Inland O3 Production Due to Nitrogen Dioxide Transport Downwind a Coastal Urban Area: A Neural Network Assessment

The tropospheric production of O-3 is complex, depending on nitrogen oxides (NOx = NO + NO2), volatile organic compounds (VOCs), and solar radiation. We present a case study showing that the O-3 concentration is higher in a rural area, 14 km downwind from a coastal town in Central Italy, compared with the urban environment. The hypothesis is that the O-3 measured inland results from the photochemical processes occuring in air masses originating at the urban site, which is richer in NOx emissions, during their transport inland.To demonstrate this hypothesis, a feed forward neural network (FFNN) is used to model the O-3 measured at the rural site, comparing the modeled O-3 and the measured O-3 in different scenarios, which include both input parameters related to local O-3 production by photochemistry and input parameters associated with regional transport of O-3 precursors. The simulation results show that the local NOx concentration is not a good input to model the observed O-3 (R = 0.17); on the contrary including the wind speed and direction as input of the FFNN model, the modelled O-3 is well correlated with that measured O-3 (R = 0.82)

The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model

The impact of assimilating GNSS-ZTD (global navigation satellite system–zenith total delay) on the precipitable water vapor and precipitation forecast over Italy is studied for the month of October 2019, which was characterized by several moderate to intense precipitation events, especially over northwestern Italy. The WRF (Weather Research and Forecasting) model, version 4.1.3, is used with its 3D-Var data assimilation system to assimilate ZTD observations from 388 GNSS receivers distributed over the country. The dataset was built collecting data from all the major national and regional GNSS permanent networks, achieving dense coverage over the whole area. The water vapor forecast is verified for the forecast hours of 1–6 h after the last data assimilation time. Results show that WRF underestimates the atmospheric water vapor content for the period, and GNSS-ZTD data assimilation improves this underestimation. The precipitation forecast is verified in the phases of 0–3 and 3–6 h after the last data assimilation time using more than 3000 rain gauges spread over Italy. The application of GNSS-ZTD data assimilation to a case study improved the precipitation forecast by increasing the rainfall maximum and by better focusing the precipitation pattern over northeastern Italy, with the main drawback being the prediction of false alarms. Considering the study over the whole period, GNSS-ZTD data assimilation had a positive impact on rainfall forecast, with an improvement in the performance up to 6 h and with statistically significant results for moderate to intense rainfall thresholds (25–30 mm (3 h)−1).</p

Precipitable water vapour content from ESR/SKYNET sun-sky radiometers: validation against GNSS/GPS and AERONET over three different sites in Europe

The estimation of the precipitable water vapour content (W) with high temporal and spatial resolution is of great interest to both meteorological and climatological studies. Several methodologies based on remote sensing techniques have been recently developed in order to obtain accurate and frequent measurements of this atmospheric parameter. Among them, the relative low cost and easy deployment of sun-sky radiometers, or sun photometers, operating in several international networks, allowed the development of automatic estimations of W from these instruments with high temporal resolution. However, the great problem of this methodology is the estimation of the sun-photometric calibration parameters. The objective of this paper is to validate a new methodology based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance at 940nm are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site. To obtain the calibration parameters some simultaneously seasonal measurements of W, from independent sources, taken over a large range of solar zenith angle and covering a wide range of W, are needed. In this work yearly GNSS/GPS datasets were used for obtaining a table of photometric calibration constants and the methodology was applied and validated in three European ESR-SKYNET network sites, characterized by different atmospheric and climatic conditions: Rome, Valencia and Aosta. Results were validated against the GNSS/GPS and AErosol RObotic NETwork (AERONET) W estimations. In both the validations the agreement was very high, with a percentage RMSD of about 6, 13 and 8% in the case of GPS intercomparison at Rome, Aosta and Valencia, respectively, and of 8% in the case of AERONET comparison in Valencia. Analysing the results by W classes, the present methodology was found to clearly improve W estimation at low W content when compared against AERONET in terms of %bias, bringing the agreement with the GPS (considered the reference one) from a %bias of 5.76 to 0.52

The Impact of Atmospheric Temperature Variations on Glycaemic Patterns in Children and Young Adults with Type 1 Diabetes

Seasonal variations in glycaemic patterns in children and young adults affected by type 1 diabetes are currently poorly studied. However, the spread of Flash Glucose Monitoring (FGM) and continuous glucose monitoring (CGM) systems and of dedicated platforms for the synchronization and conservation of CGM reports allows an efficient approach to the comprehension of these phenomena. Moreover, the impact that environmental parameters may have on glycaemic control takes on clinical relevance, implying a need to properly educate patients and their families. In this context, it can be investigated how blood glucose patterns in diabetic patients may have a link to outdoor temperatures. Therefore, in this study, the relationship between outdoor temperatures and glucose levels in diabetic patients, aged between 4 and 21 years old, has been analysed. For a one-year period (Autumn 2022-Summer 2023), seasonal variations in their CGM metrics (i.e., time in range (TIR), Time Above Range (TAR), Time Below Range (TBR), and coefficient of variation (CV)) were analysed with respect to atmospheric temperature. The results highlight a negative correlation between glucose in diabetic patients and temperature patterns (R value computed considering data for the entire year; Ry = -0.49), behaviour which is strongly confirmed by the analysis focused on the July 2023 heatwave (R = -0.67), which shows that during heatwave events, the anticorrelation is accentuated. The diurnal analysis shows how glucose levels fluctuate throughout the day, potentially correlating with atmospheric diurnal temperature changes in addition to the standard trend. Data captured during the July 2023 heatwave (17-21 July 2023) highlight pronounced deviations from the long-term average, signalling the rapid effects of extreme temperatures on glucose regulation. Our findings underscore the need to integrate meteorological parameters into diabetes management and clinical trial designs. These results suggest that structured diabetes self-management education of patients and their families should include adequate warnings about the effects of atmospheric temperature variations on the risk of hypoglycaemia and about the negative effects of excessive therapeutic inertia in the adjustment of insulin doses

Severe Acute Respiratory Syndrome Coronavirus 2 Lethality Did not Change over Time in Two Italian Provinces

This retrospective cohort study included all the subjects diagnosed with severe acute respiratory syndrome coronavirus 2 infection (n=2493) in 2 Italian provinces. Two hundred fifty-eight persons died, after a median of 14.0\ub111.0 days. Adjusting for age, gender, and main comorbidities, the 6528-day case-fatality rate did not decrease from March to April 2020 (adjusted hazard ratio, 0.93; P=.6)

International Experience of Mechanical Thrombectomy During the COVID-19 Pandemic: Insights from STAR and ENRG

Background: In response to the COVID-19 pandemic, many centers altered stroke triage protocols for the protection of their providers. However, the effect of workflow changes on stroke patients receiving mechanical thrombectomy (MT) has not been systematically studied. Methods: A prospective international study was launched at the initiation of the COVID-19 pandemic. All included centers participated in the Stroke Thrombectomy and Aneurysm Registry (STAR) and Endovascular Neurosurgery Research Group (ENRG). Data was collected during the peak months of the COVID-19 surge at each site. Collected data included patient and disease characteristics. A generalized linear model with logit link function was used to estimate the effect of general anesthesia (GA) on in-hospital mortality and discharge outcome controlling for confounders. Results: 458 patients and 28 centers were included from North America, South America, and Europe. Five centers were in high-COVID burden counties (HCC) in which 9/104 (8.7%) of patients were positive for COVID-19 compared with 4/354 (1.1%) in low-COVID burden counties (LCC) (P<0.001). 241 patients underwent pre-procedure GA. Compared with patients treated awake, GA patients had longer door to reperfusion time (138 vs 100 min, P=<0.001). On multivariate analysis, GA was associated with higher probability of in-hospital mortality (RR 1.871, P=0.029) and lower probability of functional independence at discharge (RR 0.53, P=0.015). Conclusion: We observed a low rate of COVID-19 infection among stroke patients undergoing MT in LCC. Overall, more than half of the patients underwent intubation prior to MT, leading to prolonged door to reperfusion time, higher in-hospital mortality, and lower likelihood of functional independence at discharge.info:eu-repo/semantics/publishedVersio