Citizen Science Projects in Bulgaria

We continue our series of articles on national Citizen Science (CS) projects with a more in-depth exploration of the Bulgarian CS landscape. The ensuing analysis is based on a critical review of 20 initiatives that were organised or are still running in the country. Interested readers can download the dataset developed during the mapping process where all 20 initiatives are presented and analysed in even more detail. For methodology and limitations of the research undertaken, please refer to the foundational article.


When we started the exercise, the project team was aware that CS is relatively new to the country. The main reasons for that are i) comparatively low levels of public participation in science in the region and ii) a limited number of initiatives published on international CS aggregation platforms. As regards the last point, the CitSci-X platform managed by JRC lists 9 projects for Bulgaria, most of which appear to have a questionable link to CS upon closer examination. And on EU-Citizen.Science, there is no country filter for Bulgaria in the projects section, which can give an impression that the CS landscape in the country is completely barren.


Below is a quick overview of the 20 Bulgarian initiatives. We found several projects in the domain of air quality monitoring and biodiversity monitoring. A few projects were from fields other than natural sciences i.e. social sciences, humanities and arts. The rest were individual instances related to the monitoring of water quality, vegetation, environment, waste, and odour pollution.



General overview

Our sample shows that Bulgarian CS landscape is a mix of global initiatives, European initiatives, EU-funded projects (outside-in initiatives), and activities started by local and regional stakeholders. Some of these are finished projects, some are still running. To better illustrate this diversity, we’ll briefly present a couple of projects from each category. After this, we’ll delve deeper into the sample by examining key themes related to stakeholder engagement, data collection, and impact, first for air related projects (primary cluster) and then all the other ones (secondary cluster).


Global initiatives

In this category we placed GLOBE and AirBG. Although AirBG is active nationally, the project started as part of Luftaden.info (now Sensor.Community), which originated in Germany in 2016 and has since spread to all corners of the world (there are 57 community labs in 65 countries according to the website). AirBG set itself an ambitious goal when it started - to build a national network of 1000 stations across the country - and that goal has almost been achieved judging by the number of deployed sensors on the AirTube map where results are displayed.


GLOBE was founded in 1994 in the US to improve the understanding of the Earth system and global environment among students and the public worldwide. Currently, GLOBE has presence in 125 countries, including Bulgaria and all other pilot countries. In Bulgaria, GLOBE cooperates with eight schools, two of which are in Sofia: Anglo-American School Sofia, American College of Sofia. In total, there are 247 CS sites across Bulgaria that collectively produced 582 measurements on land cover, trees and clouds.


European initiatives

By European initiatives we don’t mean EU-funded projects (as these will be discussed next) but rather projects with a pan-European scope, such as HEAL and PECBMS. HEAL was a CS project initiated by the eponymous Health and Environment Alliance. It was active in six European capitals that at the time (2019) failed to meet EU air quality standards as regards nitrogen dioxide (NO2) and particulate matter (PM). Two of them are COMPAIR pilot cities: Berlin and Sofia. In Sofia, HEAL worked with eight primary schools located in different municipal districts to measure indoor and outdoor pollution (PM2.5, NO2), as well as carbon dioxide (CO2) concentration in classrooms.


PECBMS stands for the Pan-European Common Bird Monitoring Scheme, a project that was started in 2002 by the European Bird Census Council and BirdLife International. Counting birds in the field is performed by volunteers in different countries. The number of ‘test sites’ in Bulgaria exceeded 100 in 2021, with citizen scientists making a total of 11,430 entries that year.


EU-funded projects

There are several EU-funded projects in the sample. The ones we’re going to briefly present are DNOSES and RECONNECT. DNOSES is a finished project that stands for the Distributed Network for Odour Sensing Empowerment and Sustainability. The project used CS as one of the tools to tackle odour pollution in six pilot cities, among them Sofia. The Bulgarian pilot focused on food waste collection within Sofia Municipality. By mapping and framing the issue, the pilot tried to identify bottlenecks in the municipal system for separate collection of food waste, and ultimately improve it using new insights from CS activities.


RECONNECT too is a finished project, with CS activities performed in Bulgaria, Greece and Cyprus. The project relied on volunteer divers to identify marine species and monitor changes in biodiversity over time. There were four study areas in Bulgaria, all from the Natura 2000 site Plazh Gradina - Zlatna Ribka.


Domestic initiatives

Found in this category are initiatives started by local stakeholders, for example METER.AC and EdnoDarvo. METER.AC is an ongoing CS initiative by Plovdiv University. It has a network of some 100 nodes across Bulgaria, covering Plovdiv, Sofia and many other cities, that measure atmospheric pressure, temperature, relative humidity, particulate matter, and background radiation. Essentially, METER.AC is a continuously updated dataset that provides open data with high spatiotemporal resolution for detailed atmospheric monitoring.


EdnoDarvo (OneTree) is currently active in Sofia, focusing primarily on vegetation monitoring. Volunteers and professionals gather information on urban trees via app. The results (e.g. type, height, thickness) are then displayed on a map embedded into the project website.


Now that we painted a general picture of the CS landscape in Bulgaria, we would like to proceed with a thematic analysis of the identified initiatives, focusing on their

  • Engagement approach: how did they engage volunteers, how many of them were involved, were any of them from hard-to-reach groups, were other members of the quadruple helix involved, were any of the 10 principles of good CS followed?

  • Data collection and analysis: what information did citizen scientists collect, how did they collect it, how was the information presented?

  • Impact: what impact, if any, did the project have on individuals, technology, policy?


As detailed analysis per project would take too much space and time, we will just provide an overall summary per theme based on the information we were able to find during the mapping process. Interested readers can always consult the main tables for extra details. Other caveats worth mentioning now are these.


First, just because we couldn’t find, for example, evidence of impact, use of ECSA’s 10 principles, or involvement of hard-to-reach groups for some initiatives, it doesn’t mean that these results or activities were actually absent during the project. The fact that we failed to find something could simply be due to time constraints under which the research team operated, and also because of the nature of the research itself (desktop based).


Second, although our mapping covers all projects, those in the field of air monitoring (primary cluster) will be prioritised owing to their relevance to COMPAIR. By studying what they did or didn’t do, how successful or unsuccessful they were in achieving impact, we hope to obtain some useful knowledge that can inform our planning and operations as regards pilot deployment and technical development. That said, there are some useful lessons to be learned from almost all projects, not only those in the primary cluster. We will try to do justice to some of them too by highlighting their achievements at the end of the chapter.


Primary cluster

Stakeholder engagement

Within the air monitoring cluster, no comprehensive methodology to engage stakeholders was identified. AirBG has followed a rather hands-off approach in this regard, offering copious guidance on the website (e.g. what sensor parts to buy, how to assemble them) but little in the way of a multi-stage participatory process. HEAL was also short on details regarding their work with eight schools. The only project where we were able to find some evidence of co-creation was Dustcounters, a Greenpeace initiative in Stara Zagora, but even here, it appears, the process was limited to a brief info session followed by a workshop where volunteers learned how to assemble sensor devices.


As regards participants, it’s only for Dustcounters that we were able to find the number of citizen scientists involved (n=25), while for all other projects this information either wasn’t provided or can be estimated indirectly, by looking at the number of sensors deployed e.g. 824 in the case of AirBG.


Participation of hard-to-reach groups in CS activities was not openly mentioned by any of the projects. But if they were involved, the most likely candidate where this could have happened is HEAL. If some of the eight participating schools cater to children from different social classes, we can assume that pupils from lower socioeconomic backgrounds were represented in the schools’ population (6400 pupils according to HEAL), and could therefore have been among participants that took part in CS activities.


For this cluster of projects, we couldn’t find any evidence of the involvement of all members of the quadruple helix community in a single project. In most cases, participation can be described as being double helix i.e. involving scientists and citizens. METER.AC is the only project that appears to be thinking in quadruple helix terms, judging by its intention to provide tools and CS resources to help academia, public institutions and industry achieve Sustainable Development Goals.


Finally, based on the description of CS activities performed, all projects seem to follow at least the first of the 10 principles. (Citizen science projects actively involve citizens in scientific endeavour that generates new knowledge or understanding. Citizens may act as contributors, collaborators, or as project leader and have a meaningful role in the project.) But the fact that acknowledgement of 10 principles was nowhere to be found suggests that projects did not frame their activities according to ECSA's guidance, or were even aware of it at the time of experiment design/implementation. This raises an important question, actually two. First, do projects need to acknowledge, via a statement of sorts, that they follow some or all of the 10 principles, to be deemed compliant with good CS practice? Second, is there a minimum threshold (e.g. following one, two or three principles) that projects must meet in order for their activities to be considered good CS? We will leave these questions open for now and will attend to them at the end of the deliverable when issuing recommendations for future action.


Data collection and analysis

In terms of data captured, the five projects collectively measured particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), carbon dioxide (CO2), as well as additional atmospheric information e.g. pressure, temperature, humidity, background radiation. There is a clear tendency to opt for easy-to-use, easy-to-assemble, low-cost, do-it-yourself sensors, such as those offered by the now-defunct Lufdaten.info, with the NodeMCU open source IoT platform at the core. The measurement of NO2 and CO2 was carried out, respectively, using diffusion tubes and a special CO2 monitor. All projects except HEAL and Dustcounters present results on an online map. In the case of AirBG, this was linked to the main platform of Sensor.Community.


Impact

In assessing the impact of identified initiatives we were guided by three questions. Was there anything innovative about the project from a technical point of view? Did participants change their attitudes and behaviour as a result of the project? Did the project have any impact on policy making?


With regards to technical impact, it’s worth mentioning two projects: Dustcounters and METER.AC. The innovative design of Dustcounter devices meant that they could be easily assembled from common hardware components. Moreover, they were created with open-source technology (Arduino), which made them affordable and easy to operate by non-professionals without technical expertise. As to METER.AC, we found their platform to be an interesting dissemination and awareness building resource. Not only because of the way it displays data (there are tables, maps, real-time footage), but also because the network data is licensed under Creative Commons CC0. It means that all the raw data, including the full history, is in the public domain and can be easily reused by third-party apps.


When it comes to impact on individuals and policy, we just one brief mention in the HEAL report that their recommendations would be of interest to parents, health professionals, patient groups, health sector, and schools, but whether some of these stakeholders changed their behaviour as a result of the project is anyone’s guess. In the same report, HEAL identified local authorities, national and EU decision makers as another target audience for their recommendations, however there was no further discussion on whether these recommendations ultimately had any impact on policy immediately or over time.

Secondary cluster

Highlights from other initiatives

Among the projects worth highlighting outside the air cluster is DNOSES. It’s one of the few reviewed initiatives that clearly focused on engaging members of the quadruple helix community. Participation in DNOSES extended beyond data collection; volunteers were also able to define the problem, co-design methodologies and tools that enabled them to own, share and act on their results. The results of the Sofia pilot were presented to the National Association of the Municipalities in the Republic of Bulgaria, and later circulated to 265 Bulgarian municipalities via association’s bulletin.


Looking at projects that shared information on their volunteering force, initiatives with the highest number of citizen scientists are Let’s count the sparrows (767), The Quest for the Storks (300), ANEMONE (158) and CitizenHeritage (23).


We noticed that many initiatives, especially in the field of biodiversity monitoring, relied on simple forms to report data (e.g. PECBMS, Let’s count the sparrows, Shared compost, Watermap of Bulgaria) but there were also a few that developed a special app for that (e.g. EdnoDarvo, GLOBE, The Quest for the Storks, Citizen’s App). Although many opt for online maps as a way of presenting results, not all do. REFRESH, for example, presented results only in project reports.


Finally, the most common personal impact of CS participation appears to be increased awareness of issues and ways to tackle them. Additional potential benefits include the ability to counter the influence of fake news (ANEMONE), better mental health and strengthened social bonds (RECONNECT). The Watermap of Bulgaria has a clear focus on behavioural change but whether its activities/results helped limit the use of plastic water bottles has yet to be established.


Conclusion

The 20 initiatives reviewed for the Bulgarian sample are a mix of global initiatives, European initiatives, EU-funded projects, and activities started by local and regional stakeholders. Citizens involved in air monitoring projects usually receive prior training and guidance but it’s not clear to what extent they are engaged in stages preceding data collection (e.g. problem formulation, location selection) and stages that follow it e.g. reflection, analysis, lobbying for change. Impact on individuals and policy could not be easily identified within the air cluster. And as regards technology, the project with the highest innovation potential is METER.AC, which provides a continuously updated environmental dataset as open data under CC0 license.


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