Assessing Inequitable Urban Heat Islands and Air Pollution Disparities with Low-Cost Sensors in Richmond, Virginia

Air pollution and the urban heat island effect are consistently linked to numerous respiratory and heat-related illnesses. Additionally, these stressors disproportionately impact low-income and historically marginalized communities due to their proximity to emissions sources, lack of access to green space, and exposure to other adverse environmental conditions. Here, we use relatively low-cost stationary sensors to analyze PM2.5 and temperature data throughout the city of Richmond, Virginia, on the ten hottest days of 2019. For both hourly means within the ten hottest days of 2019 and daily means for the entire record for the year, the temperature was found to exhibit a positive correlation with PM2.5. Analysis of hourly means on the ten hottest days yielded a diurnal pattern in which PM2.5 levels peaked in the early morning and reached their minima in the mid-afternoon. Spatially, sites exhibiting higher temperatures consistently had higher PM2.5 readings, with vulnerable communities in the east end and more intensely developed parts of the city experiencing significantly higher temperatures and PM2.5 concentrations than the suburban neighborhoods in the west end. These findings suggest an uneven distribution of air pollution in Richmond during extreme heat events that are similar in pattern but less pronounced than the temperature differences during these events, although further investigation is required to verify the extent of this relationship. As other studies have found both of these environmental stressors to correlate with the distribution of green space and other land-use factors in cities, innovative and sustainable planning decisions are crucial to the mitigation of these issues of inequity going forward

Assessing Inequitable Urban Heat Islands and Air Pollution Disparities with Low-Cost Sensors in Richmond, Virginia

Air pollution and the urban heat island effect are consistently linked to numerous respiratory and heat-related illnesses. Additionally, these stressors disproportionately impact low-income and historically marginalized communities due to their proximity to emissions sources, lack of access to green space, and exposure to other adverse environmental conditions. Here, we use relatively low-cost stationary sensors to analyze PM2.5 and temperature data throughout the city of Richmond, Virginia, on the ten hottest days of 2019. For both hourly means within the ten hottest days of 2019 and daily means for the entire record for the year, the temperature was found to exhibit a positive correlation with PM2.5. Analysis of hourly means on the ten hottest days yielded a diurnal pattern in which PM2.5 levels peaked in the early morning and reached their minima in the mid-afternoon. Spatially, sites exhibiting higher temperatures consistently had higher PM2.5 readings, with vulnerable communities in the east end and more intensely developed parts of the city experiencing significantly higher temperatures and PM2.5 concentrations than the suburban neighborhoods in the west end. These findings suggest an uneven distribution of air pollution in Richmond during extreme heat events that are similar in pattern but less pronounced than the temperature differences during these events, although further investigation is required to verify the extent of this relationship. As other studies have found both of these environmental stressors to correlate with the distribution of green space and other land-use factors in cities, innovative and sustainable planning decisions are crucial to the mitigation of these issues of inequity going forward

Thermal inequity in Richmond, VA: The effect of an unjust evolution of the urban landscape on urban heat islands

The urban heat island (UHI) effect is caused by intensive development practices in cities and the diminished presence of green space that results. The evolution of these phenomena has occurred over many decades. In many cities, historic zoning and redlining practices barred Black and minority groups from moving into predominately white areas and obtaining financial resources, a practice that still affects cities today, and has forced these already disadvantaged groups to live in some of the hottest areas. In this study, we used a new dataset on the spatial distribution of temperature during a heat wave in Richmond, Virginia to investigate potential associations between extreme heat and current and historical demographic, socioeconomic, and land use factors. We assessed these data at the census block level to determine if blocks with large differences in temperature also had significant variation in these covariates. The amount of canopy cover, percent impervious surface, and poverty level were all shown to be strong correlates of UHI when analyzed in conjunction with afternoon temperatures. We also found strong associations of historical policies and planning decisions with temperature using data from the University of Richmond’s Digital Scholarship Lab’s “Mapping Inequality” project. Finally, the Church Hill area of the city provided an interesting case study due to recent data suggesting the area’s gentrification. Differences in demographics, socioeconomic factors, and UHI were observed between north and (more gentrified) south Church Hill. Both in Church Hill and in Richmond overall, our research found that areas occupied by people of low socioeconomic status or minority groups disproportionately experienced extreme heat and corresponding impacts on health and quality of life

Emotion-Dependent Functional Connectivity of the Default Mode Network in Adolescent Depression

BACKGROUND: Functional magnetic resonance imaging (fMRI) research suggests that both adult and adolescent major depressive disorder (MDD) is marked by aberrant connectivity of the default mode network (DMN) during resting-state. However, emotional dysresgulation is also a key feature of MDD. No studies to date have examined emotion-related DMN pathology in adolescent depression. Comprehensively understanding the dynamics of DMN connectivity across brain states in depressed individuals with short disease histories could provide insight into the etiology of MDD. METHODS: We collected fMRI data during an emotion identification task and also during resting-state from 26 medication-free adolescents (13-17 years) with MDD and 37 wellmatched healthy controls (HCL). We examined between-group differences in blood oxygenation level-dependent task responses, emotion-dependent, and resting-state functional connectivity of the two primary nodes of the DMN: medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). Additionally, we examined between-group differences in DMN functional connectivity and its relationship to depression severity. RESULTS: Relative to HCL, unmedicated MDD adolescents demonstrated reduced mPFC and PCC emotion-related deactivation and greater mPFC and PCC emotion-dependent functional connectivity with precuneus, cingulate gyrus, and striatum/subcallosal cingulate gyrus. Importantly, PCC-subcallosal cingulate connectivity remained inflexibly elevated in MDD versus HCL during resting-state. Lastly, stronger PCC emotion-dependent functional connectivity was associated with greater depression severity and an earlier age of depression onset. CONCLUSIONS: Adolescent depression is associated with inflexibly elevated DMN connections. Given recent evidence of DMN maturation throughout adolescence, our findings suggest that early-onset depression adversely impacts normal development of functional brain networks