Influence of input climatic data on simulations of annual energy needs of a building: energyplus and WRF modeling for a case study in Rome (Italy)

The simulation of the energy consumptions in an hourly regime is necessary in order to perform calculations on residential buildings of particular relevance for volume or for architectural features. In such cases, the simplified methodology provided by the regulations may be inadequate, and the use of software like EnergyPlus is needed. To obtain reliable results, usually, significant time is spent on the meticulous insertion of the geometrical inputs of the building, together with the properties of the envelope materials and systems. Less attention is paid to the climate database. The databases available on the EnergyPlus website refer to airports located in rural areas near major cities. If the building to be simulated is located in a metropolitan area, it may be affected by the local heat island, and the database used as input to the software should take this phenomenon into account. To this end, it is useful to use a meteorological model such as the Weather Research and Forecasting (WRF) model to construct an appropriate input climate file. A case study based on a building located in the city center of Rome (Italy) shows that, if the climatic forcing linked to the heat island is not considered, the estimated consumption due to the cooling is underestimated by 35–50%. In particular, the analysis and the seasonal comparison between the energy needs of the building simulated by EnergyPlus, with the climatic inputs related to two airports in the rural area of Rome and with the inputs provided by the WRF model related to the center of Rome, show discrepancies of about (i) WRF vs. Fiumicino (FCO): Δ = −3.48% for heating, Δ = 49.25% for cooling; (ii) WRF vs. Ciampino (CIA): Δ = −7.38% for heating, Δ = +35.52% for cooling

European atmosphere in 2050, a regional air quality and climate perspective under CMIP5 scenarios

To quantify changes in air pollution in Europe at the 2050 horizon, we designed a comprehensive modelling system that captures the external factors considered to be most relevant and relies on up-to-date and consistent sets of air pollution and climate policy scenarios. Global and regional climate as well as global chemistry simulations are based on the recent Representative Concentrations Pathways (RCP) produced for the Fifth Assessment Report (AR5) of IPCC whereas regional air quality modelling is based on the updated emissions scenarios produced in the framework of the Global Energy Assessment. We explored two diverse scenarios: a reference scenario where climate policies are absent and a mitigation scenario which limits global temperature rise to within 2 degrees C by the end of this century. This first assessment of projected air quality and climate at the regional scale based on CMIP5 (5th Climate Model Intercomparison Project) climate simulations is in line with the existing literature using CMIP3. The discrepancy between air quality simulations obtained with a climate model or with meteorological reanalyses is pointed out. Sensitivity simulations show that the main factor driving future air quality projections is air pollutant emissions, rather than climate change or long range transport. Whereas the well documented "climate penalty" bearing upon ozone over Europe is confirmed, other features appear less robust compared to the literature: such as the impact of climate on PM2.5. The quantitative disentangling of each contributing factor shows that the magnitude of the ozone climate penalty has been overstated in the past while on the contrary the contribution of the global ozone burden is overlooked in the literature

First Top-Down Estimates of Anthropogenic NO_x Emissions Using High-Resolution Airborne Remote Sensing Observations

A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO_2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO_x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO_2 profiles from a high‐resolution regional model (1 × 1 km^2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO_2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO_2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 10^(15) molecules cm^(−2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions

Between Past and Future: The Mission of University of L’Aquila and Its Action on Energy and Climate Change

For the University of L’Aquila, sustainability and civic engagement are key commitments. Actions to enhance and safeguard the territory and to improve the community wellbeing are even more meaningful in a city that, after the earthquake of 2009, is re-thinking its social and economic backbone. The aim to provide buildings with a high level of seismic security, of energy efficiency and resources saving, has been particularly challenging, but that also offered an opportunity. The participation to the UI Green Metric WUR has been a natural consequence of this process of renovation. Moreover, throughout the data collection and analysis, UI GM rankings stimulates the cross disciplinary cooperation in research, innovation, social and civic engagement.Concerning “Energy and Climate Change” the University could take the opportunity to exploit the competencies of research teams worldwide known working in renewable energies production (solar, wind, hydropower), building efficiency and retrofitting, environmental impacts. The University is member of the Italian University Network for Sustainable Development, which offered guidelines to implement energy and climate change related politics. The improvements of building focused on: smart illumination appliances (61% of the area), smart automation of heating/cooling (90% of the area), renewable energy production (PV and solar thermal), and integration of climate action into the strategic plan

Present-day radiative effect from radiation-absorbing aerosols in snow

Black carbon (BC), brown carbon (BrC), and soil dust are the most important radiation-absorbing aerosols (RAAs). When RAAs are deposited on the snowpack, they lower the snow albedo, causing an increase in the solar radiation absorption. The climatic impact associated with the snow darkening induced by RAAs is highly uncertain. The Intergovernmental Panel on Climate Change (IPCC) Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) attributes low and medium confidence to radiative forcing (RF) from BrC and dust in snow, respectively. Therefore, the contribution of anthropogenic sources and carbonaceous aerosols to RAA RF in snow is not clear. Moreover, the snow albedo perturbation induced by a single RAA species depends on the presence of other light-absorbing impurities contained in the snowpack. In this work, we calculated the present-day RF of RAAs in snow starting from the deposition fields from a 5-year simulation with the GEOS-Chem global chemistry and transport model. RF was estimated taking into account the presence of BC, BrC, and mineral soil dust in snow, simultaneously. Modeled BC and black carbon equivalent (BCE) mixing ratios in snow and the fraction of light absorption due to non-BC compounds (fnon-BC) were compared with worldwide observations.We showed that BC, BCE, and fnon-BC, obtained from deposition and precipitation fluxes, reproduce the regional variability and order of magnitude of the observations. Global-average all-sky total RAA-, BC- , BrC-, and dust-snow RF were 0.068, 0.033, 0.0066, and 0.012Wm2, respectively. At a global scale, non-BC compounds accounted for 40% of RAA-snow RF, while anthropogenic RAAs contributed to the forcing for 56 %. With regard to non-BC compounds, the largest impact of BrC has been found during summer in the Arctic (C0.13Wm2). In the middle latitudes of Asia, the forcing from dust in spring accounted for 50% (C0.24Wm2) of the total RAA RF. Uncertainties in absorbing optical properties, RAA mixing ratio in snow, snow grain dimension, and snow cover fraction resulted in an overall uncertainty of 50 %/C61 %, 57 %/C183 %, 63 %/C112 %, and 49 %/C77% in BC- , BrC-, dust-, and total RAA-snow RF, respectively. Uncertainty upper bounds of BrC and dust were about 2 and 3 times larger than the upper bounds associated with BC. Higher BrC and dust uncertainties were mainly due to the presence of multiple absorbing impurities in the snow. Our results highlight that an improvement of the representation of RAAs in snow is desirable, given the potential high efficacy of this forcing

Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio