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1.
Bull Atmos Sci Technol ; 1(3-4): 491-514, 2020.
Article in English | MEDLINE | ID: mdl-38624442

ABSTRACT

The first goal of this study is to quantify the magnitude and spatial variability of air quality changes in the USA during the COVID-19 pandemic. We focus on two pollutants that are federally regulated, nitrogen dioxide (NO2) and fine particulate matter (PM2.5). NO2 and PM2.5 are both primary and secondary pollutants, meaning that they can be emitted either directly into the atmosphere or indirectly from chemical reactions of emitted precursors. NO2 is emitted during fuel combustion by all motor vehicles and airplanes. PM2.5 is emitted by airplanes and, among motor vehicles, mostly by diesel vehicles, such as commercial heavy-duty diesel trucks. Both PM2.5 and NO2 are also emitted by fossil-fuel power plants, although PM2.5 almost exclusively by coal power plants. Observed concentrations at all available ground monitoring sites (240 and 480 for NO2 and PM2.5, respectively) were compared between April 2020, the month during which the majority of US states had introduced some measure of social distancing (e.g., business and school closures, shelter-in-place, quarantine), and April of the prior 5 years, 2015-2019, as the baseline. Large, statistically significant decreases in NO2 concentrations were found at more than 65% of the monitoring sites, with an average drop of 2 parts per billion (ppb) when compared to the mean of the previous 5 years. The same patterns are confirmed by satellite-derived NO2 column totals from NASA OMI, which showed an average drop in 2020 by 13% over the entire country when compared to the mean of the previous 5 years. PM2.5 concentrations from the ground monitoring sites, however, were not significantly lower in 2020 than those in the past 5 years and were more likely to be higher than lower in April 2020 when compared with those in the previous 5 years. After correcting for the decreasing multi-annual concentration trends, the net effect of COVID-19 at the ground stations in April 2020 was a reduction in NO2 concentrations by - 1.3ppb and a slight increase in PM2.5 concentrations by + 0.28 µg/m3. The second goal of this study is to explain the different responses of these two pollutants, i.e., NO2 was significantly reduced but PM2.5 was nearly unaffected, during the COVID-19 pandemic. The hypothesis put forward is that the shelter-in-place measures affected people's driving patterns most dramatically, thus passenger vehicle NO2 emissions were reduced. Commercial vehicles (generally diesel) and electricity demand for all purposes remained relatively unchanged, thus PM2.5 concentrations did not drop significantly. To establish a correlation between the observed NO2 changes and the extent to which people were actually sheltering in place, thus driving less, we used a mobility index, which was produced and made public by Descartes Labs. This mobility index aggregates cell phone usage at the county level to capture changes in human movement over time. We found a strong correlation between the observed decreases in NO2 concentrations and decreases in human mobility, with over 4 ppb decreases in the monthly average where mobility was reduced to near 0 and around 1 ppb decrease where mobility was reduced to 20% of normal or less. By contrast, no discernible pattern was detected between mobility and PM2.5 concentrations changes, suggesting that decreases in personal-vehicle traffic alone may not be effective at reducing PM2.5 pollution.

3.
Dela J Public Health ; 3(5): 6-11, 2017 Oct.
Article in English | MEDLINE | ID: mdl-34466937

ABSTRACT

Ozone is the only pollutant that exceeds national and state standards in Delaware. Using observations and two different climate models, the number of high-ozone days (days exceeding 70 ppb based on the 8-hour average in Delaware) is investigated for the late 20th and early to mid-21st centuries using a synoptic typing methodology, which relates surface conditions conducive to high-ozone events to atmospheric circulation. High-ozone days are associated with the absence of precipitation and southwesterly to west-northwesterly flow over Delaware, which tend to bring higher daily mean temperatures (exceeding 25.5°C). Models underestimate the number of observed high-ozone days in the 20th century, because the models do not include the effects of ozone regulation, which has decreased the number of ozone days. Meanwhile, higher concentrations of greenhouse gases and the resulting higher temperatures favor increased ozone days, an effect that is captured by the models. As temperatures continue to rise in the 21st century, climate projections indicate that high-ozone conditions will occur more frequently. By mid-century, the number of high-ozone days is projected to increase by about an extra day every two years, which is faster than it was in the previous 30 years. Thus global warming cancels out a quarter of the progress made in improving air quality in the state of Delaware, meaning that the air quality in mid-century is expected to be the same as it was around 2006. In a warming world, air quality standards will need to stricter to maintain or reduce the number of high-ozone events in Delaware.

5.
Proc Natl Acad Sci U S A ; 109(39): 15679-84, 2012 Sep 25.
Article in English | MEDLINE | ID: mdl-23019353

ABSTRACT

Wind turbines convert kinetic to electrical energy, which returns to the atmosphere as heat to regenerate some potential and kinetic energy. As the number of wind turbines increases over large geographic regions, power extraction first increases linearly, but then converges to a saturation potential not identified previously from physical principles or turbine properties. These saturation potentials are >250 terawatts (TW) at 100 m globally, approximately 80 TW at 100 m over land plus coastal ocean outside Antarctica, and approximately 380 TW at 10 km in the jet streams. Thus, there is no fundamental barrier to obtaining half (approximately 5.75 TW) or several times the world's all-purpose power from wind in a 2030 clean-energy economy.


Subject(s)
Climate , Models, Theoretical , Wind
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