Observing the spatial heterogeneities of NO₂ air pollution is an important first step in quantifying NO_X emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO₂ pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine‐scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operations and high traffic, and the relatively small emission sources in rural areas, such as power plants and mining operations. We then examine NO₂ columns by day‐of‐the‐week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively, than during weekdays. We also analyze the correlation of daily maximum 2‐m temperatures and NO₂ column amounts and find that NO₂ is larger on the hottest days (>32°C) as compared to warm days (26°C–32°C), which is in contrast to a general decrease in NO₂ with increasing temperature at moderate temperatures. Finally, we demonstrate that a linear regression fit of 2019 annual TROPOMI NO₂ data to annual surface‐level concentrations yields relatively strong correlation (R² = 0.66). These new developments make TROPOMI NO₂ satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations.

To identify and characterize localized urban heat- and cool-island signals embedded within the temperature field of a large urban-climate archipelago, fine-resolution simulations with a modified urbanized version of the WRF meteorological model were carried out as basis for siting fixed weather monitors and designing mobile-observation transects. The goal was to characterize variations in urban heat during summer in Los Angeles, California. Air temperatures measured with a shielded sensor mounted atop an automobile in the summers of 2016 and 2017 were compared to model output and also correlated to surface physical properties focusing on neighborhood-scale albedo and vegetation canopy cover. The study modeled and measured the temperature response to variations in surface properties that already exist in the real world, i.e., realistic variations in albedo and canopy cover that are attainable through current building and urban design practices. The simulated along-transect temperature from a modified urbanized WRF model was compared to the along-transect observed temperature from 15 mobile traverses in one area near downtown Los Angeles and another in an inland basin (San Fernando Valley). The observed transect temperature was also correlated to surface physical properties characterizations that were developed for input to the model. Both comparisons were favorable, suggesting that (1) the model can reliably be used in siting fixed weather stations and designing mobile-transect routes to characterize urban heat and (2) that except for a few cases with opposite co-varying influences, the correlations between observed temperature and albedo and between observed temperature and canopy cover were each negative, ranging from −1.0 to −9.0 °C per 0.1 increase in albedo and from −0.1 to −2.2 °C per 0.1 increase in canopy cover. Observational data from the analysis domains pointed to a wind speed threshold of 3 m/s. Below this threshold the variations in air temperature could be explained by land use and surface properties within a 500-m radius of each observation point. Above the threshold, air temperature was influenced by the properties of the surface within a 1-km upwind fetch. Of relevance to policy recommendations, the study demonstrates the significant real-world cooling effects of increasing urban albedo and vegetation canopy cover. Based on correlations between the observed temperature (from mobile transects) and surface physical properties in the study domains, the analysis shows that neighborhood-scale (500-m) cooling of up to 2.8 °C during the daytime can be achieved by increasing albedo. A neighborhood can also be cooled by up to 2.3 °C during the day and up to 3.3 °C at night by increasing canopy cover. The analysis also demonstrates the suitability of using fine-resolution meteorological models to design mobile-transect routes or site-fixed weather monitors in order to quantify urban heat and the efficacy of albedo and canopy cover countermeasures. The results also show that the model is capable of accurately predicting the geographical locations and the magnitudes of localized urban heat and cool islands. Thus the model results can also be used to devise urban-heat mitigation measures.

Nitrogen dioxide (NO₂) is a major urban air pollutant and is associated with new onset asthma among children worldwide. Since NO₂ concentrations are spatially heterogeneous and correlated with population, the spatial resolution of concentration estimates and disease burden calculations could strongly influence the magnitude and spatial distribution of estimated NO₂-attributable pediatric asthma (PA) cases. Here, we investigate the effect of spatial resolution of exposure and population data on estimated NO₂ attributable PA incidence. We use epidemiologically derived health impact functions to estimate NO₂-attributable asthma incidence for the U.S. and India, two countries with different degrees of urbanicity, using population and NO₂ concentration estimates at 100 m resolution and aggregated to coarser spatial resolutions: 500 m, 1 km, 10 km, and 100 km. Estimated NO₂-attributable PA burdens differ by <1% for resolutions of 100 m up to 1 km for both countries. However, performing the analysis at 10 km and 100 km results in 5% and 17% fewer new asthma cases among children in India and 6% and 32% fewer in the U.S., respectively. We performed a similar analysis for the 13 000 urban areas and present the results for the 500 most populated cities at 1 km and 10 km resolution, finding that the coarser resolution leads to lower estimated NO₂-attributable asthma incidence in nearly all cities, especially for cities with smaller land areas. We conclude that 1 km spatial resolution is a good balance between accuracy and computational efficiency in estimating NO₂-attributable asthma burdens at national and urban levels, and that coarser resolutions may result in underestimates.

Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOx emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO2 pollution in the Continental United States (CONUS). The high instrument sensitivity can differentiate the fine-scale spatial heterogeneities in urban areas, such as hotspots related to airport/shipping operations and high traffic areas, and the relatively small emission sources in rural areas, such as power plants and mining operations. We also examine NO2 columns by day-of-the-week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively than during weekdays. In cities with topographic features that inhibit dispersion, such as Los Angeles, there appears to be a pollution build-up from Monday through Friday, while cities which have better dispersion have more variability during weekdays. We also analyze the correlation of temperatures and NO2 column amounts and find that NO2 is larger on the hottest days (>32C) as compared to warm days (26C - 32C), which is in contrast to a general decrease in NO2 with increasing temperature at lower temperature bins. Finally, we compare column NO2 with estimates of surface PM2.5 and find fairly poor correlation, suggesting that NO2 and PM2.5 are becoming increasingly less correlated in CONUS. These new developments make TROPOMI NO2 satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations.

The effects of neighborhood-scale land use and land cover (LULC) properties on observed air temperatures are investigated in two regions within Los Angeles County: Central Los Angeles and the San Fernando Valley (SFV). LULC properties of particular interest in this study are albedo and tree fraction. High spatial density meteorological observations are obtained from 76 personal weather-stations. Observed air temperatures were then related to the spatial mean of each LULC parameter within a 500 m radius “neighborhood” of each weather station, using robust regression for each hour of July 2015. For the neighborhoods under investigation, increases in roof albedo are associated with decreases in air temperature, with the strongest sensitivities occurring in the afternoon. Air temperatures at 14:00–15:00 local daylight time are reduced by 0.31 °C and 0.49 °C per 1 MW increase in daily average solar power reflected from roofs per neighborhood in SFV and Central Los Angeles, respectively. Per 0.10 increase in neighborhood average albedo, daily average air temperatures were reduced by 0.25 °C and 1.84 °C. While roof albedo effects on air temperature seem to exceed tree fraction effects during the day in these two regions, increases in tree fraction are associated with reduced air temperatures at night.

Background: Combustion-related nitrogen dioxide (NO2) air pollution is associated with pediatric asthma incidence. We estimated global surface NO2 concentrations consistent with the Global Burden of Disease Study for 1990-2019 at 1km resolution, and concentrations and attributable pediatric asthma incidence trends in 13,189 cities from 2000-2019. Methods: We scaled an existing surface annual average NO2 concentrations dataset for 2010-2012 from a land use regression model (based on 5,220 NO2 monitors in 58 countries and land use variables) to other years using NO2 column densities from satellite and reanalysis datasets. We applied these concentrations to epidemiologically-derived concentration-response factors, population, and baseline asthma rates to estimate NO2-attributable pediatric asthma incidence. Findings: We estimated that 1.85 million (95% uncertainty interval: 0.93 – 2.8 million) new pediatric asthma cases were attributable to NO2 globally in 2019, two-thirds of which occurred in urban areas. The fraction of pediatric asthma incidence that is attributable to NO2 in urban areas declined from 20% in 2000 to 16% in 2019. Urban attributable fractions dropped in High-income (-41%), Latin America/Caribbean (-16%), Central Europe, Eastern Europe, and Central Asia (-13%), and Southeast Asia, East Asia, and Oceania (-6%), and rose in South Asia (+23%), Sub-Saharan Africa (+11%), and North Africa and Middle East (+5%) regions. The importance of NO2 concentrations, pediatric population size, and asthma incidence rates in driving these changes differs regionally. Interpretation: Despite improvements in some regions, combustion-related NO2 pollution continues to be an important contributor to pediatric asthma incidence globally, particularly in cities. Funding: Health Effects Institute, NASA