Lake Baikal—a unique ecosystem on a global scale—is undoubtedly of great interest for a comprehensive study of its ecosystem. In recent years, one of the most significant sources of atmospheric pollution in the Baikal region was the emission of smoke aerosol and trace gases from forest fires, the number of which is increasing in the region. The transport and accumulation of aerosol and small gas impurities over water area of Lake Baikal is observed every summer due to forest fires occurring in the boreal forests of Siberia. The atmosphere above the lake covers a huge area (31,500 km²) and is still a little-studied object. This article presents the results of experimental studies of ground-level ozone, sulfur dioxide, and nitrogen oxides in the atmosphere over Lake Baikal, carried out on a research vessel during the boreal forest fires in Siberia in the summer of 2019. Full article

Environmental microbial contamination in the operating room (OR) can favour contamination of the surgical wound, posing the risk of infection of the surgical site. Thus, environmental monitoring is a useful tool for assessing environmental health and the effectiveness and efficiency of the measures adopted to control the risk of infection in the OR. This work aimed to analyse the long term environmental quality of 18 ORs throughout Sardinia, Italy, through the quantitative and qualitative characterisation of the microbial flora present in the air and on surfaces, in order to evaluate the trend over time, including in relation to any control measures adopted. The results of the sampling carried out in the period from January 2010 to December 2019 have been extrapolated from the archive-database of the Laboratory of the Hygiene and Control of Hospital Infections Unit of the University Hospital in Sassari. During the period in question, 188 air evaluations were carried out, both in empty rooms and during surgery, and 872 surface samples were taken. When the air was monitored, it emerged that significant contamination was detectable in a reduced number of examinations and a limited number of rooms. Microbial load values higher than the reference values may have been mainly determined by sub-optimal operation/maintenance of the air conditioning system. Surface testing showed a good level of sanitisation, given the low percentage of non-compliant values detected. The possibility of having data available on environmental quality is a useful educational and training tool both for those responsible for sanitisation procedures and the surgical team, in order to increase awareness of the effects of a lack of compliance with behavioural standards. Full article

With the rapid deployment of utility-scale photovoltaic (PV) plants, the impact of PV plants on the environment is a new concern of the scientific and social communities. The exchange of sensible and latent heat energy and mass between land and air in PV plants is crucial to understanding its impact. It is known that the near surface turbulence characteristics rule the exchange. Therefore, it is essential for understanding the impact to study the characteristics of near surface turbulence. However, it is not well recognized. Turbulent fluxes and strength characteristics for the PV plant and the adjacent reference site in the Xinjiang Gobi area were investigated in this study. Various surface layer parameters including friction velocity, stability parameter, momentum flux, and turbulent flux were calculated using eddy correlation system. Results indicate that compared to the reference site, near the surface boundary layer was more unstable during the daytime due to the stronger convection heating, while it was more stable at night in the PV plant. In the PV plant, $I_{\mathrm{u}}$ was weakened and $I_{\mathrm{v}}$ was strengthened during the daytime, and $I_{\mathrm{u}}$ and $I_{\mathrm{v}}$ were all weakened at night, while $I_{\mathrm{w}}$ was strengthened across the whole day. The significant difference between $I_{\mathrm{u}}$ and $I_{\mathrm{v}}$ in the PV plant indicated that the horizontally turbulence strengths were affected by the plant layout. The turbulent kinetic energy of the PV plant was lower than the reference site and the momentum in the PV plant was higher than the reference site, especially during the daytime. Compared to the reference site, the PV plant had a higher sensible heat flux and less latent heat flux. The turbulent components of wind followed the 1/3 power law in the unstable conditions and stable conditions in the PV plant and the reference site. Full article

The atmospheric oxidation of monoterpenes leads to the formation of secondary organic aerosol (SOA). While numerous works have been carried out in the past to characterise SOA at a molecular level, the structural elucidation of SOA compounds remains challenging owing to the lack of authentic standard compounds. In this work, the structures of α-pinene originating dimeric esters in SOA with m/z 357 (C₁₇H₂₅O₈^-) and m/z 367 (C₁₉H₂₇O₇^-) were characterised using UPLC/ESI(-)IMS-TOFMS² (ultra-performance liquid chromatography coupled to ion mobility spectrometry tandem time-of-flight mass spectrometry). The measured collision cross-section (Ω_N2) values were compared to theoretically calculated Ω_N2 values. Selected product ions of dimeric compounds and the authentic standard compounds of product ions were subjected to CO₂-IMS-TOFMS for more detailed structural characterisation. Our results were consistent with previously reported subunits of the m/z 357 (terpenylic acid and cis-pinic acid), and the m/z 367 (10-hydroxy-cis-pinonic acid and cis-pinic acid) ions. The measured and calculated Ω_N2 values of m/z 367 ions further support the conclusion of earlier structural characterisation; however, the structure of the m/z 357 ion remains vague and requires further characterisation studies with a synthesised reference compound. Full article

Hydrological processes are a key component of land surface models and link to the energy budget and carbon cycle. This study assessed the global hydrological processes of the Atmosphere–Vegetation Interaction Model (AVIM) using multiple datasets, including the Global Land Data Assimilation System (GLDAS), the University of New Hampshire and Global Runoff Data Centre (UNH-GRDC), the European Space Agency (ESA) Climate Change Initiative (CCI), the Global Land Evaporation Amsterdam Model (GLEAM), and the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) datasets. The comparisons showed that the AVIM gives a reasonable spatial pattern for surface soil moisture and surface runoff, but a less satisfactory spatial pattern for evapotranspiration. The AVIM clearly underestimates surface runoff worldwide and overestimates the surface soil moisture in the high latitudes of the Northern Hemisphere, while yielding moderately higher evapotranspiration in arid areas and lower evapotranspiration in low-latitude areas near the equator. The annual cycle of evapotranspiration in the AVIM shows good agreement with the GLEAM dataset, whereas the surface soil moisture in the AVIM has a poor annual cycle relative to the CCI dataset. The AVIM simulates a late start time for snowmelt, which leads to a two-month delay in the peak surface runoff. These results clearly point out the directions required for improvements in the AVIM, which will support future investigations of water–carbon–atmosphere interactions. In addition, the evapotranspiration in the MERRA-2 dataset had an overall good performance comparable with that of the GLEAM dataset, but its surface soil moisture did not perform well when validated against the CCI dataset. Full article

Reference crop evapotranspiration (ET₀) is an important indicator for precise regulation of crop water content, irrigation forecast formulation, and regional water resources management. The Hargreaves model (HG) is currently recognized as the simplest and most effective ET₀ estimation model. To further improve the prediction accuracy of the HG model, this study is based on the data of 98 meteorological stations in southwest China (1961–2019), using artificial bee colony (ABC), differential evolution (DE) and particle swarm optimization (PSO) algorithms to calibrate the HG model globally. The standard ET₀ value was calculated by FAO-56 Penman–Monteith (PM) model. We compare the calculation accuracy of 3 calibrated HG models and 4 empirical models commonly used (Hargreaves, Priestley–Taylor, Imark–Allen and Jensen–Hais). The main outcomes demonstrated that on a daily scale, the calibrated HG models (R² range 0.74–0.98) are more accurate than 4 empirical models (R² range 0.55–0.84), and ET_0-PSO-HG has the best accuracy, followed by ET_0-ABC-HG and ET_0-DE-HG, with average R² of 0.83, 0.82 and 0.80, average RRMSE of 0.23 mm/d, 0.25 mm/d and 0.26 mm/d, average MAE of 0.52 mm/d, 0.53 mm/d and 0.57 mm/d, and average GPI of 0.17, 0.05, and 0.04, respectively; on a monthly scale, ET_0-PSO-HG also has the highest accuracy, followed by ET_0-ABC-HG and ET_0-DE-HG, with median R² of 0.96, 0.95 and 0.94, median RRMSE of 0.16 mm/d, 0.17 mm/d and 0.18 mm/d respectively, median MAE of 0.46 mm/d, 0.50 mm/d, and 0.55 mm/d, median GPI of 1.12, 0.44 and 0.34, respectively. The calibrated HG models (relative error of less than 10.31%) are also better than the four empirical models (relative error greater than 16.60%). Overall, the PSO-HG model has the most accurate ET₀ estimation on daily and monthly scales, and it can be suggested as the preferred model to predict ET₀ in humid regions in southwest China regions. Full article

Planetary-scale 4-day Kelvin-type waves at the cloud top of the Venus atmosphere have been reported from the 1980s, and their significance for atmospheric dynamics has been pointed out. However, these waves have not been reproduced in Venus atmospheric general circulation models (VGCMs). Recently, horizontal winds associated with the planetary-scale waves at the cloud top have been obtained from cloud images taken by cameras onboard Venus orbiters, which could enable us to clarify the structure and roles of Kelvin-type waves. In order to examine this possibility, our team carried out an idealized observing system simulation experiment (OSSE) with a data assimilation system which we developed. The wind velocity data provided by a CCSR/NIES (Center for Climate System Research/National Institute for Environmental Studies) VGCM where equatorial Kelvin-type waves were assumed below the cloud bottom was used as idealized observations. Results show that 4-day planetary-scale Kelvin-type waves are successfully reproduced if the wind velocity between 15° S and 15° N latitudes is assimilated every 6 h at 70 km altitude. It is strongly suggested that the Kelvin-type waves could be reproduced and investigated by the data assimilation with the horizontal wind data derived from Akatsuki ultraviolet images. The present results also contribute to planning future missions for understanding planetary atmospheres. Full article

Atmospheric new particle formation (NPF) events taking place over large distances between locations, featuring similar characteristics, have been the focus of studies during the last decade. The exact mechanism which triggers NPF still remains indefinable, so are the circumstances under which simultaneous occurrence of such events take place in different environments, let alone in environments which are parted by over 1200 km. In this study, concurrent number size distribution measurements were conducted in the urban environments of Athens (Greece) and Amman (Jordan) as well as the regional background site of Finokalia, Crete, all located within a distance of almost 1300 km for a 6-month period (February–July 2017). During the study period Athens and Finokalia had similar occurrence of NPF (around 20%), while the occurrence in Amman was double. When focusing on the dynamic characteristics at each site, it occurs that formation and growth rates at Amman are similar to those at Finokalia, while lower values in Athens can be ascribed to a higher pre-existing particle number at this urban site. By comparing common NPF events there are 5 concomitant days between all three sites, highly related to air masses origin. Additionally, for another 19 days NPF takes place simultaneously between Finokalia and Amman, which also share common meteorological characteristics, adding to a total of 60% out of 41 NPF events observed at Finokalia, also simultaneously occurring in Amman. Full article

The paper considers a new approach to modeling the relationship between the increase in woody phytomass in the pine forest and satellite-derived Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) (MODIS/AQUA) data. The developed model combines the phenological and forest growth processes. For the analysis, NDVI and LST (MODIS) satellite data were used together with the measurements of tree-ring widths (TRW). NDVI data contain features of each growing season. The models include parameters of parabolic approximation of NDVI and LST time series transformed using principal component analysis. The study shows that the current rate of TRW is determined by the total values of principal components of the satellite indices over the season and the rate of tree increment in the preceding year. Full article

Wildfires can have rapid and long-term effects on air quality, human health, climate change, and the environment. Smoke from large wildfires can travel long distances and have a harmful effect on human health, the environment, and climate in other areas. More recently, in 2018–2019 there have been many large fires. This study focused on the wildfires that occurred in the United States of America (USA), Brazil, and Australia using Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) and a TROPOspheric Monitoring Instrument (TROPOMI). Specifically, we analyzed the spatial-temporal distribution of black carbon (BC) and carbon monoxide (CO) and the vertical distribution of smoke. Based on the results, the highest detection of smoke (~14 km) was observed in Brazil; meanwhile, Australia showed the largest BC column burden of ~1.5 mg/m². The meteorological conditions were similar for all sites during the fires. Moderate temperatures (between 32 and 42 °C) and relative humidity (30–50%) were observed, which resulted in drier conditions favorable for the burning of fires. However, the number of active fires was different for each site, with Brazil having 13 times more active fires than the USA and five times more than the number of active fires in Australia. However, the high number of active fires did not translate to higher atmospheric constituent emissions. Overall, this work provides a better understanding of wildfire behavior and the role of meteorological conditions in emissions at various sites. Full article

The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), on-board the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) platform, is an elastic backscatter lidar that has been providing vertical profiles of the spatial, optical, and microphysical properties of clouds and aerosols since June 2006. Distinguishing between feature types (i.e., clouds vs. aerosol) and subtypes (e.g., ice clouds vs. water clouds and dust aerosols from smoke) in the CALIOP measurements is currently accomplished using layer-integrated measurements acquired by co-polarized (parallel) and cross-polarized (perpendicular) 532 nm channels and a single 1064 nm channel. Newly developed deep machine learning (DML) semantic segmentation methods now have the ability to combine observations from multiple channels with texture information to recognize patterns in data. Instead of focusing on a limited set of layer integrated values, our new DML feature classification technique uses the full scope of range-resolved information available in the CALIOP attenuated backscatter profiles. In this paper, one of the convolutional neural networks (CNN), SegNet, a fast and efficient DML model, is used to distinguish aerosol subtypes directly from the CALIOP profiles. The DML method is a 2D range bin-to-range bin aerosol subtype classification algorithm. We compare our new DML results to the classifications generated by CALIOP’s 1D layer-to-layer operational retrieval algorithm. These two methods, which take distinctly different approaches to aerosol classification, agree in over 60% of the comparisons. Higher levels of agreement are found in homogeneous scenes containing only a single aerosol type (i.e., marine, stratospheric aerosols). Disagreement between the two techniques increases in regions containing mixture of different aerosol types. The multi-dimensional texture information leveraged by the DML method shows advantages in differentiating between aerosol types based on their classification scores, as well as in distinguishing vertical distributions of aerosol types within individual layers. However, untangling mixtures of aerosol subtypes is still challenging for both the DML and operational algorithms. Full article

In order to optimize the management of groundwater resources, accurate estimates of groundwater level (GWL) fluctuations are required. In recent years, the use of artificial intelligence methods based on data mining theory has increasingly attracted attention. The goal of this research is to evaluate and compare the performance of adaptive network-based fuzzy inference system (ANFIS) and Wavelet-ANFIS models based on FCM for simulation/prediction of monthly GWL in the Maragheh plain in northwestern Iran. A 22-year dataset (1996–2018) including hydrological parameters such as monthly precipitation (P) and GWL from 25 observation wells was used as models input data. To improve the prediction accuracy of hybrid Wavelet-ANFIS model, different mother wavelets and different numbers of clusters and decomposition levels were investigated. The new hybrid model with Sym4-mother wavelet, two clusters and a decomposition level equal to 3 showed the best performance. The maximum values of R2 in the training and testing phases were 0.997 and 0.994, respectively, and the best RMSE values were 0.05 and 0.08 m, respectively. By comparing the results of the ANFIS and hybrid Wavelet-ANFIS models, it can be deduced that a hybrid model is an acceptable method in modeling of GWL because it employs both the wavelet transform and FCM clustering technique. Full article

Daily solar radiation is a critical input for estimating plant growth and development, yet this variable is infrequently measured compared to other climate variables. This study evaluates the sensitivity of simulated maize and soybean production from the CERES-Maize and CROPGRO-Soybean modules of the Decision Support System for Agrotechnology Transfer (DSSAT) to daily solar radiation estimates obtained from traditional (stochastic, empirical, and mechanistic models) and non-traditional (satellite estimation, reanalysis datasets, and regional climate model simulations) approaches, using as an example radiation estimates for Hancock, Wisconsin, USA. When compared to observations, radiation estimates obtained from empirical and mechanistic models and a satellite-based dataset generally had smaller biases than other approaches. Daily solar radiation estimates from a reanalysis dataset and regional climate model simulations overestimate incoming daily solar radiation. When the radiation estimates were used as an input to CERES-Maize, no significant differences were found for maize yield obtained from the different radiation estimates compared to yield from observed radiation, even though differences were found in the daily values of leaf area index, crop evapotranspiration, and crop dry weight (biomass). In contrast, significant differences were found in simulated soybean yield from CROPGRO-Soybean for the majority of the radiation estimates. Full article

The Great Plains low-level jet (LLJ) is a contributing factor to the initiation and evolution of nocturnal Mesoscale Convective Systems (MCSs) in the central United States by supplying moisture, warm air advection, and a source of convergence. Thus, the ability of models to correctly depict thermodynamics in the LLJ likely influences how accurately they forecast MCSs. In this study, the Weather Research and Forecasting (WRF) model was used to examine the relationship between spatial displacement errors for initiating simulated MCSs, and errors in forecast thermodynamic variables up to three hours before downstream MCS initiation in 18 cases. Rapid Update Cycle (RUC) analyses in 3 layers below 1500 m above ground level were used to represent observations. Correlations between simulated MCS initiation spatial displacements and errors in the magnitude of forecast thermodynamic variables were examined in regions near and upstream of both observed and simulated MCSs, and were found to vary depending on the synoptic environment. In strongly-forced cases, large negative moisture errors resulted in simulated MCSs initiating further downstream with respect to the low-level flow from those observed. For weakly-forced cases, correlations were weaker, with a tendency for smaller negative moisture errors to be associated with larger displacement errors to the right of the inflow direction for initiating MCSs. Full article

Climate change might increase the frequency and severity of longer-lasting drought in the Caribbean, including in Hispaniola Island. Nevertheless, the hydroclimate changes projected by the state-of-the-art earth system models across the island remain unknown. Here, we assess 21st-century changes in hydroclimate over Hispaniola Island using precipitation, temperature, and surface soil moisture data from the 6th Phase of the Coupled Model Intercomparison Project (CMIP6). The resulting analysis indicates, as with the previous 5th Phase of CMIP (CMIP5) models, that Hispaniola Island might see a significant drying through the 21st century. The aridity appears to be robust in most of the island following the Shared Socioeconomic Pathways (SSP) 5–8.6, which assumes the “worst case” greenhouse gas emissions into the atmosphere. We find a significant reduction in both annual mean precipitation and surface soil moisture (soil’s upper 10 cm), although it appears to be more pronounced for precipitation (up to 26% and 11% for precipitation and surface soil moisture, respectively). Even though we provide insights into future hydroclimate changes on Hispaniola Island, CMIP6’s intrinsic uncertainties and native horizontal resolution precludes us to better assess these changes at local scales. As such, we consider future dynamical downscaling efforts that might help us to better inform policy-makers and stakeholders in terms of drought risk. Full article