Emissions Inventory - Stage 3

01 Update your plan

The transition from Stage 2 to Stage 3 will include a focus on emissions modeling and gridding emissions to ensure robust spatial allocation of emissions in addition to implementing higher tiers with overall improved data quality. This stage will generally require a larger technical team (approximately six full-time-equivalent staff, including collaborators or contractors) and secure access to a dedicated database or computer system capable of supporting spatial and temporal emissions processing. Check the steps below relative to those of Stage 1 and 2 to ensure you have a plan for staffing, data collection and implementation of a robust integrated emission inventory for all compounds and all reporting purposes. 

02 Secure funding

Securing continuous funding for emission inventory activities is vital. At Stage 3, this may involve a combination of some central government funding and substantial donor or project support, while institutional arrangements are developed to move progressively toward a permanent governmental budget line. Additionally, it is important to link this funding to international commitments made by the country, ensuring that they are packaged together to provide a sustainable and permanent solution. This integrated approach not only guarantees financial stability but also reinforces the country's dedication to its international obligations, enhancing accountability and fostering long-term planning for effective implementation of relevant emission reduction policies and programs. 

03 Update your inventory to Tier 2

Upgrading an existing emission inventory to incorporate Tier 2 methodologies for the relevant sources and subsectors involves several strategic steps. First, refine your key category analysis (See EMEP/EEA Key Category guidance below) to identify specific sectors and subsectors that have shown significant uncertainty or are major contributors to total emissions (See EMEP/EEA uncertainty analysis guidance below). Next, gather detailed activity data and emission factors pertinent to these categories, ensuring they align with Tier 2 standards, which typically involve more precise and site-specific data collection.
Engage with industry stakeholders and experts to enhance data accuracy, as their insights can inform better characterizations of emissions sources. Additionally, provide training for inventory personnel on Tier 2 methodologies to ensure proper implementation and data gathering techniques.  
Establish a robust documentation process that clearly outlines any new methodologies used and the rationale behind these changes. Finally, incorporate regular quality checks and revisions to this enhanced inventory, ensuring continuous improvement in data accuracy and reliability over time, while maintaining compliance with reporting requirements. This systematic approach leads to a more comprehensive and scientifically grounded emission inventory. 

04 Refine emission factors and sectors

Develop locally-specific emissions factors. Consider adding fire emissions if they are not included in your agriculture or land-use sector. Specific can mean using the national value of the Net Calorific Value and carbon content of fuel per fuel type to calculate CO2 emission factor, but it can also mean determining emission factor proper to an industry from their Continuous Emissions Monitoring System or periodic monitoring, etc. This journey does not end, it is a continuous process

05 Replicate steps 3-10 from Stage 1

Decide on a common base year for both GHG and air pollutants and repeat the process used for your Stage 1 and 2 inventory ensuring that you include all relevant sectors and pollutants. Identify potential errors or gaps in your inventory and adjust methodologies or data sources to enhance accuracy and reliability.

06 Generate GIS emission maps

Generating visualizations of emission inventory activity data using geographic coordinates enhances spatial analysis and understanding of emissions sources. Start by collecting accurate geographic coordinate data for various emission sources, such as roads (via Google Maps®), facilities, industrial stacks, and residential areas. Use Geographic Information Systems (GIS) software to visualize this data, allowing for overlaying emissions data onto maps to reveal geographic patterns and hotspots. 
Create thematic maps to illustrate emission densities by area, making it easier to identify regions with high pollution levels. Incorporate layers for different emission sources, enabling comparison between residential, industrial, and transportation emissions.  
Consider using color-coded markers or gradients to represent varying emission levels, facilitating quick interpretation of data. Additionally, integrate interactive elements in your visualizations, allowing users to zoom in on specific areas or click on facilities for detailed emission data. Regularly update these visualizations to reflect changes in operations, ensuring the data remains current and relevant for decision-making and public communication. 

07 Create gridded emissions modeling as input for air quality modeling

Coordinate with your air quality modeling team (see Source Attribution Guidance Stage 3, Step 7) using the spatially resolved inventory. To develop gridded emission fields for air quality modeling, convert point source emissions into grid cell values based on their locations and emission rates, allocate the transport emissions to road segments, etc. Incorporate temporal factors, such as activity data and seasonal variations, to enhance accuracy. Develop category- and subcategory-specific temporal profiles where data permit, such as hourly or monthly profiles for road transport and monthly operating profiles for major industrial sources. Document whether each profile is based on locally observed activity, administrative data, or transferred default assumptions. The EMEP/EEA guidance linked below provides a number techniques for spatially allocating point sources and disaggregating diffuse sources as well as estimating the uncertainty in these methods. Use GIS tools to aggregate emissions data into designated grid cells, ensuring that the spatial resolution reflects the modeling requirements. Validate the air quality model outputs against measured air quality data, ensuring your gridded emission fields provide robust inputs (e.g. appropriate spatial resolution, accurate intensities) for air quality assessments (see Source Attribution Guidance Stage 3, Step 10). 

08 Use the emissions inventory for policy tracking

The emission estimation over time is a critical tool for tracking air quality policies and assessing their effectiveness in reaching predefined objectives. By monitoring emissions from specific sectors, such as road transport, one can evaluate the impact of policies concerning age limits or technological upgrades for vehicles. Similarly, emissions can be assessed against new regulatory limits imposed on industries and power plants, allowing for timely feedback on compliance and environmental impacts. 
Additionally, an emission inventory can help track the effectiveness of incentive programs designed to promote cleaner technologies or alternative fuels, such as electric vehicles or renewable energy sources. By analyzing trends before and after policy implementation, stakeholders can determine if emissions reductions are occurring as anticipated. Generally, this kind of tracking effectiveness might need higher Tiers (Tier 2 or 3) in emission estimation.
Moreover, the inventory can facilitate identifying sources contributing to air quality violations, guiding targeted interventions. Regularly updating the inventory enables policymakers to adapt strategies as needed, ensuring continuous improvement in air quality outcomes. Finally, utilizing emissions data in public reports can enhance transparency, engaging the community and stakeholders in the policy process and fostering public support for ongoing air quality initiatives. 

09 Establish a cycle of continuous improvement

Emission inventories are never truly complete; they require ongoing improvement and updates to maintain their relevance and accuracy. Establishing a cyclical process is essential for achieving higher-quality inventories over time. Begin by implementing a routine cycle that includes a quick update every two years. This update should leverage macroeconomic indicators, such as GDP growth, industrial output, and transportation patterns, as well as readily available updated local indicators like energy consumption and population growth. These data points can provide a foundational understanding of emission trends and shifts in local activities. 
In addition to biennial updates, plan for a more comprehensive update every four years. This detailed update should involve a thorough review and revision of data collection methodologies, the incorporation of improved emission factors, and the integration of technological advancements. Additionally, engage stakeholders throughout this process to ensure diverse input and validation of data. 
Establish a feedback loop where insights gained from each update inform the next, enabling the identification of data gaps and opportunities for methodological enhancements. This iterative approach will increase the accuracy of the inventory, build stakeholder confidence, and support informed decision-making for air quality management. Continuous enhancements can also be supported through training for personnel involved in data collection and analysis, ensuring that the team remains updated on best practices. By fostering a culture of improvement and adaptation, your emission inventory will evolve into a robust tool that effectively reflects changing circumstances and supports air quality objectives.