Search results

This paper aims to investigate whether and how air pollution affects auditor behavior and audit quality. Specifically, the authors draw from studies of behavioral economics and psychology to develop a new prediction that air pollution-induced negative mood causes pessimistic bias in auditors’ risk assessments of client firms, which motivates them to put more effort into achieving higher audit quality.

This study uses a sample of Chinese public firms for the period 2013 to 2018 and an ordinary least squares model to examine the effects of air pollution on audit quality.

The results suggest that auditors exposed to higher levels of air pollution are more likely to put more effort into their audits, resulting in higher audit quality. Furthermore, the impacts of air pollution on audit quality are more pronounced when an auditor has a higher level of education, a major in accounting or a related subject and a position as a partner. A series of identification tests and sensitivity tests further support the main findings.

This study provides deeper insight into how air pollution affects auditors’ decision-making through its effect on mood.

The findings have broad potential implications for auditing and other high-skill professions. Because air pollution-induced negative mood is a common occurrence and numerous psychological experiments have demonstrated the potentially adaptive and beneficial role of negative mood in decision-making for professions like auditing that need a more conservative, alert and detail-oriented cognitive style, negative mood may to some extent facilitate decision-making. Professionals may benefit from paying closer attention to the adaptive benefits of different moods.

Few studies empirically discuss the effects of auditors’ psychology on audit outcomes. This study responds to this research gap with analyzes of how air pollution-induced negative mood can affect auditors’ professional judgment and audit outcomes. Further, this study adds to the growing literature that examines how air pollution affects various aspects of the economy and enriches the literature on behavioral economics, providing empirical evidence from a large sample of the effects of an environmental stressor on individual auditors’ professional judgment.

This study aims to assess the status of sustainable performance, given the significance of indoor air quality related to health and the environment. This research focus on the current status of indoor air quality management in these universities and simplifies its relevance and criticality in safeguarding the well-being of the academic community and the environment.

This study used the Unit-based Sustainability Assessment Tool (USAT) as a comprehensive instrument to assess sustainability performance across various modules: Operations Management, Research, Education and Social/Community. In-depth interviews were conducted across the 11 public universities in Thailand to gain a comprehensive understanding of the current practices, challenges and initiatives related to indoor air quality and sustainability management. The approach provides a foundation for future research to identify causal factors and potential solutions for the observed indoor air quality management gaps.

The research outcomes underscore the outstanding efforts in academic research, with many institutions showcasing advanced measures and a solid dedication to mitigating air pollution. However, there is a noticeable disparity in the practical management of indoor air quality, with many universities presenting unsatisfactory conditions for professors, academic staff and students.

Recognizing that proficient indoor air quality (IAQ) management strengthens the practical and scholarly intersection, this document highlights a crucial alignment with the Sustainable Development Goals (SDGs) and health implications. It advocates for carefully implementing pragmatic IAQ strategies within academic institutions, guiding the pathway towards sustainable, health-conscious environments.

This research addressed indoor air quality (IAQ) within universities. The document intertwines health implications and Sustainable Development Goals (SDGs), revealing a significant gap between academic research and practical IAQ management. While universities are committed to sustainability and community engagement, inconsistencies in IAQ management practices impact staff and student well-being and productivity. This exploration underscores the universal applicability of IAQ management strategies, driving educational institutions towards cultivating healthier, sustainable indoor environments globally.

This research introduces a new approach integrating air quality assessment and sustainability management in Thai universities. It aims to bridge the gap between environmental health and education. The Unit-based Sustainability Assessment Tool is developed as a part of this research, which provides new insights into improving indoor environments. This tool is fundamental for health and learning. The significance of this research lies in guiding policy and campus management towards sustainable, health-promoting practices, thereby adding value to the discourse on educational sustainability. This work can pave the way for enhanced well-being in academic settings, marking a significant step forward in sustainable educational practices.

To significantly adopt and improve indoor energy efficiency in building infrastructure in developing countries can be a challenging venture. Thus, this study aimed to assess the satisfaction of indoor environmental quality and its effect on energy use intensity and efficient among student housing.

The study is quantitative and hinged on the contrast theory. A survey of 1,078 student residents living in purpose-built student housing was contacted. Using Post-Occupancy Evaluation and Multiple Linear Regression, critical variables such as thermal comfort, visual comfort and indoor air quality and 21 indicators were assessed. Data on annual energy consumption and total square metre of the indoor area were utilised to assess energy use intensity.

The study found a direct relationship between satisfaction with indoor environmental quality and energy use intensity. The study showed that students were more satisfied with thermal comfort conditions than visual and indoor air quality. Overall, these indicators contributed to 75.9% kWh/m² minimum and 43.2% kWh/m² maximum energy use intensity in student housing in Ghana. High occupancy and small useable space in student housing resulted in high energy use intensity.

Inclusions of sustainable designs and installation of smart mechanical systems are feedback to student housing designers. Again, adaptation to retrofitting ideas can facilitate energy efficiency in the current state of student housing in Ghana.

Earlier studies have argued for and against the satisfaction of indoor environmental quality in student housing. However, these studies have neglected to examine the impact on energy use intensity. This is novel because the assessment of energy use intensity in this study has a positive influence on active design incorporation among student housing.

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.

Aiming to address the forecasting dilemma of seasonal air quality, the authors design the novel self-adaptive seasonal adjustment factor to extract the seasonal fluctuation information about the air quality index. Based on the novel self-adaptive seasonal adjustment factor, the novel seasonal grey forecasting models are established to predict the air quality in China.

This paper constructs a novel self-adaptive seasonal adjustment factor for quantifying the seasonal difference information of air quality. The novel self-adaptive seasonal adjustment factor reflects the periodic fluctuations of air quality. Therefore, it is employed to optimize the data generation of three conventional grey models, consisting of the GM(1,1) model, the discrete grey model and the fractional-order grey model. Then three novel self-adaptive seasonal grey forecasting models, including the self-adaptive seasonal GM(1,1) model (SAGM(1,1)), the self-adaptive seasonal discrete grey model (SADGM(1,1)) and the self-adaptive seasonal fractional-order grey model (SAFGM(1,1)), are put forward for prognosticating the air quality of all provinces in China .

The experiment results confirm that the novel self-adaptive seasonal adjustment factors promote the precision of the conventional grey models remarkably. Simultaneously, compared with three non-seasonal grey forecasting models and the SARIMA model, the performance of self-adaptive seasonal grey forecasting models is outstanding, which indicates that they capture the seasonal changes of air quality more efficiently.

Since air quality is affected by various factors, subsequent research may consider including meteorological conditions, pollutant emissions and other factors to perfect the self-adaptive seasonal grey models.

Given the problematic air pollution situation in China, timely and accurate air quality forecasting technology is exceptionally crucial for mitigating their adverse effects on the environment and human health. The paper proposes three self-adaptive seasonal grey forecasting models to forecast the air quality index of all provinces in China, which improves the adaptability of conventional grey models and provides more efficient prediction tools for air quality.

The self-adaptive seasonal adjustment factors are constructed to characterize the seasonal fluctuations of air quality index. Three novel self-adaptive seasonal grey forecasting models are established for prognosticating the air quality of all provinces in China. The robustness of the proposed grey models is reinforced by integrating the seasonal irregularity. The proposed methods acquire better forecasting precisions compared with the non-seasonal grey models and the SARIMA model.

Higher education institutions are widely known both for their promotion to education for sustainable development (ESD) and for their contribution as living labs to urban management strategies. As for strategies, smart and learning campuses have recently gained significant attention. This paper aims to report an air quality monitoring experience with focus on the smart and learning campus and discuss its implications for the university context with regard to ESD and sustainable development goal (SDG) integration.

The air quality monitoring was held at the main campus of University of Passo Fundo and focused on three pollutants directly related to vehicle emissions. The air quality index (AQI) was presented on a website, along with information regarding health problems caused by air pollution, main sources of emissions and strategies to reduce it.

The results showed how the decrease in air quality is related to the traffic emissions and the fact that exposing students to a smart and learning environment could teach them about sustainability education.

This case study demonstrated how monitoring air quality in a smart environment could highlight and communicate the impact of urban mobility on air quality and alerted to the need for more sustainable choices, including transports.

This paper contributes to the literature by showing the potential of a smart-learning campus integration and its contribution towards the ESD and the UN SDGs.

With an increasing air cargo demand in the global air cargo transport industry, not only domestic airlines but also foreign carriers are actively investing in the air cargo service sector and trying to provide a differentiated service in order to gain a competitive advantage. There are a variety of service quality models available but most research to date has not found an optimal model for the air cargo service sector.

Using questionnaire data collected from air freight forwarders in Korea with respect to the air cargo service provided by Korean Air, Asiana Airlines, and foreign carriers(JAL or China Eastern), this paper compares four models in measuring the service quality in the air cargo sector and identifies the best model. We then analyze the weakness of each airline’s service operation and make suggestions for improvement.

For demonstration analysis, the survey of domestic air cargo forwarders revealed that Reliability>Responsiveness> Supply ability>Security in important order in air cargo service quality dimension. In the context of this paper, we considered four models-unweighted SERVQUAL, unweighted SERVPERF, weighted SERVQUAL, and weighted SERVPERF–for our investigation into which is the most suitable model in the air cargo service sector with testing of goodness of fit by three criteria. Our results indicate that the most suitable model for the air cargo service sector is the weighted SERVPERF model.

This paper aims to review the rescaling of integrated planning policies for the built environment by the transposition of European directives on air quality in The Netherlands.

This is a case study examining European and Dutch policies, legislation, case law and reports by various Dutch Courts of Auditors and assessment agencies.

The paper reveals how a combination of measures that prohibit practices and measures constituting new ways of working has facilitated environmental protection and integrated planning. The case shows that transposition matters. At first, the aim of transposing European environmental directives into an integrated national legal system resulted in an erosion of integrated planning as courts nullified new development decisions. In later instances, it resulted in the National Cooperation Programme on Air Quality (NSL), an integrated system, allowing the weighing and monitoring of all policies that affect air quality.

The findings of this study of Dutch air quality regulation may contribute to other studies into the rescaling of environmental governance in relation to interactions between central norm-setting and integrated local policies.

The case study shows a real working institutional system that relies on an interactive web tool that facilitates integrated planning decisions which respect environmental limit values. The problems faced and opportunities the system afforded are also discussed.

This paper increases understanding of the process of the transposition of European directives in relation to integrated policies for the built environment, with a specific emphasis on ambient air quality.

Analysis and comparison of three existing indicators of the air quality: the American air quality index, the French Atmo, and the Italian Indice di Qualità dell'Aria.

International general and organic regulations to control air quality do not exist yet. Consequently many countries have independently implemented specific indicators to monitor the air pollution and then alert people of resulting health risks. The paper focuses on three of them. Each one is independently presented showing the peculiarities. Therefore, these indicators are compared to identify the features they have in common, as well as those that set them apart, and to figure out which are either restrictive or permissive, and what are their qualities and drawbacks.

The three mentioned indicators convert the real health risk due to air pollution into numerical information, in different ways. Doing this, they carry out some simplifications or assumptions, which can be questionable. The main difficulty is to understand if the indicators aggregate the different pollutant concentrations consistently with the real effects on human health.

This paper analyses only three specific indicators of the air quality, selected among the existing ones.

Indicators should carefully be analysed to understand if they properly represents the real effects of pollutants on human health. The most critical aspect to consider is the aggregation of the different pollutant concentrations in one information.

This paper analyses the efficacy of representation of some air quality indicators. It discusses if indicators aggregation is consistent with the real effects on human health.