The Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1) together with the Modern-Era Retrospective Analysis for Research and Applications (MERRA) meteorological fields were used to ...create a global emission data set of biogenic volatile organic compounds (BVOC) available on a monthly basis for the time period of 1980–2010. This data set, developed under the Monitoring Atmospheric Composition and Climate project (MACC), is called MEGAN–MACC. The model estimated mean annual total BVOC emission of 760 Tg (C) yr−1 consisting of isoprene (70%), monoterpenes (11%), methanol (6%), acetone (3%), sesquiterpenes (2.5%) and other BVOC species each contributing less than 2%. Several sensitivity model runs were performed to study the impact of different model input and model settings on isoprene estimates and resulted in differences of up to ±17% of the reference isoprene total. A greater impact was observed for a sensitivity run applying parameterization of soil moisture deficit that led to a 50% reduction of isoprene emissions on a global scale, most significantly in specific regions of Africa, South America and Australia. MEGAN–MACC estimates are comparable to results of previous studies. More detailed comparison with other isoprene inventories indicated significant spatial and temporal differences between the data sets especially for Australia, Southeast Asia and South America. MEGAN–MACC estimates of isoprene, α-pinene and group of monoterpenes showed a reasonable agreement with surface flux measurements at sites located in tropical forests in the Amazon and Malaysia. The model was able to capture the seasonal variation of isoprene emissions in the Amazon forest.
An eight-year long reanalysis of atmospheric composition data covering the period 2003–2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by ...assimilating satellite data into a global model and data assimilation system. This reanalysis provides fields of chemically reactive gases, namely carbon monoxide, ozone, nitrogen oxides, and formaldehyde, as well as aerosols and greenhouse gases globally at a horizontal resolution of about 80 km for both the troposphere and the stratosphere. This paper describes the assimilation system for the reactive gases and presents validation results for the reactive gas analysis fields to document the data set and to give a first indication of its quality. Tropospheric CO values from the MACC reanalysis are on average 10–20% lower than routine observations from commercial aircrafts over airports through most of the troposphere, and have larger negative biases in the boundary layer at urban sites affected by air pollution, possibly due to an underestimation of CO or precursor emissions. Stratospheric ozone fields from the MACC reanalysis agree with ozonesondes and ACE-FTS data to within ±10% in most seasons and regions. In the troposphere the reanalysis shows biases of −5% to +10% with respect to ozonesondes and aircraft data in the extratropics, but has larger negative biases in the tropics. Area-averaged total column ozone agrees with ozone fields from a multi-sensor reanalysis data set to within a few percent. NO2 fields from the reanalysis show the right seasonality over polluted urban areas of the NH and over tropical biomass burning areas, but underestimate wintertime NO2 maxima over anthropogenic pollution regions and overestimate NO2 in northern and southern Africa during the tropical biomass burning seasons. Tropospheric HCHO is well simulated in the MACC reanalysis even though no satellite data are assimilated. It shows good agreement with independent SCIAMACHY retrievals over regions dominated by biogenic emissions with some anthropogenic input, such as the eastern US and China, and also over African regions influenced by biogenic sources and biomass burning.
Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, carbon monoxide (CO) concentrations remain underestimated during Northern ...Hemisphere (NH) winter by most state-of-the-art chemistry transport models. The consequential model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of surface sources and sinks with a series of MOZART (Model for Ozone And Related Tracers) model sensitivity studies for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and vertical profiles from measurements on passenger aircraft. In our base case simulation using MACCity (Monitoring Atmospheric Composition and Climate project) anthropogenic emissions, the near-surface CO mixing ratios are underestimated in the Northern Hemisphere by more than 20 ppb from December to April, with the largest bias of up to 75 ppb over Europe in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOCs) is not able to reduce the annual course of the model bias and yields concentrations over the Southern Hemisphere which are too high. Raising global annual anthropogenic emissions with a simple scaling factor results in overestimations of surface mixing ratios in most regions all year round. Instead, our results indicate that anthropogenic CO and, possibly, VOC emissions in the MACCity inventory are too low for the industrialized countries only during winter and spring. Reasonable agreement with observations can only be achieved if the CO emissions are adjusted seasonally with regionally varying scaling factors. A part of the model bias could also be eliminated by exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes, which reduces the boreal winter dry deposition fluxes. The best match to surface observations, satellite retrievals, and aircraft observations was achieved when the modified dry deposition scheme was combined with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively). One reason for the apparent underestimation of emissions may be an exaggerated downward trend in the Representative Concentration Pathway (RCP) 8.5 scenario in these regions between 2000 and 2010, as this scenario was used to extrapolate the MACCity emissions from their base year 2000. This factor is potentially amplified by a lack of knowledge about the seasonality of emissions. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot fully exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations on the modelled CO.
Daily global analyses and 5-day forecasts are generated in the context of the European Monitoring Atmospheric Composition and Climate (MACC) project using an extended version of the Integrated ...Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The IFS now includes modules for chemistry, deposition and emission of reactive gases, aerosols, and greenhouse gases, and the 4-dimensional variational data assimilation scheme makes use of multiple satellite observations of atmospheric composition in addition to meteorological observations. This paper describes the data assimilation setup of the new Composition-IFS (C-IFS) with respect to reactive gases and validates analysis fields of ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) for the year 2008 against independent observations and a control run without data assimilation. The largest improvement in CO by assimilation of Measurements of Pollution in the Troposphere (MOPITT) CO columns is seen in the lower troposphere of the Northern Hemisphere (NH) extratropics during winter, and during the South African biomass-burning season. The assimilation of several O3 total column and stratospheric profile retrievals greatly improves the total column, stratospheric and upper tropospheric O3 analysis fields relative to the control run. The impact on lower tropospheric ozone, which comes from the residual of the total column and stratospheric profile O3 data, is smaller, but nevertheless there is some improvement particularly in the NH during winter and spring. The impact of the assimilation of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) is small because of the short lifetime of NO2, suggesting that NO2 observations would be better used to adjust emissions instead of initial conditions. The results further indicate that the quality of the tropospheric analyses and of the stratospheric ozone analysis obtained with the C-IFS system has improved compared to the previous "coupled" model system of MACC.
Two state-of-the-art models (deterministic: Weather Research and Forecast model with Chemistry (WRF-Chem) and statistic: Artificial Neural Networks: (ANN)) are implemented to predict the ground-level ...ozone concentration in São Paulo (SP), Brazil. Two domains are set up for WRF-Chem simulations: a coarse domain (with 50 km horizontal resolution) including whole South America (D1) and a nested domain (with horizontal resolution of 10 km) including South Eastern Brazil (D2). To evaluate the spatial distribution of the chemical species, model results are compared to the Measurements of Pollution in The Troposphere (MOPITT) data, showing that the model satisfactorily predicts the CO concentrations in both D1 and D2. The model also reproduces the measurements made at three air quality monitoring stations in SP with the correlation coefficients of 0.74, 0.70, and 0.77 for O3 and 0.51, 0.48, and 0.57 for NOx. The input selection for ANN model is carried out using Forward Selection (FS) method. FS-ANN is then trained and validated using the data from two air quality monitoring stations, showing correlation coefficients of 0.84 and 0.75 for daily mean and 0.64 and 0.67 for daily peak ozone during the test stage. Then, both WRF-Chem and FS-ANN are deployed to forecast the daily mean and peak concentrations of ozone in two stations during 5–20 August 2012. Results show that WRF-Chem preforms better in predicting mean and peak ozone concentrations as well as in conducting mechanistic and sensitivity analysis. FS-ANN is only advantageous in predicting mean daily ozone concentrations considering its significantly lower computational costs and ease of development and implementation, compared to that of WRF-Chem.
•Two deterministic and statistic models for ozone prediction are compared.•Deterministic model predicts the ozone episodes more satisfactorily.•Statistic model is slightly advantageous only due to its lower computational costs.•Mechanistic insights are achievable only in the deterministic model.
A model intercomparison activity was inspired by the large suite of observations of atmospheric composition made during the International Polar Year (2008) in the Arctic. Nine global and two regional ...chemical transport models participated in this intercomparison and performed simulations for 2008 using a common emissions inventory to assess the differences in model chemistry and transport schemes. This paper summarizes the models and compares their simulations of ozone and its precursors and presents an evaluation of the simulations using a variety of surface, balloon, aircraft and satellite observations. Each type of measurement has some limitations in spatial or temporal coverage or in composition, but together they assist in quantifying the limitations of the models in the Arctic and surrounding regions. Despite using the same emissions, large differences are seen among the models. The cloud fields and photolysis rates are shown to vary greatly among the models, indicating one source of the differences in the simulated chemical species. The largest differences among models, and between models and observations, are in NOy partitioning (PAN vs. HNO3) and in oxygenated volatile organic compounds (VOCs) such as acetaldehyde and acetone. Comparisons to surface site measurements of ethane and propane indicate that the emissions of these species are significantly underestimated. Satellite observations of NO2 from the OMI (Ozone Monitoring Instrument) have been used to evaluate the models over source regions, indicating anthropogenic emissions are underestimated in East Asia, but fire emissions are generally overestimated. The emission factors for wildfires in Canada are evaluated using the correlations of VOCs to CO in the model output in comparison to enhancement factors derived from aircraft observations, showing reasonable agreement for methanol and acetaldehyde but underestimate ethanol, propane and acetone, while overestimating ethane emission factors.
Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra ...mission (2000 to present). Another 15 and more years of observations will be provided by the IASI/MetOp instrument series (2007–2023 >). In order to study long-term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved quantities are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a 6-year overlap period (2008–2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms (v5T for MOPITT and v20100815 for IASI), and second using a dedicated reprocessing of MOPITT CO profiles and columns using the same a priori information as the IASI product. MOPITT total columns are generally slightly higher over land (bias ranging from 0 to 13 %) than IASI data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15 %) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to a larger variability associated with the a priori.
Arctic sea ice has decreased dramatically in the past few decades and the Arctic is increasingly open to transit shipping and natural resource extraction. However, large knowledge gaps exist ...regarding composition and impacts of emissions associated with these activities. Arctic hydrocarbon extraction is currently under development owing to the large oil and gas reserves in the region. Transit shipping through the Arctic as an alternative to the traditional shipping routes is currently underway. These activities are expected to increase emissions of air pollutants and climate forcers (e.g., aerosols, ozone) in the Arctic troposphere significantly in the future. The authors present the first measurements of these activities off the coast of Norway taken in summer 2012 as part of the European Arctic Climate Change, Economy, and Society (ACCESS) project. The objectives include quantifying the impact that anthropogenic activities will have on regional air pollution and understanding the connections to Arctic climate. Trace gas and aerosol concentrations in pollution plumes were measured, including emissions from different ship types and several offshore extraction facilities. Emissions originating from industrial activities (smelting) on the Kola Peninsula were also sampled. In addition, pollution plumes originating from Siberian biomass burning were probed in order to put the emerging local pollution within a broader context. In the near future these measurements will be combined with model simulations to quantify the influence of local anthropogenic activities on Arctic composition. Here the authors present the scientific objectives of the ACCESS aircraft experiment and the the meteorological conditions during the campaign, and they highlight first scientific results from the experiment.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The European MACC (Monitoring Atmospheric Composition and Climate) project is preparing the operational Copernicus Atmosphere Monitoring Service (CAMS), one of the services of the European Copernicus ...Programme on Earth observation and environmental services. MACC uses data assimilation to combine in situ and remote sensing observations with global and regional models of atmospheric reactive gases, aerosols, and greenhouse gases, and is based on the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts (ECMWF). The global component of the MACC service has a dedicated validation activity to document the quality of the atmospheric composition products. In this paper we discuss the approach to validation that has been developed over the past 3 years. Topics discussed are the validation requirements, the operational aspects, the measurement data sets used, the structure of the validation reports, the models and assimilation systems validated, the procedure to introduce new upgrades, and the scoring methods. One specific target of the MACC system concerns forecasting special events with high-pollution concentrations. Such events receive extra attention in the validation process. Finally, a summary is provided of the results from the validation of the latest set of daily global analysis and forecast products from the MACC system reported in November 2014.
Within the African Monsoon Multidisciplinary Analysis (AMMA), we investigate the impact of nitrogen oxides produced by lightning (LiNOx ) and convective transport during the West African Monsoon ...(WAM) upon the composition of the upper troposphere (UT) in the tropics. For this purpose, we have performed simulations with 4 state-of-the-art chemistry transport models involved within AMMA, namely MOCAGE, TM4, LMDz-INCA and p-TOMCAT. The model intercomparison is complemented with an evaluation of the simulations based on both spaceborne and airborne observations. The baseline simulations show important differences between the UT CO and O3 distributions simulated by each of the 4 models when compared to measurements from the MOZAIC program and fom the Aura/MLS spaceborne sensor. We show that such model discrepancies can be explained by differences in the convective transport parameterizations and, more particularly, the altitude reached by convective updrafts (ranging between ~200-125 hPa). Concerning UT O3 , the models exhibit a good agreement with the main observed features. Nevertheless the majority of models simulate low O3 concentrations compared to both MOZAIC and Aura/MLS observations south of the equator, and rather high concentrations in the Northern Hemisphere. Sensitivity studies are performed to quantify the effect of deep convective transport and the influence of LiNOx production on the UT composition. These clearly indicate that the CO maxima and the elevated O3 concentrations south of the equator are due to convective uplift of air masses impacted by Southern African biomass burning, in agreement with previous studies. Moreover, during the WAM, LiNOx from Africa are responsible for the highest UT O3 enhancements (10-20 ppbv) over the tropical Atlantic between 10° S-20° N. Differences between models are primarily due to the performance of the parameterizations used to simulate lightning activity which are evaluated using spaceborne observations of flash frequency. Combined with comparisons of in-situ NO measurements we show that the models producing the highest amounts of LiNOx over Africa during the WAM (INCA and p-TOMCAT) capture observed NO profiles with the best accuracy, although they both overestimate lightning activity over the Sahel.
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