Two isotropic pitches were prepared by air blowing and nitrogen distillation method using ethylene tar (ET) as a raw material. And correspondent carbon fibers were obtained through conventional melt spinning, stabilization and carbonization. The structures and properties of resultant pitches and fibers were characterized and their differences were discussed in this work. The results showed that introduction of the oxygen by air blowing method could quickly increase the yield and softening point of pitch. Moreover, the air blown pitch (ABP) composed of linear methylene chains of aromatic molecules while the nitrogen distilled pitch (NDP) mainly contained polycondensed aromatic rings, which was due to the oxygen containing functional groups existed in ABP could impede order stack of pitch molecules and form methylene bridge structure, instead of aromatic condensed structure like NDP. Meanwhile, the spinnability of ABP was not decreased even containing 2.31 wt% oxygen. In contrast, ABP had narrower molecular weight distribution, which contributed to better stabilization properties and higher tensile strength of carbon fiber. The tensile strength of carbon fibers from ABP was reached to 860 MPa with fiber diameter of about 10 μm, which was higher than that of NDP-derived carbon fibers of 640 MPa.

Ultraviolet (UV) light with a wavelength of 254 nm has proven to be effective at inactivating microorganisms, and thus has been increasingly employed as a method of disinfection for indoor environments. Solar UV wavelengths (300 to 400 nm) are known to initiate the formation of secondary organic aerosol (SOA) particles from photo-oxidation of volatile organic compounds in the atmosphere, but germicidal wavelengths have not been extensively studied for indoor environments. In this work, toluene was exposed to 254 nm UV light in a laboratory photoreactor, with varying conditions of the air, the duration of UV exposure, and the duration of post-UV time. The number of particles formed in the fine particulate matter (PM2.5) size range was measured, and significant levels of particle formation were observed for UV exposure periods of as short as 5 minutes. The particle formation ranged from 2.4x10⁶ particles/m³ for 5 minutes of UV exposure, to 1449.8x10⁶ particles/m³ for 15 minutes of UV exposure. Particle formation was found to increase with increasing concentrations of gas phase toluene, and at relative humidity of approximately 20% and higher. Variations in the initial number of particles present did not appear to have a significant effect on the particle formation, suggesting that nucleation was not a controlling factor. However, tests in a commercial environment showed no significant detectable PM2.5 formation, indicating that SOA formation during the intermittent use of germicidal UV may not significantly affect indoor air quality.

A D-grade type coal was burned under simulated domestic practices in a controlled laboratory set-up, in order to characterize emissions of volatile organic compounds (VOCs); viz. benzene, toluene, ethylbenzene and xylenes (BTEX). Near-field concentrations were collected in a shack-like structure constructed using corrugated iron, simulating a traditional house found in informal settlements in South Africa. Measurements were carried out using the Synspec Spectras GC955 real-time monitor over a three-hour burn cycle. The 3-hour average concentrations (in µg/m³) of benzene, toluene, ethylbenzene, p-xylene and o-xylene were 919 ± 44, 2051 ± 91, 3838 ±19, 4245 41 and 3576 ± 49, respectively. The cancer risk for adult males and females in a typical SA household exposure scenario, was found to be 1.1 -1.2 and 110-120 folds higher than the US EPA designated risk severity indicator (1E^-6), respectively. All four TEX compounds recorded the Hazard Quotient (HQ) of less than 1, indicating a low risk of developing related non-carcinogenic health effects. The HQ for TEX ranged from 0.001– 0.05, with toluene concentrations being the lowest and ethylbenzene the highest. This study has demonstrated that domestic coal burning may be a significant source of BTEX emission exposure.

Nowadays a recognized need for accurate observations of atmospheric aerosols (AEs) and reactive gases (RGs) exists in the framework of regional, national and global near-surface networks based on permanent or mobile measurement stations. In this context, a paramount and not-trivial issue is related to the correct execution of continuous sampling of ambient air and its subsequent distribution to measurement analyzers hosted inside the stations. Sampling artifacts must be minimized for obtaining reliable pictures of ambient air composition. To respond to this need, a suite of novel “smart” and relatively low-cost systems for the continuous sampling of ambient air was developed in the framework of the Project I-AMICA (2012 – 2015, www.i-amica.eu). These systems were designed to execute AE and RG measurements according with WMO/GAW and ACTRIS recommendations and standard operation procedures. A particular attention was dedicated to the stabilization and control of the sampling flow rates and temperatures. The analysis of one full year of operations at the WMO/GAW regional station of Capo Granitola (GAW ID: CGR, Italy), allowed to conclude that these systems are effective in meeting the technical requirements for correct execution of AE and RG measurements

Introduction: Ambient air pollution is major global health problem and commercial drivers are particularly exposed to it. No systematic assessment of the health risks associated with occupational exposure to ambient air pollution in this population has been carried out. Methods: We conducted a systematic review using a protocol-driven strategy. Papers published from inception to 20th April 2018 in MEDLINE, EMBASE, CINAHL, African journals online, Cochrane library, ISRCTN and WHO ICTRP databases were screened for inclusion by two independent reviewers. Original articles with at least an available abstract in English or French were included. Results: The initial search retrieved 1454 published articles of which 20 articles were included. 3 Studies reported a significant difference in white blood cells (106/L) among commercial motorcyclists compared to rural inhabitants (5.041±1.209 vs 5.900±1.213,p=0.001), an increased risk of lung cancer (RR=1.6, 95%CI 1.5-1.8) in bus drivers and an increased standardized mortality ratio (SMR) in bus drivers from Hodgkin’s lymphoma (SMR 2.17, 95%CI 1.19-3.87) compared to white collar workers. Other studies also found that drivers had more oxidative DNA damage and chromosome breaks. 4 papers failed to demonstrate that the drivers were more exposed to air pollution than the controls. 3 other studies also reported no significant difference in lung function parameters and respiratory symptoms. The genetic polymorphisms of detoxifying enzymes were not also homogeneously distributed compared to the controls. Conclusion: There is some evidence that occupational exposure to ambient air pollution among commercial drivers is associated with adverse health outcomes but the existing literature is limited with few studies of small sample size, methodological weaknesses and contradictory findings. Further research is recommended.

Air pollution has created a lot of problems in the developed and developing countries. To avoid or reduce these problems, constant monitoring of the air should be ensured. The conventional techniques is costly because it requires a lot of money and time consuming. Biomonitoring has been the alternative method. Moss, lichens and plants are biomonitors available to entrap air pollutants. The aim of this paper is to discuss one of the ways of monitoring air pollution – Moss bag technique. To do this, types, choice, preparation, handling of bags after preparation of moss were discussed. From the literatures consulted, it was discovered that there were differences in the techniques used by the researchers. In all, the use of mosses with emphasis on the employment of moss bag have proved to be a powerful tool in airborne particulate and toxic elements. To conclude, developing countries should focus more on this technique because it will reduce cost of air monitoring.

The development effect of water flooding in ultra-low permeability reservoir was poor due to its poor physical property and high shale content, the experimental study of air flooding which help to complement producing energy was carried out. Based on the Accelerating Rate Calorimeter experimental results, the crude oil of N block in L oilfield can produce low-temperature oxidation reaction, which was the basic condition of air flooding. Three groups of experiment natural cylinder core were designed for oil displacement, water flooding and air flooding were used respectively, and the relationship of differential pressure, oil recovery, injection capacity with injection volume was investigated. It has been showed on the result that the recovery efficiency improved sharply than water flooding, the effect of depressurization and augmented injection was obvious, and the air displacement was validation.

Ethylene Oxide (EtO) is a colorless, flammable gas at room temperature, produced by the catalytic oxidation of ethylene. EtO is widely used by medical sterilization facilities to clean medical supplies and equipment. Recent epidemiological studies showed that EtO is a more potent carcinogen than previously documented, leading the Environmental Protection Agency (EPA) to update, in December 2016, the inhalation unit risk estimate for EtO. This resulted in the identification of EtO as a potential health concern in several areas across the US, including the state of Utah. The geography surrounding Salt Lake Valley creates a bowl; ideal for collecting air pollution emissions. The region often experiences inversion episodes which inhibit vertical mixing and cause an accumulation of air pollutants, leading to unhealthy pollution levels. Using the EPA's dispersion modeling software, AERMOD, this study estimated EtO concentrations through facility stack and fugitive emissions modeling results. These values were compared with those of canister-based concentrations from ambient air samples taken near a medical device sterilization facility in the Salt Lake Valley. Stainless steel, whole-air passivated canisters were used to collect 24-hour ambient concentration samples of EtO. Eight locations surrounding a Salt Lake Valley medical device sterilization facility and four background sites were chosen to measure the ambient concentrations. Accounting for potential atmospheric impacts on EtO, measurements were sampled in winter 2022 (January-March) and summer 2022 (July-September). The modeled EtO concentrations were adjusted to account for background values associated with the winter or summer data. Then the two methodologies were compared using a Wilcoxon Sign-ranked, paired test. The statistical analysis resulted in six of the eight sample locations surrounding the sterilization facility being significantly different when comparing canister-based measurements of ambient EtO to modeled estimates. Canister-based measurements taken at sites one, three, and four were statistically greater than the modeled estimates, while sites two, five, and seven were statistically less than the modeled estimates. Also, the summer background value calculated was almost 2.5 times greater than the winter. The results do not suggest whether one method is more or less conservative than the other. In conclusion, the five of the closest sites and site seven were statistically different when comparing measured and modeled ambient concentrations of EtO. The comparison results do not clearly indicate if a correction factor could be derived for future human exposure to cancer risk assessment modeling. However, it is reasonable that the closer to the sterilization facility, the more total EtO exposure will be realized.

In water scarcity regions, using data-driven approaches to predict groundwater level is challenging due to limited data availability. However, these regions have substantial water needs and require cost-effective groundwater utilization strategies. In this study, we use artificial intelligence to predict groundwater levels to provide guidance for drilling shallow boreholes for subsistence irrigation. The Bilate watershed, which is located in southern Ethiopia, was selected as the study area. This is typical of areas in Africa with high demand for water and limited availability of well data. Using a non-time-series database of 75 boreholes, machine learning models including multiple linear regression, multivariate adaptive regression spline, artificial neural networks, random forest regression, and gradient boosting regression (GBR) were constructed to predict the depth to the water table. 20 independent variables were considered in the models. GBR performed the best of the approaches with an average 0.77 R-squared value on testing data. Finally, a map of predicted water levels in the Bilate watershed was created based on the best model with water levels ranging from 1.6 to 245.9 meters. With the limited set of borehole data, the results show a clear signal that can provide guidance for borehole drilling decisions for sustainable irrigation with additional implications for drinking water.

Production and transport of reactive species through plasma-liquid interactions plays a significant role in multiple applications in biomedicine, environment, and agriculture. We experimentally investigated the transport mechanisms of hydrogen peroxide H2O2 and ozone O3, as the typical plasma species, into water. We measured the solvation of gaseous H2O2 and O3 in airflow into water bulk vs. electrosprayed microdroplets while changing the gas and water flow rates, applied voltage that determines the gas-liquid interface area, and treatment time. The solvation rate of H2O2 and O3 increased with the treatment time and the gas-liquid interface area. The total surface area of the electrosprayed microdroplets was larger than that of the bulk, but their lifetime was much shorter. We estimated that only microdroplets with diameters below ~ 40 µm could achieve the saturation by O3 during their lifetime, while the saturation by H2O2 was impossible due to its depletion from air. Besides the short-lived flying microdroplets, the longer-lived bottom microdroplets substantially contributed to H2O2 and O3 solvation in water electrospray. This study contributes to a better understanding of the gaseous H2O2 and O3 transport into water as a function of different parameters and will lead to design optimization of the plasma-liquid interaction systems.

The goods and services produced by forest vegetation ecosystem are the driving force for the rapid, high-quality and sustainable development of human society. In history, with the increase of population and economic development, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services in a country or a region. To meet the demands, most of the original forest has become farmland, plantation and grass and crops land. As a result, the plant water relationship changed from equilibrium to non-equilibrium, which easily led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the question and realize the sustainable utilization of soil water resources and the high-quality sustainable development of forest, it is necessary to apply the limit theory of plant utilization of soil water resources and the vegetation carrying capacity theory in the critical period of plant-water relationship regulation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit and realize high-quality and sustainable development.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

Groundwater represents a pivotal asset in conserving natural water reservoirs for potable consumption, irrigation, and diverse industrial uses. Nevertheless, human activities intertwined with industry and agriculture contribute significantly to groundwater contamination, highlighting the critical necessity to appraise water quality for safe drinking and effective irrigation. This research primarily focused on employing the Water Quality Index (WQI) to gauge water's appropriateness for these purposes. However, the generation of an accurate WQI can prove time-intensive owing to potential errors in sub-index calculations. In response to this challenge, an artificial intelligence (AI) forecasting model was devised, aiming to streamline the process while mitigating errors. The study collected 422 data samples from Mirpurkash, a city nestled in the province of Sindh, for a comprehensive exploration of the region's WQI attributes. Furthermore, the study probed into unraveling the interdependencies amidst variables in the physiochemical analysis of water. Diverse machine learning classifiers were employed for WQI prediction, with findings revealing that random forest and gradient boosting eclipsed other algorithms, achieving an accuracy rate of 99%. In close pursuit were SVM and XGBoost, registering accuracy scores of approximately 95% and 93%, respectively, while KNN and Decision Trees garnered accuracy rates of 88% and 87%, respectively. In addition to WQI prediction, the study conducted an uncertainty analysis of the models using the R-factor, providing insights into the reliability and consistency of predictions. This dual approach, combining accurate WQI prediction with uncertainty assessment, contributes to a more comprehensive understanding of water quality in Mirpurkash and enhances the reliability of decision-making processes related to groundwater utilization

A very important role in determining the quality of water is the assessment of its microbiological quality. Water quality control, which could pose a direct threat to human health and life, is performed in the case of water produced at the water treatment plants, tap water or water in swimming pools. However, these traditional methods used to assess its quality are laborious and time consuming. In emergency and incidental situations, in the era of terrorist threats, the need for quick, reliable and reproducible microbiological determinations seems to be essential. In this study, an attempt was made to compare various methods of assessing the microbiological quality of water. The assessment was carried out for waters with different microbiological characteristics: surface waters, rainwater, groundwater, and water supply. The evaluation was carried out using traditional culture methods and high-speed methods: flow cytometry and luminometry. The analysis of microbiological parameters were the basis for the statistical analysis. The conducted microbiological analysis of various types of water, along with their statistical evaluation, showed different dependencies for each of the analysed waters.

Knowledge of water availability in terms of spatial (i.e., depth) and temporal variability of soil water is essential to describe soil water infiltration and storage processes accurately. Therefore, performing simulations of soil water dynamics can be a valuable tool to evaluate different land uses and their impact on water availability. Consequently, this study aimed to model the volumetric soil water content (θ, cm3 cm-3) under agroforestry systems (AFS) with cocoa. For this purpose, the θ was monitored at different depths (0-20, 20-40, 40-60, 60-80, 80-100 cm) in the soil profile of four plots (20 × 50 m) of cocoa under agroforestry systems. Environmental conditions significantly influenced the water balance of the cocoa crop. There were seven moments when evapotranspiration (ET0) was higher than 5 mm d-1. During those moments, the environment exhibited higher PAR values of 1041 µmol m-2 s-1, very low atmospheric relative humidity (RHa) levels (around 45%), higher ambient temperatures of 32.2 ºC and a vapor pressure deficit of 1.6 kPa whose θ levels reached 0.32 cm3 cm-3 and a water balance of -5.7 mm, which presented negative values during most of the study period. The θ obtained from the HYDRUS-1D model presented a slight bias as a high level of coherence between the observed values, based on the model's goodness-of-fit estimators. The above provides accurate simulations of soil water content at various depths, much-needed information for management schemes for cocoa cultivation under agroforestry systems.

Within this paper, a machine learning algorithm is used to investigate the importance of certain setpoints and parameters in the filtration processes of a large-scale water treatment facility. Previously, a model for the filtration process based on Run-to-Run Control was proposed and tested against sample data from the treatment plant, but it was quickly found that such a model was incompatible for successfully computing setpoints of operation which minimize the energy cost of running the filtration systems. The machine learning model described herein is an attempt to elucidate the importance of the available data on the filtration systems and to identify the most important variables that influence the filtration run time.

With permafrost degenerating caused by climate change, water accumulation increases in permafrost regions during last decades. Water accumulation will deteriorate existing status of engineering in cold regions. Water accumulation can make a thermal effect on permafrost under construction, even result in failure of the subgrade. Moreover, the thermal effect is related to water temperature. However, temperature variation of water accumulation is complex, and its influence factors include air temperature, environment, scope of water accumulation and so on. In order to make analysis of the damage mechanism of water accumulation on permafrost, it is necessary to explore the internal temperature change of water accumulation. This paper proposes a review about temperature calculation method of water accumulation in cold environment. The thermal calculation method between air and water boundary of water accumulation is summarized. Water temperature change of water accumulation with various type is analyzed. The thermal calculation considering phase transformation in water accumulation is discussed, and heat transfer from the bottom of water accumulation to the underlying soil is further studied. Finally, the key factors which are advantageous to make research about the thermal effect of water accumulation in permafrost is proposed to optimize calculation method.

Since the second half of the second millennium AD, water management among the Chagga people of Kilimanjaro in Tanzania has involved community collaboration in the construction, ownership and management of water infrastructure. Chagga settlement on the lower slopes of Kilimanjaro transformed the landscape significantly to reflect an agrarian society characterised by decentralised forms of socio-political and economic organisation. Such organization involved conception, construction, and post-construction management of water distribution systems, constituting high-level socio-political complexity. The study employs ethnography, archaeological surveys and GIS to document water infrastructures on the lower slopes of Kilimanjaro. We conclude that community collaboration was key in management of the water infrastructure and by extension, agriculture, which sustained Chagga and chiefdoms for centuries.

Rocks are materials with a wide variety of structures and properties. These can be unprocessed conglomerates of conglomerated minerals as well as crystallized outcrop or metamorphic rocks. Their processing, especially shaping, poses many technological difficulties. Therefore, it is very important to answer the question of how these natural materials yield to high-pressure water jet and abrasive water. It is equally important to determine the effect of key process parameters such as pressure, water nozzle diameter and feed rate on cutting efficiency. The first two parameters determine the water output and power of the jet, while the third determines the jet erosion time per unit volume of material. Their interdependence, using appropriate evaluation indicators, allows to determine the energy intensity of processing and directions for its minimization.

This study looks at the application of delayed action Passive InfraRed (PIR) sensors in the control of water use for urinal flushing. In this we briefly review the literature on urinal controls before reviewing four different approaches to PIR urinal controls. Existing literature discusses some of the pros and cons of different types of urinal control. However, the literature doesn’t consider the marked differences that can occur within individual approaches, based on the way controls operate. This study was initiated at the University of Surrey during 2019 following a water saving audit, in an attempt to bring down what had been identified as one of the largest users of water. This paper therefore aims to identify the most effective way to reduce water consumption of urinal systems, through retro-fitting PIR control systems within the variety of settings found across university campuses. This paper also reviews the different reductions achieved over periods of different levels of use, linked to term time, holidays, Covid-19 related lockdowns, and the ‘new normal’. It found that grouped delayed action flushing was the most effective form of urinal control for reducing water use. The delayed action, grouped PIR sensors, achieved between, a 59-64% adjusted reduction against the control group during non-Covid19 periods, and a 35% reduction against the control group during lockdowns.

Turbulence is a fluid dynamic problem refractory to mathematical treatment. Examining a theoretical model of liquid water flowing in a cylinder at different Raleigh numbers, we propose a novel approach to elucidate the first stages of turbulent flows. The weakly bonded molecular assemblies of liquid water form a fluctuating branched polymer in which every micro-cluster displays different density. Against the common view of liquid water as an incompressible and continuous fluid, we suggest that the occurrence of transient local aggregates could be able to generate the vortices and eddies that are the hallmarks of turbulence. We quantify the local changes in velocity, diameter and density required to engender “obstacles” to the average flow. Then, we show how these microstructures, equipped with different Raleigh numbers and characterized by high percolation index, could generate boundary layers that contribute to micro-vortices production. We conclude that the genesis of turbulence cannot be assessed in terms of collective phenomena, rather is sustained, among many other factors, by the underrated microscopic inhomogeneities of fluids like liquid water.

Stable isotope concentrations in the soil, rain and ground water have been used to trace the water extraction zones of plants in different environments. The need to identify the plant water use by plants in afforestation programs to control desertification increases the importance of sap water partitioning of plants in sand dune areas. However, the introduction of new plant covers exerts pressure on the water resources and can affect the local soil water conditions. In this study, we analyzed the isotope concentrations in rain, soil, sap, and ground water after the summer of 2010. Two experimental plots established in the Hailiutu catchment (Shaanxi province, northwest China) were selected to gather the water samples between September and October 2010. One plot is dominated by Salix bushes (Salix psammophila C. Wang \& Chang Y. Yang) and the other by the tree species Willow (Salix matsudana Koidz.). The total precipitation at the experimental site was 401 mm/yr during 2010, while 88.7 mm was collected in total for the period September to October. Willow trees transpired 12.82 kg/d being almost three times larger than Salix shrubs (4.57 kg/d). Despite the transpiration rates of both plant species and the few rain events in the region, the soil water beneath the plant covers is not depleted. Stable isotope signature of soil water beneath both covers shows the fractionation front in Salix at 20 cm depth and at Willow at 40 cm depth. However, soil water signature is closer to the groundwater than the collected rain water.

In this article, the quality of water in the reservoirs of Lake Arpi, Lake Yerevan, Akhuryan, Azat, Aparan and Kechut was estimated with usage of the Armenian Water Quality Index. It was established that in the waters of reservoirs the the maximum permissible concentration of copper, vanadium, aluminum, chromium, manganese, iron, NH4+ and NO2- regularly increases. The following computational algorithm was used for determination of the Armenian Water Quality Index values: to determine the number of cases of MPC excess of i-substance or indicator of water –n; to estimate the total amount of cases of the maximum permissible concentration (N) – N = ∑n; to computes log2N, nlog2n and ∑nlog2n; to determine geoecological syntropy (I) and entropy (H): I = ∑ nlog2n/N and H = log2N – I. Then, Geo-Ecological Evolving Organized index index was determined: G = H/I. Further, the total amount multiplicity of MAC exceedances was estimated: (M) - M=∑m and log2M was computed. Finally, Armenian Water Quality Index was obtained: AWQI = G + 0.1log2M. It was established that the Armenian Water Qquality Index showed a linear dependence on the Water Contamination Index, the Specific Combinatory Water Quality Index, the Geo-Ecological Evolving Organized index and an inverse dependence on the Canadian Water Quality Index.

For decades, the Ébrié Lagoon in Côte d'Ivoire has been the receptacle of wastewater effluent and household waste transported by runoff water. This work assesses the spatio-temporal variability of the Ébrié lagoon water quality at the city of Abidjan. The methodological approach used in this study is summarized in three stages: the choice and standardization of the parameters for assessing water quality for uses such as aquaculture, irrigation, watering, and sports and recreation; the weighting of these parameters using the Hierarchical Analysis Process (AHP) of Saaty; and finally, the aggregation of the weighted parameters or factors. Physicochemical and microbiological analysis data on the waters of the Ébrié lagoon for June and December of 2014 and 2015 were provided by the Ivorian Center for Anti-Pollution (Centre Ivoirien Anti-Pollution, CIAPOL) and the concentrations of trace elements in sediments (As, Cd, Cr, Pb, Zn) were used. The aggregation of standardized and weighted parameters allowed the determination of the Water Quality Indices (WQI) by usage for each bays of the lagoon. The results show that in both 2014 and 2015, the waters of the Ébrié lagoon were generally of poor quality for the different uses examined in this study (aquaculture, irrigation, watering and sport and recreation) with an accentuation in 2015. However, some bays of the lagoon have waters of dubious to satisfactory quality. This study contributes an improved evaluation of the Ébrié lagoon waters.

This study estimates rainfall interception losses from natural wetland ecosystems based on maximum canopy storage measurements. Rainfall interception losses play an important role in water balance, which is crucial in wetlands, and has not yet been thoroughly studied in relation to this type of ecosystem. Maximum canopy storage was measured using the weight method. Based on these measurements, daily values of interception losses were estimated and then used to calculate long term interception losses based on precipitation and potential evapotranspiration data for the 1971–2015 period. Depending mainly on the number of days with precipitation, the results show that total interception losses for the growing season as well as monthly interception losses are around 13% of gross rainfall. This value is similar to the values observed for some forests. Hence, interception losses should not be disregarded in hydrologic models of wetlands, especially because data trends in meteorological conditions (mainly number of days with precipitation) show that interception losses will increase in the future if those trends stay the same.

There is a balanced plant-water relationship in the primary vegetation of desert area. With the increase of population and social development in desert areas, people’s need for forest vegetation ecosystem’s goods and service have been changed. To meet the growing demand for plant community goods and services, more original vegetation has been changed into non-native vegetation such as in China loess plateau. However, with the plant growth, sometime soil drying happens and then becomes gradually serious with times in most of desert regions. Serious drying of soil eventually result in soil degradation, vegetation decline and agriculture failure，which influence the produce and supply of forest vegetation goods and service in market in dry year or waste of soil water resources in wet year, which wastes precious nature resources. In order to solve these problems, the soil water resources have to be used in sustainable way and plant-water relationship have to be regulated on Carrying Capacity of Soil Water for Vegetation in the key period of plant water relationship regulation, to carry out sustainable use of nature resources, high-quality and sustainable development of forest and grass or high-quality produce of fruit and crop in desert re-gions.

Radical reactions in water or aqueous media are important for organic synthesis, realizing high yielding processes under non-toxic and environmentally friendly conditions. This overview includes (i) a general introduction to organic chemistry in water and aqueous media, (ii) synthetic approaches in-, on- and with-water as well as in heterogeneous phase, (iii) reaction of carbon-centered radicals with water (or deuterium oxide) activated through coordination with various Lewis acids, (iv) photocatalysis in water and aqueous media, and (v) synthetic applications bioinspired from naturally occurring processes. A wide range of chemical processes and synthetic strategies under different experimental conditions have been reviewed that lead to important functional group translocation and transformation reactions, leading to the preparation of complex molecules. These results reveal how water as a solvent/medium/reagent in radical chemistry has matured over the last two decades and how further discoveries are foreseen to come in the near future.

This article presents a field-performance investigation on an Integrated Solar Water Supply System (SWSS) at two isolated agricultural areas in Thailand. The two case-study villages (Pongluek and Bangkloy ) have experienced severe draughts in the last decades, and therefore water supply has become a major issue. A stand-alone 15.36 kW solar power and a 15 kW solar submersible pump were installed along with the input power generated by solar panels supported by four solar trackers. The aim is to lift water at the static head of 64 and 48 m via piping length of 400 metres for each village to be stored in 1,000 m3 and 1,800 m3 reservoirs at an average of 300 m3 and 400 m3 per day, respectively for Pongluek and Bangkloy villages. The case study results have shown that the real costs of electricity generated by SWSS using solar PV systems intergraded with the solar tracking system yield better performance and are more advantageous compared with the non-tracking system. This study illustrates how system integration has been employed. System design and commercially available simulation predictions are elaborated. Construction, installation, and field tests for SWSS are discussed and highlighted. Performances of the SWSS in different weather conditions such as sunny, cloudy, and rainy days were analysed to make valuable suggestions for higher efficiency of the integrated solar water supply systems.

Drought-induced plant mortality has increased globally during the last decades and is forecasted to influence global vegetation dynamics. Timely information on plant water dynamics is essential for understanding and anticipating drought-induced plant mortality. The most common metric that has been used for decades for measuring water stress is leaf water potential (Ψ_L), which is measured destructively. To obtain information on water dynamics from trees and forested landscapes, remote sensing methods have been developed. However, the spatial and temporal resolution of the existing methods have limited our understanding of water dynamics and diurnal variation of Ψ_L within single trees. Thus, we investigated the capability of terrestrial laser scanning (TLS) intensity in observing diurnal variation in Ψ_L during a 50 hour monitoring period and aimed to improve understanding on how large part of the diurnal variation in Ψ_L can be captured using intensity observations. We found that TLS intensity at 905 nm wavelength was able to explain 78% of the variation in Ψ_L for three trees of two tree species with a root-mean square error of 0.137 MPa. Based on our experiment with three trees, time-series of TLS intensity measurements can be used in detecting changes in Ψ_L, and thus it is worthwhile to expand the investigations to cover a wider range of tree species and forests and further increase our understanding of plant water dynamics at wider spatial and temporal scales.

UV-A (ca. 365 nm wavelength, a.k.a. 'black light') photocatalysis has been investigated to comprehensively mitigate odor and selected air pollutants in the livestock environment. This study was conducted to confirm the performance of UV-A photocatalysis on the swine farm. The objectives of this research were to (1) scale-up of the UV-A photocatalysis treatment, (2) evaluate the mitigation of odorous gases from swine slurry pit, and (3) test different UV sources, (4) evaluate the effect of suspended particulate matter (PM), and (5) conduct preliminary economic analyses. We tested UV-A photocatalysis at a mobile laboratory-scale capable of treating ~0.2 - 0.8 m3·s-1 of barn exhaust air. The targeted gaseous emissions of barn exhaust air were significantly mitigated (p < 0.05) up to 40% reduction of measured odor; 63%, 44%, 32%, 40%, 66%, and 49% reduction of dimethyl disulfide, isobutyric acid, butanoic acid, p-cresol, indole, and skatole, respectively; 40% reduction of H2S; 100% reduction of O3; and 13% reduction of N2O. The PM mitigation effect was not significant. Formaldehyde levels did not change, and a 21% generation of CO2 was observed. The percent reduction of targeted gases decreased as the airborne PM increased. Simultaneous chemical and sensory analysis confirmed that UV-A treatment changed the overall nuisance odor character of swine barn emissions into weaker manure odor with 'toothpaste and 'mint' notes. The smell of benzoic acid generated in UV-A treatment was likely one of the compounds responsible for the less-offensive overall odor character of the UV-treated emissions. Results are needed to inform the design of a farm-scale trial, where the interior barn walls can be treated with the photocatalyst, and foul air will be passively treated as it moves through the barn.

(1) Aim of the study was to investigate the spatial and temporal characteristics of the airflow created by two commercially available non-contact tonometers, the CorvisST and the Ocular Re-sponse Analyser. (2) The airflow pressure was measured using a MEMS pressure sensor to inves-tigate the spatial and temporal distribution. The airflow from the CorvisST and Ocular Response Analyser were mapped to a 600µm and a 1mm resolution grid, respectively. (3) Central airflow pressure of the CorvisST (96.4 ± 1.4)mmHg was higher than the Ocular Response Analyser (91.7 ± 0.7)mmHg. The duration of the air-puffs also differed, with the CorvisST showing a shorter du-ration (21.483 ± 0.2881)ms than the ORA (23.061 ± 0.1872)ms. The rising edge of the CorvisST airflow pressure profile demonstrated a lower gradient (+8.94mmHg/ms) compared to the Oc-ular Response Analyser (+11.00mmHg/ms). Both had similar decay response edges; CorvisST -11.18mmHg/ms, Ocular Response Analyser -11.65mmHg/ms. (4) The study presents a valid method to investigate physical dimensions of the airflow pressure of non-contact tonometers. Novel findings relating to the magnitude, duration and spatial characteristics of the respective airflow pressures are reported. It is anticipated that this information will better inform clinical studies and theoretical models relating to ocular biomechanics.

Environmental impact associated with odor and gaseous emissions from animal manure is one of the challenges for communities, farmers, and regulatory agencies. Microbe-based manure additives treatments are marketed and used by farmers for mitigation of emissions. However, their performance is difficult to assess objectively. Thus, comprehensive, practical, and low-cost treatments are still in demand. We have been advancing such treatments based on physicochemical principles. The objective of this research was to test the effect of the surficial application of a thin layer (¼"; 6.3 mm) of biochar on the mitigation of gaseous emissions (as the percent reduction, % R) from swine manure. Two types of biochar were tested: highly alkaline and porous (HAP) biochar made from corn stover and red oak (RO), both with different pH and morphology. Three 30-day trials were conducted with a layer of HAP and RO (2.0 & 1.65 kg∙m^-2, respectively) applied on manure surface, and emissions of ammonia (NH₃), hydrogen sulfide (H₂S), greenhouse gases (GHG), and odorous volatile organic compounds (VOCs) were measured. The manure and biochar type and properties had an impact on the mitigation effect and its duration. RO significantly reduced NH₃ (19-39%) and p-cresol (66-78%). H₂S was mitigated (16~23%), but not significantly for all trials. Significant (66~78%) reductions for p-cresol were observed for all trials. The phenolic VOCs had relatively high % R in most trials but not significantly for all trials. HAP reduced NH₃ (4~21%) and H₂S (2~22%), but not significantly for all trials. Significant % R for p-cresol (91~97%) and skatole (74~95%) were observed for all trials. The % R for phenol and indole ranged from (60~99%) & (29~94%) but was not significant for all trials. The impact on GHGs, isobutyric acid, and the odor was mixed with some mitigation and generation effects. However, larger-scale experiments are needed to understand how biochar properties and the dose and frequency of application can be optimized to mitigate odor and gaseous emissions from swine manure. The lessons learned can also be applicable to surficial biochar treatment of gaseous emissions from other waste and area sources.

The aim of this research was to investigate the mass, substances and energy flow through two-stroke low speed Diesel engines. For this reason, a zero-dimensional model of the combustion in the engine was developed with a calculated amount and composition of exhaust gases. Due to the large amount of oxygen in the exhaust gases, a ratio of real air consumption and stoichiometric amount of air required for combustion of injected fuel was set. The calculated ratio showed that the engine consumes four times more air than needed for combustion in AFR_stoich. In this work it is called the Air Consumption Factor or Ratio and has not been mentioned in scientific literature before. Air Consumption Ratio is defined as a factor of dry or humid air. To be more comprehensive, a modified diagram of composition of the flow in and out of a two-stroke fuel injection engine and the cylinder was drawn.

Arsenic is naturally present in many geological formations around the world and is a major source of groundwater contamination. Bolivia is not exempt from this problem. Physical-chemical studies of water quality in deep and shallow wells have determined the presence of arsenic in some areas of the Bolivian Altiplano, valleys, and plains. In the Lake Poopó basin, water from shallow wells (up to 30 m) has arsenic concentrations that exceed the Bolivian drinking water standard and the WHO recommendation of 10 μg-As/l by up to 25 times. In peri-urban areas of Cochabamba, the arsenic content in groundwater is up to 113 μg-As/l. chronic exposure to arsenic is associated with neurological and dermatological problems and carcinogenic effects. To date, no measures have been taken to mitigate the arsenic problem for the rural population, who often rely on arsenic-contaminated water as their only source of drinking water. This contamination represents a serious threat to the health and economic well-being of the inhabitants and ecosystem in these areas. In this work, for arsenic removal, iron and iron oxide nanoparticles obtained from recycling metal chips by top-down and bottom-up technology have been used for arsenic adsorption in an experimental filter combined with other artisanal filtering materials in the form of layers. The results have shown that water contaminated with arsenic after passing through the filter reduces the concentration of total arsenic filtered from 83, 52 ppb to less than 5 ppb, less than the Bolivian standard 512 of 10 ppb for drinking water.

The aim of this research involves investigating the elimination of nitrogen ions from groundwater through the application of dynamic permeable reactive barriers (PRB) utilizing A400-nZVI. The aim also implyies determining barrier parameters, as well as assessing the overall retention capacity of nitrogen ions through percolation with a potassium nitrate solution. The research involves obtaining zero valent iron nanoparticles (nZVI), which were synthesized and doped onto an anionic resin support material (A400) through the reduction reaction of ferrous ions with sodium borohydride (NaBH4). This was achieved by preparing a ferrous sulfate solution, contacting it with the ion exchange resin at various solid-liquid mass ratios, and gradually adding sodium borohydride under continuous stirring in an oxygen-free environment to create the A400-nZVI barrier. The outcomes of this study, focusing on the development of permeable reactive barriers composed of nanovalent iron and ion exchangers, demonstrate significant potential in purification processes when appropriately dimensioned. The research specifically evaluated the efficacy of NO3- removal using the A400-nZVI permeable reactive barrier, conducting laboratory tests that simulated a naturally stratified aquifer with high nitrate contamination.

Nephrolithiasis affects around 10% of the population and is frequently associated with impaired dietary factors. The first one is insufficient fluid intake inducing reduced urine volume, urine supersaturation, and subsequently urinary lithiasis. Kidneys regulate 24-hour urine volume, which, under physiological conditions, approximately reflect daily fluid intake. Increasing fluid intake has a preventive effect on the risk of developing a first kidney stone (primary prevention) but also decreases the risk of stone recurrence (secondary prevention). Current guidelines recommend increasing fluid intake at least at 2.5L /day to prevent stone formation, and even at 3.5-4L in some severe forms of nephrolithiasis (primary or enteric hyperoxaluria or cystinuria). Fluid intake must also be balanced between day and night, to avoid urinary supersaturation during the night. Patients should be informed and supported in this difficult process of increasing urine dilution, with practical ways and daily routines to increase their fluid intake. The liquid of choice is water, which should be chosen depending on its composition (such as calcium, bicarbonate or magnesium content). Finally, some additional advices have to be given to avoid some beverages such as those containing fructose or phosphoric acid, which are susceptible to increase the risk of nephrolithiasis.

A biofilm is any syntrophic consortium of microorganisms in which cells adhere to one another and, in some cases, to a surface. These adherent cells become encased in a slimy extracellular matrix made up of extracellular polymeric substances (EPSs). Until now, the use of commercial disinfectants remains the main strategy to control biofilm-mediated problems. This mini review summarizes common antibiofilm mode of actions taken by disinfectants and how water channels in microbial biofilms contribute to disinfectant resistance.

This research was conducted to analyze the content of Fe, Cu, Cd, Cr, and Pb in several species of fish taken from three lakes that is closely to disposal of industrial waste in Indonesia. The fish samples were taken from three lakes, namely, Muara Angke, Weda, and Morowali. The samples from Morowali were analyzed in April 2019, those from Weda from November to December 2019, and those from Muara Angke in June 2018. All the samples were then analyzed at the chemistry laboratory of the Department of Chemistry, Faculty of Mathematics and Natural Science, University of Indonesia, and the Integrated Laboratory of IPB. The results showed that all types of fish from Morowali and Weda were no longer safe to consume because they contained Fe, Cu, Cd, and Cr exceeding the threshold of metal contamination. Meanwhile, all types of fish from Muara Angke, except for ayam-ayam, are still safe for consumption. The results of this study can be a source of information regarding metal content in fish and fish feed for safe consumption. Several studies have been done to determine the metal pollutants contained by fish. Given the high consumption rate of fish and the hazards of heavy metals on humans’ health, such research must be furthered

The Delaware River has made a marked recovery in the half-century since the adoption of the Delaware River Basin Commission (DRBC) Compact in 1961 and passage of the Federal Clean Water Act amendments during the 1970s. During the 1960s, the DRBC set a 3.5 mg/l dissolved oxygen criteria for the river based on an economic analysis that concluded a waste load abatement program designed to meet fishable water quality goals would generate significant recreation and environmental benefits. Scientists with the Delaware Estuary Program have recently called for raising the 1960s DO criteria along the Delaware River from 3.5 mg/l to 5.0 mg/l to protect anadromous American shad and Atlantic sturgeon and address the prospect of rising temperatures, sea levels, and salinity in the estuary. This research concludes through a marginal abatement cost (MAC) analysis that it would be cost effective to raise DO levels to meet a more stringent standard by prioritizing agricultural conservation and wastewater treatment investments in the Delaware River watershed to reduce 90% of the pollutant load 13.6 million kg/year of nitrogen (30 million lb/year) for $160 million at 35% of the $449 million annual cost. The annual least cost to reduce nitrogen loads and raise dissolved oxygen levels to meet more stringent water quality standards in the Delaware River totals $45 million for atmospheric NOX reduction, $130 million for wastewater treatment, $132 million for agriculture conservation, and $141 million for urban stormwater retrofitting. This 21st century least cost analysis estimates that $50 million/year is needed to reduce pollutant loads in the Delaware River to raise dissolved oxygen levels to 4.0 mg/l, $150 million/year is needed to reach 4.5 mg/l, and $449 million/year is needed to reach 5.0 mg/l.

Accurate prediction of mercury content emitted from fossil-fueled power stations is of utmost importance for environmental pollution assessment and hazard mitigation. In this paper, mercury content in the output gas of power stations’ boilers was predicted using an adaptive neuro-fuzzy inference system (ANFIS) method integrated with particle swarm optimization (PSO). The input parameters of the model include coal characteristics and the operational parameters of the boilers. The dataset has been collected from 82 power plants and employed to educate and examine the proposed model. To evaluate the performance of the proposed hybrid model of ANFIS-PSO model, the statistical meter of MARE% was implemented, which resulted in 0.003266 and 0.013272 for training and testing, respectively. Furthermore, relative errors between acquired data and predicted values were between -0.25% and 0.1%, which confirm the accuracy of the model to deal nonlinearity and representing the dependency of flue gas mercury content into the specifications of coal and the boiler type.

Water sustainability has become one of the most severe issues in the 21st Century due to dramatic urban population growth and climate change. This paper reviews some of the critical key water issues that need to be considered/incorporated in the quest for water sustainability for the upcoming decades. The purpose is to recognize the critical circumstances for maintaining water sustainability and recognize that many regions in the world have passed the ‘tipping point’ of balancing their water sustainability and failing to realize that restoring sustainability will be extremely difficult. From the water quantity perspective, several examples are used to demonstrate situations which, in hindsight, have been initially shown to be effective but highly problematic in the long term. The review considers, amongst others, the 1960s India example shows that an agricultural ‘success’ starting in the 1960s has subsequently become an environmental disaster. Additional issues, including the impacts of dietary adjustments, upstream diversions raising downstream shortfalls, and transfers of water from agriculture to urban areas, are examples that demonstrate that to achieve water sustainability, lessons must be learned from the past, and adaptive measures must be adopted to help humanity avoid adverse and irreversible environmental tragedies. Government authorities can learn from this critical review of some approaches and realize their responsibility to proactively promote better water resource management strategies (domestic and international collaborations) and strictly regulate water use practices to better manage water sustainability.

Indigenous Peoples in Canada have shown great strength and resilience in maintaining their cultures and ways of life to date in the face of settler colonialism. Centering the water crises within Indigenous sovereignty and self-determination, we explore the impacts these crises are having on community members. Particularly, the continuous failure of the Canadian government to end the water crises in remote Indigenous communities, Star Blanket Cree Nation, is investigated in this paper. What implications have these water governance gaps had on Indigenous Peoples’ sovereignty and self-determination? We adopted an Indigenist theoretical framework to guide the study. Additionally, a community-based participatory research approach was adopted. To achieve our research goals of investigating the implications of the current water crises for Indigenous sovereignty and self-determination, specific methods of sharing circles were used to gather knowledge from community members, Elders, and knowledge keepers. The research findings strongly highlight the strength and resilience shown by remote Indigenous communities in the face of the current water crises and continuous government failure. Solving the current water crises will involve remote Indigenous communities taking charge of their own water governance through Indigenous-led water governance systems. Additionally, taking steps to rebuild trust through genuine reconciliation will be key. Therefore, listening to remote Indigenous communities and taking collaborative action is fundamental.

In Mexico, the evaluations of environmental flows are regulated by the Mexican Norm NMX-AA-159-SCFI-2012 and they warrant the establishment of water reserves for the environment. Yet, the pressure for water use limits the establishment of said reserves. This research aimed to evaluate the changes through time of the variables that serve as a basis for the implementation strategy by the Mexican government. A geographical information system was built with updated variables, the desired conservation status was analyzed, and the potential reserves were estimated based on the reference values for all basins nationwide. The results were examined according to their historical, current, and potential contribution to the conservation of natural protected areas and their connectivity. The outcomes point towards an administrative implementation strategy with positive outcomes despite the growing pressure for water use, with a change rate higher than the one for the creation of new protected areas. Currently, basins with low pressure and high conservation value have the potential to contribute to 86–88% of the goal set by the present administration without affecting water availability. Finally, reserving water in the priority basins would guarantee the legal protection of the flow regime in 48–50% of the hydrographic network in a desired conservation status, 45–49% of wetlands of international importance, and other natural protected areas in 85–89% of the global ecoregions represented in Mexico.

Recreational water activities are widely recognized to have a positive impact on our physical and mental well-being. However, recreational water sources and their management are also a risk factor for human health, due to different agents, including the overgrowth of cyanobacteria and algae. These organisms have the potential to metabolize organic matter and produce thermophilic and thermotolerant toxins. Different species of algae participate in biofilm formation and impact on maintenance of equipment for water treatment. We reviewed the state of the art by providing basic definitions, taxonomy and the epidemiological and clinical issues related to the recreational uses of waters. Methods for treatments and monitoring are summarized, considering both traditional and innovative strategies. Public health and surveillance perspectives impose to focus on the detection of toxins, the formation of biofilms, the understanding of the benthonic and planktonic components as part of a larger microbial biodiversity.

Cambodia faces the challenge of managing excess water during the wet season and insufficient water during the dry season. This harms human life and endangers aquatic and natural resources, agricultural practices, and food security. In order to ensure the well-being of both people and food security, water governance is crucial. However, Cambodia's water governance is hindered by various obstacles, including sectoral and centralized influences, top-down and large-scale strategies, a lack of coordination among relevant agencies, and limited involvement of local communities. This study delves into water governance across different sectors, from centralized to community-based natural resources management to tackle these challenges. Through analyzing literature and case studies of farmer water user communities (FWUC), community fisheries (CFis), and community fish refuges (CFRs) in three Mekong Delta provinces in Cambodia, the study concludes that although water governance has improved, it has resulted in a decline in fishery resources from rivers and water bodies and an increase in water conflicts among farmers and sectors in the face of climate change. To enhance water governance in Cambodia, it is critical to integrate it at the district level. This will promote sustainable water use and management across the country and pave the way for a brighter future.

We investigate if anyone is being left behind in accessing safely managed drinking water (SM) in achieving the 2030 agenda. We use 23 countries grouped globally as critically insecure water (CIWC). The results indicate none of the CIWC had over 50% of the population accessing SM, N. America and Europe had highest percentages while Sub Saharan Africa had the least. People left behind are found in rural areas, in countries vulnerable to climate change because of poor governance, low-income, and women’s low education. Institutional quality, equity and equality should be improved in using resources critical to leaving no one behind.

In this study, we investigated water transparency estimation models in the hypertrophic lagoon of the Albufera of Valencia using Sentinel-2 images. Water transparency, a crucial environmental indicator, was assessed via Secchi disk depth (ZSD) measurements. Three optical models (R490/R560, R490/R705, R560/R705) were explored to establish a robust algorithm for ZSD estimation. Through extensive field sampling and laboratory analyses, weekly data spanning 2018 to 2023 were collected, including water transparency, temperature, conductivity, and chlorophyll-a concentration. Remote sensing imagery from the Sentinel-2 mission was employed, and images were processed using SNAP software. The R560/R705 model, calibrated for turbid lakes, emerged as the most suitable. The algorithm's calibration was validated with high correlation coefficients (R2) in both calibration (0.6149) and validation (0.916) phases, demonstrating the model's accuracy in estimating ZSD. This new algorithm significantly outperformed a previous approach, highlighting the importance of tailoring algorithms to specific water body characteristics. The study contributes to improved water quality assessment and resource management, underscoring the value of remote sensing in environmental research.

The municipal water supply, related mainly to the cities of Albanian, began to develop in the second half of the 19th century and much intensively after 1945. Today the reported mean water production for the cities, on average, is about 300 l/capita/d including drinking and industrial water supply. The territory of Albania consists of uneven distribution of very heterogeneous aquifers conditioning the reach variety of the municipal water supply solutions. In this article are analyzed and classified the hydrogeological aspects of water supply sources of the settlements, which are summarized in five groups: (a) Wells in alluvial intergranular aquifers; (b) karst springs; (c) wells in karst aquifers; (d) springs in fissured rocks, and (e) mixed water sources. For each group of the water supply sources the main concerns regarding the quantity and quality problems are analyzed facilitated by the description of a variety of representative examples of different situations. Based on the gained experience important recommendation are given for the better understanding of hydrogeological aspects of water supply systems emphasizing the problematics along the river water recharge areas and on the seawater intrusion in coastal aquifers, as well as on transboundary aquifers. However, the main problems of public water supply of Albania remain the poor management of water supply systems which is reflected in the e high water losses, as well as the low public awareness of request for sustainable use.

Nitrogen (N) applications can play a key role in achieving profitable wheat production in the low-fertility soils prevalent under rainfed conditions. The model-predicted N partitioning revealed that ammonia-nitrogen (NH4-N) contributed little to the plant N nutrition, and its concentration in the soil remained below 2 ppm throughout the crop season except immediately after the NH4-N based fertilizer application. Nitrate-nitrogen (NO3-N) gradually increased (maximum 144 ppm) with time, especially in the 0-40 cm horizons, and contributed to most N uptake during both seasons at both locations. The N losses from the soil at the medium rainfall site (3.5-20.5 kg ha-1) were mainly attributed to NH4-N volatilization (Nv) and NO3-N leaching (NL) below the crop root zone. Water productivity (8-40 kg ha-1 mm-1) and N use efficiency (31-41 kg kg-1) showed immense variability induced by climate, water availability, and N dynamics in the soil. These results suggest that combining water balance and N modeling can help manage N applications to optimize wheat production and minimize N losses in rainfed agriculture.

Differences in the physical and chemical properties of reclaimed water (RW) and natural surface water (SW) lead to the differences in terms of nitrogen and phosphorus release when pipeline sediments enter these water bodies. The nitrogen and phosphorus release kinetics from pipe sediments with different particle sizes have been investigated. The results demonstrated that both SW and RW had a pH buffering effect after sediment addition, and the final pH (approximately 8.1) of RW was lower. The release of total phosphorus (TP) and ammonia nitrogen ( NH₄⁺-N) fitted the first-order kinetic model where the release of TP reached equilibrium; TP release was inhibited in both SW and RW, where RW exhibited the lowest (by a factor of 1.23~2.44) release (0.002 mg/g). The release of NH4+-N was promoted in both SW and RW; the maximum release in RW was 0.0188 mg/g. The amounts of NH₄⁺-N released in SW and RW were 1.02-1.40 and 1.30-1.80 times that of the control group (CG), respectively. The percentage of TP and NH₄⁺-N release in the three groups was highest in 75-154 μm pipe sediment, reaching 34.53% and 43.51% in SW and RW, respectively. These results can assist in the development of water quality evolution models for specific urban scenarios, and provide important guidance for the precise regulation of recharge water quality during and after rainfall.

Multivariate predictive analysis of the Stream-Water (SW) parameters (discharge, water level, temperature, dissolved oxygen, pH, turbidity, and specific conductance) is a pivotal task in the field of water resource management during the era of rapid climate change. The highly dynamic and evolving nature of the meteorological and climatic features have a significant impact on the temporal distribution of the SW variables in recent days making the SW variables forecasting even more complicated for diversified water-related issues. To predict the SW variables, various physics-based numerical models are used using numerous hydrologic parameters. Extensive lab-based investigation and calibration are required to reduce the uncertainty involved in those parameters. However, in the age of data-informed analysis and prediction, several deep learning algorithms showed satisfactory performance in dealing with sequential data. In this research, a comprehensive Explorative Data Analysis (EDA) and feature engineering were performed to prepare the dataset to obtain the best performance of the predictive model. Long Short-Term Memory (LSTM) neural network regression model is trained using over several years of daily data to predict the SW variables up to one week ahead of time (lead time) with satisfactory performance. The performance of the proposed model is found highly adequate through the comparison of the predicted data with the observed data, visualization of the distribution of the errors, and a set of error matrices. Higher performance is achieved through the increase in the number of epochs and hyperparameter tuning. This model can be transferred to other locations with proper feature engineering and optimization to perform univariate predictive analysis and potentially be used to perform real-time SW variables prediction.

Clean production of renewable fuels is a great challenge of our scientific community. Iridium complexes have demonstrated a superior catalytic activity in the water oxidation (WO) reaction, which is a crucial step in water splitting process. Herein we have used a defective zirconium MOF with UiO-66 structure as support of a highly active Ir complex based on EDTA with formula [Ir(HEDTA)Cl]Na. The defects are induced by the partial substitution of tereftalic acid with smaller formiate groups. Anchoring of the complex occurs through a post-synthetic exchange of formiate anions, coordinated at the zirconium clusters of the MOF, with the free carboxylate group of the [Ir(HEDTA)Cl]-complex. The modified material was tested as heterogenous catalyst for the WO reaction by using Cerium Ammonium Nitrate as sacrificial agent. Although TOF and TON values are comparable to those of other iridium heterogenized catalysts, the MOF exhibits iridium leaching not limited at the first catalytic run, as usually observed, suggesting a lack of stability of the hybrid system under strong oxidative conditions.

Water hyacinth (Eichhornia crassipes) is an invasive species that has modified ecosystem functioning in the Sacramento-San Joaquin Delta (Delta), California, USA. Studies in lakes and rivers have shown that water hyacinth alters water quality. In tidal systems, such as the Delta, water moves back and forth through the water hyacinth patch so water quality directly outside the patch in either direction is likely to be impacted. In this study, we asked whether the presence or treatment of water hyacinth with herbicides resulted in changes in water quality in this tidal system. We combined existing datasets that were originally collected for permit compliance and long-term regional monitoring into a dataset that we analyzed with a before-after control-impact (BACI) framework. This approach allowed us to describe effects of presence and treatment of water hyacinth, while accounting for seasonal patterns in water quality. We found that although effects of treatment were not detectable when compared with water immediately upstream, dissolved oxygen and turbidity became more similar to regional water quality averages after treatment. Temperature became less similar to the regional average after treatment, but the magnitude of the change was small. Taken together, these results suggest that tidal hydrology exports the effects of water hyacinth upstream, just as river flow is known to transport the effects downstream, creating a buffer of altered water chemistry around patches. It also suggests that although water hyacinth has an effect on dissolved oxygen and turbidity, these parameters recover to regional averages after treatment.

Integrated Water Resources Management (IWRM) is one of the system thinking approaches emerged in the 1990s. Since then it has been applied in various countries and contexts. However, the implementation of the IWRM is contested. There are paucity of literature and guidelines as to how the concept can be operationalized. In Ethiopia, there is no evidence that IWRM is successfully instituted. Particularly, IWRM has never been implemented in the Awash River Basin. The study generated data from household and institutional surveys, in-depth interviews, focused group discussions, workshops, and secondary sources. Multiple sources of data were triangulated and thematically summarized. We found that pragmatic water resources management through system approach helps to recognize river basin as a bigger system in which the natural and human systems function. This resolves the problem of fragmentations among among various actors, sectors, interest and priorities. That it facilitates the coordination of various subsystems. The operationalization of IWRM as a system to secure water resources require the establishment and/or strengthening of the interactions of various systems, subsystems, and the elements within the entire basin system. Finally, enabling institutional environments should be considered as a medium of realizing IWRM.

Water pollution associated with flooding is one of the major problems in cities in the global South. However, studies of water quality dynamics during flood events are not often reported in literature, probably due to difficult conditions for sampling during flood events. Water quality parameters in open water (canals, rivers, and lakes), floodwater on roads and water in sewers have been monitored during the extreme fluvial flood event on 7 October 2013 in Can Tho city, Vietnam. This is the pioneering study of urban flood water pollution in real time in Vietnam. The results showed that water quality is very dynamic during flooding, especially at the beginning of the event. In addition, it was observed that the pathogen and contaminant levels in the floodwater are almost as high as in sewers. The findings show that population exposed to flood water runs a health risk that is nearly equal to that of being in contact with sewer water. Therefore the people of Can Tho not only face physical risk due to flooding, but also exposed to health risk.

An adequate representation of the water infiltration process in the soil allows improving the efficiency in application and the uniformity in surface irrigation. The Green and Ampt model has shown a good representation of the process, and researchers from the United States Department of Agriculture (USDA) determined the values of their parameters for soils of that country, which are shown in tables or through functional relationships and this information is used as reference in several parts of the world, although there is no certainty that they are representative of the soils in Mexico. In this study, the parameters of the Green & Ampt equation were determined and evaluated in some soils of agricultural importance in Mexico. The parameters were obtained in four ways: one of them applied a methodology adapted from Brooks and Corey to quantify the wetting front capillary pressure head and used an permeameter under constant hydraulic head to determine the saturated hydraulic conductivity, and the other three consisted in taking them from three studies reported by the USDA. The values of the parameters suggested in Mexico drastically underestimated the results with relative errors (RE) in a range of -49.0 to -94.0% and the most representative were those obtained with the methodology proposed in this research with RE of -15.0 to 6.0%.

Reactive oxygen species (ROS) play a pivotal role in cellular function, and their overproduction contributes to oxidative stress, fatigue, aging, and diseases. To counteract these effects, incorpo-rating antioxidant-rich nutrients is recommended. Functional waters, including electrolyzed hydrogen water (EHW), are gaining attention for potential antioxidant effects through daily in-take. This study employs aquaphotomics and near-infrared spectroscopy (NIRS) to elucidate the molecular mechanisms behind the antioxidant activity of EHW. Previous investigation reported a 100% loss in antioxidant functionality through autoclaving, and a 40% decrease with hydrogen gas removal, prompting the current investigation into the mechanisms of antioxidant effects and especially the role of water molecular structure in it. Aquaphotomics analysis of near infrared (NIR) spectral data revealed that the primary characteristic of EHW associated with anti-radical function is presence of water solvation shells. Autoclaving and degassing led to loss of these water molecular species and a significant increase in free water molecules. The study suggests that water shells (solvation shells) in EHW play a crucial role in neutralizing ROS, although the specific ions or nanoparticles responsible for creating these shells remain unidentified. This concept aligns well with existing proposals of the crucial role of water solvation shells in ROS neutralization.

Ethiopian Airlines is a leading airline in the world. Its supply chain management is one of the most critical aspects in achieving its sustainability objectives. The present study aims to assess the sustainability practices and strategies of Ethiopian Airways in its supply chain, identifying areas for improvement and recommending strategies for enhancing sustainability. The study concentrates on pertinent sustainability concerns within the aviation sector while examining antecedent research on the sustainability of Ethiopian Airlines’ supply chain management strategies. The findings of the study reveal that there are several areas in need of improvement, including the implementation of waste reduction measures, the establishment of a recycling program, and the reduction of single-use plastic usage. It is suggested that promoting responsible tourism embodying sustainable practices is imperative, particularly within the airline context.

In this paper we present a city-scale (possibly global) air pollution network made of low-cost sensors for particulate matter concentration in the air. The components of presented system are based on our research and experience from previous studies focused on air quality instruments and sensors for addressing urban air pollution. Sensor nodes are produced locally and distributed over a city of Sarajevo, Bosnia and Herzegovina. The system collects, calibrates and displays particulate metal concentrations in real-time. In comparison to the available measurements from governmental institutions, our system demonstrated good agreement of measured parameters, with several advantages including: higher resolution in space and time, lower costs, both horizontal and vertical measurements and many more. One of the capabilities of the system is the real-time air pollution city map with animations. By installing multiple sensor nodes over a slope (cable car), we receive vertical measurements of temperature, humidity and particulate matter concentration in real time, which gives a valuable insight into the dynamics of temperature inversion episodes and air pollution below the inversion layer.

Air pollution is a situation that negatively affects the health of humans and all living things in nature and causes financial damage to the environment. In the case of air pollution, harmful and foreign substances in the air reach an amount and density above normal values. Air pollution also causes climate change, which affects global warming. Particulate matter is a harmful substance that harms the health of humans and other living things, causes air pollution, increases radiation, and negatively affects cloud formation. Particulate matter is extremely small solid particles and liquid droplets suspended in the air. PM10, which is less than 10 microns in diameter, is defined as small particles that can remain in the air for a long time and settle in the respiratory tract, damaging the lungs. Many criteria affect PM10 density and changes in density. The main criteria are vehicle traffic and fuel consumption, industrialization, coal, fuel oil and wood-burning heaters, greenhouse gas impact, and unregulated urbanization. It is important to identify the underlying causes of air pollution caused by PM10. In this context, these criteria need to be evaluated to minimize the negative effects of PM10. In the study, monthly average PM10 data between 2019 and 2023 obtained from the Air Monitoring Station in Kocaeli, Türkiye are used. After determining the criteria affecting PM10, the criteria are prioritized with the Intuitionistic Fuzzy AHP (IF-AHP) method by taking expert decision-maker opinions. The proposed decision-making model aims to guide obtaining the important causes of PM10 emission in terms of danger and focusing on these causes. Additionally, PM10 data is analyzed in the context of Covid-19 and a statistical analysis is made. One-way ANOVA is used to evaluate whether there is a significant difference in the average monthly data over the years. Games-Howell test, one of the post-hoc tests, is used for differences between groups (years). The study is important in that it provides a focus on the criteria affecting PM10 with an intuitive fuzzy perspective, along with statistical analysis.

In 2011, commercial aviation contributed approximately 3.5% of global anthropogenic climate change through the emission of greenhouse gases during flight and operational non-CO2 climate effects. Over the last few years, numerous aviation-related organisations have set goals to reduce aviation’s climate impact. These goals, however, lack alignment, are poorly or ambiguously defined, or are internally inconsistent. This increases uncertainty about what aviation should work towards, how various stakeholders can contribute, and introduces problems with respect to accountability. In order to address this issue, this paper presents a comprehensive definition of a climate neutral air transport system as an “air transport system of which the climate effects of all its greenhouse gases and non-carbon dioxide effects throughout the entire life-cycle of each element of the system is balanced”. The proposed definition spans relevant system and encompasses all life cycle phases. To achieve a climate neutral air transport system by 2050, all life-cycle greenhouse gas emissions and non-CO2 climate effects remaining after in-sector reduction should be neutralised, as should all remaining non-CO2 climate forcing from emissions prior to 2050. Clarity on governance is furthermore needed, as the goal and associated targets proposed should be adopted globally.

Inhaled particulate matter (PM) is a key player in the millions of yearly deaths worldwide related to air pollution. The oxidative potential of PM provides an indication of its ability to promote an oxidative environment. When the human lungs are exposed to PM, the reactive oxygen species (ROS) generated in such oxidative environment, if excessive, may lead to cell damage via oxidative stress. Inflammation, endoplasmic reticulum stress, airway remodeling, and many different cell death modes (apoptosis, ferroptosis, pyroptosis, among others) can be triggered by oxidative stress via complex molecular pathways, which also involve the adaptive cellular response. But ROS can also directly interact with macromolecules such as proteins and lipids, as well as nucleic acids, having been reported to induce DNA damage and epigenetic modifications, which jeopardizes homeostasis. These facts have been extensively studied in in vitro models and confirmed in in vivo models.In this review, we delve beyond conventional assessments of airborne particles, discussing their oxidative potential and the PM-induced ROS-mediated cellular damage observed in in vitro models. The close link between oxidative stress and inflammation, and the manifestation of different cell death modes is highlighted by reviewing the latest literature. The effects of ROS on the balance of DNA damage and repair, carcinogenicity and epigenetics interplay are then analyzed. Finally, we expand on the latest reports on the antioxidants’ potential to counteract the deleterious effects of ROS, and disclose future perspectives for the topic.

As the demand for fossil fuels continues to rise and their availability becomes increasingly limited, it is crucial to explore innovative approaches to optimize fuel combustion in existing systems. Among various engines, diesel engines are heavily reliant on fluid motion within the engine cylinder, which plays a critical role in fuel-air mixing. This abstract focuses on the potential of dynamic mathematical model simulation for multi-compartment rotor compressed combustion engines, aiming to revolutionize power generation by enhancing fuel burning efficiency. By leveraging advanced simulation techniques, this research seeks to unlock new insights into fluid dynamics and optimize fuel-air mixing, leading to more efficient and sustainable energy utilization. Through this exploration, we aim to pave the way for groundbreaking advancements in the field of combustion engines, ultimately contributing to a greener and more sustainable future. In the realm of internal combustion engines, the fluid dynamics within the engine cylinder greatly influence the combustion processes and heat transfer. For compression ignition (C.I) engines, both the bulk gas motion and turbulence characteristics play vital roles in engine performance. This study focuses on enhancing the combustibility of the fuel-air mixture in C.I engines by modifying the engine design to induce turbulence through squish and tumble flows. The modification involves creating multiple compartments on the rotor crown, comprising three small chambers spaced 120º apart. By implementing this design, the aim is to optimize the fuel-air mixing and improve the overall combustion efficiency. Through comprehensive analysis and experimentation, we seek to revolutionize C.I engine technology and pave the way for more efficient and environmentally-friendly power generation. In this study, the performance of a compression ignition (C.I) engine with a multiple compartment rotor has been analyzed under motoring conditions using computational fluid dynamics (CFD) simulations with FLUENT software. The obtained results have been compared with those of a base C.I engine. The analysis focused on the effects of the modified engine design on the tumble ratio and squish velocity, which are important parameters for fuel-air mixing and combustion efficiency. The results indicated a significant improvement with the modified engine, with a 35% increase in tumble ratio and a 31% increase in squish velocity compared to the base engine. These findings suggest that the modified engine design has the potential to enhance fuel-air mixing and combustion performance, leading to improved overall engine efficiency. This research presents promising insights into the optimization of C.I engine design and contributes to the development of more efficient and environmentally-friendly power generation technologies..

Over the last few decades, there is a remarkable increase in air traffic worldwide; however, despite of rapid technological development and improved airport infrastructure, there is still an increasing number of aviation accidents and fatalities. In order to meet safety demands of Air Traffic Control (ATC), Machine Learning (ML) based aircraft conflict detection techniques are focused to predict events before they come to reality. This research presents a systematic literature review (SLR) about the applications of ML techniques in safety prediction of ATC system. Initially, the existing aircraft conflict prediction models are classified into three broad categories; logical, geometric and probabilistic. A formal process of SLR is then conducted which is initiated with preprocessing and effective searching. A series of filtering called title, abstract and objective-based are then applied to extract the most relevant articles. Detailed and critical reviews of selected articles are performed to identify challenges which are segregated into dataset, model and evaluation techniques, furthermore, the optimal solutions for each are proposed. Finally the matrices to map the identified challenged with their proposed solutions are constructed. This research serves as a foundation for future research and towards integration of ML based safety prediction techniques into modern ATC system.

The paper presents the relationship between the efficiency of the process of skin onion peeling and its effect in the form of waste. The research was carried out on a pilot test stand for onion peeling. The process variables were compressed air with a pressure of (p) and valve controlling opening time of flow (t). The experiment took into account the influence of the onion diameter (d0) and its hardness (H). The obtained results were subjected to statistical analysis. Standard deviations were of the percentage loss of onion mass in the form of the skin removed of onion peeling in the process in relation to obtained aver-age values. Tukey's multiple comparison test was performed in order to identify the importance of individual process variables on the final effect of onion peeling. This was the basis for the development of a predictive model in the form of a nonlinear regression Mp=f(p,t,d0,H), which is a mathematical description of the peeling onion skin process . Finally, the response surface area of relationship between analyzed variables was determined. The results of research showed the peeling efficiency of the onion and waste of skin mass depend on the compressed air pressure. Extending the onion blowing time does not improve the process efficiency, while the hardness and size of the onion are irrelevant to the process.

Background: Fungi are ubiquitous microorganisms that are easily dispersed through the air. In healthcare environments, indoor air can favor the spread of healthcare-associated fungal infections, compromising mainly immunocompromised hospitalized individuals. Thus, this study aimed to evaluate the indoor air contamination in healthcare environments, investigating mainly the presence of potentially pathogenic yeasts. Methods: Indoor air samples were collected from twelve healthcare environments (hospital and medical clinics). After the growth, isolation, and purification of the yeast colonies, the isolates were identified by polymerase chain reaction using species-specific primers for yeasts of the genus Candida and sequencing of D1/D2 domains of the large ribosomal subunit (LSU rRNA). Results: Fourteen yeast species were identified, including emerging pathogens. Species of clinical importance such as Candida parapsilosis, Candida orthopsilosis, Candida glabrata, Rhodotorula mucilaginosa, and Trichosporon mucoides were present. C. Parapsilosis was the most prevalent species, followed by Rodothorula mucilaginosa. Conclusions: The present study shows that potentially fungal pathogens were present in air samples from healthcare environments, proving the role of indoor air in spreading infections. Thus, monitoring air quality in healthcare environments is a fundamental approach in developing infection control measures, especially those related to invasive fungal infections.

The increase and diversity of low-cost Air Quality (AQ) sensors, as well as their flexibility and low power consumption, offers us the opportunity to integrate them into a broad AQ wireless sensor networks with the aim of enabling real-time monitoring and higher spatial sampling density of pollution in all parts of the cities. Considering that the vast majority of the population lives in these cities and the increase in respiratory/allergic problems in a large part of the population, it is of great interest to offer services and applications to improve their quality of life. In the ECO4RUPA project we focus on this kind of service, proposing an inclusive and intelligent routing ecosystem carried out by using a network of low-cost AQ sensors with the support of 5G communications along with official AQ monitoring stations, assisted with artificial intelligence to improve the AQ monitoring data and by spatial interpolation techniques to enhance its spatial resolution. The goal of this service is to calculate healthy walking and/or cycling routes according to the particular citizen’s profile and needs. We provide and analyse the results of the proposed route planner under different scenarios (different time tables, congestion road traffic and routes) and different user’s profiles, with special interest on citizens with asthma and pregnant women, since both require special needs. In summary, our approach can lead to an approximately average reduction in pollution exposure of 17.82%, while experiencing an approximately average increase in distance travelled of 9.8 %.

Background and Objectives: The aim of this study is to investigate the diagnostic-therapeutic prob-lem of pelvic recurrence of rectum cancer, highlighting current surgical standards and the possi-ble role of the minimally invasive approach. This retrospective analysis of our surgical case study wishes to enter this debate while suggesting a possible line of action, based on the site of recur-rence. Materials and Methods: We examined, retrospectively, all the patients diagnosed, between 2008 and 2018, with cancer of the rectum at the "Pietro Valdoni" Department of Surgery and monitored their follow-up for 5 years. The sample consisted of 368 patients with rectal neoplasm, 136 females and 232 males, with an average age of 65.8 (ranging from 37 to 86). In 103 of the cases, the neo-plasm was located in the upper rectum (28%), in 119 cases in the middle rectum (32.3%), in 102 cases in the lower rectum (27.7%), in 31 cases (8.4%) at the level of the right/sigma junction and in 13 cases it was not possible to define the site with certainty (3.5%). Results: We examined all patients diagnosed with cancer of the rectum between 2008 and 2018 at the "Pietro Valdoni" Department of Surgery retrospectively and monitored their follow-up for 5 years. The sample consists of 368 patients with rectal neoplasm, 136 females and 232 males. Conclusions: The discussion remains open as to which approach is best at surgical level, whether laparoscopic, robotic or open-air. Our experience informs us that the most dangerous site remains on the anastomotic site.

Reinforcement learning is used for air combat problems in recent years, and the idea of curriculum learning is often used for reinforcement learning, but traditional curriculum learning suffers from the problem of plasticity loss in neural networks. Plasticity loss is the difficulty of learning new knowledge after the network has converged. To this end, we propose a motivational curriculum learning distributed proximal policy optimization (MCLDPPO) algorithm, through which agents trained can significantly outperform the predictive game tree and mainstream reinforcement learning methods. The motivational curriculum learning is to help the agent gradually improve their combat ability by observing the agent's unsatisfactory performance and providing corresponding rewards as a guide. Additionally, a complete tactical maneuver is encapsulated based on existing air combat knowledge, and through the flexible use of these maneuvers, some tactics beyond human knowledge can be realized. In addition, we designed an interruption mechanism for the agent to increase the frequency of decision-making when the agent faces an emergency. When the number of threats the agent receives changes, the current action will be interrupted to reacquire observations and make decisions again. Using the interruption mechanism can significantly improve the ability of the agent. To simulate actual air combat better, we built an air combat environment based on digital twin technology to create an air combat engine core such as missiles and radars. Based on this environment, we develop a distributed intelligent training system that employs Redis as the cache and obtains the data generated in the distributed environment through a multi-threaded TCP/IP protocol, which significantly increases the training data throughput and helps the agent accelerates convergence. The experimental results demonstrate that the agent can fully exploit the situational information to make reasonable decisions and affords air combat tactical adaption, verifying the effectiveness of the algorithmic framework proposed in this paper.

Modern commercial air travel connects disparate human populations with the global airline industry transporting up to 4.5 billion passengers annually in the years leading up to the COVID-19 pandemic. While such connections are convenient for commerce and tourism, air travel networks can also be efficient distributors of infectious diseases such as influenza, SARS-CoV-1, hemorrhagic fevers, and more recently SARS-CoV-2 and monkeypox. During the COVID-19 pandemic, public health agencies used multi-layered control strategies including pre-departure testing and vaccination requirements, masking, post-arrival testing, and quarantine to manage the risk of COVID-19 transmission associated with air travel. Simultaneously, the surveillance of aircraft wastewater emerged as a promising new data source to screen for SARS-CoV-2 infections, including newly emergent lineages, among international air travelers. Herein, we review the potential of aircraft wastewater for public health surveillance. The known contributing population and flight itinerary combined with the highly concentrated waste stream and convenient sampling during routine lavatory servicing make aircraft wastewater a strategic opportunity for unintrusive surveillance of the global fluxes of human pathogens. We estimate for the cases of fecal- or urine-shed pathogens, sampling from 3,500 and 1,250 flights per week, respectively, would be required to survey 10% of all global long-haul flight passengers. In the case of the United States, achieving 10% coverage of all international arrivals would require sampling from 925 and 322 flights per week, respectively. Aircraft wastewater surveillance could also be integrated with network and infectious disease models to better inform traditional public health control measures during emerging epidemics. Given the tremendous potential for public good and the massive economic costs of epidemics, governments should consider international collaboration to create a global aircraft wastewater surveillance system.

Substantial reductions of the human and economic activities like road traffic for several months in 2020 were one of the consequences of the Coronavirus disease. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown over 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5) as well as on land surface temperature (LST), and the surface urban heat island intensity (SUHII), using satellite, modelled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change of the variables under study. In general, the results indicate a significant decrease in NO2 concentrations in most of the studied cities compared to the reference period 2015-2019. However, reductions could not be attributed to mobility changes like less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown mainly influenced by the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar as the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. Therefore, single city case studies may be misleading.

Keywords:

Accurate estimation of vehicle emissions is essential and can be helpful in the decision-making process. Thanks to calculation methods, it is possible to accurately estimate the emissions that result from driving a car and to determine their impact on, for example, the health of pedestrians who are on the pavement near an arterial road. Recent years have seen an increase in the use and importance of emission models, as well as vehicle traffic simulation models. Increasingly, emission models are being combined with traffic simulation models, as it is not practical to actually measure the on-road emissions of an entire fleet of vehicles over a given stretch of road. This paper provides an overview of the selected work on the topic of emission modelling and vehicle traffic simulation models. The models are distinguished according to their respective scales of accuracy, i.e., micro, meso, and macro. Selected work combining emission and traffic simulation models is also presented, as well as development trends in the field. In particular, the paper also highlights the fact of proper calibration of vehicle traffic simulation models in order to obtain the most reliable vehicle emissions results from computational models. The review of the works carried out may be helpful for future projects concerning the use of simulation tools for transport and environmental decision-makers in the area of arterial roads.

The research aims to improve some of the physical and hydro-physical properties of some Vertisols in the southern region (part of the eastern Houran Plateau) in Sweda Governorate at the south of Syria. Using different quantities of volcanic ash, soil samples were collected from the Al-Thahallah village from a depth of (0-30) cm, The experiment was designed according to the complete random design with one factor that represents the ash quantity (1.25, 2.5, 5) %, with three replicates for each treatment in addition to the control treatment a0. The experiment was carried out within the plastic pots during agricultural season 2018/2019, in which the wheat of the Sham variety 3 were cultivated as a cover plant. The results showed that the addition of volcanic ash at the quantity of 5% led to a significant increase in the infiltration rate by (328.60) %,%, where the filtration rate increased from 0.42 cm/hr -1 to 1.80 cm.h-1, as well as for each of the air porosity by (89) % and the volume of infiltrate water by (40) %, compared with the control. The above-mentioned addition also resulted in a decrease in both dry bulk density, total soil porosity and volumetric swelling coefficient by (18.60, 5.80, 314) % Respectively, compared to the control. The addition also contributed to the reduce in the weighted moisture content when saturation and the field capacity, at the level of significance of 5%. The research recommends adding volcanic ash to the soil at a quantity of 5%, and adding enhancements with volcanic ash at various levels such as organic waste.

Several studies have identified a relationship between air pollution and depression, particularly in relation to fine particulate matter (PM2.5) exposure. However, the strength of this association appears to be moderated by variables such as age, gender, genetic vulnerability, physical activity and climatic conditions, and has not been assessed at a cross-national level to date. The current study examines the association between the prevalence of depression in each country, based on the most recent Global Burden of Disease Study data, and the average national level of PM2.5 based on the World Health Organization’s database. The observed associations were adjusted for age, gender, level of physical activity, income, education, population density, climate, and type of depression. It was observed that there was a modest but significant positive correlation between PM2.5 level and the prevalence of depression even after adjusting for the above confounders. This association was more marked above a certain threshold and applied chiefly to major depressive episodes. These findings are of significant public health importance in terms of preventive strategies aimed at reducing the population-level burden of depression.

Ion Transport Membrane (ITM) is a well-developed technology for producing O₂ by separating air in its membrane. To decrease energy loss in air separation unit and to increase the overall efficiency of a power generation unit ITM is added with the gasification unit in this model. Ceramic materials are generally used to make ion transport membrane that produces oxygen by conducting oxygen ions at specified temperature. Potential advantages can be gained by integrating ITM technology with power generation units as 99% pure oxygen is produced from ITM. A salient comparison between ITM air separator combined with IGCC and cryogenic air separator combined with IGCC is done in this paper where the total power generation cycle remains same for both cases excluding the air separation units (ITM and cryogenic). Using ITM air separator is more beneficial compared to cryogenic air separation as ITM technology helps to improve IGCC overall efficiency and also reduces plant auxiliaries than that of power generation systems integrated with cryogenic.

Chronic obstructive pulmonary disease (COPD) is strongly associated with tobacco smoking and it is the increasing cause of morbidity and mortality worldwide. The prevalence of COPD among never smokers varies widely across regions, areas, and nations. COPD in smokers has been extensively explored worldwide, however, COPD in non-smokers is under-explored and there is limited data available on non-smoking COPD. We determined the role of environmental pollution and biomass fuel exposure in COPD patients who were non-smokers. We evaluated the clinical profile of non-smokers with COPD in a retrospective observational study. 180 non-smoker COPD patients were selected from the year 2016-to 2018. We found that many patients with COPD are non-smokers and the incidence is higher among the rural population, suggesting that non-smoking COPD is evolving rapidly due to biomass smoke and other environmental pollutant exposures.

Road vehicles are a large contributor to Nitrogen Oxides (NOx) pollution. The routine road-side monitoring stations, however, may underrepresent the severity of personal exposure in urban areas, because long-term average readings cannot capture the effects of momentary, high peaks of air pollution. While numerical modelling tools historically have been used to propose an improved distribution of monitoring stations, ultra-high resolution Computational Fluid Dynamics models can further assist the relevant stakeholders in understanding the important details of pollutant dispersion and exposure at local level. This study deploys a 10 cm-resolution CFD model to evaluate actual high peaks of personal exposure to NOx from traffic, by tracking the gases emitted from the tailpipe of moving vehicles being dispersed towards the roadside. The investigation shows that a set of four Euro 5-rated diesel vehicles travelling at constant speed may generate momentary road-side concentrations of NOx as high as 1.25 mg/m3, with 25% expected increase for doubling the number of vehicles and approximately 50% reduction when considering Euro 6-rated vehicles. The paper demonstrates how the numerical tool can be used to identify the impact of measures to reduce personal exposure, such as protective urban furniture, as traffic patterns and environmental conditions change.

Aircraft emissions represent a relevant amount of human induced CO2. Globally, up to 2.5 per cent of such emissions stem from the aviation industry. In order to investigate the effects within the atmosphere, realistic flight profiles are necessary to provide quantitatively tangible values of emissions. The flight profiles and the according fuel consumption can be calculated by using waypoints from flight plans and Base of Aircraft Data (BADA). This paper presents an approach to refine the fuel consumption by integrating the passenger load into the calculation. Since effects of emissions have to be assessed on a greater scale, such as on the European air traffic network, the presented approach provides cost functions for CO2 emissions for different aircraft types and load factors. The cost functions were derived by means of regression analyses of BADA based calculated flight profiles with a step size of one second. The calculations are based on real historic traffic scenarios of several days. The derived aircraft specific fuel burn coefficients enable a simple and efficient integration of CO2 estimations depending on the flight distance, load factor and aircraft type. This can be applied to large traffic scenarios to also study different set-ups such as travel restrictions, other disruptions or an alteration in the traffic system as a whole. In order to enable the assessment of further aspects of such changes to the European air traffic system at large and to foster reproducibility and comparability of related studies, we provide further general-purpose cost estimation functions for several important key characteristics. Besides fuel consumption, we develop cost estimations for air navigation fees and maintenance for conventional aircraft. Those functions are also provided for the design concept of a short-range all-electric aircraft. This propeller aircraft features game-changing technologies such as active laminar flow control, active load alleviation and advanced materials and structure concepts. The approaches discussed in this paper will focus on the generic aspects of aircraft related costs, which can be derived from general available data. For the sake of reproducibility, the results will be made publicly available.

Research have been conducted in many countries around the world to assess air quality during COVID-19 pandemic, especially during lockdown period, some of these studies found an increase or decrease in some pollutants. This paper investigates the impact of COVID-19 on seven air pollutants (i.e., PM_2.5, PM₁₀, NO₂, O₃, SO₂, H₂S, CO) from the period January 2020 to December 2020 in the State of Kuwait. Kuwait is a desert country located in the north-eastern part of the Arabian Peninsula, and the northeast of the Arabian Gulf (Persian as it is sometimes called). Several analytical methods were conducted, such as spatial analysis (spatial interpolation) to study the distribution of the studied variables. The data was also statistically analysed (time series analysis - Kernel density) to study the temporal changes. The analysis also included applying air quality index to the data. We found that concentrations for the pollutants decreased during the pandemic due to the decrease of anthropogenic sources including such as traffic and petroleum activities, but the concentration for PM_2.5 increased, mostly because of the transported dust coming with the northwest winds prevailing in Kuwait from the Arabian deserts and Iraq.

The vehicular technology has integrated many features in the system, which enhances the safety and comfort of the user. Among these features, heating, ventilation, and air conditioning (HVAC) is the only feature that maintains the set cabin air temperature (CAT). The user’s command drives the set CAT, and the thermostat provides feedback to the HVAC to maintain the set CAT. The CAT is increased by extracting the heat from the engine surface produced by the fuel combustion, whereas the CAT is reduced by the known processes of the air conditioning system (ACS). Therefore, the CAT driven by the user’s command may not be optimal, and estimating the optimal CAT is still unsolved. In this work, the user was allowed to input a range for CAT instead of a single value. Optimal HVAC criteria were defined, and the CAT was estimated by performing iterative analysis in the user-selected range satisfying the criteria. The HVAC criteria were defined based on two measurable parameters: air conditioning refrigerant fluid pressure (ACRFP) and engine surface temperature (EST) empirically defined as the vector CATOP. In this article, a NARX DL model by mapping the vehicle-level vectors (VLV) to predict the CATOP in real-time using field data obtained from a 2020 Cadillac CT5 test vehicle. Utilising the DL model, CATOP for future time steps were predicted by varying the CAT in the definite range and applying HVAC criteria. Thus, an optimal set CAT was estimated, corresponding to the optimal CATOP defined by the HVAC criteria. We performed the validation of the DL model for multiple datasets using traditional statistical techniques, namely, signal-to-noise ratio (SNR) values, first-order derivatives (FOD), and root-mean-square error (RMSE).

Background: this RCT assesses the 18 months clinical outcomes after regenerative therapy of periimplantitis lesions using either an electrolytic method (EC) to remove biofilms or a combination of powder spray and electrolytic method (PEC). Materials and Methods: Twenty-four patients (24 implants) suffering from periimplantitis were randomly treated by EC or PEC followed by augmentation and submerged healing. Probing pocket depth (PPD), Bleeding on Probing (BoP), suppuration and standardized radiographs were assessed before surgery (T0), 6 months after augmentation (T1), 6 (T2) and 12 (T3) months after replacement of the restoration. Results: Mean of PPD changed from 5.8 ± 1.6 mm (T0) to 3.1 ± 1.4 mm (T3). While BoP and suppuration at T0 was 100 % BoP decreased at T2 to 36.8 % and at T3 to 35.3 %. Suppuration could be found 10.6% at T2 and 11.8% at T3. Radiologic bone level measured from the implant shoulder to the first visible bone to implant contact was 4.9 ± 1.9 mm at me-sial and 4.4 ± 2.2 mm at distal sites (T0) and 1.7 ± 1.7 mm and 1.5 ± 17 mm at T3. Conclusions: Significant radiographic bone fill and improvement of clinical parameters were demonstrated 18 months after therapy.

TRPOMI instrument aboard Sentinel-5P is a relatively new, high-resolution source of information about atmosphere composition. One of the primary atmospheric trace gases that we can observe through it is nitrogen dioxide. By now, we were using the chemical weather model (GEM-AQ) as a mean for estimating nitrogen dioxide concentration on a regional scale. Although well established in atmospheric science, the GEM-AQ simulations were always based on emission data, which in the case of the energy sector were reported by stack owners. In this paper, we attempted to compare the TROPOMI and GEM-AQ derived VCDs over Poland with a particular focus on large point emitters. We also checked how cloudy conditions influence TROPOMI results. Finally, we tried to link the NO2 column number densities with surface concentration using boundary layer height as an additional explanatory variable

The concept of this prototype is to create a cold air film layer, in indoor side of the window. The function of this extra cold air layer is to increase the amount of window resistance and decrease its U-Value. It provide air film layer by using the same concept of desert cooler or wind catcher. They both bring the hot air from outside then let it go throw straw miost with cold water. After hot air move through straw, it would become cold, thus increase the window resistance and decrease the haet gian, therefore, decrease the cooling load. So, this window model works by heating the air in air room by sun radiation, then after a while, air pressure will rise and its volume will increase then it will impulse to wet hay, and become cold. Then there is fins to guide air flow to its correct direction, thus inner side of window will become cold, not like other type of window which when temperature rise, the inner side of window become hot. So, this window prevents heat transition and creare regenereted trubouland air flim in the inner side of the window. Using calculation to find air film characteristics and WINDOW7.7 software to calculate heat gain through window, shows that it is expected from this prototype to reduce heat gain by 6.85 % for double glazed clear window.

Today, air quality is one of the global concerns that governments are facing. One of the main air pollutants is the particulate matter (PM) that affects human health. This article presents the modeling of a purification system by means of negative air ions (NAIs) for air pollutant removal, using computational intelligence methods. The system uses a high voltage booster output to ionize air molecules from stainless steel electrodes; its particle-capturing efficiency reaches up to 97%. With two devices (5 x 2 x 2.5 cm), 2 trillion negative ions are produced per second, and the particulate matter (PM 2.5) can be reduced from 999 to 0 mg / m3 in a period of approximately 5 to 7 minutes (in a 40 x 40 x 40 cm acrylic chamber). This negative ion generator is a viable and sustainable alternative to reduce polluting emissions, with beneficial effects on human health.

Understanding the relationships between land cover/urban structure patterns and air pollutants is key to sustainable urban planning and development. In this study, we employ a mobile monitoring method to collect PM_2.5 and BC data in the city of Philadelphia, PA during the summer of 2019 and apply the Structure of Urban Landscapes (STURLA) methodology to examine relationships between urban structure and atmospheric pollution. We find that, while PM_2.5 and BC vary by STURLA class, many of the differences in pollutant concentrations between classes are not significant. However, we also find that the proportions in which STURLA components are present throughout the urban landscape can be used to predict urban air pollution. Among frequently sampled STURLA classes, gpl hosted the highest PM_2.5 concentrations on average (16.60 _± 4.29 µg/m³), while tgbwp hosted the highest BC concentrations (2.31 _± 1.94 µg/m³). Furthermore, STURLA combined with machine learning modeling was able to correlate PM_2.5 (R²= 0.68, RMSE 2.82 µg/m³) and BC (R² = 0.64, RMSE 0.75 µg/m³) concentrations with the urban landscape and spatially interpolate concentrations where sampling did not take place. These results demonstrate the efficacy of the STURLA methodology in modeling relationships between air pollution and land cover/urban structure patterns.

Air pollution contributes to a critical environmental problem in various towns and cities. With the emergence of the smart cities concept, appropriate methods to curb associated with exposure to pollutants must have been a portion of appropriate urban development policy. This study presents a technologically driven air quality solution in smart cities to advertise energy-efficient and cleaner sequestration in these areas. It aims to address the issue of how to integrate the data-based strategies and artificial intelligence into efficient public sector pollution management in smart cities as a core part of the smart city definition. Exploratory research has been used in 152 smart cities, and environmental experts contributed to this study. It further addresses the technical criteria for implementing such a framework that the public administration uses to prepare the renovation of public buildings, minimize energy use and costs, and link these smart police stations to monitor air pollution as a part of integrated cities. Such a digital transition in resource management will increase public governance's energy performance, a higher standard of operation, and a healthier environment.

: During the period of COVID-19, the Chinese government implemented a series of actions to prevent the spread of the virus. It is noticed that these preventive actions have generated positive effects on air pollution in Wuhan and Beijing. And, due to the differences in city functions, geographic locations, meteorological conditions, and preventive action details between the two cities, noticeable difference is observed on how they reduced air pollution. This unfortunate incident has become a social sample for studying the industrial and livelihood activities impact on air pollution, otherwise would be highly impossible. This paper starts from observing data from NASA's real-time fine particulate matter (PM2.5) and NO2, and comparing the air pollution in this special time domain with previous years. It is discovered that both PM2.5 and NO2 have been reduced in Wuhan, while only NO2 has significant reduction in Beijing, during the COVID-19 responses. This suggests that the human activity suppression by the COVID-19 control yields different effects on different pollutants and in different cities. Possible reasons for such effects are analysed by considering the public health control levels as well as the pollutant migration, industrial activities, and the weather conditions.

As air traffic demand grows, robust, data-driven anomaly detection methods are required to ensure that aviation systems become safer and more efficient. The terminal airspace is identified as the most critical airspace for both individual flight-level and system-level safety and efficiency. As such, developing data-driven anomaly detection methods to analyze terminal airspace operations is paramount. With the expansion of ADS-B technology, open-source flight tracking data has become more readily available to enable larger-scale analyses of aircraft operations. This paper makes a distinction between spatial metrics in ADS-B trajectory data and energy metrics derived from ADS-B trajectory data. Motivated by the limited number of approaches that simultaneously consider both spatial and energy metrics, this paper introduces the concepts of spatial anomalies and energy anomalies. In particular, it proposes a novel, unified framework for detection of spatial and energy anomalies in ADS-B trajectory data (and associated derived metrics). The framework consists of three main parts - a data processing procedure, a spatial anomaly detection method, and an energy anomaly detection method. The framework is demonstrated utilizing four months of ADS-B trajectory data associated with arrivals at San Francisco International Airport, and the relationship between the spatial and energy anomalies in this terminal airspace is explored. The results that stem from the implementation of this framework indicate that if an aircraft is spatially not conforming to an identified set of air traffic flows representing standard spatial operations, then this aircraft is more likely to experience non-conformance to standard operations in its energy metrics. Aviation operators, such as air traffic controllers, may benefit from this observation, as it may factor into decision-making in instances where there is the potential to instruct an aircraft to spatially deviate from standard operations. Additionally, this research revealed underlying differences between trajectories that are spatially nominal yet energy-anomalous and those trajectories that are spatially anomalous and energy-anomalous. Focusing solely on energy anomaly detection does not provide insight into potential spatial-related decisions that may have been made to result in off-nominal energy behavior.

Air conditioning system of electric vehicles has new change as the internal combustion engine is being replaced with electrified AC motor. With large amount of batteries installed at the bottom of frame, the conventional compressor which is belt-driven can be removed and another AC motor can play the role for air conditioning in electric vehicles. From this change, the system efficiency would be improved since it is possible to control the electrified compressor independently from traction system in contrast with the belt-driven compressor. As a result, by applying the electrified compressor for air conditioning system, the whole system can achieve better efficiency and longer driving distance, which is most important in electric vehicles. In this paper, 3-phase interior permanent magnet synchronous motor (IPMSM) was designed using lumped-parameter model and finite element method.

Air pollution has become the world’s single biggest environmental health risk of the past decade, causing about 7 million yearly deaths worldwide. One of the dominant air pollutants is fine particulate matter (PM2.5), a product of combustion. Exposure to PM2.5 has been associated with decreased lung function, impaired immunity, and exacerbations of lung disease. Accumulating evidence suggests that many of the adverse health effects of PM2.5 exposure are associated with lung inflammation and oxidative stress. While the physical structure and surface chemistry of PM2.5 are surrogate measures of particle oxidative potential, little is known about their contributions to negative health effects. In this study, we used functionalized carbon black particles as surrogates for atmospherically aged combustion formed soot to assess the effects of PM2.5 surface chemistry in lung cells. We exposed the BEAS-2B lung epithelial cell line to different soot at a range of concentrations, and assessed cell viability, inflammation, and oxidative stress. Our results indicate that exposure to soot with varying particle surface composition results in differential cell viability rates, expression of pro-inflammatory and oxidative stress genes, and protein carbonylation. We conclude that particle surface chemistry, specifically oxygen content, in soot modulates lung cell inflammatory and oxidative stress responses.

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

A new coronavirus (SARS-CoV-2) have determined a pneumonia outbreak in China (Wuhan and Hubei) on December 2019. While pharmaceutical and non-pharmaceutical intervention strategies are strengthened worldwide, the scientific community has been studying the risk factors associated with SARS-Cov-2, to enrich epidemiological information. For a long time, before the industrialized era, air pollution has been a real and big health concern and it is today a very serious environmental risk for many diseases and anticipated deaths in the world. It has long been known that air pollutants increasing the invasiveness of pathogens for humans by acting as a carrier and making people more sensitive to pathogens through a negative influence on the immune system. Based on scientific evidences, the hypothesis that air pollution, resulting from a combination of factors such as meteorological data, level of industrialization as well as regional topography, can acts both as an infection carrier as a harmful factor of the health outcomes of COVID-19 disease has been raised recently. This hypothesis is turning in scientific evidence, thanks to the numerous studies that have been launched all over the world. With this review, we want to provide a first unique view of all the first epidemiological studies relating the association between air pollution and SARS-CoV-2. Major findings are consistent, highlighting the important contribution of air pollution on the COVID-19 spread and with a less extent also PM₁₀.

This review chronicles the indirect transmission method which seems to be overlooked by most people and makes attempts to clearly document the various transmission ways with a hope that such information may strengthen the knowledge base of researchers towards methods of eradicating the pandemic. Current knowledge of transmission and exposure of SARS-CoV-2 has been explained. Various researchers have put forward different ways of exposure and transmission. Literature does not reveal whether the indirect transmission route is the dominant one. However total lockdown could be a veritable means to reduce both direct and indirect transmission routes. In many countries where the indirect transmission has been reduced, the scourge of the virus is less. The work creates awareness on the need to watch out for those routes of transmissions that may not be popular and suggested key knowledge gaps that needs to filled.

In the present paper, a measure of the influence of irregularities of the underlying surface (for instance, the real terrain profile) on the dynamics of air flow is estimated. It is shown that these irregularities significantly perturbing the pressure, density, velocity and temperature of air flow; for perturbed pressure, density, velocity and temperature of air flow the closed formulas in the Fourier integral form are obtained. In addition, in the present paper, it is proved that due to these perturbations, at a certain altitude of the atmosphere some surface of the "sturdy wall" form appears, on which the vertical and horizontal components of the air flow velocity become infinitesimal and infinitely large, respectively.

This retrospective study evaluates the effect of a telemedicine program developed in the central Catalan region in lowering the environmental footprint by reducing the emission of atmospheric pollutants thanks to a reduction in the number of hospital visits involving journeys by road. Between January 2018 and June 2019 a total of 12,322 referrals were made to telemedicine services in the primary care centers, avoiding a total of 9,034 face-to-face visits. In total, the distance saved was 192,682 km, with a total travel time savings of 3,779 hours and a total fuel reduction of 11,754 liters with an associated cost of €15,664. This represents an average reduction of 3,248.3 g of carbon dioxide, 4.05 g of carbon monoxide, 4.86 g of nitric oxide and 3.2 g of sulphur dioxide. This study confirms that telemedicine reduces the environmental impact of atmospheric pollutants emitted by vehicles, reducing the number of journeys made for face-to-face visits and can contribute to environmental sustainability.

Microplastics (of size < 5mm) pollution in our environment is of current concern by researchers, public media and non-governmental organizations. Implications by their presence in aquatic and soil ecosystems have been well studied and documented, but less attention has been paid on airborne microplastics (MPs). Studies concerning airborne microplastics started from 2016 and only a few (n=7) have been published till date. Although, studies may increase in the following years, since air is very important for human survival. Microplastics have been observed in atmospheric fallouts in indoor and outdoor environments using a sampling or vacuum pump, rain sampler and/or particulate fallout collector. Identification and quantification have been carried out by visual, spectroscopic and spectrometric techniques. Factors such as meterological, climatic and anthropogenic influence the distribution and movement of airborne MP. Human exposure may be through inhalation or dermal route with their potential biopersistence and translocation. Ingestion may cause localized inflammation and cancer due to responses by the immune cells, especially in individuals with compromised metabolism and poor clearance mechanisms. Ecological risks involve possible contamination of the ecosystem through a dynamic relationship of MPs in soil, water and air forming a MP contamination cycle. The present review aimed at providing a comprehensive overview of current knowledge or information regarding microplastics in air, identifies gap in knowledge and give suggestions for future research.

The purpose of this study is to assess the concentration-response relations between conjunctivitis and exposure to ambient ozone. This retrospective study includes emergency department (ED) visits for conjunctivitis in Edmonton, Canada, for the period April 1992–March 2002. Daily average levels of ozone (range: 1.2–50.9, ppb), of temperature, and of relative humidity were estimated and used for the period of the study. For each of the considered exposure lags, (from 0 to 9 days), six different models were fitted to estimate the concentration-response function. The goodness of fit was assessed using the Akaike information criterion. During the period of the study, 17,211 ED visits for conjunctivitis were recorded and used. For all subjects together, a positive statistically significant association was obtained for the exposure lagged by 5 days. For female subjects, lags 1, 3, and 9 had positive statistically significant associations (lag 2 had negative associations). For male subjects, only lag 5 had a positive statistically significant association. The estimated non-linear concentration-response functions for the considered groups (all, males, females) and lags, revealed the associations along the exposure levels. The fitted shapes are described by algebraic functions and may have various forms. The estimated functions are useful to determine the risk associated with exposure to ground-level ozone.

Air quality has been a major concern throughout the world, Nigeria inclusive. The monitoring of air quality involves indoor and outdoor air quality. In this study, our concern was on indoor air quality. The aim of this study was to assess the air quality of residential homes (17), classrooms (3), hospitals (2), offices (5), Shops (2), and laboratories (5) in Akure, Nigeria in terms of formaldehyde (HCHO), total volatile organic compound (TVOC), Particulate matter (PM_1.0; PM_2.5, and PM₁₀). A Multifunction Air Detector was used for the assessment using the manufacturers’ procedures and the locations were identified using a Mini GPS. The results revealed as follows: HCHO (0.001-0.030 mg/m³), TVOC (0.003-362 mg/m³), PM_1.0 (004-014 µg/m³), PM_2.5 (006-020 µg/m³), and PM₁₀ (006-022 µg/m³). The results obtained were below the 24 h pollution recommended standards (0.1 mg/m³- HCHO; TVOC; 10-20 μ/m³ PM) of EPA and WHO. Statistically, there were correlations within the pollutants and weather. The Indoor air quality (IAQ) depicted the areas as ‘good,’ and toxicity potential (TP) were below unity. Although the locations looked safe, it is recommended that constant monitoring of the indoors should be ensured and proper ventilation should be provided.

Rapid urbanization, increasing population and increased industrialization to cater to demands of the growing population has imposed upon us a huge environmental cost. The significantly deteriorated air quality across the globe is associated with a direct and indirect impact on public health. While associated disorders such as chronic obstructive pulmonary diseases, heart failures are well documented, less is known about the biological basis of the process. We hypothesize that the worsening air quality may likely impact common systemic inflammatory processes, thus driving communicable and non-communicable diseases alike.Receptor mediated entry of particulate matter (PM2.5) results in activation of signaling cascades which culminate in production of inflammatory chemokine and cytokine responses, traversing through the blood mediating impacting not only on other organs but also dysbiosis of microflora. For the purpose of the review we choose tuberculosis (TB) as a model for communicable infectious disease and type 2 diabetes mellitus (T2DM) as a marker for non-communicable disorder. The increasing prevalence of these co-morbidities and the burdening of public health systems justifies this example. However the hypothesis may be applicable to other inflammation driven disorders also.