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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).

Ports create harmful effects on their adjacent population because ships discharge noxious gases like SO_X, NO_X, and particulate matter (PM). To tackle this problem, some ports started to control emission through regulations such as Emission Control Areas (ECA) and Reduced Speed Zone (RSZ). This paper estimates the social cost of ship emission and eco-efficiency at the Port of Incheon (POI). We further examine how the ECA and RSZ designation can reduce the social cost. The estimation is based on the activity-based approach, where ship type, engine, and movement are used to measure fuel consumption and then emission. Results suggest that the social cost of ship emission at the POI amounts to $90,805,478. The eco-efficiency of the POI, compared to the one at the Port of Las Palmas in another study, is substantially better. Under RSZ, the corresponding emission abatement values are $4,485,308, $2,642,009 and $21,932,435 from SO₂, NO_X and PM reduction, respectively. If 1.0% and 0.1% sulfur fuel are used complying with rules of the ECA, the social cost savings amount to $8,174,947 and $12,868,842 from SO₂ reduction.

The noise and dust particles caused by the construction transport are by most stakeholders experienced as disturbing. The purpose of this study is to explore how sonification can support visualization in construction planning to decrease construction transport disturbances.

This paper presents an interdisciplinary research project, combining research on construction logistics, internet of things and sonification. First, a data recording device, including sound, particle, temperature and humidity sensors, was implemented and deployed in a development project. Second, the collected data were used in a sonification design, which was, third, evaluated with potential users.

The results showed that the low-cost sensors used could capture “good enough” data, and that the use of sonification for representing these data is interesting and a possible useful tool in urban and construction transport planning.

There is a need to further evolve the sonification design and better communicate the aim of the sounds used to potential users. Further testing is also needed.

This study introduces new ideas of how to support visualization with sonification planning the construction work and its impact on the vicinity of the site. Currently, urban planning and construction planning focus on visualizing the final result, with little focus on how to handle disturbances during the construction process.

Showing the potentials of using low-cost sensor data in sonification, and using sonification together with visualization, is the result of a novel interdisciplinary research area combination.

This purpose of this paper is to understand residents’ choice of preferred measures and their willingness-to-pay (WTP) for the measures to improve the air quality of Hanoi city.

Questionnaire surveys were conducted to collect the opinions of 212 household representatives living in Hanoi City. The survey tools were tested and adjusted through an online survey with 191 responses. Multivariate probit and linear regression models were used to identify determinants of respondents’ choices of measures and their WTP.

Respondents expressed their strong preferences for three measures for air quality improvements, including: (1) increase of green spaces; (2) use of less polluting fuels; (3) expansion of public transportation. The mean WTP for the implementation of those measures was estimated at about 148,000–282,000 Vietnamese dong, equivalent to 0.09–0.16% of household income. The respondents’ choices appear to be consistent with their characteristics and needs, such as financial affordability, time on roads and their perceived impacts of air pollution. The WTP estimates increase with perception of air pollution impacts, time on roads, education and income; but are lower for older people.

Increase of green spaces can be the measure to which policy makers should pay more attention. The match-up of residents needs and well-informed plans will be an important key to success.

This appears to be the first attempt to test the validity of public opinions on choices of measures for improving urban air quality in Vietnam. Our WTP estimates also contribute to the database on the values of improved air quality in the developing world.

This study aims to assess the effect of water variation on bioethanol production from cassava peels (CP) using Saccharomyces cerevisiae yeast as the ethanologenic agent.

The milled CP was divided into three treatment groups in a small-scale flask experiment where each 20 g CP was subjected to two-stage hydrolysis. Different amount of water was added to the fermentation process of CP. The fermented samples were collected every 24 h for various analyses.

The results of the fermentation revealed that the highest ethanol productivity and fermentation efficiency was obtained at 17.38 ± 0.30% and 0.139 ± 0.003 gL⁻¹ h⁻¹. The study affirmed that ethanol production was increased for the addition of water up to 35% for the CP hydrolysate process.

The finding of this study demonstrates that S. cerevisiae is the key player in industrial ethanol production among a variety of yeasts that produce ethanol through sugar fermentation. In order to design truly sustainable processes, it should be expanded to include a thorough analysis and the gradual scaling-up of this process to an industrial level.

This paper is an original research work dealing with bioethanol production from CP using S. cerevisiae microbe.

1. Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

2. Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

3. Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

4. Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

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.

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.

Because of the expansion of the internet and Web 2.0 phenomenon, new challenges are emerging in the disclosure practises adopted by organisations in the public-sector. This study aims to examine local governments’ (LGOs) use of social media (SM) in disclosing environmental actions/plans/information as a new way to improve accountability to citizens to obtain organisational legitimacy and the related sentiment of citizens’ judgements.

This paper analyses the content of 39 Italian LGOs’ public pages on Facebook. After the distinction between five classes of environmental issues (air, water, energy, waste and territory), an initial study is performed to detect possible sub-topics applying latent Dirichlet allocation. Having a list of posts related to specific environmental themes, the researchers computed the sentiment of citizens’ comments. To measure sentiment, two different approaches were implemented: one based on a lexicon dictionary and the other based on convolutional neural networks.

Facebook is used by LGOs to disclose environmental issues, focussing on their main interest in obtaining organisational legitimacy, and the analysis shows an increasing impact of Web 2.0 in the direct interaction of LGOs with citizens. On the other hand, there is a clear divergence of interest on environmental topics between LGOs and citizens in a dialogic accountability framework.

Sentiment analysis (SA) could be used by politicians, but also by managers/entrepreneurs in the business sector, to analyse stakeholders’ judgements of their communications/actions and plans on corporate social responsibility. This tool gives a result on time (i.e. not months or years after, as for the reporting system). It is cheaper than a survey and allows a first “photograph” of stakeholders’ sentiment. It can also be a useful tool for supporting, developing and improving environmental reporting.

To the best of the authors’ knowledge, this paper is one of the first to apply SA to environmental disclosure via SM in the public sphere. The study links modern techniques in natural language processing and machine learning with the important aspects of environmental communication between LGOs and citizens.

This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO₂ prediction models. The purpose of this paper is to pre-process a relatively large data of NO₂ from Internet of Thing (IoT) sensors with time-corresponding weather and traffic data and to use the data to develop NO₂ prediction models using BA-GS-LSSVM and popular standalone algorithms to allow for a fair comparison.

This research installed and used data from 14 IoT emission sensors to develop machine learning predictive models for NO₂ pollution concentration. The authors used big data analytics infrastructure to retrieve the large volume of data collected in tens of seconds for over 5 months. Weather data from the UK meteorology department and traffic data from the department for transport were collected and merged for the corresponding time and location where the pollution sensors exist.

The results show that the hybrid BA-GS-LSSVM outperforms all other standalone machine learning predictive Model for NO₂ pollution.

This paper's hybrid model provides a basis for giving an informed decision on the NO₂ pollutant avoidance system.

This research installed and used data from 14 IoT emission sensors to develop machine learning predictive models for NO₂ pollution concentration.

This study aims to evaluate the efficiency of various techniques for enhancing indoor air quality (IAQ) in construction. It analyzed the alterations in the concentration of indoor air pollutants over time for each product employed in controlling pollution sources and removing it, which included eco-friendly substances and adsorbents. The study will provide more precise and dependable data on the effectiveness of these control methods, ultimately supporting the creation of more efficient and sustainable approaches for managing indoor air pollution in buildings.

The research investigates the impact of eco-friendly materials and adsorbents on improving indoor air quality (IAQ) in Dubai's tall apartment buildings. Field experiments were conducted in six units of The Gate Tower, comparing the IAQ of three units built with “excellent” grade eco-friendly materials with three built with “good” grade materials. Another experiment evaluated two adsorbent products (H and Z) in the Majestic Tower over six months. Results indicate that “excellent” grade materials significantly reduced toluene emissions. Adsorbent product Z showed promising results in pollutant reduction, but there is concern about the long-term behavior of adsorbed chemicals. The study emphasizes further research on household pollutant management.

The research studied the effects of eco-friendly materials and adsorbents on indoor air quality in Dubai's new apartments. It found that apartments using “excellent” eco-friendly materials had significantly better air quality, particularly reduced toluene concentrations, compared to those using “good” materials. However, high formaldehyde (HCHO) emissions were observed from wood products. While certain construction materials led to increased ethylbenzene and xylene levels, adsorbent product Z showed promise in reducing pollutants. Yet, there is a potential concern about the long-term rerelease of these trapped chemicals. The study emphasizes the need for ongoing research in indoor pollutant management.

The research, while extensive, faced limitations in assessing the long-term behavior of adsorbed chemicals, particularly the potential for rereleasing trapped pollutants over time. Despite the study spanning a considerable period, indoor air pollutant concentrations in target households did not stabilize, making it challenging to determine definitive improvement effects and reduction rates among products. Comparisons were primarily relative between target units, and the rapid rise in pollutants during furniture introduction warrants further examination. Consequently, while the research provides essential insights, it underscores the need for more prolonged and comprehensive evaluations to fully understand the materials' and adsorbents' impacts on indoor air quality.

The research underscores the importance of choosing eco-friendly materials in new apartment constructions for better IAQ. Specifically, using “excellent” graded materials can significantly reduce harmful pollutants like toluene. However, the study also highlights that certain construction activities, such as introducing furniture, can rapidly elevate pollutant levels. Moreover, while adsorbents like product Z showed promise in reducing pollutants, there is potential for adsorbed chemicals to be rereleased over time. For practical implementation, prioritizing higher-grade eco-friendly materials and further investigation into furniture emissions and long-term behavior of adsorbents can lead to healthier indoor environments in newly built apartments.

The research offers a unique empirical assessment of eco-friendly materials' impact on indoor air quality within Dubai's rapidly constructed apartment buildings. Through field experiments, it directly compares different material grades, providing concrete data on pollutant levels in newly built environments. Additionally, it explores the efficacy of specific adsorbents, which is of high value to the construction and public health sectors. The findings shed light on how construction choices can influence indoor air pollution, offering valuable insights to builders, policymakers and residents aiming to promote public health and safety in urban living spaces.