979 resultados para Methane emissions modeling
Resumo:
An observational study was undertaken to measure odour and dust (PM10 and PM2.5) emission rates and identify non-methane volatile organic compounds (NMVOCs) and odorants in the exhaust air from two tunnel-ventilated layer-chicken sheds that were configured with multi-tiered cages and manure belts. The study sites were located in south-eastern Queensland and the West Gippsland region of Victoria, Australia. Samples were collected in summer and winter on sequential days across the manure-belt cleaning cycle. Odour emissions ranged from 58 to 512 ou/s per 1000 birds (0.03-0.27 ou/s.kg) and dust emission rates ranged 0.014-0.184 mg/s per 1000 birds for PM10 and 0.001-0.190 mg/s per 1000 birds for PM2.5. Twenty NMVOCs were identified, including three that were also identified as odorants using thermal desorption-gas chromatography-mass spectrometry/olfactometry analysis. Odour emission rates were observed to vary with the amount of manure accumulation on the manure belts, being lowest 2-4 days after removing manure. Odour emission rates were also observed to vary with diurnal and seasonal changes in ventilation rate. Dust emissions were observed to increase with ventilation rate but not with manure accumulation. Some NMVOCs were identified at both farms and in different seasons whereas others were observed only at one farm or in one season, indicating that odorant composition was influenced by farm-specific practices and season.
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We evaluate the response to regional and latitudinal changes in aircraft NOx emissions using several climate metrics (radiative forcing (RF), Global Warming Potential (GWP), Global Temperature change Potential (GTP)). Global chemistry transport model integrations were performed with sustained perturbations in regional aircraft and aircraft-like NOx emissions. The RF due to the resulting ozone and methane changes is then calculated. We investigate the impact of emission changes for specific geographical regions (approximating to USA, Europe, India and China) and cruise altitude emission changes in discrete latitude bands covering both hemispheres. We find that lower latitude emission changes (per Tg N) cause ozone and methane RFs that are about a factor of 6 larger than those from higher latitude emission changes. The net RF is positive for all experiments. The meridional extent of the RF is larger for low latitude emissions. GWPs for all emission changes are positive, with tropical emissions having the largest values; the sign of the GTP depends on the choice of time horizon.
Resumo:
We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE-EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 similar to Pg similar to C similar to yr-1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 similar to Mkm2 in 2004 to 7 similar to Mkm2 in 2010. INPE-EM process-based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non-process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 similar to Pg similar to C similar to yr-1 in 2009; the non-process model estimates a decrease from 0.33 to 0.10 similar to Pg similar to C similar to yr-1. We conclude that the INPE-EM is a powerful tool for representing deforestation-driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.
Resumo:
This dissertation represents experimental and numerical investigations of combustion initiation trigged by electrical-discharge-induced plasma within lean and dilute methane air mixture. This research topic is of interest due to its potential to further promote the understanding and prediction of spark ignition quality in high efficiency gasoline engines, which operate with lean and dilute fuel-air mixture. It is specified in this dissertation that the plasma to flame transition is the key process during the spark ignition event, yet it is also the most complicated and least understood procedure. Therefore the investigation is focused on the overlapped periods when plasma and flame both exists in the system. Experimental study is divided into two parts. Experiments in Part I focuses on the flame kernel resulting from the electrical discharge. A number of external factors are found to affect the growth of the flame kernel, resulting in complex correlations between discharge and flame kernel. Heat loss from the flame kernel to code ambient is found to be a dominant factor that quenches the flame kernel. Another experimental focus is on the plasma channel. Electrical discharges into gases induce intense and highly transient plasma. Detailed observation of the size and contents of the discharge-induced plasma channel is performed. Given the complex correlation and the multi-discipline physical/chemical processes involved in the plasma-flame transition, the modeling principle is taken to reproduce detailed transitions numerically with minimum analytical assumptions. Detailed measurement obtained from experimental work facilitates the more accurate description of initial reaction conditions. The novel and unique spark source considering both energy and species deposition is defined in a justified manner, which is the key feature of this Ignition by Plasma (IBP) model. The results of numerical simulation are intuitive and the potential of numerical simulation to better resolve the complex spark ignition mechanism is presented. Meanwhile, imperfections of the IBP model and numerical simulation have been specified and will address future attentions.
Resumo:
The causes of past changes in the global methane cycle and especially the role of marine methane hydrate (clathrate) destabilization events are a matter of debate. Here we present evidence from the North Greenland Ice Core Project ice core based on the hydrogen isotopic composition of methane [dD(CH4)] that clathrates did not cause atmospheric methane concentration to rise at the onset of Dansgaard-Oeschger (DO) events 7 and 8. Box modeling supports boreal wetland emissions as the most likely explanation for the interstadial increase. Moreover, our data show that dD(CH4) dropped 500 years before the onset of DO 8, with CH4 concentration rising only slightly. This can be explained by an early climate response of boreal wetlands, which carry the strongly depleted isotopic signature of high-latitude precipitation at that time.
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We present the first high-resolution (500 m × 500 m) gridded methane (CH4) emission inventory for Switzerland, which integrates the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest soils. National CH4 emissions were disaggregated using detailed geostatistical information on source locations and their spatial extent and process- or area-specific emission factors. In Switzerland, the highest CH4 emissions in 2011 originated from the agricultural sector (150 Gg CH4/yr), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH4/yr) mainly from landfills and the energy sector (12 Gg CH4/yr), which was dominated by emissions from natural gas distribution. Compared to the anthropogenic sources, emissions from natural and semi-natural sources were relatively small (6 Gg CH4/yr), making up only 3 % of the total emissions in Switzerland. CH4 fluxes from agricultural soils were estimated to be not significantly different from zero (between -1.5 and 0 Gg CH4/yr), while forest soils are a CH4 sink (approx. -2.8 Gg CH4/yr), partially offsetting other natural emissions. Estimates of uncertainties are provided for the different sources, including an estimate of spatial disaggregation errors deduced from a comparison with a global (EDGAR v4.2) and a European CH4 inventory (TNO/MACC). This new spatially-explicit emission inventory for Switzerland will provide valuable input for regional scale atmospheric modeling and inverse source estimation.
Resumo:
To date, only few initiatives have been carried out in Spain in order to use mathematical models (e.g. DNDC, DayCent, FASSET y SIMSNIC) to estimate nitrogen (N) and carbon (C) dynamics as well as greenhouse gases (GHG) in Spanish agrosystems. Modeling at this level may allow to gain insight on both the complex relationships between biological and physicochemical processes, controlling the processes leading to GHG production and consumption in soils (e.g. nitrification, denitrification, decomposing, etc.), and the interactions between C and N cycles within the different components of the continuum plant-soil-environment. Additionally, these models can simulate the processes behind production, consumition and transport of GHG (e.g. nitrous oxide, N2O, and carbon dioxide, CO2) in the short and medium term and at different scales. Other sources of potential pollution from soils can be identified and quantified using these process-based models (e.g. NO3 y NH3).