{"id":464557,"date":"2025-10-01T01:51:43","date_gmt":"2025-10-01T01:51:43","guid":{"rendered":"https:\/\/www.europesays.com\/uk\/464557\/"},"modified":"2025-10-01T01:51:43","modified_gmt":"2025-10-01T01:51:43","slug":"disaggregated-municipal-energy-consumption-and-emissions-in-end-use-sectors-in-germany-and-spain-for-2022","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/uk\/464557\/","title":{"rendered":"Disaggregated Municipal Energy Consumption and Emissions in End-use Sectors in Germany and Spain for 2022"},"content":{"rendered":"

The spatial disaggregation of FEC and emissions data is carried out in four steps, as illustrated in Fig.\u00a01<\/a>. The following sub-sections describe each step in detail.<\/p>\n

Fig. 1<\/b>\"figure<\/a><\/p>\n

The steps involved in the spatial disaggregation of emissions and Final Energy Consumption (FEC) data from country (NUTS0) to municipal (LAU) level.<\/p>\n

Data collection<\/p>\n

For the disaggregation work, this study utilizes three types of data: (i) FEC data for various sub-sectors (ii) emissions data for various sub-sectors and (iii) proxy data relevant to each sub-sector, which facilitates the disaggregation of FEC and emissions data.<\/p>\n

FEC and emissions data are collected at the national level, whereas proxy datasets are collected at various sub-national spatial resolutions. Figure\u00a02<\/a> illustrates the Nomenclature of Territorial Units for Statistics (NUTS) spatial hierarchy in Germany and Spain. Beginning at the national level (NUTS0), the hierarchy increases in spatial resolution through successive subdivisions: NUTS1 (federal states), NUTS2 (provinces), and NUTS3 (districts). Below NUTS3, municipalities \u2014referred to as Local Administrative Units (LAUs) \u2014represent the most granular level of administrative geography in both countries. The size of LAUs varies significantly. In Germany, the smallest LAU is Insel L\u00fctje H\u00f6rn, covering just 0.096 km2, while the largest is Berlin at 891.80 km2. In Spain, Emperador is the smallest LAU (0.026 km2) and C\u00e1ceres the largest (1,750.26 km2).<\/p>\n

Fig. 2<\/b>\"figure<\/a><\/p>\n

The spatial hierarchy in Germany and Spain, showing the availability of various proxy datasets from public data sources at different spatial levels. The data sources highlighted in orange and blue provide data only for Germany and Spian, respectively. Proxy data undergoes a step-wise spatial disaggregation to achieve final proxies at the LAU level. Emissions and FEC data, available at the NUTS0 level from Eurostat, is then disaggregated to LAU based on these final proxies.<\/p>\n

The details regarding the collection of each dataset are discussed in the following sections.<\/p>\n

Final energy consumption<\/p>\n

The FEC data, reported at the national level, is imported from the energy balance sheet published on Eurostat15<\/a>, for the year 2022. While the FEC data for both energy and non-energy use is reported on Eurostat, only the energy use FEC is considered here. The breakdown of the end-use sectors for emissions reporting on Eurostat is shown in Fig.\u00a03<\/a>.<\/p>\n

Fig. 3<\/b>\"figure<\/a><\/p>\n

Breakdown of end-use FEC sectors as reported in Eurostat, with Germany at the top and Spain at the bottom.<\/p>\n

The industry sector is broken down into energy-intensive and non-energy-intensive industries. Energy-intensive industries include iron and steel, chemical and petrochemical, non-ferrous metals, non-metallic minerals, mining and quarrying, paper, pulp, and printing, and wood and wood products manufacturing industries16<\/a>. Non-energy-intensive industries include transport equipment, machinery, food, beverages, and tobacco, textile and leather manufacturing industries, construction, and other industries that are not specified elsewhere16<\/a>. A similar categorisation is provided by Eurostat.<\/p>\n

The transport sector is categorized into rail, road, domestic aviation, and domestic navigation. Additionally, the commerce and agriculture and forestry sectors are included, though they are not further broken down.<\/p>\n

Greenhouse gas emissions<\/p>\n

The GHG emissions data used in this study is sourced from Eurostat17<\/a>, for the year 2022. Figure\u00a04<\/a> illustrates how end-use sectors are categorized for emissions reporting by Eurostat. Compared to the FEC sector classification, the industry sector emissions data provided by Eurostat is less detailed. Notably, emissions from the chemical industry are not reported for Germany, and as such, these emissions are not disaggregated in this study.<\/p>\n

Fig. 4<\/b>\"figure<\/a><\/p>\n

Breakdown of end-use emission sectors as reported in Eurostat, with Germany at the top and Spain at the bottom. Note: Emissions from the chemical industry are not reported for Germany on Eurostat and are therefore absent from the figure. Consequently, emissions from energy-intensive industries appear lower than those from non-energy-intensive industries.<\/p>\n

In contrast, the transport sector is more granular in the Eurostat data compared to the FEC categorisation. Here, sub-sectors such as rail, road, domestic aviation, and domestic navigation, are further broken down into categories like light-duty trucks, heavy-duty trucks and buses, cars, and motorcycles. For the purposes of this study, emissions from light-duty trucks and heavy-duty trucks and buses are grouped under freight transport, as specific proxies for these vehicle types are not available in publicly accessible datasets.<\/p>\n

It is important to highlight that GHG emissions in the sectors examined here primarily stem from fuel combustion. Process-related emissions in the industrial sector are excluded, with one exception: the agriculture sector, which includes non-combustion emissions. Agricultural emissions are considered under two categories-livestock and cultivation. Although Eurostat provides further disaggregation into subcategories such as enteric fermentation, manure management, agricultural soil management, and crop residue burning, only livestock and cultivation are included in this study due to the absence of matching proxies in open-source data.<\/p>\n

Proxy data<\/p>\n

Proxy data serves as the foundation for spatially disaggregating FEC and emissions across different end-use sectors. Unlike the FEC and emissions data, which is collected for the year 2022, proxy data spans multiple years, as certain datasets \u2014such as land use and land cover \u2014are not updated annually. However, all proxy datasets used represent the most recent year for which data was available at the time of collection.<\/p>\n

The selection of proxy data was guided by the following criteria: <\/p>\n