Kevin Zembower
2023-Dec-12 11:15 UTC
[R] Advice on starting to analyze smokestack emissions?
Hello, all, [Originally sent to r-sig-geo list, with no response. Cross-posting here, in the hope of a wider audience. Anyone with any experience in this topic? Thanks.] I'm trying to get started analyzing the concentrations of smokestack emissions. I don't have any professional background or training for this; I'm just an old, retired guy who thinks playing with numbers is fun. A local funeral home in my neighborhood (less than 1200 ft from my home) is proposing to construct a crematorium for human remains. I have some experience with the tidycensus package and thought it might be interesting to construct a model for the changes in concentrations of the pollutants from the smokestack and, using recorded wind speeds and directions, see which US Census blocks would be affected. I have the US Government EPA SCREEN3 output on how concentration varies with distance from the smokestack. See?https://www.epa.gov/scram/air-quality-dispersion-modeling-screening-models#screen3 if curious. As a first task, I'd like to see if I can calculate similar results in R. I'm aware of the 'plume' steady-state Gaussian dispersion package (https://rdrr.io/github/holstius/plume/f/inst/doc/plume-intro.pdf), but am a little concerned that this package was last updated 11 years ago. Do you have any recommendations for me on how to get started analyzing this problem? Is 'plume' still the way to go? I'm aware that there are many atmospheric dispersion models from the US EPA, but I was hoping to keep my work within R, which I'm really enjoying using and learning about. Are SCREEN3 and 'plume' comparable? Is this the best R list to ask questions about this topic? Thanks for any advice or guidance you have for me. -Kevin
You might also try the R-Sig-ecology list, though I would agree that it's not clearly related. Still, air pollution effects...? -- Bert On Tue, Dec 12, 2023 at 3:15?AM Kevin Zembower via R-help < r-help at r-project.org> wrote:> Hello, all, > > [Originally sent to r-sig-geo list, with no response. Cross-posting > here, in the hope of a wider audience. Anyone with any experience in > this topic? Thanks.] > > I'm trying to get started analyzing the concentrations of smokestack > emissions. I don't have any professional background or training for > this; I'm just an old, retired guy who thinks playing with numbers is > fun. > > A local funeral home in my neighborhood (less than 1200 ft from my > home) is proposing to construct a crematorium for human remains. I have > some experience with the tidycensus package and thought it might be > interesting to construct a model for the changes in concentrations of > the pollutants from the smokestack and, using recorded wind speeds and > directions, see which US Census blocks would be affected. > > I have the US Government EPA SCREEN3 output on how concentration varies > with distance from the smokestack. > See > https://www.epa.gov/scram/air-quality-dispersion-modeling-screening-models#screen3 > if curious. As a first task, I'd like to see if I can calculate similar > results in R. I'm aware of the 'plume' steady-state Gaussian dispersion > package > (https://rdrr.io/github/holstius/plume/f/inst/doc/plume-intro.pdf), but > am a little concerned that this package was last updated 11 years ago. > > Do you have any recommendations for me on how to get started analyzing > this problem? Is 'plume' still the way to go? I'm aware that there are > many atmospheric dispersion models from the US EPA, but I was hoping to > keep my work within R, which I'm really enjoying using and learning > about. Are SCREEN3 and 'plume' comparable? Is this the best R list to > ask questions about this topic? > > Thanks for any advice or guidance you have for me. > > -Kevin > > > > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]