Noise and annoyance in working environments

This paper describes a field study of the correlation between annoyance and occupational exposure to noise. Measurements of noise and annoyance were made in different types of working environments with noise dominated by low-frequency, middle-frequency or high-frequency components. The noise was described in terms of dB(A), dB(B), dB(C), dB(D), and dB(lin). Annoyance ratings of the occupational noise and of two verbally described reference noises were collected, using a rating scale. As a result of calibration, a better correlation between noise level and rated annoyance was obtained. The A-weighting procedure did not produce a better prediction of annoyance than any of the other weighting methods.     

Disturbance caused by various fluctuating single noises and combined community noises

Three experiments were conducted to investigate factors influencing the (rated) disturbance caused by various noises to subjects when they were reading: (a) comparison of disturbances from various noises at 70 dB(A) L_eq; (b) comparison of exposure-response relationships between road traffic, aircraft, and train noises; and (c) the effect of road traffic background noise on the total disturbance caused by combined noise (aircraft or train noise combined with road traffic noise). From the three experiments, the following conclusions were drawn: (1) High-level components such as peak level contributed to the disturbance, since the noise was more disturbing with the increase of peak level. (2) Although the general pattern of the exposure-response relationships for aircraft and train noises was similar, the disturbance due to road traffic noise increased with L_eq level more rapidly than for aircraft and train noise. Considering that the peak level of aircraft or train noise was always higher than that of road traffic noise at equal L_eq levels, the contribution of the high-level components to the disturbance appeared to be level-dependent. (3) The background noise level did not affect the total disturbance. Because the high-level components of combined noises were almost the same, this finding was consistent with conclusions drawn in (1) and (2).     

Road-traffic noise and factors influencing noise annoyance in an urban population

Noise annoyance is influenced by sound-related factors: type of noise, noise level and frequency, and person-related factors—physiological, psychological, and social factors. Prior to implementation of the Directive 2002/49/EC of the European Parliament and of the Council in Serbia, there was a need for the first comprehensive study on noise annoyance in Serbian urban population. The aim of this study was to determine principal factors for high noise annoyance in an adult urban population and to assess their predictive value. A cross-sectional study was performed on 3097 adult residents of a downtown municipality in Belgrade (1217 men and 1880 women), aged 18–96 years. Equivalent noise levels [Leq (dBA)] were measured during day, evening and night in all streets of the municipality. Noise annoyance was estimated using self-reported annoyance scale. Noise annoyance showed strong correlation with noise levels, personal characteristics and some housing conditions. Dose–response relationship was found between the percentage of highly annoyed residents and Lden. Logistic regression model identified increased risk for a high level of noise annoyance with regard to: orientation of living room/bedroom toward the street (Odds Ratio = 2.60; 95% Confidence Interval = 2.04–3.31), duration of stay at apartment during the day [OR = 1.04, 95%CI = 1.02–1.06 (per hour)], noise sensitivity [OR = 1.04, 95%CI = 1.03–1.04 (per scale unit)], and nighttime road-traffic noise level [OR = 1.03, 95%CI = 1.02–1.04 (per decibel)].     

Neighbour noise annoyance and psychiatric diseases

Data from a national sample survey (interview data) were used to test for possible correlations between different measures of noise annoyance and measures of psychiatric problems/diseases. The test was accomplished by crosstab programme for correlation between variables. The main variables were noise annoyance from different sources and psychiatric problems/diseases. Age and sex were used as covariables. A correlation was shown between neighbour noise annoyance and various indicators of self-reported psychiatric problems/diseases in the middle age groups, more prevalent and stronger for women than for men. The results, in accordance with research in other countries, indicate that people with psychiatric problems/diseases are more sensitive towards neighbour noise than the rest of the population. The same survey and the same method showed only low or no correlation between other sources of noise annoyance and psychiatric diseases.     

Annoyance due to aircraft noise has increased over the years—Results of the HYENA study

In the HYENA study (HYpertension and Exposure to Noise near Airports) noise annoyances due to aircraft and road traffic noise were assessed in subjects that lived in the vicinity of 6 major European airports using the 11-point ICBEN scale (International Commission on Biological Effects of Noise). A distinction was made between the annoyance during the day and during the night. L_den and L_night were considered as indicators of noise exposure. Pooled data analyses showed clear exposure–response relationships between the noise level and the noise annoyance for both exposures. The exposure–response curves for road noise were congruent with the EU standard curves used for predicting the number of highly noise annoyed subjects in European communities. Annoyance ratings due to aircraft noise, however, were higher than predicted by the EU standard curves. The data supports other findings suggesting that the people's attitude towards aircraft noise has changed over the years, and that the EU standard curve for aircraft noise should be modified.     

Transportation noise and exposed population of an urban area in the Republic of Korea

Using noise prediction models, we explored the transportation noise levels of Youngdeungpo-gu, an urbanized area of Seoul Metropolitan City in the Republic of Korea. In addition, we estimated the population exposed to transportation noise levels and determined how many people are vulnerable to noise levels that would cause serious annoyance and sleep disturbance. Compared with the World Health Organization [WHO] recommended levels, the daytime and nighttime transportation noise levels were still high enough to have the two psychosocial effects on people when considering the recommended levels of the World Health Organization (WHO; 55 decibels [dB[A]] and 40 dB[A] for daytime and nighttime, respectively). Particularly, nighttime transportation noise was discovered to be harmful to a wider area and more people than daytime noise. Approximately 91% of the Youngdeungpo-gu area experienced nighttime transportation noise levels exceeding those recommended by WHO. It was estimated that as much as 80% of the people in the study area were exposed to transportation noise levels >40 dB[A] during nighttime. Taking this into account, there is an urgent need to control and reduce transportation noise levels in Seoul, to protect residents against the potential ill health effects caused by urban transportation.     

Road traffic noise, sensitivity, annoyance and self-reported health--a structural equation model exercise

The proposed effect of road traffic noise on hypertension and ischemic heart disease finds mixed empirical support. One problem with many studies is that the directions of the causal relationships are not identified. This is often the case when cross-sectional data and multivariate regression models are utilised. The aim of the study was to explore the relationship between road traffic noise and health. More specifically the relationships between noise complaints, noise sensitivity and subjectively reported hypertension and heart problems were investigated. 1842 respondents in Oslo, Norway were interviewed about their experience of the local environment and their subjective health complaints. The interviews were conducted as part of two surveys. Individual measures of air pollution (NO(2)) and noise (Lden) were calculated. The data were analysed using Structural Equation Models. Only sensitivity to noise is related to hypertension and chest pain. No relationships between noise exposure and health complaints were identified. Rather than noise being the causal agent leading to health problems, the results suggest that the noise-health relationships in these studies may be spurious. It is conceivable that individual vulnerability is reflected both in ill health and in being sensitive to noise. The benefit of including more contextual variables in a model of noise-health relationships is supported.     

Residential exposure to outdoor air pollution from livestock operations and perceived annoyance among citizens

Epidemiological studies have shown that residential exposure to livestock odors can affect the health and wellbeing of rural citizens. However, exposure–response models for this relationship have not been developed. One of the main challenges is to identify a compound that can be used as proxy for livestock odor exposure. In this paper we developed models that describe the relationship between long-term averaged outdoor residential ammonia (NH₃) exposures and livestock odor annoyance experienced by rural residents, and investigated person-related variables associated with annoyance responses. We used emission-based atmospheric dispersion modeling data to estimate household-specific outdoor concentrations and survey data to characterize the study subjects. Binomial and multinomial logistic regressions were used for model development. Residential NH₃ exposure was positively associated with moderate, high and extreme odor annoyance (adjusted odds ratio = 10.59; 95% confidence interval: 1.35–83.13, for each unit increase in Log_eNH₃ exposure). Specific characteristics of the exposed subjects (i.e., age, time per week spent at home, presence of children at home and job) act as co-determinants of odor annoyance responses. Predictive models showed classification accuracies of 67–72%. The results suggest that NH₃ exposure in the residential outdoor environment can be used as a predictor of livestock odor annoyance in population studies.     

Policy-related goals for community response studies

Many aspects of community noise policies are based on information about people's reactions to noise. Studies of community response to noise can make direct contributions to public policy if a major goal is to report the effects of community and acoustical variables on annoyance in decibel equivalent units. Three other goals are of lesser importance but deserve more attention than they have received: specifying the shape of dose/response relationships, developing a ratio-level measurement technique for noise annoyance (magnitude scaling) and predicting the public's actions toward noise. Achieving these goals requires the widespread adoption of design and analysis approaches which have been only sporadically applied to the study of annoyance in communities: the calculation of the decibel equivalence of effects as well as correlation coefficients, the reporting of confidence intervals as well as statistical significance tests, the evaluation of sigmoid-shaped dose/response curves, and the evaluation of the effect of community as well as individual differences on the accuracy of the survey results.     

The effect of wind turbine noise on sleep and quality of life: A systematic review and meta-analysis of observational studies

Noise generated by wind turbines has been reported to affect sleep and quality of life (QOL), but the relationship is unclear. Our objective was to explore the association between wind turbine noise, sleep disturbance and quality of life, using data from published observational studies. We searched Medline, Embase, Global Health and Google Scholar databases. No language restrictions were imposed. Hand searches of bibliography of retrieved full texts were also conducted. The reporting quality of included studies was assessed using the STROBE guidelines. Two reviewers independently determined the eligibility of studies, assessed the quality of included studies, and extracted the data. We included eight studies with a total of 2433 participants. All studies were cross-sectional, and the overall reporting quality was moderate. Meta-analysis of six studies (n = 2364) revealed that the odds of being annoyed is significantly increased by wind turbine noise (OR: 4.08; 95% CI: 2.37 to 7.04; p < 0.00001). The odds of sleep disturbance was also significantly increased with greater exposure to wind turbine noise (OR: 2.94; 95% CI: 1.98 to 4.37; p < 0.00001). Four studies reported that wind turbine noise significantly interfered with QOL. Further, visual perception of wind turbine generators was associated with greater frequency of reported negative health effects. In conclusion, there is some evidence that exposure to wind turbine noise is associated with increased odds of annoyance and sleep problems. Individual attitudes could influence the type of response to noise from wind turbines. Experimental and observational studies investigating the relationship between wind turbine noise and health are warranted.     

Modeling of road traffic noise and estimated human exposure in Fulton County, Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN?. After analyzing noise levels with raster, vector and fa?ade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N=870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.     

Odor-annoyance estimates from roadtraffic combustion exhausts: Calibration with master scaling using pyridine as a reference

The present field study addressed the need for a procedure that provides a defined unit of measurement of perceived annoyance from environmental odors, calibrating the estimates for individual scaling behavior and context effects. In including 25 subjects, the purpose was to demonstrate the applicability of the master-scale procedure with magnitude estimation to perform such a calibration of odor-annoyance estimates for target stimuli such as road-traffic combustion exhausts (13 000 vehicles/d; averaging 47 μg/m³ over the day/night with peaks exceeding 100 μg/m³ of nitrogen dioxide; NO₂). For comparison, calibrated estimates were also obtained for a backyard expected to be considerably less polluted (comparable with 18 μg/m³ of NO₂) and for blank stimuli presented indoors. The data transformation for the calibration procedure with which annoyance is expressed in either master-scale units or pyridine equivalents requires estimates of a reference stimulus for which seven concentrations of pyridine were used. The results provide an illustration of master scaling of odor annoyance, and imply that use of a modulus (standard stimulus with a predefined annoyance magnitude), in contrast to master scaling, is not sufficient for calibration for individual scaling behavior and context effects.     

Strategic environmental noise mapping: Methodological issues concerning the implementation of the EU Environmental Noise Directive and their policy implications

This paper explores methodological issues and policy implications concerning the implementation of the EU Environmental Noise Directive (END) across Member States. Methodologically, the paper focuses on two key thematic issues relevant to the Directive: (1) calculation methods and (2) mapping methods. For (1), the paper focuses, in particular, on how differing calculation methods influence noise prediction results as well as the value of the EU noise indicator L_den and its associated implications for comparability of noise data across EU states. With regard to (2), emphasis is placed on identifying the issues affecting strategic noise mapping, estimating population exposure, noise action planning and dissemination of noise mapping results to the general public. The implication of these issues for future environmental noise policy is also examined.     

Effect of the shape of the exposure-response function on estimated hospital costs in a study on non-elective pneumonia hospitalizations related to particulate matter

ObjectiveWe used log-linear and log-log exposure-response (E-R) functions to model the association between PM_2.5 exposure and non-elective hospitalizations for pneumonia, and estimated the attributable hospital costs by using the effect estimates obtained from both functions.MethodsWe used hospital discharge data on 3519 non-elective pneumonia admissions from UZ Brussels between 2007 and 2012 and we combined a case-crossover design with distributed lag models. The annual averted pneumonia hospitalization costs for a reduction in PM_2.5 exposure from the mean (21.4 μg/m³) to the WHO guideline for annual mean PM_2.5 (10 μg/m³) were estimated and extrapolated for Belgium.ResultsNon-elective hospitalizations for pneumonia were significantly associated with PM_2.5 exposure in both models. Using a log-linear E-R function, the estimated risk reduction for pneumonia hospitalization associated with a decrease in mean PM_2.5 exposure to 10 μg/m³ was 4.9%. The corresponding estimate for the log-log model was 10.7%. These estimates translate to an annual pneumonia hospital cost saving in Belgium of €15.5 million and almost €34 million for the log-linear and log-log E-R function, respectively.DiscussionAlthough further research is required to assess the shape of the association between PM_2.5 exposure and pneumonia hospitalizations, we demonstrated that estimates for health effects and associated costs heavily depend on the assumed E-R function. These results are important for policy making, as supra-linear E-R associations imply that significant health benefits may still be obtained from additional pollution control measures in areas where PM levels have already been reduced.     

Modeling of road traffic noise and estimated human exposure in Fulton County,Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN®. After analyzing noise levels with raster, vector and façade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N = 870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.     

Epidemiological research on non-auditory effects of occupational noise exposure

Epidemiological studies about non-auditory effects of noise have been reviewed. For methodological reasons, only occupational studies are compared with each other. Most studies were directed, as before, to the relation between noise and arterial blood pressure. In about half of the studies, a positive relation could be demonstrated, in the other studies, however, no relation was found. Methodological comments are given. Definite conclusions are still not possible. In three investigations the effects of noise on pregnancy were studied. A negative effect on birth weight is presented in one of these studies. More research is needed. Task components probably interact with noise exposure producing annoyance and stress symptoms. The use of epidemiological methods in research of non-auditory effects of noise is still very limited.     

Applicability of a noise-based model to estimate in-traffic exposure to black carbon and particle number concentrations in different cultures

Several studies show that a significant portion of daily air pollution exposure, in particular black carbon (BC), occurs during transport. In a previous work, a model for the in-traffic exposure of bicyclists to BC was proposed based on spectral evaluation of mobile noise measurements and validated with BC measurements in Ghent, Belgium. In this paper, applicability of this model in a different cultural context with a totally different traffic and mobility situation is presented. In addition, a similar modeling approach is tested for particle number (PN) concentration.Indirectly assessing BC and PN exposure through a model based on noise measurements is advantageous because of the availability of very affordable noise monitoring devices. Our previous work showed that a model including specific spectral components of the noise that relate to engine and rolling emission and basic meteorological data, could be quite accurate. Moreover, including a background concentration adjustment improved the model considerably. To explore whether this model could also be used in a different context, with or without tuning of the model parameters, a study was conducted in Bangalore, India. Noise measurement equipment, data storage, data processing, continent, country, measurement operators, vehicle fleet, driving behavior, biking facilities, background concentration, and meteorology are all very different from the first measurement campaign in Belgium. More than 24 h of combined in-traffic noise, BC, and PN measurements were collected. It was shown that the noise-based BC exposure model gives good predictions in Bangalore and that the same approach is also successful for PN. Cross validation of the model parameters was used to compare factors that impact exposure across study sites. A pooled model (combining the measurements of the two locations) results in a correlation of 0.84 when fitting the total trip exposure in Bangalore. Estimating particulate matter exposure with traffic noise measurements was thus shown to be a valid approach across countries and cultures.     

南京市经济发展与环境污染关系的实证研究

根据南京市1991～2003年经济与环境数据,分析经济发展与环境污染的相互关系,建立了南京市经济增长与环境污染水平的计量模型,进而评价了南京市的环境保护政策。研究表明：作为一个重化工业城市,南京市自20世纪90年代以来,在经济高速发展的情况下,其环境恶化程度逐步得到遏制,部分环境指标与人均GDP演替轨迹呈现显著的环境库兹涅茨曲线特征。这主要归功于南京市政府近年来有效的环境政策和巨额的环境投资。     

Health benefits from reducing indoor air pollution from household solid fuel use in China--three abatement scenarios

According to the World Health Organization (WHO), indoor air pollution (IAP) from the use of solid fuels in households in the developing world is responsible for more than 1.6 million premature deaths each year, whereof 0.42 million occur in China alone. We argue that the methodology applied by WHO--the so-called fuel-based approach--underestimates the health effects, and suggest an alternative method. Combining exposure-response functions and current mortality and morbidity rates, we estimate the burden of disease of IAP in China and the impacts of three abatement scenarios. Using linear exposure-response functions, we find that 3.5 [0.8-14.7 95% CI] million people die prematurely due to IAP in China each year. The central estimate constitutes 47% of all deaths in China. We find that modest changes in the use of cooking fuels in rural households might have a large health impact, reducing annual mortality by 0.63 [0.1-3. 2 95% CI] million. If the indoor air quality (IAQ) standard set by the Chinese government (150 microg PM(10)/m(3)) was met in all households, we estimate that 0.9 [0.2-4.8] million premature deaths would be avoided in urban areas and 2.8 [0.7-12.4] million in rural areas. However, in urban areas this would require improvements to the outdoor air quality in addition to a complete fuel switch to clean fuels in households. We estimate that a fuel switch in urban China could prevent 0.7 [0.2-4.8] million premature deaths. The methodology for exposure assessment applied here is probably more realistic than the fuel-based approach; however, the use of linear exposure-response relationships most likely tends to overestimate the effects. The discrepancies between our results and the WHO estimates is probably also explained by our use of "all-cause mortality" which includes important causes of death like cardiovascular diseases, conditions known to be closely associated with exposure to particulate pollution, whereas the WHO estimate is limited to respiratory diseases.     

Combined toxicity of copper and phenol derivatives to Daphnia magna: effect of complexation reaction

The complexation of Cu with phenol was investigated in aqueous solution to find the changes in toxicity toward Daphnia magna in mixtures of copper and phenol derivatives and determine an appropriate prediction model for the toxicity of these mixtures. In the titration experiment, the results showed that phenol played an important role in the remarkable reduction of the Cu(2+) concentration, due to its complexation with Cu, with the subsequent reduction in the toxicity of aqueous mixtures containing both Cu and phenol. As a result, it was clearly demonstrated that Cu-phenol formed a non-toxic complex toward D. magna as the mortality declined, despite the addition of phenol to a fixed Cu concentration. Meanwhile, prediction of the combined toxicity for binary mixtures of Cu and 11 phenol derivatives more accurately followed an independent action model (p = 0.143, df = 124, and t = -1.475 in t-test) than an effect summation model (p approximately 0, df = 134, and t = 7.528 in t-test) due to the dissimilar modes of action and the complexation reactions between Cu and each of the phenolic compounds. Consequently, this study supports the importance of considering complexation reactions in assessing the combined toxicity for the formulation of water quality in mixtures of heavy metals and organic compounds, and in these cases, an independent action model was found to be appropriate.