Quantifying nitrogen loss hotspots and mitigation potential for individual fields in the US Corn Belt with a metamodeling approach
Quantifying nitrogen loss hotspots and mitigation potential for individual fields in the US Corn Belt with a metamodeling approach
复制标题
DOI：
10.1088/1748-9326/ac0d21
复制
发表时间：
2021
影响因子：
6.7
通讯作者：
Taegon Kim;Zhenong Jin;Timothy Smith;Licheng Liu;Yufeng Yang;Yi Yang;B. Peng;Kathryn Phillips;K. Guan;Luyi C Hunter;Wang Zhou
中科院分区：
文献类型：
--
作者：
Taegon Kim;Zhenong Jin;Timothy Smith;Licheng Liu;Yufeng Yang;Yi Yang;B. Peng;Kathryn Phillips;K. Guan;Luyi C Hunter;Wang Zhou
美国玉米带的高生产率很大程度上得益于数百万吨人造肥料的消耗。过量施用氮肥在该地区普遍存在，未恢复的氮素最终以一氧化二氮（N2O）排放和氮淋溶的形式从农田中逸出。由于缺乏关于应将重点放在何处以及预期有多大的缓解潜力的实际信息，减轻这些负面影响受到了阻碍。在大范围内，基于过程的作物模型是预测决策所需变量的主要工具，但它们的应用受到昂贵的计算和数据存储成本的限制。为了克服这些挑战，我们建立了一系列元模型，从一个经过验证的基于过程的生物地球化学模型ecosys中了解碳(C)和氮循环的关键机制。经过训练的元模型捕获了艾奥瓦州、伊利诺伊州和印第安纳州99个随机选择的县的生态系统模拟输出的98%以上的可变性。为了确定具有高缓解潜力的热点地区，我们引入了净社会效益（NSB）作为综合通过避免排放和污染物而造成的产量损失和社会效益的指标。研究结果表明，在研究区域内，氮肥减少10%导致N2O排放量减少9.8%，N淋溶减少9.6%，但代价是有机碳损耗增加4.9%，产量减少0.6%。估计年度NSB总额为3.95亿美元（不确定性范围从1.14亿美元到1.71亿美元），其中包括来自社会福利的3.34美元（不确定性范围从4600万美元到1.076亿美元），来自节省肥料的1亿美元（不确定性范围从1300万美元到4.55亿美元），以及来自产量变化的- 4000万美元（不确定性范围从- 2.61亿美元到6900万美元）。对于中位数情景，我们注意到研究区域的20%占NSB的近50%，因此代表了目标缓解的热点地点。尽管不确定性范围表明，开发这样一个高分辨率框架尚未确定，基于情景的估计也不适合为个别农民的管理实践提供信息，但我们的努力为新一代生命周期评估分析工具提供了启示。
The high productivity in the US Corn Belt is largely enabled by the consumption of millions of tons of manufactured fertilizer. Excessive application of nitrogen (N) fertilizer has been pervasive in this region, and the unrecovered N eventually escaped from croplands in forms of nitrous oxide (N2O) emission and N leaching. Mitigating these negative impacts is hindered by a lack of practical information on where to focus and how much mitigation potential to expect. At a large scale, process-based crop models are the primary tools for predicting variables required by decision making, but their applications are prohibited by expensive computational and data storage costs. To overcome these challenges, we built a series of metamodels to learn the key mechanisms regarding the carbon (C) and N cycle from a well-validated process-based biogeochemical model, ecosys. The trained metamodel captures over 98% of the variability of the ecosys simulated outputs for 99 randomly selected counties in Iowa, Illinois, and Indiana. To identify hotspots with high mitigation potential, we introduce net societal benefit (NSB) as an indicator for synthesizing the loss in yield and social benefits through emissions and pollutants avoided. Our results show that reducing N fertilizer by 10% leads to 9.8% less N2O emissions and 9.6% less N leaching at the cost of 4.9% more SOC depletion and 0.6% yield reduction over the study region. The estimated total annual NSB is $395 M (uncertainty ranges from $114 M to $1271 M), including $334 from social benefits (uncertainty ranges from $46 M to $1076 M), $100 M from saving fertilizer (uncertainty ranges from $13 M to $455 M), and −$40 M due to yield changes (uncertainty ranges from −$261 M to $69 M). For the median scenario, we noted that 20% of the study area accounts for nearly 50% of the NSB, and thus represent hotspot locations for targeted mitigation. Although the uncertainty range suggests that developing such a high-resolution framework is not yet settled and the scenario based estimations are not appropriate to inform the management practices for individual farmers, our efforts shed light on the new generation of analytical tools for life cycle assessment.