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Global demand for agricultural and forestry products fundamentally affects regional land-use change associated with environmental impacts (EIs) such as erosion. In contrast to aggregated global metrics such as greenhouse gas (GHG) balances, local/regional EIs of different agricultural and forestry production regions need methods which enable worldwide EI comparisons. The key aspect is to control environmental heterogeneity to reveal man-made differences of EIs between production regions. Environmental heterogeneity is the variation in biotic and abiotic environmental conditions. In the present study, we used three approaches to control environmental heterogeneity: (i) environmental stratification, (ii) potential natural vegetation (PNV), and (iii) regional environmental thresholds to compare EIs of solid biomass production. We compared production regions of managed forests and plantation forests in subtropical (Satilla watershed, Southeastern US), tropical (Rufiji basin, Tanzania), and temperate (Mulde watershed, Central Germany) climates. All approaches supported the comparison of the EIs of different land-use classes between and within production regions. They also standardized the different EIs for a comparison between the EI categories. The EIs for different land-use classes within a production region decreased with increasing degree of naturalness (forest, plantation forestry, and cropland). PNV was the most reliable approach, but lacked feasibility and relevance. The PNV approach explicitly included most of the factors that drive environmental heterogeneity in contrast to the stratification and threshold approaches. The stratification approach allows consistent global application due to available data. Regional environmental thresholds only included arbitrarily selected aspects of environmental heterogeneity; they are only available for few EIs. Especially, the PNV and stratification approaches are options to compare regional EIs of biomass or crop production such as erosion, biodiversity, or water quality impacts worldwide and thereby complement existing metrics assessing global EIs such as GHG emissions.