1 Suburban air quality monitoring. Measuring Air Pollution in the Mid-Atlantic United States Bebhinn Do Meteorologist, NC DAQ Some slide material provided.

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Presentation transcript:

1 Suburban air quality monitoring

Measuring Air Pollution in the Mid-Atlantic United States Bebhinn Do Meteorologist, NC DAQ Some slide material provided through K.G. Paterson, Ph.D., P.E. ©2007 via contract with MARAMA

3 Did You Know? There are more than 4000 air quality monitoring sites in the United States. Most are monitoring several air pollutants, every hour, every day.

4 Course Goals By the end of this session, you will Know some modern ways to measure key pollutants in emissions and ambient air Understand the trade-offs in monitoring site selection Be familiar with ways to monitor air quality remotely Be aware of a few data analysis methods

5 Discussion You’re a government leader who has just been given funding to place monitors in your state. Where do you place your monitors?

6 Monitoring Critical measurement decisions Location Infrastructure Access Interference Representativeness Supporting data Resolution Time and space Data needs Analysis skills Data storage Reporting Methodology Accuracy Sensitivity Reliability Utility

7 Monitoring State regulatory agencies routinely monitor the ambient concentration and emissions of several pollutants. Concentrations Carbon monoxide (CO) Nitrogen dioxide (NO 2 ) Ozone (O 3 ) Sulfur dioxide (SO 2 ) Particulate matter (PM 10, PM 2.5 ) Lead (Pb) Emissions Carbon monoxide (CO) Sulfur dioxide (SO 2 ) Particulate matter (PM 10, PM 2.5 ) Nitrogen oxides (NO x ) Volatile organic compounds (VOCs) Ammonia (NH 3 )

8 Monitoring Each pollutant requires a different measurement methodology (analysis + technology) Common features Automated and continuous operation Real-time measurement Data recording and/or transmission Methodologies and instrumentation are approved and recommended by the U.S. EPA

9 Monitoring: Equipment Thermo Electron Company’s (formerly Rupprecht & Patashnick) TEOM allows continuous real-time measurement of ambient PM

10 Monitoring: Equipment Environnement S.A. UV Absorption Ozone Analyzer Model O342M User programmable Remote maintenance and data acquisition Built-in storage of two month’s data 0.4 to 500 ppb

11 Monitoring Continuous emission monitoring (CEM) Required of most power plants under the Acid Rain Program (many other facilities via the New Source Performance Standards) Measured pollutants: SO 2, NO x, opacity Importance: Verifying emissions for trading programs Compliance

12 Monitoring Emission monitoring has unique challenges Sampling is in stack discharge airstream Environment can be extreme Sensors are specific to source facility Integrated to operations of facility source: Apex Instruments, Apexinst.com Mounted stack sampler Mobile stack sampler

13 Monitoring Remote sensing analyzes the air from a distant location Current techniques Lidar (Light detection and ranging) Remote target hit with pulsed lasers at two wavelengths Detects gases with good light absorption: SO 2, O 3, NH 3, H 2 S Satellite Can cover large areas, but interferences are challenging Limited to a pollutants with strong absorption signals: CO, O 3

14 Monitoring MOPITT (Measurements of Pollution in the Troposphere) sensor on NASA's Terra satellite is measuring CO around the planet (data is typically mid-troposphere)

15 Location Monitoring sites are usually not selected in isolation. Rather, the site is one of many within a monitoring network. Monitoring network strengths More robust assessment of air quality Impacts of new sources Air quality trends and patterns Site selection criteria Purpose of measurements Population density Pollutants being measured Proximity to other monitoring sites Emission inventory data Utility to modeling efforts Climatological data Topography Availability of land and power Security Obstruction-free sampling Cost Tough to find the “perfect” location. Compromises are always made.

16 Location Monitoring sites do not always have the same purpose, though. The monitoring site is established to understand the air quality at a particular area of interest. For example, Neighborhood, community, or regional levels Urban or rural levels Background levels or maximum impact A good question to ponder prior to using air quality data: is the site representative of the intended purpose?

17 18 Location

18 Location

19 Location Monitoring site locations for criteria air pollutants within the Mid-Atlantic Can you determine the logic behind the placement of these monitoring sites?

20 Data Analysis Statistical methods answer questions quantitatively. Examples of uses and typical questions: Summarize measurements (e.g. What is the average concentration today, 24-hr average?) Reveal patterns and trends (e.g. Is the air quality getting better or worse?) QA/QC (e.g. Is that high pollutant concentration an outlier or due to an unusual source?) Regulatory compliance (e.g. Does the air quality meet national standards?)

21 Data Analysis Quality assurance (QA) program goals Assessment of collected air quality data Improvement of data collection process Quality control (QC) Operational procedures, specs, and standards 1.Sampling method description 2.Instrument configuration 3.Calibration procedures 4.Zero checks 5.Corrective limits and actions 6.Preventative maintenance 7.Data recording 8.Documentation of QA activities

22 Data Analysis There are many data analysis methods among statistical methods. We will examine only a couple of these strategies: Identification of outliers Data smoothing

23 Data Analysis Identification of Outliers Outliers are extreme (high or low) values that diverge widely from the main body of a data set Outliers can have significant influence on other statistics, e.g. average, standard deviation Sources of outliers: faulty instrument transcription error technician/lab error misread instrument inconsistent sampling methodology blunders cover-up Or the outlier could reflect real, but extreme, conditions

24 Data Analysis Smoothing A way to eliminate the roughness (variability or noise) in the data that blurs the underlying pattern. We can smooth data using several techniques, let’s consider one Moving average is a way to smooth the data by determining an average based on the current and historical values (the most recent “X” data points).

25 Data Analysis Moving Average Estimate 3 year average of 4th highest daily 8-hr periods Compare to standard (0.08 ppm) To assess a long- term record, a table or graph of 3-year moving averages would be helpful Ozone from Lewes, Delaware Monitoring Site

Any Question? Thanks for making this a great class!

27 Post Test 1.In selecting a site to locate an air quality monitor, which of the following characteristics should be considered? a)Security b)Proximity to people c)Topography d)Water supply 2.Which pollutant is measured by a TEOM? a)Ozone b)Sulfur dioxide c)Nitrogen dioxide d)Fine particles 3.About how many ozone monitoring sites are there in Mid-Atlantic states? a)5 b)20 c)50 d)100

28 Further Learning & Additional Information AirData, access to air pollution data, List of Designated Reference and Equivalent Methods, Continuous Emissions Monitoring Fact Sheet, Code of Federal Regulations, continuous emission monitoring guidelines, 40 CFR Part 75, A Guide to Mid-Atlantic Regional Air Quality, Part V: Measurements, Data Analysis, and Modeling, pp MidAtlantic_RegAQ_Final.pdf