Measurements of Gross α- and ß-Activities of Archived PM2.5 and PM10 Teflon Filter Samples.

The adverse effects of ambient particulate matter (PM) on human health have been well demonstrated, but the underlying properties responsible for its toxicity are still unclear. We hypothesized that particulate radioactivity, which is due to the attachment of radioactive nuclides on particle surfaces, may be responsible for part of PM toxicity. We measured the gross α- and ß-activities for daily PM2.5 and PM10 filters collected at the Harvard Supersite in downtown Boston from 2005 to 2006 and calculated the radioactivities at the time of air sampling retrospectively based on a previously established formula. We examined the relationship between different radioactivities and compared our measurements to those measured at the Boston EPA RadNet Station. The results showed that the majority of PM10 radioactivity is associated with that of PM2.5 samples for both α-activity (98%) and ß-activity (83%). A strong linear relationship was observed between the α- and ß-activities for both PM2.5 [slope = 0.47 (±0.03); p-value < 0.0001] and PM10 [slope = 0.46 (±0.09); p-value < 0.0001] samples. Measurements at the Harvard Supersite and at EPA RadNet sites are highly correlated for both α-activities [slope = 0.17 (±0.02), p-value < 0.0001] and ß-activities [slope = 0.30 (±0.05), p-value < 0.0001]. Additionally, we identified several significant predictors for PM2.5 α-activities. This novel method we developed to measure α- and ß-activities from archived filters will make it possible to assess the retrospective particle radioactivity exposure for future epidemiological studies.

Secondary particles formed from the exhaust of vehicles using ethanol-gasoline blends increase the production of pulmonary and cardiac reactive oxygen species and induce pulmonary inflammation.

BACKGROUND: Ethanol vehicles release exhaust gases that contribute to the formation of secondary organic aerosols (SOA). OBJECTIVE: To determine in vivo toxicity resulting from exposure to SOA derived from vehicles using different ethanol-gasoline blends (E0, E10, E22, E85W, E85S, E100). METHODS: Exhaust emissions from vehicles using ethanol blends were delivered to a photochemical chamber and reacted to produce SOA. The aerosol samples were collected on filters, extracted, and dispersed in an aqueous solutions and intratracheally instilled into Sprague Dawley rats in doses of 700 µg/0.2 ml. After 45 min and 4 h pulmonary and cardiac chemiluminescence (CL) was measured to estimate the amount of reactive oxygen species (ROS) produced in the lungs and heart. Inflammation was measured by differential cell count in bronchoalveolar lavages (BAL). RESULTS: Statistically and biologically significant differences in response to secondary particles from the different fuel formulations were detected. Compared to the control group, animals exposed to SOA from gasoline (E0) showed a significantly higher average CL in the lungs at 45 min. The highest CL averages in the heart were observed in the groups exposed to SOA from E10 and pure ethanol (E100) at 45 min. BAL of animals exposed to SOA from E0 and E85S had a significant increased number of macrophages at 45 min. BAL neutrophil count was increased in the groups exposed to E85S (45 min) and E0 (4 h). Animals exposed to E0 and E85W had increased BAL lymphocyte count compared to the control and the other exposed groups. DISCUSSION: Our results suggest that SOA generated by gasoline (E0), followed by ethanol blends E85S and E85W, substantially induce oxidative stress measured by ROS generation and pulmonary inflammation measured by the recruitment of white blood cells in BAL.

Ambient PM2.5 temporal variation and source apportionment in Mbarara, Uganda.

Air pollution is the leading environmental cause of death globally, and most mortality occurs in resource-limited settings such as sub-Saharan Africa. The African continent experiences some of the worst ambient air pollution in the world, yet there are relatively little African data characterizing ambient pollutant levels and source admixtures. In Uganda, ambient PM2.5 levels exceed international health standards. However, most studies focus only on urban environments and do not characterize pollutant sources. We measured daily ambient PM2.5 concentrations and sources in Mbarara, Uganda from May 2018 through February 2019 using Harvard impactors fitted with size-selective inlets. We compared our estimates to publicly available levels in Kampala, and to World Health Organization (WHO) air quality guidelines. We characterized the leading PM2.5 sources in Mbarara using x-ray fluorescence and positive matrix factorization. Daily PM2.5 concentrations were 26.7 µg m-3 and 59.4 µg m-3 in Mbarara and Kampala, respectively (p<0.001). PM2.5 concentrations exceeded WHO guidelines on 58% of days in Mbarara and 99% of days in Kampala. In Mbarara, PM2.5 was higher in the dry as compared to the rainy season (30.8 vs 21.3, p<0.001), while seasonal variation was not observed in Kampala. PM2.5 concentrations did not vary on weekdays versus weekends in either city. In Mbarara, the six main ambient PM2.5 sources identified included (in order of abundance): traffic-related, biomass and secondary aerosols, industry and metallurgy, heavy oil and fuel combustion, fine soil, and salt aerosol. Our findings confirm that air quality in southwestern Uganda is unsafe and that mitigation efforts are urgently needed. Ongoing work focused on improving air quality in the region may have the greatest impact if focused on traffic and biomass-related sources.