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Wang T, Sun Y, Wang T, Wang Z, Hu S, Gao S. Dynamic spatiotemporal change of net anthropogenic phosphorus inputs and its response of water quality in the Liao river basin. CHEMOSPHERE 2023; 331:138757. [PMID: 37105311 DOI: 10.1016/j.chemosphere.2023.138757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 04/15/2023] [Accepted: 04/21/2023] [Indexed: 05/19/2023]
Abstract
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.
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Affiliation(s)
- Tianxiang Wang
- School of Ocean Science and Technology, Dalian University of Technology, Panjin, 124221, China; Department of Physical & Environmental Sciences, University of Toronto, Toronto, M1C 1A4, Canada; Key Laboratory of Coastal Science and Integrated Management, Ministry of Natural Resources, Qingdao, 266061, China; State Key Laboratory of Lake Science and Environment, Nanjing, 210008, China.
| | - Ya Sun
- College of Environmental Sciences and Engineering, Dalian Maritime University, Dalian, 116026, China.
| | - Tianzi Wang
- School of Ocean Science and Technology, Dalian University of Technology, Panjin, 124221, China
| | - Zixiong Wang
- Guangzhou Pearl River Water Resources Protection Technology Development Co. LTD. , Guangzhou, 510610, China
| | - Suduan Hu
- School of Ocean Science and Technology, Dalian University of Technology, Panjin, 124221, China
| | - Shanjun Gao
- School of Ocean Science and Technology, Dalian University of Technology, Panjin, 124221, China
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Liu J, Gu W, Liu Y, Li W, Shao D. Influence of anthropogenic nitrogen inputs and legacy nitrogen change on riverine nitrogen export in areas with high agricultural activity. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 338:117833. [PMID: 37004483 DOI: 10.1016/j.jenvman.2023.117833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/25/2023] [Accepted: 03/26/2023] [Indexed: 06/19/2023]
Abstract
Increased riverine nitrogen (N) concentrations due to human activities is one of the leading causes of water quality decline, worldwide. Therefore, quantitative information about the N exported from watershed to the river (TN exports) is essential for defining N pollution control practices. This paper evaluated the changes in net anthropogenic N inputs (NANI) and the N stored in land ecosystems (legacy N) in the Jianghan Plain (JHP) from 1990 to 2019 and their impacts on TN exports. Moreover, an empirical model was developed to estimate TN exports, trace its source, and predict its future variations in 2020-2035 under different scenarios. According to the results, NANI exhibited a rise-decrease-rise-decrease M-shaped trend, with N fertilizer application being the dominant driver for NANI change. In terms of the NANI components, non-point-source was the primary N input form (96%). Noteworthy is that the correlation between NANI and TN exports became weaker over time, and large differences in changing trends were observed after 2014. A likely cause for this abnormal trend was that the accumulation of N surplus in soil led to N saturation in agricultural areas. Legacy N was also an important source of TN exports. However, the contribution of legacy N has rarely been considered when defining N pollution control strategies. An empirical model, incorporating legacy N, agricultural irrigation water use, and cropland area ratio, was developed. Based on this model, legacy N contributed a large proportion (15-31%). Furthermore, the results of future predictions indicated that legacy N had a larger impact on future TN exports changes compared to other factors, and increased irrigation water would increase rather than decrease TN exports. Therefore, an integrated N management strategy considering the impact of NANI, legacy N, and irrigation water use is crucial to control N pollution in areas with intensive agriculture.
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Affiliation(s)
- Jie Liu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China
| | - Wenquan Gu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China.
| | - Yawen Liu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China
| | - Wenhui Li
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China
| | - Dongguo Shao
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China.
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Pei W, Yan T, Lei Q, Zhang T, Fan B, Du X, Luo J, Lindsey S, Liu H. Spatio-temporal variation of net anthropogenic nitrogen inputs (NANI) from 1991 to 2019 and its impacts analysis from parameters in Northwest China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 321:115996. [PMID: 36029628 DOI: 10.1016/j.jenvman.2022.115996] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 08/07/2022] [Accepted: 08/08/2022] [Indexed: 06/15/2023]
Abstract
At present, excessive nutrient inputs caused by human activities have resulted in environmental problems such as agricultural non-point source pollution and water eutrophication. The Net Anthropogenic Nitrogen Inputs (NANI) model can be used to estimate the nitrogen (N) inputs to a region that are related to human activities. To explore the net nitrogen input of human activities in the main grain-producing areas of Northwestern China, the county-level statistical data for the Ningxia province and NANI model parameters were collected, the spatio-temporal distribution characteristics of NANI were analyzed and the uncertainty and sensitivity of the parameters for each component of NANI were quantitatively studied. The results showed that: (1) The average value of NANI in Ningxia from 1991 to 2019 was 7752 kg N km-2 yr-1. Over the study period, the inputs first showed an overall increase, followed by a decrease, and then tended to stabilize. Fertilizer N application was the main contributing factor, accounting for 55.6%. The high value of NANI in Ningxia was mainly concentrated in the Yellow River Diversion Irrigation Area. (2) The 95% confidence interval of NANI obtained by the Monte Carlo approach was compared with the results from common parameters in existing literature. The simulation results varied from -6.4% to 27.4% under the influence of the changing parameters. Net food and animal feed imports were the most uncertain input components affected by parameters, the variation range was -20.7%-77%. (3) The parameters of inputs that accounted for higher proportions of the NANI were more sensitive than the inputs with lower contributions. The sensitivity indexes of the parameters contained in the fertilizer N applications were higher than those of net food and animal feed imports and agricultural N-fixation. This study quantified the uncertainty and sensitivity of parameters in the process of NANI simulation and provides a reference for global peers in the application and selection of parameters to obtain more accurate simulation results.
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Affiliation(s)
- Wei Pei
- Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Tiezhu Yan
- Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Qiuliang Lei
- Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Tianpeng Zhang
- Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Bingqian Fan
- Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xinzhong Du
- Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Jiafa Luo
- AgResearch Limited, Ruakura Research Centre, Hamilton, 3240, New Zealand
| | - Stuart Lindsey
- AgResearch Limited, Ruakura Research Centre, Hamilton, 3240, New Zealand
| | - Hongbin Liu
- Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
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Liu J, Gu W, Liu Y, Zhang C, Li W, Shao D. Dynamic characteristics of net anthropogenic phosphorus input and legacy phosphorus reserves under high human activity - A case study in the Jianghan Plain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 836:155287. [PMID: 35439512 DOI: 10.1016/j.scitotenv.2022.155287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/10/2022] [Accepted: 04/11/2022] [Indexed: 06/14/2023]
Abstract
The increase of phosphorus (P) input related to human activities is one of the main reasons for eutrophication. Notably, in areas with high population densities and intensive agricultural activities, eutrophication has occurred frequently in the Jianghan Plain, so quantitative evaluation of anthropogenic P input is of great significance for the formulation of P pollution control measures. This study estimated net anthropogenic P input (NAPI), riverine total P exports (TP exports), and the pool of P stored in the terrestrial system (legacy P reserves) at the county scale from 1990 to 2019 in the Jianghan Plain. The results showed that NAPI increased from 2645 kg·km-2·yr-1 in 1991 to 5812 kg·km-2·yr-1 in 2014, and then decreased to 4509 kg·km-2·yr-1 in 2019. Non-point sources were the main form of NAPI, of which 75-96% came from agricultural systems. Meanwhile, P fertilizer input was the largest source of NAPI. It is worth noting that the contribution of seed P input in some counties, such as Jiangling County, is relatively high, even exceeding that of net food/feed P input. The P fertilizer application and livestock density were the main drivers for NAPI change. Only 3% of NAPI was exported into rivers, so a large amount of legacy P accumulated in the terrestrial system. An empirical model incorporating NAPI components, cultivated land area ratio, and annual precipitation was established. Based on this model, the average contribution of annual NAPI and the sum of legacy P and natural background sources to TP exports were calculated to be 71% and 29%, respectively. So it is necessary to control P pollution by improving fertilizer use efficiency and enhancing manure management. The results provide a scientific basis for targeted solutions to the sources of P nutrient and its control measures in the middle reach of the Yangtze River.
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Affiliation(s)
- Jie Liu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
| | - Wenquan Gu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China.
| | - Yawen Liu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
| | - Chi Zhang
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
| | - Wenhui Li
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
| | - Dongguo Shao
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China.
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Nie B, Zeng Y, Niu L, Zhang X. Long-term impacts of reservoir operation on the spatiotemporal variation in nitrogen forms in the post-Three Gorges Dam period (2004-2016). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:65633-65643. [PMID: 34322818 DOI: 10.1007/s11356-021-15557-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/17/2021] [Indexed: 06/13/2023]
Abstract
Nitrogen (N) is an essential nutrient limiting life, and its biochemical cycling and distribution in rivers have been markedly affected by river engineering construction and operation. Here, we comprehensively analyzed the spatiotemporal variations and driving environmental factors of N distributions based on the long-term observations (from 2004 to 2016) of seven stations in the Three Gorges Reservoir (TGR). In the study period, several water quality indexes of the river reach improved, whereas N pollution was severe and tended to be aggravated after the TGR impoundment. The anti-seasonal reservoir operation strongly affected the variations in N forms. The total nitrogen (TN) concentration in the mainstream of the Yangtze River continuously increased, although it was still lower than that in the incoming tributaries (Wu and Jialing rivers). Further analysis showed that this increase occurred probably because of external inputs, including the upstream (76%), non-point (22%), and point source pollution inputs (2%). Additionally, different N forms showed significant seasonal variations; among them, the TN and nitrate nitrogen concentrations were the lowest in the impoundment season (October-February), and the ammonia nitrogen concentrations were the highest in the sluicing season (March-May). Redundancy analysis revealed that the water level and distance to the Three Gorges Dam were significant contributors to N forms distribution. Our findings could provide a basis for managing and predicting the water quality in the Yangtze River.
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Affiliation(s)
- Bei Nie
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, 430072, Wuhan, China
| | - Yuhong Zeng
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, 430072, Wuhan, China.
| | - Lanhua Niu
- Three Gorges Bureau of Hydrological and Water Resources Survey, Changjiang Water Resources Commission of the Ministry of Water Resources, Yichang, 443000, China
| | - Xiaofeng Zhang
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, 430072, Wuhan, China
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