Relation of air mass history to nucleation events in Po Valley, Italy, using back trajectories analysis

International audienceIn this paper, we study the transport of air masses to San Pietro Capofiume (SPC) in Po Valley, Italy, by means of back trajectories analysis. Our main aim is to investigate whether air masses originate over different regions on nucleation event days and on nonevent days, during three years when nucleation events have been continuously recorded at SPC. The results indicate that nucleation events occur frequently in air masses arriving from Central Europe, whereas event frequency is much lower in the air transported from southern directions and from the Atlantic Ocean. We also analyzed the behaviour of meteorological parameters during 96 h transport to SPC, and found that, on average, event trajectories undergo stronger subsidence during the last 12 h before the arrival at SPC than nonevent trajectories. This causes a reversal in the temperature and relative humidity (RH) differences between event and nonevent trajectories: between 96 and 12 h back time, temperature is lower and RH is higher for event than nonevent trajectories and between 12 and 0 h vice versa. Boundary layer mixing is stronger along the event trajectories compared to nonevent trajectories. The absolute humidity (AH) is similar for the event and nonevent trajectories between about 96 h and about 60 h back time, but after that, the event trajectories AH becomes lower due to stronger rain. We also studied transport of SO2 to SPC, and conclude that although sources in Po Valley most probably dominate the measured concentrations, certain Central and Eastern European sources also make a substantial contribution

Classifying previously undefined days from eleven years of aerosol-particle-size distribution data from the SMEAR II station, Hyytiälä, Finland

Peer reviewe

Indirect estimation of absorption properties for fine aerosol particles using AATSR observations : a case study of wildfires in Russia in 2010

The Advanced Along-Track Scanning Radiometer (AATSR) on board the ENVISAT satellite is used to study aerosol properties. The retrieval of aerosol properties from satellite data is based on the optimized fit of simulated and measured reflectances at the top of the atmosphere (TOA). The simulations are made using a radiative transfer model with a variety of representative aerosol properties. The retrieval process utilizes a combination of four aerosol components, each of which is defined by their (lognormal) size distribution and a complex refractive index: a weakly and a strongly absorbing fine-mode component, coarse mode sea salt aerosol and coarse mode desert dust aerosol). These components are externally mixed to provide the aerosol model which in turn is used to calculate the aerosol optical depth (AOD). In the AATSR aerosol retrieval algorithm, the mixing of these components is decided by minimizing the error function given by the sum of the differences between measured and calculated path radiances at 3-4 wavelengths, where the path radiances are varied by varying the aerosol component mixing ratios. The continuous variation of the fine-mode components allows for the continuous variation of the fine-mode aerosol absorption. Assuming that the correct aerosol model (i.e. the correct mixing fractions of the four components) is selected during the retrieval process, also other aerosol properties could be computed such as the single scattering albedo (SSA). Implications of this assumption regarding the ratio of the weakly/strongly absorbing fine-mode fraction are investigated in this paper by evaluating the validity of the SSA thus obtained. The SSA is indirectly estimated for aerosol plumes with moderate-to-high AOD resulting from wildfires in Russia in the summer of 2010. Together with the AOD, the SSA provides the aerosol absorbing optical depth (AAOD). The results are compared with AERONET data, i.e. AOD level 2.0 and SSA and AAOD inversion products. The RMSE (root mean square error) is 0.03 for SSA and 0.02 for AAOD lower than 0.05. The SSA is further evaluated by comparison with the SSA retrieved from the Ozone Monitoring Instrument (OMI). The SSA retrieved from both instruments show similar features, with generally lower AATSR-estimated SSA values over areas affected by wildfires.Peer reviewe

Nucleation and growth of new particles in Po Valley, Italy

Aerosol number distribution measurements are reported at San Pietro Capofiume (SPC) station (44°39' N, 11°37' E) for the time period 2002–2005. The station is located in Po Valley, the largest industrial, trading and agricultural area in Italy with a high population density. New particle formation was studied based on observations of the particle size distribution, meteorological and gas phase parameters. The nucleation events were classified according to the event clarity based on the particle number concentrations, and the particle formation and growth rates. Out of a total of 769 operational days from 2002 to 2005 clear events were detected on 36% of the days whilst 33% are clearly non-event days. The event frequency was high during spring and summer months with maximum values in May and July, whereas lower frequency was observed in winter and autumn months. The average particle formation and growth rates were estimated as ~6 cm^−3 s^−1 and ~7 nm h^−1, respectively. Such high growth and formation rates are typical for polluted areas. Temperature, wind speed, solar radiation, SO₂ and O₃ concentrations were on average higher on nucleation days than on non-event days, whereas relative and absolute humidity and NO₂ concentration were lower; however, seasonal differences were observed. Backtrajectory analysis suggests that during majority of nucleation event days, the air masses originate from northern to eastern directions. We also study previously developed nucleation event correlations with environmental variables and show that they predict Po Valley nucleation events with variable success

Determination of land surface reflectance using the AATSR dual-view capability

Peer reviewe

An airborne regional carbon balance for central amazonia

We obtained regional estimates of surface CO2 exchange rates using atmospheric boundary layer budgeting techniques above tropical forest near Manaus, Brazil. Comparisons were made with simultaneous measurements from two eddy covariance towers below. Although there was good agreement for daytime measurements, large differences emerged for integrating periods dominated by the night-time fluxes. These results suggest that a systematic underestimation of night time respiratory effluxes may be responsible for the high Amazonian carbon sink suggested by several previous eddy covariance studies. Large CO2 fluxes from riverine sources or high respiratory losses from recently disturbed forests do not need to be invoked in order to balance the carbon budget of the Amazon. Our results do not, however, discount some contribution of these processes to the overall Amazon carbon budget

Aerosol retrieval experiments in the ESA Aerosol_cci project

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust)

Atmospheric data over a solar cycle: no connection between galactic cosmic rays and new particle formation

Aerosol particles affect the Earth's radiative balance by directly scattering and absorbing solar radiation and, indirectly, through their activation into cloud droplets. Both effects are known with considerable uncertainty only, and translate into even bigger uncertainties in future climate predictions. More than a decade ago, variations in galactic cosmic rays were suggested to closely correlate with variations in atmospheric cloud cover and therefore constitute a driving force behind aerosol-cloud-climate interactions. Later, the enhancement of atmospheric aerosol particle formation by ions generated from cosmic rays was proposed as a physical mechanism explaining this correlation. Here, we report unique observations on atmospheric aerosol formation based on measurements at the SMEAR II station, Finland, over a solar cycle (years 1996–2008) that shed new light on these presumed relationships. Our analysis shows that none of the quantities related to aerosol formation correlates with the cosmic ray-induced ionisation intensity (CRII). We also examined the contribution of ions to new particle formation on the basis of novel ground-based and airborne observations. A consistent result is that ion-induced formation contributes typically significantly less than 10% to the number of new particles, which would explain the missing correlation between CRII and aerosol formation. Our main conclusion is that galactic cosmic rays appear to play a minor role for atmospheric aerosol formation events, and so for the connected aerosol-climate effects as well

Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 2: AOD time series for 1995–2017 combined from ATSR ADV and MODIS C6.1 and AOD tendency estimations

Understanding long-term variations in aerosol loading is essential for evaluating the health and climate effects of airborne particulates as well as the effectiveness of pollution control policies. The expected satellite lifetime is about 10 to 15 years. Therefore, to study the variations of atmospheric constituents over longer periods information from different satellites must be utilized.Here we introduce a method to construct a combined annual and seasonal long time series of AOD at 550 nm using the Along-Track Scanning Radiometers (ATSR: ATSR-2 and AATSR combined) and the MODerate resolution Imaging Spectroradiometer on Terra (MODIS/Terra), which together cover the 1995–2017 period. The long-term (1995–2017) combined AOD time series are presented for all of mainland China, for southeastern (SE) China and for 10 selected regions in China. Linear regression was applied to the combined AOD time series constructed for individual L3 (1°&thinsp; × &thinsp;1°) pixels to estimate the AOD tendencies for two periods: 1995–2006 (P1) and 2011–2017 (P2), with respect to the changes in the emission reduction policies in China.During P1, the annually averaged AOD increased by 0.006 (or 2&thinsp;% of the AOD averaged over the corresponding period) per year across all of mainland China, reflecting increasing emissions due to rapid economic development. In SE China, the annual AOD positive tendency in 1995–2006 was 0.014 (3&thinsp;%) per year, reaching maxima (0.020, or 4&thinsp;%, per year) in Shanghai and the Pearl River Delta regions. After 2011, during P2, AOD tendencies reversed across most of China with the annually averaged AOD decreasing by −0.015 (−6&thinsp;%) per year in response to the effective reduction of the anthropogenic emissions of primary aerosols, SO2 and NOx. The strongest AOD decreases were observed in the Chengdu (−0.045, or −8&thinsp;%, per year) and Zhengzhou (−0.046, or −9&thinsp;%, per year) areas, while over the North China Plain and coastal areas the AOD decrease was lower than −0.03 (approximately −6&thinsp;%) per year. In the less populated areas the AOD decrease was small.The AOD tendency varied by both season and region. The increase in the annually averaged AOD during P1 was mainly due to an increase in summer and autumn in SE China (0.020, or 4&thinsp;%, and 0.016, or 4&thinsp;%, per year, respectively), while during winter and spring the AOD actually decreased over most of China. The AOD negative tendencies during the 2011–2017 period were larger in summer than in other seasons over the whole of China (ca. −0.021, or −7&thinsp;%, per year) and over SE China (ca. −0.048, or −9&thinsp;%, per year).The long-term AOD variations presented here show a gradual decrease in the AOD after 2011 with an average reduction of 30&thinsp;%–50&thinsp;% between 2011 and 2017. The effect is more visible in the highly populated and industrialized regions in SE China, as expected.</p

Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017)

Aerosol optical depth (AOD) patterns and interannual and seasonal variations over China are discussed based on the AOD retrieved from the Along-Track Scanning Radiometer (ATSR-2, 1995–2002), the Advanced ATSR (AATSR, 2002–2012) (together ATSR) and the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite (2000–2017). The AOD products used were the ATSR Dual View (ADV) v2.31 AOD and the MODIS/Terra Collection 6.1 (C6.1) merged dark target (DT) and deep blue (DB) AOD product. Together these datasets provide an AOD time series for 23 years, from 1995 to 2017. The difference between the AOD values retrieved from ATSR-2 and AATSR is small, as shown by pixel-by-pixel and monthly aggregate comparisons as well as validation results. This allows for the combination of the ATSR-2 and AATSR AOD time series into one dataset without offset correction.ADV and MODIS AOD validation results show similar high correlations with the Aerosol Robotic Network (AERONET) AOD (0.88 and 0.92, respectively), while the corresponding bias is positive for MODIS (0.06) and negative for ADV (−0.07). Validation of the AOD products in similar conditions, when ATSR and MODIS/Terra overpasses are within 90&thinsp;min of each other and when both ADV and MODIS retrieve AOD around AERONET locations, show that ADV performs better than MODIS in autumn, while MODIS performs slightly better in spring and summer. In winter, both ADV and MODIS underestimate the AERONET AOD.Similar AOD patterns are observed by ADV and MODIS in annual and seasonal aggregates as well as in time series. ADV–MODIS difference maps show that MODIS AOD is generally higher than that from ADV. Both ADV and MODIS show similar seasonal AOD behavior. The AOD maxima shift from spring in the south to summer along the eastern coast further north.The agreement between sensors regarding year-to-year AOD changes is quite good. During the period from 1995 to 2006 AOD increased in the southeast (SE) of China. Between 2006 and 2011 AOD did not change much, showing minor minima in 2008–2009. From 2011 onward AOD decreased in the SE of China. Similar patterns exist in year-to-year ADV and MODIS annual AOD tendencies in the overlapping period. However, regional differences between the ATSR and MODIS AODs are quite large. The consistency between ATSR and MODIS with regards to the AOD tendencies in the overlapping period is rather strong in summer, autumn and overall for the yearly average; however, in winter and spring, when there is a difference in coverage between the two instruments, the agreement between ATSR and MODIS is lower.AOD tendencies in China during the 1995–2017 period will be discussed in more detail in Part 2 (a following paper: Sogacheva et al., 2018), where a method to combine AOD time series from ADV and MODIS is introduced, and combined AOD time series are analyzed.</p