TEMREG: Temporally Resolved Emissions Generator

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Processing UK annual emissions to sector-level temporal profiles.

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Notes on structural change:

• Code for timescale GAM with by= grouping for sectors is ready, but very computationally expensive. Takes a long time.

• Therefore code is also available to construct sector GAMs one by one and place into list. List is saved as .rds

• All of this to go in targets?

  • if you updated the raw data GAMs, you need to update NFR_to_GAM table. Targets will spot this and re-run
  • if you update the pollutants to work over, targets should spot and re-run

Info:

• UK activity data is used - not emissions data - to match to activity sectors in the NAEI

• Raw data processed to standardized output

  • Processing of data in /DUKEMS/Database/R/gam_generation.R
  • Standard input files uploaded to ./data/input_formatted (all on .gitignore)

• Each NFR code translates to an activity grouping (Profile_ID), and the grouping's total emissions will determine the its weight in the final aggregated sector.

• GAMs for every Profile_ID are produced from the raw data (data/GAM_profileID/timescale)

• They are produced for hour, hourwday (hour for specific day of week), wday, month and yday

• These GAM outputs are the basis for sector-level groupings;

  • Need to know the NFR to sector look-up (e.g. to SNAP, GNFR, custom)
  • The weights (contribution of Profile_ID to aggregated sector) influence the construction of the final sector level GAM (./output/GAM_sector)
  • Final sector level GAMs are output (./output/GAM_sector)

• As well as GAMs, standard csv outputs of temporal profiles are produced; coefficients are relative to 1

• GAMs for sectors can be constructed from year/pollutant averages or year/pollutant specific.

  • This allows for longer/shorter-term representations, multiple or single pollutants

• When further raw data is found and ingested, it must either map to current Profile_IDs or new IDs need to be added and mapped to NFR codes.

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Emissions contribution by Profile_ID per sector here; ./doc/profile_contributions_sector/

IMPORTANT: Raw data should be normalised (units removed) to enable combination of disparate data.

Aggregating GAMs When aggregating Profile_ID GAMs to aggregated GAMs, each Profile_ID GAM is sampled across the prediction interval (n times). This uses the uncertainty range properly, instead of sampling the SE (which creates false confidence).

IDEA to develop (28/01/22): Create one large table of emissions for all years and pollutants. When creating the sector GAM, use the mean grouped-NFR contribution to that sector across all years and all pollutants. That way it becomes generic. This could be a simple mean (total per sector would need to be re-adjusted to 1), a weighted mean to give more recent years more influence (as old stuff is out of date?) or another GAM. It could be fine that one % contribution figure is used to make the GAM or the range across all years/pollutants could feed into a MCMC?

Future DUKEMs work:
* Integrate wood burning hour of day data; Gary Fuller (email 25/10/2021)
* continue to add data & detail around sub-sector profiles
* Pollutant specific profiles
* Agricultural information re activity AND temperature/climate related profiles
* More year-specific data
* Spatially variable temporal profiles
* Point data temporal profiles
* (near) Real time data interface