Opinion: Insights into updating Ambient Air Quality Directive (2008/50EC)

. As the evidence for the adverse health effects of air pollution continues to increase, World Health Organization (WHO) recently published its latest edition of the Global Air Quality Guidelines. Although not legally binding, the 15 guidelines aim to provide a framework in which policymakers can combat air pollution by formulating evidence-based air quality management strategies. In the light of this, European Union has stated its intent to revise the current Ambient Air Quality Directive (2008/50/EC) to resemble closer to that of the newly published WHO guidelines (European Commission, 2020). This article provides an informed opinion on selected features of the air quality directive that we believe would benefit from a reassessment. The selected features include discussion about 1) air quality sensors as a part of hierarchical 20 observation network, 2) number of minimum sampling points and their siting criteria, and 3) new target air pollution parameters for future consideration.

parameters, typically evaluated non-regulated particle metrics also include particle number and surface area-based concentrations, particle size distributions as well as black carbon or elemental carbon (BC/EC) (e.g. de Jesus et al., 2019;Wu & Boor, 2020). Exposure to air pollution occurs both indoors and outdoors although people spend most of their time indoors (World Health Organization, 2006). 35 To combat poor outdoor air quality, World Health Organization (WHO) has produced a series of guidelines to support policymakers in setting air quality management strategies. Although being neither standards nor legally binding criteria, the guidelines are based on expert evaluation of scientific evidence and are thus a valuable source of information. The earliest guidelines were published in 1987 and the subsequent revisions in 2000 and 2006. The newest edition, which was published 40 in 2021, represents the most up-to-date understanding of air pollution and its impacts on human lives (World Health Organization, 2021). In the light of this, the European Union has stated its intent to revise the current Ambient Air Quality Directive 2008/50/EC (AAQD, European Council, 2008) to resemble closer to that of the new WHO guidelines (European Commission, 2020). The purpose of this article is to provide an expert opinion on how the AAQD should be developed taking into account the latest technological and scientific advances in air quality monitoring.  (Popoola et al., 2018). In practice, if the uncertainty of a measurement from one node to another is too large, identifying and assessing the local concentration hotspots and emission sources will not be possible. When considering dense monitoring networks alone, it could be argued that the absolute sensor accuracy is secondary to its intra-unit precision.
When testing and evaluating sensors, the manufacturer should make clear whether the data generated by a sensor is based on an actual measurement of the pollutant itself or whether it is based on the combination of, for example, machine learning and secondary data (Li et al., 2020). This is important to ensure transparency. If the sensor relies heavily on data post-processing and advanced conversion methods, the data should be treated as modelling data. In our view, this is because the data then resembles closer to a mathematical prediction rather than an independent measurement. It can be debated where exactly the 105 boundary between a measurement and a prediction is; some empirical corrections may be justifiable and reasonable (Schneider et al., 2019). However, as multiple studies have shown that sensors may entail detrimental flaws (Castell et al., 2017;Giordano et al., 2021), it is very important to distinguish between a real and valid observation and, for example, an AIbased extrapolation of the originally insufficient and inaccurate data.

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The authors are aware of the technical specification CEN/TC 264/WG 42 -Ambient air -Air quality sensors being under development, and publication of this specification is awaited with interest.

Determining the minimum amount of sampling points
In the European Union, the Member States define their zones and agglomerates in which air quality monitoring takes place.
Typically, the division between areas follows the administrative unit boarders although joint efforts, where neighbouring 115 units conduct air quality monitoring together, are also possible. In general, the minimum number of fixed sampling points for a specific area is then determined according to the population of that area, as shown in Table 2. As population is the sole factor determining the minimum number of sampling points, this may lead to cases where the number of minimum sampling points between two vastly different zones or agglomerates is strikingly similar. For example, the Finnish Laplandone of the monitoring zones in Finlandcovers an area of approximately 100 000 km2 and has 175 000 inhabitants, whereas the 120 Helsinki Metropolitan areaalso a monitoring zone in Finlandcovers an area of 1 500 km2 and has 1.2 million inhabitants. According to Table 2, if the maximum concentrations are between the upper and lower assessment thresholds, the Lapland monitoring zone requires a total of 2 sampling points (1 per 87 500 inhabitants) whereas the Helsinki Metropolitan area requires 5 sampling points (1 per 240 000 inhabitants). In our view, the proportions of the required sampling points are imbalanced, and the difference in required sampling points should be greater between the two areas. A 125 fairly similar example to that of the Finland can be found in Norway between the Oslo metropolitan agglomerate (5 sampling points; 1 per 206 000 inhabitants) and Troms and Finmark zone (2 sampling points; 1 per 117 000 inhabitants). A more sophisticated approach would be to connect the minimum number of sampling points to the population density rather than to just population alone. Population density data is readily available on-line (https://ghsl.jrc.ec.europa.eu/ghs_pop2019.php).
Implementation of this connection could be done in a multitude of ways, and it should be ensured that the scaling is 130 appropriate; on average, the number of sampling points should increase rather than decrease. Taking population density into account the determination of the amount of observation points would track more closely the real exposure citizens are subjected to and thus the directive would better fulfil its main purpose of protecting human health.

Siting criteria of sampling points
In the current AAQD, the definitions and instructions regarding the siting of sampling points are in some parts poorly 135 formulated. This has been outlined exceptionally well by Maiheu & Janssen (2019) in their report Assessing the spatial representativeness of AQ sampling points. Some examples of the poor formulation include the use of vague terms such as "some metres away" and "edge of major junction", which both can be interpreted in a multitude of ways. We propose here that rather than trying to define the ultimate set of all-encompassing siting guidelines, it is worth considering to what extent it would be appropriate to rely on the expertise and judgement of the local air quality authorities themselves. The potential 140 abuse of liberty with respect to artificially improving air quality by situating the stations to only low concentration areas is a real problem, and some boundary conditions are necessary. But in reality, practicalities such as availability of power and local regulations have a significant impact on the final site location. As the technology evolves, sensors may eventually play a key role in solving this dilemma, but as of yet, the clear and well-defined siting criteria and practical challenges related to the deployment of monitors are in odds with one another. With respect to solving the problem of "spatial representativeness" 145 and prioritising siting criteria, measurements at two different sites instead of only one solves these problems in many cases; there is no need to make decision between two equally worthy measurement locations if the amount of sampling points allows both locations to be covered. Fundamentally, the necessity of siting criteria arises from the scarcity of measurements, and the hierarchical monitoring approach is the right tool to address it. This further underlines the need and utility of dense sensor networks. 150

New target parameters for future consideration
The primary motivation of ambient air quality monitoring is the protection of human health. Epidemiological studies have shown that particulate matter is the dominant pollutant causing morbidity and premature deaths (European Environment Agency, 2020); however, it is still unclear to some degree, what the explicit mechanisms driving the adverse health effects are (Fiordelisi et al., 2017). Mass-based parameters PM2.5 and PM10 have been used as target parameters due to the clear 155 evidence of their association with adverse health effects (Burnett et al., 2018). Ultrafine particles have also been considered a factor, but the current literature suggests that besides their short-term association with inflammatory and cardiovascular changes, there is insufficient evidence showing that they drive negative health effects independently of other particulate matter constituents (Ohlwein et al., 2019). Exposure to black carbon also entails negative health effects, and it has been shown to be an important detrimental component of PM2.5 (Yang et al., 2019). Additionally, the climatic effects of black 160 carbon further underline its importance regarding air quality monitoring (Bond et al., 2013). Perhaps an often-overlooked parameter is pollen, which causes irritation symptoms to as many people as one in four in Europe each year (Bauchau & Durham, 2004). Pollen originates from plants, and besides reducing the exposure to it by personal behavioural changes, it is questionable what type of mitigation measures could be taken to reduce its concentrations; it is not reasonable to propose limit values for pollen. Nevertheless, out of all the particulate matter parameters and constituents, the adverse health effects 165 of pollen are the most visible and evident in people's daily lives. Similarly to sensor technology, measurement techniques for pollen have advanced, and monitors capable of online concentration measurement and species identification are currently available in the markets. Lastly, the monitoring of ambient aerosol parameters that are included in European emission regulations could significantly improve both the understanding of emission sources and the emission mitigation actions; for instance, regulatory emission measurements made for vehicles in road traffic include the measurement of exhaust solid 170 particle number, which is currently not monitored from traffic-influenced urban air.
Monitoring additional particulate parameters would undoubtedly be useful from the scientific point of view, and the newly published WHO guidelines supports this as it recommends monitoring of ultrafine particles (UFP) and BC/EC (World Health Organization, 2021). However, monitoring of the additional parameters would require new and extensive standardization 175 with respect to the new parameter-specific instrumentation and expensive investments by the monitoring bodies to these new instruments. Therefore, it may be more appropriate to suggest that the scientific community monitors these additional parameters with supporting, research-type Supersite stations, which remain outside of the regulatory monitoring framework.
Naturally, air quality authorities capable of conducting more extensive, voluntary-based monitoring are encouraged to do so, and initiating the preparation for instrument standardization would be useful regardless of the direction in which the AAQD 180 is headed in the future. As illustrated in Fig. 1, the idea of a Supersite station is to support and complement existing regulatory monitoring and to provide novel insights into air quality (e.g. Kulmala et al., 2021). The instrumentation could cover measurements for the additional parameters described previously as well as for the more advanced parameters such as chemical composition of particles. Moreover, due to the extensive measurement arsenal, new observation technologies could be benchmarked and calibrated rapidly. The more in-depth data generated by the Supersites would enable scientists and 185 policymakers to assess the needs and directions of future air quality regulation.

Summary and Outlook
Accurate and reliable fixed measurement monitors are, and should remain, the backbone of regulatory air quality monitoring.
Technological development of air quality sensors is advancing rapidly but more is needed for the sensors to have a major role in regulatory air quality monitoring. The full benefit of the new observational capacities of small sensors can be 7 obtained when a hierarchical observation system is considered (e.g. Hari et al., 2016). This would allow verification of the sensor network data quality against the higher quality observation sites in the vicinity. The hierarchical network would allow science-based development and rapid deployment of novel air quality devices as soon as they become available.
Instead of determining the siting criteria to match all the possible urban environments, more trust should be placed upon 195 local air quality expert analysis, and in some cases applying multiple sensors can be the way forward. Furthermore, the population density should be considered as the basis for determining the required amount of air quality observations. This will lead to an optimized air quality monitoring network providing more representative data in terms of population exposure.
At the same time, a specific focus should be placed upon constraining the intra-sensor variability to ensure that the true spatial variability of concentrations and sensor imprecision are not mixed with each other. 200 Monitoring of additional air quality parameters, such as ultrafine particles and black carbon, would be beneficial in terms of better understanding air pollution, and research-type Supersite stations operated by scientific community or, where possible, local air quality authorities could provide the platform for such monitoring. While supporting and complementing regulatory observation network, the more in-depth data generated by the Supersites could help in navigating the future air quality 205 directive requirements.

Data availability
No data sets were used in this article.  Measurements'. If random measurements are used to assess the requirements of the PM10 limit value, the 90,4 percentile (to be lower than or equal to 50 µg/m3) should be evaluated instead of the number of exceedances, which is highly influenced by data coverage.