Description

Scale as linked to D2.2 framework

• Street
• Household
• Object

Data source [ link to data framework]

• PM monitoring device

Data needs

• Concentrations of NO2 and airborne particulate matter are measured by recording PM mass per cubic metre of air (PM2.5 and PM10).
• PM - Micrograms (mcg) per cubic metre, µg/m3. (Microgram (µg) One-millionth of a gram; a milligram (mg) = 1000 micrograms).
• NO2 – ppb (parts per billion). Parts per billion (ppb) is the number of units of mass of a contaminant per 1000 million units of total mass.

Expected Outputs

• Continuous monitoring in the selected points hourly

Calculation methods

Data processing

• Calculation of (weekly, monthly and/or Annually) mean levels of NO2, PM10 and PM2.5 at each sampling location as the average value of the all the measurements done before and after of the interventions. Comparison of mean values for NBS intervention and control sample locations in the implementation area.
• Data comparison before and after of the intervention using the reference to assess possible meteorological or other factors influence
• Calculations must be done using comparable periods of time before and after the interventions (i.e., if measurement period before of the intervention goes from nov18-oct19, measurement period must be at minimum from nov19- oct21 and processing can be done for either years or Annually).
• For this KPI, continuous records of air quality are available and, therefore, a different processing of the information will be applied to evaluate the impact of the NBS

Results

• The calculated values will be compared qualitatively and quantitatively for the periods before and after the interventions in the NBS and reference sections.
• 
•  Positive or null NO2, PM10 and PM2.5 impact values indicates negative or no impact of the NBS on PM concentration for that implementation. Negative values indicates a positive impact of that NBS on NO2, PM10 and PM2.5 concentration.
• The additional methodology (using continuous data) aims to find significant differences by comparing the normalized distributions of the difference between the sections with NBS and the reference sections.
• First, the normalized distribution of the difference of the hourly values of the NBS location and the reference location is calculated. Then, the distributions of data before and after of the interventions are compared. If significant differences are found between the distributions before and after the implementation, then the impact of the NBS can be assessed.
• If the centers of the histograms of both distributions (before and after the implementation) are separated by more than the sum of the standard deviations, σ (i.e., 2σ), then they will be considered as significantly different (with a 95% probability). If the center of the histogram of the situation after the implementation is lower than that of the previous situation (and the differences are significant) then it will be concluded that the impact of the NBS is appreciable. As an equation, this statement could be presented as follows:
• 

Links and references

• URBAN GreenUP Deliverable D2.4 - Monitoring program to Valladolid. https://www.urbangreenup.eu/insights/deliverables/d2-4--- monitoring-program-to-valladolid.kl
• URBAN GreenUP Deliverable D3.4 - Monitoring program to Liverpool https://www.urbangreenup.eu/insights/deliverables/d3-4--- monitoring-program-to-liverpool.kl
• URBAN GreenUP Deliverable D4.4 – Monitoring program to Izmir https://www.urbangreenup.eu/insights/deliverables/d4-4-- monitoring-program-to-izmir.kl
• URBAN GreenUP Deliverable D5.3: City Diagnosis and Monitoring Procedures https://www.urbangreenup.eu/insights/deliverables/d5-3- city-diagnosis-and-monitoring-procedures.kl
• Air Pollution in the UK 2015. https://uk air.defra.gov.uk/library/annualreport/index
• Bottalico, F., Chirici, G., Giannetti, F., De Marco, A., Nocentini, S., Paoletti, E., Salbitano, F., Sanesi, G., Serenelli, C., Travaglini, D., 2016. Air pollution removal by green infrastructures and urban forests in the city of Florence. Agric. Agric. Sci. Procedia 8, 243–251. doi:10.1016/j.aaspro.2016.02.099.
• Mullaney, J., Lucke, T., Trueman, S.J., 2015. A review of benefits and challenges in growing street trees in paved urban environments. Landscape Urban Plan. 134, 157–166. doi:10.1016/j.landurbplan.2014.10.013.
• Baró, F., Haase, D., Gómez-Baggethun, E., Frantzeskaki, N., 2015. Mismatches between ecosystem services supply and demand in urban areas: A quantitative assessment in five European cities. Ecol. Indic. 55, 146–158. doi:10.1016/j.ecolind.2015.03.013.
• SDG indicator 3.9.1 https://unstats.un.org/sdgs/metadata/files/Metadata-03-09- 01.pdf
• SDG indicator 11.6.2. https://unstats.un.org/sdgs/metadata/files/Metadata-11-06- 02.pdf