The Amazon Basin plays key roles in the carbon and water cycles, climate change, atmospheric chemistry, and biodiversity. It has already been changed significantly by human activities, and more pervasive change is expected to occur in the coming decades. It is therefore essential to establish long-term measurement sites that provide a baseline record of present-day climatic, biogeochemical, and atmospheric conditions and that will be operated over coming decades to monitor change in the Amazon region, as human perturbations increase in the future. The Amazon Tall Tower Observatory (ATTO) has been set up in a pristine rain forest region in the central Amazon Basin, about 150 km northeast of the city of Manaus. Two 80 m towers have been operated at the site since 2012, and a 325 m tower is nearing completion in mid-2015. An ecological survey including a biodiversity assessment has been conducted in the forest region surrounding the site. Measurements of micrometeorological and atmospheric chemical variables were initiated in 2012, and their range has continued to broaden over the last few years. The meteorological and micrometeorological measurements include temperature and wind profiles, precipitation, water and energy fluxes, turbulence components, soil temperature profiles and soil heat fluxes, radiation fluxes, and visibility. A tree has been instrumented to measure stem profiles of temperature, light intensity, and water content in cryptogamic covers. The trace gas measurements comprise continuous monitoring of carbon dioxide, carbon monoxide, methane, and ozone at five to eight different heights, complemented by a variety of additional species measured during intensive campaigns (e.g., VOC, NO, NO₂, and OH reactivity). Aerosol optical, microphysical, and chemical measurements are being made above the canopy as well as in the canopy space. They include aerosol light scattering and absorption, fluorescence, number and volume size distributions, chemical composition, cloud condensation nuclei (CCN) concentrations, and hygroscopicity. In this paper, we discuss the scientific context of the ATTO observatory and present an overview of results from ecological, meteorological, and chemical pilot studies at the ATTO site.

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site. The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κ_Ait = 0.14 ± 0.03), higher values for the accumulation mode (κ_Acc = 0.22 ± 0.05), and an overall mean value of κ_mean = 0.17 ± 0.06, consistent with high fractions of organic aerosol. The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes. For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.

Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted over a full seasonal cycle at the remote Amazon Tall Tower Observatory (ATTO, March 2014–February 2015). In a preceding companion paper, we presented annually and seasonally averaged data and parametrizations (Part 1; Pöhlker et al., 2016a). In the present study (Part 2), we analyze key features and implications of aerosol and CCN properties for the following characteristic atmospheric conditions: Empirically pristine rain forest (PR) conditions, where no influence of pollution was detectable, as observed during parts of the wet season from March to May. The PR episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode with D_Ait ≈ 70 nm and N_Ait ≈ 160 cm⁻³, weak accumulation mode with D_acc ≈ 160 nm and N_acc ≈ 90 cm⁻³), a chemical composition dominated by organic compounds, and relatively low particle hygroscopicity (κ_Ait ≈ 0.12, κ_acc ≈ 0.18). Long-range-transport (LRT) events, which frequently bring Saharan dust, African biomass smoke, and sea spray aerosols into the Amazon Basin, mostly during February to April. The LRT episodes are characterized by a dominant accumulation mode (D_Ait ≈ 80 nm, N_Ait ≈ 120 cm⁻³ vs. D_acc ≈ 180 nm, N_acc ≈ 310 cm⁻³), an increased abundance of dust and salt, and relatively high hygroscopicity (κ_Ait ≈ 0.18, κ_acc ≈ 0.35). The coarse mode is also significantly enhanced during these events. Biomass burning (BB) conditions characteristic for the Amazonian dry season from August to November. The BB episodes show a very strong accumulation mode (D_Ait ≈ 70 nm, N_Ait ≈ 140 cm⁻³ vs. D_acc ≈ 170 nm, N_acc ≈ 3400 cm⁻³), very high organic mass fractions ( ∼ 90 %), and correspondingly low hygroscopicity (κ_Ait ≈ 0.14, κ_acc ≈ 0.17). Mixed-pollution (MPOL) conditions with a superposition of African and Amazonian aerosol emissions during the dry season. During the MPOL episode presented here as a case study, we observed African aerosols with a broad monomodal distribution (D ≈ 130 nm, N_CN, 10 ≈ 1300 cm⁻³), with high sulfate mass fractions (∼ 20 %) from volcanic sources and correspondingly high hygroscopicity (κ_{<  100 nm} ≈ 0.14, κ_{>  100 nm} ≈ 0.22), which were periodically mixed with fresh smoke from nearby fires (D ≈ 110 nm, N_CN, 10 ≈ 2800 cm⁻³) with an organic-dominated composition and sharply decreased hygroscopicity (κ_{<  150 nm} ≈ 0.10, κ_{>  150 nm} ≈ 0.20). Insights into the aerosol mixing state are provided by particle hygroscopicity (κ) distribution plots, which indicate largely internal mixing for the PR aerosols (narrow κ distribution) and more external mixing for the BB, LRT, and MPOL aerosols (broad κ distributions). The CCN spectra (CCN concentration plotted against water vapor supersaturation) obtained for the different case studies indicate distinctly different regimes of cloud formation and microphysics depending on aerosol properties and meteorological conditions. The measurement results suggest that CCN activation and droplet formation in convective clouds are mostly aerosol-limited under PR and LRT conditions and updraft-limited under BB and MPOL conditions. Normalized CCN efficiency spectra (CCN divided by aerosol number concentration plotted against water vapor supersaturation) and corresponding parameterizations (Gaussian error function fits) provide a basis for further analysis and model studies of aerosol–cloud interactions in the Amazon.

The Chinese capital Beijing is one of the global megacities where the effects of rapid economic growth have led to complex air pollution problems that are not well understood. In this study, ambient particle number size distributions in Beijing between 2004 and 2006 are analysed as a function of regional meteorological transport. An essential result is that the particle size distribution in Beijing depends to large extent on the history of the synoptic scale air masses. A first approach based on manual back trajectory classification yielded differences in particulate matter mass concentration by a factor of two between four different air mass categories, including three main wind directions plus the case of stagnant air masses. A back trajectory cluster analysis refined these results, yielding a total of six trajectory clusters. Besides the large scale wind direction, the transportation speed of an air mass was found to play an essential role on the PM concentrations in Beijing. Slow-moving air masses were shown to be associated with an effective accumulation of surface-based anthropogenic emissions due to both, an increased residence time over densely populated land, and their higher degree of vertical stability. For the six back trajectory clusters, differences in PM₁ mass concentrations by a factor of 3.5, in the mean air mass speed by a factor of 6, and in atmospheric visibility by a factor of 4 were found. The main conclusion is that the air quality in Beijing is not only degraded by anthropogenic aerosol sources from within the megacity, but also by sources across the entire Northwest China plain depending on the meteorological situation.

The Amazon rain forest experiences the combined pressures from human-made deforestation and progressing climate change, causing severe and potentially disruptive perturbations of the ecosystem's integrity and stability. To intensify research on critical aspects of Amazonian biosphere–atmosphere exchange, the Amazon Tall Tower Observatory (ATTO) has been established in the central Amazon Basin. Here we present a multi-year analysis of backward trajectories to derive an effective footprint region of the observatory, which spans large parts of the particularly vulnerable eastern basin. Further, we characterize geospatial properties of the footprint regions, such as climatic conditions, distribution of ecoregions, land cover categories, deforestation dynamics, agricultural expansion, fire regimes, infrastructural development, protected areas, and future deforestation scenarios. This study is meant to be a resource and reference work, helping to embed the ATTO observations into the larger context of human-caused transformations of Amazonia. We conclude that the chances to observe an unperturbed rain forest–atmosphere exchange at the ATTO site will likely decrease in the future, whereas the atmospheric signals from human-made and climate-change-related forest perturbations will increase in frequency and intensity.