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Regional estimation of net anthropogenic nitrogen inputs (NANI) and the relationships with socioeconomic factors

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Human activities have strongly influenced nitrogen loads; thus, the accurate evaluation of net anthropogenic nitrogen input (NANI) is very important for developing countermeasures to control N pollution. The spatiotemporal distribution… Click to show full abstract

Human activities have strongly influenced nitrogen loads; thus, the accurate evaluation of net anthropogenic nitrogen input (NANI) is very important for developing countermeasures to control N pollution. The spatiotemporal distribution and main components of NANI at the city scale in Hubei Province in 2008–2018 were analyzed using the NANI model. Furthermore, the relationships between NANI and socioeconomic factors, namely, the gross industrial output value per unit area (GIOV), gross agricultural output value per unit area (GAOV), grain yield per unit area (GY), fertilizer consumption density (FCD), population density (PD), and cultivated land area per unit area (CLA), were further analyzed. The results show that NANI in Hubei tended to increase from 14,422.66 kg km−2 year−1 in 2008 to 16,779.39 kg km−2 year−1 in 2012 and then fell to 13,415.74 kg km−2 year−1 in 2018. In terms of the spatial distribution, the NANI values in the mid-east region of Hubei, i.e., Xiangyang, Jingmen, Jingzhou, Suizhou, Xiaogan, Wuhan, Ezhou, and Huanggang and counties directly under the jurisdiction of the province, were significantly higher than those in the west, i.e., Shiyan, Yichang, and Enshi autonomous prefecture. The largest 11-year annual NANI, 39,462.03 kg km−2 year−1, occurred in Ezhou, while Shiyan had the lowest 11-year annual NANI of 6592.32 kg km−2 year−1. N fertilizer use (Nfer), which accounted for 55.23% of the NANI was the largest N input source, followed by net N import in food and feed (Nim), atmospheric N deposition (Ndep), N fixation (Nfix), and seeding N (Nsee). Pearson correlation analysis between the components of NANI and 6 socioeconomic factors revealed FCD as the primary factor responsible for NANI (r = 0.948), followed by GAOV (r = 0.607) and CLA (r = 0.558). The most direct driving factors of Ndep, Nfer, Nsee, and Nim were GIOV (r = 0.727), FCD (r = 0.966), CLA (r = 0.813), and GAOV (r = 0.746), respectively. All factors had a significant negative impact on Nfix. Therefore, the most efficient strategy to decrease NANI is to control the fertilizer application amount and improve agricultural development. Additionally, it is necessary to replace traditional high-polluting industries with ecological industry to reduce industrial pollution. Graphical abstract Graphical abstract

Keywords: net anthropogenic; anthropogenic nitrogen; year; area; per unit; socioeconomic factors

Journal Title: Environmental Science and Pollution Research
Year Published: 2020

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