20 Matching Annotations
  1. Feb 2021
  2. Nov 2020
  3. Oct 2020
    1. (d) All calculations shown in this appendix shall be implemented on a site-level basis. Site level concentration data shall be processed as follows: (1) The default dataset for PM2.5 mass concentrations for a site shall consist of the measured concentrations recorded from the designated primary monitor(s). All daily values produced by the primary monitor are considered part of the site record; this includes all creditable samples and all extra samples. (2) Data for the primary monitors shall be augmented as much as possible with data from collocated monitors. If a valid daily value is not produced by the primary monitor for a particular day (scheduled or otherwise), but a value is available from a collocated monitor, then that collocated value shall be considered part of the combined site data record. If more than one collocated daily value is available, the average of those valid collocated values shall be used as the daily value. The data record resulting from this procedure is referred to as the “combined site data record.”
      1. Calculate mean of all collocated NON-primary monitors' values per day
      2. Coalesce primary monitor value with this calculated mean
    1. 1.1. Monitors For the purposes of AQS, a monitor does not refer to a specific piece of equipment. Instead, it reflects that a given pollutant (or other parameter) is being measured at a given site. Identified by: The site (state + county + site number) where the monitor is located AND The pollutant code AND POC – Parameter Occurrence Code. Used to uniquely identify a monitor if there is more than one device measuring the same pollutant at the same site. For example monitor IDs are usually written in the following way: SS-CCC-NNNN-PPPPP-Q where SS is the State FIPS code, CCC is the County FIPS code, and NNNN is the Site Number within the county (leading zeroes are always included for these fields), PPPPP is the AQS 5-digit parameter code, and Q is the POC. For example: 01-089-0014-44201-2 is Alabama, Madison County, Site Number 14, ozone monitor, POC 2.

      How monitors (specific measures of specific criteria) are identified in AQS data.

  4. Sep 2020
    1. Had it not been for the attentiveness of one person who went beyond the task of classifying galaxies into predetermined categories and was able to communicate this to the researchers via the online forum, what turned out to be important new phenomena might have gone undiscovered.

      Sometimes our attempts to improve data quality in citizen science projects can actually work against us. Pre-determined categories and strict regulations could prevent the reporting of important outliers.

  5. Aug 2020
    1. Lozano, R., Fullman, N., Mumford, J. E., Knight, M., Barthelemy, C. M., Abbafati, C., Abbastabar, H., Abd-Allah, F., Abdollahi, M., Abedi, A., Abolhassani, H., Abosetugn, A. E., Abreu, L. G., Abrigo, M. R. M., Haimed, A. K. A., Abushouk, A. I., Adabi, M., Adebayo, O. M., Adekanmbi, V., … Murray, C. J. L. (2020). Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)30750-9

  6. Jul 2020
  7. Jun 2020
  8. Apr 2020
  9. Aug 2018
  10. May 2018
    1. Negative values included when assessing air quality In computing average pollutant concentrations, EPA includes recorded values that are below zero. EPA advised that this is consistent with NEPM AAQ procedures. Logically, however, the lowest possible value for air pollutant concentrations is zero. Either it is present, even if in very small amounts, or it is not. Negative values are an artefact of the measurement and recording process. Leaving negative values in the data introduces a negative bias, which potentially under represents actual concentrations of pollutants. We noted a considerable number of negative values recorded. For example, in 2016, negative values comprised 5.3 per cent of recorded hourly PM2.5 values, and 1.3 per cent of hourly PM10 values. When we excluded negative values from the calculation of one‐day averages, there were five more exceedance days for PM2.5 and one more for PM10 during 2016.
  11. May 2017
    1. volume, velocity, and variety

      volume: The actual size of traffic

      Velocity: How fast does the traffic show up.

      Variety: Refers to data that can be unstructured, semi structured or multi structured.