Technology- and facility-level energy, cost, and environmental performance in U.S. chemicals, cement, iron and steel, food, and non-manufacturing industries

This U.S. industrial facilities and technology dataset is a technology-
and facility-level collection of technological, cost, energy, and
emissions attributes for six manufacturing and three non-manufacturing
U.S. industries. The dataset is a JSON array organized by industry. Each
industry entry (except for mining and agriculture) contains four sections:
author list, assumptions, emerging technologies, and existing facilities.
The non-manufacturing industry inventories 18 solutions across
agriculture, mining and construction sectors and 6 categories, documenting
qualitative benefits and quantitative energy/emissions reduction
potentials with low/average/high estimates. The dataset integrates data
exclusively from publicly available data sources including EPA's
Greenhouse Gas Reporting Program, U.S. Geological Survey, industry
reports, peer-reviewed research to provide a unified resource for energy
systems modeling and analysis. The assumptions section standardizes units
and conversions and provides fuel and feedstock prices for operating
expenditure (OPEX) calculations, Chemical Engineering Plant Cost Index
(CEPCI) values for capital cost (CAPEX) harmonization, and price/inflation
indices to align values to a common base year. Emerging technologies with
minimal to no market share in U.S. commercial-scale production facilities
are characterized across six industries: ammonia (10 processes including
autothermal reforming, renewable hydrogen-based, biomass gasification,
methane pyrolysis, and ATR with CCS); cement (26 processes including
conventional wet/dry kiln variants, low-SCM dry kiln with
preheater+precalciner, full CCS, and full electrification options);
ethanol (8 processes including dry mill and wet mill variants, electrified
process heat via heat pumps, and dry mill BAT with CCS); ethylene and
propylene (21 processes including electrified steam cracking with
electricity-cost bands, ethanol-to-ethylene, MTO, and NGL-to-olefins);
iron and steel (10 processes including H2DRI–EAF, NGDRI–EAF with CCS, and
molten oxide electrolysis, with varied scrap utilization scenarios); and
food (9 cross-cutting process-heat decarbonization options such as
hot-water and steam heat pumps, electric boilers, RNG/biogas boilers, and
solar thermal steam). The existing facilities section covers: ammonia (36
facilities across 20 states; SMR 97.2%, coal gasification 2.8%); cement
(97 facilities across 35 states; conventional dry kiln 90.7%, wet kiln
9.3%); ethanol (201 facilities; dry mill 95.5%, wet mill 4.5%);
ethylene/propylene (35 facilities across 6 states; steam cracking 100%);
iron and steel (102 facilities across 31 states; EAF 86.4%, BF–BOF 7.8%,
DRI 2.9%, hybrid BF–BOF/EAF 0.9%); and food (production and energy
intensity by state and five subsectors: animal slaughtering, dairy, fruit
and vegetable, grain and oilseed milling, and sugar).  The
dataset offers a broad range of use cases through its standardized JSON
structure and comprehensive documentation, potentially offering
interoperability with common analytical tools. Primary uses envisioned for
this dataset include energy systems optimization modeling, multisectoral
and integrated assessment modeling of the industrial sector or the broader
economy (but with higher fidelity of technology characterization),
technology assessment comparing conventional and emerging production
routes, spatially resolved production capacity planning analysis, and
economic analysis of technology deployment costs. The dataset's
facility-level granularity enables bottom-up modeling approaches while
maintaining compatibility with top-down sectoral analyses. Technical
features enhancing reusability include standardized coordinate systems
(WGS84) for GIS integration, consistent economic units (2018 USD) for
temporal comparisons, and modular data structure supporting selective
extraction.