Geology topics

Priyanka deSouza

Publications and source records attributed to Priyanka deSouza.

6 recordsLinked to original sources

USGS2026

Moving toward a more human-oriented analysis of urban heat: Examining differences of heat exposure intensity at busy commuting locations

Examining urban thermal environments has become a critical area of research spanning epidemiology, urban planning, and ecology. While traditional metrics like air temperature ( T air ) and satellite-derived surface temperature dominate urban heat studies, these measures often fail to reflect how people actually experience thermal exposure intensity. More human-oriented metrics, such as mean radiant temperature (MRT), and the wet bulb globe temperature (WBGT), better capture this lived experience, particularly at locations where people are likely to encounter outdoor heat, such as bus stops. Human demographics further complicate heat exposure, as access to cooling resources like trees and greenspaces can vary by neighborhood income. Our study addresses these complications by collecting thermal data across 60 commuting locations in Denver, Colorado in the summer. We evaluate (1) the extent to which more human-oriented metrics capture thermal exposure compared to T air and LST, and (2) how heat exposure varies by neighborhood income levels. We observed that bus stops in low-income neighborhoods had an MRT increase 2.8 °C compared wealthier neighborhoods, and that income-driven differences in MRT and WBGT strongly depended on bus stop aspect. After accounting for solar orientation, differences in MRT increased to as much as 6.3 °C at north-facing stops. Our results suggest tree canopy shade explains some observed heat exposure patterns, with south facing bus stops seeing a MRT and WBGT decrease of 0.42 °C and 0.11 °C from a percent increase in tree canopy. Interestingly, depending on bus stop aspect, nearby buildings can increase MRT and WBGT (facing east), or decrease MRT and WBGT (facing south) If planners aim to address this issue, consideration of bus stops, and land covers configuration may help.

Colorado↗

USGS2026

The surface is not superficial: Utilizing hyper-local thermal photogrammetry for pedestrian thermal comfort inquiry

The scale and magnitude of urban heating are often assessed using Satellite-Derived Land Surface Temperature (SD-LST). Yet, discrepancies in spatial resolution limit SD-LST’s ability to reflect pedestrian thermal experience, potentially leading to ineffective mitigation strategies. Hyper-local measurements of urban heat, defined as surface temperatures (T S ) at the scale of pedestrian activity (e.g., bus stops or street segments), may provide more accurate insights into thermal comfort. This study compares hyper-local ~0.01 m resolution T S collected via consumer-grade Forward-Looking Infrared (FLIR) thermography with resampled 30 m resolution SD-LST from Landsat 8 and 9 images to evaluate their utility in predicting thermal comfort indices across 60 bus stops in Denver, Colorado. During the summer of 2023, 270 FLIR measurements were collected over 19 dates, with a four-day subset ( n = 33) coinciding with Landsat imagery. FLIR T S averaged 25.12 ± 5.39 °C, while SD-LST averaged 35.90 ± 12.56 °C, a significant 10.77 °C difference (95% CI: 6.81–14.73; p < 0.001). FLIR T S strongly correlated with biometeorological metrics such as air temperature and mean radiant temperature (r > 0.8; p < 0.001), while SD-LST correlations were weak (r < 0.3). Linear mixed-effects models using FLIR T S explained 50–66% of the variance in thermal comfort indices and met ISO 7726 standards. Each 1 °C increase in FLIR TS predicted a 0.75 °C rise in mean radiant temperature. These results highlight hyper-local thermography as a reliable, low-cost tool for urban heat resilience planning.

Colorado↗

USGS2026

Weathering the ride: Associations of heat, smoke, precipitation, and ozone with bus ridership in Colorado

Weather and climate variability increasingly shape urban travel behavior, yet the short-term temporal dynamics and contextual modifiers of weather-transit relationships remain poorly understood. We analyzed system-wide hourly bus ridership in the Denver metropolitan area from June 2022 through September 2023 using fixed-effects negative binomial distributed lag nonlinear models with lags up to 24 h. Nonlinear exposure-response and lag-response functions were specified for hourly Universal Thermal Climate Index (UTCI) and precipitation, with additional indicators for daily ozone exceedance and wildfire smoke. Models adjust for hour-of-day, day-of-week, and month-year fixed effects, with standard errors clustered by day. Stratified analyses assess heterogeneity by time period, season, fare policy, and shelter availability, with interaction evaluated using Wald tests. Cold thermal stress was associated with the largest, most persistent reductions in ridership, with cumulative declines of −15.7% (95% CI: −26.0%, −4.0%) over 0-24 h. Precipitation was associated with sharp but transient reductions concentrated within 3-6 h (−8.4% to −9.8%), with little evidence of longer-term displacement. Heat associations were weaker and context-dependent, with modest short-run increases, but net same-day declines. Associations varied by time of day and season, were attenuated during the free-fare period, and differed by shelter availability. In contrast, ozone exceedance and wildfire smoke exhibited limited and inconsistent associations, with measurable reductions primarily during morning commute during heavier smoke conditions. Overall, transit ridership is more strongly associated with short-term weather exposure, than with ambient air quality. Fare policy and stop-level infrastructure modify these associations, highlighting actionable strategies to enhance transit resilience under increasing climate variability.

Colorado↗

USGS2025

Contribution of traffic emissions to PM2.5 concentrations at bus stops in Denver, Colorado

Individuals are routinely exposed to traffic-related air pollution on their commutes, which has significant health impacts. Mitigating exposure to traffic-related pollution is a key urban sustainability concern. In Denver, Colorado, low-income Americans are more likely to rely on buses and spend time waiting at bus stops. Evaluating the contribution of traffic emissions at bus stops can provide important information on risks experienced by these populations. We measured PM 2.5 constituents at eight bus stops and one background reference site in Denver, in the summer of 2023. Source profiles, including gasoline emissions from traffic, were estimated using Positive Matrix Factorization (PMF) analysis of PM 2.5 constituents collected at a Chemical Speciation Network site in our study region. The contributions of the different sources at each bus stop were estimated by regressing the vector of species concentrations at each site (dependent variable) on the source-profile matrix from the PMF analysis (independent variables). Traffic-related emissions (~2.5–6.6 μg/m 3 ) and secondary organics (~3–5 μg/m 3 ) contributed to PM 2.5 at the bus stops in our dataset. The highest traffic-related emissions-derived PM 2.5 concentrations were observed at bus stops near local sources: a gas station and a car wash. The contribution of traffic-related emissions was lower at the background site (~1 μg/m 3 ).

Colorado↗

USGS2025

A nationwide evaluation of crowd-sourced ambient temperature data

Growing concerns about heat in urban areas paired with the sparsity of weather stations have resulted in individuals drawing on data from citizen science sensor networks to fill in data gaps. The PurpleAir are the most widely-used low-cost air quality sensors in the contiguous United States with 14,777 deployed between 1 Jan 2017 and 20 July 2021. Although the air quality data from PurpleAir sensors have been widely studied, less attention has been paid to reported temperature. We compare temperature metrics reported by PurpleAir sensors with a gridded temperature product, the North American Land Data Assimilation System (NLDAS)-2, which although not a gold-standard measure of temperature, is widely used in epidemiologic research. We evaluate the lag between indoor and outdoor PurpleAir temperatures. We report associations of the difference between outdoor PurpleAir temperatures and NLDAS-2 temperatures, an indicator of degradation, and the duration of sensor operation. Finally, based on the temperature range recorded by the outdoor PurpleAir sensors vis.a.vis NLDAS-2 temperatures, we provide a list of 271 (2.5%) sensors potentially misclassified as outdoor and likely located indoors. We observed that outdoor PurpleAir sensors agreed well with NLDAS-2 (R2 > 0.82). This association broke down under warm conditions (daily average NLDAS ≥ 21.1oC). Landcover and climate zone were significant modifiers of the association between PurpleAir and NLDAS-2 temperature metrics with the poorest PurpleAir- NLDAS-2 agreement in urban areas. Indoor PurpleAir temperatures lagged hourly NLDAS temperatures by two hours across almost all climate zones. The mean difference in hourly PurpleAir and NLDAS-2 temperatures increased by 0.57oC for every operational year, suggesting that careful attention must be paid to degradation. Overall, we find for use in epidemiological studies, that the PurpleAir sensor data is a reliable metric of daytime mean air temperature, but researchers should be aware of its limitations when examining extreme heat, or when aggregating sensor data across multiple years.

Frontiers of Environmental Science and Engineering↗

USGS2025

High-resolution multi-pollutant mapping in Denver, Colorado

Characterizing traffic-related air pollutants (TRAPs), which significantly impact health, and greenhouse gases (GHGs) can be challenging in urban environments. Mobile monitoring has the potential to capture the spatial distribution of these pollutants. We present results from a campaign using the Denver Mobile Monitoring Laboratory (DMML) in the summer of 2023 when we measured ultrafine particles (UFPs), black carbon (BC), ozone (O 3 ), methane (CH 4 ) , and carbon dioxide (CO 2 ) concentrations in Denver, CO. Despite our campaign being brief, we obtained several interesting results. We observed elevated UFP and BC concentrations on major roads. In contrast, O 3 concentrations were higher on neighborhood streets and roads and in the industrial neighborhood of Commerce City. We consistently observed elevated CH 4 concentrations (>2.5 ppm) on highway I-70, suggesting the presence of a previously unknown major source of CH 4 . The CH 4 concentrations measured in our campaign did not align with those from an overlapping aerial campaign, suggesting that mobile monitoring is crucial to capture important, potentially intermittent CH 4 hotspots in cities. We evaluated if trees mitigated pollution concentrations, as planting trees is a key policy initiative of the city of Denver. We observed significant negative associations between tree canopy coverage and UFPs, BC, and CH 4 , and a positive association with O 3 when using linear mixed-effects regression models. Our work highlights the importance of investigating the role of tree canopy coverage to mitigate TRAPs.

Colorado↗