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Sources and production of organic aerosol in Mexico City: insights from the combination of a chemical transport model (PMCAMx-2008) and measurements during MILAGRO

Urban areas are large sources of organic aerosols and their precursors. Nevertheless, the contributions of primary (POA) and secondary organic aerosol (SOA) to the observed particulate matter levels have been difficult to quantify. In this study the three-dimensional chemical transport model PMCAMx-2008 is used to investigate the temporal and geographic variability of organic aerosol in the Mexico City Metropolitan Area (MCMA) during the MILAGRO campaign that took place in the spring of 2006. The organic module of PMCAMx-2008 includes the recently developed volatility basis-set framework in which both primary and secondary organic components are assumed to be semi-volatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. The MCMA emission inventory is modified and the POA emissions are distributed by volatility based on dilution experiments. The model predictions are compared with observations from four different types of sites, an urban (T0), a suburban (T1), a rural (T2), and an elevated site in Pico de Tres Padres (PTP). The performance of the model in reproducing organic mass concentrations in these sites is encouraging. The average predicted PM1 organic aerosol (OA) concentration in T0, T1, and T2 is 18 μg m−3, 11.7 μg m−3, and 10.5 μg m−3 respectively, while the corresponding measured values are 17.2 μg m−3, 11 μg m−3, and 9 μg m−3. The average predicted locally-emitted primary OA concentrations, 4.4 μg m−3 at T0, 1.2 μg m−3 at T1 and 1.7 μg m−3 at PTP, are in reasonably good agreement with the corresponding PMF analysis estimates based on the Aerosol Mass Spectrometer (AMS) observations of 4.5, 1.3, and 2.9 μg m−3 respectively. The model reproduces reasonably well the average oxygenated OA (OOA) levels in T0 (7.5 μg m−3 predicted versus 7.5 μg m−3 measured), in T1 (6.3 μg m−3 predicted versus 4.6 μg m−3 measured) and in PTP (6.6 μg m−3 predicted versus 5.9 μg m−3 measured). The rest of the OA mass (6.1 μg m−3 and 4.2 μg m−3 in T0 and T1 respectively) is assumed to originate from biomass burning activities and is introduced to the model as part of the boundary conditions. Inside Mexico City (at T0), the locally-produced OA is predicted to be on average 60 % locally-emitted primary (POA), 6 % semi-volatile (S-SOA) and intermediate volatile (I-SOA) organic aerosol, and 34 % traditional SOA from the oxidation of VOCs (V-SOA). The average contributions of the OA components to the locally-produced OA for the entire modelling domain are predicted to be 32 % POA, 10 % S-SOA and I-SOA, and 58 % V-SOA. The long range transport from biomass burning activities and other sources in Mexico is predicted to contribute on average almost as much as the local sources during the MILAGRO period.
Aerosol effects on the photochemistry in Mexico City during MCMA-2006/MILAGRO campaign

In the present study, the impact of aerosols on the photochemistry in Mexico City is evaluated using the WRF-CHEM model for the period from 24 to 29 March during the MCMA-2006/MILAGRO campaign. An aerosol radiative module has been developed with detailed consideration of aerosol size, composition, and mixing. The module has been coupled into the WRF-CHEM model to calculate the aerosol optical properties, including optical depth, single scattering albedo, and asymmetry factor. Calculated aerosol optical properties are in good agreement with the surface observations and aircraft and satellite measurements during daytime. In general, the photolysis rates are reduced due to the absorption by carbonaceous aerosols, particularly in the early morning and late afternoon hours with a long aerosol optical path. However, with the growth of aerosol particles and the decrease of the solar zenith angle around noontime, aerosols can slightly enhance photolysis rates when ultraviolet (UV) radiation scattering dominates UV absorption by aerosols at the lower-most model layer. The changes in photolysis rates due to aerosols lead to about 2–17 % surface ozone reduction during daytime in the urban area in Mexico City with generally larger reductions during early morning hours near the city center, resulting in a decrease of OH level by about 9 %, as well as a decrease in the daytime concentrations of nitrate and secondary organic aerosols by 5–6 % on average. In addition, the rapid aging of black carbon aerosols and the enhanced absorption of UV radiation by organic aerosols contribute substantially to the reduction of photolysis rates.
Retrievals of chlorine chemistry kinetic parameters from Antarctic ClO microwave radiometer measurements

Key kinetic parameters governing the partitioning of chlorine species in the Antarctic polar stratosphere were retrieved from 28 days of chlorine monoxide (ClO) microwave radiometer measurements made during the late winter/early spring of 2005 at Scott Base (77.85° S, 166.75° E). During day-time the loss of the ClO dimer chlorine peroxide (ClOOCl) occurs mainly by photolysis. Some time after sunrise, a photochemical equilibrium is established and the ClO/ClOOCl partitioning is determined by the ratio of the photolysis frequency, J, and the dimer formation rate, kf. The values of J and kf from laboratory studies remain uncertain to a considerable extent, and as a complement to these ongoing studies, the goal of this work is to provide a constraint on that uncertainty based on observations of ClO profiles in the Antarctic. First an optimal estimation technique was used to derive J/kf ratios for a range of Keq values. The optimal estimation forward model was a photochemical box model that takes J, kf, and Keq as inputs, together with a priori profiles of activated chlorine (ClOx = ClO+2×ClOOCl), profiles of ozone, temperature, and pressure. JPL06 kinetics are used as a priori in the optimal estimation and for all other chemistry in the forward model. Using the more recent JPL09 kinetics results in insignificant differences in the retrieved value of J/kf. A complementary approach was used to derive the optimal kinetic parameters; the full parameter space of J, kf, Keq and ClOx was sampled to find the minimum in differences between measured and modelled ClO profiles. Furthermore, values of Keq up to 2.0 times larger than recommended by JPL06 were explored to test the sensitivity of the J/kf ratio to changes in Keq. The results show that the retrieved J/kf ratios bracket the range of 1.23 to 1.97 times the J/kf value recommended by JPL06 over the range of Keq values considered. The retrieved J/kf ratios lie in the lower half of the large uncertainty range of J/kf recommended by JPL06 and towards the upper portion of the smaller uncertainty range recommended by JPL09.
Source apportionment of arsenic in atmospheric dust fall out in an urban residential area, Raipur, Central India

The components and quantities of atmospheric dust fallout have been reported to be the pollution indicator of large urban areas. The multiplicity and complexity of sources of atmospheric dusts in urban regions has put forward the need of source apportionment of these sources indicating their contribution to specific environmental receptor. The study presented here is focused on investigation of source contribution estimates of Arsenic in urban dust fallout in an urban-industrial area, Raipur, India. Source-receptor based representative sampling plan using longitudinal study design has been adopted. Six sampling sites have been identified on the basis of land use for development plan of anthropogenic activities and factors related to the transportation and dispersion pattern of atmospheric dusts. Source apportionment has been done using Chemical Mass Balance (CMB 8). Good fit parameters and relative source contribution has been analyzed and documented. Dominance of coal fired industries sources on arsenic levels measured at selected ambient residential receptors compared to line sources has been observed. Road-traffic has shown highest contribution of dust at indoor houses and out door-street automobile exhaust has shows highest contribution for arsenic. The results of CMB output and regression data of source-receptor dust matrices have shown comparable pattern.
A numerical study of mountain waves in the upper troposphere and lower stratosphere

A numerical study of mountain waves in the Upper Troposphere and Lower Stratosphere (UTLS) is presented for two Intensive Observational Periods (IOPs) of the Terrain-induced Rotor Experiment (T-REX). The simulations use the Weather Research and Forecasting (WRF) model and a microscale model that is driven by the finest WRF nest. During IOP8, the simulation results reveal presence of perturbations with short wavelengths in zones of strong vertical wind shear in the UTLS that cause a reversal of momentum fluxes. The spectral properties of these perturbations and the attendant vertical profiles of heat and momentum fluxes show strong divergence near the tropopause indicating that they are generated by shear instability along shear lines locally induced by the primary mountain wave originating from the lower troposphere. This is further confirmed by results of an idealized simulation initialized with the temperature and wind profiles obtained from the microscale model. For IOP6, we analyze distributions of O3 and CO observed in aircraft measurements. They show small scale fluctuations with amplitudes and phases that vary along the path of the flight. Detailed comparisons between these fluctuations and the observed vertical velocity show that the behavior of these short fluctuations is due not only to the vertical motion, but also to the local mean vertical gradients where the waves evolve, which are modulated by larger variations. The microscale model simulation results show favorable agreement with in situ radiosonde and aircraft observations. The high vertical resolution offered by the microscale model is found to be critical for resolution of smaller scale processes such as formation of inversion layer associated with trapped lee waves in the troposphere, and propagating mountain waves in the lower stratosphere.
Chemical sensor resolution requirements for near-surface measurements of turbulent fluxes

Businger and Delany (1990) presented an approach to estimate the sensor resolution required to limit the contribution of the uncertainty in the chemical concentration measurement to uncertainty in the flux measurement to 10 % for eddy covariance, gradient, and relaxed eddy accumulation flux measurement methods. We describe an improvement to their approach to estimate required sensor resolution for the covariance method, and include disjunct eddy covariance. In addition, we provide data to support selection of a form for the dimensionless scalar standard deviation similarity function based on observations of the variance of water vapor fluctuations from recent field experiments. We also redefine the atmospheric parameter of Businger and Delany in a more convenient, dimensionless form. We introduce a "chemical parameter" based on transfer velocity parameterizations. Finally, we provide examples in which the approach is applied to measurement of carbon dioxide, dimethylsulfide, and hexachlorobenzene fluxes over water. The information provided here will be useful to plan field measurements of atmosphere-surface exchange fluxes of trace gases.
Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts

A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather simulations using model resolutions of 10 km and 2 km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the vertical distribution of the emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation led to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and cloud microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 h of the integration. During the afternoon, storms were of convective nature and appeared significantly stronger, probably as a result of both the interaction of aerosols with radiation (through an increase in CAPE) as well as the interaction with cloud microphysics.
Homogenous nucleation of sulfuric acid and water at close to atmospherically relevant conditions

In this study the homogeneous nucleation rates in the system of sulfuric acid and water were measured by using a flow tube technique. The goal was to directly compare particle formation rates obtained from atmospheric measurements with nucleation rates of freshly nucleated particles measured with particle size magnifier (PSM) which has detection efficiency of unity for particles having mobility diameter of 1.5 nm. The gas phase sulfuric acid concentration in this study was measured with the chemical ionization mass spectrometer (CIMS), commonly used in field measurements. The wall losses of sulfuric acid were estimated from measured concentration profiles along the flow tube. The initial concentrations of sulfuric acid estimated from loss measurements ranged from 108 to 3 × 109 molecules cm−3. The nucleation rates obtained in this study cover about three orders of magnitude from 10−1 to 102 cm−3 s−1 for commercial ultrafine condensation particle counter (UCPC) TSI model 3025A and from 101 to 104 cm−3 s−1 for PSM. The nucleation rates and the slopes (dlnJ/dln [H2SO4]) show satisfactory agreement when compared to empirical kinetic and activation models and the latest atmospheric nucleation data. To the best of our knowledge, this is the first experimental work providing temperature dependent nucleation rate measurements using a high efficiency particle counter with a cut-off-size of 1.5 nm together with direct measurements of gas phase sulfuric acid concentration.
Future emissions from shipping and petroleum activities in the Arctic

The Arctic sea-ice is retreating faster than predicted by climate models and could become ice free during summer this century. The reduced sea-ice extent may effectively "unlock" the Arctic Ocean to increased human activities such as transit shipping and expanded oil and gas production. Travel time between Europe and the north Pacific Region can be reduced by up to 50 % with low sea-ice levels and the use of this route could increase substantially as the sea-ice retreats. Oil and gas activities already occur in the Arctic region and given the large undiscovered petroleum resources increased activity could be expected with reduced sea-ice. We use a bottom-up shipping model and a detailed global energy market model to construct emission inventories of Arctic shipping and petroleum activities in 2030 and 2050 given estimated sea-ice extents. The emission inventories are on a 1×1 degree grid and cover both short-lived components (SO2, NOx, CO, NMVOC, BC, OC) and the long-lived greenhouse gases (CO2, CH4, N2O). We find rapid growth in transit shipping due to increased profitability with the shorter transit times compensating for increased costs in traversing areas of sea-ice. Oil and gas production remains relatively stable leading to reduced emissions from emission factor improvements. The location of oil and gas production moves into locations requiring more ship transport relative to pipeline transport, leading to rapid emissions growth from oil and gas transport via ship. Our emission inventories for the Arctic region will be used as input into chemical transport, radiative transfer, and climate models to quantify the role of Arctic activities in climate change compared to similar emissions occurring outside of the Arctic region.
Bayesian statistical modeling of spatially correlated error structure in atmospheric tracer inverse analysis

We present and discuss the use of Bayesian modeling and computational methods for atmospheric chemistry inverse analyses that incorporate evaluation of spatial structure in model-data residuals. Motivated by problems of refining bottom-up estimates of source/sink fluxes of trace gas and aerosols based on satellite retrievals of atmospheric chemical concentrations, we address the need for formal modeling of spatial residual error structure in global scale inversion models. We do this using analytically and computationally tractable conditional autoregressive (CAR) spatial models as components of a global inversion framework. We develop Markov chain Monte Carlo methods to explore and fit these spatial structures in an overall statistical framework that simultaneously estimates source fluxes. Additional aspects of the study extend the statistical framework to utilize priors on source fluxes in a physically realistic manner, and to formally address and deal with missing data in satellite retrievals. We demonstrate the analysis in the context of inferring carbon monoxide (CO) sources constrained by satellite retrievals of column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument on the TERRA satellite, paying special attention to evaluating performance of the inverse approach using various statistical diagnostic metrics. This is developed using synthetic data generated to resemble MOPITT data to define a proof-of-concept and model assessment, and then in analysis of real MOPITT data. These studies demonstrate the ability of these simple spatial models to substantially improve over standard non-spatial models in terms of statistical fit, ability to recover sources in synthetic examples, and predictive match with real data.