## 3 Results
### Average Afternoon Temperature vs. 1937 Home Owners' Loan Corporation Risk Ratings
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Variable** & **Q1 Average** & **Q4 Average** & \
\begin{tabular}{c} **Temperature Difference** \\ \({}^{\circ}\)**C (Q4–Q1)** \\ \end{tabular} &
\begin{tabular}{c} \(t\)**-Test** \\ \(p\)**-Value** \\ \end{tabular} \\ \hline Impervious surface (\%) & 17.38 & 52.71 & 1.01 & \(3.18\times 10^{-19}\) \\ \hline Canopy cover (\%) & 13.76 & 47.87 & \(-0.96\) & \(1.36\times 10^{-18}\) \\ \hline Redlining C + D (\%) & 0 & 83.79 & 0.53 & \(3.15\times 10^{-6}\) \\ \hline Drove alone to work (\%) & 47.5 & 88.13 & \(-0.51\) & \(4.27\times 10^{-6}\) \\ \hline Below poverty level (\%) & 18.21 & 30.98 & 0.51 & 0.0015 \\ \hline Median household income (\$) & 22,615 & 98,945 & \(-0.41\) & 0.0008 \\ \hline Per capita income (\$) & 11,293 & 57,490 & \(-0.37\) & 0.002 \\ \hline White population (\%) & 7.6 & 89.31 & \(-0.31\) & 0.007 \\ \hline Detached housing (\%) & 12.31 & 93.13 & \(-0.31\) & 0.009 \\ \hline Green space (\%) & 0 & 17.81 & \(-0.3\) & 0.0097 \\ \hline Black population (\%) & 6.09 & 86.9 & 0.27 & 0.0156 \\ \hline Redlining A + B (\%) & 0 & 55.53 & \(-0.26\) & 0.011 \\ \hline Non-Hispanic white population (\%) & 2.43 & 88.46 & \(-0.26\) & 0.0158 \\ \hline Attached housing (\%) & 0 & 20.07 & 0.25 & 0.024 \\ \hline Bachelor’s degree or more (\%) & 6.108 & 74.6 & \(-0.11\) & 0.248 \\ \hline Hispanic population (\%) & 0.056 & 19.2 & 0.09 & 0.378 \\ \hline \hline \end{tabular}  
* Variables were sourced from the 2018 American Community Survey (ACS), the 2016 National Land Cover Database (NLCD), 2017 green space data from the Richmond Planning and Development Office, and historical 1937 data on redlining from the Home Owners’ Loan Corporation, Division of Research and Statistics. The table lists variables from most to least significant. Q1 and Q4 averages indicate the average value of the variable within those quartiles. The temperature difference (\({}^{\circ}\)C) shows the heat difference between the Q1 average temperature and the Q4 average temperature. Positive values indicate that Q4 blocks are warmer than Q1 blocks and negative values indicate that Q1 blocks are warmer than Q4 blocks.  
\end{table} 
Table 1: Quartile analyses of the 16 variables associated with afternoon temperature. Figure 9: Comparison of variables associated with average afternoon temperature throughout Richmond, VA. Percent impervious surface, percent canopy cover, percent of a block rated Category C or D, percent drove alone to work, percent below the poverty level, and median household income produced some of the strongest associations with afternoon temperature. To evaluate the changes in the aforementioned variables over time, American Census Data from 2010 was analyzed and compared to 2018 data. In 2010, the two strongest variables associated with afternoon temperature were median household income and percent drove alone to work (Table 2). This was consistent with our 2018 analyses, in which these two variables also had the strongest associations with temperature. The magnitude of the temperature differences between the Q1 and Q4 neighborhoods were also similar between 2010 and 2018 at around 0.5 \({}^{\circ}\)C. Four out of the seven demographic variables analyzed for 2010 had a significant relationship with temperature at a significance level of \(p<0.01\) and an additional two variables were significant at a level of \(p<0.05\). The 2010 variables were only sourced from ACS data and did not include the redlining or land use and land cover variables. Figure 10: Distribution of white and Black populations throughout Richmond, VA, compared to the average afternoon temperature. In each map, the larger the circle is, the greater the population of the corresponding race. The White Alone map indicates that the greatest portion of white residents live toward the western end of the city, while the Black Alone map indicates that the greatest portion of Black residents live toward the eastern end. Notable changes occurred in the demographic data from 2010 to 2018.