Isoprene suppression of new particle formation: Potential mechanisms and implications

Secondary aerosols formed from anthropogenic pollutants and natural emissions have substantial impacts on human health, air quality, and the Earth’s climate. New particle formation (NPF) contributes up to 70% of the global production of cloud condensation nuclei (CCN), but the effects of biogenic volatile organic compounds (BVOCs) and their oxidation products on NPF processes in forests are poorly understood. Observations show that isoprene, the most abundant BVOC, suppresses NPF in forests. But the previously proposed chemical mechanism underlying this suppression process contradicts atmospheric observations. By reviewing observations made in other forests, it is clear that NPF rarely takes place during the summer when emissions of isoprene are high, even though there are sufficient concentrations of monoterpenes. But at present it is not clear how isoprene and its oxidation products may change the oxidation chemistry of terpenes and how NOx and other atmospheric key species affect NPF in forest environments. Future laboratory experiments with chemical speciation of gas phase nucleation precursors and clusters and chemical composition of particles smaller than 10nm are required to understand the role of isoprene in NPF. Our results show that climate models can overpredict aerosol’s first indirect effect when not considering the absence of NPF in the southeastern U.S. forests during the summer using the current nucleation algorithm that includes only sulfuric acid and total concentrations of low-volatility organic compounds. This highlights the importance of understanding NPF processes as function of temperature, relative humidity, and BVOC compositions to make valid predictions of NPF and CCN at a wide range of atmospheric conditions. © 2016. American Geophysical Union. All Rights Reserved.

Modeling regional air quality and climate: Improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1

Athanasios Nenes, Yi Zhang

Air quality and climate influence each other through the uncertain processes of aerosol formation and cloud droplet activation. In this study, both processes are improved in the Weather, Research and Forecasting model with Chemistry (WRF/Chem) version 3.7.1. The existing Volatility Basis Set (VBS) treatments for organic aerosol (OA) formation in WRF/Chem are improved by considering the following: the secondary OA (SOA) formation from semi-volatile primary organic aerosol (POA), a semi-empirical formulation for the enthalpy of vaporization of SOA, and functionalization and fragmentation reactions for multiple generations of products from the oxidation of VOCs. Over the continental US, 2-month-long simulations (May to June 2010) are conducted and results are evaluated against surface and aircraft observations during the Nexus of Air Quality and Climate Change (CalNex) campaign. Among all the configurations considered, the best performance is found for the simulation with the 2005 Carbon Bond mechanism (CB05) and the VBS SOA module with semivolatile POA treatment, 25% fragmentation, and the emissions of semi-volatile and intermediate volatile organic compounds being 3 times the original POA emissions. Among the three gas-phase mechanisms (CB05, CB6, and SAPRC07) used, CB05 gives the best performance for surface ozone and PM2.5 concentrations. Differences in SOA predictions are larger for the simulations with different VBS treatments (e.g., nonvolatile POA versus semivolatile POA) compared to the simulations with different gas-phase mechanisms. Compared to the simulation with CB05 and the default SOA module, the simulations with the VBS treatment improve cloud droplet number concentration (CDNC) predictions (normalized mean biases from -40.8% to a range of -34.6 to -27.7%), with large differences between CB05-CB6 and SAPRC07 due to large differences in their OH and HO2 predictions. An advanced aerosol activation parameterization based on the Fountoukis and Nenes (2005) series reduces the large negative CDNC bias associated with the default Abdul Razzak and Ghan (2000) parameterization from -35.4% to a range of -0.8 to 7.1%. However, it increases the errors due to overpredictions of CDNC, mainly over the northeastern US. This work indicates a need to improve other aerosol-cloud-radiation processes in the model, such as the spatial distribution of aerosol optical depth and cloud condensation nuclei, in order to further improve CDNC predictions. © Author(s) 2017.

Copernicus GmbH2017

Dry and ambient aerosol properties at the Jungfraujoch

Remo Nessler

Atmospheric aerosol is defined as a suspension of solid or liquid particles in air. The major concerns about aerosol particles are their adverse health effects and their role in the Earth's climate system. Atmospheric particles influence the Earth's radiation budget in two ways: either directly by scattering and absorbing incoming solar radiation (and to a far less extent longwave radiation emitted from the Earth) or indirectly by their ability to act as cloud condensation nuclei (CCN). With increasing particle concentrations, caused by, e.g., anthropogenic emissions, more CCN are available to form cloud droplets. For a fixed water content in the atmosphere this leads to more but smaller droplets and therefore to enhanced cloud albedos as well as to rain suppression. Both effects have been recognized in recent years to be of great importance for understanding the observed climate change. Nevertheless, they remain poorly understood and quantified. The Jungfraujoch (JFJ, 3580 m asl; 46.548°N, 7.984°E) High Alpine Research Station is equipped with instruments that have for decades performed important Global Climate Observations. A major part of the aerosol instruments perform in-situ measurements. However, due to the harsh weather conditions, they usually cannot be run outdoors. The ambient air has to be inducted into a housing, such that the aerosol is sampled at a temperature (T) and relative humidity (RH) different from the ambient values. Therefore, the measured aerosol properties may considerably differ from the ambient — the climate-relevant — ones. During the first Cloud and Aerosol Characterization Experiment (CLACE) at the JFJ in-situ aerosol size distributions were measured simultaneously indoor at dry conditions (T ≈ 25 °C and RH < 10%) and, for the first time in such an exposed place, outdoor at ambient conditions (T < –5 °C) by means of two scanning mobility particle sizers (SMPS). The data set was completed by measurements of hygroscopic growth factors using a hygroscopicity tandem differential mobility analyzer (H-TDMA). A comparison of dry and ambient size distributions shows two main features: First, the dry total number concentration is often considerably smaller (on average 28%) than the ambient total number concentration. This is most likely due to the evaporation of volatile material at the higher indoor temperature. These particle losses mainly concern small particles (dry diameter Ddry ≤ 100 nm), and therefore have only a minimal affect on the surface and volume concentrations. Second, the dry number size distribution is shifted towards smaller particles, reflecting the hygroscopic behavior of the aerosols. This shift was modeled using a modified Köhler equation adapted to the measured hygroscopic growth factors. The corrected dry surface and volume concentrations are in good agreement with the ambient measurements for the whole RH range, but the correction works best for RH < 80%. The results indicate that size distribution data measured at indoor conditions (i.e. dry and warm) may be successfully corrected to reflect ambient conditions. By combining these results with earlier JFJ aerosol measurements (e.g. chemical composition), it was possible to model dry and ambient optical aerosol properties for a summer and a winter case. The model calculations were based on a total of 496 size distributions representative for the JFJ aerosol, hygroscopic growth parameterizations and the following simplified aerosol structures: The fine mode (Ddry ≤ 1 µm) aerosol was assumed to consist of a water-insoluble spherical core concentrically encased by a coating comprising all water-soluble compounds, and the coarse mode (Ddry > 1 µm) particles were assumed to be water-insoluble homogeneous spheres. Ambient scattering coefficients σsca(RH) were found to be considerably different from the dry scattering coefficients σsca(RH = 0). The scattering enhancement factors ξ(RH) = σsca(RH)/σsca(RH = 0) strongly depend on the particle size. At RH = 85% they vary for example between ≈ 1.2 and ≈ 3.8. It was possible to establish a parameterization of ξ(RH) with the dry Ångström exponent å (based on scattering only). Since å follows directly from the dry scattering measurements, the parameterization allows to derive ambient scattering coefficients from the dry scattering coefficients without the need of any additional measurement other than ambient RH. RH also affects the absorption coefficient σabs. Depending on particle size and wavelength (investigated between 370 nm and 950 nm) absorption enhancement factors χ(RH) = σabs(RH)/σabs(RH = 0) were found to range from 0.84 to 1.78. However, it was possible to demonstrate that, even though the humidity effect on absorption is substantial, its contribution to the humidity effect on extinction and the single scattering albedo is negligible at the JFJ. The EPFL Raman lidar installed at the JFJ provides profiles of extinction and backscattering coefficients at the wavelengths 355 nm, 532 nm and 1064 nm for altitudes between typically 4 km and 15 km asl. These measurements are ambient but afflicted with more uncertainties than the dry in-situ measurements. A method was developed to derive microphysical aerosol properties from optical lidar data. This is a so-called ill-posed problem, i.e., small errors in the lidar data lead to huge errors in the inverted microphysical properties, unless special mathematical tools are applied. Therefore the method makes use of regularization techniques. It is shown that microphysical parameters can be inverted with acceptable accuracy from an optical dataset as it is provided by a lidar of e.g. the EPFL type.

EPFL2004

Incorporating an advanced aerosol activation parameterization into WRF-CAM5: Model evaluation and parameterization intercomparison

Athanasios Nenes, Xiuwei Zhang, Yi Zhang

Aerosol activation into cloud droplets is an important process that governs aerosol indirect effects. The advanced treatment of aerosol activation by Fountoukis and Nenes (2005) and its recent updates, collectively called the FN series, have been incorporated into a newly developed regional coupled climate-air quality model based on the Weather Research and Forecasting model with the physics package of the Community Atmosphere Model version 5 (WRF-CAM5) to simulate aerosol-cloud interactions in both resolved and convective clouds. The model is applied to East Asia for two full years of 2005 and 2010. A comprehensive model evaluation is performed for model predictions of meteorological, radiative, and cloud variables, chemical concentrations, and column mass abundances against satellite data and surface observations from air quality monitoring sites across East Asia. The model performs overall well for major meteorological variables including near-surface temperature, specific humidity, wind speed, precipitation, cloud fraction, precipitable water, downward shortwave and longwave radiation, and column mass abundances of CO, SO2, NO2, HCHO, and O3 in terms of both magnitudes and spatial distributions. Larger biases exist in the predictions of surface concentrations of CO and NOx at all sites and SO2, O3, PM2.5, and PM10 concentrations at some sites, aerosol optical depth, cloud condensation nuclei over ocean, cloud droplet number concentration (CDNC), cloud liquid and ice water path, and cloud optical thickness. Compared with the default Abdul-Razzack Ghan (2000) parameterization, simulations with the FN series produce ~107-113% higher CDNC, with half of the difference attributable to the higher aerosol activation fraction by the FN series and the remaining half due to feedbacks in subsequent cloud microphysical processes. With the higher CDNC, the FN series are more skillful in simulating cloud water path, cloud optical thickness, downward shortwave radiation, shortwave cloud forcing, and precipitation. The model evaluation identifies several areas of improvements including emissions and their vertical allocation as well as model formulations such as aerosol formation, cloud droplet nucleation, and ice nucleation. © 2015. American Geophysical Union. All Rights Reserved.

Wiley-Blackwell2015