Application of the dual-isotope approach and Bayesian isotope mixing model to identify nitrate in groundwater of a multiple land-use area in Chengdu Plain, China.

Nitrate (NO) contamination in groundwater is an environmental problem worldwide. Partitioning the pollution into its sources is the key for effective controls. In this study, NO dual isotopic compositions (δN-NO and δO-NO) were measured in groundwater samples from 28 wells in an area with multiple land-uses, followed by the application of an isotope mixing model (SIAR) to identify the main NO sources and their biogeochemical processes. The results showed that denitrification was unlikely occur at significant rates, while nitrification was an important nitrogen transformation processes. Spatial variation of groundwater NO and its isotopic compositions was associated with the land-use types. Agricultural areas were characterized by relatively high NO concentrations and low δN-NO values. In contrast, industrial areas were characterized by enriched δN-NO and δO-NO values. In crop field, vegetable field and poultry and livestock breading farm, the proportional contribution represented a similar pattern with highest contribution from chemical fertilizer followed by soil organic nitrogen, manure, atmospheric precipitation and sewage in order. Nitrate in groundwater in industrial areas has different pattern of the proportional contribution, in which groundwater NO is largely influenced by sewage discharge and atmospheric precipitation. We concluded that the combination of isotopic analysis together with land-use information and chemical analysis was an effective approach for assessing the source apportionment and the fate of nitrate in the aquifer in multiple land-use areas.