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Abstract
Abstract. Chemical and meteorological parameters measured on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe 146 Atmospheric Research Aircraft during the African Monsoon Multidisciplinary Analysis (AMMA) campaign are presented to show the impact of NOx emissions from recently wetted soils in West Africa. NO emissions from soils have been previously observed in many geographical areas with different types of soil/vegetation cover during small scale studies and have been inferred at large scales from satellite measurements of NOx. This study is the first dedicated to showing the emissions of NOx at an intermediate scale between local surface sites and continental satellite measurements. The measurements reveal pronounced mesoscale variations in NOx concentrations closely linked to spatial patterns of antecedent rainfall. Fluxes required to maintain the NOx concentrations observed by the BAe-146 in a number of cases studies and for a range of assumed OH concentrations (1×106 to 1×107 molecules cm−3) are calculated to be in the range 8.4 to 36.1 ng N m−2 s−1. These values are comparable to the range of fluxes from 0.5 to 28 ng N m−2 s−1 reported from small scale field studies in a variety of non-nutrient rich tropical and sub-tropical locations reported in the review of Davidson and Kingerlee (1997). The fluxes calculated in the present study have been scaled up to cover the area of the Sahel bounded by 10 to 20 N and 10 E to 20 W giving an estimated emission of 0.03 to 0.30 Tg N from this area for July and August 2006. The observed chemical data also suggest that the NOx emitted from soils is taking part in ozone formation as ozone concentrations exhibit similar fine scale structure to the NOx, with enhancements over the wet soils. Such variability can not be explained on the basis of transport from other areas. Delon et al. (2008) is a companion paper to this one which models the impact of soil NOx emissions on the NOx and ozone concentration over West Africa during AMMA. It employs an artificial neural network to define the emissions of NOx from soils, integrated into a coupled chemistry-dynamics model. The results are compared to the observed data presented in this paper. Here we compare fluxes deduced from the observed data with the model-derived values from Delon et al. (2008).
Highlights
Oxides of nitrogen play a key role in almost all aspects of atmospheric chemistry.Emissions of nitrogen oxides (NOx=NO+NO2) are a key factor in tropospheric ozone production and affect the oxidative capacity of the atmosphere (Wayne, 1991)
This paper employs a top-down approach using NOx concentrations measured in the boundary layer on the BAe-146 aircraft, whilst Delon et al (2008) employ a bottom-up approach by incorporating an artificial neural network (ANN), constrained by previous field studies, into a 3-D mesoscale, coupled chemistry-dynamics model and comparing the resulting NOx concentrations with those measured on the BAe146
These cases were selected from the larger series of African Monsoon Multidisciplinary Analysis (AMMA) flights because they captured well-defined soil moisture features which were detectable with LST anomaly (LSTA) due to lack of cloud
Summary
Oxides of nitrogen play a key role in almost all aspects of atmospheric chemistry. Emissions of nitrogen oxides (NOx=NO+NO2) are a key factor in tropospheric ozone production and affect the oxidative capacity of the atmosphere (Wayne, 1991). This paper employs a top-down approach using NOx concentrations measured in the boundary layer on the BAe-146 aircraft, whilst Delon et al (2008) employ a bottom-up approach by incorporating an artificial neural network (ANN), constrained by previous field studies, into a 3-D mesoscale, coupled chemistry-dynamics model and comparing the resulting NOx concentrations with those measured on the BAe146. In this current study the variation of NOx and ozone in the boundary layer is examined with respect to the soil moisture, as indicated by the surface temperature anomalies. In Delon et al (2008), the ability of the model to capture these observed features is examined
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