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This study aimed to estimate the economic benefits of PM2.5 emission abatement by Red Pine, Pinus Koraiensis and Quercus, using a metering model analyzing the amount of PM2.5 absorption in Korea.

To estimate the economic effects of PM2.5 adsorptions by trees, the frequency of hospital visits resulting from respiratory and circulatory diseases was estimated using a Probit model based on the data from National Health and Nutrition Survey.

The results show that Quercus and Pinus Koraiensis absorb and eliminate the largest amount of PM2.5. Reducing 1 ton of PM2.5 emission through the planting of trees leads to lower incidences of respiratory and circulatory diseases equivalent to the amount of 95 million won. When the trees planted are 2-year-old Red Pine, Pinus Koraiensis and Quercus, the resulting economic benefits of the PM2.5 abatement would amount to 481 million won, 173 million won and 1,027 million won, respectively. If the trees are 80 years old, the economic benefits are estimated to be 73 billion won for Red Pine, 103 billion won for Pinus Koraiensis and 38 billion won for Quercus.

One limitation of this study is that the weight of PM2.5 adsorbed by each leaf area entirely depended on the experimental results from a prior study and the values are likely to be different from those actually absorbed in natural surroundings. In addition, because of the lack of data from a domestic survey on the surface of leaf area or the reload flow rate of PM2.5, this study referred to data from foreign research. Unfortunately, this specific data may not reflect climatic and terrain characteristics specific to the target country. We used the annual wind speed to calculate the reload flow rate and elimination volume; however, the figures could be more accurate with hourly or daily climate variations. When estimating the health benefits of changes in PM2.5 emissions on respiratory and circulatory diseases, more segmented access to patients' hospital visits and hospital admissions are desirable. Finally, the study focused on the three major tree species of Korea, however, a more detailed study of PM2.5 reduction by various tree types is needed in the future.

This paper quantitatively assessed the amount of PM2.5 adsorption by each of the three tree species. Then, the economic benefits were calculated in terms of how much money would be saved on hospital visits thanks to the reduced PM2.5 levels and lower incidences of respiratory and circulatory system diseases. The net contribution of this study was to prove the trees' function of reducing PM2.5 as it relates to human health. We focused on the most common trees in Korea and compared them to provide new information on the species.

Dust (particulate matters) is very dangerous to our health as it is not visible with our naked eyes. Emissions of dust concentrations in the natural environment can occur mainly by road traffic, constructions and dust generating working environments. The purpose of this paper is to assess the ambient dust pollution status and to find out the association between PM concentrations and other determinant factors such as wind speed, ambient temperature, relative humidity and traffic congestion.

A cross-sectional study was conducted for two consecutive months (June and July, 2016) at a residential site (Defence Services Liver Hospital, Mingaladon) and a commercial site (Htouk-kyant Junction, Mingaladon) based on WHO Air Quality Reference Guideline Value (24-hour average). Hourly monitoring of PM2.5 and PM10 concentration and determinant factors such as traffic congestion, wind speed, ambient temperature and relative humidity for 24 hours a day was performed in both study sites. CW-HAT200 handheld particulate matters monitoring device was used to assess PM concentrations, temperature and humidity while traffic congestion was monitored by CCTV cameras.

The baseline PM2.5 and PM10 concentrations of Mingaladon area were (28.50±11.49)µg/m³ and (52.69±23.53)µg/m³, means 61.48 percent of PM2.5 concentration and 54.92 percent of PM10 concentration exceeded than the WHO reference value during the study period. PM concentration usually reached a peak during early morning (within 3:00 a.m.-5:00 a.m.) and at night (after 9:00 p.m.). PM2.5 concentration mainly depends on traffic congestion and temperature (adjusted R²=0.286), while PM10 concentration depends on traffic congestion and relative humidity (adjusted R²=0.292). Wind speed played a negative role in both PM2.5 and PM10 concentration with r=−0.228 and r=−0.266.

The air quality of the study area did not reach the satisfiable condition. The main cause of increased dust pollution in the whole study area was high traffic congestion (R²=0.63 and 0.60 for PM2.5 and PM10 concentration).

This study aims to examine the impact of local air pollution on the presence of central air conditioners in apartments in Lebanon.

This study applies a Probit model in a unique data set on apartments’ listings for sale in Lebanon collected by Marrouch and Sayour (2021). The data set includes information about air pollution concentrations, dwellings’ characteristics, geographic features and location characteristics.

This study finds that local air pollution positively and significantly affects the presence of central air conditioning in dwellings. The estimated increase in the probability of having central air conditioning for a one microgram per cubic meter increase in Particulate Matter 2.5 concentration is 6.4%.

The data set in this study is cross-sectional and thus does not capture variations over time for the examined variables.

The Probit regression approximates an equation that can predict the presence of central air conditioners in dwellings, which might be useful to policymakers.

The findings suggest that local pollution is a significant factor in household behavior in Lebanon.

This paper adds to the scant literature studying the effects of air pollution on the presence of central air conditioning in developing countries. To the best of the authors’ knowledge, this is the first paper to study the impact of air pollution on the presence of central air conditioning in the Middle East and North Africa Region.

Severe airborne particulate pollution frequently occurs over the North China Plain (NCP) region in recent years. To better understand the characteristics of carbonaceous components in particulate matter (PM) over the NCP region.

PM samples were collected at a typical area affected by industrial emissions in Handan, in January 2016. The concentrations of organic carbon (OC) and elemental carbon (EC) in PM of different size ranges (i.e. PM_2.5, PM₁₀ and TSP) were measured. The concentrations of secondary organic carbon (SOC) were estimated by the EC tracer method.

The results show that the concentration of OC ranged from 14.9 μg m⁻³ to 108.4 μg m⁻³, and that of EC ranged from 4.0 μg m⁻³ to 19.4μg m⁻³, when PM_2.5 changed from 58.0μg m⁻³ to 251.1μg m⁻³ during haze days, and the carbonaceous aerosols most distributed in PM_2.5 rather than large fraction. The concentrations of OC and EC PM_2.5 correlated better (r = 0.7) than in PM_2.5−10 and PM_>10, implying that primary emissions were dominant sources of OC and EC in PM_2.5. The mean ratios of OC/EC in PM_2.5, PM_2.5–10 and PM_>10 were 4.4 ± 2.1, 3.6 ± 0.9 and 1.9 ± 0.7, respectively. Based on estimation, SOC accounted for 16.3%, 22.0% and 9.1% in PM_2.5, PM_2.5–10 and PM_>10 respectively.

The ratio of SOC/OC (48.2%) in PM_2.5 was higher in Handan than those (28%–32%) in other megacities, e.g. Beijing, Tianjin and Shijiazhuang in the NCP, suggesting that the formation of SOC contributed significantly to OC. The mean mass absorption efficiencies of EC (MACEC) in PM₁₀ and TSP were 3.4 m² g⁻¹ (1.9–6.6 m² g⁻¹) and 2.9 m² g⁻¹ (1.6–5.6 m² g⁻¹), respectively, both of which had similar variation patterns to those of OC/EC and SOC/OC.

The eruption of coronavirus disease 2019 (COVID-19) has pointedly subdued global economic growth and producing significant impact on environment. As a medicine or a treatment is yet available at mass level, social distancing and lockdown is expected the key way to avert it. Some outcome advocates that lockdown strategies considered to reduce air pollution by curtailing the carbon emission. Current investigation strives to affirm the impact of lockdown and social distancing policy due to covid-19 outbreak on environmental pollution in the QUAD nations.

To calibrate the social movement of public, six indicators such residential mobility, transit mobility, workplace mobility, grocery and pharmacy mobility, retail and recreation mobility and park mobility have been deliberated. The data of human mobility have been gathered from the Google mobility database. To achieve the relevant objectives, current pragmatic analysis exerts a panel autoregressive distributed lag model (ARDL)-based framework using the pooled mean-group (PMG) estimator, proposed by Pesaran and Shin (1999), Pesaran and Smith (1995).

The outcome reveals that in the long-run public mobility change significantly impact the pollutants such as PM2.5 and nitrogen dioxide; however, it does not lead to any changes on ozone level. As per as short run outcome is concerned, the consequence unearths country wise heterogeneous impact of different indicators of public mobility on the air pollution.

The ultimate inferences of the above findings have been made merely on the basis of examination of QUAD economies; however, comprehensive studies can be performed by considering modern economies simultaneously. Additionally, finding could be constraint in terms of data; for instance, Google data used may not suitably signify real public mobility changes.

A considerable amount of investigation explores the impact of covid-19 on environmental consequences by taking carbon emission as a relevant indicator of environmental pollution. Hence, the present pragmatic investigation attempts to advance the present discernment of the above subject in two inventive ways. Primarily, by investigating other components of environmental pollution such as nitrogen dioxide, PM2.5 and ozone, to reveal the impact of covid-19 outbreak on environmental pollution, as disregarded by the all preceding studies. Additionally, it makes a methodological contribution before integrating supplementary variables accompanying with ecological air pollution. Finally, the current research article provides an alternative and creative approach of modeling the impact of public mobility on environmental sustainability.

This study aims to investigate whether and how public air environmental concern (PAEC) affects corporate environmental, social and governance (ESG) performance in emerging markets.

This study measured PAEC using the Baidu index search keyword “雾霾 (PM2.5)” and assessed its impact on corporate ESG among Chinese A-share listed companies from 2011 to 2020 through regression analysis.

The empirical results indicate a positive relationship between PAEC and corporate ESG. Moreover, PAEC facilitates enhanced corporate ESG performance by mediating through corporate reputation and government environmental regulations. Heterogeneity analysis shows that the promotion effect of PAEC on ESG is more pronounced in the subgroups of companies with an excellent green image, low perceived uncertainty, strong management political connections, low short-termism, high industry technological levels and low pollution levels.

The practical implications of this study underscore the importance for policymakers, investors and companies to prioritize PAEC and its influence on corporate ESG performance.

This study contributes to ESG literature by highlighting the positive impact of external oversight, such as PAEC.

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.

The purpose of this article was to investigate the relationship between symptoms related to air pollution, mask-wearing, mask choices and related factors.

A cross-sectional study among outpatient department (OPD) pollution clinic patients at Nopparat Rajathanee Hospital (PCNRH) during 2019 in Bangkok, Thailand.

The most common symptom after exposure to air pollution that affects treatment in the OPD is respiratory symptoms. A total of 45.7% (107/234) of the population wears a mask, 55.1% (59/107) of the population that wears a mask wears a surgical mask, and only 10.3% (11/107) of them wear an N95 mask. Mask-wearing and air quality index (AQI) onset were associated with the respiratory symptoms group, whereas wearing an N95 mask or surgical mask was found to be a protective factor for the occurrence of respiratory symptoms (adjusted OR = 0.065, 95% CI: 0.014–0.306, p = 0.001 and adjusted OR = 0.154, 95% CI: 0.058–0.404, p < 0.001, respectively). Therefore, the best practice in the face of air pollution, while the resolution needs a long period, is to wear a mask. In this study, the results showed that the best type of mask to prevent respiratory symptoms from air pollution is the N95, followed by the surgical mask; cloth masks are not recommended to use to protect against respiratory symptoms from air pollution.

Wearing an N95 and a surgical mask can help reduce respiratory symptoms. Hence, in addition to establishing hospital measures, cooperation from local and government agencies is necessary to effectively and jointly build a national health public policy framework.

1. This study provides evidence of a correlation between symptoms associated with air pollution and related factors, in-hospital visits in Bangkok, Thailand. 2. In this study, wearing an N95 mask and a surgical mask were found to be a protective factor for the occurrence of respiratory symptoms.

Over the last couple of years, the Chinese manufacturing sector was affected by the onset of the US–China trade war and the outbreak of coronavirus disease 2019 (COVID-19). In such a scenario air quality in China has encountered a shock, and the impacts of these two incidents are unknown. In this study, the authors analyze the convergence of air quality in China in the presence of multiple structural breaks and how the impacts of these two events are different from each other.

In order to assess the nature of shocks in the presence of multiple structural breaks, unit root tests with multiple structural breaks are employed.

The results reveal that air quality in China is showing the sign of convergence, and it is consistent across 18 provinces which are worst hit by the outbreak of COVID-19. In the presence of transitory shocks, the impact of COVID-19 outbreak is found to be higher, whereas the impact of the US–China trade war is found to be more persistent. Lastly, the outbreak of COVID-19 has been found to have more impact on pollutants with higher severity of health hazard.

To the best of the authors’ knowledge, this is the first study that contributes to the empirical literature in terms of investigating the convergence of overall air pollution and individual air pollutants taking COVID-19 and the trade war into account.

The purpose of this paper is to explore how information on air pollution is shaped online on an everyday basis, with a particular emphasis on digital devices and digital representations as constitutive of environmental information practices. Furthermore, this research highlights an understudied aspect of air pollution – the digital flow of multimodal representations that citizens encounter and produce in their everyday life.

The information gathering was carried out on an everyday basis during February-March 2017. The study is based on 403 microblog posts from the social media site Sina Weibo, and netnographic fieldwork, including the observation of news, advertisements, and diary writing. The collected data were mapped in clusters based on the interrelations of objects, agents, and activities, and analyzed in depth using qualitative multimodal analysis.

Information enacted through specific socio-materialist configurations depicts air pollution as self-contained and separated from human action. Air quality apps are central in connecting a wider nexus of representations and promoting such perceptions, illustrating the role of digital devices in an everyday information context.

The study reveals a schism between Chinese political environmental visions and everyday environmental information practices, which raises questions of how the battle against air pollution can be sustained in the long term.

This study suggests that digital material aspects – inbuilt applications of digital devices and digital representations of objects – are interrelated with physical experiences of air pollution, and thus constitute elements of practice in their own right.