CURBSIDE RECYCLING SURVEY 2009 J. Clifford Fox, J.D., Ph.D. Center for Environmental Studies Virginia Commonwealth University

Method 1001 Telephone Interviews. Listed, stratified sample of households in participating jurisdictions. – Chesterfield, Hanover (partial), Henrico, and Goochland (partial) Counties; Cities of Colonial Heights and Richmond. – Screened for adult respondent and eligibility by type of housing unit: “a single-family home standing by itself?” or a “home located in a building with four or fewer units within it - that is not a part of a multi-building apartment complex.” Interviews conducted from January 12-17, 2009 by Princeton Data Source, LLC.

Sampling Error, Bias, and Weighting Items answered by all respondents are subject to a sampling error of approximately plus or minus 3 ½ percentage points at the 95% level of confidence; with Chesterfield = ± 5.5% For questions in which responses are highly skewed, the sampling errors may be less. It must also be remembered that surveys are subject to errors and biases other than sampling. An effort is made to identify and minimize these errors through weighting, but other potential biases should be considered when interpreting results. Results are weighted in two ways: – Household = based upon telephones and race by geographic area. – Population = based upon telephones, population, age, sex and race by geographic area.

Participation Rates

Participation

Participation by Income

Participation by Age

Participation by Race

Conclusions (participation) Rates are generally high. Casual participants make up over 20% of participants and are a potential marketing target for increased participation. Over half of households are loyal participants. Set-outs rates are a good temporal measure of participation, and match well with loyal participant measures. African-American participation is significantly lower and needs to be better understood. Income is a good predictor of participation over-all and in literature. Chesterfield may want to target lowest and highest income groups.

Participants’ Information

Participants’ Other Recycling Methods (multiple response: Base = 265) Other Ways to Handle Recycling (Multiple Response) A recycling or drop-off center uN 140 w% (60.8%) 56.5% A non-profit donation center [If needed: Goodwill, Salvation uN 44 w% (19.3%) 19.1% Regular trash collection uN 33 w% (16.4%) 12.6% Compost uN 19 w% (8.1%) 7.7% Plastic bag return uN 22 w% (3.5%) 7.1% Battery/Electronic Recycling uN 4 w% (None) 1.7%

Materials Recycled (multiple response) Materials Recycled (Multiple Response) Paper uN 623 w% (82.2%) 81.8% Magazines uN 98 w% (11.5%) 11.9% Plastic uN 581 w% (79.4%) 79.1% Aluminum uN 379 w% (52.7%) 50.3% Glass uN 393 w% (56%) 49.9% Cardboard uN 326 w% (46.1%) 43.7% Non-Aluminum Metal uN 81 w% (12.8%) 9.6% Other [Specify] uN 40 w% (5.5%) 5.9%

Participants’ “Rules” for Recycling (multiple response) Rules for recycling (Multiple Response) Just put it out at the curb uN431 w%(65.2%) 64.2% Put it in the bin provided uN206 w%(31.2%) 30.1% No food uN58 w%(7%) 8.1% Only certain kinds of plastic (e.g. #1 and #2 plastic, only) uN56 w%(7.2%) 7.6% Break down cardboard boxes/Size of cardboard boxes uN55 w%(9.4%) 6.8% Separate materials by type uN35 w%(3.7%) 4.4% No slick paper or magazines uN6 w%(.4%) 1.1% No colored glass uN2 w%(.4%).3% Other [Specify] uN127 w%(19.3%) 19.2%

Participants’ Suggestions Participant Suggestions Bigger/More Bins uN 77 % (23.8%) 32.0% More Frequent Pick-Up uN 68 % (28.6%) 28.2% More Types of Plastics Recycled uN 28 % (9.5%) 11.6% Wheeled Bin uN 18 % (7.1%) 7.5% Incorrect Separation Issue uN 10 % (10.7%) 4.1% Other Response uN 40 % (20.2%) 16.6%

Conclusions (participant information) Participant knowledge fits the empirical profile. – Other recycling. – Materials recycled. “Put the recycling in the bin provided.” Volume concerns are present. – More frequent collection – Larger/more bins. – Tradeoffs must be considered.

Non-participant Information

Non-participants: Knowledge of the Program Q8 Before today, did you know that you can put recycling at the curb to be picked up? Yes uN 186 w% (72.4%) 64.6% No uN 61 w% (27.6%) 35.4%

Likelihood of Participation in the Future (0-10)

Conclusions (non-participant information) A significant percentage of non-participants didn’t know that they could recycle “in their neighborhood.” Almost half of non-participants rate their likelihood of participating in the future above the mid-point (6-10). – A large number of non-participants rated their likelihood of future participation as a 10. – Focus groups tell us that many of the tens live in town houses or condos where they report that curbside is not allowed and drop-off is inconvenient. Others live in neighborhoods in which they “assumed” they could not do curbside.

Recycling Knowledge and Attitudes

Recycling programs pay for themselves

Taxes or fees from my household help to provide the service.

Most recycling ends up in the landfill.

We are running out of landfill space.

We are in danger of running out of natural resources.

It makes a difference whether our household recycles.

Awareness about CVWMA

Have you ever heard of CVWMA?

Sources of Information about CVWMA Where have you heard of CVWMA? (Multiple Response) Trucks uN 244 w% 35.5% Recycling bins uN 160 w% 23.2% Calendar/Mail uN 97 w% 13.9% Television uN 42 w% 6.2% Newspaper uN 40 w% 5.7% Website uN 14 w% 2.0% Radio uN 2 w%.2% Other [Specify] uN 246 w% 35.8%

Conclusions (Attitudes and Awareness) Respondents have a strong perception of consumer effectiveness. The basic message has been received. – Market penetration of basic brand (CVWMA). – Problems of solid waste (resource depletion and land-fill capacity). Some troubling misconceptions exist. – “The program pays for itself, but tax dollars/fees are still used to support the programs.” – “Recycling eventually goes to the landfill.” Active information sources (trucks, bins, calendars) are stronger in respondent’s recall and are probably better to change behaviors.

Questions and Follow-up?