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Wastewater surveillance is crucial for the epidemiological monitoring of SARS-CoV-2. Various concentration techniques, such as skimmed milk flocculation (SMF) and polyethylene glycol (PEG) precipitation, are employed to isolate the virus effectively. This study aims to compare these two methods and determine the one with the superior recovery rates. From February to December 2021, 24-h wastewater samples were collected from the Ioannina Wastewater Treatment Plant’s inlet and processed using both techniques. Subsequent viral genome isolation and a real-time RT-qPCR detection of SARS-CoV-2 were performed. The quantitative analysis demonstrated a higher detection sensitivity with a PEG-based concentration than SMF. Moreover, when the samples were positive by both methods, PEG consistently yielded higher viral loads. These findings underscore the need for further research into concentration methodologies and the development of precise protocols to enhance epidemiological surveillance through wastewater analysis.

ABSTRACTThe disruptions associated with health and energy crisis have emphasized the need for hyperlocal cities. However, in Europe, a tool to measure the efficiency of land use and accessibility planning for localizing urban mobility is missing. In this paper, we construct a comparable 15-Minute-Walking City (15-MWC) index that assesses the walking performance of 121 European metropolitan areas and seven amenity types. The data are combined equally following the PROMETHEE II multicriteria approach to assign a final score and to present a ranking of 15-Minutes cities. The main visualization demonstrates European-level disparities and indicates that most of leading cities are in Germany, while most of the worst performers are in the UK. We also reveal a statistically significant difference in 15-MWC performance due to their GDP per capita disparities. The empirical results may serve as a referencing tool for cross-city comparisons and may support policymakers when designing transport and city-planning strategies.

Pedestrian interventions for healthier and more inclusive streetscapes can be powerful mechanisms to increase the safety and comfort of walking in African cities. This article proposes a multiscale walkability analysis approach to identify both suitable streets for pedestrian travel and problematic areas requiring small-scale improvements (e.g., pavement repairs, building maintenance, streetlights, and public seating). We applied a GIS-based framework to the central urban area of Cape Town, South Africa, which presents complex social and environmental challenges. For each street-and-crossing segment, a virtual pedestrian streetscape audit tool was used to collect micro- and mesoscale environmental indicators and assess the quality of public space. This composite street-level assessment tool was weighted with a space syntax analysis indicator (i.e., spatial integration) to detect the network’s most interconnected and high-priority pathways. The Jenks natural breaks classification algorithm was used to classify scores for each segment, which ultimately found that the highest-priority streets for redevelopment are clustered in Bo-Kaap, a relatively disadvantaged, multicultural, and hilly district on Cape Town’s west side. Policy recommendations are evaluated to increase the quality of the urban environment and the city’s overall attractiveness to pedestrians. The proposed methodology facilitates more effective place management and classifies the city’s needs in improvements, minimizing both time and budget costs.

Prostorsko urejanje območij za pešce, ki zagotavlja bolj zdravo in vključujočo ulično krajino, je lahko močan mehanizem za izboljšanje varnosti in udobnosti pešačenja v afriških mestih. Avtorja v članku predlagata pristop k analizi hodljivosti na več prostorskih ravneh, s katerim se lahko določijo ulice, primerne za pešce, in problematična območja, ki zahtevajo manjše izboljšave (npr. popravilo pločnikov, boljše vzdrževanje stavb ter ureditev ulične razsvetljave in javnih klopi). Raziskovalni okvir, ki temelji na uporabi GIS, sta uporabila za središče Cape Towna v Južni Afriki, ki se spopada s kompleksnimi družbenimi in okoljskimi izzivi. Za vsak segment ulice s prehodom za pešce sta z orodjem za virtualno presojo območij za pešce zbrala podatke o okoljskih kazalnikih na mikro- in mezoravni ter proučila kakovost javnega prostora. Rezultate, dobljene z navedenim sestavljenim orodjem za presojo ulic, sta pomnožila z normalizirano vrednostjo mere prostorske sintakse (tj. integracije), na podlagi česar sta določila poti v mreži, ki so med seboj najbolj povezane in najbolj potrebne prenove. Z Jenksovo metodo naravnih mej sta razvrstila rezultate za vsak segment, na podlagi česar sta ugotovila, da so ulice, ki so najbolj potrebne prenove, zgoščene v Bo-Kaapu, razmeroma slabo razvitem, večkulturnem in hribovitem predelu v zahodnem delu Cape Towna. Na koncu sta predstavila priporočila za izboljšanje kakovosti mestnega okolja in splošne privlačnosti mesta za pešce. Predlagana metodologija omogoča učinkovitejše upravljanje krajev in razvrščanje potreb mesta po izboljšavah, s čimer se zmanjšajo stroški in poraba časa.

Wastewater surveillance is crucial for the epidemiological monitoring of SARS-CoV-2. Various concentration techniques, such as skimmed milk flocculation (SMF) and polyethylene glycol (PEG) precipitation, are employed to isolate the virus effectively. This study aims to compare these two methods and determine the one with the superior recovery rates. From February to December 2021, 24-h wastewater samples were collected from the Ioannina Wastewater Treatment Plant's inlet and processed using both techniques. Subsequent viral genome isolation and a real-time RT-qPCR detection of SARS-CoV-2 were performed. The quantitative analysis demonstrated a higher detection sensitivity with a PEG-based concentration than SMF. Moreover, when the samples were positive by both methods, PEG consistently yielded higher viral loads. These findings underscore the need for further research into concentration methodologies and the development of precise protocols to enhance epidemiological surveillance through wastewater analysis. [ABSTRACT FROM AUTHOR]

The WRF model temperature and precipitation forecast skill for the area of northwestern Greece is examined separately for each of the 10 objectively defined Weather Types (WTs). The WTs are defined for the 10-year period: 1 January 2009–31 December 2018. Their definition is achieved with the application of k-means Cluster Analysis on ERA5 meteorological data. The WRF model is applied in three domains (Europe—Greece—NW Greece) using the one-way nesting technique in a spatial resolution of 18, 6 and 2 km. Specifically, the model runs for 64 days (10% of the number of days attributed to the WT with the highest number of days) with the lowest distances from each WT’s cluster center. The WRF forecast data of 2 m air temperature and precipitation are compared with the available meteorological observations operated by the METEO unit at the National Observatory of Athens. The validation of 2 m air temperature is performed for 04UTC and 12UTC for the first and second days of forecast using the Cressman method, separately for each meteorological station and WT. The validation of precipitation is performed for daily accumulated values for the first and second days of forecast, using forecast data from the 3 × 3 = 9 surrounding grid points of each meteorological station and calculating categorical statistics based on contingency tables for each WT and for different thresholds. According to the results, there is a remarkable overestimation of 04UTC air temperature for the anticyclonic WTs, especially for the inland stations, while the precipitation forecast skill generally depends on the threshold and the WT characteristics.

A growing body of empirical findings suggests that more satisfactory, compact, and traversable built environments can positively influence active travel, physical activity, and the walking experience. To this end, planning for better and more walkable places has been identified as a hot topic in urban studies and public health research, since. However, European-level indicators assessing aspects of pedestrian-friendly urban environments are largely lacking. This article introduces spatial and tabular data files of 17 pre-processed and microscale walkability indicators. The dataset presents relevant to the pedestrian environment information for 59 central urban areas from 26 European countries and aims to support policy analysis and assessment related to healthy and low-carbon transportation systems as well as sustainable communities. Methodologically, we applied a virtual (i.e., Google Street View) street audit tool, block-by-block and on both sides of each street and crossing segment separately. To this end, we digitized in polyline features observations and evaluations for a total of 112.577 street- and/or crossing-segments. The data collection process was a demanding and challenging process, which lasted for 21 months and involved 46 trained observers. The data tables in this paper present processed data of each audited item topic as a total share of street segments or crossings length by city. More specifically, the data tables contain indicators that describe the following seventeen themes: percent of segments with predominant commercial or/and entertainment buildings (active uses), percent of segments with access to park/plaza, percent of segments with transit stop(s), percent of segments with available public seats, percent of segments according to their street lighting conditions, percent of segments with well-maintained buildings, percent of segments where graffiti is not present, percent of segments where a bike lane is present, percent of segments where a sidewalk is present, percent of segments with well-maintained sidewalks, percent of segments with sidewalk buffers, percent of segments according to shading levels, percent of segments with wider sidewalks, percent of segments according to the number of road traffic lanes, percent of crossings with a pedestrian walk signal, percent of crossings with curb(s) ramp and percent of crossings with a marked pedestrian crosswalk. Additionally, a dedicated web-GIS platform has been designed and developed to visualize and disseminate collected data in openly available density maps of high spatial resolution (50 m × 50 m). The above data can be utilized to both raise awareness of unsatisfactory pedestrian environments and appoint them as a key health and environmental issue, as well as to assist European policy-makers to apply urban mobility strategies and monitor progress in urban sustainability and public health goals.

The study concerns the quantitative evaluation of a satellite-based rain rate (RR) estimation algorithm using measurements from a network of ground-based meteorological stations across the Epirus Region, Greece, an area that receives among the maximum precipitation amounts over the country. The utilized version of the rain estimation algorithm uses the Meteosat-11 Brightness Temperature in five spectral regions ranging from 6.0 to 12.0 μm (channels 5–7, 9 and 10) to estimate the rain intensity on a pixel basis, after discriminating the rain/non-rain pixels with a simple thresholding method. The rain recordings of the meteorological stations’ network were spatiotemporally correlated with the satellite-based rain estimations, leading to a dataset of 2586 pairs of matched values. A statistical analysis of these pairs of values was conducted, revealing a Mean Error (ME) of −0.13 mm/h and a correlation coefficient (CC) of 0.52. The optimal computed Probability of False Detection (POFD), Probability of Detection (POD), the False Alarm Ratio (FAR) and the bias score (BIAS) are equal to 0.32, 0.88, 0.12 and 0.94, respectively. The study of the extreme values of the RR (the highest 10%) also shows satisfactory results (i.e., ME of 1.92 mm/h and CC of 0.75). The evaluation statistics are promising for operationally using this algorithm for rain estimation on a real-time basis.