Comparative study of air quality indices in the European Union towards adopting a common air quality index

Abstract

This study aims to compare air quality indices applied in European Union countries towards adopting a common air quality index. The urban European cities Rome, Madrid, Paris, London, Berlin, Warsaw, Stockholm, and Oslo were selected. Using the EEA AirBase air quality database, time series data for the major atmospheric pollutants (CO, NO2, SO2, O3, PM10, and PM2.5) were recovered for each city, for most recent years available. Daily averages, maximum hourly values and maximum 8-h averages were calculated for each pollutant. The air quality indices selected were BelAQI, DAQx, DAQI, AtmoIndex, AQIH, and CAQI. The daily value of each air quality indices and the corresponding dominant atmospheric pollutant were determined for each city. A two-stage normalization procedure was applied on air quality indices in a 0–1 range, to allow their direct comparison without altering their structure. All air quality indices exhibited air quality rates over 64% for all cities, thus below the European Union air quality standard. The dominant pollutant was NO2 for both BelAQI and DAQx; O3 for both DAQI and AQIH (with an exception for Warsaw where SO2 was the dominant pollutant). For CAQI, NO2 prevails in Berlin, London, Warsaw, Stockholm, and Oslo, while O3 prevails in Rome, Madrid, and Paris. The dominant pollutant for AtmoIndex was NO2 in Berlin, Warsaw, and Stockholm; O3 in Madrid, Paris, London, and Oslo; PM10 in Rome. A very strong positive statistical correlation ( p < 0.01) was found for all cities between BelAQI and CAQI, and also between CAQI and DAQx. A strong positive statistical correlation ( p < 0.01) was found for all cities between BelAQI and DAQx. A moderate positive correlation was shown between the following pairs of indices: AtmoIndex-DAQI, AtmoIndex-AQIH, DAQI-AQIH, BelAQI-AQIH, and AQIH-CAQI. On the contrary, a weak positive correlation was noticed between the following pairs of indices: BelAQI-DAQI, BelAQI-AtmoIndex, DAQX-DAQI, DAQx-AQIH, DAQI-CAQI, and CAQI-AtmoIndex. After the normalization process that enables the direct comparison of the air quality indices, the main results are the BelAQI presents the largest normalized median (range 0.33–0.5) implying the worst air quality compared to the other air quality indices. The CAQI has a median value of 0.33, the DAQx of 0.25, while the AtmoIndex a median value range of 0.125–0.375, and the DAQI and AQIH of 0.165–0.33. Concluding, the AQIH can be proposed as a common European Union air quality index because: firstly, its calculation comprises all significant atmospheric pollutants including PM2.5, thereby being harmonized with the Directive 2008/50/EC, and, secondly, AQIH does not display extremely low or high (normalized) values compared to the other air quality indices.

PM10 and the air quality stress index in an industrial city of Eastern Mediterranean

“…In European Union (EU), although member states are subject to the same directives in respect of air quality, the use of a common Air Quality Index (AQI) has not been adopted, with most countries applies their own AQI. This is because AQIs were developed in most of countries and thus have been adapted to technical requirements, quality standards and Knowledge needs of the investigated area (Karavas et al, 2021).…”

An Overview of Experiences Made and Tools Used to Inform the Public on Ambient Air Quality

“…As a complementary comparison of the AQI values and classes, the methodology of normalization described by Lokys [20] was applied. This methodology, based on a two-stage normalization procedure, was applied by Lokys to three European AQIs and by Karavas [3] to six European AQIs to make the index values directly comparable. The AQI normalization in both works is based on European guideline values, while in this work, after a comprehensive study of national standards almost worldwide, the USA standards were chosen as reference values (or benchmarks).…”

“…A recent comparative study of air quality indexes in the European Union [3] selected some European cities (Rome, Madrid, Paris, London, Berlin, Warsaw, Stockholm, and Oslo) and calculated for them different air quality indexes starting from the row data downloaded by the European air quality database. The main pollutants were included (CO, NO 2 , SO 2 , O 3 , PM 10 , and PM 2.5 ) and the most relevant for each city was determined.…”

“…The tools used can include traditional media, but also websites, social media, and mobile apps. In most countries, rules are also set to assure public access to environmental information as a relevant obligation according to the principles of the Aarhus Convention; in such a way, information on air quality is completely shared with the public and the communication between the public and administrations is improved [3].…”

Statistical Characteristics of Air Quality Index DAQx*-Specific Air Pollutants Differentiated by Types of Air Quality Monitoring Stations: A Case Study of Seoul, Republic of Korea

“…They are often approximated by urban form variables in models such as land use regression (LUR) models to predict the spatial distribution of air pollutants [29][30][31][32]. The methodology used to determine AQIs is described in detail in the literature [10,33,34] and is not repeated here.…”