Fogs: Physical Basis, Characteristic Properties, and Impacts on the Environment and Human Health

Challenges in moving towards fog's contribution to spatial patterns of atmospheric deposition fluxes on a national scale

Fog is an important environmental phenomenon affecting, among other things, geochemical cycles via atmospheric deposition pathways. It is generally accepted that fog contributes substantially to atmospheric deposition fluxes especially in mountain forests. Nevertheless, due to intrinsic constraints, fog pathway has thus far been neglected in the quantification of atmospheric deposition and fog pathway has not been accounted for in nation-wide spatial patterns of atmospheric deposition of air pollutants. In this review we explore the causes as to why it is so complex to create a spatial pattern of fog contribution to atmospheric ion deposition fluxes on a national scale. Physical and chemical principles of fog formation are presented and factors influencing the abrupt temporal and spatial changes in both fog occurrence and fog chemistry are elucidated. The focus is on both constituents essential for fog deposition flux quantification, i.e. (i) hydrological input on fog water and (ii) chemistry of fog water.

Time-gated imaging through dense fog via physics-driven Swin transformer

Imaging through the fog is valuable for many areas, such as autonomous driving and cosmic exploration. However, due to the influence of strong backscattering and diffuse reflection generated by the dense fog on the temporal-spatial correlations of photons returning from the target object, the reconstruction quality of most existing methods is significantly reduced under dense fog conditions. In this study, we describe the optical scatter imaging process and propose a physics-driven Swin Transformer method utilizing Time-of-Flight (ToF) and Deep Learning principles to mitigate scattering effects and reconstruct targets in conditions of heterogeneous dense fog. The results suggest that, despite the exponential decrease in the number of ballistic photons as the optical thickness of fog increases, the Physics-Driven Swin Transformer method demonstrates satisfactory performance in imaging targets obscured by dense fog. Importantly, this article highlights that even in dense fog imaging experiments with optical thickness reaching up to 3.0, which exceeds previous studies, commonly utilized quantitative evaluation metrics like PSNR and SSIM indicate that our method is cutting-edge in imaging through dense fog.

A review of the methods of harvesting atmospheric moisture

Moisture is an inherent constituent of air present across the world. The relative humidity varies with the change in temperature and climate specific to a region. In some regions of the world, there may be a relatively inadequate number of grains of moisture in the air in comparison with other regions. These factors widen the scope for the deployment of decentralized technology to capture water. The effectiveness in capturing moisture gains significance in these regions. Among the numerous forms of moisture, fog and dew are studied in depth. Over time, flora and fauna in different ecosystems have adapted to capture moisture as well as repel excesses of it according to their requirements. Therefore, bio-inspired studies and tailored engineering strategies have been incorporated in this review. Since efficient technologies are required at moisture-scarce locations, active moisture harvesting has also been studied. The use of innovative materials along with different energy sources to capture water is elaborated. The effects of climate change and environmental contamination on harvested moisture are therefore assessed. Community participation and economical use of harvested fog or dew influence the sustainability of moisture-capture projects. Therefore, this article also provides an insight into the services of decentralized water-harvesting projects run by diverse organizations and researchers across the globe.

Optimal Fast Integral Decontamination of Bacillus thuringiensis Aerosols and Fast Disinfection of Contaminated Surfaces

Aerosolized anthrax (Bacillus anthracis) spores are of extreme health concern and can remain airborne for hours and contaminate all kinds of surfaces, constituting reservoirs from which resuspension is easily produced. The assessment of decontamination techniques must therefore consider both air and surfaces. In the present study, several kinds of disinfecting fogs were experimentally tested against Bacillus thuringiensis spores, which served as a surrogate for Bacillus anthracis, both as aerosols released into the air and spread on porous and non-porous surfaces with different positions and orientations. This technology removed Bacillus thuringiensis spores from the air in 20 min with just a 1 min application of fog. The dynamics and characteristics of the fog, related to aerosol and surface interactions, proved to be critical for optimal performance and decontamination. An optimal configuration could provide effective disinfection even on indirectly reached surfaces. In all cases, 8% hydrogen peroxide (H₂O₂) provided a higher disinfection rate than 2% glutaraldehyde.

Local fresh- and sea-water effects on fog occurrence

Fog is an important atmospheric phenomenon highly relevant to ecosystems and/or the environment. Two essential prerequisites of fog formation are the presence of fog condensation nuclei and water in the atmosphere. The aim of our study was to examine in detail how fog occurrence is influenced by water areas in the immediate vicinity of the fog observation site. We have used as input data long-term observations on fog occurrence measured at 56 professional meteorological stations in Romania in 1981-2017 and GIS-derived information on water areas and on two topographical indices, TWI and TPI, in the neighbourhood of these stations. We formulated three alternative models of different complexity based on a semiparametric generalised additive logistic model for the probability of fog occurrence with potentially nonlinear, smooth effects modelled via penalised splines. A radius of 9 km appeared to be the most influential when considering the water area in a circle around the fog observation station. Based on our results, we concluded that (i) the water area in the vicinity of the station is a factor influencing fog occurrence, (ii) the water's effect differs according to water type (freshwater or seawater proximity), and (iii) GIS-derived topographical indices are informative for the explanation of fog occurrence and their inclusion enhanced the fit of the models substantially. Our findings, based on a reliable long-term data set of fog occurrence and recent GIS-derived data, explored by a relevant statistical approach will enhance further considerations related to fog formation and its environmental consequences.

Assessing Health Impacts of Winter Smog in Lahore for Exposed Occupational Groups

The goal of this research was to investigate the health effects of winter pollution on various occupations in Lahore and its neighboring peri-urban areas. A questionnaire survey, key informants, and focused group discussions were employed to collect data, which included demographic, socioeconomic, and health-related information. Descriptive statistics and the multivariate logistic regression model (MLRM) were used to examine the effects of pollution on exposed occupational groups who experienced symptoms such as coughing, shortness of breath, and eye discomfort. According to data from interviews, MLRM revealed that individuals working in various occupations with outdoor and indoor environments are equally affected by winter smog, but being middle-aged (odds ratio OR = 5.73), having a history of a respiratory ailment (OR = 4.06), and location (OR = 2.26) all play important roles in determining health. However, less educated people, elders, and people who already live in polluted areas are more likely to develop respiratory health symptoms. During the smog incident, it was determined that diverse health and socioeconomic factors exacerbate an individual’s negative health impact more than others.

Data Link with a High-Power Pulsed Quantum Cascade Laser Operating at the Wavelength of 4.5 µm

This article is a short study of the application of high-power quantum cascade lasers and photodetectors in medium-infrared optical wireless communications (OWC). The link range is mainly determined by the transmitted beam parameters and the performance of the light sensor. The light power and the photodetector noise directly determine the signal-to-noise power ratio. This ratio could be maximized in the case of minimizing the radiation losses caused by atmospheric attenuation. It can be obtained by applying both radiation sources and sensors operated in the medium infrared range decreasing the effects of absorption, scattering or scintillation, beam spreading, and beam wandering. The development of a new class of laser sources based on quantum cascade structures becomes a prospective alternative. Regarding the literature, there are descriptions of some preliminary research applying these lasers in data transmission. To provide a high data transfer rate, continuous wave (cw) lasers are commonly used. However, they are characterized by low power (a few tens of mWatts) limiting their link range. Also, only a few high-power pulsed lasers (a few hundreds of mWatts) were tested. Due to their limited pulse duty cycle, the obtained modulation bandwidth was lower than 1 MHz. The main goal of this study is to experimentally determine the capabilities of the currently developed state-of-the-art high-power pulsed quantum cascade (QC) lasers and photodetectors in OWC systems. Finally, the data link range using optical pulses of a QC laser of ~2 W, operated at the wavelength of ~4.5 µm, is discussed.

Cytotoxicity induced by fine particulate matter (PM2.5) via mitochondria-mediated apoptosis pathway in rat alveolar macrophages

Although positive associations exist between ambient particulate matter (PM_2.5; diameter ≤ 2.5 μm) and the morbidity and mortality rates for respiratory diseases, the biological mechanisms of the reported health effects are unclear. Considering that alveolar macrophages (AM) are the main cells responsible for phagocytic clearance of xenobiotic particles that reach the airspaces of the lungs, the purpose of this study was to investigate whether PM_2.5 induced AM apoptosis, and investigate its possible mechanisms. Freshly isolated AM from Wistar rats were treated with extracted PM_2.5 at concentrations of 33, 100, or 300 μg/mL for 4 h; thereafter, the cytotoxic effects were evaluated. The results demonstrated that PM_2.5 induced cytotoxicity by decreasing cell viability and increasing lactate dehydrogenase (LDH) levels in AMs. The levels of reactive oxygen species (ROS) and intracellular calcium cations (Ca²⁺) markedly increased in higher PM_2.5 concentration groups. Additionally, the apoptotic ratio increased, and the apoptosis-related proteins BCL2-associated X (Bax), caspase-3, and caspase-9 were upregulated, whereas B cell lymphoma-2 (Bcl-2) protein levels were downregulated following PM_2.5 exposure. Cumulative findings showed that PM_2.5 induced apoptosis in AMs through a mitochondrial-mediated pathway, which indicated that PM_2.5 plays a significant role in lung injury diseases.

Fog Forecast Using WRF Model Output for Solar Energy Applications

The occurrence of fog often causes errors in the prediction of the incident solar radiation and the power produced by photovoltaic cells. An accurate fog forecast would benefit solar energy producers and grid operators, who could take coordinated actions to reduce the impact of discontinuity, the main drawback of renewable energy sources. Considering that information on discontinuity is crucial to optimize power production estimation and plant management efficiency, in this work, a fog forecast method based on the output of the Weather Research and Forecasting (WRF) numerical model is presented. The areal extension and temporal duration of a fog event are not easy to predict. In fact, there are many physical processes and boundary conditions that cause fog development, such as the synoptic situation, air stability, wind speed, season, aerosol load, orographic influence, humidity and temperature. These make fog formation a complex and rather localized event. Thus, the results of a fog forecast method based on the output variables of the high spatial resolution WRF model strongly depend on the specific site under investigation. In this work, the thresholds are site-specifically designed so that the implemented method can be generalized to other sites after a preliminary meteorological and climatological study. The proposed method is able to predict fog in the 6–30 h interval after the model run start time; it has been evaluated against METeorological Aerodrome Report data relative to seven selected sites, obtaining an average accuracy of 0.96, probability of detection of 0.83, probability of false detection equal to 0.03 and probability of false alarm of 0.18. The output of the proposed fog forecast method can activate (or not) a specific fog postprocessing layer designed to correct the global horizontal irradiance forecasted by the WRF model in order to optimize the forecast of the irradiance reaching the photovoltaic panels surface.

Laser and LIDAR in a System for Visibility Distance Estimation in Fog Conditions

Visibility is a critical factor for transportation, even if we refer to air, water, or ground transportation. The biggest trend in the automotive industry is autonomous driving, the number of autonomous vehicles will increase exponentially, prompting changes in the industry and user segment. Unfortunately, these vehicles still have some drawbacks and one, always in attention and topical, will be treated in this paper-visibility distance issue in bad weather conditions, particularly in fog. The way and the speed with which vehicles will determine objects, obstacles, pedestrians, or traffic signs, especially in bad visibility, will determine how the vehicle will behave. In this paper, a new experimental set up is featured, for analyzing the effect of the fog when the laser and LIDAR (Light Detection And Ranging) radiation are used in visibility distance estimation on public roads. While using our experimental set up, in the laboratory, the information offered by these measurement systems (laser and LIDAR) are evaluated and compared with results offered by human observers in the same fog conditions. The goal is to validate and unitarily apply the results regarding visibility distance, based on information arrives from different systems that are able to estimate this parameter (in foggy weather conditions). Finally, will be notifying the drivers in case of unexpected situations. It is a combination of stationary and of moving systems. The stationary system will be installed on highways or express roads in areas prone to fog, while the moving systems are, or can be, directly installed on the vehicles (autonomous but also non-autonomous).

Long-term trends in fog occurrence in the Czech Republic, Central Europe

Fog is a very important and complex atmospheric phenomenon of the utmost importance for the environment and for human society. For practical reasons, fog occurrence is observed regularly at meteorological stations worldwide. Decreasing trends in fog frequency reported from numerous regions have been often associated with either decreasing pollution or climate change, including increasing temperature and changes in atmospheric circulation. We have examined the data on fog occurrence from twelve Czech sites representing different environments (urban, rural, mountain), geographical areas, and altitudes across the country. For our analysis we used long-term records from the time period of 1961-2018, covering both the ambient air's heavily polluted periods of the 1970s and 1980s and the cleaner period, following the adoption of new, more stringent legislation and effective countermeasures after the 1990s. We applied a generalised additive model (GAM) framework as a flexible, semiparametric regression approach to address nonlinear trend shapes in a formalised and unified way. In particular, we employed a penalised spline approach with cross-validated penalty coefficient estimation. Our study confirmed non-linear behaviour for both year-to-year trends and annual seasonality. Our results showed further that over the analysed, almost sixty-year period, fog occurrence has decreased significantly at all the examined sites, though the pattern of the long-term change differed among individual sites. Moreover, we have found significant seasonality in fog occurrence, though it is different at individual sites. Furthermore, apart from the overall annual fog probability change over the years, at some sites the fog's seasonal profile has also deformed substantially over the long term.

Entropy and the Tolman Parameter in Nucleation Theory

Thermodynamic aspects of the theory of nucleation are commonly considered employing Gibbs’ theory of interfacial phenomena and its generalizations. Utilizing Gibbs’ theory, the bulk parameters of the critical clusters governing nucleation can be uniquely determined for any metastable state of the ambient phase. As a rule, they turn out in such treatment to be widely similar to the properties of the newly-evolving macroscopic phases. Consequently, the major tool to resolve problems concerning the accuracy of theoretical predictions of nucleation rates and related characteristics of the nucleation process consists of an approach with the introduction of the size or curvature dependence of the surface tension. In the description of crystallization, this quantity has been expressed frequently via changes of entropy (or enthalpy) in crystallization, i.e., via the latent heat of melting or crystallization. Such a correlation between the capillarity phenomena and entropy changes was originally advanced by Stefan considering condensation and evaporation. It is known in the application to crystal nucleation as the Skapski–Turnbull relation. This relation, by mentioned reasons more correctly denoted as the Stefan–Skapski–Turnbull rule, was expanded by some of us quite recently to the description of the surface tension not only for phase equilibrium at planar interfaces, but to the description of the surface tension of critical clusters and its size or curvature dependence. This dependence is frequently expressed by a relation derived by Tolman. As shown by us, the Tolman equation can be employed for the description of the surface tension not only for condensation and boiling in one-component systems caused by variations of pressure (analyzed by Gibbs and Tolman), but generally also for phase formation caused by variations of temperature. Beyond this particular application, it can be utilized for multi-component systems provided the composition of the ambient phase is kept constant and variations of either pressure or temperature do not result in variations of the composition of the critical clusters. The latter requirement is one of the basic assumptions of classical nucleation theory. For this reason, it is only natural to use it also for the specification of the size dependence of the surface tension. Our method, relying on the Stefan–Skapski–Turnbull rule, allows one to determine the dependence of the surface tension on pressure and temperature or, alternatively, the Tolman parameter in his equation. In the present paper, we expand this approach and compare it with alternative methods of the description of the size-dependence of the surface tension and, as far as it is possible to use the Tolman equation, of the specification of the Tolman parameter. Applying these ideas to condensation and boiling, we derive a relation for the curvature dependence of the surface tension covering the whole range of metastable initial states from the binodal curve to the spinodal curve.

Gender and Community Mainstreaming in Fog Water Collection Systems

Fog water collection is an emerging opportunity to combat local water shortages in water-scarce areas where sustainable access to water is unreliable, but fog events are frequent. Since fog water systems are implemented within or near communities, they eliminate or decrease the need to travel far distances for the collection of water during times of scarcity. As a result, these systems decrease the physical and social burden of water collection on women and girls, who are the primary water gatherers in most traditional communities. This is an important outcome because women and girls are disproportionately affected by water scarcity and are not seen as equals in water management, access, or control. This paper illustrates how several fog water collection projects have shown, empirically, that the positive outcomes for women and girls may include the freeing of time for domestic and educational pursuits, improved health outcomes, and improved perceptions of self and others’ perceptions of women. These findings are important at a time when the world at large is addressing the Sustainable Development Agenda, where Sustainable Development Goal (SDG) 6 necessitates safe water and sanitation for all and SDG 5 ensures gender equality to empower all women and girls.

Revisiting fog as an important constituent of the atmosphere

We examined observation-based fog occurrence at three Czech monitoring sites: Praha 4 - Libuš, Košetice and Churáňov, representing different environments - urban, rural and mountain - over a time span of 27 years (1989-2015). We searched for a simple model describing fog occurrence fitting the observed air pollution and meteorological data. For our analysis we used a generalized additive model, GAM, with (penalized) spline components to capture possible nonlinear and a priori unknown functional relationships. In order to cope with the binary nature of the data (indicators of fog presence on individual days), we employed a logistic regression GAM model fitted by a maximizing penalized likelihood (where the penalty coefficients were estimated via cross-validation). After testing several physically motivated models, being guided by AIC and physical interpretation of the components, we arrived at a model which uses the following explanatory variables: relative humidity, ambient SO₂ concentrations, ambient NO_x concentrations, air temperature and seasonality. All associations between the response and the analysed explanatory variables were highly significant. According to our results, the most important explanatory variables modelling the fog probability were relative humidity and air pollutants. Interestingly, we observed an increasing trend in fog occurrence at all three sites under review starting around the mid 2000s.

CAPSULE

The most important explanatory variables modelling the fog probability at three Central European sites were humidity, SO₂ and NO_x. An increasing trend in fog occurrence has been observed since the mid 2000s.

Millimeter Wave High Resolution Radar Accuracy in Fog Conditions-Theory and Experimental Verification

Attenuation and group delay effects on millimeter wave (MMW) propagation in clouds and fog are studied theoretically and verified experimentally using high resolution radar in an indoor space filled with artificial fog. In the theoretical analysis, the frequency-dependent attenuation and group delay were derived via the permittivity of the medium. The results are applied to modify the millimeter-wave propagation model (MPM) and employed to study the effect of fog and cloud on the accuracy of the Frequency-Modulated Continuous-Wave (FMCW) radar operating in millimeter wavelengths. Artificial fog was generated in the experimental study to demonstrate ultra-low visibility in a confined space. The resulted attenuation and group delay were measured using FMCW radar operating at 320–330 GHz. It was found that apart from the attenuation, the incremental group delay caused by the fog also played a role in the accuracy of the radar. The results were compared to the analytical model. It was shown that although the artificial fog has slight different characteristics compare to the natural fog and clouds, in particle composition, size, and density, the model predictions were good, pointing out that the dispersive effects should be considered in the design of remote sensing radars operating in millimeter and sub-millimeter wavelengths.