Community-based participatory research for the study of air pollution: a review of motivations, approaches, and outcomes

Supporting knowledge justice through community science air quality monitoring and a reciprocal reporting process

In community science on air quality, low-cost air monitors have emerged as an opportunity to democratize data reporting and support knowledge justice by providing participants with instantaneous access to air quality data. In this study, we equipped residents in four environmental justice communities in North Denver with low-cost air monitors to collect real-time air quality data for four separate 30-day field deployments over two years. We conceptualize an improvement to conventional report-back processes by suggesting a 3-part approach - a reciprocal reporting process that includes 1) bidirectional open channels of communication with participants, 2) democratized data access via instant monitor data and written data summaries, and 3) responsive intervention opportunities to respond in real-time to participants air quality concerns. Through 120 interviews with 30 air quality monitor users after each of the four field deployments, we identify how this reciprocal reporting process increased Air Quality (AQ) awareness and supported distinct modes of environmental learning, which we term data-driven, health-conscious, and progressive logics of inquiry. In addition, this non-prescriptive approach centered participants' alternative ways of knowing, such as sensory experiences to understand pollution exposure, and fostered collective learning that ultimately furthered knowledge justice. Our study highlights the potential for a more robust and holistic approach to report-back processes within community science projects to foster flexibility, reciprocity, and responsiveness.

Exposure assessment for air pollution epidemiology: A scoping review of emerging monitoring platforms and designs

BACKGROUND

Both exposure monitoring and exposure prediction have played key roles in assessing individual-level long-term exposure to air pollutants and their associations with human health. While there have been notable advances in exposure prediction methods, improvements in monitoring designs are also necessary, particularly given new monitoring paradigms leveraging low-cost sensors and mobile platforms.

OBJECTIVES

We aim to provide a conceptual summary of novel monitoring designs for air pollution cohort studies that leverage new paradigms and technologies, to investigate their characteristics in real-world examples, and to offer practical guidance to future studies.

METHODS

We propose a conceptual summary that focuses on two overarching types of monitoring designs, mobile and non-mobile, as well as their subtypes. We define mobile designs as monitoring from a moving platform, and non-mobile designs as stationary monitoring from permanent or temporary locations. We only consider non-mobile studies with cost-effective sampling devices. Then we discuss similarities and differences across previous studies with respect to spatial and temporal representation, data comparability between design classes, and the data leveraged for model development. Finally, we provide specific suggestions for future monitoring designs.

RESULTS

Most mobile and non-mobile monitoring studies selected monitoring sites based on land use instead of residential locations, and deployed monitors over limited time periods. Some studies applied multiple design and/or sub-design classes to the same area, time period, or instrumentation, to allow comparison. Even fewer studies leveraged monitoring data from different designs to improve exposure assessment by capitalizing on different strengths. In order to maximize the benefit of new monitoring technologies, future studies should adopt monitoring designs that prioritize residence-based site selection with comprehensive temporal coverage and leverage data from different designs for model development in the presence of good data compatibility.

DISCUSSION

Our conceptual overview provides practical guidance on novel exposure assessment monitoring for epidemiological applications.

The promise and pitfalls of community-based monitoring with a focus on Canadian examples

Community-based monitoring (CBM) is a widely used form of scientific data collection in which local community members directly participate in ecosystem research and also help the process by sharing traditional ecological knowledge and local understanding of land and resources. This paper presents a review of the challenges and opportunities associated with CBM projects in Canada and internationally. While Canadian cases are the primary focus, international examples are drawn on to provide additional context. Based on our review of 121 documents and publications, we found that CBM helps fill science research gaps by providing access to continuous data sets on the ecosystems being studied. CBM also increases the credibility of the data among users, as the community itself takes part in the environmental monitoring process. CBM supports cross-cultural learning and the co-production of knowledge by using traditional ecological knowledge with science, thereby enabling researchers, scientists and community members to learn from one another. Our review suggests that although there are multiple successes, CBM faces several challenges that constrain its progress including funding shortages, lack of support for local stewardship, and inadequate training for local users in the operation of equipment and data collection methods. Data sharing and rights on the use of data are also constraining to the long-term success of CBM programs.

Assessment of trace elements directly from archived total suspended particulate filters by laser ablation ICP-MS: A case study of South Carolina

Background

Exposure to particulate air pollution is one of the greatest environmental risk factors for adverse human health outcomes. However, the constituents that may be responsible for such adverse health effects have not been fully studied.

Methods

Total suspended particulates filters collected every 6 days in 2011 from three South Carolina locations were used in this case study. An inductively coupled plasma mass spectrometer interfaced with a laser ablation system (LA-ICP-MS) was used to directly analyze 41 inorganic elemental species on air pollution filters. Then, machine learning and multivariate statistical methods was employed to identify combinatorial patterns in the data and classify sites based on their elemental composition.

Results

Forty-one elements were assessed and 33 were used in subsequent analysis. Correlations between United States Environmental Protection Agency (US EPA)'s chemical analysis dataset and data from the current study revealed significant associations between 7/15 elements with enough variation for comparison (r between 0.28 to 0.66, p<0.05). Subsequent multivariate analyses revealed four distinct patterns in the distribution of elements by sample location throughout the year.

Conclusion

The different airborne elements may need to be assessed to understand combinations of elements which occur together over space and/or time. Such information can be helpful in planning effective counter measures and strategies to control particulate air pollution.

Perceptions and experiences of environmental health and risks among Latina mothers in urban Los Angeles, California, USA

BACKGROUND

Environmental exposures during pregnancy and early childhood can have acute and chronic adverse health impacts. As minoritized populations are more likely to reside in areas with greater pollution, it is important to understand their views and lived experiences to inform action. The purpose of this community-driven qualitative research study was to understand how urban Latina mothers in Los Angeles County, California perceived environmental health and risks.

METHODS

We conducted semi-structured individual interviews with Latina pregnant women and mothers of young children, recruited through existing collaborations with community organizations. Interviews conducted in either English or Spanish and were coded inductively according to a modified grounded theory approach.

RESULTS

Thirty-six Latina mothers completed interviews between August-October 2016. Participants lived primarily in low-income communities of South-Central Los Angeles and East Los Angeles. We identified three major themes based on the participants' responses during interviews: Defining the Environment, Environment & Health Risks, and Social & Political Responsibility. Women defined their environment in terms of both "nature" and "hazards." They consistently identified foul odors, dirtiness, noise, trash, bugs, smoke, and other visible blights as indicators of household and neighborhood environmental hazards. They expressed fear and uncertainty about how their environment could affect their health and that of their children, as well as specific concerns about respiratory health, asthma, allergies, cancer, and adverse pregnancy outcomes. Mothers often changed individual behaviors around diet and cleaning during pregnancy but were frustrated by power imbalances that left them unable to change their home or neighborhood environments, despite their desire to do so.

DISCUSSION

Our study is among the first to describe how urban Latina mothers perceive and experience environmental health risks during pregnancy and early childhood. Our research suggests additional attention is needed by public health professionals and researchers to address the environmental health risks that matter most to urban Latina mothers. They also highlight the tension that many urban Latina mothers feel between wanting to protect their families' health and well-being and feeling powerless to change their environment. Broad policy changes, rather than additional individual recommendations, are needed to address the concerns of this vulnerable population.

Engaging communities in addressing air quality: a scoping review

BACKGROUND

Exposure to air pollution has a detrimental effect on health and disproportionately affects people living in socio-economically disadvantaged areas. Engaging with communities to identify concerns and solutions could support organisations responsible for air quality control, improve environmental decision-making, and widen understanding of air quality issues associated with health. This scoping review aimed to provide an overview of approaches used to engage communities in addressing air quality and identify the outcomes that have been achieved.

METHODS

Searches for studies that described community engagement in air quality activities were conducted across five databases (Academic Search Complete, CABI, GreenFILE, MEDLINE, Web of Science). Data on study characteristics, community engagement approach, and relevant outcomes were extracted. The review process was informed by a multi-stakeholder group with an interest in and experience of community engagement in air quality. Thirty-nine papers from thirty studies were included in the final synthesis.

CONCLUSION

A range of approaches have been used to engage communities in addressing air quality, most notably air quality monitoring. Positive outcomes included increased awareness, capacity building, and changes to organisational policy and practice. Longer-term projects and further exploration of the impact of community engagement on improving air quality and health are needed as reporting on these outcomes was limited.

Design and development of an open-source framework for citizen-centric environmental monitoring and data analysis

Cities around the world are struggling with environmental pollution. The conventional monitoring approaches are not effective for undertaking large-scale environmental monitoring due to logistical and cost-related issues. The availability of low-cost and low-power Internet of Things (IoT) devices has proved to be an effective alternative to monitoring the environment. Such systems have opened up environment monitoring opportunities to citizens while simultaneously confronting them with challenges related to sensor accuracy and the accumulation of large data sets. Analyzing and interpreting sensor data itself is a formidable task that requires extensive computational resources and expertise. To address this challenge, a social, open-source, and citizen-centric IoT (Soc-IoT) framework is presented, which combines a real-time environmental sensing device with an intuitive data analysis and visualization application. Soc-IoT has two main components: (1) CoSense Unit—a resource-efficient, portable and modular device designed and evaluated for indoor and outdoor environmental monitoring, and (2) exploreR—an intuitive cross-platform data analysis and visualization application that offers a comprehensive set of tools for systematic analysis of sensor data without the need for coding. Developed as a proof-of-concept framework to monitor the environment at scale, Soc-IoT aims to promote environmental resilience and open innovation by lowering technological barriers.

Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure

BACKGROUND

Due to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure.

OBJECTIVES

The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income.

METHODS

This review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents).

RESULTS

From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 μg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources.

CONCLUSION

This review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.

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.

Air quality monitoring and measurement in an urban airshed: Contextualizing datasets from the Detroit Michigan area from 1952 to 2020

With urban air quality being a pressing public health concern, community members are becoming increasingly engaged in determining the links between air quality and human health. Although new measurement tools such as low-cost sensors make local data more accessible, a better understanding of gaps in regional datasets is needed to develop effective metropolitan-scale solutions. Using scoping review methodology, we compiled 214 published journal articles and grey literature reports of air quality data from the Detroit, Michigan area from 1952 through 2020. This critical scoping review focuses on air quality datasets, but related topics such as health studies and community-based participatory science studies were examined from the included articles. Most of these publications were peer-reviewed journal articles published after 2001. Particulate matter, nitrous oxides, and sulfur dioxide were the most commonly studied air pollutants, and asthma was the most frequently associated health outcome paired with air pollution datasets. Few publications reported methods for community-based participatory science. This critical scoping review establishes a foundation of historical air quality data for the Detroit metropolitan area and a set of evaluation criteria that can be replicated in other urban centers. This foundation enables future detailed analysis of air quality datasets and showcases strategies for implementing effective community science programs and monitoring efforts.

Community-Engaged Use of Low-Cost Sensors to Assess the Spatial Distribution of PM2.5 Concentrations across Disadvantaged Communities: Results from a Pilot Study in Santa Ana, CA

PM_2.5 is an air pollutant that is widely associated with adverse health effects, and which tends to be disproportionately located near low-income communities and communities of color. We applied a community-engaged research approach to assess the distribution of PM_2.5 concentrations in the context of community concerns and urban features within and around the city of Santa Ana, CA. Approximately 183 h of one-minute average PM_2.5 measurements, along with high-resolution geographic coordinate measurements, were collected by volunteer community participants using roughly two dozen low-cost AtmoTube Pro air pollution sensors paired with real-time GPS tracking devices. PM_2.5 varied by region, time of day, and month. In general, concentrations were higher near the city’s industrial corridor, which is an area of concern to local community members. While the freeway systems were shown to correlate with some degree of elevated air pollution, two of four sampling days demonstrated little to no visible association with freeway traffic. Concentrations tended to be higher within socioeconomically disadvantaged communities compared to other areas. This pilot study demonstrates the utility of using low-cost air pollution sensors for the application of community-engaged study designs that leverage community knowledge, enable high-density air monitoring, and facilitate greater health-related awareness, education, and empowerment among communities. The mobile air-monitoring approach used in this study, and its application to characterize the ambient air quality within a defined geographic region, is in contrast to other community-engaged studies, which employ fixed-site monitoring and/or focus on personal exposure. The findings from this study underscore the existence of environmental health inequities that persist in urban areas today, which can help to inform policy decisions related to health equity, future urban planning, and community access to resources.

Co-creating a local environmental epidemiology study: the case of citizen science for investigating air pollution and related health risks in Barcelona, Spain

BACKGROUND

While the health risks of air pollution attract considerable attention, both scholarly and within the general population, citizens are rarely involved in environmental health research, beyond participating as data subjects. Co-created citizen science is an approach that fosters collaboration between scientists and lay people to engage the latter in all phases of research. Currently, this approach is rare in environmental epidemiology and when co-creation processes do take place, they are often not documented. This paper describes the first stages of an ongoing co-created citizen science epidemiological project in Barcelona (Spain), that included identifying topics that citizens wish to investigate as regards air pollution and health, formulating their concerns into research questions and co-designing the study protocol. This paper also reflects key trade-offs between scientific rigor and public engagement and provides suggestions to consider when applying citizen science to environmental health studies.

METHODS

Experts created an online survey and analyzed responses with descriptive statistics and qualitative coding. A pop-up intervention was held to discuss with citizens their concerns about air pollution and health. Later on, a community meeting was organized to narrow down the research topics and list potential research questions. In an online survey, citizens were asked to vote for the research question they would like to investigate with the experts. A workshop was held to choose a study design in which citizens would like to partake to answer their preferred research question.

RESULTS

According to 488 respondents from the first survey, cognitive and mental health were the main priorities of investigation. Based on the second survey, with 27% of the votes from 556 citizens, the most popular research question was, "How does air pollution together with noise and green/blue spaces affect mental health?". The study design selected was an observational study in which citizens provide daily repeated measures of different cognitive and mental health outcomes and relate them to the air pollution concentrations.

CONCLUSIONS

Based on the co-creation activities and the results obtained, we conclude that applying citizen science in an environmental health project is valuable for researchers despite some challenges such as engaging citizens and maximizing representativity.

Vayu: An Open-Source Toolbox for Visualization and Analysis of Crowd-Sourced Sensor Data

Recent advances in sensor technology and the availability of low-cost and low-power sensors have changed the air quality monitoring paradigm. These sensors are being widely used by scientists and citizens for monitoring air quality at finer spatial-temporal resolution. Such practices are opening up opportunities to enhance the traditional monitoring networks, but at the same time, these sensors are producing large data sets that can become overwhelming and challenging when it comes to the scientific tools and skills required to analyze the data. To address this challenge, an open-source, robust, and cross-platform sensor data analysis toolbox called Vayu is developed that allows researchers and citizens to do detailed and reproducible analyses of air quality data. Vayu combines the power of visualization and statistical analysis using a simple and intuitive graphical user interface. Additionally, it offers a comprehensive set of tools for systematic analysis such as data conversion, interpolation, aggregation, and prediction. Even though Vayu was developed with air quality research in mind, it can be used to analyze different kinds of time-series data.

"I am an air quality scientist"- Using citizen science to characterise school children's exposure to air pollution

Children are particularly vulnerable to the harmful effects of air pollution. To tackle this issue and implement effective strategies to reduce child exposure, it is important to understand how children are exposed to this risk. This study followed a citizen science approach to air pollution monitoring, aiming to characterise school children's exposure to air pollution and to analyse how a citizen science approach to data collection could contribute to and enhance the research process. 258 children across five London primary schools attended air pollution education sessions and measured air pollution for a week using backpacks with built-in air quality sensors. Children received a summary of the results, advice and information on how to reduce exposure to air pollution. Data on the impact of the approach on the school community were collected using surveys and focus groups with children and their parents and interviews with the teachers involved. The unique data set obtained permitted us to map different routes and modes of transport used by the children and quantify different exposure levels. We identified that, on average, children were exposed to higher levels of air pollution when travelling to and from school, particularly during the morning journey where air pollution levels were on average 52% higher than exposures at school. Children who walked to and from school through busy main roads were exposed to 33% higher levels of air pollution than those who travelled through back streets. The findings from this study showed that using a citizen science approach to data collection, where children are actively involved in the research process, not only facilitated the gathering of a large data set by encouraging participation and stimulating adherence with the study protocol, but also increased children's awareness of air pollution, encouraging them to adopt positive behaviour changes to reduce their exposure.

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.

Towards a Transdisciplinary Theoretical Framework of Citizen Science: Results from a Meta-Review Analysis

This work intends to lay the foundations for a theoretical framework of citizen science combining social and organizational implications with the support of information technologies. The proposed theoretical framework moves towards a shared and common research process between experts and citizens to deal with environmental and social challenges. The role and capacity of online communities is explored and their engagement capacity by means of web-based digital platforms supporting crowdsourcing activities. In this contribution, authors highlight the most common practices, methods and issues of citizen science approaches adopted from multidisciplinary application fields to obtain insights for designing a new participative approach for organizational studies. To reach this goal, authors illustrate the results of a systematic meta-review analysis, consisting of an accurate selection and revision of journal review articles in order to highlight concepts, methods, research design approaches and tools adopted in citizen science approaches.

Connecting Top-Down and Bottom-Up Approaches in Environmental Observing

Effective responses to rapid environmental change rely on observations to inform planning and decision-making. Reviewing literature from 124 programs across the globe and analyzing survey data for 30 Arctic community-based monitoring programs, we compare top-down, large-scale program driven approaches with bottom-up approaches initiated and steered at the community level. Connecting these two approaches and linking to Indigenous and local knowledge yields benefits including improved information products and enhanced observing program efficiency and sustainability. We identify core principles central to such improved links: matching observing program aims, scales, and ability to act on information; matching observing program and community priorities; fostering compatibility in observing methodology and data management; respect of Indigenous intellectual property rights and the implementation of free, prior, and informed consent; creating sufficient organizational support structures; and ensuring sustained community members’ commitment. Interventions to overcome challenges in adhering to these principles are discussed.

Estimating hourly PM2.5 concentrations at the neighborhood scale using a low-cost air sensor network: A Los Angeles case study

Predicting PM_2.5 concentrations at a fine spatial and temporal resolution (i.e., neighborhood, hourly) is challenging. Recent growth in low cost sensor networks is providing increased spatial coverage of air quality data that can be used to supplement data provided by monitors of regulatory agencies. We developed an hourly, 500 × 500 m gridded PM_2.5 model that integrates PurpleAir low-cost air sensor network data for Los Angeles County. We developed a quality control scheme for PurpleAir data. We included spatially and temporally varying predictors in a random forest model with random oversampling of high concentrations to predict PM_2.5. The model achieved high prediction accuracy (10-fold cross-validation (CV) R² = 0.93, root mean squared error (RMSE) = 3.23 μg/m³; spatial CV R² = 0.88, spatial RMSE = 4.33 μg/m³; temporal CV R² = 0.90, temporal RMSE = 3.85 μg/m³). Our model was able to predict spatial and diurnal patterns in PM_2.5 on typical weekdays and weekends, as well as non-typical days, such as holidays and wildfire days. The model allows for far more precise estimates of PM_2.5 than existing methods based on few sensors. Taking advantage of low-cost PM_2.5 sensors, our hourly random forest model predictions can be combined with time-activity diaries in future studies, enabling geographically and temporally fine exposure estimation for specific population groups in studies of acute air pollution health effects and studies of environmental justice issues.

Participatory Research for Environmental Justice: A Critical Interpretive Synthesis

BACKGROUND

Environmental health risks are disproportionately colocated with communities in poverty and communities of color. In some cases, participatory research projects have effectively addressed structural causes of health risk in environmental justice (EJ) communities. However, many such projects fail to catalyze change at a structural level.

OBJECTIVES

This review employs Critical Interpretive Synthesis (CIS) to theorize specific elements of participatory research for environmental health that effectively prompt structural change in EJ communities.

METHODS

Academic database search was used to identify peer-reviewed literature describing participatory research with EJ communities to address environmental health. Synthetic constructs were developed iteratively related to study characteristics, design elements, and outcomes; and data were extracted for included records. Statistical analyses were performed to assess correlations between study design elements and structural change outcomes. Through critical, comparative, and contextual analyses of the "structural change" case study group and "non- structural change" group, informed by relevant theoretical literature, a synthesizing argument was generated.

RESULTS

From 505 total records identified, eligibility screening produced 232 case study articles, representing 154 case studies, and 55 theoretical articles for synthesis. Twenty-six case studies resulted in a structural change outcome. The synthesizing argument states that participatory research with EJ communities may be more likely to result in structural change when a) community members hold formal leadership roles; b) project design includes decision-makers and policy goals; and c) long term partnerships are sustained through multiple funding mechanisms. The assumption of EJ community benefit through research participation is critically examined.

DISCUSSION

Recommended future directions include establishing structural change as a goal of participatory research, employing participatory assessment of community benefit, and increased hiring of faculty of color at research institutions. The power, privilege, and political influence that academic institutions are able to leverage in partnership with EJ communities may be as valuable as the research itself. https://doi.org/10.1289/EHP6274.

Crowdsourcing without Data Bias: Building a Quality Assurance System for Air Pollution Symptom Mapping

Crowdsourcing is one of the spatial data sources, but due to its unstructured form, the quality of noisy crowd judgments is a challenge. In this study, we address the problem of detecting and removing crowdsourced data bias as a prerequisite for better-quality open-data output. This study aims to find the most robust data quality assurance system (QAs). To achieve this goal, we design logic-based QAs variants and test them on the air quality crowdsourcing database. By extending the paradigm of urban air pollution monitoring from particulate matter concentration levels to air-quality-related health symptom load, the study also builds a new perspective for citizen science (CS) air quality monitoring. The method includes the geospatial web (GeoWeb) platform as well as a QAs based on conditional statements. A four-month crowdsourcing campaign resulted in 1823 outdoor reports, with a rejection rate of up to 28%, depending on the applied. The focus of this study was not on digital sensors’ validation but on eliminating logically inconsistent surveys and technologically incorrect objects. As the QAs effectiveness may depend on the location and society structure, that opens up new cross-border opportunities for replication of the research in other geographical conditions.

Relevance of Community-Based Participatory Research in Community Medicine Training

Community-based participatory research (CBPR) is an approach in which researchers undertake research in partnership with those affected by the issue being studied, for the purpose of taking action or effecting social change. It can also incorporate those who will use the results to change practice and inform policy. The practice of CBPR is primarily focused on “Knowledge for Change.” Most research projects in such CBPR partnerships are funded through the academic partners. In many situations, academic and professional researcher institutions and researchers find it difficult to share the information and resources or to directly engage with local community and other local stakeholders. In practice, finding an intermediary partner who has good rapport with local community and local government can be very effective. While there are good initiatives in selected medical colleges for community orientation of medical undergraduates and postgraduates in community medicine, these are not immersive enough to cause an attitudinal change. It is time that we exposed our graduates and postgraduates to CBPR concepts and practice.

A primary school driven initiative to influence commuting style for dropping-off and picking-up of pupils

The use of cars for drop-off and pick-up of pupils from schools is a potential cause of pollution hotspots at school premises. Employing a joint execution of smart sensing technology and citizen science approach, a primary school took an initiative to co-design a study with local community and researchers to generate data and provide information to understand the impact on pollution levels and identify possible mitigation measures. This study was aimed to assess the hotspots of vehicle-generated particulate matter ≤2.5 μm (PM_2.5) and ≤10 μm (PM₁₀) at defined drop-off/pick-up points and its ingress into a nearby naturally ventilated primary school classroom. Five different locations were selected inside school premises for measurements during two peak hours: morning (MP; 0730-0930 h; local time), evening (EP; 1400-1600 h), and off-peak (OP; 1100-1300 h) hours for comparison. These represent PM measurements at the main road, pick-up point at the adjoining road, drop-off point, a classroom, and the school playground. Additional measurements of carbon dioxide (CO₂) were taken simultaneously inside and outside (drop-off point) the classroom to understand its build-up and ingress of outdoor PM. The results demonstrated nearly a three-fold increase in the concentrations of fine particles (PM_2.5) during drop-off hours compared to off-peak hours indicated the dominant contribution of car queuing in the school premises. Coarse particles (PM_2.5-10) were prevalent in the school playground, while the contribution of fine particles as a result of traffic congestion became more pronounced during drop-off hours. In the naturally ventilated classroom, the changes in indoor PM_2.5 concentrations during both peak hours (0.58 < R² < 0.67) were followed by the outdoor concentration at the drop-off point. This initiative resulted in valuable information that might be used to influence school commuting style and raise other important issues such as the generally fairly high PM_2.5 concentrations in the playground and future classroom ventilation plans.

Best Practices for Community-Engaged Research with Pacific Islander Communities in the US and USAPI: A Scoping Review

This scoping review identifies the best practices of community-based participatory research with Pacific Islanders in the United States and United States Affiliated Pacific Islands. Eighty-four articles from January 2000 to December 2017 were included in the review. Best practices included the importance of engaging Pacific Islander community leaders as research staff, community co-investigators, and community advisory board members. Best practices also focused on removing barriers to research by using participants' native languages, conducting research within the geographic community, and spending significant time to build trust. Novel best practices included honoring Pacific Islanders' cultural practices such as protocols for engagement, reciprocity, and social and spiritual inclusiveness and honoring Pacific Islanders' collectivist cultural structure. The goal of this scoping review is to aid community-academic partnerships working to improve the health of Pacific Islanders.

A review of reviews on principles, strategies, outcomes and impacts of research partnerships approaches: a first step in synthesising the research partnership literature

Background

Conducting research in partnership with stakeholders (e.g. policy-makers, practitioners, organisations, patients) is a promising and popular approach to improving the implementation of research findings in policy and practice. This study aimed to identify the principles, strategies, outcomes and impacts reported in different types of reviews of research partnerships in order to obtain a better understanding of the scope of the research partnership literature.

Methods

This review of reviews is part of a Coordinated Multicenter Team approach to synthesise the research partnership literature with five conceptually linked literature reviews. The main research question was ‘What principles, strategies, outcomes and impacts are reported in different types of research partnership approaches?’. We included articles describing a literature review of research partnerships using a systematic search strategy. We used an adapted version of the Revised Assessment of Multiple Systematic Reviews tool to assess quality. Nine electronic databases were searched from inception to April 2018. Principles, strategies, outcomes and impacts were extracted from the included reviews and analysed using direct content analysis.

Results

We included 86 reviews using terms describing several research partnership approaches (e.g. community-based participatory research, participatory research, integrated knowledge translation). After the analyses, we synthesised 17 overarching principles and 11 overarching strategies and grouped them into one of the following subcategories: relationship between partners; co-production of knowledge; meaningful stakeholder engagement; capacity-building, support and resources; communication process; and ethical issues related to the collaborative research activities. Similarly, we synthesised 20 overarching outcomes and impacts on researchers, stakeholders, the community or society, and the research process.

Conclusions

This review of reviews is the first that presents overarching principles, strategies, outcomes and impacts of research partnerships. This review is unique in scope as we synthesised literature across multiple research areas, involving different stakeholder groups. Our findings can be used as a first step to guide the initiation and maintenance of research partnerships and to create a classification system of the key domains of research partnerships, which may improve reporting consistency in the research partnership literature.

Trial registration

This study is registered via Open Science Framework: 10.17605/OSF.IO/GVR7Y.

Reduction in black carbon concentration and its exposure in rural settings of Northern India: An intervention analysis

The present study estimated the concentration of black carbon (BC₁₀ and BC_2.5) during cooking hours in three types of kitchen in ten households and two improved cookstoves (ICS) tested against traditional mud cookstoves (TCS) in the real field conditions. The study also used a community-engaged approach to involve the local public regarding the benefits of intervention. The results clearly revealed that personal BC concentration was highest in an enclosed kitchen (83 μg/m³) while using TCS compared to a semi-enclosed (25 μg/m³) and open kitchens (16 μg/m³), respectively. The results showed that deployment of ICS would help in reduction in personal BC concentration in all the households ranged from 36 to 84% and 33-89% in BC₁₀ and BC_2.5, respectively. The study measured the personal dose of BC concentration for women of all the selected households. The reduction in the exposure dose for personal BC₁₀ and BC_2.5 was 69% and 59%, respectively. The results showed that BC concentration during cooking greatly varies with time-activity pattern of users and which in turn affects the exposure levels of the participants. Thus, it is imperative to measure the exact time users spend near to the emission source to get actual exposure inhalation concentration. The results of the study also shared with the local communities to build their capacity for better understanding about the benefits of advanced cooking technologies, household design to improve the ventilation conditions in the kitchen areas and health benefits in terms of reduction in exposure levels especially for vulnerable group like women and children.

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.

Cancer risk from air toxics in relation to neighborhood isolation and sociodemographic characteristics: A spatial analysis of the St. Louis metropolitan area, USA

BACKGROUND

A growing body of research has examined relationships between neighborhood characteristics and exposure to air toxics in the United States. However, a limited number of studies have addressed neighborhood isolation, a measure of spatial segregation. We investigated the spatial distribution of carcinogenic air toxics in the St. Louis metropolitan area and tested the hypothesis that neighborhood isolation and sociodemographic characteristics are associated with exposure to carcinogenic air toxics.

METHODS

We obtained lifetime air toxics cancer risk data from the United States Environmental Protection Agency's National Air Toxic Assessment and sociodemographic data from the American Community Survey. We used geographic information systems to identify statistically significant clusters of census tracts with elevated all-site cancer risk due to air toxics in the St. Louis metropolitan area. Relative Risks (RR) were estimated for the association between neighborhood characteristics and air toxic hot spots. Using a local spatial isolation index to evaluate residential segregation, we also evaluated the association between neighborhood racial and economic isolation and air toxic hot spots.

RESULTS

Approximately 14% (85 of the 615) of census tracts had elevated cancer risk due to air toxics (p < 0.01). These air toxic hot spots were independently associated with neighborhoods with high levels of poverty and unemployment and low levels of education. Census tracts with the highest levels of both racial isolation of Blacks and economic isolation of poverty were more likely to be located in air toxic hotspots than those with low combined racial and economic isolation (RR = 5.34; 95% CI = 3.10-9.22).

CONCLUSIONS

These findings provide strong evidence of unequal distribution of carcinogenic air toxics in the St. Louis metropolitan area. Study results may be used to inform public health efforts to eliminate sociodemographic inequalities in exposure to air pollutants.

Towards a People's Social Epidemiology: Envisioning a More Inclusive and Equitable Future for Social Epi Research and Practice in the 21st Century

Social epidemiology has made critical contributions to understanding population health. However, translation of social epidemiology science into action remains a challenge, raising concerns about the impacts of the field beyond academia. With so much focus on issues related to social position, discrimination, racism, power, and privilege, there has been surprisingly little deliberation about the extent and value of social inclusion and equity within the field itself. Indeed, the challenge of translation/action might be more readily met through re-envisioning the role of the people within the research/practice enterprise-reimagining what "social" could, or even should, mean for the future of the field. A potential path forward rests at the nexus of social epidemiology, community-based participatory research (CBPR), and information and communication technology (ICT). Here, we draw from social epidemiology, CBPR, and ICT literatures to introduce A People's Social Epi-a multi-tiered framework for guiding social epidemiology in becoming more inclusive, equitable, and actionable for 21st century practice. In presenting this framework, we suggest the value of taking participatory, collaborative approaches anchored in CBPR and ICT principles and technological affordances-especially within the context of place-based and environmental research. We believe that such approaches present opportunities to create a social epidemiology that is of, with, and by the people-not simply about them. In this spirit, we suggest 10 ICT tools to "socialize" social epidemiology and outline 10 ways to move towards A People's Social Epi in practice.

Hybrid Resiliency-Stressor Conceptual Framework for Informing Decision Support Tools and Addressing Environmental Injustice and Health Inequities

While structural factors may drive health inequities, certain health-promoting attributes of one's "place" known as salutogens may further moderate the cumulative impacts of exposures to socio-environmental stressors that behave as pathogens. Understanding the synergistic relationship between socio-environmental stressors and resilience factors is a critical component in reducing health inequities; however, the catalyst for this concept relies on community-engaged research approaches to ultimately strengthen resiliency and promote health. Furthermore, this concept has not been fully integrated into environmental justice and cumulative risk assessment screening tools designed to identify geospatial variability in environmental factors that may be associated with health inequities. As a result, we propose a hybrid resiliency-stressor conceptual framework to inform the development of environmental justice and cumulative risk assessment screening tools that can detect environmental inequities and opportunities for resilience in vulnerable populations. We explore the relationship between actual exposures to socio-environmental stressors, perceptions of stressors, and one's physiological and psychological stress response to environmental stimuli, which collectively may perpetuate health inequities by increasing allostatic load and initiating disease onset. This comprehensive framework expands the scope of existing screening tools to inform action-based solutions that rely on community-engaged research efforts to increase resiliency and promote positive health outcomes.

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.

Increasing Environmental Health Literacy through Contextual Learning in Communities at Risk

Environmental health literacy (EHL) has recently been defined as the continuum of environmental health knowledge and awareness, skills and self-efficacy, and community action. In this study, an interdisciplinary team of university scientists, partnering with local organizations, developed and facilitated EHL trainings with special focus on rainwater harvesting and water contamination, in four communities with known environmental health stressors in Arizona, USA. These participatory trainings incorporated participants' prior environmental health risk knowledge and personal experiences to co-create training content. Mixed methods evaluation was conducted via pre-post participant surveys in all four trainings (n = 53). Participants who did not demonstrate baseline environmental science knowledge pre-training demonstrated significant knowledge increase post-training, and participants who demonstrated low self-efficacy (SE) pre-training demonstrated a significant increase in SE post-training. Participants overall demonstrated a significant increase in specific environmental health skills described post-training. The interdisciplinary facilitator-scientist team also reported multiple benefits, including learning local knowledge that informed further research, and building trust relationships with community members for future collaboration. We propose contextual EHL education as a valuable strategy for increasing EHL in environmental health risk communities, and for building academia-community partnerships for environmental health research and action.

Solution to the Problem of Calibration of Low-Cost Air Quality Measurement Sensors in Networks

We provide a simple, remote, continuous calibration technique suitable for application in a hierarchical network featuring a few well-maintained, high-quality instruments ("proxies") and a larger number of low-cost devices. The ideas are grounded in a clear definition of the purpose of a low-cost network, defined here as providing reliable information on air quality at small spatiotemporal scales. The technique assumes linearity of the sensor signal. It derives running slope and offset estimates by matching mean and standard deviations of the sensor data to values derived from proxies over the same time. The idea is extremely simple: choose an appropriate proxy and an averaging-time that is sufficiently long to remove the influence of short-term fluctuations but sufficiently short that it preserves the regular diurnal variations. The use of running statistical measures rather than cross-correlation of sites means that the method is robust against periods of missing data. Ideas are first developed using simulated data and then demonstrated using field data, at hourly and 1 min time-scales, from a real network of low-cost semiconductor-based sensors. Despite the almost naïve simplicity of the method, it was robust for both drift detection and calibration correction applications. We discuss the use of generally available geographic and environmental data as well as microscale land-use regression as means to enhance the proxy estimates and to generalize the ideas to other pollutants with high spatial variability, such as nitrogen dioxide and particulates. These improvements can also be used to minimize the required number of proxy sites.

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

BACKGROUND

Lower-cost air quality sensors (hundreds to thousands of dollars) are now available to individuals and communities. This technology is undergoing a rapid and fragmented evolution, resulting in sensors that have uncertain data quality, measure different air pollutants and possess a variety of design attributes. Why and how individuals and communities choose to use sensors is arguably influenced by social context. For example, community experiences with environmental exposures and health effects and related interactions with industry and government can affect trust in traditional air quality monitoring. To date, little social science research has been conducted to evaluate why or how sensors, and sensor data, are used by individuals and communities, or how the introduction of sensors changes the relationship between communities and air quality managers.

OBJECTIVES

This commentary uses a risk governance/responsible innovation framework to identify opportunities for interdisciplinary research that brings together social scientists with air quality researchers involved in developing, testing, and deploying sensors in communities.

DISCUSSION

Potential areas for social science research include communities of sensor users; drivers for use of sensors and sensor data; behavioral, socio-political, and ethical implications of introducing sensors into communities; assessing methods for communicating sensor data; and harnessing crowdsourcing capabilities to analyze sensor data.

CONCLUSIONS

Social sciences can enhance understanding of perceptions, attitudes, behaviors, and other human factors that drive levels of engagement with and trust in different types of air quality data. New transdisciplinary research bridging social sciences, natural sciences, engineering, and design fields of study, and involving citizen scientists working with professionals from a variety of backgrounds, can increase our understanding of air sensor technology use and its impacts on air quality and public health.