Using dual isotopes and a Bayesian isotope mixing model to evaluate sources of nitrate of Tai Lake, China

Authors: LIU, SHASHA - Chinese Research Academy Of Environmental Sciences; WU, FENGCHANG - Chinese Research Academy Of Environmental Sciences; FENG, WEIYING - Chinese Research Academy Of Environmental Sciences; GUO, WENJING - Chinese Research Academy Of Environmental Sciences; SONG, FANGHAO - Chinese Research Academy Of Environmental Sciences; WANG, HAO - Chinese Research Academy Of Environmental Sciences; WANG, YING - Chinese Research Academy Of Environmental Sciences; He, Zhongqi; GEISY, JOHN - University Of Saskatchewan; ZHU, PENG - Chinese Research Academy Of Environmental Sciences; TANG, ZHI - Chinese Research Academy Of Environmental Sciences

Submitted to: Environmental Science and Pollution Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/13/2018
Publication Date: 9/21/2018
Citation: Liu, S., Wu, F., Feng, W., Guo, W., Song, F., Wang, H., Wang, Y., He, Z., Geisy, J.P., Zhu, P., Tang, Z. 2018. Using dual isotopes and a Bayesian isotope mixing model to evaluate sources of nitrate of Tai Lake, China. Environmental Science and Pollution Research. 25:32631-32639. https://doi.org/10.1007/s11356-018-3242-1.
DOI: https://doi.org/10.1007/s11356-018-3242-1

Interpretive Summary: Surface water eutrophication is a global environmental concern. Eutrophication would greatly reduce water transparency and dissolved oxygen and result in water quality impairment. Eutrophication occurs when excess nutrients of nitrogen (N) and phosphorus (P) are available in a water ecosystem. Identification and quantification of sources of nitrate (NO'3) in freshwater lakes is one of the management practices in lake water quality improvements. This study explored the applicability of a mass balance model for the determination of appropriate NO'3 contributions of various sources in Lake Taihu, China. The resulted data were used to determine relative contributions of various sources from agricultural, industrial, domestic sewages and rain water to the NO'3 in the lake. The results would be helpful in lake pollution control and management.

Technical Abstract: Identification and quantification of sources of nitrate (NO'3) in freshwater lakes is one of the management practices in lake water quality improvements. Dual delta-15N- and delta-18O-NO'3 isotopes and a Bayesian isotope mixing model were applied to identify NO'3 sources and estimate their proportional contributions to the water NO'3 levels of Lake Taihu, China. Delta-15N values of nitrate ranged from 3.8 to 10.1‰ and delta-18O values from 2.2 to 12.0‰ for waters in the Lake, respectively, suggesting that nitrate was derived primarily from agricultural and industrial sources. Stable isotope analysis in R of the SIAR model was used to estimate the proportional contributions from four potential NO'3 sources (agricultural, industrial, domestic sewage and rain water) in the lake. SIAR results showed that the contribution of agricultural source was highest (with a mean value of 50.8%), followed by industrial source (33.9%), rainwater source (8.4%) and domestic sewage source (6.8%) for the whole lake. Additionally, the contributions of the four NO'3 sources to sub-regions varied significantly (p < 0.5). For northern region of the lake, industrial source (35.4%) was the largest nitrate contributor, followed by agricultural source (27.4%), domestic source (21.3%) and rain (15.9%). Whereas for southernlake region, the proportion of NO'3 contributed from agriculture (38.6%) was slightly greater than that contributed by industry (30.8%), which was similar to the results of nearby inflow tributaries. Thus, to improve water quality and reduce algal production, nitrate from both non-point agricultural sources and industrial point sources should be managed.