Report on Co-location of Dust Sentry PM Monitors · With the data provided it is found that the Dust Sentry performed well in relation to the BAMs and each other. The averaged difference

Report on Co-location of Dust Sentry PM10 Monitors

Prepared for Aeroqual Ltd

December 2012

© All rights reserved. This publication may not be reproduced or copied in any form without the permission of the copyright owner(s). Such permission is only to be given in accordance with the terms of the client’s contract with NIWA. This copyright extends to all forms of copying and any storage of material in any kind of information retrieval system.

Whilst NIWA has used all reasonable endeavours to ensure that the information contained in this document is accurate, NIWA does not give any express or implied warranty as to the completeness of the information contained herein, or that it will be suitable for any purpose(s) other than those specifically contemplated during the Project or agreed by NIWA and the Client.

Authors/Contributors : Nick Talbot and Guy Coulson

For any information regarding this report please co ntact: Guy Coulson Group Manager Air Quality and Health +64-9-375 2050 [email protected] National Institute of Water & Atmospheric Research Ltd 41 Market Place Auckland Central 1010 Private Bag 99940 Newmarket Auckland 1149 Phone +64-9-375-2050 Fax +64-9-375-2051

NIWA Client Report No: Ak - 2012 - 048 Report date: December 2012 NIWA Project: AK13ACHR


Contents

Executive summary ................................. ............................................................................. 5

1 Introduction ...................................... ........................................................................... 7

2 Methods ........................................... ............................................................................ 7

2.1 Metadata .............................................................................................................. 8

3 Results and Discussion ............................ ................................................................ 10

3.1 Meteorological Data ........................................................................................... 13

4 Comparison with an indicative monitoring standard.. ............................................ 16

5 Conclusions ....................................... ........................................................................ 18

Appendix A Meteorological Data ............................... ...................................................... 19

Appendix B Results ........................................... .............................................................. 21

Tables Table 2-1: List of analysers used in the co-location. 7

Table 2-2: Exculded data. 8

Table 2-3: List of data points removed during maintenance work. 9

Table 4-1: Results from Equivalency Calculator. 17

Figures Figure 2-1: Photograph of the co-location set up. 8

Figure 3-1: Daily polt of all co-located instruments. 11

Figure 3-2: Daily plot of all co-located instruments. 11

Figure 3-3: Correlations between the different instruments. 12

Figure 3-4: The ratio of BAM vs Dust Sentry values as a time series. 13

Figure 3-5: Daily average wind speed and PM10 (Dust Sentry and BAM). 14

Figure 3-6: Daily average temperature and PM10 (Dust Sentry and BAM). 14

Figure 3-7: Daily average humidity and PM10 (Dust Sentry and BAM). 15

Figure 3-8: Daily average atmospheric pressure and PM10 (Dust Sentry and BAM). 15


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Report on Co-location of Dust Sentry PM10 Monitors 5

Executive summary Aeroqual Ltd have developed a forward scattering nephelometer, named a Dust Sentry, to measure particulate matter concentrations in the air. These instruments provide real time, continuous PM10 data when a sharp cut cyclone inlet is used.

Aeroqual Ltd installed two Dust Sentry PM10 monitors at a National Environment Standard monitoring site run by Nelson City Council for the purposes of a co-location study. The Dust Sentries were run alongside two PM10 EPA designated Federal equivalence method Beta Attenuation Monitors (BAMs) and a PM10 Partisol® sampler to ascertain performance over a period of 55 days.

Using data provided by Aeroqual Ltd this report

• Re-analysed the data and formatted it into required daily means

• Applied and discussed the equivalence analysis as described in the United kingdom Environment Agency MCERTS standard for Indicative Ambient Particle Monitors.

With the data provided it is found that the Dust Sentry performed well in relation to the BAMs and each other. The averaged difference between the 2 Dust Sentries was 1.69 µg/m3, whilst the difference between the average of both Dust Sentries and the average of both BAMs is 3.25 µg/m3. The second half of the co-location period saw greater differences between the Dust Sentries and BAMs. The reason for this is not clear; however these differences coincided with windier, more changeable meteorological conditions.

In relation to MCERTS certification, NIWA was not part of the co-location field test so is unable to comment on the compliance of the Dust Sentries in relation to the overall requirements of MCERTS. However, applying the data through the provided equivalence calculator showed that the data met the uncertainty requirements of the MCERTS Standard for Indicative Ambient Particle Monitors. That is, the measured uncertainty of the instrument was less than the expanded uncertainty criteria for indicative instruments.


1 Introduction

Aeroqual Ltd have developed a forward scattering nephelometer, named a Dust Sentry, to measure particulate matter concentrations in the air. These instruments provide real time, continuous PM10 data when a sharp cut cyclone inlet is used. Two units were operated alongside two Beta Attenuation Monitors (BAM) and a Partisol® sampler in a co-location study. The goal of the study was to establish baseline performance of the Dust Sentry units against the BAMs, whose performance was verified by the Partisol® Sampler. The test ran from 28th July until 20th September 2012. This report documents the data provided by Aeroqual Ltd and gives a summary of the performance of the Dust Sentries during this period.

2 Methods

All instruments were located at the Nelson City Council (NCC) air quality monitoring station at St Vincent Street, Nelson South (LAT:-41.2782, LON: 173.2735) Table 2-1 shows the details of the units used in the co-location study. Figure 2-1shows a photograph of the site.

Table 2-1: List of analysers used in the co-locatio n.

Instrument Type manufacturer Model Serial Number Owner Identity

Partisol® Sampler Thermo Scientific Model 2000 Unknown Nelson City Council Partisol®

Beta Attenuation Monitor Thermo Scientific Series FH-62 E-0986 Nelson City Council BAM1

Beta Attenuation Monitor Thermo Scientific Series FH-62 E-1194 NIWA BAM2

Nephelometer Aeroqual Ltd Dust sentry DS-140612-030 Aeroqual Ltd DS-1

Nephelometer Aeroqual Ltd Dust Sentry DS-140612-031 Aeroqual Ltd DS-2

8 Report on Co-location of Dust Sentry PM10 Monitors

Figure 2-1: Photograph of the co-location set up. The two BAMs are inside the enclosure, the two Dust Sentries are on tripods and the Partisol is on the Ground to the left of the photo.

2.1 Metadata Table 2-2 provides a list of missing data times and reasons as provided by Aeroqual Ltd

Table 2-2: Exculded data.

Date Instrument Reason

22/08/2012 BAM 1 Temperature sensor failed on August 13th, replaced August 22nd August

26/08/2012 Partisol® Filter mass not reported due to an internal weight issue

27/08/2012 Partisol® Filter mass not reported due to double sampling of filter

28/08/2012 Partisol® Filter mass not reported due to an internal weight issue

29/08/2012 Partisol® Filter mass not reported due to double sampling of filter

5/09/2012 DS-2 Data logger failure

20/09/2012 DS-2 Data logger failure

The temperature sensor on BAM 1 failed on 13th August and was replaced on 22nd August. The data for the whole of 22nd August were removed as the instrument was not operational during the sensor replacement. Having discussed the temperature sensor fault with Paul Sheldon of Tasman District Council it was concluded that this was unlikely to have significantly affected the data and therefore data for the 13th to 21st were not removed (Paul Sheldon, Pers. Comms.).


Data from 22/08/2012, 05/09/2012 and 20/09/2012 have been omitted from the results section due to the above issues. Partisol® data from the days listed have also been omitted. The Dust Sentries collect data every 2 minutes and daily means have been calculated manually. For the purposes of co-location comparative testing all data is represented as a 24 hour average. This was carried out initially by Aeroqual Ltd; however as part of this report the raw data provided were reprocessed. The two BAMs automatically gave 24 hour averages, with those averages applied here.

The two Dust Sentries carry out a zero-test procedure twice a day, identified by a series of ‘9’s in the dataset. These have been removed, typically affecting 8 minutes of data per day. There were also twice-monthly span and zero checks carried out on the Dust Sentries. A maintenance log was provided by Aeroqual Ltd. The times of the maintenance checks listed did not match the timestamps of the zero and span check, neither was there a record of which data points had been removed by Aeroqual Ltd, therefore for the purposes of this report the zero / span calibrations were identified and then 2 data points were removed before and after to allow for possible undue influences to the data. Table 2-3 lists the dates and times when data were removed.

Table 2-3: List of data points removed during maint enance work.

Date Dust Sentry Times

removed

10-Aug DS1 09:44 - 09:54

DS2 09:25 - 09:41

20-Aug DS1 10:10 - 10:18

DS2 09:58 - 10:06

10-Sep DS1 09:38 - 09:52

DS2 09:45 - 09:53

It is reported that a full calibration was carried out on both BAMs in tandem by Paul Sheldon of Tasman District Council in accordance to the required annual service procedure including temperature, pressure, flow and mass sensors. Whilst showing no evident effect in the data and therefore not removed in this report, the failure of the ambient temperature sensor in BAM 1 could result in changes to the flow rate1 and therefore compromise the integrity of the co-location from the point of view of MCERT certification and might be required to be removed. This data is analysed in more detail in Section 3.

1 Series FH62C14 Instruction manual, Thermo Fisher Scientific Inc, 2007


3 Results and Discussion

Results for the co-location study are shown Figure 3-1 and Figure 3-2 and listed in Appendix B. The graphs show 52 days of co-location data. It is clear that the Partisol® generally reads the highest values and the Dust Sentries the lowest.

The Partisol® gave the highest reading 67.5% of the time with the BAMs sharing the rest of the peak values. DS-1 gave the lowest values 84% of the time during the co-location, which equates to all but 9 times. The largest differences between the Dust Sentries and the BAMs were on the 7th and 8th September. Overall the performance between the Dust Sentries averaged against both BAMs shows a difference of 3.25 µg/m3, however there is a general deterioration in the performance in the second half of the co-location. To demonstrate this point, taking averaged data from both Dust Sentries against both BAMs from the 28/07 until and including the 27/08 the difference is 1.65 µg/m3, for the remaining days the average difference is 5.47 µg/m3. The differences can be seen Figure 3-1 and Figure 3-2. The reason for this deterioration is unclear, meteorological conditions could be a factor and are discussed in Section 3.1.

The difference in the operating principle between the instruments and the difference in inlet temperature could explain some of the observed differences. For example, it is feasible that the hotter inlet of the Dust Sentry, plus its slower flow, result in a larger loss of volatile species than the BAM. Days when this could be seen to occur are evident in Figure 3-3. The overall average difference between the two BAMs during the co-location was 0.13 µg/m3 but between the 10th and the 22nd August it was 0.02 µg/m3. The second period corresponds to when BAM-1 presented a faulty temperature sensor. Both show very good performance, well within the manufacturer’s stipulated precision of ± 2 µg/m3 (24-hour)2.

2 http://www.thermo.com/eThermo/CMA/PDFs/Product/productPDF_7597.pdf


Figure 3-1: Daily polt of all co-located instrument s.

Figure 3-2: Daily plot of all co-located instrument s.


Figure 3-3: Correlations between the different inst ruments. a) DS1 vs BAM2, b) DS2 vs BAM2, c) DS1 vs average of both BAMS, d) DS1 vs DS2, e) Average of both BAMs vs Partisol, f) BAM 1 vs BAM 2.


Taking into account all 52 days of data the overall average concentration of Dust Sentry 1 is 16.83 µg/m3, Dust Sentry 2 is 18.52 µg/m3, BAM 1 is 20.99 µg/m3 and BAM 2 is 20.86 µg/m3. The difference between the two Dust Sentries through the 52 days is 1.69 µg/m3, whilst averaging together both Dust Sentries and the two BAMs there is a difference of 3.25 µg/m3.

The low reading from the Dust Sentries in comparison to the BAM is clearly shown in Figure 3-3 a, b, and c. These losses clearly affect the overall linearity with a correlation co-efficient for DS-1 R2 = 0.839 and DS-2 R2= 0.816. Both Dust Sentries displayed very strong linearity with correlation co-efficient, R2 = 0.988.

The average ratio of BAM to Dust Sentry is 1.18, i.e. the Dust Sentries record slightly lower values than the BAMs, as can be seen from the slopes of the regression lines in Figure 3-3. However, as can be seen from Figure 3-4 this ratio is close to one for most of the duration but is interspersed with period when the ratio is closer to two, as seen at the beginning and end of the period. The reason for this is beyond the scope of this analysis.

Figure 3-4: The ratio of BAM vs Dust Sentry values as a time series.

3.1 Meteorological Data

Figure 3-5 to Figure 3-8 show averaged Dust Sentry and BAM data against various meteorological parameters during the co-location. All data are averaged over a 24 hour period.


Figure 3-5: Daily average wind speed and PM10 (Dust Sentry and BAM).

Figure 3-6: Daily average temperature and PM10 (Dus t Sentry and BAM).


Figure 3-7: Daily average humidity and PM10 (Dust S entry and BAM).

Figure 3-8: Daily average atmospheric pressure and PM10 (Dust Sentry and BAM).


Meteorological conditions can increase disparities between different instruments depending on various factors including their principle of operation, capturing and inlet systems. The above figures show that where wind speed is lowest the difference between the instruments is at its lowest; this also coincides with a period of high humidity. Greater temperature variation seems to increase difference between BAMs and Dust Sentries. All these explanations are possible but the determination of the reason of these differences is outside the scope of this report.

4 Comparison with an indicative monitoring standard

The United Kingdom Environment Agency has established a Monitoring Certification (MCERTS) scheme to provide a homogenised framework of standards, this includes evaluating the standards of performance that monitoring equipment must meet.

This section will evaluate the Dust Sentries performance in relation to the MCERTS criterion. This assessment is solely based on the data provided by Aeroqual Ltd. The data has not been verified by NIWA. It is also noted that this section will give no opinion regarding the suitability of the chosen site, the overall operation or maintenance of the analysers. Only gravimetric methods, including Partisol, are considered reference methods while BAMs are "equivalence" methods. However Aeroqual received consent from the MCERTS certification committee to use two BAMs as reference instruments as long as a Partisol was co-located to demonstrate that the uncertainty of the BAMs was acceptable. Correlation between the BAMs and the Partisol is 0.98.

For field testing of indicative particle monitors MCERTS states that a minimum of 40 measurement results need to be included. Aeroqual co-located their instruments for 55 days and have withdrawn 3 days of BAM data due to technical issues.

The MCERTS performance standard states that during co-location field testing the candidate instruments should exhibit a highest uncertainty estimate, WCM that is less than the expanded relative uncertainty, Wdqo with Wdqo = 50%3. An equivalence calculator is provided by EU Environment agency for the purposes of testing equivalency.

MCERTS requests that within the 40 paired runs meteorological data should be as varied as possible therefore dates with the warmest, coolest, windiest, calmest and most humid conditions should be noted. The warmest daily average was 1/08/2012 at 14.3 °C; the coldest daily average was 12/09/2012 at 6.8 °C. Humidity averaged 91.1 % on the 8/08/2012. Wind speed was highest on 8/09/2012 at 4.2 m/s and calmest on the 5/08/2012 at 0.93 m/s.

The MCERTS data evaluation procedure explicitly states that data should not be removed unless there is a sound technical reason to do so. As NIWA were not party to the running or specifics of the co-location all data for this report all data should remain with the exception of calibrations and technical failures already specified.

3 Demonstration of Equivalence of Ambient Air Analytical Method. www.ec.europa.eu/environment/air/pdf/test_equivalencev31004.xls


The value for the Reference Method in-between-sampler Uncertainty (ubs) is calculated using the equation below:

Where:

yi,1 and yi,2 are parallel measurements for a single 24 or 1-hour period i.

nbs = number of in-between-sampler 24 hour or 1-hour measurement results.

When this equation is applied to the BAM data (as the reference method in this case) it yields a value of 0.21.

When all data is processed through the equivalency calculator the results shown in Table 4-1 are obtained

Table 4-1: Results from Equivalency Calculator. When the results from the co-location test are input to the equivalency calculator the results are output as a table.


5 Conclusions

With the methodology and data provided by Aeroqual Ltd, this report finds the Dust Sentries to demonstrate good stability running against each other. There is greater variability between the Dust Sentries and the BAMs, especially in the second half of the co-location period. Further exploration of meteorological parameters at a finer temporal resolution could be useful to assess the influences in changes of conditions on the performance of the Dust Sentries.

During the full period of the co-location the Dust Sentries performed within the acceptable level of inter-sampler uncertainty as stipulated by UK Environment Agency MCERTS.

The overall performance of the two BAM’s was very good over the 24hr averaged period and the two Dust Sentries also performed well in tandem with each other. It would be of interest to devise a testing mechanism to allow and quantify the possible loss of volatiles from the flow and heating of the Dust Sentry’s inlet system.


Appendix A Meteorological Data

Date Average Average Average Average Correctly averaged Average

Temperature Relative humidity Wind speed Wind speed Wind direction Pressure

Daily °C Daily % Average m s-1

Real vector m s -1

deg. hPa

28/07/2012 67.18 1.23 0.42 279.11 1024.41

29/07/2012 77.47 1.37 0.58 35.13 1013.67

30/07/2012 78.08 2.73 2.06 41.9 996.31

31/07/2012 76.65 1.92 1.19 59.52 1003.23

1/08/2012 14.32 68.36 2.96 1.7 60.01 1012.16

2/08/2012 12.69 61.58 3.08 1.66 59.25 1018.27

3/08/2012 12.87 70.86 2.17 0.52 97.3 1017.73

4/08/2012 11.7 86.13 0.99 0.69 242.75 1016.01

5/08/2012 10.49 84.89 0.93 0.57 266.12 1011.46

6/08/2012 9.25 84.26 1.13 0.13 318.97 1008.46

7/08/2012 8.61 90.66 1.05 0.13 186.88 1006.61

8/08/2012 8.99 91.14 0.94 0.77 230.01 1003.38

9/08/2012 8.58 83 1.04 0.35 230.79 1005.46

10/08/2012 8.72 82.98 1.11 0.16 308.09 1012.63

11/08/2012 9.72 83.37 0.99 0.59 261.41 1015.85

12/08/2012 10.89 84.17 1.76 0.34 349.38 1004.14

13/08/2012 10.31 86.39 1.12 0.32 351.1 1002.82

14/08/2012 10.52 80.66 1.03 0.27 322.88 1010.38

15/08/2012 10.18 86.72 1.14 0.52 36.9 1010.66

16/08/2012 10.16 86.27 1.06 0.25 322.59 1009.36

17/08/2012 8.77 78.79 1.19 0.79 233.24 1013.91

18/08/2012 7.92 82.69 1.26 0.21 323.97 1019.56

19/08/2012 8.45 90.46 0.97 0.42 218.71 1016.9

20/08/2012 10.09 86.19 1.22 0.38 279.9 1005.77

21/08/2012 9.67 84.53 1.25 0.37 8.48 1011.11

23/08/2012 8.93 80.76 1.25 0.3 339.89 1026.5

24/08/2012 8.03 78.92 1.45 0.48 26.1 1027.68

25/08/2012 9.74 78.32 1.38 0.69 42.38 1025.33

26/08/2012 13.11 88.61 3.51 3.49 47.33 1019.79

27/08/2012 13.36 73.85 3.44 0.9 24.24 1012.71

28/08/2012 8.98 70.06 1.43 0.23 342.01 1020.38

29/08/2012 7.96 79.3 1.31 0.21 332.98 1022.71

30/08/2012 10.06 65.78 1.41 0.44 281.32 1022.34

31/08/2012 8.88 72.06 1.33 0.36 292.75 1023.95

1/09/2012 9.92 77.84 1.56 0.73 38.55 1025.53

2/09/2012 12.25 82.35 3.22 3.21 50.4 1020.16

3/09/2012 12.06 85.94 3.06 2.57 48.41 1001.58


Date Average Average Average Average Correctly averaged Average

Temperature Relative humidity Wind speed Wind speed Wind direction Pressure

Daily °C Daily % Average m s-1

Real vector m s-1

deg. hPa

4/09/2012 10.32 74.05 2.42 1.69 239.75 996.78

6/09/2012 13.06 66.81 1.77 0.45 357.3 1014.07

7/09/2012 15.46 68.9 2.9 0.3 39.01 1008.26

8/09/2012 12.86 82.42 4.22 3.63 40.58 996.01

9/09/2012 9.08 77.35 1.6 0.48 232.99 994.95

10/09/2012 9.99 67.19 2.22 0.98 251.51 1003.09

11/09/2012 7.22 69.31 2.96 2.78 227.83 1009.09

12/09/2012 6.8 57.57 1.81 1.32 239 1022.67

13/09/2012 6.51 70.08 1.44 0.39 280.89 1022.15

14/09/2012 8.95 69.99 1.89 1.22 35.15 1018.61

15/09/2012 12.51 77.02 4 3.96 48.35 1013.53

16/09/2012 12.21 82.23 1.59 1.08 36.18 1011.7

17/09/2012 1007.65

18/09/2012 1021.87

19/09/2012 1019.38


Appendix B Results

Results for the co-location with maximum, minimum. All data is in µg/m3.

DATE DS-1 DS-2 E1194 BAM

E0986 BAM Partisol ® MAXIMUM MINIMUM

28/07/2012 44.76 48.73 37.42 37.5 44.00 48.73 37.42

29/07/2012 26.08 28.77 24.23 24.56 29.00 29.00 24.23

30/07/2012 6.33 7.18 9.35 9.02 9.00 9.35 6.33

31/07/2012 11.99 13.30 21.4 20.46 24.00 24.00 11.99

1/08/2012 2.68 2.97 5.33 5.31 3.00 5.33 2.68

2/08/2012 2.76 3.22 6.06 6.27 6.00 6.27 2.76

3/08/2012 9.02 10.07 11.65 11.48 14.00 14.00 9.02

4/08/2012 19.16 20.98 19.33 19.9 22.00 22.00 19.16

5/08/2012 27.99 30.55 27.13 27.85 31.00 31.00 27.13

6/08/2012 35.94 39.53 35.19 35.83 41.00 41.00 35.19

7/08/2012 26.19 29.35 26.56 26.9 28.00 29.35 26.19

8/08/2012 28.71 32.28 28.17 28.75 32.00 32.28 28.17

9/08/2012 34.73 37.83 33.67 34.06 38.00 38.00 33.67

10/08/2012 32.78 35.68 34.5 34.67 40.00 40.00 32.78

11/08/2012 34.37 37.32 33.5 34.81 39.00 39.00 33.50

12/08/2012 9.67 10.55 15.56 16 15.00 16.00 9.67

13/08/2012 19.02 20.14 21.33 20.96 24.00 24.00 19.02

14/08/2012 21.20 22.55 24.35 24.44 26.00 26.00 21.20

15/08/2012 8.87 9.41 14.13 13.92 13.00 14.13 8.87

16/08/2012 14.71 16.08 17.33 16.27 20.00 20.00 14.71

17/08/2012 29.02 31.34 31.73 32.02 37.00 37.00 29.02

18/08/2012 30.98 33.25 30.9 30.4 34.00 34.00 30.40

19/08/2012 26.46 28.49 28.17 28.25 25.00 28.49 25.00

20/08/2012 18.70 20.60 19.94 19.71 22.00 22.00 18.70

21/08/2012 21.28 23.75 24.67 24.92 27.00 27.00 21.28

23/08/2012 19.27 21.22 23.23 23.54 24.00 24.00 19.27

24/08/2012 18.87 21.25 24.06 23 25.00 25.00 18.87

25/08/2012 15.83 17.84 19.79 19.04 17.00 19.79 15.83

26/08/2012 7.78 8.94 21.94 21.31 21.94 7.78

27/08/2012 13.24 15.28 23.13 22.42 23.13 13.24

28/08/2012 14.97 17.51 19.67 19.67 19.67 14.97


DATE DS-1 DS-2

E1194

BAM

E986

BAM Partisol® MAXIMUM MINIMUM

29/08/2012 20.82 23.69 25.58 25.19 25.58 20.82

30/08/2012 18.04 20.27 21.67 20.9 21.00 21.67 18.04

31/08/2012 19.87 22.24 21.88 21.69 25.00 25.00 19.87

1/09/2012 10.74 12.49 19.27 17.15 19.00 19.27 10.74

2/09/2012 6.77 7.39 20.44 20.85 20.00 20.85 6.77

3/09/2012 17.15 18.70 18.75 18.81 21.00 21.00 17.15

4/09/2012 8.98 9.82 15.63 14.6 14.00 15.63 8.98

6/09/2012 10.20 11.91 21.75 21.48 23.00 23.00 10.20

7/09/2012 13.46 16.39 30.17 29.1 30.17 13.46

8/09/2012 12.47 13.91 27.94 28.92 28.92 12.47

9/09/2012 6.59 7.67 8.73 8.81 8.81 6.59

10/09/2012 6.25 7.23 11.02 9.98 11.02 6.25

11/09/2012 9.90 10.18 10.33 10.73 10.73 9.90

12/09/2012 13.76 15.03 16.02 15.71 16.02 13.76

13/09/2012 23.87 24.63 23.4 23.48 24.63 23.40

14/09/2012 11.97 12.64 18.73 17.71 18.73 11.97

15/09/2012 5.27 5.71 17.17 17.44 17.44 5.27

16/09/2012 5.95 7.09 14.71 14.23 14.71 5.95

17/09/2012 4.11 4.24 7.98 7.4 7.98 4.11

18/09/2012 5.50 5.50 11.85 11.65 11.85 5.50

19/09/2012 10.04 10.38 14.98 15.6 15.60 10.04

Documents

Report on Co-location of Dust Sentry PM Monitors · With the data provided it is found that the Dust Sentry performed well in relation to the BAMs and each other. The averaged difference