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Citizen Science and International Collaboration through Environmental Monitoring with Simple Chemical Sensors



05/30/16 to 06/03/16

Abstract: Building capacity for carrying out and understanding responsible science that is relevant to local challenges is a key ingredient in the OPCW’s strategy for achieving and maintaining a world free of chemical weapons. Two important contexts for building that capacity for responsible science are (1) The global attention being drawn to the rapidly increasing human chemical footprint on our planet and (2) the pervasive use of digital technologies. We describe an effort coordinated by the Organization for the Prohibition of Chemical Weapons to build capacity among young people around the world to harness the power of small mobile chemical sensors to develop data literacy in complex chemical analysis based on measuring analytes that are relevant to their lives and local contexts. This new type of data literacy is an emergent element in educational programs and is key to developing the capacity for decision making on chemical measurement data. The project brings together student and faculty collaborators from the fields of chemistry, social sciences and informatics, to provide proof of concept in four areas that support the overall goal of building a collective effort for scientific analysis; the development of low cost environmental sensors for air and water samples; the collection of representative test data sets on priority contaminants; the assessment and visualization of data; and education about the effect of priority pollutants on human and environmental health. We report on the project goals and preliminary steps taken to achieve them.



The first is a set of interdisciplinary research efforts that attempt to guide human development in the context of the impacts of the rapidly growing human footprint on the life support systems of our planet.1,2 Nine planetary boundaries are defined that describe quantitatively the state of earth system control variables that define a safe operating space for humanity.  Measurements of changes to fundamental chemical parameters are central to the definition and quantification of the nine proposed planetary boundaries, and efforts to mitigate the effects of exceeding those boundaries.  Chemical measurements relevant to these boundaries include the levels of stratospheric ozone, concentration of atmospheric carbon dioxide, global mean saturation state of aragonite in surface seawater, amount of anthropogenic nitrogen removed from the atmosphere, amount of anthropogenic phosphorus deposited in the oceans, and overall atmospheric particulate (aerosol) concentration. Chemistry educators, working in both formal and informal educational settings, are being challenged to contextualize the learning of chemistry concepts through sustainability rich contexts related to these planetary boundaries.3 

Secondly, making progress toward achieving the United Nations Sustainable Development Goals implies building capacity for citizens to understand the role for responsible and peaceful uses of chemistry to contribute to addressing climate change, providing clean water and energy, sustaining food security systems, conserving and sustainably using the oceans and marine resources, managing biomass and terrestrial ecosystems, and alleviating poverty. 

For most citizens, awareness of these global challenges begins at the local level.  Young people with an awareness of the power of science as a tool for development and who live in poverty or conditions of economic uncertainty might ask:  How does my understanding of local measurements of substances with environmental significance impact on the quality of my life, or that of my family, or my city? Is the air that I’m breathing causing ill health effects?  Is the water my family uses contaminated with harmful chemical substances or microbes? Learning how to answer these questions can build an empowering capacity to use knowledge about chemistry to improve the human condition.  But answering these questions requires the development of some fundamental knowledge about chemical substances and measurements and also enough data literacy to make sense of those measurements.


 II. The Project: Environmental Monitoring by Citizens with Simple Chemical Sensors.  We describe an effort proposed by the Organization for the Prohibition of Chemical Weapons with funding support from the European Union to build capacity among young people around the world to harness the power of small mobile chemical sensors to develop data literacy in complex chemical analysis based on measuring analytes that are relevant to their lives and local contexts. This new type of data literacy is an emergent element in educational programs and is key to developing the capacity for decision making on chemical measurement data.

This emphasis on equipping citizens to engage in responsible science and make sense of environmental measurements of chemical parameters that define the quality of local environments is also resonant with the strategic medium-range plan for the Organisation for the Prohibition of Chemical Weapons (OPCW).  OPCW is a global, treaty-based international organisation with responsibilities for disarmament and non-proliferation.  As OPCW has achieved considerable success in freeing the world of chemical weapons, recognized with the awarding of the 2013 Nobel Peace Prize, it has turned new attention to the even greater challenge of working with partners and collaborators to prevent their re-emergence.  As outlined in the first paper in this ConfChem Series by OPCW’s Ballard and Forman, the new emphasis on education and outreach “represents a potential sea-change in the way that the OPCW interacts with the world.  It represents the recognition that achieving the aims of the Chemical Weapons Convention (CWC) will in the future require a whole new kind of engagement – one that is underpinned with robust strategies, with flexible and modern educational tools, and with the support of new stakeholders.  Most importantly it means that education and outreach has a clear strategic role in the future of the Organisation.”4


II A.  Priority Air Pollutants:  Air pollution has long been one of the major byproducts of industrialized human activity that dramatically affects the health of entire human populations.  The World Health Organization estimates that ambient outdoor air pollution was responsible for 3.7 million deaths in 2012, with around 88% of those deaths being in developing countries.5  From an educational perspective, the monitoring and control of air pollution has historically been a key motivator for governmental intervention and regulation and therefore serves as an ideal example of the interplay between pollution, public health, scientific data, and governmental policy.  The World Health Organization lists four pollutants in their air quality guidelines: ozone, particulate matter, nitrogen dioxide, and sulfur dioxide.5

Particulate matter (PM) is the most prevalent air pollutant and is generated by many natural and anthropogenic processes.  Natural sources of PM include fine airborne dust generated by wind and smoke from forest fires, while anthropogenic sources include smoke from burning wood, coal combustion, and other fossil fuel combustion.  PM can be either small solid or liquid particles, usually made of sulfates, nitrates, ammonia, sodium chloride, carbon or mineral dust.5  PM is classified by size and often divided into two regions: PM10 includes all particles smaller than 10 microns and is dominated by larger particles created by mechanical processes, such as wind-blown soil erosion. PM2.5 includes particles less than 2.5 microns that are often formed in the atmosphere from substances generated primarily by combustion processes. The increased toxicity of PM2.5 can be linked both to the ability of small particles to penetrate deeper into the lungs and the chemical composition of the particles. 

One of the greatest concerns about PM2.5 is its ability to penetrate the thoracic region of the respiratory system.  Though many complicating factors exist in determining the relationship between PM levels and mortality, studies generally suggest a strong link between the two, particularly with mortality caused by cardiovascular and respiratory disease.6-8 The exact reason for the toxicity of PM varies widely, but is certainly related to the nature of the chemical substances adsorbing to the surface of the particles.  This includes compounds such as oxidative transition metals, polycyclic aromatic hydrocarbons, and other toxic organic compounds.6

WHO Guidelines for PM2.5 and NO2 9


10 μg/m3 annual mean

25 μg/m3 24-hour mean


20 μg/m3 annual mean

50 μg/m3 24-hour mean


40 μg/m3 annual mean

200 μg/m3 1-hour mean


PM2.5 levels in ambient air vary substantially across the world (Figure 1). Since PM emissions from industrialization have been one of the driving factors for the introduction of governmental air quality regulations, anthropogenic PM has dropped substantially in North America and Europe.  Currently the highest levels of PM2.5 are in equatorial regions. These high PM levels are largely dominated by natural sources, however in highly industrialized centers of South and East Asia, significant contributions from anthropogenic sources can be measured.10 Despite PM levels being lower in North America and Europe, a large fraction of the ground monitoring of PM is focused in these geographical regions.10  This highlights a key challenge for environmental scientists and epidemiologists who want to better understand the effects of high PM levels on human populations and ecosystems. The potential to use small devices in the hands of citizens around the globe to advance air quality monitoring is very large and could have the greatest impacts in regions where PM levels are abnormally high yet monitoring is limited.11



Figure 1. Estimated annual average concentration of PM2.5 in 2005 in mg / m3.10


A second priority air pollutant identified by the WHO and most governmental monitoring agencies is NOx.  NOx is a byproduct of high temperature combustion reactions, and is formed by the oxidation of nitrogen gas.  While NOx is an important primary pollutant it is also linked to secondary air pollutants such as tropospheric ozone.  NOx describes the mixture of NO and NO2 in the atmosphere.  NO is the dominant primary pollutant formed during combustion, which is converted to NO2 by oxidation mechanisms in the atmosphere.  For this reason most air quality standards are based on NO2 levels.

The health effects of NO2 levels are challenging to specify because NO2 pollution is closely related to other combustion pollutants.  Most studies suggest that elevated levels of NO2 can cause respiratory issues and decreased lung function growth in children.9


Figure 2. This global map shows the concentration of nitrogen dioxide in the troposphere as detected by the Ozone Monitoring Instrument aboard the Aura satellite, averaged over 2014. Credits: NASA12


The global distribution of NO2 has been mapped by NASA’s Aura satellite (Figure 2) and clearly shows the link between NO2 pollution and heavy industrialization.12  Elevated levels of NO2 pollution are centered around the Northeast United States and industrial centers in Europe and China.  Comparative data shows that NO2 levels in Europe and the United States have been decreasing over the past decade.  This decrease can be linked to public awareness and government intervention and demonstrates the important role the public has in controlling air pollutants.12  Educational efforts, such as this sensor project, therefore have the potential to significantly improve air quality by linking public awareness, scientific data, and governmental action. This same framework is at the heart of the OPCW’s educational mandate and provides a valuable starting point for educating people about the way they interact with and influence the chemical environment around them.

While global maps like Figure 2 are useful for understanding the general distribution of anthropogenic NO2 production, more detailed information is required to understand the levels of exposure to NO2 pollution by specific individuals in a given population.  It is well known that individual exposure to NO2 gas can vary greatly, even within the same city.  Individual behavior such as one’s house and work locations, route to work and mode of transportation, and other daily activities can lead to significant variability in an individual’s exposure.  The ideal monitoring scenario for short lived chemical pollutants such as NO2 is to monitor air quality on a scale smaller than individual neighborhoods or communities.13-15 The advent of inexpensive sensors for monitoring NO2 could allow this level of detail to be obtained.  Citizen science experiments have potential to provide health experts with a more detailed pollution distribution for epidemiological studies.


II B. Devices and sensors:  In recent years numerous small handheld devices16 for monitoring air quality have become available at relatively low cost.  Examples include the Air Quality Egg ($240 USD)17 and the Aircasting Airbeam ($249 USD) (Figure 3).18  These devices are often linked to online databases designed to map out pollutant levels based on citizen measurements.  Other efforts have focused on interfacing inexpensive sensors with Arduino computer boards.14,19 While these represent great steps forward for citizen science initiatives, these devices are still too expensive to be deployed en masse in areas outside North America and Europe.   In order to be truly deployable around the world, devices need to cost about tens of USD.  In addition, while these devices contribute to two of the goals of this project, data collection and mapping of the data, the educational component of the science being done is not prioritized. 

Figure  3 – Aircasting Airbeam PM2.5 Sensor


II C. Database and visualization:  The collection, sharing and evaluation of data obtained from citizen science projects has always been a challenge.  Many projects start with a bang, getting many people and groups involved in collecting data but then disappear as resources and interest fade.  This OPCW project endeavors to build a lasting database that can be used by multiple groups to bring many different types of chemical data together.  The goal is to produce a database that can compare citizen measurements using small sensors, municipal air quality monitoring, and large governmental monitoring projects like NASA’s Aura satellite data.  The resulting ability for citizen devices to record data that is time stamped and geolocation tagged, means that personal visualizations can be made that track individuals’ daily exposure.14,20  This individualized data can then be linked to global data collected from other sources in a user-friendly database to show individuals how their daily exposer fits into the long-term global picture.

In order to make such a database approach a meaningful tool for citizen science, it will be critical to create a low-barrier environment for those who are interested in using the database. This should include two types of online 'user services': 1) verified, machine-readable datasets for those who have a genuine interest in using the data in combination with other - often seemingly unrelated - datasets; 2) intuitive UX design for those who have an interest in the topic but limited knowledge about data analytics. For example, the project should provide an easy-to-use tool that allows investigative journalists to access, analyze, and present data without technical barriers. In addition, the tooling would need to incorporate recent developments in interactive online visualizations to capture the 'modern' online reader. Both elements are technically possible, but require an iterative process, as none of these tools are likely to work perfectly from the start. The project instead works with built-in feedback loops from user groups, applying a trial-and-error (agile) development philosophy. 

II D.  Education about the significance of measurements and the health effects of air pollutants: One of the most important primary goals of this sensor project is education.  OPCW and the collaborating research teams believe that when citizens better understand the chemical world around them they are better equipped to stand up for their right to live in a safe, clean world.  The same issues that are present when dealing with air pollution are present when dealing with trace chemical substances connected to chemical weapons.  A necessary step towards changing how humanity views chemical problems is to train citizens to understand their molecular world.

To help fulfil this important educational goal, the collaborators will develop an interactive, electronic set of learning resources that will help citizen scientists understand what air pollution is, its sources, the ways that it is measured, and the health significance of the values they measure locally.  These resources will be produced by the interdisciplinary undergraduate student research team at the King’s Centre for Visualization in Science (, and will be modelled after resources such as the International Year of Chemistry legacy resource on climate change (  Along with knowledge about how to collect and analyze data on local environmental air pollutants, the educational resources will help citizens understand ways in which they can make use of understanding in chemistry to improve the quality of life in their communities and countries.

II E.  Chemical Analysis: There are also opportunities to use sensor based data collection as an educational tool, where important concepts in analytical chemical measurement and statistics in data analysis can be explored.  Data sets from local and national environmental monitoring agencies are readily available on the internet.  For example, many cities have air monitoring programs, such as the Capital Airshed program in Edmonton Alberta or the Unites States Environmental protection Agency’s AirData site.21,22  This monitoring data can be combined with student measured data sets with matching time stamps and geolocation tags.  Data comparisons across sensors and data sets can be used to demonstrate concepts of accuracy, precision, uncertainty, instrument to instrument (and method to method) variations.   The data can also be used to introduce issues that arise in the use of data for decision making when there are differences between data sets and observations (an essential topic for those who will be moving into scientific career paths where decision making based on analytical data may be required).

II F.  Science Collaboration:  Remote data storage and online analytics tools allow access from any location with an internet connection.  This provides opportunities for projects where data collection from different regions of the world can be compared, and further facilitates the collaborative development of analysis/visualization tools among students located in different regions of the world, thereby supporting the Chemical Weapons Convention goal of using chemistry to build international collaborations (a form of “science diplomacy”).

III. Progress to date: 

To demonstrate proof of concept, we have selected for the first phases of this project a $ 16 USD PM sensor (Shinyei PPD 42NS) and an $8 NO2 sensor (MiCS 2710) (Figure 4), and interfaced them with a Raspberry Pi computer.  We are currently testing and calibrating the sensors and assessing the durability and long term reliability.  We also intend to explore other sensor options and hope that other teams around the world will be willing to collaborate on this international project. 

Figure 4 –Shinyei PPD42NS PM2.5 Sensor (left) SGX MiCS 2710 NOx Sensor (right)

We have also begun work on the educational resources that are key to this project.  These resources will describe the sources of the priority air pollutants identified by the World Health Organization, what these priority air pollutants are, and their relationship to human and environmental health.  Explanations of data quality and the importance of different global measurement techniques will also be discussed.  Finally, specific resources to guide citizen scientist through device construction, utilization and data handling and analytics will be created.


IV.  Creating synergies for long-term sustainability:

The project team hopes to build on the strengths of other initiatives that have used citizen science to collect environmental data.  We believe the joint capacity of the project partners, OPCW, KCVS, and the Leiden University Centre have the potential to bring some unique synergies to efforts in this area.  To that end, we seek feedback from the chemistry education community and this ConfChem on these questions:


  • How might this OPCW project build synergy with other citizen science projects?  What mechanisms can be used for the project to interact effectively?
  • What is the best way to build low cost sensors for use in developing countries?
  • Are NOx and PM the most reasonable starting point for priority pollutants that might be accessible with low cost mobile sensors and be of importance across the globe?
  • How might other data streams (perhaps non-chemical) be integrated with sensor data to provide a more complete picture of the environmental chemical signatures?
  • What are some creative ways low cost sensors and data analytics tools could be used as effective classroom tools?
  • How can behavior design and gamification methodologies help to sustain citizen science efforts over time? What are best practices in this regard? 
  • What can we learn from volunteer networks in other sectors (open street map, wikipedia, wikileaks, etc)?



We thank the King’s University students Andrew Fox, Aaron Loset, and Aaron Yaremchuk for their work on this project as part of their senior thesis projects.  KCVS undergraduate student researchers Mckenzie Oliver and Rachel Hislop-Hook of KCVS have given helpful input on this paper, and Dr. Brian Martin has served as a mentor. We thank the European Union for funding through Council Decision (CFSP) 2015/259 of 17 February 2015 in support of activities of the Organisation for the Prohibition of Chemical Weapons (OPCW) in the framework of the implementation of the EU Strategy against Proliferation of Weapons of Mass Destruction (project III, Chemical informatics for facilitating international collaboration,


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2. Steffen, W.; Richardson, K.; Rockström, J.; Cornell, S. E.; Fetzer, I.; Bennett, E. M.; Biggs, R.; Carpenter, S. R.; de Vries, W.; de Wit, C. A.; Folke, C.; Gerten, D.; Heinke, J.; Mace, G. M.; Persson, L. M.; Ramanathan, V.; Reyers, B.; Sörlin, S. Planetary boundaries: Guiding human development on a changing planet. Science 2015, 347, 736-747.

3. Mahaffy, P. G.; Martin, B. E.; Kirchhoff, M.; McKenzie, L.; Holme, T.; Versprille, A.; Towns, M. Infusing Sustainability Science Literacy through Chemistry Education: Climate Science as a Rich Context for Learning Chemistry. ACS Sustainable Chem. Eng. 2014, 2, 2488-2494.

4. Ballard, J.; Forman, J. E. Education, outreach and the OPCW: growing partnerships for a global ban. 2016 Spring ConfChem: Science, Disarmament, and Diplomacy in Chemical Education: The Example of the Organisation for the Prohibition of Chemical Weapons. 2016.

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6. Pelucchi, C.; Negri, E.; Gallus, S.; Boffetta, P.; Tramacere, I.; La, V. C. Long-term particulate matter exposure and mortality: a review of European epidemiological studies. BMC Public Health 2009, 9, 453.

7. Laden, F.; Schwartz, J.; Speizer, F. E.; Dockery, D. W. Reduction in fine particulate air pollution and mortality: extended follow-up of the Harvard Six Cities Study. Am. J. Respir. Crit. Care Med. 2006, 173, 667-672.

8. Brunekreef, B.; Beelen, R.; Hoek, G.; Schouten, L.; Bausch-Goldbohm, S.; Fischer, P.; Armstrong, B.; Hughes, E.; Jerrett, M.; van, d. B. P. Effects of long-term exposure to traffic-related air pollution on respiratory and cardiovascular mortality in the Netherlands: the NLCS-AIR study. Res. Rep. Health Eff. Inst. 2009, 5-71; discussion 73; 89.

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10. Brauer, M.; Amann, M.; Burnett, R. T.; Cohen, A.; Dentener, F.; Ezzati, M.; Henderson, S. B.; Krzyzanowski, M.; Martin, R. V.; Van Dingenen, R.; van Donkelaar, A.; Thurston, G. D. Exposure Assessment for Estimation of the Global Burden of Disease Attributable to Outdoor Air Pollution. Environ. Sci. Technol. 2012, 46, 652-660.

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14. Sirbu, A.; Becker, M.; Caminiti, S.; De Baets, B.; Elen, B.; Francis, L.; Gravino, P.; Hotho, A.; Ingarra, S.; Loreto, V.; Molino, A.; Mueller, J.; Peters, J.; Ricchiuti, F.; Saracino, F.; Servedio, V. D. P.; Stumme, G.; Theunis, J.; Tria, F.; Van, d. B. Participatory patterns in an international air quality monitoring initiative. PLoS One 2015, 10, 1-19.

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Bob Belford's picture

Hi Peter and all,

I would like to thank you for sharing such an ambitious and exciting project connecting citizen science, global air monitoring and education!   I really enjoyed your article, and would like to ask two completely unrelated questions.

First, can you give us more information on your low-budget air sampling detectors?  Are there detectors we could pick up, and how could we submit data if we were to purchase detectors. I guess I am asking if this project is ready for people to be involved with, and if so, how can we become involved?

Second, I remembered reading this article in C&E News “Citizen Science Faces Pushback”, and while searching for it saw this Slate article stating “Wyoming just criminalized citizen science”,

Which got me to look deeper, and I found this Union of Concerned Sciences  (UCS) ” article
that  gave links to the legislation and put into a perspective, which if I understand right, if you collect data on water pollution on the polluters land, you are trespassing, can go to jail, and the data is not legally valid, even if it is scientifically valid.  To quote the UCS, “The law was clearly written to damp the efforts of water quality citizen watchdog groups, as evidenced by their definition of “collect”.

Does anyone have any comments on people who try to outlaw or dismiss citizen science? Which actually leads to another question, which is, how will you maintain your data provenance (origin of the source of data)?

This is really an exciting project, and I really appreciate your sharing it with us.



Thanks for your comments.  I would like to comment on your second point first.  Water quality testing is a very interesting area that is more challenging for a number of reasons.  Simple water quailty tests are relatively easy but performing tests for other poullutants gets more complicated fast.  The OPCW project will hopefully turn it's attention to water in the future once we have a framework established for air.

One of the ways that all scientists, citizen or profesional, can deal with pushback is to be ahonest about the quailty of data we are collecting.  One key part of the current project is to include some tags in the database about who collected the data and using what instrument/device.  This will allow us to sort data based on expected accuracy.  From an educational perspective this can teach people about data quality.  From a monitoring perspective this can give local professional scientists an idea of broad trends in the area and possible places that need more careful, higher quailty monitoring.  One challenge with Citizen Science initiative is that they do not necissarily conect with professional scientists.  It would be the dream of this long term OPCW project that we could move past this, conecting governmental, academic, and citizen scientists together for a combined monitoing effort.

As for government laws and regulations.  In many places governments may try to limit citizens from monitoring but if we can link different levels of science, it will be much harder for industry funded governments to hide the effects of industrial pollution.  That would be the hope at least.




Hi Bob,

There are many online resources available for building sensors, collecting data and participating in citizen science projects.  We collected a set of references that you can find through the links in the citizen science and sensors sections of this newsletter:

There is also quite a bit of citizen science that can be done with smartphones, another collection of references on doing science with smartphones is contained in links in this newsletter:​

The OPCW project is really in a feasibility stage, exploring what can be done in the various areas Peter described.  How to be involved?  That’s pretty simple - share ideas and share your own experiences with data collection, analysis and visualization.  The next step for truly making this collaborative (and getting larger numbers of people involved) is to develop a data hub where anyone can deposit and share data.  We are discussing options with The Center for Innovation at Leiden University (, you’ll see two of the authors on this Confchem paper are from Leiden University).  Ultimately, we’d like to see online hosting of instructions for building sensors and analyzing data and the types of educational materials Peter describes.

Collecting data is in principle quite easy, but evaluating data quality, interpreting results from noisy data, and ensuring there is sufficient metadata on any given data set to allow people to understand where it came from and how trustworthy it is, is challenging.  Never the less, there are many projects that are faced with these same issues and we hope we can learn from their experiences and publications.

Making this much more complex (but also quite interesting), would be to look at opportunities to integrate other data streams with matching geolocation and timestamp information to the sensor measurements (for example, meteorological data, social media data and so forth) to more holistically describe what is being studied.  To get an idea of what people are doing with a variety of data sets for development and humanitarian work, take a look at UN Global Pulse projects (, would sensor data provide additional value if integrated into these kind of projects?

Regarding concerns raised by citizen science, you might also be interested in the following Nature editorial from last year:

Turning to concerns about data collection, beyond data integrity and quality, there are also ethical issues that arise when considering how data could be used (and there are of course privacy concerns).  See for example

Jan Apotheker's picture

Dear Peter,

great initiative. It should be able to generate quite some interest.

The 100 year anniversary of IUPAC would be a great opportunity to spread the word on this iniative and get people set up for monitoring the air quality. 


Jan Apotheker's picture


Dear Peter ,

I was a jury memeber at a conest called INESPO, in which this girl presented a project about the amount of P25 particles emited while deepfrying vegetables or pork.

I thought it linked nicely with your project.

There was another focusing on designing an instrument to measure CO2.

Kind regards,


Very nice example of a locally applicable project, Jan.  Thanks!  Do you know what sort of sensor she was using?  If you could possibly chase down a reference, that would be very helpful.



A few years ago I purchased an AirPi and attached it to a Raspberry Pi. It has been operating quite well sitting on my window ledge and collecting a range of data. Unfortunately they had dropped a sensor from what was advertised and that was the reason I bought it so had to make do with CO and NO2, Temp, Pressure, Humidity, light etc. The data is sent out every 2 minutes to

The AirPi project seems to have come to an end (it was developed by High School Students in the UK) and the data was never calibrated so it was only relative changes that were of interest.

The thought I had was to get a set of these into school science clubs in Jamaica and then have the clubs make comparisons between data from Kingston schools to country schools to see what differences they could spot....

I think some of the sensors Peter mentioned are the same ones that were on the AirPi.

Hope something comes out of this






Calibration of the small, inexpensive sensors is the exact problem we are struggling with right now.  We are working on a couple of ideas but would love to hear ideas from the community.

The ideas of sending sensors out with a class is a very good idea.  In theory if the students could get near a high end monitoring station they could calibrate their devices.  Asuming there is enough PM or NO2 in the air to detect.


Probably the simplest way of getting the sensors calibrated is to do what the WMO did for calibrating thermometers using travelling standards.  I would suggest a hierchy of standards.  The top level would be state of the art and housed in a central location.  This could be used to calibrate national or regional standards which need only be selected "ordinary" sensors that were stable. Depending on the number of stations participating there could be further layers.  Preliminary would could establish how often field sensors need to be calibrated and how to best maintain their stability. 


Josh Halpern

Treating low cost sensors as traditional analytical chemistry tools will certainly highlight shortcomings – calibration issues, sensitivity limitations, precision/accuracy considerations, and selectivity issues.


Yet, people are finding ways to use sensors to generate useful information despite limitations.


There is a company in The Netherlands ( that uses an array of gas sensors as an eNose.  The selectivity issues of the sensors actually work in favor of this application – the sensors give patterns of signals in the presence of certain gases (even gases that the sensors are not intended to measure).  Changes in the patterns can be used to recognize the presence of changes in the chemical composition of the air.  The company has a network of eNoses in industrial ports in different parts of the world – if a refinery in Rotterdam (Netherlands) were to have a chemical leak (the release of a cloud of hydrocarbon vapors for example) the eNose network can detect the change.  The network is wirelessly connected and data is reported and analyzed in real time. Combining data from weather stations (each eNose has a weather station) and geolocation data related to the eNose and locations from where phone calls reporting “a smell” originate, the company is able to model the dimensions of the vapor cloud and its ground speed – information that can be used in real time to alert people and inform emergency responders.


The city of Chicago is setting up a network of sensor stations that generate air quality data and provide other types of information that would be of use to city residents. The Array of Things (


There is also a company in San Francisco ( that builds sensors arrays to collect air quality data.  They completed a project using self-driving cars fitted with sensors and overlayed data on maps for visualization (


These are certainly more sophisticated endeavors than classroom citizen science projects would be, but they are interesting examples of what is possible and how people are thinking about the uses of sensors.  A recent article on the use of sensor networks in urban areas might also be of interest:

This sounds like a very interesting project, I hope it takes off soon. I'm still relatively new to the eLearning industry but the linkedIn group I am apart of recently posted some tips on using gamefication strategies to elevate learning here is the link to the article:

In regards to using low cost sensors within classrooms, how about sending a representative that is familiar with the workings of the sensor to a high school or college classroom? One that is concentrating on environmental science, be it environmental chemistry or geoscience. Some college biology labs travel outside to collect data samples from nearby for their lab projects as well.

If you could give more detail on how the sensor collects the data, I'm sure there will be numerous open source databases you could connect to help educate the student or citizen population on various environmental changes and how they affect the population.

Thanks, Zach.  I hope that these sensors will be used both in formal classroom/lab settings and also informally by citizens interested in these measurements.  Perhaps, down the road, there could be some ambassadors at the country or professional teachers association level, who could provide that sort of hands-on guidance.  As far as the education piece, we will work with the research team here at the King's Centre for Visualization in Science to develop some specific resources on the primary pollutants being measured (PM2.5 and NOx), so that participants in the project have a credible, peer-reviewed, and readily accesible site to go to as they seek to understand the health concerns and the significance of their findings.  

Great suggestion, Jan.  I know that the global water project, while challenging to implement, was an important citizen science activity during IYC-2011.  Perhaps IUPAC's Committee on Chemistry Education could consider how we might propose a global activity for IUPAC's 100th Anniversary that would get young people around the world involved in carrying out simple chemical measurements that relate to their quality of life, visualizing their data in the context of what others have collected, and interpreting the results in a meaningful way.  By then, I anticipate that this project will have established the feasibility of expanding the scale of this project, which focuses first on air and then water sampling.  


rpendarvis's picture

Science has always had an element of controversy but that has increased a lot in the last decade or so.  A friend I worked with at the College of Central Florida wanted to analyze local foods for pesticides as a student research project.  The cost was fairly modest since we had the chromatographic equipment and only lacked some standards.  He was met with fierce opposition since it would reflect poorly on some of the local merchants. 

A few years back, analysis of ground water in California showed alarming (dangerous) levels of glyphosate ("Roundup") in many areas of the state which left many water systems making excuses.  

Neither of these examples involve remote sensors but illustrate a central issue.

Ultimately, it comes down to the simple fact that truth is not always popular.

This has been a very good discussion of this important aspect of chemistry.

Best Wishes


What a great idea! Thanks to all who are working on it. 

It seems to me that one of the most important keys to the success of a Citizen Science project lies in catching people's attention and convincing them to take the time to learn about it. I'm going to send the link to this paper to my daughter's high school chemistry teacher, but I wonder if he's going to take the time to read it all. I find what you're planning fascinating, but I must confess that I only had time to read your paper very quickly and not too carefully. Are you planning to create a marketing tool that is short, simple, visual, and interactive? 

Thanks again for your work. 

Mark Bishop

Dear Peter,

Some ideas on “ How can behavior design and gamification methodologies help to sustain citizen science efforts over time? What are best practices in this regard?”

There’s a magazine article on the kinds of people who like to contribute to these kinds of projects, here it’s about Old Weather project, but it’s maybe possible to extrapolate a little: - people are drawn to a community and often it’s people who have some background in the subject, retired teachers and scientists. I remember reading another article stating these more generally, but I couldn’t find it (sorry)

Anyway, that would lead to suggesting making the project attractive to not only school students and young hip kids, but also the age group of people who have retired; and putting an emphasis on building a place for discussion and problem-solving.

There’s more analysis on which kinds of projects appear more successful (although it’s a little biased in the sense that the projects that have gone on the longest have gathered most fame and a larger following, so it’s tough to compare): 
I don’t think there’s a single project with physical manipulatives distributed in the article; but some points seem generalizable:

-          Scientific impact and public engagement are linked in the analysed projects, they’re successful either in both or none -> carefully plan public engagement as well

-          The scientists working in the project may need training on how to talk and collaborate with the citizens (e.g. convincing them to write blogs, discuss at discussion boards…)

-          The projects that keep citizens involved for most hours have an engaging tutorial and high public profile (the examples used were Snapshot Serengeti and a few others)

The way I read your paper was that it focuses on students (university? High school?) likely because of the distribution of data collecting devices required in the project. Perhaps there’s a way to reach other social groups to really gather data from the daily lives of different generations and more and less privileged groups in the same areas… 
Another part that seems to run against the success model outlined above is that the citizens will be data collectors only. This will not create lasting engagement (how many times will you be interested in collecting data from your walk to school). The planning is likely in such initial stages that there’s little to say about the analysis and how it could be shared among the participants, but that would probably be the area where a larger crowd could partake in the project and keep it going for longer and also educate more than being the vehicle for data collection.  

Some ideas that otherwise come to mind (in terms of the other data sets you mention) – maybe share ideas on other tags that should be put on the data collected by people. This could be a collaborative citizen science effort already, to have people come up with descriptors that would set their daily lives and susceptibilities to pollution apart from “everyone else”. Maybe a vote to choose the ones that seem most information rich. Would have to design a tutorial or a video or something about the different lives of people all over the world to set people into mindset of noticing the differences. 
Also, this could be already done while the sensor development is happening in the background to start raising public interest in the project (as it seems safe to say your sensors WILL work and be of reasonable cost).
Later when uploading the data to the online repository, the collectors should then choose from this predetermined list which ones apply to their data (say, “collected on foot”, “downtown”, “wood stove in the house”, etc…) and hence there’d be also more data to connect to individual social settings level patterns, rather than just cities or countries data streams overall (which obviously would be of interest as well).

What an interesting project you’re running! I wish you best of luck in the effort!

Anna-Leena Kähkönen
University of Jyväskylä, Finland

Dear Anna-Leena,

Thank you for your very thoughtful comments, and for the interesting additional examples of how sensors can be used.  I think you're quite right that this pilot project does not need to be limited to young people.  One of our reasons for this focus initially is that we hope that putting these in the hands of people who are trying to highlight their skills during challenging environments for employment may help to build both capacity and self-confidence in abilities.  

Your ideas about tagging are excellent, and we are early in the project, so this is something we can attend to as we start piloting data.

Thanks again for the helpful suggestions.


This made me think of another example of Citizen Science: the Quake-Catcher Network

Thousands of earthquake sensors have been distributed world-wide and are connected via USB to PC's that are left on 24/7. Whenever a shock is felt it sends the data to Caltech.

In addition when registering the site a report goes in from the sensor location about type of construction in the building etc so a more detailed pattern can emerge about building materials that should be used in earthquake prone areas.





Bob Belford's picture

Hi Peter and All,

I was discussing your paper with a colleague and he showed me these cheap sensors for kits like yours, which as a kit, cost under $3.00 apiece.

 This leads to several lines of questions.

First, and please understand that this is all new to me, but are you making tutorials on how these devices work?  Is there a tutorial that anyone is familiar with that could explain how the sensors you are working with work, and could it be shared with us?

Second, I was talking with another colleague who is an atmospheric chemist, and he said something to the tune of, you are seeking  three things in your probes; they need to be fast, accurate and cheap, and that you can have two of the three, but not all three.  Any thoughts on this?


Better, faster, cheaper goes back to Dan Goldin when he was NASA administrator, and the reply from the ground troops was pick two.  However, and in view of such school/citizen science projects you don't need more accurate, what you need is unbiased.  Arbitrary accuracy can be achieved by using a large number of imprecise unbiased detectors.  That indeed is the lesson of global temperature anomaly measurements.

For example, oversampling and decimation are used to increase the precision of a analog to digital converter

There is an interesting discussion at a blog that I read Moyhu including a useful story in the comments by Kevin O'Neill

"As a metrologist, I'm surprised anyone would use metrology as an argument against averaging. One must take a series of readings and average if only to know the short-term repeatability to calculate uncertainties. And of course anyone with half a brain, metrologist or not, quickly understands that averaging adds precision.

Perhaps the mental stumbling block is that averaging readings from one device adds precision - not accuracy, but averaging multiple devices adds both precision and accuracy.

I once performed a simple experiment where I showed co-workers that I could get more accurate results from twenty-five 6 1/2 digit voltmeters than from one 8 1/2 digit voltmeter - even though the 8 1/2 digit voltmeter has a presumed accuracy 50 times better than the 6 1/2 digit voltmeters. I did 'cheat' a little by using statistical bootstrapping to increase the effective sample size from 25 to 1000. I would have to go back and find the final results, but the reduction in error was approximately from 85 ppm for a single 6 1/2 digit voltmeter to low single digit ppm error after bootstrapping."


Josh Halpern


There is much “how to” information available online, for example from the Environmental Protection Agency:


Links to further information can be found on DIY community and citizen science focused websites such as these (and there are many others as well)


On how to generate better quality data with sensors, see Josh’s post above, it addresses the accuracy/precision issues quite well.  Thinking about the use of such sensors for educational purposes, they could provide an inexpensive way to get hands on experience measuring large numbers of data points. Something that might be useful in teaching statistical concepts critical for data analysis (maybe even an opportunity to consider the statistics of experimental design).


Sensors of the type we are talking about and the data measurements they generate probably need to be approached in different ways than more familair laboratory instruments for chemical measurements.  To use them to generate useful information might require approaches that include “numbering up”, integrating with other data streams, and/or comparative measurements.