Impact of perturbations of nitrogen oxide emissions from global aviation

Intercontinental transport of nitrogen oxide pollution plumes

We describe the first satellite observation of intercontinental transport of nitrogen oxides emitted by power plants, verified by simulations with a particle tracer model. The analysis of such episodes shows that anthropogenic NOx plumes may influence the atmospheric chemistry thousands of kilometers away from its origin, as well as the ocean they traverse due to nitrogen fertilization. This kind of monitoring became possible by applying an improved algorithm to extract the tropospheric fraction of NO2 from the spectral data coming from the GOME instrument.As an example we show the observation of NO2 in the time period 4-14 May, 1998, from the South African Plateau to Australia which was possible due to favourable weather conditions during that time period which availed the satellite measurement. This episode was also simulated with the Lagrangian particle dispersion model FLEXPART which uses NOx emissions taken from an inventory for industrial emissions in South Africa and is driven with analyses from the European Centre for Medium-RangeWeather Forecasts. Additionally lightning emissions were taken into account by utilizing Lightning Imaging Sensor data. Lightning was found to contribute probably not more than 25% of the resulting concentrations. Both, the measured and simulated emission plume show matching patterns while traversing the Indian Ocean to Australia and show great resemblance to the aerosol and CO2 transport observed by Piketh et al. (2000).

Role of maize stover incorporation on nitrogen oxide emissions in a non-irrigated Mediterranean barley field.

Aims Agricultural soils in semiarid Mediterranean areas are characterized by low organic matter contents and low fertility levels. Application of crop residues and/or manures as amendments is a cost-effective and sustainable alternative to overcome this problem. However, these management practices may induce important changes in the nitrogen oxide emissions from these agroecosystems, with additional impacts on carbon dioxide emissions. In this context, a field experiment was carried out with a barley (Hordeum vulgare L.) crop under Mediterranean conditions to evaluate the effect of combining maize (Zea mays L.) residues and N fertilizer inputs (organic and/or mineral) on these emissions. Methods Crop yield and N uptake, soil mineral N concentrations, dissolved organic carbon (DOC), denitrification capacity, N2O, NO and CO2 fluxes were measured during the growing season. Results The incorporation of maize stover increased N2O emissions during the experimental period by c. 105 %. Conversely, NO emissions were significantly reduced in the plots amended with crop residues. The partial substitution of urea by pig slurry reduced net N2O emissions by 46 and 39 %, with and without the incorporation of crop residues respectively. Net emissions of NO were reduced 38 and 17 % for the same treatments. Molar DOC:NO 3 − ratio was found to be a robust predictor of N2O and NO fluxes. Conclusions The main effect of the interaction between crop residue and N fertilizer application occurred in the medium term (4–6 month after application), enhancing N2O emissions and decreasing NO emissions as consequence of residue incorporation. The substitution of urea by pig slurry can be considered a good management strategy since N2O and NO emissions were reduced by the use of the organic residue.

N-Management using Nitrification inhibitor DMPP to Reduce Nitrogen Oxide Emissions in Mediterranean Winter Barley.

Increasing nitrogen (N) use efficiency during crop production is paramount both from an economic and environmental perspective. A proposed measure to achieve it is to split the addition of fertilizers with more than on application. For a winter crop under Mediterranean climatic conditions, the most common application pattern consists of a basal fertilization (October-November) an a top-dressing (February-March).

A study in the reduction of efficiency of nitrogen oxide removal catalysts for automobiles

Automotive catalysts are the most effective short-term answer to air pollution from automobiles. Since strict control of exhaust emissions is, or will be,covered by legislation in most developed countries in the world, catalytic devices will be increasingly fitted to cars. There is consequently an urgent need for the development of catalysts that will not compete for scarce precious metal resources. A number of problems have already been identified in connection with base metal catalysts but quantitative investigations are lacking. The base metal reduction catalysts developed by Imperial Chemical Industries Limited, catalysts and Chemical Group, in collaboration with the Air Pollution Control Laboratory, B L Cars Limited for automotive emission control, are susceptible to de-activation by three major mechanisms. These are: physical loss of the wash-coat (a high surface area coating which supports the active species), aggregation of the active species and poisoning by fuel and engine oil additives. This thesis is especially concerned with the first two of these and attempts to indicate the relative magnitude .of their effect on the activity of. the catalysts. Aggregation of the active species or sintering, as it is loosely called, was studied by using impregnated granules to overcome effects due to the loss of the wash-coat. Samples were aged in a synthetic exhaust gas, free from poisons, and metal crystallite sizes were measured by scanning-electron microscopy. The increase in particle size was correlated with the loss in catalytic activity. In order to maintain a link with the real conditions of service a number of monolithic catalysts were tested in an engine-dynamometer and several previously tested endurance catalysts were examined. A mechanism is proposed for the break-up and subsequent 10s.5 of the wash-coat and suggestions for improved resistance to loss of the' coating and active species are proposed.

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).

Global simulated soil biogenic nitric oxide (NO) emissions: Impact, improvement and innovation

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

Opposite effects of nitric oxide and nitroxyl on postischemic myocardial injury

Recent experimental evidence suggests that reactive nitrogen oxide species can contribute significantly to postischemic myocardial injury. The aim of the present study was to evaluate the role of two reactive nitrogen oxide species, nitroxyl (NO−) and nitric oxide (NO⋅), in myocardial ischemia and reperfusion injury. Rabbits were subjected to 45 min of regional myocardial ischemia followed by 180 min of reperfusion. Vehicle (0.9% NaCl), 1 μmol/kg S-nitrosoglutathione (GSNO) (an NO⋅ donor), or 3 μmol/kg Angeli’s salt (AS) (a source of NO−) were given i.v. 5 min before reperfusion. Treatment with GSNO markedly attenuated reperfusion injury, as evidenced by improved cardiac function, decreased plasma creatine kinase activity, reduced necrotic size, and decreased myocardial myeloperoxidase activity. In contrast, the administration of AS at a hemodynamically equieffective dose not only failed to attenuate but, rather, aggravated reperfusion injury, indicated by an increased left ventricular end diastolic pressure, myocardial creatine kinase release and necrotic size. Decomposed AS was without effect. Co-administration of AS with ferricyanide, a one-electron oxidant that converts NO− to NO⋅, completely blocked the injurious effects of AS and exerted significant cardioprotective effects similar to those of GSNO. These results demonstrate that, although NO⋅ is protective, NO− increases the tissue damage that occurs during ischemia/reperfusion and suggest that formation of nitroxyl may contribute to postischemic myocardial injury.

The role of non-thermal plasma technique in {NOx} treatment: A review

Non-thermal plasma (NTP) has been introduced over the past several years as a promising method for nitrogen oxide (NOx) removal. The intent, when using NTP, is to selectively transfer input electrical energy to the electrons, and to not expend this in heating the entire gas stream, which generates free radicals through collisions, and promotes the desired chemical changes in the exhaust gases. The generated active species react with the pollutant molecules and decompose them. This paper reviews and summarizes relevant literature regarding various aspects of the application of {NTP} technology on {NOx} removal from exhaust gases. A comprehensive description of available scientific literature on {NOx} removal using {NTP} technology is presented, including various types of NTP, e.g. dielectric barrier discharge, corona discharge and electron beam. Furthermore, the combination of {NTP} with catalyst and adsorbent for better {NOx} removal efficiency is presented in detail. The removal of {NOx} from both simulated gases and real diesel engines is also considered in this review paper. As {NTP} is a new technique and is not yet commercialized, there is a need for more studies to be performed in this field.

Load estimation with uncertainties from opportunistic sampling data: A semiparametric approach

We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Analyzing changes in macro-level drivers of country-specific emissions : The role of consumption, technology and trade

Industrial ecology is an important field of sustainability science. It can be applied to study environmental problems in a policy relevant manner. Industrial ecology uses ecosystem analogy; it aims at closing the loop of materials and substances and at the same time reducing resource consumption and environmental emissions. Emissions from human activities are related to human interference in material cycles. Carbon (C), nitrogen (N) and phosphorus (P) are essential elements for all living organisms, but in excess have negative environmental impacts, such as climate change (CO2, CH4 N2O), acidification (NOx) and eutrophication (N, P). Several indirect macro-level drivers affect emissions change. Population and affluence (GDP/capita) often act as upward drivers for emissions. Technology, as emissions per service used, and consumption, as economic intensity of use, may act as drivers resulting in a reduction in emissions. In addition, the development of country-specific emissions is affected by international trade. The aim of this study was to analyse changes in emissions as affected by macro-level drivers in different European case studies. ImPACT decomposition analysis (IPAT identity) was applied as a method in papers I III. The macro-level perspective was applied to evaluate CO2 emission reduction targets (paper II) and the sharing of greenhouse gas emission reduction targets (paper IV) in the European Union (EU27) up to the year 2020. Data for the study were mainly gathered from official statistics. In all cases, the results were discussed from an environmental policy perspective. The development of nitrogen oxide (NOx) emissions was analysed in the Finnish energy sector during a long time period, 1950 2003 (paper I). Finnish emissions of NOx began to decrease in the 1980s as the progress in technology in terms of NOx/energy curbed the impact of the growth in affluence and population. Carbon dioxide (CO2) emissions related to energy use during 1993 2004 (paper II) were analysed by country and region within the European Union. Considering energy-based CO2 emissions in the European Union, dematerialization and decarbonisation did occur, but not sufficiently to offset population growth and the rapidly increasing affluence during 1993 2004. The development of nitrogen and phosphorus load from aquaculture in relation to salmonid consumption in Finland during 1980 2007 was examined, including international trade in the analysis (paper III). A regional environmental issue, eutrophication of the Baltic Sea, and a marginal, yet locally important source of nutrients was used as a case. Nutrient emissions from Finnish aquaculture decreased from the 1990s onwards: although population, affluence and salmonid consumption steadily increased, aquaculture technology improved and the relative share of imported salmonids increased. According to the sustainability challenge in industrial ecology, the environmental impact of the growing population size and affluence should be compensated by improvements in technology (emissions/service used) and with dematerialisation. In the studied cases, the emission intensity of energy production could be lowered for NOx by cleaning the exhaust gases. Reorganization of the structure of energy production as well as technological innovations will be essential in lowering the emissions of both CO2 and NOx. Regarding the intensity of energy use, making the combustion of fuels more efficient and reducing energy use are essential. In reducing nutrient emissions from Finnish aquaculture to the Baltic Sea (paper III) through technology, limits of biological and physical properties of cultured fish, among others, will eventually be faced. Regarding consumption, salmonids are preferred to many other protein sources. Regarding trade, increasing the proportion of imports will outsource the impacts. Besides improving technology and dematerialization, other viewpoints may also be needed. Reducing the total amount of nutrients cycling in energy systems and eventually contributing to NOx emissions needs to be emphasized. Considering aquaculture emissions, nutrient cycles can be partly closed through using local fish as feed replacing imported feed. In particular, the reduction of CO2 emissions in the future is a very challenging task when considering the necessary rates of dematerialisation and decarbonisation (paper II). Climate change mitigation may have to focus on other greenhouse gases than CO2 and on the potential role of biomass as a carbon sink, among others. The global population is growing and scaling up the environmental impact. Population issues and growing affluence must be considered when discussing emission reductions. Climate policy has only very recently had an influence on emissions, and strong actions are now called for climate change mitigation. Environmental policies in general must cover all the regions related to production and impacts in order to avoid outsourcing of emissions and leakage effects. The macro-level drivers affecting changes in emissions can be identified with the ImPACT framework. Statistics for generally known macro-indicators are currently relatively well available for different countries, and the method is transparent. In the papers included in this study, a similar method was successfully applied in different types of case studies. Using transparent macro-level figures and a simple top-down approach are also appropriate in evaluating and setting international emission reduction targets, as demonstrated in papers II and IV. The projected rates of population and affluence growth are especially worth consideration in setting targets. However, sensitivities in calculations must be carefully acknowledged. In the basic form of the ImPACT model, the economic intensity of consumption and emission intensity of use are included. In seeking to examine consumption but also international trade in more detail, imports were included in paper III. This example demonstrates well how outsourcing of production influences domestic emissions. Country-specific production-based emissions have often been used in similar decomposition analyses. Nevertheless, trade-related issues must not be ignored.