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[1] A fuel-based approach is used to estimate nitrogen oxides (NO x = NO + NO 2 ) emissions from gasoline-and diesel-powered motor vehicles. Estimates are made at the national level for the period 1990-2010. Vehicle emissions are also estimated at the state level for California, and for the South Coast (Los Angeles) and San Joaquin Valley air basins. Fuel-based emission estimates are compared with predictions from widely used emission inventory models. Changes in diesel NO x emissions vary over time: increasing between 1990 and 1997, stable between 1997 and 2007, and decreasing since 2007. In contrast, gasoline engine-related NO x emissions have decreased steadily, by $65% overall between 1990 and 2010, except in the San Joaquin Valley, where reductions were not as large due to faster population growth. In the San Joaquin Valley, diesel engines were the dominant on-road NO x source in all years considered (reaching $70% in 2010). In the urbanized South Coast air basin, gasoline engine emissions dominated in the past and have been comparable to on-road diesel sources since 2007 (down from $75% in 1990). Other major anthropogenic sources of NO x are added to compare emission trends with trends in surface pollutant observations and satellite-derived data. When all major anthropogenic NO x sources are included, the overall emission trend is downward in all cases (À45% to À60%). Future reductions in motor vehicle NO x will depend on the effectiveness of new exhaust after-treatment controls on heavy-duty trucks, as well as further improvements to durability of emission control systems on light-duty vehicles.

Public bikesharing-the shared use of a bicycle fleet-has recently emerged in major North American cities. Bikesharing has been found to decrease driving and increase bicycling. But shifts in public transit have been mixed. The authors evaluate survey data from two U.S. cities to explore who is shifting toward and away from public transit as a result of bikesharing. The authors explore this question by mapping geocoded home and work locations of respondents within Washington DC and Minneapolis. Respondents were mapped by their modal shift toward or away from bus and rail transit. The results show that in Washington DC, those shifting toward bus and rail transit live on the urban periphery, whereas those living in the urban core tend to use public transit less. In Minneapolis, the shift toward rail extends to the urban core, while the modal shift for bus transit is more dispersed. The authors analyze sociodemographics associated with modal shift through cross-tabulations and four ordinal regression models. Common attributes associated with shifting toward public transit include increased age, being male, living in lower density areas, and longer commute distances. The authors conclude with a discussion of the final results in the context of bikesharing's impacts on other cities throughout North America.

Public bikesharing-the shared use of a bicycle fleet by the public-is an innovative mobility strategy that has recently emerged in major North American cities. Bikesharing systems typically position bicycles throughout an urban environment, among a network of docking stations, for immediate access. This paper discusses the modal shift that results from individuals participating in four public bikesharing systems in North America. The authors conducted an online survey (n =10,661 total sample), between November 2011 and January 2012, with members of four major bikesharing organizations (located in Montreal, Toronto, the Twin Cities, and Washington D.C.) and collected information regarding travel-behavior changes, focusing on modal shift, as well as public bikesharing perceptions. The survey probed member perceptions about bikesharing and found that a majority in the surveyed cities felt that bikesharing was an enhancement to public transportation and improved transit connectivity. With respect to modal shift, the results suggest that bikesharing generally draws from all travel modes. Three of the four largest cities in the study exhibited declines in bus and rail usage as a result of bikesharing. For example, 50% of respondents in Montreal reported reducing rail use, while 44% and 48% reported similar shifts in Toronto and Washington D.C., respectively. However, within those same cities, 27% to 40% of respondents reported using public transit in conjunction with bikesharing to make trips previously completed by automobile. In the Twin Cities, the dynamic was different, as 15% of respondents reported increasing rail usage versus only 3% who noted a decrease in rail use. In all cities, bikesharing resulted in a considerable decline in personal driving and taxi use, suggesting that public bikesharing is reducing urban transportation emissions, while at the same time freeing capacity of bus and rail networks within large cities.

Carsharing has grown considerably in North America during the past decade and has flourished in metropolitan regions across the United States and Canada. The new transportation landscape offers urban residents an alternative to automobility, one without car ownership. As car-sharing has expanded, there has been a growing demand to understand its environmental effects. This paper presents the results of a North American carsharing member survey (N = 6,281). A before-and-after analytical design is established with a focus on carsharing's effects on household vehicle holdings and the aggregate vehicle population. The results show that carsharing members reduce their vehicle holdings to a degree that is statistically significant. The average number of vehicles per household of the sample drops from 0.47 to 0.24. Most of this shift constitutes one-car households becoming carless. The average fuel economy of carsharing vehicles used most often by respondents is 10 mi/gal more efficient than the average vehicle shed by respondents. The median age of vehicles shed by carsharing households is 11 years, but the distribution covers a considerable range. An aggregate analysis suggests that carsharing has taken between 90,000 and 130,000 vehicles off the road. This equates to 9 to 13 vehicles (including shed autos and postponed auto purchases) taken off the road for each carsharing vehicle.