Measurement of Aerosols Optical Thickness of the Atmosphere using the GLOBE Handheld Sun Photometer
Summary
The goal of the methods presented here is to measure aerosol optical thickness of the atmosphere. The sun photometer is pointed at the sun and the largest voltage reading obtained on an in-built digital voltmeter is recorded. Atmospheric measurements such as barometric pressure and relative humidity are also performed.
Abstract
Here, we describe the measurement of aerosol optical thickness using the GLOBE handheld sun photometer. Aerosol optical thickness (AOT) was measured at Xavier University of Louisiana (XULA, 29.96° N, 90.11° W and 3 m above sea level). The measurements were done at two different wavelengths, 505 nm and 625 nm. AOT measurements were done 6 times a day (7 AM, 9 AM, 11 AM, solar noon, 3 PM and 5 PM). The data shown in this paper are the monthly average AOT values taken at solar noon. During each measurement time; at least five values of the sunlight voltage V and the dark voltage Vdark are taken for each channel. The mean for these five measurements is taken as the average for that measurement time. Other meteorological data such as temperature, surface pressure, rainfall and relative humidity are also measured at the same time. The whole protocol is completed within a time span of 10–15 min. The measured AOT values at 505 nm and 625 nm are then used to extrapolate the AOT values for wavelengths 667 nm, 551 nm, 532 nm and 490 nm. The measured and extrapolated AOT values were then compared with values from the nearest AERONET station at Wave CIS site 6 (AERONET, 28.87° N, 90.48° W and 33 m above sea level), which is about 96 km south of XULA. In this study we tracked the annual and daily variations of AOT for a 12 month period from September 2017 to August 2018. We also compared AOT data from two independently calibrated GLOBE handheld sun photometers at the XULA site. The data show that the two instruments are in excellent agreement.
Introduction
Atmospheric aerosols are minute solid and liquid particles (ranging from submicron to millimeter size) suspended in the air. Some aerosols are produced through human activity and others are produced by natural processes1,2,3,4. Aerosols in the atmosphere reduce the amount of solar energy reaching the earth’s surface by scattering or absorbing light and thermal radiation from the sun. The amount of aerosol in the atmosphere varies significantly with location and time. There are seasonal and annual changes as well as episodic changes due to events such as large dust storms, wild fires or volcanic eruptions5,6,7,8.
The impact of aerosols on the climate and on public health are among the dominant topics in current environmental research. Aerosols affect the weather by scattering or absorbing light and thermal radiation from the sun and by acting as condensation nuclei in the formation of clouds. Aerosols also play a role in the dispersal of pathogens in the air and they can cause or enhance respiratory and cardiovascular diseases. Aerosol optical thickness (AOT) is a measure of the amount of sunlight that is absorbed or scattered by these aerosols. There are several ground-based methods for monitoring AOT9,10,11. The biggest of the ground-based AOT monitoring system is the Aerosol Robotic Network (AERONET) project. AERONET is a network of over 400 monitoring stations spread all over the world12,13. Despite this large number of monitoring stations, there are still large gaps world-wide that are not monitored for AOT. As an example, the nearest AERONET station from our study site is about 90 km away. This paper describes the use of a portable handheld sun photometer that can be used to bridge the gaps between AERONET monitoring stations. The portable handheld sun photometer is an ideal instrument for use by students around the world in a global aerosol monitoring network14,15. The Global Learning and Observations to Benefit the Environment (GLOBE) program provides a platform for such a network, through thousands of schools in all the 50 states of the United States and in nearly 120 other countries16,17. The primary idea of the GLOBE program is to use students all over the world to provide scientifically valuable measurements of environmental parameters using inexpensive equipment. With proper guidance, students and other non-specialist can form networks of handheld sun photometers to fill the gaps between the AERONET monitoring stations. The biggest advantage of the handheld sun photometer is that it can be taken to even the remotest parts of the world. AOT measurements with other small and transportable instruments have been successfully used in the past to carry out research studies in remote and hard to access areas17,18
The main goal of this study is to use the GLOBE handheld sun photometers to track the annual, daily and hourly variation of AOT at our XULA study site and compare with measurements from a nearby AERONET station. This paper presents data for a 12 months period from September 2017 to August 2018. This is the first ever AOT recorded for the XULA site. The GLOBE sun photometer measures AOT at two wavelengths, 505 nm and 625 nm. The AERONET site at Wave CIS Site 6 measures AOT at 15 different wavelengths. For our comparison we focused on these 4 wavelengths, 667 nm, 551 nm, 532 nm and 490 nm. We chose these because they are the 4 AERONET wavelengths nearest to the GLOBE sun photometer wavelengths. To make the comparison, we extrapolated AOT values at these wavelengths for XULA site.
Measurements of AOT are done every day when the weather conditions permit. Measurements that are done when there are cirrus clouds within the vicinity of the sun are excluded in the analysis. Table 1 shows the number of days in each month that we had completely clear skies. Altogether, about 47% of the data taken was excluded.
| Month | Sept | Oct | Nov | Dec | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug |
| Number of Days | 18 | 20 | 16 | 15 | 15 | 15 | 16 | 15 | 18 | 15 | 15 | 16 |
Table 1: AOT measurements were done 6 times a day (7:00 AM, 9 AM, 11 AM, solar noon, 3 AM, and 5 AM). The data shown on the plots are the monthly average AOT values taken at solar noon. During each measurement time; at least five values of the sunlight voltage V and the dark voltage Vdark are taken for each channel. The mean for these five measurements is taken as the average for that measurement time. The error in these measurements is calculated as the standard deviations of these five measurements. AOT values are obtained using the equation shown below16:
V0 is the calibration constant of the sun photometer, R is the earth-sun distance in astronomical units, Vdark is the dark voltage recorded when light is blocked from passing through the hole on the top bracket of the sun photometer, V is the sunlight voltage recorded from the sun photometer when light passes through the hole on the top bracket, aR represents the attenuation of light due to Rayleigh scattering, P and P0 are the measured and standard atmospheric pressure, respectively, and m is the relative air mass. The relative air mass is calculated from data provided by the National Oceanic and Atmospheric Administration (NOAA). Other meteorological data such as temperature, rainfall and relative humidity are also measured at the same time. Equation 1 as given above includes the contributions of optical thickness from ozone. The effect of ozone on AOT values is calculated based on tabulated values of the ozone absorption coefficient and assumptions about the ozone amount in the atmosphere19. Bucholtz20,21 has produced tabulated values of aR based on standard atmospheres. For the 505 nm channel aR ≈ 0.13813 and for the 625 nm channel it is ~0.05793.
The data presented here represents an example of how teams of students can be organized to take long and sustained AOT measurements. In this study, two student teams used two independently calibrated GLOBE handheld sun photometers to track the annual, daily and hourly variation of the aerosol optical thickness of the atmosphere at our XULA study site. The two Globe sun photometers used in this investigation were purchased from the IESRE (Institute for Earth Science Research and Education; one had serial number RG8-989 and the other had serial number RG8-990). Before the data from the two instruments could be combined, a regression analysis was carried out to ascertain the agreement
Protocol
1. Photometer Operation
NOTE: These protocols are best done by two people working together. One person holds and aligns the sun photometer while the second person record the measurements.
- Measure the longitude and latitude for the site using GPS. At the site, the first step is to activate the GPS by choosing sensor set-up from the sensor menu and select GPS. Once GPS has acquired enough satellites, latitude and longitude values will be displayed. Once values are displayed press collect data and then press save.
- Make sure the sun photometer is working well. A properly calibrated sun photometer should produce a stable voltage of ~0.03 V indoors and up to 5 V when light is directed on the detector. The voltmeter on the Globe sun photometer is in-built on the sun photometer
- Record the air temperature. If using an alcohol in glass thermometer, give the thermometer 3–5 min to adjust to the outside temperature before recording the stable reading. If using the sun photometer’s in-built thermometer, turn the rotary switch to T and record the voltage reading on the voltmeter. The voltage reading multiplied by the 100 will give the air temperature in degrees Celsius at that time.
- Set the rotary switch to the green channel of the sun photometer.
- Have one person align the sun photometer so that light passing through the hole on the top bracket produces a sunlight spot centered over the colored dot on the bottom bracket. For best results, use a table and a chair. The person aligning the sun photometer should sit on the chair and rest his/her arms on the table in order to obtain a steady reading.
- Have the second person record the reading on the voltmeter. Make sure the sun spot is stable on the dot before taking a reading. If voltage reading is fluctuating, just record the maximum value shown.
- Record the time at which the reading was taken. Time must be recorded to the nearest 30 s. A digital watch serves this purpose better than an analogue one.
- Obtain the dark voltage. Have the person sitting down keep the sun photometer aligned to the sun with one hand and then cover the hole on the top bracket with a finger from the other hand. The second person will record the voltage reading.
- Set the rotary switch to the red channel and repeat steps 1.4–1.7.
- Repeat steps 1.4–1.8 four more times to obtain five voltages readings for the green channel and five voltage readings for the red channel
- Measure the air temperature again as in step 1.2.
2. Collection of Metadata
- Use the Globe cloud chart to observe and record the clouds near the sun. This is done by looking into the sky and checking off observed features from the GLOBE cloud chart (https://www.globe.gov/documents/348614/24331082/GLOBE+Cloud+Chart.). Visible cirrus clouds are easy to observe because of their characteristic thin wispy strands. Invisible cirrus clouds are inferred if the sunlight voltage reading on an apparently clear day is less than 0.5 V.
- Use a hygrometer to measure and record the relative humidity: Hold the hygrometer with an extended arm away from the body, leave it in the air for about 3 minutes, and then take the dry bulb reading first followed by the wet bulb reading. Find the difference in the two readings and use the relative humidity chart to establish the relative humidity
- Use a barometer to measure and record atmospheric pressure.
- Calculate AOT by plugging the measured values and the constants into Equation 1 given above.
3. Temperature Regulation
NOTE: The electronics of the sun photometer are sensitive to temperature. For optimal performance, the following steps are recommended.
- If outside temperature is more than 5 degrees below room temperature, keep the sun photometer wrapped in thermal foam when not in use.
- When taking measurements during the hot summer months, keep the sun photometer in the shade when not in use.
Representative Results
The GLOBE sun photometer measures AOT at λ= 505 nm and λ= 625 nm. The AERONET site at Wave CIS Site 6 measures AOT at 15 different wavelengths. For our comparison we focused on these 4 wavelengths of the AERONET site: 667 nm, 551 nm, 532 nm and 490 nm. To make a comparison between the two stations, we extrapolated AOT at 667 nm, 551 nm, 532 nm and 490 nm for the XULA site. This is done using the XULA site’s Angstrom coefficients. For any given site and instrument, the optical thickness τ, the wavelength λ, and the atmospheric turbidity coefficient β are connected through Angstrom’s turbidity formula
(2)
Where α is the Angstrom’s exponent. α and β are independent of the wavelength at which the optical thickness is measured. They are parameters that describe the atmosphere being measured. Given AOT at two different wavelengths (λ1 = 505 nm and λ2 = 625 nm, for our sun photometer), and the measured AOT (τ1 and τ2), the Angstrom exponent α for the XULA site is calculated from the equation,
(3)
The AOT (τ3) at a third wavelength, λ3 can be extrapolated for the same XULA atmospheric conditions using the equation:
(4)
τ1 and λ1 can be replaced with τ2 and λ2 in equation 4 to get the same value for τ3. This calculation is used to compare τ values obtained by two instruments that uses different wavelengths. Ideally the two instruments must be used at the same locality. In our case it must be noted that the two instruments were ~96 km apart.
Figure 1: A sample of the daily average AOT values for the red and green channels measured at XULA, calculated using equation 1. The figure shows data for the month of October only. Please click here to view a larger version of this figure.
Figure 1 shows a sample of the typical daily average AOT values calculated using equation 1. This figure shows the AOT data for both the green and the red channels of the GLOBE sun photometer for the month of October.
Figure 2: Seasonal variation of AOT. (a) Variation of the monthly average AOT values measured at XULA over the 12-month period. AOT values were measured at wavelengths 625 nm and 505 nm. Ozone correction was applied to this data. The error bars show the standard deviation of the five measurements taken for each measurement time. The arrows show the AOT peaks in February and in May. (b) Seasonal variation of AOT at the XULA site. Seasons were categorized thusly: winter (Dec, Jan, and Feb), spring (March, Apr, May), summer (Jun, July, Aug) and fall (Sept, Oct, Nov). Please click here to view a larger version of this figure.
Figure 2a shows variation of the average monthly AOT measured at XULA over the 12 months period. Average ozone optical thickness corrections of -0.01 and -0.03 were applied to the 505 nm and 625 nm optical thickness values, respectively. The data shows that the AOT measured at wavelength 505 nm (green light) dropped continuously from September to January and then peaked up in February. The AOT measured at wavelength 625 nm (red light) followed a similar trend but reached a minimum in December and started going up for January and February. AOT measured at 505 nm is on average higher than AOT measured at 625 nm. Figure 2b shows the average AOT values per season. The seasons were categorized as follows: winter (December, January and February), spring (March, April and May), summer (June, July and August), and fall (September, October and November). Summer had the highest average AOT and winter had the lowest average AOT. High values of AOT during the summer months may be due to the warming of the earth’s surface due to the high air temperatures. The warm earth increases the rate of evaporation. The drops and ice crystals that form when this water vapor freezes or condenses increases aerosols in the atmosphere. Low values of AOT in the winter months may be due to cloud scavenging and rain wash out processes as the winter months are also associated with high rainfall.
Figure 3: Comparison between XULA and AERONET. (a) Extrapolated AOT at XULA. These AOT values were extrapolated for 4 wavelengths (667 nm, 551 nm, 532 nm and 490 nm) using equation 3. (b) AERONET AOT at the same wavelengths. The AERONET data used here is classified as level 2.0. Cloud screening and ozone correction algorithms and were automatically applied to the data. The error bars in panel b are based on the minimum uncertainty of 0.02 AOT units for the level 2.0 AERONET data25. The arrows show the AOT peaks in February and in May for both (a) and (b). Please click here to view a larger version of this figure.
To make a comparison between the XULA site and the AERONET site, we extrapolated AOT values at wavelengths 667 nm, 551 nm, 532 nm and 490 nm for the XULA site. This was done using equation 3 above. Figure 3a shows the extrapolated AOT at XULA for the wavelengths 667 nm, 551 nm, 532 nm and 490 nm. Figure 3b shows the measured AERONET AOT at the same wavelengths. These data show good qualitative agreement but, considering the distance between the two sites, there is no justification for more quantitative comparisons. Even though we observed peaks in February and May, the average AOT for the winter and spring months were the lowest. This suggests that these peaks are due to some random events. These events could be anything from smoke from forest fires and agricultural activities in neighboring states to aerosols coming from across the Gulf of Mexico. It requires measurements for many seasons to be definitive about the cause of the AOT peaks in May and February.
Figure 4: Linear regressions curves for AOT values from two different handheld sun photometers at the XULA site. Serial numbers RG-989 and RG-9990. (a) 625 nm and (b) 505 nm. Please click here to view a larger version of this figure.
We checked the reliability of the GLOBE sun photometers by comparing two independently calibrated instruments against each other. Figure 4 shows AOT data from the GLOBE sun photometer with serial number RG8-989 and another with serial number RG8-990. The figure shows that the agreement between the two sun photometers is stronger for the 505 nm channel than the 625 nm channel. The R-squared value for the 505 nm (green) channel was 95.3% and the slope of the linear regression line between the two sun photometers was 0.89. For the 625 nm (red) channel, R-squared was 91.6% and the slope linear regression line was 0.82. The agreement on the red channel is lower because of the effects of heating on the red LED. The red LED is more sensitive to temperature than the green LED. Agreement for both channels is improved when data collectors control the exposure of the instrument to direct sunlight between measurements.
Figure 5: Diurnal variability of hourly mean values of AOT computed over the 12 month period. The time shown on the graph is local time. Please click here to view a larger version of this figure.
Figure 5 shows the hourly variation of AOT averaged over the 12-month period. Each data point was an average of 194 measurements. The daily variation was between 0.265 in the morning and 0.06 in the evening for the 505 nm channel, which corresponds to about 77% variation. The data shows a peak at 9:00 AM of 0.265 and another peak at 3:00 PM of 0.182 for the 505 nm channel. The 625 nm channel showed similar peaks. Even though these times coincided with the traffic peak hours in New Orleans, more investigations are needed to establish if the peaks are solely due to vehicle emissions.
Discussion
The first step in this protocol is to define the study site. This is done by using a GPS to find the longitude and latitude of the study site. The longitude and latitude values are critical in the calculation of AOT using equation 1. During measurement, it is crucial that the sun photometer is pointed directly and firmly at the sun. The tiny hole at the top bracket of the handheld sun photometer reduces the amount of scattered light reaching the LED detectors in the sun photometer. Equation 1 is an approximation that assumes that no scattered light passes through the hole at the top bracket. If the sun photometer is aligned properly, the error introduced by this assumption is negligible compared to other sources of error in the measurement22,23,24. The LEDs in the sun photometer are sensitive to extreme temperatures. During the hot summer months, the sun photometer must be kept in the shade when not in use. During the cold winter months, the sun photometer must be wrapped in protective thermal cloth between measurements. In extremely cold environments, thermal protection must be used throughout the measurements. When operating normally, the sun photometer should read a few millivolts in the dark and between 1.0 V and 3.0 V when directly pointed at the sun. Measurements with the sun photometer are reliable when the sun is clear of any clouds. Wearing sunglasses with an auburn tint will help to detect faint clouds which are otherwise invisible to the necked eye25,26.
The AOT calculated from equation 1 must be corrected for ozone contribution to AOT. This is done by subtracting ~0.01 and ~0.03 from the AOT values calculated for the green and red channels respectively22. When these protocols are carefully followed, the accuracy should be ~0.02 AOT units. This level of accuracy allows us to ignore any contributions to AOT due to water vapor absorption. The protocols given above are simple and can be followed by students from middle school to college level. The handheld sun photometer uses LEDs which are inexpensive and are easily obtained from electronic shops. The instrument itself is robust and does not need special care.
At present there are over 400 AERONET monitoring stations around the world, but even these are not enough to cover the whole planet. Handheld sun photometers, using the protocols described here can be used to bridge the gaps left out by AERONET. The thousands of schools around the globe can be organized to form a network of ground-based monitoring stations that are much closer to each other than the AERONET stations27,28. The handheld sun photometer with the given protocols can also be used to validate current and future space-based aerosol monitoring platforms.
One of the limitations of the protocols given here is that the alignment with the sun is done manually, which is susceptible to human errors. There are also limitations brought about by the design of the LED based handheld sun photometer. The bandwidth (FWHM) for the LED detectors is ~75 nm which could cause errors in the measurement. The other challenge with the given protocols is to organize student teams so that data is collected continuously and on a regular basis. Students can be motivated to collect data by giving them some credit towards their final grade.
Offenlegungen
The authors have nothing to disclose.
Acknowledgements
This work was supported financially by the DOD ARO grant #W911NF-15-1-0510 and National Science Foundation Research Initiation Awards under Grant No. 1411209. We express our sincere gratitude to Physics and Computer Science Department and the Division of Education at Xavier University of Louisiana.
Materials
| A Calibrated GLOBE handheld sun photometer | IESRE, USA (GLOBE sun photometer) and TERNUM, UK (Calitoo sun photometer | The GLOBE sun photometer measures AOT at 505nm and 625nm. | |
| Barometer | Forestry suppliers, USA, Cat# 43316 | 43316 | The aneroid barometer must have a clear scale with a pressure range between 940 and 1060 millibars. |
| GLOBE cloud chart | Forestry Suppliers, USA Cat#33485 | 33485 | A free cloud identification chart is obtained from www.globe.gov. |
| Hygrometer | Forestry suppliers, USA, Cat# 76254 | 76245 | Any digital hygrometer which measures relative humidity in the range of 20-95% with an accuracy of 5% is acceptable. |
| Labquest2 GPS | Vernier, USA, Cat LABQ2 | LABQ2 | Vernier LabQuest 2 is a standalone interface used to collect sensor data with its built-in graphing and analysis application. GPS is one of its built-in sensors |
| Taylor Orchid Thermometer | Forestry Suppliers, USA Cat# 89129 | 89129 | |
| Watch | Forestry suppliers, USA, Cat# 39137 | 39137 | The watch must be digital and capable of measuring time up to seconds. |
Referenzen
- Mondol, P. K., Mamun, M. M. I., Islam, M. M. Construction of an inexpensive sun photometer to measure aerosol optical depth and comparisons between the measured data and satellite observations. American Journal of Remote Sensing. 2 (5), 37-43 (2014).
- Toledano, C., et al. Overview of sun photometer measurements of aerosol properties in Scandinavia and Svalbard. Atmospheric Environment. 52, 182-188 (2012).
- . Aerosol Protocol – GLOBE.gov Available from: https://www.globe.gov/documents/348614/e9acbb7a-5e1f-444a-bdd3-acff62b50759 (2019)
- Heintzenber, J., Boutron, F., et al. The life cycle of the atmospheric aerosol. Topics in atmospheric and terrestrial physics and chemistry. , (1994).
- Gong, W., Zhang, S., Ma, Y. Aerosol Optical Properties and Determination of Aerosol Size Distribution in Wuhan, China. Atmosphere. 5, 81-91 (2014).
- Cisek, M., et al. Aerosol Optical Depth variations due to local breeze circulation in Kongsfjorden, Spitsbergen. Oceanologia. 59, 422-430 (2017).
- Charlson, R. J., et al. Climate forcing by anthropogenic aerosols. Science. 255, 423-430 (1992).
- Kohil, E. E., et al. A study of atmospheric aerosol optical properties over Alexandria city. Egypt Journal of Physics Conference. 810, 012033 (2017).
- Altaratz, O., Bar-Or, R. Z., Wollner, U., Koren, I. Relative humidity and its effect on aerosol optical depth in the vicinity of convective clouds. Environmental Research Letters. 8, 034025 (2013).
- Jung, C. H., Shin, H. J., Lee, J. Y., Kim, Y. P. Sensitivity and Contribution of Organic Aerosols to Aerosol Optical Properties Based on Their Refractive Index and Hygroscopicity. Atmosphere. 7 (65), (2016).
- Sharma, N. P., Sapkota, B. K., Bhattarai, B., Kjeldstad, B. Study on Aerosol Optical Depth in winter and Summer Season in Bhaktapur. Journal of the Institute of Engineering. 8 (1), 269-276 (2009).
- Mims, F. M. An international haze-monitoring network for students. Bulletin of the American. Meteorological Society. 80, 1421-1431 (1999).
- Mielonen, T., et al. Temperature-dependence of aerosol optical depth over the southeastern US. Atmospheric Chemistry and Physics Discussion. , (2016).
- Coakley, J. A., Cess, R. D., Yurevich, F. B. The effect of tropospheric aerosols on the earth’s radiation budget: A parameterization for climate models. Journal of Atmospheric Science. 40, 116-138 (1983).
- Stachlewska, I. S., Zawadzka, O., Engelmann, R. Effect of Heat Wave Conditions on Aerosol Optical Properties Derived from Satellite and Ground-Based Remote Sensing over Poland. Remote Sensing. 9, 1199 (2017).
- Brooks, D. R. Development of an inexpensive handheld LED-based Sun photometer for the GLOBE program. Journal of Geophysical Research. 106 (5), 4733-4740 (2001).
- Sellitto, P., et al. A novel methodology to determine volcanic aerosols optical properties in the UV and NIR and Ångström parameters using Sun photometry. Journal of Geophysical Research Atmospheres. 122 (8), (2017).
- Schmid, B., Wehrli, C. Comparison of Sun photometer calibration by use of the Langley technique and the standard lamp. Applied Optics. 34, 45014512 (1995).
- Shiobara, M., Spinhirne, J. D., Uchiyama, A., Asano, S. Optical depth measurements of aerosol, cloud and water vapor using sun photometers during theFIRE Cirrus II. Journal of Applied Meteorology. 35, 364-366 (1991).
- Aïssani, O., Mokhnache, A. Aerosol size distribution retrieved from optical depth measurements in Tamanrasset and Blida. Revue des Energies Renouvelables. 15 (2), 207-218 (2012).
- Bucholtz, A. Rayleigh-scattering calculations for the terrestrial atmosphere. Applied Optics. 34, 2765-2773 (1995).
- Brooks, D. R. Monitoring Solar Radiation and Its Transmission through the Atmosphere. The GLOBE Program’s Aerosols, Water Vapor, and UVA Monitoring Projects. , (2006).
- Holben, B. N., et al. AERONET – A federated instrument network and data archive for aerosol characterization. Remote Sensing of the Environment. 66, 1-16 (1998).
- Toledo, F., et al. AOT retrieval procedure for distributed measurements with low-cost Sun photometers. Journal of Geophysical Research Atmospheres. 123, 1113-1131 (2017).
- Giles, D. M., et al. Advancements in the Aerosol Robotic Network (AERONET) 1 Version 3 Database – Automated Near Real-Time Quality Control Algorithm with Improved Cloud Screening for Sun Photometer Aerosol Optical Depth (AOD) Measurements. Atmospheric Measurement Techniques Discussions. , (2018).
- Zawadzka, I., et al. Studies of aerosol optical depth with the use of Microtops II sun photometers and MODIS detectors in coastal areas of the Baltic Sea. Acta Geophysica. 62 (2), 400-422 (2014).
- Bovchaliuk, V., et al. Aerosol Microtops II sunphotometer observations over Ukraine. Advances in Astronomy and Space Physics. 3, 46-52 (2013).
- More, S., Kumar, P. P., Gupta, P., Devara, P. C. S., Aher, G. R. Comparison of Aerosol Products Retrieved from AERONET, MICROTOPS and MODIS over a Tropical Urban City, Pune, India. Aerosol and Air Quality Research. 13, 107-121 (2013).
- Boersma, K. F., de Vroom, J. P. Validation of MODIS aerosol observations over the Netherlands with GLOBE student measurements. Journal of Geophysical Research. 111, D20311 (2006).
- Porter, J. N., et al. Handheld Sun Photometer Measurements from Light Aircraft. Journal of Atmospheric and Oceanic Technology. 24, 1588-1597 (2007).
