Papers in this session are devoted to analyzing data from both conventional and remote-sensing observational platforms. In particular, presentations are invited on the integration of data collected from different platforms, and on the use of new satellite data products in air quality modeling. Session topics include:
- Satellite processing products and its use
- Monitoring air pollution and meteorology
- Field measurement studies
- Laboratory smog chamber experiments
- Aerosol detection and sampling
In addition, new sensor technologies, due to their characteristics (e.g., low cost, small size, high portability), are becoming increasingly important for individual exposure assessment, especially since this kind of instrument can provide measurements at high spatial and temporal resolution, which is a notable advantage when approaching assessment of exposure to environmental contaminants.
This session will provide information about advancements on the developments and use of sensor technology for air quality and health studies.
Topics include, but are not limited to, the following:
- Novel air sensor technologies for monitoring air quality and health conditions
- Evaluation and validation of sensor performance
- Application of sensor network on air quality, exposure and health studies
Presentations
Waluyo Eko Cahyono
Fernando Campo
Presentation: 2486DEPLOYMENT OF MOBILE AND FIXED AIR SENSOR PLATFORMS IN THE CITY OF FLORIANPOLIS, BRAZIL: PRELIMINARY RESULTS
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DEPLOYMENT OF MOBILE AND FIXED AIR SENSOR PLATFORMS IN THE CITY OF FLORIANPOLIS, BRAZIL: PRELIMINARY RESULTSFernando Campo, Andy Blanco-Rodriquez, Robson Will, Thiago Vieira Vasques, Nathan Campos Teixeira, Davide Franco, Alejandro Garcia-Ramirez, Leonardo Hoinaski
In this work, we present the preliminary results of deploying mobile and fixed air sensor platforms in the city of Florianopolis, Brazil, as a way of addressing the matter of collecting locally representative air quality data. The basic structure of the sensor nodes consists of: an Arduino Mega, an array of electrochemical gas sensors, a GPS module for geo-location, an SD card for data storage, a Real-Time Clock, and an ESP8266 module for Wi-Fi communication. Each node measures gaseous pollutants that are regulated by the Brazilian environmental laws. Both mobile and fixed nodes use digital gas sensors for IoT from SPEC Sensors; the fixed node, in particular, includes an array of Alphasense B4 series sensors for air quality networks.
The problem of local representativeness of air quality data is an issue for government offices and environmental agencies. The lack of relevant information may result in a deficient estimation of air pollution and on the implementation of poorly effective air quality management policies. This topic is especially relevant in Brazil, where regulatory monitoring is still limited. The high costs of the regulatory stations and their maintenance, as well as the lack of qualified staff, hamper the deployment of spatially broader and denser monitoring networks.
The main objective of this presentation is to discuss the performance of the sensor platforms according to some expected behavior and the influence of environmental conditions. The way to tackle this is by checking the existence of a correspondence between the sensor responses, the daily and weekly traffic patterns, and the levels of air pollution expected at different locations. Another analysis compares the outputs of Alphasense versus SPEC sensors, as well as the mobile node versus a Sniffer 4D V1 multi-gas detector. Finally, the effect of environmental variables such as temperature and relative humidity on the electrochemical sensors is analyzed.
The air sensors systems developed are still in its prototype phase and require further enhancements and assessment, especially what regards to laboratory calibrations, in-field co-location with regulatory monitoring stations, and long term performance. However, the results that this work presents point to more basic problems on the platforms that require improvement and also define a pathway for future analysis and processing of new data. These platforms have the potential for increasing the spatial and temporal resolution of monitoring networks in the city, as well as for opening the way to new monitoring services and applications such as the creation of air pollution maps, the detection of "hotspots" in the city, citizen science and education on air pollution topics, assessment of personal exposure to gas contaminants and evaluation of the impacts that the performance of physical activities on polluted environments has to the human health.
Peiyang Cheng
Jingting Huang
Hossein Khajehpour
Maria Makarova
Presentation: 2463Emission Monitoring Mobile Experiment (EMME): an overview and results of the St. Petersburg (Russia) megacity campaigns of 2019-2020
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Emission Monitoring Mobile Experiment (EMME): an overview and results of the St. Petersburg (Russia) megacity campaigns of 2019-2020Maria Makarova1, Frank Hase2, Dmitry Ionov1, Carlos Alberti2, Stefani Foka1, Thomas Blumenstock2, Vladimir Kostsov1, Thorsten Warneke3, Yana Virolainen1, Anatoly Poberovskii1
1 Department of Atmospheric Physics, Faculty of Physics, St. Petersburg State University, Russia
2 Institute of Meteorology and Climate Research IMK-ASF, Karlsruhe Institute of Technology, Karlsruhe, Germany
3 University of Bremen, Germany
In 2019 and 2020, the mobile experiment EMME (Emission Monitoring Mobile Experiment) was conducted within the St. Petersburg agglomeration (Russia) aiming to estimate the emission intensity of greenhouse (CO2, CH4) and reactive (CO, NOx) gases for St. Petersburg which is the largest Northern megacity. The area of St. Petersburg urban agglomeration is about 1440 km2. As of 2018, the city has a population of ~5.4 million people (the official data for 2018); according to unofficial data the population is now more than 7 million. The entire campaign consisted
of 11 mostly cloudless days of measurements in March-April 2019 and 6
days in March-early May 2020. In 2020, the EMME experiment was carried out during three days before the COVID 19 pandemic lockdown and three days during the lockdown.
The core instruments of the campaign were two portable FTIR spectrometers Bruker EM27/SUN which were used for ground-based remote sensing measurements of the total column amount of CO2, CH4 and CO at upwind and downwind locations on the opposite sides of the city. The NO2 tropospheric column amount was observed along a circular highway around the city by continuous mobile measurements of scattered solar visible radiation with OceanOptics HR4000 spectrometer using the DOAS technique.
The estimates of the St. Petersburg area fluxes for the considered greenhouse and reactive gases were obtained by coupling a box model and the results of the EMME observational campaign using the mass balance approach. The area fluxes for St. Petersburg city center were estimated as (89 x 28) kt km-2 yr-1 of CO2, (135 x 68) t km-2 yr-1 of CH4, (251 - 104) t km-2 yr-1 of CO and (66 - 28) t km-2 yr-1 of NOx.
Coupling the EMME 2019&2020 observations with HYSPLIT simulations and the a priori information on CO2 emissions from the ODIAC database, we evaluated the total CO2 emission from St.Petersburg megacity which amounts to (76-5) million tons per year for 2019 and (68-7) million tons per year for 2020.
Acknowledgements
This activity has received funding from the European Union's Horizon 2020 research and innovation programme under grantagreement No 776810 (VERIFY project). The research was supported by Russian Foundation for Basic Research through the project No.18-05-00011. Ancillary experimental data were acquired using the scientific equipment of "Geomodel" research centre of St. Petersburg State University.
Junhua Zhang