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Diesel engine exhausts from a common rail 3.0 L F1C diesel engine were analyzed at two different load conditions of the WLTC testing cycle downstream of both the diesel particulate filter (DPF) and selective catalytic reactor (SCR) to verify their effect on the characteristics of carbon particulate matter. An array of chemical, physical and spectroscopic techniques (gas chromatography coupled with mass spectrometry (GC-MS), mobility analyzer, UV-Visible absorption and fluorescence spectroscopy) was applied for characterizing polycyclic aromatic hydrocarbons (PAH), heavy aromatic compounds and soot, constituting the particulate matter (PM) sampled from the exhaust. The engine was operated in half load (HL) (188 Nm, representing the more common condition for engine in urban traffic) and full load (FL) (452 Nm, representing the best performance of the engine operation) conditions, at the same engine speed (2000 rpm). Soot formation was enhanced in HL condition, with respect to FL, but, just because of the much lower soot amount, the after-treatment systems in this last condition resulted to be less efficient in the soot abatement. Indeed, the abatement through DPF was about 40% lower in the FL condition with respect to HL condition, and any significant further concentration decrease was found after SCR, in both conditions. By contrast, PAH concentration after DPF abatement was found to be higher in the HL with respect to FL condition. A further PAH concentration decrease of about 30% was found after the SCR in the HL condition whereas in FL the reduction was only about 5-6%. Also the heavy aromatic compounds having molecular weight above the GC-MS detection limit (300 u), were mitigated by SCR. Therefore, SCR did not cause a further soot reduction, whereas it was effective in largely reducing PAH and heavy aromatics emissions, especially in the lower temperature condition featuring the half-load condition, when combustion efficiency is worse. Moreover, SCR system reduced the emission of small particles probably due to an enhanced agglomeration of particles, with beneficial effect on the harmfulness to human health.

In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to -21°C (9°C) for Tmrt and up to -6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.

It is recognised that several constraints such as the lack of knowledge and expertise of farmers, land users and policy makers concerning agroforestry systems establishment and management hamper the adoption of agroforestry systems (Camilli et al. 2017). AFINET project acts at EU level in order to direct research results into practice and promote innovative ideas to face challenges and solve practitioners' problems. AFINET proposes an innovative methodology based on the creation of a European Interregional Network, linking different Regional Agroforestry Innovation Networks (RAINs). RAINs represent different climatic, geographical, social and cultural conditions and enclose a balanced representation of the key actors with complementary types of expertise (farmers, policy makers, advisory services, extension services, etc.). The Italian RAIN is focused on the Extra-Virgin Olive Oil (EVOO) value chain, with the main aim to promote agroforestry management of local olive orchards. Olive trees are still managed traditionally, often in marginal sites, with minimal mechanization and relatively low external inputs such as chemical treatments in comparison to other crops. The presence of permanent crops (olive trees) guarantees a partially tree cover reducing hydrogeological risk. Soil management usually keeps natural grassing reducing soil carbon emission and increasing soil fertility (Bateni et al. 2017). Intercropping with cereals and/or fodder legumes and livestock can also be practiced in olive orchards, increasing the complexity of the olive tree multifunctional system. Moreover, olive orchards can be managed as agroforestry systems since they can be intercropped with arable crops (cereals, legumes) and/or combined with livestock (sheep, poultry). The RAIN process, involving local stakeholders, highlighted the main bottlenecks of the EVOO value chain related to communication and dissemination of knowledge, technical and management aspects, market and policy. In order to contrast bottlenecks and exploit opportunities of the olive oil supply chain, the identified innovations are: i) adoption of best practices: testing and experimenting innovative agroforestry systems introducing different crop/animals species and varieties; ii) improve the management of the olive orchards: encouraging and increasing the organic production; iii) valorisation of olive processing residues: identifying and testing innovative products (bio-materials, olive paste as example); iv) arise the awareness among consumers: educating people about the benefits of olive oil consumption, creating networks among stakeholders, improving marketing and commercialization. Creating a Bio-district, defined as a geographical area where farmers, citizens, tourist operators, associations and public authorities enter into an agreement for the sustainable management of local resources, emerged a powerful tool to implement the innovation in the local EVOO value chain.

Abstract The question whether coexistence of marine renewable energy (MRE) projects and marine protected areas (MPAs) is a common spatial policy in Europe and how a number of factors can affect it, has been addressed by empirical research undertaken in eleven European marine areas. Policy drivers and objectives that are assumed to affect coexistence, such as the fulfillment of conservation objectives and the prioritization of other competing marine uses, were scored by experts and predictions were crosschecked with state practice. While in most areas MRE-MPA coexistence is not prohibited by law, practice indicates resistance towards it. Furthermore expert judgment demonstrated that a number of additional factors, such as the lack of suitable space for MRE projects and the uncertainty about the extent of damage by MRE to the MPA, might influence the intentions of the two major parties involved (i.e. the MRE developer and the MPA authority) to pursue or avoid coexistence. Based on these findings, the interactions of these two players are further interpreted, their policy implications are discussed, while the need towards efficient, fair and acceptable MRE-MPA coexistence is highlighted.

The correlations between skeletal parameters (bulk density, micro-density and porosity), coral age and sea surface temperature were assessed along a latitudinal gradient in the zooxanthellate coral Balanophyllia europaea and in the azooxanthellate coral Leptopsammia pruvoti. In both coral species, the variation of bulk density was more influenced by the variation of porosity than of micro-density. With increasing polyp age, B. europaea formed denser and less porous skeletons while L. pruvoti showed the opposite trend, becoming less dense and more porous. B. europaea skeletons were generally less porous (more dense) than those of L. pruvoti, probably as a consequence of the different habitats colonized by the two species. Increasing temperature had a negative impact on the zooxanthellate species, leading to an increase of porosity. In contrast, micro-density increased with temperature in the azooxanthellate species. It is hypothesized that the increase in porosity with increasing temperatures observed in B. europaea could depend on an attenuation of calcification due to an inhibition of the photosynthetic process at elevated temperatures, while the azooxanthellate species appears more resistant to variations of temperature, highlighting possible differences in the sensitivity/tolerance of these two coral species to temperature changes in face of global climate change.

Estuaries are among the most valuable aquatic systems by their services to human welfare. However, increasing human activities at the watershed along with the pressure of climate change are fostering the co-occurrence of multiple environmental drivers, and warn of potential negative impacts on estuaries resources. At present, no clear understanding of how coastal ecosystems will respond to the non-stationary effect of multiple drivers. Here we analysed the temporal interaction among multiple environmental drivers and their changing priority on shaping phytoplankton response in the Bahía Blanca Estuary, SW Atlantic Ocean. The interaction among environmental drivers and the number of significant direct and indirect effects on chlorophyll concentration increased over time in concurrence with enhanced anthropogenic stress, changing winter climate and wind patterns. Over the period 1978-1993, proximal variables such as nutrients, water temperature and salinity, showed a dominant effect on chlorophyll, whereas in more recent years (1993-2009) climate signals (SAM and ENSO) boosted indirect effects through its influence on precipitation, wind, water temperature and turbidity. Turbidity emerged as the dominant driver of chlorophyll while in recent years acted synergistically with the concentration of dissolved nitrogen. As a result, chlorophyll concentration showed a significant negative trend and a loss of seasonal peaks reflecting a pronounced reorganisation of the phytoplankton community. We stress the need to account for the changing priority of drivers to understand, and eventually forecast, biological responses under projected scenarios of global anthropogenic change.

Available methods for measuring the impact of ocean acidification (OA) and leakage from carbon capture and storage (CCS) on marine sedimentary pH profiles are unsuitable for replicated experimental setups. To overcome this issue, a novel optical sensor application is presented, using off-the-shelf optode technology (MOPP). The application is validated using microprofiling, during a CCS leakage experiment, where the impact and recovery from a high CO2 plume was investigated in two types of natural marine sediment. MOPP offered user-friendliness, speed of data acquisition, robustness to sediment type, and large sediment depth range. This ensemble of characteristics overcomes many of the challenges found with other pH measuring methods, in OA and CCS research. The impact varied greatly between sediment types, depending on baseline pH variability and sediment permeability. Sedimentary pH profile recovery was quick, with profiles close to control conditions 24 h after the cessation of the leak. However, variability of pH within the finer sediment was still apparent 4 days into the recovery phase. Habitat characteristics need therefore to be considered, to truly disentangle high CO2 perturbation impacts on benthic systems. Impacts on natural communities depend not only on the pH gradient caused by perturbation, but also on other processes that outlive the perturbation, adding complexity to recovery.

AbstractPlant species exert a dominant control over the nitrogen (N) cycle of natural and managed grasslands. Although in intensively managed systems that receive large external N inputs the emission of the potent greenhouse gas nitrous oxide (N2O) is a crucial component of this cycle, a mechanistic relationship between plant species and N2O emissions has not yet been established. Here we use a plant functional trait approach to study the relation between plant species strategies and N2O emissions from soils. Compared to species with conservative strategies, species with acquisitive strategies have higher N uptake when there is ample N in the soil, but also trigger N mineralization when soil N is limiting. Therefore, we hypothesized that (1) compared to conservative species, species with acquisitive traits reduce N2O emissions after a high N addition; and (2) species with conservative traits have lower N2O emissions than acquisitive plants if there is no high N addition. This was tested in a greenhouse experiment using monocultures of six grass species with differing above‐ and below‐ground traits, growing across a gradient of soil N availability. We found that acquisitive species reduced N2O emissions at all levels of N availability, produced higher biomass and showed larger N uptake. As such, acquisitive species had 87% lower N2O emissions per unit of N uptake than conservative species (p < .05). Structural equation modelling revealed that specific leaf area and root length density were key traits regulating the effects of plants on N2O emission and biomass productivity. These results provide the first framework to understand the mechanisms through which plants modulate N2O emissions, pointing the way to develop productive grasslands that contribute optimally to climate change mitigation.