ASSESSMENT OF THE STATE OF FOREST STANDS OF ROSSOSHANSKY FORESTRY

This article discusses the results of the assessment of the state of forest stands of the Rossoshansky forestry. The research was conducted in 2020 at 2 trial sites. When conducting a survey on wood species from infectious pathologies at the trial sites of the Rossoshansky forestry, diseases of the assimilation apparatus, necrotic-cancerous diseases, root and stem rot were noted. Also identified entomovrediteley this plant. The stability class, the average score of the stand state, the digression stage, and the fautiness of the trees were determined.

Avalanche danger level characteristics from field observations of snow instability

Avalanche danger levels are described in qualitative terms that mostly are not amenable to measurements or observations. However, estimating and improving forecast consistency and accuracy require descriptors that can be observed or measured. Therefore, we aim to characterize the avalanche danger levels based on expert field observations of snow instability. We analyzed 589 field observations by experienced researchers and forecasters recorded mostly in the region of Davos (Switzerland) during 18 winter seasons (2001–2002 to 2018–2019). The data include a snow profile with a stability test (rutschblock, RB) and observations on snow surface quality, drifting snow, signs of instability and avalanche activity. In addition, observers provided their estimate of the local avalanche danger level. A snow stability class (very poor, poor, fair, good, very good) was assigned to each profile based on RB score, RB release type and snowpack characteristics. First, we describe some of the key snowpack characteristics of the data set. In most cases, the failure layer included persistent grain types even after a recent snowfall. We then related snow instability data to the local avalanche danger level. For the danger levels 1–Low to 4–High, we derived typical stability distributions. The proportions of profiles rated poor and very poor clearly increased with increasing danger level. For our data set, the proportions were 5 %, 13 %, 49 % and 63 % for the danger levels 1–Low to 4–High, respectively. Furthermore, we related the local avalanche danger level to the occurrence of signs of instability such as whumpfs, shooting cracks and recent avalanches. The absence of signs of instability was most closely related to 1–Low and the presence of them to 3–Considerable. Adding the snow stability class and the 3 d sum of new snow depth improved the discrimination between the lower three danger levels. Still, 2–Moderate was not well described. Nevertheless, we propose some typical situations that approximately characterize each of the danger levels. Obviously, there is no single easily observable set of parameters that would allow us to fully characterize the avalanche danger levels. One reason for this shortcoming is the fact that the snow instability data we analyzed usually lack information on spatial frequency, which is needed to reliably assess the danger level.

Evaluation Method of Complex Slope Stability in Construction Industry Based on Correlation Calculation

Based on the basic-element expression method and correlation function theory in Extenics, combined with the knowledge of slope engineering, a method for evaluating the stability of complex slope is proposed. The evaluation process includes the selection of suitable evaluation indexes of slope stability, identificationof the classification standard for the slope stability, identificationof the weights of evaluation indexes by using the improved analytic hierarchy process,identificationof the classical domain, node domain and matter-element under evaluation,the calculation of the correlation of each stability class for each evaluation index, normalization of correlation,and so on. The selection rule of the slop stability evaluation indexes and selection of correlation function and optimal points are also discussed, which can provide reference for slope engineering designin construction industry.

The Relationship between Air Stability and Visibility over Baghdad City

In this study, Pasquill atmospheric stability determined at daytime for January and July 2010 fixed for Baghdad city. The classification of stability was made using data of wind speed and solar radiation. These classes were compared with atmospheric stability recorded hourly in Baghdad airport station. The results show that stability class, B and C make up the highest percentages, while class A is non-existent during winter "this" can be attributed to prevailing parameter weather and their frequencies such as temperature, wind speed, and solar radiation. The stability classes were estimated to be medium to moderate. In summer, B and A-B stability classes were more predominant than others. Visibility in January month is very high and concentrated at 8500-11500 meters and has a rate of 75%, while the bad visibility range at this month is about 7.6%. In July month the rate of clear weather conditions of visibility is about 65.8%. Atmospheric elements (temperature, relative humidity wind speed, solar radiation) are compared with visibility at specified stability class to show it’s affected on visibility. If more stable conditions existed this refers to the better extent of visibility, this means unstable conditions reduce atmospheric visibility with help of atmospheric elements. Overall, the most affected class on the visibility is neutral condition and near-neutral condition, but you may determine the location if there is near to the location of emission pollutant or aerosols, consequently, the case is different.

Avalanche danger level characteristics from field observations of snow instability

Avalanche danger levels are described in qualitative terms that mostly are not amenable to measurements or observations. However, estimating and improving forecast consistency and accuracy requires descriptors that can be observed or measured. Therefore, we aim to characterize the avalanche danger levels based on expert field observations of snow instability. We analyzed 589 field observations by experienced researchers and forecasters recorded mostly in the region of Davos (Switzerland) during 18 winter seasons (2001–2002 to 2018–2019). The data include a snow profile with a stability test (rutschblock, RB) and observations on snow surface quality, drifting snow, signs of instability and avalanche activity. In addition, observers provided their estimate of the local avalanche danger level. A snow stability class (very poor, poor, fair, good, very good) was assigned to each profile based on RB score, RB release type and snowpack characteristics. First, we describe some of the key snowpack characteristics of the data set. In most cases, the failure layer included persistent grain types, even after a recent snowfall. We then related snow instability data to the local avalanche danger level. For the danger levels 1–Low to 4–High, we derived typical stability distributions. The proportions of profiles rated poor and very poor clearly increased with increasing danger level. For our data set, the proportions were 5 %, 13 %, 49 % and 63 % for the danger levels 1–Low to 4–High, respectively. Furthermore, we related the local avalanche danger level to the occurrence of signs of instability such as whumpfs, shooting cracks and recent avalanches. The absence of signs of instability was most closely related to 1–Low, the presence to 3–Considerable. Adding the snow stability class and the 3-day sum of new snow depth improved the discrimination between the lower three danger levels. Still, 2–Moderate was not well described. Nevertheless, we propose some typical situations that approximately characterize each of the danger levels. Obviously, there is no single easily observable set of parameters that would allow fully characterizing the avalanche danger levels. One reason for this shortcoming is the fact that the snow instability data we analyzed usually lack information on spatial frequency, which is needed to reliably assess the danger level.

Estimation of Radiological Consequences at a Proposed Nuclear Power Plant Site Using Atmospheric Dispersion Code

Atmospheric dispersion modeling and radiation dose calculation have been performed for a generic 1000 MW water-water energy reactor (VVER-1000) assuming a hypothetical loss of coolant accident (LOCA). Atmospheric dispersion code, International Radiological Assessment System (InterRAS), was employed to estimate the radiological consequences of a severe accident at a proposed nuclear power plant (NPP) site. The total effective dose equivalent (TEDE) and the ground deposition were calculated for various atmospheric stability classes, A to F, with the site-specific averaged meteorological conditions. From the analysis, 3.7×10−1 Sv was estimated as the maximum TEDE corresponding to a downwind distance of 0.1 km within the dominating atmospheric stability class (class A) of the proposed site. The intervention distance for evacuation (50 mSv) and sheltering (10 mSv) were estimated for different stability classes at different distances. The intervention area for evacuation ended at 0.5 km and that for sheltering at 1.5 km. The results from the study show that designated area for public occupancy will not be affected since the estimated doses were below the annual regulatory limits of 1 mSv.

Characterization of Atmospheric Radiological Dispersion Alongside Risky Location Designation and Shelter House Proposition Around the Planned Rooppur Nuclear Power Plant

The prevailing meteorological conditions around the site of the proposed Rooppur Nuclear Power Plant have been studied vigorously. The in-depth perusal has revealed the existence of three seasons—summer, rainy, and winter with stability classes A, B, and A, respectively, during the day and F during the night. The eventual wind speed and direction of the seasons have been observed. Subsequent locations along the dispersion directions have been identified using googleearthpro, which includes highways, educational institution, medical centers, commercial area, etc. Dose contours corresponding to a source term equivalent to Fukushima accident have been created to verify the dispersion direction and perceive the plume arrival time in the designated locations using health physics code HotSpot. Strong dependency of plume arrival time on the stability classes has been observed, and lowest values are found for F stability class. Finally, some shelter houses are proposed to accommodate endangered inhabitants during emergency.

Assessing Peak-To-Mean Ratios of Odour Intensity in the Atmosphere near Swine Operations

Odour in the atmosphere is usually characterized by an intermittent time series of high peaks and periods of low (or zero) concentrations. The peak-to-mean ratio (PMR) is commonly used to estimate short-term peaks from long-term averages to assess the odour impact. The objective of this study was to quantify the peak-to-mean ratio of odour intensity (PMR_OI) in the atmosphere near swine operations. Fifteen human assessors (sniffers) were trained to use an 8 point odour intensity scale to measure odour intensity in the ambient air near two swine operations. In each measurement session, the sniffers were placed 0° (in the direction of wind), 30°, and 45° from the wind directions at 100, 500, and 1000 m from the swine operations to sniff odour in the air every 10 s for 30 min. The results showed that odour in the atmosphere was intermittent. The intermittency (% of time when odour was detected) increased with the averaging time and decreased with the distance from the odour source and the direction from the wind. The measured intermittency ranged from 13% to 85%. The PMR_OI increased with the averaging time, the distance from the source, and the direction from the wind. In the wind direction, the largest difference in PMR_OI between 1 and 30 min averaging times was 68% (2.5 vs. 4.2), which occurred at 1000 m from the odour source under stability class B. The average PMR_OI increased from 1.5 at 100 m to 3.5 at 1000 m. Atmospheric stability had a noticeable effect on PMR_OI. At 1000 m, the 30 min PMR_OI decreased from 4.2 at stability class B (unstable) to 2.4 at E (slightly stable).

A modeled radiological dispersive device release and the impact to decision-making in an urban environment

A radiological dispersion device is a weapon that combines radioactive material with conventional explosives for spreading radioactive material across an inhabited area. This study is focused on evaluating key parameters in an radiological dispersion device scenario. The calculations were performed to include two different situations: by using explosives and by simple mechanical release. Simulations were conducted with the use of the HotSpot Health Physics Codes. The results suggest the existence of significant correlations between stability classes in scenarios where they evolve with time, producing alternations between them. As long as the stability class remains constant, this latter finding offers the possibility of creating a suitable response, based on temporal evolutions. Therefore, the purpose of this study is to: estimate the size of the potentially affected population, estimate absorbed doses, and estimate the cost-effectiveness in order to help initial responses by providing time-sensitive information about the event. A methodology capable of providing useful information allows prompt decisions and initial assessments of future risks to be made efficiently. This approach can also provide a training environment for the personnel responsible for the decision-making at an early stage of the response.