Source: SFMTA

Introduction

The automobile industry boomed over a century ago, quickly becoming a key aspect of American culture. Over the past 100 years, the economy and infrastructure have grown and developed in reflection of this culture, resulting in car-dependent cities and an industry worth over 100 billion USD in 2022 (IBIS World, 2022). Cities in the United States are now heavily trafficked and heavily polluted with the emissions that result from such a high concentration of vehicles. “It’s easy to see why having a car in the US is synonymous with mobility and freedom to travel – without one, you’re beholden to poor transit services that might include one-hour waits for buses that may or may not arrive, minimal or non-existent bike lanes and limited rail service, among other challenges. The car-centric infrastructure and culture of the US is also the crux of its greenhouse gas emissions” (Simek, 2021).

In 2020 alone, passenger vehicles in the US produced 617.7 million tons of carbon dioxide (Tiseo, 2022). According to the EPA, each of these vehicles burns 4.6 tons of carbon dioxide every year. The average American’s carbon footprint (16 tons) is about 4 times the global average (Murphy, 2022). In other words, one vehicle in the United States, only one component of someone’s carbon footprint, emits more tons of carbon dioxide than the global average of someone’s total carbon dioxide emissions every year.

Approximately 85 percent of American commuters drove to work in 2019. Only 5 percent of American commuters used public transportation as their mode of transportation to work, 2.6 percent walked to work, and only 0.5 percent of American commuters biked to work in 2019 (Burrows et. al, 2021). To compare, these statistics differ significantly from Germany, a country with the 4th largest GDP in the world and large automobile industry. According to Germany’s Federal Statistics Office, 40 percent of German commuters drive to work, 28 percent walk, 23 percent bike, and 8 percent use public transportation (Clean Energy Wire, 2017).

In a study conducted by Christian Brand at the University of Oxford, it was found that on average, someone choosing to ride their bike instead of driving their car just once a day can reduce their transportation carbon emissions by 67 percent. Cyclists produce 84 percent less carbon emissions over their lifetime from daily travel than a non cyclist (Brand et. al., 2021). Not only does biking infrastructure benefit the whole community by less vehicle pollution, but it also reduces traffic, promotes pedestrian safety, and offers major health benefits for cyclists. The benefits of regular cycling are both mental and physical. These include reduced anxiety and depression and decreased stress levels, as well as prevention or management of disease, increased cardiovascular fitness, improved joint mobility, increased muscle strength and flexibility, and more (Woodstock et. al., 2009, Millard, 2022.)

San Francisco was ranked the most bikeable cities in the country in 2021 (Geler, 2021), yet only 3 percent of residents in San Francisco used biking as their daily mode of transportation in 2021. For context, 24 percent of San Francisco residents walked, 11 percent used transit, and 61 percent used vehicles (Moran, 2022). Although these statistics are better compared to the average American, they still reflect the major lack of “green infrastructure,” i.e. biking networks and public transportation in the US.

In the following analysis, I will be focusing on the biking infrastructure in San Francisco. My research goals and aims are the following: 1) Examine what is currently being done to build better biking infrastructure in the city, 2) Designate specific locations or neighborhoods that are lacking a bike network, 3) Identify how existing inequalities manifest themselves in the distribution of biking networks in low-income neighborhoods, marginalized communities, and areas with higher pollution. I hope to discover a solution for how to better implement biking infrastructure in San Francisco and demonstrate how beneficial biking infrastructure can be for the mental and physical well-being of people. I will focus my argument on the “Equity Strategy Neighborhoods,” which are 8 neighborhoods in San Francisco designated by the MUNI Service Equity Strategy to be prioritized in improving public transit accessibility and reliability. I will demonstrate how biking infrastructure is also lacking in these neighborhoods and why it should be considered a “next step” in the MUNI Service Equity Strategy. The audience for my analysis will be the San Francisco city planners. I want to influence them to increase their efforts toward a more bikeable city while being very mindful of social justice issues and what communities of San Francisco would most benefit from a more extensive biking network. Through my arguments and research, I also hope to influence readers to realize the benefits of biking and incorporate it into their lives.

Current biking infrastructure in the City of San Francisco

Data and Methods

A large majority of my datasets are from DataSF, an online database provided by the City of San Francisco:

Bike Volume This data includes manual counts of bikes at 119 different intersections throughout San Francisco, collected from 2007 to 2019 (with the exception of 2012.) The data does not specify the time period in which the bikes are counted annually, but the locations remain constant throughout. I used this data by choosing a random intersection, 5th and Market, to demonstrate how counts have increased over time.

MTA Bike Network This data includes linestring data of the current biking infrastructure in the city of San Francisco. The network is classified between Bike Lanes, Bike Routes, and Bike Paths. A “Path” is closed to motor vehicles and is mostly used for bicycle traffic, however, can be multiuse. A “Lane” is a separate lane on the street, indicated by traffic paint, alongside vehicle traffic. A “Route” is specified for bicycle traffic, often a planned route that includes several different bike paths and is designed to guide bicycle traffic through an especially scenic or convenient route. I used this data to determine where biking networks were most concentrated within the city. By transforming the linestring data to a shape, I was able to calculate the volume of biking network per census tract, in square feet.

Equity Strategy Neighborhoods This data contains a shapefile of the 8 different Equity Strategy Neighborhoods. Within the shapefile, the data also provides information on the amount of zero-vehicle households within the specified neighborhoods. I used this data to demonstrate that biking infrastructure is lacking and used the amount of zero-vehicle households to designate which of these neighborhoods should be prioritized.

Other datasets used come from CalEnviroScreen 4.0, the California Communities Environmental Health Screening Tool, provided by the Office of Environmental Health Hazard Assessment (OEHHA). As defined by OEHHA, CalEnviroScreen is a screening methodology that can be used to help identify California communities that are disproportionately burdened by multiple sources of pollution. This was an invaluable tool in my data analysis. Within this shapefile, I used the current indicators: Population Density, CI Score, Education, Unemployment, HousingBurden, PollutionBurden, Poverty, and Race/Ethnicity identifications. With this data I was able to demonstrate how the Equity Strategy neighborhoods are largely disadvantaged in comparison to other parts of San Francisco, and analyze how improving biking infrastructure can be socially and environmentally beneficial.

Refer to this key to better understand the following indicators:

Population Density: Population Density per census tract. Population in 2010 divided by the area of census tract (persons per square mile)

CI Score: CalEnviroScreen Score, Pollution Score multiplied by Population Characteristics Score, measured in grams of carbon dioxide equivalent per megajoule of energy (gCO2e/MJ)

Education: Percent of population over 25 with less than a high school education

Unemployment: Percent of the population over the age of 16 that is unemployed and eligible for the labor force

HousingBurden: Percent housing-burdened low-income households

PollutionBurden: Average of percentiles from the Pollution Burden indicators (with a half weighting for the Environmental Effects indicators)

Poverty: Percent of population living below two times the federal poverty level

Hispanic: 2019 ACS population estimates of the percent per census tract of those who identify as Hispanic or Latino

White: 2019 ACS population estimates of the percent per census tract of those who identify as non-Hispanic white

AfricanAmerican: 2019 ACS population estimates of the percent per census tract of those who identify as non-Hispanic African American or Black

NativeAmerican: 2019 ACS population estimates of the percent per census tract of those who identify as non-Hispanic Native American

AsianAmerican: 2019 ACS population estimates of the percent per census tract of those who identify as non-Hispanic Asian or Pacific Islander

Other: 2019 ACS population estimates of the percent per census tract of those who identify as non-Hispanic “other” or as multiple races

By applying the following indicators to Equity Strategy Neighborhoods and using the Bike Network Data to find the volume of biking network per census tract, I created the following indicator: “Biking Network Area,” which describes ratio of biking network area to the area of each ESN in square feet. Using this indicator in combination with the social and environmental indicators, I determined where biking infrastructure is lacking and what locations should be prioritized for future improvement.

Analysis

SFMTA Equity Strategy Neighborhoods

Learn more on the website

The Muni Service Equity Strategy is a project that began in the summer of 2017 to make public transit in San Francisco more accessible and affordable. According to the SFMTA website, the Equity Strategy will “benefit eight selected Equity Neighborhoods, seniors and people with disabilities, by implementing service treatments that can be implemented quickly while delivering measurable improvements to safety, connectivity to key destinations, reliability, frequency and crowding. Moreover, the strategy will establish a performance baseline for Muni routes serving each Equity neighborhood, which will be monitored annually.”

It is crucial to note that car-dependent cities not only result in higher pollution and negative environmental affects, but they also exacerbate existing inequalities. The effect is compounding. Car-dependent cities contribute to climate change. Climate change disproportionately affects marginalized communities. Marginalized communities have unequal access to vehicles and safe, reliable transportation. The ease of mobility that reliable transportation provides is not just physical mobility, but also social. According to the Bureau of Transportation Statistics, “households with an annual income of less than $25,000 are almost nine times as likely to be a zero-vehicle household than households with incomes greater than $25,000.” Racism has manifested itself in transportation as well:

“Income and wealth disparities have caused Americans of color to have less access to vehicles than White Americans. Racial segregation forged through the expropriation of land from Indigenous people and racially discriminatory practices such as redlining dispossessed communities of color and excluded them from economic prosperity. As a result, people of color are more likely to experience poverty and lack generational wealth than their White counterparts. This trend along with racially discriminatory pricing for auto loans and car insurance that make car ownership more costly drive inequities in car access between White Americans and Americans of color” (National Equity Atlas).

Reliability is a recurring topic when it comes to public transportation in California. Transit vehicles are often late, or don’t show up altogether. In the 2021-2022 Muni Service Equity Strategy report, one of the most notable findings was that “missed service due to operator shortage is a significant source of stress that impacts people with low income the most.” A young student in San Francisco was quoted in the report saying:

“It took me 1 hour and 20 minutes to get home from school today. A trip that by car should take 15 minutes… I now have to stay up until 1AM trying to get my homework done, get 5 HOURS of sleep, and get up at 6 AM…Imagine having an hour long commute and being diagnosed with something called chronic stress at the age of 15.”

If someone is without a car, as many people in the city of San Francisco are, they are completely dependent on the faulty transit system. By building better biking infrastructure and encouraging these people to bike we can provide these people with a middle-ground option that is much more accessible and affordable than buying a car, while also giving them the freedom and flexibility that public transportation cannot. This freedom also promotes personal dignity and autonomy, which are “at the the very foundation of human rights, and are inextricably linked to the principles of equality and non-discrimination” (Social Protection and Human Rights Platform).

By clicking on the neighborhood, you can explore specific Cal EnviroScreen indicators.

What is the presence of biking infrastructure in these neighborhoods?

To determine which of these neighborhoods was most lacking biking infrastructure, I considered two variables: the number of households with zero vehicles in that neighborhoods, and the ratio of the total square footage of the neighborhood, and total square footage of the biking network within that neighborhood.

In the map below, the darkest colors represent where there is the smallest ratio of biking network per the total area of the neighborhood. The darker the red, the more need for improved biking infrastructure.

In the map below, the darkest colors represent where there is the largest amount of households without vehicles. The darker the red, the more need for improved biking infrastructure.

Note: The Bayview and Vistacon Valley neighborhoods still have a significant number of zero vehicle households.

Using CES 4.0 Indicators to Designate Greatest Need

Pollution Burden

Population Density

Conclusion and Recommendations

After analyzing the previous indicators and maps, it is evident that the MUNI Equity Strategy should consider the task of improving biking infrastructure in the Equity Strategy Neighborhoods, which are clearly disadvantaged communities with inadequate access to biking networks. This improvement in infrastructure in unique to the improvement of public transit as it provides individual and community benefits. With better access to and safety biking, individuals in these neighborhoods can experience improvements in mental and physical health, as well as improved autonomy and social mobility. Bayview Neighborhood should be listed as top priority in these improvements, as it experiences the brunt of pollution burden, very little biking network, high population density, and high unemployment. The following is a prioritized list of the Equity Strategy Neighborhoods according to indicated environmental and social burden:

  1. Bayview
  2. Visitacion Valley
  3. Mission
  4. Downtown/Civic Center
  5. Excelsior-Outer Mission
  6. Western Addition
  7. Chinatown
  8. Ocean View-Ingleside

I strongly encourage San Francisco city planners and those in charge of the MUNI Equity Strategy to consider this as a necessary project to improve equity in these communities, address environmental injustices, and grant these communities better autonomy. Additionally, I strongly encourage all abled readers to bike as much as possible, to the extent that the safety of their roads and traffic allow them, and join the growing number of Americans realizing how great cycling is not only for their own health but for the health of their communities and environment as well.

Works Cited

Industry market research, reports, and Statistics. IBISWorld. Retrieved December 8, 2022, from https://www.ibisworld.com/industry-statistics/market-size/car-automobile-manufacturing-united-states/#:~:text=The%20market%20size%2C%20measured%20by,to%20increase%202.6%25%20in%202022

Tiseo, I. (2022, June 21). U.S. passenger car GHG emissions 1990-2020. Statista. Retrieved December 8, 2022, from https://www.statista.com/statistics/1235091/us-passenger-car-ghg-emissions-by-vehicle-type/

Simek, P. (2021, October 25). America needs to kick its car dependency. are local investments in urban design the answer? D Magazine. Retrieved December 8, 2022, from https://www.dmagazine.com/frontburner/2021/10/america-needs-to-kick-its-car-dependency-are-local-investments-in-urban-design-the-answer/

C. Brand, E. Dons, E. Anaya-Boig, et al. The climate change mitigation effects of daily active travel in cities. Transp Res Part Transp Environ, 93 (2021), Article 102764, 10.1016/j.trd.2021.102764

Burd, C., Burrows, M., & McKenzie, B. (2021, March). Travel time to work in the United States: 2019 - American Community Survey Reports. United States Census Bureau. Retrieved December 8, 2022, from https://www.census.gov/content/dam/Census/library/publications/2021/acs/acs-47.pdf

Murphy, J. (2022, November 9). Average American carbon footprint by State. 8 Billion Trees: Carbon Offset Projects & Ecological Footprint Calculators. Retrieved December 8, 2022, from https://8billiontrees.com/carbon-offsets-credits/reduce-carbon-footprint/average-footprint-per-person/american/#ref-2

Burrows, M., Burd, C., & McKenzie, B. (2021, March). Commuting by Public Transportation in the United States: 2019 - American Community Survey Reports. United States Census Bureau. Retrieved December 8, 2022, from https://www.census.gov/content/dam/Census/library/publications/2021/acs/acs-48.pdf

Millard, E. (2022, August). What are the health benefits of cycling? EverydayHealth.com. Retrieved December 8, 2022, from https://www.everydayhealth.com/fitness/reasons-cycling-is-good-for-your-health/

Hammon, D. (2022, July 7). Where is the most green and sustainable city in the US? Inhabitat. Retrieved December 8, 2022, from https://inhabitat.com/where-is-the-most-green-and-sustainable-city-in-the-us/

Social Protection and Human Rights (Unknown Author). (2019, December 11). Dignity and autonomy in Social Protection Systems. Social Protection and Human Rights. Retrieved December 8, 2022, from https://socialprotection-humanrights.org/framework/principles/dignity-and-autonomy/

Yip, L. (2022, November 9). Why marginalised groups are disproportionately affected by climate change. Earth.Org. Retrieved December 8, 2022, from https://earth.org/marginalised-groups-are-disproportionately-affected-by-climate-change/#:~:text=How%20Marginalised%20Groups%20are%20Disproportionately%20Affected%20by%20Climate%20Change,-by%20Leonardo%20Yip&text=Marginalised%20groups%20and%20minority%20communities,as%20future%20and%20younger%20generations

R Script

The R script for this project can be found here.