Reagan Cerci, Senior Research Analyst at Boundless Impact Research & Analytics, also adheres to standards such as ISO 14040/44, as well as databases such as Ecoinvent, when conducting LCAs for alternative proteins companies. Also like Briand, she believes that transparency is key to success – along with the need to acknowledge the shifting sands facing all researchers in this sector.

“Accuracy and reliability come down to data quality, transparency, and sensitivity analysis,” Cerci comments. “Given how rapidly the alternative protein landscape is evolving, we prioritize primary data collection directly from producers wherever possible – whether it’s energy use, inputs, or yields. Where direct data isn’t available, we document assumptions meticulously and conduct uncertainty analyses to highlight variability. Importantly, we treat LCAs as living documents that must evolve as the technology and supply chains mature.”

Cerci works across all facets of the alternative proteins industry, so is ideally placed to comment on specific challenges each part faces when conducting LCAs. For precision fermentation, she says that the work is often IP-sensitive, “so firms are reluctant to share upstream process data such as titers, yields, or energy demands. Fermentation inputs (e.g. sugars, growth media) can also vary widely.”

For cultivated meat, she observes, “Much of the tech is still pre-commercial for the most part, so we’re often modeling lab-scale processes and projecting to industrial scale, which introduces huge uncertainty. Cell growth rates, media recycling, and bioreactor energy efficiency are all highly variable and not standardized. Broadly across the industry, it is difficult to get accurate data for cultivation media due to IP protections.”

And with regard to plant-based proteins, Cerci notes, “Agricultural inputs are more accessible, but there’s often a lack of granularity in how crops are grown (e.g. rainfed versus irrigated), processed, and transported, especially across global supply chains.”

When asked how assumptions about energy sources (e.g. renewable versus fossil-based) impact LCA results for alternative proteins, Cerci emphasizes that they can make or break the carbon footprint. “Energy is often the largest contributor to impacts, especially in alternative proteins. A system powered by coal versus one running on solar or hydro can differ by an order of magnitude in GHG emissions.” Hence, Cerci and the team at Boundless often run LCAs under multiple energy scenarios – baseline grid mix, 100% renewable, and transitional mixes – to show the range and help companies make region-specific decisions. “It’s also critical for identifying the marginal benefit of decarbonizing energy inputs,” she adds.

Cerci offers some valuable insight when discussing how LCAs for alternative proteins compare to those used for conventional animal agriculture. “Animal agriculture LCAs benefit from decades of data, especially for ruminants, but they often exclude key externalities such as land-use change or biodiversity loss,” she details. “They are also often inconsistent in allocation methodology as most animal agriculture is conducted for a variety of co-products, which then need to be individually assigned a portion of the carbon footprint. Using databases such as Ecoinvent can help standardize the conventional approach, but they limit the researchers’ ability to compare specific parameters.”

Cerci also points out that there is a gap in data for conventional fish products. “Fisheries can have impacts on fish population abundance, physical structures of environments, megafauna and top predator populations, and nutrient flows. Accidental fishing (commonly referred to as ‘ghost fishing’), resulting from discarded or broken gear left in marine ecosystems, can also have detrimental impacts on marine health. However, this is often difficult or impossible to accurately track due to a lack of reporting or knowledge.”

Putting this into context, she says, “Although most LCAs do not attempt to quantify these ecosystem impacts, it can be inferred that, as alternative proteins are producing fish meat without the necessity of fishing, they are avoiding these biodiversity and ecosystem impacts.”

In general, Cerci says that LCAs for alternative proteins are typically more detailed in modeling supply chains and energy use but often rely on early-stage data. She notes that researchers here face gaps in areas such as infrastructure impacts (e.g. stainless steel fermenters) or waste management. “Closing the gaps will require open-data sharing and more real-world, operational data from commercial producers,” she states.