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Liu D, Li X, Zhang Y, Bai L, Shi H, Qiao Q, Li T, Xu W, Zhou X, Wang H. Industrial fluoride emissions and their spatial characteristics in the Nansi Lake Basin, Eastern China. Environ Sci Pollut Res Int 2024; 31:27273-27285. [PMID: 38507167 DOI: 10.1007/s11356-024-32941-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/11/2024] [Indexed: 03/22/2024]
Abstract
Excessive fluoride emissions threaten ecological stability and human health. Previous studies have noted that industrial sources could be significant. However, quantifying industrial fluoride emissions has not been yet reported. In this study, both bottom-up and top-down approaches were used to estimate the fluoride emissions in the Nansi Lake Basin. Global and local spatial autocorrelation were adopted to reveal the spatial agglomeration effects. The fluoride emissions calculated by the bottom-up approach were larger than those calculated by the top-down method. The highest fluoride input mainly occurred in Zoucheng and Mudan. The highest fluoride emissions mainly occurred in Zoucheng and Rencheng using the bottom-up approach. The highest fluoride emissions mainly occurred in Zoucheng and Yanzhou using the top-down approach. Mining and washing of bituminous coal and anthracite (BAW) was the most significant source of fluoride input and emissions. A significant spatial agglomeration effect of fluoride emissions was found. These findings could provide a method for accurate industrial fluoride emission estimation, complement the critical data on the fluoride emissions of main industrial sectors, and provide a scientific basis for tracing fluoride sources.
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Affiliation(s)
- Dandan Liu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- Key Laboratory of Eco-Industry of the Ministry of Environmental Protection, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Xueying Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- Key Laboratory of Eco-Industry of the Ministry of Environmental Protection, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yue Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- Key Laboratory of Eco-Industry of the Ministry of Environmental Protection, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Lu Bai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- Key Laboratory of Eco-Industry of the Ministry of Environmental Protection, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Huijian Shi
- Center for Soil Pollution Control of Shandong, Jinan, 250000, China
| | - Qi Qiao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- Key Laboratory of Eco-Industry of the Ministry of Environmental Protection, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Tianran Li
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China
| | - Wen Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- Key Laboratory of Eco-Industry of the Ministry of Environmental Protection, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Xiaoyun Zhou
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
- Key Laboratory of Eco-Industry of the Ministry of Environmental Protection, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Hejing Wang
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China.
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Zhang Z, Deng C, Dong L, Zou T, Yang Q, Wu J, Li H. Nitrogen flow in the food production and consumption system within the Yangtze River Delta city cluster: Influences of cropland and urbanization. Sci Total Environ 2022; 824:153861. [PMID: 35176380 DOI: 10.1016/j.scitotenv.2022.153861] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 02/07/2022] [Accepted: 02/09/2022] [Indexed: 06/14/2023]
Abstract
Intensive anthropogenic activities associated with the food production and consumption system (FPC) drive massive reactive nitrogen inputs to city clusters resulting in serious nitrogen (N) pollution. We conducted a substance flow analysis to examine N flows in the FPC within the Yangtze River Delta city cluster from 2011 to 2019. The total N input and output showed parabolic downward trends, with decreases from 4008.27 to 3472.57 Gg N yr-1 and 3518.65 to 3061.29 Gg N yr-1, respectively; chemical fertilizer (54.7%-57.3%) and N loss (87.1%-90.9%) were the primary components of N input and output, respectively. The decreased total N input was related to reductions in chemical fertilizers and livestock numbers. However, a notable increase in N input to the human subsystem was observed, and urbanization was associated with increased N inputs within the human subsystem via higher amounts of food N consumed per capita and proportions of animal-based food N consumed. Total N loss initially increased then decreased; Nantong, Jiaxing, Shanghai, Yancheng, Taizhou, and Yangzhou were the top six cities in N loss intensity. The proportion of cultivated land area, livestock numbers per unit area, and population density were important factors influencing the spatial heterogeneity of N loss intensity. Twenty-six cities were divided into six groups based on their N loss composition, and various N management strategies were proposed. This study highlights the strong influences of cropland and urbanization on N flows within the FPC, which can be used as a reference for N management at a city cluster scale.
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Affiliation(s)
- Zeqian Zhang
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Chenning Deng
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Li Dong
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Tiansen Zou
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Queping Yang
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jia Wu
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Haisheng Li
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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