ARTICLE IN PRESS. Renewable Energy

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1 Renewable Energy xxx (2009) 1 10 Contents lists available at ScienceDirect Renewable Energy journal homepage: Relationships between environmental noise and social economic factors: Case studies based on NHS hospitals in Greater London Hui Xie, Jian Kang * School of Architecture, University of Sheffield, Western Bank, Sheffield S10 2TN, UK abstract Keywords: Noise NHS Hospital Social Economic Greater London Sound environment is an important part of the overall environmental sustainability. For example, the windows of buildings in noisy environments often need to be sealed, which would discourage low energy strategies based on natural ventilation. The aim of this study is to investigate the relationships between environmental noise levels, especially in hospitals, and selected social economic factors; as well as to determine how noisy the NHS (National Health Service) hospitals in Greater London are. Calculated noise maps are used through a series of data processing, and 28 social and economic factors are considered. As expected, the NHS hospitals in Inner London are considerably noisier than those in Outer London, by 5.4 dba in average. It is shown that the environmental noise levels of NHS hospitals in Greater London have close relationships with a number of social economic factors. Generally speaking, with a higher noise level in an area, the household size is smaller and there are more one-person households. Detached, semi-detached and terraced houses are more likely located in relatively quieter areas, while flats are more likely to be found in noisier areas. This is also associated with the unemployment rate, which tends to be higher in noisier areas. The pupil/teacher ratio has a significant negative correlation with noise levels. It is interesting to note that although the population factors, including population density, total fertility rate and crude death rate, have significant correlations with the environmental noise levels, correlations between noise levels and residents health conditions are rather low. Ó 2009 Elsevier Ltd. All rights reserved. 1. Introduction Noise, defined as unwanted sounds, could affect people both psychologically and physiologically [1], with reported effects including cardiovascular stimulation, hearing loss, increased gastric secretion, pituitary and adrenal gland stimulation, suppression of the immune response to infection, as well as female reproduction and fertility [2 7]. The World Health Organisation (WHO) recommended that noise levels within hospital wards should not surpass 30 dba in terms of sleep disturbance [8]. Unfortunately, many case studies show that noise levels inside hospitals are much higher than the guideline values [9 11]. Since the 1960s the average noise levels inside hospitals have increased by an average of 0.38 dba (day) and 0.42 dba (night) per year [11]. Noise is often on the top list of complaints by patients and staff, whereas little work has been done to characterise and reduce hospital noise. The increased noise * Corresponding author. Tel.: þ ; fax: þ address: j.kang@sheffield.ac.uk (J. Kang). levels are caused both by the increased use of hospital equipment, and the increased environmental noise around hospitals. In noisy environments the windows of buildings often need to be sealed, which would discourage low energy strategies (a key to sustainability) based on natural ventilation. Greater London covers 1579 km 2 and had a 2005 mid-year estimated population of 7,517,700 [12]. Given the high environmental noise level in London, 58.0 dba in day time and 49.7 dba in night time (outside buildings) according to the Building Research Establishment (BRE) s report in 2001 [13], the Greater London Authority (GLA) has paid great attention to the noise issues and is leading the way for the UK with the first city-wide strategy for ambient noise in Considering the health and well being of Londoners, the strategy focuses on reducing noise through better management of transport systems, better town planning and better design of buildings [14]. In a questionnaire survey in 2003 with a sample of residents across Greater London, people were asked Thinking about the quality of the environment in London, how much of a problem, if at all, do you consider noise to be? 46% of the respondents considered /$ see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi: /j.renene

2 2 H. Xie, J. Kang / Renewable Energy xxx (2009) 1 10 Fig. 1. An example showing the data processing of a noise map: (a) typical noise map of a London hospital [19]; (b) matrix A, representing the noise distribution in the hospital site; (c) matrix B, representing the noise environment around the hospital buildings. Note: Fig. 1b and c represent the noise levels around the building at the bottom of Fig. 1a.

3 H. Xie, J. Kang / Renewable Energy xxx (2009) Fig. 2. Interactive map from the Focus on London 2003 [24]. noise to be a problem (13% major problem, 33% lower level of problem), and 24% included noise in their two or three top priorities for improving the quality of the environment in London [15]. In the last two decades there have been many major new developments in the field of urban sound environment in terms of research and practice [1]. Recently noise mapping has become an essential requirement, especially in Europe [16,17], and corresponding software/techniques have been widely used in practice [18 21]. Those research and practical works, however, mostly concern the general noise distribution across a large urban area, rather than concentrating on a specific building type. In particular, the study on the environmental noise of hospitals has been very limited. The aim of this study is to investigate the relationships between environmental noise levels, especially in hospitals, and selected social economic factors; as well as to determine how noisy the Table 1 Data of population factors in London boroughs. Factors Population density (per sq km) Population change (%) Crude birth rate (per 1000 population) Total fertility rate Crude death rate (per 1000 population) City of London City of Westminster Kensington and Chelsea Hammersmith and Fulham Wandsworth Lambeth Southwark Tower Hamlets Hackney Islington Camden Brent Richmond Kingston upon Thames Sutton Croydon Bromley Lewisham Greenwich Bexley Havering Barking and Dagenham Redbridge Newham Waltham Forest Haringey Enfield Barnet Harrow Hillingdon Standardised mortality ratio (UK ¼ 100)

4 4 H. Xie, J. Kang / Renewable Energy xxx (2009) 1 10 Table 2 Data of household factors in London boroughs. Factors Household size (people) Lone-parent households (%) One-person households (%) Detached houses (%) Semi-detached houses (%) Terraced houses (%) Purpose-built flats (%) City of London City of Westminster Kensington and Chelsea Hammersmith and Fulham Wandsworth Lambeth Southwark Tower Hamlets Hackney Islington Camden Brent Richmond Kingston upon Thames Sutton Croydon Bromley Lewisham Greenwich Bexley Havering Barking and Dagenham Redbridge Newham Waltham Forest Haringey Enfield Barnet Harrow Hillingdon Flats in converted houses (%) Table 3 Data of economic factors in London boroughs. Factors Economic activity rate (%) Employment rate (%) Claimant count rate (%) Claimant count > 1 year (%) Income support beneficiary (%) Employee jobs in manufacturing (%) City of London N/A N/A City of Westminster Kensington and Chelsea Hammersmith and Fulham Wandsworth Lambeth Southwark Tower Hamlets Hackney Islington Camden Brent Richmond Kingston upon Thames Sutton Croydon Bromley Lewisham Greenwich Bexley Havering Barking and Dagenham Redbridge Newham Waltham Forest Haringey Enfield Barnet Harrow Hillingdon Employee jobs in services (%)

5 H. Xie, J. Kang / Renewable Energy xxx (2009) Table 4 Data of educational factors in London boroughs. Factors Pupil/teacher ratio in primary school Pupil/teacher ratio in secondary school Expenditure/pupil in pre-primary and primary school ( ) Expenditure/pupil in secondary school ( ) City of London N/A N/A 4727 N/A N/A City of Westminster Kensington and Chelsea Hammersmith and Fulham Wandsworth Lambeth Southwark Tower Hamlets Hackney Islington Camden Brent Richmond Kingston upon Thames Sutton Croydon Bromley Lewisham Greenwich Bexley Havering Barking and Dagenham Redbridge Newham Waltham Forest Haringey Enfield Barnet Harrow Hillingdon Pupil with statements (%) Table 5 Data of health conditions in London boroughs. Factors Long-term illness (%) Claiming good health (%) City of London City of Westminster Kensington and Chelsea Hammersmith and Fulham Wandsworth Lambeth Southwark Tower Hamlets Hackney Islington Camden Brent Richmond Kingston upon Thames Sutton Croydon Bromley Lewisham Greenwich Bexley Havering Barking and Dagenham Redbridge Newham Waltham Forest Haringey Enfield Barnet Harrow Hillingdon NHS (National Health Service) hospitals in Greater London are, given that Greater London has the largest number of hospitals among all the areas in the UK. This in turn will contribute to the overall low energy strategy of hospital buildings. 2. Methodology Based on the NHS official website [22], 79 NHS hospitals in Greater London were selected and verified in accordance with the availability of appropriate noise maps [19]. Data in both noise and social economic aspects were then collected. The former were based on published noise map data and the latter were from some commercial survey companies or official sources. The two sets of data were then integrated and analysed using statistics software SPSS. For the analysis a series of data processing of the noise maps was made using MATLAB. The noise and social economic data were put in the same geographical system, where the geographical platform was the London boroughs Processing of noise map data The data used for the noise levels of hospitals in Greater London are from the database called London noise maps [19], which consider road traffic noise sources. The maps represent the average noise levels at a height of 4 m above the local ground level, where it is assumed that the roads are dry but the wind is adverse, namely blowing from the road to the receiving position. The published colour noise maps have been processed to obtain digital numbers for the subsequent analysis. The studied area of a given hospital was firstly identified from the noise map database according to the postcode. Each noise map

6 6 H. Xie, J. Kang / Renewable Energy xxx (2009) 1 10 Fig. 3. The boroughs of Greater London. obtained usually contains many other buildings and areas around the hospitals. In order to make sure that every building of the studied hospital was not excluded, the hospital boundary should be accurately identified. This was carried out according to the detailed site map or the hospital layout from its own website and the Ordnance Survey Map [23]. A MATLAB program has been developed for the data processing of noise maps [21]. Fig. 1a illustrates a typical noise map of a NHS hospital in Greater London, where each colour represents a 5 dba difference. When a noise map is read into MATLAB, the program will automatically replace all the colours by the corresponding noise values in a 2D grid system with a given resolution. Correspondingly, two sets of matrix are generated. In matrix A, as illustrated in Fig.1b, 0 represents the location of building blocks, 90 represents the areas outside the hospital site, and other values indicate the actual noise levels in dba at grid points within the hospital site. Based on matrix A, matrix B is produced, as illustrated in Fig. 1c, to represent the noise environment around the hospital buildings, i.e. only the noise levels at the grid points representing the locations at 1 m outside the hospital buildings are kept, and all the other values are assigned as 0. It should be noted that Fig. 1b and c represents the noise levels around the building at the bottom of Fig. 1a. Having identified all the buildings of a hospital and their noise levels, the next step is to find out the indices of noise levels for this hospital. Six noise indices are used in this research, including the average noise level L ave (dba), maximum noise level L max (dba), minimum noise level L min (dba), intrusive noise level L 10 (dba), median noise level L 50, and background noise level L 90 (dba). It is noted that L n generally represents the level of noise exceeded for n% of the specified measurement period, whereas in this research they are used to represent spatial rather than temporal distribution. In other words, if N noise level values are obtained for a hospital from matrix B and they are sorted in an descending order, then L n is the (100 n/n)th noise levels in the order Social economic factors The effects of various social and economic factors on the noise evaluation have been intensively studied [1], although not specifically for hospitals. In this research, 28 factors, which might affect noise assessments based on previous research, were selected from the Focus on London 2003, which is a statistical digest bringing together a wide range of demographic, social, industrial and economic statistics to provide a comprehensive view of London [24]. It is produced jointly by the Office for National Statistics, the Government Office for London, the Greater London Authority and the London Development Agency. As illustrated in Fig. 2, the factors used included: 1. population density by borough (people per sq km), 2001; 2. population change, from 1991 to 2001(%); 3. crude birth rate (per 1000 population), 2001; 4. total fertility rate, 2001; 5. crude death rate (per 1000 population), 2001; 6. standardised mortality ratio (UK ¼ 100), 2001; 7. average household size (people), 2001; 8. lone-parent households (% of all households), April 2001; 9. one-person households (% of all households), April 2001; 10. detached houses (% of all household spaces), April 2001; 11. semi-detached houses (% of all household spaces), 2001; 12. terraced houses (% of all household spaces), 2001; 13. purpose-built flats (% of all household spaces), 2001; 14. flats in converted houses (% of all household spaces), 2001; 15. economic activity rate (%), from March 2001 to February 2002; 16. employment rate (%), from March 2001 to February 2002; 17. claimant count rate (%), October 2002; 18. claimant count: % claiming for more than 1 year, October 2002; 19. income support beneficiaries (% of the population aged 16 or over), 2002; Table 6 Comparison in noise levels (dba) of NHS hospitals between Inner (38 sampled hospitals) and Outer (41 sampled hospitals) London. Mean Standard deviation (STD) t-test for equality of means Inner London Outer London Inner London Outer London Mean difference Sig. (2-tailed) L ave L max L min L L L

7 H. Xie, J. Kang / Renewable Energy xxx (2009) Table 7 Environmental noise levels (dba) of NHS hospitals grouped by London boroughs. Noise indices L ave L max L min L 90 L 50 L 10 City of London City of Westminster Kensington and Chelsea Hammersmith and Fulham Wandsworth Lambeth Southwark Tower Hamlets Hackney Islington Camden Brent Richmond Kingston upon Thames Sutton Croydon Bromley Lewisham Greenwich Bexley Havering Barking and Dagenham Redbridge Newham Waltham Forest Haringey Enfield Barnet Harrow Hillingdon and 32 London boroughs. It is officially divided into Inner and Outer London, with varying definitions. For this research, Inner London Education Authority (ILEA) s definition was adopted, as illustrated in Fig. 3. According to the definition, Inner London consists of those boroughs whose former area comprised the County of London [26]: Camden, Greenwich, Hackney, Hammersmith and Fulham, Islington, Kensington and Chelsea, Lambeth, Lewisham, Southwark, Tower Hamlets, Wandsworth, and City of Westminster. Inner London is the third-richest inner city in the European Union, with a GDP per capita of 48,425 in 2004, after Paris and Frankfurt [25]. The City of London is not a London borough but it can be included in Inner London. The Outer London includes Barking and Dagenham, Barnet, Bexley, Brent, Bromley, Croydon, Ealing, Enfield, Haringey, Harrow, Havering, Hillingdon, Hounslow, Kingston upon Thames, Merton, Newham, Redbridge, Richmond upon Thames, Sutton, and Waltham Forest Data analysis The statistical software SPSS was used for the data analysis. For the investigation of how noise levels and social economic factors are related, the Pearson correlation was applied. In order to compare the environmental noise levels of hospitals in Inner and Outer London, the independent-samples t test was performed. It is noted that while the focus of this study is the environmental noise levels of NHS hospitals, those levels can also represent, to a certain extent, the overall environmental noise levels of an area. As a result, some of the analyses below are for general noise levels rather than hospital levels specifically. 20. employee jobs in manufacturing industries (as % of all employee jobs), 2001; 21. employee jobs in service industries (as % of all employee jobs), 2001; 22. pupil/teacher ratio: maintained primary schools, 2001/02; 23. pupil/teacher ratio: maintained secondary schools, 2001/02; 24. expenditure per pupil, pre-primary/primary education ( ), 2001; 25. expenditure per pupil, secondary education ( ), 2001/02; 26. pupils in maintained schools: with statements of special educational needs (%), 2001/02; 27. people with limiting long-term illness (%), April 2001; and 28. people claiming good health (%), April In the analysis below the 28 factors are divided into five categories, including population (factors 1w6), household (factors 7w14), economy (factors 15w21), education (factors 22w26) and health (factors 27w28). Tables 1 5 show the data of each of the five categories, respectively, considering all London boroughs. The administrative area of Greater London covers the City of London 3. Results 3.1. Comparison of environmental noise levels of NHS hospitals between Inner and Outer London Table 6 compares the six noise indices, namely the average, maximum, minimum, spatial intrusive, median and background noise levels between hospitals located in Inner and Outer London. It can be seen that the former is significantly higher than the latter, as expected. Whilst the differences in the six noise indices range from 2.7 dba to 12.7 dba, the difference in the average noise level L ave is 5.4 dba. It is interesting to note that the general noise level in Outer London, based on the site measurements carried out by the BRE in 2001 considering seven boroughs including Kingston upon Thames, Havering, Enfield, Harrow, Redbridge, Croydon and Waltham Forest [13], is considerably higher than the average noise level of NHS hospitals in Outer London, by about 8 dba. A possible reason is that the hospital sites are usually rather large and thus, there are many internal façades, which are not directly exposed to road traffic. Table 8 Correlation between hospital noise levels and population factors, where the significance levels (2-tailed) are also shown. Population density Population change Crude birth rate Total fertility rate Crude birth rate Mortality ratio L ave ** * * L max ** * L min ** ** L * * ** L ** * ** L ** * ** indicates p < * indicate p < 0.05.

8 8 H. Xie, J. Kang / Renewable Energy xxx (2009) 1 10 Table 9 Correlation between hospital noise levels and household factors, where the significance levels (2-tailed) are also shown. Household size Lone-parent household One-person household Detached houses Semi-detached houses Terraced houses Purpose-built flats L ave ** ** * ** ** ** ** L max * ** * ** * * ** L min * ** ** ** * ** ** L * ** * ** * ** ** L ** ** * ** ** ** ** L * * * * * ** ** indicates p < * indicate p < Flats in converted houses 3.2. Correlations between the environmental noise levels and social economic factors Except for Ealing, Hounslow and Merton, all the other 30 boroughs, including City of London, have more than one NHS hospital selected for this study. In this section the relationships between the environmental noise levels of NHS hospitals and the social economic factors are analysed by treating each borough as a sample. Table 7 shows the environmental noise levels (dba) of NHS hospitals grouped by London boroughs Population factors (factors 1w6) Table 8 shows the correlations between the hospital noise levels and the population factors, including population density, population change, crude birth rate, total fertility rate, crude death rate and standardised mortality ratio, by treating each borough as a sample. It is noted that in Table 8 and other tables in this paper, ** indicates p < 0.01 and * indicates p < It is interesting to note that the population density has a significant positive correlation with the noise level (p < 0.01 except for L 90 ). The correlation coefficient is in terms of L ave. In other words, the boroughs with a higher population density would also have nosier hospitals. Both the total fertility rate and crude death rate have significant negative correlations with the hospital noise level. A possible reason is that, generally speaking, the death rate is mainly affected by the number of old people, who may tend to live away from noisy areas. For young couples, after they decide to have children, they may also move to a quiet and less dense area. For the other three population factors, namely population change, crude birth rate, and standardised mortality ratio, their correlations with noise levels are generally not significant Household size and type (factors 7w14) The correlations between hospital noise levels and various household factors are shown in Table 9. It can be seen that almost all the household factors of London boroughs have significant correlations with the noise levels of the NHS hospitals. With a higher noise level, the household size is smaller and there are more one-person households. This could suggest that larger families may tend to prefer quiet environment, especially families with children, which is also suggested by the results in Table 8. The results in Table 9 also demonstrate that detached, semidetached and terraced houses are more likely to be located in areas with relatively lower noise levels, while flats including purposebuilt flats and flats in converted houses are more likely to be found in noisier areas. It is interesting to note that flats in converted houses have the highest correlation coefficients with the noise levels, around Economic issues (factors 15w21) Table 10 shows the correlations between hospital noise levels and seven economic factors. While no clear correlation is shown in terms of economic activity rate, employment rate and income support beneficiaries, the claimant count has a significantly positive relationship with noise levels. The claimant count is the UK s most timely measure of unemployment, for it serves as a barometer for the health of the UK labour market. It measures the number of people who claim unemployment benefits, but actively seeking work. The index claimant count > 1 year represents those who have been claiming for more than 12 months as a percentage of all claimants [24]. The results in Table 10 suggest that the unemployment rate tends to be higher in noisier areas. The results in Table 10 also suggest that noise level may influence the employee job sectors to a certain extent. It seems that in relatively noisy area there are less manufacturing jobs but more services jobs. It is noted, however, that the results in terms of job sectors are based on limited sample size and therefore, further studies are still needed Educational factors (factors 22w26) The relationships between noise levels and education factors are shown in Table 11. It can be seen that the pupil/teacher ratio in primary and secondary schools has a significant negative correlation with the noise levels, which means that the pupil/teacher ratio is lower in nosier areas. On the other hand, expenditure per pupil in pre-primary, primary and secondary educations has a positive correlation with the noise levels. It is also interesting to note that in Table 10 Correlation between hospital noise levels and economic factors, where the significance levels (2-tailed) are also shown. Economic activity rate Employment rate Claimant count rate Claimant count >1 year Income support beneficiary Employee jobs in manufacturing Employee jobs in services L ave * ** * ** L max * ** ** ** L min ** ** * ** * L * * ** * L ** ** L * ** * ** ** indicates p < * indicate p < 0.05.

9 H. Xie, J. Kang / Renewable Energy xxx (2009) Table 11 Correlation between hospital noise levels and educational factors, where the significance levels (2-tailed) are also shown. Pupil/teacher ratio in primary school Pupil/teacher ratio in secondary school Expenditure/pupil in pre-primary and primary school Expenditure/pupil in secondary school L ave ** ** * * L max ** * * * L min * * ** ** L * * ** * L ** * L ** ** * ** indicates p < * indicate p < Pupil with statements Table 11 the correlation coefficients between the factors of primary education and hospital noise level are generally higher than those of secondary education. In terms of the pupils in maintained schools with statements of special educational needs, the correlation with noise levels is insignificant. According to the National Statistics [24], the pupil/teacher ratio only refers to the public sector schools, excluding the private or independent schools. In England and Wales, only qualified teachers are included for public sector schools. This means that all other teaching staffs at these schools are excluded. The pupil / teacher ratio in a school is the ratio of all pupils on the register to all qualified teachers employed within the schools during the census week. Part-time teachers and part-time pupils are included on a full-time equivalent basis [24]. A low pupil/pupils ratio (i.e. each teacher being responsible for only a few pupils) is often used as a selling point to those choosing schools. However, according to School s Census sponsored by the Department for Education and Skills (DfES) in the UK, from 2001 to 2003, the total number of the registered pupils in public sector schools in Greater London increased slightly by 0.36%, but the number of teachers reduced by 2.45% on the contrary [27,28]. That means the pupil/teacher ratio is increasing gradually on a national scale. Whilst parents and pupils may not prefer a noisy school, the pupil/teacher ratio may play a more important role in attracting more pupils. On the other hand, since the total fertility rate in noisy boroughs is relatively low, less and less potential pupils will be born and then register in the primary and secondary schools in those boroughs Health conditions (factors 27w28) Although the population factors have significant correlations with the environmental noise levels, it is rather surprising that the correlations between noise levels and residents health conditions, including long-term illness and claiming good health are generally low and not significant, as shown in Table 12. A possible reason is that noise at this level could make residents annoying and uncomfortable, but the health effects are not significant. Table 12 Correlation between hospital noise levels and health conditions, where the significance levels (2-tailed) are also shown. Long-term illness Claiming good health L ave L max L min L L L ** indicates p < * indicate p < Conclusions The analysis of noise map data shows that the NHS hospitals in Inner London are much noisier than those in Outer London, with a difference in average noise level of 5.4 dba. The environmental noise levels of NHS hospitals in Greater London have close relationships with a number of social economic factors. Generally speaking, with a higher noise level in an area, the household size is smaller and there are more one-person households. Detached, semi-detached and terraced houses are more likely located in relatively quieter areas, while flats are more likely to be found in noisy areas. This is also associated with the unemployment rate, which tends to be higher in noisier areas. The pupil/ teacher ratio has a significant negative correlation with noise levels. It is interesting to note that although the population factors, including population density, total fertility rate and crude death rate, have significant correlations with the environmental noise levels, the correlations between noise levels and residents health conditions are rather low. It is noted that this investigation is based on Great London and the results might not be directly applicable to other regions due to some localised effects. While noise mapping techniques are suitable for large scale investigation like in this study, for more detailed small scale studies, mapping techniques considering micro-scale sound propagation should be integrated and more noise sources need to be taken into account. Acknowledgements The authors are indebted to Dr. Rong Li for his help on developing the MATLAB program. References [1] Kang J. Urban sound environment. London: Taylor & Francis incorporating Spon; [2] Snyder-Halpern R. The effect of critical care unit noise on patient sleep cycles. Critical Care Quarterly 1985;4: [3] Thomas KA, Martin PA. NICU sound environment and the potential problems for caregivers. Journal of Perinatology 2000;20:S94 9. [4] Tomei F, Papaleo B, Baccolo TP, Persechino B, Spano G, Rosati MV. Noise and gastric secretion. American Journal of Industrial Medicine 1994;26: [5] Falk SA, Woods N. Hospital noise: levels and potential health hazards. The New England Journal of Medicine 1973;289: [6] Wysocki A. The effect of intermittent noise exposure on wound healing. Advanced Wound Care 1996;9(1):35 9. [7] Nurminen T. Female noise exposure, shift work and reproduction. Journal of Occupational and Environmental Medicine 1995;37(8): [8] World Health Organization, Geneva, Guidelines for Community Noise; [9] Bayo MV, Garcia AM, Garcia A. Noise levels in an urban hospital and workers subjective responses. Archives of Environment Health 1995;50: [10] Gomes CF, Crivari NMF. Os ruídos hospitalares e a audição do bebê: parte 1. Revista Brasileira de Otorrinolaringologia 1998;64(5): [11] West JE, Busch-Vishniac I. What do we know about noise in hospitals? The Journal of the Acoustical Society of America 2005;118(3):1949.

10 10 H. Xie, J. Kang / Renewable Energy xxx (2009) 1 10 [12] London Assembly and the Greater London Authority, UK, gov.uk/, accessed 15/07/07. [13] Skinner C, Grimwood C. The national noise incidence study 2000/2001 (United Kingdom). In: Noise Levels, vol. 1. UK Building Research Establishment; [14] Greater London Authority. Sounder city the Mayor s ambient noise strategy. UK: Greater London Authority; [15] MORI for Greater London Authority, Annual London Survey 2003; [16] The European Parliament and the Council of the European Union. Directive (2002/49/EC) of the European Parliament and of the Council Relating to the Assessment and Management of Environmental Noise; [17] UK Department for Environment, Food and Rural Affairs (DEFRA), Towards a national ambient noise strategy; [18] UK Department for Environment, Food and Rural Affairs (DEFRA), A report on the production of noise maps of the city of Birmingham; [19] UK Department for Environment, Food and Rural Affairs (DEFRA), Traffic noise mapping in London, 2003, accessed 30/ 05/07. [20] Kang J, Huang J. Noise-mapping: accuracy and strategic application. Proceedings of inter-noise, Rio de Janeiro, Brazil; [21] Jiang G, Li R, Kang J. An investigation of the correlation between urban sound environment and social aspects. 6th UK CARE (Chinese Association of Resources and Environment), Annual General Meeting, Sheffield, UK; [22] UK National Health Service, NHS Hospitals in London, England/Hospitals/; accessed 15/07/07. [23] Ordnance Survey, Britain s National Mapping Agency, EDINA Digimap, digimap.edina.ac.uk/; accessed 20/06/07. [24] Office for National Statistics. Focus on London, 2003 edition, UK: A National Statistics Publication; [25] Eurostat. Regionales BIP je Einwohner in der EU27.23/2007, eurostat.ec.europa.eu/, accessed 15/07/07. [26] Saint A. Politics and the people of London: the London County Council, Continuum International Publishing Group; [27] Pupils and Teachers: by Type of School, 2001/02, Office for National Statistics, UK, Regional Trends asp?vlnk ¼ 5839/; accessed 15/07/07. [28] Pupils and Teachers: by Type of School, 2002/03, Office for National Statistics. UK, Regional Trends asp?vlnk ¼ 7727/; accessed 15/07/07.