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Air quality, noise and proximity to urban infrastructure can arguably have an important impact on the quality of life. Environmental quality (the price of good health) has become a central tenet for consumer choice in urban locales when deciding on a residential neighbourhood. Unlike the market for most tangible goods, the market for environmental quality does not yield an observable per unit price effect. As no explicit price exists for a unit of environmental quality, this paper aims to use the housing market to derive its implicit price and test whether these constituent elements of health and well-being are indeed capitalised into property prices and thus implicitly priced in the market place.

A considerable number of studies have used hedonic pricing models by incorporating spatial effects to assess the impact of air quality, noise and proximity to noise pollutants on property market pricing. This study presents a spatial analysis of air quality and noise pollution and their association with house prices, using 2,501 sale transactions for the period 2013. To assess the impact of the pollutants, three different spatial modelling approaches are used, namely, ordinary least squares using spatial dummies, a geographically weighted regression (GWR) and a spatial lag model (SLM).

The findings suggest that air quality pollutants have an adverse impact on house prices, which fluctuate across the urban area. The analysis suggests that the noise level does matter, although this varies significantly over the urban setting and varies by source.

Air quality and environmental noise pollution are important concerns for health and well-being. Noise impact seems to depend not only on the noise intensity to which dwellings are exposed but also on the nature of the noise source. This may suggest the presence of other externalities that arouse social aversion. This research presents an original study utilising advanced spatial modelling approaches. The research has value in further understanding the market impact of environmental factors and in providing findings to support local air zone management strategies, noise abatement and management strategies and is of value to the wider urban planning and public health disciplines.

Construction activities generate noise that is harmful to workers and the neighbouring community. Engineering control methods are often used for its control which are expensive and limited in effectiveness. This study aims to investigate factors that affect employee behaviour and how it could be used by construction companies to manage noise pollution on sites.

Norm Activation Model (NAM) is used to investigate the relationship between attitudes and behaviour of site-based employees using a questionnaire survey administered in Colombo, Sri Lanka. The responses were analysed using structural equation modelling to discern behavioural patterns and how it differs between managers and workers.

The results showed that behaviour of site employees could be influenced when they are aware of the consequences of noise pollution and take responsibility for its control. Personal norm of an employee and company's environmental behaviour are found to influence the behaviour in a positive manner.

Construction companies should focus more on how to harness their employee's behaviour in order to reduce noise pollution on sites. Employees should be made aware of consequences of noise pollution and feel responsible for their actions through training, awareness campaigns, signage and so on.

This study contributes to the literature by building a theoretical model of employee noise control behaviour in construction organizations and empirically testing it among managers and workers. It compares the differences between these two groups which enhances one’s understanding of behavioural control methods when applied in a construction project setting. The study also evaluates the effects of company's environmental behaviour on employee behaviour.

This article deals with the determination of the benefits of environmental assets, involving an application for noise. In determining these benefits the so‐called Cost of Illness Method is applied. An important part of the research is the estimation of the relationship between environmental pollution (noise) and the number of lost workdays. This relationship is estimated by using the Lisrel technique with latent variables. The empirical results show that, for the sample concerned, a relationship between noise and lost workdays does not exist. The research also shows that noise causes annoyance and that annoyance influences people′s wellbeing negatively.

Cement industry for both developed and developing countries is important from the economic point of view. It is playing a vital role in economic development of a developing country like Pakistan. However, these industries are posing threat to the environment, human health and plant species. The purpose of this paper is to identify the most critical factors of cement industry that have a negative impact on the environment, human health and plant species in the context of Pakistan.

The factors are categorized into air pollution, noise pollution, soil pollution, human health and plant species. These factors are categorized on the basis of previous literature and environmental safety reports. Air pollution is caused by iron and sulphur while noise pollution is mainly caused by crusher room and rotatory kiln end. The soil is being polluted by zinc and lead while human health and plant species are being damaged by sulphur dioxide and nitrogen dioxide. For the analysis purpose, a multi-criteria decision-making (MCDM) technique, i.e., decision-making trial and evaluation laboratory (DEMATEL) is used.

The result shows that the major cause of air pollution is “sulphur” while “crusher room and rotatory kiln end” are responsible for noise pollution. On the other hand, “mercury” is responsible for causing soil pollution while human health and plant species are influenced by the toxic effect of “nitrogen dioxide.”

The results obtained are specific to cement manufacturing industry of Pakistan and cannot be generalized for any other manufacturing sector.

The proposed methodology shows the most critical factors toward which concertation should be given for mitigating their impact. This study will help the government and the cement industry to focus on all those elements that are the most responsible for causing different types of pollution.

No such work is reported in previous research that proposes a framework using DEMATEL technique for analysis of critical factors of cement industries that have a dangerous impact on the environment and human health, especially in a developing country, like Pakistan.

Environmental pollution and corresponding adverse health impacts have now become a significant concern for the entire planet. In this regard, analysts and experts are continually formulating policies to reduce environmental pollution and improve natural ecological conditions. To aid in coping with the ecological predicament, a framework has been developed in the present study to inspect the adverse environmental impacts and related health issues of coal mining.

The parameters for this study have been identified through a review of the literature and finalized 23 critical parameters of air, water, land and soil, and noise related to coal mining by consultation with experts from industry and academia. Finally, the parameters have been categorized in accordance with the level of threat they pose to the environment by assigning weight using the Bradley–Terry model considering attitudinal data acquired by a questionnaire survey.

It is found that coal mining has a relatively higher impact on four attributes of “air pollution” (suspended particulate matter [SPM], respiratory particulate matter [RPM], sulfur dioxide [SO₂] and oxides of nitrogen [NO_x]), followed by “land and soil pollution” (deforestation and surface structure diversion), “noise pollution” (vehicle movement) and “water pollution” (water hardness, total solids (TSS/TDS) and iron content). It is also found that raising the air concentration of SPM and RPM results in increased respiratory and cardiopulmonary mortality. Therefore, reducing dust concentrations into the air generated during coal mining is recommended to reduce air pollution caused by coal mining, which will reduce contamination of water and land and soil.

The model built in this study is a hypothesized model that relied on the experts' opinions considering the parameters of coal production only. However, the parameters related to the usage of coal and its consequences have been excluded. Further, only industrial and academic experts were considered for this study; however, they excluded local people, coal mining personnel, policy authorities, etc. Therefore, the study findings might differ in real circumstances. The research can further be reproduced by considering the parameters related to the use of coal and its consequences, considering the opinions of the local people, coal mining personnel and policy authorities.

Categorizing the parameters according to the threat they pose to the environment due to coal mining can help the decision-maker develop an effective policy to reduce environmental pollution due to coal mining by considering the parameters on a priority basis. In addition, the results further help the decision-makers to assess the environmental impact of coal mining and take necessary action.

The study has developed a framework using the Bradley–Terry model to categorize the environmental parameters of coal mining to develop effective environmental policies, which are original and unique in nature.

Nigeria, a prominent country in Sub-Sahara Africa, is plagued with a protracted, erratic and low power supply. The purpose of this paper is to present an experimental investigation of the noise levels and pollutants’ (CO, CO₂ and particulate matter (PM_2.5)) concentrations associated with the prevalent use of diesel-powered generators in the country. It is aimed to provide information on the level of gaseous, particulate and noise pollutants that are related to diesel-powered generators that could assist in policy formulation and create public awareness on the possible health risks.

Diesel-fueled generators (105) with age and installed capacity ranging from 0.5 to 14 years and 10 to 500 kVA, respectively, were engaged in this work at Sango area of Ogun State, Nigeria. Standard measuring instruments were placed at 1 m from the diesel-powered generators to determine the noise levels and concentrations of CO, CO₂ and PM_2.5.

Ranges of 72.6–115.6 dB, 19–198 ppm, 501–5,805 ppm and 221–492 µg/m³ for the noise level, CO, CO₂ and PM_2.5 concentrations, respectively, were obtained. Both the averages and ranges of the noise levels and pollutants’ concentrations were considerably higher than the recommended maximum limits. Thus, this study substantiated the pollution of ambient noise and air because of the operation of diesel-fueled generators. Furthermore, the health risks connected to the exposure to CO and PM_2.5 as implied via the evaluation of the air quality index revealed very unhealthy and hazardous conditions, respectively.

The measurement of the pollutants’ concentrations at the tips of the exhaust pipes of the diesel-powered generators was desirable but could not be achieved using manually logged devices. Nonetheless, adequate pollutants’ concentration data that satisfactorily represent the level of air pollution associated with diesel-fueled generators’ operations were obtained at around 1 m from the exhaust pipes.

The study provided additional knowledge on the levels of noise and pollutants, and the public health risks connected to the operations of diesel-powered generators that will be beneficial to the public and policymakers.

The results revealed a considerably high level of noise and air pollution, and the inherent environmental and public health problems connected to diesel-powered generators’ usage in Nigeria. This could serve as a viable tool for formulating environmental policy and providing the necessary societal awareness in this regard.