Air Temperature Measurements Research Articles

Assessment of various microwave brightness temperature products and methods for surface melt detection over Greenland ice sheet

Microwave brightness temperature have widely been used for the detection of the ice sheet's surface melt conditions and understanding their spatio-temporal variability. In this study, we investigated the sensitivity of microwave brightness temperature products from three different sensors, namely, Advanced Microwave Scanning Radiometer-2 (AMSR2), Special Sensor Microwave Imager/Sounder (SSMIS) and Indian scatterometer satellite (SCATSAT-1) for surface melt detection over the Greenland ice sheet (GrIS). In-situ air temperature measurements from GC-Net AWSs were used for sensitivity and inter-comparison analysis. Our findings show that brightness temperature (Tb) from SSMIS better correlates (Pcoef = 0.81 for 19 GHz) with air temperature measurements in comparison to AMSR2 (Pcoef = 0.7 for 18 GHz) and SCATSAT-1 (Pcoef = 0.67). However, interestingly, AMSR2 and SCATSAT-1 uniquely discriminated the surface conditions during pre- and post-melt period, due to their heterogeneity in Tb values during the two period. Error analysis with respect to AWS melt days shows that SSMIS 19 GHz Tb (Tb/SSMIS/19H) products with TED method giving the most promising observations. A wide variability in Tb values is observed during the melt season across the various AWS sites depending upon the elevation, location and frequency. During our study period, using Tb/SSMIS/19H for TED method, we observed the highest melt extent area for the extreme melt event in year 2019 (∼1.12 million km2), followed by another melt event year 2021 when it went as high as ∼1.02 million km2.

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

Abstract Mountains play an outsized role in water resource availability, and the amount and timing of water they provide depend strongly on temperature. To that end, we ask the question: How well are atmospheric models capturing mountain temperatures? We synthesize results showing that high-resolution, regionally relevant climate models produce 2-m air temperature (T2m) measurements colder than what is observed (a “cold bias”), particularly in snow-covered midlatitude mountain ranges during winter. We find common cold biases in 44 studies across global mountain ranges, including single-model and multimodel ensembles. We explore the factors driving these biases and examine the physical mechanisms, data limitations, and observational uncertainties behind T2m. Our analysis suggests that the biases are genuine and not due to observation sparsity or resolution mismatches. Cold biases occur primarily on mountain peaks and ridges, whereas valleys are often warm biased. Our literature review suggests that increasing model resolution does not clearly mitigate the bias. By analyzing data from the Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign in the Colorado Rocky Mountains, we test various hypotheses related to cold biases and find that local wind circulations, longwave (LW) radiation, and surface-layer parameterizations contribute to the T2m biases in this particular location. We conclude by emphasizing the value of coordinated model evaluation and development efforts in heavily instrumented mountain locations for addressing the root cause(s) of T2m biases and improving predictive understanding of mountain climates.

Research on the Three-Level Integrated Environmental Evaluation Model for Multi-Greenhouse Potatoes

Aiming at the problems of large error and redundancy in the multi-node data acquisition of multi-greenhouse photo growth environmental information, a three-level fusion algorithm based on adaptive weighting, an LMBP network, and an improved D-S theory is proposed. The box-and-line graph method recognizes the original data and then replaces it based on the mean value method; the air temperature, humidity, and light intensity measurements are unbiased estimations of the true value to be estimated, so the first level of fusion chooses the adaptive weighted average algorithm to find the optimal weights of each sensor under the condition of minimizing the total mean-square error and obtains the optimal estimation of the weights of the homogeneous sensors of a greenhouse. The Levenberg–Marquardt algorithm was chosen for the second level of fusion to optimize the weight modification of the BP neural network, i.e., the LMBP network, and the three environmental factors corresponding to “suitable”, “uncertain” and “unsuitable” potato growth environments were trained for the three environmental factors in the reproductive periods. The output of the hidden layer was converted into probability by the Softmax function. The third level is based on the global fusion of evidence theory (also known as D-S theory), and the network output is used as evidence to obtain a consistent description of the multi-greenhouse potato cultivation environment and the overall scheduling of farming activities, which better solves the problem of the difficulty in obtaining basic probability assignments in the evidence theory; in the case of a conflict between the evidence, the BPA of the conflicting evidence is reallocated, i.e., the D-S theory is improved. Example validation shows that the total mean square error of the adaptive weighted fusion value is smaller than the variance of each sensor estimation, and sensors with lower variance are assigned lower weights, which makes the fusion result not have a large deviation due to the failure of individual sensors; when the fusion result of a greenhouse feature level is “unsuitable”, the fusion result of each data level is considered comprehensively, and the remote control agency makes a decision, which makes full use of the complementary nature of multi-sensor information resources and solves the problem of fusion of multi-source environmental information and the problem of combining conflicting environmental evaluation factors. Compared with the traditional D-S theory, the improved D-S theory reduces the probability of the “uncertainty” index in the fusion result again. The three-level fusion algorithm in this paper does not sacrifice data accuracy and greatly reduces the noise and redundancy of the original data, laying a foundation for big data analysis.

The impact of local microclimates and Urban Greening Factor on schools’ thermal conditions during summer: A study in Coventry, UK

Thermal comfort in schools affects children's wellbeing and educational outcomes. Global warming and frequent heatwaves have worsened the overheating issue in schools, especially in Western European countries, like the UK. While previous studies have mainly focused on residential and commercial buildings, school-related research often emphasised indoor thermal conditions, neglecting the broader influence of microclimates on the overall thermal conditions. Therefore, this research explores the thermal conditions in schools, during the summer of 2023, with a specific focus on the impact of greenery and materials. Urban Greening Factor (UGF) and its relationship with indoor and outdoor air temperatures were explored for the first time.Field studies were conducted in four primary schools in Coventry, UK, measuring indoor air temperatures and micrometeorological parameters. Tree shade demonstrated a substantial cooling effect, reducing air temperature and mean radiant temperature by up to 6.4 °C and 22.9 °C, respectively. Considerable difference between measured air temperatures in sunlight and official meteorological records highlights the need for microclimatic studies in schools. Thermal imagery identified high surface temperatures on artificial grass (67 °C) and asphalt (55 °C). Urban Greening Factor showed a strong correlation with classroom temperatures but failed to account for spatial greenery distribution and subsequently outdoor thermal conditions. The study concludes that optimising tree shade and replacing dark and artificial materials, are necessary for effective heat mitigation, offering valuable insights for policymakers and urban planners to create thermally comfortable and sustainable school environments.

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, developed for hectometer scale applications. HICAR can run more than 500x faster than conventional atmospheric models, while containing many of the same physics parameterizations. Station measurements of air temperature, wind speed, and radiation, in combination with data from a scanning Doppler wind LiDAR, are compared to 50 m resolution HICAR output during late spring. We examine the model’s performance over bare ground and melting snow. The model shows a smaller root mean squared error in 2 m air temperature than the driving model, and approximates the 3D flow features present around ridges and along slopes. Timing and magnitude of changes in shortwave and longwave radiation also show agreement with measurements. Nocturnal cooling during clear nights is overestimated at the snow covered site. Additionally, the thermal wind parameterization employed by the model typically produces excessively strong surface winds, driven in part by this excessive nocturnal cooling over snow. These findings highlight the utility of HICAR as a tool for dynamically downscaling forcing datasets, and expose the need for improvements to the snow model used in HICAR.

Acoustic travel time tomography for simultaneous indoor air temperature and airflow measurements

Acoustic travel time tomography for simultaneous indoor air temperature and airflow measurements

The influence of air movement in providing thermal comfort in naturally ventilated old Mosque Gunong Kleng, West Aceh, Indonesia

Abstract Mosques were created to fulfill the needs of Muslims in prayer, therefore thermal comfort is critical to consider so that the congregation is comfortable and can focus and feel at home while praying. The typology of ancient mosques reflects the community’s traditions and culture, as well as local knowledge values. Natural ventilation, which acts as a natural air exchange mechanism, is one facet of thermal comfort. The Gunong Kleng Mosque, founded in 1927, is one of West Aceh Regency’s ancient mosques. However, design adjustments have been made, such as the installation of wooden boards to on terraced roof. The air flow from the building’s roof is blocked, resulting in inefficient air exchange. The goal of this study is to determine thermal performance and the effect of air movement on thermal comfort at the Old Gunong Kleng Mosque. This study employed a quantitative approach using field measurements of air temperature, relative humidity, and air velocity. An anemometer and a USB data logger were utilized to collect data. Field measurements revealed that ET comfort in the mosque was 78% too hot, 16% warm comfortable, and 6% for optimal comfort. Ansys Fluet simulation with two types of situations was used to forecast air speed, demonstrating that changes in the design of the stepped roof had a significant impact on the air speed within the mosque. When opposed to an open roof, a closed roof slightly lowered the ambient temperature in the prayer room.

Methane (CH4) Detection System Using The TGS2611 Sensor and MQ-4 Sensor

Abstract This research focused on cow dung digesters as measurement samples, utilizing the TGS2611 and MQ-4 sensors, both known for their affordability. The objective was to develop a low-cost gas sensor system for monitoring methane gas concentrations through a straightforward web-based data acquisition platform. The DHT11 sensor was employed to measure air temperature and humidity. The electronic sensor circuit in this research utilized a voltage divider circuit. Testing the performance of the low-cost gas sensor involved integrating it with an anaerobic digestion system. For both the TGS2611 and MQ-4 sensors, the graph illustrating the relationship between sensor voltage (volts) and methane gas concentration (ppm) formed a logarithmic or non-linear pattern. The measurement range for the system was around 4700 ppm to 6300 ppm for TGS2611 and 4000 ppm to 5100 ppm for MQ-4. The sensor sensitivity was determined as 0.5433 Volts/ppm for TGS2611 and 0.5639 Volt/ppm for MQ-4. The TGS2611 sensor exhibited a higher response to changes in methane gas concentration, while the MQ-4 sensor successfully detected methane gas within its designated range. Interestingly, the TGS2611 sensor accurately detected methane gas concentrations above its specified range. The gas sampling procedure involved automatic gas sampling in a vacuum chamber for measurement, a strategy potentially enhancing sensor robustness. This research successfully amalgamated sensor advantages, circuit control, and data analysis to realize an economical yet reliable monitoring system.

Evaluating the effects of different tree species on enhancing outdoor thermal comfort in a post-industrial landscape

A frequently emphasized strategy to reduce the burden of heat in cities across the world is the implementation of street trees. Here, we examine the effects of deciduous and coniferous tree deployment on meteorological variables and pedestrian thermal comfort through analysis of the new dynamic thermal comfort (dPET) index, using the latest version of the computational fluid dynamics model ENVI-met. We performed on site observational measurements of air temperature (Ta), relative humidity (Rh), wind speed (Ws), and mean radiant temperature (MRT) at five different locations on the hottest day of summer 2023, in a post-industrial urban landscape located in Tehran, Iran. Observations were used to evaluate ENVI-met simulation performance and served as a baseline against which sensitivity experiments—based on a minimum (35%) and maximum (75%) intervention scenario for deciduous and coniferous trees—were compared against. Our analysis indicates that 35% and 75% deployment reduced Ta by 1.2 °C and 4.2 °C, respectively, for deciduous tree species, compared to a 0.9 °C and 3.1 °C reduction for coniferous species, during the hottest day of summer 2023. The maximum deployment scenario decreased MRT by approximately 60 °C and 43 °C for deciduous and coniferous tree deployment, respectively. The maximum tree deployment scenario decreased dPET by nearly 16 °C and 14 °C for deciduous and coniferous trees, respectively, during the time of day that diurnal heating is maximized. Our findings highlight micrometeorological and personalized thermal comfort effects associated with variable tree species type and extent through examination of a pedestrian’s ambulatory experience across diverse urban microclimates in a region of the world that is particularly understudied.

Residual canopy cover provides buffering of near-surface temperatures, but benefits are limited under extreme conditions

Increasing summer temperatures and higher probabilities of extreme heat events have led to concerns about tree damage and mortality. However, insufficient attention has been given to conditions leading to heat-related regeneration failures in temperate forests. To address this, managers need to understand how microclimate varies under a range of overstory conditions. We measured air temperatures at 2 cm above-ground underneath a gradient of canopy cover on south-facing slopes in recently thinned Douglas-fir stands in western Oregon, USA. To expand the ecological relevance of these data to impacts on regeneration, we created the stress degree hours (SDH) metric, representing the amount of time—and by how much—temperatures exceeded biologically relevant stress thresholds. Overall, for every 10% increase in canopy cover, maximum temperatures at 2 cm were 1.3 °C lower, the odds of temperatures exceeding stress thresholds for conifer regeneration declined by a multiplicative factor of 0.26, and the total of SDH decreased by 40%. These reductions are large enough to be worthy of attention when managing for tree regeneration. However, data collected during the Pacific Northwest Heat Dome in June 2021 indicate that with various climate change scenarios and heatwave occurrences, temperatures will be unfavorable for regeneration regardless of overstory cover.

Multi-Sensor Device for Traceable Monitoring of Indoor Environmental Quality.

The Indoor Environmental Quality (IEQ) combines thermal, visual, acoustic, and air-quality conditions in indoor environments and affects occupants' health, well-being, and comfort. Performing continuous monitoring to assess IEQ is increasingly proving to be important, also due to the large amount of time that people spend in closed spaces. In the present study, the design, development, and metrological characterization of a low-cost multi-sensor device is presented. The device is part of a wider system, hereafter referred to as PROMET&O (PROactive Monitoring for indoor EnvironmenTal quality & cOmfort), that also includes a questionnaire for the collection of occupants' feedback on comfort perception and a dashboard to show end users all monitored data. The PROMET&O multi-sensor monitors the quality conditions of indoor environments thanks to a set of low-cost sensors that measure air temperature, relative humidity, illuminance, sound pressure level, carbon monoxide, carbon dioxide, nitrogen dioxide, particulate matter, volatile organic compounds, and formaldehyde. The device architecture is described, and the design criteria related to measurement requirements are highlighted. Particular attention is paid to the calibration of the device to ensure the metrological traceability of the measurements. Calibration procedures, based on the comparison to reference standards and following commonly employed or ad hoc developed technical procedures, were defined and applied to the bare sensors of air temperature and relative humidity, carbon dioxide, illuminance, sound pressure level, particulate matter, and formaldehyde. The next calibration phase in the laboratory will be aimed at analyzing the mutual influences of the assembled multi-sensor hardware components and refining the calibration functions.

Interchangeability of multi-decade skin and surface air temperature trends over land in models

Satellite land surface temperature (Ts ) records have now reached 20+ year length, but their trends may differ from historical records built from in-situ measurements of near-surface air temperature (Tas ). In the ERA5 reanalysis, 60° S–60° N land Ts and Tas trends can differ by up to ±0.06 °C decade−1 over 20 years, depending on the period, or more on smaller spatial scales. Here I use 1979–1998 outputs from ACCESS1-0 climate model simulations with prescribed land Ts to understand changes in Ts and Tas . CO2’s effective radiative forcing causes adjustments that warm Tas relative to Ts . In ACCESS1-0, vegetation enhances the adjustments to CO2 over land. Meanwhile, feedbacks in ACCESS1-0 oppose the adjustments, resulting in small long-term net effects on global temperature estimates. In coupled simulations from other models, there is no agreement on whether Ts or Tas warms more and the most extreme case shows global long-term differences of just 5% between land Ts or land Tas trends. The results contrast with over-ocean behavior where adjustments and feedbacks reinforce each other, and drive larger long-term Tas warming relative to Ts across all models.

Chemical and Thermal Exposure Risks in a Multi Compartment Training Structure

Providing NFPA 1403 compliant live-fire training can present thermal and chemical exposure risk to instructors and students. To reduce risk, training academies, fire departments, instructors, and standards setting technical committees need more information on how different training fuels used in common training structures can impact the environment in which firefighter training occurs. This study utilized a traditional concrete training structure with multiple compartments to characterize training environments with three different fuel package materials [i.e., low density wood fiberboard, oriented strand board (OSB), and wood pallets]. Exposure risks for a fire instructor located on either the first or second floor were characterized using measurements of heat flux, air temperature and airborne concentrations of several contaminants including known, probable, or possible carcinogens. It was hypothesized that utilizing a training fuel package with solid wood pallets would result in lower concentrations of these airborne contaminants [aldehydes, polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs)] than wood-based sheet goods containing additional resins and/or waxes. Additionally, it was hypothesized that these concentrations would be lower than in the single compartment Fire Behavior Lab presented in a companion manuscript. For all measured compounds other than hydrochloric acid, airborne concentrations were 10 to 100 times lower than in the Fire Behavior Lab. OSB-fueled fires produced the highest median concentrations of total PAHs and VOCs such as benzene, while the pallet fuel package produced the lowest median concentrations of these compounds. These trends generally followed the qualitative visual obscuration created by each fuel. Additional tests were conducted on the OSB-fueled fires with increased ventilation and an alternate means of reducing visibility through smoldering smoke barrels. This OSB experiment with increased ventilation resulted in the highest temperatures in the fire room but the lowest impact on visibility throughout the structure, as well as the lowest overall concentrations of contaminants in this study. In contrast, the smoldering straw-filled smoke barrel created a highly obscured environment (with minimal impact on thermal environment) and some of the highest concentrations of the targeted contaminants of any test. These data may be useful in balancing obscuration for training with potential exposure to thermal stressors and contaminants.

Increasing duration of heatwaves poses a threat to oyster sustainability in the Gulf of Mexico

The future of the wild oyster fishery in the northern Gulf of Mexico is largely uncertain due to changing environmental conditions and declining abundance of harvestable oysters. Specifically, rising temperatures can directly impact the physiological thresholds of the eastern oyster (Crassostrea virginica) at all life history stages and alter the narrow ecological niche this oyster occupies. The impact of rising temperatures is likely most pronounced during atmospheric heatwaves, defined as three or more days above the 90th percentile of daily maximum air temperatures, which have been shown to be increasing in frequency. Increasing exposure to high temperature extremes may contribute to and exacerbate an already declining oyster fishery. Critical to fishery health is recruitment i.e., the addition of new harvestable biomass, which is a dynamic process strongly driven by temperature. Here, we examine the relationship between heatwave characteristics and the prediction of poor oyster recruitment, measured as the abundance of post-larval oysters (e.g. spat) below the site-specific median density observed in historically productive oyster fisheries over 46-years (1976 – 2020) in Mobile Bay, Alabama and 21-years (1993 – 2014) in Apalachicola Bay, Florida. We acquired daily maximum air temperature measurements measured over 50 years (1970 – 2020) at weather monitoring stations adjacent to the bays to identify site specific annual heatwave events (maximum yearly air temperature, yearly and consecutive heatwave days, and number of annual heatwaves). Then, years with extreme heatwaves that exceeded the 75th percentile for the 50-year measurements were compared to years with non-extreme heatwave events. Years with extreme total heatwave days and extreme consecutive heatwave days were correlated with low post-larval oyster density. Across both bay systems, if consecutive heatwave days exceeded 11 days, then poor recruitment of oysters occurred 83 % of the time. Extreme heatwave duration as an indicator for poor recruitment has the potential to be a powerful tool for fishery managers to forecast recruitment and inform sustainable oyster harvest based on year-to-year variability in heatwave duration and long-term warming trends. Our findings illustrate how extreme temperatures can exacerbate multiple physiological and ecological stressors resulting in the loss of a keystone species for healthy and resilient coastal ecosystems.

Urban heat load assessment in Zagreb, Croatia: a multi-scale analysis using mobile measurement and satellite imagery.

A limited number of meteorological stations and sparse data challenge microclimate assessment in urban areas. Therefore, it is necessary to complement these data with additional measurements to achieve a denser spatial coverage, enabling a detailed representation of the city's microclimatic features. In this study, conducted in Zagreb, Croatia, mobile air temperature measurements were utilized and compared with satellite-derived land surface temperature (LST). Here, air temperature measurements were carried out using bicycles and an instrument with a GPS receiver and temperature probe during a heat wave in June 2021, capturing the spatial pattern of air temperature to highlight the city's microclimate characteristics (i.e. urban heat load; UHL) in extremely hot weather conditions. Simultaneously, remotely sensed LST was retrieved from the Landsat-8 satellite. Air temperature measurements were compared to city-specific street type classification, while neighbourhood heat load characteristics were analysed based on local climate zones (LCZ) and LST. Results indicated significant thermal differences between surface types and urban forms and between street types and LCZs. Air temperatures reached up to 35 °C, while LST exceeded 40 °C. City parks, tree-lined streets and areas near blue infrastructure were 1.5-3 °C cooler than densely built areas. Temperature contrasts between LCZs in terms of median LST were more emphasised and reached 9 °C between some classes. These findings highlight the importance of preserving green areas to reduce UHL and enhance urban resilience. Here, exemplified by the city of Zagreb, it has been demonstrated that the use of multiple datasets allows a comprehensive understanding of temperature patterns and their implications for urban climate research.

Temporal variation in aphid abundance throughout cucumber plant growth stages

This study aims to analyze the abundance of aphids (Aphis gossypii) on cucumber plants (Cucumis sativus L.) during both the vegetative and generative growth phases in the agricultural land of the Jambi farming community. The research employs a descriptive exploratory approach. Data were collected using a total sampling technique, involving the counting of all aphids found on sampled cucumber plants. Measurements of air humidity, temperature, and light intensity were conducted during the observation period. The results revealed that during the vegetative phase, the highest abundance of aphids occurred in the third week after planting (696 individuals), with an average abundance of 174. Conversely, the lowest abundance was observed in the first week after planting (42 individuals), averaging 10.5. In the generative phase, the highest abundance of aphids was recorded in the fifth week after planting (798 individuals), with an average abundance of 133; whereas the lowest abundance was noted in the tenth week after planting (36 individuals), averaging 6.

Urban heat island analysis based on high resolution measurement data: A case study in Beijing

Urban heat island (UHI) is a widely concerned urban climate which impacts billions of residents worldwide. Nevertheless, inadequate rigorous air temperature (Tair) measurement has become an obstacle to UHI research and mitigation, especially in megacities like Beijing. In this study, we applied a 1-km hourly Tair dataset interpolated from records of 521 stations in Beijing. The dataset enables us to analyze UHI patterns on a block scale and the impacts of landscapes combined with the local climate zones (LCZ) scheme. Our results indicate that: (1) Tair and its temporal variation in each LCZ vary significantly, which are highly relevant to their morphology and thermal-radiative properties. (2) LCZ 1 and LCZ 2 have the highest nocturnal UHI intensities (UHII). Discrepancies among LCZs also cause various temporal variations in their UHII. (3) The spatial pattern of LCZs affects regional temperature. Area ratio and aggregation extent of LCZ 1&2 show significant positive correlations with regional temperature, while LCZ A&D&G have the opposite regularity. (4) Distinct mitigation strategies are put forward for each subarea in Beijing with various endowments of population and the LCZ structure. The study provides insight into Beijing UHI and plausible mitigation advice in megacities like Beijing.

Интенсивность нейтронной компоненты космических лучей и влажность воздуха

Neutron monitor data is currently corrected only for the barometric effect. We cannot, however, exclude that changes in air humidity affect the intensity of the cosmic-ray neutron component recorded by neutron monitors. In this regard, we have carried out continuous measurements of air humidity and temperature when observing variations in the cosmic ray intensity with a neutron monitor in Novosibirsk. Analysis of the results of observations of meteorological parameters and cosmic ray intensity in Novosibirsk, as well as data from the global network of neutron monitors, made it possible to identify neutron component intensity variations caused by changes in air humidity. The estimated humidity effect indicates the need to regularly take it into account in the neutron monitor data. To do this, along with atmospheric pressure, regular measurements of humidity and air temperature should be performed.

Intensity of the neutron component of cosmic rays and air humidity

Neutron monitor data is currently corrected only for the barometric effect. We cannot, however, exclude that changes in air humidity affect the intensity of the cosmic-ray neutron component recorded by neutron monitors. In this regard, we have carried out continuous measurements of air humidity and temperature when observing variations in the cosmic ray intensity with a neutron monitor in Novosibirsk. Analysis of the results of observations of meteorological parameters and cosmic ray intensity in Novosibirsk, as well as data from the global network of neutron monitors, made it possible to identify neutron component intensity variations caused by changes in air humidity. The estimated humidity effect indicates the need to regularly take it into account in the neutron monitor data. To do this, along with atmospheric pressure, regular measurements of humidity and air temperature should be performed.

Computational simulation of the heat and mass transfer processes occurring in the containment of Novovoronezh NPP II’s units 1 and 2

The paper presents information on the key approaches to the design of the containment ventilation system for units 1 and 2 of Novovoronezh NPP II (NPP-2006 project). The authors have developed a CFD model for the containment of Novovoronezh NPP II’s units 1 and 2, which includes the key structural components and the basic equipment installed within the containment. A series of the containment air temperature measurements was undertaken during power operation of the units. Based on the measured temperature values, a series of calculations was undertaken to determine the air temperature field inside the containment. It is revealed that when ensuring the design characteristics of the cooling capacity of the ventilation system stages, the design parameters of the containment air, wall and equipment temperature are achieved. In addition, with proper mixing of the containment air, it is possible to significantly reduce the average air temperature in the most “hot” rooms. Based on the calculation results, causes have been identified for the low efficiency of the ventilation system, and specific measures have been proposed for increasing significantly the system capacity. The proposed approach to determining the characteristics of ventilation systems using modern methods of three-dimensional computational hydro-gas dynamics makes it possible to optimize and modernize existing ventilation systems, as well as to assess the efficiency of ventilation at the design stage of nuclear power plants. The developed and proposed CFD model makes it possible to do this at the modern level without resorting to bench/experimental modeling issues.