Search

NH3 retrievals from the NASA Tropospheric Emission Spectrometer (TES), as well as surface and aircraft observations of NH3(g) and submicron NH4(p), are to used to evaluate modelled concentrations of NH3(g) and NH4(p) from the Community Multiscale Air Quality (CMAQ) model in the San Joaquin Valley (SJV) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) campaign. We find that simulations of NH3 driven with the California Air Resources Board (CARB) CalNex emission inventory are qualitatively and spatially consistent with TES satellite observations, with a correlation coefficient (r2) of 0.54. However, the surface observations at Bakersfield indicate a missing diurnal cycle in the model bias, with CMAQ overestimating surface NH3 at night and underestimating it during the day. The surface, satellite, and aircraft observations all suggest that the afternoon NH3 emissions in the CARB inventory are underestimated by at least a factor of two, while the night-time overestimate of NH3(g) is likely due to a combination of overestimated NH3 emissions, underestimated deposition, and insufficient vertical mixing in the WRF meteorological fields used to drive CMAQ. We used the surface observations at Bakersfield to derive an empirical diurnal cycle of NH3 emissions in the SJV, in which night-time and midday emissions differed by about a factor of 4.5. Adding this diurnal profile to the CMAQ simulations while keeping the daily NH3 emissions constant at the CARB values significantly improved the model performance at night, but sizable errors (up to 15 ppbv) in night-time NH3 remain, likely due to remaining errors in vertical mixing at night. The model performance is slightly degraded during the afternoon when the diurnal cycle is adjusted, but this may reflect relatively small (∼ 20 %) errors in the total NH3 emissions rather than remaining errors in the diurnal cycle. Running CMAQv5.0.2 with bi-directional NH3 flux also improves model performance on a similar scale, while combining bi-directional NH3 fluxes and adjusted emissions significantly reduces the model bias at night. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NOx) have fallen steadily across the US over the last fifteen years. At the same time, due to patterns diesel truck activities, NOx concentrations decrease on weekends relative to weekdays, largely without co-occurring changes in other gas-phase emissions. These trends taken together provide two independent constraints on the role of NOx in the nonlinear chemistry of atmospheric oxidation. In this context, we interpret interannual trends in wintertime ammonium nitrate (NH4NO3) in the San Joaquin Valley of California, a location with the worst aerosol pollution in the US and where a large portion of aerosol mass is NH4NO3. Here, we show that NOx reductions have simultaneously decreased nighttime and increased daytime NH4NO3 production over the last decade. We find a substantial decrease in NH4NO3 since 2000 and conclude that this decrease is due to reduced nitrate radical-initiated production at night in residual layers that are decoupled from fresh emissions at the surface. Further reductions in NOx are imminent in California, and nationwide, and we make a quantitative prediction of the response of NH4NO3. We show that the combination of rapid chemical production and efficient NH4NO3 loss via deposition of gas-phase nitric acid implies high aerosol days in cities in the San Joaquin Valley air basin are responsive to local changes in NOx within those individual cities. Our calculations indicate that large decreases in NOx in the future will not only lower wintertime NH4NO3 concentrations, they will also cause a transition in the dominant NH4NO3 source from nighttime to daytime chemistry. [ABSTRACT FROM AUTHOR]

The wealth of air quality information provided by satellite infrared observations of ammonia (NH3), carbon monoxide (CO), formic acid (HCOOH), and methanol (CH3OH) is currently being explored and used for number of applications, especially at regional or global scales. These applications include air quality monitoring, trend analysis, emissions, and model evaluation. This study provides one of the first direct validations of Tropospheric Emission Spectrometer (TES) satellite retrieved profiles of NH3, CH3OH, and HCOOH through comparisons with coincident aircraft profiles. The comparisons are performed over the Canadian oil sands region during the intensive field campaign (August-September 2013) in support of the Joint Canada-Alberta Implementation Plan for the Oil Sands Monitoring (JOSM). The satellite/aircraft comparisons over this region during this period produced errors of: (i) +0.08±0.25 ppbv for NH3, (ii) +7.5±23 ppbv for CO, (iii) +0.19±0.46 ppbv for HCOOH, and (iv) -1.1±0.39 ppbv for CH3OH. These values mostly agree with previously estimated retrieval errors; however, the relatively large negative bias in CH3OH and the significantly greater positive bias for larger HCOOH and CO values observed during this study warrant further investigation. Satellite and aircraft ammonia observations during the field campaign are also used in an initial effort to perform preliminary evaluations of Environment Canada's Global Environmental Multi-scale - Modelling Air quality and CHemistry (GEM-MACH) air quality mod elling system at high-resolution (2.5km×2.5 km). These initial results indicate model under-prediction of ~ 0.6 ppbv (~ 60 %) for NH3, during the field campaign period. The TES-model CO comparison differences are ~ +20 ppbv (~ +20 %), but given that under these conditions the TES/aircraft comparisons also show a small positive TES CO bias indicates that the overall model under-prediction of CO is closer to ~ 10% at 681 hPa (~ 3 km) during this period. [ABSTRACT FROM AUTHOR]

We use the Global Modeling Initiative (GMI) chemical transport model with a cloud droplet parameterization adjoint to quantify the sensitivity of cloud droplet number concentration to uncertainties in predicting CCN concentrations. Published CCN closure prediction uncertainties for six different sets of simplifying compositional and mixing state assumptions are used as proxies for modeled CCN uncertainty arising from application of those scenarios. It is found that cloud droplet number concentrations are fairly insensitive to CCN-active aerosol number concentrations over the continents (∂Nd/∂Nd ~ 10-30%), but the sensitivities exceed 70% in pristine regions such as the Alaskan Arctic and remote oceans. Since most of the anthropogenic indirect forcing is concentrated over the continents, this work shows that the application of Köhler theory and attendant simplifying assumptions in models is not a major source of uncertainty in predicting cloud droplet number or anthropogenic aerosol indirect forcing for the liquid, stratiform clouds simulated in these models. However, it does highlight the sensitivity of some remote areas to pollution brought into the region via long-range transport (e.g. biomass burning) or from seasonal biogenic sources (e.g. phytoplankton as a source of dimethylsulfide in the southern oceans). Since these transient processes are not captured well by the climatological emissions inventories employed by current large-scale models, the uncertainties in aerosol-cloud interactions during these events could be much larger than those uncovered here. This finding motivates additional measurements in these pristine regions, which have received little attention to date, in order to quantify the impact of, and uncertainty associated with, transient processes in effecting changes in cloud properties. [ABSTRACT FROM AUTHOR]

The article presents a study on high-order decoupled direct method in three dimensions for particulate matter (HDDM-3D/PM) development. It mentions its enforcement towards advanced sensitivity analysis in the Community Multiscale Air Quality (CMAQ) model. It also notes its creation for investigating the inorganic aerosol module of the model, ISORROPIA.

We present the development of ANISORROPIA, the discrete adjoint of the ISORROPIA thermodynamic equilibrium model that treats the Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed. aerosol system, and we demonstrate its sensitivity analysis capabilities. ANISORROPIA calculates sensitivities of an inorganic species in aerosol or gas phase with respect to the total concentrations of each species present with only a two-fold increase in computational time over the forward model execution. Due to the highly nonlinear and discontinuous solution surface of ISORROPIA, evaluation of the adjoint required a new, complex-variable version of the the model, which determines first-order sensitivities with machine precision and avoids cancellation errors arising from finite difference calculations. The adjoint is verified over an atmospherically relevant range of concentrations, temperature, and relative humidity. We apply ANISORROPIA to recent field campaign results from Atlanta, GA, USA, and Mexico City, Mexico, to characterize the inorganic aerosol sensitivities of these distinct urban air masses. The variability in the relationship between PM2.5 mass and precursor concentrations shown has important implications for air quality and climate. ANISORROPIA enables efficient elucidation of aerosol concentration dependence on aerosol precursor emissions in the context of atmospheric chemical transport model adjoints. [ABSTRACT FROM AUTHOR]