Advancing global aerosol simulations with size-segregated anthropogenic particle number emissions

Climate models are important tools that are used for generating climate change projections, in which aerosol-climate interactions are one of the main sources of uncertainties. In order to quantify aerosol-radiation and aerosolcloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in pre-compiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few, very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. In the GAINS model the emission number size distributions vary, for example, with respect to the fuel and technology. Special attention was paid to accumulation mode particles (particle diameter d(p) > 100 nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100 nm particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol-climate interactions, are expected to be affected. Analysis of global particle number concentrations and size distributions reveals that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particles agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (d(p) <100 nm) particle number concentrations. This suggests that revisions are needed in the new particle formation and growth schemes currently applied in global modeling frameworks.Peer reviewe

Curating scientific information in knowledge infrastructures

Interpreting observational data is a fundamental task in the sciences, specifically in earth and environmental science where observational data are increasingly acquired, curated, and published systematically by environmental research infrastructures. Typically subject to substantial processing, observational data are used by research communities, their research groups and individual scientists, who interpret such primary data for their meaning in the context of research investigations. The result of interpretation is information—meaningful secondary or derived data—about the observed environment. Research infrastructures and research communities are thus essential to evolving uninterpreted observational data to information. In digital form, the classical bearer of information are the commonly known “(elaborated) data products,” for instance maps. In such form, meaning is generally implicit e.g., in map colour coding, and thus largely inaccessible to machines. The systematic acquisition, curation, possible publishing and further processing of information gained in observational data interpretation—as machine readable data and their machine readable meaning—is not common practice among environmental research infrastructures. For a use case in aerosol science, we elucidate these problems and present a Jupyter based prototype infrastructure that exploits a machine learning approach to interpretation and could support a research community in interpreting observational data and, more importantly, in curating and further using resulting information about a studied natural phenomenon. © 2018 The Author(s).Peer reviewe

Parameterization of ion-induced nucleation rates based on ambient observations

Atmospheric ions participate in the formation of new atmospheric aerosol particles, yet their exact role in this process has remained unclear. Here we derive a new simple parameterization for ion-induced nucleation or, more precisely, for the formation rate of charged 2-nm particles. The parameterization is semi-empirical in the sense that it is based on comprehensive results of one-year-long atmospheric cluster and particle measurements in the size range ~1–42 nm within the EUCAARI (European Integrated project on Aerosol Cloud Climate and Air Quality interactions) project. Data from 12 field sites across Europe measured with different types of air ion and cluster mobility spectrometers were used in our analysis, with more in-depth analysis made using data from four stations with concomitant sulphuric acid measurements. The parameterization is given in two slightly different forms: a more accurate one that requires information on sulfuric acid and nucleating organic vapor concentrations, and a simpler one in which this information is replaced with the global radiation intensity. These new parameterizations are applicable to all large-scale atmospheric models containing size-resolved aerosol microphysics, and a scheme to calculate concentrations of sulphuric acid, condensing organic vapours and cluster ions

Future biogeochemical forcing in Eastern Siberia: cooling or warming?

Over-proportional warming in the northern high latitudes, and large carbon stocks in boreal and (sub)arctic ecosystems have raised concerns as to whether substantial positive climate feedbacks from biogeochemical process responses should be expected. Such feedbacks occur if increasing temperatures lead to e.g., a net release of CO2 or CH4. However, temperature-enhanced emissions of biogenic volatile organic compounds (BVOC) have been shown to contribute to a cooling feedback via growth of secondary organic aerosol (SOA), and related aerosol forcings. Combining measurements in Eastern Siberia with model-based estimates of vegetation and permafrost dynamics, BVOC emissions and aerosol growth, we show here that the additional climate forcing from changes in ecosystem CO2 balance and BVOC-SOA interactions nearly cancel on a regional scale. The interactions between emissions and vegetation dynamics that underlie individual forcing estimates are complex and highlight the importance of addressing ecosystem-climate feedbacks in consistent, process-based model frameworks that account for a multitude of system processes

Future vegetation–climate interactions in Eastern Siberia: an assessment of the competing effects of CO2 and secondary organic aerosols

Disproportional warming in the northern high latitudes, and large carbon stocks in boreal and (sub)arctic ecosystems have raised concerns as to whether substantial positive climate feedbacks from biogeochemical process responses should be expected. Such feedbacks occur if increasing temperatures lead to e.g. a net release of CO2 or CH4. However, temperature-enhanced emissions of biogenic volatile organic compounds (BVOC) have been shown to contribute to the growth of secondary organic aerosol (SOA) which is known to have a negative radiative climate effect. Combining measurements in Eastern Siberia with model-based estimates of vegetation and permafrost dynamics, BVOC emissions and aerosol growth, we assess here possible future changes in ecosystem CO2 balance and BVOC-SOA interactions, and discuss these changes in terms of possible climate effects. On global level, both are very small but when concentrating on Siberia and the northern hemisphere the negative forcing from changed aerosol direct and indirect effects become notable – even though the associated temperature response would not necessarily follow a similar spatial pattern. While our analysis does not include other important processes that are of relevance for the climate system, the CO2 and BVOC-SOA interplay used serves as an example of the complexity of the interactions between emissions and vegetation dynamics that underlie individual terrestrial feedbacks and highlights the importance of addressing ecosystem-climate feedbacks in consistent, process-based model frameworks

Estimating the atmospheric concentration of Criegee intermediates and their possible interference in a FAGE-LIF instrument

We analysed the extensive dataset from the HUMPPA-COPEC 2010 and the HOPE 2012 field campaigns in the boreal forest and rural environments of Finland and Germany, respectively, and estimated the abundance of stabilised Criegee intermediates (SCIs) in the lower troposphere. Based on laboratory tests, we propose that the background OH signal observed in our IPI-LIF-FAGE instrument during the aforementioned campaigns is caused at least partially by SCIs. This hypothesis is based on observed correlations with temperature and with concentrations of unsaturated volatile organic compounds and ozone. Just like SCIs, the background OH concentration can be removed through the addition of sulfur dioxide. SCIs also add to the previously underestimated production rate of sulfuric acid. An average estimate of the SCI concentration of ∼ 5.0 x 104 molecules cm−3 (with an order of magnitude uncertainty) is calculated for the two environments. This implies a very low ambient concentration of SCIs, though, over the boreal forest, significant for the conversion of SO2 into H2SO4. The large uncertainties in these calculations, owing to the many unknowns in the chemistry of Criegee intermediates, emphasise the need to better understand these processes and their potential effect on the self-cleaning capacity of the atmosphere

Simple proxies for estimating the concentrations of monoterpenes and their oxidation products at a boreal forest site

The oxidation products of monoterpenes likely have a crucial role in the formation and growth of aerosol particles in boreal forests. However, the continuous measurements of monoterpene concentrations are usually not available on decadal timescales, and the direct measurements of the concentrations of monoterpene oxidation product have so far been scarce. In this study we developed proxies for the concentrations of monoterpenes and their oxidation products at a boreal forest site in Hyytiala, southern Finland. For deriving the proxies we used the monoterpene concentration measured with a proton transfer reaction mass spectrometer (PTR-MS) during 2006-2013. Our proxies for the monoterpene concentration take into account the temperature-controlled emissions from the forest ecosystem, the dilution caused by the mixing within the boundary layer and different oxidation processes. All the versions of our proxies captured the seasonal variation of the monoterpene concentration, the typical proxy-to-measurements ratios being between 0.8 and 1.3 in summer and between 0.6 and 2.6 in winter. In addition, the proxies were able to describe the diurnal variation of the monoterpene concentration rather well, especially in summer months. By utilizing one of the proxies, we calculated the concentration of oxidation products of monoterpenes by considering their production in the oxidation and their loss due to condensation on aerosol particles. The concentration of oxidation products was found to have a clear seasonal cycle, with a maximum in summer and a minimum in winter. The concentration of oxidation products was lowest in the morning or around noon and highest in the evening. In the future, our proxies for the monoterpene concentration and their oxidation products can be used, for example, in the analysis of new particle formation and growth in boreal environments.Peer reviewe

Aerosol Particle Number Emissions and Size Distributions: Implementation in the GAINS Model and Initial Results

Particulate matter affects our health and climate. In addition to well based knowledge on the adverse health effects related to particle mass concentrations, there is increasing evidence showing that the number concentrations of ultra-fine aerosol particles, with diameters below 0.1 um, have negative health impacts, which are significantly different from those caused by larger particles with sizes over 1 um. Particles with diameters between 0.1 and 1 um can also be activated as cloud droplets; thereby, higher number concentrations can increase the cloud albedo and thus the proportion of solar radiation reflected back to space, causing a cooling aerosol climate effect. In addition to this indirect effect, aerosol particles affect Earth radiation budget directly by either scattering solar radiation (e.g. sulphate aerosol, cooling effect) or absorbing it (black carbon aerosol, warming effect). Currently, European air quality legislation on particulate matter is mainly focussing on particle mass, although emission standards for particle numbers have been introduced for mobile sources. Mass concentration is dominated by particles larger than 0.1 um, and it is not well associated with number concentration, due to the often different formation mechanisms of ultra-fine and larger particles. For combustion sources, some emission control technologies affect mainly large particle emissions, and may even increase emissions of ultra-fine particles. Hence, in order to comprehensively estimate health and climate effects of anthropogenic aerosol particles, it is necessary to quantify their emissions with both mass and number based metrics, including information on their size distribution. Currently, European air quality legislation on particulate matter is mainly focussing on particle mass, although emission standards for particle numbers have been introduced for mobile sources. Mass concentration is dominated by particles larger than 0.1 um, and it is not well associated with number concentration, due to the often different formation mechanisms of ultra-fine and larger particles. For combustion sources, some emission control technologies affect mainly large particle emissions, and may even increase emissions of ultra-fine particles. Hence, in order to comprehensively estimate health and climate effects of anthropogenic aerosol particles, it is necessary to quantify their emissions with both mass and number based metrics, including information on their size distribution. This report describes the implementation of size segregated particle number emission calculations in the GAINS model. Results show that in 2010 in Europe more than 60% of particle number emissions emerge from road transport, even though their share in total PM1 mass emissions (i.e., the mass of emitted particles with diameters below 1 um) is only 12%. Particle number emissions from road transport are expected to decrease rapidly in the future due to further tightening of exhaust emission legislation (EURO-standards). Due to the envisaged more pronounced particle number emission reduction in the road transport sector compared to the currently second and third largest source sectors, shipping and combustion of fuel wood and coal in the residential sector, emissions from the latter two sectors are anticipated to exceed road transport emissions by 2025. Estimated shares in total European emissions in 2025 range, depending on the applied future scenario, from 35 to 41% for shipping, from 26 to 29% for residential combustion and from 17 to 21% for road transport. The presented initial results are, however, subject to significant uncertainties, primarily due to limited measurement data for several emission sources

Global anthropogenic particle number emissions and their size distributions

Aerosol particle number concentrations and size distributions affect our climate by determining the formation of cloud droplets and thus altering the cloud reflective properties. The aerosol-cloud interactions are one of the main uncertainties in estimating the future climate change. One of the weaknesses in current climate modelling is the description of number emissions and size distributions of particles. Here, we present the first global results of implementing particle number emission factors to GAINS emission scenario model and discuss the related uncertainties. The uncertainties for different source sectors vary significantly, causing a steep difference in total uncertainties in different parts of the world. The reason for these uncertainties is the scarcity of data on particle number size distributions for certain sources. The implemented particle number emission factors, however, are expected to be a significant improvement over previously applied particle number emissions estimates in climate modelling