How to estimate economic value, jobs and emissions at industrial clusters level

The industrial sector currently contributes 30% of global carbon dioxide (CO2) emissions, necessitating concerted decarbonization efforts at scale. Industrial clusters can achieve this through effective collaboration and sharing of infrastructure while also harmoniously delivering economic and social benefits.

The World Economic Forum’s Transitioning Industrial Clusters initiative, in collaboration with Accenture and EPRI, aims to accelerate the decarbonization of hard-to-abate industrial sectors within clusters, enhancing energy efficiency and maximizing job creation and economic competitiveness.

A key step towards transitioning industrial clusters is to track and report credible key performance indicators (KPIs) across greenhouse gas emissions, job creation and protection and gross domestic product (GDP) contribution by industrial players. Cleveland State University has demonstrated a high-level approach for these three KPIs, focusing on industrial clusters in the United States.

Cleveland State University has leveraged the Ohio Clean Hydrogen Hub Alliance industrial cluster (one of 23 signatory clusters participating in the initiative) to illustrate the potential approach for KPI calculation in the United States, which could also be applied in the United Kingdom and the European Union (EU).

The university’s methodology uses publicly available bottom-up emissions data. Emission intensities by sector are then used as a rule of thumb to estimate the jobs and GDP contribution on the cluster level.

The cluster is part of the Appalachian Regional Clean Hydrogen Hub, with more than 150 signatory parties. It was formed to explore hydrogen’s potential to supercharge economic growth within Ohio’s industrial core.

It includes the state’s large-scale industrial facilities, which emit more than 25,000 metric tonnes of CO2 equivalent per year, for utilities, pipeline transportation, oil and gas extraction and mining, durable and non-durable goods manufacturing and waste management.

It has encompassed well-noted activities, such as Stark Area Regional Transit Authority’s operation of one of the largest hydrogen fuel cell-powered bus fleets in the Western Hemisphere. This shows how the cluster is leading clean hydrogen technology advancement, underscoring its economic and environmental significance.

Clusters in the United States can use data readily available from federal sources at the regional level to calculate KPIs.

The Environmental Protection Agency’s Greenhouse Gas Reporting Programme provides greenhouse gas emissions data from large industrial facilities. It captures most US greenhouse gas emissions, including methane, nitrous oxide and fluorinated gases such as hydrofluorocarbons and perfluorocarbons.

Under this programme, facility owners in hard-to-abate sectors, including power generation, manufacturing and waste management, annually report point source emissions – those produced at a known location. The submitted data is then reviewed regularly by the Environmental Protection Agency for quality and accuracy.

No publicly available data source directly measures the emissions impact of jobs or GDP at the facility or cluster level. However, the US Bureau of Economic Analysis provides KPIs by state, often with industry detail (for example, annual jobs and GDP for motor vehicle manufacturing in Ohio). If GDP and jobs state-level data are unavailable, national data can also be used.

That said, industrial clusters do not necessarily align neatly with state boundaries. Therefore, cluster-specific KPI estimations can be performed by calculating the emissions intensity of GDP or jobs for a given region and sector and then applying these rules of thumb to the combined facility-level emissions within a cluster.

Determining the emission intensity of GDP and employment in a given region can indirectly calculate cluster-level KPIs.

For GDP, the calculation involves dividing the attributed emissions for the sector by the value added over the year. Emissions intensity of employment (e.g. CO2 emissions per 1,000 jobs) can be calculated in the same manner using Environment Protection Agency and Bureau of Economic Analysis data for various sectors, using number of jobs created or protected in place of GDP.

The second step is to apply the facility-level emissions data for greenhouse gases gathered from within the cluster boundary to sectorial emissions intensity estimates, calculate GDP and job metrics at a facility level and then aggregate this to show KPIs at the cluster level.

The table below shows the KPIs by aggregated sectors for the Ohio Clean Hydrogen Hub Alliance industrial cluster, which represents about 11% of the state’s economy and 8% of its workforce.

European industrial clusters can similarly calculate their core KPIs using publicly available data and rules of thumb from sector-level emissions intensities.

As with the United States, emissions intensity at a regional level, per sector, can be calculated from attributed emissions data for the EU and the United Kingdom. Attributed emissions data can be found in the European Industrial Emissions Portal and the National Atmospheric Emissions Inventory, respectively. Data on jobs and GDP at a regional level are available from Eurostat and the Office for National Statistics, for the EU and United Kingdom respectively.

The same method for Ohio can be applied to the facility-level emissions and then aggregated to calculate specific cluster KPIs from the emissions intensity measurements.

While rule-of-thumb methods help clusters estimate impact, more accurate approaches are needed for tracking progress. Regulation is progressing in this sense, with mandatory reporting rules emerging, such as the EU’s Corporate Sustainability Reporting Directive. Accurate reporting requires a strong technology foundation, with integrated enterprise platforms improving data collection and management.

Technologies, including AI, machine learning and blockchain, enhance data processing, forecasting and traceability, while dashboards enable real-time monitoring. The EU’s directive emphasizes digital reporting standards, data integration and auditability, reflecting the global shift toward transparent environmental, social and governance reporting.

Measuring industrial cluster metrics is key not only for evaluating decarbonization strategies but also for enhancing the evidence base that can strengthen funding applications.

In the United States, the Appalachian Regional Clean Hydrogen Hub secured up to $925 million from the Department of Energy – via the Bipartisan Infrastructure Investment and Jobs Act​ – by demonstrating viability, job creation and economic growth. Similarly, the HyVelocity Hub was awarded up to $1.2 billion, aiming to reduce air pollution and create 45,000 jobs under the Justice40 programme.

In the United Kingdom, the carbon capture, utilization and storage government funding programme assesses social, economic and environmental KPIs. After proving their value for money to consumers and taxpayers, HyNet and Humber were selected to negotiate with the government to receive Track-1 funding.

These funding examples highlight the long-term economic benefits, which can help alleviate concerns about job loss, offshoring, and reduced competitiveness during the net-zero transition.

Balancing economic resilience with environmental goals is essential for a successful energy transition. Clear tracking and benchmarking of these balanced KPIs can ensure a harmonious and successful journey towards decarbonization.