This user guide will guide you through the process of calculating your Scope 1 emissions using Avarni. From preparing your data and importing it to reviewing your emission entries, we'll take you step by step through the entire process.
For more information on what Avarni covers for Scope 1, please refer to the below link:
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Preparing your data
1. Start by gathering the necessary information related to your organization's activities and operations.
2. Use the Data Requirement Document as a guide. You may copy and paste your collected data into the template, or alternatively, use the document as a reference and structure your data in your preferred format, as long as the required fields are included and the file format is correct.
The headers in your file do not need to match with the data requirement document. During the import process, Avarni will give you the opportunity to match the headers that you have in your file against the fields within the platform. For example: If you have the header 'Vendor Name' in your data set, when uploading it to Avarni, you will be asked to confirm if 'Vendor Name' in your data set should be matched against 'Supplier' in Avarni.
📌 Note:
You may only be able to upload one unit type each time. For example: If you have a file that contains Volume (kL) and Currency (USD), you will need to separate the data into two files/uploads.
If you would like to add custom fields, refer to our user guide on Custom fields.
For accurate mapping with our AI, a useful benchmark is to ensure that your data is comprehensible to an average person. Poor data inputs = Poor data outputs.
Our AI utilizes the vendor, description, and accounts fields for mapping emission factors.
Date of Activity Format
Date of Activity Format
The format for dates in the file can be mm/dd/yyyy (e.g. 01/13/2024) or dd-month-yyyy (e.g. 13-Jan-2024). For example:
23-Oct-2024, 23 October 2024, 10/23/2024
If you only have the month and year available for the activity, you may use just Year, or Month/Year. For example:
October 2024 (Avarni will automatically adjust this to 1st October 2024)
2024 (Avarni will automatically adjust this to 1st January 2024)
List of Country Names and Codes
List of Country Names and Codes
To view the list of Country Names and the ISO Country Codes, refer to list of country names and codes here.
You may enter the name of a country in various forms (for example: Aus, AU, Australia). Regardless of the format used, Avarni will validate the input and automatically convert it to the appropriate country code. In the case where Avarni cannot recognize the country you have listed, refer to the list and check the spelling or the name.
Format Requirements
Format Requirements
File Format: .csv, .tsv, .xls, .xlsx, .xml, .txt spreadsheets accepted
Size Limitations: ~ 550,000 rows
Importing your data
Now that your data is ready, follow these steps to import it into Avarni’s platform.
1. Click on Import Data on the left hand menu and then select Import Data:
2. Select the applicable values:
Scope: Select Scope 1.
Category: Select the applicable Category (Non-transport combustion, Transport combustion, Fugitive).
💡 Tip: The category will change depending on which Scope you select.
Unit Type: Select the applicable Unit Type.
📌 Note: You may only be able to upload one unit type each time. For example: If you have a file that contains Volume (kL) and Currency (USD), you will need to separate the data into two files/uploads.
💡 Tip: If you are unsure of which unit type to select, type in an example such as kL, USD, kg and Avarni will be able to determine which unit type it belongs to.
3. Choose the file from your computer to proceed with the upload:
4. Once the data is uploaded, you will be asked to change or confirm header selection. The header should be highlighted in blue. Click Next.
You can choose a different row if the header is not at the very top. For example: if the header is in row 2 instead of row 1, you will need to select and highlight row 2 in order for the system to identify that row 2 is the header.
5. Match the columns in your file to the applicable template fields in Avarni. Click Continue.
Uploaded Columns: Header fields in the file that you have uploaded.
Sample Data: Sample data in the file that you have uploaded.
Template Columns: Fields in Avarni - you will need to change this to match it against the correct field.
💡 Tip: Click on 'Edit Input Unit values' to check if the input unit that you have entered matches with the input unit value in Avarni.
6. Review any errors by selecting the Error tab and adjusting the relevant fields.
💡 Tips:
You can modify any rows that have errors by double clicking on the relevant cell.
You can discard a row by selecting the row and then right click, and select Delete Row.
Use the Find and replace feature to bulk edit fields.
Use the Export function to export the file with any new updates you have made on this screen.
📌 Note:
You must clear all errors in order to proceed with the import. You can quickly delete all rows with errors on the right hand side of the screen when an error appears.
7. Click Import.
8. Provide a value for all required fields where values were missing from your file. Select from the dropdown list and then click Next:
9. Select the applicable Factor Set and click Next.
📌 Note: Refer to this link for more information on existing and custom emission factor sources
💡 Tip: Avarni have automatically selected the factor set with the highest percentage of matches between years and countries, and then the most unique factor names, based off the data you have uploaded. You may proceed with the suggested factor set or alternatively you may select a different factor set if you wish.
💡Tip: If a country does not have a matching country in a factor set, Avarni will be able to automatically match the country to a region that it belongs to. For example: In the below screenshot, the data uploaded has multiple countries that does not exist in EXIOBASE (factor set). Avarni has reviewed the countries and applied it to the applicable region (Mongolia, Vietnam and Egypt = Middle East, Asia and Egypt).
10. Select the fields you want the AI to reference when matching your data to an emission factor.
💡Tip: The quality of the data that is sent to the AI will have a direct effect on the accuracy of the emission factor mappings. For example, if the data in your Description contains invoice numbers, procurement codes or abbreviations that would not be understood by the layperson, then unselecting Description would ensure the AI has the best quality data for its mapping process.
11. Review your import. Click Complete Import:
🎉🥳 Congratulations! You have now imported your data are ready for the next step: Reviewing emission entries.