Estimating Scope 1 Carbon Footprint with Amazon Athena

Right now, greater than 400 organizations have signed The Local weather Pledge, a dedication to achieve net-zero carbon by 2040. A number of the drivers that result in setting specific local weather targets embody buyer demand, present and anticipated authorities relations, worker demand, investor demand, and sustainability as a aggressive benefit. AWS clients are more and more considering methods to drive sustainability actions. On this weblog, we’ll stroll by means of how we are able to apply present enterprise knowledge to higher perceive and estimate Scope 1 carbon footprint utilizing Amazon Easy Storage Service (S3) and Amazon Athena, a serverless interactive analytics service that makes it straightforward to research knowledge utilizing commonplace SQL.

The Greenhouse Fuel Protocol

The Greenhouse Fuel Protocol (GHGP) offers requirements for measuring and managing world warming impacts from a company’s operations and worth chain.

The greenhouse gases coated by the GHGP are the seven gases required by the UNFCCC/Kyoto Protocol (which is commonly known as the “Kyoto Basket”). These gases are carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), the so-called F-gases (hydrofluorocarbons and perfluorocarbons), sulfur hexafluoride (SF₆) nitrogen trifluoride (NF3). Every greenhouse gasoline is characterised by its world warming potential (GWP), which is decided by the gasoline’s greenhouse impact and its lifetime within the environment. Since carbon dioxide (CO₂) accounts for about 76 p.c of whole man-made greenhouse gasoline emissions, the worldwide warming potential of greenhouse gases are measured relative to CO₂, and are thus expressed as CO₂-equivalent (CO₂e).

The GHGP divides a company’s emissions into three major scopes:

• Scope 1 – Direct greenhouse gasoline emissions (for instance from burning fossil fuels)
• Scope 2 – Oblique emissions from bought power (usually electrical energy)
• Scope 3 – Oblique emissions from the worth chain, together with suppliers and clients

How will we estimate greenhouse gasoline emissions?

There are totally different strategies to estimating GHG emissions that features the Steady Emissions Monitoring System (CEMS) Technique, the Spend-Primarily based Technique, and the Consumption-Primarily based Technique.

Direct Measurement – CEMS Technique

A company can estimate its carbon footprint from stationary combustion sources by performing a direct measurement of carbon emissions utilizing the CEMS methodology. This methodology requires repeatedly measuring the pollution emitted in exhaust gases from every emissions supply utilizing tools similar to gasoline analyzers, gasoline samplers, gasoline conditioning tools (to take away particulate matter, water vapor and different contaminants), plumbing, actuated valves, Programmable Logic Controllers (PLCs) and different controlling software program and {hardware}. Though this method might yield helpful outcomes, CEMS requires particular sensing tools for every greenhouse gasoline to be measured, requires supporting {hardware} and software program, and is usually extra appropriate for Atmosphere Well being and Security purposes of centralized emission sources. Extra info on CEMS is out there right here.

Spend-Primarily based Technique

As a result of the monetary accounting perform is mature and sometimes already audited, many organizations select to make use of monetary controls as a basis for his or her carbon footprint accounting. The Financial Enter-Output Life Cycle Evaluation (EIO LCA) methodology is a spend-based methodology that mixes expenditure knowledge with monetary-based emission components to estimate the emissions produced. The emission components are printed by the U.S. Atmosphere Safety Company (EPA) and different peer-reviewed educational and authorities sources. With this methodology, you’ll be able to multiply the amount of cash spent on a enterprise exercise by the emission issue to provide the estimated carbon footprint of the exercise.

For instance, you’ll be able to convert the quantity your organization spends on truck transport to estimated kilograms (KG) of carbon dioxide equal (CO₂e) emitted as proven under.

Estimated Carbon Footprint = Sum of money spent on truck transport * Emission Issue

Though these computations are very straightforward to make from basic ledgers or different monetary information, they’re most useful for preliminary estimates or for reporting minor sources of greenhouse gases. As the one user-provided enter is the quantity spent on an exercise, EIO LCA strategies aren’t helpful for modeling improved effectivity. It is because the one method to cut back EIO-calculated emissions is to cut back spending. Subsequently, as an organization continues to enhance its carbon footprint effectivity, different strategies of estimating carbon footprint are sometimes extra fascinating.

Consumption-Primarily based Technique

From both Enterprise Useful resource Planning (ERP) methods or digital copies of gasoline payments, it’s easy to find out the quantity of gasoline a company procures throughout a reporting interval. Gas-based emission components can be found from a wide range of sources such because the US Environmental Safety Company and commercially-licensed databases. Multiplying the quantity of gasoline procured by the emission issue yields an estimate of the CO₂e emitted by means of combustion. This methodology is commonly used for estimating the carbon footprint of stationary emissions (as an example backup mills for knowledge facilities or fossil gasoline ovens for industrial processes).

If for a specific month an enterprise consumed a recognized quantity of motor gasoline for stationary combustion, the Scope 1 CO₂e footprint of the stationary gasoline combustion will be estimated within the following method:

Estimated Carbon Footprint = Quantity of Gas Consumed * Stationary Combustion Emission Issue

Organizations might estimate their carbon emissions through the use of present knowledge present in gasoline and electrical energy payments, ERP knowledge, and related emissions components, that are then consolidated in to a knowledge lake. Utilizing present analytics instruments similar to Amazon Athena and Amazon QuickSight a company can acquire perception into its estimated carbon footprint.

The info structure diagram under reveals an instance of how you can use AWS companies to calculate and visualize a company’s estimated carbon footprint.

Prospects have the flexibleness to decide on the companies in every stage of the information pipeline primarily based on their use case. For instance, within the knowledge ingestion section, relying on the prevailing knowledge necessities, there are lots of choices to ingest knowledge into the information lake similar to utilizing the AWS Command Line Interface (CLI), AWS DataSync, or AWS Database Migration Service.

Instance of calculating a Scope 1 stationary emissions footprint with AWS companies

Let’s assume you burned 100 commonplace cubic toes (scf) of pure gasoline in an oven. Utilizing the US EPA emission components for stationary emissions we are able to estimate the carbon footprint related to the burning. On this case the emission issue is 0.05449555 Kg CO₂e /scf.

Amazon S3 is good for constructing a knowledge lake on AWS to retailer disparate knowledge sources in a single repository, as a consequence of its nearly limitless scalability and excessive sturdiness. Athena, a serverless interactive question service, permits the evaluation of knowledge straight from Amazon S3 utilizing commonplace SQL with out having to load the information into Athena or run advanced extract, remodel, and cargo (ETL) processes. Amazon QuickSight helps creating visualizations of various knowledge sources, together with Amazon S3 and Athena, and the flexibleness to make use of customized SQL to extract a subset of the information. QuickSight dashboards can offer you insights (similar to your organization’s estimated carbon footprint) shortly, and likewise present the flexibility to generate standardized reviews for your corporation and sustainability customers.

On this instance, the pattern knowledge is saved in a file system and uploaded to Amazon S3 utilizing the AWS Command Line Interface (CLI) as proven within the following structure diagram. AWS recommends creating AWS assets and managing CLI entry in accordance with the Greatest Practices for Safety, Id, & Compliance steering.

The AWS CLI command under demonstrates the way to add the pattern knowledge folders into the S3 goal location.

aws s3 cp /path/to/native/file s3://bucket-name/path/to/vacation spot

The snapshot of the S3 console reveals two newly added folders that comprises the recordsdata.

To create new desk schemas, we begin by working the next script for the gasoline utilization desk within the Athena question editor utilizing Hive DDL. The script defines the information format, column particulars, desk properties, and the placement of the information in S3.

CREATE EXTERNAL TABLE `gasutilization`(
`fuel_id` int,
`month` string,
`yr` int,
`usage_therms` float,
`usage_scf` float,
`g-nr1_schedule_charge` float,
`accountfee` float,
`gas_ppps` float,
`netcharge` float,
`taxpercentage` float,
`totalcharge` float)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
STORED AS INPUTFORMAT
'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
's3://<bucketname>/Scope 1 Pattern Knowledge/gasutilization'
TBLPROPERTIES (
'classification'='csv',
'skip.header.line.rely'='1')

The script under reveals one other instance of utilizing Hive DDL to generate the desk schema for the gasoline emission issue knowledge.

CREATE EXTERNAL TABLE `gas_emission_factor`(
`fuel_id` int,
`gas_name` string,
`emission_factor` float)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
STORED AS INPUTFORMAT
'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
's3://<bucketname>/Scope 1 Pattern Knowledge/gas_emission_factor'
TBLPROPERTIES (
'classification'='csv',
'skip.header.line.rely'='1')

After creating the desk schema in Athena, we run the under question towards the gasoline utilization desk that features particulars of gasoline payments to indicate the gasoline utilization and the related prices, similar to gasoline public objective program surcharge (PPPS) and whole prices after taxes for the yr of 2020:

SELECT * FROM "gasutilization" the place yr = 2020;

We’re additionally capable of analyze the emission issue knowledge exhibiting the totally different gasoline sorts and their corresponding CO2e emission as proven within the screenshot.

With the emission issue and the gasoline utilization knowledge, we are able to run the next question under to get an estimated Scope 1 carbon footprint alongside different particulars. On this question, we joined the gasoline utilization desk and the gasoline emission issue desk on gasoline id and multiplied the gasoline utilization in commonplace cubic foot (scf) by the emission issue to get the estimated CO₂e influence. We additionally chosen the month, yr, whole cost, and gasoline utilization measured in therms and scf, as these are sometimes attributes which can be of curiosity for patrons.

SELECT "gasutilization"."usage_scf" * "gas_emission_factor"."emission_factor" 
AS "estimated_CO2e_impact", 
"gasutilization"."month", 
"gasutilization"."yr", 
"gasutilization"."totalcharge", 
"gasutilization"."usage_therms", 
"gasutilization"."usage_scf" 
FROM "gasutilization" 
JOIN "gas_emission_factor" 
on "gasutilization"."fuel_id"="gas_emission_factor"."fuel_id";

Lastly, Amazon QuickSight permits visualization of various knowledge sources, together with Amazon S3 and Athena, and the flexibleness to make use of customized SQL to get a subset of the information. The next is an instance of a QuickSight dashboard exhibiting the gasoline utilization, gasoline prices, and estimated carbon footprint throughout totally different years.

We now have simply estimated the Scope 1 carbon footprint for one supply of stationary combustion. If we had been to do the identical course of for all sources of stationary and cell emissions (with totally different emissions components) and add the outcomes collectively, we may roll up an correct estimate of our Scope 1 carbon emissions for all the enterprise by solely using native AWS companies and our personal knowledge. An identical course of will yield an estimate of Scope 2 emissions, with grid carbon depth within the place of Scope 1 emission components.

Abstract

This weblog discusses how organizations can use present knowledge in disparate sources to construct a knowledge structure to achieve higher visibility into Scope 1 greenhouse gasoline emissions. With Athena, S3, and QuickSight, organizations can now estimate their stationary emissions carbon footprint in a repeatable means by making use of the consumption-based methodology to transform gasoline utilization into an estimated carbon footprint.

Different approaches accessible on AWS embody Carbon Accounting on AWS, Sustainability Insights Framework, Carbon Knowledge Lake on AWS, and basic steering detailed on the AWS Carbon Accounting Web page.

In case you are considering info on estimating your group’s carbon footprint with AWS, please attain out to your AWS account workforce and take a look at AWS Sustainability Options.

References

Concerning the Authors

Thomas Burns, SCR, CISSP is a Principal Sustainability Strategist and Principal Options Architect at Amazon Internet Providers. Thomas helps manufacturing and industrial clients world-wide. Thomas’s focus is utilizing the cloud to assist corporations cut back their environmental influence each inside and outdoors of IT.

Aileen Zheng is a Options Architect supporting US Federal Civilian Sciences clients at Amazon Internet Providers (AWS). She companions with clients to supply technical steering on enterprise cloud adoption and technique and helps with constructing well-architected options. She can be very obsessed with knowledge analytics and machine studying. In her free time, you’ll discover Aileen doing pilates, taking her canine Mumu out for a hike, or looking down one other great place for meals! You’ll additionally see her contributing to tasks to assist range and girls in know-how.