California: Bringing the Heat

Rising levels of greenhouse gases in the atmosphere over the last few decades have led to a host of environmental concerns, including an increasing frequency and intensity of extreme climatic events. Among these are heatwaves: periods of prolonged, abnormally hot weather, often accompanied by high levels of humidity. According to the US Global Change Research Program, the average number of heat waves has tripled since the 1960s across 50 major American cities.

The effects of heat waves can be exacerbated in cities as a result of the ‘heat islands’, an effect resulting from urbanization in heavily populated areas. Because cities tend to have a much higher concentration of absorptive surfaces, such as asphalt and concrete, surface temperatures tend to be higher than in nearby rural areas. Given that 80% of the population in the United States lives in cities, the combination of the heat island effect and increasing temperatures caused by climate change can result in serious health effects for millions of people. Modifications to the built environment such as the introduction of plant species, reflective paving surfaces, and natural ventilation are all sustainable methods that can create a real difference in reducing heat exposure in these vulnerable areas. These solutions are an alternative to increased AC use, whose fossil fuel energy sources create waste heat that can exacerbate the heat island effect.

Although they may not look as impressive as other extreme climate events like hurricanes, heat waves can have devastating effects for human health. Heat stress, heat stroke, and other heat related illnesses such as cardiovascular complications are all associated with high temperatures. According to the Center for Climate and Energy Solutions, extreme heat is one of the leading causes of weather-related deaths in the US. In addition, heat waves can negatively affect air quality. High temperatures can increase atmospheric ozone levels and lead to increased use of indoor cooling systems, which in turn can emit pollution of their own.

California is highly urban, with 95% of its population in urban areas. It hosts one of the fastest growing populations in the United States. This speedy urbanization is especially of concern in regards to housing, income, and new climate extremes. In addition to the need for newer housing to be prepared for climate extremes such as heat waves, pre-existing housing infrastructure also need to be prepared. Our project is focusing on existing urban dynamics, with the aim of identifying which groups are the most vulnerable to high temperatures. These dynamics can be used to find which populations in different urban populations need to be focused on for assistance and can also be taken into consideration with new urbanizing populations.

In a recent study about the effects of urbanization on heat waves in the Fujian Province of Southeast China, researchers examined the changes in frequency, duration, magnitude, and timing of heat waves in this part of the country from 1971-2014. The study utilized a dynamical classification scheme using time-varying land use and cover maps to analyze the effects that urbanization had on the intensity of the heat wave events. The results of this study showed that the intensifying heat wave activities were especially pronounced in more densely populated and highly urbanized areas of the province. We expect to see a similar pattern in our research, with more intense heat events occurring in more densely populated urbanized areas in California.

A national vulnerability assessment of the United States was created by Reid, et al., 2009. It found that eight of the thirteen census tracts with the highest cumulative heat vulnerability were in the San Francisco Bay Area and another one in Los Angeles County. The Pacific Coast, especially California, is showing large areas of vulnerability. The study also found a strong correlation of living below the poverty line, and race other than white, with social/environmental vulnerability. Social/environmental vulnerability was one of the four factors that explained 75.7% of the variability in the original 10 vulnerability variables that they analyzed. 

Another study was done in Cologne, Germany to map and study its social vulnerability to heatwaves. The distribution, location, and general layout of building structures of different economic classes in the city were analyzed and compared to thermal maps of a summer day and night heat to see how different areas of the city were affected. Socioeconomic data, such as population and elderly distribution, was primarily used for mapping vulnerable communities for comparison with the thermal maps to understand which districts and groups were the most vulnerable. It was found that the center of the city and places that lacked greenery were the warmest and had the most susceptibility. Most of the population along with many of the elderly living alone were in these areas. It was assessed that elderly, unemployed, and dense populations, especially in the center of cities, are some of the more at risk and of concerned populations. This study indicates that while poverty and race are indicators of heat vulnerability, there are also other factors that influence vulnerability. 

A study on India used GIS to map and forecast potential areas of heat waves across India and different provinces. It qualified heat waves based on a several degree departure from the normal maximum temperature. The degree of departure and concern were mapped as heat wave alerts were labeled with increasing warming and severity as “No Severe Weather”, “Be Aware”, “Be Prepared”, and “Take Action”. The maps were developed so the public could access them online and be made aware of current and near future predictions of heat waves and their affected area. Their analysis’s setup can be reapplied to many present and future studies of heat waves, and provides an example of a further application of GIS mapping in informing urban planners and the public.

We decided to create a map based on some of the variables that contributed to these studies. They were quantified as layers and data tables. The studies that we observed indicated a need for mapping areas of vulnerability at multiple levels of scale. We picked California since it is an intermediately scale that has yet to be fully explored and mapped. Like the study on India and its heat waves, we decided to categorize heat waves as a level of departure from normal maximum temperature. We compared data from this layer to other layers of socioeconomic vulnerability. Many studies agreed upon socioeconomic vulnerability as an important factor in assessment of regions and populations at risk. We analyzed household income, race/ethnicity, and population density for this factor. Each is known to be population variables of much concern. Overlaying these variables with the heat wave data, we were able to assess which populations are vulnerable and map their locations, with the goal of assisting with their assessment.

How do population dynamics such as race and socioeconomic status contribute to identifying areas with high vulnerability to heat waves in California?

This map shows a raster layer containing information on temperature anomalies in the state of California. This map was created by subtracting the 30 year average temperature in California from the average temperature in 2018 - thus illustrating the abnormal temperature differences that occurred in 2018. As seen in the map, most areas in California had an average temperature in 2018 higher than the average temperature of the last 30 years. This supports the hypothesis that temperatures are generally increasing as a result of climate change.

The map to the left was constructed using CA Census data to illustrate the poverty levels of all counties. The green layers represent every 10th percent until the 50th percentile, and the diagonal lines illustrate the 50th-100th poverty percentiles as a means of examining average and above average poverty levels.

This map illustrates the CA ethnicity distribution through a predominant population display. It also serves as a guide for population distribution throughout California, with more tightly packed points indicating a higher population density.

This final map shows the combination of the temperature anomaly, poverty percentile, and California ethnicity distribution maps. With these three layers together, correlations could be observed in order to determine “vulnerable” areas. In many cases the crosshatch areas (indicating above 50th poverty percentile) lined up with orange/red areas (indicating higher temperature deviations) as expected. In many cases, clusters of points could be seen near these same areas from the ethnicity map, indicating higher population densities in these areas. Once the more "vulnerable" areas had been located, the predominant races present in these areas could be determined in order to analyze how ethnicity can also be associated with heat wave vulnerability.

Figure 1: The above graph depicts the poverty percentile against mean temperature deviation in degrees Fahrenheit. Poverty percentile is broken up at every ten percent. As seen above, the peak mean standard deviation can be seen in the 50th poverty percentile. Overall, the temperature deviation in the 50-100th percentiles (avg. 0.7588) is 125% greater than the 0-50th percentiles (0.6205). This shows that demographics in the 50th percentile and higher are experiencing higher rates of mean temperature deviation than populations in the 0-50th percentiles.

Figure 2: This graph shows the breakdown of mean temperature deviation sorted predominant population. The demographic that is experiencing the highest warming in the Hispanic population, with a mean warming of 0.699 deg F. Not far behind are the American Inuit/ Alaskan population with 0.628 deg F, tied (not a singular dominant ethnicity) at 0.593 deg F, and African American at 0.570 deg F. These populations are more vulnerable to and are experiencing higher rates of mean temperature deviation than other ethnic populations.

As the data shows, there are clearly populations that experienced a more significant increase in temperature deviations in 2018. Communities of color and low income areas are seeing the highest average rise in temperature, making them much more vulnerable to climate change and indicating that these communities should be high-priority targets for policy makers. However, there is more that needs to be talked about in terms of vulnerability than just the two above mentioned variables. Other considerations when looking at heat island effect can be age, amount of greenery in a city, and so on. The study we conducted is a rudimentary start to examining the increasing impact of global warming on cities and people. Every geographic location is undergoing area-specific climate crises and need to be examined with their particular demographics, climate patterns, and urbanization in mind. Heat related deaths are preventable, but cities and states need to be proactive by having an in depth understanding of heat waves and vulnerable communities and preparing emergency response protocol.

We could not have completed this project without the assistance of Professor Heilmayr and our Teaching Assistant, Erica Goto. Thank you both so much for all of your help!

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