979 resultados para Methane emissions modeling
Resumo:
The summer diel variation of methane (CH4) flux was investigated in a eutrophic, subtropical lake in China. The CH4 concentration was always supersaturated, and the emission rate ranged from 0.24 to 45.51 mg m(-2) h(-1). The diel variations of CH4 flux in June and August showed a single peak in early afternoon and a minimum in the morning, while the pattern varied irregularly in May. There was a moderate relationship between water and sediment temperature and CH4 emission rate in some months.
Resumo:
The effect of acid rain SO42− deposition on peatland CH4 emissions was examined by manipulating SO42− inputs to a pristine raised peat bog in northern Scotland. Weekly pulses of dissolved Na2SO4 were applied to the bog over two years in doses of 25, 50, and 100 kg S ha−1 yr−1, reflecting the range of pollutant S deposition loads experienced in acid rain-impacted regions of the world. CH4 fluxes were measured at regular intervals using a static chamber/gas chromatographic flame ionization detector method. Total emissions of CH4 were reduced by between 21 and 42% relative to controls, although no significant differences were observed between treatments. Estimated total annual fluxes during the second year of the experiment were 16.6 g m−2 from the controls and (in order of increasing SO42− dose size) 10.7, 13.2, and 9.8 g m−2 from the three SO42− treatments, respectively. The relative extent of CH4 flux suppression varied with changes in both peat temperature and peat water table with the largest suppression during cool periods and episodes of falling water table. Our findings suggest that low doses of SO42− at deposition rates commonly experienced in areas impacted by acid rain, may significantly affect CH4 emissions from wetlands in affected areas. We propose that SO42− from acid rain can stimulate sulfate-reducing bacteria into a population capable of outcompeting methanogens for substrates. We further propose that this microbially mediated interaction may have a significant current and future effect on the contribution of northern peatlands to the global methane budget.
Resumo:
Excrement patches of grazing animals play an important role in greenhouse gas (GHG) fluxes due to the high nitrogen (N) and available carbon (C) deposited in small areas, but little information is available for the effect of excrement in the Inner Mongolian grassland (43 26 degrees N, 116 degrees 40'E). To elucidate the effect of grazing sheep urine, fresh dung and compost on fluxes of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O), a short-term field study (65 days) was carried out in the typical grassland of Inner Mongolia with the optimised closed chamber/GC technique. Compared with the control, cumulative net CH4 consumption decreased 36, 31, and 18% from urine, fresh dung, and compost plots, respectively; net CO2-C output increased by 6.5, 1.5, and 1.2% from urine, fresh dung, and compost treated soil, respectively; about three times as much N2O-N was emitted from urine and the fresh dung treatments during 65 days. Nitrous oxide emission was positively correlated with CO, emission (R = 0.691, P < 0.01) and water-filled pore space (R = 0.698, P < 0.01). The percentages of N2O-N loss of applied-N were 0.44 and 1.05% for urine and fresh dung, respectively. Our results suggest that in autumn in the degraded grassland of Inner Mongolia, the effect of sheep excrement may be ignored when evaluating the total GHG emissions.
Resumo:
To assess the impact of livestock grazing on the emission of greenhouse gases from grazed wetlands, we examined biomass growth of plants, CO2 and CH4 fluxes under grazing and non-grazing conditions on the Qinghai-Tibetan Plateau wetland. After the grazing treatment for a period of about 3 months, net ecosystem CO2 uptake and aboveground biomass were significantly smaller, but ecosystem CH4 emissions were remarkably greater, under grazing conditions than under non-grazing conditions. Examination of the gas-transport system showed that the increased CH4 emissions resulted from mainly the increase of conductance in the gas-transport system of the grazed plants. The sum of global warming potential, which was estimated from the measured CO2 and CH4 fluxes, was 5.6- to 11.3-fold higher under grazing conditions than under non-grazing conditions. The results suggest that livestock grazing may increase the global warming potential of the alpine wetlands. (c) 2005 Elsevier Ltd. All rights reserved.
Resumo:
Economic analyses of climate change policies frequently focus on reductions of energy-related carbon dioxide emissions via market-based, economy-wide policies. The current course of environment and energy policy debate in the United States, however, suggests an alternative outcome: sector-based and/or inefficiently designed policies. This paper uses a collection of specialized, sector-based models in conjunction with a computable general equilibrium model of the economy to examine and compare these policies at an aggregate level. We examine the relative cost of different policies designed to achieve the same quantity of emission reductions. We find that excluding a limited number of sectors from an economy-wide policy does not significantly raise costs. Focusing policy solely on the electricity and transportation sectors doubles costs, however, and using non-market policies can raise cost by a factor of ten. These results are driven in part by, and are sensitive to, our modeling of pre-existing tax distortions. Copyright © 2006 by the IAEE. All rights reserved.
Resumo:
Concentrations and flux densities of methane were determined during a lagrangian study of an advective filament in the permanent upwelling region off western Mauritania. Newly upwelled waters were dominated by the presence of North Atlantic Central Water and surface CH4 concentrations of 2.2 ± 0.3 nmol L-1 were largely in equilibrium with atmospheric values, with surface saturations of 101.7 ± 14%. As the upwelling filament aged and was advected offshore, CH4 enriched South Atlantic Central Water from intermediate depths of 100 to 350m was entrained into the surface mixed layer of the filament following intense mixing associated with the shelf break. Surface saturations increased to 198.9 ± 15% and flux densities increased from a mean value over the shelf of 2.0 ± 1.1 µmol m-2d-1 to a maximum of 22.6 µmol m-2d-1. Annual CH4 emissions for this persistent filament were estimated at 0.77 ± 0.64 Gg which equates to a maximum of 0.35% of the global oceanic budget. This raises the known outgassing intensity of this area and highlights the importance of advecting filaments from upwelling waters as efficient vehicles for air-sea exchange.
Resumo:
Soil gas emissions of methane and carbon dioxide on brownfield sites are usually attributed to anthropogenic activities; however geogenic sources of soil gas are often not considered during site investigation and risk management strategies. This paper presents a field study at a redeveloped brownfield site on a flood plain to identify accumulations of methane biogas trapped in underlying sediments. The investigation is based on a multidisciplinary approach using direct multi-level sampling measurements and Earth resistivity tomography . Resistivity imaging was applied to evaluate the feasibility of identifying the size and spatial continuity of soil gas accumulations in anthropogenic and naturally occurring deposits. As a result, biogas accumulations are described within both anthropogenic deposits and pristine organic sediments. This result is important to identify the correct approaches to identify and manage risks associated with soil gas emissions on brownfield and pristine sites. The organic-rich sediments in Quaternary fluvial environments of São Paulo Basin in particular the Tietê River, biogas reservoirs can be generated and trapped beneath geogenic and anthropogenic layers, potentially requiring the management of brownfield developments across this region.
Resumo:
Environmental problems, especially climate change, have become a serious global issue waiting for people to solve. In the construction industry, the concept of sustainable building is developing to reduce greenhouse gas emissions. In this study, a building information modeling (BIM) based building design optimization method is proposed to facilitate designers to optimize their designs and improve buildings’ sustainability. A revised particle swarm optimization (PSO) algorithm is applied to search for the trade-off between life cycle costs (LCC) and life cycle carbon emissions (LCCE) of building designs. In order tovalidate the effectiveness and efficiency of this method, a case study of an office building is conducted in Hong Kong. The result of the case study shows that this method can enlarge the searching space for optimal design solutions and shorten the processing time for optimal design results, which is really helpful for designers to deliver an economic and environmental friendly design scheme.
Resumo:
New scaled carbon atomic electron-impact excitation data is utilized to evaluate comparisons between experimental measurements and fluid emission modeling of detached plasmas at DIII-D. The C I and C II modeled emission lines for 909.8 and 514.7 nm were overestimated by a factor of 10-20 than observed experimentally for the inner leg, while the outer leg was within a factor of 2. Due to higher modeled emissions, a previous study using the UEDGE code predicted that a higher amount of carbon was required to achieve a detached outboard divertor plasma in L-mode at DIII-D. The line emission predicted by using the new scaled carbon data yields closer results when compared against experiment. We also compare modeling and measurements of Dα emission from neutral deuterium against predictions from newly calculated R-Matrix with pseudostates data available at the ADAS database. © 2013 Published by Elsevier B.V.
Resumo:
Nos últimos anos, o número de vítimas de acidentes de tráfego por milhões de habitantes em Portugal tem sido mais elevado do que a média da União Europeia. Ao nível nacional torna-se premente uma melhor compreensão dos dados de acidentes e sobre o efeito do veículo na gravidade do mesmo. O objetivo principal desta investigação consistiu no desenvolvimento de modelos de previsão da gravidade do acidente, para o caso de um único veículo envolvido e para caso de uma colisão, envolvendo dois veículos. Além disso, esta investigação compreendeu o desenvolvimento de uma análise integrada para avaliar o desempenho do veículo em termos de segurança, eficiência energética e emissões de poluentes. Os dados de acidentes foram recolhidos junto da Guarda Nacional Republicana Portuguesa, na área metropolitana do Porto para o período de 2006-2010. Um total de 1,374 acidentes foram recolhidos, 500 acidentes envolvendo um único veículo e 874 colisões. Para a análise da segurança, foram utilizados modelos de regressão logística. Para os acidentes envolvendo um único veículo, o efeito das características do veículo no risco de feridos graves e/ou mortos (variável resposta definida como binária) foi explorado. Para as colisões envolvendo dois veículos foram criadas duas variáveis binárias adicionais: uma para prever a probabilidade de feridos graves e/ou mortos num dos veículos (designado como veículo V1) e outra para prever a probabilidade de feridos graves e/ou mortos no outro veículo envolvido (designado como veículo V2). Para ultrapassar o desafio e limitações relativas ao tamanho da amostra e desigualdade entre os casos analisados (apenas 5.1% de acidentes graves), foi desenvolvida uma metodologia com base numa estratégia de reamostragem e foram utilizadas 10 amostras geradas de forma aleatória e estratificada para a validação dos modelos. Durante a fase de modelação, foi analisado o efeito das características do veículo, como o peso, a cilindrada, a distância entre eixos e a idade do veículo. Para a análise do consumo de combustível e das emissões, foi aplicada a metodologia CORINAIR. Posteriormente, os dados das emissões foram modelados de forma a serem ajustados a regressões lineares. Finalmente, foi desenvolvido um indicador de análise integrada (denominado “SEG”) que proporciona um método de classificação para avaliar o desempenho do veículo ao nível da segurança rodoviária, consumos e emissões de poluentes.Face aos resultados obtidos, para os acidentes envolvendo um único veículo, o modelo de previsão do risco de gravidade identificou a idade e a cilindrada do veículo como estatisticamente significativas para a previsão de ocorrência de feridos graves e/ou mortos, ao nível de significância de 5%. A exatidão do modelo foi de 58.0% (desvio padrão (D.P.) 3.1). Para as colisões envolvendo dois veículos, ao prever a probabilidade de feridos graves e/ou mortos no veículo V1, a cilindrada do veículo oposto (veículo V2) aumentou o risco para os ocupantes do veículo V1, ao nível de significância de 10%. O modelo para prever o risco de gravidade no veículo V1 revelou um bom desempenho, com uma exatidão de 61.2% (D.P. 2.4). Ao prever a probabilidade de feridos graves e/ou mortos no veículo V2, a cilindrada do veículo V1 aumentou o risco para os ocupantes do veículo V2, ao nível de significância de 5%. O modelo para prever o risco de gravidade no veículo V2 também revelou um desempenho satisfatório, com uma exatidão de 40.5% (D.P. 2.1). Os resultados do indicador integrado SEG revelaram que os veículos mais recentes apresentam uma melhor classificação para os três domínios: segurança, consumo e emissões. Esta investigação demonstra que não existe conflito entre a componente da segurança, a eficiência energética e emissões relativamente ao desempenho dos veículos.
Resumo:
Future changes in population exposures to ambient air pollution are inherently linked with long-term trends in outdoor air quality, but also with changes in the building stock. Moreover, the burden of disease is further driven by the ageing of the European populations. This study aims to assess the impact of changes in climate, emissions, building stocks and population on air pollution related human health impacts across Europe in the future. Therefore an integrated assessment model combining atmospheric models and health impacts has been setup for projections of the future developments in air pollution related premature mortality. The focus is here on the regional scale impacts of exposure to surface ozone (O3), Secondary Inorganic Aerosols (SIA) and primary particulate matter (PPM).
Resumo:
Landwirtschaft spielt eine zentrale Rolle im Erdsystem. Sie trägt durch die Emission von CO2, CH4 und N2O zum Treibhauseffekt bei, kann Bodendegradation und Eutrophierung verursachen, regionale Wasserkreisläufe verändern und wird außerdem stark vom Klimawandel betroffen sein. Da all diese Prozesse durch die zugrunde liegenden Nährstoff- und Wasserflüsse eng miteinander verknüpft sind, sollten sie in einem konsistenten Modellansatz betrachtet werden. Dennoch haben Datenmangel und ungenügendes Prozessverständnis dies bis vor kurzem auf der globalen Skala verhindert. In dieser Arbeit wird die erste Version eines solchen konsistenten globalen Modellansatzes präsentiert, wobei der Schwerpunkt auf der Simulation landwirtschaftlicher Erträge und den resultierenden N2O-Emissionen liegt. Der Grund für diese Schwerpunktsetzung liegt darin, dass die korrekte Abbildung des Pflanzenwachstums eine essentielle Voraussetzung für die Simulation aller anderen Prozesse ist. Des weiteren sind aktuelle und potentielle landwirtschaftliche Erträge wichtige treibende Kräfte für Landnutzungsänderungen und werden stark vom Klimawandel betroffen sein. Den zweiten Schwerpunkt bildet die Abschätzung landwirtschaftlicher N2O-Emissionen, da bislang kein prozessbasiertes N2O-Modell auf der globalen Skala eingesetzt wurde. Als Grundlage für die globale Modellierung wurde das bestehende Agrarökosystemmodell Daycent gewählt. Neben der Schaffung der Simulationsumgebung wurden zunächst die benötigten globalen Datensätze für Bodenparameter, Klima und landwirtschaftliche Bewirtschaftung zusammengestellt. Da für Pflanzzeitpunkte bislang keine globale Datenbasis zur Verfügung steht, und diese sich mit dem Klimawandel ändern werden, wurde eine Routine zur Berechnung von Pflanzzeitpunkten entwickelt. Die Ergebnisse zeigen eine gute Übereinstimmung mit Anbaukalendern der FAO, die für einige Feldfrüchte und Länder verfügbar sind. Danach wurde das Daycent-Modell für die Ertragsberechnung von Weizen, Reis, Mais, Soja, Hirse, Hülsenfrüchten, Kartoffel, Cassava und Baumwolle parametrisiert und kalibriert. Die Simulationsergebnisse zeigen, dass Daycent die wichtigsten Klima-, Boden- und Bewirtschaftungseffekte auf die Ertragsbildung korrekt abbildet. Berechnete Länderdurchschnitte stimmen gut mit Daten der FAO überein (R2 = 0.66 für Weizen, Reis und Mais; R2 = 0.32 für Soja), und räumliche Ertragsmuster entsprechen weitgehend der beobachteten Verteilung von Feldfrüchten und subnationalen Statistiken. Vor der Modellierung landwirtschaftlicher N2O-Emissionen mit dem Daycent-Modell stand eine statistische Analyse von N2O-und NO-Emissionsmessungen aus natürlichen und landwirtschaftlichen Ökosystemen. Die als signifikant identifizierten Parameter für N2O (Düngemenge, Bodenkohlenstoffgehalt, Boden-pH, Textur, Feldfrucht, Düngersorte) und NO (Düngemenge, Bodenstickstoffgehalt, Klima) entsprechen weitgehend den Ergebnissen einer früheren Analyse. Für Emissionen aus Böden unter natürlicher Vegetation, für die es bislang keine solche statistische Untersuchung gab, haben Bodenkohlenstoffgehalt, Boden-pH, Lagerungsdichte, Drainierung und Vegetationstyp einen signifikanten Einfluss auf die N2O-Emissionen, während NO-Emissionen signifikant von Bodenkohlenstoffgehalt und Vegetationstyp abhängen. Basierend auf den daraus entwickelten statistischen Modellen betragen die globalen Emissionen aus Ackerböden 3.3 Tg N/y für N2O, und 1.4 Tg N/y für NO. Solche statistischen Modelle sind nützlich, um Abschätzungen und Unsicherheitsbereiche von N2O- und NO-Emissionen basierend auf einer Vielzahl von Messungen zu berechnen. Die Dynamik des Bodenstickstoffs, insbesondere beeinflusst durch Pflanzenwachstum, Klimawandel und Landnutzungsänderung, kann allerdings nur durch die Anwendung von prozessorientierten Modellen berücksichtigt werden. Zur Modellierung von N2O-Emissionen mit dem Daycent-Modell wurde zunächst dessen Spurengasmodul durch eine detailliertere Berechnung von Nitrifikation und Denitrifikation und die Berücksichtigung von Frost-Auftau-Emissionen weiterentwickelt. Diese überarbeitete Modellversion wurde dann an N2O-Emissionsmessungen unter verschiedenen Klimaten und Feldfrüchten getestet. Sowohl die Dynamik als auch die Gesamtsummen der N2O-Emissionen werden befriedigend abgebildet, wobei die Modelleffizienz für monatliche Mittelwerte zwischen 0.1 und 0.66 für die meisten Standorte liegt. Basierend auf der überarbeiteten Modellversion wurden die N2O-Emissionen für die zuvor parametrisierten Feldfrüchte berechnet. Emissionsraten und feldfruchtspezifische Unterschiede stimmen weitgehend mit Literaturangaben überein. Düngemittelinduzierte Emissionen, die momentan vom IPCC mit 1.25 +/- 1% der eingesetzten Düngemenge abgeschätzt werden, reichen von 0.77% (Reis) bis 2.76% (Mais). Die Summe der berechneten Emissionen aus landwirtschaftlichen Böden beträgt für die Mitte der 1990er Jahre 2.1 Tg N2O-N/y, was mit den Abschätzungen aus anderen Studien übereinstimmt.
Resumo:
Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------
Resumo:
Land use has become a force of global importance, considering that 34% of the Earth’s ice-free surface was covered by croplands or pastures in 2000. The expected increase in global human population together with eminent climate change and associated search for energy sources other than fossil fuels can, through land-use and land-cover changes (LUCC), increase the pressure on nature’s resources, further degrade ecosystem services, and disrupt other planetary systems of key importance to humanity. This thesis presents four modeling studies on the interplay between LUCC, increased production of biofuels and climate change in four selected world regions. In the first study case two new crop types (sugarcane and jatropha) are parameterized in the LPJ for managed Lands dynamic global vegetation model for calculation of their potential productivity. Country-wide spatial variation in the yields of sugarcane and jatropha incurs into substantially different land requirements to meet the biofuel production targets for 2015 in Brazil and India, depending on the location of plantations. Particularly the average land requirements for jatropha in India are considerably higher than previously estimated. These findings indicate that crop zoning is important to avoid excessive LUCC. In the second study case the LandSHIFT model of land-use and land-cover changes is combined with life cycle assessments to investigate the occurrence and extent of biofuel-driven indirect land-use changes (ILUC) in Brazil by 2020. The results show that Brazilian biofuels can indeed cause considerable ILUC, especially by pushing the rangeland frontier into the Amazonian forests. The carbon debt caused by such ILUC would result in no carbon savings (from using plant-based ethanol and biodiesel instead of fossil fuels) before 44 years for sugarcane ethanol and 246 years for soybean biodiesel. The intensification of livestock grazing could avoid such ILUC. We argue that such an intensification of livestock should be supported by the Brazilian biofuel sector, based on the sector’s own interest in minimizing carbon emissions. In the third study there is the development of a new method for crop allocation in LandSHIFT, as influenced by the occurrence and capacity of specific infrastructure units. The method is exemplarily applied in a first assessment of the potential availability of land for biogas production in Germany. The results indicate that Germany has enough land to fulfill virtually all (90 to 98%) its current biogas plant capacity with only cultivated feedstocks. Biogas plants located in South and Southwestern (North and Northeastern) Germany might face more (less) difficulties to fulfill their capacities with cultivated feedstocks, considering that feedstock transport distance to plants is a crucial issue for biogas production. In the fourth study an adapted version of LandSHIFT is used to assess the impacts of contrasting scenarios of climate change and conservation targets on land use in the Brazilian Amazon. Model results show that severe climate change in some regions by 2050 can shift the deforestation frontier to areas that would experience low levels of human intervention under mild climate change (such as the western Amazon forests or parts of the Cerrado savannas). Halting deforestation of the Amazon and of the Brazilian Cerrado would require either a reduction in the production of meat or an intensification of livestock grazing in the region. Such findings point out the need for an integrated/multicisciplinary plan for adaptation to climate change in the Amazon. The overall conclusions of this thesis are that (i) biofuels must be analyzed and planned carefully in order to effectively reduce carbon emissions; (ii) climate change can have considerable impacts on the location and extent of LUCC; and (iii) intensification of grazing livestock represents a promising venue for minimizing the impacts of future land-use and land-cover changes in Brazil.
Resumo:
Little is known about gaseous carbon (C) and nitrogen (N) emissions from traditional terrace agriculture in irrigated high mountain agroecosystems of the subtropics. In an effort towards filling this knowledge gap measurements of carbon dioxide (CO_2), methane (CH_4), ammonia (NH_3) and dinitrous oxide (N_2O) were taken with a mobile photoacoustic infrared multi-gas monitor on manure-filled PE-fibre storage bags and on flood-irrigated untilled and tilled fields in three mountain oases of the northen Omani Al Jabal al Akhdar mountains. During typical 9-11 day irrigation cycles of March, August and September 2006 soil volumetric moisture contents of fields dominated by fodder wheat, barley, oats and pomegranate ranged from 46-23%. While manure incorporation after application effectively reduced gaseous N losses, prolonged storage of manure in heaps or in PE-fibre bags caused large losses of C and N. Given the large irrigation-related turnover of organic C, sustainable agricultural productivity of oasis agriculture in Oman seems to require the integration of livestock which allows for several applications of manure per year at individual rates of 20 t dry matter ha^−1.