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Unwatched Pollution: The Effect of Incomplete Monitoring on Air Quality. (2017). Zou, Eric.
In: 2017 Annual Meeting, July 30-August 1, Chicago, Illinois.
RePEc:ags:aaea17:258274.

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  1. The effects of increased pollution on COVID-19 cases and deaths. (2021). Johnson, Kathryn R ; Persico, Claudia L.
    In: Journal of Environmental Economics and Management.
    RePEc:eee:jeeman:v:107:y:2021:i:c:s0095069621000140.

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  23. [30] United States Environmental Protection Agency. 1997a. Memorandum: Guidelines for granting schedule exemptions for PM10 monitoring. <https://www3.epa. gov/ttnamti1/files/ambient/pm25/pm10_wav.pdf> [31] United States Environmental Protection Agency. 1997b. Guidance for network design and optimum site exposure for PM2.5 and PM10. EPA-454/R-99-022.
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  35. A PM 2.5 sampler may also follow the 1/6day schedule if it is a collocating sampler to a 1/3day or a 1/1day sampler. By the EPA's regulation, for each reporting organization (usually a state), 25% of its PM samplers are required to be collocated with an identical samplers to estimate data precision, and these collocating samplers sample at the 1/6day rate (40 CFR Part 58). This rate dropped to 15% in March 2003, when EPA decided that reduced collocation rate would not significantly deteriorate precision estimation. In principle, PM data collected by collocating samplers should not be used toward NAAQS comparison, unless the corresponding main sampler malfunctioned or did not collect a valid sample on a sampling day. Also, states should be clear about which samplers are collocators when reporting data to the AQS.
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  36. As an alternative to the TRI, I use data from the EPA's 2011 National Emission Inventory (NEI). The data is created to support the EPA's National Ambient Air Quality Standards program under the Clean Air Act. Maintained by the EPA's Office of Air Quality Planning and Standards, the NEI combines polluter information from a variety of data sources, including the TRI, and provides the most comprehensive list of polluters in the US. The advantage of this data over the TRI is that it allows me to directly observe PM emitters. The disadvantage of the NEI 2011 data is that it only provides a snapshot of polluters in 2011 and so I'm forced to assume that polluter profiles stay unchanged over the study period of 2001 to 2013.
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  37. Figure 7: Issuance of Action Day Advisories by Days in 1/6day Monitoring Cycle Panel A: Raw distribution 10 12.5 15 17.5 20 Percent of action days -3-2 -1 0 1 2 Days since scheduled monitoring Off days avg. = 16.5% Panel B: Consecutive Action Days adjustment 10 12.5 15 17.5 20 Percent of action days -3-2 -1 0 1 2 Days since scheduled monitoring Off days avg. = 16.4% Notes: Panel A shows the raw distribution of air pollution action day issuance by days in the 1/6day cycle. Day 0 marks the scheduled sampling day. Panel B shows adjusted distribution by including only the first issuance for consecutive action days episode. The sample includes all action day issuances reported to the EPA’s airnow program from 2004 to 2013, aggregated to the core based statistical area (CBSA) by day level. See the text for more details.
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  38. First, I observe controlled burning events from the Federal Emergency Management Agency's (FEMA) National Fire Incident Reporting System (NFIRS) Version 5.0. For each fire incident, NFIRS contains a type code which I use to identify controlled burning (incident code 632). Other key variables included in the NFIRS are the ZIP Code location and date of the incident. In computing distance from fires to PM monitors, I assume that all fires occur at the centroid of the ZIP Code location. Using NFIRS I identify 42,449 controlled burning incidents at the ZIP Code-daily level from 2001 to 2013.
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  39. One such example would be that selective approval of control burning plan takes into account wind direction. In that case, an average effect estimate as used in this subsection will be diluted. a D. Additional Figures and Tables Figure D.1: 10km×10km Level Aerosol Concentration, 2001-2013 Average Notes: Map shows 13 year (2001-2013) average 10km×10km pixel level aerosol concentration. Legend presents ranges of deciles aerosol concentration. Number of pixels in each decile in parentheses.
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  40. Specifically, collocating samplers should all have a Parameter Occurrence Code (POC) of “2” in the AQS data whereas the main sampler has a POC of “1”. In practice, however, states had substantial misconceptions about how data from collocating samplers should be treated, e.g. in some cases states reported collocators' PM data for NAAQS comparison even when the main sampler has already collected valid samples; wrong POCs were also assigned to samplers. See EPA's memorandum Use of Collocated PM2.5 Data and Parameter Occurrence Codes (POCs) which can be found here: <https://www.epa.gov/sites/production/files/2015-09/documents/25colo_0.pdf>. For this reason, in the 4 main analysis I do not attempt to identify and exclude collocating PM samplers from the estimation sample. I do confirm that near sites with standalone 1/6day samplers (i.e. sites where the 1/6day sampler must not be a collocator) the gaming effect is stronger.
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