scholarly journals Study of car emissions in the Athens Restriction Ring from the mid 1980s to 2007 with a prediction scenario for 2011 using air quality indices

2010 ◽  
Author(s):  
A. Loster-Mańka ◽  
K. Karkalis ◽  
G. Arapis ◽  
M. Jedziniak
Keyword(s):  
Air Quality ◽  
Quality Indices ◽  
Prediction Scenario

scholarly journals Promoting Pollution-Free Routes in Smart Cities Using Air Quality Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2507 ◽  
Author(s):  
Francisco Ramos ◽  
Sergio Trilles ◽  
Andrés Muñoz ◽  
Joaquín Huerta
Keyword(s):  
Quality Of Life ◽  
Air Quality ◽  
Smart Cities ◽  
Extensive Study ◽  
Current Work ◽  
Quality Level ◽  
Quality Indices ◽  
Big City ◽  
Precautionary Measures

Nowadays, citizens have a huge concern about the quality of life in their cities, especially regarding the level of pollution. Air quality level is of great importance, not only to plan our activities but also to take precautionary measures for our health. All levels of governments are concerned about it and have built their indexes to measure the air quality level in their countries, regions or cities. Taking into account the existing sensor infrastructure within smart cities, it makes possible to evaluate these indices and to know anywhere the level of pollution in real-time. In this scenario, the main objective of the current work is to foster citizens’ awareness about pollution by offering pollution-free routes. To achieve this goal, a technology-agnostic methodology is presented, which allows for creating pollution-free routes across cities depending on the level of pollution in each zone. The current work includes an extensive study of existing air quality indices, and proposes and carries forward to deployment of the defined methodology in a big city, such as Madrid (Spain).

Evaluation and Management of Ambient Air Quality, with Special Reference to China

1980 ◽  
Vol 7 (3) ◽  
pp. 223-228 ◽  
Author(s):  
Yao Zhi-Qi
Keyword(s):  
Air Quality ◽  
Geometric Mean ◽  
Monitoring And Evaluation ◽  
Ambient Air ◽  
Average Concentration ◽  
Quality Indices ◽  
Ambient Air Quality ◽  
Annual Average ◽  
Hygienic Standard ◽  
Annual Average Concentration

Monitoring and evaluation of air quality in urban and industrial areas are essential for air quality management. For evaluating the composite air-quality in the concomitant presence of several pollutants in the atmosphere, many air quality indices have been developed. This paper presents two indices, the ‘composite air-quality index (I1)’ and ‘the standard-exceeding index of air pollution (I2)’ together with their respective sub-indices, for the pollutants monitored and for use in combination.The first index, I1, is based on the annual average concentration measured in a year for each pollutant; it measures the overall composite air-quality. By relating the annual average concentration (Ci) of each pollutant to its hygienic standard (Si), as many (Ci/Si) values as the number of pollutant parameters monitored are found, whereupon I1 is computed as the geometric mean of the maximum and average of all (Ci/Si) values. A greater value of I1 means worse composite air-quality. It is simpler to compute than those more sophisticated ones in the literature, and holds the unique characteristic of considering, and yet not overemphasizing as formula (3) does (Nemerow, 1974), the maximum (Ci/Si) value.

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

2020 ◽  
pp. 0958305X2092184
Author(s):  
Zissis Karavas ◽  
Vayos Karayannis ◽  
Konstantinos Moustakas
Keyword(s):  
European Union ◽  
Air Quality ◽  
Quality Index ◽  
Statistical Correlation ◽  
Air Quality Index ◽  
The Other ◽  
Atmospheric Pollutants ◽  
The European Union ◽  
Quality Indices ◽  
Positive Correlation

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.

scholarly journals The development of Air Quality Indices using AOD-Retrieved Images during haze events in Peninsular Malaysia

2019 ◽  
Vol 373 ◽  
pp. 012027
Author(s):  
Khaled Ali Ahmed Ben Youssef ◽  
Ahmad Makmom Abdullah ◽  
Helmi Zulhaidi Mohd Shafri ◽  
Zulfa Hanan Ashaari
Keyword(s):  
Air Quality ◽  
Peninsular Malaysia ◽  
Quality Indices

Air quality assessment in a heavily polluted urban Mediterranean environment through air quality indices

2012 ◽  
Vol 18 ◽  
pp. 259-268 ◽  
Author(s):  
P.A. Kassomenos ◽  
A. Kelessis ◽  
M. Petrakakis ◽  
N. Zoumakis ◽  
Th. Christidis ◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Assessment ◽  
Quality Indices ◽  
Mediterranean Environment ◽  
Air Quality Assessment

The development of air quality indices through image-retrieved AOT and PM10measurements in Limassol Cyprus

2012 ◽  
Author(s):  
Kyriacos Themistocleous ◽  
Diofantos G. Hadjimitsis ◽  
Adrianos Retalis ◽  
Nektarios Chrysoulakis
Keyword(s):  
Air Quality ◽  
Quality Indices

A comparison of air quality indices for a port and harbour region in India

2006 ◽  
Vol 26 (4) ◽  
pp. 313 ◽  
Author(s):  
A.K. Gupta ◽  
Rashmi S. Patil ◽  
S.K. Gupta
Keyword(s):  
Air Quality ◽  
Quality Indices

scholarly journals Www.airqualitynow.eu, a common website and air quality indices to compare cities across Europe

2007 ◽  
Author(s):  
S. vd. Elshout ◽  
K. Leger ◽  
H. Heich ◽  
N. Hodges ◽  
F. Nussio
Keyword(s):  
Air Quality ◽  
Quality Indices
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