Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin

Wu, Zening; Jiang, Mengmeng; Wang, Shuangfeng; Di, Danyang; Guo, Xi

doi:10.1007/s11356-022-19440-3

Cited by 11 publications

(10 citation statements)

References 77 publications

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“…In terms of N input sources of NANI, fertilizer N, atmospheric N deposition and food/feed N inputs were dominant in the Pearl River Basin (Figure 4), which was similar to the results of some existing studies [15,16,35,42]. However, fertilizer N in the Pearl River Basin tended to decrease but remained large, while food/feed input N and atmospheric deposition N tended to increase.…”

Section: Comparison Of Nani and Its N Input Sources With Other Region...supporting

confidence: 87%

“…Compared to other basins in the world, the NANI values in the Pearl River basin was also higher than 5861 kg N km −2 y −1 in the Michigan basin in the USA [10] and 8800 kg N km −2 y −1 in the Baltic Sea basin in Europe [11]. Compared to other basins in China, NANI values in the Pearl River basin were higher than those in the Yellow River basin (6787 kg N km −2 y −1 ) [35], the Yangtze River basin (7297 kg N km −2 y −1 ) [41], and the Three Gorges Reservoir Area (12,399 kg N km −2 y −1 ) [16], and lower than that in the Huaihe River basin (28,000 kg N km −2 y −1 ) [20].…”

Section: Comparison Of Nani and Its N Input Sources With Other Region...mentioning

confidence: 79%

“…Nitrogen consumption in livestock/aquaculture feeds (N l f nc ): nitrogen intakes during farming of pigs, cattle, sheep, poultry and aquatic products were mainly calculated. The annual nitrogen intake coefficients for relevant livestock and aquatic products were categorized as 54.82 kg y −1 for cattle, 9.5 kg y −1 for pigs, 14.45 kg y −1 for sheep, 0.188 kg y −1 for poultry and 29.4 g kg −1 for aquatic products [15,17,35].…”

Section: Estimation Of Nani Valuesmentioning

confidence: 99%

“…Crop/fruit N production (N cpn ): the N cpn is the sum of the N yields of different crops/fruits. There are 12 major crops /fruits in the study area and their N contents were taken as 5.62% for soybean, 1.93% for peanut, 1.18% for rice, 0.32% for vegetables, 1.79% for wheat, 1.4% for maize, 0.32% for potato, 4.46% for rapeseed, 0.19% for sugarcane, 0.17% for citrus, 0.93% for banana and 0.32% for pear [16,35,36].…”

Section: Estimation Of Nani Valuesmentioning

confidence: 99%

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Effect of Agricultural Structure Adjustment on Spatio-Temporal Patterns of Net Anthropogenic Nitrogen Inputs in the Pearl River Basin from 1990 to 2019

Jiaogen

Lei

et al. 2023

Land

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Worldwide urbanization has brought dramatic changes in agricultural structures, as well as serious agricultural non-point source pollutions of nitrogen and phosphorus. However, understanding the effect of agricultural structure adjustment on net anthropogenic nitrogen inputs (NANI) has been still limited. In this paper, statistical data from the agricultural statistical Yearbook, the National Economic and Social Development Statistical Bulletin were collected from 1990 to 2019 in the Pearl River Basin, China, and used to analyze the spatial and temporal patterns of NANI and its influencing factors. The results indicated that the agricultural structure adjustment has significantly influenced the spatial and temporal patterns of NANI in the last 30 years in the Pearl River Basin. The NANI decreased from 1990 to 2019, and had a spatial pattern of higher values in the upstream areas and lower in the downstream areas. In terms of the nitrogen input sources of NANI, in the economically developed regions downstream, nitrogen inputs are dominated by food/feed nitrogen, which accounted for an average of 49.6% of total nitrogen inputs. In upstream areas with relatively low economic development, fertilizer nitrogen accounted for an average of 54.9% of total nitrogen inputs. A novel nitrogen input source index of NANI, namely the ratio of agricultural nitrogen inputs to non-agricultural nitrogen inputs of NANI(ASNA), was also proposed to characterize the impact of the agricultural industry restructuring on NANI changes over time. Similar to the characteristics of NANI from 1990 to 2019, the ASNA showed a decreasing trend in the study area. Moreover, agricultural variables (agricultural land area, nitrogen fertilizer consumption and livestock farming density) tended to contribute less to the explained ASNA variances, while the contributions of the non-agricultural factors (population density and non-agricultural GDP) increased from 1990 to 2019. This indicated that the contribution of nitrogen inputs from agricultural sources to the NANI decreased while the contribution of nitrogen inputs from non-agricultural sources increased, with the shifts of agricultural sectors to the secondary and tertiary sectors in the Pearl River Basin. Our findings also suggest that differently regional targeting should be considered for the nitrogen pollution management in the Pearl River Basin, which focuses on the nitrogen pollution management of non-agricultural sources in the downstream areas, and but highlights agricultural nitrogen pollution management in the upstream areas.

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Section: Comparison Of Nani and Its N Input Sources With Other Region...supporting

confidence: 87%

Section: Comparison Of Nani and Its N Input Sources With Other Region...mentioning

confidence: 79%

Section: Estimation Of Nani Valuesmentioning

confidence: 99%

Section: Estimation Of Nani Valuesmentioning

confidence: 99%

See 2 more Smart Citations

Effect of Agricultural Structure Adjustment on Spatio-Temporal Patterns of Net Anthropogenic Nitrogen Inputs in the Pearl River Basin from 1990 to 2019

Jiaogen

Lei

et al. 2023

Land

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“…However, the setting of the SBM model's direction vector is subjective and cannot overcome the deviation from using the same decision-making unit under different direction vector settings. 29 Mancini et al 30 used a three-dimensional ecological footprint model to evaluate the dynamic evolution of natural capital while Wu et al 31 applied Moran's I to calculate the spatial correlation effect of the Yellow River basin's total nitrogen pollution.…”

Section: Introductionmentioning

confidence: 99%

Temporal and spatial evolution and influencing factors of urban ecological total factor productivity in the Yellow River basin under strong sustainable development

et al. 2023

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A growing consensus worldwide has indicated the need to protect the ecological environment and achieve sustainable development. Ensuring ecological protection and high-quality development of the Yellow River basin have become China's major national strategy. We reviewed extant literature, summarised government reports and guidance documents on the Yellow River basin, and proposed introducing a strong sustainable development theory into the study of total factor productivity (TFP). The spatial–temporal evolution and influencing factors of urban ecological TFP in the Yellow River basin are of great practical significance. We proposed a new ecological TFP indicator: the modified input-oriented Luenberger productivity indicator (MIL). Using panel data from 78 cities in the Yellow River basin during 2003–2019, we measured the urban ecological TFP. We adopted the geographic information system tool and kernel density estimation to analyse the temporal and spatial evolution of the indicator, as well as its spatial effects and influencing factors, using the global Moran's I index and dynamic spatial Durbin model (SDM). Our results show that, during the sample period, our indicator increased in cities in the region with an average annual growth rate of 0.627%, driven by technological progress. The average annual growth rate in urban areas showed a decreasing distribution of ‘downstream-midstream-upstream’. Fiscal decentralisation (FD), industrial structure (IND), financial development (FIN), urbanisation level (URB) and research and development (RD) investment improved growth rates in this and the adjacent regions through direct and indirect effects. However, environmental regulation (ER), opening level (OPEN) of cities and population density (POP) were obstacles to TFP growth.

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Variations and its driven factors of anthropogenic nitrogen loads in the Yangtze River Economic Belt during 2000–2019

Meng

Guo

Wei

et al. 2022

Environ Sci Pollut Res

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Since the millennium, China has economically taken off with rapid urbanization, and anthropogenic nitrogen emission intensity has undergone remarkable changes. To better understand the impact of urbanization on anthropogenic nitrogen, this study calculated the spatio-temporal heterogeneity of anthropogenic nitrogen in the Yangtze River Economic Belt (YREB) since 2000, based on the estimation, using obstacle analysis to quantify the driving of industry and agriculture on N growth and using the gray model to analyze the impact of urbanization on N changes. Additionally, using the environmental pressure model to predict the future N load. The results indicated N load in the YREB increased rapidly from 21.4 Tg in 2001 to a peak of 24.5 Tg in 2012 and then decreased to 22.2 Tg in 2019. Although N flux gradually increased from the west to the east of the YREB, the growth rate had an opposite trend with a negative growth in the eastern region. Hotspots are mainly concentrated in urban agglomerations, which contributed to ~ 60% N load of the YREB, and the YREB contributed to ~ 90% N load of the Yangtze River Basin. Obstacle degree scores indicated wastewater was a major industrial driver of N growth before 2010, and then became waste gas; increased mechanization and fertilizer control effectively reduced nitrogen emissions during agricultural development. The gray analysis of urbanization indicated urban population, industry, and services had the strongest correlation with N load changes. Scenario simulations suggest N loads of the YREB remain at a high level by 2030; however, there are still opportunities to effectively control N growth through high technological innovation and reducing the proportion of industry under an enormous population. This research contributes to a better understanding of the impact of urbanization on anthropogenic nitrogen and helps developing countries to precisely control nitrogen hotspots and sources. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-022-21943-y.

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Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin

Cited by 11 publications

References 77 publications

Effect of Agricultural Structure Adjustment on Spatio-Temporal Patterns of Net Anthropogenic Nitrogen Inputs in the Pearl River Basin from 1990 to 2019

Effect of Agricultural Structure Adjustment on Spatio-Temporal Patterns of Net Anthropogenic Nitrogen Inputs in the Pearl River Basin from 1990 to 2019

Temporal and spatial evolution and influencing factors of urban ecological total factor productivity in the Yellow River basin under strong sustainable development

Variations and its driven factors of anthropogenic nitrogen loads in the Yangtze River Economic Belt during 2000–2019

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