My Research

I have been working with my current research group, headed by Dr. Michael Hannigan, for over five years now providing the opportunity for in-depth research into low-cost sensor validation and the wide variety of potential applications for these systems.

I am particularly interested in the following questions…

How can low-cost, next-generation monitoring technologies supplement our existing monitoring systems (FRMs) and provide data that can further the protection of public and environmental health?

How can multi-gas-phase sensor arrays be used to collect data on target pollutants, such as groups of or even specific hydrocarbons?

How can scientists support community-driven science? For example, how can scientists provide additional tools and education to facilitate the collection of high-quality data by citizen scientists using low-cost air quality monitors and other accessible methods?

Below are some of my current and former projects digging into these questions…

Monitoring in California Communities

With public health research partners from the University of Southern California, and partners in community based organizations, we working with communities to collect neighborhood-scale data that might shed light on how local sources are impacting residents, as well as, learning about how high spatial and temporal resolution sensor data might aid in untangling the complex  air quality trends in areas like LA. Additionally, given the community engagement, we are able to explore how leveraging different types of data (i.e., quantitative sensor data, and qualitative observational information) may be able to provide a more complete picture of air quality emissions and their effects.

MetaSense.png

The MetaSense Project

Through a collaboration with researchers at the University of California, San Diego, we are able to bring in new tools for sensor quantification, namely machine-learning.  Currently we have several sensor packages deployed to monitoring stations with varying environmental and background conditions. This data will allow us to explore calibration transferability and also help us to isolate the impact of specific variable on sensor signal. The  availability of a variety of reference signals will also allow for work leveraging multiple sensor signal to better understand and possibly identify local sources.

Education/Outreach & Community-Based Science

In 2013 we began working with a community in rural Colorado – the North Fork Valley.  The NFV is community primarily dependent on agriculture and also several area coal mines, they also face the possibility of increased energy development due to oil and gas extraction activities.  For this reason a local community group (the Western Slope Conservation Center) was interested in collecting data on current air quality conditions.

However, as we began planning we found that local high school teachers were very interested in getting their students involved. What we came to learn is that these rural schools are often under-served in terms of resources and their connections to institutions for higher education. And what grew out of this was an education and outreach program combining (1) a project-based learning curriculum, (2) university undergraduate mentors, and (3) low-cost air quality monitors in an effort  to support rural high school students in conducting their own air quality investigations.

The curriculum, available on the TeachEngineering Digital Library, introduces air quality concepts and monitoring, it then takes students through data collection and analysis, and finally study design.  At which point students conduct their own research project and we provide the support for them to collect, interpret, and present their data.  The curriculum is intended to be versatile for teachers and can be used with our lab’s air quality monitors, but could easily be adjusted if another design is available.

In addition to the curriculum we are currently developing, we have also conducted workshops with tribal students and environmental interns. Specifically we have worked with Dine Navajo College in the Four Corners region, and the Haskell Indian Nations University.

Screen-Shot-2014-10-24-at-12.35.24-PM

I have also been involved in community-based participatory research (CBPR) with a Denver organization, Taking Neighborhood Health to Heart and AGU’s Thriving Earth Exchange for several years. The project began with a community interested in learning more about their air quality concerns. In the spirit of CBPR, we collaboratively refined the research question, designed a study, and collected data. Since then we have continued to pursue additional iterations of the project, each year responding to what we are learning.There is more info on the Pilot Project here: https://experiment.com/iaq

 

FRAPPE/DISCOVER-AQ Campaigns

During the summer of 2014 our group participated in the FRAPPE and DISCOVER-AQ sampling campaigns, during which a multitude of methods (air craft, satellite, and ground-based) were used to investigate air quality on the front range in Colorado.   DISCOVER-AQ was a NASA initiated campaign, and FRAPPE was driven by NCAR (the National Center for Atmospheric Research).  Our group was responsible for deploying approximately 20 low-cost monitors, 13 of which were within a 10 x 10 km grid cell.  These measurements allowed us to examine spatial variability of pollutants, as well as, providing us with the opportunity to co-locate our instruments throughout the field deployment with a variety of reference instruments.

 

Learn more about the other work my lab is involved in here: http://hanniganlabs.wixsite.com/cuboulder

 

 

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s