Understanding social and behavioral drivers and impacts of air quality sensor use

Public engagement with air quality data: using health behaviour change theory to support exposure-minimising behaviours

Exposure to air pollution prematurely kills 7 million people globally every year. Policy measures designed to reduce emissions of pollutants, improve ambient air and consequently reduce health impacts, can be effective, but are generally slow to generate change. Individual actions can therefore supplement policy measures and more immediately reduce people's exposure to air pollution. Air quality indices (AQI) are used globally (though not universally) to translate complex air quality data into a single unitless metric, which can be paired with advice to encourage behaviour change. Here we explore, with reference to health behaviour theories, why these are frequently insufficient to instigate individual change. We examine the health behaviour theoretical steps linking air quality data with reduced air pollution exposure and (consequently) improved public health, arguing that a combination of more 'personalised' air quality data and greater public engagement with these data will together better support individual action. Based on this, we present a novel framework, which, when used to shape air quality interventions, has the potential to yield more effective and sustainable interventions to reduce individual exposures and thus reduce the global public health burden of air pollution.

From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model

The topic of indoor air pollution has yet to receive the same level of attention as ambient pollution. We spend considerable time indoors, and poorer indoor air quality affects most of us, particularly people with respiratory and other health conditions. There is a pressing need for methodological case studies focusing on informing households about the causes and harms of indoor air pollution and supporting changes in behaviour around different indoor activities that cause it. The use of indoor air quality (IAQ) sensor data to support behaviour change is the focus of our research in this paper. We have conducted two studies-first, to evaluate the effectiveness of the IAQ data visualisation as a trigger for the natural reflection capability of human beings to raise awareness. This study was performed without the scaffolding of a formal behaviour change model. In the second study, we showcase how a behaviour psychology model, COM-B (Capability, Opportunity, and Motivation-Behaviour), can be operationalised as a means of digital intervention to support behaviour change. We have developed four digital interventions manifested through a digital platform. We have demonstrated that it is possible to change behaviour concerning indoor activities using the COM-B model. We have also observed a measurable change in indoor air quality. In addition, qualitative analysis has shown that the awareness level among occupants has improved due to our approach of utilising IoT sensor data with COM-B-based digital interventions.

Building the Bridge to a Participatory Citizenship: Curricular Integration of Communal Environmental Issues in School Projects Supported by the Internet of Things

Generally, there is much to praise about the rise in acknowledging the need for young citizens to exercise their rights and duties, but the belief remains that this is not yet entrenched in young citizens' overall democratic involvement. A lack of citizenship and engagement in community issues was revealed by a recent study conducted by the authors in a secondary school from the outskirts of Aveiro, Portugal, during the 2019/2020 school year. Under the umbrella of a Design-Based Research methodological framework, citizen science strategies were implemented in the context of teaching, learning, and assessment, and at the service of the educational project of the target school, in a STEAM approach, and under Domains of Curricular Autonomy activities. The study's findings suggest that to build the bridge for participatory citizenship, teachers should engage students in collecting and analyzing data regarding communal environmental issues in a Citizen Science approach supported by the Internet of Things. The new pedagogies addressing the lack of citizenship and engagement in community issues promoted students' involvement at school and in the community, contributed to inform municipal education policies, and promoted dialogue and communication between local actors.

Addressing systemic problems with exposure assessments to protect the public's health

BACKGROUND

Understanding, characterizing, and quantifying human exposures to environmental chemicals is critical to protect public health. Exposure assessments are key to determining risks to the general population and for specific subpopulations given that exposures differ between groups. Exposure data are also important for understanding where interventions, including public policies, should be targeted and the extent to which interventions have been successful. In this review, we aim to show how inadequacies in exposure assessments conducted by polluting industries or regulatory agencies have led to downplaying or disregarding exposure concerns raised by communities; that underestimates of exposure can lead regulatory agencies to conclude that unacceptable risks are, instead, acceptable, allowing pollutants to go unregulated; and that researchers, risk assessors, and policy makers need to better understand the issues that have affected exposure assessments and how appropriate use of exposure data can contribute to health-protective decisions.

METHODS

We describe current approaches used by regulatory agencies to estimate human exposures to environmental chemicals, including approaches to address limitations in exposure data. We then illustrate how some exposure assessments have been used to reach flawed conclusions about environmental chemicals and make recommendations for improvements.

RESULTS

Exposure data are important for communities, public health advocates, scientists, policy makers, and other groups to understand the extent of environmental exposures in diverse populations. We identify four areas where exposure assessments need to be improved due to systemic sources of error or uncertainty in exposure assessments and illustrate these areas with examples. These include: (1) an inability of regulatory agencies to keep pace with the increasing number of chemicals registered for use or assess their exposures, as well as complications added by use of 'confidential business information' which reduce available exposure data; (2) the failure to keep assessments up-to-date; (3) how inadequate assumptions about human behaviors and co-exposures contribute to underestimates of exposure; and (4) that insufficient models of toxicokinetics similarly affect exposure estimates.

CONCLUSION

We identified key issues that impact capacity to conduct scientifically robust exposure assessments. These issues must be addressed with scientific or policy approaches to improve estimates of exposure and protect public health.

Farmers and Local Residents Collaborate: Application of a Participatory Citizen Science Approach to Characterising Air Quality in a Rural Area in The Netherlands

In rural areas, livestock farming is a source of environmental concern. We describe a citizen science (CS) project in Venray, the Netherlands, where air quality was measured at livestock farms and surrounding residential premises. We used low-cost methods to measure air quality components and facilitated a dialogue between stakeholders about the results and solutions for cleaner air. PM_2.5 and PM₁₀ were measured using Nova Fitness SDS011 sensors, nitrogen dioxide (NO₂) and ammonia (NH₃) using Palmes tubes and odour annoyance was reported. Particulate Matter (PM) concentrations were higher close to layer farms, but elevated concentrations were limited at other farms and residential locations. NO₂ concentrations were elevated near busy roads, and higher NH₃ values were measured near livestock farms. Reporting of odour annoyance was limited, yet during the dialogue residents indicated that this was their largest concern. While both farmers and residents agreed with the general conclusions, they still preferred opposing measures. We conclude that characterisation of air quality using low-cost methods is possible, but expert guidance is needed. Moreover, education, commitment of participants and involvement of independent parties are crucial to ensuring a productive dialogue between stakeholders. The insights gained by participants and resulting dialogue were the greatest benefits of this CS approach.

High Resolution On-Road Air Pollution Using a Large Taxi-Based Mobile Sensor Network

Traffic-related air pollution (TRAP) was monitored using a mobile sensor network on 125 urban taxis in Shanghai (November 2019/December 2020), which provide real-time patterns of air pollution at high spatial resolution. Each device determined concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), and PM2.5, which characterised spatial and temporal patterns of on-road pollutants. A total of 80% road coverage (motorways, trunk, primary, and secondary roads) required 80-100 taxis, but only 25 on trunk roads. Higher CO concentrations were observed in the urban centre, NO2 higher in motorway concentrations, and PM2.5 lower in the west away from the city centre. During the COVID-19 lockdown, concentrations of CO, NO2, and PM2.5 in Shanghai decreased by 32, 31 and 41%, compared with the previous period. Local contribution related to traffic emissions changed slightly before and after COVID-19 restrictions, while changing background contributions relate to seasonal variation. Mobile networks are a real-time tool for air quality monitoring, with high spatial resolution (~200 m) and robust against the loss of individual devices.

Exploring the distributional environmental justice implications of an air quality monitoring network in Los Angeles County

Non-governmental air quality monitoring networks include low-cost, networked air pollution sensors hosted at homes and schools that display real-time pollutant concentration estimates on publicly accessible websites. Such networks can empower people to take health-protective actions, but their unplanned organization may produce an uneven spatial distribution of sensors. Barriers to acquiring sensors may disenfranchise particular social groups. To test this directly, we quantitatively examine if there are social inequalities in the distribution of sensors in a non-governmental air quality monitoring network (PurpleAir) in Los Angeles County, California. We paired sociodemographic data from the American Community Survey and estimates of PM_2.5 concentrations from the USEPA's Downscaler model at the census tract level (n = 2203) with a sensors per capita (SPC) variable, which is based on population proximity to PurpleAir sensors (n = 696) in Los Angeles County. Findings from multivariable generalized estimating equations (GEEs) controlling for clustering by housing age and value reveal patterns of environmental injustice in the distribution of PurpleAir sensors across Los Angeles County census tracts. Tracts with higher percentages of Hispanic/Latino/a and Black residents and lower median household income had decreased SPC. There was a curvilinear (concave) relationship between the percentage of renter-occupants and SPC. Sensors were concentrated in tracts with greater percentages of adults and seniors (vs. children), higher occupied housing density, and higher PM_2.5 pollution. Results reveal social inequalities in the self-organizing PurpleAir network, suggesting another layer of environmental injustice such that residents of low-income and minority neighborhoods have reduced access to information about local air pollution.

Towards the Development of a Sensor Educational Toolkit to Support Community and Citizen Science

As air quality sensors increasingly become commercially available, a deeper consideration of their usability and usefulness is needed to ensure effective application by the public. Much of the research related to sensors has focused on data quality and potential applications. While this information is important, a greater understanding of users’ experience with sensors would provide complementary information. Under a U.S. EPA-funded Science to Achieve Results grant awarded to the South Coast Air Quality Management District in California, titled “Engage, Educate, and Empower California Communities on the Use and Applications of Low-Cost Air Monitoring Sensors”, approximately 400 air quality sensors were deployed with 14 California communities. These communities received sensors and training, and they participated in workshops. Widely varying levels of sensor installation and engagement were observed across the 14 communities. However, despite differences between communities (in terms of participation, demographics, and socioeconomic factors), many participants offered similar feedback on the barriers to sensor use and strategies leading to successful sensor use. Here, we assess sensor use and participant feedback, as well as discuss the development of an educational toolkit titled “Community in Action: A Comprehensive Toolkit on Air Quality Sensors”. This toolkit can be leveraged by future community and citizen science projects to develop networks designed to collect air quality information that can help reduce exposure to and the emissions of pollutants, leading to improved environmental and public health.

Low-Cost Sensors for Air Quality Monitoring - the Current State of the Technology and a Use Overview

In recent years the monitoring of air quality using cheap sensors has become an interesting alternative to conventional analytical techniques. Apart from vast price differences conventional techniques need to be performed by the trained personnel of commercial or research laboratories. Sensors capable of measuring dust, ozone, nitrogen and sulphur oxides, or other air pollutants are relatively simple electronic devices, which are comparable in size to a mobile phone. They provide the general public with the possibility to monitor air quality which can contribute to various projects that differ in regional scale, commercial funding or community-base. In connection with the low price of sensors arises the question of the quality of measured data. This issue is addressed by a number of studies focused on comparing the sensor data with the data of reference measurements. Sensory measurement is influenced by the monitored analyte, type and design of the particular sensor, as well as by the measurement conditions. Currently sensor networks serve as an additional source of information to the network of air quality monitoring stations, where the density of the network provides concentration trends in the area that may exceed specific measured values of pollutant concentrations and low uncertainty of reference measurements. The constant development of all types of sensors is leading to improvements and the difference in data quality between sensors and conventional monitoring techniques may be reduced.

Key Concerns and Drivers of Low-Cost Air Quality Sensor Use

Low-cost sensors are revolutionizing air pollution monitoring by providing real-time, highly localized air quality information. The relatively low-cost nature of these devices has made them accessible to the broader public. Although there have been several fitness-of-purpose appraisals of the various sensors on the market, little is known about what drives sensor usage and how the public interpret the data from their sensors. This article attempts to answer these questions by analyzing the key themes discussed in the user reviews of low-cost sensors on Amazon. The themes and use cases identified have the potential to spur interventions to support communities of sensor users and inform the development of actionable data-visualization strategies with the measurements from such instruments, as well as drive appropriate ‘fitness-of-purpose’ appraisals of such devices.

User-Centred Design of a Final Results Report for Participants in Multi-Sensor Personal Air Pollution Exposure Monitoring Campaigns

Using low-cost portable air quality (AQ) monitoring devices is a growing trend in personal exposure studies, enabling a higher spatio-temporal resolution and identifying acute exposure to high concentrations. Comprehension of the results by participants is not guaranteed in exposure studies. However, information on personal exposure is multiplex, which calls for participant involvement in information design to maximise communication output and comprehension. This study describes and proposes a model of a user-centred design (UCD) approach for preparing a final report for participants involved in a multi-sensor personal exposure monitoring study performed in seven cities within the EU Horizon 2020 ICARUS project. Using a combination of human-centred design (HCD), human-information interaction (HII) and design thinking approaches, we iteratively included participants in the framing and design of the final report. User needs were mapped using a survey (n = 82), and feedback on the draft report was obtained from a focus group (n = 5). User requirements were assessed and validated using a post-campaign survey (n = 31). The UCD research was conducted amongst participants in Ljubljana, Slovenia, and the results report was distributed among the participating cities across Europe. The feedback made it clear that the final report was well-received and helped participants better understand the influence of individual behaviours on personal exposure to air pollution.

Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign

Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended.

Can Air Quality Citizen-Sensors Turn into Clean Air Ambassadors? Insights from a Qualitative Study

While the figure of ambassador is being increasingly called upon in the field of environmental health, its scope remains fuzzy and its success factors have been little studied. This article presents the results of a qualitative study performed over three years on a French citizen-sensor scheme for air quality. The scheme draws on volunteer citizens to measure fine particles by means of micro-sensors. Volunteers are also tasked with raising awareness in their entourage about environmental issues with the aim of changing people's behaviour. We investigated this strategy and sought to identify the conditions that enable citizens to become effective clean air ambassadors. The scheme's intervention logic was first reconstructed and a literature review of similar projects was conducted. Then, three surveys were carried out with the scheme's volunteers. Each survey consisted of an observation of the volunteers' practices and individual interviews (70 in all) in order to understand these citizen-sensors motivations and experiences, and characterize how they fulfilled their role. We concluded that, for citizen sensing, the scope and role of ambassador should be reconsidered insofar as these citizens serve as peer leaders and mediators. In this respect, we try to define the success factors for citizen-sensing-based ambassadors programmes.

On the distribution of low-cost PM2.5 sensors in the US: demographic and air quality associations

BACKGROUND

Low-cost sensors have the potential to democratize air pollution information and supplement regulatory networks. However, differentials in access to these sensors could exacerbate existing inequalities in the ability of different communities to respond to the threat of air pollution.

OBJECTIVE

Our goal was to analyze patterns of deployments of a commonly used low-cost sensor, as a function of demographics and pollutant concentrations.

METHODS

We used Wilcoxon rank sum tests to assess differences between socioeconomic characteristics and PM_2.5 concentrations of locations with low-cost sensors and those with regulatory monitors. We used Kolomogorov-Smirnov tests to examine how representative census tracts with sensors were of the United States. We analyzed predictors of the presence, and number of, sensors in a tract using regressions.

RESULTS

Census tracts with low-cost sensors were higher income more White and more educated than the US as a whole and than tracts with regulatory monitors. For all states except for California they are in locations with lower annual-average PM_2.5 concentrations than regulatory monitors. The existing presence of a regulatory monitor, the percentage of people living above the poverty line and PM_2.5 concentrations were associated with the presence of low-cost sensors in a tract.

SIGNIFICANCE

Strategies to improve access to low-cost sensors in less-privileged communities are needed to democratize air pollution data.

Understanding and Correcting Unwanted Influences on the Signal from Electrochemical Gas Sensors

Humidity- and temperature-dependent errors in concentrations reported by electrochemical sensors for atmospheric nitrogen dioxide significantly limit the reliability of the data. A basic understanding of the source of these errors has been missing. Empirical, software-based corrections are of limited reliability. The sensors feature a 40 wt % (≈4 molal) sulfuric acid electrolyte, and carbon working and quasi-reference (QRE) electrodes. We show that the sensor behaves as a truncated transmission line with resistance and capacitance elements varying with humidity. High-amplitude current fluctuations are due to humidity fluctuations, and are charging currents in response to fluctuations in interfacial capacitance. Baseline currents are due to very small differences in the open-circuit electrode potential between working and reference electrodes. We deduce that acid concentration changes in the meniscus within the porous electrode structure, in response to changes in the ambient temperature and humidity, cause both the capacitance fluctuations and the baseline changes. The open-circuit potential differences driving the baseline current variations are in part due to a difference in the liquid junction potential between the QRE and working electrode, dependent on humidity and temperature and caused by a gradient of acid concentration, and in part due to temperature- and acid-concentration-dependent variations in the rate of the potential-determining reactions. Based on the understanding obtained, we demonstrate a simple hardware change that corrects these unwanted errors.

Can portable air quality monitors protect children from air pollution on the school run? An exploratory study

With air quality issues in urban areas garnering increasing media attention, concerned citizens are beginning to engage with the technology as a means of identifying and responding to the environmental risks posed. However, while much has been written about the accuracy of the units, little research has been conducted into its effects on users. As such, this research deploys coping theory to explore the specific ways in which portable air quality sensors influence user behaviour. This is done using a qualitative exploratory design, targeting parents and carers of children on the school run. Drawing from survey and interview responses, the article illustrates the decision-making pathways underpinning engagement with monitors and the ways in which they influence behaviour and disrupt misconceptions around air pollution. The study demonstrates that personal environmental monitors can play a role in protecting children from air pollution on the school run. They can raise awareness about air pollution and disrupt misconceptions about where does and does not occur. They can also encourage the public to change their behaviour in an attempt to mitigate and manage risks. However, the findings additionally reveal that sensor technology does not generate a simple binary response among users, of behavioural change or not. When attempts at behavioural change fail to reduce risk, resulting negative feelings can lead to inaction. Hence, the relationship between the technology and the individual is entwined with various social circumstances often beyond a parent or carer's control. Thus, top-down support aimed at tackling air pollution at source is essential if this bottom-up technology is to fulfil its full potential.

Community-Engaged Air Monitoring to Build Resilience Near the US-Mexico Border

Initiated in response to community concerns about high levels of air pollution and asthma, the Imperial County Community Air Monitoring Project was conducted as a collaboration between a community-based organization, a non-governmental environmental health program, and academic researchers. This community-engaged research project aimed to produce real-time, community-level air quality information through the establishment of a community air monitoring network (CAMN) of 40 low-cost particulate matter (PM) monitors in Imperial County, California. Methods used to involve the community partner organization and residents in the development, operation, and use of the CAMN included the following: (1) establishing equitable partnerships among the project collaborators; (2) forming a community steering committee to guide project activities; (3) engaging residents in data collection to determine monitor sites; (4) providing hands-on training to assemble and operate the air monitors; (5) conducting focus groups to guide display and dissemination of monitoring data; and (6) conducting trainings on community action planning. This robust community engagement in the project resulted in increased awareness, knowledge, capacity, infrastructure, and influence for the community partner organization and among community participants. Even after the conclusion of the original research grant funding for this project, the CAMN continues to be operated and sustained by the community partner, serving as a community resource used by residents, schools, researchers, and others to better understand and address air pollution and its impacts on community health, while strengthening the ability of the community to prepare for, respond to, and recover from harmful air pollution.

Out of sight, out of mind: participatory sensing for monitoring indoor air quality

In southern Chile, epidemiological studies have linked high levels of air pollution produced by the use of wood-burning stoves with the incidence of numerous diseases. Using a quasi-experimental design, this study explores the potential of participatory sensing strategies to transform experiences, perceptions, attitudes, and daily routine activities in 15 households equipped with wood-burning stoves in the city of Temuco, Chile. The results suggest that the experience of using a low-cost sensor improves household members' awareness levels of air pollution. However, the information provided by the sensors does not seem to improve the participants' self-efficacy to control air quality and protect themselves from pollution. The high degree of involvement with the participatory sensing experience indicates that the distribution of low-cost sensors could be a key element in the risk communication policies.

Youth Engaged Participatory Air Monitoring: A 'Day in the Life' in Urban Environmental Justice Communities

Air pollution in Southern California does not impact all communities equally; communities of color are disproportionately burdened by poor air quality and more likely to live near industrial facilities and freeways. Government regulatory monitors do not have the spatial resolution to provide air quality information at the neighborhood or personal scale. We describe the A Day in the Life program, an approach to participatory air monitoring that engages youth in collecting data that they can then analyze and use to take action. Academics partnered with Los Angeles-based youth environmental justice organizations to combine personal air monitoring, participatory science, and digital storytelling to build capacity to address local air quality issues. Eighteen youth participants from four different neighborhoods wore portable personal PM2.5 (fine particles <2.5 µm in diameter) monitors for a day in each of their respective communities, documenting and mapping their exposure to PM2.5 during their daily routine. Air monitoring was coupled with photography and videos to document what they experienced over the course of their day. The PM2.5 exposure during the day for participants averaged 10.7 µg/m3, although the range stretched from <1 to 180 µg/m3. One-third of all measurements were taken <300 m from a freeway. Overall, we demonstrate a method to increase local youth-centered understanding of personal exposures, pollution sources, and vulnerability to air quality.

Institutional insights on integrating social and environmental science for solutions-driven research

Solving complex environmental problems requires interdisciplinary research involving the social and environmental sciences. The U.S. Environmental Protection Agency is working toward solutions-driven research and interdisciplinary integration within its Office of Research and Development. This article details the history of this process and discusses lessons learned from other federal agencies seeking to integrate social and biophysical research: finding the right combination of top down and bottom up approaches; balancing objectives of advancing science and/or supporting programmatic operations; using social science methods to inform the process; and engaging multiple stakeholders. Attention to the social context of scientific practice, including research processes and research use, fosters success. Three strategies for integrating social sciences to support solutions-driven environmental research are: weaving social science throughout the research process, strengthening social networks, and fostering interdisciplinary hubs. Integration into planning and carrying out research has greater transformative potential than integration into product development and distribution. This article provides insights into institutional considerations for advancing interdisciplinarity and the social context of scientific practice in government agencies. It illustrates the multiple decision contexts and inclusion of social science at the science-policy interface.

The aggravation of urban air quality deterioration due to urbanization, transportation and economic development - Panel models with marginal effect analyses across China

In this paper, panel data models are established to examine the impacts of urban construction, transport facilities, and economic development on the urban air quality. Combined with data from different tiers of Chinese cities for two time series, 2010 and 2015, the variable-intercept model (VIM) is used to determine the parameters and significance of each independent variable. The marginal effects of different categories of independent variables (urbanization, transportation and economy) on the urban air quality are also studied with regard to the results of different VIMs. The results show that transportation factors (such as annual passenger trips, bus numbers and taxi numbers) have the most significant effects on the air quality for all the Chinese cities. Moreover, urbanized area and annual gross value of industrial output also have prominent impacts on the air quality across China. In addition, the marginal effects of the air quality index obtained via VIMs with classified local variables reflect that the influences of urbanization, transportation and economy on urban air quality are substantially different among different tiers of cities. Therefore, based on the findings, we propose measures to improve air quality for different tiers of cities, such as rational use of space resources, optimizing transport modes, and encouraging carpooling.

Testing the performance of sensors for ozone pollution monitoring in a citizen science approach

Tropospheric ozone (O₃) is an environmental pollutant of growing concern, especially in suburban and rural areas where the density of air quality monitoring stations is not high. In this type of areas citizen science strategies can be useful tools for awareness raising, but sensor technologies must be validated before sensor data are communicated to the public. In this work, the performance under field conditions of two custom-made types of ozone sensing devices, based on metal-oxide and electrochemical sensors, was tested. A large array of 132 metal-oxide (Sensortech MICS 2614) and 11 electrochemical (Alphasense) ozone sensors, built into 44 sensing devices, was co-located at reference stations in Italy (4 stations) and Spain (5). Mean R² between sensor and reference data was 0.88 (0.78-0.96) and 0.89 (0.73-0.96) for Captor (metal-oxide) and Raptor (electrochemical) nodes. The metal-oxide sensors showed an upper limit (approximately 170 μg/m³) implying that these sensors may be useful to communicate mean ozone concentrations but not peak episodes. The uncertainty of the nodes was 10% between 100 and 150 μg/m³ and 20% between 150 and 200 μg/m³, for Captors, and 10% for >100 μg/m³ for Raptors. Operating both types of nodes up to 5 months did not evidence any clear influence of drifts. The use of these sensors in citizen science can be a useful tool for awareness raising. However, significant data processing efforts are required to ensure high data quality, and thus machine learning strategies are advisable. Relative uncertainties should always be reported when communicating ozone concentration data from sensing nodes.

Scientific Landscape of Citizen Science Publications: Dynamics, Content and Presence in Social Media

Citizen science (CS) aims primarily to create a new scientific culture able to improve upon the triple interaction between science, society, and policy in the dual pursuit of more democratic research and decision-making informed by sound evidence. It is both an aim and an enabler of open science (OS), to which it contributes by involving citizens in research and encouraging participation in the generation of new knowledge. This study analyses scientific output on CS using bibliometric techniques and Web of Science (WoS) data. Co-occurrence maps are formulated to define subject clusters as background for an analysis of the impact of each on social media. Four clusters are identified: HEALTH, BIO, GEO and PUBLIC. The profiles for the four clusters are observed to be fairly similar, although BIO and HEALTH are mentioned more frequently in blogposts and tweets and BIO and PUBLIC in Facebook and newsfeeds. The findings also show that output in the area has grown since 2010, with a larger proportion of papers (66%) mentioned in social media than reported in other studies. The percentage of open access documents (30.7%) is likewise higher than the overall mean for all areas.

Impact of Multi-Sensor Technology for Enhancing Global Security in Closed Environments Using Cloud-Based Resources

By nature, some jobs are always in closed environments and employees may stay for long periods. This is the case for many professional activities such as military watch tours of borders, civilian buildings and facilities that need efficient control processes. The role assigned to personnel in such environments is usually sensitive and of high importance, especially in terms of security and protection. With this in mind, we proposed in our research a novel approach using multi-sensor technology to monitor many safety and security parameters including the health status of indoor workers, such as those in watchtowers and at guard posts. In addition, the data gathered for those employees (heart rate, temperature, eye movement, human motion, etc.) combined with the room’s sensor data (temperature, oxygen ratio, toxic gases, air quality, etc.) were saved by appropriate cloud services, which ensured easy access to the data without ignoring the privacy protection aspect of such critical material. This information can be used later by specialists to monitor the evolution of the worker’s health status as well as its cost-effectiveness, which gives the possibility to improve productivity in the workplace and general employee health.

Development of an in-home, real-time air pollutant sensor platform and implications for community use

Air pollution exposure characterization has been shaped by many constraints. These include technologies that lead to insufficient coverage across space and/or time in order to characterize individual or community-level exposures with sufficient accuracy and precision. However, there is now capacity for continuous monitoring of many air pollutants using comparatively inexpensive, real-time sensors. Crucial questions remain regarding whether or not these sensors perform adequately for various potential end uses and whether performance varies over time or across ambient conditions. Performance scrutiny of sensors via lab- and field-testing and calibration across their lifetime is necessary for interpretation of data, and has important implications for end users including cost effectiveness and ease of use. We developed a comparatively lower-cost, portable, in-home air sampling platform and a guiding development and maintenance workflow that achieved our goal of characterizing some key indoor pollutants with high sensitivity and reasonable accuracy. Here we describe the process of selecting, validating, calibrating, and maintaining our platform - the Environmental Multi-pollutant Monitoring Assembly (EMMA) - over the course of our study to-date. We highlight necessary resources and consider implications for communities or researchers interested in developing such platforms, focusing on PM_2.5, NO, and NO₂ sensors. Our findings emphasize that lower-cost sensors should be deployed with caution, given financial and resource costs that greatly exceed sensor costs, but that selected community objectives could be supported at lesser cost and community-based participatory research strategies could be used for more wide-ranging goals.

End-User Feedback on a Low-Cost Portable Air Quality Sensor System-Are We There Yet?

Low-cost sensors are a current trend in citizen science projects that focus on air quality. Until now, devices incorporating such sensors have been tested primarily for their technical capabilities and limitations, whereas their usability and acceptability amongst the public rarely goes beyond proof of concept, leaving user experience (UX) unstudied. The authors argue that UX should be taken into account to make sure that products and services are fit for purpose. Nineteen volunteers tested and evaluated a prototype device and provided feedback through semi-structured interviews and during focus group sessions. Their UX was then coded using mixed coding methods regarding device functionality and recommendations for future product development. The results indicate that UX can identify potentially problematic design aspects while giving deeper insights into user needs. For example, UX recognized that one of the most important aspects of user involvement and motivation was successful data harvesting, which frequently failed. This study recommends that future developers of low-cost portable air quality sensor systems prioritize reliable data transmission to minimize data loss. This will ensure an efficient and positive UX that supports user engagement in citizen science based research where collecting sensor-based data is the primary objective.