This paper examines the daily activity-travel behavior of undergraduate students, graduate students, faculty, and staff at a large university to better understand their activity travel demands for automobile, active transportation (AT), and transit trips. The data were derived from the first university-based activity travel diary survey [Environmentally Aware Travel Diary Survey (EnACT)] conducted in spring 2016 at Dalhousie University, Canada. Results show that students reside nearer to the campus than faculty and staff, and their trip length from home to school is significantly shorter. Zero-inflated negative binomial (ZINB) models show that if housing tenure is less than 1 year, it is more likely that the traveler will make more AT trips but fewer automobile trips. It indicates that individuals living far from the campus will produce fewer transit trips than those who live nearer. Interestingly, the mean number of AT trips per day for the overall sample is more than one trip, whereas for automobile trips and transit trips it is less than one. The behavioral analysis and empirical models provide useful insights that can be utilized to represent university populations in regional travel demand models, as well as to develop campus-based travel demand management (TDM) strategies.

Marine oil spill response operations could generate a large volume of liquid oily wastes (e.g., emulsified oil, non-emulsified oil, and wastewater) that can be up to 30 to 40 times greater than the original volume of spilled oil. Oil decanting technologies are used globally for recovering spilled oil and handling liquid wastes. Canada follows the standards set out in the MARPOL 73/78 Annex 1 International regulations in most areas, with more strict discharge requirements in certain locations. For instance, inland waters discharge should not exceed 5 ppm, and in special areas, such as the Great Lakes, the discharge standard is under 0 ppm. In the event of an oil spill, decanted seawater should be barged to shore for disposal, which significantly constrains the response capacity and efficiency of oil recovery by skimmers due to limited temporary storage space in barges and the long time and high cost of transportation. This has become one of the greatest challenges the Canadian governments and oil spill response industries are facing in Canada. Moreover, when the spill response team decides that decanting is an appropriate way to handle the spilled oil, the approval process may take a long time, which negatively impacts the spill that has already occurred. Moreover, Canada uses a 10,000-tonne planning standard for oil spill preparedness, whereas the United States uses a worst-case scenario, and Europe uses a 60,000 m³ planning standard. The existing planning threshold in Canada can cause the country to be not fully prepared when it comes to responding to a very large oil spill if one should occur. This study conducted a comprehensive review of the current Canadian oil spill response system and framework, regulations, roles and responsibilities of federal and provincial governments, existing decanting capabilities, and capacities of Canadian oil spill responders. More importantly, this study identified the gaps in the current oil spill response system and regulatory and technological barriers to oil decanting. Marine oil decanting regulations and practices in the US and selected European countries have also been reviewed to support addressing the challenges and improving the Canadian experience. It is expected that this study would help the stakeholders and professionals to better understand the oil spill response system and oil decanting status quo in Canada and facilitate Canadian governments and industries to better address the challenges in oil spill regulations and practices.

Transportation planners and engineers seek to make informed decisions on transportation infrastructure development and planning. Travel demand models forecast the usage demands on transportation infrastructure and services under various socio-demographic scenarios, and for different mode choices and land-use characteristics. The transportation literature emphasizes that accurate prediction of travel behavior is a required input to travel demand models. This need has increased with a recent shift from long-term transport infrastructure investment to shorter-term management policies, such as staggering work schedules, tele-commuting, and congestion pricing. These paradigm shifts have resulted in replacement of statistically-oriented, trip-based models by behaviorally-oriented, activity-based models. This paper discusses the strengths and weaknesses of these models and their relationship to broader travel behavioral issues, with special consideration to the needs of transportation planners and modelers.

This study aims to investigate the mode choices and housing location choices for university population segments (undergraduate students, graduate students, faculty, and staff) using comprehensive statistical analyses and bivariate probit models. The data used in this study are derived from a web-based online survey conducted at Dalhousie University, Canada, in April 2016. Respondents who live within 1.0 km from their university campus choose to walk or bike for their commuting trips to campus. With an increase in commuting distance, the choice of using motorized vehicles and carpooling increases. Most importantly, it is found from the bivariate probit models that housing location choices and mode choices are joint decisions. The choice of living more than 1.0 km from the campus significantly reduces the choice of active transportation (AT) and significantly increases the choice of motorized vehicle for commute trips. This study provides in-depth analyses which can be further utilized for integrated housing-transportation planning and group-sensitive policies to promote sustainable commuting to campus.