hackAIR: Towards Raising Awareness about Air Quality in Europe by Developing a Collective Online Platform

Kosmidis, E.; Syropoulou, Panagiota; Tekes, Stavros; Schneider, Philipp; Spyromitros-Xioufis, Eleftherios; Riga, Marina; Charitidis, Polychronis; Moumtzidou, Anastasia; Papadopoulos, Symeon; Vrochidis, Stefanos; Kompatsiaris, Ioannis; Hloupis, George; Loukidis, Andronikos; Kourtidis, Konstantinos; Georgoulias, Aristeidis K.; Alexandri, Georgia

doi:10.3390/ijgi7050187

Cited by 35 publications

(19 citation statements)

References 33 publications

(37 reference statements)

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“…The performance characteristics of the available low-cost sensors should be well known, before their deployment for sensor-based management of air pollution [10]. This study is one of the major tasks within the EU H2020 project hackAIR (www.hackair.eu) [31], which is building a collective, awareness-raising platform for outdoor air quality with pilots in local communities in Norway and Germany. In this study, PM2.5 measurements from a set of three low-cost PM sensor units (SDS011) were compared against tapered element oscillating microbalance (TEOM) observations made at an air quality monitoring station in Oslo, Norway.…”

Section: Nova Pm Sensor Sds011mentioning

confidence: 99%

Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, Norway

et al. 2019

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The very low-cost Nova particulate matter (PM) sensor SDS011 has recently drawn attention for its use for measuring PM mass concentration, which is frequently used as an indicator of air quality. However, this sensor has not been thoroughly evaluated in real-world conditions and its data quality is not well documented. In this study, three SDS011 sensors were evaluated by co-locating them at an official, air quality monitoring station equipped with reference-equivalent instrumentation in Oslo, Norway. The sensors’ measurement results for PM2.5 were compared with data generated from the air quality monitoring station over almost a four-month period. Five performance aspects of the sensors were examined: operational data coverage, linearity of response and accuracy, inter-sensor variability, dependence on relative humidity (RH) and temperature (T), and potential improvement of sensor accuracy, by data calibration using a machine-learning method. The results of the study are: (i) the three sensors provide quite similar results, with inter-sensor correlations exhibiting R values higher than 0.97; (ii) all three sensors demonstrate quite high linearity against officially measured concentrations of PM2.5, with R2 values ranging from 0.55 to 0.71; (iii) high RH (over 80%) negatively affected the sensor response; (iv) data calibration using only the RH and T recorded directly at the three sensors increased the R2 value from 0.71 to 0.80, 068 to 0.79, and 0.55 to 0.76. The results demonstrate the general feasibility of using these low cost SDS011 sensors for indicative PM2.5 monitoring under certain environmental conditions. Within these constraints, they further indicate that there is potential for deploying large networks of such devices, due to the sensors’ relative accuracy, size and cost. This opens up a wide variety of applications, such as high-resolution air quality mapping and personalized air quality information services. However, it should be noted that the sensors exhibit often very high relative errors for hourly values and that there is a high potential of abusing these types of sensors if they are applied outside the manufacturer-provided specifications particularly regarding relative humidity. Furthermore, our analysis covers only a relatively short time period and it is desirable to carry out longer-term studies covering a wider range of meteorological conditions.

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Section: Nova Pm Sensor Sds011mentioning

confidence: 99%

Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, Norway

et al. 2019

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“…During the project phase (2016)(2017)(2018), it was also possible to take pictures of the sky with the hackAIR smartphone app (Kosmidis et al 2018). Its technology enabled the estimation of air quality based on sky-depicting images.…”

Section: Box 222: Hackair Citizen Science Platformmentioning

confidence: 99%

Citizen Science Platforms

Liu

Dörler

Heigl

et al. 2021

The Science of Citizen Science

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Adequate infrastructure for citizen science is constantly growing and has become increasingly important in providing support to citizen science activities, both nationally and internationally. Many types of citizen science infrastructures exist, with different functionalities. This chapter focuses on current citizen science platforms. The platforms addressed in this chapter are those which display citizen science data and information, provide good practical examples and toolkits, collect relevant scientific outcomes, and are accessible to different stakeholders, ranging from interested citizens to scientific institutions to authorities, politicians, and public media. We present current citizen science platforms in Europe and associated (inter)national citizen science networks and discuss how these platforms have become increasingly vital within citizen science. Based on these examples, we elaborate on challenges for citizen science platforms, such as establishing and financing platforms, designing user interfaces, maintaining platforms, promoting the usage of platforms, etc. We conclude with an outlook into potential development needs of citizen science platforms in the future.

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“…Other approaches have used spectropolarimeters as add-ons, such as within the iSpex project (Snik et al, 2014), to measure PM concentration level. The idea of using a smartphone camera to measure air pollution has been adopted by the HackAir project (Kosmidis et al, 2018). Furthermore, the most recent smartphone cameras and ash function-based development of a ne dust measurement system called FeinPhone (Budde et al, 2019) suggests that low-cost PM sensors may become default equipment in next-generation smartphones.…”

Section: Contribution Of Citizen Science To Improvements In Air Pollumentioning

confidence: 99%

Crowdsourcing Without Data Bias: Building a Quality Assurance System for Air Pollution Symptom Mapping Toward an SDG Indicator

Samulowska

Chmielewski

Raczko

et al. 2020

Preprint

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The United Nations (UN) sustainable development goals (SDGs), a strategy to guide the world’s social and economic transformation, highlight the issue of urban air pollution in SDG 11. Open data, as an output of citizen science (CS), are needed to supply and improve the SDG indicator system. Therefore, we propose a CS framework to extend the paradigm of urban air pollution monitoring from particulate matter concentration levels to air quality-related health symptom load, and foster the development of a tier-3 SDG indicator (which we call indicator 11.6.3). Building this new perspective for CS contributions to the achievement of SDGs, we address the problem of crowdsourced data bias as a prerequisite for better quality open data output. The aim of this study is to propose an air pollution symptom mapping framework for citizen-driven research and to find the most robust data quality assurance system (QAs) in this field. The method includes a GeoWeb application as well as data quality assurance mechanisms based on conditional statements, in order to reduce crowdsourced data bias. A four-month crowdsourcing campaign, released in Lubelskie voivodship (Poland), resulted in 1823 outdoor reports with a rejection rate of up to 28%, depending on the applied QA system (QAs). Testing the QAs variants, we find the most robust data bias solving method in survey-based symptom mapping. The framework output is shared via GeoWeb dashboards, including the 11.6.3 indicator evaluation. By familiarizing the public with citizen science, a city can track the progress of its SDG achievements and increase the transparency of the process through the use of GeoWeb.

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hackAIR: Towards Raising Awareness about Air Quality in Europe by Developing a Collective Online Platform

Cited by 35 publications

References 33 publications

Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, Norway

Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, Norway

Citizen Science Platforms

Crowdsourcing Without Data Bias: Building a Quality Assurance System for Air Pollution Symptom Mapping Toward an SDG Indicator

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