1. Air Quality Assessment Using Affordable Monitoring Units – Nairobi Demonstration Project

2. UN Environment Assembly Adopts Resolution to strengthen UNEP’s Air Quality work
June Governments Adopt UNEA Resolution #7: Strengthening the role of the United Nations Environment Programme in promoting air quality

3. Air Quality Data currently available
GAPS!
Source: UNEP Live

4. Air Quality Monitors: High cost to Affordable
Mt. Kenya
St. Scholastica School
Reference Air Quality Monitoring
Station
-High accuracy
-High Costs ($150,000-$200,000)
-High installation costs
-High operation costs
Affordable Air Quality Monitor
-Sufficient accuracy
-Affordable (~few $100-$1000)
-Low installation costs
-Low operation costs

5. Assessment through enhanced and low-cost monitoring
UNEP National Air Quality Monitoring Programme
Many countries and cities in world regions have limited or no air pollution data
UNEP offers services to support deployment of low-cost monitoring networks and assessment of air quality
Requests received from Peru, Paraguay, Costa Rica, Ro Korea, Cote D’Ivoire, Indonesia, Mongolia, Moldova, Austria
UNEP has developed an affordable air quality monitoring unit
Using electro-chemical sensors for gases and Optical Particle Counter for particulate matter
Blue prints publically available
Calibration at US EPA ongoing

6. Nairobi Low-Cost AQ Network
, mostly schools in NASA Globe Program

7. Nairobi PM2.5 – scaled individually
Distinct local emission features evident across Nairobi

8. Policy Relevance
Continuous indicative monitoring helps inform policy formulations and implementation:
Illustrative measurements from data generated gives a snapshot of pollution events
Source attribution to determine pollution sources and hotspots
SDG Reporting
11.6.2: Annual mean levels of particulate matter (PM10 and PM2.5) in cities
3.9.1: Mortality rate attributed to household and ambient air pollution
Continuous data stream established with Kenyan authorities for use in policy and decision making

9. Policy Relevance – Illustrative measurements
Time series PM2.5

10. Policy Relevance – Source Apportionment
The Where? – Pollution sources
Site 1 – Kibera
Site 2 – Viwandani
Site 3 – Scholastica
Site 4 – UNEP HQ
Site 5 – All Saints
Site 6 – Alliance

11. Policy Relevance – Source Attribution
The What? - St. Scholastica PM2.5
Daily Patterns
Diurnal Pattern
Monthly Averages
Daily Means
Traffic related source…

12. Policy Relevance – Intervention Study
Nairobi Placemaking Week
Street closures around Jeevanjee Gardens – Nov 2016

13. Conclusion The successful deployment has shown that:
Low-cost monitoring units are able to generate data for processing, verification and visualization
Data collected is sufficiently accurate to determine the state of air quality, pollution hot spots and pollution sources
**Maintaining reliability of the data and increasing accuracy would require access to calibration of the network alongside reference instrumentation at one location
The network can be implemented and maintained locally
The units are deployable in cities with limited infrastructure and difficult operating conditions

14. Summary
Low cost sensors viable for ‘indicative’ (<25% error) monitoring, mapping and source apportionment of urban pollution. Network intelligence and availability of reference station can increase the accuracy to make the data viable for compliance (<15% error)
EU CEN/TC 264/WG 42 is working towards defining a framework for validation of low cost sensors. Few years away!!
We are still learning about deployment. Still some caveats (T/RH effects)
Proven success in use of low cost sensors elsewhere e.g OpenSense, SNAQ, CitiSense, Village Green, MIT Clairity
Low cost sensors (particulates including Black Carbon, gas phase including Volatile Organic Compounds) continue to advance