Human exposure assessment to air pollutants: application of a new portable air monitoring instrument

Mapping Intimacies ◽

10.5194/egusphere-egu2020-9075 ◽

2020 ◽

Author(s):

Sheng Ye ◽

Mark Wenig

Keyword(s):

Air Quality ◽

Air Pollutants ◽

Urban Pollution ◽

Air Monitoring ◽

Raspberry Pi ◽

Data Logging ◽

Data Set ◽

Individual Exposure ◽

Pollution Levels ◽

Human Exposure Assessment

Air pollution has been gaining increasing global attention. The public is concerned about urban pollution levels including both in- and outdoor air quality. A handheld Air Quality Inspection Box (Airquix) was developed in order to monitor air pollutants in real-time, and determine individual exposure to different pollutants in different environments. The Airquix is equipped with air quality sensors: electrical chemical NO2, O3, NO sensors, NDIR CO2 sensor, OPC-N3 PM sensor; environment sensor (T, RH, P), GPS sensor and a raspberry pi for data logging, processing and display. To achieve a relatively high accuracy, e.g. +/- 5ppb at 5 seconds time resolution for the NO2 concentration, the pre- and post- calibration for the Airquix were performed by comparison with high-end air monitoring instruments. In this study, several Airquixes were distributed to different persons to assess individual exposure. The daily activities were distinguished by different commutes, in- and outdoor behaviors, the personal habits and potential episodes. The resulting data set can be used for the assessment of health impacts.

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Urban Air Quality: Assessing Traffiffic and Building Architecture Impacts using Portable Measuring Devices in Toronto, Ontario

STEM Fellowship Journal ◽

10.17975/sfj-2019-004 ◽

2019 ◽

Vol 5 (1) ◽

pp. 5-12

Author(s):

Cuilian Fang ◽

Cheol H. Jeong ◽

Greg J. Evans

Keyword(s):

Air Quality ◽

Air Pollutants ◽

Ultrafine Particles ◽

Tall Buildings ◽

Urban Pollution ◽

Urban Air Quality ◽

Urban Air ◽

Portable Devices ◽

Pollution Levels ◽

King Street

Vehicle emissions are one of the largest local contributors to poor urban air quality. High emissions are often associated with traffic congestion, and pollution may also become trapped between tall buildings creating a street canyon effect. The spatial variability of traffic-related air pollutants in microenvironments should be considered in evaluating changes in urban planning. This study focuses on assessing the air quality and commuter exposure in Toronto, Ontario, Canada, specifically focusing on the effect of the King Street Pilot Project on local urban air quality by reducing traffic. Increased vehicular density is expected to contribute to higher urban pollution levels and tall buildings may trap these contaminants. Field measurements were made within the King Street Pilot area during weekday rush hours to capture the best representation of peak activity and pollutant levels when there were similar average wind speeds and directions for the sampling dates. A suite of portable devices was carried along predesigned and timed routes through traffic dense areas to measure vehicle-related air pollutants including black carbon (BC), ultrafine particles (UFP, particles smaller than 0.1 μm), and particulate matter (PM2.5, particles smaller than 2.5 μm). Data was normalized, corrected and analyzed using centralized pollutant while considering meteorological site measurements located about 1.5 km away from the study area. Results indicated higher BC and UFP levels during peak commuting times between 8 am to 10 am and relatively increased pollution levels within the area of tall buildings versus the area with shorter buildings. Strong spatial variations of BC and UFP were found, while PM2.5 levels remained relatively constant in the downtown area. Elevated levels of BC and UFP were observed around nearby construction sites. This study contributes to establishing a baseline to evaluate the King Street Pilot Project’s air quality impact as well as proposing potential methods of detailed data collection within microenvironments to observe the air quality of urban centres.

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Changes of air pollutants’ concentrations in selected Romanian cities during the pandemic year 2020

10.5194/egusphere-egu21-1800 ◽

2021 ◽

Author(s):

Gabriela Iorga ◽

George-Bogdan Burghelea

Keyword(s):

Air Pollution ◽

Air Quality ◽

European Commission ◽

Air Pollutants ◽

Meteorological Parameters ◽

Dust Particles ◽

Spatial And Temporal Variation ◽

Pollution Level ◽

Data Set ◽

Air Mass

Present research contributes to scientific knowledge concerning spatial and temporal variation of major air pollutants with high resolution at the country scale bringing statistical information on concentrations of NOx, O3, CO, SO2 and particulate matter with an aerodynamic diameter below 10&#160;&#956;m (PM10) and below 2.5&#160;&#956;m (PM2.5) during the pandemic year 2020 using an observational data set from the Romanian National Air Quality Network in seven selected cities spread out over the country. These cities have different level of development, play regional roles, might have potential influence at European scale and they are expected to be impacted by different pollution sources. Among them, three cities (Bucharest, Bra&#537;ov, Ia&#537;i) appear frequently on the list of the European Commission with reference to the infringement procedure that the European Commission launched against Romania in the period 2007-2020 regarding air quality.Air pollutant data was complemented with local meteorological parameters at each site (atmospheric pressure, relative humidity, temperature, global solar radiation, wind speed and direction). Statistics of air pollutants provide us with an overview of air pollution in main Romanian cities.&#160; Correlations between meteorological parameters and ambient pollutant levels were analyzed. Lowest air pollution levels were measured during the lockdown period in spring, as main traffic and non-essential activities were severely restricted. Among exceptions were the construction activities that were not interrupted. During 2020, some of selected cities experienced few pollution episodes which were due to dust transport from Sahara desert. However, in Bucharest metropolitan area, some cases with high pollution level were found correlated with local anthropogenic activity namely, waste incinerations. Air mass origins were investigated for 72 hours back by computing the air mass backward trajectories using the HYSPLIT model. Dust load and spatial distribution of the aerosol optical depth with BSC-DREAM8b v2.0 and NMBM/BSC-Dust models showed the area with dust particles transport during the dust events.The obtained results are important for investigations of sources of air pollution and for modeling of air quality.&#160;Acknowledgment:The research leading to these results has received funding from the NO Grants 2014-2021, under Project contract no. 31/2020, EEA-RO-NO-2019-0423 project. NOAA Air Resources Laboratory for HYSPLIT transport model, available at READY website https://www.ready.noaa.gov &#160;and the Barcelona dust forecast center for BSC-DREAM8b and NMBM/BSC-Dust models, available at: &#160;https://ess.bsc.es/bsc-dust-daily-forecast are also acknowledged. The data regarding ground-based air pollution and meteorology by site was extracted from the public available Romanian National Air Quality Database, www.calitateaer.ro.

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IoT-Based Air Quality and Sound Intensity Monitoring System using Raspberry Pi

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b3207.079220 ◽

2020 ◽

Vol 9 (2) ◽

pp. 126-130

Keyword(s):

Air Quality ◽

Monitoring System ◽

Environmental Changes ◽

Sound Intensity ◽

Raspberry Pi ◽

Notification System ◽

Remote Areas ◽

Pollution Levels ◽

Precautionary Measures ◽

Use Of The Internet

In day to day life, the increase in Air and Sound pollution has become a distressing problem. It has now become a vital issue that is to be considered. To overcome this problem, an IoT based system to monitor the pollution levels constantly has been proposed. Nowadays Internet of things (IoT) is one of the most widely used and researched technology to monitor the environmental changes. It gives an innovative approach where various devices can be connected together with the use of the internet. By interconnecting different objects located at different locations, we can collectively analyze the data at a single place. This feature is useful in data analytics. Raspberry Pi mini-computer is used to collect different data from different sensors and this data is monitored. In our proposed system we are using four different modules namely Air Quality Monitoring System, Sound Intensity Monitoring System, Cloud based Monitoring System, Notification system. These modules are integrated together to monitor the environmental changes. This system can be implemented in remote areas where the bulky equipment cannot be placed. Industrial areas where the pollution levels are high can be constantly monitored and precautionary measures can be implemented if the pollution is more.

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Development of a high-resolution air quality forecasting system, based on WRF-Chem model, for the greater area of Thessaloniki, Greece

10.5194/egusphere-egu2020-21296 ◽

2020 ◽

Author(s):

Irene Zyrichidou ◽

Stavros Solomos ◽

Stylianos Kotsopoulos ◽

Panagiota Syropoulou ◽

Evangelos Kosmidis

Keyword(s):

Air Quality ◽

High Resolution ◽

Regional Scale ◽

Surface Wind ◽

Model Performance ◽

Urban Pollution ◽

Atmospheric Conditions ◽

Pollution Levels ◽

Implementation Period ◽

Simulated Surface

Air pollution models play an important role in science because of their capability to give a description of the air quality problem including an analysis of factors and causes (emission sources, meteorological processes, and physical and chemical changes). Real-time forecast of urban air quality is highly important to the public as advanced information for both air quality and safety assessment.&#160;This study presents the development of a regional scale high-resolution modeling system for simulating air quality and forecasting changes in urban pollution levels. The air quality system based on the state-of-the-art Weather Research and Forecasting model coupled with chemistry (WRF-Chem)&#160;has been applied over the greater area of Thessaloniki, Greece. The model performance, in terms of simulated surface major air pollutants&#8217; concentrations, is evaluated using ground-based measurements during the operational implementation period in winter-spring 2020. Our study highlights the importance of resolving local scale atmospheric conditions such as surface wind flow and boundary layer properties for describing the pollutants&#8217; concentrations and the importance of constraining emissions over the study area.&#160;

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Exploring the Association between Urban Form and Air Quality in China

Journal of Planning Education and Research ◽

10.1177/0739456x17711516 ◽

2017 ◽

Vol 38 (4) ◽

pp. 413-426 ◽

Cited By ~ 22

Author(s):

Man Yuan ◽

Yan Song ◽

Yaping Huang ◽

Shijian Hong ◽

Liejia Huang

Keyword(s):

Air Quality ◽

Population Density ◽

Urban Form ◽

Air Pollutants ◽

Cross Sectional ◽

Data Set ◽

Chinese Cities ◽

Explanatory Variables ◽

The Relationship ◽

Linear Regressions

This article aims to evaluate the association between urban form and air quality in China through the use of empirical evidence. The relationship between a variety of urban form metrics and concentrations of air pollutants were analyzed through linear regressions using a data set of cross-sectional observations from 157 Chinese cities. After controlling for other explanatory variables, higher population density and lower urban continuity are commonly associated with better air quality, and urban form could play a modest but important role in improving air quality for Chinese cities.

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Air pollution in the locality of buildings

Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences ◽

10.1098/rsta.1971.0049 ◽

1971 ◽

Vol 269 (1199) ◽

pp. 515-526 ◽

Cited By ~ 12

Keyword(s):

Air Pollution ◽

Wind Tunnel ◽

Air Pollutants ◽

Mixing Layer ◽

Urban Pollution ◽

Background Level ◽

Heat Island ◽

Pollution Levels ◽

Quantitative Estimates ◽

Local Sources

Concentrations of air pollutants at any point in a city are due to contributions from ( a ) the background level of the inflowing 'rural’ air, ( b ) the 'overall’ urban pollution, and ( c ) the sources ‘local’ to the point in question. The influence of buildings on the over-all pollution levels is effected through the heat island phenomenon and the geometry and temporal variation of the mixing layer into which the contaminants are dispersing. The enhancement of downwind dispersion of pollutants from local sources upwind is appreciated, but more studies are needed to quantify all factors involved. Wind-tunnel investigations have been demonstrated to be valuable in providing quantitative estimates of the distribution of gas concentrations in the flow field around a building complex.

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High-resolution air-quality observations onboard commercial Zeppelin flights in Germany

10.5194/egusphere-egu21-6470 ◽

2021 ◽

Author(s):

Ralf Tillmann ◽

Franz Rohrer ◽

Georgios I. Gkatzelis ◽

Benjamin Winter ◽

Christian Wesolek ◽

...

Keyword(s):

Air Quality ◽

Greenhouse Gases ◽

Air Pollutants ◽

Electrochemical Sensors ◽

Trace Gas ◽

Source Attribution ◽

Data Set ◽

Gas Measurements ◽

Air Speed

A Zeppelin NT airship has been used as a platform for in-situ measurement of greenhouse gases and air pollutants in the planetary boundary layer (PBL). The Zeppelin especially with its long flight endurance, low air speed and potential high payload fills a gap between stationary ground based and remote sensing measurements, payload limited UAV based air monitoring, long range-high-altitude aircraft, and satellite observations. Its flight properties render unique applications for the observation of PBL dynamics and air quality monitoring. Highly resolved spatial and temporal trace gas measurements provide input required for modelling of air pollution and validation of emission inventories.The core instrument deployed was a novel Quantum Cascade Laser (QCL) based multi-compound gas analyzer (MIRO Analytical AG) to measure in-situ concentrations of 10 greenhouse gases and air pollutants simultaneously. The analyzer measured CO2, N2O, H2O and CH4, and the pollutants CO, NO, NO2, O3, SO2 and NH3 with high precision and a measurement rate of 1 Hz. The instrument was operated remotely without the need of on-site personnel. The instrument package was complemented by electrochemical sensors for NO, NO2, Ox and CO (alphasense), an optical particle counter (alphasense), temperature, humidity, altitude and position monitoring. Three campaigns of two weeks each were conducted in 2020 comprising unattended operation during commercial passenger flights.The acquired data set will be discussed in regard to (1) diurnal height profiles of trace gases such as NO2, (2) a detailed source attribution by fingerprinting, and (3) a comparison to observations from ground-based monitoring stations. The results demonstrate the QCL spectrometer as an all-in-one solution for air-borne trace gas monitoring. By measuring 10 compounds at once it helps to greatly reduce payload, space requirements and power consumption.

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Impact of Lockdown on Air Quality in India

Shanlax International Journal of Economics ◽

10.34293/economics.v10i1.4440 ◽

2021 ◽

Vol 10 (1) ◽

pp. 1-10

Author(s):

V Dhulasi Birundha ◽

S Ganesan ◽

M Chitra

Keyword(s):

Air Pollution ◽

Air Quality ◽

Quality Indicators ◽

Living Organism ◽

Data Set ◽

The Sustainable Development ◽

Pollution Levels ◽

Industrial Sites ◽

Chennai City

The Covid-19 crisis has forced activity freezes, Lockdowns and calls to shelter-in-place have closed schools and non -essential businesses. Minimal activities from industrial sites, factories and construction sectors have minimized the risks for toxins to escape, in turn improving air quality. People are forced to stay at home practicing social distancing and working remotely. It is all aimed at controlling the spread of Covid-19 and hopefully reducing the death toll. But all this change has also led to some unexpected consequences. One among them is pollution levels and the natural environment. Before the start of the Covid-19 pandemic, the air around us had been deemed very toxic to breathe in due to the number of greenhouse gases that had been emitted over the centuries. But after the coronavirus lockdown commenced, there were slight changes in the environment. In the above context, a study should be undertaken to analyze the air quality indicators during non-lockdown period and the lockdown period is inevitable and essential. In this regard, the researcher wants to analyze the air quality of Chennai City by comparing the air quality indicators values like P.M.2.5, NO2, SO2, CO for the year 2019 with 2020 (same period). Accordingly, the researcher has collected data information and analysed it with the help of regression analysis and trend lines. The results revealed that during the lockdown period, everything was shut down and it would decrease the values of the above said air quality indicators, especially the concentration of P.M.2.5 because it is the major factor contributing to air pollution. It was proved by many earlier studies and this study also proved the same. The data set revealed that nearly 80 percent of the air pollution was due to the concentration of P.M.2.5 and its concentration was lowered during the lockdown period. Hence, to avoid air pollution, authorities should be taken steps to reduce P.M.2.5 concentration. It is good for the environment, the health of the living organism and the sustainable development of the economy.

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A driver drowsiness and distraction warning system based on raspberry Pi 3 Kit

Transport and Communication Science Journal ◽

10.25073/tcsj.70.3.4 ◽

2019 ◽

Vol 70 (3) ◽

pp. 184-192

Author(s):

Toan Dao Thanh ◽

Vo Thien Linh

Keyword(s):

Processing System ◽

Warning System ◽

Raspberry Pi ◽

Data Set ◽

Lower Lip ◽

Driver Drowsiness ◽

Image Sensing ◽

The Face ◽

The Common ◽

University Laboratory

In this article, a system to detect driver drowsiness and distraction based on image sensing technique is created. With a camera used to observe the face of driver, the image processing system embedded in the Raspberry Pi 3 Kit will generate a warning sound when the driver shows drowsiness based on the eye-closed state or a yawn. To detect the closed eye state, we use the ratio of the distance between the eyelids and the ratio of the distance between the upper lip and the lower lip when yawning. A trained data set to extract 68 facial features and “frontal face detectors” in Dlib are utilized to determine the eyes and mouth positions needed to carry out identification. Experimental data from the tests of the system on Vietnamese volunteers in our University laboratory show that the system can detect at realtime the common driver states of “Normal”, “Close eyes”, “Yawn” or “Distraction”

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