scholarly journals Relationships between Vertical Temperature Gradients and PM10 Concentrations during Selected Weather Conditions in Upper Silesia (Southern Poland)

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 125
Author(s):  
Ewa Bożena Łupikasza ◽  
Tadeusz Niedźwiedź
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Wind Speed ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Weather Conditions ◽  
Temperature Inversion ◽  
Temperature Gradients ◽  
Upper Silesia ◽  
Southern Poland

This paper studies surface air temperature inversions and their impact on air pollution under the background of meteorological conditions in southern Poland. The relationship of temperature gradients and air quality classes with weather conditions in the most urbanized and polluted part of Poland as represented by the Upper Silesia region (USR) within the administrative boundaries of the Górnośląsko-Zagłębiowska Metropolis (GZM) is presented. Based on probability analysis this study hierarchized the role of the selected weather elements in the development of surface-based temperature inversion (SBI) and air quality (AQ). The thresholds of weather elements for a rapid increase in the probability of oppressive air pollution episodes were distinguished. Although most SBI occurred in summer winter SBIs were of great importance. In that season a bad air quality occurred during >70% of strong inversions and >50% of moderate inversions. Air temperature more strongly triggered AQ than SBI development. Wind speed was critical for SBI and significant for AQ development. A low cloudiness favored SBI occurrence altered air quality in winter and spring during SBI and favored very bad AQ5 (>180 µg/m3) occurrence. The probability of high air pollution enhanced by SBI rapidly increased in winter when the air temperature dropped below −6 °C the wind speed decreased below 1.5 m/s and the sky was cloudless. Changes in the relative humidity did not induce rapid changes in the occurrence of bad AQ events during SBI

scholarly journals Influence of Meteorological Parameters on Air Quality at Hashemite University, Jordan

2017 ◽  
Vol 12 (2) ◽  
pp. 211-221
Author(s):  
Sana’a Odata ◽  
Abu- Allabanb ◽  
Khitam Odibatb
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Wind Speed ◽  
Relative Humidity ◽  
Air Temperature ◽  
Negative Correlation ◽  
Air Pollutants ◽  
Meteorological Parameters ◽  
Positive Correlation ◽  
Hashemite University

Four threshold air pollutants (SO2, NO, NO2, and O3) in addition to meteorological parameters were monitored at the Campus of the Hashemite University (HU) for two years (1/1/2012 through 30/12/013). Correlations between air pollution and meteorological parameters were derived. The results showed that O3 has a positive correlation with air temperature, wind speed and wind direction, but has a negative correlation with the relative humidity (RH). SO2 was found to have a negative correlation with the RH and wind speed, but positive correlation with air temperature. NO has negative correlation with air temperature, RH, and wind speed. And finally, NO2 has a negative correlation with RH and wind speed, but it has positive correlation with air temperature. Justify the reasons in brief with recommendations to improve the air quality

scholarly journals Air pollution forecasting application based on deep learning model and optimization algorithm

2021 ◽  
Author(s):  
Azim Heydari ◽  
Meysam Majidi Nezhad ◽  
Davide Astiaso Garcia ◽  
Farshid Keynia ◽  
Livio De Santoli
Keyword(s):  
Air Pollution ◽  
Wind Speed ◽  
Power Plant ◽  
Air Temperature ◽  
Short Term Memory ◽  
Combined Cycle ◽  
Short Term ◽  
Term Memory ◽  
Proposed Model ◽  
Long Short Term Memory

AbstractAir pollution monitoring is constantly increasing, giving more and more attention to its consequences on human health. Since Nitrogen dioxide (NO2) and sulfur dioxide (SO2) are the major pollutants, various models have been developed on predicting their potential damages. Nevertheless, providing precise predictions is almost impossible. In this study, a new hybrid intelligent model based on long short-term memory (LSTM) and multi-verse optimization algorithm (MVO) has been developed to predict and analysis the air pollution obtained from Combined Cycle Power Plants. In the proposed model, long short-term memory model is a forecaster engine to predict the amount of produced NO2 and SO2 by the Combined Cycle Power Plant, where the MVO algorithm is used to optimize the LSTM parameters in order to achieve a lower forecasting error. In addition, in order to evaluate the proposed model performance, the model has been applied using real data from a Combined Cycle Power Plant in Kerman, Iran. The datasets include wind speed, air temperature, NO2, and SO2 for five months (May–September 2019) with a time step of 3-h. In addition, the model has been tested based on two different types of input parameters: type (1) includes wind speed, air temperature, and different lagged values of the output variables (NO2 and SO2); type (2) includes just lagged values of the output variables (NO2 and SO2). The obtained results show that the proposed model has higher accuracy than other combined forecasting benchmark models (ENN-PSO, ENN-MVO, and LSTM-PSO) considering different network input variables. Graphic abstract

scholarly journals Regional Features of Long-Term Exposure to PM2.5 Air Quality over Asia under SSP Scenarios Based on CMIP6 Models

2021 ◽  
Vol 18 (13) ◽  
pp. 6817
Author(s):  
Sungbo Shim ◽  
Hyunmin Sung ◽  
Sanghoon Kwon ◽  
Jisun Kim ◽  
Jaehee Lee ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
East Asia ◽  
Climate Model ◽  
Fine Particulate Matter ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Quality Controls ◽  
Quality Guidelines

This study investigates changes in fine particulate matter (PM2.5) concentration and air-quality index (AQI) in Asia using nine different Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from historical and future scenarios under shared socioeconomic pathways (SSPs). The results indicated that the estimated present-day PM2.5 concentrations were comparable to satellite-derived data. Overall, the PM2.5 concentrations of the analyzed regions exceeded the WHO air-quality guidelines, particularly in East Asia and South Asia. In future SSP scenarios that consider the implementation of significant air-quality controls (SSP1-2.6, SSP5-8.5) and medium air-quality controls (SSP2-4.5), the annual PM2.5 levels were predicted to substantially reduce (by 46% to around 66% of the present-day levels) in East Asia, resulting in a significant improvement in the AQI values in the mid-future. Conversely, weak air pollution controls considered in the SSP3-7.0 scenario resulted in poor AQI values in China and India. Moreover, a predicted increase in the percentage of aged populations (>65 years) in these regions, coupled with high AQI values, may increase the risk of premature deaths in the future. This study also examined the regional impact of PM2.5 mitigations on downward shortwave energy and surface air temperature. Our results revealed that, although significant air pollution controls can reduce long-term exposure to PM2.5, it may also contribute to the warming of near- and mid-future climates.

scholarly journals Exposure-Dependent Variations in Air Temperature and Humidity on the Moraine of the Aavatsmark Glacier (Nw Spitsbergen) in the Summer Season of 2010

2012 ◽  
Vol 5 (1) ◽  
pp. 57-75
Author(s):  
Andrzej Araźny ◽  
Rajmund Przybylak
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Weather Conditions ◽  
Active Surface ◽  
Summer Season ◽  
Lateral Moraine ◽  
Near Surface ◽  
Mean Values ◽  
Temperature And Humidity ◽  
Surface Air Layer

Abstract The article presents results of research on the development of air temperature and relative humidity at a height of 5 cm above the active surface of the terminal lateral moraine of the Aavatsmark Glacier, relative to its exposure in the summer season of 2010. Variations in the two conditions were analysed for five measurement sites situated on northerly (SN), easterly (SE), southerly (SS) and westerly (SW) slopes, as well as on the flat top surface of the moraine (STop), in different weather conditions. The article also includes a temperature and humidity stratification in the near surface air layer (5-200 cm) above the moraine. The issues were investigated for mean values from the whole period of research, as well as for individual days demonstrating distinct degrees of cloudiness and wind speed.

The Influence of Weather On Incubation Scheduling of the White-Rumped Sandpiper (Calidris Fuscicollis): a Uniparental Incubator in a Cold Environment

Behaviour ◽  
1985 ◽  
Vol 95 (3-4) ◽  
pp. 261-289 ◽  
Author(s):  
Robert D. Montgomerie ◽  
Ralph V. Cantar
Keyword(s):  
Circadian Rhythm ◽  
Wind Speed ◽  
Air Temperature ◽  
Weather Conditions ◽  
Barometric Pressure ◽  
High Arctic ◽  
Collective Effects ◽  
Incubation Behaviour ◽  
The Individual

AbstractWe studied the incubation scheduling of 8 white-rumped sandpipers (Calidris fuscicollis), a species in which only the female incubates. Because the female is small and nests in the high arctic, these birds are probably under more cold stress than birds nesting in the temperate zone. We examined the individual and collective effects of several weather variables on a female's incubation behaviour to ascertain what amount of the variability within a day was directly attributable to weather conditions. Birds made an average of 25.1 off-nest trips each day, averaging 10.5 min each. This resulted in spending, on average, 82.5% of their time incubating eggs. There was a clear within-day cycle in incubation scheduling; birds made more and longer trips in the middle of the day and, as a result, spent more total time off the nest in that period. Birds adjusted their hour-by-hour schedules to weather largely by altering the number of trips made, and less so by adjusting trip length. There was a circadian rhythm in recess time/h, explaining at least 11% of the variation in recess time/h. When the circadian rhythm was controlled statistically, weather accounted for an average of 38% of the explainable variation in recess time/h. The relative importance of each weather variable on the recess time/h was (in descending order of importance): wind speed, air temperature, solar radiation, barometric pressure, and relative humidity. Weather (primarily wind speed and temperature) exerted its strongest effects early and late in the bird's active day (0400-2300 h). On cold and windy days, birds increased the time spent on their nests early and late in the day, and made more trips than usual in the middle of the day, when air temperature was highest. We suggest that the incubation scheduling of these birds conformed to the long-term predictability of the daily weather cycle by following a circadian rhythm of behaviour modified by a response to concurrent weather that would have reduced egg cooling.

scholarly journals Outdoor thermal performance simulation in campus area during the dry season, Yogyakarta

2019 ◽  
Vol 2 (1) ◽  
pp. 15
Author(s):  
Hasti Widyasamratri ◽  
Arif Kusumawanto ◽  
Fadhilla Tri Nugrahaini
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Thermal Performance ◽  
Meteorological Parameters ◽  
Anthropogenic Activities ◽  
Surface Air Temperature ◽  
Dry Season ◽  
Performance Simulation ◽  
Near Surface ◽  
Significant Area

The outdoor thermal performance reflects the microclimate condition in any significant area. This study simulated the thermal performance with measured and modeled three meteorological parameters, air temperature (Ta), relative humidity (RH), and wind speed in the dry season tropical city. The research focused on thermal performance simulation and distribution, here, we were neglecting anthropogenic activities as the heat source. The result showed that there were different ranges between a measured and simulated value of Ta, RH, and wind speed. The highest Ta difference between measure and simulation occurred at 11 AM, which was 1.97⸰C. The highest difference of RH occurred at 13 PM (26.75%), and the highest different of wind speed was at 11 AM (0.37 m/s) respectively. The heat distribution in the focus area was influenced by the solar direction which impacted the ground and near-surface air temperature.  

scholarly journals AIR QUALITY IN MINING AREAS: THE CASE OF STRATONI, CHALKIDIKI, GREECE

2017 ◽  
Vol 43 (5) ◽  
pp. 2510
Author(s):  
D. Papastamatiou ◽  
N. Skarpelis ◽  
A. Argyraki
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Wind Speed ◽  
Particle Concentration ◽  
Mineral Dust ◽  
Quality Standards ◽  
Mining Areas ◽  
Mineral Particles ◽  
Sulfide Ore ◽  
Better Than

Air quality sampling tests are conducted on a 24h basis by “HELLENIC GOLD S.A.” in the Stratoni mining settlement. The settlement is located in the neighbourhood of a flotation plant where galena and sphalerite concentrates are produced after crushing and processing of Pb-Ag-Zn sulfide ore. Old piles of mineral waste occur close to the settlement. The mineralogy of mineral dust collected on filters of 3 air samplers from August to December 2008 was studied. Elemental analysis of mineral dust collected from January to December 2008 was conducted. The purpose of the study was to determine levels of air pollution, type of mineral particles as well as potential sources. Measurements of air quality included PM10. Statistical analysis of the collected data included tests to determine the control on daily particle concentration and mineralogy of fluctuations of temperature, humidity, wind direction and wind speed. Air quality was better than during 1998-2000. Air quality was typically at its worse during hot summer days when wind speed was high. The concentration of PM10 particulate matter was quite low when compared to International Air Quality Standards regulations, indicating that levels of air pollution in the area do not pose human health hazards.

scholarly journals Evaluation of the Performance of Low-Cost Air Quality Sensors at a High Mountain Station with Complex Meteorological Conditions

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 212 ◽  
Author(s):  
Hongyong Li ◽  
Yujiao Zhu ◽  
Yong Zhao ◽  
Tianshu Chen ◽  
Ying Jiang ◽  
...  
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Random Forest ◽  
Linear Regression ◽  
Reference Data ◽  
Low Cost ◽  
Weather Conditions ◽  
Air Pressure ◽  
High Mountain ◽  
Positive Effect

Low-cost sensors have become an increasingly important supplement to air quality monitoring networks at the ground level, yet their performances have not been evaluated at high-elevation areas, where the weather conditions are complex and characterized by low air pressure, low temperatures, and high wind speed. To address this research gap, a seven-month-long inter-comparison campaign was carried out at Mt. Tai (1534 m a.s.l.) from 20 April to 30 November 2018, covering a wide range of air temperatures, relative humidities (RHs), and wind speeds. The performance of three commonly used sensors for carbon monoxide (CO), ozone (O3), and particulate matter (PM2.5) was evaluated against the reference instruments. Strong positive linear relationships between sensors and the reference data were found for CO (r = 0.83) and O3 (r = 0.79), while the PM2.5 sensor tended to overestimate PM2.5 under high RH conditions. When the data at RH >95% were removed, a strong non-linear relationship could be well fitted for PM2.5 between the sensor and reference data (r = 0.91). The impacts of temperature, RH, wind speed, and pressure on the sensor measurements were comprehensively assessed. Temperature showed a positive effect on the CO and O3 sensors, RH showed a positive effect on the PM sensor, and the influence of wind speed and air pressure on all three sensors was relatively minor. Two methods, namely a multiple linear regression model and a random forest model, were adopted to minimize the influence of meteorological factors on the sensor data. The multi-linear regression (MLR) model showed a better performance than the random forest (RF) model in correcting the sensors’ data, especially for O3 and PM2.5. Our results demonstrate the capability and potential of the low-cost sensors for the measurement of trace gases and aerosols at high mountain sites with complex weather conditions.

scholarly journals Understanding the Spatial-Temporal Patterns and Influential Factors on Air Quality Index: The Case of North China

2019 ◽  
Vol 16 (16) ◽  
pp. 2820 ◽  
Author(s):  
Wenxuan Xu ◽  
Yongzhong Tian ◽  
Yongxue Liu ◽  
Bingxue Zhao ◽  
Yongchao Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Wind Speed ◽  
Quality Index ◽  
North China ◽  
Ambient Air ◽  
Air Quality Index ◽  
Rapid Expansion ◽  
Spatial Data Analysis ◽  
Prevailing Wind Direction

North China has become one of the worst air quality regions in China and the world. Based on the daily air quality index (AQI) monitoring data in 96 cities from 2014–2016, the spatiotemporal patterns of AQI in North China were investigated, then the influence of meteorological and socio-economic factors on AQI was discussed by statistical analysis and ESDA-GWR (exploratory spatial data analysis-geographically weighted regression) model. The principal results are as follows: (1) The average annual AQI from 2014–2016 exceeded or were close to the Grade II standard of Chinese Ambient Air Quality (CAAQ), although the area experiencing heavy pollution decreased. Meanwhile, the positive spatial autocorrelation of AQI was enhanced in the sample period. (2) The occurrence of a distinct seasonal cycle in air pollution which exhibit a sinusoidal pattern of fluctuations and can be described as “heavy winter and light summer.” Although the AQI generally decreased in other seasons, the air pollution intensity increased in winter with the rapid expansion of higher AQI value in the southern of Hebei and Shanxi. (3) The correlation analysis of daily meteorological factors and AQI shows that air quality can be significantly improved when daily precipitation exceeds 10 mm. In addition, except for O3, wind speed has a negative correlation with AQI and major pollutants, which was most significant in winter. Meanwhile, pollutants are transmitted dynamically under the influence of the prevailing wind direction, which can result in the relocation of AQI. (4) According to ESDA-GWR analysis, on an annual scale, car ownership and industrial production are positively correlated with air pollution; whereas increase of wind speed, per capita gross domestic product (GDP), and forest coverage are conducive to reducing pollution. Local coefficients show spatial differences in the effects of different factors on the AQI. Empirical results of this study are helpful for the government departments to formulate regionally differentiated governance policies regarding air pollution.

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