Funding
NSF Phase I
Methodology developed under a U.S. National Science Foundation Phase I SBIR grant. Specific grant number disclosed on the technical whitepaper.
Methodology
The science behind every number.
TotalView is the first marginal Life Cycle Impact platform for energy — peer-reviewed, ISO 14040/14044-aligned, NSF-funded. Every number we publish has a documented data source, a documented method, and propagated uncertainty.
Beyond marginal carbon
Same dispatch-aware lens. Full chain of consequences.
A generation of platforms moved energy accounting from the average grid emissions factor to the marginal one — telling you which fossil unit your project actually displaced, hour by hour, and how many tonnes of CO₂ that avoided. That’s a real step forward, and it’s now widely adopted.
TotalView is the next step. We apply the same dispatch-aware, hour-by-hour lens to the full chain of consequences that comes with every megawatt-hour: particulate matter that lands in lungs, sulfur compounds that acidify watersheds, heavy metals that persist in soil, water consumed in cooling, land disturbed in mining. Each is mapped from the displaced generator and fuel basin to the place it would have done its harm, and translated into peer-reviewed endpoint currencies — DALYs, species·yr, USD.
This is what we mean by marginal Life Cycle Impact Assessment: the rigour of marginal carbon, applied to the fourteen ReCiPe 2016 impact categories. Same data sources. Same hourly resolution. A fundamentally bigger picture.
What is LCA?
Beyond carbon. Across the full chain.
Life Cycle Assessment (LCA) is the international standard for quantifying the environmental consequences of a product or system across its full life — from raw materials through manufacturing, operation, and end of life. The methodology is codified in ISO 14040 (principles and framework) and ISO 14044 (requirements and guidelines).
Most renewable-energy reporting collapses LCA into a single number — kilograms of CO₂. That number is real, but it answers exactly one question. TotalView produces the full set: the air-quality footprint that lands as DALYs of human health, the freshwater and ecosystem effects, the economic value of resource depletion, and the avoided counterpart of each.
We don’t invent factors. We draw on the leading Life Cycle Inventory (LCI) databases for upstream emissions and the most cited impact-assessment framework (ReCiPe 2016, hierarchist). The novelty is what we do at the grid edge — modeling the actual fuel each megawatt-hour displaces, hour by hour, in the balancing authority where it landed.
What we measure
Fourteen impact categories. Three areas of protection.
Drawn from the ReCiPe 2016 framework. Mid-point categories quantify the physical effect; end-point categories translate it to human health (DALYs), ecosystem quality (species·yr), and resource depletion (USD).
Mid-point indicators
- Climate change (kg CO₂-eq)
- Fine particulate matter (kg PM₂.₅-eq)
- Photochemical ozone formation
- Stratospheric ozone depletion
- Ionizing radiation
- Terrestrial acidification (kg SO₂-eq)
- Freshwater & marine acidification
- Terrestrial eutrophication
- Freshwater & marine eutrophication
- Terrestrial, freshwater, marine ecotoxicity
- Human carcinogenic toxicity (kg 1,4-DCB-eq)
- Human non-carcinogenic toxicity
- Land use
- Mineral & fossil resource scarcity
End-point indicators
- Human health — DALYs
- Disability-adjusted life years lost to particulate matter, toxicity, and climate change. Lets a CFO compare a megawatt-hour to a public-health intervention.
- Ecosystem quality — species·yr
- Fractional species loss from land use, ecotoxicity, and acidification. Speaks to biodiversity disclosures (TNFD, CSRD) without the hand-waving.
- Resource depletion — USD
- The economic cost of depleting non-renewable resources, in 2013 USD per ReCiPe. Turns a procurement choice into a balance-sheet line.
Hourly grid displacement
Annual averages hide the actual fuel.
Solar at noon in MISO doesn’t displace the same fuel as wind at 3 a.m. in SPP. Annual averages — used by most reporting frameworks — obscure that difference, and routinely under-count the value of well-timed renewables while over-claiming the value of poorly-timed ones. Marginal accounting answers the harder question: when a megawatt-hour shows up, what actually changes on the grid?
That question is harder than it sounds. Grid dispatch is opaque: there is no public per-unit emissions feed; wholesale markets clear at zonal or aggregate level; and the marginal response is shaped by physics — energy balance, capacity headroom, ramp-rate limits — that a naive regression on demand cannot capture. A correlation model finds patterns; a physical model finds the machinery underneath them.
TotalView’s grid-displacement model is physics-informed. During training, the model is constrained to respect energy balance, generation capacity limits, and ramp-rate physics — it cannot fit a parameter set that violates the dispatch laws that govern real grids. It is then fit to seven years of observed generation data (EIA-930 across 47 U.S. balancing authorities, ENTSO-E Transparency Platform across 34 European member-state zones, Elexon BMRS for Great Britain). The model produces, for each of the 8,760 hours of the year and each balancing authority, the marginal fuel mix that would respond to an incremental megawatt-hour — and which generators would absorb the change.
We’re deliberately leaving the architecture and parameter set out of the public methodology — that’s in the peer-reviewed whitepaper, and partially in the patent filings. What lives here is the validation: every claim TotalView publishes is stress-tested against the grid’s observed behavior across four lenses.
- Empirical comparison. Modelled marginal shares are compared against hour-over-hour generation deltas in the training data.
- Physical plausibility. Results are checked against known dispatch characteristics — MISO is coal-heavy on the margin; PJM swings to gas peakers in shoulder hours; GB is gas-dominated.
- Backtesting. The model is run on grid conditions before large renewable projects came online historically, and its predicted displacement compared against the actual observed change after they came online.
- Uncertainty propagation. Pedigree-matrix uncertainty per ISO 14044 §4.2.3.6 propagates from input data quality through to the published endpoint values. Customers see the confidence interval, not just the point estimate.
The model is retrained quarterly as new EIA-930 / ENTSO-E / BMRS data accumulates and as the grid fleet changes — large coal retirements, new gas peaker capacity, accelerated renewable build-out all shift the marginal response, and the model has to track that. Where the model is at its limits (very clean grids with near-zero fossil margin — Sweden, parts of Norway), we publish the limitation, not a confident wrong number.
47
U.S. balancing authorities
34
EU member-state zones
8,760
Hours modeled per year
30-yr
Cumulative lifetime view
Spatial allocation
A solar farm in Wisconsin can deliver health benefits to Indiana.
Standard LCA tools apply the same per-MWh damage factor to a project regardless of which fossil generator it actually displaces, regardless of who lives downwind, regardless of where the coal came out of the ground. Two identical 100 MW gas-displacement projects — one in Cincinnati (high baseline asthma, Ohio-Valley ozone, dense downwind population) and one in eastern Wyoming (low background, cool, sparse population) — receive the same per-MWh ozone-DALY credit under ReCiPe. They shouldn’t.
TotalView’s spatial allocation traces every kilogram of avoided pollutant to the place it would have done its harm. Combustion-pathway impacts attribute to the displaced generator and its airshed. Upstream-pathway impacts attribute to the fuel-extraction basin (Powder River, Marcellus, Permian, Appalachia…). Climate impacts attribute globally — well-mixed, everywhere.
Worked example
A solar farm in Wisconsin displacing a coal plant in Indiana delivers:
- PM2.5 health benefits to communities along the Wabash River (not Wisconsin)
- Avoided mining ecosystem damage to the Powder River Basin in Wyoming (not Indiana, not Wisconsin)
- Climate benefits to the global atmosphere (well-mixed; everyone)
This is built by composing the peer-reviewed spatial models the atmospheric and LCA communities have already converged on:
- InMAP ISRM v1.2.1 — reduced-complexity atmospheric model, Tessum et al. 2017, peer-reviewed and used widely in EPA and environmental-justice work. Source-receptor matrix on a 1–48 km variable-resolution grid.
- EASIUR — county-resolution marginal damages from photochemical ozone (Heo & Adams, peer-reviewed).
- LC-IMPACT 2019 — ecosystem damage from acid and nitrogen deposition, country-resolution.
- USEtox 2.14 — multi-media toxicity damages, sub-continental fate-and-transport.
- ReCiPe 2016 — globally well-mixed categories (climate change, stratospheric ozone depletion).
The novel work is the integration: stitching displaced-generator inventories from the marginal-dispatch model into a multi-engine spatial pipeline that anchors every category to consistent LCA totals while honestly disclosing different spatial resolutions per category. Customers see which model powered each category, at what resolution, alongside every result.
European and UK markets get an additional piece: a congestion-aware allocation. When a renewable project’s zone has saturated interconnectors, electricity physically can’t flow to the generators it would otherwise displace. We combine zonal price divergence and interconnector saturation signals into a congestion factor — a 50 MW Dutch solar build on a congested grid hour may effectively displace 10.34 MWh of gas instead of 15.3 MWh, because borders were at thermal limits.
Illustrative — 853 GWh renewable build, mixed U.S. fleet displacement, 2025
848 DALYs avoided per year — broken out by where the benefit physically lands:
- Local — 50 km of plant
- <1%
- Regional — airshed
- 44%
- Global — atmosphere
- 55%
Direct vicinity of the displaced generator. Primary PM, water, land use.
PM2.5 dispersion footprint, downwind ozone, acidification, ecotoxicity. Mapped to actual InMAP ISRM polygons.
Climate change and stratospheric categories. Well-mixed; everywhere benefits.
Sources of trust
Independent footing for every claim.
External recognition
World Economic Forum case study
Featured by the WEF as a global case study in infrastructure impact quantification. Specific publication cited in the technical whitepaper.
Standard
ISO 14040 / 14044
Methodology aligned with ISO 14040 (principles) and ISO 14044 (requirements). Independent critical review framework is currently in progress; report status disclosed per project.
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