|Core||Joey Lee, Dr. Andreas Christen, Zoran Nesic (Research Engineer), Rick Ketler (Senior Technician)|
|Advisory Committee||Prof. Ron Kellett, Dr. Les Lavkulich|
|Funding & Support||NSERC CREATE TerreWEB Program, UBC Geography, Mozilla Science Lab, Moovel Lab|
|Paper||Atmospheric Measurement Techniques|
In the fall of September 2013, I started my master’s at the Department of Geography at the University of British Columbia (UBC) in Vancouver, BC. Under the supervision of Dr. Andreas Christen, Prof. Ron Kellett and Zoran Nesic, I developed a mobile sensor system to map CO2 emissions in cities.
Currently (Oct. 2016) there are no methods to measure and map CO2 emissions at the micro scale (0 - 100m) across entire urban areas. There are plenty of models that use data on building energy use, traffic counts, etc to estimate emissions from the building to the city scale, but they rely heavily on input data that isn’t readily available to researchers and governments and cannot be validated with physical measurements across an entire urban area. Stationary sensor systems can measure emissions however they can only measure the emissions within their “source area” and are extremely cost and labor intensive. While satellite-based emissions sensors are now orbiting the earth providing emissions data at around 2 km2 resolution, these systems have low temporal resolution and also need to be validated.
My master’s thesis, ‘A Mobile Sensor Network to Map CO2Emissions in Urban Environments’ is about exploring the potential of urban mobility as a platform for mapping CO2 at the street-scale in cities. Inspired by the changing landscape of opensource micro-technologies (e.g. Arduino) and the increasing number of pervasive and connected environmental sensors, I asked the question, “is it possible to map CO2 emissions with a fleet of mobile sensors in an urban environment?” and “what could the future of emissions monitoring look like if the correct methodologies and technologies are in place?”.
To answer this question, I developed a “compact” CO2 sensor that can be deployed on bikes and cars, developed tests to evaluate the sensor performance (e.g. accuracy, precision, etc), and applied an “aerodynamic resistance approach” to deriving CO2 emissions from measures of CO2 concentrations.
Our research showed that, under a given set of environmental conditions, our mapping approach generated results that were positively correlated by at least 78.4% when compared to an independently generated emissions inventory (for combined buildings and traffic); 99.43% of our measured emissions were within ± 1 order of magnitude of the emissions inventory. Ultimately, the research demonstrated the possibility of using a network of mobile sensors and an aerodynamic resistance approach to map emissions at high spatial resolution across a city. While further research is necessary, microscale emissions maps may be used to better inform urban policy and design as well as engage citizens about emissions reductions strategies.
- Our work was published in the open access journal Atmospheric Measurement Techniques.
- If you’re interested in knowing more about the technical implementation and looking into some of the software and hardware, you can also check out the DIYSCO2 project page.
- I also made a little visualization to explore the emissions here.
I learned a lot from this experience - dabbling with arduino and hardware engineering, working deeper with geoprocessing and analysis, building emissions models, writing my first, first-author scientific paper, presenting at conferences, doing open science, and much more. That being said, there’s still a lot I hope to see develop from this project from the product design, analysis tools, deployment routing and experimental setup, and more. In any case, it is my hope this work helps to establish a strong methodological framework for future work and look forward to seeing new projects or remixes come from this work.