A Guide to Understanding Emission Factors

Authors – Julian Burger, Zeinab Chamas, Ivona Palinkas

Definition of Emission Factors

Emission factors are representative values which quantify the environmental impact of an activity and are essential in order to calculate greenhouse gas (GHG) emissions.Typically, emission factors are presented in units of mass of pollutant per relevant units of the activity studied (ie. mass, kilowatt hour, joules) (EPA).

Examples of emission factors include:

• An average car with unknown fuel emits 0.04508 kg of CO2e per km (BEIS 2022).
• Landfilled disposal of organic waste emits 445.72819 kg of CO2e per tonne (BEIS 2022).

Emission factors are usually geographically specific, as activities/operations vary depending on location. For example, an electricity grid relying on coal generated energy will have a significantly different emission factor than an electricity grid in a different location using hydroelectric power.

Importance of Emission Factors

Within the world of GHG accounting, emission factors have been a fundamental tool for companies, organizations, and governments to develop their emissions inventories. Emission factors have emerged as the most viable method for companies to track their emissions due to their ease of use, accessibility, standardization, and the ability to leverage already existing data collection structures [1].

Accessibility and Transparency of Emission Factors

One of the most important advantages of using emission factors in the development of GHG inventories is their accessibility and simple calculation methodology. Factors are often stored in publicly available databases that are rigorously tested, well-documented and transparent in their calculation methodologies. For example, a company in Canada looking to develop a GHG inventory could leverage the publicly available Government of Canada National Inventory report to derive emission factors that are both geographically and temporally accurate [2].

Synergy with existing Data Collection

Companies routinely collect all sorts of data for financial accounting purposes or to improve their operation efficiency. One of the key advantages of using emission factors is their ability to make use of this existing information. Data such as energy consumption that would be collected through utility bills, business travel data collected for accounting purposes or even fuel purchase records for company transportation can all be converted into emissions through the use of emission factors [3].

Standardization and Alignment with Environmental Goals and Reporting

Another compelling advantage of emission factors is their ability to represent emissions using a common unit: tonnes of CO2 equivalent (CO2e). This standardization allows for benchmarking between different companies, geographical locations, and industries. It also allows companies to align themselves with well-recognized reporting standards such as the Science Based Target initiative (SBTi) or the Carbon Disclosure Project (CDP).

Not only is the use of emission factors important in reporting compliance, it can also be a strategic tool for a company’s environmental goals and ESG performance. By using emission factors to generate yearly inventories, a company can gain a comprehensive understanding of its highest emitting sectors and trends in emissions over time. Armed with this knowledge, companies can strategically target high-emitting areas to reduce their carbon footprint over time.

Emission factors are a key tool in the development of GHG inventories offering a practical, standardized, and accessible method for environmental reporting. Making use of emission factors is key, not only in achieving environmental goals for businesses, but also in a globally coordinated effort to curb climate change.

Calculation of Emission Factors

From direct measurement and modelling to estimation techniques, a range of methods stand ready to calculate emission factors.

Method 1: Direct Measurement

Direct measurement involves collecting real-time emission data directly from the source, using advanced instruments and equipment. This method provides an accurate measurement of the emitted pollutants’ quantity. Yet, to calculate the emission factor using this method, an additional step is essential: evaluating the activity level that prompts the release of the measured pollutants.

Consider the example of evaluating vehicle emission factors. In addition to capturing the volume of emitted pollutants (referred to as emission data), it’s essential to account for concurrent activity levels, like distance travelled or fuel consumption. With both emission data and activity levels documented, the emission factor is calculated by dividing the pollutant quantity emitted by the associated activity level.

Direct measurement, like any other method, has its own set of benefits and drawbacks. One of its main advantages is its high level of accuracy. However, achieving this accuracy is both resource and time intensive. It’s also worth noting that this approach can be restricted by technical limitations in certain cases and might not be applicable to measure emissions. Hence, alternative methods must be used to measure emission factors.

Method 2: Modelling

This method is often used when direct measurement is impractical. Modelling involves creating mathematical models to simulate the emission process to allow for the prediction of emissions based on a set of input parameters (e.g., source characteristics, operating conditions) and assumptions. Like direct measurement, after estimating the emission data, we divide emissions by the corresponding activity data. This calculation yields the emission factor, representing the rate of pollutant emissions per unit of activity.

A crucial step in this method is the validation process. By comparing the model emission predictions with real-world emissions from similar processes, the accuracy of the developed model and results are assessed. Validated models are a reliable, flexible, and adaptable approach for estimating emission factors. However, their level of accuracy depends on the quality of the input data and the assumptions made. They can also be complex to develop as they require advanced expertise in various disciplines.

Method 3: Estimation

Estimation is another powerful method that adds to our toolkit of emission factor techniques. It gives us a means to estimate emission factors without relying on complex models and when direct measurements hit roadblocks. Estimation uses higher-level data (e.g., regional, or national scales), allowing us to estimate emission factors and trends at finer scales. For instance, estimating emission factors for an urban street’s transport system when direct measurement of air quality is not feasible. Here, using coarser air quality data in combination with street-specific attributes like vehicle density, allows us to derive emission factors at the street level.

Estimation is a versatile tool that could also be used to estimate emission factors at a larger scale using finer scale data. For example, to quantify urban GHG emissions from transportation when the vehicle type mix is a puzzle (i.e. a mix of cars, trucks, buses, hybrid, electric etc…). In this scenario, the use of average emission factors emerges as an effective and practical solution. Here estimation becomes an invaluable tool for determining GHG emissions in urban areas, even when the vehicle mix is undetermined.

Although this method has a breadth of advantages when other methods are not applicable, it must be used cautiously as uncertainties are tied to it and inherent in the process.

Application of Emission Factors

With the advent of emission factor databases published by governmental agencies and large environmental organisations, companies can apply industry-specific emission factors to cover the entirety of their operations.

Emission Factor Databases

Databases of emission factors serve as an inventory of standardised and rigorously checked factors for use across different industries and regions. These databases are often compiled by governmental agencies such as the UK Department for Business, Energy and Industrial Strategy (BEIS), The United States Environmental Protection Agency (EPA) or the Department of Environment and Climate Change Canada (ECCC). Additionally, some environmental and energy organisations also provide large-scale emission factor databases such as the International Energy Agency (IEA) and the Intergovernmental Panel on Climate Change (IPCC).

Through the use of these large-scale databases, companies across various industries can leverage standardized emission factors to convert their activities into emissions on a global scale. We collate and curate our own database which is used to power Ecometrica’s platform.

Application of Emission Factors Across Industries

Energy: Energy and utilities companies make use of emission factors to determine the GHG emissions associated with the life-cycle use of energy sources (extraction, processing, generation, transportation and distribution) such as electricity and natural gas. The use of emission factors in the calculation of emissions for the generation of different energy sources allows end-use energy users to calculate the emissions resulting from the consumption of energy.

This data helps push both energy companies and users to find ways to reduce the carbon intensity of their operations through optimised efficiency and incentivising lower carbon-intensive energy sources.

Transportation: Emission factors help the transportation sector calculate the emissions associated with the consumption of energy for travel. This is done by using vehicle specific factors that can calculate the emission on a per kilometer or mile of distance travelled or on a per litre of fuel consumed basis. By being able to compare the emissions intensity between different means of transportation and vehicle types, the transportation industry can make informed decisions to shift towards lower carbon options.

Agriculture: The agriculture industry makes use of various emission factors to determine the emissions associated with activities such as livestock, crop production, and energy usage. This can guide decision making on different cultivation or livestock management practices, fertiliser or equipment usage and more, to determine how best to reduce emissions.

Emission Factor Use at Ecometrica

Ecometrica’s sustainability platform is powered by a database of global emission factors, which is compiled and maintained by our sustainability analysts. Each factor is derived from reputable sources such as governmental institutions or peer reviewed journals. Emission factors are updated as soon as the most recent data is available. Our database is also verified by an annual auditing process carried out by PwC.

Our database contains over 120,000 factors, spanning over 219 countries. For each activity, there is typically a carbon dioxide (CO2), methane (CH4) and nitrous oxide (NO2) factor. Combined, these gases produce a carbon dioxide equivalent (CO2e) factor. Using these emission factors and the intensity at which an activity is performed, such as kWh of electricity used or kilometers driven, the Ecometrica platform is able to calculate the total greenhouse gas emissions emitted by each activity.

These factors are embedded in our platform and power the calculations that provide the emissions, however they are also available to buy as spreadsheets here if you prefer to calculate your emissions in spreadsheets.

Challenges and Limitations of Emission Factors

While emission factors have proven valuable in determining GHG emissions and developing GHG inventories, they come with inherent limitations and challenges that must be navigated to ensure accurate and comprehensive GHG accounting. Among those limitations we list:

Variability in Calculation Methods: The availability of multiple methods for determining emission factors is akin to a double-edged sword. Although it provides a way to explore alternate approaches in cases where one might not be applicable, it introduces an increased level of variability in the obtained results.

System boundary variation: Another limitation associated with the use of emission factors is the variation in the system boundaries used for calculation. Certain emission factors are developed by adopting a cradle-to-gate approach, while others are developed for a specific point within the chain. Hence it is paramount to properly describe the approach used when determining those emission factors to avoid confusion and misinterpretation of data.

Variability and context dependency: Emission factors provide valuable averages based on standardised assumptions, assuming uniformity across a given activity. However, they often overlook the complex mix of factors that influence emissions in real-world scenarios (e.g., technology, geographic location). This can often lead to inaccurate quantification of GHG emissions.

Data variability across time: A well-known limitation of emission factors is their time-sensitivity. Periodic updates are essential to ensure alignment with the latest data. However, many of the emission factors in current use rely on outdated data that no longer accurately mirrors the evolving real-world conditions. This mismatch often leads to either underestimating or overestimating emissions.

The requirement for supplementary data: Emission factors don’t serve as a complete input on their own. They must be complemented by activity data to be able to calculate GHG emissions. This adds an extra layer of complexity to the data gathering process.

The EPA has called for an increase in the quantification of uncertainty in emission factors and inventories to limit the cons of using emission factors.