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#CrowdCloudLIVE After each episode's WORLD premiere in April, show host, producer, and people seen on the show participated in post-premiere roundtable discussions. Viewers like you listened in, asked questions, and were able to dive deeper into the power of Citizen Science.

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Counting Trucks: Clearing the Air
Neighborhood Knowledge for Change
Q&A with Brian Beveridge

I'm Brian Beveridge, and I'm the Co-Director of the West Oakland Environmental Indicators Project.

What is the West Oakland Environmental Indicators Project?

In the late '90s, there was a real interest in this notion of indicator sets which are real snapshots of large ecological settings. I was interested at that time and said, "What would it look like if we apply the same techniques to a neighborhood?" Our first report, published in 2002, was called "Neighborhood Knowledge for Change." That report, because it was through a neighborhood lens and took existing data, allowed the community to go to regulators in the port and city and say, "Here is our data on our community. Here's how the trucks, the ships, and the freeways sort of correlate with the asthma levels and the health impacts." Now, it's not just us complaining that kids have asthma. We have a basis to demonstrate why kids have asthma.

Tell us a little about the report?

I believe it was instrumental in supporting work that the state was trying to do at the time to reduce diesel emissions. Regulators can do a lot, but they take their reports to the legislature, and either something happens or it doesn't. There is always the need for communities to raise their voice in support of change. There is always push back from the people who will have to pay for the change. Science isn't enough. There always has to be a human face attached to it. Unfortunately, in a way, we live in a world where humanity isn't enough, either.

A lot of our work is to combine science and humanity in a way that supports each other and makes that case. There hasn't been any way, in the past, for regulators to address your issue specifically, or my issue specifically. Even the health care system has trouble addressing our issues very specifically. This has meant that we dealt with environmental problems, especially in the urban areas, in broad strokes. We will reduce the total volume of traffic in the whole region in order to reduce ozone levels in the region. But we have no idea what's going on right here on this street, as we're breathing the air here.

It's not only to get data, but to make it freely available, easily distributed, and easily used. It's not some complicated spreadsheet that it's just something you can look at and say, "Oh, I need to make a different choice today." Our work is really grounded in having people engaged in what's taking place in their community. Understanding their community through data, and being able to use that data for change. We started with existing information to look at the snapshot of the neighborhood. That allowed us, as a community, to prioritize the issues. Let's start with air. "Well, what is the key health problem? It appears to be diesel pollution from the whole freight industry. Then what will we do about that?" The community came up with thirteen recommendations on how you would reduce the impacts of diesel pollution. We put that out in a little report called "Clearing the Air." Among those were things like modifying truck routes, providing truck parking outside the neighborhood, providing food and fuel and the other things that trucks come in the neighborhood to get.

The idea of doing something about trucks, because trucks were right here in our face every day, became a priority. We got a little grant, and we put together a committee that would work on truck routes. Before we could do that, we really needed some data on where the trucks were and how many trucks there were, because no one had ever owned (i.e. monitored) the trucks. For decades, the people of the neighborhood had been trying to get somebody to care. It wasn't until we were able to get some funding and decide, "If no one else is going to do a traffic analysis of the trucks, we'll do it ourselves." We taught community members to sit on the corner in a little lawn chair with a clipboard, and they counted trucks. We did it under the oversight of professional traffic surveyors, and had research assistants to then assess the data.

We took the data from the traffics survey and went to our city council member. We reached out to the trucking community, who were actually pretty responsible. We met every month talking for 25 months. For the most part, we were all able to rationalize or work our way through the logic of having the trucks go on the freeway, around the neighborhood rather than right through the middle of the neighborhood. That was very successful. It was a unanimous vote at city council when they changed the ordinance.

What are you doing for air quality presently?

We started thinking about, “What is it that we're actually breathing as we walk down the street? What is our daily experience in the air?” We did a study sometime after the truck count where we put these black carbon monitors in the homes of 20 senior citizens around the neighborhood. It turned out there were much higher levels of black carbon, which is a reference for diesel soot inside their homes than in typical homes around the state. We started to suggest at the Air District that they should be looking at the worst case neighborhoods, the hotspots. If they started to regulate for that everybody else would win too. What we were really saying is we need to shrink the scale of our understanding of the environment around us to identify where those conditions are the worst and begin to address them at that point.

That notion of shrinking the scale kept getting smaller and smaller until it turned out to be each and every one of us walking down the street. We say, "How would we figure that out?" The Air District said, "You can't do that. It's too confusing. There are too many factors. We can't regulate that way." That was when we started looking around for ways to do it. The work with the backpacks has continued to expand into the whole area of access to information. It's not only getting a machine that can get the data, it's figuring out what to do with the data, then how do you distribute it.

There's a movement now around open data and the democratization of data, getting data out of these big archives and institutions and getting it to the people where they can use it. This whole thing is “citizen science,” as they call it. We call it “community based participatory research.” It's really powerful, and it's powerful beyond the data. There's an element of understanding your own life that's very powerful. Filling in the blanks or adding a lot of color to the picture of our world. Things we hadn't noticed before now become things we notice. Just look around and become more aware of the impacts on our life of the activities taking place in our world. We're talking about citizen science. The science part is important, and sometimes we get hung up on the science part. That's really just taking the job of researchers and seeing if we can plug a community member in. There's a lot value in community members understanding science.

We're not going to experts and asking them to please apply their expertise to us. We're going to experts and saying, "We are experts, too. We are experts in our own community. We are experts in our own lives." We can prove it, and we can work together. This kind of work is really in it's earliest stages, and I think in the next 10 years we'll see a huge change in the way we view data, the way we view regulation, the way we view access to information, and the way that information, that access, affects this society as a whole.

Why not use data from the EPA?

The Air District was very impressed with our report, they were very happy with the level of accuracy that was collected. It turned out to be a very successful partnership, which included a government agency, private contractors, a community based organization, and 30 community members who had never done anything like this before in their lives. When we do this work, it's very important that the people who are directly impacted by the research are participating in the research. This is a hard one, especially for academia, to understand. The way they do their quality control was that they would have an Air District engineer go out and just do duplicate data gathering for an hour at selected stations. It was a random redundancy factor. If their data matched to the data from the field surveyors, then they would say, "OK, they must be doing it OK."

We're not saying we don't need PhDs. We're saying that if you can teach a graduate student to do it, you can teach a community member to do it. We're not trying to replace anybody. We are trying to engage communities in an understanding of their own lives in their own communities. We're trying to respect them for what they already know. Respect people for their lived experience, to respect them as experts in their own lives, and to add that to a body of professional expertise. It creates a better picture for policy making, or for social change. We have huge amounts of data. We sometimes frighten the statisticians, because they would prefer to have a little bit of perfectly pristine, absolutely 100 percent data from a million dollar machine. We're saying, "No, no, let's take this $200 machine and start making decisions based on it." If you had a one million dollar machine, you could do so much with that, but if you had a million hundred dollar machines all spewing data into the cloud, and giving it back to us in a direct feedback loop, that we start to adjust behavior immediately.