"Health care is vital to all of us some of the time, but public health is vital to all of us all of the time."
- Everett Koops (1916-2013)
Predicting intraurban airborne PM1.0-trace elements in a port city: Land use regression by ordinary least squares and a machine learning algorithm
Airborne particulate matter (PM) has been associated with cardiovascular and respiratory morbidity and mortality, and there is some evidence that spatially varying metals found in PM may contribute to adverse health effects. We developed spatially refined models for PM trace elements using ordinary least squares land use regression (OLS-LUR) and machine leaning random forest land-use regression (RF-LUR). Two-week integrated measurements of PM1.0 (median aerodiameter < 1.0 μm) were collected at 50 sampling sites during fall (2010), winter (2011), and summer (2011) in the Halifax Regional Municipality, Nova Scotia, Canada. PM1.0 filters were analyzed for metals and trace elements using inductively coupled plasma-mass spectrometry. OLS- and RF-LUR models were developed for approximately 30 PM1.0 trace elements in each season. RF generated more accurate models than OLS for most trace elements based on 5-fold cross validation. Taking overpredictions and cross validation performances into account, OLS-LUR performed better than RF-LUR in roughly 20% of the seasonal trace element models. RF-LUR models provided more interpretable predictors in most cases. Seasonal predictors varied, likely due to differences in seasonal distribution of trace elements related to source activity, and meteorology.
I'm Daniel Rainham, an associate professor at Dalhousie University. I work with a fantastic team of trainees and colleagues to explore the relationships between the quality of the environment and human health. The quality of the environment can be beneficial, like when we take time to immerse ourselves in nature; or, it can be detrimental such as when we are exposed to harmful contaminants.
My research is focused on measuring the characteristics of the environment, investigating how these characteristics affect our health, and experimenting with solutions and interventions toward a sustainable, healthy lifespan. If this type of work sounds interesting or even fascinating to you then please get in touch.
I'm always looking for enthusiastic and motivated individuals to join or support the team. Opportunities.