Equiangular tight frames and fourth root seidel matrices

AbstractIn this paper we construct complex equiangular tight frames (ETFs). In particular, we study the grammian associated with an ETF whose off-diagonal entries consist entirely of fourth roots of unity. These ETFs are classified, and we also provide some computational techniques which give rise to previously undiscovered ETFs

A FAST MODEL FOR FLOW AND POLLUTANT DISPERSION AT THE NEIGHBOURHOOD SCALE

This paper deals with the development of a simple urban model for flow and dispersion in the urban canopy layer (UCL). The flow module of the model calculates spatially-averaged wind profiles adopting a technique recently proposed in the literature, which is based on a balance equation between the obstacle drag force and the local shear stress. Spatially-averaged wind profiles are used as input for a newly proposed dispersion model which solves the advection-diffusion equation at neighbourhood scale. In the model, the effects of the buildings within the UCL are taken into account by means of morphological parameters λf and λp (the ratios of plan area and frontal area of buildings to the lot area). Spatially-averaged mean concentrations output by the developed model are compared with numerical results obtained from the computational fluid dynamics (CFD) model FLUENT. In particular, two configurations of constant height UCL have been considered, which refer to as λp = λf = 0.16 and λp = λf = 0.44. The originality of the study is that the dispersion model itself integrates the equations without explicitly resolving the flow around individual buildings but still accounts for their effects. The computational costs are much reduced which makes it suitable for the predictions of concentrations over the neighbourhood scale in an operational context

Oncological outcomes in fertility-sparing treatment in stage IA-G2 endometrial cancer

Background: The gold standard treatment for early-stage endometrial cancer (EC) is hysterectomy with bilateral salpingo-oophorectomy (BSO) with lymphadenectomy. In selected patients desiring pregnancy, fertility-sparing treatment (FST) can be adopted. Our review aims to collect the most incisive studies about the possibility of conservative management for patients with grade 2, stage IA EC. Different approaches can be considered beyond demolition surgery, such as local treatment with levonorgestrel-releasing intra-uterine device (LNG-IUD) plus systemic therapy with progestins. Study design: Our systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. PubMed, EMBASE, and Scopus databases were consulted, and five studies were chosen based on the following criteria: patients with a histological diagnosis of EC stage IA G2 in reproductive age desiring pregnancy and at least one oncological outcome evaluated. Search imputes were “endometrial cancer” AND “fertility sparing” AND “oncologic outcomes” AND “G2 or stage IA”. Results: A total of 103 patients were included and treated with a combination of LNG-IUD plus megestrol acetate (MA) or medroxyprogesterone acetate (MPA), gonadotrophin-releasing hormone (GnRH) plus MPA/MA, hysteroscopic resectoscope (HR), and dilation and curettage (D&C). There is evidence of 70% to 85% complete response after second-round therapy prolongation to 12 months. Conclusions: Conservative measures must be considered temporary to allow pregnancy and subsequently perform specific counseling to adopt surgery. Fertility-sparing management is not the current standard of care for young women with EC. It can be employed for patients with early-stage diseases motivated to maintain reproductive function. Indeed, the results are encouraging, but the sample size must be increased

Evaluating the capability of regional-scale air quality models to cature the vertical distribution of pollutants

This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias ≤ 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km−1). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next

TM5-FASST: a global atmospheric source–receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants

This paper describes, documents, and validates the TM5-FAst Scenario Screening Tool (TM5-FASST), a global reduced-form air quality source–receptor model that has been designed to compute ambient pollutant concentrations as well as a broad range of pollutant-related impacts on human health, agricultural crop production, and short-lived pollutant climate metrics, taking as input annual pollutant emission data aggregated at the national or regional level. The TM5-FASST tool, providing a trade-off between accuracy and applicability, is based on linearized emission-concentration sensitivities derived with the full chemistry-transport model TM5. The tool has been extensively applied in various recent critical studies. Although informal and fragmented validation has already been performed in various publications, this paper provides a comprehensive documentation of all components of the model and a validation against the full TM5 model. We find that the simplifications introduced in order to generate immediate results from emission scenarios do not compromise the validity of the output and as such TM5-FASST is proven to be a useful tool in science-policy analysis. Furthermore, it constitutes a suitable architecture for implementing the ensemble of source–receptor relations obtained in the frame of the HTAP modelling exercises, thus creating a link between the scientific community and policy-oriented users.</p

Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

© 2016. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Ioannis Kioutsioukis, et al, ‘Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data’, Atmospheric Chemistry and Physics, Vol 16(24): 15629-15652, published 20 December 2016, the version of record is available at doi:10.5194/acp-16-15629-2016 Published by Copernicus Publications on behalf of the European Geosciences Union.Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.Peer reviewedFinal Published versio

The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990-2018

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990-2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), which is well in line with the national inventories. Over 2011-2015, the CO2 land sources and sinks from NGHGI estimates report-90 Tg C yr-1 ± 30 Tg C yr-1 while all other BU approaches report a mean sink of-98 Tg C yr-1 (± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr-1 ± 400 Tg C yr-1). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of "CO2 flux"obtained from different approaches. The referenced datasets related to figures are visualized. © 2021 Ana Maria Roxana Petrescu et al