Index Geophysics

Items

• The effects of global change upon United States air quality

  To understand more fully the effects of global changes on ambient concentrations of ozone and particulate matter with aerodynamic diameter smaller than 2.5 μm (PM_2.5) in the United States (US), we conducted a comprehensive modeling effort to evaluate explicitly the effects of changes in climate, biogenic emissions, land use and global/regional anthropogenic emissions on ozone and PM_2.5 concentrations and composition. Results from the ECHAM5 global climate model driven with the A1B emission scenario from the Intergovernmental Panel on Climate Change (IPCC) were downscaled using the Weather Research and Forecasting (WRF) model to provide regional meteorological fields. We developed air quality simulations using the Community Multiscale Air Quality Model (CMAQ) chemical transport model for two nested domains with 220 and 36 km horizontal grid cell resolution for a semi-hemispheric domain and a continental United States (US) domain, respectively. The semi-hemispheric domain was used to evaluate the impact of projected global emissions changes on US air quality. WRF meteorological fields were used to calculate current (2000s) and future (2050s) biogenic emissions using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). For the semi-hemispheric domain CMAQ simulations, present-day global emissions inventories were used and projected to the 2050s based on the IPCC A1B scenario. Regional anthropogenic emissions were obtained from the US Environmental Protection Agency National Emission Inventory 2002 (EPA NEI2002) and projected to the future using the MARKet ALlocation (MARKAL) energy system model assuming a business as usual scenario that extends current decade emission regulations through 2050. Our results suggest that daily maximum 8 h average ozone (DM8O) concentrations will increase in a range between 2 to 12 parts per billion (ppb) across most of the continental US. The highest increase occurs in the South, Central and Midwest regions of the US due to increases in temperature, enhanced biogenic emissions and changes in land use. The model predicts an average increase of 1–6 ppb in DM8O due to projected increase in global emissions of ozone precursors. The effects of these factors are only partially offset by reductions in DM8O associated with decreasing US anthropogenic emissions. Increases in PM_2.5 levels between 4 and 10 μg m⁻³ in the Northeast, Southeast, Midwest and South regions are mostly a result of increase in primary anthropogenic particulate matter (PM), enhanced biogenic emissions and land use changes. Changes in boundary conditions shift the composition but do not alter overall simulated PM_2.5 mass concentrations.

• Radiative forcing and climate response to projected 21st century aerosol decreases

  It is widely expected that global emissions of atmospheric aerosols and their precursors will decrease strongly throughout the remainder of the 21st century, due to emission reduction policies enacted to protect human health. For instance, global emissions of aerosols and their precursors are projected to decrease by as much as 80 % by the year 2100, according to the four Representative Concentration Pathway (RCP) scenarios. The removal of aerosols will cause unintended climate consequences, including an unmasking of global warming from long-lived greenhouse gases. We use the Geophysical Fluid Dynamics Laboratory Coupled Climate Model version 3 (GFDL CM3) to simulate future climate over the 21st century with and without the aerosol emission changes projected by each of the RCPs in order to isolate the radiative forcing and climate response resulting from the aerosol reductions. We find that the projected global radiative forcing and climate response due to aerosol decreases do not vary significantly across the four RCPs by 2100, although there is some mid-century variation, especially in cloud droplet effective radius, that closely follows the RCP emissions and energy consumption projections. Up to 1 W m⁻² of radiative forcing may be unmasked globally from 2005 to 2100 due to reductions in aerosol and precursor emissions, leading to average global temperature increases up to 1 K and global precipitation rate increases up to 0.09 mm day⁻¹. However, when using a version of CM3 with reduced present-day aerosol radiative forcing (−1.0 W m⁻²), the global temperature increase for RCP8.5 is about 0.5 K, with similar magnitude decreases in other climate response parameters as well. Regionally and locally, climate impacts can be much larger than the global mean, with a 2.1 K warming projected over China, Japan, and Korea due to the reduced aerosol emissions in RCP8.5, as well as nearly a 0.2 mm day⁻¹ precipitation increase, a 7 g m⁻² LWP decrease, and a 2 μm increase in cloud droplet effective radius. Future aerosol decreases could be responsible for 30–40 % of total climate warming (or 10–20 % with weaker aerosol forcing) by 2100 in East Asia, even under the high greenhouse gas emissions scenario (RCP8.5). The expected unmasking of global warming caused by aerosol reductions will require more aggressive greenhouse gas mitigation policies than anticipated in order to meet desired climate targets.

• Estimation of continuous anthropogenic CO2: model-based evaluation of CO2, CO, δ13C(CO2) and Δ14C(CO2) tracer methods

  We investigate different methods for estimating anthropogenic CO₂ using modeled continuous atmospheric concentrations of CO₂ alone, as well as CO₂ in combination with the surrogate tracers CO, δ¹³C(CO₂) and Δ¹⁴C(CO₂). These methods are applied at three hypothetical stations representing rural, urban and polluted conditions. We find that, independent of the tracer used, an observation-based estimate of continuous anthropogenic CO₂ is not yet feasible at rural measurement sites due to the low signal-to-noise ratio of anthropogenic CO₂ estimates at such settings. The tracers δ¹³C(CO₂) and CO provide an accurate possibility to determine anthropogenic CO₂ continuously, only if all CO₂ sources in the catchment area are well characterized or calibrated with respect to their isotopic signature and CO to anthropogenic CO₂ ratio. We test different calibration strategies for the mean isotopic signature and CO to CO₂ ratio using precise Δ¹⁴C(CO₂) measurements on monthly integrated as well as on grab samples. For δ¹³C(CO₂), a calibration with annually averaged ¹⁴C(CO₂) grab samples is most promising, since integrated sampling introduces large biases into anthropogenic CO₂ estimates. For CO, these biases are smaller. The precision of continuous anthropogenic CO₂ determination using δ¹³C(CO₂) depends on measurement precision of δ¹³C(CO₂) and CO₂, while the CO method is mainly limited by the variation in natural CO sources and sinks. At present, continuous anthropogenic CO₂ could be determined using the tracers δ¹³C(CO₂) and/or CO with a precision of about 30 %, a mean bias of about 10 % and without significant diurnal discrepancies. Hypothetical future measurements of continuous Δ¹⁴C(CO₂) with a precision of 5 ‰ are promising for anthropogenic CO₂ determination (precision ca. 10–20 %) but are not yet available. The investigated tracer-based approaches open the door to improving, validating and reducing biases of highly resolved emission inventories using atmospheric observation and regional modeling.

• Direct radiative effect by brown carbon over the Indo-Gangetic Plain

  The importance of light-absorbing organic aerosols, often called brown carbon (BrC), has become evident in recent years. However, there have been relatively few measurement-based estimates for the direct radiative effect of BrC so far. In earlier studies, the AErosol RObotic NETwork (AERONET)-measured aerosol absorption optical depth (AAOD) and absorption Angstrom exponent (AAE) were exploited. However, these two pieces of information are clearly not sufficient to separate properly carbonaceous aerosols from dust, while imaginary indices of refraction would contain more and better justified information for this purpose. This is first time that the direct radiative effect (DRE) of BrC is estimated by exploiting the AERONET-retrieved imaginary indices. We estimated it for four sites in the Indo-Gangetic Plain (IGP), Karachi, Lahore, Kanpur and Gandhi College. We found a distinct seasonality, which was generally similar among all the sites, but with slightly different strengths. The monthly warming effect up to 0.5 W m⁻² takes place during the spring season. On the other hand, BrC results in an overall cooling effect in the winter season, which can reach levels close to −1 W m⁻². We then estimated similarly also the DRE of black carbon and total aerosol, in order to assess the relative significance of the BrC radiative effect in the radiative effects of other components. Even though BrC impact seems minor in this context, we demonstrated that it is not insignificant. Moreover, we demonstrated that it is crucial to perform spectrally resolved radiative transfer calculations to obtain good estimates for the DRE of BrC.

• On the potential of the ICOS atmospheric CO2 measurement network for estimating the biogenic CO2 budget of Europe

  We present a performance assessment of the European Integrated Carbon Observing System (ICOS) atmospheric network for constraining European biogenic CO₂ fluxes (hereafter net ecosystem exchange, NEE). The performance of the network is assessed in terms of uncertainty in the fluxes, using a state-of-the-art mesoscale variational atmospheric inversion system assimilating hourly averages of atmospheric data to solve for NEE at 6 h and 0.5° resolution. The performance of the ICOS atmospheric network is also assessed in terms of uncertainty reduction compared to typical uncertainties in the flux estimates from ecosystem models, which are used as prior information by the inversion. The uncertainty in inverted fluxes is computed for two typical periods representative of northern summer and winter conditions in July and in December 2007, respectively. These computations are based on a observing system simulation experiment (OSSE) framework. We analyzed the uncertainty in a 2-week-mean NEE as a function of the spatial scale with a focus on the model native grid scale (0.5°), the country scale and the European scale (including western Russia and Turkey). Several network configurations, going from 23 to 66 sites, and different configurations of the prior uncertainties and atmospheric model transport errors are tested in order to assess and compare the improvements that can be expected in the future from the extension of the network, from improved prior information or transport models. Assimilating data from 23 sites (a network comparable to present-day capability) with errors estimated from the present prior information and transport models, the uncertainty reduction on a 2-week-mean NEE should range between 20 and 50 % for 0.5° resolution grid cells in the best sampled area encompassing eastern France and western Germany. At the European scale, the prior uncertainty in a 2-week-mean NEE is reduced by 50 % (66 %), down to ~ 43 Tg C month⁻¹ (26 Tg C month⁻¹) in July (December). Using a larger network of 66 stations, the prior uncertainty of NEE is reduced by the inversion by 64 % (down to ~ 33 Tg C month⁻¹) in July and by 79 % (down to ~ 15 Tg C month⁻¹) in December. When the results are integrated over the well-observed western European domain, the uncertainty reduction shows no seasonal variability. The effect of decreasing the correlation length of the prior uncertainty, or of reducing the transport model errors compared to their present configuration (when conducting real-data inversion cases) can be larger than that of the extension of the measurement network in areas where the 23 station observation network is the densest. We show that with a configuration of the ICOS atmospheric network containing 66 sites that can be expected on the long-term, the uncertainties in a 2-week-mean NEE will be reduced by up to 50–80 % for countries like Finland, Germany, France and Spain, which could significantly improvement (and at least a high complementarity to) our knowledge of NEE derived from biomass and soil carbon inventories at multi-annual scales.

• Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model

  The Community Atmosphere Model (CAM5), equipped with a technique to tag black carbon (BC) emissions by source regions and types, has been employed to establish source–receptor relationships for atmospheric BC and its deposition to snow over western North America. The CAM5 simulation was conducted with meteorological fields constrained by reanalysis for year 2013 when measurements of BC in both near-surface air and snow are available for model evaluation. We find that CAM5 has a significant low bias in predicted mixing ratios of BC in snow but only a small low bias in predicted atmospheric concentrations over northwestern USA and western Canada. Even with a strong low bias in snow mixing ratios, radiative transfer calculations show that the BC-in-snow darkening effect is substantially larger than the BC dimming effect at the surface by atmospheric BC. Local sources contribute more to near-surface atmospheric BC and to deposition than distant sources, while the latter are more important in the middle and upper troposphere where wet removal is relatively weak. Fossil fuel (FF) is the dominant source type for total column BC burden over the two regions. FF is also the dominant local source type for BC column burden, deposition, and near-surface BC, while for all distant source regions combined the contribution of biomass/biofuel (BB) is larger than FF. An observationally based positive matrix factorization (PMF) analysis of the snow-impurity chemistry is conducted to quantitatively evaluate the CAM5 BC source-type attribution. While CAM5 is qualitatively consistent with the PMF analysis with respect to partitioning of BC originating from BB and FF emissions, it significantly underestimates the relative contribution of BB. In addition to a possible low bias in BB emissions used in the simulation, the model is likely missing a significant source of snow darkening from local soil found in the observations.

• Retrieval of ammonia from ground-based FTIR solar spectra

  We present a retrieval method for ammonia (NH₃) total columns from ground-based Fourier transform infrared (FTIR) observations. Observations from Bremen (53.10° N, 8.85° E), Lauder (45.04° S, 169.68° E), Réunion (20.9° S, 55.50° E) and Jungfraujoch (46.55° N, 7.98° E) were used to illustrate the capabilities of the method. NH₃ mean total columns ranging 3 orders of magnitude were obtained, with higher values at Bremen (mean of 13.47 &times; 10¹⁵ molecules cm⁻²) and lower values at Jungfraujoch (mean of 0.18 &times; 10¹⁵ molecules cm^&minus;2). In conditions with high surface concentrations of ammonia, as in Bremen, it is possible to retrieve information on the vertical gradient, as two layers can be distinguished. The retrieval there is most sensitive to ammonia in the planetary boundary layer, where the trace gas concentration is highest. For conditions with low concentrations, only the total column can be retrieved. Combining the systematic and random errors we have a mean total error of 26 % for all spectra measured at Bremen (number of spectra (<I>N</I>) = 554), 30 % for all spectra from Lauder (<I>N</I> = 2412), 25 % for spectra from Réunion (<I>N</I> = 1262) and 34 % for spectra measured at Jungfraujoch (<I>N</I> = 2702). The error is dominated by the systematic uncertainties in the spectroscopy parameters. Station-specific seasonal cycles were found to be consistent with known seasonal cycles of the dominant ammonia sources in the station surroundings. The developed retrieval methodology from FTIR instruments provides a new way of obtaining highly time-resolved measurements of ammonia burdens. FTIR-NH₃ observations will be useful for understanding the dynamics of ammonia concentrations in the atmosphere and for satellite and model validation. It will also provide additional information to constrain the global ammonia budget.

• New particle-dependent parameterizations of heterogeneous freezing processes: sensitivity studies of convective clouds with an air parcel model

  Based on the outcome of laboratory results, new particle-dependent parameterizations of heterogeneous freezing were derived and used to improve and extend a two-dimensional spectral microphysics scheme. They include (1) a particle-type-dependent parameterization of immersion freezing using the numbers of active sites per mass, (2) a particle-type and size-resolved parameterization of contact freezing, and (3) a particle-type-dependent description of deposition freezing. The modified microphysical scheme was embedded in an adiabatic air parcel model with entrainment. Sensitivity studies were performed to simulate convective situations and to investigate the impact of ice nuclei concentrations and types on ice formation. As a central diagnostic parameter, the ice water fraction (IWF) was selected, which is the relation of the ice water content to the total amount of water in the condensed form. The following parameters were varied: initial aerosol particle number size distributions, types of ice nucleating particles, final temperature, and the fractions of potential ice nucleating particles. Single and coupled freezing processes were investigated. The results show that immersion freezing seems to be the most efficient process. Contact freezing is constrained by the collision kernel between supercooled drops and potential ice nucleating particles. The importance of deposition freezing lies in secondary ice formation; i.e., small ice particles produced by deposition nucleation trigger the freezing of supercooled drops by collisions. Thus, a broader ice particle spectrum is generated than that by immersion and contact freezing. During coupled immersion–contact and contact–deposition freezing no competition was observed, and both processes contribute to cloud ice formation but do not impede each other. As already suggested in the literature, mineral dust particles seem to be the most important ice nucleating particles. Biological particles are probably not involved in significant ice formation. The sensitive parameters affecting cloud properties are temperature, aerosol particle composition and concentration, and particle size distribution.

• A process-based 222radon flux map for Europe and its comparison to long-term observations

  Detailed ²²²radon (²²²Rn) flux maps are an essential pre-requisite for the use of radon in atmospheric transport studies. Here we present a high-resolution ²²²Rn flux map for Europe, based on a parameterization of ²²²Rn production and transport in the soil. The ²²²Rn exhalation rate is parameterized based on soil properties, uranium content, and modelled soil moisture from two different land-surface reanalysis data sets. Spatial variations in exhalation rates are primarily determined by the uranium content of the soil, but also influenced by soil texture and local water-table depth. Temporal variations are related to soil moisture variations as the molecular diffusion in the unsaturated soil zone depends on available air-filled pore space. The implemented diffusion parameterization was tested against campaign-based ²²²Rn soil profile measurements. Monthly ²²²Rn exhalation rates from European soils were calculated with a nominal spatial resolution of 0.083° × 0.083° and compared to long-term direct measurements of ²²²Rn exhalation rates in different areas of Europe. The two realizations of the ²²²Rn flux map, based on the different soil moisture data sets, both realistically reproduce the observed seasonality in the fluxes but yield considerable differences for absolute flux values. The mean ²²²Rn flux from soils in Europe is estimated to be 10 mBq m⁻² s⁻¹ (ERA-Interim/Land soil moisture) or 15 mBq m⁻² s⁻¹ (GLDAS (Global Land Data Assimilation System) Noah soil moisture) for the period 2006–2010. The corresponding seasonal variations with low fluxes in winter and high fluxes in summer range in the two realizations from ca. 7 to ca. 14 mBq m⁻² s⁻¹ and from ca. 11 to ca. 20 mBq m⁻² s⁻¹, respectively. These systematic differences highlight the importance of realistic soil moisture data for a reliable estimation of ²²²Rn exhalation rates. Comparison with observations suggests that the flux estimates based on the GLDAS Noah soil moisture model on average better represent observed fluxes.

• Global evaluation of ammonia bidirectional exchange and livestock diurnal variation schemes

  Bidirectional air–surface exchange of ammonia (NH₃) has been neglected in many air quality models. In this study, we implement the bidirectional exchange of NH₃ in the GEOS-Chem global chemical transport model. We also introduce an updated diurnal variability scheme for NH₃ livestock emissions and evaluate the recently developed MASAGE_NH₃ bottom-up inventory. While updated diurnal variability improves comparison of modeled-to-hourly in situ measurements in the southeastern USA, NH₃ concentrations decrease throughout the globe, up to 17 ppb in India and southeastern China, with corresponding decreases in aerosol nitrate by up to 7 μg m⁻³. The ammonium (NH₄⁺) soil pool in the bidirectional exchange model largely extends the NH₃ lifetime in the atmosphere. Including bidirectional exchange generally increases NH₃ gross emissions (7.1 %) and surface concentrations (up to 3.9 ppb) throughout the globe in July, except in India and southeastern China. In April and October, it decreases NH₃ gross emissions in the Northern Hemisphere (e.g., 43.6 % in April in China) and increases NH₃ gross emissions in the Southern Hemisphere. Bidirectional exchange does not largely impact NH₄⁺ wet deposition overall. While bidirectional exchange is fundamentally a better representation of NH₃ emissions from fertilizers, emissions from primary sources are still underestimated and thus significant model biases remain when compared to in situ measurements in the USA. The adjoint of bidirectional exchange has also been developed for the GEOS-Chem model and is used to investigate the sensitivity of NH₃ concentrations with respect to soil pH and fertilizer application rate. This study thus lays the groundwork for future inverse modeling studies to more directly constrain these physical processes rather than tuning bulk unidirectional NH₃ emissions.