The correlations between particulate matter concentrations, planetary boundary layer height and meteorological parameters

THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY DO MINH HONG THE CORRELATIONS BETWEEN PARTICULATE MATTER CONCENTRATIONS, PLANETARY BOUNDARY LAYER HEIGHT AND METEOROLOGICAL PARAMETERS BACHELOR THESIS Study Mode: Full-time Major : Environmental Science and Management Faculty : International Training and Development Center Batch : 2012-2016 Thai Nguyen, 05/12/2016 Thai Nguyen University of Agriculture and Forestry Degree program Bachelor of Environmental Science and Management Full name DO MINH HONG Student ID DTN1253150038 Thesis title The correlations between particulate matter concentration, planetary boundary layer height and meteorological parameters Supervisor Ph.D., Associate Professor Tang-Huang Lin (National Central University, Taiwan) MSc Nguyen Van Hieu (Thai Nguyen University of Agriculture and Forestry, Vietnam) Abstract: In this study, data describing PM10 concentrations, planetary boundary layer height, atmospheric temperature, relative humidity and wind speed in 2015 were analyzed and correlated for the further application to the air quality assessment in Taoyuan city, Taiwan PM10 data were collected from an air quality station in urban area The characteristics of PM10 concentrations were explored, and it's relationwith meteorological parameters were examinedaccordingly The studied area is characterized by low wind speed and humidity, with mild to warm winter and hot summer Daily mass concentration of PM10 ranged from 10 to 104 µg/m3, which was under the limit of national air quality standards (125 µg/m3) The highest level of PM10 i was observed duringwinter, while the lowest loading was during summer.Pearson analysis revealed strong negative correlations between PM10 and temperature, humidity and wind speed (>4 m/s) with the correlation coefficient of -0.84, -0.92, and 0.86, respectively Although, there was a weak correlation (-0.48) between PM10 and planetary boundary layer height for all observations, the relations during an interval near surface are significant (almost more than -0.8) indicating the impact of weather system Keywords Particulate matter, PM10, planetary boundary layer, wind speed, Taiwan Number of pages 38 Date of submission December 2016 ii ACKNOWLEDGEMENTS First and foremost,I would like to thank myadvisorAssoc Prof Tang-Huang Linfor being supportive, guiding and understanding during a difficult time.You have set an example of excellence as a researcher, mentor, instructor, who spent endless hours proofreading my research papers and giving me excellent suggestions which resulted in improved versions of documents I would like to thank my advisor MSc Nguyen Van Hieufor his constant enthusiasm and encouragement I would also like to thank members of "Environmental Remote Sensing Laboratory": Kuo-En Chang,Wei-HungLien, Yi-Ling Chang,Yuan-Hsiang Chang, Tsung-Ting Lee and Sheng-Kai Zeng.I am very grateful to all of you for your support and kindness Finally, I take this opportunity to record my sense of gratitude to my families and friends who encourage and backing me unceasingly Thai Nguyen, 05/12/2016 Author Do Minh Hong iii TABLE OF CONTENT LIST OF FIGURES .1 LIST OF TABLES LIST OF ABBREVIATION PART I INTRODUCTION 1.1 Research rationale .4 1.2 Research's objectives 1.3 Research questions 1.4 Limitations PART II LITERATURE REVIEW 2.1 Particulate Matter 2.1.1 Particulate Matter 2.1.2 Factors that affect particulate matter 2.2 Planetary Boundary Layer .9 2.3 Taiwan Air Quality Monitoring Network .10 2.3.1 TAQMN Background 10 2.3.2 TAQMN Goal .10 2.4 Global Modeling and Assimilation Office 11 2.4.1 GMAO Mission 11 2.4.2 GMAO Data Products .12 2.5 Matlab 13 2.6 Pearson's Correlation Coefficient 14 PART III MATERIALS AND METHODS .16 iv 3.1 Description of the Study Area 18 3.2 Data and Equipment 19 3.3 Methodology 19 PART IV RESULTS AND DISCUSSION 22 4.1 Statistics of the variables 22 4.2 Relationship between the variables 29 4.2.1 Relationship between PM10 and planetary boundary layer 29 4.2.2 Relationship between PM10 and meteorological parameters 30 PART V CONCLUSION 33 REFERENCES 34 v was observed duringwinter, while the lowest loading was during summer.Pearson analysis revealed strong negative correlations between PM10 and temperature, humidity and wind speed (>4 m/s) with the correlation coefficient of -0.84, -0.92, and 0.86, respectively Although, there was a weak correlation (-0.48) between PM10 and planetary boundary layer height for all observations, the relations during an interval near surface are significant (almost more than -0.8) indicating the impact of weather system Keywords Particulate matter, PM10, planetary boundary layer, wind speed, Taiwan Number of pages 38 Date of submission December 2016 ii LIST OF TABLES Page Table Brief description of GMAO data products 13 Table Monthly means of meteorological elements in Taoyuan in 2015 23 Table Correlation of particulate matter and planetary boundary layer heightin 30 2015 Table Correlation of particulate matter and meteorological parameters in 31 2015 LIST OF ABBREVIATION EOS Earth Observing System EPA Environmental Protection Agency GEOS Goddard Earth Observing System GMAO Global Modeling and Assimilation Office NASA National Aeronautics and Space Administration PBL Planetary Boundary Layer PBLH Planetary Boundary Layer Height PM Particulate matter TAQMN Taiwan Air Quality Monitoring Network PART I INTRODUCTION 1.1 Research rationale Particulate matters are complex pollutants of different sizes, shapes and origins suspended in the atmosphere Those with aerodynamic size not greater than 10 µm in diameter are collectively referred to as PM10 Due to their small sizes, PM10 can be inhaled readily and can penetrate deep into the human body Hence respiratory health effects on people can be observed when they are exposed at elevated concentrations Studies indicated that an increase in daily mean PM10 concentrations might cause an increase in daily mortality and hospital admissions (Bell et al., 2008; Pope & Dockery, 1992) Meteorology is a major factor in ambient PM concentrations since dispersion processes, removal mechanisms, and chemical formation of atmospheric particles depend on parameters The meteorological parameters such as wind speed (WS), temperature (T), relative humidity (RH), and planetary boundary layer height (PBLH) etc are expected to have important effects on PM10 variation For the reason, some studies carried out in urban areas have investigated the relationship between meteorological variables and PM concentration(Galindo et al., 2011; Hien et al., 2002; Wai, 2005) In addition, planetary boundary layer has a significant effect on the air pollutants, especiallythe particulate matters near surface(Quan et al., 2013; Rigby et al., 2006) For the case of Taoyuan city, it's a special municipality in northwestern Taiwan, which is prosperous in commerce and industry Due to trade prosperity in recent years and the proliferation of job opportunities, Taoyuan has developed into a major Fig is the diurnal mean variations of PBLH in Taoyuan in 2015 for spring (March–April–May), summer (June–Jul–August), autumn (September–October– November) and winter (December– January–February) PBLH is about 700 m during nighttime, rises gradually from 06:00 in the morning, reaches the maximum of over 9000 m at 12:00, and then decreases gradually to nocturnal average height at 21:00 The seasonal diurnal cycles coincide with the annual average diurnal variations (Fig.10) The seasonal maximum diurnal PBLH ordering from highest to lowest are winter, spring, autumn and summer with the height of 1255.8, 978.1, 967.7, and 922.8084 m, respectively Fig.8.Daily mean values of PM10concentrations in Taoyuan stationin 2015 Hourly values of PM10 concentration during the studied period ranged from to 148 µg/m3, with a mean value of 40 µg/m3 The 90th percentile of the PM10 observations was less than 71 µg/m3, which is less than a half of the maximum monitored value Daily mass concentrations of PM10 ranged from 10 to 104 24 µg/m3(Fig.8) It is indicates that the daily average concentration was under the limit of 125 µg/m3 stated in the EPA Taiwan air quality standards Fig.9.shows the box plot of the monthly mean PM10 concentrations recorded in Taoyuan station in 2015 The box plot graphically describes several prominent features of the PM10 concentrations recorded in each month The lower and upper boundaries of the box are the 25th percentiles (lower fourth) and the 75th percentiles (upper fourth) of the distribution The median is shown as a line across the box and two horizontal lines drawn away from the box are the lower and upper extremes of the distribution The dots represent the mean value of PM10 concentrations in each month The values fall within the lower and upper fourth would represent the main trend and hence are useful for understanding the general behavior of the PM10 variations The monthly box plot indicates that the concentrations inflate substantially in the summer period and increase during winter The highest monthly mean was 53µg/m3 on January, while the lowest values were 28 µg/m3 on August Fig.9 Variation of monthly PM10 concentrations in Taoyuan station in 2015 25 The depressed levels of ambient PM10 concentrations in summer might be attributed to the precipitations which occur more frequently in the region during the summer, particularly, the summer monsoon rainfall in Taiwan increases dramatically in May and continues for four months (May–August)(Chen, Yen, Hsieh, & Arritt, 1999; C Y Lin et al., 2005).Precipitation can effectively decrease PM10 mass concentrations through wet deposition(Tiwari et al., 2012) In the winter and spring, Taiwan is often under the influence of northeasterly winter monsoon winds originating in central Asia The winter monsoon not only brings cold air but can also transport air pollutants and dust over a long distance to Taiwan(Husar et al., 2001; Nakajima, 2003) Fig.10 Time series of particulate matter concentrations in Taoyuan in 2015 Time series for the monitored data are presented in Figs.10 and 11 The day-today variations of PM10 concentrations are not only caused by the local emissions but are also influenced by equal sources and strongly linked to the meteorological conditions, that is, air temperatures, wind speed and relative humidity (Lin et al., 2006; Lu, 2002) as well as particularly linked to solar radiation and turbulence in the planetary boundary layer (Quan et al., 2013) 26 LIST OF TABLES Page Table Brief description of GMAO data products 13 Table Monthly means of meteorological elements in Taoyuan in 2015 23 Table Correlation of particulate matter and planetary boundary layer heightin 30 2015 Table Correlation of particulate matter and meteorological parameters in 31 2015 LIST OF TABLES Page Table Brief description of GMAO data products 13 Table Monthly means of meteorological elements in Taoyuan in 2015 23 Table Correlation of particulate matter and planetary boundary layer heightin 30 2015 Table Correlation of particulate matter and meteorological parameters in 31 2015 LIST OF TABLES Page Table Brief description of GMAO data products 13 Table Monthly means of meteorological elements in Taoyuan in 2015 23 Table Correlation of particulate matter and planetary boundary layer heightin 30 2015 Table Correlation of particulate matter and meteorological parameters in 31 2015 The relationships between the mean values of suspended particle concentrations and planetary boundary layer height were analyzed using Pearson's correlation analysis, the analyses results are represented in Fig 13 and Table A weak negative correlation was found between PM10 and planetary boundary layer height for all observations (correlation coefficient r = -0.48) However, the planetary boundary layer height below 900m showed a high correlation with PM10 (r = -0.83).Whereas, the planetary boundary layer height upper 900m showed a weaker correlation with PM10 (r = -0.68) Table Correlation of particulate matter and planetary boundary layer height in 2015 PBLH Pearson Correlation Coefficient of (m) Coefficient Determination (r) (R2) All observations -0.48 0.26 1300 -0.92 0.86 4.2.2 Relationship between PM10 and meteorological parameters The relationships between the mean values of suspended particle concentrations and meteorological variables (wind speed, relative humidity and ambient temperature) were analyzed using Pearson's correlation analysis, the analyses results are represented in Fig 14 and Table A strong negative correlation was found between PM10 and atmospheric temperature (correlation coefficient r = -0.84) 30 High humidity conditions are inversely correlated with PM10, as indicated by a strong negative coefficient (r = -0.92); this correlation may be due to the effects of humidity on coalescence and settling of suspended particles, where atmospheric moisture helps fine suspended particles to stick together forming heavier particles and then fall down A moderate negative correlation was observed between wind speed and PM10 (r = -0.62).The best correlation was observed with wind speeds < m/s (r = -0.82) and > m/s (r = -0.87) The study suggests that during the light winds, particulate matters from local sources are not readily dispersed which allow PM10 concentration to build up over an area and tend to become more concentrated Whereas,strong winds that accompanyparticulate enriched air masses from other sources to Taoyuanand correspondingly the PM10 concentration is expected to be higher Table Correlation of PM10 and meteorological parameters in 2015 Parameter Pearson Correlation Coefficient of Coefficient Determination (r) (R2) Temperature (°C) -0.84 0.71 Relative Humidity (%) -0.92 0.85 All observations -0.62 0.39 2< -0.82 0.67 2-4 0.48 0.23 >4 -0.86 0.75 Wind speed (m/s ) 31 Wind Speed Relative Humidity Temperature Fig.14 Relationships between PM10 and meteorological parameters 32 PART V CONCLUSION Based on a comprehensive data analysis of PM10 concentrations and a series of meteorological parameters, the conclusions can be summarized as the followings: (1) The studied area is characterized by low wind speeds and humid, with mild to warm winters and hot summers; (2) Daily mass concentrations of PM10 ranged from 10 to 104 µg/m3, which was under thelimit of national air quality standards (125 µg/m3); (3)The highest level of PM10 was observed during winter, while the lowest level was during summer; and (4) Pearson's analysis showed that there were strong negative correlations between PM10 and temperature, humidity and wind speed (>4 m/s) with the correlation coefficient of -0.84, -0.92, and -0.86, respectively Although, there was a weak correlation (-0.48) between PM10 and planetary boundary layer height for all observations, the relations during an interval near surface are significant (almost more than -0.8) indicating the impact of weather system 33 LIST OF ABBREVIATION EOS Earth Observing System EPA Environmental Protection Agency GEOS Goddard Earth Observing System GMAO Global Modeling and Assimilation Office NASA National Aeronautics and Space Administration PBL Planetary Boundary Layer PBLH Planetary Boundary Layer Height PM Particulate matter TAQMN Taiwan Air Quality Monitoring Network GMAO Mission (2015) RetrievedMay 28, 2016 from http://gmao.gsfc.nasa.gov/gmao_mission/ Goel, P.K and Trivedy, R K (1998) An Introduction to Air Pollution Technoscience Publication Gray, G (2009) Analysis of the effects of global change on the natural environment ans human systems In Scientific Assessment of the Effects of Global Change on the United States, pp 182–183 DIANE Publishing Hien, P D., Bac, V T., Tham, H C., Nhan, D D., & Vinh, L D (2002) Influence of meteorological conditions on PM2.5 and PM2.5−10 concentrations during the monsoon season in Hanoi, Vietnam Atmospheric Environment, 36(21), pp 3473– 3484 doi:10.1016/S1352-2310(02)00295-9 History About Taoyuan (2014) Retrieved Jun 11, 2016from http://www.tycg.gov.tw/eng/home.jsp?id=14&parentpath=0,9 Husar, R B., Tratt, D M., Schichtel, B A., Falke, S R., Li, F., Jaffe, D., Malm, W C (2001) Asian dust events of April 1998 concentration over the valleys of the West Coast was about peaks mass mean diameter was 2-3 /• m , and the dust, 106(April 1998) Kavouras, I G., Koutrakis, P., Cereceda-Balic, F., & Oyola, P (2001) Source apportionment of PM10 and PM2.5 in five Chilean cities using factor analysis Journal of the Air & Waste Management Association (1995), 51(3), pp 451–464 doi:10.1080/10473289.2001.10464273 35 Lin, C Y., Liu, S C., Chou, C C K., Huang, S J., Liu, C M., Kuo, C H., & Young, C Y (2005) Long-range transport of aerosols and their impact on the air quality of Taiwan Atmospheric Environment, 39(33), pp 6066–6076 doi:10.1016/j.atmosenv.2005.06.046 Lin, C.-Y., Wang, Z., Chen, W.-N., Chang, S.-Y., Chou, C C K., Sugimoto, N., & Zhao, X (2006) Long-range transport of Asian dust and air pollutants to Taiwan: observed evidence and model simulation Atmospheric Chemistry and Physics Discussions, 6(5), pp 10183–10216 doi:10.5194/acpd-6-10183-2006 Liu, S., & Liang, X Z (2010) Observed diurnal cycle climatology of planetary boundary layer height Journal of Climate, 23(21), pp 5790–5809 doi:10.1175/2010JCLI3552.1 Longnecker, M., & Ott, R (2010) An introduction to statistical methods and data analysis Isbn-13 Lu, H.-C (2002) The statistical characters of PM10 concentration in Taiwan area Atmospheric Environment, 36(3), pp 491–502 doi:10.1016/S13522310(01)00245-X MATLAB R2012a (2016) Retrieved May 16, 2016, from http://matlabr2012a.software.informer.com/ Nakajima, T (2003) Significance of direct and indirect radiative forcings of aerosols in the East China Sea region Journal of Geophysical Research, 108(D23), pp 1– 16 doi:10.1029/2002JD003261 36 NRC (2005a) Radiative Forcing of Climate Change Radiative Forcing of Climate Change: Expanding the Concept and Addressing Uncertainties Washington, D.C.: National Academies Press doi:10.17226/11175 Pope, C A., & Dockery, D W (1992) Acute Health Effects of PM10 Pollution on Symptomatic and Asymptomatic Children American Review of Respiratory Disease, 145(5), pp 1123–1128 Quan, J., Gao, Y., Zhang, Q., Tie, X., Cao, J., Han, S., Zhao, D (2013) Evolution of planetary boundary layer under different weather conditions, and its impact on aerosol concentrations Particuology, 11(1), pp 34–40 doi:10.1016/j.partic.2012.04.005 Rigby, M., Timmis, R., & Toumi, R (2006) Similarities of boundary layer ventilation and particulate matter roses Atmospheric Environment, 40(27), pp 5112–5124 doi:10.1016/j.atmosenv.2006.01.037 Rodríguez, S., Querol, X., Alastuey, A., Viana, M M., Alarcón, M., Mantilla, E., & Ruiz, C R (2004) Comparative PM10-PM2.5 source contribution study at rural, urban and industrial sites during PM episodes in Eastern Spain Science of the Total Environment, 328(1-3), 95–113 doi:10.1016/S0048-9697(03)00411-X Shi, B., Zheng, F and Cao, G (1997) On the Determination of Mixed Layer Height J Xi’an Univ Archit Technol, 28, pp 138–141 Tan, Z (2014) Air Pollution and Greenhouse Gases - From Basic Concepts to Engineering Applications for Air Emission Control Springer 37 TAQMN (2015) Goal Retrieved May 24, 2016from http://taqm.epa.gov.tw/taqm/en/b0106.aspx Tiwari, S., Chate, D M., Pragya, P., Ali, K., & Bisht, D S (2012) Variations in mass of the PM 10,PM 2.5 and PM during the monsoon and the winter at New Delhi Aerosol and Air Quality Research, 12(1), pp 20–29 doi:10.4209/aaqr.2011.06.0075 US EPA (n.d.) Particulate Matter - Basic Information Retrieved May 13, 2016, from https://www3.epa.gov/pm/basic.html Wai, K.-M (2005) Relationship between ionic composition in PM 10 and the synoptic-scale and mesoscale weather conditions in a south China coastal city: A 4-year study Journal of Geophysical Research, 110(18), D18210 doi:10.1029/2004JD005385 Ying, Z., Tie, X., & Li, G (2009) Sensitivity of ozone concentrations to diurnal variations of surface emissions in Mexico City: A WRF/Chem modeling study Atmospheric Environment, 43(4), pp 851–859 doi:10.1016/j.atmosenv.2008.10.044 38 [...]... conducted The correlations between particulate matter concentration, planetary boundary layer height and meteorological parameters" 1.2 Research's objectives The objective of this study is to explore the influence of meteorological parameters onPM10concentrationsin Taoyuan city, Taiwanduring 2015.PM10 and meteorological parameters data were collected from an ambient air quality station in Taoyuan; planetary. .. calculated at each gradient of the meteorological variables to allow Pearson's correlation analysis and to investigate correlation between PM and meteorological parameters( Longnecker & Ott, 2010) Temporal variation of the PM concentrations, planetary boundary layer height and meteorological variables were analyzed, and their correlations were identified All of the steps are showed in the flowchart below: PBLH... matter and planetary boundary layer heightin 30 2015 Table 4 Correlation of particulate matter and meteorological parameters in 31 2015 2 LIST OF TABLES Page Table 1 Brief description of GMAO data products 13 Table 2 Monthly means of meteorological elements in Taoyuan in 2015 23 Table 3 Correlation of particulate matter and planetary boundary layer heightin 30 2015 Table 4 Correlation of particulate matter. .. into the air, the wind speed determines how quickly the pollutants mix with the surrounding air and, of course, how fast they move away from their source Strong winds tend to lower the concentration of particulate matters by spreading them apart as they move downstream Moreover, the stronger the wind, the more turbulent the air Turbulent air produces swirling eddies that dilute the particulate matters... Correlation of particulate matter and meteorological parameters in 31 2015 2 The relationships between the mean values of suspended particle concentrations and planetary boundary layer height were analyzed using Pearson's correlation analysis, the analyses results are represented in Fig 13 and Table 3 A weak negative correlation was found between PM10 and planetary boundary layer height for all observations... in particulate ammonium nitrate concentrations as temperature increases (Gray, 2009) 2.2 Planetary Boundary Layer The planetary boundary layer (PBL) is the lowest layer of the troposphere where wind is influenced by friction (Fig.2) The thickness (depth) of the PBL is not constant and it is dependent on many factor At night and in the cool season the PBL tends to be lower in thickness while during the. .. for all observations (correlation coefficient r = -0.48) However, the planetary boundary layer height below 900m showed a high correlation with PM10 (r = -0.83).Whereas, the planetary boundary layer height upper 900m showed a weaker correlation with PM10 (r = -0.68) Table 3 Correlation of particulate matter and planetary boundary layer height in 2015 PBLH Pearson Correlation Coefficient of (m) Coefficient... of meteorological elements in Taoyuan in 2015 23 Table 3 Correlation of particulate matter and planetary boundary layer heightin 30 2015 Table 4 Correlation of particulate matter and meteorological parameters in 31 2015 2 LIST OF TABLES Page Table 1 Brief description of GMAO data products 13 Table 2 Monthly means of meteorological elements in Taoyuan in 2015 23 Table 3 Correlation of particulate matter. .. station in Taoyuan; planetary boundary layer height data were obtained from the online outputs provided by GMAOin 2015 These data have been analyzed to assess ambient PM10 levels, diurnal and monthly variation, and inter -correlations of the variables 1.3 Research questions 1 What is the content of PM10 in Taoyuan city? 2 How does planetary boundary layer and meteorological parameters effect on concentrations... Time series of particulate matter concentrations in Taoyuan in 2015 26 Fig.11 Time series for planetary boundary layer height and meteorological 27 variables (wind speed, relative humidity and temperature) in Taoyuan in one year Fig.12 Diurnal variations of parameter in Taoyuan for the studied period (a) 28 PM10, (b) planetary boundary layer height, (c) wind speed, and (d) relative humidity and temperature ... the studied period (a) 28 PM10, (b) planetary boundary layer height, (c) wind speed, and (d) relative humidity and temperature Fig.13 Relationships between PM10 and planetary boundary layer height. .. variation of the PM concentrations, planetary boundary layer height and meteorological variables were analyzed, and their correlations were identified All of the steps are showed in the flowchart below:... means of meteorological elements in Taoyuan in 2015 23 Table Correlation of particulate matter and planetary boundary layer heightin 30 2015 Table Correlation of particulate matter and meteorological