Values Of Wind Direction Research Articles

Study on optimization of shelter locations and evacuation routes of gas leakage accidents in chemical industrial park

Safety hazards cannot be ignored during the promotion of local economic development in chemical parks. In a crowded chemical industrial park, heavy casualties and serious economic losses may be incurred in a toxic gas leak accident. Accordingly, the location of emergency shelters and occupant escape routes in chemical parks during gas leakage accidents were examined in this study. Additionally, the risk of leakage in chemical parks throughout the year was assessed by selecting the average values of wind direction, wind speed and temperature across four seasons, and criteria for selecting emergency shelters were set according to the minimum risk of toxic gas leakage throughout the year. Moreover, a 30,000 t/a carbon-five separation construction project was adopted as a case study, where instantaneous leakage of an auxiliary raw material liquid ammonia storage tank occurred. The Floyd algorithm was then used to calculate the evacuation paths for people at multiple sources and multiple endpoints. The influence of the dynamic diffusion of toxic gas around the leakage source point on evacuation route safety was thoroughly analyzed, and occupant evacuation plans were employed in the chemical park based on the shortest evacuation path with the least impact from toxic gases. The findings produced by this study may provide reliable technical support guidance for safety evacuation in regard to toxic gas leakage accidents for personnel in chemical industry parks.

Comparison of multiple machine learning algorithms for urban air quality forecasting

Environmental air pollution has become one of the major threats to human lives nowadays in developed and developing countries. Due to its importance, there exist various air pollution forecasting models, however, machine learning models proved one of the most efficient methods for prediction. In this paper, we assessed the ability of machine learning techniques to forecast NO2, SO2, and PM10 in Amman, Jordan. We compared multiple machine learning methods like artificial neural networks, support vector regression, decision tree regression, and extreme gradient boosting. We also investigated the effect of the pollution station and the meteorological station distance on the prediction result as well as explored the most relevant seasonal variables and the most important minimal set of features required for prediction to improve the prediction time. The experiments showed promising results for predicting air pollution in Amman with artificial neural network outperforming the other algorithms and scoring RMSE of 0.949 ppb, 0.451 ppb, and 5.570 µg/m3 for NO2, SO2, and PM10 respectively. Our results indicated that when the meteorological variables were obtained from the same pollution station the results were better. We were also able to reduce the time by reducing the set of variables required for prediction from 11 down to 3 and achieved major time improvement by about 80% for NO2, 92% for SO2, and 90% for PM10. The most important variables required for predicting NO2 were the previous day values of NO2, humidity and wind direction. While for SO2 they were the previous day values of SO2, temperature, and wind direction values of the previous day. Finally, for PM10 they were the previous day values of PM10, humidity, and day of the year.

BOUNDARY LAYER WIND PROFILE MEASUREMENT BASED ON A SIX-ROTOR UAV ANEMOMETER

They studied the feasibility of boundary layer wind field measurement based on a six-rotor drone equipped with an anemometer, and analyzed the measured wind characteristics including average wind speed, wind direction, turbulence intensity, gust factor, the turbulence integral length and power spectrum. The results are compared with the measured results of anemometers fixed on a wind tower. The results show that the wind speed and wind direction values measured by the UAV are basically the same as the measured values on the wind tower after correction, and the error between the two is within ±3%. The accuracy of fitted wind profile by the UAV is high. The wind profile is close to the B-type geomorphic wind profile specified by the Chinese standard. The average ground roughness calculated by data fitting is 0.148. The various fluctuating wind characteristic parameters measured by the UAV are close to the measured values on the wind tower, and the error between the two is within ±5%. There is an exponential correlation between the turbulence intensity and the gust factor. The wind power spectrum measured by the UAV is basically consistent with that measured on the wind tower and is consistent with the Karman spectrum.

Regional wind pattern, a basis for defining the appropriate lapse of time for sugarcane burning in the Cauca Valley (Colombia)

Pre-harvest burning, an activity associated with manual sugarcane cutting, repels poisonous animals and makes harvesting considerably more straightforward and quicker. However, some reports from other countries that associate pre-harvest burning with human illness determined a change in the sugarcane harvest management. New crop management was based on green harvesting and the use of wind data to decide the right moment for burning. This work aimed to know the standard wind patterns to design strategies that allow sugar mills to burn sugarcane crops with minimum human health impacts. This study was based on the elaboration and analysis of 4320 wind rose plots of 30 weather stations located in the Colombian sugarcane production region. The analysis was performed at daily and monthly scales. The analysis considered the wind speed and wind direction values that increase the risk of affecting a settlement with the particulate matter when burning is done. Results showed that this region has local wind patterns that predominate direction and speed changes in response to the daily cycle. The main factor increasing the risk mentioned above is the wind speed. In this area, calm events (wind speed 5 m s−1) determine restrictions for crop burning 66% of the time. In the remaining 34% of the time, risk depends on the wind direction, and this is the ideal lapse of time for seeking the right moment for burning. The results are a tool for decision-making at different levels.

Evaluation of wind turbine power outputs with and without uncertainties in input wind speed and wind direction data

This paper analyses importance of including wind direction (WD) as an additional explanatory variable to the wind speed (WS) for evaluating uncertainty in wind turbine (WT) power output (P out). Using available measurements of an actual WT, the paper compares a ‘two-dimensional’ (2D) P out-WS model with a ‘three-dimensional’ (3D) P out-WS-WD model for two general cases: (a) for the specific input WS and WD values (i.e. WS and WD without uncertainties), and (b) for the forecasted input WS and WD values (i.e. WS and WD with uncertainties). In paper, 2D and 3D Gaussian mixture Copula model and vine Copula framework are combined with 2D and 3D Markov chain models, which are used to forecast input WS and WD data with uncertainties. The obtained results show that inclusion of WD will provide noticeable improvement for models with no uncertainties in input WS and WD data, while in the case of forecasted WS and WD data with uncertainties, WS is a much stronger contributor to the total WT P out uncertainty than WD.

An investigation to the design of high-precision wind sensing device based on piezoelectric array

A new wind sensing device based on bimorphs array is designed for apperceiving wind direction and velocity, whose structure is an L-shaped cantilevers array. A coupling model of the array is proposed to predict the response voltage stimulated by wind. By extracting the response voltage ([Formula: see text]) on each bimorph cantilever, the values of wind direction ([Formula: see text]) and velocity ([Formula: see text]) can be calculated in terms of the geometric relation. Further, the relations among wind errors, array amounts ( m) and array radius ( r) are acquired, and m & r can be utilized to decreasing angle error [Formula: see text] and velocity error [Formula: see text] of wind. The calculated and experimental results show that, increasing m initially yields decreasing these two errors, then it begins to increase the errors when m is larger than 6. The minimal wind angle and velocity errors of the array are 0.14° and 0.34%, respectively, at actual wind of 13.4 m/s, m = 6 and r = 20 mm. Meanwhile, increasing r can decrease [Formula: see text] and [Formula: see text], Besides, for calculating 20 random incidence wind angles, respectively, the range of wind velocity error is from 0.34% to 0.87%, the range of wind angle error is from 0.12°to 0.38°, and the response time is 10 ms.

1.55-μm pulse coherent LIDAR with 10-km detection range

Recently, a 1.55-μm pulsed coherent Doppler LIDAR system using all fiber optical components was developed to achieve real-time measurements of wind fields. The system employs 100-μJ pulse energy at 10 kHz pulse repetition rate. In addition, the system consists of a fiber-based optical transceiver unit, a two-axis scanner, and a multicore digital signal processor (DSP) for real-time signal processing. With compact and mobile design, the LIDAR is easy to transport and deploy for different field campaigns. For a different application of LIDAR, the range resolution can change manually. A horizontal detection range of 10 km is achieved with the temporal and spatial resolution of 1 s and 30 m, respectively. Field experiments compared with an anemometer show that correlation coefficient of the different wind speed measurements is 0.953; the correlation coefficient for wind direction values is 0.967. Continuous wind profiles of the planetary boundary layer are presented to demonstrate the stability of the system.

EFFECT OF BUILDING PLAN FORM ON HUMAN THERMAL COMFORT IN NATURALLY VENTILATED OPEN-PLAN ENCLOSURES LOCATED IN HOT CLIMATES

This study aims to examine the effect of building plan form on internal thermal comfort conditions in naturally ventilated open-plan buildings located in hot climates. The study examined the square and the rectangular plan forms in relation to several values of wind direction, building plan depth, and climatic conditions. The study utilised CFD for ventilation prediction, DesignBuilder for thermal modelling, and the Tropical Summer Index (TSI) for thermal comfort assessment. These three tools were integrated in a quantitative approach to fulfil the study aim. The study concluded that the use of area-weighted average velocity magnitude is more accurate in the assessment of natural ventilation performance, as it accounts for both internal velocity magnitude and distribution. The study confirmed the common observation that the use of shallow building plans is more effective to increase internal air velocity and improve internal thermal comfort. At some point of increased plan depth, the internal air velocity magnitude dramatically decreases. In the three examined wind directions, this occurred when the plan depth exceeded 3H in the square cases and 2.5H in the rectangular ones, where H is the building height. This value is much less than the commonly recommended maximum value of 5H. The study also concluded that reducing building depth in the square cases has generally more potential to improve thermal comfort conditions when compared with the rectangular cases. The gross increase in Percentage of People Comfortable, PPC, in all the examined cases was 23% in the square cases, compared to 11% in the rectangular cases.

The Investigation of Hourly,Daily and Seasonal Changes of Duzce Air Quality Monitoring Station 2014 Data

Aim: To evaluate data of air quality in the year 2004 in Duzce by days, hours and seasons. Method: In this study, sulfur dioxide, particulate matter levels, wind speed and wind direction values of Duzce city center obtained from the web page of Ministry of Envoriment and Planning between 1 January -31 December 2014 were studied. Data were examined by on the time of hours, days, days of the week, months and seasons. Results: Annual average PM10 was 106,42±102 μg/m3 , SO2 concentration was 6,15±5,39 μg/m3. Winter PM10 and SO2 measurements were significantly higher than summer season. Wind speed in the summer season had a higher average than the winter season. Highest average PM10 was at November 189,4 ± 171,8 μg/m3. The lowest PM10 was at June 58,0±24,5 μg/m3. The highest average wind speed was at June, the lowest average wind speed is at December. PM10 and SO2 measurements were positively correlated with wind direction, shows a negative correlation with wind speed. The highest PM10 measurements in the summer season were on Thursdays, in the winter season on Wednesdays. The lowest PM10 measurements both in two seasons were on Sundays. Average PM10 was significantly higher on weekdays than weekends. The highest PM10 value of 146,6 ± 131,3 μg/m3 was measured at 23.00. The lowest PM10 value of 73,8±55,9 μg/m3 was measured at 15.00. Conclusion: There is air pollution in Duzce both in the summer and winter. Continuous monitoring of the emissions of existing establishments in the industrial pollution control should be provided. The high PM10 measurements in the evening may be due to traffic during the day and fuel use for heating purposes. Widespread use of natural gas and creating socially conscious individual measures can be effective in reducing air pollution.

Investigation of Wind Energy Distribution in Height in Latvia

In the National Development Plan of Latvia for the time 2014 – 2020 a significant role is assigned to the renewable energy, whose share in the total energy production should be 40 %. This will facilitate the efficient use of wind energy. The paper is devoted to the investigation into the wind energy potential based on long-term observations of the wind speed and energy density fluctuations at heights from 10 to 160 m in the Latvian territory and on the coast of Baltic Sea.The wind speed and wind direction values were measured and the statistical database has been accumulated during long-term observations in 2004 – 2013 using a LOGGER 9200 Symphonie measuring systems mounted on 60 m masts – one on the western coast and the second on the north-east of Latvia. From June 2011 to May 2012, these measurements were complemented with the data for the heights from 40 to 160 m obtained by means of a ZephIR lidar located on the western coast of Latvia and with the metrological data provided by “Latvian Environment, Geology and Meteorology Centre” for the same period. The results are presented in the form of tables, bar charts and graphs. The graphs of seasonal fluctuations in the wind speed have been obtained for the heights up to 160 m by measurements over the period of 2007 – 2013. The histograms are composed for the relative frequency of repetition of the wind speed. The wind speed distribution on heights up to 200 m are analysed and the coefficients of approximating functions for two areas with different terrain types are calculated. Extrapolation results of the distribution curves of wind velocity and density mean values on heights up to 200 m are presented. The results of the research on the wind speed distribution up to 200 m are promising for evaluation of the wind energy potential in Latvia and should help in assessment of prospective sites for construction of WPPs.

Development and Application of Artificial Neural Network Modeling in Forecasting PM10 Levels in a Mediterranean City

The study of atmospheric concentration levels at a local scale is one of the most important topics in environmental sciences. Multivariate analysis, fuzzy logic, and neural networks have been introduced in forecasting procedures in order to elaborate operational techniques for level characterization of specific atmospheric pollutants at different spatial and temporal scales. Particularly, approaches based on artificial neural networks (ANNs) have been proposed and successfully applied for forecasting concentration levels of PM10, NO2, SO2, CO, and O3. The present study explores the development and application of ANN models for forecasting, 24 h ahead, not only the daily concentration levels of PM10 but also the number of hours exceeding the PM10 concentration threshold during the day in five different regions within the greater Athens area (GAA). The ANN modeling was based on measurements and estimates of the mean daily PM10 concentration, the maximum hourly NO2 concentration, air temperature, relative humidity, wind speed, and the mode daily value of wind direction from five different monitoring stations for the period 2001–2005. The evaluation of the model performance showed the risk of daily PM10 concentration levels exceeding certain thresholds as well as the duration of the exceedances can be successfully predicted. Despite the limitations of the model, the results indicate that ANNs, when adequately trained, have considerable potential to be used for 1 day ahead PM10 concentration forecasting and the duration within the GAA.

Comparison of Oceansat-2 scatterometer winds with buoy observations over the Indian Ocean and the Pacific Ocean

Oceansat-2 scatterometer (OSCAT)-derived winds were compared with in situ observations made by Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) and Triangle Trans-Ocean Buoy Network (TRITON) buoys in the Indian Ocean and the Pacific Ocean, respectively. Root mean square deviation (RMSD) for wind speed is 1.71 m s−1 for the Indian Ocean and 1.92 m s−1 for the Pacific Ocean. The wind speed accuracies are within the mission requirement (<2 m s−1), but the wind direction errors are higher than the mission requirement (>20°). The RMSD values of wind direction are 51.38° and 44.61° for the Indian Ocean and the Pacific Ocean, respectively. OSCAT winds tend to underestimate the buoy value when the wind speeds were low (<4 m s−1) and overestimate the buoy value when the wind speeds were high (>4 m s−1). The wind speed residuals show an increasing trend with the increase of wind speeds. Interestingly, the wind direction residuals decrease with increasing wind speed and deviations of wind directions are conspicuously large for lower wind speeds than for higher wind speeds. OSCAT wind speeds were relatively more accurate for the Indian Ocean than those for the Pacific Ocean.

미국 서부 국립공원 지역의 미국 서부 국립공원 지역의 PM2.5에 대한 오염원 확인 및 기여도 추정

The objective of this study was to estimate the <TEX>$PM_{2.5}$</TEX> source apportionment at the Pinnacles National Monument IMPROVE site in western coastal USA. The PMF was applied to identify the existing sources and apportion the <TEX>$PM_{2.5}$</TEX> mass to each source. To analyze local source impacts from various wind directions, the NPR analysis was performed using source contribution results with the wind direction values measured at the site. Also, PSCF was applied to identify the locations by point sources relative to the back trajectories. A total of 1,634 samples were collected from March 1988 to May 2004 by IMPROVE sampler and 32 chemical species were analyzed by PIXE, PESA, XRF, IC, and TOR methods. The PMF modeling identified seven sources and the average mass was apportioned to gasoline vehicle, secondary sulfate, aged sea salt, secondary nitrate, wood/field burning, diesel emission, and soil, respectively. In this study, the average mass was apportioned to gasoline vehicle (33.0%), secondary sulfate (25.7%), aged sea salt (17.8%), and secondary nitrate (10.1%). Also, this study suggests the possible role for source apportionment study of <TEX>$PM_{2.5}$</TEX> at similar areas such as wildness, national park, and coastal areas in Korea.

Comparison of Synthetic Aperture Radar–Derived Wind Speeds with Buoy Wind Speeds along the Mountainous Alaskan Coast

Abstract Satellite-borne synthetic aperture radar (SAR) offers the potential for remotely sensing surface wind speed both over the open sea and in close proximity to the coast. The resolution improvement of SAR over scatterometers is of particular advantage near coasts. Thus, there is a need to verify the performance of SAR wind speed retrieval in coastal environments adjacent to very complex terrain and subject to strong synoptic forcing. Mountainous coasts present a challenge because the wind direction values required for SAR wind speed retrieval algorithms cannot be obtained from global model analyses with as much accuracy there as over the open ocean or adjacent to gentle coasts where most previous SAR accuracy studies have been conducted. The performance of SAR wind speed retrieval in this challenging environment is tested using a 7-yr dataset from the mountainous coast of the Gulf of Alaska. SAR-derived wind speeds are compared with direct measurements from three U.S. Navy Oceanographic Meteorological Automatic Device (NOMAD) buoys. Both of the commonly used SAR wind speed retrieval models, CMOD4 and CMOD5, were tested, as was the impact of correcting the buoy-derived wind speed profile for surface-layer stability. Both SAR wind speed retrieval models performed well although there was some wind speed–dependent bias. This may be either a SAR wind speed retrieval issue or a buoy issue because buoys can underestimate winds as wind speed and thus sea state increase. The full set of tests is performed twice, once using wind directions from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model analyses and once using wind direction observations from the buoys themselves. It is concluded that useful wind speeds can be derived from SAR backscatter and global model wind directions even in proximity to mountainous coastlines.

미국 서부 해안 IMPROVE 측정소에 대한 대기 중 PM2.5의 오염원 기여도 추정

In this study, the chemical compositions of samples collected at the Redwood National Park IMPROVE site in California from March 1988 to May 2004 were analyzed to provide source identification and apportionment. A total of 1,640 samples were collected and 33 chemical species were analyzed by particle induced X-ray emission, proton elastic scattering analysis, photon induced X-ray fluorescence, ion chromatography, and thermal optical reflectance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified five sources and the average mass was apportioned to motor vehicle (35.8%, ), aged sea salt (23.2%, ), fresh sea salt (21.4%, ), wood/field burning (16.1%, ), and airborne soil (3.5%, ), respectively. To analyze local source impacts from various wind directions, the CPF and NPR analyses were performed using source contribution results with the wind direction values measured at the site. These results suggested that sources of are also sources of visibility degradation and then source apportionment studies derived for are also used for understanding visibility problem.

Simulation of nitrate aerosol concentrations over East Asia with the model system RAMS-CMAQ

The Models-3 Community Multi-scale Air Quality modeling system (CMAQ) coupled with the Regional Atmospheric Modeling System (RAMS) is used to analyse the geographical and the seasonal characteristics of nitrate aerosol (ANO3) concentration distributions over East Asia. Three-dimensional concentrations in January,March, April, July and October of 2001 are simulated, and for the evaluation of model performances, the simulated values of wind direction, wind speed, temperature, specific humidity, nitric oxide (NO), nitrogen oxide (NO2), ANO3 and ammonium aerosol (ANH4) are compared with the observational data obtained onboard the P-3B aircraft during its four consecutive flights over the South China Sea, the East China Sea, the Yellow Sea and the water areas to the east of Japan conducted on 13, 17, 18 and 21 March 2001. The observed data are 5-min averaged and the model results with a 1-hour temporal resolution are interpolated to the aircraft location and time using trilinear interpolation. Comparison shows that the observed values exhibit strong temporo-spatial variations, and the model reproduces these variations reasonably well. The simulated values of wind direction, wind speed, temperature and specific humidity are generally in good agreement with the observed ones, their correlation coefficients reach 0.66, 0.94, 0.99 and 0.96, respectively. Comparison also shows that the average mixing ratios of modelled and observed NO, NO2, ANO3 and ANH4 agree reasonably well with each other, the correlation coefficient for ANO3 and ANH4 are larger than 0.8, but the simulated standard deviations are smaller than the observed one, and the correlation coefficient for NO and NO2 are 0.48 and 0.44.Analysis of horizontal distributions of monthly averaged ANO3 concentrations in the boundary layer indicates that the ANO3 mixing ratios have noticeable differences among the four seasons. Generally the concentrations are high in the winter, spring and fall and low in the summer, and seasonal variations are typically strongest over China and Japan. Highest concentrations are found over eastern China where emissions of nitrogen oxides and ammonia are high and long-range transport may cause elevated concentrations in remote areas under favourable meteorological conditions, but the seasonal variation in the ANO3 concentrations is heavily influenced by the changes in precipitation and temperature.

Statistical comparison of Regional Atmospheric Modelling System forecasts with observations

AbstractA statistical comparison of observations and forecasts using the Regional Atmospheric Modelling System (RAMS) for operations at the Savannah River Site (SRS) in South Carolina is discussed. Simulated and observed values of wind direction and wind speed, collected twice daily for a two‐year period from April 1998 to March 2000, are compared in a variety of ways for five different locations in the southeastern United States. Simulated and observed turbulence intensities are also compared for a one‐year period beginning in February 1999 for the SRS. Statistical measures used for comparison are the mean absolute error, mean relative error and standard deviation. Directional errors tend to increase with forecast time while speeds tend to be underestimated over the entire forecast range, especially those exceeding 8 m s−1. Seasonally, winds are predicted with greater accuracy during the winter and spring months, when speeds in the southeastern United States are higher and direction is less variable. Vertical turbulence intensity at SRS is slightly underestimated, while horizontal turbulence intensity is slightly overestimated. In general, the statistical measures show that the model produces results with reasonable skill for the wind speed, direction and turbulence. Copyright © 2004 Royal Meteorological Society.

Winds on the 500 hPa isobaric level over Estonia (1953–1998)

The aim of the paper is to get an overview of the wind climatology in the free atmosphere above Estonia, i.e., in the middle of the Baltic Sea catchment area. Aerological soundings have been carried out at Tallinn Aerological Station since 1953. From the recorded data, daily values of wind direction and speed on the 500 hPa isobaric level have been chosen for analysis. Zonal and meridional components of wind velocity have been calculated and their average seasonal variations described. The zonal component is the largest in autumn and the weakest in summer, the meridional component is positive from April to August and negative from September to March. Separate analysis of changes in the wind speed and direction permits to establish that these changes are mostly due to changes in the wind direction. From the time series analysis, trends in the wind velocity components during the period of 1953–1992 have been estimated for different months. The analysis shows an increase in the meridional component in March and an increase in the zonal component in winter.

An investigation of winds up to 300 hPA over Turkey between 1970 and 1984

AbstractTurkish radiosonde data obtained at the meteorological stations in Istanbul, Ankara, and Izmir have been analysed in order to study the winds between 850 hPa and 300 hPa pressure levels between 1970 and 1984. The monthly mean values of both the zonal (ū) and the meridional (v̄) wind velocity components, their variances, σ2u and σ2v, and the monthly mean values of wind direction, α, were statistically determined. The constancy, Q, of the winds was then computed by taking the ratio of the monthly mean resultant wind speed (V̄t) and the monthly mean scalar wind speed (V̄s). The results were interpreted by taking local wind patterns into consideration.

Meteorological factors affecting SO 2 pollution levels in venice

Sulfur dioxide concentrations in the historical center of Venice and its surroundings are related to meteorological parameters using mean hourly SO 2 measurements. These were recorded over a two year period at ten automatic stations belonging to the air quality monitoring network installed by the Governmental Health Department. Meteorological data, including mean hourly values of wind direction and speed, temperature, cloudiness, pressure, humidity, rainfall and visibility were provided by a meteorological station in the network. Effects of various meteorological parameters on measured SO 2 concentrations were examined individually and in combination. Analysis showed that the relationship between SO 2 concentration and a particular meteorological parameter can often be explained by the relationship between wind direction and that parameter. Additional results regarding the seasonal and diurnal cycles of pollution levels are also presented. Finally, a detailed study was carried out of the causes of high concentration pollution episodes in the historical center of Venice, whose artistic patrimony, unique in the world, is being seriously damaged by air pollution. Analysis showed that a limited number of such episodes occur only in winter and mainly in conjunction with very light westerly winds.