M. Schaap

Anthropogenic black carbon and fine aerosol distribution over Europe

We present a model simulation for the year 1995 accounting for primary particles, which are an important component of fine aerosols over Europe. A new emission inventory for black carbon, (BC) was developed on the basis of the recent European emission inventory of anthropogenic primary particulate matter (Coordinated European Programme on Particulate Matter Emission Inventories, Projections and Guidance (CEPMEIP)). The annual BC emissions of Europe and the former Soviet Union for 1995 are estimated at 0.47 and 0.26 Tg C, respectively, with highest contributions from transport (off-road and on-road) and households. Modeled BC concentrations range from ≤0.05 μtg/m 3 in remote regions to more than 1 μtg/m3 over densely populated areas. The modeled BC concentration is about 25% of the total primary aerosol concentration. The primary aerosol fields were combined with previously calculated secondary aerosol concentrations to obtain an estimate of the total anthropogenic fine aerosol distribution. Modeled BC levels contribute only 4 10% to fine aerosol mass, whereas sulphate and nitrate contribute 25-50 and 5-35%, respectively. Comparison with experimental data revealed that the model underestimates PM2.5 levels, mostly caused, by the underprediction of total carbonaceous material (BC and OC) by a factor of e12. The underestimation can partly be explained by the influence of local emissions, measurement uncertainties, natural sources, and representation of wet deposition. However, the uncertainties associated with the emission inventory for BC (and total PM) may be the most important cause for the discrepancy. In comparison with previous studies, our BC emission estimate is a factor of 2 lower, caused by the choice of more recent emission factors. Therefore a better knowledge of emission factors is urgently needed to. estimate the BC (and PM) emissions reliably. Copyright 2004 by the American Geophysical Union.

Anthropogenic and natural constituents in particulate matter in the Netherlands

To develop mitigation strategies for reducing concentrations of both PM2.5 and PM10, the origin of particulate matter (PM) needs to be established. An intensive, one-year measurement campaign from August 2007 to August 2008 was carried out to determine the composition of PM 10 and PM2.5 at five locations in the Netherlands, aiming at reducing the uncertainties on the origin of PM. Generally, a considerable conformity in the chemical composition of PM 2.5 (and PM10) is observed. From all constituents present in PM 2.5, the secondary inorganic aerosol is the most dominant (42– 48%), followed by the total carbonaceous matter (22–37%). Contributions from sea salt (maximum 8%), mineral dust and metals (maximum 5%) are relatively low. For the first time, a detailed overview of the composition of the coarse fraction can be presented. Compared to the fine fraction, contributions of sea salt, mineral dust and metals are larger resulting in a more balanced distribution between the various constituents. Through mass closure a considerable part of the PM mass could be defined (PM 2.5: 80–94%). The chemical distribution on days with high PM levels shows a distinct increase in nitrate as well as in the unaccounted mass. Contributions of the other constituents remain equal or are lower (sea salt) when expressed in percentages. A correspondence between nitrate and the unaccounted mass is observed hinting at the presence of water on the filters. The contribution from natural sources in the Netherlands (at a rural station) was estimated to be 19 to 24% for PM 10 and 13 to 17% for PM2.5. Correspondence to: E. P. Weijers (weijers@ecn.nl)

Is regional air quality model diversity representative of uncertainty for ozone simulation

We examine whether seven state-of-the-art European regional air quality models provide daily ensembles of predicted ozone maxima that encompass observations. Using tools borrowed from the evaluation of ensemble weather forecasting, we analyze statistics of simulated ensembles of ozone daily maxima over an entire summer season. Although the model ensemble overestimates ozone, the distribution of simulated concentrations is representative of the uncertainty. The spread of simulations is due to random fluctuations resulting from differences in model formulations and input data, but also to the spread between individual model systematic biases. The ensemble average skill increases as the spread decreases. The skill of the ensemble in giving probabilistic predictions of threshold exceedances is also demonstrated. These results allow for optimism about the ability of this ensemble to simulate the uncertainty of the impact of emission control scenarios.

Construction of Satellite Derived PM2.5 Maps using the Relationship between AOD and PM2.5 at the Cabauw Experimental Site for Atmospheric Research (CESAR) - The Netherlands

To acquire daily estimates of PM2.5 distributions based on satellite data one depends critically on a well established relation between AOD and ground level PM2.5. In this study we aimed to experimentally establish the AOD-PM2.5 relationship for the Netherlands. For that purpose an experiment was set-up at the AERONET site Cabauw. The average PM2.5 concentration during this ten month study was 18 mug/ m3, which confirms that the Netherlands are characterized by a high PM burden. A first inspection of the AERONET level 1.5 (L1.5) AOD and PM2.5 data at Cabauw showed a low correlation between the two properties. However, after screening for cloud contamination in the AERONET L1.5 data, the correlation improved substantially. When also constraining the dataset to data points acquired around noon, the correlation between AOD and PM2.5 amounted to R 2 =0.6 for situations with fair weather. This indicates that AOD data contain information about the temporal evolution of PM2.5. We used lidar observations to detect residual cloud contamination in the AERONET L1.5 data. Comparison of our cloud-screed L1.5 with AERONET L2 data that became available near the end of the study showed favorable agreement. The final relation found for Cabauw is PM2.5 = 124.5* AOD - 0.34 (with PM2.5 in mug/m3) and is valid for fair weather conditions. The relationship determined between MODIS AOD and ground level PM2.5 at Cabauw is very similar to that based on the much larger dataset from the sun photometer data, after correcting for a systematic overestimation of the MODIS data of 0.05. We applied the relationship to a MODIS composite map to assess the PM2.5 distribution over the Netherlands for the first time based on MODIS data only.

Aerosol optical depth over Europe: Satellite retrieval and modeling

Aerosol optical depth (AOD) and Angstrom coefficients over Europe retrieved from satellite data for August 1997 provide information on the spatial variations of these aerosol properties. The AOD results are compared with initial results from model calculations, showing the relative influences of sulphate and nitrate aerosol.

Parameterization of oceanic whitecap fraction based on satellite observations

Satellite-based whitecap fraction (W) data have been used to predict sea spray aerosol (SSA) emission rates. This allows to evaluate how an account for natural variability of whitecaps in the W parameterization would affect SSA mass flux predictions when using a sea spray source function (SSSF) based on the whitecap method. Data set containing W data for 2006 together with matching wind speed U10 and sea surface temperature (SST) T has been used. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global scale assessment of the data set yielded approximately quadratic correlation between W and U10. A regional scale analysis yielded a new W(U10, T) parameterization which explicitly accounted for the effect of SST on W. The analysis of W values obtained with the new W(U10) and W(U10, T) parameterizations indicates that the influence of secondary factors on W is for the largest part embedded in the exponent of the wind speed dependence. In addition, the W(U10, T) parameterization is capable to model the spread (or variability) of the satellite-based W data. The satellite-based parameterization W(U10, T) was applied in an SSSF to estimate the global SSA emission rate. The thus obtained SSA production rate is within previously reported estimates, however with distinctly different spatial distribution.

Can We Explain the Observed Decrease in Secondary Inorganic Aerosol and Its Precursors Between 1990 and 2009 over Europe Using LOTOS-EUROS?

In this study we investigate the ability of the Chemistry Transport Model (CTM) LOTOS-EUROS to explain the observed decrease in secondary inorganic aerosol (SIA) and its precursors between 1990 and 2009 over Europe. The model explicitly accounts for cloud chemistry and aerosol thermodynamics. The results have shown that the model largely captures the observed trends in SIA and its precursors’ concentrations while it underestimates the interannual variability. Using a source-apportionment module the amount of SIA formed per unit emission was traced for a number of regions. The results show 20–50 % more efficient SO4 2− formation in 2009 compared to 1990, whereas the change in NO3 − formation per unit NOx emission is lower (−10 % to +20 %) for the same time period.

Comparison between satellite retrieved aerosol optical thickness and results obtained from the LOTOS model

Aerosols affect the Earth radiation balance by absorbing and scattering solar radiation and changing the albedo and the lifetime of clouds. Aerosols also play a role in health-related problems. The aerosol lifetime varies from a few days 10 about a week and their quite strong but rather Iocalised sources produce highly variable aerosol concentrations in space and time. Satellite remote sensing can provide the spatial and temporal resolution to monitor such variations, However, usually only total column-integrated aerosol properties are obtained that are useful for, e.g., climate applications. For other purposes, the satellite data interpretation requires the use of a transport model. Therefore sulphate and nitrate aerosols are introduced in the LOTOS model (Builtjes, 1992) and preliminary results are used to interpret the relative contribution of these aerosol types to the observed aerosol optical thickness (AOT)