Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.

The nationwide extent of surface ozone pollution in China and its comparison to the global ozone distribution have not been recognized because of the scarcity of Chinese monitoring sites before 2012. Here we address this issue by using the latest 5 year (2013–2017) surface ozone measurements from the Chinese monitoring network, combined with the recent Tropospheric Ozone Assessment Report (TOAR) database for other industrialized regions such as Japan, South Korea, Europe, and the United States (JKEU). We use various human health and vegetation exposure metrics. We find that although the median ozone values are comparable between Chinese and JKEU cities, the magnitude and frequency of high-ozone events are much larger in China. The national warm-season (April–September) fourth highest daily maximum 8 h average (4MDA8) ozone level (86.0 ppb) and the number of days with MDA8 values of >70 ppb (NDGT70, 29.7 days) in China are 6.3–30% (range of regional mean differences) and 93–575% higher, respectively, than the JKEU regional averages. Health exposure metrics such as warm-season mean MDA8 and annual SOMO35 (sum of ozone means over 35 ppb) are 6.3–16 and 25–95% higher in China, respectively. We also find an increase in the surface ozone level over China in 2016 and 2017 relative to 2013 and 2014. Our results show that on the regional scale the exposure of humans and vegetation to ozone is greater in China than in other developed regions of the world with comprehensive ozone monitoring.

Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). Assessing the relative importance of CH4 in comparison to CO2 is complicated by its shorter atmospheric lifetime, stronger warming potential, and atmospheric growth rate variations over the past decade, the causes of which are still debated. Two major difficulties in reducing uncertainties arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (top-down approach) to be 572 Tg CH4 yr−1 (range 538–593, corresponding to the minimum and maximum estimates of the ensemble), of which 357 Tg CH4 yr−1 or ~ 60 % are attributed to anthropogenic sources (range 50–65 %). This total emission is 27 Tg CH4 yr−1 larger than the value estimated for the period 2000–2009 and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for the period 2003–2012 (Saunois et al. 2016). Since 2012, global CH4 emissions have been tracking the carbon intensive scenarios developed by the Intergovernmental Panel on Climate Change (Gidden et al., 2019). Bottom-up methods suggest larger global emissions (737 Tg CH4 yr−1, range 583–880) than top-down inversion methods, mostly because of larger estimated natural emissions from sources such as natural wetlands, other inland water systems, and geological sources. However the strength of the atmospheric constraints on the top-down budget, suggest that these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric-based emissions indicates a predominance of tropical emissions (~ 65 % of the global budget,

Abstract. Current estimates of agricultural ammonia (NH 3 ) emissions in China differ by more than a factor of 2, hindering our understanding of their environmental consequences. Here we apply both bottom-up statistical and top-down inversion methods to quantify NH 3 emissions from agriculture in China for the year 2008. We first assimilate satellite observations of NH 3 column concentration from the Tropospheric Emission Spectrometer (TES) using the GEOS-Chem adjoint model to optimize Chinese anthropogenic NH 3 emissions at the 1/2 • × 2/3 • horizontal resolution for MarchOctober 2008. Optimized emissions show a strong summer peak, with emissions about 50 % higher in summer than spring and fall, which is underestimated in current bottom-up NH 3 emission estimates. To reconcile the latter with the topdown results, we revisit the processes of agricultural NH 3 emissions and develop an improved bottom-up inventory of Chinese NH 3 emissions from fertilizer application and livestock waste at the 1/2 • × 2/3 • resolution. Our bottom-up emission inventory includes more detailed information on crop-specific fertilizer application practices and better accounts for meteorological modulation of NH 3 emission factors in China. We find that annual anthropogenic NH 3 emissions are 11.7 Tg for 2008, with 5.05 Tg from fertilizer application and 5.31 Tg from livestock waste. The two sources together account for 88 % of total anthropogenic NH 3 emissions in China. Our bottom-up emission estimates also show a distinct seasonality peaking in summer, consistent with topdown results from the satellite-based inversion. Further evaluations using surface network measurements show that the model driven by our bottom-up emissions reproduces the observed spatial and seasonal variations of NH 3 gas concentrations and ammonium (NH + 4 ) wet deposition fluxes over China well, providing additional credibility to the improvements we have made to our agricultural NH 3 emission inventory.

No abstract

We quantify the source contributions to surface PM2.5 (fine particulate matter) pollution over North China from January 2013 to 2015 using the GEOS-Chem chemical transport model and its adjoint with improved model horizontal resolution (1/4°× 5/16°) and aqueous-phase chemistry for sulfate production. The adjoint method attributes the PM2.5 pollution to emissions from different source sectors and chemical species at the model resolution. Wintertime surface PM2.5 over Beijing is contributed by emissions of organic carbon (27% of the total source contribution), anthropogenic fine dust (27%), and SO 2 (14%), which are mainly from residential and industrial sources, followed by NH 3 (13%) primarily from agricultural activities. About half of the Beijing pollution originates from sources outside of the city municipality. Adjoint analyses for other cities in North China all show significant regional pollution transport, supporting a joint regional control policy for effectively mitigating the PM2.5 air pollution. use the nested-grid GEOS-Chem CTM and its adjoint model with a horizontal resolution of 1/4°× 5/16°to examine the sources of PM2.5 pollution over North China, and we interpret the source attribution results based on emission sectors, chemical species, and local versus regional transport influences.

Abstract. Atmospheric carbon monoxide (CO) concentrations have been decreasing since 2000, as observed by both satellite- and ground-based instruments, but global bottom-up emission inventories estimate increasing anthropogenic CO emissions concurrently. In this study, we use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric CO variations to its sources and sinks in order to achieve a full closure of the global CO budget during 2000–2017. Our observation constraints include satellite retrievals of the total column mole fraction of CO, formaldehyde (HCHO), and methane (CH4) that are all major components of the atmospheric CO cycle. Three inversions (i.e., 2000–2017, 2005–2017, and 2010–2017) are performed to use the observation data to the maximum extent possible as they become available and assess the consistency of inversion results to the assimilation of more trace gas species. We identify a declining trend in the global CO budget since 2000 (three inversions are broadly consistent during overlapping periods), driven by reduced anthropogenic emissions in the US and Europe (both likely from the transport sector), and in China (likely from industry and residential sectors), as well as by reduced biomass burning emissions globally, especially in equatorial Africa (associated with reduced burned areas). We show that the trends and drivers of the inversion-based CO budget are not affected by the inter-annual variation assumed for prior CO fluxes. All three inversions contradict the global bottom-up inventories in the world's top two emitters: for the sign of anthropogenic emission trends in China (e.g., here -0.8±0.5 % yr−1 since 2000, while the prior gives 1.3±0.4 % yr−1) and for the rate of anthropogenic emission increase in South Asia (e.g., here 1.0±0.6 % yr−1 since 2000, smaller than 3.5±0.4 % yr−1 in the prior inventory). The posterior model CO concentrations and trends agree well with independent ground-based observations and correct the prior model bias. The comparison of the three inversions with different observation constraints further suggests that the most complete constrained inversion that assimilates CO, HCHO, and CH4 has a good representation of the global CO budget, and therefore matches best with independent observations, while the inversion only assimilating CO tends to underestimate both the decrease in anthropogenic CO emissions and the increase in the CO chemical production. The global CO budget data from all three inversions in this study can be accessed from https://doi.org/10.6084/m9.figshare.c.4454453.v1 (Zheng et al., 2019).

The limited availability of ammonia (NH) measurements is currently a barrier to understanding the vital role of NH in secondary aerosol formation during haze pollution events and prevents a full assessment of the atmospheric deposition of reactive nitrogen. The observational gaps motivated us to design this study to investigate the spatial distributions and seasonal variations in atmospheric NH on a national scale in China. On the basis of a 1-year observational campaign at 53 sites with uniform protocols, we confirm that abundant concentrations of NH [1 to 23.9 μg m] were identified in typical agricultural regions, especially over the North China Plain (NCP). The spatial pattern of the NH surface concentration was generally similar to those of the satellite column concentrations as well as a bottom-up agriculture NH emission inventory. However, the observed NH concentrations at urban and desert sites were comparable with those from agricultural sites and 2-3 times those of mountainous/forest/grassland/waterbody sites. We also found that NH deposition fluxes at urban sites account for only half of the emissions in the NCP, suggesting the transport of urban NH emissions to downwind areas. This finding provides policy makers with insights into the potential mitigation of nonagricultural NH sources in developed regions.