Large-scale citizen science protocol provides high-resolution nitrogen dioxide values while enhancing community knowledge and collective action.
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ABSTRACT:
SUBMITTER: Perello J
PROVIDER: S-EPMC8374703 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Dataset from a large-scale air quality citizen science campaign is presented (xAire, 725 measurements, see Ref. [1]). A broad partnership with 1650 citizens from communities around 18 primary schools across Barcelona (Spain) provided the capacity to obtain unprecedented high-resolution NO2 levels which had in turn the capacity to provide an updated asthma Health Impact Assessment. Nitrogen dioxide levels being obtained in a 4-week period during February and March 2018 with Palmes' diffusion samplers are herein provided. Dataset includes NO2 levels from outdoor locations n=671, playgrounds n=31, and inside school buildings (mostly classrooms) n=23. Data was calibrated and annualized with concentration levels from automatic reference stations. It is shown that NO2 levels vary considerably with at some cases very high levels. Strong differences might also however be explained by the fact that ambient air pollution is reduced exponentially with distance from an emission source like traffic meaning that two samplers located about 100 m away can measure a tenfold difference concentration level.
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Project description:The "noisy labeler problem" in crowdsourced data has attracted great attention in recent years, with important ramifications in citizen science, where non-experts must produce high-quality data. Particularly relevant to citizen science is dynamic task allocation, in which the level of agreement among labelers can be progressively updated through the information-theoretic notion of entropy. Under dynamic task allocation, we hypothesized that providing volunteers with an "I don't know" option would contribute to enhancing data quality, by introducing further, useful information about the level of agreement among volunteers. We investigated the influence of an "I don't know" option on the data quality in a citizen science project that entailed classifying the image of a highly polluted canal into "threat" or "no threat" to the environment. Our results show that an "I don't know" option can enhance accuracy, compared to the case without the option; such an improvement mostly affects the true negative rather than the true positive rate. In an information-theoretic sense, these seemingly meaningless blank votes constitute a meaningful piece of information to help enhance accuracy of data in citizen science.
| S-EPMC6392254 | biostudies-literature
Project description:Titanium dioxide (TiO2) is a common component in personal care products (PCP), which through use enters the wastewater treatment plant (WWTP) and ultimately the environment. A citizen science approach is utilized here to inform the prevalence and usage of TiO2 containing PCP on a household scale, which generates information as to the quantity of TiO2 entering the WWTP, and the portion ultimately discharged to the environment. Meanwhile, citizen science sourced inventories were generated to estimate the quantity of TiO2, and potentially nanoscale TiO2 entering the WWTP from consumer products and to determine which products had the greatest contribution. The estimated values were compared with water samples from the WWTP which quantified the amount of total titanium present using ICP-AES. These values were at a similar level with other top-down estimation approaches and suggest that a citizen science approach is valid to estimate the loading of TiO2, and potentially other emerging contaminants, while at the same time engaging with community stakeholders.
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Project description:The skyglow produced by artificial lights at night is one of the most dramatic anthropogenic modifications of Earth's biosphere. The GLOBE at Night citizen science project allows individual observers to quantify skyglow using star maps showing different levels of light pollution. We show that aggregated GLOBE at Night data depend strongly on artificial skyglow, and could be used to track lighting changes worldwide. Naked eye time series can be expected to be very stable, due to the slow pace of human eye evolution. The standard deviation of an individual GLOBE at Night observation is found to be 1.2 stellar magnitudes. Zenith skyglow estimates from the "First World Atlas of Artificial Night Sky Brightness" are tested using a subset of the GLOBE at Night data. Although we find the World Atlas overestimates sky brightness in the very center of large cities, its predictions for Milky Way visibility are accurate.
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Project description:BACKGROUND:Disaster citizen science, or the use of scientific principles and methods by "non-professional" scientists or volunteers, may be a promising way to enhance public health emergency preparedness (PHEP) and build community resilience. However, little research has focused on understanding this emerging field and its implications for PHEP. To address research gaps, this paper: (1) assesses the state of disaster citizen science by developing an inventory of disaster citizen science projects; (2) identifies different models of disaster citizen science; and (3) assesses their relevance for PHEP. METHODS:We searched the English-language peer-reviewed and grey literature for disaster citizen science projects with no time period specified. Following searches, a team of three reviewers applied inclusion/exclusion criteria that defined eligible disasters and citizen science activities. Reviewers extracted the following elements from each project: project name and description; lead and partner entities; geographic setting; start and end dates; type of disaster; disaster phase; citizen science model; and technologies used. RESULTS:A final set of 209 projects, covering the time period 1953-2017, were included in the inventory. Projects were classified across five citizen science models: distributed or volunteer sensing (n =?19; 9%); contributory (n =?98; 47%); distributed intelligence (n =?52; 25%); collaborative research (n =?32; 15%); and collegial research (n =?8; 4%). Overall, projects were conducted across all disaster phases and most frequently for earthquakes, floods, and hurricanes. Although activities occurred globally, 40% of projects were set in the U.S. Academic, government, technology, and advocacy organizations were the most prevalent lead entities. Although a range of technologies were used, 77% of projects (n =?161) required an internet-connected device. These characteristics varied across citizen science models revealing important implications for applications of disaster citizen science, enhancement of disaster response capabilities, and sustainability of activities over time. CONCLUSIONS:By increasing engagement in research, disaster citizen science may empower communities to take collective action, improve system response capabilities, and generate relevant data to mitigate adverse health impacts. The project inventory established a baseline for future research to capitalize on opportunities, address limitations, and help disaster citizen science achieve its potential.
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Project description:BackgroundBiodiversity is being lost rapidly and its conservation is thus one of the most urgent tasks today. For biodiversity conservation to be successful, the public needs to gain an awareness and understanding of biodiversity and its importance. Moreover, species experts are needed who have the skills necessary for identifying and recording biodiversity. Previous research showed that citizen science projects can contribute to educating the public about biodiversity. However, it is still unclear how project characteristics connect to participants' knowledge and skills and how citizen science projects should be designed if they are to foster participants' learning.AimWe aimed to investigate specific characteristics of biodiversity citizen science projects that could potentially influence participants' learning. We explored the following project characteristics from both the project coordinators' and the participants' perspectives: information and training provided to participants, social interaction among participants, contact between participants and staff, and feedback and recognition provided to participants.Methods and resultsIn order to examine the extent to which these project characteristics are connected to participants' gains in knowledge and skills, we conducted a comprehensive study across 48 biodiversity citizen science projects in Europe and Australia. We found that participants' perceived gains in knowledge and skills were significantly related to the five project characteristics as reported by the participants: information received by the participants, training received by the participants, social interaction among participants, contact between participants and staff, and feedback and recognition received by the participants.ConclusionWe conclude that by deliberately designing citizen science projects to include features such as interaction and feedback, these projects could achieve higher learning outcomes for the participants. Thereby, suitable modes of communication between projects and their participants are crucial. We provide specific suggestions for the design of biodiversity citizen science projects and for future research on project characteristics and participant outcomes.
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Project description:Recent outbreaks of Zika, chikungunya and dengue highlight the importance of better understanding the spread of disease-carrying mosquitoes across multiple spatio-temporal scales. Traditional surveillance tools are limited by jurisdictional boundaries and cost constraints. Here we show how a scalable citizen science system can solve this problem by combining citizen scientists' observations with expert validation and correcting for sampling effort. Our system provides accurate early warning information about the Asian tiger mosquito (Aedes albopictus) invasion in Spain, well beyond that available from traditional methods, and vital for public health services. It also provides estimates of tiger mosquito risk comparable to those from traditional methods but more directly related to the human-mosquito encounters that are relevant for epidemiological modelling and scalable enough to cover the entire country. These results illustrate how powerful public participation in science can be and suggest citizen science is positioned to revolutionize mosquito-borne disease surveillance worldwide.
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Project description:The Covid-19 pandemic served as the impetus to implement activities designed to engage students in the remote instructional environment while simultaneously developing scientific literacy skills. In a high enrollment general education animal science course, numerous activities were designed to improve scientific literacy. These included specifically developed videos covering strategies for reading published science literature, the utilization of topically relevant scientific articles that captured student interest, and engaging students in a citizen science exercise on whether dogs align themselves to the Earth's magnetic field during excretion behavior. Employing pre- and post-self-perception surveys coupled with tasking students to apply their scientific literacy skills in an assessment scenario demonstrated that students' self-perception of their scientific literacy improved 30% (P < 0.05) with approximately 80% of students accurately applying their literacy skills. The citizen science study on excretory behavior was modeled on previously published findings thereby providing an opportunity to validate the published work which had indicated that dogs align their bodies in a North-South axis during excretion. The present study did not demonstrate preferential alignment to any geomagnetic orientation which emphasized to the students the need for scientific replication. Inclusion of simple activities that were relevant to students' daily lives, and providing interpretive context for those activities, resulted in improved self-perceived scientific literacy.
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Project description:Sonmat, a citizen-science enabled Kimjang kimchi case study on associations between hand and kimchi microbiota
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Project description:We organized a crowdsourcing experiment in the form of a snapshot sampling campaign to assess the spatial distribution of nitrogen solutes, namely, nitrate, ammonium and dissolved organic nitrogen (DON), in German surface waters. In particular, we investigated (i) whether crowdsourcing is a reasonable sampling method in hydrology and (ii) what the effects of population density, soil humus content and arable land were on actual nitrogen solute concentrations and surface water quality. The statistical analyses revealed a significant correlation between nitrate and arable land (0.46), as well as soil humus content (0.37) but a weak correlation with population density (0.12). DON correlations were weak but significant with humus content (0.14) and arable land (0.13). The mean contribution of DON to total dissolved nitrogen was 22%. Samples were classified as water quality class II or above, following the European Water Framework Directive for nitrate and ammonium (53% and 82%, respectively). Crowdsourcing turned out to be a useful method to assess the spatial distribution of stream solutes, as considerable amounts of samples were collected with comparatively little effort.
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