Improving The Characterization Of Several Natural Emissions In CMAQ by US Government | Environmental and Climate Sciences

About this Dataset

Improving The Characterization Of Several Natural Emissions In CMAQ

These datasets contains all the data used to make the figures in the associated paper. The excel files are self-explanatory and can be directly used. While the other files in netcdf format, need a visualization tool (such as VERDI) or statistical software (such as R) to make statistical summary or plots. Portions of this dataset are inaccessible because: data will be uploaded when paper will be accepted by journal. They can be accessed through the following means: For excel files, the data can be directly used to make summary or plots. For netcdf files, another visualization tool or statistical package (such as R) can be used. All the netcdf files can be visualized using VERDI. Format: Two types of data formats. One is the excel files which are self-explanatory. The other type is netcdf files which are used to make the spatial plots in the paper.

This dataset is associated with the following publication:
Kang, D., J. Willison, G. Sarwar, M. Madden, C. Hogrefe, R. Mathur, B. Gantt, and S. Alfonso. Improving the Characterization of the Natural Emissions in CMAQ. EM Magazine. Air and Waste Management Association, Pittsburgh, PA, USA, (10): 1-7, (2021).
Organization: U.S. Environmental Protection Agency
Last updated: 2023-09-03T04:27:40.000989
Tags: beis, bvocs, halogen, lightning-nox-emissions, megan, natural-emissions

Tables

AQS Daily O3 V53 INTEL 12US1–2016 CON MG3

@usgov.epa_gov_improving_the_characterization_of_several_natu_4bd0a269.aqs_daily_o3_v53_intel_12us1_2016_con_mg3

1.77 MB
39187 rows
33 columns


CREATE TABLE aqs_daily_o3_v53_intel_12us1_2016_con_mg3 (
  "unnamed_0" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "n__m" VARCHAR,
  "n__deg" VARCHAR,
  "n__deg_1" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR,
  "mm_dd_yyyy_hh_mm" VARCHAR,
  "mm_dd_yyyy_hh_mm_1" VARCHAR,
  "mm" VARCHAR,
  "dd" VARCHAR,
  "yyyy" VARCHAR,
  "mm_1" VARCHAR,
  "dd_1" VARCHAR,
  "yyyy_1" VARCHAR,
  "ppb" VARCHAR,
  "ppb_1" VARCHAR,
  "ppb_2" VARCHAR,
  "ppb_3" VARCHAR,
  "hour" VARCHAR,
  "hour_1" VARCHAR,
  "ppb_4" VARCHAR,
  "ppb_5" VARCHAR,
  "ppb_6" VARCHAR,
  "ppb_7" VARCHAR,
  "hour_2" VARCHAR,
  "hour_3" VARCHAR,
  "ppm_hours" VARCHAR,
  "ppm_hours_1" VARCHAR,
  "ppm_hours_2" VARCHAR,
  "ppm_hours_3" VARCHAR
);

AQS Daily O3 V53 INTEL 12US1–2016 CON BE3

@usgov.epa_gov_improving_the_characterization_of_several_natu_4bd0a269.aqs_daily_o3_v53_intel_12us1_2016_con_be3

1.77 MB
39187 rows
33 columns


CREATE TABLE aqs_daily_o3_v53_intel_12us1_2016_con_be3 (
  "unnamed_0" VARCHAR,
  "unnamed_1" VARCHAR,
  "unnamed_2" VARCHAR,
  "unnamed_3" VARCHAR,
  "n__m" VARCHAR,
  "n__deg" VARCHAR,
  "n__deg_1" VARCHAR,
  "unnamed_7" VARCHAR,
  "unnamed_8" VARCHAR,
  "mm_dd_yyyy_hh_mm" VARCHAR,
  "mm_dd_yyyy_hh_mm_1" VARCHAR,
  "mm" VARCHAR,
  "dd" VARCHAR,
  "yyyy" VARCHAR,
  "mm_1" VARCHAR,
  "dd_1" VARCHAR,
  "yyyy_1" VARCHAR,
  "ppb" VARCHAR,
  "ppb_1" VARCHAR,
  "ppb_2" VARCHAR,
  "ppb_3" VARCHAR,
  "hour" VARCHAR,
  "hour_1" VARCHAR,
  "ppb_4" VARCHAR,
  "ppb_5" VARCHAR,
  "ppb_6" VARCHAR,
  "ppb_7" VARCHAR,
  "hour_2" VARCHAR,
  "hour_3" VARCHAR,
  "ppm_hours" VARCHAR,
  "ppm_hours_1" VARCHAR,
  "ppm_hours_2" VARCHAR,
  "ppm_hours_3" VARCHAR
);