Development of Inexpensive and Portable Devices for Chemical Measurements and Environmental Analysis
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Portable sensing devices are a rapid growth area with application in households, classrooms, and within analytical chemistry. This dissertation research describes some inexpensive and portable devices that have been developed for chemical measurements and environmental analysis. The devices include a portable electronic fluid dispenser that has been built for chemical measurements in classroom settings; a smartphone-based sun photometer that has been applied for remote sensing of aerosol optical depth; a portable ozone sensor, and a PM2.5 dust sensor capable of personal exposure monitoring. Chapter II describes a syringe-based, electronic fluid dispenser. The device mechanically connects a syringe plunger to a linear-slide potentiometer. As the syringe plunger moves, the electrical resistance between terminals of the potentiometer varies. Application and subsequent measurement of a DC voltage between the potentiometer pins is used to track the syringe plunger position and meter the volume dispensed. The syringe’s plunger is actuated manually by the device’s user. The dispensing device offers volumetric accuracy of better than 1% when the dispensed volumes were >10 mL. The device has been used for a traditional acid–base titration experiment and produced quantitative results indistinguishable from the conventional volumetric approach using a buret. The device is inexpensive, easy for students to understand, and simple to construct. Employing the device may lead to improvements in student engagement. Chapter III describes how a smartphone can be used as a sun photometer for the remote sensing of atmospheric optical depth. The top-of-the-atmosphere (TOA) irradiance was estimated through the construction of Langley plots on days when the sky was cloudless and clear. Changes in optical depth were monitored on a different day when clouds intermittently blocked the sun. The device demonstrated a measurement precision of 1.2% relative standard deviation for replicate photograph measurements (38 trials, 134 datum). However, when the accuracy of the method was assessed through using optical filters of known transmittance, a more substantial uncertainty was apparent in the data. Roughly 95% of replicate smart phone measured transmittances are expected to lie within ±11.6% of the true transmittance value. This uncertainty in transmission corresponds to an optical depth of approx. ±0.12–0.13 suggesting the smartphone sun photometer would be useful only in polluted areas that experience significant optical depths. The device can be used as a tool in the classroom to present how aerosols and gases effect atmospheric transmission. In Chapter IV, an inexpensive and portable device for monitoring personal ozone exposure is described and its performance characterized. The device is built from commercially available components, exhibits time resolution of approx. 60-90 s, and highest analytical sensitivity under 100 ppbv ozone. The sensor has been employed to provide insights into ozone exposure for 8 volunteers living in Lubbock, Texas during the winter months of 2015. Consistent with previous literature, the results indicate the volunteers were exposed to highest levels of ozone when outdoors during daylight hours. Exposure to ozone indoors was typically only a fraction (0.3-0.7) of the dose observed during times spent outdoors. The sensing system described requires minimal technical skills to assemble and use at a cost of approximately $150 USD per unit. The device's batteries provide power for 8-10 h on a single charge and the sensor can be re-used many times after recharging the battery pack. A major advantage of the sensor over chromogenic paper sensors for exposure monitoring is the collection of time-series data that allows users to better understand when and where individuals are exposed to highest ozone concentrations. The device may prove useful for industries requiring a low-cost solution to monitor employee exposure to ozone for specific work environments or for epidemiological research. Chapter V discusses a field portable device for logging PM2.5 mass concentration. The device combines the Arduino microprocessor with an SD card, a Sharp DN7C3CA006 optical dust monitor, and 10 000 mAh battery. The PM2.5 dust sensor uses a virtual impactor to size select particles prior to illuminating them with an LED. The LED is triggered by a circuit controlled with the Arduino. Nephelometric detection at 120º referenced to incidence is employed. The voltage signal reported by the dust sensor is converted to PM2.5 mass through calibration with a reference aerosol monitor instrument. Data points can be saved to the SD card as rapidly as 0.3 sec, although averaging signals over 60 seconds produced optimal detection limits. For a 60 second average, the PM2.5 mass limit of detection was 9 µg/m3 indicating the sensor will be useful for monitoring human exposure to fine particles. Portable exposure monitoring has been demonstrated with the sensing platform as several individuals carried the device with them during daily activities in Lubbock, TX and Atlanta, GA. For this group of test subjects, values of PM2.5 exposure varied from 0 – 1000 µg/m3 during the sampling periods. It was observed that, by far, the highest levels of PM2.5 occur during periods of cooking, or being near cooking operations. Other periods of high PM2.5 occurred during ground transportation, use of personal care products, vacuuming, and visiting restrooms. When hourly personal exposure data was correlated with hourly average PM2.5 for outdoor air for the Atlanta dataset, a very weak correlation was found (R2 = 0.026). For only 2 of 8 sampling periods did the personal monitoring estimate of exposure agree with that predicted by outdoor monitoring to within 15%. Personal exposure was often affected by circumstantial, short-term, high exposure events that are difficult to model or predict effectively. The short-term exposure events generally cause true P.M. exposure to be higher than that predicted by using outdoor ambient PM2.5 to generate estimates. This finding complicates interpretation of epidemiological studies that find links between ambient outdoor PM2.5 levels and human health, while it buttresses the case for employing personal ambient monitors.