Reconsidering emissions of ammonia from chemical fertilizer usage in Midwest USA
Reconsidering emissions of ammonia from chemical fertilizer usage in Midwest USA
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DOI：
10.1002/2015jd023219
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发表时间：
2015-06
期刊：
影响因子：
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通讯作者：
Srinidhi Balasubramanian;S. Koloutsou-Vakakis;D. McFarland;M. Rood
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作者：
Srinidhi Balasubramanian;S. Koloutsou-Vakakis;D. McFarland;M. Rood
我们提出了替代方法估计的空间替代品和时间因素氨（NH3）的排放量从化肥的使用（CFU），在美国，在空间和时间尺度上用于模拟区域空气质量和沉积的活性氮的生态系统。新开发的改进空间替代（ISS）方法结合了特定年份的化肥销售数据，高分辨率和特定年份的作物地图以及当地作物氮需求，以4 km × 4 km网格单元分配NH3排放量。结果与常用的网格排放估计稀疏矩阵算子核排放（SMOKE）预处理器进行了比较。在美国伊利诺斯州中部地区的NH3排放，在4 km × 4 km网格水平上用SMOKE和ISS方法估算，显示出-10%至120%的差异，58%的网格单元显示出超过±10%的差异。将ISS方法应用于美国中西部4 km × 4 km的较大区域，也反映出类似的差异。我们还采用了反硝化分解（DNDC）模型，使用多站点和多年分析来开发CFU中NH3排放的每日时间因子。用SMOKE和DNDC方法估算的时间因子之比为0.54 ± 2.35，DNDC确定的日排放峰值比SMOKE大2.5-8倍。确定的排放峰值将是有用的，为未来的空气质量建模工作，了解颗粒物事件，以及在区域颗粒物形成和氮沉降的趋势，为中西部美国，使用拟议的NH3排放清单。
We present alternative methods for estimating spatial surrogates and temporal factors for ammonia (NH3) emissions from chemical fertilizer usage (CFU), in the USA, at spatial and temporal scales used to simulate regional air quality and deposition of reactive nitrogen to ecosystems. The newly developed Improved Spatial Surrogate (ISS) method incorporates year‐specific fertilizer sales data, high resolution and year‐specific crop maps, and local crop nitrogen demands to allocate NH3 emissions at 4 km × 4 km grid cells. Results are compared with the commonly used gridded emission estimates by the Sparse Matrix Operator Kernel Emissions (SMOKE) preprocessor. NH3 emissions over Central Illinois in the USA, estimated at the 4 km × 4 km grid level in SMOKE and ISS methods, exhibit differences between −10% and 120%, with 58% of the grid cells exhibiting more than ±10% difference. Application of the ISS method for a larger domain over the Midwest USA, at 4 km × 4 km, reflected similar differences. We also employed the Denitrification Decomposition (DNDC) model to develop daily temporal factors of NH3 emissions from CFU using multi‐site and multi‐year analyses. Ratio of temporal factors estimated by SMOKE and DNDC methods is 0.54 ± 2.35, with DNDC identifying daily emission peaks 2.5–8 times greater than SMOKE. Identified emission peaks will be useful for future air quality modeling efforts to understand particulate matter episodes, as well as trends in regional particulate matter formation and nitrogen deposition for Midwest USA, using the proposed NH3 emissions inventory.