Spatial Analysis (Measurements at Heights of 10 m and 20 m above Ground Level) of the Concentrations of Particulate Matter (PM10, PM2.5, and PM1.0) and Gaseous Pollutants (H2S) on the University Campus: A Case Study

Mitigating air and noise pollution through highway capping: The Bundang-Suseo Highway Cap Project case study

Highways, while vital for transportation, often lead to heightened air and noise pollution, adversely affecting nearby communities. This study delves into the effectiveness of highway capping, a sustainable urban development strategy, in addressing these environmental challenges, with a specific focus on the Bundang-Suseo Highway in South Korea. This study employed a multifaceted approach, incorporating on-road monitoring, in situ measurements, and vertical assessments using UAVs. Following the cap's installation, the area experienced more stable pollutant levels, marking a notable shift from the previously fluctuating conditions heavily influenced by the highway. In-depth in situ monitoring near the cap revealed significant reductions in noise and pollutants like UFP and BC. Furthermore, UAV monitoring captured these changes in pollutant levels at different altitudes. Notably, the installation of the highway cap led to increased PM2.5, PM10, and NO2 levels at ground level, but a decrease above the cap, emphasizing the critical importance of intentional highway cap design in enhancing urban air quality and reducing exposure to harmful pollutants. This research yields invaluable insights for urban planners, health authorities, and policymakers, aiding the precise identification of pollution-prone areas and advocating for improved highway cap design to enhance urban environments.

Urban workers' cardiovascular health due to exposure to traffic-originated PM2.5 and noise pollution in different microenvironments

The cardiovascular health of the people in urbanised cities is linked to traffic air, and noise pollution. This study investigated the cardiovascular health of people working in two microenvironments such as street (vendors) and workplace (office workers) whose blood pressure (BP) and heart rate (HR) might be affected due to regular exposure to PM_2.5 and traffic noise. The PM_2.5 and noise levels measurements, face-to-face questionnaire survey and health check-ups were carried out on working days from 10 A.M. to 8 P.M. in Jan-Dec 2019. The data was analysed by various statistical approaches in which the link between the traffic-borne PM_2.5 and noise level at 1/3rd octave frequencies has been established with the participants' BP and HR considering the demographic, socio-contextual, habitual and annoyance perception factors. The median measure of PM_2.5 and noise levels violated the WHO and NAAQS limits, i.e. 106.67 μg/m³ at street level and 33.33 μg/m³ at office indoor; and 71.35 dB (A) at the street and 65.78 dB (A) at office indoor. The results further showed that the workers working in traffic corridors had abnormally high BP and HR. The systolic BP, diastolic BP and HR values were higher than normal in male workers than female workers. The influence of low noise spectrum (50-630 Hz) was mostly observed. Therefore, the combined effect of PM_2.5 > 50 μg/m³ and noise spectrum (63 and 100 Hz) > 30 dB (A) significantly affect office workers' health in traffic corridors. The hearing aids, breathing troubles in the traffic corridor and annoyance perception also influenced the BP and HR of the respondents. The results are indicative and might be helpful in urban environmental planning to improve the well-being of urban traffic corridor users.

Health impacts quantification attributed to ambient particulate matter in the nearest Iranian city to the main dust source

Urban air contamination is one of the ten most dangerous parameters for human health, which causes cardiovascular disease, respiratory, metabolic diseases, and decreased lung function. Air Q is a reliable software for studying the impacts of atmospheric contaminants on human health, and today, it is widely used in the environment. The purpose of this research was to quantify the mortality and morbidity rates that corresponded to ambient particulate matter (PM) in Rigan City. To perform this, the Air Q software was used. The findings reflected that the yearly mean values of PM₁₀ and PM_2.5 are 264.83 and 50.45 μg/m³. The findings indicated that the PM₁₀ and PM_2.5 content in Rigan was above standard levels described by WHO. The total number of deaths, cardiovascular deaths, and respiratory deaths due to PM in Rigan were estimated as 70.3, 45.8, and 10.7 persons, respectively. Hospital admissions for cardiovascular and respiratory diseases correlated to PM₁₀ were estimated at 154.2 and 59 persons, respectively. Acute myocardial infarction associated with PM_2.5 was 2.7 persons. Overall, the data in this study may be helpful to national and regional policymakers who are responsible for managing and preventing atmospheric contamination and assessing the costs of health risks.

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Fighting Earth's degradation and safeguarding the environment are subjects of topical interest and sources of hot debate in today's society. According to the United Nations, there is a compelling need to take immediate actions worldwide and to implement large-scale monitoring policies aimed at counteracting the unprecedented levels of air, land, and water pollution. This requires going beyond the legacy technologies currently employed by government authorities and adopting more advanced systems that guarantee a continuous and pervasive monitoring of the environment in all its different aspects. In this paper, we take the research on integrated and large-scale environmental monitoring a step further by providing a comprehensive review that covers transversally all the main applications of wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs), and crowdsensing monitoring technologies. By outlining the available solutions and current limitations, we identify in the cooperation among terrestrial (WSN/crowdsensing) and aerial (UAVs) sensing, coupled with the adoption of advanced signal processing techniques, the major pillars at the basis of future integrated (air, land, and water) and large-scale environmental monitoring systems. This review not only consolidates the progresses achieved in the field of environmental monitoring, but also sheds new lights on potential future research directions and synergies among different research areas.

Modeling Pollutant Emissions: Influence of Two Heat and Power Plants on Urban Air Quality

Large industrial plants, power plants, and combined heat and power plants are popularly believed to be the main sources of point emissions, affecting both local and global air quality. This is because these installations emit significant amounts of pollutants at high altitudes every year. In this study, we investigate the impact of two solid fuel (hard coal)-fired CHP plants located within the urban agglomeration on the air quality of the city of Lodz in Poland (Europe). We used an OPA03 computer software to model the spatial distribution of pollutants. The results show that the annual average concentrations of pollutants were highest at an altitude of 25 m above ground level and decreased at lower measurement heights. The concentrations did not exceed permissible levels, reaching only 4% of national and international regulatory limits. We also made field measurements during the winter heating period, using an unmanned aerial vehicle (UAV) equipped with sensors to map the distributions of dust and gas pollutants in the areas with the highest concentrations of emissions from the two heat and power plants. Overall, the field measurements confirmed that it is not high-altitude emissions that have the greatest impact on local air quality.

Development of Drone-Mounted Multiple Sensing System with Advanced Mobility for In Situ Atmospheric Measurement: A Case Study Focusing on PM2.5 Local Distribution

This study was conducted using a drone with advanced mobility to develop a unified sensor and communication system as a new platform for in situ atmospheric measurements. As a major cause of air pollution, particulate matter (PM) has been attracting attention globally. We developed a small, lightweight, simple, and cost-effective multi-sensor system for multiple measurements of atmospheric phenomena and related environmental information. For in situ local area measurements, we used a long-range wireless communication module with real-time monitoring and visualizing software applications. Moreover, we developed four prototype brackets with optimal assignment of sensors, devices, and a camera for mounting on a drone as a unified system platform. Results of calibration experiments, when compared to data from two upper-grade PM2.5 sensors, demonstrated that our sensor system followed the overall tendencies and changes. We obtained original datasets after conducting flight measurement experiments at three sites with differing surrounding environments. The experimentally obtained prediction results matched regional PM2.5 trends obtained using long short-term memory (LSTM) networks trained using the respective datasets.

Development of UAV-Based PM2.5 Monitoring System

This paper proposes a UAV-based PM2.5 air quality and temperature-humidity monitoring system. The system includes an air quality detector comprising four Arduino sensor modules. Specifically, it includes a dust (DSM501A) sensor and a temperature and humidity (DHT11) sensor. The NEO-6M GPS module and DS3231 real-time module are also included for input visualization. A DIY SD card logging shield and memory module is also available for data recording purposes. The Arduino-based board houses multiple sensors and all are programmable using the Arduino integrated development environment (IDE) coding tool. Measurements conducted in a vertical flight path show promise where comparisons with ground truth references data showed good similarity. Overall, the results point to the idea that a light-weight and portable system can be used for accurate and reliable remote sensing data collection (in this case, PM2.5 concentration data and environmental data).

3D Spatial Analysis of Particulate Matter (PM10, PM2.5 and PM1.0) and Gaseous Pollutants (H2S, SO2 and VOC) in Urban Areas Surrounding a Large Heat and Power Plant

In many regions of the world, the winter period is a time of poor air quality, due primarily to the increased use of individual and district heating systems. As a consequence, the atmospheric air contains increased concentrations of both particulate matter and gaseous pollutants (as a result of “low” emissions at altitudes of up to 40 m and “high” emissions more than 40 m above ground level). In winter, the increased pollution is very often exacerbated by meteorological conditions, including air temperature, pressure, air speed, wind direction, and thermal inversion. Here, we analyze the concentrations of particulate matter (PM10, PM2.5, and PM1.0) and gaseous pollutants (H2S, SO2, and VOC) in the immediate vicinity of a large solid fuel-fired heat and power plant located in an urban agglomeration. Two locations were selected for analysis. The first was close to an air quality measurement station in the center of a multi-family housing estate. The second was the intersection of two main communication routes. To determine the impact of “low” and “high” emissions on air quality, the selected pollutants were measured at heights of between 2 and 50 m using an unmanned aerial vehicle. The results were compared with permissible standards for the concentration of pollutants. Temperature inversion was found to have a strong influence on the level of pollutants at various heights, with higher concentrations of particulate matter registered at altitudes above 40 m. The source of PM, H2S, and SO2 pollutants was confirmed to be “low emission” from local transport, industrial plant areas, and the housing estate comprising detached houses located in the vicinity of the measuring points. “High emission” was found to be responsible for the high concentrations of VOC at altitudes of more than 40 m above the intersection and in the area of the housing estate.