Publications by authors named "Paolo Tuccella"
The primary environmental concern related to nuclear power is the production of radioactive waste hazardous to humans and the environment. The main scientific and technological problems to address this are related to the storage and disposal of the nuclear waste and monitoring the dispersion of radioactive species into the environment. In this work, we determined an anomalously high C activity, well above the modern natural background, on surface and seasonal snow sampled in early May 2019 on glaciers in the Hornsund fjord area (Svalbard).
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- Accurate simulations of aerosol absorption properties are essential for understanding their impact on meteorology and climate, with the mixing state of chemical species being a significant source of uncertainty.
- This study compares aerosol optical property simulations in Europe and North America with one year of AERONET data to find a better representation of mixing states that fits observed data, focusing on black carbon's absorption enhancement.
- Findings indicate that both external and core-shell mixing assumptions lead to biases in single scattering albedo, but using a combination (partial internal mixing) helps reduce these biases while highlighting issues with the spectral dependence of absorption.
Article Synopsis
- The AQMEII3 initiative assesses the effects of a 20% reduction in anthropogenic emissions on air pollutant levels in 2010, focusing on Europe and North America.
- Different regional air quality modeling groups utilize advanced chemistry and transport models to simulate these changes based on data from the global C-IFS model.
- Results indicate a nearly linear correlation between reduced emissions and decreased concentrations of pollutants like NO, SO, and PM, with notable geographical variations in effects, particularly in emission hotspots.
The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Initiative (AQMEII3). The modeled surface concentrations of O, CO, SO and PM are used as input to the Economic Valuation of Air Pollution (EVA) system to calculate the resulting health impacts and the associated external costs from each individual model. Along with a base case simulation, additional runs were performed introducing 20 % anthropogenic emission reductions both globally and regionally in Europe, North America and east Asia, as defined by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2).
View Article and Find Full Text PDFIn this study we introduce a consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models.
View Article and Find Full Text PDFLocal emissions of Arctic air pollutants and their impacts on climate, ecosystems and health are poorly understood. Future increases due to Arctic warming or economic drivers may put additional pressures on the fragile Arctic environment already affected by mid-latitude air pollution. Aircraft data were collected, for the first time, downwind of shipping and petroleum extraction facilities in the European Arctic.
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- The study compares regional-scale chemistry transport models for air quality in Europe and North America to identify sources of modeling errors and areas needing further research.
- It uses a framework known as AQMEII Phase 3 to assess model performance by comparing measurements with simulated data across multiple pollutants.
- Key findings highlight the influence of model inputs like emissions, the importance of accurately representing the stable boundary layer, and the interconnectedness of meteorological and chemical variables in evaluating model bias.