ALBERT

Description: Chemistry plays an indispensable role in investigations of the atmosphere; however, many climate models either ignore or greatly simplify atmospheric chemistry, limiting both their accuracy and their scope. We present the development and evaluation of the online global atmospheric chemical model BCC-GEOS-Chem v1.0, coupling the GEOS-Chem chemical transport model (CTM) as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model (BCC-AGCM). The GEOS-Chem atmospheric chemistry component includes detailed tropospheric HOx–NOx–volatile organic compounds–ozone–bromine–aerosol chemistry and online dry and wet deposition schemes. We then demonstrate the new capabilities of BCC-GEOS-Chem v1.0 relative to the base BCC-AGCM model through a 3-year (2012–2014) simulation with anthropogenic emissions from the Community Emissions Data System (CEDS) used in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The model captures well the spatial distributions and seasonal variations in tropospheric ozone, with seasonal mean biases of 0.4–2.2 ppbv at 700–400 hPa compared to satellite observations and within 10 ppbv at the surface to 500 hPa compared to global ozonesonde observations. The model has larger high-ozone biases over the tropics which we attribute to an overestimate of ozone chemical production. It underestimates ozone in the upper troposphere which is likely due either to the use of a simplified stratospheric ozone scheme or to biases in estimated stratosphere–troposphere exchange dynamics. The model diagnoses the global tropospheric ozone burden, OH concentration, and methane chemical lifetime to be 336 Tg, 1.16×106 molecule cm−3, and 8.3 years, respectively, which is consistent with recent multimodel assessments. The spatiotemporal distributions of NO2, CO, SO2, CH2O, and aerosol optical depth are generally in agreement with satellite observations. The development of BCC-GEOS-Chem v1.0 represents an important step for the development of fully coupled earth system models (ESMs) in China.

Description: We developed the WRF-GC model, an online coupling of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the GEOS-Chem atmospheric chemistry model, for regional atmospheric chemistry and air quality modeling. WRF and GEOS-Chem are both open-source community models. WRF-GC offers regional modellers access to the latest GEOS-Chem chemical module, which is state of the science, well documented, traceable, benchmarked, actively developed by a large international user base, and centrally managed by a dedicated support team. At the same time, WRF-GC enables GEOS-Chem users to perform high-resolution forecasts and hindcasts for any region and time of interest. WRF-GC uses unmodified copies of WRF and GEOS-Chem from their respective sources; the coupling structure allows future versions of either one of the two parent models to be integrated into WRF-GC with relative ease. Within WRF-GC, the physical and chemical state variables are managed in distributed memory and translated between WRF and GEOS-Chem by the WRF-GC coupler at runtime. We used the WRF-GC model to simulate surface PM2.5 concentrations over China during 22 to 27 January 2015 and compared the results to surface observations and the outcomes from a GEOS-Chem Classic nested-China simulation. Both models were able to reproduce the observed spatiotemporal variations of regional PM2.5, but the WRF-GC model (r=0.68, bias =29 %) reproduced the observed daily PM2.5 concentrations over eastern China better than the GEOS-Chem Classic model did (r=0.72, bias =55 %). This was because the WRF-GC simulation, nudged with surface and upper-level meteorological observations, was able to better represent the pollution meteorology during the study period. The WRF-GC model is parallelized across computational cores and scales well on massively parallel architectures. In our tests where the two models were similarly configured, the WRF-GC simulation was 3 times more efficient than the GEOS-Chem Classic nested-grid simulation due to the efficient transport algorithm and the Message Passing Interface (MPI)-based parallelization provided by the WRF software framework. WRF-GC v1.0 supports one-way coupling only, using WRF-simulated meteorological fields to drive GEOS-Chem with no chemical feedbacks. The development of two-way coupling capabilities, i.e., the ability to simulate radiative and microphysical feedbacks of chemistry to meteorology, is under way. The WRF-GC model is open source and freely available from http://wrf.geos-chem.org (last access: 10 July 2020).

Description: We analyzed seasonality and interannual variability of tropospheric hydrogen cyanide (HCN) columns in densely populated eastern China for the first time. The results were derived from solar absorption spectra recorded with a ground-based high-spectral-resolution Fourier transform infrared (FTIR) spectrometer in Hefei (31∘54′ N, 117∘10′ E) between 2015 and 2018. The tropospheric HCN columns over Hefei, China, showed significant seasonal variations with three monthly mean peaks throughout the year. The magnitude of the tropospheric HCN column peaked in May, September, and December. The tropospheric HCN column reached a maximum monthly mean of (9.8±0.78)×1015 molecules cm−2 in May and a minimum monthly mean of (7.16±0.75)×1015 molecules cm−2 in November. In most cases, the tropospheric HCN columns in Hefei (32∘ N) are higher than the FTIR observations in Ny-Ålesund (79∘ N), Kiruna (68∘ N), Bremen (53∘ N), Jungfraujoch (47∘ N), Toronto (44∘ N), Rikubetsu (43∘ N), Izana (28∘ N), Mauna Loa (20∘ N), La Reunion Maido (21∘ S), Lauder (45∘ S), and Arrival Heights (78∘ S) that are affiliated with the Network for Detection of Atmospheric Composition Change (NDACC). Enhancements of tropospheric HCN column were observed between September 2015 and July 2016 compared to the same period of measurements in other years. The magnitude of the enhancement ranges from 5 % to 46 % with an average of 22 %. Enhancement of tropospheric HCN (ΔHCN) is correlated with the concurrent enhancement of tropospheric CO (ΔCO), indicating that enhancements of tropospheric CO and HCN were due to the same sources. The GEOS-Chem tagged CO simulation, the global fire maps, and the potential source contribution function (PSCF) values calculated using back trajectories revealed that the seasonal maxima in May are largely due to the influence of biomass burning in Southeast Asia (SEAS) (41±13.1 %), Europe and boreal Asia (EUBA) (21±9.3 %), and Africa (AF) (22±4.7 %). The seasonal maxima in September are largely due to the influence of biomass burnings in EUBA (38±11.3 %), AF (26±6.7 %), SEAS (14±3.3 %), and North America (NA) (13.8±8.4 %). For the seasonal maxima in December, dominant contributions are from AF (36±7.1 %), EUBA (21±5.2 %), and NA (18.7±5.2 %). The tropospheric HCN enhancement between September 2015 and July 2016 at Hefei (32∘ N) was attributed to an elevated influence of biomass burnings in SEAS, EUBA, and Oceania (OCE) in this period. In particular, an elevated number of fires in OCE in the second half of 2015 dominated the tropospheric HCN enhancement between September and December 2015. An elevated number of fires in SEAS in the first half of 2016 dominated the tropospheric HCN enhancement between January and July 2016.

Description: Although nitrogen oxide (NOx) emission controls have been implemented for several years, northern China is still facing high particulate nitrate (NO3-) pollution during severe haze events in winter. In this study, the thermodynamic equilibrium model (ISORROPIA-II) and the Weather Research and Forecast model coupled with chemistry (WRF-Chem) were used to study the efficiency of NH3 emission controls on alleviating particulate NO3- during a severe winter haze episode. We found that particulate-NO3- formation is almost NH3-limited in extremely high pollution but HNO3-limited on the other days. The improvements in manure management of livestock husbandry could reduce 40 % of total NH3 emissions (currently 100 kt month−1) in northern China in winter. Consequently, particulate NO3- was reduced by approximately 40 % (on average from 40.8 to 25.7 µg m−3). Our results indicate that reducing livestock NH3 emissions would be highly effective in reducing particulate NO3- during severe winter haze events.

Description: The North China Plain has been identified as a significant hotspot of ammonia (NH3) due to extensive agricultural activities. Satellite observations suggest a significant increase of about 30 % in tropospheric gas-phase NH3 concentrations in this area during 2008–2016. However, the estimated NH3 emissions decreased slightly by 7 % because of changes in Chinese agricultural practices, i.e., the transition in fertilizer types from ammonium carbonate fertilizer to urea, and in the livestock rearing system from free-range to intensive farming. We note that the emissions of sulfur dioxide (SO2) have rapidly declined by about 60 % over the recent few years. By integrating measurements from ground and satellite, a long-term anthropogenic NH3 emission inventory, and chemical transport model simulations, we find that this large SO2 emission reduction is responsible for the NH3 increase over the North China Plain. The simulations for the period 2008–2016 demonstrate that the annual average sulfate concentrations decreased by about 50 %, which significantly weakens the formation of ammonium sulfate and increases the average proportions of gas-phase NH3 within the total NH3 column concentrations from 26 % (2008) to 37 % (2016). By fixing SO2 emissions of 2008 in those multi-year simulations, the increasing trend of the tropospheric NH3 concentrations is not observed. Both the decreases in sulfate and increases in NH3 concentrations show highest values in summer, possibly because the formation of sulfate aerosols is more sensitive to SO2 emission reductions in summer than in other seasons. Besides, the changes in NOx emissions and meteorological conditions both decreased the NH3 column concentrations by about 3 % in the study period. Our simulations suggest that the moderate reduction in NOx emissions (16 %) favors the formation of particulate nitrate by elevating ozone concentrations in the lower troposphere.

Description: Current estimates of agricultural ammonia (NH3) 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 NH3 emissions from agriculture in China for the year 2008. We first assimilate satellite observations of NH3 column concentration from the Tropospheric Emission Spectrometer (TES) using the GEOS-Chem adjoint model to optimize Chinese anthropogenic NH3 emissions at the 1∕2°  ×  2∕3° horizontal resolution for March–October 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 NH3 emission estimates. To reconcile the latter with the top-down results, we revisit the processes of agricultural NH3 emissions and develop an improved bottom-up inventory of Chinese NH3 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 NH3 emission factors in China. We find that annual anthropogenic NH3 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 NH3 emissions in China. Our bottom-up emission estimates also show a distinct seasonality peaking in summer, consistent with top-down 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 NH3 gas concentrations and ammonium (NH4+) wet deposition fluxes over China well, providing additional credibility to the improvements we have made to our agricultural NH3 emission inventory.

Description: Five-year (2011–2015) measurements of gaseous NH3, NO2, and HNO3 and particulate NH4+ and NO3− in air and/or precipitation were conducted at 27 sites in the Nationwide Nitrogen Deposition Monitoring Network (NNDMN) to better understand spatial and temporal (seasonal and annual) characteristics of reactive nitrogen (Nr) concentrations and deposition in eastern China. Our observations reveal annual average concentrations (16.4–32.6 µg N m−3), dry deposition fluxes (15.8–31.7 kg N ha−1 yr−1), and wet/bulk deposition fluxes (18.4–28.0 kg N ha−1 yr−1) based on land use, ranked as urban 〉 rural 〉 background sites. Annual concentrations and dry deposition fluxes of each Nr species in air were comparable at urban and background sites in northern and southern regions, but were significantly higher at northern rural sites. These results, together with good agreement between spatial distributions of NH3 and NO2 concentrations determined from ground measurements and satellite observations, demonstrate that atmospheric Nr pollution is heavier in the northern region than in the southern region. No significant inter-annual trends were found in the annual Nr dry and wet/bulk N deposition at almost all of the selected sites. A lack of significant changes in annual averages between the 2013–2015 and 2011–2012 periods for all land use types suggests that any effects of current emission controls are not yet apparent in Nr pollution and deposition in the region. Ambient concentrations of total Nr exhibited non-significant seasonal variation at all land use types, although significant seasonal variations were found for individual Nr species (e.g. NH3, NO2, and pNO3−) in most cases. In contrast, dry deposition of total Nr exhibited a consistent and significant seasonal variation at all land use types, with the highest fluxes in summer and the lowest in winter. Based on sensitivity tests by the GEOS-Chem model, we found that NH3 emissions from fertilizer use (including chemical and organic fertilizers) were the largest contributor (36 %) to total inorganic Nr deposition over eastern China. Our results not only improve the understanding of spatial–temporal variations of Nr concentrations and deposition in this pollution hotspot, but also provide useful information for policy-makers that mitigation of NH3 emissions should be a priority to tackle serious N deposition in eastern China.

Description: Lower tropospheric (surface to 600 hPa) ozone over India poses serious risks to both human health and crops, and potentially affects global ozone distribution through frequent deep convection in tropical regions. Our current understanding of the processes controlling seasonal and long-term variations in lower tropospheric ozone over this region is rather limited due to spatially and temporally sparse observations. Here we present an integrated process analysis of the seasonal cycle, interannual variability, and long-term trends of lower tropospheric ozone over India and its linkage to the South Asian monsoon using the Ozone Monitoring Instrument (OMI) satellite observations for years 2006–2014 interpreted with a global chemical transport model (GEOS-Chem) simulation for 1990–2010. OMI observed lower tropospheric ozone over India averaged for 2006–2010, showing the highest concentrations (54.1 ppbv) in the pre-summer monsoon season (May) and the lowest concentrations (40.5 ppbv) in the summer monsoon season (August). Process analyses in GEOS-Chem show that hot and dry meteorological conditions and active biomass burning together contribute to 5.8 Tg more ozone being produced in the lower troposphere in India in May than January. The onset of the summer monsoon brings ozone-unfavorable meteorological conditions and strong upward transport, which all lead to large decreases in the lower tropospheric ozone burden. Interannually, we find that both OMI and GEOS-Chem indicate strong positive correlations (r=0.55–0.58) between ozone and surface temperature in pre-summer monsoon seasons, with larger correlations found in high NOx emission regions reflecting NOx-limited production conditions. Summer monsoon seasonal mean ozone levels are strongly controlled by monsoon strengths. Lower ozone concentrations are found in stronger monsoon seasons mainly due to less ozone net chemical production. Furthermore, model simulations over 1990–2010 estimate a mean annual trend of 0.19 ± 0.07 (p value 

Description: Air quality models have not been able to reproduce the magnitude of the observed concentrations of fine particulate matter (PM2.5) during wintertime Chinese haze events. The discrepancy has been at least partly attributed to low biases in modeled sulfate production rates, due to the lack of heterogeneous sulfate production on aerosols in the models. In this study, we explicitly implement four heterogeneous sulfate formation mechanisms into a regional chemical transport model, in addition to gas-phase and in-cloud sulfate production. We compare the model results with observations of sulfate concentrations and oxygen isotopes, Δ17O(SO42-), in the winter of 2014–2015, the latter of which is highly sensitive to the relative importance of different sulfate production mechanisms. Model results suggest that heterogeneous sulfate production on aerosols accounts for about 20 % of sulfate production in clean and polluted conditions, partially reducing the modeled low bias in sulfate concentrations. Model sensitivity studies in comparison with the Δ17O(SO42-) observations suggest that heterogeneous sulfate formation is dominated by transition metal ion-catalyzed oxidation of SO2.

Description: We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618 hPa) ozone–carbon monoxide (O3–CO) correlations determined by the measurements from the Tropospheric Emission Spectrometer (TES) aboard NASA's Aura satellite during boreal summer (July–August). The model is driven by three meteorological data sets (finite-volume General Circulation Model (fvGCM) with sea surface temperature for 1995, Goddard Earth Observing System Data Assimilation System Version 4 (GEOS-4 DAS) for 2005, and Modern-Era Retrospective Analysis for Research and Applications (MERRA) for 2005), allowing us to examine the sensitivity of model O3–CO correlations to input meteorological data. Model simulations of radionuclide tracers (222Rn, 210Pb, and 7Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O3 values are evaluated with climatological profiles from ozonesonde measurements and satellite tropospheric O3 columns. Despite the fact that the three simulations show significantly different global and regional distributions of O3 and CO concentrations, they show similar patterns of O3–CO correlations on a global scale. All model simulations sampled along the TES orbit track capture the observed positive O3–CO correlations in the Northern Hemisphere midlatitude continental outflow and the Southern Hemisphere subtropics. While all simulations show strong negative correlations over the Tibetan Plateau, northern Africa, the subtropical eastern North Pacific, and the Caribbean, TES O3 and CO concentrations at 618 hPa only show weak negative correlations over much narrower areas (i.e., the Tibetan Plateau and northern Africa). Discrepancies in regional O3–CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O3–CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O3 and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NOx emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O3–CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O3–CO correlations than other emissions but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O3 is consumed and CO generated during the atmospheric oxidation process of isoprene under low-NOx conditions. We find that lightning NOx emissions degrade both positive correlations at mid- and high latitudes and negative correlations in the tropics because ozone production downwind of lightning NOx emissions is not directly related to the emission and transport of CO. Our study concludes that O3–CO correlations may be used effectively to constrain the sources of regional tropospheric O3 in global 3-D models, especially for those regions where convective transport of pollution plays an important role.