Telecommuting and environmental policy - lessons from the Ecommute program



Walls, Nelson, Safirova


Telecommuting and Environmental Policy

According to the Federal Highway Administration (FHWA), the average car on the road in 2000 was 9-
years-old, nearly 4 ½ years older than the vehicles owned by participants in the ecommute program
(U.S. FHWA, 2003). This could be significant. If telecommuters own newer - and thus cleaner - than
average vehicles, the emissions benefits of telecommuting may not be that great.

Table 10. Distribution of Types of Vehicles Owned by Employees in ecommute Program
as of March 1, 2004

Vehicle type

Percentage of employees in
ecommute program

Light-duty gasoline vehicles

(i.e., passenger cars)

Light-duty gasoline trucks

(6,000-8,500 lbs gross vehicle weight)

Light-duty gasoline trucks

(>8,500 lbs gross vehicle weight

Light-duty gasoline trucks

(<6,000 lbs gross vehicle weight

Motorcycles

Light-duty diesel vehicles (i.e., passenger cars)

Light-duty diesel trucks (under 8,500 lbs gross

67.5

17.8

7.5

5.2

0.9

0.6

0.6

vehicle weight)

Table 11. Distribution of Ages of Vehicles Owned by Employees in ecommute
Program

as of March 1, 2004

Vehicle Model Year

Percentage of employees in ecommute program

1984 - 1989

1990 - 1994

1995 - 1999

2000 & 2001

2002 & 2003

5.6

15.3

37.8

27.1

14.0

To generate specific emission factors for NOx and VOC for each city, we use the assumptions
employed by local planners for their regulatory demonstrations. This means that assumptions about
temperatures, traffic congestion, inspection and maintenance programs, and the like are consistent with
those used by the cities for purposes of demonstrating transportation conformity and other regulatory
uses. The scenario run for all cities except Denver was a Summer day in 2005. For Denver a winter run
was used because unlike the other cities Denver has a greater problem with carbon monoxide (which is
worse in the winter) than ozone (which is worse in the summer).

Two important issues emerge for calculating total emissions reductions: (1) whether we assume
that the employee would have driven alone to work had they not telecommuted, and (2) whether we
assume that there is any change in non-work trips as a result of working at home. Since we do not have
any travel information on the individuals in the program other than their journeys to work, we cannot
speak to (2). We simply assume there is no change in non-work travel as a result of telecommuting.
With respect to (1), we show emissions results under two assumptions. In the first scenario, we assume
that everyone who telecommuted would otherwise have driven alone to and from work in the vehicle
they report that they own. The emissions reduction from telecommuting is then the emissions factor, in

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