scholarly journals Study the Concentration of SO2 Emitted From Daura Refinery by Using Screen View Model

2019 ◽  
Vol 29 (3) ◽  
pp. 7
Author(s):  
Ramiz M. Shubbar ◽  
Abthal Jihad Suadi ◽  
Monim H. Al-Jiboori
Keyword(s):  
Wind Speed ◽  
Ambient Temperature ◽  
Atmospheric Stability ◽  
Weather Conditions ◽  
Ambient Air ◽  
Point Sources ◽  
Oil Refinery ◽  
Physical Factors ◽  
Buoyant Force ◽  
Surrounding Atmosphere

In this study, the concentrations of sulfur dioxide (SO2) were emitted from the Daura oil refinery units and their effect on the surrounding areas of the refinery were investigated, and also, study the atmospheric stability effective by using the Screen View model, and check the effect of the wind speed and direction on the spread of pollutants. As indicated during this study, the physical factors of the sources of pollution, such as the height of the chimney, its diameter and the surrounding environmental conditions, contributed to the increase in the concentration of contaminants. It was generally observed that the concentration of SO2 increased by increasing the rates of airflow and ambient temperature. This work was prove the influences of weather conditions in the transmission and spread of pollutants such as wind speed, wind direction, atmospheric stability and ambient temperature, but the effect of ambient air temperature was lower than others variables. When the distance increases between the plume and the source of pollution, a heat exchange takes place with the surrounding atmosphere, the difference between the temperature of the emitted gas and the surrounding atmosphere decreases and the buoyant force increases. This leads to a lack of vertical movement that disperses the contaminants. In addition, the concentration of the pollutants decreases with the distance increases from the source of the pollution. In the present work, emission rate of SO2, and stack gas exit velocity calculated for all stacks (point sources) of the twelve production units during August 2013, and February 2014 by using the actual amounts of fuel consumed in Daura refinery in this period.

Analisis Kosentrasi Total Solid Particulate (TSP) dan Karbon Monoksida (CO) Pada Ruas Jalan Utama di Kota Kendari

2021 ◽  
Vol 4 (2) ◽  
pp. 34-39
Author(s):  
Sirajuddin Sarah Soraya ◽  
Sumarlin Marlin ◽  
Rosdiana Rosdiana
Keyword(s):  
Wind Speed ◽  
Quality Standards ◽  
Ambient Air ◽  
Total Solid ◽  
Quality Standard ◽  
Anthropogenic Factors ◽  
Physical Factors ◽  
Vehicle Traffic

This study analyzed the concentrations of TSP and CO at 2 different sites in Kota Kendari. Measurement of TSP levels at the site I, Jl. MT Haryono, the highest concentration occurred in the morning (79 g/Nm3) compared to midday (51 g/Nm3) and in the afternoon (46 g/Nm3). Judging from the quality standards based on PP No. 41 of the year 1999, the concentration of TSP and CO on Jl. MT Haryono has not exceeded the quality standard. However, according to PP No. 22 of the year 2021, the CO level has reached the quality standard threshold. At site II, the TSP level at Jl. The highest Achmad Yani occurred in the morning at 63 g/Nm3 compared to midday (28 g/Nm3) and in the afternoon (35 g/Nm3) while CO levels in the morning, afternoon, and evening remained stable at 12,000 g/Nm3. Based on PP No. 41 of the year 1999, the concentrations of TSP and CO in ambient air on Jl. Ahmad Yani has not exceeded the quality standard, but if it is reviewed based on PP no. 22 of the year 2021, CO levels have exceeded the quality standard threshold. Physical factors (temperature, wind speed, and humidity) and anthropogenic factors such as motorized vehicle traffic are maybe contributions.

scholarly journals Modeling NOx, CO, SO2 and PM emissions from Sabzevar cement plant using SCREEN3 software

2022 ◽  
Author(s):  
SS Keykhosravi ◽  
F Nejadkoorki ◽  
Amin Toosi
Keyword(s):  
Wind Speed ◽  
Environmental Protection Agency ◽  
Sampling Period ◽  
Weather Conditions ◽  
Cement Industry ◽  
Fuel Oil ◽  
Physical Factors ◽  
Factors Associated ◽  
Cement Factory ◽  
Clean Air

Introduction: Nowadays, the cement industry is regarded as one of the most important air pollution industries globally. This study aimed to simulate the emission of NOx, CO, SO2, and PM pollutants caused by the Sabzevar Cement Factory chimney by SCREEN3 software.  Materials and Methods: In this study, the SCREEN3 software was employed for the distribution of NOx, CO, SO2, and PM pollutants. The inputs of the model include the concentration and emission of pollutant gases, physical factors associated with the cement factory chimney, wind speed and direction, ambient temperature, and stability classes.  Results: The results of this study indicated that the maximum concentrations of NOx, CO, SO2, and PM by the SCREEN3 software occurred in unstable weather conditions (B) and wind speed of 5 m.s. The highest concentrations of NOx, CO, and PM (use of gas) were at a distance of 1400 meters from the factory chimney with the rates of 0.9, 0.32, 6.2 μg.m³, respectively. Moreover, the highest concentrations of NOx, CO, SO2, and PM (using fuel oil) were predicted at a distance of 1100 m from the factory chimney with 19.5, 360, 9, and 7.9 μg.m³, respectively. A comparison of the obtained results with the standard of the Environmental Protection Agency of Iran (EPA) revealed that the concentrations of NOx, CO, SO2, and PM were not higher than the standards.  Conclusion: The comparison of results with EPA standard and Iranian clean air standard showed that NOX, CO, SO2, and PM concentrations were not higher than standards during the sampling period.

Bioaerosols from the land application of biosolids in the desert southwest USA

2004 ◽  
Vol 50 (1) ◽  
pp. 7-12 ◽  
Author(s):  
J.P. Brooks ◽  
B.D. Tanner ◽  
K.L. Josephson ◽  
C.P. Gerba ◽  
I.L. Pepper
Keyword(s):  
Dry Weight ◽  
Weather Conditions ◽  
Ambient Air ◽  
Land Application ◽  
Point Sources ◽  
Plate Count ◽  
Cotton Field ◽  
Application Process ◽  
Air Samples ◽  
Soil Particles

This study evaluated bioaerosol emissions during land application of Class B biosolids in and around Tucson, Arizona, to aid in developing models of the fate and transport of bioaerosols generated from the land application of biosolids. Samples were collected for 20 min at distances between 2 m and 20 m downwind of point sources, using an SKC BioSampler® impinger. A total of six samples were collected per sampling event, which consisted of a biosolid spray applicator applying liquid biosolids to a cotton field. Each application represented one exposure. Samples were collected in deionised water amended with peptone and antifoam agent. Ambient weather conditions were also monitored every 10 min following initiation of sampling. Concurrently with downwind samples, background (ambient) air samples were collected to compensate for any ambient airborne microorganisms. In addition, biosolids samples were collected for analysis of target indicator and pathogenic organisms. Soil samples were also collected and analysed. Significant numbers of heterotrophic plate count (HPC) bacteria were found in air samples collected during the biosolid application process. These could have arisen from soil particles being aerosolised during the land application process. Aerosolised soil may contribute significantly to the amount of aerosolised microorganisms. Soil particles may be able to more readily aerosolise, due to their low density, small particle size and low mass. Aerosolised HPC bacteria found during biosolids land application were similar to those found during normal tractor operation on non-biosolids applied fields. Coliforms and coliphages were not routinely detected even though they were found to be present in the biosolids at relatively high concentrations, 106 and 104/g (dry weight) of biosolids respectively. This could be due to the die-off rate of aerosolised Gram-negative bacteria or sorption to the solid portion of the biosolids. Low numbers of aerosolised coliphages may likewise be due to sorption phenomena. We theorise that only organisms in the aqueous phase of the biosolids were available to desorb and be aerosolised. Animal viruses, which were not detected in the biosolids, were likewise not detected in the aerosol samples. Clostridium perfringens was detected in only a small percent of aerosol samples although it was detected during all weather conditions; other microorganisms were detected during more favourable environmental conditions (relative humidity >10%). Despite the fact that many of these organisms were present in the biosolids at significant concentrations, their presence in bioaerosols generated during the land application of biosolids was limited to only a small percentage of samples. Bacteria as well as viruses may sorb to biosolids, which contain a high percentage of organic matter, and desorption during land application of biosolids may not readily take place; therefore, these microorganisms may not be readily aerosolised.

scholarly journals Characteristics of the Springtime Alpine Valley Atmospheric Boundary Layer Using Self-Organizing Maps

2015 ◽  
Vol 54 (10) ◽  
pp. 2077-2085 ◽  
Author(s):  
Marwan Katurji ◽  
Bob Noonan ◽  
Peyman Zawar-Reza ◽  
Tobias Schulmann ◽  
Andrew Sturman
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Atmospheric Boundary Layer ◽  
Learning Algorithm ◽  
Potential Temperature ◽  
Atmospheric Stability ◽  
Weather Conditions ◽  
Self Organizing Maps ◽  
Alpine Valley ◽  
Self Organizing

AbstractVertical profiles of wind velocity and air temperature from a sound detection and ranging (sodar) radio acoustic sounding system (RASS)-derived dataset within an alpine valley of the New Zealand Southern Alps were analyzed. The data covered the month of September 2013, and self-organizing maps (SOM; a data-clustering approach that is based on an unsupervised machine-learning algorithm) are used to detect topological relationships between profiles. The results of the SOM were shown to reflect the physical processes within the valley boundary layer by preserving valley boundary layer dynamics and its response to wind shear. By examining the temporal evolution of ridgetop wind speed and direction and SOM node transitions, the sensitivity of the valley boundary layer to ridgetop weather conditions was highlighted. The approach of using a composite variable (wind speed and potential temperature) with SOM was successful in revealing the coupling of dynamics and atmospheric stability. The results reveal the capabilities of SOM in analyzing large datasets of atmospheric boundary layer measurements and elucidating the connectivity of ridgetop wind speeds and valley boundary layers.

scholarly journals The Relationship between Air Stability and Visibility over Baghdad City

2021 ◽  
Vol 32 (2) ◽  
pp. 82
Author(s):  
Ahmed F. Hassoon ◽  
Mohammed M. Ahmed ◽  
Nadia M. Abd
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Atmospheric Stability ◽  
Weather Conditions ◽  
Neutral Condition ◽  
Stability Class ◽  
Stable Conditions ◽  
Class B ◽  
Using Data ◽  
The Stability

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.

scholarly journals Changes in ambient temperature increase hospital outpatient visits for allergic rhinitis in Xinxiang, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jianhui Gao ◽  
Mengxue Lu ◽  
Yinzhen Sun ◽  
Jingyao Wang ◽  
Zhen An ◽  
...  
Keyword(s):  
Allergic Rhinitis ◽  
Ambient Temperature ◽  
Positive Association ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Hospital Outpatient ◽  
Distributed Lag ◽  
Outpatient Visits ◽  
Daily Data ◽  
The Relationship

Abstract Background The effect of ambient temperature on allergic rhinitis (AR) remains unclear. Accordingly, this study aimed to explore the relationship between ambient temperature and the risk of AR outpatients in Xinxiang, China. Method Daily data of outpatients for AR, meteorological conditions, and ambient air pollution in Xinxiang, China were collected from 2015 to 2018. The lag-exposure-response relationship between daily mean temperature and the number of hospital outpatient visits for AR was analyzed by distributed lag non-linear model (DLNM). Humidity, long-time trends, day of the week, public holidays, and air pollutants including sulfur dioxide (SO2), and nitrogen dioxide (NO2) were controlled as covariates simultaneously. Results A total of 14,965 AR outpatient records were collected. The relationship between ambient temperature and AR outpatients was generally M-shaped. There was a higher risk of AR outpatient when the temperature was 1.6–9.3 °C, at a lag of 0–7 days. Additionally, the positive association became significant when the temperature rose to 23.5–28.5 °C, at lag 0–3 days. The effects were strongest at the 25th (7 °C) percentile, at lag of 0–7 days (RR: 1.32, 95% confidence intervals (CI): 1.05–1.67), and at the 75th (25 °C) percentile at a lag of 0–3 days (RR: 1.15, 95% CI: 1.02–1.29), respectively. Furthermore, men were more sensitive to temperature changes than women, and the younger groups appeared to be more influenced. Conclusions Both mild cold and mild hot temperatures may significantly increase the risk of AR outpatients in Xinxiang, China. These findings could have important public health implications for the occurrence and prevention of AR.

Robust Environmental Sensing Using UAVs

2021 ◽  
Vol 2 (4) ◽  
pp. 1-20
Author(s):  
Ahmed Boubrima ◽  
Edward W. Knightly
Keyword(s):  
Air Pollution ◽  
Gas Sensors ◽  
High Performance ◽  
Weather Conditions ◽  
Ambient Air ◽  
Mission Planning ◽  
Pollution Monitoring ◽  
Compound Pollution ◽  
Planning Algorithm

In this article, we first investigate the quality of aerial air pollution measurements and characterize the main error sources of drone-mounted gas sensors. To that end, we build ASTRO+, an aerial-ground pollution monitoring platform, and use it to collect a comprehensive dataset of both aerial and reference air pollution measurements. We show that the dynamic airflow caused by drones affects temperature and humidity levels of the ambient air, which then affect the measurement quality of gas sensors. Then, in the second part of this article, we leverage the effects of weather conditions on pollution measurements’ quality in order to design an unmanned aerial vehicle mission planning algorithm that adapts the trajectory of the drones while taking into account the quality of aerial measurements. We evaluate our mission planning approach based on a Volatile Organic Compound pollution dataset and show a high-performance improvement that is maintained even when pollution dynamics are high.

scholarly journals Ambient temperature and subsequent COVID-19 mortality in the OECD countries and individual United States

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Costas A. Christophi ◽  
Mercedes Sotos-Prieto ◽  
Fan-Yun Lan ◽  
Mario Delgado-Velandia ◽  
Vasilis Efthymiou ◽  
...  
Keyword(s):  
United States ◽  
Ambient Temperature ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Weather Conditions ◽  
Oecd Countries ◽  
Epidemiological Studies ◽  
Sociodemographic Factors ◽  
Sensitivity Analyses ◽  
Inverse Association

AbstractEpidemiological studies have yielded conflicting results regarding climate and incident SARS-CoV-2 infection, and seasonality of infection rates is debated. Moreover, few studies have focused on COVD-19 deaths. We studied the association of average ambient temperature with subsequent COVID-19 mortality in the OECD countries and the individual United States (US), while accounting for other important meteorological and non-meteorological co-variates. The exposure of interest was average temperature and other weather conditions, measured at 25 days prior and 25 days after the first reported COVID-19 death was collected in the OECD countries and US states. The outcome of interest was cumulative COVID-19 mortality, assessed for each region at 25, 30, 35, and 40 days after the first reported death. Analyses were performed with negative binomial regression and adjusted for other weather conditions, particulate matter, sociodemographic factors, smoking, obesity, ICU beds, and social distancing. A 1 °C increase in ambient temperature was associated with 6% lower COVID-19 mortality at 30 days following the first reported death (multivariate-adjusted mortality rate ratio: 0.94, 95% CI 0.90, 0.99, p = 0.016). The results were robust for COVID-19 mortality at 25, 35 and 40 days after the first death, as well as other sensitivity analyses. The results provide consistent evidence across various models of an inverse association between higher average temperatures and subsequent COVID-19 mortality rates after accounting for other meteorological variables and predictors of SARS-CoV-2 infection or death. This suggests potentially decreased viral transmission in warmer regions and during the summer season.

Analysis of the Ventilation Effects on Radon-222 Exhalation in a Dead-End Tunnel

2015 ◽  
Vol 713-715 ◽  
pp. 304-313
Author(s):  
Shu Guang Wang ◽  
Wei Yang ◽  
Qing Chen ◽  
Jian Hua Chen ◽  
Cong Han
Keyword(s):  
High Temperature ◽  
Ambient Temperature ◽  
Natural Ventilation ◽  
Weather Conditions ◽  
Calculation Model ◽  
Radon Exhalation Rate ◽  
Exhalation Rate ◽  
Radon Exhalation ◽  
Exhaust Ventilation ◽  
Dead End

The regularity of radon exhalation rate in the over-broken granite tunnel is susceptible to weather conditions and ventilation styles. Based on the calculation model of radon exhalation in tunnel, some experiments have been carried out to analyze the variations of radon exhalation in cases of natural ventilation, blowing ventilation and exhaust ventilation separately. The results show that there is a linear relation between the radon exhalation and the natural ventilation quantity, and also between the radon exhalation and the ambient temperature; the radon exhalation in the case of exhaust ventilation is 63% higher than that in the blowing case under the condition of the same ventilation quantity and ambient temperature. Therefore, it is suggested that operation in the tunnel in high temperature be avoided in summer, and the blowing ventilation be adopted as an effective way for ventilation.

Statistical Analysis of Weather Effects on PM2.5

2012 ◽  
Vol 610-613 ◽  
pp. 1033-1040
Author(s):  
Wei Dai ◽  
Jia Qi Gao ◽  
Bo Wang ◽  
Feng Ouyang
Keyword(s):  
Statistical Analysis ◽  
Wind Speed ◽  
Relative Humidity ◽  
Statistical Methods ◽  
Predictive Analytics ◽  
Hypothesis Test ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Statistical Distribution ◽  
Weather Effects

Effects of weather conditions including temperature, relative humidity, wind speed, wind and direction on PM2.5 were studied using statistical methods. PM2.5 samples were collected during the summer and the winter in a suburb of Shenzhen. Then, correlations, hypothesis test and statistical distribution of PM2.5 and meteorological data were analyzed with IBM SPSS predictive analytics software. Seasonal and daily variations of PM2.5 have been found and these mainly resulted from the weather effects.

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