See https://data.lacounty.gov/Transportation/County-Employee-Average-Vehicle-Ridership-AVR-2012/b92g-vuub for more detail.

Average Vehicle Ridership (AVR) is the figure derived by dividing the employee population at a given worksite that reports to work weekdays between 6:00 a.m. and 10:00 a.m. by the number of vehicles driven by these employees commuting from home to the worksite during these hours. The AVR is calculated using a weekly averaging period. The applicable employee population is multiplied by the number of weekdays in the selected averaging period, then divided by the total number of vehicles driven by these employees to the worksite during the same period.

The survey is administered to each county department by location. The calculated AVR for each responding location was included in the data from the CSO (who received the data from the Department of Human Resources) for years 2012-2018, except 2017. An AVR of “1” means that every employee drove alone; therefore a greater AVR is a better outcome. The target AVR is set for each county department, and targets range mostly from 1.5-1.75.
For each year, a weighted average for the total AVR across county departments was calculated to account for the varied number of employees at each location and graphically presented the data.

Average Vehicle Ridership (AVR) is the figure derived by dividing the employee population at a given worksite that reports to work weekdays between 6:00 a.m. and 10:00 a.m. by the number of vehicles driven by these employees commuting from home to the worksite during these hours. The AVR is calculated using a weekly averaging period. The applicable employee population is multiplied by the number of weekdays in the selected averaging period, then divided by the total number of vehicles driven by these employees to the worksite during the same period.
The survey is administered to each county department by location. The calculated AVR for each responding location was included in the data from the CSO (who received the data from the Department of Human Resources) for years 2012-2018, except 2017. An AVR of “1” means that every employee drove alone; therefore a greater AVR is a better outcome. The target AVR is set for each county department, and targets range mostly from 1.5-1.75.
For each year, a weighted average for the total AVR across county departments was calculated to account for the varied number of employees at each location and graphically presented the data.

Stationary source lead emission data available from the EPA (TRI Explorer).

This is a combination of two datasets:
(1) LA County tree canopy data (TreePeople (University of Vermont)
(2) LA County land cover data, 2014 imagery (Los Angeles Regional Imagery Acquisition Consortium)

This is a combination of two datasets:
(1) LA County tree canopy data from TreePeople/University of Vermont
(2) LA County land cover data, 2014 imagery (Los Angeles Regional Imagery Acquisition Consortium)
Urban and rural tree canopy areas and percentages. Urban areas are defined as those census block groups whose centroids are within the Census’s “Urban Areas” shapefile.

This dataset was produced by harvesting/scraping addresses from LA County and City of LA websites for cooling centers, recreation centers, and year-round pools (2019 data).

https://www.lacounty.gov/heat/
https://emergency.lacity.org/heat

Data includes cooling center addresses from LA County and City of LA websites for cooling centers, LA city recreation centers, and LA city year-round pools (2019 data).

DRAFT

Active/ inactive wells for all cities and unincorporated county with one or more active well sourced from Division of Oil, Gas, and Geothermal Resources, Oil & Gas Well Shapefile for California.

Downloaded annual reports of HAP metal emissions from TRI Explorer for LA County.
Cleaned data and totaled masses of point source and fugitive air emissions for each of the pollutants for each year.
Generated line graphs showing the emitted masses per year for the HAP metals included in the TRI report list.
Three separate plots were required to show the changes in emitted masses over time since they range over four orders of magnitude.
Created heat maps of median household income and created proportional marker symbols for each emitter address location (2017).