Tracing nitrogen sources and transformation characteristics in a large basin with spatially heterogeneous pollution distribution.

This study used dual stable isotopes to examine nitrate sources and geographical distribution in the Liao River Basin (LRB), one of China's seven major river basins. During a normal hydrological season in April 2021, water samples were taken from the main streams of the Liao River (MLR), Shuangtaizi River (STR), Hun River (HR), Taizi River (TZR), and Daliao River (DLR). Monitoring results indicated that 93% of the water samples had a total nitrogen level exceeding the Class IV limit (1.5 mg/L) of the 'Environmental Quality Standards (EQS) for surface water', indicating a serious nitrogen pollution status. 71.3% of the total nitrogen on average was in the form of nitrate. The scatterplots of δD-H2O and δ18O-H2O showed that water in TZR and DLR were mainly affected by precipitation, while MLR, STR and HR were additionally impacted by evaporation and groundwater. The overall δ15N and δ18O of NO3- varied from 7.7‰ to 17.9‰ and 0.6‰-11.2‰, respectively. The correlations between δ15N-NO3- and δ18O-NO3-, along with attribution results from the Bayesian isotopic mixing model, indicated a predominant role of manure/sewage (MS) pollution in affecting river nitrate, accounting for 78% of total nitrate in MLR and 72% in DLR. A positive correlation between δ15N-NO3- and δ18O-NO3- in MLR indicated the occurrence of denitrification process. Overall, attribution results showed that the primary nitrate sources varied in different river systems within such a large basin, mainly due to spatially varied land use and human activities. Tailored nitrogen management strategies should be implemented to address the main anthropogenic pressures.

Dynamic spatiotemporal change of net anthropogenic phosphorus inputs and its response of water quality in the Liao river basin.

The Liao river is one of the seven major rivers in China, and the process of phosphorus (P) cycling and change of water quality in this basin are influenced to a considerable extent human activities. In this work, the traditional net anthropogenic phosphorus inputs (NAPI) model was improved by considering the dynamic change of wastewater treatment capacity and P deposition (PDEP) and reclassifying the sources of phosphorus into human P consumption (PHUM), agriculture P consumption (PAGR), livestock P consumption (PANIM) and PDEP to analyze its dynamic spatio-temporal change in the Liao river basin. The results showed that the annual mean NAPI was 785.53 kg P km-2 yr-1 (2001-2020), the maximum value was 940.49 kg P km-2 yr-1 in 2009, and the minimum value was 586.04 kg P km-2 yr-1 in 2001. The temporal variation of NAPI presented an increasing-fluctuation-increasing trend and was basically in line with that of the water quality throughout the three stages, and the spatial distribution of NAPI gradually increased from upstream to downstream. During the two decades, PANIM was the predominant component of NAPI with a share of 64.32%. PHUM, PAGR, and PDEP accounted for 15.97%, 11.54%, and 8.17%, respectively, and the point source NAPI (NAPIP) contributed to 4.95% of NAPI. Further, the INAPI (Improved NAPI) -MR (Multiple Regression) -SWAT (Soil and Water Assessment Tool) model was developed to predict the spatial distribution of P flux under two scenarios. The results showed that the Liao river basin experienced a reduction in P flux to different degrees due to the improvement of the wastewater treatment system, which was more significant in its downstream area. Long-term water quality monitoring is encouraged to develop refined water quality models in the future.

Residues, potential source and ecological risk assessment of polycyclic aromatic hydrocarbons (PAHs) in surface water of the East Liao River, Jilin Province, China.

The environmental risks posed by polycyclic aromatic hydrocarbons (PAHs) and the diversity of their anthropogenic origins make them a global issue. Therefore, it is of utmost significance for protecting the aquatic environment and the growth of neighboring populations to identify their possible origins and ecological risk. Here, we detail the contamination profiles of 15 PAHs found in the East Liao River's surface waters in Jilin Province and use the receptor model Absolute Principal Component Analysis - Multiple Linear Regression (APCS-MLR) and diagnostic ratios method to identify the primary potential sources of pollution. Based on the natural hazard risk formation theory (NHRFT), an ecological risk assessment (ERA) model for PAHs in the East Liao River was developed. The method assesses the ecological risk status of PAHs by integrating the risk quotient (RQ) approach and the DPSIRM (driving force, pressure, state, impact, response, management) conceptual framework. Total concentrations in the surface water body were between 396.42 and 624.06 ng/L, with an average of 436.99 ng/L. The source research revealed that coal, biomass, and traffic emission sources are the most likely PAH contributors to the East Liao River. The ERA found that the majority of the sites' locations of the study were at low risk for PAHs in surface water bodies (30.7 % and 32.2 %, respectively), while only a tiny percentage of sites were at high or very high risk (1.8 % and 13.6 %). The study results provide theoretical support for the East Liao River's ecological, environmental protection, and policy formulation.

Assessing impacts of global climate change on water and food security in the black soil region of Northeast China using an improved SWAT-CO2 model.

Future climate change may have substantial impacts on both water resources and food security in China's black soil region. The Liao River Basin (LRB; 220,000 km2) is representative of the main black soil area, making it ideal for studying climate change effects on black soil. In this study, the Soil and Water Assessment Tool (SWAT) model was first initialized for the LRB. Actual evapotranspiration (ETa) values calculated using the Surface Energy Balance System (SEBS) model and city-level corn (Zea mays L.) yields were then used to calibrate the SWAT model. Finally, the SWAT model was modified to accept dynamic CO2 input and output crop transpiration, soil evaporation, and canopy interception separately to explore the impacts of future climate change on ET related variables and crop water productivity (CWP) in the LRB. Simulation scenario design included 22 General Circulation Models (GCMs) and 4 Shared Socioeconomic Pathways (SSPs) scenarios from the latest Coupled Model Intercomparison Project 6 (CMIP6) for two 30-year periods of 2041-2070 and 2071-2100. The predicted results showed a significant (P < 0.05) increase in air temperatures and precipitation in the LRB. In contrast, solar radiation decreased significantly and was most reduced for the SSP3-7.0 scenario. Reference evapotranspiration (ETo), ETa, and soil evaporation significantly increased in future scenarios, while canopy interception and crop transpiration showed significant reductions, particularly under the 2071-2100 SSP5-8.5 scenario. Overall, corn yield elevated considerably (P < 0.05) with the largest increase for the SSP5-8.5 scenario during 2071-2100. However, the SSP3-7.0 scenario indicated a significant decline in yield. Future changes in CWP were similar to those for corn yield, with significant increases in the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. These findings suggested future climate change may have a positive impact on corn production in the black soil region of the LRB.