A Near-Real-Time Method for Estimating Volcanic Ash Emissions Using Satellite Retrievals

We present a Bayesian inversion method for estimating volcanic ash emissions using satellite retrievals of ash column load and an atmospheric dispersion model. An a priori description of the emissions is used based on observations of the rise height of the volcanic plume and a stochastic model of the possible emissions. Satellite data are processed to give column loads where ash is detected and to give information on where we have high confidence that there is negligible ash. An atmospheric dispersion model is used to relate emissions and column loads. Gaussian distributions are assumed for the a priori emissions and for the errors in the satellite retrievals. The optimal emissions estimate is obtained by finding the peak of the a posteriori probability density under the constraint that the emissions are non-negative. We apply this inversion method within a framework designed for use during an eruption with the emission estimates (for any given emission time) being revised over time as more information becomes available. We demonstrate the approach for the 2010 Eyjafjallajökull and 2011 Grímsvötn eruptions. We apply the approach in two ways, using only the ash retrievals and using both the ash and clear sky retrievals. For Eyjafjallajökull we have compared with an independent dataset not used in the inversion and have found that the inversion-derived emissions lead to improved predictions.

The impact of spatially varying wetland source signatures on the atmospheric variability of δD-CH4

We present the first spatially resolved distribution of the [Formula: see text] signature of wetland methane emissions and assess its impact on atmospheric [Formula: see text]. The [Formula: see text] signature map is derived by relating [Formula: see text] of precipitation to measured [Formula: see text] of methane wetland emissions at a variety of wetland types and locations. This results in strong latitudinal variation in the wetland [Formula: see text] source signature. When [Formula: see text] is simulated in a global atmospheric model, little difference is found in global mean, inter-hemispheric difference and seasonal cycle if the spatially varying [Formula: see text] source signature distribution is used instead of a globally uniform value. This is because atmospheric [Formula: see text] is largely controlled by OH fractionation. However, we show that despite these small differences, using atmospheric records of [Formula: see text] to infer changes in the wetland emissions distribution requires the use of the more accurate spatially varying [Formula: see text] source signature. We find that models will only be sensitive to changes in emissions distribution if spatial information can be exploited through the spatially resolved source signatures. In addition, we also find that on a regional scale, at sites measuring excursions of [Formula: see text] from background levels, substantial differences are simulated in atmospheric [Formula: see text] if using spatially varying or uniform source signatures. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

Emerging reporting and verification needs under the Paris Agreement: How can the research community effectively contribute?

Greenhouse gas (GHG) emission inventories represent the link between national and international political actions on climate change, and climate and environmental sciences. Inventory agencies need to include, in national GHG inventories, emission and removal estimates based on scientific data following specific reporting guidance under the United Nation Framework Convention on Climate Change (UNFCCC) and the Paris Agreement, using the methodologies defined in the Intergovernmental Panel on Climate Change (IPCC) Guidelines. Often however, research communities and inventory agencies have approached the problem of climate change from different angles and by using terminologies, metrics, rules and approaches that do not always match. This is particularly true dealing with "Land Use, Land-Use Change and Forestry" (LULUCF), the most challenging among the inventory sectors to deal with, mainly because of high level of complexity of its carbon dynamics and the difficulties in disaggregating the fluxes between those caused by natural and anthropogenic processes. In this paper, we facilitate the understanding by research communities of the current (UNFCCC) and future (under the Paris Agreement) reporting requirements, and we identify the main issues and topics that should be considered when targeting improvement of the GHG inventory. In relation to these topics, we describe where and how the research community can contribute to producing useful inputs, data, methods and solutions for inventory agencies and policy makers, on the basis of available literature. However, a greater effort by both communities is desirable for closer cooperation and collaboration, for data sharing and the understanding of respective and common aims.

Eight-Year Estimates of Methane Emissions from Oil and Gas Operations in Western Canada Are Nearly Twice Those Reported in Inventories

The provinces of Alberta and Saskatchewan account for 70% of Canada's methane emissions from the oil and gas sector. In 2018, the Government of Canada introduced methane regulations to reduce emissions from the sector by 40-45% from the 2012 levels by 2025. Complementary to inventory accounting methods, the effectiveness of regulatory practices to reduce emissions can be assessed using atmospheric measurements and inverse models. Total anthropogenic (oil and gas, agriculture, and waste) emission rates of methane from 2010 to 2017 in Alberta and Saskatchewan were derived using hourly atmospheric methane measurements over a six-month winter period from October to March. Scaling up the winter estimate to annual indicated an anthropogenic emission rate of 3.7 ± 0.7 MtCH₄/year, about 60% greater than that reported in Canada's National Inventory Report (2.3 MtCH₄). This discrepancy is tied primarily to the oil and gas sector emissions as the reported emissions from livestock operations (0.6 MtCH₄) are well substantiated in both top-down and bottom-up estimates and waste management (0.1 MtCH₄) emissions are small. The resulting estimate of 3.0 MtCH₄ from the oil and gas sector is nearly twice that reported in Canada's National Inventory (1.6 MtCH₄).

The Impact of Ensemble Meteorology on Inverse Modeling Estimates of Volcano Emissions and Ash Dispersion Forecasts: Grímsvötn 2011

Volcanic ash can interact with the earth system on many temporal and spatial scales and is a significant hazard to aircraft. In the event of a volcanic eruption, fast and robust decisions need to be made by aviation authorities about which routes are safe to operate. Such decisions take into account forecasts of ash location issued by Volcanic Ash Advisory Centers (VAACs) which are informed by simulations from Volcanic Ash Transport and Dispersion (VATD) models. The estimation of the time-evolving vertical distribution of ash emissions for use in VATD simulations in real time is difficult which can lead to large uncertainty in these forecasts. This study presents a method for constraining the ash emission estimates by combining an inversion modeling technique with an ensemble of meteorological forecasts, resulting in an ensemble of ash emission estimates. These estimates of ash emissions can be used to produce a robust ash forecast consistent with observations. This new ensemble approach is applied to the 2011 eruption of the Icelandic volcano Grímsvötn. The resulting emission profiles each have a similar temporal evolution but there are differences in the magnitude of ash emitted at different heights. For this eruption, the impact of precipitation uncertainty (and the associated wet deposition of ash) on the estimate of the total amount of ash emitted is larger than the impact of the uncertainty in the wind fields. Despite the differences that are dominated by wet deposition uncertainty, the ensemble inversion provides confidence that the reduction of the unconstrained emissions (a priori), particularly above 4 km, is robust across all members. In this case, the use of posterior emission profiles greatly reduces the magnitude and extent of the forecast ash cloud. The ensemble of posterior emission profiles gives a range of ash column loadings much closer in agreement with a set of independent satellite retrievals in comparison to the a priori emissions. Furthermore, airspace containing volcanic ash concentrations deemed to be associated with the highest risk (likelihood of exceeding a high concentration threshold) to aviation are reduced by over 85%. Such improvements could have large implications in emergency response situations. Future research will focus on quantifying the impact of uncertainty in precipitation forecasts on wet deposition in other eruptions and developing an inversion system that makes use of the state-of-the-art meteorological ensembles which has the potential to be used in an operational setting.

Emissions and Marine Boundary Layer Concentrations of Unregulated Chlorocarbons Measured at Cape Point, South Africa

Unregulated chlorocarbons, here defined as dichloromethane (CH₂Cl₂), perchloroethene (C₂Cl₄), chloroform (CHCl₃), and methyl chloride (CH₃Cl), are gases not regulated by the Montreal Protocol. While CH₃Cl is the largest contributor of atmospheric chlorine, recent studies have shown that growth in emissions of the less abundant chlorocarbons could pose a significant threat to the recovery of the ozone layer. Despite this, there remain many regions for which no atmospheric monitoring exists, leaving gaps in our understanding of global emissions. Here, we report on a new time series of chlorocarbon measurements from Cape Point, South Africa for 2017, which represent the first published high-frequency measurements of these gases from Africa. For CH₂Cl₂ and C₂Cl₄, the majority of mole fraction enhancements were observed from the north, consistent with anthropogenically modified air from Cape Town, while for CHCl₃ and CH₃Cl, we found evidence for both oceanic and terrestrial sources. Using an inverse method, we estimated emissions for south-western South Africa (SWSA). For each chlorocarbon, SWSA accounted for less than 1% of global emissions. For CH₂Cl₂ and C₂Cl₄, we extrapolated using population statistics and found South African emissions of 8.9 (7.4-10.4) Gg yr^-1 and 0.80 (0.64-1.04) Gg yr^-1, respectively.

Source estimation of an unexpected release of Ruthenium-106 in 2017 using an inverse modelling approach

For the first time since the Chernobyl accident, detectable concentrations of ruthenium-106 were measured across Europe in September and October 2017. The source of this radioactive cloud remains unconfirmed. In this paper we present a forensic inverse modelling study to simultaneously estimate the source location, timing and magnitude of the unexpected ruthenium-106 release using 473 measurements of atmospheric concentration. To do this, we introduce a novel method, which estimates the uncertainty in the often unknown transport error using a Markov chain Monte Carlo approach. We corroborate the conclusions of other studies which suggest the source location is in the Southern Ural region of Russia, where the Mayak nuclear complex is located. Assuming that the Mayak nuclear complex is the most plausible release location, the method estimates that 441±13 TBq was released 12:00-18:00 UTC 24 September 2017, assuming a six hour release window.

Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries.

Atmospheric HCFC-22, HFC-125, and HFC-152a at Cape Point, South Africa

One hydrochlorofluorocarbon and two hydrofluorocarbons (HCFC-22, HFC-125, and HFC-152a) were measured in air samples at the Cape Point observatory (CPT), South Africa, during 2017. These data represent the first such atmospheric measurements of these compounds from southwestern South Africa (SWSA). Baseline atmospheric growth rates were estimated to be 8.36, 4.10, and 0.71 ppt year^-1 for HCFC-22, HFC-125, and HFC-152a, respectively. The CPT measurements were combined with an inverse model to investigate emissions from SWSA. For all three halocarbons, Cape Town was found to be the dominant source within SWSA. These estimates were extrapolated, based on population statistics, to estimate emissions for the whole of South Africa. We estimate South Africa's 2017 emissions to be 3.0 (1.6-4.4), 0.8 (0.5-1.2), and 1.1 (0.6-1.6) Gg year^-1 for HCFC-22, HFC-125, and HFC-152a, respectively. For all three halocarbons, South Africa's contribution to global emissions is small (<2.5%), but future monitoring is needed to ensure South Africa's compliance with regulation set out by the Montreal Protocol and its Amendments.

Increase in CFC-11 emissions from eastern China based on atmospheric observations

The recovery of the stratospheric ozone layer relies on the continued decline in the atmospheric concentrations of ozone-depleting gases such as chlorofluorocarbons¹. The atmospheric concentration of trichlorofluoromethane (CFC-11), the second-most abundant chlorofluorocarbon, has declined substantially since the mid-1990s². A recently reported slowdown in the decline of the atmospheric concentration of CFC-11 after 2012, however, suggests that global emissions have increased^3,4. A concurrent increase in CFC-11 emissions from eastern Asia contributes to the global emission increase, but the location and magnitude of this regional source are unknown³. Here, using high-frequency atmospheric observations from Gosan, South Korea, and Hateruma, Japan, together with global monitoring data and atmospheric chemical transport model simulations, we investigate regional CFC-11 emissions from eastern Asia. We show that emissions from eastern mainland China are 7.0 ± 3.0 (±1 standard deviation) gigagrams per year higher in 2014-2017 than in 2008-2012, and that the increase in emissions arises primarily around the northeastern provinces of Shandong and Hebei. This increase accounts for a substantial fraction (at least 40 to 60 per cent) of the global rise in CFC-11 emissions. We find no evidence for a significant increase in CFC-11 emissions from any other eastern Asian countries or other regions of the world where there are available data for the detection of regional emissions. The attribution of any remaining fraction of the global CFC-11 emission rise to other regions is limited by the sparsity of long-term measurements of sufficient frequency near potentially emissive regions. Several considerations suggest that the increase in CFC-11 emissions from eastern mainland China is likely to be the result of new production and use, which is inconsistent with the Montreal Protocol agreement to phase out global chlorofluorocarbon production by 2010.

Detection of Fossil and Biogenic Methane at Regional Scales Using Atmospheric Radiocarbon

Regional emissions of methane and their attribution to a variety of sources presently have large uncertainties. Measurements of radiocarbon (14C) in methane (CH4) may provide a method for identifying regional CH4 emissions from fossil versus biogenic sources because adding 14C-free fossil carbon reduces the 14C/C ratio (Δ14CH4) in atmospheric CH4 much more than biogenic carbon does. We describe an approach for estimating fossil and biogenic CH4 at regional scales using atmospheric Δ14CH4 observations. As a case study to demonstrate expected Δ14CH4 and Δ14CH4-CH4 relationships, we simulate and compare Δ14CH4 at a network of sites in California using two gridded CH4 emissions estimates (Emissions Database for Global Atmospheric Research, EDGAR, and Gridded Environmental Protection Agency, GEPA) and the CarbonTracker-Lagrange model for 2014, and for 2030 under business-as-usual and mitigation scenarios. The fossil fraction of CH4 (F) is closely linked with the simulated Δ14CH4-CH4 slope and differences of 2-21% in median F are found for EDGAR versus GEPA in 2014, and 7-10% for business-as-usual and mitigation scenarios in 2030. Differences of 10% in F for >200 ppb of added CH4 produce differences of >10‰ in Δ14CH4, which are likely detectable from regular observations. Nuclear power plant 14CH4 emissions generally have small simulated median influences on Δ14CH4 (0-7‰), but under certain atmospheric conditions they can be much stronger (>30‰) suggesting they must be considered in applications of Δ14CH4 in California. This study suggests that atmospheric Δ14CH4 measurements could provide powerful constraints on regional CH4 emissions, complementary to other monitoring techniques.

Continued Emissions of the Ozone-Depleting Substance Carbon Tetrachloride From Eastern Asia

Carbon tetrachloride (CCl₄) is an ozone-depleting substance, accounting for about 10% of the chlorine in the troposphere. Under the terms of the Montreal Protocol, its production for dispersive uses was banned from 2010. In this work we show that, despite the controls on production being introduced, CCl₄ emissions from the eastern part of China did not decline between 2009 and 2016. This finding is in contrast to a recent bottom-up estimate, which predicted a significant decrease in emissions after the introduction of production controls. We find eastern Asian emissions of CCl₄ to be 16 (9-24) Gg/year on average between 2009 and 2016, with the primary source regions being in eastern China. The spatial distribution of emissions that we derive suggests that the source distribution of CCl₄ in China changed during the 8-year study period, indicating a new source or sources of emissions from China's Shandong province after 2012.

Atmospheric observations show accurate reporting and little growth in India's methane emissions

Changes in tropical wetland, ruminant or rice emissions are thought to have played a role in recent variations in atmospheric methane (CH₄) concentrations. India has the world’s largest ruminant population and produces ~ 20% of the world’s rice. Therefore, changes in these sources could have significant implications for global warming. Here, we infer India’s CH₄ emissions for the period 2010–2015 using a combination of satellite, surface and aircraft data. We apply a high-resolution atmospheric transport model to simulate data from these platforms to infer fluxes at sub-national scales and to quantify changes in rice emissions. We find that average emissions over this period are 22.0 (19.6–24.3) Tg yr⁻¹, which is consistent with the emissions reported by India to the United Framework Convention on Climate Change. Annual emissions have not changed significantly (0.2 ± 0.7 Tg yr⁻¹) between 2010 and 2015, suggesting that major CH₄ sources did not change appreciably. These findings are in contrast to another major economy, China, which has shown significant growth in recent years due to increasing fossil fuel emissions. However, the trend in a global emission inventory has been overestimated for China due to incorrect rate of fossil fuel growth. Here, we find growth has been overestimated in India but likely due to ruminant and waste sectors.

India’s methane emissions have been quantified using atmospheric measurements to provide an independent comparison with reported emissions. Here Ganesan et al. find that derived methane emissions are consistent with India’s reports and no significant trend has been observed between 2010–2015.

Measurements of δ13C in CH4 and using particle dispersion modeling to characterize sources of Arctic methane within an air mass

A stratified air mass enriched in methane (CH4) was sampled at ~600 m to ~2000 m altitude, between the north coast of Norway and Svalbard as part of the Methane in the Arctic: Measurements and Modelling campaign on board the UK's BAe-146-301 Atmospheric Research Aircraft. The approach used here, which combines interpretation of multiple tracers with transport modeling, enables better understanding of the emission sources that contribute to the background mixing ratios of CH4 in the Arctic. Importantly, it allows constraints to be placed on the location and isotopic bulk signature of the emission source(s). Measurements of δ13C in CH4 in whole air samples taken while traversing the air mass identified that the source(s) had a strongly depleted bulk δ13C CH4 isotopic signature of -70 (±2.1)‰. Combined Numerical Atmospheric-dispersion Modeling Environment and inventory analysis indicates that the air mass was recently in the planetary boundary layer over northwest Russia and the Barents Sea, with the likely dominant source of methane being from wetlands in that region.

Re-Evaluation of the UK's HFC-134a Emissions Inventory Based on Atmospheric Observations

Independent verification of national greenhouse gas inventories is a vital measure for cross-checking the accuracy of emissions data submitted to the United Nations Framework Convention on Climate Change (UNFCCC). We infer annual UK emissions of HFC-134a from 1995 to 2012 using atmospheric observations and an inverse modeling technique, and compare with the UK's annual UNFCCC submission. By 2010, the inventory is almost twice as large as our estimates, with an "emissions gap" equating to 3.90 (3.20-4.30) Tg CO₂e. We evaluate the RAC (Refrigeration and Air-Conditioning) model, a bottom up model used to quantify UK emissions from refrigeration and air-conditioning sectors. Within mobile air-conditioning (MAC), the largest RAC sector and most significant UK source (59%), we find a number of assumptions that may be considered oversimplistic and conservative; most notably the unit refill rate. Finally, a Bayesian approach is used to estimate probable inventory inputs required for minimization of the emissions discrepancy. Our top-down estimates provide only a weak constraint on inventory model parameters and consequently, we are unable to suggest discrete values. However, a significant revision of the MAC servicing rate, coupled with a reassessment of non-RAC aerosol emissions, are required if the discrepancy between methods is to be reduced.

Reconciling reported and unreported HFC emissions with atmospheric observations

We infer global and regional emissions of five of the most abundant hydrofluorocarbons (HFCs) using atmospheric measurements from the Advanced Global Atmospheric Gases Experiment and the National Institute for Environmental Studies, Japan, networks. We find that the total CO2-equivalent emissions of the five HFCs from countries that are required to provide detailed, annual reports to the United Nations Framework Convention on Climate Change (UNFCCC) increased from 198 (175-221) Tg-CO2-eq ⋅ y(-1) in 2007 to 275 (246-304) Tg-CO2-eq ⋅ y(-1) in 2012. These global warming potential-weighted aggregated emissions agree well with those reported to the UNFCCC throughout this period and indicate that the gap between reported emissions and global HFC emissions derived from atmospheric trends is almost entirely due to emissions from nonreporting countries. However, our measurement-based estimates of individual HFC species suggest that emissions, from reporting countries, of the most abundant HFC, HFC-134a, were only 79% (63-95%) of the UNFCCC inventory total, while other HFC emissions were significantly greater than the reported values. These results suggest that there are inaccuracies in the reporting methods for individual HFCs, which appear to cancel when aggregated together.

Fully automated, high-precision instrumentation for the isotopic analysis of tropospheric N2O using continuous flow isotope ratio mass spectrometry

RATIONALE

Measurements of the isotopic composition of nitrous oxide in the troposphere have the potential to bring new information about the uncertain N2O budget, which mole fraction data alone have not been able to resolve. Characterizing the expected subtle variations in tropospheric N2O isotopic composition demands high-precision and high-frequency measurements. To enable useful observations of N2O isotopic composition in tropospheric air to reduce N2O source and sink uncertainty, it was necessary to develop a high-precision measurement system with fully automated capabilities for autonomous deployment at remote research stations.

METHODS

A fully automated pre-concentration system for high-precision measurements of N2O isotopic composition (δ(15)N(β) , δ(15)N(α), δ(18)O) in tropospheric air has been developed which combines a custom liquid-cryogen-free cryo-trapping system and gas chromatograph interfaced to a continuous flow isotope ratio mass spectrometry (IRMS) system. A quadrupole mass spectrometer was coupled in parallel to the IRMS system during development to evaluate peak interference. Multi-port inlet and fully-automated capabilities allow streamlined analyses between in situ air inlet, air standards, flask air sample, or other gas source in exactly replicated analysis sequences.

RESULTS

The system has the highest precision to date for (15)N site-specific composition results (δ(15) N(α) ±0.11‰, δ(15)N(β) ±0.14‰ (1σ)), attributed mostly to uniformity of analytical cycles and particular attention to fluorocarbon interference noted for (15)N site-specific measurements by IRMS. Air measurements demonstrated the fully automated capacity and performance.

CONCLUSIONS

The system makes substantial headway in measurement precision, possibly defining the limits of IRMS measurement capabilities in low concentration N2O air samples, with fully automated capabilities to enable high-frequency in situ measurements.

Nitrogen trifluoride global emissions estimated from updated atmospheric measurements

Nitrogen trifluoride (NF(3)) has potential to make a growing contribution to the Earth's radiative budget; however, our understanding of its atmospheric burden and emission rates has been limited. Based on a revision of our previous calibration and using an expanded set of atmospheric measurements together with an atmospheric model and inverse method, we estimate that the global emissions of NF(3) in 2011 were 1.18 ± 0.21 Gg⋅y(-1), or ∼20 Tg CO(2)-eq⋅y(-1) (carbon dioxide equivalent emissions based on a 100-y global warming potential of 16,600 for NF(3)). The 2011 global mean tropospheric dry air mole fraction was 0.86 ± 0.04 parts per trillion, resulting from an average emissions growth rate of 0.09 Gg⋅y(-2) over the prior decade. In terms of CO(2) equivalents, current NF(3) emissions represent between 17% and 36% of the emissions of other long-lived fluorinated compounds from electronics manufacture. We also estimate that the emissions benefit of using NF(3) over hexafluoroethane (C(2)F(6)) in electronics manufacture is significant-emissions of between 53 and 220 Tg CO(2)-eq⋅y(-1) were avoided during 2011. Despite these savings, total NF(3) emissions, currently ∼10% of production, are still significantly larger than expected assuming global implementation of ideal industrial practices. As such, there is a continuing need for improvements in NF(3) emissions reduction strategies to keep pace with its increasing use and to slow its rising contribution to anthropogenic climate forcing.

UK emissions of the greenhouse gas nitrous oxide

Signatories of the Kyoto Protocol are obliged to submit annual accounts of their anthropogenic greenhouse gas emissions, which include nitrous oxide (N(2)O). Emissions from the sectors industry (3.8 Gg), energy (14.4 Gg), agriculture (86.8 Gg), wastewater (4.4 Gg), land use, land-use change and forestry (2.1 Gg) can be calculated by multiplying activity data (i.e. amount of fertilizer applied, animal numbers) with simple emission factors (Tier 1 approach), which are generally applied across wide geographical regions. The agricultural sector is the largest anthropogenic source of N(2)O in many countries and responsible for 75 per cent of UK N(2)O emissions. Microbial N(2)O production in nitrogen-fertilized soils (27.6 Gg), nitrogen-enriched waters (24.2 Gg) and manure storage systems (6.4 Gg) dominate agricultural emission budgets. For the agricultural sector, the Tier 1 emission factor approach is too simplistic to reflect local variations in climate, ecosystems and management, and is unable to take into account some of the mitigation strategies applied. This paper reviews deviations of observed emissions from those calculated using the simple emission factor approach for all anthropogenic sectors, briefly discusses the need to adopt specific emission factors that reflect regional variability in climate, soil type and management, and explains how bottom-up emission inventories can be verified by top-down modelling.

The challenge of estimating regional trace gas emissions from atmospheric observations

This paper discusses some of the major issues that surround estimating regional emissions of trace gases from atmospheric observations through inversion modelling. Inversion methods use modelled knowledge of how emissions dilute in the atmosphere as they travel from their source to an observation point, together with the observations, to calculate a grid of emissions. The problem is one of minimizing the mismatch between a modelled and observed time series of concentration. There are many methods of comparing time series, some involving a priori knowledge others without. The location, terrain and height of the observation station can also be very significant in determining how well a model can represent the dilution from emission source to receptor. The inversion solution (emission map) will assign some of the sources incorrectly for a variety of reasons, e.g. local sources, intermittent releases, errors in the modelled transport or observation, and the choice of the spatial and temporal resolution of the emission map. The reasons for uncertainty in the modelled emissions are discussed along with suggestions as to how some of these can be minimized. Using multiple stations to further constrain the inversion should reduce the uncertainty; however, care is needed if the potential improvements are to be realized.