Fixed bugs for Scope 1 and Scope 3 (non-electricity sources) emissions apportionment for September 2023 and October 2023 and Scope 2 location-based emissions for October 2023

## Fix Fixed bugs for Scope 1 and Scope 3 (non-electricity sources) emissions apportionment for September 2023 and October 2023 and Scope 2 location-based emissions for October 2023\. Specifically: * In September and October 2023, incorrect apportionment factors were used to estimate emissions from non-electricity sources. Some customers might have seen an increase in Scope 1 emissions and a decrease in Scope 3 emissions in their reports. To address the issue, we have corrected the apportionment factors from September 2023 onwards. * For more information on how we allocate Scope 1 and 3 emissions, refer to the [Non-electricity emission sources](https://cloud.google.com/carbon-footprint/docs/methodology#non-electricity-allocation) Section in our public methodology document. * Customers may have seen an increase across all services in Scope 2 location-based emissions in October 2023\. This was due to an error in an upstream hourly carbon intensity data source. The error has now been corrected for Scope 2 location-based emissions for October 2023\. Please note that data already [exported to BigQuery](https://cloud.google.com/carbon-footprint/docs/export) for previous months is not automatically corrected in your exported tables. To see the corrected data, [schedule a manual data backfill](https://cloud.google.com/bigquery/docs/working-with-transfers#manually%5Ftrigger%5Fa%5Ftransfer%5For%5Fbackfill) for the desired time period. Note that there is half a month lag of our data release. For example, to backfill September and October 2023 data, run the backfill for October 15, 2023 and November 15, 2023, which will update the data for September and October 2023 in your BigQuery table. ## Fix Improved data consistency on BigQuery exports, particularly on the `project_id` field. In our BigQuery [data exports](https://cloud.google.com/carbon-footprint/docs/export), there were instances where the `project_id` field contained a NULL value, and in some of these cases, carbon for a particular project was split between two rows where the project ID was listed as NULL and non-NULL. (Note that the `project_number` field is always populated, and the total carbon when summed across all rows is correct for a given project number.) We have updated our reports for all prior months in order to populate the `project_id` field consistently, with a non-NULL value wherever possible. We have ensured each project's carbon is reported as a single row within a given month, service, and location. To update previous months of data, [schedule a manual data backfill](https://cloud.google.com/bigquery/docs/working-with-transfers#manually%5Ftrigger%5Fa%5Ftransfer%5For%5Fbackfill) for the desired time period.