Much can be at stake depending on the choice of words used to describe citizen science, because terminology impacts how knowledge is developed. Citizen science is a quickly evolving field that is mobilizing people's involvement in information development, social action and justice, and large-scale information gathering. Currently, a wide variety of terms and expressions are being used to refer to the concept of 'citizen science' and its practitioners. Here, we explore these terms to help provide guidance for the future growth of this field. We do this by reviewing the theoretical, historical, geopolitical, and disciplinary context of citizen science terminology; discussing what citizen science is and reviewing related terms; and providing a collection of potential terms and definitions for 'citizen science' and people participating in citizen science projects. This collection of terms was generated primarily from the broad knowledge base and on-the-ground experience of the authors, by recognizing the potential issues associated with various terms. While our examples may not be systematic or exhaustive, they are intended to be suggestive and invitational of future consideration. In our collective experience with citizen science projects, no single term is appropriate for all contexts. In a given citizen science project, we suggest that terms should be chosen carefully and their usage explained; direct communication with participants about how terminology affects them and what they would prefer to be called also should occur. We further recommend that a more systematic study of terminology trends in citizen science be conducted.
Abstract. In many urban areas the population is exposed to elevated levels of air pollution. However, real-time air quality is usually only measured at few locations. These measurements provide a general picture of the state of the air, but they are unable to monitor local differences. New low-cost sensor technology is available for several years now, and has the potential to extend official monitoring networks significantly even though the current generation of sensors suffer from various technical issues. Citizen science experiments based on these sensors must be designed carefully to avoid generation of data which is of poor or even useless quality. This study explores the added value of the 2016 Urban AirQ campaign, which focused on measuring nitrogen dioxide (NO2) in Amsterdam, the Netherlands. Sixteen low-cost air quality sensor devices were built and distributed among volunteers living close to roads with high traffic volume for a 2-month measurement period. Each electrochemical sensor was calibrated in-field next to an air monitoring station during an 8-day period, resulting in R2 ranging from 0.3 to 0.7. When temperature and relative humidity are included in a multilinear regression approach, the NO2 accuracy is improved significantly, with R2 ranging from 0.6 to 0.9. Recalibration after the campaign is crucial, as all sensors show a significant signal drift in the 2-month measurement period. The measurement series between the calibration periods can be corrected for after the measurement period by taking a weighted average of the calibration coefficients. Validation against an independent air monitoring station shows good agreement. Using our approach, the standard deviation of a typical sensor device for NO2 measurements was found to be 7 µg m−3, provided that temperatures are below 30 ∘C. Stronger ozone titration on street sides causes an underestimation of NO2 concentrations, which 75 % of the time is less than 2.3 µg m−3. Our findings show that citizen science campaigns using low-cost sensors based on the current generations of electrochemical NO2 sensors may provide useful complementary data on local air quality in an urban setting, provided that experiments are properly set up and the data are carefully analysed.
Citizen science is increasingly being used in diverse research domains. With the emergence and rapid development of sensor technologies, citizens potentially have more powerful tools to collect data and generate information to understand their living environment. Although sensor technologies are developing fast, citizen sensing has not been widely implemented yet and published studies are only a few. In this paper, we analyse the practical experiences from an implementation of citizen sensing for urban environment monitoring. A bottom-up model in which citizens develop and use sensors for environmental monitoring is described and assessed. The paper focuses on a case study of Amsterdam Smart Citizens Lab using NO2sensors for air quality monitoring. We found that the bottom-up citizen sensing is still challenging but can be successful with open cooperation and effective use of online and offline facilities. Based on the assessment, suggestions are proposed for further implementations and research.
Soon after publication the authors were made aware of an error within Table 3 of the original publication. The example given as the 'Scientist' term 'Citizen scientist, Scientist-citizen, public scientist, community scientist' previously read: "Citizen scientists investigated anecdotal evidence to construct hypotheses regarding developmental disorders that members of the public claimed were triggered by a MMR vaccine." This should have read: "Citizen scientists investigated anecdotal evidence to construct hypotheses regarding developmental disorders that members of the public claimed were triggered by chemical pollution." The corrected Table 3 is presented here.
Abstract. In many urban areas the population is exposed to elevated levels of air pollution. However, air quality is usually 10 only measured at a few locations. These measurements provide a general picture of the state of the air, but they are unable to monitor local differences. Since a few years new low-cost sensor technology is available, which has the potential to extend the official monitoring network significantly. These sensors, however, are still in an experimental stage and suffer from various technical issues which limit their applicability.This study explores the added value of alternative air quality measurements, focusing on nitrogen dioxide (NO 2 ) in 15Amsterdam, the Netherlands. 16 low-cost air quality sensor devices were built and distributed among volunteers living close to roads with high traffic volume for a two-month measurement campaign.Careful calibration of individual sensors is essential to measure ambient concentrations of NO 2 significantly. Field calibration was done next to an air monitoring station during an 8-day period, resulting in R 2 ranging from 0.3 to 0.7. The NO 2 accuracy can be improved by including temperature and humidity measurements from an additional low-cost sensor, R 2 20 ranging from 0.6 to 0.9. Recalibration is crucial, as all sensors show significant signal drift after the two-month measurement campaign. The measurement series between the calibration periods can be corrected in hindsight by taking a weighted average of the calibration coefficients.Validation against an independent air monitoring station shows good agreement. Using our approach, the standard deviation of a typical sensor device for NO 2 measurements was found to be 7 μg m -3 . This shows that, if properly treated, low-cost 25 sensors based on the current generations of electrochemical NO 2 sensors may provide useful complementary data on local air quality in an urban setting.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.