2019, Braakhekke, Maarten C., Doelman, Jonathan C., Baas, Peter, Müller, Christoph, Schaphoff, Sibyll, Stehfest, Elke, van Vuuren, Detlef P.

We present an extension of the dynamic global vegetation model, Lund-Potsdam-Jena Managed Land (LPJmL), to simulate planted forests intended for carbon (C) sequestration. We implemented three functional types to simulate plantation trees in temperate, tropical, and boreal climates. The parameters of these functional types were optimized to fit target growth curves (TGCs). These curves represent the evolution of stemwood C over time in typical productive plantations and were derived by combining field observations and LPJmL estimates for equivalent natural forests. While the calibrated model underestimates stemwood C growth rates compared to the TGCs, it represents substantial improvement over using natural forests to represent afforestation. Based on a simulation experiment in which we compared global natural forest versus global forest plantation, we found that forest plantations allow for much larger C uptake rates on the timescale of 100 years, with a maximum difference of a factor of 1.9, around 54 years. In subsequent simulations for an ambitious but realistic scenario in which 650Mha (14% of global managed land, 4.5% of global land surface) are converted to forest over 85 years, we found that natural forests take up 37PgC versus 48PgC for forest plantations. Comparing these results to estimations of C sequestration required to achieve the 2°C climate target, we conclude that afforestation can offer a substantial contribution to climate mitigation. Full evaluation of afforestation as a climate change mitigation strategy requires an integrated assessment which considers all relevant aspects, including costs, biodiversity, and trade-offs with other land-use types. Our extended version of LPJmL can contribute to such an assessment by providing improved estimates of C uptake rates by forest plantations. © 2019 American Institute of Physics Inc.. All rights reserved.

2018, Sun, J., Birmili, W., Hermann, M., Tuch, T., Weinhold, K., Spindler, G., Schladitz, A., Bastian, S., Löschau, G., Cyrys, J., Gu, J., Flentje, H., Briel, B., Asbac, C., Kaminski, H., Ries, L., Sohme, R., Gerwig, H., Wirtz, K., Meinhardt, F., Schwerin, A., Bath, O., Ma, N., Wiedensohler, A.

This work reports the first statistical analysis of multi-annual data on tropospheric aerosols from the German Ultrafine Aerosol Network (GUAN). Compared to other networks worldwide, GUAN with 17 measurement locations has the most sites equipped with particle number size distribution (PNSD) and equivalent black carbon (eBC) instruments and the most site categories in Germany ranging from city street/roadside to High Alpine. As we know, the variations of eBC and particle number concentration (PNC) are influenced by several factors such as source, transformation, transport and deposition. The dominant controlling factor for different pollutant parameters might be varied, leading to the different spatio-temporal variations among the measured parameters. Currently, a study of spatio-temporal variations of PNSD and eBC considering the influences of both site categories and spatial scale is still missing. Based on the multi-site dataset of GUAN, the goal of this study is to investigate how pollutant parameters may interfere with spatial characteristics and site categories. © 2019 The Authors