A long-term monitoring results and summary of airborne ...
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4 th International Conference On Building Energy, Environment A long-term monitoring results and summary of airborne particle size distribution from 10nm to 10μm under different PM contamination level s in Beijing X. Feng 1 , H. Zhang 1 , Y. Zhang 1 , J. Bai 2 1 Air Cleaning Technique Center, China Academy of Building Research, 30 North 3rd Ring East Rd., Beijing, China 2 Beijing Institute of Architectural Design, 62 South Lishi Rd., Beijing, China SUMMARY Particulate Matter (PM) pollution of the environmental air is now a critical issue in China and other developing countries. This leads to enormous demands on both air cleaning equipments and a more scientific standardized method on performance evaluation of such instruments. In this work, a long-term monitoring on indoor/outdoor atmospheric particle number size distribution from 10nm to 10μm under different PM2.5 concentration levels was conducted in an office building in Beijing. Measurement results in this work show that atmospheric number size distribution could be regarded as the combination of two lognormal distributions with peaks occur in similar size range, although the PM2.5 mass concentration varies greatly from less than 50μg/m³ to over 400μg/m³. Indoor airborne particle size distribution is strongly affected by outdoor air in case of no obvious indoor contamination sources existing. Particles with diameter from ~100nm to ~300nm are the part hardest to be removed. INTRODUCTION The removing efficiency of most air cleaning equipments varies according to challenge particles size due to the combination effect of different particle collection mechanism (William C. Hinds, 1999). Furthermore particle number size distribution would significantly affect the particle piling procedure on filter fibers. Thus the test particle number size distribution is a key factor for both the particulate matter (PM) removing performance and life cycle energy consumption evaluation of air cleaning equipments. Nevertheless challenge particles as well as the loading dust recommended in the current international standardization system are not designed to reflect the size distribution character of the real atmospheric air, and thus insufficient to make scientific evaluation comparable with real life performance for air cleaning equipments. In previous researches, atmospheric particle size distribution were measured and analysed to determine the influence of climate (Wolfram Birmili etc., 2001), seasons (F.J.Gomez- Moreno etc., 2011;LI Ling-jun etc., 2008), traffic (Ismael Luis Schneider etc., 2015), times and altitude(Vladimir Zdimal etc., 2011) etc.. The focus of the previous researches was mainly about the ambient particles' "dynamic" procedure and mechanism, including generation and formation, transportation and revolution etc. Such researches would lead to useful information for air pollution control and people's exposure control. But not much efforts were made to figure out characters in common of the atmospheric particle number size distribution in different time, different seasons and different PM contamination levels. Such characters would finally help us build "typical and representative" challenge particles which are much closer to the real atmospheric air, and would allow the possibility to evaluate the filtration performance and life cycle energy consumption based on a more scientific methodology. In this work, a long-term monitoring on indoor/outdoor atmospheric particle number size distribution from 10nm to 10μmunder different PM2.5 concentration levels was conducted. We hope the measurement results could offer useful information for the development of new typical test aerosol for the evaluation of air cleaning equipments. METHODS Instruments A wide-range particle spectrometer (WPS) (Benjamin Y.H. Liu etc., 2010) was used in this research to collect particle size distribution information from nano-size to supermicron- size. This instrument comprises a differential mobility analyzer (DMA) and a condensation particle counter (CPC) for particle measurement from 0.01 to 0.5μm up to 96 channels based on particle mobility classification under electricity field, and a Laser Particle Spectrometer (LPS) for particle measurement from 0.35 to 10μm. For PM2.5 mass concentration test. Fig 1 illustrates the schematic flow diagram of WPS. For the total PM2.5 mass concentration test, a light scattering test instrument, TSI Dusttrack 8532, was used. Fig 2 shows how the two instruments are set and work together. Fig 1 Schematic flow diagram of the WPS ISBN: 978-0-646-98213-7 COBEE2018-Paper221 page 652
Transcript of A long-term monitoring results and summary of airborne ...
4th International Conference On Building Energy, Environment
A long-term monitoring results and summary of airborne particle size distribution from 10nm to 10μm under different PM contamination levels
in Beijing
X. Feng1, H. Zhang 1, Y. Zhang 1, J. Bai2 1Air Cleaning Technique Center,
China Academy of Building Research, 30 North 3rd Ring East Rd., Beijing, China 2Beijing Institute of Architectural Design, 62 South Lishi Rd., Beijing, China
SUMMARY Particulate Matter (PM) pollution of the environmental air is now a critical issue in China and other developing countries. This leads to enormous demands on both air cleaning equipments and a more scientific standardized method on performance evaluation of such instruments. In this work, a long-term monitoring on indoor/outdoor atmospheric particle number size distribution from 10nm to 10μm under different PM2.5 concentration levels was conducted in an office building in Beijing. Measurement results in this work show that atmospheric number size distribution could be regarded as the combination of two lognormal distributions with peaks occur in similar size range, although the PM2.5 mass concentration varies greatly from less than 50μg/m³ to over 400μg/m³. Indoor airborne particle size distribution is strongly affected by outdoor air in case of no obvious indoor contamination sources existing. Particles with diameter from ~100nm to ~300nm are the part hardest to be removed.
INTRODUCTION The removing efficiency of most air cleaning equipments varies according to challenge particles size due to the combination effect of different particle collection mechanism (William C. Hinds, 1999). Furthermore particle number size distribution would significantly affect the particle piling procedure on filter fibers. Thus the test particle number size distribution is a key factor for both the particulate matter (PM) removing performance and life cycle energy consumption evaluation of air cleaning equipments. Nevertheless challenge particles as well as the loading dust recommended in the current international standardization system are not designed to reflect the size distribution character of the real atmospheric air, and thus insufficient to make scientific evaluation comparable with real life performance for air cleaning equipments. In previous researches, atmospheric particle size distribution were measured and analysed to determine the influence of climate (Wolfram Birmili etc., 2001), seasons (F.J.Gomez-Moreno etc., 2011;LI Ling-jun etc., 2008), traffic (Ismael Luis Schneider etc., 2015), times and altitude(Vladimir Zdimal etc., 2011) etc.. The focus of the previous researches was mainly about the ambient particles' "dynamic" procedure and mechanism, including generation and formation, transportation and revolution etc. Such researches would lead to useful information for air pollution control and people's exposure control. But not much efforts were made to figure out characters in common of the atmospheric particle number size distribution in different time, different seasons and different PM contamination levels. Such
characters would finally help us build "typical and representative" challenge particles which are much closer to the real atmospheric air, and would allow the possibility to evaluate the filtration performance and life cycle energy consumption based on a more scientific methodology. In this work, a long-term monitoring on indoor/outdoor atmospheric particle number size distribution from 10nm to 10μmunder different PM2.5 concentration levels was conducted. We hope the measurement results could offer useful information for the development of new typical test aerosol for the evaluation of air cleaning equipments.
METHODS Instruments A wide-range particle spectrometer (WPS) (Benjamin Y.H. Liu etc., 2010) was used in this research to collect particle size distribution information from nano-size to supermicron-size. This instrument comprises a differential mobility analyzer (DMA) and a condensation particle counter (CPC) for particle measurement from 0.01 to 0.5μm up to 96 channels based on particle mobility classification under electricity field, and a Laser Particle Spectrometer (LPS) for particle measurement from 0.35 to 10μm. For PM2.5 mass concentration test. Fig 1 illustrates the schematic flow diagram of WPS. For the total PM2.5 mass concentration test, a light scattering test instrument, TSI Dusttrack 8532, was used. Fig 2 shows how the two instruments are set and work together.
Fig 1 Schematic flow diagram of the WPS
ISBN: 978-0-646-98213-7 COBEE2018-Paper221 page 652
4th International Conference On Building Energy, Environment
Fig 2 WPS and Dusttrack
Sampling Protocol The samples for outdoor and indoor air were taken successively in an office building at Beijing. For each sampling procedure, outdoor air was firstly sampled and measured for both WPS and Dusttrack. 30 cycles of sampling was conducted by WPS for atmospheric particle number size distribution. PM2.5 mass concentration was measured by Dusttrack at the same time. After the outdoor air sampling was accomplished, the windows of the office would be closed, and remote HEPA inlet filters would be connected to both WPS and TSI Dusttrack for the cleaning of all sampling pipes and inner space of the instruments. The inner part cleaning of all the instruments normally takes 15 to 20 minutes depending on the contamination level of the outdoor air. After cleaning procedure, sampling of the indoor ambient particle number size distribution and PM2.5 mass concentration would be conducted by following the same protocol as outdoor air. The measurement results of each sampling days which were picked randomly from May 2015 to February 2017, and are grouped according to different PM2.5 contamination levels for further analysis.
RESULTS AND DISCUSSIONS Indoor/outdoor atmospheric aerosol size distribution sampling were conducted in 107 days randomly distributed in 21 months in order to get enough samples in all seasons and all PM2.5 contamination level from less than 50 μg/m³ to over 400μg/m³. Tab 1 summarizes number of days sampled in different seasons and Figure 3 illustrates the number of days sampled and grouped in different PM2.5 levels.
Tab 1 Number of days sampled in different seasons Season Winter Spring Summer Autumn
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SEP-NOV
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% 15.0% 15.0% 43.9% 26.1%
Fig 3 Number of days sampled in different PM2.5 level
All samples collected are grouped into 8 groups according to the PM2.5 mass concentration measured simultaneously. As can be seen in Figure 3, 8 PM2.5 level groups are 0-50μg/m³, 50-100μg/m³, 100-150μg/m³, 150-200μg/m³, 200-250μg/m³, 250-300μg/m³, 300-400μg/m³, and >400μg/m³ correspondently. Such grouping method would allow the measurement results sampled in different days easy to compare with others with similar total concentration of both number and mass. Outdoor atmospheric particle number size distribution Figure 4 (a to i) summarize the average atmospheric particle number size distribution under different PM2.5 levels. It is well accepted that the atmospheric particles are combined by 3 ranges or modes due to different formation and removing mechanism, which would be presented as the combination of lognormal distribution curve with 1 to 3 peaks in each range (Kenneth T. Whitby, 1978). As can been seen in Figure 4, the particle number size distribution could be presented asa dual-peaks lognormal function in most PM2.5 levels because the number concentration of particles in coarse mode is so low that the peak could normally be recognized in mass size distribution. A few recent researches illustrated that high concentration of nucleation mode particles (< 30nm) would be observed in some dry and sunny morning, hours after sunrise (Wolfram Birmili etc., 2001). In such cases, the atmospheric particle number size distribution would show as a one-peak mode curve especially in low PM 2.5 level. So for samples measured in days with PM2.5 mass concentration lower than 50μg/m³, size distribution curve with one peak and two peaks are separated into different sub-groups for average and analysis (Fig 4a and Fig 4b).
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Fig 4 Average atmospheric particle number size distribution with different PM2.5 mass concentration levels. Bars indicate a 10%
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It is well accepted that the detailed atmospheric particle number size distribution varies as the time, metrological conditions changes (Wolfram Birmil etc.i, 2001). While in this work, we are trying to find if there is some common characters (i.e. number and location of the peaks) which would allow the possibility of building "typical" challenge particles more close to reflect the real life performance of air cleaning equipments. Based on the samples collected, we could find that the number size distribution could be regarded as the combination of two lognormal distributions: one is in the Aitken nucleation mode, the other is in the accumulation mode although the PM2.5 mass concentration varies greatly from less than 50μg/m³ to over 400μg/m³. Furthermore, for all PM2.5 mass concentration groups, the peaks of both modes locate in similar particle sizes. Tab 2 summarizes the location of peaks in Aitken mode and accumulation mode, as well as the ratio of number concentration of the peaks of all PM2.5 groups. As can be concluded, the peak in Aitken mode normally occurs between 20 to 50nm, and for accumulation mode, the peak mainly locates between 100 to 140nm. Similar size distribution could be found in other measurement research conducted in other countries including Germany(Wolfram Birmili etc., 2001), Greece (I.Kopanakis etc., 2013), Brazil (Ismael Luis Schneider, 2015) and Spain (F.J.Gomez-Moreno etc., 2011).
The ratio of the number concentration of peaks in two modes could be found to be inversely proportion to the PM2.5 mass concentration. In lower PM2.5 level, small particles in Aitken mode counts obviously more than large particles in accumulation mode. The ration of Peak 1 to Peak 2 could be as high as 2:1. As PM2.5 concentration goes higher, the ratio goes lower correspondingly, and would be around 0.8:1 in high contamination conditions.
Tab 2 Summarization of the atmospheric particle size distribution in different PM2.5 levels
PM2.5 mass concentration
μg/m³
Peak1 nm
Peak2 nm
Number Concentration Ratio of Peak1 to Peak 2
0-50 25.57 - - 0-50 19.10 86.06 2.02
50-100 46.31 119.30 1.62 100-150 34.34 101.14 0.97 150-200 29.61 101.14 1.00 200-250 46.31 141.33 1.10 250-300 25.57 119.30 1.40 300-400 39.85 141.33 0.75
>400 34.34 119.30 0.84
(a) PM2.5:0-50μg/m³ (b) PM2.5:0-50μg/m³ (c) PM2.5:50-100μg/m³ (single peak) (dual-Peaks)
(d) PM2.5:100-150μg/m³ (e) PM2.5:150-200μg/m³ (f) PM2.5:200-250μg/m³
(g) PM2.5:250-300μg/m³ (h) PM2.5:300-400μg/m³ (i) PM2.5:>4000μg/m³
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Size-dependent particle Indoor/Outdoor relationship The size dependent indoor/outdoor relationship for atmospheric particles is always the research focus in finding out how the outdoor air pollution would impact indoor environment (N. Hodas etc., 2016). In this project, airborne particle size distribution was measured as well about 15-20 minutes after the outdoor samples were collected and after cleaning of all the sampling tubes and inner part of instruments. I/O ratio of all particle channels from 10 nm to 10000 nm were calculated and then grouped according to the outdoor PM2.5 concentration level.
Figure 5 (a to i) show the comparison of average indoor/outdoor atmospheric particle number size distribution in the group with the same outdoor PM2.5 mass concentration level. To figure out the size-dependent impact of outdoor ambient airborne particles on indoor air, indoor samples were measured when the doors and windows were closed, people movement was limited (which means only necessary movement like check the status of sampling instruments was allowed), and all internal contamination sources like smoking and photocopying etc. were forbidden.
(a) PM2.5:0-50μg/m³ (b) PM2.5:0-50μg/m³ (c) PM2.5:50-100μg/m³ (single peak) (dual-Peaks)
(d) PM2.5:100-150μg/m³ (e) PM2.5:150-200μg/m³ (f) PM2.5:200-250μg/m³
(g) PM2.5:250-300μg/m³ (h) PM2.5:300-400μg/m³ (i) PM2.5:>4000μg/m³
Fig 5 Comparison of indoor/outdoor airborne particle number size distribution based on different outdoor PM2.5 mass concentration.
When the impact of indoor particle contamination source is neglectable, indoor ambient airborne particle number size distribution would show quite similar characters with outdoor atmospheric environment. Numbers and Locations of peaks in the size distribution curve of indoor airborne particles occur just like the outdoor atmospheric counterpart. On the other hand the decay rate, i.e. the particle deposition rate would vary as the particle size changes. So the I/O ratio of all particles were calculated for further analysis. Figure 6 summarizes the I/O ratio of different particle size in different PM2.5 concentration levels. As can be seen, the relationships of I/O ratio and particle size of different PM2.5 groups are quite similar although the PM2.5 mass concentration varies greatly from less than 50μg/m³ to over 400μg/m³. Fig 7 illustrates the overall average and standard deviation of all samples.
Fig 6 I/O ration of different PM2.5 levels
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Fig 7 Overall average I/O ratio of all samples. Bars indicate
standardization deviation calculated by the average numbers of different PM2.5 levels.
As can be concluded, particle size itself rather than outdoor PM mass concentration is the predominant factor to determine how the outdoor atmosphere would impact the indoor built environment. Particles from ~100nm to ~300nm are the part which are easiest to penetrate the envelop of buildings and thus impact indoor air mostly. Penetration of particles in this range is about 0.9 while penetration of most particles is other parts is lower than 0.8 with the lowest part of ~0.3. This phenomenon could be explained by particle dynamics and particle removing mechanism. When particles is entering the building shell along with the infiltrating air, deposition loss would happen due to inertia effect such as gravitational sedimentation or impaction, and Brownian diffusion. Diffusion plays predominant role for determining the motion of small particles. The smaller the particle is, the greater the intensity of the diffusion motion would be. Thus a 10nm particle would be transported by diffusion 20,000 times faster than a 10μm particle (William C. Hinds, 1999).While for large particles, the inertia effect would become the predominant factor. The possibility of the particle loss due to sedimentation and impaction would be proportion to the particle size. Finally as the result of combination of both effects, particles between 100nm to 300nm became the hardest part to be removed (William J. Riley, 2002). In air cleaning industry similar phenomena happens in the procedure of particles collected by fibrous media (William C. Hinds, 1999). Such particles are therefore called particles with “Most Penetrate Particle Size, MPPS”. In the current standardization system for test method of indoor use portable air cleaners, cigarette smoke is normally used as the challenge particle source to determine the particle removing performance. Nevertheless smoke particles generated by cigarette combustion are sticky, easy to coagulate, and might be unstable in particle size distribution and total concentration(Bradley J. Ingebrethsen, 1986). On the other hand, impact of the outdoor atmosphere rather than indoor cigarette smokers should be regarded as the major indoor PM contamination source at present century. The relationship of I/O ratio and particle size illustrated in this work therefore would offer useful information for the development of a new challenge particle source for indoor use air cleaners.
CONCLUSIONS In this project, a 21 month monitoring on the outdoor and indoor atmospheric particle number size distribution from nanosize as low as 10 nm to supermicron range until10μm has been conducted. Measurement results have been
grouped and analysed based on the PM 2.5 mass concentration levels. According to the measurement results, we could find that the atmospheric number size distribution could be regarded as the combination of two lognormal distributions: one is in the Aitken nucleation mode, the other is in the accumulation mode although the PM2.5 mass concentration varies greatly from less than 50μg/m³ to over 400μg/m³. The peak in Aitken mode normally occurs between 20 to 50nm, and for accumulation mode, the peak mainly locates between 100 to 140nm. The ratio of number concentration of peaks would change inversely proportion to PM2.5 mass concentration. Such characters allow the possibility to develop particle generation system for further filtration performance and life cycle energy consumption evaluation of filters and other air cleaning equipments installed in mechanical ventilation system and dealing with outdoor air. Indoor airborne particle size distribution is strongly affected by outdoor air in case of no obvious indoor contamination sources existing. In most cases, indoor airborne particle number size distribution could be fitted as the combination of two lognormal distribution like outdoor atmospheric counterpart. Locations of peaks occur at similar particle size like outdoor air. While penetration of airborne particles entering building shell along with infiltration air varies as particle size changes rather different particle concentration. According to the measurement results of this work, particles with diameter from ~100nm to ~300nm are the part hardest to be removed or deposit.
ACKNOWLEDGEMENT This project is financially funded by National Key R&D Program of China, Research and Demonstration of Key Technology of Net-Zero Energy Building（Project Number：2016YFE0102300） .
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