This paper presents a detailed analysis of the climate of the last interglacial simulated by two climate models of different complexities, CCSM3 (Community Climate System Model 3) and LOVECLIM (LOch-Vecode-Ecbilt-CLio-agIsm Model). The simulated surface temperature, hydrological cycle, vegetation and ENSO variability during the last interglacial are analyzed through the comparison with the simulated pre-industrial (PI) climate. In both models, the last interglacial period is characterized by a significant warming (cooling) over almost all the continents during boreal summer (winter) leading to a largely increased (reduced) seasonal contrast in the Northern (Southern) Hemisphere. This is mainly due to the much higher (lower) insolation received by the whole Earth in boreal summer (winter) during this interglacial. The Arctic is warmer than PI through the whole year, resulting from its much higher summer insolation, its remnant effect in the following fall-winter through the interactions between atmosphere, ocean and sea ice and feedbacks from sea ice and snow cover. Discrepancies exist in the sea-ice formation zones between the two models. Cooling is simulated by CCSM3 in the Greenland and Norwegian seas and near the shelves of Antarctica during DJF but not in LOVECLIM as a result of excessive sea-ice formation. Intensified African monsoon is responsible for the cooling during summer in northern Africa and on the Arabian Peninsula. Over India, the precipitation maximum is found further west, while in Africa the precipitation maximum migrates further north. Trees and grassland expand north in Sahel/Sahara, more clearly seen in LOVECLIM than in CCSM3 results. A mix of forest and grassland occupies continents and expands deep into the high northern latitudes. Desert areas reduce significantly in the Northern Hemisphere, but increase in northern Australia. The interannual SST variability of the tropical Pacific (El-Niño Southern Oscillation) of the last interglacial simulated by CCSM3 shows slightly larger variability and magnitude compared to the PI. However, the SST variability in our LOVECLIM simulations is particularly small due to the overestimated thermocline's depth

We developed a model (CiTTy-Street-UFP) of traffic-related particle behaviour in a street canyon and in the nearby downwind urban background that accounts for aerosol dynamics and the variable vapour pressure of component organics. The model simulates the evolution and fate of traffic generated multicomponent ultrafine particles (UFP) composed of a non-volatile core and 17 Semi-Volatile Organic Compounds (SVOC, modelled as n-alkane proxies). A two-stage modelling approach is adopted: (1) a steady state simulation inside the street canyon is achieved, in which there exists a balance between traffic emissions, condensation/evaporation, deposition, coagulation and exchange with the air above roof-level; and (2) a continuing simulation of the above-roof air parcel advected to the nearby urban park during which evaporation is dominant. We evaluate the component evaporation and associated composition changes of multicomponent organic particles in realistic atmospheric conditions and compare our results with observations from London (UK) in a street canyon and an urban park. With plausible input conditions and parameter settings, the model can reproduce, with reasonable fidelity, size distributions in central London in 2007. The modelled nucleation-mode peak diameter, which is 23 nm in the steady-state street canyon, decreases to 9 nm in a travel time of just 120 s. All modelled SVOC in the sub-10 nm particle size range have evaporated leaving behind only non-volatile material, whereas modelled particle composition in the Aitken mode contains SVOC between C26H54 and C32H66. No data on particle composition are available in the study used for validation, or elsewhere. Measurements addressing in detail the size resolved composition of the traffic emitted UFP in the atmosphere are a high priority for future research. Such data would improve the representation of these particles in dispersion models and provide the data essential for model validation. Enhanced knowledge of the chemical composition of nucleation-mode particles from diesel engine exhaust is needed to predict both their atmospheric behaviour and their implications for human health.

No abstract

No abstract