Proceedings of the Institute of Acoustics

 

 

 

Noise and deprivation in Scotland’s four largest cities: Glasgow, Edinburgh, Aberdeen and Dundee

 

Ashley Leiper¹, SSE Renewables, 1 Waterloo St, Glasgow, G2 6AY, UK
Andrew Hood², EnviroCentre, 8 Eagle St, Glasgow, G4 9XA, UK

 

ABSTRACT

 

Scotland’s draft National Planning Framework 4 (NPF4) Integrated Impact Assessment states that deprived communities tend to be exposed to higher levels of noise than those in less deprived areas. However, this has not yet been specifically investigated in Scotland. The majority of studies find a higher likelihood of noise exposure in deprived communities, although some find the opposite to be true, suggesting that the relationship is highly dependent on the context of the study area. To address a need in the literature for more research in this area and to comment on the statement in NPF4, a spatial analysis has been conducted using Scottish Government published datasets, the Scottish Index of Multiple Deprivation and the Round 3 Noise Mapping. A statistically significant positive relationship between noise exposure and multiple deprivation is found in Glasgow. No statistically significant relationship between noise exposure and multiple deprivation is found for Aberdeen, Dundee or Edinburgh. The relationships between deprivation and both Noise Management Areas and proximity to Quiet Areas are explored.

 

1. INTRODUCTION

 

A key policy in Scotland’s draft National Planning Framework 4 (NPF4) is the promotion of liveable places, a key factor of which being to address longstanding inequalities [1]. Additionally, in 2015 the Scottish Government committed to align with the UN’s sustainable development goals [2]. These goals include reduced inequalities, as well as other factors which feed into an unequal distribution of deprivation such as poverty, hunger, health, education and quality of work. As exposure to high levels of noise has been linked to adverse health outcomes [3], an unequal distribution of noise exposure would contribute to existing inequalities.

 

An accompanying environmental report to NPF4 states that “people in deprived communities tend to be exposed to higher levels of noise and air pollution compared to those in less deprived areas” [4]. This statement is made in relation to two proposed national developments, the upgrading and provision of active travel and the continued revitalisation of Dundee waterfront. The statement is informed by Public Health Scotland’s briefing note to NPF4 [5], which in turn references a range of literature. However, of the literature referenced in relation to this statement, only one is specific to Scotland [6], which only correlates deprivation with higher likelihood of animal nuisance, defined as including noise and dog fouling.

 

Numerous studies have been conducted investigating the relationship between noise and deprivation in recent years. While the majority of studies indicate a relationship between high deprivation and noise levels, the findings are not conclusive [7] [8]. It is broadly suggested that any relationship is influenced by contextual factors, and that findings in one area cannot readily be translated to another.

 

There is, therefore, a need to validate this statement from NPF4 in relation to Scotland. A study has been conducted investigating whether a relationship is evident between noise exposure and deprivation using Scottish Government datasets in Scotland’s largest four cities, Glasgow, Edinburgh, Aberdeen and Dundee. The study also looks at whether a relationship between deprivation and both Noise Management Areas (NMAs) and Quiet Areas (QAs) is evident.

 

2. RELATIONSHIPS BETWEEN NOISE AND DEPRIVATION

 

An early study investigating the relationship between noise exposure and deprivation on a city wide scale was conducted in Birmingham in 2003, using the outputs of a trial for city-wide noise exposure mapping [9]. The study found weak but statistically significant relationships between noise exposure and both socioeconomic deprivation and ethnicity. In spite of this, the study also noted many areas of high deprivation without especially high noise levels and many areas of low deprivation with high levels of noise exposure, commenting that in some cases living in proximity to noise sources, such as transport hubs, might be desirable despite resultant high levels of noise exposure. A number of subsequent studies have also found a relationship between higher noise exposure and indicators of deprivation, for example in Hong Kong [10], Montreal [11], Minnesota [12], and in areas of Germany [13].

 

However, this relationship is not always found to be true. A higher socioeconomic status was linked to higher road traffic noise in Paris [14] and higher air traffic noise in the Netherlands [15]. In Marseilles it was found that noise exposure was highest for those in the middle of the scale of deprivation [16]. In some areas the relationship is complex. For example, in Barcelona no relationship was found between noise and low-income households, whereas higher noise exposure was found to be linked to unemployment [17], while in London the relationship was found to be dependent on the source of noise [18]. In Ghent a relationship between air pollution and deprivation was found, but not between noise exposure and deprivation [19]. Generally, relationships between deprivation and noise have been found to be weaker than for air quality.

 

While meta-analyses do find that it is more common for there to be a positive relationship between high noise exposure and deprivation [7] [8], it is broadly commented that any relationship is highly dependent on the local context [16]. This context could be on a large scale, for example in differences between urban planning between continents, or it could be on a local scale, for example depending on whether noisy areas of specific cities are desirable places to live. Additionally, evidence that residents buy their way out of noisy environments only holds true for small to medium sized cities [20]. A range of factors are balanced in the decision of choosing a property, of which an environmental issue such as noise is only one of many [21].

 

Perhaps understandably due transport noise being second to air pollution in terms of disease burden from environmental polluters in Europe [22], relationships between deprivation and noise are less studied than air quality [19]. A common theme among research is a need for more studies investigating any potential relationships covering more study areas [16] [8].

 

Planning policy decisions have been said to reinforce existing environmental inequalities [9] [23], in addition to the fact that deprived communities are more likely to suffer from the adverse health effects of noise exposure [7] [8]. However, ambitious policies can be effective, as has been observed in London, where the relationship between air quality and deprivation has decreased in recent years [24].

 

The European Noise Directive (END) recommends that QAs in agglomerations are protected [25], providing respite for residents subject to high levels of noise exposure and a restorative environment as a resource. QAs should be more readily available for communities which are subject to high levels of noise exposure at home. If there is a positive relationship between deprivation and noise exposure, there should also be a positive relationship between deprivation and access to QAs [8]. There is an identified lack of research in this [7], with only one study understood to have been conducted [26]. In this study it was found that likelihood of access to quiet areas reduced with a higher proportion of low-income residents, with the study defining quiet areas as areas with levels less than 55 dB rather than QAs adopted as a result of the END.

 

3. METHODOLOGY

 

The following section details the methodology adopted for this study as well as summarising associated limitations.

 

3.1. Datasets

 

A desktop study has been conducted using publicly available data published by the Scottish Government. The data comprises the Scottish Index of Multiple Deprivation (SIMD) and the noise mapping conducted for Round 3 of the END [25]. While both noise and deprivation may be predicted or rated in various ways, these datasets have been published by the Scottish Government, and have therefore been through a more rigorous review and adoption process than would be the case if redefined as part of this project. Their adoption means that any outcomes of the project less likely to be contested by policymakers. It should be considered that the noise data are based on levels modelled from 2017, while the SIMD ratings are based on data from 2020. In some cases, this may result in inconsistencies, for example in proximity to the Aberdeen Western Peripheral Route, which opened in 2019. Each dataset is summarised in more detail below.

 

Scottish Noise Mapping – Round 3: Consolidated Noise Levels

 

The analysis uses data from Round 3 of the Scottish Government’s noise mapping. The majority of studies investigate a relationship between road traffic noise and deprivation, and there is evidence to suggest that the relationship between noise and deprivation is dependent on the source type [7]. However, as the purpose of the study is to validate the statement within NPF4, which is not specific to source type, the analysis focuses on consolidated noise levels, i.e. cumulative road traffic, rail, air and industry, where applicable. The analysis focuses on L_den, the most commonly used metric for this type of study [7].

 

The noise mapping data was produced using the CNOSSOS modelling protocol [27], which uses data provided by government agencies and airports as well as acoustic data collected in proximity to large industrial sites. There are a number of shortcomings in drawing conclusions from this data, including:

• The models identify areas impacted by noise from sources which meet the thresholds for modelling, determined through non acoustic factors [28]. However, this means that other sources of noise which will contribute to the acoustic environment are not included in the consolidated noise maps.
• The consolidated noise mapping data published by the Scottish Government for download is missing various data points, which are not missing from the online interactive maps [29]. A means of accounting for this is discussed in Section 3.3, but this could have a bearing on the analysis.
• Local variations in the environment not accounted for in the modelling may have a significant impact on noise levels, in particular cobbled roads, such as those in Edinburgh’s Old and New Towns, which are generally characterised by low levels of multiple deprivation. The CNOSSOS model does allow for road surface corrections to be amended based on measurement or member state’s adopted guidance. However, there is no provision within Calculation of Road Traffic Noise to model cobbled roads [30], nor is there a suggestion in Scottish Government documents that measures were taken to address this.

 

In spite of these limitations, the fact that the modelling protocol is consistent across noise mapping exercises in Europe and that the protocol is broadly accepted is beneficial in that analyses in different areas can be meaningfully compared. Figure 1 shows the procured consolidated Round 3 noise mapping data for Glasgow.

 

 

Figure 1: Consolidated Noise Map, Glasgow

 

Scottish Noise Mapping – Round 3: Noise Management Areas

 

Candidate Noise Management Areas (CNMAs) were identified by the Scottish Government through the use of the noise maps as part of the drafting of Noise Action Plans. CNMAs represent areas which should be prioritised in the avoidance, prevention and reduction of the harmful effects of noise [31] and are identified as the top 1% affected by noise within each agglomeration. This percentile is defined based on three variables: the predicted noise level at the property; the number of people within that property; and the annoyance response of the primary noise source.

 

It is up to local planning authorities to determine which CNMAs are adopted as NMAs. These NMAs are generally not well publicised by local planning authorities, and were confirmed through freedom of information requests for this analysis. NMAs in Aberdeen are shown in Figure 2, along with QAs and buffers around QAs, both discussed below.

 

Scottish Noise Mapping – Round 3: Quiet Areas

 

The END recommends the protection of both QAs in agglomerations and QAs in open country, with both terms being differently defined. The Scottish Government only adopted the QAs in agglomerations in the Environmental Noise (Scotland) Act 2006 [32].

 

 

Figure 2: NMAs, QAs and 500m Buffers Around QAs, Aberdeen

 

The Scottish Government guidance to identify Candidate Quiet Areas (CQAs) comprises the identification of public spaces with an area greater than 9 hectares, with over 75% of the land being predicted through the noise mapping to have levels below 55 dB L_day [33]. CQAs are then presented to local authorities to determine which should be adopted as QAs. These QAs are also generally not well publicised by local planning authorities, and were confirmed through freedom of information requests for this analysis. QAs in Aberdeen are shown in Figure 2.

 

It has been shown that areas which do not conform with the criteria for CQAs in Scotland can still readily be found which provide the intended benefits of QAs [34]. As a result, and due to the arbitrary minimum size for CQAs, the adopted QAs may not directly correspond with areas most valued by residents for their low noise levels or restorative features. Accordingly, any findings of a spatial analysis of the relationship between QAs and multiple deprivation should be interpreted with relevant caution.

 

Scottish Index of Multiple Deprivation

 

Relationships between deprivation and noise exposure are more likely to be robust when using multiple indices of deprivation rather than specific indicators [8]. The Scottish Index of Multiple Deprivation (SIMD) is a multifactor measure of deprivation [35], developed by Oxford University on behalf of the Scottish Government in 1999. The measure has been used with tweaks to rank small areas (data zones) of approximately equal populations in order of deprivation in 2004, 2006, 2009, 2012, 2016 and most recently in 2020 [36].

 

The metric combines 33 measurands in seven weighted categories: income (28%); employment (28%); health (14%), education, skills and training (14%); geographical access to services (9%); crime (5%); and housing (2%). The data zones are then ranked by score. Figure 3 shows the mapped SIMD data for Glasgow grouped in vigintiles.

 

 

Figure 3: SIMD Distribution, Glasgow

 

Guidance provided by the Scottish Government recommends that the SIMD can be used to find areas where many people experience multiple deprivation and for the comparison of overall deprivation of small areas [35], as required in this study. The supplementary guidance does clarify that there is significant variation of deprivation within each data zone, and that the ranking is relevant at a population rather than individual level. It also clarifies that analyses in urban areas are more robust than in rural areas and that a linear relationship between the ranking and magnitude of deprivation cannot be assumed [35].

 

It is recommended that the SIMD is not used to compare deprivation between countries. The metrics and method used to determine the SIMD might not be directly comparable to deprivation in other countries. However, as this study looks at the relationship between noise exposure and deprivation, there is benefit in using definition of multiple deprivations which is relevant for the specific country in question. This allows the context of each country to be considered in a way which is relevant to its population.

 

3.2. Study Areas

 

As described in supplementary guidance, caution should be applied in the analysis of SIMD data in rural areas [35]. The study, therefore, focusses on Glasgow, Edinburgh, Aberdeen and Dundee, the four largest metropolitan areas in Scotland, each of which is defined as an agglomeration in accordance with the END [28], therefore having more comprehensive consolidated noise maps. Smaller cities and towns across Scotland have fewer sources which meet the thresholds for being inclusion in the END modelling, and therefore less accurately reflect actual noise levels within the area.

 

3.3. Analysis

 

A spatial analysis has been carried out using both sets of spatial data. The SIMD data is analysed in vigintiles. The consolidated noise exposure level is presented in seven bands: <55, 55 – 60, 60 – 65, 65 – 70, 70 – 75, 75 – 80 and >80 dB L_den. Due to the small number of areas with noise levels greater than 80 dB L_den, the upper two categories have been combined in analysis to reduce the influence of random distribution in small datasets.

 

A limitation of the spatial analysis is the modifiable area unit problem (MAUP), whereby the arbitrary grouping of spatial areas can impact the findings of the survey. Generally, a good method to reduce the impact of MAUP is to use the finest spatial resolution available [19]. In this case, the purpose of the study is to determine whether a relationship between noise and deprivation is evident using Scottish Government published datasets. As a result, the implications of MAUP are defined to some extent by the SIMD data and the noise mapping data resolution. However, measures have been taken to minimise the effects of MAUP as far as practical through the analysis of data using vigintiles of multiple deprivation and the use of six noise categories, as opposed to the three from which Scottish Government draw key conclusions. Additionally, within each SIMD data zone there are often numerous bands of noise exposure. Each SIMD data zone will have its own distribution of deprivation, which is not identified in the analysis.

 

As discussed in Section 3.1, the published consolidated data is missing packets of data. The missing data has been visually interpreted and it appears to be randomly distributed both spatially and across noise exposure categories. As a result, SIMD data zones have been trimmed to remove areas corresponding to the missing noise data. The populations of the trimmed data zone have been estimated based on their population density and trimmed area. The estimated population exposed to each category of noise is based on the population density of each SIMD data zone, and the overlapping area of each noise category and data zone.

 

As the SIMD ranks areas on a national basis, each agglomeration has its own distinct distribution of multiple deprivation. The results have been normalised based on each agglomeration’s distribution of multiple deprivation. Models of multiple linear regression are used to investigate the interaction between noise exposure and multiple deprivation and find the corresponding p-value.

 

Similar methods of analysis were conducted for QAs and NMAs, however with specific considerations for each area. Different regions define their NMAs differently. For example, in Glasgow, NMAs are identified as the portion of the source which results in excessive noise exposure, while Aberdeen identifies an area which encompasses residential properties and the source. Where the identified areas encompass source and residential buildings, the whole area was used for analysis, otherwise the affected residential areas were used for analysis.

 

QAs represent the publicly accessible area within an agglomeration. As a result, these amenities are most accessible to the surrounding population. Therefore, analysis has been conducted within a 500m buffer zone. The QAs and associated buffer zones in Aberdeen are shown in Figure 2. It is acknowledged that within this buffer there will be significant variation in accessibility to the QA, and future analysis could refine this by defining a buffer area based on walking time rather than radius.

 

4. RESULTS AND DISCUSSION

 

4.1. Noise Exposure and Deprivation

 

Only in Glasgow was a statistically significant relationship found between noise exposure and multiple deprivation (p=0.05). The relationship was found to be positive, i.e. areas of high noise exposure are more likely to be located in areas with high multiple deprivation. Relationships in Aberdeen (p=0.16), Dundee (p=0.54) and Edinburgh (p=0.18) were found to be not significant.

 

In spite of the relationship in Edinburgh not being statistically significant, the analysis suggests there might be the opposite trend to that of Glasgow. This different trend appears to be due to two important contextual factors, which should be tested further:

• Edinburgh’s UNESCO World Heritage Old and New Towns result in more desirable city centre living than in Glasgow.
• Edinburgh does not have any high speed roads within the City Bypass, in comparison to Glasgow which has four motorways running through the city. As a result, living in proximity to the western extent of the Edinburgh City Bypass and the eastern end of the M8 is desirable in that it enables more efficient commuting to Glasgow, Lanarkshire and the central belt. This area is characterized by high noise levels and low deprivation.

 

Considering Aberdeen, Dundee and Edinburgh, it should be noted that a lack of statistically significant relationship does not necessarily mean that a relationship does not exist, but only that a relationship is not evident using these datasets. However, this finding suggests that the statement in NPF4 may not be attributable across the whole of Scotland. Specifically, the use of the statement in relation to Dundee Waterfront should be further investigated given that Dundee was found to have the weakest relationship between noise and multiple deprivation.

 

4.2. Noise Management Areas and Deprivation

 

Given the above, it might be expected that the same broad conclusions are found with regards to the relationship between NMAs and multiple deprivation. However, no significant relationship is found in Aberdeen (p=0.34), Edinburgh (p=0.35) or Glasgow (p=0.17). A significant relationship is found in Dundee (p=0.03), where NMAs are more likely to be situated in areas of high multiple deprivation. This is interesting given that Dundee was found to have the weakest relationship between noise and multiple deprivation. However, it should also be considered that there are only three NMAs in Dundee. This small sample size might account for the significant relationship.

 

4.3. Quiet Areas and Deprivation

 

No significant correlations were found between proximity to QAs and multiple deprivation in Aberdeen (p=0.45), Dundee (p=0.33) or Edinburgh (p=0.16). In Glasgow a positive relationship between proximity to QAs and multiple deprivation was observed, and this was found to be significant (p<0.01).

 

This finding is interesting in that only in Glasgow is a significant positive relationship between noise and deprivation found, and there is also a significant positive relationship between proximity to QAs and multiple deprivation. On the face of it this might suggest that communities facing higher levels of multiple deprivation are more likely to be subject to higher levels of noise exposure, but have a greater likelihood of access to QAs for respite from noise exposure. However, further analysis would be required to confirm this, as it is not evident whether the areas facing higher levels of multiple deprivation which are subject to higher noise exposure are also those in proximity to QAs.

 

5. CONCLUSIONS AND FURTHER WORK

 

An environmental report accompanying NPF4 statesthat deprived communitiestend to be exposed to higher levels of noise. However, this relationship has not been explicitly tested in Scotland. The literature suggests that any relationship is highly dependent on context and findings from one location cannot readily be translated to another. A study has been conducted to validate this statement in Aberdeen, Dundee, Edinburgh and Glasgow using Scottish Government datasets, the SIMD and the Round 3 noise mapping data. Only in Glasgow is a statistically significant relationship found, with a higher likelihood of high noise exposure affecting areas of high multiple deprivation. However, no statistically significant relationship was found for Aberdeen, Dundee and Edinburgh. Further, in Edinburgh a trend, while not statistically significant, suggests that areas of high noise exposure might be more likely to affect areas of low multiple deprivation, and the different urban contexts of Glasgow and Edinburgh are discussed with regards to the different relationships.

 

Only in Dundee was a statistically significant relationship found between deprivation and NMAs, with NMAs more likely to be located in areas of higher multiple deprivation, however the findings could be influenced by the small number of NMAs in Dundee. A significant relationship between proximity to QAs and deprivation was found in Glasgow, with QAs more likely to be located in proximity to areas of high deprivation. This appears to support the intended use of QAs, to provide areas of respite from noise for those subject to high levels of noise exposure. However, this study has not looked at whether the communities subject to high levels of noise exposure are also those in proximity to QAs, and this is an important point of clarification that is needed to be investigated further before drawing firm conclusions.

 

Across the analysis, it should be considered that a lack of apparent statistically significant relationship does not mean there is no relationship between noise exposure and multiple deprivation, but that it is not evident using the Scottish Government datasets. Further work should address the limitations identified in this study, which could provide firmer conclusions. Some limitations could be addressed which might find different conclusions from the same datasets. For example, procuring the missing data from the consolidated noise maps, correlating the population with known residential buildings rather than assuming an even distribution within each data zone or the use of spatial autocorrelation in the analysis might all lead to different findings [19]. The use of other datasets could also lead to different conclusions, however they would not not benefit from being adopted by the Scottish Government, and therefore may not be seen with the same strength in terms of informing policy decisions.

 

6. REFERENCES

 

1. Scottish Government. Scotland 2045 - Our Fourth National Planning Framework: Draft, Edinburgh (2021).
2. Scottish Government. Scotland and the Sustainable Development Goals - A National Review to Drive Action Edinburgh (2020).
3. World Health Organization. Environmental Noise Guidelines for the Europe Region, World Health Organization, Copenhagen (2018).
4. Scottish Government. Scotland 2045 - Scotland's Fourth National Planning Framework: Draft - Integrated Impact Assessment Environmental Report, Edinburgh (2021).
5. Public Health Scotland. National Planning Framework 4: Briefing on Health and Proposed National Developments, (2021).
6. Scottish Government. Scotland's People. Annual Report: Results from 2012. Scottish Household Survey, Edinburgh (2013).
7. Trudeau, C & Guastavino, C. Environmental Inequality of Sound Environments: A Comparative Analysis, The 13th ICBEN Congress on Noise as a Public Health Problem, Stockholm. (2021).
8. Dreger, S, Schüle, S. A., Hilz, L. K. & Bolte, G. Social Inequalities in Environmental Noise Exposure: A Review of Evidence in the WHO European Region, International Journal of Environmental Research and Public Health, 16(6) (2019).
9. Brainard, J. S., Jones, A. P., Bateman, I. J. & Lovett, A. A. Exposure to Environmental Urban Noise Pollution in Birmingham, UK, Urban Studies, 41(13) (2004).
10. Lam, K.-C. & Chan, P.-K. Socio-economic Status and Inequalities in Exposure to Transportation Noise in Honk Kong, Environmental Sciences, 2 (2008).
11. Dale, L. M., Goudreau, S., Perron, S., Ragettli, M. S., Hatzoloulou, M. & Smargiassi, A. Socioeconomic Status and Environmental Noise Exposure in Montreal, Canada, BMC Public Health, 15 (2015).
12. Nega, T. H., Chihara, L., Smith, K. & Jayaraman, M. Traffic Noise and Inequality in the Twin Cities, Minnesota, Human and Ecological Risk Assessment: An International Journal, 19(3) (2013).
13. Hoffman, B., Robra, B. P. & Swart, E. Social Inequality and Noise Pollution by Traffic in the Living Environment - An Analysis by the German Federal Health Survey, Gesundheitswesen, 65(6) (2003).
14. Harvard, S., Reich, B. J., Bean, K. & Chaix, B. Social Inequalities in Residential Exposure to Road Traffic Noise: An Environmental Justice Analysis based on the RECORD Cohort Study, Occupational and Environmental Medicine, 68(5) (2011).
15. Kruize, H. & Bouwman, A. A. Environmental (In) Equity in the Netherlands - A Case Study on the Distribution of Environmental Quality in the Rijnmond Region, (2004).
16. Bocquier, A., Cortaredona, S., Boutin, C., David, A., Bigot, A., Chaix, B., Gaudart, J. & Verger, P., Small-area Analysis of Social Inequalities in Residential Exposure to Road Traffic Noise in Marseilles, France, European Journal of Public Health, 23(4) (2013).
17. Lagonigro, R., Martori, J. C. & Apparicio, P. Environmental Noise Inequity in the City of Barcelona, Transportation Research Part D: Transport and Environment, 63 (2018).
18. Tonne, C., Milà, C., Fecht, D., Alvarez, M., Gulliver, J., Smith, J., Beevers, S., Anderson, H. R. & Kelly, F. Socioeconomic and Ethnic Inequalities in Exposure to Air and Noise Pollution in London, Environment International, 115 (2018).
19. Varbeek, T., Unequal residential exposure to air pollution and noise: a geospatial environmental justice analysis for Ghent, Belgium, SSM-population health, 7 (2019).
20. Fyhri, A. & Klæboe, R. Direct, Indirect Influences of Income on Road Traffic Noise Annoyance, Journal of Environmental Psychology, 26(1) (2006).
21. Hite, D. A Random Utility Model of Environmental Equity, Growth and Change, 31(1) (2000).
22. World Health Organization, Burden of Disease from Environmental Noise - Quantification of Healthy Life Years Lost in Europe, World Health Organization, Copenhagen (2011).
23. Riedel, N., van Kamp, I., Dreger, S., Botle, G., Andringa, T., Payne, S. R., Schreckenberg, D., Fenech, B., Lavia, L., Notley, H., Guski, R., Simon, D., Kolcher, H., Bartels, S., Weber M. & Paviotti, M. Considering 'Non-acoustic Factors' as Social and Environmental Determinants of Health Equity and Environmental Justice. Reflections on Research and Fields of Action towards a Vision for Environmental Noise Policies, Transportation Research Interdisciplinary Perspectives, 11 (2021).
24. Logica Air Quality Consultants, Air Pollution and Inequalities in London 2019 Update (2021).
25. The European Parliament, Directive 2002/49/EC of the European Parliament and of the Council of 25 June 2002 Relating to the Assessment and Management of Environmental Noise, Official Journal of the European Communities, L189(EN) (2002).
26. Delaunay, D., Apparicio, P., Séguin, A.-M., Gelb, J. & Carrier, M., L'identification des zones calmes et un diagnostic d’équité environnementale à Montréal, The Canadian Geographer/Le Géographe canadien, 62(2) (2019).
27. Institute for Health and Consumer Protection, Common noise assessment methods in Europe (CNOSSOS-EU), European Commission (2012).
28. The Scottish Government, Guidance on Noise Action Planning (2007).
29. Scottish Government, Scotland's Noise - Noise Map, [Online]. Available: https://noise.environment.gov.scot/noisemap/ [Accessed 18 April 2022].
30. Department of Transport, Calculation of Road Traffic Noise (1988).
31. Scottish Government, Technical Guidance for CNMA to NMA.
32.  Scottish Government, The Environmental Noise (Scotland) Regulations 2006, (2006).
33. Scottish Government, Technical Guidance for Quiet Areas, under Strategic Noise Action Plans.
34. Payne, S. & Bruce, N. Exploring the Relationship between Urban Quiet Areas and Perceived. Restorative Benefits, Journal of Environmental Research and Public Health, 16(9) (2019).
35. Scottish Government, Introducing the Scottish Index of Multiple Deprivation 2020, Edinburgh (2020).
36. Scottish Government, SIMD 2020 Technical Notes, Edinburgh (2020).

 

---

¹ Ashley.Leiper@sse.com

² AHood@envirocentre.co.uk