Atmosphere

This study investigates the variations of middle and low latitude sporadic-E (Es) layers in response to a geomagnetic storm. Es layers are observed by five ionosondes located in the Eastern Asian sector. The critical frequencies of Es layers (foEs) at six stations increased in sequence from high latitude stations to low latitude stations after IMF/Bz turning southward. Lomb–Scargle analysis shows the amplification of semidiurnal oscillation amplitude in the vertical height of Es layers during geomagnetic disturbance. Modeling results of the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) show the enhancement of the wind field in the mesosphere and the lower thermosphere (MLT) region. Our study provides evidence that the enhanced wind field in the MLT region during the storm period could result in the enhancement of Es layers at middle and low latitude. Full article

In order to forecast some high intensity and rapidly changing phenomena, such as thunderstorms, heavy rain, and hail within 2 h, and reduce the influence brought by destructive weathers, this paper proposes a weather radar echo extrapolation method based on deep learning. The proposed method includes the design and combination of the data preprocessing, convolutional long short-term memory (Conv-LSTM) neuron and encoder–decoder model. We collect eleven thousand weather radar echo data in high spatiotemporal resolution, these data are then preprocessed before they enter the neural network for training to improve the data’s quality and make the training better. Next, the neuron integrates the structure and the advantages of convolutional neural network (CNN) and long short-term memory (LSTM), called Conv-LSTM, is applied to solve the problem that the full-connection LSTM (FC-LSTM) cannot extract the spatial information of input data. This operation replaced the full-connection structure in the input-to-state and state-to-state parts so that the Conv-LSTM can extract the information from other dimensions. Meanwhile, the encoder–decoder model is adopted due to the size difference of the input and output data to combine with the Conv-LSTM neuron. In the neural network training, mean square error (MSE) loss function weighted according to the rate of rainfall is added. Finally, the matrix “point-to-point” test method, including the probability of detection (POD), critical success index (CSI), false alarm ratio (FAR) and spatial test method contiguous rain areas (CRA), is used to examine the radar echo extrapolation’s results. Under the threshold of 30 dBZ, at the time of 1 h, we achieved 0.60 (POD), 0.42 (CSI) and 0.51 (FAR), compared with 0.42, 0.28 and 0.58 for the CTREC algorithm, and 0.30, 0.24 and 0.71 for the TITAN algorithm. Meanwhile, at the time of 1 h, we achieved 1.35 (total MSE ) compared with 3.26 for the CTREC algorithm and 3.05 for the TITAN algorithm. The results demonstrate that the radar echo extrapolation method based on deep learning is obviously more accurate and stable than traditional radar echo extrapolation methods in near weather forecasting. Full article

A climatology of Mesospheric Inversion Layers (MIL) has been created using the Rayleigh lidar located in the south of France at L’Observatoire de Haute Provence (OHP). Using criteria based on lidar measurement uncertainties and climatological mean gravity wave amplitudes, we have selected significant large temperature anomalies that can be associated with MILs. We have tested a novel approach for classifying MILs based on a k-mean clustering technique. We supplied different parameters such as the MIL amplitudes, altitudes, vertical extension, and lapse rate and allowed the computer to classify each individual MIL into one of three clusters or classes. For this first proof of concept study, we selected k = 3 and arrived at three distinct MIL clusters, each of which can be associated with different processes generating MILs in different regimes. All clusters of MIL exhibit a strong seasonal cycle with the largest occurrence in winter. The four decades of measurements do not reveal any long-term changes that can be associated with climate changes and only show an inter-annual variability with a quasi-decadal oscillation. Full article

Due to the particularity of the site selection of hydropower stations, the canyon wind with large fluctuations often occurs during the construction of the hydropower station, which will seriously affect the safety of construction personnel. Especially in the early stage of the construction of the hydropower station, the historical data and information on the canyon wind are scarce. Short-term forecasting of canyon wind speed has become extremely important. The main innovation of this paper is to propose a time series prediction method based on transfer learning. This method can achieve short-term prediction when there are few wind speed sample data, and the model is relatively simple while ensuring the accuracy of prediction. Considering the temporal and nonlinear characteristics of canyon wind speed data, a hybrid transfer learning model based on a convolutional neural network (CNN) and gated recurrent neural network (GRU) is proposed to predict short-term canyon wind speed with fewer observation data. In this method, the time sliding window is used to extract time series from historical wind speed data and temperature data of adjacent cities as the input of the neural network. Next, CNN is used to extract the feature vector from the input, and the feature vector can form time series. Then, the GRU network is used for short-term wind speed prediction by the time series. Experimental results show that the proposed method improves MAE and RMSE by nearly 20%, which will provide new ideas for the application of wind speed forecasting in canyons under complex terrain. The research contents of this paper contribute to the actual construction of hydropower stations. Full article

Atmospheric carbonyl sulfide (COS) was monitored at the GIF site (France) from August 2014 to November 2021. A significant decreasing trend in the seasonal cycle amplitude (SCA) of the COS was observed for the first time in the Northern Hemisphere (−27 ppt over 6 years). The lowest SCA was recorded in 2021 (80 ppt vs. 107 ppt in 2015). The trend in the SCA results revealed a steeper decline in the spring maximum than in that of the autumn minimum (−49 ppt vs. −10 ppt over 6 years, respectively). These negative trends were qualitatively consistent with those in the tropospheric COS put forward by the NDACC network of ground-based FTIR instruments, which were attributed to a slowing in the rate of COS anthropogenic emissions. Simulations using the ORCHIDEE land-surface model showed that a decrease in COS lowers the uptake of this gas by plants. Our observations suggest the existence of a causal relationship between the decline in the SCA and that in the tropospheric COS, implying that the temporal variations in the COS SCA over Western Europe are essentially driven by plant uptake. However, the transport by the LMDz 3-D model of surface fluxes for each component of the COS budget failed to reproduce this feature at GIF, pointing to a likely misrepresentation of the marine and anthropogenic fluxes in the footprint of this station. Full article

Air pollution dispersion over Durban is studied using satellite, reanalysis and in situ measurements. This coastal city of 4 million people located on the east coast of South Africa contributes 29 million T/yr of trace gases, mostly from transport and industry. Terrestrial and agricultural particulates derive from the Kalahari Desert, Zambezi Valley and Mozambique. Surface air pollutants accumulate during winter (May–August) and provide a focus for statistical analysis of monthly, daily and hourly time series since 2001. The mean diurnal cycle has wind speed minima during the land−sea breeze transitions that follow morning and evening traffic emissions. Daily air pollution concentrations (CO, NO₂, O₃, PM_2.5 and SO₂) vary inversely with dewpoint temperature and tend to peak during winter prefrontal weather conditions. Descending airflow from the interior highlands induces warming, drying and poor air quality, bringing dust and smoke plumes from distant sources. Spatial regression patterns indicate that winters with less dispersion are preceded by warm sea surface temperatures in the tropical West Indian Ocean that promote a standing trough near Durban. Statistical outcomes enable the short- and long-range prediction of atmospheric dispersion and risk of exposure to unhealthy trace gases and particulates. The rapid inland decrease of mean wind speed from 8 to 2 m/s suggests that emissions near the coast will disperse readily compared with in interior valleys. Full article

Dermal exposure to nicotine is common due to the widespread use of tobacco products. Here, we assessed the effects of nicotine at concentrations found in thirdhand smoke (THS) contaminated environments and electronic cigarette (EC) spills or leaks on a 3D human skin model (EpiDerm^TM) and on submerged keratinocyte cultures. Air liquid interface treatment of EpiDerm^TM with 10 or 400 μg/mL of nicotine for 24 h followed by proteomics analysis showed altered pathways related to inflammation, protein synthesis, cell–cell adhesion, apoptosis, and mitochondrial function. Submerged cultured keratinocytes were used to validate the proteomics data and further characterize the response of skin cells to nicotine. Mitochondrial phenotype changed from networked to punctate in keratinocytes treated with 10 or 400 μg/mL of nicotine for 48 h and 24 h, respectively. After 72 h, all concentrations of nicotine caused a significant decrease in the networked phenotype. In Western blots, keratinocytes exposed to 400 μg/mL of nicotine had a significant decrease in mitofusin 2, while mitofusin 1 decreased after 72 h. The shift from networked to punctate mitochondria correlated with a decrease in mitofusin 1/2, a protein needed to establish and maintain the networked phenotype. Mitochondrial changes were reversible after a 24 h recovery period. Peroxisomes exposed to 400 μg/mL of nicotine for 24 h became enlarged and were fewer in number. Nicotine concentrations in THS and EC spills altered the proteome profile in EpiDerm^TM and damaged organelles including mitochondria and peroxisomes, which are involved in ROS homeostasis. These changes may exacerbate skin infections, inhibit wound healing, and cause oxidative damage to cells in the skin. Full article

With global warming and the rapid development of urbanization, the outdoor thermal environment is deteriorating. More and more research focuses on the outdoor thermal environment and thermal comfort. The globe thermometer method is widely used in more than half of the outdoor thermal environment research studies, but there is a large error compared with the six-direction method. In order to explore the accuracy of the results of the globe thermometer method and its impact on the subsequent thermal comfort indicators, this study carried out a year-round comparative experiment under multiple working conditions outdoors in cold areas to explore the impact of meteorological parameters such as shortwave radiation, wind speed, and wind direction on the results of the globe thermometer method. The results show that the continuous increase of shortwave radiation reduces the accuracy of the black bulb thermometer to less than 60%, and the instantaneous change of wind speed will make the deviation of the mean radiation temperature obtained by the globe thermometer method exceed 5 °C. The influence of the mean radiation temperature obtained by the globe thermometer method on the thermal comfort index is mainly reflected in the working condition of a high temperature and strong radiation in summer. Taking the six-direction method as the standard, this study gives the scope of application of the globe thermometer method; and taking the human body calculation model of PET as an example, a universal optimization method for detailed division of radiation heat transfer calculation is proposed, so that it can get more accurate and rigorous conclusions in the evaluation of outdoor complex radiation environment. Full article

The rainfall regime is changing in the Catalan territory, likely in most areas in the Mediterranean Basin. This variability, spatial and temporal, means that there may be periods of severe drought combined with periods of heavy rainfall and floods. In this way, the management of water resources is complicated and can produce a high impact on different social aspects. The high convective activity leads to investigating the relationship between the electric discharges and radar parameters (reflectivity, echo top, vertically integrated liquid, and accumulated rainfall). The correlation allows identifying some elements that may be significant in terms of changes in rainfall regimes. Besides, using several radar parameters apart from precipitation accumulation reveals interesting explicit patterns of the previously known. These patterns can help better understand the precipitation behavior and the changes associated with it. Full article

Ionosphere disturbances are mainly caused by solar activities and earth surface activities. Different electromagnetic wave disturbances show different shapes on the spectrogram, such as artificial very low frequency transmitting stations, power systems, and satellite platform disturbances which all show a horizontal shape. Due to the electric field coupling or superposition by other electromagnetic disturbances, the horizontal electromagnetic wave clarity on the spectrogram is reduced, interrupted, or disappears. Aiming at this phenomenon, based on computer vision technology, this paper proposes an automatic detection and recognition algorithm for the space electric field abnormal interference. Firstly, the horizontal electromagnetic wave on the spectrogram is detected, and then the detected window density on the horizontal line is counted. We then record and save the density anomaly windows on multiple horizontal lines at the same time, so as to realize the electric field anomaly disturbance automatic detection. The accuracy of the algorithm for detecting continuous electromagnetic wave disturbance with a wide frequency and time interval is up to 98.2%. Through the space electromagnetic disturbances automatic identification from massive data, combined with space events and multi-dimensional information, such as time, space and orbit, it is helpful to further find out the global space-time transformation laws of space events. Full article

This study investigates the environmental Kuznets curve (EKC) for haze in 31 cities and provinces across China using the spatial data for a period of 15 years, from 2000 to 2014. We utilized the geographically weighted regression (GWR) model to consider the spatial non-stationary characteristics of the air quality in a vast territory. This approach allowed us to verify the region-specific characteristics, while the global model estimated the average relationship across the entire nation. Although the EKC for haze was statistically significant in the global models, the results only confirmed the existence of an EKC between the overall air quality and economic performance. Thus, it was difficult to determine the regional differences in an EKC. The results of the GWR model found the spatial variability of each variable and showed significant spatial heterogeneity in the EKC across regions. Although six regions—Beijing, Gansu, Heilongjiang, Jiangxi, Jilin, Liaoning, Shanghai, Tianjin, Xinjiang, and Zhejiang—showed inverted U-shaped EKCs, these were only statistically significant in three big cities—Beijing, Tianjin, and Shanghai. The results demonstrated no EKCs in the other 25 provinces and cities. These results provide strong empirical evidence that there is significant spatial heterogeneity in the EKC of China. Thus, a more regionally specialized air pollution control policy is required to create an effective policy for balanced economic growth in China. Full article

Thailand is located in the Southeast Asian region, where the summer rainfall exhibits strong interannual variability, and the successful simulation of rainfall variation in Thailand by current climate models remains a challenge. Therefore, this paper evaluates the capability of the state-of-the-art Atmospheric GCM of the Institute of Atmospheric Physics (IAP-AGCM) in simulating summer rainfall over Thailand by comparing the model’s results with ground-truth observation during 1981–2012. Generally, the model shows a certain skill in reproducing the observed spatial distribution of the summer rainfall climatology and its interannual variability over Thailand, although the model underestimated both rainfall amount and its variability. Using Empirical Orthogonal Function (EOF) analysis, it is found that the IAP climate model reproduced creditably the spatial patterns of the first three dominant modes of summer rainfall in Thailand, whereas it underestimated the explained variance of the observed EOF-1 and overestimated the explained variance of the observed EOF-2 significantly. It was further found that the correlation between the observed rainfall anomalies in Thailand and the Niño3.4 index can be reproduced by the IAP model. However, the observed negative correlation is largely underestimated by the IAP climate model, and this could be the reason for the underestimation of explained variance of the EOF-1 by the IAP model. The evaluation results would be of great importance for further model improvement and thus potential application in seasonal prediction in the region. Full article

In recent years, industries such as oil and gas production, waste management, and renewable natural gas/biogas have made a concerted effort to limit and offset anthropogenic sources of methane emissions. However, the state of emissions, what is emitting and at what rate, is highly variable and depends strongly on the micro-scale emissions that have large impacts on the macro-scale aggregates. Bottom-up emissions estimates are better verified using additional independent facility-level measurements, which has led to industry-wide efforts such as the Oil and Gas Methane Partnership (OGMP) push for more accurate measurements. Robust measurement techniques are needed to accurately quantify and mitigate these greenhouse gas emissions. Deployed on both fixed-wing and multi-rotor unmanned aerial vehicles (UAVs), a miniature tunable diode laser absorption spectroscopy (TDLAS) sensor has accurately quantified methane emissions from oil and gas assets all over the world since 2017. To compare bottom-up and top-down measurements, it is essential that both values are accompanied with a defensible estimate of measurement uncertainty. In this study, uncertainty has been determined through controlled release experiments as well as statistically using real field data. Two independent deployment methods for quantifying methane emissions utilizing the in situ TDLAS sensor are introduced: fixed-wing and multi-rotor. The fixed-wing, long-endurance UAV method accurately measured emissions with an absolute percentage difference between emitted and mass flux measurement of less than 16% and an average error of 6%, confirming its suitability for offshore applications. For the quadcopter rotary drone surveys, two flight patterns were performed: perimeter polygons and downwind flux planes. Flying perimeter polygons resulted in an absolute error less than 36% difference and average error of 16.2%, and downwind flux planes less than 32% absolute difference and average difference of 24.8% when flying downwind flux planes. This work demonstrates the applicability of ultra-sensitive miniature spectrometers for industrial methane emission quantification at facility level with many potential applications. Full article

The problem of low efficiency of coal mine methane utilization is caused by the concentration of methane of less than 10%, or a concentration that varies dramatically directly emitted into the atmosphere. This work deals with the concept of a co-production system that blends lean methane and biogas to produce electric energy. It is recommended to add the biogas generated by straws around the mines in a controlled manner to the lean methane flow to obtain the desired gas concentration in order to generate electricity. Potential electricity generation and reduced greenhouse gas emissions were also evaluated. The result shows that the co-production system can significantly improve the utilization efficiency of lean methane in coal mines; the average use of pure methane in three coal mines is 0.18, 1.12, and 5.32 million m³ every year, respectively, and the emission reduction effect of carbon dioxide (CO₂) equivalent is, respectively, 3081, 18,796, and 89,050 tons. The electricity generated and the economic environmental benefits of the co-production system are remarkable, and it has economic feasibility and broad perspectives for popularization. It not only has the advantage of improving the utilization rate of methane and biomass and providing power supply and heat source for mines, but also has practical significance in terms of saving energy, reducing environmental pollution, adjusting the energy structure, and achieving the target of carbon emission peak and carbon neutrality. Full article

Aged refuse with a landfill age of 1.5 years was collected from a municipal solid waste landfill with high kitchen waste content and mixed with soil as biocover material for landfill. A series of laboratory batch tests was performed to determine the methane oxidation potential and optimal mixing ratio of landfill cover soil modified with aged refuse, and the effects of water content, temperature, CO₂/CH₄, and O₂/CH₄ ratios on its methane oxidation capacity were analyzed. The microbial community analysis of aged refuse showed that the proportions of type I and type II methane-oxidizing bacteria were 56.27% and 43.73%, respectively. Aged refuse could significantly enhance the methane oxidation potential of cover soil, and the optimal mixing ratio was approximately 1:1. The optimal temperature and water content were about 25 °C and 30%, respectively. Under the conditions of an initial methane concentration of 15% and an O₂/CH₄ ratio of 0.8–1.2, the measured methane oxidation rate was negatively correlated with the O₂/CH₄ ratio. The maximum methane oxidation capacity measured in the test reached 308.5 (μg CH₄/g)/h, indicating that the low-age refuse in the landfill with high kitchen waste content is a biocover material with great application potential. Full article

Snow covers are very sensitive to contamination from soot agglomerates derived from vehicles. A spectroradiometric system covering a wavelength from 300 to 2500 nm with variable resolution (from 2.2 to 7.0 nm) was used to characterize the effect of soot derived from a diesel vehicle whose exhaust stream was oriented towards a limited snowed area. The vehicle was previously tested in a rolling test bench where particle number emissions and size distributions were measured, and fractal analysis of particle microscopic images was made after collecting individual agglomerates by means of an electrostatizing sampler. Finally, the experimental results were compared to modelled results of contaminated snow spectral albedo obtained with a snow radiative transfer model developed by our research group (OptiPar) and with other models. Both experimental and modelled results show that increasingly accumulated soot mass reduces the snow albedo with a constant rate of around 0.03 units per mg/kg, with a predominant effect on the UV-VIS range. Based on the small size of the primary particles (around 25 nm), the Rayleigh-Debye-Gans approximation, further corrected to account for the effect of multiple scattering within the agglomerates, was revealed as an appropriate technique in the model. Full article

Aims: With the ongoing pandemic and increased interest in measures to improve indoor air quality, various indoor air purifiers have become very popular and are widely used. This review presents the advantages and disadvantages of various types of technologies used in air purifiers in terms of reducing microbial contamination. Methods: A literature search was performed using Web of Science, Scopus, and PubMed, as well as technical organizations dealing with indoor air-quality to identify research articles and documents within our defined scope of interest. Relevant sections: The available literature data focus mainly on the efficiency of devices based on tests conducted in laboratory conditions with test chambers, which does not reflect the real dimensions and conditions observed in residential areas. According to a wide range of articles on the topic, the actual effectiveness of air purifiers is significantly lower in real conditions than the values declared by the manufacturers in their marketing materials as well as technical specifications. Conclusions: According to current findings, using indoor air purifiers should not be the only measure to improve indoor air-quality; however, these can play a supporting role if their application is preceded by an appropriate technical and environmental analysis considering the real conditions of its use. Full article

The South-to-North Water Diversion Project (SNWDP) is a national strategic project for water shortages in northern China. Climate change will affect the availability of water resources in both source and receiving areas. A grid-based RCCC-WBM model based on climate projections from nine Global Climate Models under SSP2-4.5 was used for analyzing the changes in temperature, precipitation, and streamflow in the near future (2025–2045, NF) and far future (2040–2060, FF) relative to the baseline (1956–2000). The results showed that: (1) the temperature of the western route will increase significantly in the NF and FF with an extent of 1.6 °C and 2.0 °C, respectively, (2) precipitation will very likely increase even though Global Climate Model (GCM) projections are quite dispersed and uncertain, and (3) over half of the GCMs projected that streamflow of receiving area will slightly increase with a rate of 1.68% [−8.67%, 12.3%] and 2.78% [−3.30%, 11.0%] in the NF and FF, respectively. Climate change will support the planning of the western route to a certain extent. However, water supply risk induced by the extreme situation of climate change should be paid adequate consideration when the project operates in practice due to the large dispersion and uncertainty of GCM projections. Full article

In recent decades, a new generation of waste treatment plants based on biological treatments (mainly anaerobic digestion and/or composting) has arisen all over the world. These plants have been progressively substituted for incineration facilities and landfills. Although these plants have evident benefits in terms of their environmental impact and higher recovery of material and energy, the release into atmosphere of malodorous compounds and its mitigation is one of the main challenges that these plants face. In this review, the methodology to determine odors, the main causes of having undesirable gaseous emissions, and the characterization of odors are reviewed. Finally, another important topic of odor abatement technologies is treated, especially those related to biological low-impact processes. In conclusion, odor control is the main challenge for a sustainable implementation of modern waste treatment plants. Full article