Global simulated soil biogenic nitric oxide (NO) emissions: Impact, improvement and innovation
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Abstract
rnNitric oxide (NO) is important for several chemical processes in the atmosphere. Together with nitrogen dioxide (NO2 ) it is better known as nitrogen oxide (NOx ). NOx is crucial for the production and destruction of ozone. In several reactions it catalyzes the oxidation of methane and volatile organic compounds (VOCs) and in this context it is involved in the cycling of the hydroxyl radical (OH). OH is a reactive radical, capable of oxidizing most organic species. Therefore, OH is also called the “detergent” of the atmosphere. Nitric oxide originates from several sources: fossil fuel combustion, biomass burning, lightning and soils. Fossil fuel combustion is the largest source. The others are, depending on the reviewed literature, generally comparable to each other. The individual sources show a different temporal and spatial pattern in their magnitude of emission. Fossil fuel combustion is important in densely populated places, where NO from other sources is less important. In contrast NO emissions from soils (hereafter SNOx) or biomass burning are the dominant source of NOx in remote regions.rnBy applying an atmospheric chemistry global climate model (AC-GCM) I demonstrate that SNOx is responsible for a significant part of NOx in the atmosphere. Furthermore, it increases the O3 and OH mixing ratio substantially, leading to a ∼10% increase in the oxidizing efficiency of the atmosphere. Interestingly, through reduced O3 and OH mixing ratios in simulations without SNOx, the lifetime of NOx increases in regions with other dominating sources of NOx , leading to a counterintuitive increase in the NOx mixing ratio there.rnWith a compilation of previous and recent measurements from the literature I improve the algorithm to calculate SNOx without changing the underlying mathematical principles. This leads to increased emissions, which are in better agreement with satellite derived emissions. To support future development in the field, I identify regions without measurements.rnThe most commonly applied algorithm to calculate SNOx uses a classification of twelve ecosystem, four that do not include any emissions and two are treated separately. The remaining six are categorized in either a wet or a dry soil moisture state and emissions are calculated as a function of soil temperature. However, global models have become more complex since the development of the previous algorithm, and therefore I can make use a continuous function of the soil moisture and soil temperature to calculate SNOx. I apply additional physical parameters, taken from a world soil database, and chemical parameters, taken from a biosphere model, to derive a new method for simulating SNOx. The results vary between 22 Tg(N) yr−1 and 31 Tg(N) yr−1 , which are above previous estimates (5.5 – 21 Tg(N) yr−1 ). However, the spatial pattern in general agrees well with previous estimates, indicating the promise of this future direction for SNOx.