Lawrence Berkeley National Laboratory

We present a structured dataset that characterizes select technologies and facilities across U.S. industry. This dataset enables consistent, cross-sector techno-economic and energy/emissions characterization of U.S. industrial production for modeling and benchmarking analysis. The dataset covers six manufacturing sectors—ammonia, cement, ethanol, ethylene and propylene, iron and steel, and food, and three non-manufacturing sectors—agriculture, mining, and construction. Organized as an industry-level JSON array, the dataset integrates standardized assumptions, characterizations of incumbent and emerging technologies , and inventories of existing facilities. The assumptions harmonize units and prices, normalize operating costs using common feedstock and fuel base-lines, apply chemical engineering plant cost index factors to capital costs, and index all cost values to 2018 USD. For manufacturing sectors, the dataset provides facility-level inventories including 36 ammonia, 97 cement, 201 ethanol, 35 1 ethylene and propylene, and 102 iron and steel plants. Also included are state-level food production and energy intensities. For non-manufacturing sectors, the dataset catalogs 18 technology options rather than facility inventories, documenting qualitative benefits and low/average/high estimates of potential resource use, emissions, and cost reductions. Data sources include publicly available datasets from federal agencies, industry, and academic literature. The dataset supports energy systems optimization, capacity planning, integrated assessment modeling, and benchmarking analysis.