We recently wrote a post about a handy Excel workbook you can use to query elevations for a set of coordinates in the Google Maps Application Programming Interface (API). Here, we’ll go over how to do the same thing using Python.
One Air Sciences’ team member’s graduate research at Portland State University (Oregon) clocked a lot of time with a tabletop ultraviolet (UV)-visible spectrometer. This equipment measures how much a chemical substance absorbs light. You see, Matt had painstakingly prepared hundreds of passive air pollution monitoring devices to conduct high-density measurements of nitrogen dioxide (NO2) in east Portland. To “extract” the adsorbed NO2 from the devices, an aqueous solution was prepared with spectral properties that changed with the amount of NO2 present. Perfect, tedious work for a grad student, but it ultimately produced some gratifying results.
In our last post on this topic we left off asking the question, “given how much wildland fires change year to year, how do we build an emissions inventory (EI) that is representative of a multi-year period, or a future period?” This is a confounding problem not only for the Regional Haze planning process but for any air quality planning exercise that a regulatory agency engages with.
In 2011, the United States Environmental Protection Agency (EPA) promulgated National Emissions Standards for Hazardous Air Pollutants (NESHAP) for gold ore processing and production facilities. This rule is set forth in Volume 40 of the Code of Federal Regulations (CFR) Part 63 Subpart EEEEEEE (40 CFR 63 Subpart EEEEEEE). These gold ore processing and production facilities are required to obtain a federal permit under 40 CFR part 70 or 40 CFR part 71 (Title V operating permit), even if they are not associated with a major source.
The Oregon Department of Environmental Quality (DEQ) has issued the final Oregon Nonroad Diesel Equipment Survey and Emissions Inventory, completed with the help of Eastern Research Group, Inc. (ERG); Good Company LLC; and Oak Leaf Environmental, Inc. The aim of this study was to generate Oregon-specific data of non-road equipment characteristics, such as: engine age, activity rate, fuel consumption, and geographic distribution.