CarbonCAD

Production and manufacturing engineers don't have a way to efficiently measure the externality variance impacts of individual projects in a way that the finance team can use for sustainability-linked debt, grants, tac equity, and carbon credits.

carboncad.climastry.com

CarbonCAD is a partial life cycle based environmental assessment tool that enables engineers, artisans, and makers to compare the relative environmental effects or trade-offs across alternative manufacturing process design solutions at the project design and management phases. These outputs are applicable in sustainability-linked business cases to finance the immediate abatement of externalities in relevant production processes. Some of CarbonCAD’s specific features include:

• The ability to model the manufacturing facility or workcell and process envelope(s); 
• The ability to build emissions and externality “layers” upon pre-designed production processes.
• the ability to model maintenance and replacement life cycle effects based on process type, location and a user defined expected life (“run”) of the product or production process;
• a grid sensitive calculator to convert operating energy to primary energy and emissions and/or other externalities to allow users to compare embodied and operating energy environmental effects over the processes life (requires a separate estimate of operating energy as an input);
• a “scenario analysis” module, which simulates a project/credit’s time-to-retirement and abatement durability relative to actual and expected production volume;
• a contextual, fluid, and federated “artificial intelligence” that iteratively challenges externality point data with engineers/users.

CarbonCAD can measure the environmental impacts of:

• Material manufacturing, including resource extraction and recycled content
• Related transportation
• On-site construction
• Regional variation in energy use, transportation and other factors
• Process type and assumed lifespan
• Maintenance, repair and replacement effects
• Demolition and end-of-life disposition
• Operating energy emissions and pre-combustion effects

However, user training emphasizes partial-LCA modeling and a typical project may not include all of these data points simultaneously to increase the fidelity of the process component being studied.

Life Cycle Inventory Results Table:

• Energy – total and primary energy consumed
• Air Emissions
• Water Emissions
• Land Emissions
• Resource Use

or Traditional LCA Measures:

• Total Primary Energy
• Non-Renewable Primary Energy
• Fossil Fuel Consumption
• Acidification Potential
• Global Warming Potential
• Human Health Criteria
• Ozone Depletion Potential
• Smog Potential
• Eutrophication Potential

or Advanced Externality Factors:

• Carbon Dioxide
• Methane
• Nitrous Oxide
• Chlorofluorocarbons
• Hydrofluorochlorocarbons
• Hydrofluorocarbons
• Chlorocarbons
• Hydrochlorocarbons
• Bromocarbons
• Hydrobromocarbons
• Halons
• Fully Fluorinated Species
• Halogenated Alcohols
• Ethers
• Furans
• Aldehydes
• Ketones
• SDS-listed Compounds
• Miscellaneous Compounds

A comprehensive list can be found from the most recent IPCC report, currently AR6: https://www.ipcc.ch/report/ar6...

or Future Externality Factors:

• Biodiversity (i.e. eDNA) (Kunming-Montreal Global Biodiversity Framework aka GBF)
• Industry-specific disclosure requirements (Corporate Sustainability Reporting Directive aka CSRD)
• Environmental Production Declarations (EPDs)
• Green/Social/Impact Bonds (Sustainable Finance Disclosure Regulation aka SFDR)

Detailed LCA Results

Results from an individual design can be seen in summary tables and graphs by externality group and life cycle stage. Detailed tables and graphs show individual energy use by type or form of energy and emissions by individual substance for both the externality group and life cycle stage breakouts.

Make Flexible Comparison of Alternate Process Designs

Accommodating up to three comparisons at once, CarbonCAD allows users to change the design, substitute materials, and make side–by–side comparisons for any one or all of the environmental impact indicators.

This is a future of work tool for CAD farms. Hundreds of thousands of engineers and other knowledge workers are facing early retirements or inability to even enter the job market because optimization for OpEx alone is not delivering the strongest alpha at the given concentration of human capital.

Engineers must learn how to express externality deltas so they can begin to finance their own design choices instead of relying solely on project budgets.

Engineering, alongside medicine and law - is a key route to class transition and wealth building, and without it, socioeconomic instability is incubated.

This is best discussed over coffee.

But this is our third product iteration and my third team. The most recent collapsing only 2 months ago.

We first built an ESG disclosure platform, then a carbon accounting platform, and after a grant from UK for statistics research, and bunch of misadventures, landed on CarbonCAD.

I originally started this in 2020 with a cofounder in Costa Rica but she wanted to go into crypto/web3 and I wanted to go the securities route. The second team I built grew to 13 over the next three years with people who believed in what we were doing and were willing to work for free. I liked this team but after 3 failed pre-seeds where customers were waiting on delivery, the team wasn't fundable.

So I rebuilt a team of 5 developers and data scientists and two general mangers, and I stepped aside as CEO to Chief Scientific Officer where I'm focusing on non-dilutive funding and product ownership.

The GM Profiles (Confidential):

Tina: Fortune 20 Chief Risk Officer

Anastasia: Citi VP, CFA, CPA

Three pilots, 1 co-development contract valued at $500k

Robust digital infrastructure + product ownership and technical team building

Following the theory of change,

Please see detailed attachment on impact OKRs.

Piece Rate Emissions Factors or PREF, are an evolutionary development of process-based emission factors that create a direct link between specific emissions factor regression variables and projects that impact their emissions intensity or rate of emissions output. The variables of the regression model used for manufacturing specific PREF can include variables such as energy consumption, raw material inputs, or human inputs; with an acute emphasis on industrial process types such as lathing, milling, and associated work instructions or programmable logic controller (PLC) data.

In the PREF equation, represents the production quantity at a given production quality, including waste streams and their associated impacts. The emissions factor is a coefficient that captures the emissions intensity of the manufacturing process per mapped emissions factor variable identified on the manufacturing line. Piece-rate emissions factors (PREF) set regression analysis (LCA) equal to emissions factor regression variables. Said regression variables are statistically associated with projects that significantly impact their emissions intensity or rate of emissions output.

PREF =  +                                                                           (5)

where;                                                                                                                                                                    

The piece-rate methodology can be applied to life cycle analysis (LCA) by breaking down the life cycle of a product into individual stages or tasks, and then calculating the environmental impact associated with each stage or task. In this context, the "piece rate" () would be task completed, and the quantity of output would be the amount of the product produced at each stage or task. Where the regression variable () is environmental impact associated with each unit of the given output or task.

To find the emissions rate of running a given manufacturing line, we use a multiple regression model that includes the environmental impact of each stage or task as individual regression variables. The equation can be expressed as:

                                         (6)

where;                                                                                                                                                                                      

= intercept, the baseline level of emissions when all PREFs are equal to zero                              

 associated with                                                                    one-unit increase in each PREF, holding all other PREFs constant                          = Error, representing random variation not explained by PREFs                                                        

Multiple PREFs can be altered by multiple projects simultaneously in real-world practice. However statistical best practice changes variables (executes projects) sequentially to keep the other variables independent. The PREF approach allows for more targeted reductions in emissions intensity or rate of emissions output, since the method identifies specific variables that drive emissions and thus can be used to implement targeted reductions. “Manufacturing Line” can be substituted for “Product”; however, a consistent facility level accounting methodology needs to be followed. This can vary by organization and product.