Electronic waste (e-waste) has become the main contributor of lead to landfills in the United States. Households also store large volumes of e-waste, yet little is known about their willingness to recycle e-waste. This article starts filling this gap based on a 2004 mail survey of California households. Using multivariate models, the authors find that gender, education, convenience, and environmental beliefs but not income or political affiliation are key factors explaining the willingness to drop off e-waste at recycling centers. A comparison of an ordered probit with a semi-nonparametric extended ordered probit model of the survey responses shows that the latter better predicts less frequent answers. The results suggest targeting public education programs about recycling at teenagers or younger adults and making recycling more convenient for older adults; moreover, e-waste drop-off centers should first be created in communities that already offer curbside collection programs for conventional recyclable products.

This paper relies on a unique dataset collected during a national survey of US households to explore how different sources of information (print, television, radio, family/friends, work/school and others) influence the decision to start recycling. Although print media are influential, it is found that face-to-face communication (through family/friends or work/school) is the most effective medium to get people to start recycling. However, it is even better to provide households with recycling information from multiple sources. The respondents in this study identify concerns about storage space, time and the safety of recycling as the main obstacles to start recycling. In addition, age and ethnicity are statistically significant but not income or education. These findings should be useful for crafting information campaigns designed to boost recycling, although to be successful these campaigns need to incorporate findings from environmental psychology and knowledge of specific communities.household recycling, recycling information, environmental attitudes, logistic regression,

When streets with high traffic stress—on which the mainstream population is unwilling to ride a bike—are removed, the remaining network of streets and paths can be fragmented and poorly connected. This paper describes the development of methods to visualize and to analyze the lack of connectivity in a low-stress bicycling network. A proposed measure to evaluate bicycling networks is the fraction of origin–destination pairs, which are connected without the use of high stress, without excessive detour, and with the origin–destination pairs weighted by travel demand. A new method is proposed to classify segments and crossings into four levels of traffic stress (LTS) on the basis of Roger Geller’s classification of the cyclist population and Dutch design standards, which are known to attract the mainstream population. As a case study, every street in San Jose, California, was classified by LTS value. Maps that showed only lower stress links revealed a city divided into islands within which low-stress bicycling was possible, but these islands were separated from one another by barriers that could be crossed only with the use of high-stress links. The fraction was 4.7% of home-to-work trips up to 6 mi long that were connected at a low LTS value. The figure would almost triple if a modest slate of improvements were implemented to connect low-stress streets and paths with each other.

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The growth of electronic waste (e-waste) is of increasing concern because of its toxic content and low recycling rates. The e-waste recycling infrastructure needs to be developed, yet little is known about people's willingness to fund its expansion. This paper examines this issue based on a 2004 mail survey of California households. Using an ordered logit model, we find that age, income, beliefs about government and business roles, proximity to existing recycling facilities, community density, education, and environmental attitudes are significant factors for explaining people's willingness to pay an advanced recycling fee (ARF) for electronics. Most respondents are willing to support a 1% ARF. Our results suggest that policymakers should target middle-aged and older adults, improve programs in communities with existing recycling centers or in rural communities, and consider public-private partnerships for e-waste recycling programs.