• Energy Research

AbstractClimate warming will affect terrestrial ecosystems in many ways, and warming‐induced changes in terrestrial carbon (C) cycling could accelerate or slow future warming. So far, warming experiments have shown a wide range of C flux responses, across and within biome types. However, past meta‐analyses of C flux responses have lacked sufficient sample size to discern relative responses for a given biome type. For instance grasslands contribute greatly to global terrestrial C fluxes, and to date grassland warming experiments provide the opportunity to evaluate concurrent responses of both plant and soil C fluxes. Here, we compiled data from 70 sites (in total 622 observations) to evaluate the response of C fluxes to experimental warming across three grassland types (cold, temperate, and semi‐arid), warming methods, and short (≤3 years) and longer‐term (>3 years) experiment lengths. Overall, our meta‐analysis revealed that experimental warming stimulated C fluxes in grassland ecosystems with regard to both plant production (e.g., net primary productivity (NPP) 15.4%; aboveground NPP (ANPP) by 7.6%, belowground NPP (BNPP) by 11.6%) and soil respiration (Rs) (9.5%). However, the magnitude of C flux stimulation varied significantly across cold, temperate and semi‐arid grasslands, in that responses for most C fluxes were larger in cold than temperate or semi‐arid ecosystems. In semi‐arid and temperate grasslands, ecosystem respiration (Reco) was more sensitive to warming than gross primary productivity (GPP), while the opposite was observed for cold grasslands, where warming produced a net increase in whole‐ecosystem C storage. However, the stimulatory effect of warming on ANPP and Rs observed in short‐term studies (≤3 years) in both cold and temperate grasslands disappeared in longer‐term experiments (>3 years). These results highlight the importance of conducting long‐term warming experiments, and in examining responses across a wide range of climate.

This paper presents a dynamic model and experimental results of a 7.2. kWp photovoltaic (PV) installation located at the Polytechnic University of Valencia (Spain). The modelling of the monocrystalline cells has been realised in TRNSYS and has been validated during an extensive experimental campaign from January 2001 to March 2003, using the data of a fully monitored PV field. The simulation results with TRNSYS provide an accurate prediction of the long-term performance. In addition to the dynamic models, algebraic methods such as the constant fill factor have also been applied.In the design of PV systems, there are several important uncertainties which have to be taken into account, such as the reduction of power with respect to the nominal power under Standard Test Conditions (STC), the choice of the meteorological database, and the models for the calculation of the radiation on tilted surface and of the cell temperature. These aspects are analyzed thoroughly in this paper, as well as the problems inherent to the PV power injection into the grid.

Land-cover change (LCC) is an important driver of climate change through carbon emissions (biochemical effects), but also through changes in the surface energy balance (biophysical effects). Quantifying magnitude and sign of surface temperature responses to biophysical effects is still challenging and under debate. We develop a new semi-empirical model based on a linearized surface energy balance for biophysical and an empirical model for the biochemical responses to LCC. Neglecting indirect effects, we find average global direct biophysical and biochemical warmings in response to a stylized deforestation scenario (1.22 K and 0.50 K) and historical LCC (0.42 K and 0.15 K), whereas an afforestation experiment leads to cooling (−1.95 K and −0.96 K). Our results underline the non-negligible impact of biophysical effects, especially non-radiative effects, and stress the importance of including these in the assessment of climate change mitigation and adaptation policies.

ABSTRACT: In democracies around the world, societies have demonstrated that elections can have major consequences for the environment. In Colombia, the 2022 presidential elections will take place at a time when progress towards peace has stalled and socioeconomic, security, and environmental conditions have deteriorated. The recent declines in these conditions largely coincide with the change of government after the 2018 elections, and the associated rise to power of a party that boycotted the peace negotiations from the beginning. These indicators suggest that 2018 marked the end of a decade of improvements in safety, wealth, and equality—societal factors that can interact with the environment in multiple ways. A spike in assassinations of land and environmental defenders in 2019 and 2020 made Colombia one of the most dangerous places in the world for environmentalists. With the 2022 presidential election, Colombians will once again decide who will govern the country and what new social, economic, and environmental policies will be implemented. In preparation for elections like this, we believe that it is important for scientists with relevant backgrounds to highlight relationships between political events and the environment, to enrich the political debate, help prioritize public resources, and inform policymaking. Here, we provide a multidisciplinary analysis of different socioeconomic and environmental trends that can help inform the public and decision-makers. We intend for this analysis to be useful not only in Colombia, but also to other societies under similar situations, managing biodiversity-rich ecosystems in sociopolitical environments of increasing violence, poverty, and inequality. ; COL0008619

Abstract. To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land use and climate change on biodiversity and ecosystem services (i.e. nature’s contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenarios selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem service models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modelling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modelling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

Anthropogenic land cover changes (LCC) affect regional and global climate through biophysical variations of the surface energy budget mediated by albedo, evapotranspiration, and roughness. This change in surface energy budget may exacerbate or counteract biogeochemical greenhouse gas effects of LCC, with a large body of emerging assessments being produced, sometimes apparently contradictory. We reviewed the existing scientific literature with the objective to provide an overview of the state-of-the-knowledge of the biophysical LCC climate effects, in support of the assessment of mitigation/adaptation land policies. Out of the published studies that were analyzed, 28 papers fulfilled the eligibility criteria, providing surface air temperature and/or precipitation change with respect to LCC regionally and/or globally. We provide a synthesis of the signal, magnitude and uncertainty of temperature and precipitation changes in response to LCC biophysical effects by climate region (boreal/temperate/tropical) and by key land cover transitions. Model results indicate that a modification of biophysical processes at the land surface has a strong regional climate effect, and non-negligible global impact on temperature. Simulations experiments of large-scale (i.e. complete) regional deforestation lead to a mean reduction in precipitation in all regions, while air surface temperature increases in the tropics and decreases in boreal regions. The net global climate effects of regional deforestation are less certain. There is an overall consensus in the model experiments that the average global biophysical climate response to complete global deforestation is atmospheric cooling and drying. Observed estimates of temperature change following deforestation indicate a smaller effect than model-based regional estimates in boreal regions, comparable results in the tropics, and contrasting results in temperate regions. Regional/local biophysical effects following LCC are important for local climate, water cycle, ecosystems, their productivity and biodiversity, and thus important to consider in the formulation of adaptation policy. However before considering the inclusion of biophysical climate effects of LCC under the UNFCCC, science has to provide robust tools and methods for estimation of both country and global level effects.