[1] We explore the relationship between column aerosol optical thickness (AOT) derived from the Moderate Resolution Imaging SpectroRadiometer (MODIS) on the Terra/Aqua satellites and hourly fine particulate mass (PM 2.5 ) measured at the surface at seven locations in Jefferson county, Alabama for 2002. Results indicate that there is a good correlation between the satellite-derived AOT and PM 2.5 (linear correlation coefficient, R = 0.7) indicating that most of the aerosols are in the well-mixed lower boundary layer during the satellite overpass times. There is excellent agreement between the monthly mean PM 2.5 and MODIS AOT (R > 0.9), with maximum values during the summer months due to enhanced photolysis. The PM 2.5 has a distinct diurnal signature with maxima in the early morning (6:00 $ 8:00AM) due to increased traffic flow and restricted mixing depths during these hours. Using simple empirical linear relationships derived between the MODIS AOT and 24hr mean PM 2.5 we show that the MODIS AOT can be used quantitatively to estimate air quality categories as defined by the U.S. Environmental Protection Agency (EPA) with an accuracy of more than 90% in cloud-free conditions. We discuss the factors that affect the correlation between satellite-derived AOT and PM 2.5 mass, and emphasize that more research is needed before applying these methods and results over other areas.

No abstract

No abstract

The Amazon Basin provides an excellent environment for studying the sources, transformations, and properties of natural aerosol particles and the resulting links between biological processes and climate. With this framework in mind, the Amazonian Aerosol Characterization Experiment (AMAZE-08), carried out from 7 February to 14 March 2008 during the wet season in the central Amazon Basin, sought to understand the formation, transformations, and cloud-forming properties of fine- and coarse-mode biogenic aerosol particles, especially as related to their effects on cloud activation and regional climate. Special foci included (1) the production mechanisms of secondary organic components at a pristine continental site, including the factors regulating their temporal variability, and (2) predicting and understanding the cloud-forming properties of biogenic particles at such a site. In this overview paper, the field site and the instrumentation employed during the campaign are introduced. Observations and findings are reported, including the large-scale context for the campaign, especially as provided by satellite observations. New findings presented include: (i) a particle number-diameter distribution from 10 nm to 10 μm that is representative of the pristine tropical rain forest and recommended for model use; (ii) the absence of substantial quantities of primary biological particles in the submicron mode as evidenced by mass spectral characterization; (iii) the large-scale production of secondary organic material; (iv) insights into the chemical and physical properties of the particles as revealed by thermodenuder-induced changes in the particle number-diameter distributions and mass spectra; and (v) comparisons of ground-based predictions and satellite-based observations of hydrometeor phase in clouds. A main finding of AMAZE-08 is the dominance of secondary organic material as particle components. The results presented here provide mechanistic insight and quantitative parameters that can serve to increase the accuracy of models of the formation, transformations, and cloud-forming properties of biogenic natural aerosol particles, especially as related to their effects on cloud activation and regional climate

Abstract. The remote and high elevation regions of central Asia are influenced by black carbon (BC) emissions from a variety of locations. BC deposition contributes to melting of glaciers and questions exist, of both scientific and policy interest, as to the origin of the BC reaching the glaciers. We use the adjoint of the GEOS-Chem model to identify the location from which BC arriving at a variety of locations in the Himalayas and Tibetan Plateau originates. We then calculate its direct and snow-albedo radiative forcing. We analyze the seasonal variation in the origin of BC using an adjoint sensitivity analysis, which provides a detailed map of the location of emissions that directly contribute to black carbon concentrations at receptor locations. We find that emissions from northern India and central China contribute the majority of BC to the Himalayas, although the precise location varies with season. The Tibetan Plateau receives most BC from western and central China, as well as from India, Nepal, the Middle East, Pakistan and other countries. The magnitude of contribution from each region varies with season and receptor location. We find that sources as varied as African biomass burning and Middle Eastern fossil fuel combustion can significantly contribute to the BC reaching the Himalayas and Tibetan Plateau. We compute radiative forcing in the snow-covered regions and find the forcing due to the BC induced snow-albedo effect to vary from 5-15 W m −2 within the region, an order of magnitude larger than radiative forcing due to the direct effect, and with significant seasonal variation in the northern Tibetan Plateau. Radiative forcing fromCorrespondence to: D. L. Mauzerall (mauzeral@princeton.edu) reduced snow albedo likely accelerates glacier melting. Our analysis may help inform mitigation efforts to slow the rate of glacial melt by identifying regions that make the largest contributions to BC deposition in the Himalayas and Tibetan Plateau.

[1] Concurrent (August 2006) measurements of tropospheric NO 2 columns from OMI aboard Aura (1330 local overpass time) and SCIAMACHY aboard Envisat (1000 local overpass time) offer an opportunity to examine the consistency between the two instruments under tropospheric background conditions and the effect of different observing times. For scenes with tropospheric NO 2 columns <5.0 Â 10 15 molecules cm À2 , SCIAMACHY and OMI agree within 1.0-2.0 Â 10 15 molecules cm À2 , consistent with the detection limits of both instruments. We find evidence for a low bias of 0.2 Â 10 15 molecules cm À2 in OMI observations over remote oceans. Over the fossil fuel source regions at northern midlatitudes, we find that SCIAMACHY observes up to 40% higher NO 2 at 1000 local time (LT) than OMI at 1330 LT. Over biomass burning regions in the tropics, SCIAMACHY observes up to 40% lower NO 2 columns than OMI. These differences are present in the spectral fitting of the data (slant column) and are augmented in the fossil fuel regions and dampened in the tropical biomass burning regions by the expected increase in air mass factor as the mixing depth rises from 1000 to 1330 LT. Using a global 3-D chemical transport model (GEOS-Chem), we show that the 1000-1330 LT decrease in tropospheric NO 2 column over fossil fuel source regions can be explained by photochemical loss, dampened by the diurnal cycle of anthropogenic emissions that has a broad daytime maximum. The observed 1000-1330 LT NO 2 column increase over tropical biomass burning regions points to a sharp midday peak in emissions and is consistent with a diurnal cycle of emissions derived from geostationary satellite fire counts.

[1] We use an ensemble of satellite (MODIS), aircraft, and ground-based aerosol observations during the ICARTT field campaign over eastern North America in summer 2004 to (1) examine the consistency between different aerosol measurements, (2) evaluate a new retrieval of aerosol optical depths (AODs) and inferred surface aerosol concentrations (PM 2.5 ) from the MODIS satellite instrument, and (3) apply this collective information to improve our understanding of aerosol sources. The GEOS-Chem global chemical transport model (CTM) provides a transfer platform between the different data sets, allowing us to evaluate the consistency between different aerosol parameters observed at different times and locations. We use an improved MODIS AOD retrieval based on locally derived visible surface reflectances and aerosol properties calculated from GEOS-Chem. Use of GEOS-Chem aerosol optical properties in the MODIS retrieval not only results in an improved AOD product but also allows quantitative evaluation of model aerosol mass from the comparison of simulated and observed AODs. The aircraft measurements show narrower aerosol size distributions than those usually assumed in models, and this has important implications for AOD retrievals. Our MODIS AOD retrieval compares well to the ground-based AERONET data (R = 0.84, slope = 1.02), significantly improving on the MODIS c005 operational product. Inference of surface PM 2.5 from our MODIS AOD retrieval shows good correlation to the EPA-AQS data (R = 0.78) but a high regression slope (slope = 1.48). The high slope is seen in all AOD-inferred PM 2.5 concentrations (AERONET: slope = 2.04; MODIS c005: slope = 1.51) and could reflect a clear-sky bias in the AOD observations. The ensemble of MODIS, aircraft, and surface data are consistent in pointing to a model overestimate of sulfate in the mid-Atlantic and an underestimate of organic and dust aerosol in the southeastern United States. The sulfate overestimate could reflect an excessive contribution from aqueous-phase production in clouds, while the organic carbon underestimate could possibly be resolved by a new secondary pathway involving dicarbonyls.

Fertilized soils have large potential for production of soil nitrogen oxide (NOx=NO+NO2), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NOx contributes to formation of tropospheric ozone (O3), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NOx emissions in a high-temperature agricultural region of California. We also investigate whether soil NOx emissions are capable of influencing regional air quality. We report some of the highest soil NOx emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NOx emissions and NOx at the surface and in the troposphere. Adjusting the model to match NOx observations leads to elevated tropospheric O3. Our results suggest management can greatly reduce soil NOx emissions, thereby improving air quality.