What are the most effective air pollution monitoring strategies for policy development?

1 Stationary monitoring

Stationary monitoring refers to the use of fixed devices or stations that measure the concentration and composition of air pollutants in specific locations. Stationary monitoring can provide continuous and consistent data on the spatial and temporal variations of air pollution, as well as the compliance with air quality standards and regulations. Stationary monitoring can use different methods and technologies, such as filter-based samplers, optical analyzers, electrochemical sensors, and remote sensing instruments. Stationary monitoring can cover a wide range of pollutants, such as particulate matter, ozone, nitrogen oxides, sulfur dioxide, carbon monoxide, and volatile organic compounds.

2 Mobile monitoring

Mobile monitoring refers to the use of portable or movable devices or vehicles that measure the concentration and composition of air pollutants in different locations. Mobile monitoring can provide flexible and dynamic data on the spatial and temporal variations of air pollution, as well as the identification of hotspots and sources of emissions. Mobile monitoring can use similar methods and technologies as stationary monitoring, but with lower power consumption, smaller size, and higher mobility. Mobile monitoring can cover a similar range of pollutants as stationary monitoring, but with higher spatial resolution and lower temporal resolution.

3 Personal monitoring

Personal monitoring refers to the use of wearable or handheld devices or instruments that measure the personal exposure and intake of air pollutants by individuals or groups. Personal monitoring can provide personalized and relevant data on the health effects and risks of air pollution, as well as the behavior and lifestyle factors that influence exposure. Personal monitoring can use different methods and technologies, such as passive badges, active pumps, micro-sensors, and smart phones. Personal monitoring can cover a limited range of pollutants, such as particulate matter, ozone, nitrogen dioxide, carbon monoxide, and benzene.

4 Modeling and estimation

Modeling and estimation refer to the use of mathematical or statistical tools or techniques that simulate or predict the concentration and composition of air pollutants in different locations and times. Modeling and estimation can provide comprehensive and integrated data on the regional and global patterns and trends of air pollution, as well as the scenarios and impacts of policy interventions. Modeling and estimation can use different methods and techniques, such as emission inventories, dispersion models, chemical transport models, exposure models, and health impact models. Modeling and estimation can cover a broad range of pollutants, such as particulate matter, ozone, nitrogen oxides, sulfur dioxide, carbon monoxide, volatile organic compounds, and greenhouse gases.

5 Citizen science

Citizen science refers to the involvement of non-professional or volunteer participants in the collection or analysis of air pollution data. Citizen science can provide participatory and inclusive data on the local and community perceptions and preferences of air pollution, as well as the engagement and empowerment of citizens in policy making. Citizen science can use different methods and approaches, such as crowdsourcing, gamification, education, and advocacy. Citizen science can use different devices or platforms, such as low-cost sensors, mobile apps, online platforms, and social media. Citizen science can cover a variable range of pollutants, depending on the availability and quality of the devices or platforms used.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?