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1. THE GLOBAL AEROSOL SYNTHESIS AND SCIENCE PROJECT (GASSP) : Measurements and Modeling to Reduce Uncertainty

Author

Reddington, C. L., Carslaw, K. S., Stier, P., Schutgens, N., Coe, H., Liu, D., Allan, J., Browse, J., Pringle, K. J., Lee, L. A., Yoshioka, M., Johnson, J. S., Regayre, L. A., Spracklen, D. V., Mann, G. W., Clarke, A., Hermann, M., Henning, S., Wex, H., Kristensen, T. B., Leaitch, W. R., Pöschl, U., Rose, D., Andreae, M. O., Schmale, J., Kondo, Y., Oshima, N., Schwarz, J. P., Nenes, A., Anderson, B., Roberts, G. C., Snider, J. R., Leck, C., Quinn, P. K., Chi, X., Ding, A., Jimenez, J. L., and Zhang, Q.

Published
2017

2. Atmospheric composition change – global and regional air quality

Author

Monks, PS, Granier, C, Fuzzi, S, Stohl, A, Williams, ML, Akimoto, H, Amann, M, Baklanov, A, Baltensperger, U, Bey, I, Blake, N, Blake, RS, Carslaw, K, Cooper, OR, Dentener, F, Fowler, D, Fragkou, E, Frost, GJ, Generoso, S, Ginoux, P, Grewe, V, Guenther, A, Hansson, HC, Henne, S, Hjorth, J, Hofzumahaus, A, Huntrieser, H, Isaksen, ISA, Jenkin, ME, Kaiser, J, Kanakidou, M, Klimont, Z, Kulmala, M, Laj, P, Lawrence, MG, Lee, JD, Liousse, C, Maione, M, McFiggans, G, Metzger, A, Mieville, A, Moussiopoulos, N, Orlando, JJ, O'Dowd, CD, Palmer, PI, Parrish, DD, Petzold, A, Platt, U, Pöschl, U, Prévôt, ASH, Reeves, CE, Reimann, S, Rudich, Y, Sellegri, K, Steinbrecher, R, Simpson, D, Brink, H ten, Theloke, J, van der Werf, GR, Vautard, R, Vestreng, V, Vlachokostas, Ch, and von Glasow, R

Subjects
Climate Action, Atmosphere, Troposphere, Air quality, Emissions, Climate, Co-benefit, Oxidation chemistry, Aerosols, Transport of pollutants, Ozone, Statistics, Atmospheric Sciences, Environmental Engineering, Meteorology & Atmospheric Sciences
Abstract

Air quality transcends all scales with in the atmosphere from the local to the global with handovers and feedbacks at each scale interaction. Air quality has manifold effects on health, ecosystems, heritage and climate. In this review the state of scientific understanding in relation to global and regional air quality is outlined. The review discusses air quality, in terms of emissions, processing and transport of trace gases and aerosols. New insights into the characterization of both natural and anthropogenic emissions are reviewed looking at both natural (e.g. dust and lightning) as well as plant emissions. Trends in anthropogenic emissions both by region and globally are discussed as well as biomass burning emissions. In terms of chemical processing the major air quality elements of ozone, non-methane hydrocarbons, nitrogen oxides and aerosols are covered. A number of topics are presented as a way of integrating the process view into the atmospheric context; these include the atmospheric oxidation efficiency, halogen and HOx chemistry, nighttime chemistry, tropical chemistry, heat waves, megacities, biomass burning and the regional hot spot of the Mediterranean. New findings with respect to the transport of pollutants across the scales are discussed, in particular the move to quantify the impact of long-range transport on regional air quality. Gaps and research questions that remain intractable are identified. The review concludes with a focus of research and policy questions for the coming decade. In particular, the policy challenges for concerted air quality and climate change policy (co-benefit) are discussed. © 2009 Elsevier Ltd.

Published
2009

4. The Detection of Large HNO 3 -Containing Particles in the Winter Arctic Stratosphere

Author

Fahey, D. W., Gao, R. S., Carslaw, K. S., Kettleborough, J., Popp, P. J., Northway, M. J., Holecek, J. C., Ciciora, S. C., McLaughlin, R. J., Thompson, T. L., Winkler, R. H., Baumgardner, D. G., Gandrud, B., Wennberg, P. O., Dhaniyala, S., McKinney, K., Salawitch, R. J., Bui, T. P., Elkins, J. W., Webster, C. R., Atlas, E. L., Jost, H., Wilson, J. C., Herman, R. L., Kleinböhl, A., and von König, M.

Published
2001

6. Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach:exploring model uncertainty with a Gaussian process emulator

Author

Reyes-Villegas, E., Lowe, D., Johnson, J. S., Carslaw, K. S., Darbyshire, E., Flynn, Michael, Allan, J. D., Coe, Hugh, Chen, Y., Wild, O., Archer-Nicholls, Scott, Archibald, A., Singh, S., Shrivastava, M., Zaveri, R. A., Singh, Vikas, Beig, G., Sokhi, R., McFiggans, G., Reyes-Villegas, E., Lowe, D., Johnson, J. S., Carslaw, K. S., Darbyshire, E., Flynn, Michael, Allan, J. D., Coe, Hugh, Chen, Y., Wild, O., Archer-Nicholls, Scott, Archibald, A., Singh, S., Shrivastava, M., Zaveri, R. A., Singh, Vikas, Beig, G., Sokhi, R., and McFiggans, G.

Abstract

The nature and origin of organic aerosol in the atmosphere remain unclear. The gas–particle partitioning of semi-volatile organic compounds (SVOCs) that constitute primary organic aerosols (POAs) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem (Weather Research and Forecasting model with Chemistry), can be a useful tool to describe emissions of POA and its chemical evolution. However, the evaluation of model uncertainty and the optimal model parameterization may be expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterization is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing 10 parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model's uncertainty space and to compare outputs from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the aerosol mass spectrometer (AMS). However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimized VBS approach in WRF-Chem, we were able to apply the emulator in the following two periods: the full period (1–29 May) and a subperiod period of 14:00–16:00 h LT (local time) on 1–29 May. The combination of emulator analysis and model evaluation metrics

Published
2023

7. Aerosols in climate and air quality policy

Author

Carslaw, K., Collins, W., Klimont, Z., Carslaw, K., Collins, W., and Klimont, Z.

Abstract

This chapter discusses the links between aerosol as a pollutant and as a climate forcer, and how future changes in aerosol will be affected by policies in both spheres. The chapter starts with some historical background. It then describes how aerosol particles impact human health and the environment and the regulations that exist to limit these effects. It then describes how aerosol is represented as one of several short-lived climate forcers and how the climatic effects of these are compared to long-lived greenhouse gases in carbon budgets and climate metrics. The chapter describes the effects of policies related to air quality and climate, including the co-benefits and trade-offs of these policies. It concludes by summarizing how integrated assessment models allow policymakers to explore many forward-looking or optimized scenarios of future changes in air pollutant and greenhouse gas emissions.

Published
2022
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8. Constraints on global aerosol number concentration, SO₂ and condensation sink in UKESM1 using ATom measurements

Author

Ranjithkumar, A, Gordon, H, Williamson, C, Rollins, A, Pringle, K, Kupc, A, Abraham, NL, Brock, C, and Carslaw, K

Abstract

Understanding the vertical distribution of aerosol helps to reduce the uncertainty in the aerosol life cycle and therefore in the estimation of the direct and indirect aerosol forcing. To improve our understanding, we use measurements from four deployments of the Atmospheric Tomography (ATom) field campaign (ATom1–4) which systematically sampled aerosol and trace gases over the Pacific and Atlantic oceans with near pole-to-pole coverage. We evaluate the UK Earth System Model (UKESM1) against ATom observations in terms of joint biases in the vertical profile of three variables related to new particle formation: total particle number concentration (NTotal), sulfur dioxide (SO2) mixing ratio and the condensation sink. The NTotal, SO2 and condensation sink are interdependent quantities and have a controlling influence on the vertical profile of each other; therefore, analysing them simultaneously helps to avoid getting the right answer for the wrong reasons. The simulated condensation sink in the baseline model is within a factor of 2 of observations, but the NTotal and SO2 show much larger biases mainly in the tropics and high latitudes. We performed a series of model sensitivity tests to identify atmospheric processes that have the strongest influence on overall model performance. The perturbations take the form of global scaling factors or improvements to the representation of atmospheric processes in the model, for example by adding a new boundary layer nucleation scheme. In the boundary layer (below 1 km altitude) and lower troposphere (1–4 km), inclusion of a boundary layer nucleation scheme (Metzger et al., 2010) is critical to obtaining better agreement with observations. However, in the mid (4–8 km) and upper troposphere (> 8 km), sub-3 nm particle growth, pH of cloud droplets, dimethyl sulfide (DMS) emissions, upper-tropospheric nucleation rate, SO2 gas-scavenging rate and cloud erosion rate play a more dominant role. We find that perturbations to boundary layer nucleation, sub-3 nm growth, cloud droplet pH and DMS emissions reduce the boundary layer and upper tropospheric model bias simultaneously. In a combined simulation with all four perturbations, the SO2 and condensation sink profiles are in much better agreement with observations, but the NTotal profile still shows large deviations, which suggests a possible structural issue with how nucleation or gas/particle transport or aerosol scavenging is handled in the model. These perturbations are well-motivated in that they improve the physical basis of the model and are suitable for implementation in future versions of UKESM.

Published
2021

9. Size-dependent influence of NOₓ on the growth rates of organic aerosol particles

Author

Yan, C., Nie, W., Vogel, A. L., Dada, L., Lehtipalo, K., Stolzenburg, D., Wagner, R., Rissanen, M. P., Xiao, M., Ahonen, L., Fischer, L., Rose, C., Bianchi, F., Gordon, H., Simon, M., Heinritzi, M., Garmash, O., Roldin, P., Dias, A., Ye, P., Hofbauer, V., Amorim, A., Bauer, P. S., Bergen, A., Bernhammer, A.-K., Breitenlechner, M., Brilke, S., Buchholz, A., Buenrostro Mazon, S., Canagaratna, M. R., Chen, X., Ding, A., Dommen, J., Draper, D. C., Duplissy, J., Frege, C., Heyn, C., Guida, R., Hakala, J., Heikkinen, L., Hoyle, C. R., Jokinen, T., Kangasluoma, J., Kirkby, J., Kontkanen, J., Kürten, A., Lawler, M. J., Mai, H., Mathot, S., Mauldin, R. L., III, Molteni, U., Nichman, L., Nieminen, T., Nowak, J., Ojdanic, A., Onnela, A., Pajunoja, A., Petäjä, T., Piel, F., Quéléver, L. L. J., Sarnela, N., Schallhart, S., Sengupta, K., Sipilä, M., Tomé, A., Tröst, J., Väisänen, O., Wagner, A. C., Ylisirniö, A., Zha, Q., Baltensperger, U., Carslaw, K. S., Curtius, J., Flagan, R. C., Hansel, A., Riipinen, I., Smith, J. N., Virtanen, A., Winkler, P. M., Donahue, N. M., Kerminen, V.-M., Kulmala, M., Ehn, M., and Worsnop, D. R.

Abstract

Atmospheric new-particle formation (NPF) affects climate by contributing to a large fraction of the cloud condensation nuclei (CCN). Highly oxygenated organic molecules (HOMs) drive the early particle growth and therefore substantially influence the survival of newly formed particles to CCN. Nitrogen oxide (NOₓ) is known to suppress the NPF driven by HOMs, but the underlying mechanism remains largely unclear. Here, we examine the response of particle growth to the changes of HOM formation caused by NOₓ. We show that NOₓ suppresses particle growth in general, but the suppression is rather nonuniform and size dependent, which can be quantitatively explained by the shifted HOM volatility after adding NOₓ. By illustrating how NOₓ affects the early growth of new particles, a critical step of CCN formation, our results help provide a refined assessment of the potential climatic effects caused by the diverse changes of NOₓ level in forest regions around the globe.

Published
2020

10. Intercomparison and Evaluation of Global Aerosol Microphysical Properties Among Aerocom Models of a Range of Complexity

Author

Mann, G. W, Carslaw, K. S, Reddington, C. L, Pringle, K. J, Schulz, M, Asmi, A, Spracklen, D. V, Ridley, D. A, Woodhouse, M. T, Lee, L. A, Zhang, K, Ghan, S. J, Easter, R. C, Liu, X, Stier, P, Lee, Y. H, Adams, P. J, Tost, H, Lelieveld, J, Bauer, S. E, Tsigaridis, K, van Noije, T. P. C, Strunk, A, Vignati, E, and Bellouin, N

Subjects
Geophysics, Meteorology And Climatology
Abstract

Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multimodel- mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation an growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

Published
2014
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11. An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice

Author

Jiao, C, Flanner, M. G, Balkanski, Y, Bauer, S. E, Bellouin, N, Bernsten, T. K, Bian, H, Carslaw, K. S, Chin, M, DeLuca, N, Diehl, T, Ghan, S. J, Iversen, T, Kirkevag, A, Koch, D, Liu, X, Mann, G. W, Penner, J. E, Pitari, G, Schulz, M, Seland, O, Skeie, R. B, Steenrod, S. D, Stier, P, and Tkemura, T

Subjects
Meteorology And Climatology
Abstract

Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng/g for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng/g for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng/g. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90degN) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W/sq m and 0.18 (0.06-0.28) W/sq m in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W/sq m for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.

Published
2014
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12. Bounding Global Aerosol Radiative Forcing of Climate Change

Author

Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A. -L., Dufresne, J. -L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, Thorsten, McCoy, D. T., Myhre, G., Muelmenstaedt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., Stevens, B., Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A. -L., Dufresne, J. -L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, Thorsten, McCoy, D. T., Myhre, G., Muelmenstaedt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.

Abstract

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol-radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of -1.6 to -0.6Wm(-2), or -2.0 to -0.4Wm(-2) with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial-era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds. Plain Language Summary Human activities emit into the atmosphere small liquid and solid particles called aerosols. Those aerosols change the energy budget of the Earth and trigger climate changes, by scattering and absorbing solar and terrestrial radiation and playing important roles in the forma

Published
2020
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13. The APE-THESEO Tropical Campaign: An Overview

Author

Stefanutti, L., MacKenzie, A. R., Santacesaria, V., Adriani, A., Balestri, Stefano, Borrmann, S., Khattatov, V., Mazzinghi, P., Mitev, V., Rudakov, V., Schiller, C., Toci, G., Volk, C. M., Yushkov, V., Flentje, H., Kiemle, C., Redaelli, G., Carslaw, K. S., Noone, K., and Peter, Th.

Published
2004
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17. Iceland is an episodic source of atmospheric ice-nucleating particles relevant for mixed-phase clouds

Author

Sanchez-Marroquin, A., primary, Arnalds, O., additional, Baustian-Dorsi, K. J., additional, Browse, J., additional, Dagsson-Waldhauserova, P., additional, Harrison, A. D., additional, Maters, E. C., additional, Pringle, K. J., additional, Vergara-Temprado, J., additional, Burke, I. T., additional, McQuaid, J. B., additional, Carslaw, K. S., additional, and Murray, B. J., additional

Published
2020
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18. Size-dependent influence of NO x on the growth rates of organic aerosol particles

Author

Yan, C., primary, Nie, W., additional, Vogel, A. L., additional, Dada, L., additional, Lehtipalo, K., additional, Stolzenburg, D., additional, Wagner, R., additional, Rissanen, M. P., additional, Xiao, M., additional, Ahonen, L., additional, Fischer, L., additional, Rose, C., additional, Bianchi, F., additional, Gordon, H., additional, Simon, M., additional, Heinritzi, M., additional, Garmash, O., additional, Roldin, P., additional, Dias, A., additional, Ye, P., additional, Hofbauer, V., additional, Amorim, A., additional, Bauer, P. S., additional, Bergen, A., additional, Bernhammer, A.-K., additional, Breitenlechner, M., additional, Brilke, S., additional, Buchholz, A., additional, Mazon, S. Buenrostro, additional, Canagaratna, M. R., additional, Chen, X., additional, Ding, A., additional, Dommen, J., additional, Draper, D. C., additional, Duplissy, J., additional, Frege, C., additional, Heyn, C., additional, Guida, R., additional, Hakala, J., additional, Heikkinen, L., additional, Hoyle, C. R., additional, Jokinen, T., additional, Kangasluoma, J., additional, Kirkby, J., additional, Kontkanen, J., additional, Kürten, A., additional, Lawler, M. J., additional, Mai, H., additional, Mathot, S., additional, Mauldin, R. L., additional, Molteni, U., additional, Nichman, L., additional, Nieminen, T., additional, Nowak, J., additional, Ojdanic, A., additional, Onnela, A., additional, Pajunoja, A., additional, Petäjä, T., additional, Piel, F., additional, Quéléver, L. L. J., additional, Sarnela, N., additional, Schallhart, S., additional, Sengupta, K., additional, Sipilä, M., additional, Tomé, A., additional, Tröstl, J., additional, Väisänen, O., additional, Wagner, A. C., additional, Ylisirniö, A., additional, Zha, Q., additional, Baltensperger, U., additional, Carslaw, K. S., additional, Curtius, J., additional, Flagan, R. C., additional, Hansel, A., additional, Riipinen, I., additional, Smith, J. N., additional, Virtanen, A., additional, Winkler, P. M., additional, Donahue, N. M., additional, Kerminen, V.-M., additional, Kulmala, M., additional, Ehn, M., additional, and Worsnop, D. R., additional

Published
2020
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19. Constraining Uncertainty in Aerosol Direct Forcing

Author

Watson‐Parris, D., primary, Bellouin, N., additional, Deaconu, L. T., additional, Schutgens, N. A. J., additional, Yoshioka, M., additional, Regayre, L. A., additional, Pringle, K. J., additional, Johnson, J. S., additional, Smith, C. J., additional, Carslaw, K. S., additional, and Stier, P., additional

Published
2020
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20. Bounding Global Aerosol Radiative Forcing of Climate Change

Author

Bellouin, N., primary, Quaas, J., additional, Gryspeerdt, E., additional, Kinne, S., additional, Stier, P., additional, Watson‐Parris, D., additional, Boucher, O., additional, Carslaw, K. S., additional, Christensen, M., additional, Daniau, A.‐L., additional, Dufresne, J.‐L., additional, Feingold, G., additional, Fiedler, S., additional, Forster, P., additional, Gettelman, A., additional, Haywood, J. M., additional, Lohmann, U., additional, Malavelle, F., additional, Mauritsen, T., additional, McCoy, D. T., additional, Myhre, G., additional, Mülmenstädt, J., additional, Neubauer, D., additional, Possner, A., additional, Rugenstein, M., additional, Sato, Y., additional, Schulz, M., additional, Schwartz, S. E., additional, Sourdeval, O., additional, Storelvmo, T., additional, Toll, V., additional, Winker, D., additional, and Stevens, B., additional

Published
2020
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22. The Detection of Large HNO3-Containing Particles in the Winter Arctic Stratosphere

Author

Fahey, D. W., Gao, R. S., Carslaw, K. S., Kettleborough, J., Popp, P. J., Northway, M. J., Holecek, J. C., Ciciora, S. C., McLaughlin, R. J., Thompson, T. L., Winkler, R. H., Baumgardner, D. G., Gandrud, B., Wennberg, P. O., Dhaniyala, S., McKinney, K., Peter, Th., Salawitch, R. J., Bui, T. P., Elkins, J. W., Webster, C. R., Atlas, E. L., Jost, H., Wilson, J. C., Herman, R. L., Kleinböhl, A., and von König, M.

Published
2001

23. Recent observed changes in the North Atlantic climate system with a focus on 2005-2016

Author

Robson, J, Sutton, RT, Archibald, A, Cooper, F, Christensen, M, Grey, LJ, Holliday, NP, Macintosh, C, McMillan, M, Moat, B, Russo, M, Tilling, R, Carslaw, K, Desbruyères, D, Embury, O, Feltham, D, Grosvenor, D, Josey, S, King, B, Lewis, A, McCarthy, GD, Merchant, C, New, AL, O'Reilly, CH, Osprey, SM, Read, K, Scaife, A, Shepherd, A, Sinha, B, Smeed, D, Smith, D, Ridout, A, Woollings, TJ, and Yang, M

Abstract

Major changes are occurring across the North Atlantic climate system, including in the atmosphere, ocean and cryosphere, and many observed changes are unprecedented in instrumental records. As the changes in the North Atlantic directly affect the climate and air quality of the surrounding continents, it is important to fully understand how and why the changes are taking place, not least to predict how the region will change in the future. To this end, this article characterizes the recent observed changes in the North Atlantic region, especially in the period 2005–2016, across many different aspects of the system including: atmospheric circulation; atmospheric composition; clouds and aerosols; ocean circulation and properties; and the cryosphere. Recent changes include: an increase in the speed of the North Atlantic jet stream in winter; a southward shift in the North Atlantic jet stream in summer, associated with a weakening summer North Atlantic Oscillation; increases in ozone and methane; increases in net absorbed radiation in the mid‐latitude western Atlantic, linked to an increase in the abundance of high level clouds and a reduction in low level clouds; cooling of sea surface temperatures in the North Atlantic subpolar gyre, concomitant with increases in the western subtropical gyre, and a decline in the Atlantic Ocean's overturning circulation; a decline in Atlantic sector Arctic sea ice and rapid melting of the Greenland Ice Sheet. There are many interactions between these changes, but these interactions are poorly understood. This article concludes by highlighting some of the key outstanding questions.

Published
2018

24. Multi-model comparison of the volcanic sulfate deposition from the 1815 eruption of Mt. Tambora

Author

Marshall, L., Schmidt, A., Toohey, M., Carslaw, K. S., Mann, G. W., Sigl, M., Khodri, Myriam, Timmreck, C., Zanchettin, D., Ball, W. T., Bekki, S., Brooke, J. S. A., Dhomse, S., Johnson, C., Lamarque, J. F., LeGrande, A. N., Mills, M. J., Niemeier, U., Pope, J. O., Poulain, V., Robock, A., Rozanov, E., Stenke, A., Sukhodolov, T., Tilmes, S., Tsigaridis, K., Tummon, F., Institute for Climate and Atmospheric Science [Leeds] (ICAS), School of Earth and Environment [Leeds] (SEE), University of Leeds-University of Leeds, Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, National Centre for Atmospheric Science [Leeds] (NCAS), Natural Environment Research Council (NERC), Laboratory of Environmental Chemistry [Villigen] (LUC), Paul Scherrer Institute (PSI), Océan et variabilité du climat (VARCLIM), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Max Planck Institute for Meteorology (MPI-M), Department of Environmental Sciences, Informatics and Statistics [Venezia], University of Ca’ Foscari [Venice, Italy], Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), School of Chemistry [Leeds], University of Leeds, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Atmospheric Chemistry Observations and Modeling Laboratory (ACOML), National Center for Atmospheric Research [Boulder] (NCAR), NASA Goddard Space Flight Center (GSFC), British Antarctic Survey (BAS), Processus de la variabilité climatique tropicale et impacts (PARVATI), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Department of Environmental Sciences [New Brunswick], School of Environmental and Biological Sciences [New Brunswick], Rutgers, The State University of New Jersey [New Brunswick] (RU), Rutgers University System (Rutgers)-Rutgers University System (Rutgers)-Rutgers, The State University of New Jersey [New Brunswick] (RU), Rutgers University System (Rutgers)-Rutgers University System (Rutgers), NASA Goddard Institute for Space Studies (GISS), Center for Climate Systems Research [New York] (CCSR), Columbia University [New York], The Arctic University of Norway [Tromsø, Norway] (UiT), US National Science Foundation grant AGS-1430051, German Federal Ministry of Education and Research (BMBF), research program 'MiKliP' (FKZ: 01LP1517B, Swiss National Science Foundation grant 20F121_138017, NERC grant NEK/K012150/1, ANR-10-LABX-0018,L-IPSL,LabEx Institut Pierre Simon Laplace (IPSL): Understand climate and anticipate future changes(2010), European Project: 603557,EC:FP7:ENV,FP7-ENV-2013-two-stage,STRATOCLIM(2013), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), and The Arctic University of Norway (UiT)

Subjects
[SDU.STU.VO]Sciences of the Universe [physics]/Earth Sciences/Volcanology, Settore GEO/12 - Oceanografia e Fisica dell'Atmosfera
Abstract

Source at https://doi.org/10.5194/acp-18-2307-2018. The eruption of Mt. Tambora in 1815 was the largest volcanic eruption of the past 500 years. The eruption had significant climatic impacts, leading to the 1816 "year without a summer", and remains a valuable event from which to understand the climatic effects of large stratospheric volcanic sulfur dioxide injections. The eruption also resulted in one of the strongest and most easily identifiable volcanic sulfate signals in polar ice cores, which are widely used to reconstruct the timing and atmospheric sulfate loading of past eruptions. As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), five state-of-the-art global aerosol models simulated this eruption. We analyse both simulated background (no Tambora) and volcanic (with Tambora) sulfate deposition to polar regions and compare to ice core records. The models simulate overall similar patterns of background sulfate deposition, although there are differences in regional details and magnitude. However, the volcanic sulfate deposition varies considerably between the models with differences in timing, spatial pattern and magnitude. Mean simulated deposited sulfate on Antarctica ranges from 19 to 264 kg km−2 and on Greenland from 31 to 194 kg km−2, as compared to the mean ice-core-derived estimates of roughly 50 kg km−2 for both Greenland and Antarctica. The ratio of the hemispheric atmospheric sulfate aerosol burden after the eruption to the average ice sheet deposited sulfate varies between models by up to a factor of 15. Sources of this inter-model variability include differences in both the formation and the transport of sulfate aerosol. Our results suggest that deriving relationships between sulfate deposited on ice sheets and atmospheric sulfate burdens from model simulations may be associated with greater uncertainties than previously thought.

Published
2018
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26. Ensembles of Global Climate Model Variants Designed for the Quantification and Constraint of Uncertainty in Aerosols and Their Radiative Forcing

Author

Yoshioka, M., primary, Regayre, L. A., additional, Pringle, K. J., additional, Johnson, J. S., additional, Mann, G. W., additional, Partridge, D. G., additional, Sexton, D. M. H., additional, Lister, G. M. S., additional, Schutgens, N., additional, Stier, P., additional, Kipling, Z., additional, Bellouin, N., additional, Browse, J., additional, Booth, B. B. B., additional, Johnson, C. E., additional, Johnson, B., additional, Mollard, J. D. P., additional, Lee, L., additional, and Carslaw, K. S., additional

Published
2019
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32. Impact on short-lived climate forcers increases projected warming due to deforestation

Author

Scott, C. E., primary, Monks, S. A., additional, Spracklen, D. V., additional, Arnold, S. R., additional, Forster, P. M., additional, Rap, A., additional, Äijälä, M., additional, Artaxo, P., additional, Carslaw, K. S., additional, Chipperfield, M. P., additional, Ehn, M., additional, Gilardoni, S., additional, Heikkinen, L., additional, Kulmala, M., additional, Petäjä, T., additional, Reddington, C. L. S., additional, Rizzo, L. V., additional, Swietlicki, E., additional, Vignati, E., additional, and Wilson, C., additional

Published
2018
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34. Quantifying sources of inter-model diversity in the cloud albedo effect

Author

Wilcox, L. J., Highwood, E. J., Booth, B. B. B., and Carslaw, K. S.

Abstract

There is large diversity in simulated aerosol forcing among models that participated in the fifth Coupled Model Intercomparison Project (CMIP5), particularly related to aerosol interactions with clouds. Here we use the reported model data and fitted aerosol-cloud relations to separate the main sources of inter-model diversity in the magnitude of the cloud albedo effect. There is large diversity in the global load and spatial distribution of sulfate aerosol, as well as in global-mean cloud-top effective radius. The use of different parameterizations of aerosol-cloud interactions makes the largest contribution to diversity \ud in modeled radiative forcing (up to -39%, +48% about the mean estimate). Uncertainty in pre-industrial sulfate load also makes a substantial contribution (-15%, +61% about the mean estimate), with smaller contributions from inter-model differences in the historical change in sulfate load and in mean cloud fraction.

Published
2015

35. Synthesis of CCN data from the ACTRIS network and complementary observation sites

Author

Kos, G.P.A., Whitehead, J., Baltensperger, U., Carslaw, K., Stratmann, F., Holzinger, R., Henzing, J.S., Schmale, J., Schlag, P., Aalto, P.P., Keskinen, H., Paramonov, M., Henning, S., Poulain, L., Sellegri, K., Ovadnevaite, J., Krüger, M., Carbone, S., Brito, J., Jefferson, A., Yum, S.S., Park, M., Fröhlich, R., Herrmann, E., Hammer, E., Gysel, M., CCN Team, University of Crete, Heraklion, Greec., and Energieonderzoek Centrum Nederland

Published
2015

36. Effect of ions on sulfuric acid-water binary particle formation : 2. Experimental data and comparison with QC-normalized classical nucleation theory

Author

Duplissy, J., Merikanto, J., Franchin, A., Tsagkogeorgas, G., Kangasluoma, J., Wimmer, D., Vuollekoski, H., Schobesberger, S., Lehtipalo, K., Flagan, R. C., Brus, D., Donahue, N. M., Vehkamaki, H., Almeida, J., Amorim, A., Barmet, P., Bianchi, F., Breitenlechner, M., Dunne, E. M., Guida, R., Henschel, Henning, Junninen, H., Kirkby, J., Kuerten, A., Kupc, A., Maattanen, A., Makhmutov, V., Mathot, S., Nieminen, T., Onnela, A., Praplan, A. P., Riccobono, F., Rondo, L., Steiner, G., Tome, A., Walther, H., Baltensperger, U., Carslaw, K. S., Dommen, J., Hansel, A., Petaja, T., Sipila, M., Stratmann, F., Vrtala, A., Wagner, P. E., Worsnop, D. R., Curtius, J., Kulmala, M., Duplissy, J., Merikanto, J., Franchin, A., Tsagkogeorgas, G., Kangasluoma, J., Wimmer, D., Vuollekoski, H., Schobesberger, S., Lehtipalo, K., Flagan, R. C., Brus, D., Donahue, N. M., Vehkamaki, H., Almeida, J., Amorim, A., Barmet, P., Bianchi, F., Breitenlechner, M., Dunne, E. M., Guida, R., Henschel, Henning, Junninen, H., Kirkby, J., Kuerten, A., Kupc, A., Maattanen, A., Makhmutov, V., Mathot, S., Nieminen, T., Onnela, A., Praplan, A. P., Riccobono, F., Rondo, L., Steiner, G., Tome, A., Walther, H., Baltensperger, U., Carslaw, K. S., Dommen, J., Hansel, A., Petaja, T., Sipila, M., Stratmann, F., Vrtala, A., Wagner, P. E., Worsnop, D. R., Curtius, J., and Kulmala, M.

Published
2016
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37. Effect of ions on sulfuric acid‐water binary particle formation: 2. Experimental data and comparison with QC‐normalized classical nucleation theory

Author

Duplissy, J., primary, Merikanto, J., additional, Franchin, A., additional, Tsagkogeorgas, G., additional, Kangasluoma, J., additional, Wimmer, D., additional, Vuollekoski, H., additional, Schobesberger, S., additional, Lehtipalo, K., additional, Flagan, R. C., additional, Brus, D., additional, Donahue, N. M., additional, Vehkamäki, H., additional, Almeida, J., additional, Amorim, A., additional, Barmet, P., additional, Bianchi, F., additional, Breitenlechner, M., additional, Dunne, E. M., additional, Guida, R., additional, Henschel, H., additional, Junninen, H., additional, Kirkby, J., additional, Kürten, A., additional, Kupc, A., additional, Määttänen, A., additional, Makhmutov, V., additional, Mathot, S., additional, Nieminen, T., additional, Onnela, A., additional, Praplan, A. P., additional, Riccobono, F., additional, Rondo, L., additional, Steiner, G., additional, Tome, A., additional, Walther, H., additional, Baltensperger, U., additional, Carslaw, K. S., additional, Dommen, J., additional, Hansel, A., additional, Petäjä, T., additional, Sipilä, M., additional, Stratmann, F., additional, Vrtala, A., additional, Wagner, P. E., additional, Worsnop, D. R., additional, Curtius, J., additional, and Kulmala, M., additional

Published
2016
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38. The impact of European legislative and technology measures to reduce air pollutants on air quality, human health and climate

Author

Turnock, S T, primary, Butt, E W, additional, Richardson, T B, additional, Mann, G W, additional, Reddington, C L, additional, Forster, P M, additional, Haywood, J, additional, Crippa, M, additional, Janssens-Maenhout, G, additional, Johnson, C E, additional, Bellouin, N, additional, Carslaw, K S, additional, and Spracklen, D V, additional

Published
2016
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39. Particulate matter, air quality and climate : lessons learned and future needs

Author

Fuzzi, S., Baltensperger, U., Carslaw, K., Decesari, S., van der Gon, H. Denier, Facchini, M. C., Fowler, D., Koren, I., Langford, B., Lohmann, U., Nemitz, E., Pandis, S., Riipinen, Ilona, Rudich, Y., Schaap, M., Slowik, J. G., Spracklen, D. V., Vignati, E., Wild, M., Williams, M., Gilardoni, S., Fuzzi, S., Baltensperger, U., Carslaw, K., Decesari, S., van der Gon, H. Denier, Facchini, M. C., Fowler, D., Koren, I., Langford, B., Lohmann, U., Nemitz, E., Pandis, S., Riipinen, Ilona, Rudich, Y., Schaap, M., Slowik, J. G., Spracklen, D. V., Vignati, E., Wild, M., Williams, M., and Gilardoni, S.

Abstract

The literature on atmospheric particulate matter (PM), or atmospheric aerosol, has increased enormously over the last 2 decades and amounts now to some 1500-2000 papers per year in the refereed literature. This is in part due to the enormous advances in measurement technologies, which have allowed for an increasingly accurate understanding of the chemical composition and of the physical properties of atmospheric particles and of their processes in the atmosphere. The growing scientific interest in atmospheric aerosol particles is due to their high importance for environmental policy. In fact, particulate matter constitutes one of the most challenging problems both for air quality and for climate change policies. In this context, this paper reviews the most recent results within the atmospheric aerosol sciences and the policy needs, which have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-aerosol interactions and effects of PM on human health and the environment. However, while airborne particulate matter is responsible for globally important influences on premature human mortality, we still do not know the relative importance of the different chemical components of PM for these effects. Likewise, the magnitude of the overall effects of PM on climate remains highly uncertain. Despite the uncertainty there are many things that could be done to mitigate local and global problems of atmospheric PM. Recent analyses have shown that reducing black carbon (BC) emissions, using known control measures, would reduce global warming and delay the time when anthropogenic effects on global temperature would exceed 2 degrees C. Likewise, cost-effective control measures on ammonia, an important agricultural precursor gas for secondary inorganic aerosols (SIA), would reduce regional eutrophication and PM concentrations in large areas of Europe, C

Published
2015
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40. Impact of gas-to-particle partitioning approaches on the simulated radiative effects of biogenic secondary organic aerosol

Author

Scott, C. E., Spracklen, D. V., Pierce, J. R., Riipinen, Ilona, D'Andrea, S. D., Rap, A., Carslaw, K. S., Forster, P. M., Artaxo, P., Kulmala, M., Rizzo, L. V., Swietlicki, E., Mann, G. W., Pringle, K. J., Scott, C. E., Spracklen, D. V., Pierce, J. R., Riipinen, Ilona, D'Andrea, S. D., Rap, A., Carslaw, K. S., Forster, P. M., Artaxo, P., Kulmala, M., Rizzo, L. V., Swietlicki, E., Mann, G. W., and Pringle, K. J.

Abstract

The oxidation of biogenic volatile organic compounds (BVOCs) gives a range of products, from semi-volatile to extremely low-volatility compounds. To treat the interaction of these secondary organic vapours with the particle phase, global aerosol microphysics models generally use either a thermodynamic partitioning approach (assuming instant equilibrium between semi-volatile oxidation products and the particle phase) or a kinetic approach (accounting for the size dependence of condensation). We show that model treatment of the partitioning of biogenic organic vapours into the particle phase, and consequent distribution of material across the size distribution, controls the magnitude of the first aerosol indirect effect (AIE) due to biogenic secondary organic aerosol (SOA). With a kinetic partitioning approach, SOA is distributed according to the existing condensation sink, enhancing the growth of the smallest particles, i.e. those in the nucleation mode. This process tends to increase cloud droplet number concentrations in the presence of biogenic SOA. By contrast, an approach that distributes SOA according to pre-existing organic mass restricts the growth of the smallest particles, limiting the number that are able to form cloud droplets. With an organically mediated new particle formation mechanism, applying a mass-based rather than a kinetic approach to partitioning reduces our calculated global mean AIE due to biogenic SOA by 24 %. Our results suggest that the mechanisms driving organic partitioning need to be fully understood in order to accurately describe the climatic effects of SOA.

Published
2015
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41. Impact of gas-to-particle partitioning approaches on the simulated radiative effects of biogenic secondary organic aerosol

Author

University of Helsinki, Department of Physics, Scott, C. E., Spracklen, D. V., Pierce, J. R., Riipinen, I., D'Andrea, S. D., Rap, A., Carslaw, K. S., Forster, P. M., Artaxo, P., Kulmala, M., Rizzo, L. V., Swietlicki, E., Mann, G. W., Pringle, K. J., University of Helsinki, Department of Physics, Scott, C. E., Spracklen, D. V., Pierce, J. R., Riipinen, I., D'Andrea, S. D., Rap, A., Carslaw, K. S., Forster, P. M., Artaxo, P., Kulmala, M., Rizzo, L. V., Swietlicki, E., Mann, G. W., and Pringle, K. J.

Abstract

The oxidation of biogenic volatile organic compounds (BVOCs) gives a range of products, from semi-volatile to extremely low-volatility compounds. To treat the interaction of these secondary organic vapours with the particle phase, global aerosol microphysics models generally use either a thermodynamic partitioning approach (assuming instant equilibrium between semi-volatile oxidation products and the particle phase) or a kinetic approach (accounting for the size dependence of condensation). We show that model treatment of the partitioning of biogenic organic vapours into the particle phase, and consequent distribution of material across the size distribution, controls the magnitude of the first aerosol indirect effect (AIE) due to biogenic secondary organic aerosol (SOA). With a kinetic partitioning approach, SOA is distributed according to the existing condensation sink, enhancing the growth of the smallest particles, i.e. those in the nucleation mode. This process tends to increase cloud droplet number concentrations in the presence of biogenic SOA. By contrast, an approach that distributes SOA according to pre-existing organic mass restricts the growth of the smallest particles, limiting the number that are able to form cloud droplets. With an organically mediated new particle formation mechanism, applying a mass-based rather than a kinetic approach to partitioning reduces our calculated global mean AIE due to biogenic SOA by 24 %. Our results suggest that the mechanisms driving organic partitioning need to be fully understood in order to accurately describe the climatic effects of SOA.

Published
2015

42. Modelled and observed changes in aerosols and surface solar radiation over Europe between 1960 and 2009

Author

Turnock, S. T., Spracklen, D. V., Carslaw, K. S., Mann, G. W., Woodhouse, M. T., Forster, P. M., Haywood, J., Johnson, C. E., Dalvi, M., Bellouin, N., Sánchez-Lorenzo, Arturo, Turnock, S. T., Spracklen, D. V., Carslaw, K. S., Mann, G. W., Woodhouse, M. T., Forster, P. M., Haywood, J., Johnson, C. E., Dalvi, M., Bellouin, N., and Sánchez-Lorenzo, Arturo

Abstract

Substantial changes in anthropogenic aerosols and precursor gas emissions have occurred over recent decades due to the implementation of air pollution control legislation and economic growth. The response of atmospheric aerosols to these changes and the impact on climate are poorly constrained, particularly in studies using detailed aerosol chemistry climate models. Here we compare the HadGEM3-UKCA coupled chemistry-climate model for the period 1960 to 2009 against extensive ground based observations of sulfate aerosol mass (1978–2009), total suspended particle matter (SPM, 1978–1998), PM10 (1997–2009), aerosol optical depth (AOD, 2000–2009) and surface solar radiation (SSR, 1960–2009) over Europe. The model underestimates observed sulfate aerosol mass (normalised mean bias factor (NMBF) = −0.4), SPM (NMBF = −0.9), PM10 (NMBF = −0.2) and aerosol optical depth (AOD, NMBF = −0.01) but slightly overpredicts SSR (NMBF = 0.02). Trends in aerosol over the observational period are well simulated by the model, with observed (simulated) changes in sulfate of −68% (−78%), SPM of −42% (−20%), PM10 of −9% (−8%) and AOD of −11% (−14%). Discrepancies in the magnitude of simulated aerosol mass do not affect the ability of the model to reproduce the observed SSR trends. The positive change in observed European SSR (5%) during 1990–2009 (>brightening>) is better reproduced by the model when aerosol radiative effects (ARE) are included (3%), compared to simulations where ARE are excluded (0.2%). The simulated top-of-the-atmosphere aerosol radiative forcing over Europe under all-sky conditions increased by 3 W m−2 during the period 1970–2009 in response to changes in anthropogenic emissions and aerosol concentrations. © Author(s) 2015.

Published
2015

43. Tropospheric Aerosol: Formation, Trasformation, Fate and Impacts. General Discussion

Author

Wahner, A., Pandis, S., Allan, J., Mc Figgans, G., Abbatt, J., Freedman, M., Johnston, M., Harrison, R., Donahue, N., Percival, C., Heard, D., Carslaw, K., Jacobson, M., Olenius, T., Vehkamaki, H., Nizkorodov, S., Kiendler Scharr, A., Cappelletti, David Michele, Herrmann, H., Cox, T., Mcneill, V. F., Lewis, A., Colomer Ortega, I. K., Krieger, U., Colussi, A., Aumont, B., Kroll, J., Volkamer, R., Noziere, B., Abbat, J., Rudich, Y., Knopf, D., Held, A., and Villenave, E.

Published
2013

44. General discussion. Tropospheric aerosol - formation, transformation, fate and impacts

Author

Wahner, A., Pandis, S., Allan, J., Mcfiggans, G., Abbatt, J., Freedman, M., Johnston, M., Harrison, R., Donahue, N., Percival, C., Heard, D., Carslaw, K., Jacobson, M., Olenius, T., Vehkamaki, H., Nizkorodov, S., Kiendler Scharr, A., Cappelletti, David Michele, Herrmann, H., Cox, T., Mcneill, Vf, Lewis, A., Colomer Ortega, Ik, Krieger, U., Colussi, A., Aumont, A., Kroll, J., Volkamer, R., Noziere, B., Rudich, Y., Knopf, D., Held, A, and Villenave, E.

Published
2013

45. Impact of gas-to-particle partitioning approaches on the simulated radiative effects of biogenic secondary organic aerosol

Author

Scott, C. E., primary, Spracklen, D. V., additional, Pierce, J. R., additional, Riipinen, I., additional, D'Andrea, S. D., additional, Rap, A., additional, Carslaw, K. S., additional, Forster, P. M., additional, Artaxo, P., additional, Kulmala, M., additional, Rizzo, L. V., additional, Swietlicki, E., additional, Mann, G. W., additional, and Pringle, K. J., additional

Published
2015
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47. Particulate matter, air quality and climate: lessons learned and future needs

Author

Fuzzi, S., primary, Baltensperger, U., additional, Carslaw, K., additional, Decesari, S., additional, Denier van der Gon, H., additional, Facchini, M. C., additional, Fowler, D., additional, Koren, I., additional, Langford, B., additional, Lohmann, U., additional, Nemitz, E., additional, Pandis, S., additional, Riipinen, I., additional, Rudich, Y., additional, Schaap, M., additional, Slowik, J. G., additional, Spracklen, D. V., additional, Vignati, E., additional, Wild, M., additional, Williams, M., additional, and Gilardoni, S., additional

Published
2015
Full Text
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48. Experimental investigation of ion–ion recombination under atmospheric conditions

Author

Franchin, A., primary, Ehrhart, S., additional, Leppä, J., additional, Nieminen, T., additional, Gagné, S., additional, Schobesberger, S., additional, Wimmer, D., additional, Duplissy, J., additional, Riccobono, F., additional, Dunne, E. M., additional, Rondo, L., additional, Downard, A., additional, Bianchi, F., additional, Kupc, A., additional, Tsagkogeorgas, G., additional, Lehtipalo, K., additional, Manninen, H. E., additional, Almeida, J., additional, Amorim, A., additional, Wagner, P. E., additional, Hansel, A., additional, Kirkby, J., additional, Kürten, A., additional, Donahue, N. M., additional, Makhmutov, V., additional, Mathot, S., additional, Metzger, A., additional, Petäjä, T., additional, Schnitzhofer, R., additional, Sipilä, M., additional, Stozhkov, Y., additional, Tomé, A., additional, Kerminen, V.-M., additional, Carslaw, K., additional, Curtius, J., additional, Baltensperger, U., additional, and Kulmala, M., additional

Published
2015
Full Text
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50. Experimental investigation of ion-ion recombination at atmospheric conditions

Author

Franchin, A., primary, Ehrhart, S., additional, Leppä, J., additional, Nieminen, T., additional, Gagné, S., additional, Schobesberger, S., additional, Wimmer, D., additional, Duplissy, J., additional, Riccobono, F., additional, Dunne, E., additional, Rondo, L., additional, Downard, A., additional, Bianchi, F., additional, Kupc, A., additional, Tsagkogeorgas, G., additional, Lehtipalo, K., additional, Manninen, H. E., additional, Almeida, J., additional, Amorim, A., additional, Wagner, P. E., additional, Hansel, A., additional, Kirkby, J., additional, Kürten, A., additional, Donahue, N. M., additional, Makhmutov, V., additional, Mathot, S., additional, Metzger, A., additional, Petäjä, T., additional, Schnitzhofer, R., additional, Sipilä, M., additional, Stozhkov, Y., additional, Tomé, A., additional, Kerminen, V.-M., additional, Carslaw, K., additional, Curtius, J., additional, Baltensperger, U., additional, and Kulmala, M., additional

Published
2015
Full Text
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