Research Team

Dr. Adams is accepting motivated MSc and PhD students with interests in urban pollution and exposure. Students have the opportunity to include field work, analytical labratory work, and computation in their research. 

Our focus is individuals’ exposure to air contaminants in the urban environment. Research outputs cross between the social and natural sciences, leveraging and advancing spatial analysis; while helping to understand social science problems, such as examining the relationship of human behaviour and the built environment on exposure. 

Current Research Themes

  • Children's Exposure
  • Pollution Related to Transit Development
  • Utility of Low-cost Sensors
  • Mobile Air Pollution Monitors

Graduate Program Information: http://geography.utoronto.ca/graduate-geography/


Current Group Members

Postdoctoral Research Fellow

Egide Kalisa

Postdoctoral Fellow

egide.kalisa@utoronto.ca

 
 

My current research addresses the Spatio-temporal characteristics of urban air pollution in African Cities and aims to identify measures to tackle air pollution while engaging with the locations and communities that are most vulnerable. My commitment to a scientific career has driven me to lead the nascent field of air quality research in sub-Saharan Africa, which has the potential to transform the lives of many millions of people. My research also investigates the exposure risk assessment of traffic-related air pollution in kindergarten playgrounds in Africa and Canada focussing on environmental distribution and composition of carcinogenic/mutagenic polycyclic aromatic hydrocarbons (PAHs) and their nitrated congeners (NPAHs).

Graduate Students (PhD)

Jenny Siliang Cui

PhD Student

jenny.cui@mail.utoronto.ca

 
 

My current research focuses on near-road air pollution in Ontario. One of the aspects of transportation related air pollution is its dispersion adjacent to freeways, since twenty eight percent of Ontario population are living near highways and major roads. My study tries to identify how roadside structures affect ambient air pollution concentrations in areas near major roads. There are two objectives of my research. The first objective is to determine the influence of roadside structures on local NOx, O3, PM, including trace metal speciation, and noise levels. The second objective is to quantify the effectiveness of different types of roadside structures on air pollutants and noise reduction in residential areas near freeways. The result of my study will help urban planners, engineers, and scientists explore feasible and cost-effective roadside structures to reduce noise and pollution dispersion near freeways.

Chandula Fernando

PhD Student

chandula.fernando@mail.utoronto.ca

 
 

My current research addresses the concern that most assessment protocols remain greatly outdated with many requiring humans to make physical measurements. Further, most advancement in unmanned monitoring techniques (such as the use of drones) occur in response to major disasters and incidents of accidental release. My study proposes a pipeline through which innovation during disasters can convert to routine environmental assessment protocols. The key difference between disaster and routine situations is the availability of contaminant. In disaster conditions, levels of pollutants can be high and easily detected. In comparison, routine situations require vastly different search strategies, flight patterns, build designs and algorithms. This study compares and identifies facets in disaster technology to improve routine assessment in the energy sector. In addition to quantifying the ability to identify contaminants through limits of detection and resolution, comparison focuses on exposure metrics such as “user-time per area covered”. Besides improving safety and quality assurance, it is hoped that a consolidated platform of impact assessment across different facilities in the region would allow for an enriched discussion when comparing energy solutions, in planning to meet future climate and energy targets.

Graduate Students (MSc)

Felix Massey

MSc Student

 
 

My research investigates the effectiveness of using various mobile monitoring methods to generate land-use regression (LUR) models to predict the spatial variation of ambient air pollution concentrations in five Canadian cities: Toronto, Mississauga, Hamilton, Montréal and Québec. The pollutants being monitored include nitrogen dioxide (NO2) and ozone (O3) which are sampled using bicycles equipped with low-cost air pollution sensors and a mobile air pollution laboratory with research-grade instruments. This study is significant because there are only a few passive air monitoring stations located throughout the region which may not capture the entire temporal and spatial complexity of air pollution. Mobile monitoring techniques are used to obtain spatially-varying air pollution estimates across a mix of land-use conditions and socioeconomic regions. The LUR models produced from this study can be used to generate interpolated continuous pollution surfaces across the region to identify exposure levels at unobserved locations while also assessing the effectiveness of pollution modelling using low-cost sensors. This research provides an evidence-based assessment of nitrogen dioxide and ozone pollution exposure which could be employed for administrative purposes and designing local air pollution monitoring systems.

Anna Shadrova 

MSc Student

anna.shadrova@mail.utoronto.ca

 

My current research focuses on spatial and temporal co-modelling nitrogen dioxide, nitric oxide, and ground-level ozone. These pollutants are considered to be major urban air pollutants in North America and are associated with congestion, vehicular exhaust, and have adverse health effects. Typically, these three pollutants have been examined in isolation; however, they are related as they convert between species due to photochemical processes in the atmosphere. My hypothesis is that both spatial and temporal air pollution modelling can be improved by looking at the sum of the three pollutants opposed to each pollutant in isolation. In my research, these pollutants are being sampled with diffusion based passive monitors (Ogawa Passive Sampler) that have shown strong agreement with EPA reference methods. The passive samplers are distributed at 30-50 fixed sites across each study area. Monitoring campaigns are taking place between May 2019 and September 2019 in Southern Ontario: Mississauga, Toronto, Hamilton, and London. Combining these two sampling methods will allow for spatially and temporally varying observations of NO2, NO, and O3 and provide an opportunity to assess the related interactions of these pollutants. 

 

Spencer Elford

MSc Student

NSERC CGS-M Scholar

- Michael Smith Foreign Study Supplements Program

- Environment Canada Atmospheric and Meteorological Graduate Supplements

spencer.elford@mail.utoronto.ca

My research examines air pollution exposure of school-aged children during commutes between their home and their school location in the Greater Toronto Area (GTA). Toronto is a major North American city; whose large population and high traffic volume make it an ideal location for air pollution studies. By applying a Geographic Information System (GIS) based approach to air pollution modelling known as Land-Use Regression, ambient pollution concentration estimates are developed on spatially precise scales. By simulating commute routes on along Toronto’s road and cycling network we examine variations in exposure attributed to commute timing, vehicle used, and route taken.

 

Past Group Members

Karl Chastko

MSc Graduate

NSERC CGS-M Scholar​ 

- Michael Smith Foreign Study Supplements Program

- Environment Canada Atmospheric and Meteorological Graduate Supplements

karl.chastko@mail.utoronto.ca

My research is focused on investigating the error produced by mobile and portable air pollution monitoring campaigns. The rise in popularity of these monitors has led to the development of spatially refined exposure models but has also led to new challenges related the spatially and temporally discontinuous nature of mobile data. Mobile air pollution monitors are often employed to capture the spatial variability of air pollution and to estimate long term exposure values. These long term estimates introduce some degree of error which is poorly understood and largely undocumented. My research utilizes simulated mobile monitoring campaigns to assess the accuracy of various estimation techniques. This research will be used to produce best practices when utilizing mobile and portable air pollution monitors.       

Tuo Shi

Visiting PhD Student from Institute of Applied Ecology, Chinese Academy of Sciences

Major: Ecology, Landscape Ecology

tuoshi0411@163.com

My research focuses on the atmospheric environment effect in the background of urban expansion. This includes the distribution characteristics of atmospheric pollutants at different urban scales (urban agglomerations, cities, districts and street valleys), so as to find out how to apply pattern optimization and urban planning methods to mitigate atmospheric environment pollution.

Wentao Run

Thesis Student

Environmental Science Specialist Program (HBSc) in progress

Biology Minor Program (HBSc) in progress  

September 2018 - April 2019

My current research project aims to devise time-specific travel routes of low combined air pollutants within the Ward 6 of Mississauga.  The findings of this research may yield practical solutions for cyclists and pedestrians to plan their work/leisure commute in ways that minimize their chance of exposure to location-specific peak-time ambient air pollution.  

Fatimah Taghdi ​

Thesis Student

September 2018 - April 2019
 
 

My research will take on developing a method of forecasting extreme air pollutantion events using machine learning techniques.

Melanie Maddix ​

Thesis Student

September 2018 - April 2019
 
 

The cities of Mississauga and Hamilton are beginning construction of light rail transportation (LRT) projects. To understand the impact of such projects on air pollution it is first necessary to establish a baseline pollution level of the area. I am researching the development of a land-use regression model that includes data acquired from passive samplers of NO and NO2. The goal is a model that can be used as baseline for monitoring the ongoing effects of LRT construction in Hamilton and Mississauga.

 

Dariya Darvin

Major: Mathematics

Minor: Biology, Computer Science

May 2018 - April 2019

 

My research aims to measure air pollution at schools and in households across Hamilton and Mississauga. In Ontario, the introduction of the Kiss-and-Ride program has caused more private vehicles to idle in drop—off zones during school start and dismissal times. This research will investigate how this increase in vehicle idling affects the air quality in elementary school playgrounds which are located closed to these drop-off zones.PM2.5 levels will be monitored for this study and the data will be collected using real-time air pollution monitors installed at various schools in Mississauga and Hamilton. This data is significant since particulate Matter (PM) exposure has been linked to many respiratory and cardiovascular problems with children being one of the high risk groups.  Real-time air quality monitoring will also be conducted in selected households across Hamilton to measure particulate matter(PM10, PM2.5 and PM1 ) air pollution, how it varies across Hamilton and throughout the year. 

Nick Dirienzo​

Visting Student from Carelton University

The Centre for Global Change Science - Summer Undergraduate Intern Programme

May 2018 to August 2018

My research involves the monitoring of NO and NO2 via the use of passive samplers set up throughout Mississauga and Hamilton. This is in order to determine the baseline local atmospheric concentrations of NO and NOthroughout Mississauga and Hamilton before their respective LRT plans begin to be implemented. With construction of the Mississauga and Hamilton LRT systems beginning shortly, there will be an expected increase in NO and NO2. This is of importance because NO and NO2 exposure (among other pollutants) can result in decrease of lung function and a myriad of respiratory problems.

Haseeb Malik

Major: Geographical Information Systems (HBSc.)
Minor: Computer Science.

May 2018 to August 2018
 

Maria Deligero​

HBSc Student
Major: Geographical Information Systems
Minor: Physical and Human Geography

May 2018 to August 2018

My work involves the acquisition and preparation of census, air pollution, and land use data for the city of Hamilton. These datasets are processed by the Land Use Regression tool on ArcMap using various buffer sizes, which were chosen based on one hundred Land Use Regression research articles that were collected. The ultimate goal for my work is to prepare and provide datasets that can be useful for new and ongoing GIS projects.

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