The Airmodus A10 PSM determines the size distribution of particles between 1 and 3 nm diameter. Particles grow inside the PSM with diethylene glycol as a working fluid to about 90 nm in diameter, after which counting is performed with an Airmodus A20 butanol condensation particle counter (CPC). The cut-off size of the PSM can be varied by altering the mixing ratio of the sample and diethylene glycol saturated flows.
The NAIS is an ion mobility spectrometer that measures the number size distribution of ions and total (charged and neutral) particles with electrical mobilities that range from 3.2 to 0.0013 cm2 V−1 s−1, or from 0.8 to 42 nm mobility diameters for ions and from 2 to 42 nm for neutral particles. Two differential mobility analysers classified the positive and negative ions.
The APi-TOF mass spectrometer measures the chemical composition of the naturally charged ions (TOFWERK AG and Aerodyne Research). In the APi section, the sample air passed through a critical orifice with a flow rate of 0.8 l min−1, after which the ions were guided by two quadrupoles and an ion lens to the time-of-flight mass spectrometer.
Atmospheric measurements are largely influenced by synoptic meteorology and local topography of the measurements site. Thus, accurate information on air mass origin and transport pathways to high-altitude sites is required. The ABC group have developed a new method, based on the source–receptor relationship (SRR) obtained from backwards WRF-FLEXPART simulations and a k-means clustering approach, to identify source regions of air masses arriving at measurement sites.
A key aspect of our method is that it is probabilistic, and for each observation time, more than one air mass (cluster) can influence the station, and the percentage influence of each air mass can be quantified. This is in contrast to binary methods, which label each observation time as influenced by either boundary layer or free-troposphere air masses.
The method was successfully applied in areas characterized by complex topography (i.e. the Chacaltaya Observatory) and for stations influenced by both local and long-range sources.
To generate a high-resolution, gridded dataset of meteorological variables that can be used to drive a Lagrangian dispersion model, we use the Advanced Research WRF model version 4.0.3 (Skamarock et al., 2019). One-way nesting is used: the outer domain provides boundary data for the inner nest, but the inner nest does not provide any feedback to the outer domain. To ensure that the long simulation remains close to reality throughout the 6-month period, the outer domain is nudged (i.e. analysis nudging) to the boundary conditions every 6 h.
The FLEXible PARTicle dispersion model (FLEXPART) is a Lagrangian transport and dispersion model which can be used for both forward and backward simulations. We use version FLEXPART-WRF_v3.3.2 to perform backward simulations and thus to determine the source regions of air masses arriving at a specific location. The FLEXPART simulations are driven using the meteorological output from the WRF simulation. Output from all the WRF output domains are used at a temporal resolution of 15 min. This high temporal resolution is a clear advantage over using reanalysis data, which at best are only available once per hour.
Emissions of both anthropogenic and biogenic chemical compounds are highly dependent on their geographical location, meteorological condition and human habits. Once released from the local source into the various layers of the atmosphere, those compounds undergoes hundred of thousands of chemical reactions - eventually leading to the formation of new particles - and are subject to removal process such as dry and wet deposition. These - non-linear - processes are highly depended on the physical and chemical characteristics of the aerosols population.
Additionally, aerosol particles can affect climate by interacting with the incoming solar radiation (direct effect) and by acting as cloud condensation nuclei (CCN), therefore changing the microphysics of cloud.
We use the WRF-CHIMERE Chemical Transport model (
We simulate meteorological input data using the Weather Research and Forecast (WRF) regional model. We nudge the simulations on the coarser grid towards reanalysis data from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (
Initial and boundary conditions of aerosols and gas-phase constituents were retrieved from the climatological simulations of LMDz-INCA3 (
Annual anthropogenic emissions of black carbon (BC), organic carbon (OC), methane (CH4), carbon dioxide (CO2), carbon monoxide (CO), ammonia (NH3), non-methane volatile organic compounds (NMVOCs), nitrogen oxides (NOx) and sulfur dioxide (SO2) are retrieved from CAMS (
Biogenic emissions of NO, isoprene, limonene, α-pinene, β-pinene, ocimene, and humulene are prepared using the MEGAN (
Emission of seasalt, dust (including detailed mineralogy), NOx from lightning and resuspension material are included.
The chemical mechanism used for the gas-phase chemistry is the MELCHIOR2 scheme (alike the SAPRC scheme), including up to about 120 reactions with updated reaction rates. The ISORROPIA thermodynamic model is used to calculate the partitioning of the inorganic aerosol constituents and a logarithmic sectional distribution approach is deployed to treat the size distribution of aerosol particles using tens of adaptable bins (from 1nm up to 40µm). The model additionally account for coagulation process as well as binary nucleation of sulfuric acid (H2SO4) and water with the addition of HOMs formation and nucleation from biogenic compounds (i.e. α-pinene). The treatment of the organic aerosol chemistry in the model is treated within in the framework of the Volatility Basis Set (VBS) scheme.