Citizen Science - NYCCAS, New York City Community Air Survey
- Ana M. C. Ilie
- Holger M. Eisl
Community science offers unique opportunities for non-professional involvement of volunteers in the scientific process, not just during the data acquisition, but also in other phases, like problem definition, quality assurance, data analysis and interpretation, and the dissemination of results. Moreover, community science can be a powerful tool for public engagement and empowerment during policy formulation. This paper aims to present a pilot study on personal exposure to fine particulate matter (PM2.5) and raises awareness of the hazards of air pollution. As part of data acquisition conducted in 2019, high school students gathered data at their schools, schoolyards, and playgrounds using low-cost monitors AirBeam2. The data was automatically uploaded every second onto the AirCasting mobile app. Besides, a stationary network of air monitors (fixed stations) was deployed in the neighborhood to collect real-time ambient air concentrations of PM2.5. Students involved in the project attended workshops, training sessions, and researched to better understand air pollution, as part of their science class curriculum and portfolio. This air quality monitoring was incorporated into the “Our Air/Nuestro Aire” — El Puente grassroots campaign. The main goals of this campaign included sharing the data collected with the community, engaging academic partners to develop a set of policy and urban design solutions, and to be considered into a 5-point policy platform.
Traditional approaches to air quality monitoring typically involve regulatory agencies that utilize expensive and complex stationary equipment, maintained by trained staff, to provide the type of highly accurate data needed to demonstrate attainment with federal air quality standards. While this type of monitoring is a vital component to air quality management, in urban areas these monitors are often deployed at, only, a limited number of rooftop locations. Though intended to track urban scale trends in pollution levels, the placement of these monitors is not spatially dense enough to characterize intra-urban spatial variation in air quality, due to local emissions sources such as traffic. To address this limitation, this project explored the feasibility of using stationary low-cost monitoring networks for spatial and temporal estimation of ambient fine particulate concentrations in two environmental justice communities in New York City – El Puente (Brooklyn) and Youth Ministries for Peace and Justice (the Bronx).
This project explored the feasibility of using stationary low-cost monitoring networks for spatial and temporal estimation of ambient fine particulate concentrations in two environmental justice communities in New York City-El Puente (Brooklyn) and Youth Ministries for Peace and Justice (Bronx). The data from the community-based low-cost stationary monitoring networks were compared to FEM/FRM data and the findings land use regression (LUR) analysis of the New York City Community Air Survey (NYCCAS).
The study intended to explore the feasibility of using low-cost instrumentation (AirBeam2) to create a more accessible platform for measuring air quality. The monitors were calibrated by the manufacture itself and this study validated them through field colocation against a FEM instrument. The minimum and maximum R2 values obtained were 0.79 and 0.87 respectively. Data were collected at 11 monitoring locations and daily PM2.5 average was around 15 μg/m3, and no location exceeded the limit of 35μg/m3 for 24 hours based on the National Ambient Air Quality Standards (NAAQS) under EPA regulations.
Increase citizen engagement in accessing, collecting, and communicating air quality data, thus providing tools to better inform communities on air quality issues. Provide communities with information for advocating for clean air. Increase data collection in communities that can offer additional spatial and temporal da-ta on pollution levels beyond existing NYCCAS and regulatory methods. These data can offer valuable insights into gradients near major sources and temporal characteristics that contribute to chronically high levels of pollution in many neighborhoods. Produce data for research efforts aimed at combining data from low-cost sensor networks with data from existing NYCCAS or regulatory monitoring networks. These statistical fusion techniques can help develop more spatiotemporally resolved exposure maps of air pollution exposure and inform how the City and other researchers use sensor data in the future. Develop data systems that allow for remote uploading of data to servers or citizen uploading of air quality data.
Increase community awareness of local air quality. Increasing citizen participation in acquiring, interpreting, and communicating air quality data. Help develop methods for citizen air quality monitoring that can be scaled to other communities. Develop strategies for disseminating research findings to the public, community, policymakers and stakeholders. https://aeg.mclms.net/en/package/1878/course/4313/view#course-content
In collaboration with the New York State Department of Environment Conservation (DEC) at Queens College, NY, low-cost air quality monitors were surveyed and assessed through field collocation and integrated into a cellular data acquisition system. This project explored the feasibility of using stationary low-cost monitoring networks for spatial and temporal estimation of ambient fine particulate concentrations (PM2.5) in an environmental justice community in New York City –Youth Ministries for Peace and Justice, in the Bronx a borough which is characterized by a high rate of asthma and cardio-respiratory issues due to the presence of high levels of particulate matter in the atmosphere.
There is a growing field of ‘citizen scientists’, non-scientists engaged in specific issues who collect or analyze data to contribute to scientific research or advocate for environmental or public health improvements. Specific aims of this study included increase citizen engagement in accessing, collecting, and communicating air quality data, thus providing tools to better inform communities on air quality issues and increased data collection in communities that can offer additional spatial and temporal data on pollution levels beyond existing New York City Community Air Survey (NYCCAS) program and regulatory methods in the New York City.
This Air Quality Citizen Science research project aims to provide a better awareness and understanding of local hotspots of fine particulate matter (PM2.5) concentrations in the Williamsburg, Brooklyn neighborhood, which is prone to a high rate of asthma and cardio-respiratory diseases. A key component of the project is to involve the local population in all aspects of the study, ranging from project design to implementation. Members of the community and high school students participated in both defining the study objectives and the collection of air quality data using low-cost sensor technology (AirBeam2) on the basis of personal monitoring procedures. Key targets for the data collection on PM2.5 exposure included schools and playgrounds near major roadways. Project participants attended workshops and training sessions to better understand air pollution in their community and to learn how to use low cost sensor technology to collect and analyze environmental data. In addition to personal monitoring activities, a fixed-site monitoring network, using low-cost Airbeam2 devices, was set up at 12 locations in the Williamsburg neighborhood, which provide real-time PM2.5 air concentrations that are transmitted to a cloud server. Tableau software is being used for data visualization and risk communication. Prior to the use of low cost sensor technology for personal monitoring and the fixed-site network in the project area, an assessment of the performance of all Airbeam2 instruments was performed under ambient conditions at the Queens College-based regulatory monitoring site. Preliminary data indicate distinct spatial patterns of PM2.5 concentrations in the project area of Williamsburg. Some of the questions which will be answered through this Citizen Science pilot study involve a better understanding of the effectiveness of community and volunteer collaboration and an assessment of the efficacy of low cost sensor technology to describe fine scale spatial-temporal characteristics of the project area in Williamsburg, Brooklyn.
Traditional approaches to air quality monitoring generally involve regulatory agencies that utilize expensive and complex stationary equipment maintained by trained staff to provide the type of highly accurate data needed for demonstrating attainment with federal air quality standards. While this type of monitoring is a vital component to air quality management, in urban areas these monitors are often deployed at a limited number of rooftop locations. They are intended to track urban scale trends in pollution levels and are not spatially dense enough to characterize intra-urban spatial variation in air quality due to local emissions sources such as traffic. To address this limitation, in 2007 the NYCDOHMH in partnership with Queens College launched the New York City Community Air Survey, a high density monitoring network designed to assess spatial variation in longer term exposures (seasonal and annual average) at the neighborhood-level. NYCCAS uses less expensive monitoring technology than those that meet federal requirements for NAAQS-attainment determination (Federal Reference Methods), trading high temporal resolution achieved by more expensive monitoring methods with increased spatial coverage that can be achieved by deploying larger numbers or lower cost and easier to deploy instrumentation. NYCCAS has become vital to the City’s understanding of the variation in pollution exposures within New York City; however, its operation relies on trained technical, analytic, and field staff to collect and analyze air quality data. In recent years, technological advancements in air quality monitoring have brought to market many lower-cost, easy-to-use, portable air quality sensors that provide high time resolution data in real time which provides exciting opportunities for additional data collection. Simultaneously, there is a growing field of ‘citizen scientists’, non-scientists who are engaged in specific issues that collect or analyze data to contribute to scientific research or advocate for environmental or public health improvements. The NYCCAS team is currently expanding into the area of community engagement and community-based participatory research by developing air quality “citizen-science” toolkits that will include how-to guides for accessing available data on emission sources, designing neighborhood air pollution surveys using new, low-cost technologies, and sharing data online. We will discuss the role of citizen science projects in metropolitan areas where a considerable understanding of local air pollution exposure already exists.