Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments
Abstract
:1. Introduction
2. Materials and Methods
2.1. Designing the Sampler
2.1.1. Concept and Design Criteria
- Materials cost less than 10 USD per sampler.
- Sampler parts (except for exposure surfaces and identifying labels) are re-usable and recyclable.
- Samplers are fully passive during monitoring.
- Samplers can be left in place for weeks to months indoors.
- Samplers are easy to assemble and to deploy.
2.1.2. Iterative Design Phases
2.1.3. Design of the Sampler
Exposure Surface
Casing
Assembly and Deployment
Cost Estimate for Sampler
2.1.4. Approach for Estimating Sampler Change in Reflectance from Digital Images
Imaging Sampler Surfaces
Estimating Change in Sampler Reflectance
Cost Estimate for Approach
2.2. Testing of the Sampler
2.2.1. Laboratory Testing
2.2.2. Field Testing
3. Results
3.1. Laboratory Testing
3.2. Field Testing
4. Discussion
4.1. Performance, Cost-Effectiveness, and Ease-of-Use
4.1.1. Performance
4.1.2. Cost-Effectiveness
4.1.3. Ease-of-Use
4.2. Limitations, Further Testing Needs, and Potential Improvements
4.2.1. Limitations
4.2.2. Further Testing Needs
4.2.3. Potential Improvements
4.3. Potential Applications of Method
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A. Supporting Information for Design of Sampler and Approach
Component | Manufacturer and Product | Approximate Cost per Unit [USD] |
---|---|---|
Sampler hardware1 | ||
3-D printed | ||
Batch of 50 | Custom | 9.6 |
Injection molded | ||
Batch of 1000 | Custom | 3.2 |
Batch of 2000 | Custom | 2.5 |
Batch of 5000 | Custom | 2.0 |
Exposure surface | Whatman 1002110 | 0.03 |
Labels | Brother TZE211 | 0.06 |
Component | Manufacturer and Product | Approximate Cost per Unit [USD] |
---|---|---|
Digital camera | Basler puA2500-14um | 320 |
Lightbox | Custom | 120 |
Appendix B. Supporting Information for Laboratory Testing Methods
Appendix C. Supporting Information for Field Testing Methods
Appendix D. Supporting Information for Laboratory Testing Results
Sampler A | Sampler B | Sampler C | |
---|---|---|---|
Sampler A | - | 1.000 | 0.998 |
Sampler B | 0.992 | - | 0.998 |
Sampler C | 0.992 | 0.999 | - |
Sampler A | Sampler B | Sampler C | Mean | |
---|---|---|---|---|
Root mean square error (RMSE) [PI] | 120 | 56 | 83 | 86 |
Mean [PI] | −1100 | −930 | −960 | −990 |
RMSE/Mean [%, absolute value] | 11 | 6.0 | 8.6 | 8.6 |
Appendix E. Supporting Information for Field Testing Results
References
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Variability within Locations | Variability among Locations | |||
---|---|---|---|---|
Exposure Time (Sampling Date) | Mean absolute difference a in ΔPI between paired samplers at same location (range of absolute differences) [PI] | Mean CV b [%] | Absolute difference c in ΔPI among location averages (range of location averages) [PI] | CV b [%] |
33 days (1 February) | 63 (5.0 to 220) | 34 | 2800 (−2700 to +60) | 150 |
55 days (23 February) | 45 (1.0 to 120) | 8.2 | 3000 (−3000 to −46) | 110 |
90 days (30 March) | 58 (7.0 to 160) | 6.5 | 3100 (−3200 to −83) | 85 |
118 days (27 April) | 92 (14 to 310) | 8.2 | 2700 (−2900 to −150) | 81 |
173 days (21 June) | 96 (4.0 to 700) | 8.7 | 2700 (−2900 to −100) | 73 |
209 days (27 July) | 63 (1.0 to 510) | 8.3 | 2800 (−2900 to −32) | 80 |
258 days (14 September) | 61 (5.0 to 450) | 5.2 | 2900 (−2900 to −52) | 71 |
Correlation in ΔPI | Error in ΔPI | |||||
---|---|---|---|---|---|---|
Samplers | Number of pairs, n | MeanΔPI [PI] | Pearson’s coeff., r | Spearman’s rank coeff., s | RMSE a [PI] | RMSE a/mean [|%|] |
All samplers, all sampling dates | 140 | −850 | 0.99 | 0.99 | 110 | 8.8 |
Samplers by sampling date: | ||||||
1 February (range: −2700 to +60) | 20 | −440 | 0.99 | 0.99 | 41 | 9.3 |
23 February (range: −3000 to −46) | 20 | −720 | 0.99 | 0.99 | 30 | 4.2 |
30 March (range: −3200 to −83) | 20 | −930 | 0.99 | 0.99 | 37 | 4.0 |
27 April (range: −2900 to −150) | 20 | −890 | 0.98 | 0.98 | 140 | 1.6 |
21 June (range: −2900 to −100) | 20 | −970 | 0.97 | 0.97 | 90 | 9.3 |
27 July (range: −2900 to −32) | 20 | −930 | 0.99 | 0.98 | 62 | 6.7 |
14 September (range: −2900 to −52) | 20 | −1100 | 0.99 | 0.98 | 57 | 5.3 |
Samplers by quintile ΔPI: | ||||||
Q1 (range: +60 to −180) | 28 | −83 | 0.89 | 0.85 | 18 | 22 |
Q2 (range: −180 to −360) | 28 | −280 | 0.87 | 0.85 | 20 | 7.1 |
Q3 (range: −360 to −1100) | 28 | −670 | 0.96 | 0.92 | 33 | 4.7 |
Q4 (range: −1100 to −1400) | 28 | −1200 | 0.15 | 0.20 | 110 | 8.5 |
Q5 (range: −1400 to −3200) | 28 | −2000 | 0.98 | 0.98 | 220 | 11 |
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Clark, L.P.; Sreekanth, V.; Bekbulat, B.; Baum, M.; Yang, S.; Baylon, P.; Gould, T.R.; Larson, T.V.; Seto, E.Y.W.; Space, C.D.; et al. Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments. Sensors 2020, 20, 3417. https://doi.org/10.3390/s20123417
Clark LP, Sreekanth V, Bekbulat B, Baum M, Yang S, Baylon P, Gould TR, Larson TV, Seto EYW, Space CD, et al. Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments. Sensors. 2020; 20(12):3417. https://doi.org/10.3390/s20123417
Chicago/Turabian StyleClark, Lara P., V. Sreekanth, Bujin Bekbulat, Michael Baum, Songlin Yang, Pao Baylon, Timothy R. Gould, Timothy V. Larson, Edmund Y. W. Seto, Chris D. Space, and et al. 2020. "Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments" Sensors 20, no. 12: 3417. https://doi.org/10.3390/s20123417
APA StyleClark, L. P., Sreekanth, V., Bekbulat, B., Baum, M., Yang, S., Baylon, P., Gould, T. R., Larson, T. V., Seto, E. Y. W., Space, C. D., & Marshall, J. D. (2020). Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments. Sensors, 20(12), 3417. https://doi.org/10.3390/s20123417