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Month: February 2019

Making Sense of the Data: Air Quality Index (AQI)

by C.J. Hatziadoniu

In a previous post, we discussed particulate mater, especially PM10 and 2.5 and how one can interpret the data. In this post, we will discuss the air quality index (AQI) and how it can be computed from measured concentrations of pollutants.

Air quality assessment takes into account the concentrations of several different pollutants such as PM, CO, CO2, O3, and NO2. The effect on the human health of each of the pollutants varies with the concentration level. AQI was devised to provide a single measure that can be compared across all relevant air pollutants. Furthermore, AQI provides descriptive quality classes (categories) indicating danger on human health.

Wikipedia offers a good source for first hand information about AQI [1]. The higher the value of AQI the worse the air quality. When the effect of more than one pollutants is measured, a separate AQI is computed for each pollutant and the highest value among all indices is taken as an overall measurement (e.g. a compounded index).

As an example, below we look at two different standards using AQI: The EPA and the EU standard and we compare them versus the same measured data for PM2.5 and 10 concentrations.

The EPA Index

The EPA (Environmental Protection Agency) is a government agency in the US providing standards and regulations affecting the environment. The AQI developed by the EPA is graded from 0 to 500 with increasing concentrations of pollutants. Six quality categories are specified with a descriptive name and a color code from “Good” (in green) corresponding to the lowest values of AQI to “Hazardous” (in purple) for AQI exceeding 300. The standard also specifies the averaging period of the measurement. Table 1 shows the AQI definition for PM2.5, PM10 and CO [1].

Table 1. AQI developed by EPA for PM2.5, PM10 and CO pollutants [1]

Each line in the table gives the lower and upper concentration limits of the pollutant in the category and the corresponding lower and upper values of the AQI. A linear interpolation is used to obtain the AQI for concentrations in between these limits.It should be noted that pollutant concentrations are reported as averages over specified time intervals. For example, PM2.5 and 10 concentrations are reported as 24-hour averages, while CO concentrations are reported as 8-hour averages. EPA has developed a different AQI range for different averaging periods: the longer the averaging period the greater the AQI for the same nominal concentration of the pollutant. Therefore, if one applies the AQI specified for 24-hour averages to measurements taken on 1-hour averages, the value of the computed index will be higher then the actual value–a pessimistic result.

Example. Consider the following daily average emissions of PM2.5 and 10 pollutants in Fig. 1 collected from the air-monitor tagged 8200015E from October 6 to December 31, 2018. The AQI is computed for each day according to Table 1 (24-hour averages). The results are shown in Fig. 2.

Fig. 1: Daily averages of PM10 and PM2.5.
Fig. 2: AQI indices derived from Fig. 1 and Table 1.

The figure includes in the same color code the quality categories in Table 1. Three bars are given for each day: the AQIs computed from the PM2.5 and 10 averages and the compounded AQI (i.e. the greater of the two for each day). In all cases, the PM2.5 concentrations determine the compounded index.

The figure shows that for most of the time of the data, pollution levels were not worse than moderate and that the great majority of the days fall under the category “good”. Also in the same figure, we see that there are couple of days (Oct. 22-23), where the AQI index came very close to 100, which is the lower bound of the category “unhealthy for sensitive groups”.

EU Index

EU defines the common air quality index (CAQI). The index resembles the one from EPA. The index is graded from 0 to 100. There are five categories with descriptive names from “Very Low” to “Very High”. As in the EPA standard, different indices are used for different averaging periods. Also CAQI specifies different values for measurements near traffic and in the city. Table 2 [2] gives the CAQI and corresponding categories for 24-hour average PM2.5 and 10 concentrations in a city. Note that the standard specifies PM2.5 as optional when a compounded index is computed.

Table 2. CAQI for 24-hour average PM2.5 and 10 concentrations in a city [2]

Example. The data in Fig. 1 are used here to derive the CAQI values for each day. The results are plotted in Fig. 3 along with a colored region giving the quality of CAQI. As in Fig. 2, three bars are given for each day with the CAQI from PM2.5 and 10 and the compounded CAQI. In all days, the CAQI from the PM2.5 concentrations determines the compounded CAQI.

Fig. 3: CAQI derived from the data of Fig. 1.

With reference to Fig. 3, most of the days the pollution levels are low or very low. There are a few days with medium levels and two days where the levels were high; the latter are the Oct. 22 and 23, the same days when the EPA index was very close to the “high” category. Fig. 2 and 3 give consistent qualitative assessment of the air quality, with the difference occurring only in the boundary between categories.

As concluding remarks, we can say the CAQI provides a standard and a better way of reporting measurements of air pollutants; one that directly assesses effects on human health. Furthermore, CAQI (or AQI) can be computed simply in a spreadsheet like Excel, by importing data and performing simple numerical calculations.

References

[1] “Air Quality Index”, Wikipedia, https://en.wikipedia.org/wiki/Air_quality_index

[2]  CiteairII — Common Information to European Air (2012-07-09). “CAQI Air quality index — Comparing Urban Air Quality across Borders – 2012” (PDF). Archived (PDF)from the original on 2018-02-18. Retrieved 2018-02-18.

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