Detailed data on hard-to-abate industrial sectors is crucial for developing targeted decarbonization measures in energy system modeling, yet such information is rarely available through open sources. This paper presents a top-down methodology to estimate detailed industrial site-level energy and emissions databases by integrating and expanding publicly available data. The methodology addresses three key challenges: (1) the disaggregation of national energy consumption data to site level, (2) the categorization of process heat by four temperature ranges (<100 °C, 100 °C-500 °C, 500 °C-1000 °C, and >1000 °C) and direct use of electricity, and (3) the integration of process emissions from feedstock use in hard-to-abate industrial sectors. The approach is demonstrated through application to the Italian industrial sector for the year 2022, resulting in a database that documents site-specific consumption across seven energy sources: solid fossil fuels, manufactured gases, oil and petroleum products, natural gas, biofuels, non-renewable wastes, naphtha and electricity. The method can be replicated for other European countries, providing researchers and policymakers with a standardized approach to create detailed industrial energy databases. Results show that the chemical and petrochemical sector dominates the industrial energy landscape of Italy, followed by iron and steel, non-metallic minerals, and paper and pulp. The geographical distribution reveals a concentration of major industrial facilities in northern Italy, with notable exceptions including significant steel production in Taranto (south) and petrochemical complexes in Sicily and Sardinia.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11870218PMC
http://dx.doi.org/10.1016/j.dib.2025.111365DOI Listing

Publication Analysis

Top Keywords

site-level energy
8
energy consumption
8
consumption data
8
hard-to-abate industrial
8
industrial sectors
8
detailed industrial
8
industrial energy
8
energy
7
industrial
7
data
5

Similar Publications

Detailed data on hard-to-abate industrial sectors is crucial for developing targeted decarbonization measures in energy system modeling, yet such information is rarely available through open sources. This paper presents a top-down methodology to estimate detailed industrial site-level energy and emissions databases by integrating and expanding publicly available data. The methodology addresses three key challenges: (1) the disaggregation of national energy consumption data to site level, (2) the categorization of process heat by four temperature ranges (<100 °C, 100 °C-500 °C, 500 °C-1000 °C, and >1000 °C) and direct use of electricity, and (3) the integration of process emissions from feedstock use in hard-to-abate industrial sectors.

View Article and Find Full Text PDF

A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or 'proximal' remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site-level eddy-covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high-spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions.

View Article and Find Full Text PDF
Article Synopsis
  • Tidal wetlands can absorb greenhouse gases, but methane emissions can vary due to environmental factors and human activities.
  • Land managers require detailed maps of methane properties in these wetlands for effective restoration and greenhouse gas inventories, yet current sampling methods don't align well with broader mapping products.
  • Research involved sampling 27 tidal wetlands, revealing that sulfate concentration is the strongest predictor of methane levels, while salinity also plays a significant role; future studies should focus on understanding local environmental influences on methane variation.
View Article and Find Full Text PDF
Article Synopsis
  • * Sites with warmer, wetter conditions and more species generally saw increased biomass, while arid, species-poor areas experienced declines, alongside notable changes in seasonal plant growth patterns.
  • * Factors like grazing and nutrient input didn't consistently predict biomass changes, indicating that grasslands are undergoing substantial transformations that could affect food security, biodiversity, and carbon storage, particularly in dry regions.
View Article and Find Full Text PDF

This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!