Assessment of the Air Pollution Level in the City of Rome (Italy)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Characteristics of the Study Area
2.2. Pollutant Legislation
2.3. Post Processing Techniques
- Probability distribution describes the possible values that a random variable can take within a given range.
- Kurtosis is a measure of whether the data have a flattening or elongation from the normal distribution. High kurtosis indicates a flattering distribution, while low values indicate an elongation distribution.
- Skewness is a measure of the asymmetry of the distribution. A data set is symmetric if it looks the same to the left and right of the center point.
- Poincaré sections are a way to represent a dynamical system. The surface of section presents a trajectory in n-dimensional phase space in an (n-1)-dimensional space. By picking one phase element constant and plotting the values of the other elements each time the selected element has the desired value, an intersection surface is obtained. The phase space is a surface that describes all the possible states of a system.
- Cross-correlation is a measure of similarity of two data series as a function of the lag of one relative to the other.
- Coefficient of variation normalizes the standard deviation with the mean of a data. This index gives information about the variability of a data set.
- Generalized Extreme Value distribution is often applied to analyse a large set of data characterized by small or large value. In this approach three simpler distributions into a single form are combined, allowing a continuous range of possible shapes.
2.4. Monitoring Station Network
3. Results and Discussion
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Pollutant | Concentration | Averaging Period | Permitted Excess Each Year |
---|---|---|---|
PM10 | 50 µg/m3 | 24 h | 35 |
PM10 | 40 µg/m3 | 1 year | - |
PM2.5 | 25 µg/m3 | 1 year | - |
NO2 | 200 µg/m3 | 1 h | 18 |
NO2 | 40 µg/m3 | 1 year | - |
SO2 | 350 µg/m3 | 1 h | 24 |
SO2 | 125 µg/m3 | 24 h | 3 |
O3 | 120 µg/m3 | Maximum daily 8 h mean | 25 days averaged over 3 years |
CO | 10 mg/m3 | Maximum daily 8 h mean | - |
C6H6 | 5 µg/m3 | 1 year | - |
Pollutant | PMs | NOx | SO2 | O3 | CO | C6H6 |
---|---|---|---|---|---|---|
Sensors | MP101MC | M200 A-API | TE 43i | M400E API | TE 48i | AIR Toxic |
SWAMDC FAI | ||||||
SWAM5a FAI | ||||||
M100E API | M300E API | CP 7001 | ||||
SWAM DC FAI | ||||||
TE SHARP 5030 |
Specie | Kurtosis | Skewness | Coefficient of Variation |
---|---|---|---|
[CO] | 14.3 | 2.7 | 66% |
[NO] | 17.1 | 3.3 | 155% |
[SO2] | 9.6 | 2.2 | 91% |
[C6H6] | 9.4 | 2.1 | 72% |
[NO2] | 3.9 | 0.7 | 48% |
[PM2.5] | 4.2 | 1.3 | 60% |
[PM10] | 3.7 | 1.0 | 46% |
[O3] | 2.8 | 0.7 | 80% |
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Battista, G.; Pagliaroli, T.; Mauri, L.; Basilicata, C.; De Lieto Vollaro, R. Assessment of the Air Pollution Level in the City of Rome (Italy). Sustainability 2016, 8, 838. https://doi.org/10.3390/su8090838
Battista G, Pagliaroli T, Mauri L, Basilicata C, De Lieto Vollaro R. Assessment of the Air Pollution Level in the City of Rome (Italy). Sustainability. 2016; 8(9):838. https://doi.org/10.3390/su8090838
Chicago/Turabian StyleBattista, Gabriele, Tiziano Pagliaroli, Luca Mauri, Carmine Basilicata, and Roberto De Lieto Vollaro. 2016. "Assessment of the Air Pollution Level in the City of Rome (Italy)" Sustainability 8, no. 9: 838. https://doi.org/10.3390/su8090838