Background
The increased availability, quality, and affordability of low-cost air monitors in recent years has enabled communities and regulators to deploy denser networks of low-cost air monitors. The air quality data from these networks can be used to inform local air pollution mitigation strategies and protect public health.
As a result of California Assembly Bill 617 (AB 617), and with support from the California Air Resources Board (CARB) through the Community Air Grants Program, PSE Healthy Energy (PSE) and the Asian Pacific Environmental Network (APEN) established the Richmond Air Monitoring Network (RAMN) in 2020. RAMN stands out as the first high-density community air monitoring network to collect continuous measurements of three important criteria air pollutants—particulate matter (PM2.5), nitrogen dioxide (NO2), and ground-level ozone (O3)—along with periodic measurements of black carbon (BC), all with very high spatial and temporal resolution.
RAMN is part of California Climate Investments, a statewide program that puts billions of Cap-and-Trade dollars to work reducing greenhouse gas emissions, strengthening the economy, and improving public health and the environment—particularly in disadvantaged communities.
Findings
The purpose of this report is to share details on our air quality monitoring efforts, key findings, and recommendations with regulators, community-based organizations, and the general public. The data collected by RAMN between January 2020 and March 2022 suggests that:
- Traffic is an important source of PM2.5, NOx, and BC in the Richmond-San Pablo region.
- Average PM2.5 levels varied by neighborhood throughout Richmond-San Pablo.
- Black carbon (soot) measurements provide additional context on PM2.5 sources, pointing to diesel engines as likely sources.
- Average NO2 levels were highest near major freeways and expressways.
- Dense sensor networks are able to detect fast-moving pollutant plumes and identify acute exposure events.
- Average PM2.5 concentrations over the study period exceeded health-based standards.
Conclusions
In the broader context of cumulative burdens, many factors—including but not limited to air pollution—contribute to the health outcomes experienced by the community. Communities with elevated health risk factors, including higher prevalence of underlying health conditions, lack of access to healthcare, socioeconomic burdens, and poor housing conditions, face much greater risk from exposure to air pollution.
RAMN data point to commuter traffic and industrial diesel-truck activities as key sources of local air pollution, suggesting that heavy-duty vehicle electrification and other emissions reductions from traffic should be prioritized. This can be achieved through (1) requiring or providing incentives for small and large businesses to electrify truck fleets, (2) retiring old medium- and heavy-duty diesel trucks, (3) rerouting trucks away from areas experiencing cumulative environmental burdens, and (4) restricting industrial development that brings heavy traffic into dense, urban areas and environmental justice communities. Community groups would also benefit from tree planting and other urban greening efforts along traffic corridors to protect sensitive groups from vehicular air pollution.
