Using low cost particle sensors for characterization of urban air pollution: insights from Birmingham and Nairobi

Dr Francis Pope

School of Geography, Earth and Environmental Sciences

University of Birmingham

f.pope@bham.ac.uk

Acknowledgements

Collaborators:

University of Birmingham – Leigh Crilley and Louisa Kramer

University of York – Marvyn Shaw and Ally Lewis

University of Nairobi – Michael Gatari and David N’gang’a

Funding:

EPSRC

DFID (East Africa Research Fund)

Royal Society and Royal Society of Chemistry

Particulate Matter Air Pollution

Image: https://www.epa.gov/pm-pollution/particulate-matter-pm-basics

Annual mean / g m-3

24-hour mean / g m-3

PM2.5 10 25

PM10 20 50

WHO Recommendations

Particulate matter and human health

• Exposure to air pollutants causes a range of adverse effects upon human health

• It was estimated that the exposure of PM2.5 alone was responsible for almost half a million premature deaths in Europe in 2005.

• Mechanisms of toxic action include the following:

• (a) Effects on the respiratory system.

• (b) Effects via the cardiovascular system. (c) Carcinogenesis. A number of common air pollutants are known to be carcinogenic

• Epidemiological studies linking air pollution exposure with mortality and disease indicate that air pollution exposure has both short- and long-term effects.

Harrison R.M., F.D. Pope and Z. Shi (2013) ‘Pollution, Air’ Chapter within ‘Encyclopaedia of Physical Science and Technology (Third Edition)’ Ed. S. Elias, Elsevier. http://dx.doi.org/10.1016/B978-0-12-409548-9.09097-7

Nelson’s column in the great London smog of 1952, in which ca. 4000 people died and 100000 were made ill. Image: N T Stobbs (Wikipedia)

What can you do with low cost sensors that you cannot do with more expensive kit?

1. Monitoring networks allow for finer scale measurement and understanding of air pollution sources 2. Hard to access or extreme locations e.g. volcanoes 3. Low and middle income countries which previously could not afford air quality monitoring

https://www.aeroqual.com/sensor-network-combats-pollution-vancouver

Measurement of Holuhraun plume. Credit: Evgenia Ilyinskaya, University of Leeds

Evaluation of low cost sensors (Alphasense OPC-N2) in Birmingham

Rank order plot of OPC observations in terms of

concentration measured

The precision of the low cost sensors was assessed by co-locating 14 instruments at 2 sites in Birmingham: - Urban background site at the University of

Birmingham - Urban background AURN site at Tyburn Road in

Birmingham Comparison to two different reference optical particle counters as well as a TEOM-FDMS enabled the accuracy of the OPC-N2 to be evaluated. Crilley et al. (2017): Evaluation of a low-cost optical particle counter (Alphasense OPC-N2) for ambient air monitoring, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-308

Low cost sensors: Quality Assurance

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TEOM OPC6 OPC8 OPC10 OPC11 GRIMM

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OPC6 corr OPC8 corr OPC10 corr OPC11 corr

Need to calibrate instruments under conditions relevant to measurement conditions. i.e. no good just to measure in an air conditioned lab with constant temperature and relative humidity.

Clear RH dependence

Summary of Birmingham tests

• Comparison of the OPC-N2 to the reference optical instruments demonstrated reasonable agreement for the measured mass concentrations of PM1, PM2.5 and PM10.

• A significant positive artefact in measured particle mass during times of high ambient RH (> 85 %) and a calibration factor was developed based upon κ-Kohler theory, using average bulk particle aerosol hygroscopicity.

• Application of this RH correction factor resulted in the OPC-N2 measurements being within 33 % of the TEOM-FDMS, comparable to the agreement between a reference optical particle counter and the TEOM-FDMS (20 %).

• Reasonable inter-unit precision for the 14 OPC-N2 sensors was observed.

• Overall, the OPC-N2 was found to accurately measure ambient airborne particle mass concentration provided they are

i) correctly calibrated

ii) corrected for ambient RH

Using low cost sensors in Nairobi, Kenya Jan-Mar 2017

Air pollution in East Africa: Problem Analysis Urban air pollution is a pressing and multi-sectoral development challenge, representing a major health, economic and social threat to cities of the global south.

In Africa, air pollution was associated with an estimated 712,000 premature deaths and an economic cost of US$ 215 billion .

Country Outdoor air pollution

Household air pollution

Unsafe water Unsafe sanitation

Childhood underweight

Ethiopia 19993 57591 54473 42015 20040

Kenya 3952 15440 25066 18670 7012

Uganda 5933 16630 14861 11168 8786

Country specific premature deaths by selected risk factor in 2013

(Institute of Health Metrics and Evaluation, IHME, 2015)

http://www.healthdata.org/infographic/global-burden-air-pollution

Air Pollution in Nairobi

• From satellite observations, Kenya as a whole is relatively clean with respect to particulate matter pollution (similar to UK).

• However within Nairobi, air quality is poor.

• But few long term measurements.

van Donkelaar et al., Global Estimates of Fine Particulate Matter using a Combined

Geophysical-Statistical Method with Information from Satellites, Models, and Monitors, Environ. Sci. Technol, doi: 10.1021/acs.est.5b05833, 2016.

PM2.5 estimates in g/m3

Air Pollution in Nairobi: Using visibility as a proxy.

Visibility is inversely proportional to particulate matter concentration. The greater the amount of PM pollution, the more light is scattered by the particles, and the worse visibility gets. Visibility is the only long term record of air pollution in most African countries.

Singh, A., Bloss, W.J. and Pope, F.D., 2017. 60 years of UK visibility

measurements: impact of meteorology and atmospheric pollutants on

visibility. Atmospheric Chemistry and Physics, 17(3), pp.2085-2101.

Air Pollution in Nairobi: setting up low cost pollution sensors • Site 1. Urban roadside site

• Site 2. Urban background site

• Site 3. Rural background site upwind

Air Pollution in Nairobi: time series Hourly time series data

showing PM10 and PM2.5

mass concentrations.

Red line = urban roadside,

black line = urban

background and blue line =

rural background.

Mass calibration performed

with collocated gravimetric analysis.

In Nairobi dataset, no RH dependence observed, but conditions were dry with RH < 85%

WHO 24 hour recommendation

Air Pollution in Nairobi: ‘Lenschow’ approach

Lenschow et al. (2001) Atmospheric Environment http://www.sciencedirect.com/science/article/pii/S1352231001001224

Air Pollution in Nairobi: ‘Lenschow’ approach

Lenschow et al. (2001) Atmospheric Environment http://www.sciencedirect.com/science/article/pii/S1352231001001224

Air Pollution in Nairobi: time dependence

Air Pollution in Nairobi: Comparison with wind speed and direction

Summary • Particulate matter pollution is a serious environmental risk factor

which causes human mortality and morbidity.

• Many ways to measure particulate matter pollution.

• Low cost sensors are a topic of major growth (scientifically and in general)

• Low cost sensors are not perfect

• They need to be calibrated for local conditions

• They offer measurement possibilities where:

• Lots of sensors required

• Difficult or dangerous locations

• Low and middle income countries (LMICS)