Impact of perturbations of nitrogen oxide emissions from global aviation

Application of the Lighthill-Ford theory of spontaneous imbalance to clear-air turbulence forecasting

A new method of clear-air turbulence (CAT) forecasting based on the Lighthill–Ford theory of spontaneous imbalance and emission of inertia–gravity waves has been derived and applied on episodic and seasonal time scales. A scale analysis of this shallow-water theory for midlatitude synoptic-scale flows identifies advection of relative vorticity as the leading-order source term. Examination of leading- and second-order terms elucidates previous, more empirically inspired CAT forecast diagnostics. Application of the Lighthill–Ford theory to the Upper Mississippi and Ohio Valleys CAT outbreak of 9 March 2006 results in good agreement with pilot reports of turbulence. Application of Lighthill–Ford theory to CAT forecasting for the 3 November 2005–26 March 2006 period using 1-h forecasts of the Rapid Update Cycle (RUC) 2 1500 UTC model run leads to superior forecasts compared to the current operational version of the Graphical Turbulence Guidance (GTG1) algorithm, the most skillful operational CAT forecasting method in existence. The results suggest that major improvements in CAT forecasting could result if the methods presented herein become operational.

Spontaneous generation and impact of inertia-gravity waves in a stratified, two-layer shear flow

Inertia-gravity waves exist ubiquitously throughout the stratified parts of the atmosphere and ocean. They are generated by local velocity shears, interactions with topography, and as geostrophic (or spontaneous) adjustment radiation. Relatively little is known about the details of their interaction with the large-scale flow, however. We report on a joint model/laboratory study of a flow in which inertia-gravity waves are generated as spontaneous adjustment radiation by an evolving large-scale mode. We show that their subsequent impact upon the large-scale dynamics is generally small. However, near a potential transition from one large-scale mode to another, in a flow which is simultaneously baroclinically-unstable to more than one mode, the inertia-gravity waves may strongly influence the selection of the mode which actually occurs.

Biogenic nitric oxide emissions from soils: impact on NOx and ozone over West Africa during AMMA (African Monsoon Multidisciplinary Analysis) - observational study

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).

Biogenic nitric oxide emissions from soils: impact on NOx and ozone over West Africa during AMMA (African Monsoon Multidisciplinary Analysis) - Modelling study

Nitrogen oxide biogenic emissions from soils are driven by soil and environmental parameters. The relationship between these parameters and NO fluxes is highly non linear. A new algorithm, based on a neural network calculation, is used to reproduce the NO biogenic emissions linked to precipitations in the Sahel on the 6 August 2006 during the AMMA campaign. This algorithm has been coupled in the surface scheme of a coupled chemistry dynamics model (MesoNH Chemistry) to estimate the impact of the NO emissions on NOx and O3 formation in the lower troposphere for this particular episode. Four different simulations on the same domain and at the same period are compared: one with anthropogenic emissions only, one with soil NO emissions from a static inventory, at low time and space resolution, one with NO emissions from neural network, and one with NO from neural network plus lightning NOx. The influence of NOx from lightning is limited to the upper troposphere. The NO emission from soils calculated with neural network responds to changes in soil moisture giving enhanced emissions over the wetted soil, as observed by aircraft measurements after the passing of a convective system. The subsequent enhancement of NOx and ozone is limited to the lowest layers of the atmosphere in modelling, whereas measurements show higher concentrations above 1000 m. The neural network algorithm, applied in the Sahel region for one particular day of the wet season, allows an immediate response of fluxes to environmental parameters, unlike static emission inventories. Stewart et al (2008) is a companion paper to this one which looks at NOx and ozone concentrations in the boundary layer as measured on a research aircraft, examines how they vary with respect to the soil moisture, as indicated by surface temperature anomalies, and deduces NOx fluxes. In this current paper the model-derived results are compared to the observations and calculated fluxes presented by Stewart et al (2008).

Best Available Techniques (BAT) and coal fired power stations: Can the energy gap be plugged without increasing emissions?

At present, there is much anxiety regarding the security of energy supplies; for example, the UK and other European States are set to become increasingly dependant upon imports of natural gas from states with which political relations are often strained. These uncertainties are felt acutely by the electricity generating sector, which is facing major challenges regarding the choice of fuel mix in the years ahead. Nuclear energy may provide an alternative; however, in the UK, progress in replacing the first generation reactors is exceedingly slow. A number of operators are looking to coal as a means of plugging the energy gap. However, in the light of ever more stringent legal controls on emissions, this step cannot be taken without the adoption of sophisticated pollution abatement technology. This article examines the role which legal concepts such as Best Available Techniques (BAT) must play in bringing about these changes.

Direct estimates of emissions from the megacity of Lagos

We report here top-down emissions estimates for an African megacity. A boundary layer circumnavigation of Lagos, Nigeria was completed using the FAAM BAe146 aircraft as part of the AMMA project. These observations together with an inferred boundary layer height allow the flux of pollutants to be calculated. Extrapolation gives annual emissions for CO, NOx, and VOCs of 1.44 Tg yr−1, 0.03 Tg yr−1 and 0.37 Tg yr−1 respectively with uncertainties of +250/−60%. These inferred emissions are consistent with bottom-up estimates for other developing megacities and are attributed to the evaporation of fuels, mobile combustion and natural gas emissions.

Association between ovarian follicle development and pregnancy rates in dairy cows undergoing spontaneous oestrous cycles

Ovarian follicle development continues in a wave-like manner during the bovine oestrous cycle giving rise to variation in the duration of ovulatory follicle development. The objectives of the present study were to determine whether a relationship exists between the duration of ovulatory follicle development and pregnancy rates following artificial insemination (AI) in dairy cows undergoing spontaneous oestrous cycles, and to identify factors influencing follicle turnover and pregnancy rate and the relationship between these two variables. Follicle development was monitored by daily transrectal ultrasonography from 10 days after oestrus until the subsequent oestrus in 158 lactating dairy cows. The cows were artificially inseminated following the second observed oestrus and pregnancy was diagnosed 35 days later. The predominant pattern of follicle development was two follicle waves (74.7%) with three follicle waves in 22.1% of oestrous cycles and four or more follicle waves in 3.2% of oestrous cycles. The interval from ovulatory follicle emergence to oestrus (EOI) was 3 days longer (P < 0.0001) in cows with two follicle waves than in those with three waves. Ovulatory follicles from two-wave oestrous cycles grew more slowly but were approximately 2 mm larger (P < 0.0001) on the day of oestrus. Twin ovulations were observed in 14.2% of oestrous cycles and occurred more frequently (P < 0.001) in three-wave oestrous cycles; consequently EOI was shorter in cows with twin ovulations. Overall, 57.0% of the cows were diagnosed pregnant 35 days after AI. Linear logistic regression analysis revealed an inverse relationship between EOI and the proportion of cows diagnosed pregnant, among all cows (n = 158; P < 0.01) and amongst those with single ovulations (n = 145; P < 0.05). Mean EOI was approximately I day shorter (P < 0.01) in cows that became pregnant than in non-pregnant cows; however, pregnancy rates did not differ significantly among cows with different patterns of follicle development. These findings confirm and extend previous observations in pharmacologically manipulated cattle and show, for the first time, that in dairy cows undergoing spontaneous oestrous cycles, natural variation in the duration of post-emergence ovulatory follicle development has a significant effect on pregnancy rate, presumably reflecting variation in oocyte developmental competence.

Results of a mechanistic model estimating methane in relation to methane emissions measured in dairy cows

This investigation determines the accuracy of estimation of methanogenesis by a dynamic mechanistic model with real data determined in a respiration trial, where cows were fed a wide range of different carbohydrates included in the concentrates. The model was able to predict ECM (Energy corrected milk) very well, while the NDF digestibility of fibrous feed was less well predicted. Methane emissions were predicted quite well, with the exception of one diet containing wheat. The mechanistic model is therefore a helpful tool to estimate methanogenesis based on chemical analysis and dry matter intake, but the prediction can still be improved.