The indicator’s value can be determined either by:
- Using existing data regularly collected by the public authorities (or any other competent actor). This approach is likely to be less expensive and time-consuming; however, it is possible to use existing data only if they cover the area where your project aims to decrease ambient air pollution (which often is not the case).
- Conducting your own measurements is likely to require more money, expertise and time; however, it allows you to collect data in the areas where your project is working on decreasing air pollution. If your team has limited experience with monitoring air quality, contract a relevant specialist / company, to support you with the data collection and analysis process (alternatively, you can sub-contract the entire measurement process).
If you decide to gain (a part or all of) the required data by conducting your own measurement, use the following steps:
1) Specify the pollutant, including its thresholds
Define the exact pollutant that you intend to measure and the relevant threshold. The thresholds for the main air pollutants are usually set by the national authorities; alternatively, you can use WHO recommendations (see below).
2) Decide on the monitoring technology
The choice of sensors depends on which pollutant you want to measure and which sensor you are able to use (considering their availability, price, ease-of-use). See an overview of sensors in this article though also check more recent products, as the market for low-cost air quality monitors is evolving rapidly. If your team has limited experience with using sensors, contract a relevant specialist, such as an expert from a company / state authority or a freelance consultant, to support you with the data collection and analysis process.
3) Define the installation and data collection process
In collaboration with a specialist (if required), define the installation and data collection process, including:
- How many sensors will you use: The more sensors you use, the more locations you can monitor but it will also cost you more money.
- Where the sensors will be placed: Even monitors located some 5 – 10 metres apart can provide very different data as pollution levels vary depending on the location. In the urban contexts, the most common monitoring places are junctions, along the roads (within 1 metre and 1 – 5 metres), near other major sources of pollution (which are close to people’s homes) and in background sites that are not dominated by one single nearby pollution source (see more details in the guide below). In the rural areas, you can collect data along the main roads and near people’s houses (at least 15 metres from any source of pollution).
- When the data will be collected: Pollution levels vary by season – data from a baseline study from a cold and rainy period will not be comparable with data from an endline study conducted during the peak of a hot and dry season. Similarly, pollution levels might differ by day – for example, traffic pollution levels on Monday might be different from traffic pollution levels on Tuesday. Similarly, traffic pollution levels will be different during peak and off-peak hours.
- How long the sensors will be deployed, such as 24 or 48 hours.
- Which quality assurance measures will be followed and by whom: There are many factors that can negatively influence the reliability of your air quality data, such as choice of sensors (precision, reliability, weather resistance, etc.), their location, installation, the timing of data collection, etc. Consult with relevant specialists about these and ensure that appropriate quality assurance measures are followed.
4) Collect the required data using the monitoring process defined under point 3.
5) To calculate the indicator’s value:
- list the areas with ambient air pollution exceeding relevant thresholds
- use existing data (e.g. from local authorities) to determine the number of people living in areas where ambient air pollution exceeded relevant thresholds
- (if you need to report in percentages) divide the result by the total number of people living in all the monitored areas. Multiply the result by 100 to convert it to a percentage.