Stable isotopes (¹⁸O and ²H) in precipitation of Bangkok has been sampled since 1968 when GNIP stablished its first station in Thailand. In this study, the role of various local (wind speed, potential evaporation, vapor pressure, air temperature, and precipitation amount) as well as regional parameters (teleconnection indices such as IOD, BEST, NAO, SOI, and QBO) on stable isotopes content in Bangkok precipitation has been investigated. Firstly, simple artificial neural network (ANN) as well as Deep Learning Neural Network (DNN) models have been used to predict stable isotopes content in precipitation. Comparing the simulated and real stable isotopes data shows that both DNN and ANN models can simulate the stable isotopes in precipitation with acceptable accuracy. Secondly, studying the fractional importance of various parameters on stable isotopes content of precipitation demonstrates that among the local parameters (precipitation amount and potential evaporation) and among the regional parameters (BEST index) have the dominant role in controlling the stable isotopes content of precipitation.

Cold fronts are the meteorological systems that affect the country in the dry season, which when combined with other meteorological conditions or local factors can generate precipitation, which is sometimes greater than 100 mm in 24 hours. Some studies have analyzed the synoptic patterns associated with cold fronts that generate heavy rains in Cuba and the internal structure of these patterns. Similarly, from the 1990s, studies associated with the behavior of the NAO teleconnection event within the winter period and the systems that are developed in it increased. However, the incidence of this event in the cold fronts that generate intense rains in Cuba in the winter period 1980-1981 to 2016-2017 has not been taken into account. For this, the tropospheric patterns associated with these winter systems were identified, the behavior of this event was characterized in those winter seasons with intense rains and the mean field of temperature, humidity, wind and its derivatives associated with these meteorological systems when they generate rains intense and its relationship with said teleconnective event. The results obtained show that the NAO teleconnective event in the study period showed preference to be negative. The temperature, the relative humidity, and the fields derived from the wind presented homogeneity in the two phases of this event.

Polarimetric radars use differential reflectivity (Z_dr) in addition to the radar reflectivity (Z_h) to determine the two main parameters governing rain drop size distributions (DSD), typically the mass-weighted mean diameter, D_m, and the normalized intercept parameter (N_W). One built-in assumption is that the drops are oblate and that the minor-to-major axis ratios reduce with increasing size in accordance with theoretically- based approximations. For light rain, however, the Z_dr approaches 0 dB because of the dominance of the small drops (D<0.8 mm) which are spherical in shape. Our scattering calculations using measured DSDs in light rain and drizzle show that for DSDs with D_m < 0.8 mm, the S-band Z_dr tends to be < 0.2 dB and that using Z_dr to retrieve D_m will have large uncertainties due to measurement errors as well as parameterization errors. On the other hand, D_m shows a more gradual variation with Z_h for light rain and drizzle DSDs. Simulations of Z_h and Z_dr using measured DSDs with optical array probe and 2D-video disdrometer located inside a Double Fence International Reference (DFIR) wind shield were used to develop an algorithm to estimate D_m=f(Z_h) for light rain. For drizzle, the fitted equation was derived using aircraft-based data in stratocumulus rain. Validation of the D_m retrievals was performed using Z_h measured by scanning S-band polarimetric radars (CSU-CHILL in Colorado and NPOL in Delmarva peninsula) over two DFIR locations versus D_m from disdrometer measurements in the two locations. Consistent results were obtained but only for reflectivity less than 18 dBZ for light rain and 5 dBZ for drizzle. Finally, 500m by 500m gridded data from NPOL, are used to identify light rain and drizzle regions and their D_m histograms are compared with those derived from stratiform and convective rain regions. Comparisons are also made for the histograms of the normalized intercept parameter (N_W).

Local Climate Zones (LCZs) refer to a classification system that exists out of 17 classes, 10 of which can be described as urban, proposed as new standard for characterizing and comparing urban landscapes. (Stewart and Oke, 2012; Lehnert et al., 2021). The World Urban Database and Access Portal Tools (WUDAPT, www.wudapt.org) community project mapped until now ~150 cities. WUDAPT has a hierarchic approach to gathering data: Level 0 contains mainly 2-dimensional urban morphological information and rough urban function based on their effect on the local air temperature; Level 1 and 2 provide more detailed 3-dimensional urban morphological information, material composition data and anthropogenic functions at building level, so they are suitable for various meteorological and climate models. The Level 0 procedure relies on a workflow that integrates training areas (TAs) identified using Google Earth and Landsat imagery. A LCZ Generator web application has been further proposed to simplify the process (Demuzere et al., 2021).

All the efforts done until now mainly aim at speeding up and improving the creation of Level 0 maps based on user detection of TAs. In this work, the main objective is to produce a more detailed LCZ map. Specifically, after a brief literature review on LCZ methodology, by collecting morphological data from Digital Elevation Models of several Italian cities, a detailed morphological characterization of the city is carried out through the Geographical Information System (GIS) software. Different physical parameters are estimated such as: planar area index, frontal area index, impervious surface index, aspect ratio, sky view factor, average height, ratio of building area to floor area, many of which are then used for the detailed classification of LCZ classes.

Demuzere et al., 2021. Doi: 10.3389/fenvs.2021.637455

Lehnert et al., 2021. Doi: 10.3390/ijgi10040260

Stewart and Oke, 2012. Doi: 10.1175/BAMS-D-11-00019.1

Waste of electrical and electronic equipment (WEEE) is commonly considered a secondary raw material for the recovery of valuable components. Precious metals, plastics, glass, ceramics can be recovered for production of durable goods. Nevertheless, e-wastes are characterized by the presence of chemicals harmful to the environment and to the waste disposal workers (Golnoush, 2020). Flame retardants (FR) are usually added to or otherwise incorporated into plastic compounds to provide varying degrees of flammability protection. Particular attention, in this work, was paid to classes of compounds as PBDEs and PCBs, banned from manufacture and use, but still persistent in outdated electrical equipment and new flame retardants and plasticizers (NBFRs), frequently detected in WEEE recycling facilities

Several studies showed as prolonged exposure and accumulation of these chemicals are associated with many adverse effects such as endocrine disruption, cancer, immunotoxicity, reproductive toxicity etc. (Pomata et al., 2020). The aim of the present paper was to compare concentration of several harmful substances in dust samples, collected in 2017 and in 2022 in order to monitoring the same e-waste plant, located in Central Italy, five years after the first time, focusing both on risk assessment study, than on the progress on long-term developed in this specific e-waste plant.

In particular, these collected dusts were produced during recycling operations, in a disassembly area where workers manually crush and select the different components that are subsequently sent to the recovery plants. Dust samples were analysed for PCBs, PBDEs, and NBFRs and the concentration values were used to carry out the risk Assessment, using specific equations (USEPA, 2011), by considering three different exposure routes: inhalation, ingestion, and dermal absorption of particles. For the inhalation risk assessment, airborne particulate matter concentration was used. The results obtained in this study showed how the various advances in plant management over the years, highlighted an overall improvement in the occupational risk levels despite the presence of toxic substances prohibited by law and new chemicals not yet legislated, are not negligible and reveal that continuous monitoring was the only way for a correct prevention and protection the of workers health.

References

Golnoush et al. (2020) Pure Appl Chem, 92, 1733–1767

Pomata et al. (2020) Int J Environ Anal Chem, 100(13), 1479-1496.

US EPA 2011 - EPA/600/R-090/052F.