Categories
Community Science

Edmonton’s Air Quality in the Time of Covid Part II: April Data

As discussed in a previous blog post, we saw in many other jurisdictions, such as the US Eastern Seaboard, China and Korea, a reduction in NO2 emissions brought on by physical distancing and movement restriction policies resulting from COVID-19. Edmonton is no different.

Anecdotally, during the height of the lock-down, I felt that the roads were less busy, and that it was easier (the odd time I actually left the house) to move through the city. I also saw distinct times when the Whitemud had no traffic, and the sound from the freeway was greatly reduced.  Well, we have some data to back up that anecdotal evidence, supporting the notion that Edmonton’s air quality may have improved during the COVID-19 lock-down, perhaps as a result of less traffic.

As noted at the conclusion of “Edmonton’s Air Quality in the Time of Covid”,  the ambient concentrations of NO2  in March 2020 were almost 30% lower than the average of NO2 for  March from 2015 to 2019. That is a significant decrease, but is it an anomaly?

Figure 1 (below) documents the data trends for the Edmonton Central Monitoring Station located downtown at the SE corner of 104 Street and 103 Avenue. These data were worked up by the Alberta Capital Airshed’s data scientist, Dr. Kevin McCullum.

The lower image shows the data trends for the month of April from 2000 to 2020. While the April 2020 data is not as drastically reduced compared to the Aprils from 2019 or prior (I’m curious to know what happened in 2010), it is reduced.

In conclusion, the March 2020 data was about 30% lower than the average March data for previous years, and the April 2020 data was also reduced, but not as much and not as clearly linked to a lock-down resulting from the COVID-19 pandemic. It is still unclear whether that was as a result of COVID-19 or, as demonstrated in the header image for annual data from 2000 – 2020, a more general seasonal trend that occurs NOx and NO2.

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Categories
Community Science Events

July 11 Walking Tour: Citizen Science: Community, Change and the Environment

Categories
Community Science Events

Queen Alexandra Citizen Science Pilot Project

Poor air quality threatens the health of all living things from humans to plants. There are many types of air pollution, and each have a different effect on human health (source)
Here’s the thing. You can make a difference, and together we can make a difference, transforming Edmonton’s air quality for the better.
Are you interested in how air quality measures stack up against traffic counts within the Edmonton neighbourhood context? If so, you could become a CITIZEN SCIENTIST!
Join us for a meeting about this pilot project within the Queen Alexandra community.
Thursday, June 11, 2020 from 6:30-7:30 PM 
At this meeting, we will discuss:

  • what the air quality/traffic monitoring project in Queen Alexandra is all about
  • how regular citizens can become citizen scientists & carry experiments
  • other roles and volunteer opportunities beyond the “citizen scientist”

Additional questions? Email our Executive Director, Julie Kusiek, at [email protected].


RSVP below by June 10 to receive the meeting link.

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Categories
Community Science

Edmonton’s Air Quality in the Time of Covid

I live adjacent to the Whitemud, and late one evening I woke-up to an odd absence of sound. My bedroom window was open to let in some night air, and gazing out onto the Whitemud, I saw that there were no cars on the highway. Having lived in this house, with this view of the Whitemud, for 10 years this was the first time that I saw an empty highway. COVID-19 was in full effect, and people were clearly staying at home.

We’ve all seen the images of the dramatic reductions in air pollution brought on by social distancing and movement restriction policies resulting from COVID-19 in other parts of the world. Here is a great NASA data visualization for the Eastern Seaboard. Here is another of China and Korea. The Eastern Seaboard map compares the monthly average of March from 2015-2019 with March 2020, and demonstrated a 30% drop in atmospheric NO2 . The China and Korea map compared January 1-20, 2020 with February 10-25 2020, and also showed a significant drop in NO2 . The article does not specify how big the drop is.

A couple of notes on these maps:

(a) According to the USEPA, NO2

“… primarily gets in the air from the burning of fuel. NO2 forms from emissions from cars, trucks and buses, power plants, and off-road equipment.”

(b) The NO2  shown on these maps was measured using a satellite-based remote sensing tool that detects atmospheric NO2 . This is different from the collection method used for the Edmonton data (see below), which was measured using a ground-based regulatory ambient air quality continuous monitor. The specific readings are not comparable between the satellite data and the air quality monitor.

(c) As Figure 1 indicates, NO2  cycles annually. This is important because there may have been a drop in NO2  in the S.E. Asian example from January to February due to this cycle. The data does not distinguish between what portion of the drop is due to annual cycles, and what is due to factors related to COVID-19.

(d) Both the American Eastern Seaboard and S.E. Asian maps represent areas that are much more densely populated than Northern Alberta, with many more emissions sources. As such, the relative change in NO2  levels will be much greater in both these examples, as compared to Edmonton.

Now, on to Edmonton!

I’m not the only one to experience a ‘traffic moment’ in Edmonton. Many of my friends have commented on how easy it is to drive places given the lack of traffic. There has been no discernible rush hour. Bike shops are open and considered essential. So essential, in fact, that I had a hard time finding a new bike for my daughter – I was told that bikes were being sold before they even made it to the store. And, finally, the air does seem fresher, cleaner. Maybe it’s my imagination…

These Edmonton data come from the Edmonton Central Ambient Air Quality (AAQ) Monitoring Station located at 104 Street and 103 Avenue in downtown Edmonton (it’s on top of the building on the southeast corner).  Summary graphs for these data can be found in Figure 1 and Figure 2.

Figure 1 shows that, for central Edmonton, NO2 readings have been going down over time since 2000, but that there are large (mostly predictable) daily and weekly swings in the data all within an annual cycle. As noted above, the NO2  these data represent comes from the burning of fossil fuels, and much of the NO2 from Edmonton Central comes from vehicle emissions. Since 2000, the ambient concentrations of NO2 have declined, mainly as a result of more stringent vehicle fuel efficiency standards.

Figure 2 (top image) highlights weekly trends where Saturday and Sunday have lower readings compared to weekdays; (bottom left image) weekdays have a ‘rush hour spike’ of emissions in the morning, and then a second, gentler upward trend for a more prolonged evening rush hour; (bottom middle image) readings are higher in the winter, likely due to more people driving, and climate conditions such as temperature inversions which hamper the dispersion of pollution.

In reference to Figure 3: Average March Readings from 2000 to 2020 (an explanation on how to read a box chart can be found at footnote 1 below). These data compare the average concentration of NO2  for the month of March from March 2000 to March 2020. The ambient concentrations of NO2  in March 2020 were almost 30% lower than the average of NO2 for  March from 2015 to 2019 (footnote 2). That is a significant decrease.

What accounts for the improvement in air quality at this station? What portion is due to COVID-19? Is this 30% in NO2  an anomaly?

I’m not sure, but I am anxious to look at April’s data.

Acknowledgements

I’d like to acknowledge the Alberta Capital Airshed for sharing their data and creating all of the charts in this blog. Any mistakes are mine and mine alone.

Footnotes:

  1. Box charts can be tricky to read.  A box chart is a cool way to show a summary of the data while also showing the calculated value. For instance, March 2020 shows a rectangle with a line through it. The line indicates the calculated average, while the rectangle shows where the middle 50% of the readings fall (half above the line, half below). The line below the box (a lower whisker) shows the smallest 25% of readings, and the line above the box (an upper whisker) shows the highest 25% of readings. The dots are outliers, meaning that they differ significantly (for a variety of reasons) from the other cluster of readings.
  2. In reference to Figure 3 which shows average NO2 Average Monthly March Readings from 2000 to 2020, March 2014 (18.8 ppb) and 2016 (17.3 ppb) both saw a lower average NO2 than  2015 or 2017-19, but higher than 2020 (15.2 ppb).
Categories
Community Science

What is Citizen Science?

Let’s start with a definition for Citizen Science. I like definitions as they provide a common understanding of what a word or concept means. Citizen Science (CS) is a collaborative scientific investigation and exploration that strives to address community defined questions where a community is engaged in the entirety of the scientific process (1). This notion of CS does not sit in isolation, but rather fits into a spectrum of activities that engage citizens in some form of data creation. 

That spectrum is broad (Figure 1) and ranges from the simple ‘citizens as sensors’ where, for example, citizens passively provide location data through an app (2). The traffic app Waze is a good example. Waze gathers location and speed data from a users phone, aggregates those individual data with all other user generated data, creating information in the form of best routes and fastest times to a destination. The citizen in this example is not actively participating, but rather passively letting Waze access data on their phone to use in combination with other people’s data. There are a number of problems with this model that include privacy concerns and the financial motivation of those who make the app (3). How do they make their money? Do they sell the data that they collect from users? 

If the broad domain of CS exists within a continuum, Collaborative Science sits at the other end of the spectrum. Collaborative Science describes community members who are engaged from the conception of the project through to its conclusion, and act as equal partners with scientists.

Figure 1: Levels of Participation in Citizen Science(2)

A great example of Collaborative Citizen Science can be found with the Mapping for Change – Science in the City Project (4). Science in the City was a collaboration between communities in London, England, and a local city council. The goal of the project was to collect air quality data in a scientifically rigorous manner and then use that data to advocate for policy changes at the municipal level. Here is a great YouTube overview of the project.

For example, the goal of the Science of the City project was:

Science in the City was initiated with the aim to increase public understanding about air pollution, its causes, and effects, amongst local residents, and how concentrations of different pollutants vary over space and time.(5)

The main ingredients of the project were (a) the inclusion of a defined community to guide the questions being asked, and help define the range of policy outcomes desired, (b) scientists who knew the science of collecting air quality (and other) data and who could train community members, and (c) appropriate air quality sensing technology. And, as evident in the quote above, the motivation of this model is “.. to increase public understanding…”. There are no financial or privacy considerations.

The results from this Citizen Science study were impressive. In brief, the Barbican study indicated that:

  1. There is a great deal of spatial and temporal variation in air quality (PM2.5 and NOx)  within the study area (Note: this is of interest because it is a small area with a significant amount of spatial variation in air quality);
  2. That ambient air quality levels of NOx were intermittently above the European Union’s guidelines;
  3. Citizens were able to track the impact of a Sahara dust storm on AQ in London! (Note: this may be analogous to a BC forest fire impact in Alberta), and;
  4. Traffic did not have as big an impact on AQ as citizens thought it would.

The final paragraph of the report offers some great insight into the power of ‘Extreme’ Citizen Science:

The project’s success was made possible by combining residents’ local knowledge and their commitment, with the technical knowledge and experience provided by Mapping for Change… Local insights gave context to the monitoring programme making the data collected more relevant to those involved, adding scientific evidence to the residents’ opinions giving strength to the voice of the community. The results of this project offer a valuable resource which can be used as a foundation to effect change and tackle the problem of poor air quality in the City of London. (6)

The outcome of the Science in the City Project highlights that we are smarter and more capable together, as a group of people with a range of knowledge and experience, than each on our own as  individuals.

References:

  1. This definition is adopted from: Dosemagen, S. and Parker, A. (2019). Citizen Science Across a Spectrum: Broadening the Impact of Citizen Science and Community Science. Science & Technology Studies. Special Issue: Many Modes of Citizen Science. Volume 32, Issue 2.  
  2. From: Haklay, M.( 2013). Citizen Science and volunteered geographic information: Overview and typology of participation, Crowdsourcing Geographic Knowledge in Sui, D.Z., Elwood, S. and M.F. Goodchild (eds.), 2013. Crowdsourcing Geographic Knowledge:Volunteered Geographic Information (VGI) in Theory and Practice. Berlin: Springer.pp 105-122 
  3. Haklay, M.( 2013). Citizen Science and volunteered geographic information: Overview and typology of participation, Crowdsourcing Geographic Knowledge in Sui, D.Z., Elwood, S. and M.F. Goodchild (eds.), 2013. Crowdsourcing Geographic Knowledge:Volunteered Geographic Information (VGI) in Theory and Practice. Berlin: Springer.pp 105-122 
  4. The Science in the City: The Barbican Final Report can be found here: https://mappingforchange.org.uk/wp-content/uploads/2015/08/Barbican-Final-Report-draft_12012015_edited.pdf
  5. From pp. 6 of Science in the City: The Barbican Final Report.
  6. From pp. 34 of Science in the City: The Barbican Final Report.