The Forecasts dashboards are part of the SINAI Dashboards section in SINAI. Use these dashboards to review forecasted emissions, compare emissions by year, understand emissions intensity, and estimate carbon tax exposure.

Forecasts include:

To open a dashboard:

The Absolute Emissions dashboard shows forecasted emissions for the selected filters. Use this dashboard to understand projected emissions, compare emissions across years, and drill into the categories contributing to emissions.

This dashboard can show either:

Available filters may vary depending on your setup, but this dashboard may include:

This dashboard measures forecasted emissions or emissions intensity based on the selected View by option.

For emissions, the typical calculation is:

Total emissions = SUM(emissions_co2e)

For intensity, the dashboard normalizes emissions by the relevant business metric configured for your organization.

The dashboard applies the selected filters first, then displays the matching forecasted values.

The Absolute Emissions dashboard includes several views.

This chart shows emissions by year. It displays historical and forecasted emissions through future years.

A higher bar means that the year has higher emissions under the selected filters.

The Emissions breakdown chart shows the selected year’s emissions grouped by the selected breakdown category, such as Activity Data.

Use this view to identify the largest emissions contributors for the selected year.

The Emissions hierarchy section helps identify which business entities or operational areas have disproportionately high emissions or intensity.

Available hierarchy views may include:

In the Outlier view, entities farther to the right have higher emissions or intensity. The Y-axis is used only to visually separate points when emissions or intensity values are close together.

Start with a broad view, such as all business units and all facilities. Review the yearly emissions chart to understand the overall forecast trend.

Then select a specific year and use the emissions breakdown to identify the biggest categories contributing to emissions. Use the hierarchy section to find outliers or major contributors that may need further investigation.

The Absolute Emissions dashboard helps you understand where forecasted emissions are concentrated and how they change over time. It is often the starting point before reviewing detailed contributors or financial exposure from carbon tax.

The Emissions By Year dashboard shows emissions in a table by hierarchy level, source, and year. Use this dashboard to compare annual emissions across the business hierarchy and identify which sources contribute to emissions over time.

Available filters may vary depending on your setup, but this dashboard may include:

This dashboard measures emissions by year for each available hierarchy and source combination.

The typical calculation is:

Yearly emissions = SUM(emissions_co2e), grouped by hierarchy level, source, and year

The dashboard applies the selected filters, groups the remaining data by hierarchy and source, and displays emissions values across year columns.

This dashboard is structured as a table.

Read each row as a hierarchy path and source. Then scan across the year columns to see how emissions change over time.

Look for rows with consistently high values, sharp increases, or values that appear in forecast years after being low or zero in historical years. These rows may represent important emissions drivers or areas that need further investigation.

Use the Business Unit filter to narrow the table to one part of the organization.

The Emissions By Year dashboard provides the detailed year-by-year emissions data behind the Forecasts views. It is useful for auditing values, comparing historical and projected emissions, and identifying the specific hierarchy paths and sources that drive annual emissions.

The Carbon Tax (by lowest level) dashboard shows the estimated carbon tax impact at the most detailed available operational level.

This view is primarily a table. It helps you identify the specific business units, facilities, processes, activities, sources, or other low-level contributors with the highest estimated carbon tax exposure.

Available filters may vary depending on your setup, but this dashboard may include:

The Carbon Tax value is editable and acts as a scenario input.

This dashboard measures the estimated carbon tax cost at the most detailed hierarchy level.

The dashboard labels the calculation as:

tCO₂e * carbon tax

The typical calculation is:

Carbon tax amount = tCO₂e × carbon tax

Values are filtered by the selected business unit and calculated using the selected carbon tax value.

This dashboard is structured as a table.

Each row represents a hierarchy path or contributor. Each year column shows the estimated tax value for that contributor in that year.

Look for the largest values in the yearly columns. These rows represent the contributors with the highest estimated tax impact. Use the hierarchy levels to understand where the exposure sits in the organization or operations. Then use the Business Unit filter to narrow the table to a specific part of the business. Change the Carbon Tax value to test different tax assumptions.

This dashboard helps you move from a high-level tax estimate to the specific operational contributors behind it. That makes it useful for investigation, planning, forecasting, and prioritizing reduction opportunities.

The Carbon Tax Chart dashboard shows aggregate estimated carbon tax by year. Use this dashboard to understand historical and projected carbon tax exposure based on the selected business unit and carbon tax value.

Available filters may vary depending on your setup, but this dashboard may include:

This dashboard measures aggregate estimated carbon tax over time.

The dashboard labels the calculation as:

Aggregate Carbon Tax (tCO₂e * carbon tax)

The typical calculation is:

Aggregate carbon tax = SUM(tCO₂e) × carbon tax

The dashboard applies the selected business unit filter, calculates the estimated carbon tax using the carbon tax value, and displays annual totals.

A taller bar means a higher estimated carbon tax amount for that year.

Use this chart to compare estimated carbon tax exposure across years. Historical years and projected years appear in the same chart, with a projected marker showing where forecasted values begin.

If projected bars increase over time, carbon tax exposure is expected to grow under the selected assumptions. If you change the Carbon Tax value, the chart recalculates to show the estimated financial impact under the new scenario.

The Carbon Tax Chart translates emissions into estimated financial exposure over time. It is useful for forecasting, scenario analysis, and understanding the potential cost impact of future emissions.

The Carbon Tax Chart (source) dashboard shows estimated carbon tax impact over time for the selected source-level view.

Use this dashboard when you want to understand carbon tax exposure over time with additional year context.

Available filters may vary depending on your setup, but this dashboard may include:

The Carbon Tax value is editable and can be used as a scenario input.

This dashboard measures the estimated carbon tax over time using emissions and the selected carbon tax value.

The typical calculation is:

Carbon tax amount = tCO₂e × carbon tax

The dashboard calculates annual values for the selected data and displays them as yearly bars.
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Use this dashboard to understand how estimated carbon tax exposure changes over time.

A taller bar means a higher estimated tax amount for that year. If values increase over time, the selected source-level view may represent growing financial exposure under the current tax scenario.

Adjust the Selected Year or Carbon Tax to test different scenarios.

This dashboard helps connect forecasted emissions to projected financial exposure. It is useful for planning, forecasting, and understanding how carbon tax assumptions may affect future costs.

If you see No data available, the selected filters may not have matching data.

Try this:

For most forecast analyses, start broad and then narrow down:

This workflow helps you move from “What are my forecasted emissions?” to “Where are they concentrated?” and then to “What could the financial impact be?”