Story 1


From late October 2013 to early June 2015, the Citizen Sense research project collaborated with residents of northeastern Pennsylvania to develop a citizen-led air-quality monitoring project. Residents in this area were particularly concerned about the inadequate environmental regulation and monitoring in relation to expanding hydraulic fracturing activities, and had already begun to undertake community activities for monitoring environmental pollutants.

Citizen Sense worked with local residents to develop a monitoring kit that included Speck PM2.5 sensors, BTEX badges (for monitoring benzene toluene, ethylbenzene and xylene, volatile organic compounds commonly associated with petroleum-related activities), a community platform for mapping monitoring locations and viewing real-time and historic data, and a Frackbox, which monitored nitrogen oxides, ozone, volatile organic compounds, temperature, humidity and wind direction. Residents were also provided with a logbook of instructions, which suggested several options for recording observations of environmental conditions and health effects.

The Citizen Sense kit and sensors were distributed in October 2014 during a monitoring workshop and walk. In total, 30 monitors and kits were distributed to residents, and 3 Frackboxes were placed near infrastructure. The monitoring period ran for over 7 months, until June 2015. During peak monitoring activity, there were 23 active monitoring sites, and there was consistent monitoring taking place at up to 16 sites over a period of 7 months.

Sensing practices video, Catherine Pancake

The data stories are generated using the Citizen Sense Airsift Data Analysis Toolkits, which were developed to allow for citizen-led interpretation of datasets. The core data available for interpretation is the PM2.5 sensor data using the Airsift PM2.5 Data Analysis toolkit. The Frackbox data and Airsift Frackbox Data Toolkit are also available as part of the resources section of our website. The Airsift toolkits use and adapt the open source software, openair, developed by atmospheric scientists for the analysis of air pollution data. In order to blur the exact monitoring locations, the monitoring locations have been labeled with township locations, which can be found in relation to Pennsylvania counties.

The 5 data stories presented on this site demonstrate the different patterns that have emerged from the data. Our hope is that the stories and the Airsift toolkits will provide a method and guide for others to undertake their own analysis of this citizen-gathered dataset, and to contribute to the wider development of citizen-led environmental monitoring and data analysis tools and practices.

I. The Location

Bridgewater N 56 is located in Susquehanna County, approximately 1 mile east of the small town of Montrose, Pennsylvania. The PM2.5 monitor was located on the porch of a residential property, set back approximately 30 feet (15 meters) from the tarmac road.

The Citizen Sense kit and monitors were distributed in October 2014 during a monitoring workshop and walk. In total, 30 monitors and kits were distributed to residents, and 3 Frackboxes were placed near infrastructure.

Local sources of particulate pollution
The Bridgewater N 56 monitoring site is situated in a low-traffic area, with the major highway, Interstate 81, located approximately 35 miles to the east. One small family dairy farm is located south of Bridgewater N 56. There is no industrial-scale farming in the immediate area.

As can be seen in Figure 1, which includes geo-location data on hydraulic fracturing infrastructure documented by resident and participant Meryl Solar, there are a number of fracking sites surrounding the Bridgewater N 56 monitoring site. (Note that this map is historic data to reflect conditions at the time of monitoring. The landscape is continually changing, and to see a more up-to-date map of current conditions see During the monitoring period, fracking was taking place at a nearby well pad located 500 feet northeast of the monitor during December 2014 to March 2015. There are also 5 well pads in operation to the northeast, south, southwest and west within a 2-mile radius as can be seen on the map. A compressor station is located 2 miles south of the site. Additionally there are compressors located 7 miles southwest, 6 miles west to southwest and 5 miles southeast of the PM2.5 monitor.

There are over 30 compressor stations within a 20-mile radius of the monitoring location. The Procter & Gamble factory is approximately 22 miles to the southwest of the monitoring site.

Regional sources of particulate pollution
Eighteen miles to the north of the monitoring location is the city of Binghamton, New York, and 32 miles to the southeast is the city of Scranton, Pennsylvania. The cities of Pittsburgh, Pennsylvania, and Harrisburg, Pennsylvania, are located over 200 miles to the southwest of the site.

II. Is there evidence of a problem?

The Speck device used to monitor PM2.5 particles is an “indicative” monitor. This means that measurements can give an indication of pollutant concentrations, but cannot be directly compared with national and international guidelines and standards in an “official” or regulatory sense. Despite this, indicative monitors are a well-established method within atmospheric science for carrying out initial surveys of an area to establish whether a potential problem merits further investigation. Indicative monitors are also increasingly becoming available for citizen-based air-quality monitoring, similar to this study.

Indicative daily mean concentrations of PM2.5 are shown as a time-series chart in Figure 2. The World Health Organisation (WHO) guideline of 25 µg m-3 for 24-hour daily mean concentration of PM2.5 is breached on a number of occasions, suggesting that further investigation may be merited. However, it is important to determine whether these breaches were caused by “local” sources of pollution close to the sensor (i.e., within 1000 feet (300 meters)), by sources within a few miles (or kilometers), or by regional sources affecting the whole area. Regional sources of PM2.5 typically include large urban areas, major industrial or agricultural processes, or main transport routes.

Figure 2: Time series chart of daily mean PM2.5 concentrations from November 2014 to June 2015 at Bridgewater N 56 (units: µg m-3)

Figure 3 shows an extract of the monitoring at the Bridgewater N 56 monitoring site presented as 1-minute mean concentrations of PM2.5 over the course of approximately 3 weeks from late April to mid-May. Measurements from the Liberty E 111 site are shown for comparison. Regional sources of pollution are identifiable as broad “humps” of elevated pollution affecting both sites, for example, the period between May 11 to 13, 2015. Local sources of pollution appear as short “spikes” typically affecting only one or the other site, for example, April 29 to May 1, 2015, at Bridgewater N 56 (but not at Liberty E 111). In a general sense, this regional-local pattern occurs because pollution mixes in the atmosphere as it travels away from a source, smoothing the speed of changes in concentrations.

Local sources often augment regional sources, which can be revealed as a spike on top of a hump (e.g., April 18, 2015, at Bridgewater N 56). Figure 3 therefore indicates that there are significant local sources of particulate pollution elevating ambient concentrations well above those caused by regional sources across the monitoring period.

Figure 3: Comparison of 1-minute mean PM2.5 concentrations at Bridgewater N 56 and Liberty E 111 from late April to mid-May 2015, highlighting local “spikes” and regional “humps.”

There are many possible sources of pollution in the area and we have to look at the measurements more closely to see if we can deduce what activities are causing these spikes. Knowing the source of pollution is important as some activities produce more toxic particulate matter than others, and actions to mitigate sources should be targeted to the cause of the problem.

III. Characterizing the problem

When is the source most evident?
We are most interested in these “spikes” in pollution relating to a possible local source. We can characterize this source by plotting a number of charts, filtering out concentrations above the regional baseline. Referring to Figure 3, this can be set at 15 µg m-3 in this case, which is the approximate concentration at which regional “humps” in pollution peak.

Figure 4: Mean PM2.5 concentrations at Bridgewater N 56 grouped by hour, month and weekday.

Figure 4 investigates when these “spikes” in pollution occur by grouping concentrations by hour, month and day of the week. Sources of pollution related to commuter or transit traffic typically show peaks in concentrations coincidental with peaks in traffic flow, i.e., morning and evening rush hour with notably lower levels at night and on Sundays. However, on average, the local source at Bridgewater N 56 is highest early in the morning (before rush hour) and on Sundays. These charts can be used to match patterns in the occurrence of spikes with working patterns of particulate-generating activities in the area. Figure 4 shows that on most days there are elevated levels in the early hours of the morning at Bridgewater N 56.

In a general sense, it should be noted that the weather plays a large role in particulate levels. For example, dust tends to be dispersed more slowly during the hours of darkness, as vertical and horizontal wind speeds are generally lower. This phenomenon may skew charts somewhat.

Which direction is PM2.5 coming from?
Wind direction has a considerable influence on pollution measurements. A sensor will only record emissions from a particular source or activity if the wind blows it from the source towards the sensor. Therefore, we can investigate where a source of pollution is likely to be located by plotting wind direction against pollution concentrations.

Figure 5: A scatter plot showing the relationship between PM2.5 concentrations and wind direction (in degrees).

Figure 5 shows how pollutant concentrations at Bridgewater N 56 are influenced by wind direction. It is clear that the highest peaks are recorded when the wind blows from the southwest (210O to 230O) and from the south (170O to 190O).

A polar plot is a more intuitive way of looking at this relationship. This shows color contours of pollutant concentrations in relation to wind direction and wind speed (zero wind in the center, increasing to 35 ms-1 at the outer ring). The highest mean concentrations are shown in red, lowest in blue

Figure 6a: A polar plot of average PM2.5 concentrations at Bridgewater N 56 (left panel) and Liberty E 111 (right panel) during different wind conditions. The color scale shows mean concentration, wind direction around the polar axis, and wind speed from the center outwards. Note that the mean concentrations shown are relative (e.g., highest mean concentration is 8 µg m-3 at Bridgewater N 56, and 100 µg m-3 at Liberty E 111).
Figure 6b: A polar plot of PM2.5 concentrations higher than 15 µg m-3 at Bridgewater N 56 (left panel) and Liberty E 111 (right panel). The color scale shows mean concentration, wind direction around the polar axis, and wind speed from the center outward.

In common with Figure 4, Figure 6a highlights the fact that, on average, the highest concentrations are recorded at Bridgewater N 56 during southwesterly winds. It also shows a very local source at low winds, together with a more regional to middle-distance northerly source, particularly during stronger winds. In contrast, there is clearly a source of pollution to the northeast of Liberty E 111, not evident at Bridgewater N 56. As both sites show a source to the southwest, there may be a regional source of air pollution in that direction, which is detected by most sensors in the area. In addition, Figure 6b, which shows PM2.5 concentrations higher than
15 µg m-3, shows that spikes in PM2.5 concentrations at Bridgewater N 56 are measured during winds from the southwest.

Under which weather conditions are PM2.5 levels most evident?
Different sources of pollution will behave in distinct ways according to the weather. For example, windblown dust will primarily occur during dry, windy conditions. Sometimes, you can learn about a source by characterizing this weather-related behavior.

Figure 7: Relationship between PM2.5 and wind speed, indicating that higher concentrations tend to occur at lower wind speeds.

The relationship between particulate pollution concentrations and wind speed is shown in Figure 7. This suggests that the main source of PM2.5 at Bridgewater N 56 is not wind-blown dust, as peak concentrations are recorded during lower wind speeds. This conclusion is supported by Figure 8, which shows that the highest 1-minute means were recorded during relatively humid conditions (around 50% to 90% humidity), and during high humidity there would be fewer occurrences of wind-blown dust.

Figure 8: Relationship between PM2.5 and humidity at Bridgewater N 56.

IV. Drawing the evidence together

Using the tools provided through the Citizen Sense Airsift Data Analysis Toolkits, we have characterized sources of particulate pollution detected by the Bridgewater N 56 sensor as follows:

  • While regional sources of pollution were detected, there was clear evidence of additional local source or sources.
  • The strongest local source(s) appear to be to the southwest, of the sensor site, and are therefore not related to Highway I-81 to the east. Looking at all other local sites and industries capable of generating PM2.5 as documented in Figure 1, it is possible that the compressor station and well pad to the south of the site are a local source of PM2.5.
  • The local source is strongest during the early hours before 6 am, and the highest mean concentrations occurred on Sundays. It is therefore unlikely to be related to commuter or transit road traffic.
  • PM2.5 levels are unlikely to be related to re-suspended or wind-blown dust due to low wind speeds at which higher concentrations occur.
Look ma, no flare video, Meryl Solar


The Citizen Sense project is led by Dr Jennifer Gabrys, working in collaboration with researcher Helen Pritchard.

Dr Benjamin Barratt at the Environmental Research Group, King’s College, University of London contributed to the co-authoring and analysis of the data stories.

Lau Thiam Kok contributed to the co-development of the Citizen Sense Airsift Data Analysis Toolkits, using and adapting openair software developed by Dr David Carslaw.

Raphael Faeh contributed to the digital design and layout of the data stories.

Special thanks are due to the participants and residents in northeastern Pennsylvania who contributed to the design, development, and testing of the monitoring kit, as well as to the collection and analysis of data, and communication of results to wider publics and regulators. The Bridgewater data story received additional contributions from Vera Scroggins. For more information on project contributors, see Citizen Sense People.

This data story is prepared under the assumption that all pollutant, cartographic and meteorological measurements are valid and not sufficiently biased to cause misrepresentation of results. Please refer to the Airsift Data Analysis Toolkits and Terms of Use for further information.

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 313347, “Citizen Sensing and Environmental Practice: Assessing Participatory Engagements with Environments through Sensor Technologies.”

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