Search

The UI for the portal is straightforward and easy to use and also doubles as a GIS. Through the advanced search function users can use either the criteria or filter tabs to narrow their searches to specific sites. For example when you narrow down the search to RMP facilities only you can quickly pinpoint all of these facilities on a map of an area to show how burdened an area may be with these types of facilities.

The data can very quickly show you how many facilities a geographical area may have. This can allow users to see how burdened a neighborhood for example may be with specific facilities.

One of the only data visualizations this site offers is plotting down pinpoints on a map showing individual facilities. If there is more than one site in a certain geographical area then it will group the sites together and provide a circle for where the sites are contained with the number of sites listed on the circle. This makes this data resource not super flexible in ways it can display information. However this is a helpful visualization as it can quickly show you how many specific facilities a certain location may have

You can also generate simple graphs with the data that displays the amounts of certain facilities throughout the state. This is a good tool for tracking all regulated facilities which can help users address Ej on a statewide scale.

What this lacks in visualizations it makes up for drastically in easy to use UI and for creating one location for all of the state's facility data. By using its advanced search tool users can quickly find a plethora of data on extremely specific sites. This tool will show when the facilities had their most recent evaluations and whether or not there were violations, rough estimates on onsite stored chemicals, which regulatory programs they are a part of, CalEnviroScreen percentile ranges, and a contact list for facility employees.

This data resource can scale from the state level down to the census tract in terms of facility locations. For data visuals it groups sites together so you can not get a comprehensive visualization of regulated sites beyond the neighborhood and census tract level.

CalEPA Regulated Site Portal (CalEPA RSP) does not generate any of their own data but combines data from 7 state data sets and 2 federal datasets. 

State Data Sets: Cal/OSHA, CERS, CIWQS, EnviroStor, GeoTracker, SMARTS and, SWIS

Federal Data Sets: EIS and TRI

CalEPA made this resource in order to create a “...holistic view of regulated activities statewide.”(CalEPA.2022).

This data resource is called ‘CalEPA Regulated Site Portal’.

Recommended Citation: CalEPA. Regulated Site Portal. 2022. https://siteportal.calepa.ca.gov/nsite/map/help.

The authors "define disaster media as a heuristic, or approach, that recognizes the ways “natural” and human-made disasters are communicated about, constructed, and variously exacerbated or relieved through media means. This heuristic is not simply a temporary model for problem solving but tries to account for ecological forces and material conditions" (my emphasis).

They close the article with three provocations:

1) All Media on Deck: the current moment of combo disaster (COVID and climate crisis) requires the production of more public and open access materials (of various kinds), but also boosting of media literacy. The auhtors acknowledge the conundrum of producing more media, while being confronted with sustainability issues and the call for "no-carbon" media.

2) Relief and media Production: a critical look at the kinds of assumptions that governments/NGOs/industry bring to COVID-19 relief efforts (videos, websites, maps, algorithms...) -- what counts as relief and for whom? 

3) Focus on Social and Environmental Justice: "In moving forward, it will be crucial to approach disaster media as a domain in which structural reform agendas that interweave social and environmental justice can flourish."

In the article, the authors address visualizations of COVID cases, including related satellite mages of air pollution in Southern California and China (generated by NASA/ESA) as well as of mass graves in Iran.

First, they provide basic framing of how to critically read air pollution satellite imagery. Connections between COVID-19 measures and improvements in air pollution are not identifiable in a straightforward way.

"Figure 1a, for instance, uses bright magenta to indicate greater concentrations of nitrogen dioxide and light blue to signify cleaner air. However, such color choices can be misleading: there is no material correlation between nitrogen dioxide and the color magenta; and reduced traces of this chemical do not turn the sky a paler shade of blue. [...] color-coding selections imply, satellite images are not just scientific; they are cultural as well."

Second, they point out the paradox role of satellite imagery to account for the inequitable impact of COVID-19

"satellite image, from a US satellite operator, locates pandemic “excesses” in an Iranian “elsewhere.” But this is an increasingly deceptive proposition, given that the United States has one of the highest COVID-19 per capita transmission and fatality rates in the world."

Third, they draw comparisons between the "hockey stick" visualization of global Climate Change and the various "curves" used to display COVID-19 developments:

From a disaster media perspective, the film’s global warming graph depicts a dramatic climate shift, projects imminent catastrophe, and issues a world warning. Its circulation in global media culture for the past fifteen years potentially informs the ways people are engaging now with similar-looking charts of coronavirus death and illness. Historically, news media have relied on sensationalistic photos of human suffering to convey a sense of disaster, but in the age of big data and the current pandemic, numbers speak, and graphs and curves tend to dominate the mediascape. In both cases, scientific experts and publics must grapple with how these graphs make meaning, what datasets they rely upon, and how these media come to stand in for highly complex conditions.

Finally, they remark that COVID-19 visualizations are always incomplete - because of lack of testing and withholding of data - but also because stories of e.g. workers are missing. They reference the cover of the New York Times (May 24, 2020) that displayed the names of 100,000 people who had died from COVID.