PlumX Metrics
Embed PlumX Metrics

A geostatistical approach to identify and mitigate agricultural nitrous oxide emission hotspots

Science of The Total Environment, ISSN: 0048-9697, Vol: 572, Page: 442-449
2016
  • 25
    Citations
  • 0
    Usage
  • 89
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

Article Description

Anthropogenic emissions of nitrous oxide (N 2 O), a trace gas with severe environmental costs, are greatest from agricultural soils amended with nitrogen (N) fertilizer. However, accurate N 2 O emission estimates at fine spatial scales are made difficult by their high variability, which represents a critical challenge for the management of N 2 O emissions. Here, static chamber measurements ( n = 60) and soil samples ( n = 129) were collected at approximately weekly intervals ( n = 6) for 42-d immediately following the application of N in a southern Minnesota cornfield (15.6-ha), typical of the systems prevalent throughout the U.S. Corn Belt. These data were integrated into a geostatistical model that resolved N 2 O emissions at a high spatial resolution (1-m). Field-scale N 2 O emissions exhibited a high degree of spatial variability, and were partitioned into three classes of emission strength: hotspots, intermediate, and coldspots. Rates of emission from hotspots were 2-fold greater than non-hotspot locations. Consequently, 36% of the field-scale emissions could be attributed to hotspots, despite representing only 21% of the total field area. Variations in elevation caused hotspots to develop in predictable locations, which were prone to nutrient and moisture accumulation caused by terrain focusing. Because these features are relatively static, our data and analyses indicate that targeted management of hotspots could efficiently reduce field-scale emissions by as much 17%, a significant benefit considering the deleterious effects of atmospheric N 2 O.

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know