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<p>Excess nitrogen (N) within the landscape can lead to environmental issues such as water pollution and downstream eutrophication. Quantification of landscape N fluxes can help identify areas of excess N and can improve our understanding of the sources, sinks, and transport of N within ecosystems. The gTREND-Nitrogen dataset provides a comprehensive, long-term (1930-2017) N mass balance for the contiguous United States at a spatial resolution of 250 meters. This dataset integrates county-scale estimates of N fluxes with gridded land use and population data to estimate grid-scale surface fluxes of N, including fertilizer, atmospheric deposition, manure inputs, biological N fixation, crop N uptake, and population-based human waste. The downscaled gTREND-Nitrogen data will allow for fine-scale insights into both historical and current N dynamics, addressing the limitations of previous datasets developed at coarser spatial scales. The data is openly available and will help to inform the development of effective policy and management strategies to mitigate the negative impacts of excess N and to promote sustainable nutrient management practices.</p>

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gTREND-Nitrogen - Long-term nitrogen mass balance data for the contiguous United States (1930-2017)

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月28日

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  • Shuyu Y. Chang,
  • Danyka K. Byrnes,
  • Nandita B. Basu,
  • Kimberly J. Van Meter

摘要

Excess nitrogen (N) within the landscape can lead to environmental issues such as water pollution and downstream eutrophication. Quantification of landscape N fluxes can help identify areas of excess N and can improve our understanding of the sources, sinks, and transport of N within ecosystems. The gTREND-Nitrogen dataset provides a comprehensive, long-term (1930-2017) N mass balance for the contiguous United States at a spatial resolution of 250 meters. This dataset integrates county-scale estimates of N fluxes with gridded land use and population data to estimate grid-scale surface fluxes of N, including fertilizer, atmospheric deposition, manure inputs, biological N fixation, crop N uptake, and population-based human waste. The downscaled gTREND-Nitrogen data will allow for fine-scale insights into both historical and current N dynamics, addressing the limitations of previous datasets developed at coarser spatial scales. The data is openly available and will help to inform the development of effective policy and management strategies to mitigate the negative impacts of excess N and to promote sustainable nutrient management practices.