Editor’s Choice Articles

This paper describes the modification of a simple land snow cover module of the INM RAS climate model. The possible liquid water and refreezing of meltwater in the snow layer are taken into account by the proposed parameterization. This is particularly important for modelling the transition season, as this phenomenon is mainly observed during the formation and melting of the snow cover when the surface temperature fluctuates around $0 °$C. The snow density evolution simulation is also added. This parameterization is implemented in the INM-CM snow module and verified on observation data using the ESM-SnowMIP-like protocol. As a result, the INM-CM mean climate snow melt periods are refined, particularly in middle and high latitudes. The snow-covered area according to the model is also improved. In the future, a modified version of the land snow module can be used, coupled with a snow albedo model that takes into account snow metamorphism. This module can also be applied to sea ice snow. Full article

The large amounts of greenhouse gases, such as carbon dioxide, produced by severe forest fires not only seriously affect the ecosystems in the area where the fires occur but also cause a greenhouse effect that has a profound impact on the natural environment in other parts of the world. Numerical simulations of greenhouse gas transport processes are often affected by uncertainties in the location and timing of the emission sources and local meteorological conditions, and it is difficult to obtain accurate and credible predictions by combining remote sensing satellite data with given meteorological forecasts or reanalyses. To study the regional transport processes and impacts of greenhouse gases produced by sudden large-scale forest fires, this study applies the Lagrangian particle dispersion model Massive-Parallel Trajectory Calculations (MPTRAC) to conduct forward simulations of the CO₂ transport process of greenhouse gases emitted from forest fires in the central region of Saskatchewan, Canada, during the period of 17 May to 25 May 2021. The simulation results are validated with the Orbiting Carbon Observatory-2 Goddard Earth Observing System (OCO-2 GEOS) Level 3 daily gridded CO₂ product over the study area. In order to leverage the high computational costs of the numerical simulations of the model, we implement the forward simulations on the Tianhe-2 supercomputer platform and the JUWELS HPC system, which greatly improves the computational efficiency through parallel computation and makes near-real-time predictions of atmospheric transport processes feasible. Full article

A current challenge in realising clean road transport is non-exhaust emissions. Important advances regarding measurement systems, including well-defined characterisation techniques, as well as regulation, will be made in the next few years. In this work, we present the detailed results of particle emission analyses, consisting of aerosol (size distribution, particle number (PN), and mass (PM)) and electron microscopy (EM) measurements, under different load conditions on a test bed for a wheel suspension and brakes. Standard tyres and brakes from serial production were tested with a high-load driving cycle, while particle measurements were conducted by gravimetric measurements and with a TSI SMPS, a TSI APS, and a GRIMM OPS. Furthermore, samples were analysed by electron microscopy. A bimodal particle size distribution (PSD) was obtained with an SMPS, with peaks at 20 $\mathrm{n}$$\mathrm{m}$ and around 400 $\mathrm{n}$$\mathrm{m}$. The results of an EM analysis of $>1400$ single particles from the electrostatic sampler match the PSD results. The EM analysis also showed ultrafine particles, mainly containing O, Fe, Si, Ba, Mg, and S, and also fractal particles with high-C fractions. Our results suggest, in agreement with the previously published literature, that particulate emissions are related to the brake disc temperature and occur in significant amounts above a threshold temperature. Full article

Though the impact of urban vegetation on air quality and the microclimate has attracted increasing attention, there have been few studies quantitatively assessing this impact in North China, where air pollution is severe. In this study, we investigated the impact of urban forests and urban parks on air quality and the microclimate in Jinan, northern China. Six sites were chosen to represent urban forest, urban park, and downtown areas, respectively. The results indicate that urban forest can effectively reduce PM_2.5 and ozone (O₃) concentrations in the warm season, when temperatures are higher and plants are lush. The PM_2.5 and O₃ concentrations in the urban forest areas were 6.3–6.5 μg m⁻³ and 21–23 μg m⁻³ lower than those in downtown areas during the period of 10:00–15:00. In contrast, urban park areas can reduce PM_2.5 concentrations but have little impact on gaseous pollutants such as nitrogen dioxide and O₃. Furthermore, both urban forest and urban park areas reduced temperatures, by approximately 4.1–6.8 °C and 1.36 °C, respectively, and increased relative humidity, by about 13.4–12.9% and 0.9%, promoting a more comfortable thermal environment for residents. Therefore, this study highlights the crucial role of urban vegetation in improving air quality and creating a comfortable environment for residents. Full article

A study was carried out in Santiago de Chile, located in a geographic basin, on the sustainability and diffusion of the recent SARS-CoV-2 pandemic. Hourly measurements were used (carried out for 3.25 years in seven communes of the city) to quantify the accumulated sick (AS) population, urban meteorology variables (MVs) (temperature (T), relative humidity (RH), and magnitude of wind speed (WS)), and air pollution (P) (PM₁₀, PM_2.5, 0₃). Time series (TS) were constructed for each commune, which related AS to MVs, called AS/VM, and to P, noted AS/P. Chaos theory was applied to each TS, requiring the following variables: the Lyapunov exponent (λ > 0), the correlation dimension (D_C < 5), Kolmogorov entropy (S_K > 0), the Hurst exponent (H, such that 0 < H < 1), Lempel–Ziv complexity (LZ > 0), and information loss (<ΔI> < 0). Every TS complied with chaos theory. For each commune, C_K was calculated as a quotient between the sum of AS/T, AS/WS, and AS/RH entropies and the sum of AS/PM₁₀, AS/PM_2.5, and AS/O₃ entropies. The results show that the entropy for the AS/P ratio is lower than that of the AS/VM ratio in three of the seven communes, since between 2020 and early 2022, the population was confined, reducing pollution. The TS of the AS/P ratio is more persistent and complex. The predictability times of the ratios are comparable in four of the seven communes. The TS of the AS/MV ratios shows greater information loss and chaos. According to the calculated C_K values, it is possible to relate it to anomalous diffusion (sub/super-diffusion) and the context that favored the expansion of the pandemic: urban densification, pollution, urban meteorology, population density, etc. Using Fréchet heavy-tailed probability, the compatibility of the results with C_K is verified. Full article

Oxidation potential (OP), reflecting the redox activities of particle matter (PM), is considered an optimal measure to explain the biological effects of PM exposure. However, the size resolution of the relationship between OP and chemical composition in PM, especially how the relationship changes after respiratory exposure, has not been well investigated. In this study, size-resolved indoor PM₁₀ samples were collected from a waste recycling plant from November to December 2021 using an Anderson eight-stage cascade impactor. OP, measured by a dithiothreitol (DTT) assay (defined as OP^DTT), and elements, determined by inductively coupled plasma–mass spectrometry (ICP-MS) in size-resolved PM, were determined to check their relationships and the related human exposure risk. The results indicated that compared with PM_0.4 and PM_0.4–2.1, PM_2.1–10 contributed the most to total OP^DTT and its bound elements contributed the most to potential health risks, both before and after respiratory exposure. The association between OP^DTT and the elements varied with PM size. Pearson correlation analysis showed that the PM_0.4- and PM_0.4–2.1-bound elements were moderate-to-strongly positively correlated with OP_v^DTT (r: 0.60–0.90). No significant correlation or dose–response relationship was found in PM_2.1–10. After respiratory exposure, several PM_0.4- and PM_0.4–2.1-bound elements had a moderate-to-strongly positive correlation with deposition fluxes of OP (defined as OP^Flux) (0.69–0.90). A generalized linear model analysis showed that the interquartile range (IQR) increase in the PM-bound elements (ng h⁻¹) was associated with a 41.7–58.1% increase in OP^Flux. Our study is a special case that enriches the knowledge of the association between OP^DTT and the chemical composition of PM of different sizes, especially after respiratory exposure, but the generalizability of the findings to other settings or types of PM may be limited. The associations among OP^DTT, other chemical compositions of PM, and human exposure risk merit further research. Full article

The Intergovernmental Panel on Climate Change (IPCC) concluded that the latest decade was warmer than any multi-century period over the past 125,000 years. This statement rests on a comparison of modern instrumental measurements against the course of past temperatures reconstructed from natural proxy archives, such as lake and marine sediments, and peat bogs. Here, we evaluate this comparison with a focus on the hundreds of proxy records developed by paleoclimatologists across the globe to reconstruct climate variability over the Holocene (12,000 years) and preceded by the Last Glacial Period (125,000 years). Although the existing proxy data provide a unique opportunity to reconstruct low-frequency climate variability on centennial timescales, they lack temporal resolution and dating precision for contextualizing the most recent temperature extremes. While the IPCC’s conclusion on the uniqueness of latest-decade warming is thus not supported by comparison with these smoothed paleotemperatures, it is still likely correct as ice core-derived forcing timeseries show that greenhouse gases were not elevated during any pre-instrumental period of the Holocene. Full article

Fine particulate matter with an aerodynamic diameter less than 2.5 µm ($\mathrm{P}{\mathrm{M}}_{2.5}$) profoundly affects environmental systems, human health and economic structures. Multi-source data and advanced machine or deep-learning methods have provided a new chance for estimating the $\mathrm{P}{\mathrm{M}}_{2.5}$ concentrations at a high spatiotemporal resolution. In this paper, the Random Forest (RF) algorithm was applied to estimate hourly $\mathrm{P}{\mathrm{M}}_{2.5}$ of the North China area (Beijing–Tianjin–Hebei, BTH) based on the next-generation geostationary meteorological satellite Himawari-8/AHI (Advanced Himawari Imager) aerosol optical depth (AOD) products. To improve the estimation of $\mathrm{P}{\mathrm{M}}_{2.5}$ concentration across large areas, we construct a method for co-weighting the environmental similarity and the geographical distances by using an attention mechanism so that it can efficiently characterize the influence of spatial–temporal information hidden in adjacent ground monitoring sites. In experiment results, the hourly $\mathrm{P}{\mathrm{M}}_{2.5}$ estimates are well correlated with ground measurements in BTH, with a coefficient of determination (${\mathrm{R}}^2$) of 0.887, a root-mean-square error (RMSE) of 18.31 $\mathsf{\mu }$g/${\mathrm{m}}^3$, and a mean absolute error (MAE) of 11.17 µg/${\mathrm{m}}^3$, indicating good model performance. In addition, this paper makes a comprehensive analysis of the effectiveness of multi-source data in the estimation process, in this way, to simplify the model structure and improve the estimation efficiency of the model while ensuring its accuracy. Full article

This study explores the spatiotemporal variability of the onset, end, and duration of the rainy season in Senegal. These phenological parameters, crucial for agricultural planning in West Africa, exhibit high interannual and spatial variability linked to precipitation. The objective is to detect and spatially classify these indices across Senegal using different approaches. Daily precipitation data and ERA5 reanalyses from 1981 to 2018 were utilized. The employed method enables the detection of key dates. Subsequently, the Kohonen algorithm spatially classifies these indices on topological maps. The results indicate a meridional gradient of the onset, progressively later from the southeast to the northwest, whereas the end follows a north–south gradient. The duration varies from 45 days in the north to 150 days in the south. The use of self-organizing maps allows for classifying the onset, end, and duration of the season into four zones for the onset and end, and three zones for the duration of the season. They highlight the interannual irregularity of transitions, with both early and late years. The dynamic analysis underscores the complex influence of atmospheric circulation fields, notably emphasizing the importance of low-level monsoon flux. These findings have tangible implications for improving seasonal forecasts and agricultural activity planning in Senegal. They provide information on the onset, end, and duration classes for each specific zone, which can be valuable for planning crops adapted to each region. Full article

Meteorological conditions and air quality are important environmental factors in the occurrence and development of cardiovascular diseases (CVDs) such as hypertension. The aim of this study was to take Haikou City, located on the tropical edge, as the research area and to analyze the exposure–response relationship and lag effect between its meteorological conditions, air quality, and the number of hypertensive patients. Using the data from the hypertension outpatient department of Hainan Provincial People’s Hospital from 2016 to 2018, together with meteorological data and air quality data, a distributed lag nonlinear model based on the nested generalized addition model of meteorological element base variables was established. The results showed that the impact of temperature on the risk of hypertension was mainly due to the cold effect, which was associated with high risk, with a lag of 1–10 days. When the temperature dropped to 10 °C, the cumulative effect on the risk of hypertension of relative risk (RR) reached its highest value on the day the low temperature occurred (RR was 2.30 and the 95% confidence interval was 1.723~3.061), passing the test with a significance level of 0.05. This result indicated that efforts should be made to strengthen the prevention of hypertension under low-temperature conditions and the prediction and early warning of disease risks. The impact of the air-quality effect (the environmental Air Quality Index was selected as an indicator) on the risk of hypertension was mainly characterized by a low air-quality effect, with a lag effect of 0–8 days. When the risk reached approximately 124, the RR was highest (RR was 1.63 and the 95% confidence interval was 1.104~2.408), passing the test with a significance level of 0.05. The research results can provide technical support for conducting medical meteorological forecasting, early warning, and services for hypertension. A joint work and research mechanism among multiple departments such as meteorology and medical health should be established to improve the level of medical and health care, optimize the allocation of social resources, and develop targeted prevention and control strategies to reduce the health and economic burden of hypertension. Full article

This study aims to estimate the surface runoff and examine the impact of climate change on water resources in the Upper Kabul River Basin (UKRB). A hydrological model was developed using the Soil and Water Assessment Tool (SWAT) from 2009 to 2019. The monthly calibration was conducted on streamflow in six stations for the period from 2010 to 2016, and the results were validated from 2017 to 2018 based on available observed data. The hydrological sensitivity parameters were further prioritized using SWAT-CUP. The uncertainty of the model was analyzed by the 95% Prediction Uncertainty (95PPU). Future projections were analyzed for the 2040s (2030–2049) and 2090s (2080–2099) compared to the baseline period (1986–2005) under two representation concentration pathways (RCP4.5, RCP8.5). Four Regional Climate Models (RCMs) were bias-corrected using the linear scaling bias correction method. The modeling results exhibited a very reasonable fit between the estimated and observed runoff in different stations, with NS values ranging from 0.54 to 0.91 in the calibration period. The future mean annual surface runoff exhibited an increase in the 2040s and 2090s compared to the baseline under both RCPs of 4.5 and 8.5 due to an increase in annual precipitation. The annual precipitation is projected to increase by 5% in the 2040s, 1% in the 2090s under RCP4.5, and by 9% in the 2040s and 2% in the 2090s under RCP8.5. The future temperature is also projected to increase and consequently lead to earlier snowmelt, resulting in a shift in the seasonal runoff peak to earlier months in the UKRB. However, the shifts in the timing of runoff could lead to significant impacts on water availability and exacerbate the water stress in this region, decreasing in summer runoff and increasing in the winter and spring runoffs. The future annual evapotranspiration is projected to increase under both scenarios; however, decreases in annual snowfall, snowmelt, sublimation, and groundwater recharge are predicted in the UKRB. Full article

In the context of global climate change and rising sea levels, the adverse impacts of storm surges on the environment, economy, and society of affected areas are becoming increasingly significant. However, due to differences in geography, climate, and other conditions among the affected areas, a single method for assessing the risk of storm surge disasters cannot be fully applicable to all regions. To address this issue, an increasing number of new methods and models are being applied in the field of storm surge disaster risk assessment. This paper introduces representative traditional statistical methods, numerical simulation methods, and artificial intelligence-based techniques in this field. It compares these assessment methods in terms of accuracy, interpretability, and implementation difficulty. The paper emphasizes the importance of selecting appropriate assessment methods based on specific conditions and scientifically combining various methods in practice to improve the accuracy and reliability of storm surge disaster risk assessments. Full article

We conducted a cross-sectional study of 130 participants living near a ferromanganese alloy plant, analyzing Pb and Mn exposure by biomarkers (blood, hair, and fingernails) and particulate matter personal environmental monitors (PEMs). Cognitive and motor function were assessed by five and three tests, respectively. Mean differences (MDs) adjusted for age, sex, and study level were determined. In addition, MDs for Pb were adjusted for Mn levels and vice versa. Medians of 9.14 µg/L, 149.04 ng/g, and 96.04 ng/g were obtained for blood, scalp hair, and fingernails Pb levels, respectively. Regarding PEMs, median Pb levels were 6.56 ng/m³ for the fine fraction and, for the coarse fraction, they were below the limit of detection in 97% of participants. Exposure to Pb at low levels was not associated with worse cognitive function. In comparison, exposure to high levels of Mn was associated with worse cognitive function at least in the domains evaluated through Stroop, Digit Span, and Verbal Fluency tests. In terms of motor function, our results suggest that even the currently low Pb levels may have negative health effects on dynamometer-determined strength—adjusted MD on dominant hand = −2.68; 95%CI (−4.85 to −0.51), p = 0.016. Further studies should investigate this association. Full article

Lidar observations of metal layers play a significant role in research on the chemistry and dynamics of the mesosphere and lower thermosphere. This work reports on Fe lidar observations conducted in Beijing and Mohe. Utilizing the same laser emission system, a 1064 nm seed laser was injected into an Nd: YAG laser to generate a single longitudinal-mode pulse 532 nm laser, which pumped a dye laser to produce a 572 nm laser. The 572 nm laser and the remaining 1064 nm fundamental frequency laser passed through a sum–frequency module to generate a 372 nm laser to detect the Fe layer. According to a total of 52.6 h of observations for 10 nights in Beijing, the Fe layer has an average column density of 1.24 × 10¹⁰ cm⁻², an RMS width of 4.4 km and a centroid altitude of 89.4 km. In Mohe, observed for 16 nights and a total of 91.5 h, the Fe layer has an average column density of 1.08 × 10¹⁰ cm⁻², an RMS width of 4.6 km and a centroid altitude of 89.5 km. The probability of the occurrence of sporadic Fe layers was 42.4% in Beijing and 29.4% in Mohe. Compared to simultaneously observed Na layers, the occurrence probabilities of sporadic Fe layers were higher than those of sporadic Na layers in both stations. Based on the two cases observed in Beijing, it is conjectured that the formation mechanism of sporadic metal layers above approximately 100 km has a more significant influence on sporadic Fe layers than on sporadic Na layers. The lower thermospheric Fe layers with densities significantly larger than those of the main layer were observed during two nights in Mohe. This work contributes to the refinement of the global distribution of Fe layers and provides abundant observational data for the modeling and study of the metal layers. Full article

Over the last years the Athens Cosmic Ray Group of the National & Kapodistrian University of Athens has implemented a warning tool called GLE Alert, which is a highly credible application that issues alerts when a ground level enhancement (GLE) starts due to very high energy solar energetic particles reaching the Earth. This application warns of a high intensity solar energetic particle event up to several minutes before it reaches near the near-Earth space environment. In this work, an assessment of the latest updated version of GLE Alert, GLE Alert++, is presented. GLE Alert++ is a federated product of the ESA S2P SWE Space Radiation Expert Service Centre, which is part of the ESA Space WEather Service NETwork (SWESNET) project. The assessment of the GLE Alert++, which was finalized in October 2022, focused on: (a) the availability of the real-time data provided by the neutron monitor stations that contribute to the GLE Alert++, (b) the behaviour of each station regarding the different Alert levels status (Watch, Warning and Alert), and (c) the definition of the real-time assessment index. The results of this work are of essential importance since they ensure a reliable and trustworthy warning tool, and can be highly useful in protecting humans during extreme solar energetic events. Full article

Urban trees play a vital role in mitigating climate changes, maintaining the sustainability of ecosystems. This study focuses on the assessment of the resilience of cherry plums to climate changes, a fruit-bearing species that offers diverse ecosystem services within multifunctional urban and suburban landscapes. This study examines flowering and fruiting in the context of climate characteristics, expressed through the Day of the Year (DOY), Growing Degree Days (GDDs), and a yield over 17 consecutive years. The results indicate significant shifts in the DOY but not in the GDD, apart from the end of flowering. The onset of flowering was earlier and the end postponed, extending the phenophase by an average of 4 days. The cherry plum’s yield was unaffected by climate changes, including extreme events like a late-spring frost. The stability of the cherry plum was confirmed by the phenological patterns of the bullace (cherry plum and blackthorn hybrid) exhibiting repeated flowering in the warmest year of 2023. The cherry plum is an adaptive species, with a high adaptability to a changing climate and a high resistance to late-spring frosts; thus, it is a favorable choice in urban design and planning, demonstrating resilience to climate shifts and thriving in polluted urban environments. It is especially appreciated for multiple ecosystem services: biodiversity conservation in natural and semi-natural areas, yielding good provisions in challenging environments, and the preservation of ornamental values through an extended flowering phenophase. Full article

Air pollution is one of the most important problems in big cities, resulting in adverse health effects. The aim of the present study was to characterize the personal exposure to indoor and outdoor pollution in the Greater Athens Area in Greece by taking measurements during a journey from suburban to mixed industrial–urban areas, encompassing walking, waiting, bus travel, and metro travel at various depths. For this reason, low-cost (LC) sensors were used, and the inhaled dose of particulate matter with an aerodynamic diameter of less than or equal to 2.5 μm (PM_2.5) in different age groups of passengers was calculated. Specific bus routes and the Athens metro network were monitored throughout different hours of the day. Then, the average particulate matter (PM_2.5) exposure for a metro passenger was calculated and evaluated. By considering the ventilation rate of a passenger, an estimation of the total PM_2.5 inhaled dose for males and females as well as for different age groups was made. The results showed that the highest PM_2.5 concentrations were observed inside the wagons with significant increases during rush hours or after rush hours. Furthermore, there should be a concern regarding older individuals using the subway network in Athens during rush hours and in general for sensitive groups (people with asthma, respiratory and cardiovascular problems, etc.). Full article

One of the most popular indices for monitoring the occurrence and intensity of ionospheric L-band irregularities is the Rate of TEC Index (ROTI). Due to low TEC in the mid-latitude ionosphere, ROTI has received significantly less attention than the equatorial and polar ionosphere. On the other hand, spread F is an established ionogram irregularity signature. The present study aims to correlate ROTI and spread F activity over European Digisonde stations for a low-to-moderate solar activity year (2011). With a focus on the latitude-dependent occurrence, the analysis demonstrates that range spread F (RSF) has been identified for all notable ROTI (>0.15 TECU/min) cases which also coincide with MSTID activity over the stations, suggesting induced gravity waves or polarization electric fields as the driving mechanism for enhanced ROTI activity. The diurnal and seasonal features are also presented. Maximum irregularity occurrence was observed around the 45° N from 18:00 to 05:00 UT with the seasonal maximum occurrence in January. Over lower mid-latitude Digisonde stations (latitude < 45° N), the diurnal and seasonal occurrence was observed from 19:00 to 04:30 UT in July. Full article

The monitoring of anthropogenic CO₂ emissions, which increase the atmospheric CO₂ concentration, plays the most important role in the management of emission reduction and control. With the massive increase in satellite-based observation data related to carbon emissions, a data-driven machine learning method has great prospects for predicting anthropogenic CO₂ emissions. Training samples, which are used to model predictions of anthropogenic CO₂ emissions through machine learning algorithms, play a key role in obtaining accurate predictions for the spatial heterogeneity of anthropogenic CO₂ emissions. We propose an approach for predicting anthropogenic CO₂ emissions using the training datasets derived from the clustering of the atmospheric CO₂ concentration and the segmentation of emissions to resolve the issue of the spatial heterogeneity of anthropogenic CO₂ emissions in machine learning modeling. We assessed machine learning algorithms based on decision trees and gradient boosting (GBDT), including LightGBM, XGBoost, and CatBoost. We used multiple parameters related to anthropogenic CO₂-emitting activities as predictor variables and emission inventory data from 2019 to 2021, and we compared and verified the accuracy and effectiveness of different prediction models based on the different sampling methods of training datasets combined with machine learning algorithms. As a result, the anthropogenic CO₂ emissions predicted by CatBoost modeling from the training dataset derived from the clustering analysis and segmentation method demonstrated optimal prediction accuracy and performance for revealing anthropogenic CO₂ emissions. Based on a machine learning algorithm using observation data, this approach for predicting anthropogenic CO₂ emissions could help us quickly obtain up-to-date information on anthropogenic CO₂ emissions as one of the emission monitoring tools. Full article

PM_2.5 particles with an aerodynamic diameter of less than 2.5 μm are receiving increasing attention in China. Understanding how complex factors affect PM_2.5 particles is crucial for the prevention of air pollution. This study investigated the influence of meteorological factors and land use on the dynamics of PM_2.5 concentrations in four urban agglomerations of China at different scales from 2010 to 2020, using the Durbin spatial domain model (SDM) at five different grid scales. The results showed that the average annual PM_2.5 concentration in four core urban agglomerations in China generally had a downward trend, and the meteorological factors and land use types were closely related to the PM_2.5 concentration. The impact of temperature on PM_2.5 changed significantly with an increase in grid scale, while other factors did not lead to obvious changes. The direct and spillover effects of different factors on PM_2.5 in inland and coastal urban agglomerations were not entirely consistent. The influence of wind speed on coastal urban clusters (the Pearl River urban agglomeration (PRD) and Yangtze River urban agglomeration (YRD)) was not significant among the meteorological factors, but it had a significant impact on inland urban clusters (the Beijing–Tianjin–Hebei urban agglomeration (BTH) and Chengdu–Chongqing urban agglomeration (CC)). The direct effect of land use type factors showed an obvious U-shaped change with an increase in the research scale in the YRD, and the direct effect of land use type factors was almost twice as large as the spillover effect. Among land use type factors, human factors (impermeable surfaces) were found to have a greater impact in inland urban agglomerations, while natural factors (forests) had a greater impact in coastal urban agglomerations. Therefore, targeted policies to alleviate PM_2.5 should be formulated in inland and coastal urban agglomerations, combined with local climate measures such as artificial precipitation, and urban land planning should be carried out under the consideration of known impacts. Full article

Precipitable water vapor (PWV) is a crucial factor in regulating the Earth’s climate. Moreover, it demonstrates a robust correlation with precipitation. Situated in a region known for the generation and development of tropical cyclones, Guangxi in China is highly susceptible to floods triggered via intense rainfall. The atmospheric water vapor in this area displays prominent spatiotemporal features, thus posing challenges for precipitation forecasting. The water vapor products within the MERRA-2 and ERA5 reanalysis datasets present an opportunity to overcome constraints associated with low spatiotemporal resolution. In this study, the PWV data derived from GNSS and meteorological measurements in Guangxi from 2016 to 2018 were used to evaluate the accuracy of MERRA-2 and ERA5 water vapor products and their relationship with water vapor variations during extreme rainfall. Using GNSS PWV as a reference, the average bias of MERRA-2 PWV and ERA5 PWV for heavy rainfall was −0.22 mm and 1.84 mm, respectively, with average RMSE values of 3.72 mm and 3.31 mm. For severe rainfall, the average bias of MERRA-2 PWV and ERA5 PWV was −0.14 mm and 2.92 mm, respectively, with average RMSE values of 4.28 mm and 4.01 mm. During heavy rainfall days from Days 178 to 184 in 2017, the average bias of MERRA-2 PWV and ERA5 PWV was 0.92 mm and 2.42 mm, respectively, with average RMSE values of 4.04 mm and 3.40 mm. The accuracy was highest at the Guiping and Hechi stations and lowest at the Hezhou and Rongshui stations. Furthermore, when comparing MERRA-2/ERA5 PWV with GNSS PWV and actual precipitation, the trends in the variations of MERRA-2/ERA5 PWV were generally consistent with GNSS PWV and aligned with the increasing or decreasing trends of actual precipitation. In addition, ERA5 PWV exhibited high accuracy. Before the onset of heavy rainfall, PWV has a sharp surge. During heavy rainfall, PWV reaches its peak value. Subsequently, after the cessation of heavy rainfall, PWV tends to stabilize. Therefore, the reanalysis data of PWV can effectively reveal significant changes in water vapor and actual precipitation during periods of heavy rainfall in the Guangxi region. Full article

Secondary minerals in SNC meteorites from Mars exhibit O isotope ratios believed to be consistent with the non-thermal escape of O from the atmosphere. The primary source of the non-thermal O is the dissociative- recombination of O₂⁺ in the ionosphere. I present here the results of a model that accounts for the probability of escape of non-thermal O isotopes due to collisions with overlying CO₂, combined with a model for Rayleigh fractionation of the atmosphere remaining as a result of O escape. Previous analyses of MAVEN number density data have shown a strong variability with latitude and season of the heights of the homopause and exobase, with a mean homopause at 110 km and a mean difference of about 60 km. Rayleigh model results demonstrate a dependence on homopause height and on temperature profile and require a more accurate calculation of fractionation factors for the Rayleigh equation. Isothermal temperature profiles yield much smaller variation in ¹⁷O with homopause height. These results demonstrate the need for a careful assessment of O isotope enrichment due to non-thermal escape both for the modern atmosphere and for the evolution of the atmosphere over the age of the planet. Full article

In the present paper, the response of the ionospheric Total Electron Content (TEC) at low latitudes during several geomagnetic storms occurring in different seasons of the year is investigated. In the analysis of the ionospheric response, the following three geomagnetic events were selected: (i) 23–24 April 2023; (ii) 22–24 June 2015 and (iii) 16 December 2006. Global TEC data were used, with geographic coordinates recalculated with Rawer’s modified dip (modip) latitude, which improved the accuracy of the representation of the ionospheric response at low and mid-latitudes. By decomposition of the zonal distribution of the relative deviation of the TEC values from the hourly medians, the spatial distribution of the anomalies, the dependence of the response on the local time and their evolution during the selected events were analyzed. As a result of the study, it was found that the positive response (i.e., an increase in electron density relative to quiet conditions) in low latitudes occurs at the modip latitudes 30° N and 30° S. An innovative result related to the observed responses during the considered events is that they turn out to be relatively stationary. The longitude variation in the observed maxima changes insignificantly during the storms. Depending on the season, there is an asymmetry between the two hemispheres, which can be explained by the differences in the meridional neutral circulation in different seasons. Full article

The Weather Research and Forecasting (WRF) model was used to simulate Typhoon Rumbia in this paper. The sensitivity experiments were conducted with 16 different parameterization combination schemes, including four microphysics (WSM6, WSM5, Lin, and Thompson), two boundary layers (YSU and MYJ), and two cumulus convection (Kain–Fritsch and Grell–Freitas) schemes. The impacts of 16 parameterization combination schemes and the data assimilation (DA) of Global Navigation Satellite System (GNSS) water vapor were evaluated by the simulation accuracy of typhoon track and intensity. The results show that the typhoon track and intensity are significantly influenced by parameterization schemes of cumulus and boundary layers rather than microphysics. The averaged track error of Lin_KF_Y is 104.73 km in the entire 72-h simulation period. The track errors of all the other combination schemes are higher than Lin_KF_Y. During the entire 72-h, the averaged intensity error of Thompson_GF_M is 1.36 hPa. It is the lowest among all the combination schemes. As for data assimilation, the simulation accuracy of typhoon tracks can be significantly improved by adding the GNSS water vapor. Thompson_GF_M-DA combination scheme has the lowest average track error of 45.05 km in the initial 24 h. The Lin_KF_Y-DA combination scheme exhibits an average track error of 32.17 km on the second day, 28.03 km on the third day, and 35.33 km during 72-h. The study shows that the combination of parameterization schemes and the GNSS water vapor data assimilation significantly improve the initial conditions and the accuracy of typhoon predictions. The study results contribute to the selection of appropriate combinations of physical parameterization schemes for the WRF-ARW model in the mid-latitude region of the western Pacific coast. Full article

The vertical mass exchange of ozone (O₃) plays an important role in determining surface O₃ air quality, the understanding of which, however, is greatly limited by the lack of continuous measurements in the vertical direction. Here, we characterize O₃ variations at a high-altitude monitoring site at the top of Shanghai Tower (SHT) and discuss the potential impacts of the vertical exchange of air pollutants on O₃ air quality within the urban planetary boundary layer (PBL) based on continuous measurements during 2017–2018. During the daytime, two distinct patterns of vertical O₃ gradient are detected. In summer, the daytime O₃ formation at SHT is observed to be more limited by nitrogen oxides (NO_x) than the surface, which, together with the efficient vertical mixings, results in higher O₃ levels in the upper mixing layer. In cold months, the opposite vertical gradient is observed, which is associated with weak vertical exchange and NO_x-saturated O₃ formation. A nighttime O₃ reservoir layer and consistent morning O₃ entrainments are detected all year round. These results provide direct evidence of the vertical mixings within the urban PBL, underscoring the pressing need for improving vertical resolution in near-surface layers of air quality models. Full article

The mechanism of aerosol pollution transport remains highly elusive owing to the myriad of influential factors. In this study, ground station data, satellite data, ground-based LiDAR remote sensing data, sounding data, ERA5 reanalysis and a backward trajectory model were combined to investigate the formation process and optical properties of winter aerosol pollution in Beijing and surrounding areas. The analysis of ground station data shows that compared to 2019 and 2021, the pandemic lockdown policy resulted in a decrease in the total number of pollution days and a decrease in the average concentration of particulate matter in the Beijing area in 2020. The terrain characteristics of the Beijing-Tianjin-Hebei (BTH) made it prone to northeast and southwest winds. The highest incidence of aerosol pollution in Beijing occurs in February and March during the spring and winter seasons. Analysis of a typical heavy aerosol pollution process in the Beijing area from 28 February to 5 March 2019 shows that dust and fine particulate matter contributed to the primary pollution; surface air temperature inversion and an average wind speed of less than 3 m/s were conducive to the continuous accumulation of pollutants, which was accompanied by the oxidation reaction of NO₂ and O₃, forming photochemical pollution. The heavy aerosol pollution was transmitted and diffused towards the southeast, gradually eliminating the pollution. Our results provide relevant research support for the prevention and control of aerosol pollution. Full article

Achieving ambitious climate targets, such as the 1.5 °C goal, demands significant financial commitment. While technical feasibility exists, the economic implications of delayed action and differing scenarios remain unclear. This study addresses this gap by analyzing the investment attractiveness and economic risks/benefits of different climate scenarios through a novel emissions cost budgeting model. A simplified model is developed using five global scenarios: announced policies (type 1 and 2), 2.0 °C, and 1.5 °C. A unit marginal abatement cost estimated the monetary value of avoided and unavoided emissions costs for each scenario. Net present value (NPV) and cost–benefit index (BI) were then calculated to compare the scenario attractiveness of the global emission budgets. The model was further applied to emissions budgets for China, the USA, India, and the European Union (EU). Increasing discount rates and gross domestic product (GDP) led to emission increases across all scenarios. The 1.5 °C scenario achieved the lowest emissions, while the baseline scenario showed the highest potential emissions growth (between 139.48% and 146.5%). Therefore, emphasis on the need for further financial commitment becomes important as the emissions’ abatement cost used as best case was estimated at USD 2.4 trillion per unit of 1 Gtons CO₂ equivalent (eq.). Policy delays significantly impacted NPV and BI values, showcasing the time value of investment decisions. The model’s behavior aligns with real-world observations, including GDP growth influencing inflation and project costs. The simplified model could be coupled to existing integrated assessment frameworks or models (IAMs) as none offer cost–benefit analysis of climate scenarios to the best of our knowledge. Also, the model may be used to examine the economic attractiveness of carbon reduction programs in various nations, cities, and organizations. Thus, the model and analytical approach presented in this work indicate promising applications. Full article

Herein, the absorption of CO₂ by the TMG-based (TMG: 1,1,3,3-tetramethylguanidine) ionic liquids (ILs) and the absorbents formed by TMG ILs and ethylene glycol (EG) is studied. The TMG-based ILs used are formed by TMG and 4-fluorophenol (4-F-PhOH) or carvacrol (Car), and their viscosities are low at 25 °C. The CO₂ uptake capacities of [TMGH][4-F-PhO] and [TMGH][Car] are low (~0.09 mol CO₂/mol IL) at 25 °C and 1.0 atm. However, the mixtures [TMGH][4-F-PhO]-EG and [TMGH][Car]-EG show much higher capacities (~1.0 mol CO₂/mol IL) than those of parent ILs, which is unexpected because of the low CO₂ capacity of EG (0.01 mol CO₂/mol EG) in the same conditions. NMR spectra and theoretical calculations are used to determine the reason for these unexpected absorption behaviors. The spectra and theoretical results show that the strong hydrogen bonds between the [TMGH]⁺ cation and the phenolate anions make the used TMG-based ILs unreactive to CO₂, resulting in the low CO₂ capacity. In the Ils-EG mixtures, the hydrogen bonds formed between EG and phenolate anions can weaken the [TMGH]⁺–anion hydrogen bond strength, so ILs-EG mixtures can react with CO₂ and present high CO₂ capacities. Full article

The importance of ElectroMagnetic Ion Cyclotron (EMIC) ultra-low-frequency (ULF) waves (and their Pc1 counterparts) is connected to their critical role in triggering energetic particle precipitation from the magnetosphere to the conjugated ionosphere via pitch angle scattering. In addition, as a prominent element of the ULF zoo, EMIC/Pc1 waves can be considered a perfect tool for the remote diagnosis of the topologies and dynamic properties of near-Earth plasmas. Based on the availability of a comprehensive set of instruments, operating on the ground and in the top-side ionosphere, the present case study provides an interesting example of the evolution of EMIC propagation to both ionospheric hemispheres up to the polar cap. Specifically, we report observations of Pc1 waves detected on 30 March 2021 under low Kp, low Sym-H, and moderate AE conditions. The proposed investigation shows that high-latitude ground magnetometers in both hemispheres and the first China Seismo-Electromagnetic Satellite (CSES-01) at a Low Earth Orbit (LEO) detected in-synch Pc1 waves. In strict correspondence to this, energetic proton precipitation was observed at LEO with a simultaneous appearance of an isolated proton aurora at subauroral latitudes. This supports the idea of EMIC wave-induced proton precipitation contributing to energy transfer from the magnetosphere to the ionosphere. Full article

Although cycling is the most prevalent means of locomotion in the world, little research has been done in evaluating the ultraviolet (UV) radiation exposure of cyclists. In this study, a volunteer using a men’s bike was equipped with 10 miniature UV-meters at different body sites. Besides erythemally effective irradiance, the ratio of personal UV exposure to ambient UV radiation was determined for solar elevations up to 65°, taking into account different orientations with respect to the sun. This method provides a universal model that allows for the calculation of UV exposure whenever ambient UV radiation and solar elevation are available. Our results show that the most exposed body sites are the back, forearm, upper arm, and anterior thigh, receiving between 50% and 75% of ambient UV radiation on average. For certain orientations, this percentage can reach 105% to 110%. However, the risk of UV overexposure depends on ambient UV radiation. At lower solar elevations (<40°), the risk of UV overexposure clearly decreases. Full article

The effects of emissions of diesel engines on black carbon and particle number concentrations, as well as climate-relevant aerosol properties, are explored for a summertime period in the Eastern U.S. using the chemical transport model PMCAMx-UF. A 50% reduction in diesel particulate emissions results in lower (23%) black carbon mass concentrations, as expected, and similar changes both in magnitude (27–30%) and spatial pattern for the absorption coefficient. However, an average 2% increase in the total particle number concentrations is predicted due to a decrease in the coagulation and condensation sinks and, at the same time, a 2% decrease in N₁₀₀ (particles larger than 100 nm) concentrations. The diesel reduction results suggest that mitigation of large diesel particles and/or particle mass emissions can reduce climate-relevant properties related to the absorption of black carbon and provide health benefits; however, the changes could also have the unintended effect of increased ultrafine particle number concentrations. Changes in cloud condensation nuclei are predicted to be significantly less than expected, assuming a proportional reduction during this photochemically active period. Doubling the diesel emissions results in a domain-averaged 3% decrease in total particle number concentrations and a 3% increase in N₁₀₀ concentrations. PM_2.5 BC concentrations increase on average by 46%, and similar changes (52–60%) are predicted for the absorption coefficient. Extinction coefficients for both perturbation simulations changed by only a few percent due to the dominance of scattering aerosols in the Eastern U.S. during this period characterized by high photochemical activity. Full article

The problem of atmospheric complex pollution led by PM_2.5 and O₃ has become an important factor restricting the improvement of air quality in China. In drawing on observations and Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model simulations, this study analyzed the characteristics and causes of a regional PM_2.5-O₃ complex pollution episode in North China Plain, in the period from 3 to 5 April 2019. The results showed that in static and stable weather conditions with high temperature and low wind speed, despite photochemical reactions of O₃ near the ground being weakened by high PM_2.5 concentrations, a large amount of O₃ generated through gas-phase chemical reactions at high altitudes was transported downwards and increased the O₃ concentrations at the ground level. The high ground-level O₃ could facilitate both the conversion of SO₂ and NO₂ into secondary inorganic salts and volatile organic compounds into secondary organic aerosols, thereby amplifying PM_2.5 concentrations and exacerbating air pollution. The contributions of transport from outside sources to PM_2.5 (above 60%) and O₃ (above 46%) increased significantly during the episode. This study will play an instrumental role in helping researchers to comprehend the factors that contribute to complex pollution in China, and also offers valuable references for air pollution management. Full article

Identifying the types and vertical distribution of aerosols plays a significant role in evaluating the influence of aerosols on the climate system. Based on the aerosol optical properties obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), this study analyzed the long-term aerosol characteristics of seven cities in East Asia (Ulaanbaatar, Beijing, Lanzhou, Shanghai, Lhasa, Hong Kong, and Bangkok) from 2007 to 2021, including the spatiotemporal variations of aerosol optical depth (AOD), the vertical stratification characteristics of aerosols, and the main aerosol subtype. The results showed that, except for Lhasa, the AOD values of all cities exhibited a trend of initially increasing and then decreasing over the years. Except for Shanghai, the high values of AOD in the other cities occurred in the spring and summer seasons, while the low values occurred in the autumn and winter seasons. In all four seasons, the AOD contribution within the 1–3 km range accounted for more than 50% of the total. In the autumn and winter seasons, this proportion reached over 80%. The main types of aerosols and their contributions varied at different altitudes. Overall, dust, polluted continental/smoke, polluted dust, and elevated smoke dominated in all aerosol layers across each city. On the other hand, clean marine, clean continental, and dusty marine had very small proportions, accounting for less than 5% of all the cities’ aerosol layers. Full article

In order to better understand the thermal comfort of urban parks and provide empirical reference for urban green space optimization design, 5 days’ field monitoring was conducted in People’s Park in Urumqi, an oasis city in an arid region of China. Combined with GIS spatial interpolation, correlation analysis, and regression analysis, the spatial and temporal distribution of thermal comfort (HI and WBGT) of urban parks was discussed. The results showed the following. (1) The thermal comfort in the morning was generally higher than that in the afternoon, and the thermal comfort near the water body and lush vegetation in the park was higher, while the thermal comfort on the road was lower, especially on Hotan Street and Binhenan Road, which were far away from the park. Therefore, it is recommended that nearby residents exercise outdoors in the morning as much as possible and in the park, and in the afternoon, keep to the park and its vicinity and try to sit quietly or walk slowly, avoiding the less comfortable areas, such as Hotan Road and Binhenan Road. (2) Due to dense vegetation and lack of infrastructure construction, the thermal comfort area does not have the conditions for crowd gathering. Therefore, it is recommended that the park improve the infrastructure of relevant areas. (3) Through the analysis of the significant influence of explanatory variables on the explained variables, it shows that the ventilation effect in the park is insufficient. Therefore, it is recommended to appropriately increase the number of trees, water bodies, and wind channels to promote ventilation in the park so as to improve the thermal comfort of the park. These findings provide a theoretical basis and technical reference for optimizing the thermal comfort of urban green space and establishing a healthier and more comfortable living environment for urban residents. Full article

Several investigations have proven the existence of monsoons in Indonesia. However, this has received little attention due to the scientific argument that the region of 10° N–10° S is not monsoonal because it receives precipitation all year round. This study used space–time SVD analysis of atmospheric and oceanic field data for 30 years (1990–2020) to detect monsoon signals and related features. The single-field SVD analysis of rainfall revealed that the first mode accounts for only 33% of the total variance, suggesting it is highly variable. Both the PC space and time series show the well-known monsoon pattern. Further, the Indonesian monsoon regimes and phases are defined based on the revealed rainfall features. The wet season lasts from November to April, accounting for more than 77% of annual precipitation. The coupled-field SVD analyses show that Indonesian monsoon rainfall strongly correlates with local SST (PC1 accounts for 70.4%), and the pattern is associated with the Asian winter monsoon. The heterogonous vector correlation map analysis revealed that the related features during the monsoon, including the strengthening and weakening of subtropical anticyclones, the intertwining of westerly wind in the Indian Ocean, and variations in the north–south dipole structure of the ocean temperature, are linked to variations in Indonesia’s monsoon rainfall. This result can serve as the dynamic basis for defining the Indonesian monsoon index in the context of the center of action. Full article

Regardless of the increasingly intensive application of vehicles with electric drives, internal combustion engines are still dominant as power units of mobile systems in various sectors of the economy. In order to reduce the emission of exhaust gases and satisfy legal regulations, as a temporary solution, hybrid drives with optimized internal combustion engines and their associated systems are increasingly being used. Application of the variable compression ratio and diesel fuel injection timing, as well as the tribological optimization of parts, contribute to the reduction in fuel consumption, partly due to the reduction in mechanical losses, which, according to test results, also results in the reduction in emissions. This manuscript presents the results of diesel engine testing on a test bench in laboratory conditions at different operating modes (compression ratio, fuel injection timing, engine speed, and load), which were processed using a zero-dimensional model of the combustion process. The test results should contribute to the optimization of the combustion process from the aspect of minimal particulate matter emission. As a special contribution, the results of tribological tests of materials for strengthening the sliding surface of the aluminum alloy piston and cylinder of the internal combustion engine and air compressors, which were obtained using a tribometer, are presented. In this way, tribological optimization should also contribute to the reduction in particulate matter emissions due to the reduction in fuel consumption, and thus emissions due to the reduction in friction, as well as the recorded reduction in the wear of materials that are in sliding contact. In this way, it contributes to the reduction in harmful gases in the air. Full article

Trajectory ensemble receptor models (TERMs) were widely used to determine the likely source locations and apportionment of air pollutants. This paper describes the development and applications of the Trajectory-ensemble Potential Source Apportionment Web application (TraPSA-Web), a comprehensive toolkit for likely atmospheric pollutant source location apportionments using TERMs and back trajectories generated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The TERMs integrated within the TraPSA-web include Concentration Field Analysis (CFA), Concentration Weighted Trajectory (CWT), single-site and multiple-site Potential Source Contribution Function (PSCF), and Simplified Quantitative Transport Bias Analysis (SQBA). TraPSA-Web is designed as a web application with a user-friendly modern graphical user interface (GUI), which largely enhances the accessibility to the users. TraPSA-Web will provide the air quality research community with a sophisticated toolkit for (1) easy management of the research project and datasets, (2) efficient automatization for HYSPLIT configurations, calculations, and result aggregations, (3) flexible configurations for the research scenarios and TERM parameters, and (4) interactive visualizations for the pollutant pattern analysis and TERM result mapping. Full article

The sun plays a crucial role as the primary source of energy for the Earth’s climate system and the issue of the influence of solar activity on the climate has been actively discussed recently. However, the precise impact of solar activity on extreme precipitation on the decadal timescale remains insufficiently confirmed. In this study, we investigate the relationship between summer extreme precipitation events exceeding 20 mm (R20mm) in China and the 11-year sunspot number (SSN) cycle from 1951 to 2018. Results showed that the first mode of June–July R20mm, a “south-drought and north-flooding (SDNF)” distribution, exhibited a significant correlation with the SSN cycle (p = 0.02). The fundamental driver is likely the pronounced periodic response of stratospheric ozone to solar forcing. During summer of the high-solar-activity years (HSY), there is a notable increase in ozone concentration and high temperatures in the stratosphere, particularly in the Southern Hemisphere. This phenomenon leads to a layer of anomalous temperature inversion, suppressing convection at the subtropics. This induced downward anomalous airflow toward the north stimulates convective activity in the equatorial region and generates northward wave activities. These wave activities produce rising and sinking anomalies at different latitudes in the Northern Hemisphere troposphere, finally causing the “SDNF” pattern in China. Full article

High-gravity wet dust removal technology has attracted much attention because of its potential to cut liquid into smaller liquid droplets and lower energy consumption. However, the complex structure and the high-speed rotation of the rotating packed bed do not allow us to analyze the flow field using conventional methods, and thus the capture mechanism of fine particles in a high-gravity environment is poorly understood. In this study, a two-dimensional computational fluid dynamics model was established to investigate the distribution of the gas–liquid two-phase flow field inside of a rotating packed bed. The characteristics of the flow field, such as the liquid form, gas–liquid contact time, and gas flow path, were investigated, and the droplet size distribution and gas–liquid slip velocity were quantitatively analyzed. The inertial capture efficiency was calculated using the Stokes number, and the dust removal efficiency distribution in the rotating packed bed was compared. The reason for the high collection efficiency of fine particles by the high-gravity wet dust removal technology was explained by numerical simulations. Two new structures were designed to improve the total dust removal efficiency. Full article

The study evaluated the ECMWF model ability in forecasting lightning in Portugal during four fire seasons (2019–2022). The evaluation was made based on lightning data from the national lightning detector network, which was aggregated into resolutions of 0.5° and 1° over 3 h periods and analyzed from statistical indices using two contingency tables. The results showed that the model overestimates the lightning occurrence, with a BIAS greater than 1, with a success rate of 57.7% (49%) for a horizontal resolution of 1° (0.5°). The objective analysis was complemented by the spatial lightning distribution analysis, which indicated a time lag between the two data, i.e., the model started predicting lightning before its occurrence and finished the prediction earlier. Furthermore, such analysis revealed the lightning distribution being consistent with some weather patterns. The findings of this study provide insights into the applicability of the ECMWF lightning forecast data in the context of forecasting natural forest fires in Portugal. Full article

Observational analyses reveal that a dominant mode in the South Asian Monsoon region in boreal summer is a westward-propagating synoptic-scale disturbance with a typical wavelength of 4000 km that is coupled with moistening and precipitation processes. The disturbances exhibit an eastward tilt during their development before reaching their maximum activity center. A 2.5-layer model that extends a classic 2-level quasi-geostrophic model by including a prognostic lower-tropospheric moisture tendency equation and an interactive planetary boundary layer was constructed. The eigenvalue analysis of this model shows that the most unstable mode has a preferred zonal wavelength of 4000 km, a westward phase speed of 6 m s⁻¹, an eastward tilt vertical structure, and a westward shift of maximum moisture/precipitation center relative to the lower-tropospheric vorticity center, all of which agree with the observations. Sensitivity experiments show that the moisture–vortex instability determines, to a large extent, the growth rate, while the baroclinic instability helps set up the preferred zonal scale. Ekman-pumping-induced vertical moisture advection prompts an in-phase component of perturbation moisture relative to the low-level cyclonic center, allowing the generation of available potential energy and perturbation growth, regardless of whether or not a low-level mean westerly is presented. In contrast to a previous study, the growth rate is reversely proportional to the convective adjustment time. The current work sheds light on understanding the moisture–vortex and the baroclinic instability in a monsoonal environment with a pronounced easterly vertical shear. Full article

Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe. Full article

Rainfall, or more generally the precipitation process (flux), is a clear example of chaotic variables resulting from a highly nonlinear dynamical system, the atmosphere, which is represented by a set of physical equations such as the Navier–Stokes equations, energy balances, and the hydrological cycle, among others. As a generalization of the Euclidean (ordinary) measurements, chaotic solutions of these equations are characterized by fractal indices, that is, non-integer values that represent the complexity of variables like the rainfall. However, observed precipitation is measured as an aggregate variable over time; thus, a physical analysis of observed fluxes is very limited. Consequently, this review aims to go through the different approaches used to identify and analyze the complexity of observed precipitation, taking advantage of its geometry footprint. To address the review, it ranges from classical perspectives of fractal-based techniques to new perspectives at temporal and spatial scales as well as for the classification of climatic features, including the monofractal dimension, multifractal approaches, Hurst exponent, Shannon entropy, and time-scaling in intensity–duration–frequency curves. Full article

Regional air quality and major sources can be reflected by dust. 87 dust samples in Nanchang (four residential areas and three roadside points) were collected, with particle size and carbon components determined to discuss the distribution characteristics and the sources. The distribution of dust particle size in different sampling areas was similar, composed mainly of particles larger than 10 μm (over 69.8%). Dust particle size showed a decreasing trend with increasing horizontal distance from the main road and vertical height from the ground. EC in road dust was higher than that in residential dust. EC outdoors was higher than EC indoors in the same area. OC in indoor dust was higher than that in atmospheric dust when there were obvious indoor OC emission sources. The main carbon fractions in residential dust were OC3 and EC1, and in road dust were EC2 and OC3. The distribution of carbon fractions showed that OC3 and EC2 were mainly affected by human activities and motor vehicle emissions, respectively. The ratio of OC/EC and SOC in dust decreased from autumn to winter. SOC in the dust of Nanchang was at a medium level compared to other cities/regions around world. Clustering analysis and principal component analysis indicated that combustion sources (coal and biomass combustion, etc.), motor vehicle exhaust sources (gasoline and diesel vehicles), and human sources (cooking fumes, cigarette smoking, etc.) were the main contributors to the carbon components in dust. Full article

Citizens in urban areas are affected by the urban heat island (UHI) effect, resulting in increased thermal heat compared to rural areas. This threat is exacerbated by global climate change. Therefore, it is necessary to assess human thermal comfort and risk for decision making. This is important for planners (climate resilience), the health sector (information for vulnerable people), tourism, urban designers (aesthetics), and building architects. Urban structures modify local meteorological parameters and thus human thermal comfort at the microscale. Knowledge of the pattern of a city’s UHI is typically limited. Based on previous research, generalized additive models (GAMs) were built to predict the spatial pattern of the UHI in the city of Karlsruhe. The models were trained with administrative, remotely sensed, and land use and land cover geodata, and validated with measurements in Freiburg. This identified the hot and cold spots and the need for further urban planning in the city. The model had some limitations regarding water bodies and anthropogenic heat production, but it was well suited for applications in mid-latitude cities which are not topographically characterized. The model can potentially be used for other cities (e.g., in heat health action plans) as the training data are freely available. Full article

Ensemble weather forecasting involves the integration of multiple simulations to improve the accuracy of predictions by introducing a probabilistic approach. It is difficult to accurately predict heavy rainfall events that cause flash floods and, thus, ensemble forecasting could be useful to reduce uncertainty in the forecast, thus improving emergency response. In this framework, this study presents the efforts to develop and assess a flash flood forecasting system that combines meteorological, hydrological, and hydraulic modeling, adopting an ensemble approach. The integration of ensemble weather forecasting and, subsequently, ensemble hydrological-hydraulic modeling can improve the accuracy of flash flood predictions, providing useful probabilistic information. The flash flood that occurred on 26 January 2023 in the Evrotas river basin (Greece) is used as a case study. The meteorological model, using 33 different initial and boundary condition datasets, simulated heavy rainfall, the hydrological model, using weather inputs, simulated discharge, and the hydraulic model, using discharge data, estimated water level at a bridge. The results show that the ensemble modeling system results in timely forecasts, while also providing valuable flooding probability information for 1 to 5 days prior, thus facilitating bridge flood warning. The continued refinement of such ensemble multi-model systems will further enhance the effectiveness of flash flood predictions and ultimately save lives and property. Full article

Sterile medical masks are essential in preventing infectious diseases. However, the ethylene oxide contained within these masks is a class I carcinogen. The standard method for measuring ethylene oxide is gas chromatography-mass spectrometry, which is not fit with the dynamic process of human inhalation. Thus, the amount of ethylene oxide volatilized from masks and inhaled by users is unknown. In this work, ethylene oxide was detected by using proton-transfer-reaction mass spectrometry, which can measure volatile quantities in milliseconds. We found that ethylene oxide was volatilized from masks during use. Within the first minute, the ethylene oxide concentration decreased by 84.65%, and then the rate of reduction gradually slowed. After 5 min, all ethylene oxide was effectively volatilized, and the average mass of ethylene oxide inhaled was 299.02 μg. We investigated three methods to reduce the concentration of ethylene oxide in masks before use: natural airing, shaking the mask, and blowing the mask with a hair dryer. The hair dryer method produced the best results: the ethylene oxide concentration decreased by 88.3% after only 10 s. The natural airing method was the least effective: the ethylene oxide concentration decreased by 60.7% even after 3 h. Full article

In this study, we reviewed smog chamber systems and methodologies used in secondary organic aerosol (SOA) formation studies. Many important chambers across the world have been reviewed, including 18 American, 24 European, and 8 Asian chambers. The characteristics of the chambers (location, reactor size, wall materials, and light sources), measurement systems (popular equipment and working principles), and methodologies (SOA yield calculation and wall-loss correction) are summarized. This review discussed key experimental parameters such as surface-to-volume ratio (S/V), temperature, relative humidity, light intensity, and wall effect that influence the results of the experiment, and how the methodologies have evolved for more accurate simulation of atmospheric processes. In addition, this review identifies the sources of uncertainties in finding SOA yields that are originated from experimental systems and methodologies used in previous studies. The intensity of the installed artificial lights (photolysis rate of NO₂ varied from 0.1/min to 0.40/min), SOA density assumption (varied from 1 g/cm³ to 1.45 g/cm³), wall-loss management, and background contaminants were identified as important sources of uncertainty. The methodologies developed in previous studies to minimize those uncertainties are also discussed. Full article

The impact of elevated air temperature and heat stress on human health is a global concern. It not only affects our well-being directly, but also reduces our physical work capacity, leading to negative effects on society and economic productivity. Climate change has already affected the climate in Luxembourg and, based on the results of regional climate models, extreme heat events will become more frequent and intense in the future. To assess historical conditions, the micro-scaleRayManPro 3.1 model was used to simulate the thermal stress levels for different genders and age classes based on hourly input data spanning the last two decades. For the assessment of future conditions, with a special emphasis on heat waves, a multi-model ensemble of regional climate models for different emission scenarios taken from the Coordinated Regional Climate Downscaling Experiment (CORDEX) was used. For both, the past and future conditions in Luxemburg, an increase in the heat stress levels was observed. Small differences for different age groups and genders became obvious. In addition to the increase in the absolute number of heat waves, an intensification of higher temperatures and longer durations were also detected. Although some indications of the adaptation to rising air temperatures can be observed for high-income countries, our results underscore the likelihood of escalating heat-related adverse effects on human health and economic productivity unless more investments are made in research and risk management strategies. Full article