PEIR Science

Impact / Exposure Models Used by PEIR

The Models Used by PEIR

At the heart of PEIR are four models that calculate your exposure and impact based on your uploaded location traces. Particulate Exposure and Fast Food Exposure provide feedback about the hazards you encounter as you move through your day. Carbon Impact and Particulate Impact on Sensitive Sites describe how you affect the places you pass through. The four PEIR models combine your location trace with data about the urban environment to produce estimates for each trip you make. These are then presented on a per-trip basis, together with aggregates by week and by month. For consistency, we have chosen to report your impacts in terms of the estimated quantities of pollutants you emit, reported in units of grams. We report your estimated exposures in units of time, the time spent near hazardous conditions.

The values output by some of these models may mean very little to you at first. We hope that as you examine how they change over time, and how they compare to those of your friends and other users of PEIR, you will start to discover your own ways to interpret them. We believe they can show how the situations we face and our choices affect our relationship with the environment.

While we’ve made every effort to employ well-known and scientifically accepted models in a responsible way, the PEIR project cannot and does not claim that the specific values generated for you have any correlation to your actual exposure, impact or health outcomes

Particulate Exposure

When vehicles burn fuel, they create particles of pollution thought to have a significant impact on human health. While the research as to specific health effects is still ongoing, we know that, overall, increases in particulate emissions in the air are linked to poorer health. Particulate pollution has been linked to significant disease risks, including cancer, heart disease, and asthma. Particulate pollution is a “localized” type of pollution because many kinds of particles don’t make it very far past where they were emitted. This means that where you go can significantly change how much particulate matter you breathe.

PEIR’s Particulate Exposure model calculates the amount of particulate pollution (specifically, PM2.5) produced by the total estimated traffic through which a PEIR user is traveling. To calculate these values, we use the Emission Factors (EMFAC) model, designated by the California Air Resources Board as the model to use when evaluating the pollution impacts of traffic in California. The EMFAC model takes traffic and weather data and outputs pollutant quantities. For a PEIR user’s exposure, we calculate the quantity of particulate pollution generated by traffic on roads within 200 meters of the user’s GPS location trace . We use estimated traffic by time of day, so one can expect that the model will find more traffic and assign more pollution to a user’s path if he is traveling during the morning rush than in the middle of the night. The quantity of pollution that an individual is exposed to is measured in micrograms per cubic meter of air, caused by traffic.

To make this quantity somewhat interpretable, we divide your exposure into three categories: Low (fewer than 15 micrograms per cubic meter), Medium (between 15 and 65 micrograms per cubic meter) and High (over 65 micrograms per cubic meter). For each trip you take, we then report the amount of time you spend in either Medium or High pollution conditions.

Particulate Impact Near Sensitive Sites

Whenever you choose to drive, you add to the presence of particulates in the air. Airborne particulates have their most significant impact on health near sensitive sites, like schools and hospitals.

The Particle Pollution impact model calculates the amount of particulate pollution emitted by the PEIR user near sites with potentially vulnerable populations, like schools and hospitals. As in the Particulate Exposure model, we use EMFAC to estimate pollutants—in this case, those based on your vehicle only. We assign this pollution value to schools and hospitals within two hundred meters of the user’s travel path. We then report the total amount of particulate pollution (in grams) you emit per trip near sensitive sties.

Carbon Impact Model

The latest United Nations report on the climate provides significant evidence connecting greenhouse gas emissions, including CO2, with climate change. Increased production of CO2 causes a range global climate change effects, including drought, extreme weather, and the melting of the ice caps, by trapping more of the sun’s energy in the Earth’s atmosphere. According to the EPA, fossil fuel combustion, including from driving, causes 82% of total US greenhouse gas emissions. PEIR can help users track where they travel and how much each trip contributes to each person’s total greenhouse gas production.

To calculate the amount of CO2 produced by each trip, we again employ EMFAC, which is fed data about your speed and duration of travel, what kind of car you drive, and the weather, and outputs pollutant quantities. For a PEIR user’s CO2 emissions, we calculate the amount of emissions (in grams) generated by the user’s travel.

Fast Food Exposure

PEIR calculates exposure to fast food establishments to offer insight into the options for eating available to a PEIR user on a daily basis. It does not directly measure health, but we hope PEIR can shed light on how our access to fast food affects our eating habits.

To model a PEIR user’s exposure to fast food and healthy food options, we need two kinds of data. First, PEIR uses an individual’s GPS-based location trace to determine where the user has been. We also use a database of the locations of all food-related establishments in the region, fast food and convenience stores (our junk food choices) and restaurants and grocery stores (the other food options). PEIR counts the number of total food options and junk food options within one-quarter mile of your travel through the city. We place this number into one of three categories: Low (three or fewer restaurants), Medium (between three and five restaurants) and High (over five). Finally, we report the amount of time you spend in the Medium or High categories per trip.