhood
Cndm - Building Works - Large Development
2
Construction
061 Council Owned land
5
Non-noise
Res - Barking Dog(s)
3
Neighbourhood
C36 Litter
5
Non-noise
N10 Noise from music (other)
3
Neighbourhood
C80 Commercial Waste Enforcement
5
Non-noise
Drunken behaviour
5
Non-noise
N46 Noise Pollution Advice/Enquir
4
Undefined
N56 Television/Radio
3
Neighbourhood
Noise Commercial Retail
3
Neighbourhood
Vehicle alarm noise
3
Neighbourhood
NMSC Noise Miscellaneous
4
Undefined
ELDN Early/ Late Delivery Noise
3
Neighbourhood
DOMA Domestic Appliance noise
3
Neighbourhood
UQ0 Criminal damage / vandalism
5
Non-noise
N32 Equipment(Loudspeakers)-Stree
3
Neighbourhood
N08 Noise from voice (singing)
3
Neighbourhood
L14 Out of Hours noise - domestic (DIY)
3
Neighbourhood
E07 Light Nuisance - Commercial
5
Non-noise
Commerial - Voices, Singing, Banging etc
3
Neighbourhood
CONTROL OF POLLUTION (AMEND) ACT 1989
5
Non-noise
S26 Working Hours
5
Non-noise
NASB - Noise Anti Social Behaviour
3
Neighbourhood
Other Animals & Birds
3
Neighbourhood
Cmls - Leisure Premises (eg Football, Sports, Play)
3
Neighbourhood
E09 Music
3
Neighbourhood
E08 People Noise
3
Neighbourhood
Cndm - Diy Noise / Build Work
3
Neighbourhood
E10 Party
3
Neighbourhood
Noise-Music
3
Neighbourhood
Noise-Plant/machinery (mobile) e.g. construction site
2
Construction
Noise-People
3
Neighbourhood
N06 Car Alarms on Prems-Dom
3
Neighbourhood
UE1 Loitering
5
Non-noise
E07 Mobile Plant
5
Non-noise
N06 Commercial noise - music (club/pub/restaurant)
3
Neighbourhood
RS - Highways Pol - Misc (Anything Else)
5
Non-noise
Cndm - Building Works - Single House/small Site (eg Single House Renovation, Extension)
3
Neighbourhood
E02 Barking Dogs
3
Neighbourhood
39
Noise-Unidentified/other
4
Undefined
Noise-Party
3
Neighbourhood
E01 Alarms
3
Neighbourhood
E13 Vehicle Noise
3
Neighbourhood
RS - Domestic - Air Pollution
5
Non-noise
Mice
5
Non-noise
Noise-TV/Radio
3
Neighbourhood
0
5
Non-noise
N01 Domestic noise (children running)
3
Neighbourhood
E15 DIY
3
Neighbourhood
E06 Fixed Machinery
3
Neighbourhood
E24 Littering - street
5
Non-noise
W-Vehicle-related
3
Neighbourhood
Noise Domestic Dogs and other animals
3
Neighbourhood
Noise Anti Social Behaviour
3
Neighbourhood
Dust/Fumes/Smoke
5
Non-noise
Res - Alarm - House Alarm
3
Neighbourhood
B33 Suspected banned breed
5
Non-noise
S13 Noise
4
Undefined
063 Highways
1
Industry
N21 Light Motor Vehic./Prem.-Comm
3
Neighbourhood
Loitering
5
Non-noise
Noise Domestic TV
3
Neighbourhood
Noise Domestic Intruder Alarms
3
Neighbourhood
D07 Bonfires - Demolition/Constru
3
Neighbourhood
E11 TV/Radio
3
Neighbourhood
Vm - Delivery / Loading Activities From Vehicle
3
Neighbourhood
Vm - Engine Noise
3
Neighbourhood
CLEAN NEIGHBOURHOODS & ENV ACT 2005
5
Non-noise
Helicopter and aircraft movements
1
Industry
LITE Light Pollution
5
Non-noise
E03 Other Animals/Birds
3
Neighbourhood
Noise-Barking Dog
3
Neighbourhood
Res - Noise Other (eg High Freq, Other Misc, Snoring)
3
Neighbourhood
I25 Pigeons
5
Non-noise
B16 Dogs - Noise - Domestic
3
Neighbourhood
I18 Oak Processionary Moth
5
Non-noise
Commercial - Generators
5
Non-noise
ASB - Vulnerable Victims
5
Non-noise
Commercial - Audible Intruder Alarm etc
3
Neighbourhood
017 Pro-active
5
Non-noise
Noise in Street Machinery
3
Neighbourhood
Noise Domestic DIY
3
Neighbourhood
DOGB Dogs Barking
3
Neighbourhood
Noise Domestic Building Works
3
Neighbourhood
D02 Bonfires - Commercial
3
Neighbourhood
Commercial - Do it Yourself
3
Neighbourhood
N14 Garden Equipment - Domestic
3
Neighbourhood
E12 Fireworks
3
Neighbourhood
Vm - Busker / Street Peformer With Equipment
3
Neighbourhood
N12 DIY Activities - on Street
3
Neighbourhood
A18 Dust - Domestic
5
Non-noise
E16 Litter - private land
5
Non-noise
Highways - - Car Alarms all vehicles
3
Neighbourhood
40
Artificial light pollution
5
Non-noise
UK4 Hooliganism / loutish behavio
5
Non-noise
NNC Noise-Other Animals and Birds
3
Neighbourhood
NNA Noise-Alarm
3
Neighbourhood
Noise-Machinery (fixed) e.g. fans, boiler
3
Neighbourhood
Noise-Burglar Alarm
3
Neighbourhood
N05 Intruder Alarms -Commercial
3
Neighbourhood
N20 Light Motor Vehic./Street-Dom
3
Neighbourhood
Traffic noise
1
Industry
Service ENQUIRY Noise and Nuisance
4
Undefined
Email complaint
5
Non-noise
PSH HMO - Mechanical Noise within the Home
3
Neighbourhood
Noise-Vehicles
3
Neighbourhood
N62 Sct 61 Applications
3
Neighbourhood
Res - Transmittion Of Footfall (impacts)
3
Neighbourhood
NCAR - Noise - Car Alarm
3
Neighbourhood
Busking
3
Neighbourhood
NNR Noise-Low frequency
3
Neighbourhood
N26 Motorbikes - on Street
3
Neighbourhood
E19 Commercial Waste - private la
5
Non-noise
POTH - Pollution - Other
5
Non-noise
N11 People Noise (e.g. footsteps,
3
Neighbourhood
N02 Car Alarm
3
Neighbourhood
N05 Construction Noise
2
Construction
N07 Music
3
Neighbourhood
Noise from Fireworks
3
Neighbourhood
N04 Intruder Alarms - Domestic
3
Neighbourhood
ASBIT Seeking Prior Consent for Noise (Section 61)
3
Neighbourhood
D05 Chimney - Commercial
5
Non-noise
K02 Fly-tipping
5
Non-noise
Vm - Alarm - Vehicle
3
Neighbourhood
Vm - Music From Vehicle In Street
3
Neighbourhood
C30 Dumped Fridges/Freezers
5
Non-noise
N52 Industrial Noise
1
Industry
Domestic - Fixed Air Handling Units
3
Neighbourhood
N30 Deliveries/Collections
3
Neighbourhood
N17 Party
3
Neighbourhood
N24 Buskers / Street Performers
3
Neighbourhood
N13 Burglar/Fire Alarm
3
Neighbourhood
N23 Roadworks
2
Construction
TRCA Traffic / Car Noise
1
Industry
NSAN Noisy Animals/Birds (Not dogs)
3
Neighbourhood
GDFU Grit/Dust/Fumes
5
Non-noise
Bus/commercial - Intruder Alarm
3
Neighbourhood
(NSE) CIEH - Other / Unidenitified
4
Undefined
N27 Other
4
Undefined
N01 Machinery (fixed) e.g fan, pu
3
Neighbourhood
L25 OOH noise from vehicle/property alarm
3
Neighbourhood
L01 Out of Hours noise - domestic (children running)
3
Neighbourhood
N18 Rave
3
Neighbourhood
N44 Fire Alarm - Commercial
3
Neighbourhood
A12 Smell nuisance - Rest./Takeaw
5
Non-noise
NDIY - Noise from DIY activities
3
Neighbourhood
Rats
5
Non-noise
41
Low Frequency
4
Undefined
UB1 Street drinking
5
Non-noise
C85 Graffiti - Other
5
Non-noise
N03 Domestic noise (loud TV)
3
Neighbourhood
UA1 Taking drugs
5
Non-noise
N12 DIY
3
Neighbourhood
RWNS Railway Noise
1
Industry
E17 Other/Unidentified
4
Undefined
Noise-DIY
3
Neighbourhood
N41 High Frequency Noise
4
Undefined
RS Commercial Pol - Misc (Anything Else)
5
Non-noise
(NSE) CIEH - Other Animals and Birds
5
Non-noise
Civil dispute
5
Non-noise
E05 Exhumation
5
Non-noise
N22 Noise from rail
1
Industry
Vm - Machinery Or Equipment Noise In Street (eg Generator, Roadworks/utilities)
3
Neighbourhood
N45 Fire Alarm - Domestic
3
Neighbourhood
X15 Waste/Dumping
5
Non-noise
Commercial - Railway Traffic
1
Industry
Dog - Other
3
Neighbourhood
N10 Amplified sound (TV/Radio/Mus
3
Neighbourhood
NNK Noise-TV/Radio
3
Neighbourhood
NNJ Noise-Party
3
Neighbourhood
Noise-Public Address Systems
3
Neighbourhood
N25 Motorbikes - on Land
3
Neighbourhood
L20 Our of Hours noise in the street
3
Neighbourhood
Noise Commercial Sports and Leisure
3
Neighbourhood
N06 Delivery / Collection
3
Neighbourhood
N04 Animals noise
3
Neighbourhood
Covid-19 Licensing related enquiries
5
Non-noise
D03 Bonfires - Open Land
5
Non-noise
N03 Site
5
Non-noise
UH1 Inconvenient / illegal parkin
5
Non-noise
Commercial - Car Alarms all vehicles
3
Neighbourhood
QAD Other Complaint or Enquiry
5
Non-noise
Domestic - Vibration
3
Neighbourhood
UL6 Impeding access to communal a
5
Non-noise
RS - Commercial - Odours, fumes and gas
5
Non-noise
Domestic - Sound Insulation
3
Neighbourhood
HIGHWAYS ACT 1980
5
Non-noise
L03 Out of Hours noise - domestic (loud TV)
3
Neighbourhood
Fireworks
3
Neighbourhood
Res - Musical Instrument (non Amplified)
3
Neighbourhood
N63 Other
4
Undefined
OTH Other
5
Non-noise
Shouting and swearing
3
Neighbourhood
K07 Hazardous waste
5
Non-noise
N08 Plant / Equipment (mobile)
3
Neighbourhood
Public Address System
3
Neighbourhood
Noise - Car Alarms
3
Neighbourhood
C68 Grass Cutting
3
Neighbourhood
N21 Noise on street (can't deal)
3
Neighbourhood
C58 Overhanging Vegetation
5
Non-noise
E04 Bells
3
Neighbourhood
42
Commercial - Vibration
3
Neighbourhood
S21 Hazardous Substances
5
Non-noise
PADS Public Address System
3
Neighbourhood
NNQ Noise-DIY
3
Neighbourhood
PSMC - Non Domestic bonfire
3
Neighbourhood
PSMO - Domestic Smoke
5
Non-noise
Licensing request
5
Non-noise
Uncontrolled Animals
5
Non-noise
UE2 Pestering residents
3
Neighbourhood
C24 Other Refuse - Domestic
5
Non-noise
C11 Dumped/Accum. - Street/Land
5
Non-noise
N12 Aircraft Noise
1
Industry
W-Drug-and-drink
5
Non-noise
Light Pollution
5
Non-noise
L04 Our of Hours noise - domestic (sewing machine)
3
Neighbourhood
N09 Noise from music in studio
3
Neighbourhood
L28 Out of Hours noise - domestic (hard flooring)
3
Neighbourhood
D04 Chimney - Domestic
5
Non-noise
UK3 Drunken behaviour
5
Non-noise
UF2 Indecent exposure
5
Non-noise
Noise - Alarm
3
Neighbourhood
UP2 Verbal abuse
5
Non-noise
UH0 Vehicle related nuisance & In
5
Non-noise
B14 Poultry/Cockerels
3
Neighbourhood
UP1 Groups or individuals making
5
Non-noise
Refuse Dumping
5
Non-noise
Hooliganism/loutish behaviour
5
Non-noise
Highways - Non amplified musical instr
3
Neighbourhood
Refuse Collection - Domestic/Trade
5
Non-noise
RS - Commercial - Air Pollution
5
Non-noise
Light nuisance
5
Non-noise
N09 Car Alarms on Street-Comm
3
Neighbourhood
Noise - Religious Establishment
3
Neighbourhood
R33 Bollard Over
5
Non-noise
L11 Out of Hours noise - domestic alarm
3
Neighbourhood
L06 Out of Hours noise - commercial music
3
Neighbourhood
L05 Out of Hours noise - domestic (other)
3
Neighbourhood
N01 Commercial
3
Neighbourhood
N22 Light Motor Vehic./Prem.-Dom.
3
Neighbourhood
C41 Leaf
5
Non-noise
C53 Encroachment/footway obstruct
5
Non-noise
RS - Domestic - Dust Pollution
5
Non-noise
Commercial - Barking Dog
3
Neighbourhood
Noise Commercial Deliveries
3
Neighbourhood
C54 Builders materials
5
Non-noise
C35 Litter Bins
5
Non-noise
BSRA Building site rapids
5
Non-noise
Animal (not dogs)
5
Non-noise
Domestic incident
5
Non-noise
W-Nuisance behaviour
5
Non-noise
N02 Residential
3
Neighbourhood
Noise-Vehicle repairs
3
Neighbourhood
V05 Anti-Social Behaviour
5
Non-noise
M31 Domestic waste - put out late
5
Non-noise
43
Highways - Road, Traffic, Vehicles etc
1
Industry
G14 Noise Limits
4
Undefined
N27 Motorbikes - on Premises
3
Neighbourhood
L29 Out of Hours noise from car sound system
3
Neighbourhood
NTC TEN Licensing consultation
5
Non-noise
N14 Instrument
3
Neighbourhood
Noise Commercial Pubs Clubs Entertmt
3
Neighbourhood
Noise Commercial Food Premises
3
Neighbourhood
Noise Place of Worship
3
Neighbourhood
L18 Out of Hours noise - barking dog
3
Neighbourhood
Entertainment noise (Pub, Licensed prem)
3
Neighbourhood
PLAN Planning Enquiry
5
Non-noise
000 General Housing Inspection
5
Non-noise
V08 Other - specify in text line
5
Non-noise
Noise Task
4
Undefined
Cml - Licensed Prem (pubs, Clubs, Rests)
5
Non-noise
016 Non Urgent
5
Non-noise
N53 Slamming Doors
3
Neighbourhood
E09 Blocked Drain/Sewer - Council
5
Non-noise
LONDON LOCAL AUTHORITES ACT 1990
5
Non-noise
Commercial - Non amplified musical instr
3
Neighbourhood
NNE Noise-Public Address Systems
3
Neighbourhood
Noise-Low frequency
4
Undefined
Begging/Vagrancy
5
Non-noise
Boat Noise
1
Industry
C87 "A" Advertising Boards
5
Non-noise
RS - Highways - Bonfires, vehicle, etc
5
Non-noise
E02 Blocked/Defective Public Sewe
5
Non-noise
N20 Railway
1
Industry
H&S Smoking
5
Non-noise
L10 Out of Hours noise- music (other)
3
Neighbourhood
Aircraft noise
1
Industry
N42 Low Frequency Noise
4
Undefined
CGD Grimebuster dumped rubbish
5
Non-noise
R13 Noise (res)
3
Neighbourhood
Domestic - Other Animals
3
Neighbourhood
N09 Vehicle / Traffic/Aircraft
1
Industry
B22 Dogs Fouling - Garden
5
Non-noise
L31 Out of Hours noise - vehicle alarm
3
Neighbourhood
B01 Dogs Fouling - On Street
5
Non-noise
Complaint Stage 2 (Noise Team Only)
4
Undefined
UA5 Presence of dealers or users
5
Non-noise
015 Urgent
5
Non-noise
N54 Moving Furniture
3
Neighbourhood
UA4 Crack houses
5
Non-noise
Comments on variations to lic premises
5
Non-noise
V07 Unlicensed Premises/Traders
5
Non-noise
H07 Obstruction on the Highway
5
Non-noise
E00 Blocked/Defec.- Gully Soakawa
5
Non-noise
FIRW Fireworks
3
Neighbourhood
N02 Demolition Site
2
Construction
FLTH Filthy & Verminous Premises
5
Non-noise
(NSE) CIEH - Low Frequency
4
Undefined
N13 Railway Noise
1
Industry
44
N15 Speakers/Public address syste
3
Neighbourhood
F46 Spillage/Littering
5
Non-noise
Highways - Construction and Demolition
2
Construction
N39 Explosives/Fireworks
3
Neighbourhood
Commercial - Sports and Leisure
3
Neighbourhood
N33 Equipment (Loudspeakers)-Prem
3
Neighbourhood
N04 Noise From Party
3
Neighbourhood
RS - Commercial - Security Flood lights
5
Non-noise
X08 Houses in Multiple Occupation
5
Non-noise
L30 Out of Hours noise from raves
3
Neighbourhood
E16 Low Frequency Noise
4
Undefined
I27 Foxes
5
Non-noise
UQ6 Damage to trees / plants / he
5
Non-noise
E03 Blocked Drains/Private Sewer
5
Non-noise
C31 Hazardous Waste
5
Non-noise
Noise-Other Animals and Birds
3
Neighbourhood
(NSE) CIEH - Public Address Systems
3
Neighbourhood
Loud party/gathering
3
Neighbourhood
B05 Dogs Stray - On Street
5
Non-noise
E22 Accumulation - CPN - domestic
5
Non-noise
B25 Dog Missing
5
Non-noise
B17 Dogs - Noise - Commercial
3
Neighbourhood
UDO Prostitution
5
Non-noise
Discarded condoms
5
Non-noise
UL7 Games in restricted / inappro
5
Non-noise
UF0 Sexual acts
5
Non-noise
C67 Trees to be Removed
5
Non-noise
Noise-Fireworks
3
Neighbourhood
RP TEST
5
Non-noise
M19 Clinical waste - missed dome
5
Non-noise
C81 Suspected Fly-tippers
5
Non-noise
BELL Bells
3
Neighbourhood
S06 H&S - Miscellaneous
5
Non-noise
NSIN - Noise (Sound Insulation)
3
Neighbourhood
N19 Underground
1
Industry
Noise Commercial Industrial
1
Industry
E05 PA Systems
3
Neighbourhood
E23 Invasive plants
5
Non-noise
L12 Out of Hours noise - domestic and commercial alarm
3
Neighbourhood
Railway noise (not construction)
1
Industry
A14 Spraying Vehicles - Commercia
3
Neighbourhood
Oi - Other Industry Eg. Cement/glass Works
1
Industry
E14 Vehicle Repairs
3
Neighbourhood
Highways - Industrial Noise
1
Industry
N60 Noise - Smoking outside Premi
3
Neighbourhood
N24 Heavy Motor Vehic./Street-Com
3
Neighbourhood
A13 Spraying Vehicles - Domestic
3
Neighbourhood
Noise from Parked Vehicle
3
Neighbourhood
UK2 Fighting
5
Non-noise
RS - Domestic - Water Pollution
5
Non-noise
Waste accumulation
5
Non-noise
Amplified music from cars
3
Neighbourhood
G01 Night Time Flying-Sleep Depri
5
Non-noise
K15 Street Cleansing - general
5
Non-noise
45
K06 Clinical waste - Dumped needl
5
Non-noise
A06 Motor Engine Exhaust
5
Non-noise
(NSE) CIEH - Fireworks
3
Neighbourhood
Highways - Mobile refrigeration plant
3
Neighbourhood
I38 Requests for Information
5
Non-noise
Noise Domestic Fireworks
3
Neighbourhood
H09 Damage to the Highway
5
Non-noise
SERC Service Complaint
5
Non-noise
Noise - Licensing Case
4
Undefined
ASB - Commercial - Dust emissions
5
Non-noise
N11 Traffic Noise
1
Industry
N23 Heavy Motor Vehic./Prem.-Comm
3
Neighbourhood
L27 Out of Hours noise from smoking outside commercial premises
3
Neighbourhood
Vm - Aircraft Noise
1
Industry
Commercial - Karaoke
3
Neighbourhood
K24 Overflowing litter bins
5
Non-noise
C84 Graffiti - Council
5
Non-noise
L23 Out of Hours noise - river/water activity
3
Neighbourhood
S18 Lighting
5
Non-noise
Animal nuisance
5
Non-noise
(NSE) CIEH - Boat Noise (all forms of water transport)
1
Industry
UP4 Following people
5
Non-noise
S08 Asbestos
5
Non-noise
PEDI Noise and Disturbance from Pedicabs
3
Neighbourhood
V06 Street Trading - Unauthorised
5
Non-noise
NLIC - Noise from licensed premises
3
Neighbourhood
K10 Glass
5
Non-noise
G11 Vortex/Physical Damage(eg.ice
5
Non-noise
UP9 Menacing gestures
5
Non-noise
Noise Events
4
Undefined
C83 Graffiti - Racist/Offensive
5
Non-noise
CCU Community Clean Up
5
Non-noise
W-Agressive behaviour
5
Non-noise
CARN Carnival
3
Neighbourhood
AQPG Air Quality Not Traffic
5
Non-noise
L22 Out of Hours noise - rail
1
Industry
J01 Asbestos Land
5
Non-noise
Cmls - Party Boats (eg Music On Thames)
3
Neighbourhood
PSH HS - Mechanical noise within the home
3
Neighbourhood
Section 61 prior consent
3
Neighbourhood
Cmls - Gym - Mixed Use Development (only Gyms In Resi Blocks)
3
Neighbourhood
CWE Other waste education/enforce
5
Non-noise
VREP Vehicle Repair Noise
3
Neighbourhood
MFE Flats above shops - enquiry
5
Non-noise
Noise-Bells (e.g. Church/Phone)
3
Neighbourhood
N06 Noise from HMO
3
Neighbourhood
Carnival
3
Neighbourhood
G17 Vibration
4
Undefined
W08 CCTV - Non-LBH
5
Non-noise
W21 PROW - General Enquiry
5
Non-noise
Animals
5
Non-noise
ASB - Commercial - Industrial noise(factory/plant)
1
Industry
N16 Low frequency (hums)
4
Undefined
ISMO Individual Smoking
5
Non-noise
46
PREVENTION OF DAMAGE BY PESTS ACT 1949
5
Non-noise
C69 Vehicle to pound
5
Non-noise
UL3 Inappropriate use of firework
5
Non-noise
ASB - Commercial - Construction noise
2
Construction
N05 Noise Loud Music
3
Neighbourhood
F20 Recycling collections - items
5
Non-noise
I07 Bedbugs
5
Non-noise
UH4 Joyriding
5
Non-noise
NVR Vehicle repairs
3
Neighbourhood
ASB - Commercial - Music noise
3
Neighbourhood
D06 Cable Burning
5
Non-noise
Highways - Generators
5
Non-noise
Bells
3
Neighbourhood
B09 Dangerous/Worrying Dog -Stree
5
Non-noise
B32 Dog acting Aggressively
5
Non-noise
E21 Accumulation - CPN - commerci
5
Non-noise
Advice and Queries
5
Non-noise
C51 Damage/deposits on highway
5
Non-noise
B28 Dog Fouling-Communal Area Ext
5
Non-noise
Noise-Boats
1
Industry
E20 Education - environmental pro
5
Non-noise
Commercial - In Car Entertainment stereo
3
Neighbourhood
B15 Pet Animals Noise (Not Dogs)
3
Neighbourhood
Cllr/MP Enquiry Noise
4
Undefined
N43 Funfairs
3
Neighbourhood
Individual Smoking Shisha
5
Non-noise
V01 Licensing - Advice Requested
5
Non-noise
C37 Street Cleansing - General
5
Non-noise
CTW GM/Trees/Weeds
5
Non-noise
K14 Weeds
5
Non-noise
RS - Commercial - Dust Pollution
5
Non-noise
MBR Replacement bin - lost/damage
5
Non-noise
R43 Out - Not working At All
5
Non-noise
RS - Highways - Air Pollution
5
Non-noise
F41 Garden waste sack sales
5
Non-noise
O08 Private
5
Non-noise
701 Call Centre
5
Non-noise
R16 L/col. - Lighting Out
5
Non-noise
B13 Feral Cats
5
Non-noise
(NSE) CIEH - Bells (e.g. church, telephone)
3
Neighbourhood
N07 Car Alarms on Prems-Comm
3
Neighbourhood
N04 Domestic noise (sewing machine)
3
Neighbourhood
Drainage defect
5
Non-noise
NNS Noise-Unidentified/other
4
Undefined
SASB Asbestos
5
Non-noise
K20 Fouling
5
Non-noise
Noise - Advice Only
4
Undefined
Barking Dogs
3
Neighbourhood
Fireworks
3
Neighbourhood
Music
3
Neighbourhood
People Noise(i.e Talking/Shout
3
Neighbourhood
Machinery - Fixed(i.e Fan/Pump
3
Neighbourhood
Alarm (house/Car/fire/etc)
3
Neighbourhood
Plant- Mobile(i.e. const.equip
3
Neighbourhood
47
DIY
3
Neighbourhood
TV/Radio
3
Neighbourhood
Other/Unidentified
4
Undefined
Party
3
Neighbourhood
Vehicle Noise
3
Neighbourhood
Other Animals & Birds
3
Neighbourhood
Vehicle Repairs
3
Neighbourhood
Section 61
3
Neighbourhood
Loud Music Residential
3
Neighbourhood
Cockerels
3
Neighbourhood
Construction
2
Construction
House Alarm
3
Neighbourhood
Commercial Alarm
3
Neighbourhood
People Noise - Movement
3
Neighbourhood
Loud Music Commercial
3
Neighbourhood
People Noise - Vocal
3
Neighbourhood
D I Y
3
Neighbourhood
Deliveries or Collections
3
Neighbourhood
Table S3. Coefficients between urban factors and the change rate of noise complaints
844
based on Spearman and Kendall's Tau correlation.
845
Factors
Indicators
Spearman correlation
coefficients
Kendall’s tau
correlation coefficients
Housing
Median House Price (£)
-.108*
-.068*
Median Household income estimate
-.140**
-.094**
% Households Owned
-.078
-.044
% Households Social Rented
.160**
.109**
% Households Private Rented
-.073
-.061
% dwellings in council tax bands A or B
.087
.052
% dwellings in council tax bands C, D or E
.134**
.085*
% dwellings in council tax bands F, G or H
-.131*
-.079*
Demographic
Population density
.059
.026
Mean Age
-.066
-.025
Unemployment rate
.114*
.069*
% with no qualifications
.129*
.087*
Life Expectancy
-.123*
-.064
Subjective well-being average score
-.016
-.027
Transport
Road density
-.080
-.058
Cars per household
-.064
-.033
Average Public Transport Accessibility score
-.043
-.041
% travel by bicycle to work
.119*
.085*
Noise level band
Road Lden rank
-.114*
-.092*
Rail Lden rank
.006
.050
% in the highest noise level band (road Lden≥75dBA)
-.082
-.066
% in the highest noise level band (rail Lden≥75dBA)
-.068
.050
Table S4. Significant level of differences in the number of noise complaints between 2019 and
846
2020 by boroughs and noise source categories via Mann-Withney U test
847
Borough
Significance level
(p value)
Mann-Whitney U
Z
Median 2019
Median 2020
All boroughs
0.000**
319.000
-8.461
285.50
431.00
Barking and Dagenham
0.000**
331.000
-8.410
16.00
33.00
Barnet
0.008**
1606.500
-2.640
3.50
1.50
Bexley
0.000**
965.000
-5.553
3.00
6.00
Camden
0.006**
1572.500
-2.762
6.50
11.00
Croydon
0.096
1814.000
-1.666
4.00
5.50
Greenwich
0.126
1842.500
-1.532
9.00
11.00
Hammersmith and Fulham
0.015*
1645.500
-2.426
16.00
19.00
Haringey
0.000**
315.500
-8.483
7.50
22.00
Havering
0.075
1791.000
-1.783
2.50
3.00
Hillingdon
0.000**
1272.500
-4.131
7.50
10.00
Hounslow
0.000**
335.500
-8.389
18.50
41.50
Islington
0.000**
607.000
-7.152
27.00
46.50
48
Kensington and Chelsea
0.001**
1454.500
-3.296
34.00
41.00
Kingston upon Thames
0.260
1939.500
-1.125
1.00
2.00
Lambeth
0.002**
1506.500
-3.059
17.50
23.50
Merton
0.074
1788.000
-1.785
3.00
6.00
Richmond upon Thames
0.002**
1510.000
-3.061
3.00
5.00
Sutton
0.002**
1512.500
-3.051
4.00
6.00
Tower Hamlets
0.000**
1300.500
-4.001
8.50
14.00
Waltham Forest
0.954
2165.500
-0.058
6.50
5.00
Wandsworth
0.000**
907.000
-5.792
8.50
14.50
City of Westminster
0.000**
803.500
-6.258
53.00
68.00
Industry
0.126
1936.000
-1.105
8.00
7.00
Construction
0.000**
1318.000
-3.916
25.50
33.50
Neighbourhood
0.000**
398.500
-8.099
201.00
304.00
Undefined