RCE Peel - 2024

Freight Data Warehouse
CSV
Basic Information
Title of project : 
Freight Data Warehouse
Submitting RCE: 
RCE Peel
Contributing organization(s) : 
Peel Region, Smart Freight Centre, University of Toronto
Focal point(s) and affiliation(s)
Name: 
RCE Peel
Organizational Affiliation: 
Peel Region
E-mail: 
rcepeel@peelregion.ca
Format of project: 
Report
Language of project: 
English
Date of submission:
Wednesday, October 9, 2024
Web link: 
N/A
Additional resources: 
N/A
Does this project link to any education and/or sustainable development policy or policies?: 
Yes
The study follows Long-Term Pathway 3 of Peel Region’s Long-Term Goods Movement (2019): Develop a publicly available Peel Freight Data Warehouse for planning purposes
At what level is the policy operating?: 
Local
Geographical & Education Information
Region: 
Americas
Country: 
Canada
Location(s): 
Peel Region
Address of focal point institution for project: 
N/A
Ecosystem(s):
Urban/Peri-urban
Target Audience:
Community
Socioeconomic and environmental characteristics of the area : 
Peel Region is a regional municipality in the province of Ontario, Canada. It encompasses the cities of Brampton and Mississauga, and the Town of Caledon. Peel is characterized by a diverse and rapidly growing region with a strong industrial and commercial base, and extensive transportation network.
Peel Region is a major economic hub, particularly in the logistics and manufacturing sectors, due to its strategic location near Toronto and its access to key transportation infrastructure. Peel benefits from its proximity to major highways which enable efficient goods movement across Ontario and into the United States. Peel Region is also home to Toronto Pearson International Airport, the busiest airport in Canada, which plays a vital role in air cargo operations and connects the region to global markets. This combination of robust transportation infrastructure supports Peel's role as a key logistics and manufacturing center, attracting businesses that rely on efficient access to domestic and international markets.
Environmentally, Peel faces challenges related to urban sprawl, traffic congestion, and air quality, but is also home to significant green spaces and agricultural areas, balancing urban development with environmental preservation efforts.
Description of sustainable development challenge(s) in the area the project addresses: 
Peel Region faces sustainable development challenges such as balancing rapid urbanization with environmental preservation, mitigating traffic congestion, and reducing greenhouse gas (GHG) emissions from freight and passenger transport.
Additionally, ensuring equitable access to green spaces and transit, addressing air quality and health impacts, and implementing resilient infrastructure to withstand climate change are critical areas of focus for sustainable growth.
Contents
Period: 
January, 2020 to January, 2024
Rationale: 
The prototype allows users to view up-to-date representations of GHG emissions and air contaminants from commercial vehicles by time of day and roadway links. Utilizing data and data science applications provides transportation professionals with novel avenues to analyze demand patterns, network design, and operational strategies.
This project is crucial for several reasons. First, it addresses the urgent need to reduce GHG emissions and improve air quality, both of which are critical for public health and environmental sustainability. By providing detailed and real-time data, the dashboard enables policymakers to identify pollution hotspots and implement targeted measures to mitigate emissions.
Secondly, the tool enhances decision-making processes by offering empirical evidence on the impact of commercial vehicle traffic. This can lead to more informed infrastructure planning and traffic management strategies, optimizing the flow of goods while minimizing environmental impact.
Moreover, the Freight Data Warehouse (FDW) fosters collaboration between stakeholders, including government agencies, transportation companies, and environmental organizations. It creates a shared platform for monitoring and addressing issues related to freight transportation and environmental impact.
Ultimately, this project supports the development of sustainable transportation systems, contributing to the broader goals of reducing carbon footprints and promoting healthier urban environments.
Objectives: 
This project focuses on the digitalization of supply chains by developing an operational web dashboard prototype to visualize GHG emissions and air contaminants on freeways in the Greater Toronto and Hamilton Area (GTHA).
Specifically, the project establishes the Smart Freight Centre Data Warehouse within the ITSoS platform, hosted on the ITS Private Cloud at the University of Toronto. It acquires and integrates data from HERE, ATRI, and Shaw/Ommitracs into the ITSoS system, develops querying systems, analytics, and visualization capabilities, and provides secure access to Transport Canada and researchers at the Smart Freight Centre.
Activities and/or practices employed: 
The dashboard prototype uses several data sources, applies data fusion techniques made available through the Freight Data Warehouse, and showcases the analytics, monitoring, and modeling capabilities of the FDW.
This project uses complementary datasets to calculate GHG emissions produced by freight vehicles throughout the day. The four data sources used are traffic speed data, traffic volume data from permanent counting stations, emissions factors calibrated for the GTHA, and vehicle type distributions from traffic counts.
Size of academic audience: 
N/A
Results: 
The dashboard prototype is divided into three areas.
The first is the query panel on the dashboard's left side. Within this panel, the user must follow four steps to do the query in the dashboard.
The central panel of the dashboard shows an interactive map of emissions on a per-kilometer basis.
The right panel of the dashboard is divided into three sub-sections. The first sub-section (on the top right) displays the top 25 links with the network's highest emissions. The second sub-section (on the center-right) shows some general statistics of the query (total pollutants in the network, average pollutants per km, average pollutants per hour, average pollutants per km hour, etc.)
The third subsection (on the bottom right) shows a histogram with the distribution of pollutants by km of road.
Lessons learned: 
This project highlighted several key lessons.
First, integrating diverse data sources was essential for providing accurate and comprehensive emissions visualizations but posed technical challenges in data fusion and system compatibility. Collaboration among stakeholders, including government agencies and transportation companies, proved vital for data acquisition and system development.
Additionally, real-time data visualization significantly enhanced decision-making capabilities, demonstrating the potential for similar tools in other regions. However, maintaining data privacy and security while ensuring accessibility remains a critical challenge.
Overall, the project underscored the importance of interdisciplinary cooperation and robust data management in developing effective digital tools for sustainable transportation.
Key messages: 
This project developed a dashboard to visualize GHG emissions and air contaminants from commercial vehicles on GTHA freeways. It aids policymakers in identifying pollution hotspots, optimizing traffic management, and reducing environmental impact, thereby promoting sustainable transportation and healthier urban environments.
Relationship to other RCE activities: 
This project is an outcome of the Smart Freight Centre’s activities by the University of Toronto. The Smart Freight Centre (SFC) has established a collaborative network with Peel Region, McMaster University, the University of Toronto, and York University. SFC works to reduce community and environmental impacts of moving goods in the Greater Toronto Area.
Funding: 
This study was funded by Peel Region and the University of Toronto.
UN Sustainable Development Goals (SDGs)
(https://sustainabledevelopment.un.org/sdgs) and other themes of Education for Sustainable Development (ESD)
SDG 3 - Ensure healthy lives and promote wellbeing for all at all ages 
Indirect
SDG 8 - Promote sustained, inclusive and sustainable economic growth, full and productive employment, and decent work for all 
Indirect
SDG 9 - Build resilient infrastructure, promote inclusive and sustainable industrialisation, and foster innovation 
Direct
SDG 11 - Make cities and human settlements inclusive, safe, resilient and sustainable 
Direct
SDG 12 - Ensure sustainable consumption and production patterns 
Indirect
SDG 13 - Take urgent action to combat climate change and its impacts 
Direct
SDG 16 - Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels 
Indirect
Theme
Forests/Trees 
Indirect
ESD for 2030-Priority Action Areas
Priority Action Area 1 - Advancing policy 
state: 
Direct
Priority Action Area 2 - Transforming learning and training environments 
state: 
Indirect
Priority Action Area 3 - Developing capacities of educators and trainers 
state: 
Indirect
Priority Action Area 5 - Accelerating sustainable solutions at local level 
state: 
Direct
Update: 
No
I acknowledge the above: 
Yes