scholarly journals Assessment of ambient dust pollution status at selected point sources (residential and commercial) of Mingaladon area, Yangon region, Myanmar

2018 ◽  
Vol 32 (1) ◽  
pp. 60-68 ◽  
Author(s):  
Sai Nyan Lin Tun ◽  
Than Htut Aung ◽  
Aye Sandar Mon ◽  
Pyay Hein Kyaw ◽  
Wattasit Siriwong ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Ambient Temperature ◽  
Traffic Congestion ◽  
Pm10 Concentration ◽  
Particulate Matters ◽  
Dust Pollution ◽  
Content Type ◽  
Pm2.5 And Pm10 ◽  
Pm2.5 Concentration

Purpose Dust (particulate matters) is very dangerous to our health as it is not visible with our naked eyes. Emissions of dust concentrations in the natural environment can occur mainly by road traffic, constructions and dust generating working environments. The purpose of this paper is to assess the ambient dust pollution status and to find out the association between PM concentrations and other determinant factors such as wind speed, ambient temperature, relative humidity and traffic congestion. Design/methodology/approach A cross-sectional study was conducted for two consecutive months (June and July, 2016) at a residential site (Defence Services Liver Hospital, Mingaladon) and a commercial site (Htouk-kyant Junction, Mingaladon) based on WHO Air Quality Reference Guideline Value (24-hour average). Hourly monitoring of PM2.5 and PM10 concentration and determinant factors such as traffic congestion, wind speed, ambient temperature and relative humidity for 24 hours a day was performed in both study sites. CW-HAT200 handheld particulate matters monitoring device was used to assess PM concentrations, temperature and humidity while traffic congestion was monitored by CCTV cameras. Findings The baseline PM2.5 and PM10 concentrations of Mingaladon area were (28.50±11.49)µg/m3 and (52.69±23.53)µg/m3, means 61.48 percent of PM2.5 concentration and 54.92 percent of PM10 concentration exceeded than the WHO reference value during the study period. PM concentration usually reached a peak during early morning (within 3:00 a.m.-5:00 a.m.) and at night (after 9:00 p.m.). PM2.5 concentration mainly depends on traffic congestion and temperature (adjusted R2=0.286), while PM10 concentration depends on traffic congestion and relative humidity (adjusted R2=0.292). Wind speed played a negative role in both PM2.5 and PM10 concentration with r=−0.228 and r=−0.266. Originality/value The air quality of the study area did not reach the satisfiable condition. The main cause of increased dust pollution in the whole study area was high traffic congestion (R2=0.63 and 0.60 for PM2.5 and PM10 concentration).

scholarly journals Influence of Meteorological Parameters on Particle Pollution (PM2.5 and PM10) in the Tropical Climate of Port Harcourt, Nigeria

2019 ◽  
pp. 1-12
Author(s):  
Christopher U. Onuorah ◽  
Tambari G. Leton ◽  
Yusuf O. L. Momoh
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Air Temperature ◽  
Meteorological Parameters ◽  
Atmospheric Stability ◽  
Pm10 Concentration ◽  
Trade Wind ◽  
North East ◽  
Port Harcourt ◽  
Pm2.5 And Pm10

Aims: This study explores the influence of meteorological parameters such as wind direction, wind speed, rainfall, air temperature and relative humidity on PM2.5 and PM10 concentration. Place and Duration of Study: The study was conducted in Woji, an urban area of Port Harcourt city in Nigeria, between May and December 2019 covering wet and dry season. Methodology: The PM10 and PM2.5 concentrations were monitored for 236 days using photometric laser based particulate monitor while meteorological parameters were collected using Misol weather station mounted 10m above ground at Woji monitoring location. Results: PM concentration for all the months under study were below USEPA 24-hr standard except the month of December with PM2.5 = 58.8 μg/m³ and PM10 = 164.5 μg/m³. The result showed a significant but positively strong correlation between PM2.5 and PM10 (r = 0.97, P < .001). The wind speed significantly influenced PM2.5 and PM10 concentration with a weak negative correlation (r = - 0.22 and -0.23) respectively at P < .001. Also, PM2.5 and PM10 concentration exhibited a weak negative but significant correlation with rainfall (r = - 0.05 and -0.05) and air temperature (r = - 0.12 and -0.14) respectively at P< .001. Relative humidity showed a weak negative but not significant correlation with PM2.5 concentration (r = - 0.01) while PM10 exhibited weak but significant correlation with relative humidity (r = 0.04). Conclusion: The PM concentration exceedances recorded in month of December could be attributed to dry dusty north east trade wind that comes with harmattan as well as high atmospheric stability which is associated with low wind speed. The study revealed that meteorological parameters such as temperature, wind speed and rainfall plays significant role in the reduction of particulate matter loading through air dispersion, atmospheric instability and washout process  while relative humidity increases PM10 concentration.

scholarly journals Analysis of Ozone Pollution Characteristics and Influencing Factors in Northeast Economic Cooperation Region, China

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 843
Author(s):  
Jiaqi Tian ◽  
Chunsheng Fang ◽  
Jiaxin Qiu ◽  
Ju Wang
Keyword(s):  
Wind Speed ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Economic Cooperation ◽  
Ozone Pollution ◽  
Temporal And Spatial Variation ◽  
Temporal And Spatial ◽  
Pm2.5 And Pm10 ◽  
Peak Pattern ◽  
Pm2.5 Concentration

The increase in tropospheric ozone (O3) concentration has become one of the factors restricting urban development. This paper selected the important economic cooperation areas in Northeast China as the research object and collected the hourly monitoring data of pollutants and meteorological data in 11 cities from 1 January 2015 to 31 December 2019. The temporal and spatial variation trend of O3 concentration and the effects of meteorological factors and other pollutants, including CO (carbon monoxide), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and PM2.5 and PM10 (PM particles with aerodynamic diameters less than 2.5 μm and 10 μm) on ozone concentration were analyzed. At the same time, the variation period of O3 concentration was further analyzed by Morlet wavelet analysis. The results showed that the O3 pollution in the study area had a significant spatial correlation. The spatial distribution showed that the O3 concentration was relatively high in the south and low in the northeast. Seasonally, the O3 concentration was the highest in spring, followed by summer, and the lowest in winter. The diurnal variation of O3 concentration presented a “single peak” pattern. O3 concentration had a significant positive correlation with temperature, sunshine duration, and wind speed and a significant anticorrelation with CO, NO2, SO2, and PM2.5 concentration. Under the time scale of a = 9, 23, O3 had significant periodic fluctuation, which was similar to those of wind speed and temperature.

A New Approach for Meteorological Variables Prediction at Kuala Lumpur, Malaysia, Using Artificial Neural Networks: Application for Sizing and Maintaining Photovoltaic Systems

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Tamer Khatib ◽  
Azah Mohamed ◽  
M. Mahmoud ◽  
K. Sopian
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Energy ◽  
Ambient Temperature ◽  
Meteorological Variables ◽  
Mean Bias Error ◽  
Artificial Neural ◽  
Prediction Approach

This research presents a new meteorological variables prediction approach for Malaysia using artificial neural networks. The developed model predicts four meteorological variables using sun shine ratio, day number, and location coordinates. These meteorological variables are solar energy, ambient temperature, wind speed, and relative humidity. However, three statistical values are used to evaluate the proposed model. These statistical values are mean absolute percentage error (MAPE), mean bias error (MBE), and root mean square error (RMSE). Based on results, the developed model predicts accurately the four meteorological variables. The MAPE, RMSE, and MBE in predicting solar radiation are 1.3%, 5.8 (1.8%), and 0.9 (0.3%), respectively, while the MAPE, RMSE, and MBE values for ambient temperature prediction are 1.3%, 0.4 (1.7%), and 0.1 (0.4%), respectively. In addition, the MAPE, RMSE, and MBE values in relative humidity prediction are 3.2%, 3.2, and 0.2. As for wind speed prediction, it is the worst in accuracy among the predicted variables because the MAPE, RMSE, and MBE values are 28.9%, 0.5 (31.3%), and 0.02 (1.25%). Such a developed model helps in sizing photovoltaic (PV) systems using solar energy and ambient temperature records. Moreover, wind speed and relative humidity records could be used in estimating dust concentration group which leads to dust deposition on a PV system.

Grey relation between main meteorological factors and mortality

2019 ◽  
Vol 9 (2) ◽  
pp. 185-196
Author(s):  
Xiaodong Chen ◽  
Desheng Pei ◽  
Liping Li
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Climate Changes ◽  
Meteorological Factors ◽  
Air Pressure ◽  
Content Type ◽  
Relational Analysis ◽  
Curve Approximation ◽  
Grey Relational ◽  
Grey Relation

PurposeThe purpose of this paper is to explore the effects of main meteorological factors on the mortality of urban residents and provide empirical evidence for the prevention of effects of climate changes.Design/methodology/approachGrey relational analysis (GRA) was used to analyse the interrelationships between meteorological factors and mortality among residents in Chaoyang District, Beijing, during the period between 1998 and 2008.FindingsThe changes of annual average mortality had a strong grey relation with temperature and relative humidity. The monthly average mortality (MAM) showed a strong grey relation with air pressure and the MAM in Summer season had a strong grey relation with air pressure, relative humidity and wind speed.Originality/valueMeteorological factors including temperature, relative humidity, air pressure and wind speed are all related with mortality changes. GRA can well reveal the trend of the curve approximation between meteorological factors and mortality and can quantify the different approximation.

scholarly journals Estimacion Del Potencial De Captura De Agua Atmosferica En Guásimas, Sonora

2018 ◽  
Vol 14 (9) ◽  
pp. 68
Author(s):  
Ana Laura Bautista-Olivas ◽  
Fidencio Cruz Bautista
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Ambient Temperature ◽  
Meteorological Station ◽  
Atmospheric Conditions ◽  
Atmospheric Water

This paper focuses on estimating the potential of the atmospheric conditions in the locality of Guásimas Sonora for the capture of atmospheric water. To achieve this goal, an automated meteorological station was installed to record the ambient temperature, relative humidity, wind speed, and precipitation at the study site. According to the results obtained, the potential of the atmospheric conditions for the capture of water in the locality of Guásimas, in general, is medium. It presents a period of 20 to 30 days a year to capture atmospheric water with passive collectors and between 105 and 130 days during the year for the condensation of atmospheric water with active collectors.

Heat strain models applicable for protective clothing systems: comparison of core temperature response

1997 ◽  
Vol 83 (3) ◽  
pp. 1017-1032 ◽  
Author(s):  
R. R. Gonzalez ◽  
T. M. McLellan ◽  
W. R. Withey ◽  
S. K. Chang ◽  
K. B. Pandolf
Keyword(s):  
Heat Stress ◽  
Wind Speed ◽  
Relative Humidity ◽  
Ambient Temperature ◽  
Core Temperature ◽  
Protective Clothing ◽  
Temperature Response ◽  
The United States ◽  
Heat Strain ◽  
Intermittent Work

Gonzalez, R. R., T. M. McLellan, W. R. Withey, S. K. Chang, and K. B. Pandolf. Heat strain models applicable for protective clothing systems: comparison of core temperature response. J. Appl. Physiol. 83(3): 1017–1032, 1997.—Core temperature (Tc) output comparisons were analyzed from thermal models applicable to persons wearing protective clothing. The two models evaluated were the United States (US) Army Research Institute of Environmental Medicine (USARIEM) heat strain experimental model and the United Kingdom (UK) Loughborough (LUT25) model. Data were derived from collaborative heat-acclimation studies conducted by three organizations and included an intermittent-work protocol (Canada) and a continuous-exercise/heat stress protocol (UK and US). Volunteers from the US and the UK were exposed to a standard exercise/heat stress protocol (ambient temperature 35°C/50% relative humidity, wind speed 1 m/s, level treadmill speed 1.34 m/s). Canadian Forces volunteers did an intermittent-work protocol (15 min moderate work/15 min rest at ambient temperature of 40°C/30% relative humidity, wind speed ≈0.4 m/s). Each model reliably predicted Tc responses (within the margin of error determined by 1 root mean square deviation) during work in the heat with protective clothing. Models that are analytically similar to the classic Stolwijk-Hardy model serve as robust operational tools for prediction of physiological heat strain when modified to incorporate clothing heat-exchange factors.

scholarly journals The Reducing Effect of Green Spaces with Different Vegetation Structure on Atmospheric Particulate Matter Concentration in BaoJi City, China

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 332 ◽  
Author(s):  
Ling Qiu ◽  
Fang Liu ◽  
Xiang Zhang ◽  
Tian Gao
Keyword(s):  
Wind Velocity ◽  
Vegetation Structure ◽  
Green Space ◽  
Pm10 Concentration ◽  
Atmospheric Particulate Matter ◽  
Green Spaces ◽  
Atmospheric Particulate ◽  
Significant Difference ◽  
Pm2.5 And Pm10 ◽  
Pm2.5 Concentration

With the acceleration of urbanisation and industrialisation, atmospheric particulate pollution has become one of the most serious environmental problems in China. In this study, green spaces in Baoji city were classified into different patterns on the basis of vegetation structural parameters, i.e., horizontal structure, vertical structure and vegetation type. Eleven types of green space with different structures were selected for investigating the relationships between atmospheric particulate matter (PM) concentration and green spaces with different vegetation structure, based on the “matrix effect” of environmental factors, i.e., location, time, wind velocity, temperature, humidity and area to the concentration of PM2.5 and PM10 in the green spaces. The results showed that: (1) Location, time, wind velocity, temperature and humidity had highly significant effects on the concentration of PM2.5 and PM10. In sunny and breeze weather conditions, PM2.5 and PM10 concentration increased with the wind velocity and humidity, and decreased with the temperature. The range of PM10 concentration was greater than the range of PM2.5 concentration. (2) Less than 2 hectares of the green space had no significant influence on the concentration of PM2.5 and PM10. (3) The concentration of PM2.5 and PM10 showed no significant difference between all the green spaces and the control group. There was no significant difference in the reduction of PM2.5 concentration between different structural green spaces, but there was a significant difference in the reduction of PM10 concentration. The above results will provide a theoretical basis and practical methods for the optimisation of urban green space structures for improving urban air quality effectively in the future.

Effects of Hot and Humid Environments on Thermoregulation and Aerobic Endurance Capacity of Laser Sailors

2021 ◽  
Author(s):  
Yi-Xiao Xu ◽  
Bing-Hong Gao ◽  
Yong-Cai Zhao ◽  
Zhi-Jun Meng ◽  
Ran Li
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Temperature Gradient ◽  
Ambient Temperature ◽  
Skin Temperature ◽  
Heat Storage ◽  
Muscle Power ◽  
Endurance Capacity ◽  
Mean Power ◽  
Physiological Strain

Abstract The purpose was to investigate the effects of hot and humid environments on thermoregulation and aerobic endurance capacity of Laser sailors. A randomized cross-over design was applied to this study, in which nine Laser sailors performed the 6 km rowing test (6 km test) in both a warm (ambient temperature: 23±1.4 °C; relative humidity: 60.5±0.7 %; wind speed: 0 km/h; WARM) and hot environment (ambient temperature: 31.8±1.1 °C; relative humidity: 63.5 ± 4.9 %; wind speed: 3.5±0.7 km/h; HOT). The time for completing 6 km test of HOT group was significantly longer than that of WARM group (P=0.0014). Mean power of 3-4 km, 4-5 km and 5-6 km were significant lower in HOT group (P=0.014, P=0.02, P=0.003). Gastrointestinal temperature and skin temperature were significantly higher in HOT group during the 6 km test (P=0.016, P=0.04). Heat storage at 5 min and 15 min of HOT group were significantly higher than that of WARM group (P=0.0036; P=0.0018). Heart rate and physiological strain index of HOT group were significantly higher than that of WARM group during the 6 km test (P=0.01, P<0.01). The increase magnitude of skin temperature was more obvious than the changes of core temperature during exercise in hot and humid environments. The higher skin temperature narrowed the core to skin temperature gradient and skin to ambient temperature gradient, which may result in greater accumulation of heat storage. The greater heat storage led to the lower muscle power output, which contributed to the reduction of the heat production.

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