Papers by Keyword: PM₁₀

Abstract: Nowadays due to the active step of urbanisation and rapid development of industry, the contamination of atmospheric air is one of the key aspects of environmental mechanics. Polluted air deteriorates the appearance of historical buildings and architectural monuments. With the help of modern methods, aimed at preservation of cultural heritage objects, it is possible to evaluate the impact of dusty air on the appearance of historical buildings in order to save them, because it is a demonstration of architectural and design features of various temporary periods.

Abstract: Pathumthani is a metropolitan area where has a lot of industries and agricultures. The aim of this work was to study the assessment of heavy metal content in PM₁₀ (particulate matter ≤ 10 mm) at Amphoe Muang Pathumthani Province. The samples of PM₁₀ (particulate matter ≤ 10 mm) were collected in 7 stations during February to March 2013. The particles were trapped on glass fiber filters using high volume samplers. The concentration of heavy metals was evaluated by using the Inductively Coupled Plasma - Optical Emission Spectrometry (ICP-OES). The results showed that the concentration of heavy metals in PM₁₀ was BDL-0.41 µg/m³. Zinc, a heavy metal, was found in every sampling station. The order-average concentration of heavy metals in atmospheric air, at Amphoe Muang Pathumthani, was Zn > Cu > Mn > Ba > Ni > Cd.

Abstract: Hourly measured PM₁₀ concentration at eight monitoring stations within peninsular Malaysia in 2006 was used to conduct the simulated missing data. The gap lengths of the simulated missing values are limited to 12 hours since the actual trend of missingness is considered short. Two percentages of simulated missing gaps were generated that are 5 % and 15 %. A number of single imputation methods (linear interpolation (LI), nearest neighbour interpolation (NN), mean above below (MAB), daily mean (DM), mean 12-hour (12M), mean 6-hour (6M), row mean (RM) and previous year (PY)) were calculated to fill in the simulated missing data. In addition, multiple imputation (MI) was also conducted to compare between the single imputation methods. The performances were evaluated using four statistical criteria namely mean absolute error, root mean squared error, prediction accuracy and index of agreement. The results show that 6M perform comparably well to LI. Thus, this show that the effect of smaller averaging time gives better prediction. Other single imputation methods predict the missing data well except for PY. RM and MI performs moderately with the increasing performance in higher fraction of missing gaps whereas LR makes the worst methods for both simulated missing data percentages.

Abstract: Air pollution causes health problem. The paper simply analyzed the changes of air quality in the Yuxi city urban area from 2006 to 2012. In the Yuxi city urban area between 2006 and 2012, SO₂ levels increased about 43.9 percent; NO₂ levels increased about 13.3 percent; PM10 levels in 2012 decreased about 1.5 percent. By evaluating the air quality in the Yuxi city urban area, the results showed that air quality index was the maximum in 2009, and the quality of the air in Yuxi became worse from 2006 to 2012, air pollution in 2009 was the heaviest between 2006 to 2012. After adopting P.R.C EPA air quality standards (GB3095-2012) in 2013, the first air pollutant in Yuxi is PM₁₀, and then it is SO₂ among SO₂, NO₂ and PM₁₀.Much should beend done to reduce the amount of PM₁₀ and SO₂ released.

Abstract: Three consecutive severe traffic monitoring points collected in different atmospheric particulate pollution concentrations data during February 2014 in Beijing. The results show that the hourly mean concentration of PM_2.5 often exceeded 200 ug/m³, with a maximum concentration of 300 ug/m³on Feb.22,2014. The hourly mean concentration of PM₁₀ either exceeded 258 ug/m³.The concentration of PM_2.5 and PM₁₀ was significantly increased during haze events, especially PM_2.5 concentrations increased gradually and a slight decline in the middle, then rise.

Abstract: The composition and origin of organic matter (OM) released form three PM₁₀ samples obtained from biomass and oil combustion was investigated in this study. The Py-GC/MS system was applied and experiments were conducted at 5 °C/min to 750 °C. A difference in the composition and therefore in OM between the examined samples was observed. The greatest variation in released compounds was noted for PM₁₀ sample obtained from biomass combustion. Whereas the least variation in composition was observed for PM₁₀ sample obtained from B oil sample. The latter consisted in majority of squalene (81.5 %). As a result, the quantity of OM released by the biomass sample was greater by 18.2 % and 33.9 % that the quantity released by A and B oil samples, respectively.

Abstract: In this paper, the contamination of heavy metals in atmospheric particles of PM_2.5 and PM₁₀ in a city in China was analyzed, meanwhile the sources of different heavy metals (Cd, Hg, As and Pb) in atmospheric particles (PM_2.5 and PM₁₀) were confirmed by source apportionment in a city in China area through principal component analytical method. The research results showed that the heavy metals in PM_2.5 and PM₁₀ contaminated the atmosphere environment dramatically. The heavy metal Cd, Hg and Pb came mainly from incomplete combustion of petrol, while the heavy metal of As was the product of electronic metallurgy, which provides the theoretical basis for controlling of atmospheric heavy metal contamination. This method can be also applied to source apportionment of other heavy metals in atmosphere environment.

Abstract: After studying the toxicity of the PM₁₀ samples, collected in the Spring and the Summer of 2010 in Beijing, Tianjing and Tangshan, as well as their water soluble fraction with the method of Plasmid DNA assay and comparing the toxicity differences of PM₁₀ in different regions in different periods, we get the findings: Due to particulate matters’ different resources and complicate components, samples of the same mass concentration have different damage rates. The correlation between mass concentration and damage rate of the samples is not linear, indicating that the degree of particulate matters’ damage will reach a threshold value and then the range of damage will change with the increase of mass concentration under the effect of their complex components. The damage ability of the samples collected in spring is less than that in summer. In spring, the damage ability of particulate matters in Tangshan is the largest, Tianjin the second and the third is Beijing’s particulate matters. In summer, the damage ability of particulate matters in three cities is that Tianjin > Tangshan > Beijing. There is no much difference in toxicity between the samples and their water soluble fraction in the three cities in both spring and summer, which means that the toxicity of particulate matters in the same city under the same meteorological condition is similar to their water soluble fraction, showing that the components of particulate matters that cause the damage are largely water soluble.

Abstract: Almost all real life datasets consist missing values. These are usually due to machine failure, routine maintenance, changes in siting monitors and human error. The occurence of missing values requires special attention on analysing the data. Incomplete datasets can cause bias due to systematic differences between observed and unobserved data. Therefore, the need to find the best way in estimating missing values is very important so that the data analysed is ensured of high quality. In this research, three types of mean imputation techniques that are mean, mean above and mean above below methods were used to replace the missing values. Annual hourly monitoring data for PM₁₀ were used to generate missing values. Four randomly simulated missing data were evaluated in order to test the efficiency of the methods used. They are 5%, 10%, 15%, 25% and 40%. Three types of performance indicators that are mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R²) were calculated to describe the goodness of fit for all the method. From all the method applied, it was found that mean above below method is the best method for estimating data for all percentages of simulated missing values.

Abstract: This paper analyses the microstructure of different types of particles in PM₁₀ in Beijing-Tianjin-Tangshan urban agglomeration atmosphere in spring and summer by using field emission scanning electron microscopy (FESEM), in which the distribution characteristics of the size and number of the different types of particles in PM₁₀ are specifically analyzed by using image analysis software. The research result shows that the types of particles in Beijing-Tianjin-Tangshan urban agglomeration atmosphere are unknown particles, soot aggregates, mineral particles and spherical particles. According to the proportion of the three partials in the atmosphere, the three cities ranks as follows: in the aspect of unknown particles, Tianjin ranks first, which is followed by Tangshan and Beijing; in the aspect of soot aggregates, Tangshan ranks first ,which is followed by Beijing and Tianjin; in the aspect of mineral particles, Beijing ranks first ,which is followed by Tangshan and Tianjin; in the aspect of spherical particles, Beijing ranks first ,which is followed by Tangshan and Tianjin;