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.

Atmospheric aerosol has a considerable impact on air quality and climate. One of important characteristics of atmospheric aerosol is aerosol optical depth (AOD). It is a measure of the column integrated aerosol load. Global ground-based network of sun photometers AERONET provides AOD data with low uncertainty. However, AERONET observations are sparse in space and time. To obtain an estimate of the spatial and temporal distribution of AOD, data assimilation technique can be applied. One of the commonly used data assimilation methods is optimal interpolation (OI). In OI, observational data and a model forecast are linearly combined according to their relative accuracies. Weight coefficients are chosen to minimize the mean-square error in the estimate. To obtain weight coefficients, correlations between model errors in the different grid points are used. In the classical OI, only spatial correlations are considered. We use spatial and temporal correlation functions. To obtain error statistics, we use observations from AERONET sites over European region, and simulations by the global chemical transport model GEOS-Chem, assuming a negligible error of AERONET AOD observations. The estimates of the daily mean AOD distribution over Europe are obtained using proposed approach. The reduction of the root-mean-square error of the AOD estimate based on the OI method in comparison with the GEOS-Chem model results is discussed.

Africa, particularly West and North Africa, has some of the highest levels of average PM pollution, second only to South and East Asia and the Middle East. These areas, however, have the fewest air pollution monitoring stations per capita for either PM10 or PM2.5. While China and India have substantial air pollution problems, they also have at least moderate monitoring networks, with over 350 PM10 monitoring sites in India and over 1000 PM2.5 monitoring sites in China (although this is still well below per capita monitoring levels in developed countries in Europe, for example). In contrast, in all Africa, there are fewer than 150 PM10 and 50 PM2.5 monitoring stations, with Egypt and South Africa accounting for more than half of these stations, leaving the majority of the continent unmonitored. Outdoor air pollution is a risk factor for several of the world's leading causes of mortality, including stroke, heart disease, lung cancer, and respiratory disorders like asthma. This study reports the PM2.5 and PM10 concentrations and their emissions sectors in North Africa from 1990 to 2019. The data were collected online from the following platforms: EDGAR (Emissions Database for Global Atmospheric Research), Climate Watch, Our World in Data, and the World Bank. The analysis of data indicated that outdoor air pollution in North Africa is the 4th leading risk factor for death, with 3.4 million deaths in total from 1990 to 2019. The number of deaths related to outdoor air pollution in all the 5 North African countries has increased in 2019 compared to 1990. Tunisia, Algeria, and Egypt all had higher death rates in 1990 meaning they have since decreased; however, Morocco and Libya, have higher death rates in 2019, indicating that they had risen in recent decades. Globally, 43% of PM10 emissions in North Africa from 1970 to 2015, were contributed by buildings, 16.6% by other industrial combustion, 13.7% by transport, 11.4% by other sectors, 9.6% by agriculture, 5.3% by power industry, and 0.2% by waste. For PM2.5, the major emitter sector in North Africa, during the same period, was also buildings with 38.2%, followed by transport (21.5%), other industrial combustion (17.3%), other sectors (12.4%), power industry (6%), agriculture (4.5%) and waste (0.2%). The North African country with the highest numbers of PM2.5-attributable deaths is Egypt, followed by Algeria, Tunisia, Libya, and Morocco. But since 2010, except for Egypt which has kept its leading position, the ranking of the other 4 North African countries, according to the number of PM2.5 attributable deaths, have changed as follows: Morocco has climbed to the second position after Egypt, followed by Algeria, Libya, and Tunisia.

Greece is located over a prone region regarding the climate change. The aim of this study is to investigate the projection of cloud cover fraction and surface relative humidity during the period from 1970 to 2099. In this analysis we use six high-resolution regional climate model simulations (RCMs) available from the EURO-CORDEX program. The RCMs include the historical period from 1970 to 2005 and the future period from 2006 to 2099 under the influence of the representative concentration pathways (rcp) rcp2.6, rcp4.5 and rcp8.5. Results show significant projected changes mainly during the last period of 21st century according to the rcp8.5 scenario. In particular, during the 2070-2099 period, with respect to a reference period (1976-2005), both the cloud cover fraction and the surface relative humidity are reduced about 5% and 4% - 8% respectively, over the continental Greece. Focusing on the winter season, the comparison between future and reference periods shows that cloud cover fraction presents a significant relative decrease about 10 % to 20% mainly during the last period of 21st century. Finally, surface relative humidity during 2070-2099 shows insignificant changes according low and moderate scenarios (rcp2.6 and 4.5) , and limited changes for the high emission scenario (rcp8.5).

The Western Mediterranean region is frequently affected by torrential rains, causing important economic losses and human casualties. The ocean-atmosphere exchanges of heat and moisture is a key role in the development of such heavy rain events, such as that developed from 10^th to 14^th September 2019 in eastern Spain. This intense storm affected the southeast of the Iberian Peninsula, mainly the northern and southern areas of Alicante province as well as the east of the Murcia region. In some areas, accumulated rainfall values greater than 400 mm were recorded considering the whole precipitation event, while precipitation observations near 200 mm where recorded over some locations in just 2 hours. The synoptic environment of this event is characterised by an advection of easterly maritime winds focusing in the southeast Western Mediterranean basin and the presence of an upper level isolated low over the area of intense torrential rainfall. The current study presents a meteorological analysis of this rain event highlighting the synoptic ingredients and their dynamics. ERA5 reanalysis dataset together with satellite observations are used for this purpose. This information, together with surface measurements obtained from different weather stations located over the area of study, are used as well to characterize the spatial distribution and rain period of the observed extreme rainfall.

Since inhalation is the major route of entry for NMs into the body, it is necessary to assess the deposition of nanomaterials (NMs) in the respiratory system and their subsequent translocation to extra-pulmonary tissues. This is achieved with the aid of lung dosimetry models. The main mechanism responsible for the deposition of NMs in the respiratory tract is diffusion as the NMs collide with air molecules, while other deposition mechanisms, including inertial impaction, gravitational settling, and interception, do not contribute significantly. The significance of each mechanism depends on particle characteristics (such as size, shape and hygroscopicity), location in the lung (trachea, bronchi and alveoli) and ventilation parameters such as breathing rates, tidal volume, breathing frequency. In the end, the toxicology and risk assessment of inhaled NMs will depend on deposition rates in various parts of the lung coupled with clearance/retention rates that may include physical removal by ciliary clearance, macrophage-mediated clearance and lymphatic clearance, as well as dissolution and disintegration. In particular, the rate of dissolution of NMs in the lungs significantly affects the clearance rate, while the distribution of the NMs to other parts of the body largely depends on particle size. A number of models have been designed to estimate the deposition and retention of inhaled particles, ranging from empirical models that do not incorporate lung geometry through stochastic statistical models to mechanistic multiple-path models that are based on actual airway measurements. Various assumptions that are used in these models, including use of a symmetrical or asymmetrical lung, affect the performance of the models. This study presents the state of the art in in vivo dosimetry in nanotoxicology, with a focus on the design of the models and the required input data used, as well as verification and validation status of the model.