Story 5


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.

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.

Liberty E 111 is located in Susquehanna County, Pennsylvania. John Hotvedt and Barabara Scott used the Citizen Sense Kit at this location to monitor their air quality for 7 months, from October 2014 to June 2015.

As can be seen in Figure 1, which includes geo-location data on hydraulic fracturing infrastructure documented by participant Meryl Solar, there are a number of fracking sites surrounding the Liberty E 111 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 The monitoring location is sited at the northern edge of the Endless Mountains region, which includes forests, farms and valleys, as well as creeks, lakes and ponds. Ground fog and low-lying clouds are common in this region, where temperatures can fall below 5 degrees Fahrenheit during the night.

The PM2.5 monitor was located on an open ledge in a covered open-sided shed, which housed their farm tractor and firewood adjacent to their garage. The shed and garage are located on a gentle slope at 1700 feet in elevation in the middle of 2 acres of field, garden and orchard. The land climbs to 1790 feet west of the shed, and to about 1800 feet on a ridge that is 800 feet to the east.

Local sources of particulate pollution
Major Highways: I-81 is a 4-lane highway located 5.5 miles due west of Liberty E 111, which carries heavy truck traffic between Canada and the Mid-Atlantic states. In Binghamton, New York, I-81 intersects with 2 other major interstate highways. By contrast, almost all of the local township roads in Susquehanna County are unpaved and carry a combination of light residential and commercial traffic. Only dirt roads that directly access heavy industry like quarries, mines, oil and gas wells, or processing facilities have been improved in order to carry heavy trucks and high traffic volumes. Otherwise, only paved state routes, such as SR 29 (a two-lane undivided route) that intersects with Jones Creek Rd, carry heavy traffic without restriction.

Rail Line: There is a railroad freight line that carries a number of daily freight trains along the US Route 11 corridor, 5.25 miles east of the monitoring location.

Industrial Sites: There are a number of natural gas compressor stations located in proximity to Liberty E 111. The compressor station shown in the aerial above, which is 1 of 2 compressor stations serving nearby transmission pipelines, is located just over 1 mile from the monitoring location. This compressor station is currently configured with 2 engines as judged by the stacks that are observable in the aerial images viewed in May 2015. This type of compressor station built to supply gas for transmission lines uses Caterpillar G3606 LE natural gas engines according to the proposal for the project cited in a 2011 Clean Air Council letter to the Pennsylvania Department of Environmental Protection (PA DEP).

In addition to the above compressor station, there are 5 additional compressor stations within a 7-mile radius of Liberty E 111. There are also 11 producing well pads within a 3.5-mile radius of the monitoring location, and 5 rock quarries within a 2-mile radius of the site.

Regional sources of particulate pollution
Binghamton, New York, a city with a population of 47,000, is 10 miles north of Liberty E 111. There are 317,331 people in the Binghamton metropolitan area (or within a 30-mile radius of the city). Binghamton is a trucking hub for many companies because of the convergence of highways in the region.

There was little visible evidence of well and compressor station development in the Liberty E 111 area during the Citizen Sense study. There were also no new transmission or gathering lines constructed within the period of the study. The natural gas infrastructure remained relatively the same throughout the course of the monitoring period. There may have been some re-fracturing or development of existing well pads, and existing compressor stations or pipelines could also have had new equipment added during the time of the study, but there is no evidence of these developments.

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.

Figure 2:Time series chart of daily mean PM2.5 concentrations at Liberty E 111 (units: µg m-3).

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 3a: Comparison of 1-minute mean concentrations of PM<sub>2.5</sub> at Liberty E 111 and Liberty S 13, highlighting local “spikes.”
Figure 3b: Comparison of 1-minute mean concentrations of PM2.5 at Liberty E 111 and Liberty E 13 during May 2015, highlighting local “spikes” and regional “humps.”

Figures 3a and 3b show an extract of the monitoring at the Liberty E 111 monitoring site presented as 1-minute mean concentrations of PM2.5. Measurements from the Liberty S 13 site, which is approximately 2 miles southwest of Liberty E 111, are shown for comparison. Regional sources of pollution appear as broad “humps” of elevated pollution affecting both sites, for example, the period between May 23 to 26, 2015 (Figure 3b). Local sources of pollution appear as short “spikes” typically affecting only one or the other site, for example from May 24 to 26, 2015, at Liberty E 111, (but not at Liberty S 13) (Figure 3b). This pattern occurs because pollution mixes in the atmosphere as it travels away from a source, smoothing the speed of changes in concentrations. Figure 2b 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.

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 the “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. We refer to Figure 3 in Data Story 1 to set the regional baseline of 15 µg m-3, which is the approximate concentration at which regional “humps” in pollution peak. Data Story 1 provides the most comprehensive and extensive monitoring data, and is a good point of comparison across all data stories.

Figure 4: Mean PM2.5 concentrations at Liberty E 111 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, at Liberty E 111 the local source 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.

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 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 Liberty E 111 are influenced by wind direction. It is clear that the highest peaks are recorded when the wind blows from the southeast to the southwest (140O to 170O and 190O 250O) and northeast to east (40O to 90O).

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 6: A polar plot of PM2.5 concentrations higher than 15 µg m-3 at Liberty E 111 (left panel) and Liberty S 13 (right panel). The color scale shows mean concentration, wind direction around the polar axis, and wind speed from the center outward.

Figure 6 highlights the fact that, on average, the most frequent high concentrations of PM2.5 are recorded at Liberty E 111 during southeasterly winds. Similar to Figure 5, this figure also shows that there are high concentrations of PM2.5 from the northeast. In contrast, there is clearly a source of pollution to the southwest of Liberty S 13, which is not evident at Liberty E 111. Figure 6 further shows that Liberty E 111 has higher concentrations of PM2.5 than Liberty S 13.

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 figure suggests that the main source 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 mean concentrations of PM2.5 were recorded during relatively humid conditions (around 70% to 90% humidity), and during high humidity there would be fewer occurrences of wind-blown dust. However, some PM2.5 readings at lower humidity at this site may be due to wind-blown dust. Furthermore, while there were some reports of fog observed at this site, there is no clear or consistent relationship between high PM2.5 readings and fog events evident at this site. (As noted on the Speck sensor ‘Frequently Asked Questions’ website, high humidity can affect PM2.5 readings. We have drawn on observations of site conditions in order to assess whether fog conditions may be affecting readings.)

Figure 8: Relationship between PM2.5 and humidity at Liberty E 111.

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 Liberty E 111 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(s) to be to the southeast of the sensor site, and as these are not shown at Liberty S 13, this suggest that they are not related to Highway I-81 or to the railroad, which are both located to the east. Looking at all other local sites and industries capable of generating PM2.5 as documented in the introduction to this Data Story, it is possible that the nearby compressor station to the southeast of the site is a local source of PM2.5.
  • Because there are also elevated levels to the northeast of the site, the nearby well pad could be a contributing local source of PM2.5.
  • The local source(s) is strongest during the early hours before 6 am, and the highest mean concentrations of PM2.5 occurred on Sundays. These elevated concentrations are 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 the low wind speeds at which higher concentrations occur.
  • If we look at Figure 8 and discount the high spikes at higher humidity, we can see there is a distribution of data across humidity readings. This suggests that a small percentage of readings may be due to wind-blown dust. Based on the data and observed site conditions, this also suggests that not all high PM2.5 levels during moderate to high humidity could be attributed to fog.
Industrial countryside video, Catherine Pancake


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 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 Liberty data story received additional contributions from John Hotvedt and Barbara Scott. 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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