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An earthquake with a magnitude ranging from Mw = 6.9 (KOERI) to Mw = 7.0 (USGS) struck Samos Island in the Aegean Sea on October 30, 2020, with an epicentre 70 kms from the Izmir city centre in Turkey. The earthquake took place at 14:51 local time (11:51 UTC). The peak ground acceleration (PGA) of this earthquake was recorded to be 0.179 g at the epicentre of the earthquake. This earthquake occurred at a depth of 17.26 km (AFAD (2020) Izmir Earthquake Report, (In Turkish)) and lasted 16 s. The main shock from the earthquake triggered a tsunami that hit the building stocks built near the coast. During the gradual deregulation of COVID-19 pandemic regulations, various events caused considerable damage to the building stock, particularly in the Izmir Seferihisar and Bayrakli regions and resulted in a massive disruption of daily habits. The main shock caused 117 deaths in both Turkey and Greece, and 1632 people were also injured in Turkey. Moreover, several injuries occurred in Greece. A total of 103 buildings collapsed, 700 were severely damaged, 814 buildings were moderately damaged, and 7889 were slightly damaged. The basic aim of this paper is to briefly present the past and present seismotectonic characteristics of the region, present building stock, and former structural conditions before the earthquake, assess structural performance and classify distinguished earthquake-induced failures and damage due to the basin effect.

The conservation of water resources in developed countries has become an increasing concern. In integrated water resource management, water quality indicators are critical. The low groundwater quality quantitates mainly attributed to the absence of protection systems for polluted streams that collect and recycle the untreated wastewater. Egypt has a limited river network; thus, the supply of water resources remains inadequate to satisfy domestic demand. In this regard, high-quality groundwater is one of the main strategies for saving water supplies with water shortage problems. This paper investigates the critical issues of groundwater protection and environmental management of polluted streams, leading to overcoming water demand-about 18 × 103 km of polluted open streams with a discharge of 9.70 billion Cubic Metter (BCM). We have proposed proposals and policies for the safe use of groundwater and reuse of wastewater recycling for agriculture and other purposes. This study was carried out using the numerical model MODFLOW and MT3DMS—(Mass Transport 3-Dimension Multi-Species) to assess the Wastewater Treated Plant's (WWTP) best location and the critical path for using different lining materials of polluted streams to avoid groundwater contamination. The three contaminants are BOD, COD, and TDS. Five scenarios were applied for mitigating the impact of polluted water: (1) abstraction forcing, (2) installing the WWTP at the outlet of the main basin drain with and without a lining of main and sub-basin streams (base case), (3) lining of main and sub-main streams, (4) installing WWTP at the outlet of the sub-basin streams, and (5) lining of the sub-basin and installing WWTP at the outlet of the sub-basin. The results showed that the best location of WWTP in polluted streams is developed at the outlets of sub-basin with the treatment of main basin water and the lining of sub-basins streams. The contamination was reduced by 76.07, 76.38, and 75.67% for BOD, COD, and TDS, respectively, using Cascade Aeration Biofilter or Trickling Filter, Enhancing Solar water Disinfection [(CABFESD)/(CATFESD)] and High-Density Polyethylene lining. This method is highly effective and safe for groundwater and surface water environmental protection. This study could be managing the water poverty for polluted streams and groundwater in the Global South and satisfy the environmental issues to improve water quality and reduce the treatment and health cost in these regions.

Recent years have seen growing interest in enabling volunteers to play a more pronounced role in disaster response, and yet efforts to systematically analyse this crisis volunteer action, particularly among young people, have been surprisingly limited. This study examines the case of the Student Volunteer Army (SVA) in Aotearoa New Zealand, a student-led group which over the space of a decade has responded to multiple disasters, including earthquakes, floods, fires, a terrorist attack and the Covid-19 pandemic. Drawing on in-depth interviews, our analysis compares the practices adopted by the SVA in response to these different crises and identifies how members and supporters of the group have come to understand its capabilities, limitations, and conditions for effective operation. We present a framework of cross-cutting lessons of "why", "who", "when", "what" and "how" and demonstrate the ways they have been built upon for each new disaster mobilisation. In distilling, the key lessons of a youth-led crisis volunteer group that has mobilised for a spectrum of disasters, this paper contributes to theoretical understandings of how groups at a local level learn after sequential disasters, and the conditions and considerations that enable such groups to effectively-and repeatedly-"meet a need" in disaster response.

The purpose of the study was to investigate the quality and reliability of YouTube videos as a source of information in water treatments. We searched videos on YouTube ( www.youtube.com ) using the following keywords: "health resort medicine," "spa treatment," "spa therapy," "hydrotherapy," "thermal medicine," "balneology," and "balneotherapy" on June 17th, 2021. The global quality scale (GQS) was used to evaluate the quality of the videos. The assessment of reliability was evaluated using the modified DISCERN tool. Some other video parameters and sources of the videos were also recorded. One hundred twenty-one (121) videos were analyzed. The most common video source was advertisement (46.3%). GQS and modified DISCERN median scores were generally low. They were superior for "hydrotherapy" and "balneotherapy" and were also higher in videos uploaded by health-related persons or organizations (physicians, health-related professionals, and health-related websites). A statistically significant positive correlation was found between investigated parameters (like view ratio, number of likes, video power index, video length) and GQS. Only video length was correlated with modified DISCERN for investigated parameters. The median video power index scores were statistically higher for "spa therapy" and "spa treatment." The YouTube content linked with water treatments has poor quality and reliability most of time. The hydrotherapy and balneotherapy keywords have the best quality and reliability.We think that designers of water treatment videos should involve health professionals more often so that the content of their video will better explain the details of medical conditions or interventions.The scientific experts should ensure a consensus in terminology to straighten the awareness of water treatments for patients and physicians.

Heat stress decreases human physical work capacity (PWC), but the extent to which solar radiation (SOLAR) compounds this response is not well understood. This study empirically quantified how SOLAR impacts PWC in the heat, considering wide, but controlled, variations in air temperature, humidity, and clothing coverage. We also provide correction equations so PWC can be quantified outdoors using heat stress indices that do not ordinarily account for SOLAR (including the Heat Stress Index, Humidex, and Wet-Bulb Temperature). Fourteen young adult males (7 donning a work coverall, 7 with shorts and trainers) walked for 1 h at a fixed heart rate of 130 beats∙min−1, in seven combinations of air temperature (25 to 45°C) and relative humidity (20 or 80%), with and without SOLAR (800 W/m2 from solar lamps). Cumulative energy expenditure in the heat, relative to the work achieved in a cool reference condition, was used to determine PWC%. Skin temperature was the primary determinant of PWC in the heat. In dry climates with exposed skin (0.3 Clo), SOLAR caused PWC to decrease exponentially with rising air temperature, whereas work coveralls (0.9 Clo) negated this effect. In humid conditions, the SOLAR-induced reduction in PWC was consistent and linear across all levels of air temperature and clothing conditions. Wet-Bulb Globe Temperature and the Universal Thermal Climate Index represented SOLAR correctly and did not require a correction factor. For the Heat Stress Index, Humidex, and Wet-Bulb Temperature, correction factors are provided enabling forecasting of heat effects on work productivity. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02205-x.

Temperature has been studied in relation to many health outcomes. However, few studies have explored its effect on the risk of hospital admission for rheumatoid arthritis (RA). A distributed lag non-linear model (DLNM) was used to analyze associations between mean temperature, diurnal temperature range (DTR), temperature change between neighboring days (TCN), and daily admissions for RA from 2015 to 2019 in Anqing, China. Subgroup analyses based on age, gender, rheumatoid factors, and admission route were performed. In total, 1456 patients with RA were hospitalized. Regarding the cumulative-lag effects of extreme cold temperature (5th percentile = 3℃), the risks of admissions for RA were increased and highest at lag 0–11 (RR = 2.68, 95% CI: 1.23–5.86). Exposing to low (5th percentile = 1.9℃) and high (95th percentile = 14.2℃) DTRs both had increased risks of RA admission, with highest RRs of 1.40 (95% CI: 1.03–1.91) and 1.24 (95% CI: 1.0–1.53) at lag 0 day, respectively. As for TCN, the marginal risk of admission in RA patients was found when exposed to high TCN (95th percentile = 2.9℃) with the largest single-day effect at lag 10 (RR = 1.11, 95% CI: 1.01–1.23). In subgroup analyses, females were more susceptible to extreme cold temperature, low and high DTRs, and high TCN. In regard to extreme cold temperature, significant risk of hospital admission in females only appeared at lag 2 (RR = 1.48, 95% CI: 1.02–2.15) and lag 0–2 (RR = 2.35, 95% CI: 1.11–4.95). It is clear that RA patients exposed to changing temperature may increase risks of admission. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02207-9.

The occurrence of long-lasting severe heat stress, such as in July–August 2003, July 2010, or in April–May 2018 has been one of the biggest meteorological threats in Europe in recent years. The paper focuses on the biometeorological and mortality effects of the hot June that was observed in Central Europe in 2019. The basis of the study was hourly and daily Universal Thermal Climate Index (UTCI) values at meteorological stations in Poland for June 2019. The average monthly air temperature and UTCI values from 1951 to 2018 were analysed as background. Grosswetterlagen calendar of atmospheric circulation was used to assess synoptic conditions of heat wave. Several heat strain measures were applied : net heat storage (S), modelled heart rate (HR), sultriness (HSI), and UTCI index. Actual total mortality (TM) and modelled strong heat-related mortality (SHRM) were taken as indicators of biometeorological consequences of the hot June in 2019. The results indicate that prolonged persistence of unusually warm weather in June 2019 was determined by the synoptic conditions occurring over the European region and causing advection of tropical air. They led to the emergence of heat waves causing 10% increase in TM and 5 times bigger SHRM then in preceding 10 years. Such increase in SHRM was an effect of overheating and overload of circulatory system of human organism. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02202-0.

International and domestic tourism is a growing industry in Costa Rica, with the most attractive places located along the coast. Despite their beauty, Costa Rican beaches can pose a high risk for foreign visitors: Drowning is the primary cause of unintentional death among international visitors. This study presents a comprehensive analysis of demographics, spatial and temporal trends of national and foreigner fatal drowning occurring at Costa Rican beaches during 2001–2019. For national beachgoers, teens and young male adults, ages 15–30 years are at greatest risk of drowning, while for foreigners, older adults ages 45–60 years exhibit higher risk. Temporal trends in drowning appear to be correlated with the number of beach visitors, which seem to be driven mainly by a combination of socioeconomical and climatic/weather factors. For instance, strong economic indicators for the Costa Rican population combined with good weather fostered during warm phases of El Nino Southern Oscillation attract more national beachgoers, which may increase the number of drowning deaths. These results will help authorities better understand the complex and dynamic drowning situation to develop better prevention strategies and policies that improve beach safety and raise awareness about coastal hazards and risk. Such actions will bolster the reputation of Costa Rica as a safe touristic destination.

Effluent treatment plants act as the last line of defense against the discharge of pollutants from industrial effluents. The higher resource consumption, variety of dyes, and auxiliary chemicals used for textile manufacturing classify it as a highly polluting industry. Standards for color, organics, and dissolved solids are becoming more stringent with time, and local regulators are forced to insist on the establishment of zero liquid discharge (ZLD) units. However, the application of the ZLD concept has the major limitation of high energy consumption when compared with the conventional wastewater treatment plant. The application of carbon footprint analysis to both units would provide a comprehensive solution to the carbon footprint computation and bring out the advantages of the ZLD. The carbon footprint of a typical ZLD treatment facility in south India was found to be 10,598 tons of carbon dioxide equivalent per year (tCO2eq/year), which is only one-third more than that of a conventional treatment plant. The carbon footprint of a given ZLD treatment facility can effectively be used as a performance indicator to limit the overall energy consumption. HIGHLIGHTS Comparative evaluation of the carbon footprint between conventional and zero liquid discharge (ZLD) treatment plants for textile wastewater is the first of its kind.; Comprehensive carbon emission quantification by the inclusion of carbon footprint due to the discharge of treated effluent into water bodies/land and ground water extraction within the system boundaries.; Carbon footprint of the ZLD treatment plant was found to be nearly 35% higher than the carbon footprint of the conventional treatment plant with a capacity of 4.4 million liters per day.; The application of carbon footprint analysis is a novel performance analysis tool for comparing the different industrial wastewater treatment plants including the ZLD system.

The U.S. 2020 hurricane season was extraordinary because of a record number of named storms coinciding with the COVID-19 pandemic. This study draws lessons on how individual hurricane preparedness is influenced by the additional risk stemming from a pandemic, which turns out to be a combination of perceptions of flood and pandemic risks that have opposite effects on preparedness behavior. We conducted a survey in early June 2020 of 600 respondents in flood-prone areas in Florida to obtain insights into households’ risk perceptions and preparedness for the upcoming hurricane season under COVID-19. The results show that concerns over COVID-19 dominated flood risk perceptions and negatively impacted people’s evacuation intentions. Whereas hotel costs were the main obstacle to evacuating during Hurricane Dorian in 2019 in the same geographic study area, the main evacuation obstacle identified in the 2020 hurricane season is COVID-19. Our statistical analyses investigating the factors influencing evacuation intentions show that older individuals are less likely to evacuate under a voluntary order, because they are more concerned about the consequences of becoming infected by COVID-19. We observe similar findings based on a real-time survey we conducted in Florida with another group of respondents under the threat of Hurricane Eta at the end of the hurricane season in November 2020. We discuss the implications of our findings for risk communication and emergency management policies that aim to improve hurricane preparedness when dealing with additional health risks such as a pandemic, a situation that may be exacerbated under the future climate. Supplementary Information The online version contains supplementary material available at 10.1007/s11069-021-05064-2.

Excess mortality not directly related to the virus has been shown to have increased during the COVID-19 pandemic. However, changes in heat-related mortality during the pandemic have not been addressed in detail. Here, we performed an observational study crossing daily mortality data collected in Portugal (SICO/DGS) with high-resolution temperature series (ERA5/ECMWF), characterizing their relation in the pre-pandemic, and how it aggravated during 2020. The combined result of COVID-19 and extreme temperatures caused the largest annual mortality burden in recent decades (~ 12 000 excess deaths [~ 11% above baseline]). COVID-19 caused the largest fraction of excess mortality during March to May (62%) and from October onwards (85%). During summer, its direct impact was residual, and deaths not reported as COVID-19 dominated excess mortality (553 versus 3 968). A prolonged hot spell led mortality to the upper tertile, reaching its peak in mid-July (+ 45% deaths/day). The lethality ratio (+ 14 deaths per cumulated ºC) was higher than that observed in recent heatwaves. We used a statistical model to estimate expected deaths due to cold/heat, indicating an amplification of at least 50% in heat-related deaths during 2020 compared to pre-pandemic years. Our findings suggest mortality during 2020 has been indirectly amplified by the COVID-19 pandemic, due to the disruption of healthcare systems and fear of population in attending healthcare facilities (expressed in emergency room admissions decreases). While lockdown measures and healthcare systems reorganization prevented deaths directly related to the virus, a significant burden due to other causes represents a strong secondary impact. This was particularly relevant during summer hot spells, when the lethality ratio reached magnitudes not experienced since the 2003 heatwaves. This severe amplification of heat-related mortality during 2020 stresses the need to resume normal healthcare services and public health awareness. This work was partially funded by national funds through Fundação para a Ciência e a Tecnologia (FCT) under project IMPECAF (PTDC/CTA-CLI/28902/2017) and project HOLMODRIVE (PTDC/CTA-GEO/29029/2017). AR, PMS, and RT are also grateful by the FCT funding UID GEO 50019 2020–Instituto Dom Luiz. JLG acknowledges FCT (Fundação para a Ciência e a Tecnologia) for the PhD Grant 2020.05198. info:eu-repo/semantics/publishedVersion

Even if the sensitivity of vegetation phenology to climate change has been accepted on global and continental scales, the correlation between global warming and phenotypic variability shows a modulated answer depending on altitude, latitude, and the local seasonal thermal trend. To connect global patterns of change with local effects, we investigated the impact of the observed signal of warming found in Central Italy on two different willow species, Salix acutifolia and Salix smithiana, growing in three phenological gardens of the International Phenological Gardens’ network (IPG) located in different orographic positions. The time series of temperatures and phenological data for the period 2005–2018 were analysed first to find trends over time in the three gardens and then to correlate the recent local warming and the change in the two species phenology. The results confirmed the correlation between phenological trends and local trend of temperatures. In particular: budburst showed a trend of advancement of 1.4 days/year on average in all three gardens; flowering showed a divergent pattern between the gardens of either advancement of 1.0 days/year on average or delay of 1.1 days/year on average; while senescence showed a delay reaching even 3.3 days/year, although significant in only two gardens for both species. These trends were found to be correlated mainly with the temperatures of the months preceding the occurrence of the phase, with a shift in terms of days of the year (DOY) of the two species. Our conclusion is that the observed warming in Central Italy played a key role in controlling the phenophases occurrences of the two willow species, and that the orographic forcing leads to the different shift in DOY of phenophases (from 5 to 20 days) due to the local thermal forcing of the three phenological gardens.

International audience; With highly variable types of coronavirus disease 2019 (COVID-19) symptoms in both severity and duration, there is today an important need for early, individualized, and multidisciplinary strategies of rehabilitation. Some patients present persistent affections of the respiratory function, digestive system, cardiovascular function, locomotor system, mental health, sleep, nervous system, immune system, taste, smell, metabolism, inflammation, and skin. In this context, we highlight here that hydrothermal centers should be considered today as medically and economically relevant alternatives to face the urgent need for interventions among COVID-19 patients. We raise the potential benefits of hydrotherapy programs already existing which combine alternative medicine with respiratory care, physical activity, nutritional advice, psychological support, and physiotherapy, in relaxing environments and under medical supervision. Beyond the virtues of thermal waters, many studies reported medical benefits of natural mineral waters through compressing, buoyancy, resistance, temperature changes, hydrostatic pressure, inhalations, or drinking. Thermal institutions might offer individualized follow-up helping to unclog hospitals while ensuring the continuity of health care for the different clinical manifestations of COVID-19 in both post-acute and chronic COVID-19 patients. Our present review underlines the need to further explore the medical effectiveness, clinical and territorial feasibility, and medico-economic impacts of the implementation of post-COVID-19 patient management in hydrotherapeutic establishments.

Three semi-technical scale biofilters were applied to treat waste gases at different industrial sites in Poland: a mechanical–biological treatment plant of municipal solid waste, a wastewater treatment plant and a food industry plant. Two types of materials were used as beds in the biofilters: stumpwood chips and pine bark, and stumpwood chips, pine bark and compost from green waste. Both bed materials supported the microbial growth and high numbers (106–108 cfu/g dry mass (DM)) of culturable bacteria, and fungi in beds were observed. There was no correlation between the number of microorganisms (cfu/g DM) and the respiratory activity in the biofilter beds. However, microbial respiration activity corresponded with microbial abundance expressed as microbial equivalents (ME), which was calculated based on adenosine triphosphate (ATP) determination. The biofilters either reduced or increased bioaerosol emissions from industrial plants, depending on the microbial content in the waste gases. A high microbial content in the waste gases made the effect of microbial emission from the biofilter bed negligible. The type of biofilter bed and number of microorganisms in the bed also influenced the final bioaerosol emission, but these factors were relevant for biofilters that treated waste gases with low microbial concentrations.

Currently, due to the global pandemic caused by severe acute respiratory syndrome coronavirus SARS-CoV-2, new procedures and devices for effective disinfection of indoor air are of obvious interest. Various studies demonstrated quite broad ranges of the efficiency of essential oils in the control of biological aerosols. This project reports the results of investigation of the antimicrobial activity of essential oils natural for Australia (tea tree oil, eucalyptus oil and lemon myrtle) distributed by newly developed VaxiPod device for various scenarios, including bacterial, viral and fungal inactivation on various surfaces and in aerosol form. It was found that the device was capable of operating continuously over 24-h periods, providing sufficient aerosol concentration to efficiently inactivate microorganisms both on the surface and in airborne form. Twenty-four to forty-eight hours were required to achieve inactivation above 90% of most of the tested microbes on solid surfaces (stainless steel discs and agar plates), whilst similar efficiency of inactivation on fibrous filter surface as well as in aerosol form was achieved over 30–60 min of the process run. The results look very promising for further development of bioaerosol inactivating procedures and technologies for air quality control applications.

Quote: “What I hear, I forget. What I see, I remember. What I do, I understand.” (Xunzi, ∼300 BCE). Modelling complex interactions involving climatic features, socio-economic vulnerability or responses, and long impact transmissions is associated with substantial uncertainty. Physical climate storylines are proposed as an approach to explore complex impact transmission pathways and possible alternative unfoldings of event cascades under future climate conditions. These storylines are particularly useful for climate risk assessment for complex domains, including event cascades crossing multiple disciplinary or geographical borders. For an effective role in climate risks assessments, development guidelines are needed to consistently develop and interpret the storyline event analyses. This paper elaborates on the suitability of physical climate storyline approaches involving climate event induced shocks propagating into societal impacts. It proposes a set of common elements to construct the event storylines. In addition, criteria for their application for climate risk assessment are given, referring to the need for storylines to be physically plausible, relevant for the specific context, and risk-informative. Apart from an illustrative gallery of storyline examples found in literature, three examples of varying scope and complexity are presented in detail, all involving the potential impact on European socio-economic sectors induced by remote climate change features occurring far outside the geographical domain of the European mainland. The storyline examples illustrate the application of the proposed storyline components and evaluate the suitability of the criteria defined in this paper. It thereby contributes to a rigorous design and application of event-based climate storyline approaches.

The requirement to monitor and control industrial processes has increased over recent years, therefore innovative techniques are required to meet the demand for alternative methods of particulate measurement. Resonant mass sensors are now strong candidates for accurate mass measurement and are frequently used in many diverse fields of science and engineering. This paper presents the design, modelling, and optimal geometry selection for sensitivity improvement of a U-shaped glass tube as a resonant mass sensing cantilever with a view to becoming a component of particulate measurement equipment. Finite Element Analysis (FEA) was used to develop the system which was validated experimentally using a physical model. This paper focuses on both the proof of concept and the geometry selection of the sensor using analysis of the system sensitivity for best selection. Modal and harmonic analysis were undertaken across a range of commercially available glass tube sizes from 6 mm to 10 mm diameter, to determine the optimal geometry selection, validated with practical experimental data. Results show a consistent difference of 3–5% between the simulation and experimental results, showing strong correlation. This research provides a methodology on the development of using a U-shaped glass tube for accurate mass measurement with a view to exploring the design as a component of particulate emissions equipment. The experimental and simulation results confirm that the highest sensitivity is achieved when the geometry dimensions, and therefore the vacant mass of the tube, is reduced. The 6 mm diameter tube with the smallest bend radius was the most suitable design to meet the design criteria. The calibration curve was plotted to allow an unknown mass to be calculated, which gave an R2 value of 0.9984. All experimental work was repeated three times with results giving an average of 0.44% between the minimum and maximum showing strong linearity and suggesting the potential for implementation of the methodology in its intended application. The design provides possible solutions to some of the issues currently seen with particulate measurement from stationary sources.

This paper presents a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection, named DeLiAn, is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements, conducted mainly with lidars that have been developed at the Leibniz Institute for Tropospheric Research. The intensive optical properties are presented at two wavelengths, 355 and 532 nm, for 13 aerosol categories. The categories cover the basic aerosol types (i.e., marine, pollution, continental European background, volcanic ash, smoke, mineral dust), as well as the most frequently observed mixtures they form. This extensive collection also incorporates more peculiar aerosol categories, including dried marine aerosol that, compared to marine aerosol, exhibits a significantly enhanced depolarization ratio (up to 15 %). Besides Saharan dust, additional mineral dust types related to their source region were identified due to their lower lidar ratios (Central Asian and Middle Eastern dust). In addition, extreme wildfire events (such as in north America and Australia) emitted smoke into the stratosphere showing significantly different optical properties, i.e., high depolarization values (up to 25 %), compared to tropospheric smoke. The data collection reflects and underlines the variety of aerosol mixtures in the atmosphere and can be used for the development of aerosol-typing schemes. The paper contains the most up-to-date and comprehensive overview of optical properties from aerosol lidar measurements and, therefore, provides a solid basis for future aerosol retrievals in the frame of both spaceborne and ground-based lidars. Furthermore, DeLiAn can assist the efforts for the harmonization of satellite records of aerosol properties performed at different wavelengths.

With the rapid development of urbanization, ambient air pollution is becoming increasingly serious. Out of many pollutants, fine particulate matter (PM2.5) is the pollutant that affects the urban atmospheric environment to the greatest extent. Fine particulate matter (PM2.5) concentration prediction is of great significance to human health and environmental protection. This paper proposes a CNN-SSA-DBiLSTM-attention deep learning fusion model. This paper took the meteorological observation data and pollutant data from eight stations in Bijie from 1 January 2015 to 31 December 2022 as the sample data for training and testing. For the obtained data, the missing values and the data obtained from the correlation analysis performed were first processed. Secondly, a convolutional neural network (CNN) was used for the feature selection. DBILSTM was then used to establish a network model for the relationship between the input and actual output sequences, and an attention mechanism was added to enhance the impact of the relevant information. The number of units in the DBILSTM and the epoch of the whole network were optimized using the sparrow search algorithm (SSA), and the predicted value was the output after optimization. This paper predicts the concentration of PM2.5 in different time spans and seasons, and makes a comparison with the CNN-DBILSTM, BILSTM, and LSTM models. The results show that the CNN-SSA-DBiLSTM-attention model had the best prediction effect, and its accuracy improved with the increasing prediction time span. The coefficient of determination (R2) is stable at about 0.95. The results revealed that the proposed CNN-SSA-DBiLSTM-attention ensemble framework is a reliable and accurate method, and verifies the research results of this paper in regard to the prediction of PM2.5 concentration. This research has important implications for human health and environmental protection. The proposed method could inspire researchers to develop even more effective methods for atmospheric environment pollution modeling.

General circulation models (GCMs) run at regional resolution or at a continental scale. Therefore, these results cannot be used directly for local temperatures and precipitation prediction. Downscaling techniques are required to calibrate GCMs. Statistical downscaling models (SDSM) are the most widely used for bias correction of GCMs. However, few studies have compared SDSM with multi-layer perceptron artificial neural networks and in most of these studies, results indicate that SDSM outperform other approaches. This paper investigates an alternative architecture of neural networks, namely the long-short-term memory (LSTM), to forecast two critical climate variables, namely temperature and precipitation, with an application to five climate gauging stations in the Lake Chad Basin. Lake Chad is a data scarce area which has been impacted by severe drought, where water resources have been influenced by climate change and recent agricultural expansion. SDSM was used as the benchmark in this paper for temperature and precipitation downscaling for monthly time–scales weather prediction, using grid resolution GCM output at a 5 degrees latitude × 5 degrees longitude global grid. Three performance indicators were used in this study, namely the root mean square error (RMSE), to measure the sensitivity of the model to outliers, the mean absolute percentage error (MAPE), to estimate the overall performance of the predictions, as well as the Nash Sutcliffe Efficiency (NSE), which is a standard measure used in the field of climate forecasting. Results on the validation set for SDSM and test set for LSTM indicated that LSTM produced better accuracy on average compared to SDSM. For precipitation forecasting, the average RMSE and MAPE for LSTM were 33.21 mm and 24.82% respectively, while the average RMSE and MAPE for SDSM were 53.32 mm and 34.62% respectively. In terms of three year ahead minimum temperature forecasts, LSTM presents an average RMSE of 4.96 degree celsius and an average MAPE of 27.16%, while SDSM presents an average RMSE of 8.58 degree celsius and an average MAPE of 12.83%. For maximum temperatures forecast, LSTM presents an average RMSE of 4.27 degree celsius and an average MAPE of 11.09 percent, while SDSM presents an average RMSE of 9.93 degree celsius and an average RMSE of 12.07%. Given the results, LSTM may be a suitable alternative approach to downscale global climate simulation models’ output, to improve water management and long-term temperature and precipitations forecasting at local level.

The iron and steel industry is an important foundation of the national economy. It is the inevitable choice, to achieve high-quality development in the new era of the iron and steel industry, to speed up the green development of the iron and steel industry. This paper studies the effect of steel industry agglomeration on regional economic growth and air pollution. Through the analysis of the characteristics of iron and steel industry agglomeration, and the empirical analysis of the relationship between iron and steel industry agglomeration, regional economic growth, and air pollution, it is found that: (1) Iron and steel industry agglomeration helps to promote economic growth; (2) Iron and steel industry agglomeration has an obvious spatial correlation effect and obviously drives the development of surrounding areas; (3) Iron and steel industry agglomeration will cause air pollution. The marginal effect of air pollution will decline rapidly with the development of iron and steel industry agglomeration. (4) The impact of green process innovation investment on air pollution presents an inverted U-shaped effect, which has a positive effect on air recovery after exceeding the critical point. (5) The air self-purification capacity represented by precipitation, helps to reduce air pollution. Based on the above conclusions, this paper puts forward some policy suggestions, such as making a scientific development plan for the iron and steel industry, accelerating green process innovation, effectively improving regional precipitation and precipitation times, vigorously promoting high-quality development of the regional economy, and comprehensively promoting coordinated development of the iron and steel industry, so as to cope with the dilemma of the coordinated development of the iron and steel industry, regional economic growth, and smog pollution, and strive for international development in the future. In the competition, we should gain the first opportunity and obvious competitive advantage.

In this paper, a typical vortex system based on quasi-linear thermal-dynamic equations to reflect the development and extinction of the China Southwest Vortex is established using the vortex motion stability method combined with the outer environmental field and cumulus convective latent heat release. The development and extinction of the China Southwest Vortex in catastrophic weather systems are studied from the aspects of stability and development mechanisms for the primary-stage China Southwest Vortex, the transition mechanism from the primary-stage China Southwest Vortex to the mature vortex, and stability and development mechanisms of the mature China Southwest Vortex. The results show the following: (1) the convergence and divergence of the surrounding flow field is the main factor influencing the development and extinction of the primary-stage China Southwest Vortex, while gravity wave disturbance is the main driving force for the maintenance and development of the primary vortex. Based on the convergence of the external flow field, the gravity wave disturbance must exceed the critical frequency, or the vortex will tend to die out. (2) The convergence and divergence of the surrounding flow field is also the main factor for the transition from the primary vortex to the mature vortex. Based on the convergence of the surrounding flow field, the primary vortex transforms into a mature vortex only when the gravity wave disturbance strongly exceeds the critical frequency and causes the vertical disturbance to become unstable. (3) The convergence and divergence of the external flow field is also the main factor for the development and extinction of the mature China Southwest Vortex. In the early stage, the vortex can be maintained and developed as long as the surrounding flow field converges. In the case of the divergence of the external flow field, the vortex may be maintained for a short time, but eventually dissipates when the gravity wave disturbance exceeds the critical frequency. In the later stage, under the convergence of the surrounding flow field, the vortex can be maintained when the gravity wave disturbance exceeds the critical frequency. However, with the divergence of the surrounding flow field, the vortex may be maintained for a short time, but it will eventually dissipate when the gravity wave disturbance is extremely strong. In addition, the observations of the evolution of China Southwest Vortexes and gravity wave activities under the influence of southwest airflow and atmospheric disturbance in the Western Sichuan Plateau–Sichuan Basin are explained by the above physical mechanism. It is also pointed out that the heating effect can be an obstacle to the development of the China Southwest Vortex by increasing the critical frequency of gravity waves during unstable layer formation, and the divergent environment flow field under the condition of stable layer formation. Therefore, this paper deepens the understanding of the evolution process and anomalous mechanisms of the China Southwest Vortex.

There is currently no way for subway air-conditioning systems to adjust to changes in passenger capacity in terms of air-supply volume and air-supply temperature. In this paper, a study of the setting of the air-supply volume and controlling the temperature in subway trains was conducted. Based on the fact that the air-supply volume in a subway train needs to meet the requirements of cooling load and humidity load, as well as fresh-air volume, the minimum critical air-supply volume curve was determined on the basis of theoretical calculations under different passenger capacities. Under different passenger capacity and air-supply-volume conditions, the PMV (predicted mean vote) distribution of the subway train was simulated and calculated, and the results indicated that increasing the air-supply volume would not be sufficient to achieve PMV = 0. Therefore, in accordance with the theoretical formulation of the PMV, multiple linear regression was used to fit the temperature-control curve for various passenger capacities. A simulation calculation of the subway train was used to assess the uniformity of the flow field and the temperature field within the subway train in accordance with EN14750. It is evident from the results that under the control curve of the air-supply volume and temperature under different passenger capacities, the uniformity of the flow field and the temperature field can meet the standard requirements. By using the air-supply volume and temperature-control curve proposed in this paper, it is possible to adjust the air-supply volume in real-time, control the temperature of the air-conditioning system of the subway train, improve the passenger comfort of the train, and reduce the energy consumption of the air-conditioning system.

The Joint Polar Satellite System (JPSS) mission has provided over ten years of high-quality data products for environment forecasting and monitoring through the current Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites. Particularly, the sensor data record (SDR) and the derived environmental data record (EDR) products from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), the Advanced Technology Microwave Sounder (ATMS), and the Ozone Mapping and Profiler Suite (OMPS) offer an unprecedented opportunity to observe severe weather and environmental events over the Earth. This paper presents the observations about atmospheric features of the Hunga Tonga Volcanic eruption of January 2022, e.g., the gravity wave, volcanic cloud, and aerosol (sulfate) plume phenomena, by using the ATMS, CrIS, OMPS, and VIIRS SDR and EDR products. Powerful gravity waves ringing through the atmosphere after the eruption of the Hunga Tonga volcano are discovered at two CrIS upper sounding channels (670 cm−1 and 2320 cm−1) in the deviations of the observed brightness temperature (O) from the simulated baseline brightness temperature (B) using the Community Radiative Transfer Model (CRTM), i.e., O—B. A similar pattern is also observed in the ATMS global maps at channel 15, whose peak weighting function is around 40 km, showing the atmospheric disturbance caused by the eruption that reached 40 km above the surface. The Tonga volcanic cloud (plume) was also captured by the OMPS SO2 EDR product. The gravity wave features were also captured in the native resolution image of the S-NPP VIIRS I-5 band nighttime observations. In addition, the VIIRS Aerosol Optical Depth (AOD) captured and tracked the volcanic aerosol (sulfate) plume successfully. These discoveries demonstrate the scientific potential of the JPSS SDR and EDR products in monitoring and tracking the eruption of the Hunga Tonga volcano and its severe environmental impacts. This paper presents the atmospheric features of the Hunga Tonga volcano eruption that is uniquely captured by all four advanced sensors onboard JPSS satellites, with different spectral coverages and spatial resolutions.

The rescaling of rainfall requires measurements of rainfall rates over many dimensions. This paper develops one approach using 10 m vertical spatial observations of the Doppler spectra of falling rain every 10 s over intervals varying from 15 up to 41 min in two different locations and in two different years using two different micro-rain radars (MRR). The transformation of the temporal domain into spatial observations uses the Taylor “frozen” turbulence hypothesis to estimate an average advection speed over an entire observation interval. Thus, when no other advection estimates are possible, this paper offers a new approach for estimating the appropriate frozen turbulence advection speed by minimizing power spectral differences between the ensemble of purely spatial radial power spectra observed at all times in the vertical and those using the ensemble of temporal spectra at all heights to yield statistically reliable scaling relations. Thus, it is likely that MRR and other vertically pointing Doppler radars may often help to obviate the need for expensive and immobile large networks of instruments in order to determine such scaling relations but not the need of those radars for surveillance.

This paper investigates the effect of the architectural design of deep learning models in combination with a feature engineering approach considering the temporal variation in the features in the case of tropospheric ozone forecasting. Although deep neural network models have shown successful results by extracting features automatically from raw data, their performance in the domain of air quality forecasting is influenced by different feature analysis approaches and model architectures. This paper proposes a simple but effective analysis of tropospheric ozone time series data that can reveal temporal phases of the ozone evolution process and assist neural network models to reflect these temporal variations. We demonstrate that addressing the ozone evolution phases when developing the model architecture improves the performance of deep neural network models. As a result, we evaluated our approach on the CNN model and showed that not only does it improve the performance of the CNN model, but also that the CNN model in combination with our approach boosts the performance of the other deep neural network models such as LSTM. The development of the CNN, LSTM-CNN, and CNN-LSTM models using the proposed approach improved the prediction performance of the models by 3.58%, 1.68%, and 3.37%, respectively.

Public participation is playing an increasingly important role in environmental governance. This paper uses panel data from Chinese cities to evaluate the causal relationship between public participation, regional carbon emissions, and regional carbon intensity. We obtain the following conclusions: (1) Public participation significantly reduces regional carbon emissions and regional carbon intensity, which remains robust after a series of robustness and endogeneity discussions. (2) The carbon reduction effect of public participation performs better in eastern regions, regions with higher per capita income, and regions with a concentration of tertiary industries and talents. (3) We divided the public participation into resident participation and environment non-governmental organizations (ENGOs) participation. We found an excellent interactive emission reduction effect with resident participation and a good interaction between resident participation and government and environmental organizations. (4) This paper finds that promoting regional green technology innovation is a significant mechanism for public participation in achieving carbon emission reduction. (5) Finally, this paper found an “inverted U-shaped” non-linear relationship between public participation and regional carbon emissions. The results reveal the importance of public participation in regional carbon emissions and provide an empirical basis for promoting informal environmental regulation.

The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant “warming and wetting” since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO.

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II (WGII) to categorize, assess and communicate a wide range of regional and sectoral key risks from climate change. These are risks expected to become severe due to the potentially detrimental convergence of changing climate conditions with the exposure and vulnerability of human and natural systems. Other papers in this special issue treat each of eight RKRs holistically by assessing their current status and future evolution as a result of this convergence. However, in these papers, such assessment cannot always be organized according to a systematic gradation of climatic changes. Often the big-picture evolution of risk has to be extrapolated from either qualitative effects of “low”, “medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C), together with consideration of the socio-economic context and possible adaptation choices. In this study we offer a representation – as systematic as possible given current literature and assessments – of the future evolution of the hazard components of RKRs. We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels (GWLs) to the extent possible. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group I supplemented when needed by more recent literature. For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with increasing GWLs has been identified. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - that link can only be described qualitatively. For some processes - like the behavior of ice sheets, or changes in circulation dynamics - large uncertainties about the effects of different GWLs remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems, in the absence of compensating changes in these systems’ exposure and vulnerability, and in the absence of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in their often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future potential evolution, an important component – if never the only one – of the future evolution of risk severity., Climate Risk Management, 40, ISSN:2212-0963

Nighttime medium-scale traveling ionospheric disturbances (MSTIDs) have been generally observed by ground-based instruments. However, they provide 2-dimensional images over only a limited field of view and are not distributed globally. The ground-based observations reported that MSTID wavefronts exhibit backward-C shapes virtually straddling the dip equator. In situ plasma density measurements onboard individual satellites could overcome the limited coverage of ground-based MSTID observations. But, most of those spacecrafts could obtain only 1-dimensional profiles of plasma density, which leaves uncertain whether the observed perturbations generally have the characteristic directivity of MSTIDs. This paper addresses this knowledge gap by statistically investigating nighttime perturbations in the mid-latitude topside ionosphere observed by tandem satellites, Swarm A and C. We cross-correlate the plasma density profiles observed by Swarm A and C. The correlation coefficient tends to increase as the two spacecraft move closer, allowing us to derive the disturbances' directivity whenever the Swarm A and C observations are correlated significantly. The directivity statistics agree well with the backward-C shape. Furthermore, the wavefront directions have clear dependence on magnetic latitudes while they are not as well aligned with local time, which is also consistent with previous reports on nighttime MSTIDs using ground-based observations and computer simulations. Additionally, we demonstrate that the nighttime MSTIDs can increase the topside Rate Of Total electron content Index above Swarm. All the above-mentioned results support that the nighttime mid-latitude perturbations observed by Swarm can be identified as MSTIDs on the whole, which is the most important finding of this paper.

This paper describes the new International Comprehensive Ocean–Atmosphere Data Set (ICOADS) near-real-time (NRT) release (R3.0.2), with greatly enhanced completeness over the previous version (R3.0.1). R3.0.1 had been operationally produced monthly from January 2015 onward, with input data from the World Meteorological Organization (WMO) Global Telecommunication Systems (GTS) transmissions in the Traditional Alphanumeric Codes (TAC) format. Since the release of R3.0.1, however, many observing platforms have changed, or are in the process of transitioning, to the Binary Universal Form for Representation of Meteorological Data (BUFR) format. R3.0.2 combines input data from both BUFR and TAC formats. In this paper, we describe input data sources; the BUFR decoding process for observations from drifting buoys, moored buoys, and ships; and the data quality control of the TAC and BUFR data streams. We also describe how the TAC and BUFR streams were merged to upgrade R3.0.1 into R3.0.2 with duplicates removed. Finally, we compare the number of reports and spatial coverage of essential climate variables (ECVs) between R3.0.1 and R3.0.2. ICOADS NRT R3.0.2 shows both quantitative and qualitative gains from the inclusion of BUFR reports. The number of observations in R3.0.2 increased by nearly 1 million reports per month, and the coverage of buoy and ship sea surface temperatures (SSTs) on monthly 2° × 2° grids increased by 20%. The number of reported ECVs also increased in R3.0.2. For example, observations of SST and sea level pressure (SLP) increased by around 30% and 20%, respectively, as compared to R3.0.1, and salinity is a new addition to the ICOADS NRT product in R3.0.2. Significance Statement The International Comprehensive Ocean–Atmosphere Data Set (ICOADS) is the largest collection of surface marine observations spanning from 1662 to the present. A new version, ICOADS near-real-time 3.0.2, includes data transmitted in the Binary Universal Form for Representation of Meteorological Data (BUFR) format, in combination with Traditional Alphanumeric Codes (TAC) data. Many of the organizations that report observations in near–real time have moved to BUFR, so this update brings ICOADS into alignment with collections and archives of these international data distributions. By including the BUFR reports, the number of observations in the upgraded version of ICOADS increased by nearly one million reports per month and spatial coverage of buoy and ship SSTs increased by 20% over the previous version.

Addressing energy provision and access in Sub-Saharan Africa is a key global challenge. This paper builds a deep understanding of how fair and just energy policies and realties are in this context. It qualitatively assesses the perceptions of stakeholders in Malawi, where electricity access remains amongst the lowest in the region. Insufficient and unreliable systems of grid energy generation and distribution limit access to electricity in both urban and rural settings. Using wood fuel remains high for meeting cooking, heating, and lighting needs. Responding to these dual challenges, of lacking electricity access and ongoing wood fuel use, must be rooted in notions of equity, fairness, and justice. This paper argues that energy justice provides key insights into how best to respond to complex and interconnected issues of energy generation and access in low-income settings. Drawing on interviews with key stakeholders in policy and Malawi on addressing these challenges, this paper also outlines recommendations for policy. Overall, a just response to these energy challenges is possible, but only if it is built on local inclusive governance with fairer and effective systems of investment.

In high altitude, scarcely gauged basins, climate change impact assessment on river discharge is important for sustainable management of water resources. These basins are sources for irrigation and hydropower generation in the region. Expected changes in precipitation and temperature can affect the basin's hydrological regime which will have consequential impacts on the dependent sectors. For quantifying the impacts of major climatic variables on hydrological processes, this paper examined bias-corrected GCM outputs coupled with a hydrological model – HBV for Chenab basin. Trend analysis shows that precipitation would decrease after the short-term period and temperature is expected to increase throughout the century. Simulated river discharge is expected to increase throughout the 21st century under both RCP 4.5 and RCP 8.5 scenarios. It is also observed that there would be a shift in seasonal discharge patterns with increased pre- and post-monsoon contributions. Increase in snow and ice melt contribution to the overall discharge is also expected and would range between 50 and 59% until 2100. This study concluded that expected increase in discharge volume coupled with shift in seasonal discharge pattern would impact the basin water management and thus it is important to consider the impact of climate change on the hydrological regimes of basins. HIGHLIGHTS Paper deals with the ungauged basin originating from the Himalayas and assesses shifts in seasonal discharge patterns which highlights increased pre- and post- monsoon contributions in annual discharge.; Output from the study is important for the data scarce Himalayan region and for better planning and management of water resources.

The paper presents the Simulator for Investigation of Solar Temperature Error of Radiosondes (SISTER), a setup that was developed to quantify the solar heating of the temperature sensor of radiosondes under laboratory conditions by recreating as closely as possible the atmospheric and illumination conditions that are encountered during a daytime radiosounding ascent. SISTER controls the pressure (3 to 1020 hPa) and ventilation speed of the air inside the wind-tunnel-like setup to simulate the conditions between the surface and 35 km altitude, to determine the dependence of the radiation temperature error on the irradiance and the convective cooling. The radiosonde is mounted inside a quartz tube, while the complete sensor boom is illuminated by an external light source to include the conductive heat transfer between sensor and boom. A special feature of SISTER is that the radiosonde is rotated around its axis to imitate the spinning of the radiosonde in flight. The characterisation of the radiation temperature error is performed for various pressures, ventilation speeds, and illumination angles, yielding a 2D parameterisation of the radiation error for each illumination angle, with an uncertainty smaller than 0.2 K (k=2) for typical ascend speeds. This parameterisation is applied in the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) processing for radiosonde data, which relies on the extensive characterisation of the sensor properties to produce a traceable reference data product which is free of manufacturer-dependent effects. The GRUAN radiation correction model combines the laboratory characterisation with model calculations of the actual radiation field during the sounding to estimate the correction profile. In the second part of this paper it is described how this procedure was applied in the development of the GRUAN data product for the Vaisala RS41 radiosonde (version 1, RS41-GDP.1). The magnitude of the averaged correction profile increases gradually from 0.1 K at the surface to approximately 0.8 K at 35 km altitude. Comparisons between sounding data (N=154) that were GRUAN-processed and Vaisala-processed reveal that the daytime differences (GRUAN−Vaisala) are smaller than +0.1 K in the troposphere and increase above the tropopause steadily with altitude to +0.35 K at 35 km. These differences are just within the limits of the combined uncertainties (with coverage factor k=2) of both data products, meaning that the GRUAN processing and the Vaisala processing are in agreement.