Sources, Modifiable Factors, and Spatiotemporal Variations of PM2.5
PM2.5 as well as various gaseous pollutants are harmful to both human health and the environment. In order to best mitigate the hazardous effects of these pollutants it is important to first understand them. This thesis explores (1) spatial and temporal evolution of emissions as well as (2) emission sources of PM2.5. The emission sources evaluated include both field measurements of primary sources (e.g. traffic and industrial) as well as laboratory investigations of less traditional sources of PM2.5 (e.g. emissions from volatile chemical products, VCPs). Through the use of state of the art laboratory instrumentation (e.g. PTR-MS and GC-MS) as well as lower-cost sensor networks in the field, a greater understanding of PM2.5 emissions, concentrations, and dispersion is obtained.
Air quality monitoring has traditionally been conducted using sparsely distributed, expensive reference monitors. In order to understand variations in PM2.5 on a finely resolved spatiotemporal scale a dense network of over 40 low-cost monitors was deployed throughout and around Pittsburgh, Pennsylvania, USA. Monitor locations covered a wide range of site types with varying traffic and restaurant density, varying influences from local sources, and varying socioeconomic (environmental justice, EJ) characteristics. Variability between and within site groupings was observed. Concentrations were higher near the source-influenced sites than the Urban or Suburban Residential sites. Gaseous pollutants (NO2 and SO2) were used to differentiate between traffic (higher NO2 concentrations) and industrial (higher SO2 concentrations) sources of PM2.5. Statistical analysis proved these differences to be significant (COD>0.2). The highest mean PM2.5 concentrations were measured downwind (east) of the two industrial facilities while background level PM2.5 concentrations were measured at similardistances upwind (west) of the point sources. We were not able to detect correlation between socioeconomic factors, including the fraction of non-white population and fraction of population living under the poverty line, to increases in PM2.5 or NO2 concentration with our sensor network. This however does not mean that such correlations do not exist either in this city or elsewhere, but rather they may need to be further explored with more sensitive sensor networks. The analysis conducted here highlights differences in PM2.5 concentration within site groupings that have similar land use thus demonstrating the utility of a dense sensor network. Our network captures temporospatial pollutant patterns that sparse regulatory networks cannot.
The low-cost sensor network was subsequently used to identify the impact of a decrease in emissions from modifiable factors on pollutant concentrations as a result of the COVID-19 pandemic. COVID-19 related closures offered a novel opportunity to observe and quantify the impact of activity levels of modifiable factors on ambient air pollution in real-time. We use data from a network of low-cost Real-time Affordable Multi-Pollutant (RAMP) sensor packages deployed throughout Pittsburgh, Pennsylvania along with data from EPA regulatory monitors. The RAMP locations were divided into four site groups based on land use. Concentrations of PM2.5, CO, and NO2 following the COVID-related closures at each site group were compared to measurements from “business-as-usual” periods. Overall, PM2.5 concentrations decreased across the domain by ~3 μg/m3. The morning rush-hour induced CO and NO2 concentrations at the High Traffic sites were both reduced by ~50%, which is consistent with observed reductions in commuter traffic (~50%). The morning rush-hour PM2.5 enhancement from traffic emissions was reduced nearly 100%, from 1.4 μg/m3 to ~0 μg/m3 across all site groups. There was no significant change in the industrial related intra-day variability of CO and PM2.5 at the Industrial sites following the COVID-related closures. If PM2.5 National Ambient Air Quality Standards(NAAQS) are tightened this natural experiment sheds light on to what extent reductions in traffic related emissions are able to aid in meeting more stringent regulations.
This thesis work then turns to laboratory experimentation to quantify emissions from an important source of PM2.5. Volatile chemical products (VCPs) have become an increasingly important source of Volatile Organic Compounds (VOCs) and Intermediate-Volatile Organic Compounds (IVOCs) emitted into urban environments. These VOCs play a potentially important role in national Secondary Organic Aerosol (SOA) formation. In this study we conduct headspace and extended emissions tests of paints to quantify the emission factors of I/VOCs over paint’s emission timescale. Then SOA yield predictions were calculated. We found that paints are not expected to be a long term emission source of I/VOCs as the majority of all I/VOCs measured reached background levels within two days post paint application. On a national scale paints emit 0.51 kg/person per year of I/VOCs. This means that 291g of I/VOCs are emitted per kg of paint used in the U.S. each year. The SOA mass yield from these emissions were calculated to be 4.7% [+/-2%]. Even though the majority of the I/VOC emissions from the paints were VOCs (59%), the majority of the SOA formed from paint emissions (68%) were from the IVOC portion of the paint emissions. Interestingly the I/VOC paint emissions come predominately from Oil-based paints (making up 87% of the SOA formed from paints) and Semi-Gloss Exterior paints (making up the remaining 13% of SOA formed from paints). Both of these paints are primarily used outdoors where theoretically all of their I/VOC emissions have the opportunity to interact with the ambient environment and form their full potential SOA.
PM2.5 is an important pollutant with unwanted negative effects on both human health and the environment. In order to best understand the impacts of PM2.5 and to limit those impacts weneed to first understand where it comes from and how concentrations change over time and space. The work in this thesis addresses those two questions.
- Doctor of Philosophy (PhD)