Excerpt
Table of Content
Laboratory Report 1
Laboratory Report 2
Laboratory Report 3
Field trip report of Northeast New Territories Landfill
GEH Basic Environmental Sciences
Laboratory Report 1
Date: 29/09/2015
Time: 3:30pm-5:30pm
Location: D3-G-03, D2-LP-03,D2-LP-09(HKIED)
Part one: Objective
This experiment aims to measure the air quality in term of level of PM2.5 in the Hong Kong Institute of Education.
Part two: Background information
It is undoubted that atmospheric particulate matter (PM) is a primary pollutant, widely reported as important for public health especially for respiratory problems (as cited in Robinson, 2014). But what is atmospheric particulate matter (PM) and how to cause the health problems indeed?
Particulate matter (PM) or particulates is microscopic solid or liquid matter suspended in the Earth's atmosphere. The term aerosol commonly refers to the particulate or air mixture, as opposed to the particulate matter alone (Seinfeld & Pandis, 1998). Sources of PM can be man-made or natural. They have impacts on climate and precipitation that adversely affect human health. Subtypes of atmospheric particulate matter include suspended particulate matter (SPM), respirable suspended particulate or PM10 (RSP; Respirable Suspended Particle; particles with diameter of 10 micrometres or less), fine particles or PM2.5 (diameter of 2.5 micrometres or less), ultrafine particles, and soot.
About the public health, high PM concentration affects the human health in several ways leading to short and long term diseases. The International Agency for Research on Cancer (IARC) and World Health Organization (WHO) designate airborne particulates a Group 1 carcinogen. Particulates are the deadliest form of air pollution due to their ability to penetrate deep into the lungs and blood streams unfiltered, causing permanent DNA mutations, heart attacks, and premature death (United States Environmental Protection Agency, 2015). In 2013, a study involving 312,944 people in nine European countries revealed that there was no safe level of particulates and that for every increase of 10 μg/m3 in PM10, the lung cancer rate rose 22%. The smaller PM2.5 were particularly deadly, with a 36% increase in lung cancer per 10 μg/m3 as it can penetrate deeper into the lungs (Raaschou-Nielsen, O. et al., 2013).
Therefore, in this experiment, the air quality in term of level of PM2.5 will be measured in the Hong Kong Institute of Education. Thus, we can have brief idea of the air quality in the Hong Kong Institute of Education.
Part three :Experiment
1. Design rationale of the experiment:
The experiment, aiming at measuring the level of PM2.5, can be divided into two parts, by using Minivol and by using DustTrak.
Minivol measurement took place from 16:00, 29th September, 2015, to 16:00 30th September, 2015, for 24 hours about 1m above ground at D3-G-03, which is an air-conditioned science laboratory with a seating capacity of 40 people. The model of Minivol is TAS 5.0 with a serial number of 6162. Once the Minivol-TAS is turned on, its pump continuously draws air from the atmosphere into the preseperator with an impactor and a filter, and then the air is exhausted to the atmosphere again. Impactor with a 2.5 micron cut-point was used. The particle matters with diameter smaller than 2.5µm could pass through the impactor and be collected on the filter paper. By subtracting the weight of filter paper after the 24-hour experiment with that before the experiment, the level of PM2.5 in µg/ m3 could be calculated.
Minivol can provide an accurate data of indoor PM2.5, but it is heavy, noisy and cannot give instant results. As a result, DustTrak was used to measure other locations in the Hong Kong Institute of Education. Despite being less precise, it is lighter, so is easier to carry around the campus. Moreover, it could provide real time measurement of PM2.5 concentration. DustTrak measurement took place at different locations in order to investigate the factors affecting the concentration of PM2.5. DUSTTRAK™ II AEROSOL MONITOR MODEL 8532 was used. There are two comparison sets. D2-LP-03 is a classroom with the same capacity as D3-G-03, but it was not air conditioned. Therefore, results in these two locations were compared to investigate how air conditioning affect PM2.5 concentration. The second comparison was done between D2-LP-03 and D2-LP-09. D2-LP-09 is a lecture room with a capability of 98 people, which was not air-conditioned when the DustTrak experiment was carrying out. The results therefore were used to find out the influence of room size on PM2.5 concentration.
Comparison set one:
Factors under investigation: air conditioning
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Comparison set two ：
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2. Procedures
For apparatus and procedures, please refer the the appendix.
3. Precautions:
Before the experiment, the PM2.5 impactor should be cleaned and greased by solvent and specific impactor grease so as to prevent the accumulation of particulate matters affecting the actual flow rate. Moreover, when installing the filter paper into the filter cassette and transferring filter paper to the balance, a pair of clean forceps should be used in order to prevent dust attachment.
Owing to the fact that the measuring pan of an analytical balance is enclosed with doors, air currents’ influence on weight measurement in the room is minimized. One should be noted that, however, slight touch on the machine can still affect the reading, and the weight of the filter paper should be recorded only when the reading on the screen remains unchanged for a period of time. It is also essential to calibrate the balance before any measurement is conducted.
Part four: Experiment Results
1. Result of Minivol measurement:
The table showing the difference in weights of the filter paper before test and after test.
Abbildung in dieser Leseprobe nicht enthalten
Air flow rate: 5 L/ min
PM2.5 Concentration at D3-G-03
= 0.0003g/ (5L/min X 60min X 24hrs)
=0.0003g/ 7200L
= 300µg / 7.2m3
= 41.667µg / m3
2. Result of DustTrak measurement:
The below table shows the average level of PM2.5 in different locations of the Hong Kong Institute of Education.
Abbildung in dieser Leseprobe nicht enthalten
* Omitted due to sudden flash of extreme data
Part five: Discussion of results
1. Influence of air-conditioning on PM2.5 concentration:
D3-G-03, a room with air-conditioning with 40 seating capacity, has readings between 0.068 mg/m3 and 0.073 mg/m3 (range: 0.005 mg/m3), comparing with D2-LP-03, a room without air-conditioning with also 40 seating capacity, has readings between 0.098 mg/m3 and 0.100 mg/m3 (range: 0.002 mg/m3). The bigger fluctuation of data in an air-conditioned room may be due to air convection, for the fact that air moves more.
Air-conditioners are installed near the ceilings to efficiently cool down sparse hot air raised to the top, hot air that are cooled then become denser and lowered to the floor, which may be pushed up again when air from the top are cooled cold enough to be lowered to replace them. Such convection makes concentration of PM2.5 more evenly distributed among the air. Vice versa, as the test in D2-LP-03 is conducted near the hand level (about 1m above floor), without air convection, much of the particulates sink, creating the larger concentration reading comparing to D3-G-03, as in the case of atmospheric inversion ("Atmospheric Inversion", 2003). It is believed that if the test is carried near the ceiling in D2-LP-03, the reading may be slightly smaller, which is worth further investigation.
2. Influence of room size on PM2.5 concentration:
D2-LP-03, a classroom without air-conditioning with 40 seating capacity, has an average reading of 0.0993 mg/m3, when comparing to D2-LP-09, a lecture theatre with 98 seating capacity, with an average reading of 0.0284 mg/m3, is a very high reading. The concentration of PM2.5 in atmospheric air shall be similar in both rooms, as they come from the same atmosphere. From our readings, however, D2-LP-09’s readings are much lower. We therefore put forward another hypothesis. Besides atmospheric air, there are particulates that have settled on the ground. Given that each human movement in a room triggers a certain amount of PM2.5 into the air, whether such amount is distributed in a large space or a small space is concerned. D2-LP-09, larger, thus PM2.5 inside is more sparsely distributed.
3. Comparison of Minivol and DustTrak in measurement:
MiniVol data is less consistent than DustTrak, as it can easily affected by ‘environmental variables or a problem with the field site’ (Kingham, 2006, p.345). For example, in the research carried out by Kingham (2006, p.344) on woodsmoke air pollution, the result was affected by ‘two small stacks emitting diesel exhaust and the outlet from a swimming pool’s air conditioning unit nearby’. Generally, however, Minivol measurement complies with the federal and state air quality standards, while DustTrak do not (Lancaster, 2009; Kingham, 2006). This is because DustTrak uses a laser beam to measure dust concentrations in a chamber within the instrument and was factory-calibrated for aerosols of different optical properties (Kingham, 2006). This causes a constant over-reading of the true PM mass by DustTrak (Kingham, 2006).
However, DustTrak do have some merits, including ‘relatively low cost, portability, real-time data capability, and the concurrent measurement of PM1, PM2.5, PM4, PM10 and TSP’ (TSI, 2012, p.5). Given these merits cannot be achieved by Minivol, DustTrak is also frequently used by researchers, as it can ‘feasibly be adjusted with a site-specific factor’ to produce accurate data (Kingham, 2006). Such factor varies in different settings (Kingham, 2006, p.345). By contrast, Minivol needs hours to be installed by a considerable person, plus that collecting and processing filters as well as quality control protocols processes are required, making Minivol a much expensive means for measurement (Kingham, 2006).
4. Comparison of Minivol result with other Minivol measurements on PM2.5 in literature:
Minivol has been popularly used for PM2.5 measurement in many different countries, given its accuracy. Some of the Minivol measurements from literature are compared below with our experiment:
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From the above chart, we can see that PM2.5 concentration levels acquired using Minivol varies greatly around the world. The highest readings of the above chart is from China and Brazil, as China is among the most air-polluted countries in the world and Brazil has a large number of diesel vehicles (Yale University, 2014; Brito et. al., 2013). Comparatively, HKIEd already is the least polluted in China, and HKIEd air is 6.7 times less polluted than the air in Rodoanel Tunnel, Brazil.
For countries that have cleaner air, such as South Korea, still some of the readings are higher than HKIEd, such as readings from Internet cafés and underground subway stations, because the smoking is allowed in the former and the large amount of passenger flow in the latter. Other readings in South Korea is much lower than HKIEd, with the lowest reading at 4.1µg/m3 from a movie theatre, which is 10 times less polluted than the HKIEd air.
Part six: Limitations
There is one variable that cannot be controlled in Comparison set A. As there was limited time during the lesson to carry out the tests, we could not find a classroom with similar capacity on the ground floor for the set. It is possible that the lower floor level that D2-LP-03 is located, as we have discussed in the previous paragraph, contributes to the higher concentration of PM2.5, but not air-conditioning. The room size of both rooms also varies. By observation, D3-G-03 is comparatively larger. Although both rooms in the set are designed for a seating capacity of 40, D3-G-03, for the fact that it is a laboratory, have a much spacious design than D2-LP-03, for the use of an ordinary classroom.
Comparison set B, investigating the influence of room size of PM2.5 concentration, have also uncontrollable variables. One example is the presence of mat in D2-LP-09. It may have contributed to the low reading as particulates are trapped when they reach the mat, whereas in D2-LP-03, with no mat, particulates cannot be trapped and can only accumulate in the air, thus creating higher readings.
For all rooms involved in the experiment, we cannot know before the investigation team’s arrival, the number of people in the room, the amount of time they stayed, and how proximate was between their stay and our arrival. As people move, dust can be removed from their position into the air, and that people can bring dust attached on their bodies and belongings, which can affect readings. Human factors cannot be controlled due to the fact that we do not have the authority to prohibit other users from entering the classrooms.
Part seven: Conclusion
There are a lot of limitations in carrying out this experiment, especially the presence of a lot of uncontrollable factors. If it is to ignore these factors, however, it is deducible that rooms with air-conditioning, larger room size and higher floor level can help lower the concentration of PM2.5 in the air of human reach.
Part eight : Reference
Atmospheric Inversion. (2003). In M. Bortman, P. Brimblecombe & M.A. Cunningham (Eds.), Environmental Encyclopedia (3rd ed.) (Vol. 1, p. 97). Detroit, MI: Gale. Retrieved from http://go.galegroup.com/ps/i.do?id=GALE%7CCX3404800133&v=2.1&u=hkioel&it=r&p=GVRL&sw=w&asid=2aaefc5cb4143d55248450192c90c307
Brito, J., Rizzo, L.V., Herckes, P., Vasconcellos, P.C., Caumo, S.E.S., Fornaro, A., & ... Andrade, M.F. (2013). Physical–chemical characterisation of the particulate matter inside two road tunnels in the São Paulo Metropolitan Area. Atmospheric Chemistry and Physics, 13, 12199-12213 doi:10.5194/acp-13-12199-2013
Kim, H.-H., Lee, G.-W., Yang, J.Y., Jeon, J.-M., Lee, W.-S., Lim, J.Y., & ... Lim, Y.-W. (2014). Indoor Exposure and Health Risk of Polycyclic Aromatic Hydrocarbons (PAHs) via Public Facilities PM2.5, Korea (II). Asian Journal of Atmospheric Environment, 8(1), 35-47 doi:10.5572/ajae.2014.8.1.035
Kingham, S., Durand, M., Harison, J., Gaines Wilson, J., Aberkane, T. & Epton, M. (2006). Winter comparison of TEOM, MiniVol and DustTrak PM10 monitors in a woodsmoke environment. Atmospheric Environment, 40(2), 338-347 doi:10.1007/s10653-013-9557-4
Lancaster, N. (2009). Aeolian Features and Processes. In R. Young & L. Norby (Eds.), Geographical Monitoring. Boulder, CO: The Geological Society of America. Retrieved from https://books.google.com.hk/books?id=qHrF2uqSlUEC&pg=PA13&lpg=PA13&dq=minivol+dusttrak+better&source=bl&ots=SJjDrzNNDU&sig=r_FTuJkcb3E2Pvv6Gp4WKXSTfuo&hl=en&sa=X&ved=0CDgQ6AEwBWoVChMI16ao0t-WyQIViR2UCh0QUAFc#v=onepage&q=minivol%20dusttrak%20better&f=false
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Raaschou-Nielsen, O., Andersen, Z. J., Beelen, R., Samoli, E., Stafoggia, M., Weinmayr, G., & ... Nafstad, P. (2013). Air pollution and lung cancer incidence in 17 European cohorts: prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE). Lancet Oncology, 14(9), 813-822 doi:10.1016/S1470-2045(13)70279-1
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TSI (2012). DustTrak™ DRX in Environmental Applications. Retrieved from Nov 17, 2015. http://www.tsi.com/uploadedFiles/_Site_Root/Products/Literature/Application_Notes/EXPMN-006-A4_DustTrak_DRX_in_Environmental_Applications-web.pdf
United States Environmental Protection Agency (2015). Health Effects Notebook for Hazardous Air Pollutants. Retrieved from Nov 17, 2015. http://www3.epa.gov/airtoxics/hlthef/hapindex.html
Wang, J., Lai, S., Ke, Z., Zhang, Y., Yin, S. & Zheng, J. (2014). Exposure assessment, chemical characterization and source identification of PM2.5 for school children and industrial downwind residents in Guangzhou, China. Environmental Geochemistry & Health, 36(3), 385-397 doi:10.1007/s10653-013-9557-4
Yale University (2014). Air Pollution Trends in Countries and Cities. Retrieved from Nov 17, 2015. http://epi.yale.edu/pollution-map/
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