Purpose: Emissions and resource use are influenced by soil and climate as well as by farm management. In addition, characterisation factors (CFs) used in life cycle assessment (LCA) to translate emissions and resource use into environmental impacts also depend on the location. The purpose of this study was to evaluate how regional differences in emissions, resource use, and CFs influence the variability of the environmental impacts of agricultural products from the perspective of an LCA practitioner. Methods: We examined four databases—AGRIBALYSE®, SALCA, WFLDB, and Agri-footprint®—differentiating both emissions/resource uses and their environmental impacts at the country level. Only the Agri-footprint® database had data from at least ten different countries considered sufficient for a statistical analysis. The country-specific environmental impacts of the products in Agri-footprint® were calculated according to the Swiss Agricultural Life Cycle Assessment (SALCA) method using Brightway and analysed for seven spatially explicit impact categories: water use, land occupation, terrestrial acidification, eutrophication, water scarcity, soil quality, and biodiversity. Results and discussion: Spatial differences in emissions, resources, and CFs contributed to the spatial variability of environmental impacts at the product level. For nutrient-related impacts, such as eutrophication and acidification, the spatial variability of the contributing emissions had a stronger influence than the variability of the CFs. This is evident for marine and freshwater eutrophication, where characterisation is assumed to be uniform across all countries. For biodiversity the variability in CFs was more dominant. Most of the impact categories showed more significant positive than significant negative correlations between agricultural land occupation and the impact score. A higher yield per area thus generally leads to lower impacts per product unit. In summary, a spatial differentiation is needed if the parameters driving the impacts show high spatial variability or have a strong influence on the emission, and this emission has an important contribution to the impact. Conclusions: Our analysis highlighted that emission fluxes and CFs significantly influence the spatial variability of midpoint-level environmental impacts. Inventory flows exhibited greater variability than CFs, except for the land-use-related impact categories. Most impacts correlated positively with agricultural land occupation, showing a strong effect on yield levels. Our results underlined the importance of accounting for the spatial variability of emissions and CFs to adequately reflect the environmental impacts of agricultural products. The results are primarily representative of European conditions and temperate regions, as Agri-footprint® mainly includes products cultivated in Europe.