History of anthropogenic Nitrogen inputs (HaNi) to the terrestrial biosphere: A 5-arcmin resolution annual dataset from 1860 to 2019
- 1International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849, USA
- 2Research Center for Eco-Environmental Sciences, State Key Laboratory of Urban and Regional Ecology, Chinese Academy of Sciences, Beijing 100085, China
- 3Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- 4Statistics Division, Food and Agriculture Organization of the United Nations, Via Terme di Caracalla, Rome, Italy
- 5College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
- 6School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- 7Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80523, USA
- 8Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523, USA
- 9Biogeochemical Cycle Modeling and Analysis Section, Earth System Division, National Institute for Environmental Studies 16-2, Onogawa, Tsukuba, 305-8506, Japan
- 10Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97330, USA
- 11Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK 74078, USA
- 12International Food Policy Research Institute (IFPRI), 1201 Eye Street, NW, Washington, DC 20005, USA
- 13Department of Environment, Geology, and Natural Resources, Ball State University, Muncie, IN 47306, USA
Abstract. Excessive anthropogenic nitrogen (N) inputs to the biosphere have disrupted the global nitrogen cycle. To better quantify the spatial and temporal patterns of anthropogenic N enrichments, assess their impacts on the biogeochemical cycles of the planet and other living organisms, and improve nitrogen use efficiency (NUE) for sustainable development, we have developed a comprehensive and synthetic dataset for reconstructing the History of anthropogenic N inputs (HaNi) to the terrestrial biosphere. The HaNi dataset takes advantage of different data sources in a spatiotemporally consistent way to generate a set of high-resolution gridded N input products from the preindustrial to present (1860–2019). The HaNi dataset includes annual rates of synthetic N fertilizer, manure application/deposition, and atmospheric N deposition in cropland, pasture, and rangeland at a spatial resolution of 5-arcmin. Specifically, the N inputs are categorized, according to the N forms and land uses, as ten types: 1) NH4+-N fertilizer applied to cropland, 2) NO3-N fertilizer applied to cropland, 3) NH4+-N fertilizer applied to pasture, 4) NO3-N fertilizer applied to pasture, 5) manure N application on cropland, 6) manure N application on pasture, 7) manure N deposition on pasture, 8) manure N deposition on rangeland, 9) NHx-N deposition, and 10) NOy-N deposition. The total anthropogenic N (TN) inputs to global terrestrial ecosystems increased from 29.05 Tg N yr-1 in the 1860s to 267.23 Tg N yr-1 in the 2010s, with the dominant N source changing from atmospheric N deposition (before the 1900s) to manure N (the 1910s–2000s), and to synthetic fertilizer in the 2010s. The proportion of synthetic NH4+-N fertilizer increased from 64 % in the 1960s to 90 % in the 2010s, while synthetic NO3-N fertilizer decreased from 36 % in the 1960s to 10 % in the 2010s. Hotspots of TN inputs shifted from Europe and North America to East and South Asia during the 1960s-2010s. Such spatial and temporal dynamics captured by the HaNi dataset are expected to facilitate a comprehensive assessment of the coupled human-earth system and address a variety of social welfare issues, such as climate-biosphere feedback, air pollution, water quality, and biodiversity.
Hanqin Tian et al.
Hanqin Tian et al.
HaNi: A Historical dataset of Anthropogenic Nitrogen Inputs to the terrestrial biosphere (1860-2019) https://doi.pangaea.de/10.1594/PANGAEA.942069
Hanqin Tian et al.
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