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Air Quality and Forecasts: Measuring Behavioral Impacts. Douglas S. Noonan School of Public Policy Georgia Institute of Technology. Air Quality Advisories. Last time I counted, 357 different cities have some kind of program. Air Quality Advisories. A program by any other name ….
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Air Quality and Forecasts: Measuring Behavioral Impacts Douglas S. Noonan School of Public Policy Georgia Institute of Technology
Air Quality Advisories • Last time I counted, 357 different cities have some kind of program
Air Quality Advisories • A program by any other name …. • Air Awareness • Air Quality Action Day • Air Quality Advisory Day • Air Quality Alert Day • Air Quality Health Advisory • Air Quality Health Alert • AirWatch • Care About Clean Air • Health Advisory • Health Advisory Episode • Ozone Action Day • Ozone Alert • Ozone Watch • Smog Alert • Smog Watch
Air Quality Advisories • Last time I counted, 357 different cities have some kind of program • They differ in their: • Context (populations, infrastructure, history, etc.) • Message (content, dissemination) • Incentives (perks, policies, etc.) • Program details (source of forecasts, thresholds, days of operation, etc.)
Advisory: Giving Advice • Should I run behind the bus? • Should I run (or walk, or sit on the couch, or…) • Should I take the bus (and wait roadside, or drive, or …) “The best way to protect yourself from the harmful effects of air pollution is to be informed”
The Atlanta Journal-Constitution By David A. Markiewicz Published on: March 20, 2008 Exercise die-hards have their own strategies against smog:Some get miles in early on bad summer days For the physically active, outdoor exercise in Atlanta during the summer presents a conundrum: When the smog is high, do you recreate or hibernate? … Greg Masterson, president of the Metro Atlanta Cycling Club, said he's "aware" of smog alert days, "but I go ride anyway, and I will continue to do that." … Masterson said poor air quality, "makes you want to drive to Dahlonega."
Message(s) • Reduce pollution (“spare the air”) • Carpool, use public transit, telework • Reduce vehicle trips • Change the time of polluting activities (driving, refueling, lawnmowing, using household chemicals) • Avoid exposure (“protect yourself”) • Limit outdoor exertion, exercise • Jog less, or walk • Limit outdoor activities generally • The alert is triggered on exceedance days • Implying the message doesn’t apply on non-exceedance days?
Behavioral Impacts • Impacts of what on behavior? • The trick here is to isolate the effects of the advisory itself on behavior… …not the effects of bad air quality on behavior. • What if the advisory triggers incentives (beyond the info alert)?
Behavioral Impacts • Hospital visits fall • Outdoor activities fall • Less biking, walking, (waiting for transit?) • Indoor activities rise? • Transportation changes • More alternative modes • Different timing • Strategic commuters? • Timing of activities change • Different time-of-day, different days
What do we know? • A lot of anecdotal evidence • Several studies of awareness • Some studies of impacts • rely on self-reported behaviors • voluntary programs that do not account for selection bias • A few rigorous studies out there… (measuring behavioral responses not as easy as it might seem)
What do we know? • Los Angeles(Neidell 2005) • kids’ asthma-related hospital visits • at-risk groups’ zoo/observatory visits • visits at major museum • San Francisco(Cutter & Neidell 2007) • traffic • BART ridership • observed ozone levels • Chicago (Welch et al. 2005) • CTA’s turnstile counts • no impact on total; some shifting within day
What about Atlanta? • Atlanta begins alert programs in 1998: • household surveyin 1998 by Henry & Gordon (2003) • Only significant effects for government workers • traffic countsin 1998 by Cummings & Walker (2000) • No significant impacts • I looked at two types of behavior: • driving patterns (2001) • household travel diary data from ARC • activities in Piedmont Park (2005) • observations of park users at various sites, times, days, etc.
What about Atlanta? • Impacts depend on the behavior: • No significant effect of alerts on household VMTs, traffic flow in the park • Alerts do affect composition of park flow • Fewer elderly • Fewer exercisers (and, less so, runners)
Summary • Average treatment effect on: • Ozone-producing activities (i.e., driving) • mixed (insig. in ATL, CHI; sig. in SFO) • Non-emitting activities (i.e., visits, exercise) • significant • This leaves a lot of unanswered questions
What we don’t know • Generalizability • Through space, through time • What are the alternatives? • Exposures of alternatives • Net benefits of alternatives • Linking the responders (& nonresponders) and whether they “got the message”
What we don’t know • How do different messages affect responses? • What about coupling messages and incentives? De-coupling? • Crying wolf? Rebound effects? • Impact of alerts, alert programs on AQ • peak AQ, also non-peak AQ • alerts have no discernible effects in SFO • similar method: alerts bring higher O3 in ATL
Missing links • Systematic data collection on (targeted) behaviors • collected over multiple seasons, cities • tracking of behavior of message recipients • Data collection on substitute behaviors • track un-targeted behaviors also • health risks, emissions • Rigorous research design aimed at measuring effects of advisories on behavior • It may be a risky question to ask…
Speculations • Imagine a simple situation: • People care about 3 things: • their travel time • their exposure to air pollution • “warm glow” from reducing their emissions • They choose their transportation mode (walk, bike, bus, train, drive) • How might this choice change with a red alert? • How do we get drivers to switch?
Speculations • Effectiveness of alerts hinges on: • Efficacy/warm-glow of altruistic non-driving • Lowering perceived extra exposure of non-driving • Reducing the higher travel costs of non-driving • Simpler prediction (avoidance) for non-emitting activities
Speculations • Advisory (from theory) to get people out of cars: • Get more trains • Message: extra trains on red alert days • Emphasize a bonus “warm glow” • Message: alternative modes are even better on red alert days • De-couple the alerts from AQ / risk levels • Message: no threshold effect in AQI • Advertise personal risks of driving, emitting • Psychology, risk communication have much to contribute also…
Speculations • Advisory (from evidence): • Responsiveness is high when: • it is a sensitive population • time is flexible, substitutes are easy • reducing exposure is independent of (or involves reducing) emissions • Responsiveness is low (or adverse) when: • reducing exposure involves increasing emissions • Temporal switching also likely • Be careful: people might be listening!
Ozone forecast effects • Following Nichols (2007), the share of observations jumps by 1.1%*** at the 85ppb cutoff Figure 7: Kernel density of observed (ozact) and forecasted (ozpred) daily ozone levels, 1999-2003
Ozone forecast effects • Significant tendency to overpredict up to the threshold, then actual levels jump +9.7ppb to remove the bias Observed ozone levels Figure 8: Local regression fit of ozone forecasts to observed levels, with cutoff at 85ppb (mean at cutoff = 75.3ppb) Forecasted ozone levels