Low-cost sensors can improve air quality monitoring and people’s health
Amid mounting concern about the health and environmental impacts of air pollution, a new report from the World Meteorological Organization points out the potential for low-cost sensor systems to assess levels of air pollution, identify sources and to support air quality strategies to reduce them.
- Low-cost sensors can fill gaps in existing networks
- Low and middle income countries can benefit
- They are an important additional tool which can be harnessed at the community level
- Data-driven policy supports action towards combating air pollution
- The effects of air pollution lead to an estimated 7 million deaths every year
Low-cost sensor systems (LCS) represent a key tool for filling gaps in existing global and local air quality monitoring networks and contributing information for policy-relevant air quality strategies.
In recent years, wide-scale deployments of LCS have been made in low- and middle-income countries, where they often provide air quality information in regions lacking the more traditional (and more expensive) reference grade monitors. In high-income countries, they supplement existing reference grade monitors with more localized near real-time air quality information – for instance, to monitor fire and smoke or vehicle emissions on busy roads.
“Air quality forecasting involving low-cost sensors is an increasingly important field due to its potential to support widespread monitoring and early warning systems, particularly in areas lacking more traditional monitors. Air quality forecasting is important to support effective decision-making to manage air quality impacts, especially in terms of human health. They are an important additional tool which can be harnessed at the community level to make a real difference in people’s lives,” said Sara Basart, WMO Scientific Officer and one of the report's authors.
The report, Integrating Low-Cost Sensor Systems and Networks to Enhance Air Quality Applications, was produced by WMO’s Global Atmosphere Watch network in collaboration with the UN Environment Programme (UNEP), International Global Atmospheric Chemistry project (IGAC) and international experts on technical and application areas. It was released to coincide with the WMO Executive Council meeting, which has a focus on transforming science and practical services for society.
“Life begins and is sustained with breath, but too many around the world are suffering health problems and death due to breathing dirty air. Data-driven policy action towards combating air pollution is critical for efforts to improve global air quality – the more tools we have to support this, the greater our chances of recreating healthy environments for all life on earth,” said Richard Munang, Head of Global Environment Monitoring Systems and Early Warning for Environment Unit at UNEP.
“We had more than 30 contributors from many different countries. We were able to get a broad spectrum of different opinions and experiences worldwide and synthesise them into a report which really summarises the best practises for air quality applications from many different experiences around the world.” said Carl Malings, lead coordinating author of the report.
The effects of air pollution lead to an estimated 7 million deaths every year, according to WHO. Mounting evidence links ambient and household air pollution to various health outcomes like non-communicable diseases including respiratory, cardiovascular and pulmonary diseases, cancer, low birth weight, diabetes, cognitive impairment and mental health impacts.
Network level
An LCS contains one or more sensing elements together with hardware and software for control, power supply, data management, and weatherproofing, constituting a complete system capable of collecting atmospheric composition data.
The “low cost” of LCS refers to their per-unit capital cost in relation to more traditional reference grade monitors. However, technical trade-offs which enable this lower cost usually also limit data quality, selectivity, sensitivity to low concentrations, robustness under high concentrations, and/or operational lifetime.
In order to overcome these limitations of individual LCS, the report examines the use of LCS at a network level and in conjunction with other data sources, such as air quality models and satellites. It intends to provide a valuable foundation by summarizing recommendations and best practices for those seeking to make effective use of LCS networks alongside other data sources to improve understanding and management of air quality.
For example, the increased availability of locally and even personally specific air quality information enabled by LCS has led to their increased use for health studies. Also, multipollutant LCS are useful for determining vehicle emission factors. LCS networks covering both roadside sites and background locations can help identify the relative contribution of traffic to local air pollution.
These recommendations and others are supported by a survey of the available academic literature, as well as practical case study examples.
Case Study examples
Examples of case studies in LCS network design include:
- In London, United Kingdom, the Breathe London pilot programme involved the deployment of a network of over 100 LCS to monitor nitrogen dioxide over 2 years. This network has since expanded to over 420 LCS measuring PM2.5 (fine inhalable particulate matter) and nitrogen dioxide – both of which are hazardous to health.
- In Lagos, Nigeria, the World Bank and the Lagos State Environmental Protection Agency used an LCS network for long-term observations of air quality at six sites across the city. This network provided data for initial health and economic impact assessments of air quality, as well as for evaluation of air quality models. The study recommended expanding the network by 8 to 12 sites, with a focus on assessing the impacts of ports, traffic, and industrial activity by using paired upwind and downwind sites.
- In Uganda, the AirQo network has been locally designed specifically for operation in resource-constrained environments, taking limitations on power and communications infrastructure as well as environmental stressors on the sensing technology into account. This local development has provided opportunities for technical capacity-building, and facilitated sensor deployment to other parts of Sub-Saharan Africa with similar constraints.
- In Mexico, the objective of the VER-PM2.5 (Variación Espacial Regional de PM2.5) network is to provide information on the spatial variations of PM2.5 and the exchange of plumes between different urban centres, and to support RGM in critical areas. The network currently has 50 sites and will expand to 150 sites across states surrounding Mexico City, covering not only the main urban centres but also non-urbanized areas.
Community engagement and education
Examples of programmes that incorporate LCS deployments in their educational strategy include:
- Love My Air. This programme combines LCS deployment with educational materials to provide diverse communities in Denver, USA, with visible, accessible, and actionable air quality information. The Love My Air information allowed school employees to make informed decisions on outdoor activities on bad air quality days and empowered students to take preventive asthma medication or find alternative activities to protect their own health.
- EducAIR. This programme in the metropolitan region of Manaus, Brazil is an effort aimed at educating students and their families about the importance of forest conservation and clean air.
- Cityzens4CleanAir. This campaign involves urban runners with air quality data collection using wearable LCS, leading to analysis, advocacy, and awareness-raising activities.
- sensors.AFRICA. This programme of the Code for Africa non-profit organization provides do-it-yourself (DIY) kits available through the open-source Luftdaten project (also known as Sensor.Community) allowing individuals to construct and operate LCS. The programme also offers instruction in data collection and analysis and guidance about how to communicate findings. This increases awareness of air quality issues, technical capacity for air quality measurement, and ability to advocate for air quality policies more effectively.
- Clean Air Catalyst. A five-year programme funded by the USA Agency for International Development to build capacity in three pilot cities: Indore, India; Jakarta, Indonesia; and Nairobi, Kenya. RGM are installed in the pilot cities and stakeholders are trained to educate, implement and incorporate air quality in their local governance.
- MoveGreen. An environmental non-profit based in Kyrgyzstan which supports and promotes general environmental awareness and has deployed LCS to various locations in Central Asia.
- Aire Ciudadano. Based in Colombia, Aire Ciudadano utilizes citizen science to learn about air quality. They have deployed DIY PM2.5 LCS in Colombia and neighbouring countries.
- Ciudadanos Científicos. A local science, education and technology programme developed by the Aburrá Valley Early Warning System (SIATA) and funded by the Aburrá Valley Metropolitan Area (AMVA), Colombia. The programme began in 2015 and currently has 250 LCS distributed throughout the metropolitan area. Each citizen scientist hosts a PM2.5 LCS in their home. SIATA also operates the RGM network in the Aburrá Valley.
- Pakistan Air Quality Initiative. Launched by a citizen in 2016, the initiative has deployed LCS across cities in Pakistan, and has led advocacy and engagement on air quality.
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