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Cities in the United States have announced initiatives to become more sustainable, healthy, resilient, livable, and environmentally friendly. However, indicators for measuring all outcomes related to these targets and the synergies between them have not been well defined or studied. One such relationship is the linkage between air quality with emotional well-being (EWB) and neighborhood infrastructure. Here, regulatory monitoring, low-cost sensors (LCSs), and air quality modeling were combined to assess exposures to PM 2.5 and traffic-related NO x in 6 Minneapolis, MN, neighborhoods of varying infrastructure parameters (median household income, urban vs suburban, and access to light rail). Residents of the study neighborhoods concurrently took real-time EWB assessments using a smart phone application, Daynamica, to gauge happiness, tiredness, stress, sadness, and pain. Both LCS PM 2.5 observations and mobile-source-simulated NO x were calibrated using regulatory observations in Minneapolis. No statistically significant (α = 0.05) PM 2.5 differences were found between urban poor and urban middle-income neighborhoods, but average mobile-source NO x was statistically significantly (α = 0.05) higher in the 4 urban neighborhoods than in the 2 suburban neighborhoods. Close proximity to light rail had no observable impact on average observed PM 2.5 or simulated mobile-source NO x . Home-based exposure assessments found that PM 2.5 was negatively correlated with positive emotions such as happiness and to net affect (the sum of positive and negative emotion scores) and positively correlated (ie, a higher PM 2.5 concentration led to higher scores) for negative emotions such as tiredness, stress, sadness, and pain. Simulated mobile-source NO x , assessed from both home-based exposures and in situ exposures, had a near-zero relationship with all EWB indicators. This was attributed to low NO x levels throughout the study neighborhoods and at locations were the EWB-assessed activities took place, both owing to low on-road mobile-source NO x impacts. Although none of the air quality and EWB responses were determined to be statistically significant (α = 0.05), due in part to the relatively small sample size, the results are suggestive of linkages between air quality and a variety of EWB outcomes.

In response to the emergence of COVID-19 during Spring 2020, many countries implemented nationwide lockdowns and mandatory stay-at-home orders, which resulted in historically clean ambient air quality. However, in many parts of the world, biomass burning for cooking is a common activity, and in India specifically, it has been implicated as the leading contributor to indoor and ambient PM _2.5 , and its activity was not stopped and likely increased during lockdowns. Here, we first estimate baseline and lockdown PM _2.5 exposures specific to India using new, nationwide time-use survey data coupled with fine-scale PM _2.5 estimates within various microenvironments. We then extend this framework to estimate the population globally that will have experienced higher PM _2.5 exposures during lockdowns, due both to an increase in residential biomass burning activity as well as the entire day being spent in the more-polluted home environment for biomass fuel using households. Sixty five percent of Indians, the percent that uses biomass fuels for cooking, were exposed to higher PM _2.5 levels during the lockdown compared to their modeled baseline exposures, with the average modeled exposure increasing by 13% (95% distribution: 8–26) (from 116 (82–157) to 131 (104–170) μ g m ^−3 ). We further leverage this exposure framework to present India’s most comprehensive, to date, PM _2.5 exposure disparity and environmental justice assessment; although women were still exposed to the highest levels of PM _2.5 during the lockdown (from 135 (91–191) μ g m ^−3 baseline to 147 (106–200) μ g m ^−3 during the lockdown; 8.8% (5–18) increase), the demographic groups that experienced the highest exposure increases were working-age men and school-age children, whose average modeled exposures increased by 24% (18–48) (from 88 (63–118) to 108 (94–139) μ g m ^−3 ) and 18% (8–31) (from 98 (75–134) to 115 (98–145) μ g m ^−3 ), respectively. Globally, we conservatively estimate that 34.5% (21–51) of the global population observed increased PM _2.5 exposures during COVID-19 lockdowns, concentrated in low-income regions with high biomass usage. There have been a number of clean-cooking initiatives introduced in India and throughout the world to replace biomass cookstoves, but the finding that PM _2.5 exposures increased for the majority of Indians and a third of the global population—driven largely by residential biomass burning for cooking—during a period of historically clean ambient air quality, re-emphasizes the urgent need to further address clean cooking interventions to reduce PM _2.5 exposures and in turn improve health outcomes.

Emissions from on-road mobile sources have historically been an important anthropogenic contributor to ambient air pollution leading to high levels of air pollution near major roadways. The U.S. EPA recently implemented the Near-Road (monitoring) Network to measure NO _2 concentrations by high-traffic roadways in urban centers throughout the U.S., as these locations were believed to characterize worst-case human exposures to traffic-related air pollutants. Many near-road sites also include PM _2.5 and CO measurements, which along with the NO _2 observations, were compared in a pairwise manner against non-near-road monitors located within the city-scale boundary. After controlling for primary emissions from the target highways, we found the PM _2.5 concentration difference (i.e. near-road concentration minus non-near-road site concentration) between the near-road and non-near-road urban sites to be δ = 0.42 µ g m ^−3 ( H _0 : µ _diff = 0; H _a : µ _diff > 0 ( µ _non-near-road > µ _near-road ); p = 0.051; α = 0.05, 95% CI: −0.08–0.90 µ g m ^−3 , n = 35 comparisons). NO _2 and CO levels were on average higher at the near-road sites compared to the non-near-road urban sites by 5.0 (95% CI: 3.4–6.5) ppb (n = 44 comparisons) and 9.2 × 10 ^−2 ( 95% CI: 0.04–0.14) ppm (n = 42 comparisons), respectively. The average PM _2.5 difference found here is 5%, and at 14 of the 35 (∼40%) urban monitor comparisons and 28 of the 72 (∼39%) overall comparisons, PM _2.5 is actually higher at the non-near-road site relative to its near-road pair. Cleaner vehicle fleets, formation of secondary PM from on-road emissions occurring downwind (i.e. away from the road), decreased secondary organic aerosol (SOA) formation rates in the near-road environment, the prevalence of other low-volume vehicular and local, non-vehicular sources of emissions at the non-near-road sites (e.g. railyards, truck yards, ports, biomass-fueled heating, backyard barbecuing, and commercial cooking, etc) and local meteorology (e.g. wind speed and wind direction) explain this finding. The wintertime PM _2.5 concentration difference was higher than the other seasons, likely a result of higher primary PM _2.5 tailpipe emissions and lower temperatures that both reduced near-road PM volatility and decreased photochemical activity resulting in lower SOA production at the urban scale. Further, all near-road NO _2 and CO concentrations were below the annual and hourly NAAQS, while eight (most of which were in wildfire-prone locations) of the 94 PM _2.5 sites used in this study were above the annual National Ambient Air Quality Standards. In addition, strong agreement with both annual average daily traffic and fleet-equivalent AADT were found for near-road NO2 and CO concentrations, while weaker, but still positive relationships were found for near-road PM _2.5 levels. Lastly, same observational data was used to assess on-road mobile source emission estimates from the EPA National Emission Inventory, and analysis of the observations are in rough agreement with the current ratio of NO _x to CO emissions from on-road mobile sources.

The Taj Mahal—an iconic World Heritage monument built of white marble—has become discolored with time, due, in part, to high levels of particulate matter (PM) soiling its surface (Bergin et al 2015 Environ. Sci. Technol. http://dx.doi.org/10.1021/es504005q 49 http://dx.doi.org/10.1021/es504005q ). Such discoloration has required extensive and costly treatment (2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi) and despite previous interventions to reduce pollution in its vicinity, the haze and darkening persists (Bergin et al 2015 Environ. Sci. Technol. http://dx.doi.org/10.1021/es504005q 49 http://dx.doi.org/10.1021/es504005q ; 2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi). PM responsible for the soiling has been attributed to a variety of sources including industrial emissions, vehicular exhaust and biomass burning, but the contribution of the emissions from the burning of open municipal solid waste (MSW) may also play an important role. A recent source apportionment study of fine particulate matter (PM _2.5 ) at the Taj Mahal showed biomass burning emissions, which would include MSW emissions, accounted for nearly 40% of organic matter (OM)—a component of PM—deposition to its surface (Bergin et al 2015 Environ. Sci. Technol. http://dx.doi.org/10.1021/es504005q 49 http://dx.doi.org/10.1021/es504005q ); dung cake burning, used extensively for cooking in the region, was the suggested culprit and banned within the city limits (2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi), although the burning of MSW, a ubiquitous practice in the area (Nagpure et al 2015 Environ. Sci. Technol. http://dx.doi.org/10.1021/acs.est.5b03243 49 http://dx.doi.org/10.1021/acs.est.5b03243 ), may play a more important role in local air quality. Using spatially detailed emission estimates and air quality modeling, we find that open MSW burning leads to about 150 (±130) mg m ^−2 yr ^−1 of PM _2.5 being deposited to the surface of the Taj Mahal compared to about 12 (±3.2) mg m ^−2 yr ^−1 from dung cake burning. Those two sources, combined, also lead to an estimated 713 (377–1050) premature mortalities in Agra each year, dominated by waste burning in socioeconomically lower status neighborhoods. An effective MSW management strategy would reduce soiling of the Taj Mahal, improve human health, and have additional aesthetic benefits.