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Author(s): Fischer, Marc L.; Parazoo, Nicholas; Brophy, Kieran; Cui, Xinguang; Jeong, Seongeun; Liu, Junjie; Kelling, Ralph; Taylor, Thomas E.; Gurney, Kevin; Oda, Tomohiro; Graven, Heather | Abstract: We report simulation experiments estimating the uncertainties in California regional fossil fuel 36 and biosphere CO2 exchanges that might be obtained using an atmospheric inverse modeling 37 system driven by the combination of ground-based observations of radiocarbon and total CO2, 38 together with column-mean CO2 observations from NASA’s Orbiting Carbon Observatory 39 (OCO-2). The work includes an initial examination of statistical uncertainties in prior models for 40 CO2 exchange, in radiocarbon-based fossil fuel CO2 measurements, in OCO-2 measurements, 41 and in a regional atmospheric transport modeling system. Using these nominal assumptions for 42 measurement and model uncertainties, we find that flask measurements of radiocarbon and total 43 CO2 at 10 towers can be used to distinguish between different fossil fuel emissions data products 44 for major urban regions of California. We then show that the combination of flask and OCO-2 45 observations yield posterior uncertainties in monthly-mean fossil fuel emissions of ~ 5-10%, 46 levels likely useful for policy relevant evaluation of bottom-up fossil fuel emission estimates. 47 Similarly, we find that inversions yield uncertainties in monthly biosphere CO2 exchange of ~ 48 6%-12%, depending on season, providing useful information on net carbon uptake in 49 California’s forests and agricultural lands. Finally, initial sensitivity analysis suggests that 50 obtaining the above results requires control of systematic biases below approximately 0.5 ppm, 51 placing requirements on accuracy of the atmospheric measurements, background subtraction, and 52 atmospheric transport modeling.

We present measurements of CO mole fraction and CO stable isotopes (δ13CO and δC18O) in air during the winters of 2013–14 and 2014–15 at tall tower sampling sites in and around Indianapolis, USA. A tower located upwind of the city was used to quantitatively remove the background CO signal, allowing for the first unambiguous isotopic characterization of the urban CO source and yielding 13CO of –27.7 ± 0.5‰ VPDB and C18O of 17.7 ± 1.1‰ VSMOW for this source. We use the tower isotope measurements, results from a limited traffic study, as well as atmospheric reaction rates to examine contributions from different sources to the Indianapolis CO budget. Our results are consistent with earlier findings that traffic emissions are the dominant source, suggesting a contribution of 96% or more to the overall Indianapolis wintertime CO emissions. Our results are also consistent with the hypothesis that emissions from a small fraction of vehicles without functional catalytic systems dominate the Indianapolis CO budget.

The biophysical–climate and combined biophysical and carbon–climate feedbacks of tropical deforestation rates are explored through sensitivity analyses using the Community Climate System Model 4 with prognostic carbon–nitrogen and dynamic vegetation. Simulations test 5%, 2%, 1%, and 0.5% annual deforestation rates, each paired with preservation targets of 10% per tropical tree type. Perturbations are applied over pan-tropical land but analyses also investigate responses over the subcontinental areas of the Amazon basin, central Africa, and Southeast Asia. Sensitivities [expressed as the change in a variable per million square kilometers (Mkm2) of change in tree cover] and means of selected biophysical, carbon, and climate variables during and after deforestation are compared across rates. The most apparent effect of the rates is in hastening/postponing climate change, but otherwise results show no consistent differences across rates and vary more across subcontinents (with the Amazon basin reflecting highest sensitivities in albedo and ground temperatures, and Southeast Asia for total ecosystem carbon). Additionally, biophysical feedbacks alone were found to have significant impact on climate over subcontinental scales. In the Amazon, ground temperature increase due to biophysical feedbacks is as much as 55%, and precipitation decrease up to 61%, of combined biophysical and carbon impacts. Replication with other models is required. Although it is still unclear whether a slow but prolonged deforestation differs in impacts from one that is rapid but short, the rate can still be relevant to planning with regards to the timing of impacts.

[1] Through an analysis of multiple global fossil fuel CO2 emission data sets, Vulcan emission data for the United States, Canada’s National Inventory Report, and NO2 variability based on satellite observations, we derive scale factors that can be applied to global emission data sets to represent weekly and diurnal CO2 emission variability. This is important for inverse modeling and data assimilation of CO2, which use in situ or satellite measurements subject to variability on these time scales. Model simulations applying the weekly and diurnal scaling show that, although the impacts are minor far away from sources, surface atmospheric CO2 is perturbed by up to 1.58ppm and column-averaged CO2 is perturbed by 0.10.5ppm over some major cities, suggesting the magnitude of model biases for urban areas when these modes of temporal variability are not represented. In addition, we also derive scale factors to account for the large per capita differences in CO2 emissions between Canadian provinces that arise from differences in per capita energy use and the proportion of energy generated by methods that do not emit CO2, which are not accounted for in population-based global emission data sets. The resulting products of these analyses are global 0.25 0.25 gridded scale factor maps that can be applied to global fossil fuel CO2 emission data sets to represent weekly and diurnal variability and 1 1 scale factor maps to redistribute spatially emissions from two common global data sets to account for differences in per capita emissions within Canada.

INTRODUCTION The influence of El Niño on climate is accompanied by large changes to the carbon cycle, and El Niño–induced variability in the carbon cycle has been attributed mainly to the tropical continents. However, owing to a dearth of observations in the tropics, tropical carbon fluxes are poorly quantified, and considerable debate exists over the dominant mechanisms (e.g., plant growth, respiration, fire) and regions (e.g., humid versus semiarid tropics) on the net carbon balance. RATIONALE The launch of the Orbiting Carbon Observatory-2 (OCO-2) shortly before the 2015–2016 El Niño, the second strongest since the 1950s, has provided an opportunity to understand how tropical land carbon fluxes respond to the warm and dry climate characteristics of El Niño conditions. The El Niño events may also provide a natural experiment to study the response of tropical land carbon fluxes to future climate changes, because anomalously warm and dry tropical environments typical of El Niño are expected to be more frequent under most emission scenarios. RESULTS The tropical regions of three continents (South America, Asia, and Africa) had heterogeneous responses to the 2015–2016 El Niño, in terms of both climate drivers and the carbon cycle. The annual mean precipitation over tropical South America and tropical Asia was lower by 3.0σ and 2.8σ, respectively, in 2015 relative to the 2011 La Niña year. Tropical Africa, on the other hand, had near equal precipitation and the same number of dry months between 2015 and 2011; however, surface temperatures were higher by 1.6σ, dominated by the positive anomaly over its eastern and southern regions. In response to the warmer and drier climate anomaly in 2015, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere than in 2011, which accounts for 83.3% of the global total 3.0–gigatons of carbon (gigatons C) net biosphere flux differences and 92.6% of the atmospheric CO 2 growth-rate differences between 2015 and 2011. It indicates that the tropical land biosphere flux anomaly was the driver of the highest atmospheric CO 2 growth rate in 2015. The three tropical continents had an approximately even contribution to the pantropical net carbon flux anomaly in 2015, but had diverse dominant processes: gross primary production (GPP) reduced carbon uptake (0.9 ± 0.96 gigatons C) in tropical South America, fire increased carbon release (0.4 ± 0.08 gigatons C) in tropical Asia, and respiration increased carbon release (0.6 ± 1.01 gigatons C) in Africa. We found that most of the excess carbon release in 2015 was associated with either extremely low precipitation or high temperatures, or both. CONCLUSION Our results indicate that the global El Niño effect is a superposition of regionally specific effects. The heterogeneous climate forcing and carbon response over the three tropical continents to the 2015–2016 El Niño challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability, which could also be due to previous disturbance and soil and vegetation structure. The similarity between the 2015 tropical climate anomaly and the projected climate changes imply that the role of the tropical land as a buffer for fossil fuel emissions may be reduced in the future. The heterogeneous response may reflect differences in temperature and rainfall anomalies, but intrinsic differences in vegetation species, soils, and prior disturbance may contribute as well. A synergistic use of multiple satellite observations and a long time series of spatially resolved fluxes derived from sustained satellite observations will enable tests of these hypotheses, allow for a more process-based understanding, and, ultimately, aid improved carbon-climate model projections. Diverse climate driver anomalies and carbon cycle responses to the 2015–2016 El Niño over the three tropical continents. Schematic of climate anomaly patterns over the three tropical continents and the anomalies of the net carbon flux and its dominant constituent flux (i.e., GPP, respiration, and fire) relative to the 2011 La Niña during the 2015–2016 El Niño. GtC, gigatons C.

Scientific research shows that deforestation can drive climate not only through changes in carbon stocks but also through biophysical feedbacks. These can alter the climate effectiveness of emission reductions and will thus have important implications for REDD+. Explored here are the implications for motivating tropical developing country participation, and for motivating efforts to measure integrated biophysical–carbon climate impacts of land use change. In the tropics, biophysical impacts of deforestation are found to enhance local warming, which suggests that REDD+ participants benefit from a locally concentrated good in the form of local climate impacts, in addition to the global public good in the form of emissions reductions. To capture the breadth of climate impacts of land use change, composite biophysical–carbon indices have been proposed, but are hampered by issues of scale and uncertainty. These issues must at least be acknowledged in policy discussions to allow land-based initiatives to move f...

Deforestation perturbs both biophysical and carbon feedbacks on climate. However, biophysical feedbacks operate at temporally immediate and spatially focused scales and thus may be sensitive to the rate of deforestation rather than just to total forest-cover loss. Explored here is a method for simulating annual tropical deforestation in the fully coupled Community Climate System Model, version 3.0 (CCSM3) with the Dynamic Global Vegetation Model (DGVM) for testing biosphere climate sensitivity to “preservation pathways.” Two deforestation curves were simulated—a 10% deforestation curve with a 10% preservation target (DFC10-PT10) versus a 1% deforestation curve with a 10% preservation target (DFC1-PT10). During active deforestation, albedo, net radiation, latent heat flux, and climate variables were compared for time dependence and sensitivity to tropical tree cover across the tropical band and the Amazon basin, central African, and Southeast Asian regions. The results demonstrated the feasibility of modeling incremental deforestation and detecting both transient and long-term impacts, although a warm/dry bias in CCSM3–DGVM and the absence of carbon feedbacks preclude definitive conclusions on the magnitude of sensitivities. The deforestation rates produced characteristic trends in biophysical variables with DFC10-PT10 resulting in rapid increase/decrease during the initial 10–30 years before leveling off, whereas DFC1-PT10 exhibits gradual changes. The rate had little effect on biophysical and climate sensitivities when averaged over tropical land but produced significant differences at a regional level. Over the long term, the rates produced dissimilar vegetation distributions, despite having the same preservation target in both cases. Overall, these results indicate that the question of rates is one worth further analysis.

This paper examined the relationship between remotely sensed anthropogenic heat discharge and energy use from residential and commercial buildings across multiple scales in the city of Indianapolis, Indiana, USA. The anthropogenic heat discharge was estimated with a remote sensing-based surface energy balance model, which was parameterized using land cover, land surface temperature, albedo, and meteorological data. The building energy use was estimated using a GIS-based building energy simulation model in conjunction with Department of Energy/Energy Information Administration survey data, the Assessor’s parcel data, GIS floor areas data, and remote sensing-derived building height data. The spatial patterns of anthropogenic heat discharge and energy use from residential and commercial buildings were analyzed and compared. Quantitative relationships were evaluated across multiple scales from pixel aggregation to census block. The results indicate that anthropogenic heat discharge is consistent with building energy use in terms of the spatial pattern, and that building energy use accounts for a significant fraction of anthropogenic heat discharge. The research also implies that the relationship between anthropogenic heat discharge and building energy use is scale-dependent. The simultaneous estimation of anthropogenic heat discharge and building energy use via two independent methods improves the understanding of the surface energy balance in an urban landscape. The anthropogenic heat discharge derived from remote sensing and meteorological data may be able to serve as a spatial distribution proxy for spatially-resolved building energy use, and even for fossil-fuel CO2 emissions if additional factors are considered.

In order to advance the scientific understanding of carbon exchange with the land surface, and contribute to quantitative-based US climate change policy interests, quantification of fossil fuel CO2 emissions (the primary greenhouse gas), at fine spatial and temporal scales, is essential. Known as the ‘Hestia Project’, this pilot study has quantified all fossil fuel CO2 emissions down to the scale of individual buildings, road segments and industrial/electricity production facilities on an hourly basis for the greater Indianapolis region, IN, USA. Here, we describe the method used to quantify the on-site fossil fuel CO2 emissions in the residential and commercial sectors. By downscaling the Vulcan Project’s 2002 county-level commercial and residential fossil fuel CO2 emissions, we quantified the CO2 emissions for all building structures using a combination of multiple datasets and energy simulation. At the landscape scale, the spatial variation in CO2 emissions is driven by building density, height and typ...

Local policy makers could benefit from a national, high-resolution inventory of energy consumption and related carbon dioxide (CO 2 ) emissions based on the Vulcan data product, which plots emissions on a 100 km 2 grid. We evaluate the ability of Vulcan to measure energy consumption in urban areas, a scale of analysis required to support goals established as part of local energy, climate or sustainability initiatives. We highlight the methodological challenges of this type of analytical exercise and review alternative approaches. We find that between 37% and 86% of direct fuel consumption in buildings and industry and between 37% and 77% of on-road gasoline and diesel consumption occurs in urban areas, depending on how these areas are defined. We suggest that a county-based definition of urban is preferable to other common definitions since counties are the smallest political unit for which energy data are collected. Urban counties, account for 37% of direct energy consumption, or 50% if mixed urban counties are included. A county-based definition can also improve estimates of per-capita consumption.

Quantification of fossil fuel CO2 emissions at fine space and time resolution is emerging as a critical need in carbon cycle and climate change research. As atmospheric CO2 measurements expand with the advent of a dedicated remote sensing platform and denser in situ measurements, the ability to close the carbon budget at spatial scales of approximately 100 km2 and daily time scales requires fossil fuel CO2 inventories at commensurate resolution. Additionally, the growing interest in U.S. climate change policy measures are best served by emissions that are tied to the driving processes in space and time. Here we introduce a high resolution data product (the "Vulcan" inventory: www.purdue.edu/eas/carbon/vulcan/) that has quantified fossil fuel CO2 emissions for the contiguous U.S. at spatial scales less than 100 km2 and temporal scales as small as hours. This data product completed for the year 2002, includes detail on combustion technology and 48 fuel types through all sectors of the U.S. economy. The Vulcan inventory is built from the decades of local/regional air pollution monitoring and complements these data with census, traffic, and digital road data sets. The Vulcan inventory shows excellent agreement with national-level Department of Energy inventories, despite the different approach taken by the DOE to quantify U.S. fossil fuel CO2 emissions. Comparison to the global 1degree x 1 degree fossil fuel CO2 inventory, used widely by the carbon cycle and climate change community prior to the construction of the Vulcan inventory, highlights the space/time biases inherent in the population-based approach.

Megacities are major sources of anthropogenic fossil fuel CO2 emissions. The spatial extents of these large urban systems cover areas of 10,000 km2 or more with complex topography and changing landscapes. We present a high-resolution land-atmosphere modelling system for urban CO2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO2 emission product, Hestia-LA, to simulate atmospheric CO2 concentrations across the LA megacity at spatial resolutions as fine as ~ 1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as validated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate- (4-km) and high- (1.3-km) resolution simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved PBL heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3-km resolution) fossil fuel CO2 emission products to evaluate the impact of the spatial resolution of the CO2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO2 concentrations. We find that high spatial resolution in the fossil fuel CO2 emissions is more important than in the atmospheric model to capture CO2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO2 fields to qualitatively evaluate greenhouse gas measurements over the LA megacity. Spatial correlations in the atmospheric CO2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO2 emissions monitoring in the LA megacity requires FFCO2 emissions modelling with ~ 1 km resolution since coarser resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO2 mole fractions and Δ14C and δ13C values of CO2 in the Los Angeles megacity observed in inland Pasadena (2006–2013) and coastal Palos Verdes peninsula (autumn 2009–2013), we have determined time series for CO2 contributions from fossil fuel combustion for both sites and broken those down into contributions from petroleum/gasoline and natural gas burning for Pasadena. We find a 10 % reduction in Pasadena CO2 emissions from fossil fuel combustion during the Great Recession of 2008–2010, which is consistent with the bottom-up inventory determined by the California Air Resources Board. The isotopic variations and total atmospheric CO2 from our observations are used to infer seasonality of natural gas and petroleum combustion. For natural gas, inferred emissions are out of phase with the seasonal cycle of total natural gas combustion seasonal patterns in bottom-up inventories but are consistent with the seasonality of natural gas usage by the area's electricity generating power plants. For petroleum, the inferred seasonality of CO2 emissions from burning petroleum is delayed by several months relative to usage indicated by statewide gasoline taxes. Using the high-resolution Hestia-LA data product to compare emissions from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO2 reflect seasonal variations in wind direction. The seasonality of the local CO2 excess from fossil fuel combustion along the coast, on Palos Verdes peninsula, is higher in fall and winter than spring and summer, almost completely out of phase with that from Pasadena, also because of the annual variations of winds in the region. Variations in fossil fuel CO2 signals are consistent with sampling the bottom-up Hestia-LA fossil CO2 emissions product for sub-city source regions in the LA megacity domain when wind directions are considered.

Cities need to understand and manage their carbon footprint at the level of streets, buildings and communities, urge Kevin Robert Gurney and colleagues.

▪ Abstract Agriculture and industrial development have led to inadvertent changes in the natural carbon cycle. As a consequence, concentrations of carbon dioxide and other greenhouse gases have increased in the atmosphere and may lead to changes in climate. The current challenge facing society is to develop options for future management of the carbon cycle. A variety of approaches has been suggested: direct reduction of emissions, deliberate manipulation of the natural carbon cycle to enhance sequestration, and capture and isolation of carbon from fossil fuel use. Policy development to date has laid out some of the general principles to which carbon management should adhere. These are summarized as: how much carbon is stored, by what means, and for how long. To successfully manage carbon for climate purposes requires increased understanding of carbon cycle dynamics and improvement in the scientific capabilities available for measurement as well as for policy needs. The specific needs for scientific information to underpin carbon cycle management decisions are not yet broadly known. A stronger dialogue between decision makers and scientists must be developed to foster improved application of scientific knowledge to decisions. This review focuses on the current knowledge of the carbon cycle, carbon measurement capabilities (with an emphasis on the continental scale) and the relevance of carbon cycle science to carbon sequestration goals.

On June 2, 2014, the United States Environmental Protection Agency proposed goals and guidelines aimed at lowering carbon dioxide (CO2) emissions from existing power plants in the United States. Should it be successfully implemented, US power plant CO2 emissions would be reduced approximately 30 percent below 2005 levels by the year 2030. Rather than a single national reduction goal, the proposed rule specifies reduction targets unique to each US state but leaves the means by which states meet those targets, flexible to individual state conditions. Regardless of the policy mixture adopted in each US state, quantification of CO2 emissions at the level of individual power plants will be a critical need. Recent research examining power plant CO2 emissions has noted potentially large uncertainties at the individual facility level, uncertainty that remains poorly understood. At the same time, carbon scientists working on aspects of monitoring, reporting and verification of anthropogenic CO2 emissions have developed a mixture of measurement and modeling capabilities as part of the development of a “carbon monitoring system”, that could assist in assessing how well independent emissions quantification is performing currently and identify a path towards improved monitoring. Equally important is an assessment of uncertainty at the various space and time scales the EPA proposed rule implies. Application of these recent scientific capabilities to the needs of the EPA’s proposed rule could offer a cogent, near-term example of how scientific research can directly enable better decision-making. This paper provides a review of the proposed rule and what role scientific research could play in the evolution of the rulemaking and its application in the future.

The terrestrial biosphere can release or absorb the greenhouse gases, carbon dioxide (CO[subscript 2]), methane (CH[subscript 4]) and nitrous oxide (N[subscript 2]O), and therefore has an important role in regulating atmospheric composition and climate. Anthropogenic activities such as land-use change, agriculture and waste management have altered terrestrial biogenic greenhouse gas fluxes, and the resulting increases in methane and nitrous oxide emissions in particular can contribute to climate change. The terrestrial biogenic fluxes of individual greenhouse gases have been studied extensively,but the net biogenic greenhouse gas balance resulting from anthropogenic activities and its effect on the climate system remains uncertain. Here we use bottom-up (inventory, statistical extrapolation of local flux measurements, and process-based modelling) and top-down (atmospheric inversions) approaches to quantify the global net biogenic greenhouse gas balance between 1981 and 2010 resulting from anthropogenic activities and its effect on the climate system. We find that the cumulative warming capacity of concurrent biogenic methane and nitrous oxide emissions is a factor of about two larger than the cooling effect resulting from the global land carbon dioxide uptake from 2001 to 2010. This results in a net positive cumulative impact of the three greenhouse gases on the planetary energy budget, with a best estimate (in petagrams of CO[subscript 2] equivalent per year) of 3.9 ± 3.8 (top down) and 5.4 ± 4.8 (bottom up) based on the GWP100 metric (global warming potential on a 100-year time horizon). Our findings suggest that a reduction in agricultural methane and nitrous oxide emissions, particularly in Southern Asia, may help mitigate climate change., United States. National Aeronautics and Space Administration (NASA Grant NNX08AL73G), United States. National Aeronautics and Space Administration (NASA Grant NNX14AO73G), United States. National Aeronautics and Space Administration (NASA Grant NNX10AU06G), United States. National Aeronautics and Space Administration (NASA Grant NNX11AD47G), United States. National Aeronautics and Space Administration (NASA Grant NNG04GM39C), National Science Foundation (U.S.) (NSF grant AGS 1243232), National Science Foundation (U.S.) (Grant AGS-1243220), National Science Foundation (U.S.) (NSF grant CNH1210360), United States. National Oceanic and Atmospheric Administration (NOAA Climate Program Office award NA13OAR4310059), Australian Climate Change Science Programme, National Science Foundation (U.S.) (NSF CAREER (AGS-0846358)), United States. National Aeronautics and Space Administration (NASA Upper Atmosphere Research Program AGAGE, grant NNX11AF17G)

We report the CH4 emission flux from the city of Indianapolis, IN, the site of the Indianapolis Flux Experiment (INFLUX) project for developing, assessing, and improving top-down and bottom-up approaches for quantifying urban greenhouse gas emissions. Using an aircraft-based mass balance approach, we find that the average CH4 emission rate from five flight experiments in 2011 is 135 ± 58 (1σ) moles s-1 (7800 ± 3300 kg hr-1). The effective per capita CH4 emission rate for Indianapolis is 77 kg CH4 person-1 yr-1, a figure that is less than the national anthropogenic CH4 emission (∼91 kg CH4 person-1 yr-1) but considerably larger than the global figure (∼48 kg CH4 person-1 yr-1). We consistently observed elevated CH4 concentrations at specific coordinates along our flight transects downwind of the city. Inflight investigations as well as back trajectories using measured wind directions showed that the elevated concentrations originated from the southwest side of the city where a landfill and a natural gas transmission regulating station (TRS) are located. Street level mobile measurements downwind of the landfill and the TRS supported the results of aircraft-based data, and were used to quantify the relative contributions from the two sources. We find that the CH4 emission from the TRS was negligible relative to the landfill, which was responsible for 33 ± 10% of the citywide emission flux. A regression of propane versus methane from aircraft flask samples suggests that the remaining citywide CH4 emissions (∼67%) derive from the natural gas distribution system. We discuss the combination of surface mobile observations and aircraft city-wide flux measurements to determine the total flux and apportionment to important sources.

Independent lines of research on urbanization, urban areas, and carbon have advanced our understanding of some of the processes through which energy and land uses affect carbon. This synthesis integrates some of these diverse viewpoints as a first step toward a coproduced, integrated framework for understanding urbanization, urban areas, and their relationships to carbon. It suggests the need for approaches that complement and combine the plethora of existing insights into interdisciplinary explorations of how different urbanization processes, and socio-ecological and technological components of urban areas, affect the spatial and temporal patterns of carbon emissions, differentially over time and within and across cities. It also calls for a more holistic approach to examining the carbon implications of urbanization and urban areas, based not only on demographics or income but also on other interconnected features of urban development pathways such as urban form, economic function, economic-growth policies, and other governance arrangements. It points to a wide array of uncertainties around the urbanization processes, their interactions with urban socio-institutional and built environment systems, and how these impact the exchange of carbon flows within and outside urban areas. We must also understand in turn how carbon feedbacks, including carbon impacts and potential impacts of climate change, can affect urbanization processes. Finally, the paper explores options, barriers, and limits to transitioning cities to low-carbon trajectories, and suggests the development of an end-to-end, coproduced and integrated scientific understanding that can more effectively inform the navigation of transitional journeys and the avoidance of obstacles along the way.

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales., JRC.H.7-Climate Risk Management

This paper investigates the expected capabilities of the new generation of infrared satellite sounders for detecting CO2. A general circulation model is used to simulate realistic CO2 fields and to define the needed accuracy of CO2 observations in order to be useful in constraining surface sources and sinks of CO2, which will be described in more detail in a future paper. Optimal estimation retrieval theory is then used to determine the possible accuracy of the satellite measurements and to define the retrieval characteristics. A discussion of several factors that affect the retrievals is also included. We conclude that tropospheric column retrievals of CO2 are possible with an accuracy of better than 1 ppmv on a monthly mean basis. Several factors, like thin cirrus clouds and radiative transfer modeling errors, will degrade these results if not carefully accounted for. The possibility of extensive time and spatial averaging of the satellite observations will overcome some of these problems.

In China, as in other nations that produce carbon dioxide from fossil fuels on a large scale, the terrestrial biosphere mops up a proportion of the emissions. Estimates of the amounts involved are now available. The publication of a comprehensive assessment of China's terrestrial carbon budget fills a major gap in the geographical spread of carbon balance data, and helps to further reduce uncertainties in the Northern Hemisphere carbon balance. Three different indicators were used to monitor China's carbon balance and its driving mechanisms during the 1980s and 1990s: biomass and soil carbon inventories extrapolated from satellite greenness measurements, ecosystem models and atmospheric inversions. The three methods produce similar estimates for the net carbon sink at 0.19 to 0.26 petagrams per year. Global terrestrial ecosystems, in comparison, have absorbed carbon at a rate of 1 to 4 Pg carbon per year during the 1980s and 1990s, which offsets 10–60% of fossil fuel emissions. Northeast China is a net source of CO2 to the atmosphere as a result over-harvesting and degradation of forests. In contrast, southern China accounts for over 65% of the carbon sink, attributable to regional climate change, tree planting and shrub recovery.

Sulfur hexafluoride (SF 6 ) is an excellent tracer of large-scale atmospheric transport, because it has slowly increasing sources mostly confined to northern midlatitudes, and has a lifetime of thousands of years. We have simulated the emissions, transport, and concentration of SF 6 for a 5-year period, and compared the results with atmospheric observations. In addition, we have performed an intercomparison of interhemispheric transport among 11 models to investigate the reasons for the differences among the simulations. Most of the models are reasonably successful at simulating the observed meridional gradient of SF 6 in the remote marine boundary layer, though there is less agreement at continental sites. Models that compare well to observations in the remote marine boundary layer tend to systematically overestimate SF 6 at continental locations in source regions, suggesting that vertical trapping rather than meridional transport may be a dominant control on the simulated meridional gradient. The vertical structure of simulated SF 6 in the models supports this interpretation. Some of the models perform quite well in terms of the simulated seasonal cycle at remote locations, while others do not. Interhemispheric exchange time varies by a factor of 2 when estimated from 1-dimensional meridional profiles at the surface, as has been done for observations. The agreement among models is better when the global surface mean mole fraction is used, and better still when the full 3-dimensional mean mixing ratio is used. The ranking of the interhemispheric exchange time among the models is not sensitive to the change from station values to surface means, but is very sensitive to the change from surface means to the full 3-dimensional tracer fields. This strengthens the argument that vertical redistribution dominates over interhemispheric transport in determining the meridional gradient at the surface. Vertically integrated meridional transport in the models is divided roughly equally into transport by the mean motion, the standing eddies, and the transient eddies. The vertically integrated mass flux is a good index of the degree to which resolved advection vs. parameterized diffusion accomplishes the meridional transport of SF 6 . Observational programs could provide a much better constraint on simulated chemical tracer transport if they included regular sampling of vertical profiles of nonreactive trace gases over source regions and meridional profiles in the middle to upper troposphere. Further analysis of the SF 6 simulations will focus on the subgrid-scale parameterized transports. DOI: 10.1034/j.1600-0889.1999.00012.x

This paper presents analysis of noontime ultraviolet irradiance measurements made at Point Barrow, Alaska (71.2° N, 159° W) between the years 1991 and 1996. Eighteen wavelengths of the solar irradiance spectrum between 290 nm and 340 nm were examined for multiyear trends. This spectral region is particularly critical as these wavelengths are known to cause biological damage. After reducing the effects of clouds, 305 nanometer wavelength increases ranging between 3 and 10% per year were found in all daylit months except June which exhibited an annual average decline of approximately −3% per year at this wavelength. The correlation between the absorption cross-section of ozone and the spectral character of the UV-B changes suggest that declines in column ozone are responsible for the dramatic 305 nm increases. The unexpected decline in June 305 nm irradiance may be due to an increase in column ozone over this location in June.

[1] The international carbon cycle research community is currently coordinating the largest, most comprehensive assessment it has ever undertaken: the Regional Carbon Cycle Assessment and Processes (RECCAP; http://www.globalcarbonproject.org/reccap). The objective is to establish the mean carbon balance and change over the period 1990–2009 for all subcontinents and ocean basins. The global coverage will provide, for the first time, opportunities to link regional budgets with the global carbon budget. Regional details on or insights into processes driving fluxes have not, to date, been incorporated into efforts addressing the global carbon budget [Canadell et al., 2007; Le Quere et al., 2009]. The consistency check between the sum of regional fluxes and the global budget will be a unique measure of the level of confidence there is in scaling carbon budgets up and down.

Power plants constitute roughly 40% of carbon dioxide (CO2) emissions in the United States. Climate change science, air pollution regulation, and potential carbon trading policies rely on accurate, unbiased quantification of these large point sources. Two US federal agencies—the Department of Energy and the Environmental Protection Agency—tabulate the emissions from US power plants using two different methodological approaches. We have analyzed those two data sets and have found that when averaged over all US facilities, the median percentage difference is less than 3%. However, this small difference masks large, non-Gaussian, positive and negative differences at individual facilities. For example, over the 2001–2009 time period, nearly one-half of the facilities have monthly emission differences that exceed roughly ±6% and one-fifth exceed roughly ±13%. It is currently not possible to assess whether one, or both, of the datasets examined here are responsible for the emissions difference. Differences this large at the individual facility level raise concerns regarding the operationalization of policy within the United States such as the recently announced Clean Power Plan. This policy relies on the achievement of state-level CO2 emission rate targets. When examined at the state-level we find that one-third of the states have differences that exceed 10% of their assigned reduction amount. Such levels of uncertainty raise concerns about the ability of individual states to accurately quantify emission rates in order to meet the regulatory targets.

In order to advance the scientific understanding of carbon exchange with the land surface, build an effective carbon monitoring system, and contribute to quantitatively based U.S. climate change policy interests, fine spatial and temporal quantification of fossil fuel CO(2) emissions, the primary greenhouse gas, is essential. Called the "Hestia Project", this research effort is the first to use bottom-up methods to quantify all fossil fuel CO(2) emissions down to the scale of individual buildings, road segments, and industrial/electricity production facilities on an hourly basis for an entire urban landscape. Here, we describe the methods used to quantify the on-site fossil fuel CO(2) emissions across the city of Indianapolis, IN. This effort combines a series of data sets and simulation tools such as a building energy simulation model, traffic data, power production reporting, and local air pollution reporting. The system is general enough to be applied to any large U.S. city and holds tremendous potential as a key component of a carbon-monitoring system in addition to enabling efficient greenhouse gas mitigation and planning. We compare the natural gas component of our fossil fuel CO(2) emissions estimate to consumption data provided by the local gas utility. At the zip code level, we achieve a bias-adjusted Pearson r correlation value of 0.92 (p0.001).

[1] We developed a new inversion method to calculate an emission inventory for an anthropogenic pollutant without a prior emission estimate at mesoscale. This method employs slopes between mixing ratio enhancements of a given pollutant (CO2, for instance) with other co-emitted tracers in conjunction with the emission inventories of those tracers (CO, NOy, and SO2 are used in this example). The current application of this method employed in situ measurements onboard the NOAA WP-3 research aircraft during the 2006 Texas Air Quality Study (TexAQS 2006). We used 3 different transport models to estimate the uncertainties introduced by the transport models in the inversion. We demonstrated the validity of the new inversion method by calculating a 4 × 4 km2 emission inventory of anthropogenic CO2 in the Houston area in Texas, and comparing it to the 10 × 10 km2 Vulcan emission inventory for the same region. The calculated anthropogenic CO2 inventory for the Houston Ship Channel, home to numerous major industrial and port emission sources, showed excellent agreement with Vulcan. The daytime CO2 average flux from the Ship Channel is the largest urban CO2 flux reported in the literature. Compared to Vulcan, the daytime urban area CO2 emissions were higher by 37% ± 6%. Those differences can be explained by uncertainties in emission factors in Vulcan and by increased emissions from point sources and on-road emitters between 2002, the reference year in Vulcan, and 2006, the year that the TexAQS observations were made.

[1]The relationship between the El Nino/Southern Oscillation (ENSO), volcanic aerosol, and the carbon cycle has been characterized through analyses of atmospheric CO 2 , biogeochemical modeling and recently through inverse estimation. However, the studies to date contain weaknesses that make quantitative assessment of the relationship unreliable. Here we present a systematic quantification of the relationship between ENSO, volcanic aerosols and regional net carbon exchange using results from the TransCom Atmospheric CO 2 Inversion Intercomparison and a simple 2-step regression method. A modified ENSO index (ENSOt) is created by estimating the component of ENSO variability that is linearly uncorrelated to aerosol optical depth, and the relationships are estimated by performing correlation analysis with the TransCom 3 tropical terrestrial carbon flux estimates. Flux anomalies from the tropical land regions (Tropical America, Northern Africa, Tropical Asia) show statistically significant correlations with anomalies of ENSOt, with carbon exchange lagging the ENSOtby two to six months. Further analysis by season and warm phase/cold phase shows the ENSOtwarm phase explaining >70% of the variability in tropical net carbon exchange. Tropical Asia shows the largest response with positive carbon flux anomalies following two to three months behind the peak of the ENSOtwarm phase. Total tropical land carbon flux anomalies of +0.59 GtC/year result from a typical (one standard deviation) warm ENSOtevent and are consistent with estimates of carbon loss via tropical fire. Citation:Gurney, K. R., K. Castillo, B. Li, and X. Zhang (2012), A positive carbon feedback to ENSO and volcanic aerosols in the tropical terrestrial biosphere,Global Biogeochem. Cycles,26, GB1029, doi:10.1029/2011GB004129.

Attributing observed CO2 variations to human or natural cause is critical to deducing and tracking emissions from observations. We have used in situ CO2, CO, and planetary boundary layer height (PBLH) measurements recorded during the CalNex-LA (CARB et al., 2008) ground campaign of 15 May–15 June 2010, in Pasadena, CA, to deduce the diurnally varying anthropogenic component of observed CO2 in the megacity of Los Angeles (LA). This affordable and simple technique, validated by carbon isotope observations and WRF-STILT (Weather Research and Forecasting model – Stochastic Time-Inverted Lagrangian Transport model) predictions, is shown to robustly attribute observed CO2 variation to anthropogenic or biogenic origin over the entire diurnal cycle. During CalNex-LA, local fossil fuel combustion contributed up to ~50% of the observed CO2 enhancement overnight, and ~100% of the enhancement near midday. This suggests that sufficiently accurate total column CO2 observations recorded near midday, such as those from the GOSAT or OCO-2 satellites, can potentially be used to track anthropogenic emissions from the LA megacity.

Second letter to editor in response to author response published in J. Air Waste Manage. Assoc. 64: 1218–1220

To improve fossil fuel CO2 emissions estimates, high spatial and temporal resolution inventories are replacing coarse resolution, annual-mean estimates distributed by population density. Because altering the emissions changes a key boundary condition to inverse-estimated CO2 fluxes, it is essential to analyse the atmospheric impacts of redistributing anthropogenic emissions. Using a coupled ecosystem–atmosphere model, we compare 2004 atmospheric CO2 concentrations resulting from coarse and high-resolution inventories. Using fossil fuel CO2 emissions inventories with coarse spatial and temporal resolution creates spatially coherent biases in the atmospheric CO2 concentrations. The largest changes occur from using seasonally varying emissions: in heavily populated areas along the west coast and the eastern United States, the amplitude of the near-surface CO2 concentration seasonal cycle changed by >10 ppm, with higher concentrations in summer and lower concentrations in fall. Due to changes in the spatial distribution, spatially coherent annual mean concentration differences >6 ppm occur; and including the diurnal cycle causes changes >3 ppm. To avoid significant errors in CO2 source and sink estimates from atmospheric inversions, it is essential to include seasonality in fossil fuel emissions, as well as to utilize higher-resolution, process-based spatial distributions.DOI: 10.1111/j.1600-0889.2010.00480.x

TransCom 3 is an intercomparison project for CO2 source inversions. Annual mean CO2 concentration data are used to estimate CO2sources using 16 different atmospheric transport models. Here we test the sensitivity of the inversion to the concentration data. We examine data network choice, time period of data, baseline data selection and the choice of data uncertainty used. We find that in most cases regional source estimates lie within the source uncertainty range of the control inversion. This indicates that the estimated sources are relatively insensitive to the changes in data that were tested. In the data network tests, only the Australian region source estimates varied over a much larger range than that given by the control case uncertainty estimate. For the other regions, the sensitivity to data network was within or close to the uncertainty range. Most of the sensitivity was found to be associated with a small number of sites (e.g. Darwin, Easter Island). These sites are often identified by the inability of the inversion to fit the data at these locations. The model-mean inversion values are mostly insensitive to the time period of data used, with the exception of temperate North America and the tropical Indian ocean. Data selection has a small impact on source estimates for the mean across models, but individual model sensitivity can be large. The magnitude of data uncertainties controls the relative magnitude of the estimated source uncertainty and the spread in model source estimates. Smaller data uncertainties lead to larger differences in source estimates between models. Overall, the data sensitivity tests performed here support the robustness of the control inversion source estimates presented in Gurney et al. (2003. Tellus55B, this issue). The test results also provide guidance in setting up and interpreting other inversions.DOI: 10.1034/j.1600-0889.2003.00053.x

The trends of terrestrial carbon exchange and their mechanistic drivers are key components in understanding how carbon reservoirs will respond to climate change. Here we show trends in seasonal non-fossil land–atmosphere carbon exchange from 1980 to 2008 using atmospheric CO 2 inversion results. Four indices were analysed: growing-season net flux (GSNF), dormant-season net flux (DSNF), amplitude and annual net carbon flux (NCF). We find that the global land carbon sink is intensifying at −0.057 ± 0.01 PgC yr -2 , resulting in −1.65 ± 0.29 PgC of additional uptake over the period examined. This increased total land uptake is driven by a decline in the DSNF (−0.04 ± 0.01 PgC yr -2 ) and intensification of the GSNF (−0.02 ± 0.008 PgC yr -2 ). Regional analysis shows the dominant role of the southern half of the African continent; intensification of the GSNF (−0.02 ± 0.005 PgC yr -2 ) and a decline in the DSNF (−0.013 ± 0.004 PgC yr -2 ) imply that Africa has shifted from a net carbon source in the 1980s to near-neutral emissions. By contrast, a weakening of the GSNF is found in temperate North America (0.015 ± 0.007 PgC yr -2 ) and tropical America (0.01 ± 0.005 PgC yr -2 ). DOI: 10.1111/j.1600-0889.2011.00534.x

Studies indicate that, historically, terrestrial ecosystems of the northern high latitude region may have been responsible for up to 60% of the global net land-based sink for atmospheric CO2. However, these regions have recently experienced remarkable modification of the major driving forces of the carbon cycle, including surface air temperature warming that is significantly greater than the global average and associated increases in the frequency and severity of disturbances. Whether arctic tundra and boreal forest ecosystems will continue to sequester atmospheric CO2 in the face of these dramatic changes is unknown. Here we show the results of model simulations that estimate a 41 Tg C yr-1 sink in the boreal land regions from 1997 to 2006, which represents a 73% reduction in the strength of the sink estimated for previous decades in the late 20th Century. Our results suggest that CO2 uptake by the region in previous decades may not be as strong as previously estimated. The recent decline in sink strength is the combined result of 1) weakening sinks due to warming-induced increases in soil organic matter decomposition and 2) strengthening sources from pyrogenic CO2 emissions as a result of the substantial area of boreal forest burned in wildfiresmore » across the region in recent years. Such changes create positive feedbacks to the climate system that accelerate global warming, putting further pressure on emission reductions to achieve atmospheric stabilization targets.« less

[1] Quantification of the spatial distribution of sector‐specific fossil fuel CO2 emissions provides strategic information to public and private decision makers on climate change mitigation options and can provide critical constraints to carbon budget studies being performed at the national to urban scales. This study analyzes the spatial distribution and spatial drivers of total and sectoral fossil fuel CO2 emissions at the state and county levels in the United States. The spatial patterns of absolute versus per capita fossil fuel CO2 emissions differ substantially and these differences are sector‐specific. Area‐based sources such as those in the residential and commercial sectors are driven by a combination of population and surface temperature with per capita emissions largest in the northern latitudes and continental interior. Emission sources associated with large individual manufacturing or electricity producing facilities are heterogeneously distributed in both absolute and per capita metrics. The relationship between surface temperature and sectoral emissions suggests that the increased electricity consumption due to space cooling requirements under a warmer climate may outweigh the savings generated by lessened space heating. Spatial cluster analysis of fossil fuel CO2 emissions confirms that counties with high (low) CO2 emissions tend to be clustered close to other counties with high (low) CO2 emissions and some of the spatial clustering extends to multistate spatial domains. This is particularly true for the residential and transportation sectors, suggesting that emissions mitigation policy might best be approached from the regional or multistate perspective. Our findings underscore the potential for geographically focused, sector‐specific emissions mitigation strategies and the importance of accurate spatial distribution of emitting sources when combined with atmospheric monitoring via aircraft, satellite and in situ measurements. Citation: Zhou, Y., and K. R. Gurney (2011), Spatial relationships of sector‐specific fossil fuel CO2 emissions in the United States, Global Biogeochem. Cycles, 25, GB3002, doi:10.1029/2010GB003822.

International audience; Forestry – including afforestation (the planting of trees on land where they have not recently existed), reforestation, avoided deforestation, and forest management – can lead to increased sequestration of atmospheric carbon dioxide and has therefore been proposed as a strategy to mitigate climate change. However, forestry also influences land-surface properties, including albedo (the fraction of incident sunlight reflected back to space), surface roughness, and evapotranspiration, all of which affect the amount and forms of energy transfer to the atmosphere. In some circumstances, these biophysical feedbacks can result in local climate warming, thereby counteracting the effects of carbon sequestration on global mean temperature and reducing or eliminating the net value of climate-change mitigation projects. Here, we review published and emerging research that suggests ways in which forestry projects can counteract the consequences associated with biophysical interactions, and highlight knowledge gaps in managing forests for climate protection. We also outline several ways in which biophysical effects can be incorporated into frameworks that use the maintenance of forests as a climate protection strategy.

High-resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high-resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long-term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long-term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter-term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set.

There has never been a greater need for delivering timely and policy-relevant information on the magnitude and evolution of the human-disturbed carbon cycle. In this paper, we present the main thematic areas of an ongoing global research agenda and prioritize future needs based on relevance for the evolution of the carbon-climate-human system. These include firstly, the delivery of routine updates of global and regional carbon budgets, including its attribution of variability and trends to underlying drivers; secondly, the assessment of the magnitude of the carbon-climate feedback; and thirdly, the exploration of pathways to climate stabilization and their uncertainties. Underpinning much of this research is the optimal deployment of a global carbon monitoring system that includes biophysical and socio-economic components. © 2010 Elsevier B.V.

International audience; Efforts to control climate change require the stabilization of atmospheric CO2 concentrations. This can only be achieved through a drastic reduction of global CO2 emissions. Yet fossil fuel emissions increased by 29% between 2000 and 2008, in conjunction with increased contributions from emerging economies, from the production and international trade of goods and services, and from the use of coal as a fuel source. In contrast, emissions from land-use changes were nearly constant. Between 1959 and 2008, 43% of each year's CO2 emissions remained in the atmosphere on average; the rest was absorbed by carbon sinks on land and in the oceans. In the past 50 years, the fraction of CO2 emissions that remains in the atmosphere each year has likely increased, from about 40% to 45%, and models suggest that this trend was caused by a decrease in the uptake of CO2 by the carbon sinks in response to climate change and variability. Changes in the CO2 sinks are highly uncertain, but they could have a significant influence on future atmospheric CO2 levels. It is therefore crucial to reduce the uncertainties.

The quantification of greenhouse gas emissions requires high precision measurements made with high spatial resolution. Here we describe measurements of carbon dioxide (CO2) and methane (CH4) conducted using Purdue University's Airborne Laboratory for Atmospheric Research (ALAR), aimed at the quantification of the "footprints" for these greenhouse gases for Indianapolis, IN. A cavity ring-down spectrometer measured atmospheric concentrations, and flask samples were obtained at various points for comparison. Coupled with pressure, temperature, and model-derived horizontal winds, these measurements allow for flux estimation. Long horizontal transects were flown perpendicular to the wind downwind of the city. Emissions were calculated using the wind speed and the difference between the concentration in the plume and the background concentration. A kriging method is applied to interpolate the measured values to a vertical plane traced out by the flight pattern within the mixed layer. Results show the urban plume is clearly distinguishable in the downwind concentrations for most flights. Additionally, there is large variability in the measured day-to-day emissions fluxes as well as in the relative CH4 and CO2 fluxes. Uncertainties in the method are discussed, and its potential utilityin determining sector-based emission factors is shown.

[1] We use an ensemble-based data assimilation method, known as the maximum likelihood ensemble filter (MLEF), which has been coupled with a global atmospheric transport model to estimate slowly varying biases of carbon surface fluxes. Carbon fluxes for this test consist of hourly gross primary production and ecosystem, respiration over land, and air-sea gas exchange. Persistent multiplicative biases intended to represent incorrectly simulated biogeochemical or land-management processes such as stand age, soil fertility, or coarse woody debris were estimated for 1 year at 10° longitude by 6° latitude spatial resolution and with an 8-week time window. We tested the model using a pseudodata experiment with an existing observation network that includes flasks, aircraft profiles, and continuous measurements. Because of the underconstrained nature of the problem, strong covariance smoothing was applied in the first data assimilation cycle, and localization schemes have been introduced. Error covariance was propagated in subsequent cycles. The coupled model satisfactorily recovered the land biases in densely observed areas. Ocean biases, however, were poorly constrained by the atmospheric observations. Unlike in batch mode inversions, the MLEF has a capability of assimilating large observation vectors and hence is suitable for assimilating hourly continuous observations and satellite observations in the future. Uncertainty was reduced further in our pseudodata experiment than by previous batch methods because of the ability to assimilate a large observation vector. Propagation of spatial covariance and dynamic localization avoid the need for prescribed spatial patterns of error covariance centered at observation sites as in previous grid-scale methods.

[1] Interannually varying net carbon exchange fluxes from the TransCom 3 Level 2 Atmospheric Inversion Intercomparison Experiment are presented for the 1980 to 2005 time period. The fluxes represent the model mean, net carbon exchange for 11 land and 11 ocean regions after subtraction of fossil fuel CO2 emissions. Both aggregated regional totals and the individual regional estimates are accompanied by a model uncertainty and model spread. We find that interannual variability is larger on the land than the ocean, with total land exchange correlated to the timing of both El Nino/Southern Oscillation (ENSO) as well as the eruption of Mt. Pinatubo. The post-Pinatubo negative flux anomaly is evident across much of the tropical and northern extratropical land regions. In the oceans, the tropics tend to exhibit the greatest level of interannual variability, while on land, the interannual variability is slightly greater in the tropics and northern extratropics. The interannual variation in carbon flux estimates aggregated by land and ocean across latitudinal bands remains consistent across eight different CO2 observing networks. The interannual variation in carbon flux estimates for individual flux regions remains mostly consistent across the individual observing networks. At all scales, there is considerable consistency in the interannual variations among the 13 participating model groups. Finally, consistent with other studies using different techniques, we find a considerable positive net carbon flux anomaly in the tropical land during the period of the large ENSO in 1997/1998 which is evident in the Tropical Asia, Temperate Asia, Northern African, and Southern Africa land regions. Negative anomalies are estimated for the East Pacific Ocean and South Pacific Ocean regions. Earlier ENSO events of the 1980s are most evident in southern land positive flux anomalies.

We present a new methodological approach to incorporating deforestation within the international climate change negotiating regime. The approach, called "Preservation Pathway" combines the desire for forest preservation with the need to reduce emissions associated with forest loss by focusing on the relative rate of change of forest cover as the criteria by which countries gain access to trading preserved forest carbon stocks. This approach avoids the technically challenging task of quantifying historical or future deforestation emission baselines. Rather, it places emphasis on improving quantification of contemporary stocks and the relative decline in deforestation rates necessary to preserve those stocks. This approach places emphasis on the complete emissions trajectory necessary to attain an agreed-upon preserved forest and as such, meets both forest conservation and climate goals simultaneously.

Current uncertainty in quantifying the global carbon budget remains a major contributing source of uncertainty in reliably projecting future climate change. Furthermore, quantifying the global carbon budget and characterising uncertainties have emerged as critical to a successful implementation of the United Nations Framework Convention on Climate Change and its Kyoto Protocol. Beyond fundamental quantification, attribution of the processes responsible for the so-called ‘residual terrestrial uptake’ is important to the carbon cycle communities' ability to simulate the future response of the terrestrial biosphere to climate change and intentional sequestration activities. The objective of this chapter is to describe the approaches to model-data fusion enabling continued advances in quantifying carbon cycling and the terrestrial mechanisms at work. The major impediments to advances in this field include accounting for climate variability and uncertainties in model outcomes. One proposed solution to overcome these obstacles is the use of data from the FLUXNET network to characterise the relative strength of climate impact on plant productivity and respiration. Other solutions involve the use of atmospheric CO2 concentration measurements for model validation and the use of remote sensing data.