21 resultados para Global emissions

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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We report ground-based atmospheric measurements and emission estimates for the halons H-1211 (CBrClF₂), H-1301 (CBrF₃), and H-2402 (CBrF₂CBrF₂) from the AGAGE (Advanced Global Atmospheric Gases Experiment) and the National Oceanic and Atmospheric Administration global networks. We also include results from archived air samples in canisters and from polar firn in both hemispheres, thereby deriving an atmospheric record of nearly nine decades (1930s to present). All three halons were absent from the atmosphere until ~1970, when their atmospheric burdens started to increase rapidly. In recent years H-1211 and H-2402 mole fractions have been declining, but H-1301 has continued to grow. High-frequency observations show continuing emissions of H-1211 and H-1301 near most AGAGE sites. For H-2402 the only emissions detected were derived from the region surrounding the Sea of Japan/East Sea. Based on our observations, we derive global emissions using two different inversion approaches. Emissions for H-1211 declined from a peak of 11 kt yr⁻¹ (late 1990s) to 3.9 kt yr⁻¹ at the end of our record (mean of 2013–2015), for H-1301 from 5.4 kt yr⁻¹ (late 1980s) to 1.6 kt yr⁻¹, and for H-2402 from 1.8 kt yr⁻¹ (late 1980s) to 0.38 kt yr⁻¹. Yearly summed halon emissions have decreased substantially; nevertheless, since 2000 they have accounted for ~30% of the emissions of all major anthropogenic ozone depletion substances, when weighted by ozone depletion potentials.

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Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. Based on energy statistics, we estimate that the global emissions of CO2 from fossil fuel combustion and cement production were 9.5 ± 0.5 PgC yr−1 in 2011, 3.0 percent above 2010 levels. We project these emissions will increase by 2.6% (1.9–3.5%) in 2012 based on projections of Gross World Product and recent changes in the carbon intensity of the economy. Global net CO2 emissions from Land-Use Change, including deforestation, are more difficult to update annually because of data availability, but combined evidence from land cover change data, fire activity in regions undergoing deforestation and models suggests those net emissions were 0.9 ± 0.5 PgC yr−1 in 2011. The global atmospheric CO2 concentration is measured directly and reached 391.38 ± 0.13 ppm at the end of year 2011, increasing 1.70 ± 0.09 ppm yr−1 or 3.6 ± 0.2 PgC yr−1 in 2011. Estimates from four ocean models suggest that the ocean CO2 sink was 2.6 ± 0.5 PgC yr−1 in 2011, implying a global residual terrestrial CO2 sink of 4.1 ± 0.9 PgC yr−1. All uncertainties are reported as ±1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future.

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Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

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Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

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Although laboratory experiments have shown that organic compounds in both gasoline fuel and diesel engine exhaust can form secondary organic aerosol (SOA), the fractional contribution from gasoline and diesel exhaust emissions to ambient SOA in urban environments is poorly known. Here we use airborne and ground-based measurements of organic aerosol (OA) in the Los Angeles (LA) Basin, California made during May and June 2010 to assess the amount of SOA formed from diesel emissions. Diesel emissions in the LA Basin vary between weekdays and weekends, with 54% lower diesel emissions on weekends. Despite this difference in source contributions, in air masses with similar degrees of photochemical processing, formation of OA is the same on weekends and weekdays, within the measurement uncertainties. This result indicates that the contribution from diesel emissions to SOA formation is zero within our uncertainties. Therefore, substantial reductions of SOA mass on local to global scales will be achieved by reducing gasoline vehicle emissions.

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Ocean acidification from the uptake of anthropogenic carbon is simulated for the industrial period and IPCC SRES emission scenarios A2 and B1 with a global coupled carbon cycle-climate model. Earlier studies identified seawater saturation state with respect to aragonite, a mineral phase of calcium carbonate, as a key variable governing impacts on corals and other shell-forming organisms. Globally in the A2 scenario, water saturated by more than 300%, considered suitable for coral growth, vanishes by 2070 AD (CO2≈630 ppm), and the ocean volume fraction occupied by saturated water decreases from 42% to 25% over this century. The largest simulated pH changes worldwide occur in Arctic surface waters, where hydrogen ion concentration increases by up to 185% (ΔpH=−0.45). Projected climate change amplifies the decrease in Arctic surface mean saturation and pH by more than 20%, mainly due to freshening and increased carbon uptake in response to sea ice retreat. Modeled saturation compares well with observation-based estimates along an Arctic transect and simulated changes have been corrected for remaining model-data differences in this region. Aragonite undersaturation in Arctic surface waters is projected to occur locally within a decade and to become more widespread as atmospheric CO2 continues to grow. The results imply that surface waters in the Arctic Ocean will become corrosive to aragonite, with potentially large implications for the marine ecosystem, if anthropogenic carbon emissions are not reduced and atmospheric CO2 not kept below 450 ppm.

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Methane is an important greenhouse gas, responsible for about 20 of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios � which differ in fossil fuel and microbial emissions � to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.

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The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

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Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

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Rapid changes in atmospheric methane (CH4), temperature and precipitation are documented by Greenland ice core data both for glacial times (the so called Dansgaard-Oeschger (D-O) events) as well as for a cooling event in the early Holocene (the 8.2 kyr event). The onsets of D-O warm events are paralleled by abrupt increases in CH4 by up to 250 ppb in a few decades. Vice versa, the 8.2 kyr event is accompanied by an intermittent decrease in CH4 of about 80 ppb over 150 yr. The abrupt CH4 changes are thought to mainly originate from source emission variations in tropical and boreal wet ecosystems, but complex process oriented bottom-up model estimates of the changes in these ecosystems during rapid climate changes are still missing. Here we present simulations of CH4 emissions from northern peatlands with the LPJ-Bern dynamic global vegetation model. The model represents CH4 production and oxidation in soils and transport by ebullition, through plant aerenchyma, and by diffusion. Parameters are tuned to represent site emission data as well as inversion-based estimates of northern wetland emissions. The model is forced with climate input data from freshwater hosing experiments using the NCAR CSM1.4 climate model to simulate an abrupt cooling event. A concentration reduction of ~10 ppb is simulated per degree K change of mean northern hemispheric surface temperature in peatlands. Peatland emissions are equally sensitive to both changes in temperature and in precipitation. If simulated changes are taken as an analogy to the 8.2 kyr event, boreal peatland emissions alone could only explain 23 of the 80 ppb decline in atmospheric methane concentration. This points to a significant contribution to source changes from low latitude and tropical wetlands to this event.

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Climate targets are designed to inform policies that would limit the magnitude and impacts of climate change caused by anthropogenic emissions of greenhouse gases and other substances. The target that is currently recognized by most world governments1 places a limit of two degrees Celsius on the global mean warming since preindustrial times. This would require large sustained reductions in carbon dioxide emissions during the twenty-first century and beyond2, 3, 4. Such a global temperature target, however, is not sufficient to control many other quantities, such as transient sea level rise5, ocean acidification6, 7 and net primary production on land8, 9. Here, using an Earth system model of intermediate complexity (EMIC) in an observation-informed Bayesian approach, we show that allowable carbon emissions are substantially reduced when multiple climate targets are set. We take into account uncertainties in physical and carbon cycle model parameters, radiative efficiencies10, climate sensitivity11 and carbon cycle feedbacks12, 13 along with a large set of observational constraints. Within this framework, we explore a broad range of economically feasible greenhouse gas scenarios from the integrated assessment community14, 15, 16, 17 to determine the likelihood of meeting a combination of specific global and regional targets under various assumptions. For any given likelihood of meeting a set of such targets, the allowable cumulative emissions are greatly reduced from those inferred from the temperature target alone. Therefore, temperature targets alone are unable to comprehensively limit the risks from anthropogenic emissions.

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A recent study relying purely on statistical analysis of relatively short time series suggested substantial re-thinking of the traditional view about causality explaining the detected rising trend of atmospheric CO2 (atmCO2) concentrations. If these results are well-justified then they should surely compel a fundamental scientific shift in paradigms regarding both atmospheric greenhouse warming mechanism and global carbon cycle. However, the presented work suffers from serious logical deficiencies such as, 1) what could be the sink for fossil fuel CO2 emissions, if neither the atmosphere nor the ocean – as suggested by the authors – plays a role? 2) What is the alternative explanation for ocean acidification if the ocean is a net source of CO2 to the atmosphere? Probably the most provocative point of the commented study is that anthropogenic emissions have little influence on atmCO2 concentrations. The authors have obviously ignored the reconstructed and directly measured carbon isotopic trends of atmCO2 (both δ13C, and radiocarbon dilution) and the declining O2/N2 ratio, although these parameters provide solid evidence that fossil fuel combustion is the major source of atmCO2 increase throughout the Industrial Era.

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The large, rapid increase in atmospheric N2O concentrations that occurred concurrent with the abrupt warming at the end of the Last Glacial period might have been the result of a reorganization in global biogeochemical cycles. To explore the sensitivity of nitrogen cycling in terrestrial ecosystems to abrupt warming, we combined a scenario of climate and vegetation composition change based on multiproxy data for the Oldest Dryas–Bølling abrupt warming event at Gerzensee, Switzerland, with a biogeochemical model that simulates terrestrial N uptake and release, including N2O emissions. As for many central European sites, the pollen record at the Gerzensee is remarkable for the abundant presence of the symbiotic nitrogen fixer Hippophaë rhamnoides (L.) during the abrupt warming that also marks the beginning of primary succession on immature glacial soils. Here we show that without additional nitrogen fixation, climate change results in a significant increase of N2O emissions of approximately factor 3.4 (from 6.4 ± 1.9 to 21.6 ± 5.9 mg N2O–N m− 2 yr− 1). Each additional 1000 mg m− 2 yr− 1 of nitrogen added to the ecosystem through N-fixation results in additional N2O emissions of 1.6 mg N2O–N m− 2 yr− 1 for the time with maximum H. rhamnoides coverage. Our results suggest that local reactions of emissions to abrupt climate change could have been considerably faster than the overall atmospheric concentration changes observed in polar ice. Nitrogen enrichment of soils due to the presence of symbiotic N-fixers during early primary succession not only facilitates the establishment of vegetation on soils in their initial stage of development, but can also have considerable influence on biogeochemical cycles and the release of reactive nitrogen trace gases to the atmosphere.

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Accurate assessments of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. Finally, the global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms. For the last decade available (2002–2011), EFF was 8.3 ± 0.4 PgC yr−1, ELUC 1.0 ± 0.5 PgC yr−1, GATM 4.3 ± 0.1 PgC yr−1, SOCEAN 2.5 ± 0.5 PgC yr−1, and SLAND 2.6 ± 0.8 PgC yr−1. For year 2011 alone, EFF was 9.5 ± 0.5 PgC yr−1, 3.0 percent above 2010, reflecting a continued trend in these emissions; ELUC was 0.9 ± 0.5 PgC yr−1, approximately constant throughout the decade; GATM was 3.6 ± 0.2 PgC yr−1, SOCEAN was 2.7 ± 0.5 PgC yr−1, and SLAND was 4.1 ± 0.9 PgC yr−1. GATM was low in 2011 compared to the 2002–2011 average because of a high uptake by the land probably in response to natural climate variability associated to La Niña conditions in the Pacific Ocean. The global atmospheric CO2 concentration reached 391.31 ± 0.13 ppm at the end of year 2011. We estimate that EFF will have increased by 2.6% (1.9–3.5%) in 2012 based on projections of gross world product and recent changes in the carbon intensity of the economy. All uncertainties are reported as ±1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future.