1,721,032 research outputs found
The formation of secondary inorganic aerosols: A data-driven investigation of Lombardy's secondary inorganic aerosol problem
No full textThis study performs a data-driven investigation of the impact of agriculture on air pollution in Lombardy, Italy, focusing on secondary inorganic particulate matter (PM) formation resulting from ammonia (NH3) emissions. Leveraging on the predictive power of machine learning models and exploiting the reduction in non-agricultural emissions during the 2020 COVID-19 lockdown, we analyze the complex relationship between NH3, nitrogen dioxide (NO2), and secondary inorganic aerosols (SIA). We find that even substantially large reduction in precursor emissions may not deliver large drops in secondary inorganic PM. While NO2 plays a significant role in urban environments, in rural areas where NH3 levels are high, both NO2 and NH3 contribute to SIA formation. This emphasizes the importance of considering both NH3 and NO2 emissions in policies controlling secondary inorganic PM, as reductions in both precursors may be necessary for significant improvements. The study provides insights into the interplay between agricultural practices and air pollution, more specifically the NH3–NO2 regime and its implications for effective air pollution control strategies in Lombardy
Exploring the impact of livestock on air quality: A deep dive into Ammonia and particulate matter in Lombardy
Get PDFThe linkage between agricultural activities, particularly livestock farming, and atmospheric pollution is broadly acknowledged, and its magnitude is widely analyzed. Lombardy, one of Europe's most critical areas with regard to air pollution, has significantly large contributions from the farming industry. Although studies aimed at informing policy reflect uncertain and moderate pollution reduction even under simulated stringent policy scenarios, granular causal evidence at a sub-sector level remains insufficient to inform local and regional policies effectively. In this study, we employ a spatially and temporally indexed econometric model to investigate the specific impact of bovine and swine farming on the concentration levels of ammonia (NH3) and coarse particulate matter (PM10) in Lombardy's atmosphere. Our findings indicate that an increase of 1000 units in livestock, equating to roughly a 1% and 0.3% rise in the average per-quadrant bovine and swine populations, respectively—triggers a corresponding daily increase in NH3 and PM10 concentrations. These increases are quantified as 0.26 [0.22; 0.33] and 0.29 [0.27; 0.41] μg/m3 for bovines (about 2% and 1% of the respective daily averages) and 0.01 [0.01; 0.05] and 0.04 [0.004; 0.16] μg/m3 for swine. Notably, these impacts are intensified under northerly upwind conditions, minimizing the potential for concurrent pollution sources and reinforcing the robustness of our estimated impacts. Finally, we employ our findings to extrapolate the potential environmental implications of reducing livestock emissions. Our analysis suggests that bovine and swine farming could account for up to 25% of local pollution exposure, empathizing the need for targeted mitigation strategies
COVID-19 lockdown only partially alleviates health impacts of air pollution in Northern Italy
Get PDFEvaluating the reduction in pollution caused by a sudden change in emissions is complicated by the confounding effect of weather variations. We propose an approach based on machine learning to build counterfactual scenarios that address the effect of weather and apply it to the COVID-19 lockdown of Lombardy, Italy. We show that the lockdown reduced background concentrations of PM2.5 by 3.84 μg m−3 (16%) and NO2 by 10.85 μg m−3 (33%). Improvement in air quality saved at least 11% of the years of life lost and 19% of the premature deaths attributable to COVID-19 in the region during the same period. The analysis highlights the benefits of improving air quality and the need for an integrated policy response addressing the full diversity of emission sources
Expert views - and disagreements - about the potential of energy technology R&D
Get PDFMitigating climate change will require innovation in energy technologies. Policy makers are faced with the question of how to promote this innovation, and whether to focus on a few technologies or to spread their bets. We present results on the extent to which public R&D might shape the future cost of energy technologies by 2030. We bring together three major expert elicitation efforts carried out by researchers at UMass Amherst, Harvard, and FEEM, covering nuclear, solar, Carbon Capture and Storage (CCS), bioelectricity, and biofuels. The results show experts believe that there will be cost reductions resulting from R&D and report median cost reductions around 20 % for most of the technologies at the R&D budgets considered. Although the improvements associated to solar and CCS R&D show some promise, the lack of consensus across studies, and the larger magnitude of the R&D investment involved in these technologies, calls for caution when defining what technologies would benefit the most from additional public R&D. In order to make R&D funding decisions to meet particular goals, such as mitigating climate change or improving energy security, or to estimate the social returns to R&D, policy makers need to combine the information provided in this study on cost reduction potentials with an analysis of the macroeconomic implications of these technological changes. We conclude with recommendations for future directions on energy expert elicitations
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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