A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased ...spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment.
Low-cost air quality sensors continue to spread. While their measurement quality does not compete with high-end instrumentation deployed in official air quality monitoring stations, they have a great ...potential to complement existing air quality assessments. However, we still see challenges related to data quality, data interoperability, and for collaborating on data assimilation and calibration. In order to move ahead we gathered as a group of 38 organisations from 14 different countries, including governmental authorities, network operators, citizen science initiatives, environmental Non-Governmental Organisations (NGOs), and academic researchers to explore how we can collaborate and better leverage each other’s work. This statement captures our joint findings and recommendations.
Our key observations include:
Co-operation between official monitoring networks (reference quality data) and lower-cost sensor operators is a key to make air quality data more usable.
To be able to combine forces and benefit from each other’s expertise, the different perspectives of all stakeholders should be taken into account.
There is a need to ensure that all users understand the possibilities and the limitations of making sense out of observations from different sensors.
It is not realistic to expect that in the near future the data quality of lower-cost sensors will be as good as that of the official data. A way to make use of data that is of lower accuracy is by employing them in air quality modelling.
Transparency about data quality is important to build more trust in the data, and to avoid unrealistic expectations.
The need for interoperability should be clearly articulated and promoted by potential data users.
There a need (and an opportunity) to provide guidance and standard operating procedures for the deployment and calibration of lower-cost sensors in order to increase the data quality delivered by participants of citizen science projects.
Presently, we prefer to consider fixed-stationary sensors in a network instead of mobile sensor data. Furthermore, stationary data should not be aggregated with data from mobile sensors.
Publishing and sharing this statement is only small step in the right direction and further actions have to be taken, inlcuding more in-depth discussions of the recommendations in smaller groups and follow-up meetings on dedicated topics.
Co-operation between official monitoring networks (reference quality data) and lower-cost sensor operators is a key to make air quality data more usable.
To be able to combine forces and benefit from each other’s expertise, the different perspectives of all stakeholders should be taken into account.
There is a need to ensure that all users understand the possibilities and the limitations of making sense out of observations from different sensors.
It is not realistic to expect that in the near future the data quality of lower-cost sensors will be as good as that of the official data. A way to make use of data that is of lower accuracy is by employing them in air quality modelling.
Transparency about data quality is important to build more trust in the data, and to avoid unrealistic expectations.
The need for interoperability should be clearly articulated and promoted by potential data users.
There a need (and an opportunity) to provide guidance and standard operating procedures for the deployment and calibration of lower-cost sensors in order to increase the data quality delivered by participants of citizen science projects.
Presently, we prefer to consider fixed-stationary sensors in a network instead of mobile sensor data. Furthermore, stationary data should not be aggregated with data from mobile sensors.
Publishing and sharing this statement is only small step in the right direction and further actions have to be taken, inlcuding more in-depth discussions of the recommendations in smaller groups and follow-up meetings on dedicated topics.
The modified Target Diagram (MTD) was developed to evaluate the performance of low-cost sensors (LCS) for air quality monitoring in comparison with reference methods by reporting relative expanded ...uncertainty and its contributors. An MTD provides several pieces of information, including compliance with regulation, sources of error and how to diminish them, completeness and validity of LCS calibration etc. It allows the user to examine the effect of selecting different regression types and residual fitting on the LCS measurement uncertainty. The ordinary least squared regression with fitted residuals and dynamic between reference analyser uncertainty rather than constant ones yielded more realistic LCS measurement uncertainty compared to other options. The MTD is a fast visual tool to extract several pieces of information on evaluation of any candidate method against reference method.
•A graphical tool to evaluate performances of sensors was developed.•Uncertainty of sensors and its' contributors can be displayed.•Checking compliance of sensors with legislation is easy and fast.•Several other information can be extracted.
The present investigation, carried out as a case study in a typical major city situated in a European coal combustion region (Krakow, Poland), aims at quantifying the impact on the urban air quality ...of residential heating by coal combustion in comparison with other potential pollution sources such as power plants, industry, and traffic. Emissions were measured for 20 major sources, including small stoves and boilers, and the particulate matter (PM) was analyzed for 52 individual compounds together with outdoor and indoor PM10 collected during typical winter pollution episodes. The data were analyzed using chemical mass balance modeling (CMB) and constrained positive matrix factorization (CMF) yielding source apportionments for PM10, B(a)P, and other regulated air pollutants namely Cd, Ni, As, and Pb. The results are potentially very useful for planning abatement strategies in all areas of the world, where coal combustion in small appliances is significant. During the studied pollution episodes in Krakow, European air quality limits were exceeded with up to a factor 8 for PM10 and up to a factor 200 for B(a)P. The levels of these air pollutants were accompanied by high concentrations of azaarenes, known markers for inefficient coal combustion. The major culprit for the extreme pollution levels was demonstrated to be residential heating by coal combustion in small stoves and boilers (>50% for PM10 and >90% B(a)P), whereas road transport (<10% for PM10 and <3% for B(a)P), and industry (4−15% for PM10 and <6% for B(a)P) played a lesser role. The indoor PM10 and B(a)P concentrations were at high levels similar to those of outdoor concentrations and were found to have the same sources as outdoors. The inorganic secondary aerosol component of PM10 amounted to around 30%, which for a large part may be attributed to the industrial emission of the precursors SO2 and NO x .
Air quality, especially in urban areas, deteriorated with the industrial revolution and the following centuries. It is only during the last 60 years, following e.g. the infamous London smog episode ...(1952), that the health impacts of air pollution have been recognised and acted upon. In the developed world, abatement strategies and closure of major industries have led to significant air quality improvements (Harrison, 2004, Lamarque et al., 2010, Monks et al., 2009, Smith et al., 2011 and Tørseth et al., 2012). However, current air pollution levels in Europe and North America have still important short-term (Samoli et al., 2008) and long-term health effects (Beelen et al., 2013, Pope et al., 2009 and Raaschou-Nielsen et al., 2013) including increases in mortality and corresponding decreases in life expectancy, as well as effects on respiratory and cardiovascular morbidity (WHO REVIHAAP project, 2013). The evaluation of current research within the Clean Air for Europe (CAFE) process has clearly shown that investments in further air quality improvements will have a beneficial return financially, in terms of population health, environmental improvements and in quality of life (Bell et al., 2011, EEA, 2007 and Pascal et al., 2013). This is similarly seen in the USA (Esworthy, 2013) and supported e.g. by the results of Parrish et al. (2009) in mega-cities across the world...
Low-cost sensors (LCSs), thanks to their affordable costs, size and relatively ease of use, make the monitoring of air quality possible for general public with limited knowledge of sensor technology, ...data analysis and visualisation. Nevertheless, due to the huge range of available LCSs and relatively new practise in implementation, a guide helping on knowing sensor technology, pros and cons... is necessary for non-expert users. This guidance aims at providing information on deploying LCSs by public, e.g. citizens, non-governmental organisations, local-authorities, communities... The guidance describes the selection of LCSs, verification and utilisation of LCSs data but not calibration of LCSs. The guidance focuses on LCSs of particulate matter, ozone, nitrogen dioxide, carbon monoxide, and nitrogen monoxide. In this guide, we summarised the types of LCSs, details of JRC-developed open source AirSensEUR Sensor System and major steps of designing a monitoring study using such Sensor Systems. For single use of Sensor System, measurement accuracy should be assessed at a reference air quality monitoring station, otherwise, some uncertainty in measurement must be considered when data are used. It is recommended to integrate such single use Sensor Systems into city-air quality sensor network, if exists, which will help to monitor air quality city-wise. Sensor networks are crucial to monitor air quality temporally and spatially, and this guide summarises designing monitoring network, verification, quality control and data usage etc.
This guidance provides information to be utilised by experts for the management of networks of low-cost sensors (LCSs) for monitoring of air quality. The guidance includes: - Selection of LCSs ...including general performance information, price, pros and cons etc. - Design of field study for the calibration and performance assessment purposes. - Description of the open source computation platform for data integration used for several purposes such as selecting calibration intervals, evaluation of calibration models as well as their performances and drifts, and uncertainty of predictions. - The standard operating procedure (SOP) of automated calibration, quality assurance/control (QA/QC) strategies, and recommended period of re-calibration. - Operation of LCS network including managing of data, QA/QC and presentation of results to stakeholders including plotting of time series and mapping.
The potential of the voltammetry method was examined for the determination of heavy metals in ambient air particulate matter (PM sub(10)) on quartz filter. Cd, Pb, Cu, Zn, As were determined by ...anodic stripping voltammetry while adsorptive stripping voltammetry was used for the analysis of Ni. The method detection limit of these metals were 9.3, 0.1, 0.8, 0.3, 0.4, 0.1 ng m super(-3) for Zn, Cd, Pb, Cu, Ni and As, respectively. In addition, the analysis of a Certified Reference Material NIST 1648, yielded recoveries between 92% and 103%. Consequently, both the detection limit and recovery of the voltammetric method satisfy the requirements of the European Standard for the analyses of heavy metals in PM sub(10) (EN 14902). A comparison of the inductively coupled plasma- mass spectrometry (ICP-MS) and voltammetry method on the NIST 1648 and PM sub(10) filters showed the differences between them remained well within the level of uncertainty on the NIST 1648 requested by European Directives for heavy metals (25% for Pb and 40% for As, Cd and Ni, respectively). In addition to its compliance with legislations, the voltammetry method benefits from low investment cost and the potential of complete automation. As such, one may expect voltammetry to provide a reliable alternative to the European laboratories in charge of ambient air monitoring at the time when the European Directives require to measure heavy metals in PM sub(10) on a regularly basis.
The potential of the voltammetry method was examined for the determination of heavy metals in ambient air particulate matter (PM
10) on quartz filter. Cd, Pb, Cu, Zn, As were determined by anodic ...stripping voltammetry while adsorptive stripping voltammetry was used for the analysis of Ni. The method detection limit of these metals were 9.3, 0.1, 0.8, 0.3, 0.4, 0.1
ng
m
−3 for Zn, Cd, Pb, Cu, Ni and As, respectively. In addition, the analysis of a Certified Reference Material NIST 1648, yielded recoveries between 92% and 103%. Consequently, both the detection limit and recovery of the voltammetric method satisfy the requirements of the European Standard for the analyses of heavy metals in PM
10 (EN 14902). A comparison of the inductively coupled plasma-mass spectrometry (ICP-MS) and voltammetry method on the NIST 1648 and PM
10 filters showed the differences between them remained well within the level of uncertainty on the NIST 1648 requested by European Directives for heavy metals (25% for Pb and 40% for As, Cd and Ni, respectively). In addition to its compliance with legislations, the voltammetry method benefits from low investment cost and the potential of complete automation. As such, one may expect voltammetry to provide a reliable alternative to the European laboratories in charge of ambient air monitoring at the time when the European Directives require to measure heavy metals in PM
10 on a regularly basis.
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