scholarly journals EVALUATION OF LITHUANIAN AIR QUALITY MONITORING DATA APPLYING SYNOPTICAL ANALYSIS

2007 ◽  
Vol 15 (3) ◽  
pp. 173-181 ◽  
Author(s):  
Vilma Bimbaitė ◽  
Raselė Girgždienė
Keyword(s):  
Air Quality ◽  
Ozone Concentration ◽  
Warm Season ◽  
Cold Season ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Air Quality Monitoring ◽  
Ozone Level ◽  
Ozone Concentrations ◽  
Ozone Levels

Relationship between synoptical patterns and different pollutants was analysed in the study. Cases with ozone concentrations higher or equal to the 95th percentile of monthly ozone concentrations were analysed over the period 2002–2005. Ozone concentration cases were grouped into seven concentration intervals and analysed according to synoptical patterns (cold, warm and occluded fronts). Relationship between SO2, SO4 and NO2 and synoptical objects was analysed during warm and cold seasons. The influence of cold, warm and occluded fronts on the high ozone level formation are very similar at both Lithuanian rural stations of Preila and Rūgšteliškes. The influence of all the fronts was more significant during night hours at a relatively low (50–100 μg/m3) and high (>100 μg/m3) ozone levels during day hours. The concentrations of gaseous SO2, NO2 and aerosol SO4 pollutants for the cases with hourly ozone concentration values ≥95th percentile were analysed. The influence of different synoptical patterns was found to be stronger during a warm season and lower during a cold season of the year.

Air Quality Data Management System Based on VB.NET

2014 ◽  
Vol 955-959 ◽  
pp. 1147-1150
Author(s):  
A Gu Da Mu Liu ◽  
Peng Yang ◽  
Wen Sheng Lv ◽  
Jie Liu
Keyword(s):  
Air Quality ◽  
Data Management ◽  
Management System ◽  
System Development ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Data Management System ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Air Quality Data

In order to achieve the automatic management of air quality monitoring data, the air quality data management system has been developed using VB.NET platform and Oracle as background database. It is also combined with the situation of the air quality in Beijing and based on the air quality monitoring data. The paper analyzes the system from 6 aspects, including technology selection, system architecture, system data flow diagram, system development environment, system functions and system features. Finally this paper explains the significance of the system development and application prospects.

scholarly journals On the Use of Air Quality Monitoring Networks for the Evaluation of Nitrogen Oxide Emission Inventories

2008 ◽  
Vol 2 (1) ◽  
pp. 232-248 ◽  
Author(s):  
I.B. Konovalov ◽  
M. Beekmann
Keyword(s):  
Air Quality ◽  
Nitrogen Oxide ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Emission Inventories ◽  
Air Quality Monitoring ◽  
Data Set ◽  
Rural Background ◽  
Study Results ◽  
Different Types

The usefulness of ground based air quality monitoring data for diagnostics of uncertainties in gridded emission inventories is examined. A general probabilistic procedure for comparison of levels of uncertainties in different emission datasets is developed. It implies the evaluation of the agreement between modeling results obtained with these emission datasets and corresponding measurements. This procedure is applied to the evaluation of different datasets for European gridded nitrogen oxide (NOx) emissions by using the AirBase monitoring data and the CHIMERE chemistry-transport model. Numerical experiments are performed for two different types of spatial distributions of emission uncertainties and five different types of monitors. The results are also generalized for various levels of uncertainties in simulated and measured data. It is found, in particular, that most informative, from the point of view of diagnostics of NOx emission uncertainties, are the measurements of NO2 at rural background sites and measurements of ozone at suburban sites situated in the vicinity of intensive sources of emissions. A more precise conclusion regarding the relative accuracy of two emission datasets can be drawn with a larger number of monitors in a network and a higher accuracy of the model and measurements. For example, with a network of 50 rural background NO2 monitors, the probability of choosing the more certain emission data set is more than 90 percent, if differences in uncertainty of two sets are more than 50 percent. Practical recommendations for designing or evolving surface measurement networks, in light of the study results, are given.

Quality screening for air quality monitoring data in China

2016 ◽  
Vol 216 ◽  
pp. 720-723 ◽  
Author(s):  
Jianzheng Liu ◽  
Weifeng Li ◽  
Jie Li
Keyword(s):  
Air Quality ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Air Quality Monitoring

scholarly journals Analysis of short-term air quality monitoring data in a coastal area

2021 ◽  
Vol 8 (6) ◽  
pp. 517-531
Author(s):  
Suwimon Kanchanasuta ◽  
◽  
Sirapong Sooktawee ◽  
Natthaya Bunplod ◽  
Aduldech Patpai ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Coastal Area ◽  
Source Area ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
World Health ◽  
Air Quality Monitoring ◽  
Short Term ◽  
Potential Source

<abstract> <p>Short-term air quality monitoring in a coastal area, Naklua Subdistrict, Pattaya, Thailand is an activity to support the designated area under Thailand's sustainable tourism development. This study provided a short-term monitoring data analysis on time series and Bivariate Polar Plot (BVP) to provide the status of air quality and to determine the potential source area of air pollution. The result showed that NO<sub>2</sub>, SO<sub>2</sub>, CO and PM<sub>10</sub> were not higher than the national air quality standards, while the 24-hour average of PM<sub>2.5</sub> and the 8-hour average of O<sub>3</sub> were slightly higher than the World Health Organization (WHO) air quality guideline values. The nighttime PM<sub>2.5</sub> concentration was higher than the daytime concentration, and its potential source area is urban areas in the south. However, the daytime O<sub>3</sub> concentration is higher than the nighttime concentration. Its potential source area is from the northwest, where Sichang island is located. This result could be used to support air pollution management by controlling and reducing emissions in the potential source areas as the first priority. Also, the study revealed that the BVP technique could be used to determine the source area of air pollution in the coastal area, where wind circulation is more complex than that over the land.</p> </abstract>

Quantifying source apportionment for ambient haze: An image haze extraction approach with air quality monitoring data

2020 ◽  
Vol 184 ◽  
pp. 109216 ◽  
Author(s):  
Feng-Cheng Lin ◽  
Sheng-Hua Lu ◽  
Chen-Jui Liang ◽  
Yen-Hung Chen ◽  
Jeng-Jong Liang
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Air Quality Monitoring
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