1. An Inexpensive Method for Estimating Particle Pollution The relationship between black carbon in snow and PM2.5 mass concentration in air Michael Seltzer – Grade 11 Introduction Research Question Methods Conclusions It is a viable method, requiring little cost, that can be transported anywhere there is snow It could allow for more data to be acquired, allowing for the further study of the effects of black carbon and PM2.5 With improved and specially designed equipment, the process could be streamlined, allowing for more samples to be run in less time and with less work The data shows that the ratio of black carbon in snow to PM2.5 in air is consistent for the sites tested This instrument has a specific range limit and if measuring beyond that range (ie: multiple layers of carbon on the filter) the volume must be decreased (not changing the ratio)  Consequences:  This method could be used in a global network of people sending in samples, analyzing and creating a global crowd sourced database  Could be used in third world countries without the need for electricity, or extensive training  Future Research Improvements:  Further research is needed to test the same process with rain  Further research is needed to test the accuracy of this method with a larger, more diverse sample size Results and Discussion Bibliography How does the amount of black carbon collected through snow compare with PM2.5 mass concentration in air? Hypothesis Given that precipitation is the dominant method of air particulate cloud scavenging and PM2.5 air quality measures aerosols that are under 2.5 micrometers, there may be a relationship between the amount of aerosols present in snow and PM2.5 mass concentration. Research Papers: [1] Harder, S. L., S. G. Warren et al. Filtering of Air Through Snow as a Mechanism for Aerosol Deposition to the Antarctic Ice Sheet, J. Geophysics. Res. Vol. 101 no. D13 pp. 18, 718-29. 1996 [2] T. Novakov et al. Large Historical Changes of Fossil-Fuel Black Carbon Aerosols.Geophysics. Res. Vol. 30 no.6 pp. 1324. 2003 [3] J. E. Penner et al. Short Lived Uncertainty? Cambridge Univ. Press. 2001 Hansen J et al. Global Climate Change. PNAS. Vol. 103 no. 39 pp. 14288-14293.2006 [4] Surabi Menon, James Hansen et al. Climate Effects of Black Carbon Aerosols in China and India. Science.Vol. 297 no. 5590 pp. 2250-2253.2002. Current Event Sources: [5] Borenstein, Seth. "Scientists: Cut soot, methane." Boulder DailyCamera. http://www.dailycamera.com/ci_19733431 (accessed January 12, 2012). [6] Tierney, John. "Countering Climate Change Without Waiting for a Payoff." The New York Times. http://www.nytimes.com/2012/01/17/science/countering-climate-change-without-waiting-for-a-payoff.html?_r=1&emc=eta1 (accessed January 18, 2012). [7] LaFraniere, Sharon. "Internet Criticism Pushes China to Act on Pollution." The New York Times. http://www.nytimes.com/2012/01/28/world/asia/internet-criticism-pushes-china-to-act-on-air- pollution.html?pagewanted=1&_r=1&emc=eta1 (accessed January 28, 2012). Pollution Data/Information [8] Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.) “Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007”. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. TS 2.5. [9] Colorado Air Pollution Control Division. [10] “Particle Pollution and Your Health." AIRNow. http://www.airnow.gov/index.cfm?action=particle_health.page1#2 Particulate Matter in our Air Particles in our air can lead to various health complications [10]: Bronchitis (Acute and Chronic) Aggravated Asthma Respiratory Infections Reduced lung function China: A Case Study of Measuring PM2.5 In 2007, the World Health Organization estimated that 656,000 people in China die prematurely every year due to air pollution. [7] The Chinese government has said that air quality has improved each year, however outside agencies have said that since 1998, PM2.5 has increased by 3-4%.In May of 2011, activists in China raised $4000 in order to purchase an air quality monitor and share the data online. [4] A portable, inexpensive, simple method like the water based method tested in this study could empower anyone to measure what hazards are in the air they breathe. Collection Top layer scraped off to avoid collecting carbon that fell after snowfall Multiple 5qt. Paint Containers per site Filtration 25mm filter holder sized down to a 4.8mm hole with a steel ring Compared to a spot reference tool (shown below) of different light ratios Analysis Using the Beer-Lambert law the following equation was derived to relate the light ratio to black carbon mass concentration: where: Vol is volume of the melted snow Area is the area of the filter opening TrG is the light ratio M AE is the Mass Absorption Efficiency of black carbon Measuring air quality is important in order to understand the health and environmental hazards in the air around us. However there are issues that exist with the real time measurement methods (such as PM2.5) that are currently employed. They are: Expensive Not readily portable Require electricity Require training and calibration Collecting precipitation is a possible alternative. It has been largely untested, and to this day has mainly been used to measure carbon in ice cores. [1] This study will test the viability of filtering snow to measure black carbon mass concentrations, and its relationship with PM2.5 air quality measurements. Filtration System Filtration Steel Ring (inside of 25mm filter holder) Black Carbon in our Air Black carbon is only about ~1-10% of the particulates in the air quality PM2.5 mass concentration. But in addition to being an indicator of the relative amount of particle pollution at a location, black carbon has important effects including: Black carbon changes the surface albedo of snow which heats the surface of the earth, and causes snow and ice to melt faster [3] Black materials such as black carbon absorb heat from the sun and can play a role in climate change[5,6] Because of the hexagonal elemental structure, pollutants and other particulates that negatively affect health, stick to black carbon Through measuring black carbon mass concentrations in snow, this experiment will seek to create an inexpensive method of estimating the particle pollution in the air. To create a truly cost effective, simple measurement system, a predefined spot reference tool was used. The different levels of blackness were compared to the snow filters and used to determine the light ratio (Transmission) and calculate the mass concentration of black carbon. Finding : Black carbon has a correlation r 2 of.85 with PM2.5 Mass Concentration data Explanation : This result fits with the theory of air particulate cloud scavenging (also known as cloud condensation nuclei) which explains that aerosols (such as black carbon) serve as nuclei for condensation. In other words, precipitation forms around aerosols such as black carbon. Even though black carbon is a relatively small portion of what PM2.5 measures, the amount of black carbon per total number of particles remains nearly the same at the urban locations chosen in this experiment, as was observed in the data. As seen on the graph, two main points skew the relationship, however even if they are taken out of the sample size, the regression analysis shows a P value of.007, and thus the null hypothesis can be rejected.  Sources of Error: Black carbon falling after snowfall (attempted to mitigate by removing first layer of snow before collection) Inconsistent amounts of black carbon in different areas of snow (attempted to mitigate with multiple samples from area) Other materials present in snow (attempted to mitigate by measuring blackness with spot reference tool ) Loss to storage vessel walls (each sample was stirred before filtration to avoid particle settlement) Partial Filtration (glass funnel was used, and equipment cleaned before and after each filtration) Black Particles filtered on pads may not have been black carbon and may have been other particles 1 PM2.5 readings from colorado.gov air pollution control division [9] Example of a Filter Pad with a light ratio of.84 BOU LNGM CAMP DMAS Sites Best Fit Equationr²P Value y = 3140x + 2970.85.00014 Statistics 1 Photo Credit Wayne Seltzer 1 All Photos © Michael Seltzer, Except Where Noted