DALY-Based Health Risk Assessment of Construction Noise in Beijing, China

Relation between Noise Pollution and Life Satisfaction Based on the 2019 Chinese Social Survey

Noise pollution is a leading cause of decreasing well-being of residents in both developed and developing countries. Improving residents’ well-being measured by life satisfaction is a key goal of government policy. Individuals with high life satisfaction usually have positive emotions, life orientation, and codes of conduct, which are positive and beneficial for individuals, families, and society as a whole. In order to supplement relevant research and provide policy suggestions for individuals, government, and societies, this study explores the relationship between noise pollution and the life satisfaction of Chinese residents. Based on data from 4869 observations from the Chinese Social Survey in 2019, the effect of noise pollution on life satisfaction is estimated by using ordinary least squares and propensity score matching methods. The results show that noise pollution has a significant negative effect on Chinese life satisfaction. Moreover, the effect is heterogeneous depending on individuals’ education levels and ages. Finally, residents’ living environment satisfaction is shown to be the potential mechanism by which noise pollution affects life satisfaction.

Evaluating the Environmental Impact of Construction within the Industrialized Building Process: A Monetization and Building Information Modelling Approach

Industrialization has been widely regarded as a sustainable construction method in terms of its environmental friendliness. However, existing studies mainly consider the single impact of greenhouse gas emissions or material consumption in the construction process of industrialized buildings, and pay less attention to ecological pollution and community interest, which leads to an insufficient understanding. There is an urgent need to systematically carry out accurate assessment of comprehensive construction environmental impact within industrialized building processes. Various methods, including face-to-face interviews, field research and building information modeling (BIM), were used for data collection. Four categories selected for the study included resource consumption, material loss, ecological pollution, and community interest. A life cycle assessment (LCA) model, namely input-process-output model (IPO), is proposed to analyze the construction environmental impact of the standard layer of industrialized buildings from four life cycle stages, namely, transportation, stacking, assembly and cast-in-place. The monetization approach of willingness to pay (WTP) was applied to make a quantitative comparison. Results reveal that the assembly stage has the largest impact on the environment at 66.13% among the four life cycle stages, followed by transportation at 16.39%, stacking at 10.29%, and cast-in-place at 7.19%. The key factors include power consumption, noise pollution, material loss, fuel consumption and component loss, which altogether account for more than 85% of the total impact. Relevant stakeholders can conduct their project using the same approach to determine the construction environmental performance and hence introduce appropriate measures to mitigate the environmental burden.

Influences of Migrant Construction Workers' Environmental Risk Perception on their Physical and Mental Health: Evidence from China

Employing Chinese General Social Survey 2013 data (N = 678), this study examines the influences of migrant construction workers' environmental risk perception (ERP) on their physical and mental health. The ERP of migrant construction workers is characterized by six dimensions: perceptions of air pollution, industrial waste pollution and noise pollution at working sites, and perceptions of domestic waste pollution, water pollution and food pollution at living sites. The results indicate that migrant construction workers with stronger ERP have better physical and mental health. The results also suggest the influences of ERP on the physical and mental health of migrant construction workers with different gender and age (<50 and ≥50 years) are heterogeneous. Perceptions of industrial waste pollution, noise pollution and domestic waste pollution significantly affect female workers' physical health, but not that of male workers. The six dimensions of ERP all significantly influence male workers' mental health, while except for domestic waste pollution perception, the other perceptions do not influence that of female workers. Perceptions of air pollution, domestic waste pollution, and water pollution significantly influence physical health of workers aged 50 and above, while those of ERP do not work on that of workers younger than 50. Perception of food pollution significantly influences mental health of workers younger than 50, but not that of workers aged 50 and above. The seemingly unrelated regression shows the results in this paper are robust.

Assessing personal noise exposure and its relationship with mental health in Beijing based on individuals' space-time behavior

BACKGROUND

Most prior studies adopted a static residence-based approach in the assessment of noise exposure, which may lead to biased exposure estimates and misleading findings in noise-health relationships. Relatively little is known about personal noise exposure based on individuals' space-time behavior and its effect on mental health.

OBJECTIVES

This study aims to analyze and geo-visualize personal exposure to noise in various microenvironments based on individuals' space-time trajectories at a very fine resolution and to further investigate the relationships between mental health and personal noise exposure at both the activity/travel episode level and the entire day level.

METHODS

Individual-level real-time data were collected with portable noise sensors and GPS trackers from a sample of 117 residents aged 18-60 years old from December 2017 to February 2018 in Beijing, China. Descriptive statistics and geo-visualization methods were used to examine how personal noise exposure varied across different activity types, travel modes, and among residents living in the same residential neighborhood on workdays and weekends based on individuals' space-time behaviors. Logistic regression models were applied to examine the relationships between personal noise exposure and self-reported mental health.

RESULTS

We observed substantial differences in personal noise exposure across different activity types. The equivalent sound levels (L_eq, dB(A)) for sleeping were the lowest, while the average L_eq for work-related activities was the highest in indoor environments. The noise exposure levels for activities in outdoor environments were higher than indoor noise levels but differed between workdays and weekends. Variations in noise exposure associated with different travel modes were also evident, with the average L_eq for public transport being much higher than that of other travel modes. A-weighted equivalent sound pressure level measured over 24 h for each individual (L_eq,24h, dB(A)) varied significantly for residents living in the same residential neighborhood, ranging from 36 to 97 dB(A), with the majority of respondents being exposed to noise levels above 55 dB(A) on both workdays and weekends. Regarding the noise-health relationships, the modeling results showed that individual-level objective noise exposure based on space-time behaviors measured over a 24-h period (L_eq,24h) was strongly associated with residents' self-reported mental health. Higher exposure to noise was significantly associated with worse mental health. However, personal noise exposure at the activity/travel episode level (L_eq) was not significantly associated with mental health on weekdays, but this link turned out to be significant in the weekend model.

CONCLUSIONS

There were large variations in personal noise exposure associated with different activity types and travel modes, and the individual-level noise exposure varied significantly across time of day and between residents living in the same residential neighborhood. Variations in personal exposure strongly depend on different space-time behaviors and individual-specific microenvironments experienced in daily life, and they were significantly correlated with mental health.

Evidence for Environmental Noise Effects on Health for the United Kingdom Policy Context: A Systematic Review of the Effects of Environmental Noise on Mental Health, Wellbeing, Quality of Life, Cancer, Dementia, Birth, Reproductive Outcomes, and Cognition

This systematic review commissioned by the UK Department for the Environment, Food and Rural Affairs (Defra), considers how the evidence base for noise effects on health has changed following the recent reviews undertaken for the WHO Environmental Noise Guidelines. This systematic review assesses the quality of the evidence for environmental noise effects on mental health, wellbeing, and quality of life; birth and reproductive outcomes; and cognition for papers published since the WHO reviews (mid-2015 to March 2019), as well as for cancer and dementia (January 2014 to March 2019). Using the GRADE methodology (Grading of Recommendations Assessment, Development and Evaluation) most evidence was rated as low quality as opposed to very low quality in the previous reviews. There is now low-quality evidence for a harmful effect of road traffic noise on medication use and interview measures of depression and anxiety and low quality evidence for a harmful effect of road traffic noise, aircraft noise, and railway noise on some cancer outcomes. Many other conclusions from the WHO evidence reviews remain unchanged. The conclusions remain limited by the low number of studies for many outcomes. The quantification of health effects for other noise sources including wind turbine, neighbour, industrial, and combined noise remains a research priority.

Effect of Income Heterogeneity on Valuation of Mortality Risk in Taiwan: An Application of Unconditional Quantile Regression Method

According to theory and existing empirical results, heterogeneity in personal characteristics, with income variation being one of them, affects the marginal willingness to pay (WTP) for reducing fatal risk. In this study, the effect of income heterogeneity on the value of statistical life (VSL) in Taiwan through unconditional quantile regression analysis using the data collected by the “Manpower Utilization Survey” is investigated. The results of this empirical study show that the hedonic wage function that was constructed using empirical data from Taiwan was in line with the general form of non-linear function rather than the semi-log function that has been often used in previous studies, which should have great impact on the estimation of the VSL. The empirical results also show that the estimated VSL of Taiwanese labor varied with the difference in wages, which needs to be taken into account when discussing the public policies using VSL.

Strategic Noise Maps and Action Plans for the reduction of population exposure in a Mediterranean port city

One of the major environmental problems in contemporary societies is noise pollution, as it is well-known that noise adversely affects both the physiological and the psychological human health and well-being. This paper presents the development of Strategic Noise Maps and Action Plans for the "agglomeration of Piraeus", an area with >15% of the total population and almost 12% of the total area of the "Athenian - Piraeus conurbation". In Piraeus different noise sources, such as the railway, port activities, the road network, industrial and logistic activities etc., in combination with mixed land uses, dense urban canopy characteristics, residential areas adjacent to major road arterials etc. create a complicated noise environment that causes annoyance to the population. For this study, a campaign of 55 24-hour noise measurements was carried out and a series of 200 traffic counts were used for the estimation of traffic characteristics. Annual road traffic data were derived from a validated traffic model, while vessel, rail and industrial activity data were obtained from the service operators and in-situ surveys. The aforementioned noise/traffic measurements were used to calibrate a complex geographical model of the urban canopy and the noise sources layout. Strategic Noise Maps were then developed, along with estimations of the population exposure and DALYs lost from environmental noise per source. Action Plans including intervention measures aiming at the reduction of noise pollution in the area were then proposed. It was found that when implementing the interventions proposed both the noise levels and the exposure of population were significantly reduced, highlighting the importance of exposure reduction, especially for the vulnerable subpopulations, through prevention measures and strategies.

Health impact assessment of PM2.5-related mitigation scenarios using local risk coefficient estimates in 9 Japanese cities

Previous studies have highlighted the negative effects of PM_2.5 on mortality, expressed in terms of attributable deaths and life years lost. However, there are very few studies assessing the health impacts of air pollution in terms of economic burden/benefits. This study assessed the health impact of two hypothetical interventions among sex- and age-specific risk populations using a robust risk estimation and economic valuation process. We utilized the sex- and age-stratified daily all-cause mortality together with the daily PM_2.5 of the 9 Japanese cities from 2002 to 2008 in estimating the relative risks. The estimated risks were then utilized for the economic valuation of co-benefits/burden with respect to the two hypothetical PM_2.5-related mitigation scenarios, in comparison to status quo, namely: i) decrease to Japanese standards, and ii) decrease to WHO standards. Impact of these interventions on health were assessed using the following HIA metrics: attributable mortality, attributable years life lost, and environmental health impact. A 10-μg/m³ increase in PM_2.5 would increase the risk by 0.52% (95% CI: -0.91% to 1.99%) for all-cause mortality, with varying risk estimates per subgroup. High economic burdens were estimated at status quo, with particularly distinct burden difference for age-specific mortality; 0.40 trillion yen (0-64 y.o.) and 1.50 trillion yen (>64 y.o.). If stricter standards, relative to status quo, were to be enforced, i.e. WHO standard, there is a potential to yield economic benefits in the same risk population; 0.26 trillion yen (0-64 y.o.) and 0.98 trillion yen (>64 y.o.). We did not observe any substantial difference with the burden and benefit related to sex-specific mortality. Using the estimated local risk coefficients complemented with the valuation of the risks, policymaking entities will have the opportunity to operate their own HIA to assess the relevant air pollution-related health impacts.

A Multilevel Analysis of Perceived Noise Pollution, Geographic Contexts and Mental Health in Beijing

With rapid urbanization and increase in car ownership, ambient noise pollution resulting from diversified sources (e.g., road traffic, railway, commercial services) has become a severe environmental problem in the populated areas in China. However, research on the spatial variation of noise pollution and its potential effects on urban residents’ mental health has to date been quite scarce in developing countries like China. Using a health survey conducted in Beijing in 2017, we for the first time investigated the spatial distributions of multiple noise pollution perceived by residents in Beijing, including road traffic noise, railway (or subway) noise, commercial noise, and housing renovation (or construction) noise. Our results indicate that there is geographic variability in noise pollution at the neighborhood scale, and road traffic and housing renovation/construction are the principal sources of noise pollution in Beijing. We then employed Bayesian multilevel logistic models to examine the associations between diversified noise pollution and urban residents’ mental health symptoms, including anxiety, stress, fatigue, headache, and sleep disturbance, while controlling for a wide range of confounding factors such as socio-demographics, objective built environment characteristics, social environment and geographic context. The results show that perceived higher noise-pollution exposure is significantly associated with worse mental health, while physical environment variables seem to contribute little to variations in self-reported mental disorders, except for proximity to the main road. Social factors or socio-demographic attributes, such as age and income, are significant covariates of urban residents’ mental health, while the social environment (i.e., community attachment) and housing satisfaction are significantly correlated with anxiety and stress. This study provides empirical evidence on the noise-health relationships in the Chinese context and sheds light on the policy implications for environmental pollution mitigation and healthy city development in China.

Association between environmental noise and subjective symptoms related to cardiovascular diseases among elderly individuals in Japan

Noise in housing environments may increase the risk of cardiovascular diseases (CVDs); however, the most significant sources of noise among elderly individuals remain poorly understood. A nationwide cross-sectional study comprised of 6,181 elderly people (age ≥ 65 years) was conducted using a web-based self-reported questionnaire in 2014. Questions pertaining to CVD-related subjective symptoms within the past year addressed symptoms of chest pain, disturbances in pulse, acute impaired tongue movement, limb paralysis, and foot pain or numbness during walking. Questions concerning noise included awakening during the night due to noise, automobile, neighborhood, construction, railway, and aircraft noise. The multivariable analyses revealed that all symptoms were significantly associated with awakening during the night due to noise. Automobile, construction, railway, and aircraft noise were significantly associated with more CVD-related symptoms at nighttime than at daytime. Our results suggest that noise at nighttime is an important risk factor for CVDs. Although several different sources of environmental noise, including automobile, neighborhood, construction, railway, and aircraft noise were found to be significantly associated with CVD-related symptoms, the strongest association was observed for construction noise, followed by neighborhood and automobile noise. The adjusted odds ratios (95% confidence intervals) for construction noise at nighttime were 1.12 (1.06–1.19) with disturbances in pulse, 1.21 (1.08–1.35) in acute impaired tongue movement, 1.25 (1.15–1.36) in limb paralysis, and 1.19 (1.12–1.28) in foot pain or numbness during walking. The associations with railway and aircraft noise were found to be weaker than those with automobile, neighborhood, and construction noise. Our study suggests that CVD-related symptoms may exhibit a greater association with construction, neighborhood, and automobile noise than with railway and aircraft noise.