Viewing and interpreting data from the Black Carbon Module on Dashboard

How to view data from your Black Carbon Module after field setup with a Node-S, including guidance on reading charts.

What is Black Carbon?

Black carbon (BC), sometimes referred to as “soot”, is a component of fine particulate matter formed during incomplete combustion of fossil fuels and biomass. BC is an important contributor to global warming and is known to have harmful effects on human health. Unlike other components of particulate matter, BC is only formed during combustion. Common emissions sources of BC include:

• Vehicle (both gas and diesel) engines
• Coal-fired power plants
• Industrial activities
• Biomass burning (e.g., wildfires, brush fires, residential wood heating)

BC is never emitted in isolation; there are always co-emitted products  (e.g., organic carbon or organic matter). In addition to contributing further to poor air quality, assumptions about these co-emitted products are used to identify the source category of the BC emissions (fossil fuel or biomass). For wood burning, the mass of organic matter is typically 5-10x higher than that of BC, which helps identify biomass burning sources. 

How do I interpret Black Carbon measurements using the Clarity Dashboard?

Once the Clarity Node-S has been configured and paired with your Black Carbon Module, you can use the Clarity Dashboard to view real-time data. To do that, navigate to the Datasource Measurements page as follows:

• On the Datasources page, select a Datasource with source device paired to a Black Carbon Module.
• Select View Measurements from the Actions dropdown. The Datasource Measurements page will load.

On the Datasource Measurements page:

• Select Black Carbon | 1-Hour Mean | Mass Concentration (All Sources) from the parameter selector
• Look at the time series plot for All Sources of BC
  • As a reference point, annual average BC concentrations in rural areas are approximately in the 0-500 ng m^-3 range. Annual average BC concentrations in urban areas under moderate traffic and combustion emissions are in the range of 500 - 2,500 ng m^-3. Finally, heavily polluted areas may experience annual average BC concentrations above 5,000 ng m^-3.
  • Over the course of several days, hourly BC concentrations may drop near-zero when the influence of combustion emissions on air quality is low and may peak in the thousands when local air quality is heavily impacted by combustion sources. 
  • In urban areas heavily impacted by traffic, it is common to see peaks in BC repeating around a similar time each day due to morning commuting traffic patterns. In areas impacted by residential wood-burning as a heating source, there is often a peak in BC concentrations in the evening. Finally, regions impacted by wildfires, brush fires, or agricultural burning experience transient peaks during the season where these events are most frequent.
• Look at real-time source apportionment between fossil fuels and biomass for sources of BC. To do that, make sure that Show Source Attribution Concentrations is toggled on above the time series plot.
  • This source apportionment plot will allow you to see how biomass and fossil fuel sources are contributing to overall BC concentrations over time.
  • Periods with increasing fossil fuel contributions to BC may be associated with vehicular traffic activity. Traffic patterns often repeat during similar times of day. Other potential sources of BC from fossil fuel include industrial activity and power plants.
  • Periods with increasing contributions to  biomass burning may be indicative of wildfires, brush fires, or residential heating. 

• Compare the trend of each source over time.
  • For instance, is the biomass contribution to BC higher today than yesterday? Also consider the location of the monitoring site. For instance, a site located near a busy highway may measure a larger fossil fuel contribution than biomass contribution to BC even on days where air quality is impacted by a wildfire event due to the influence and proximity of the traffic source.

• Compare PM2.5 and BC measurements in the Comparison section. To do that, make sure to select PM2.5 Mass Concentration in the dropdown above the Comparison time series plot.
  • Look at PM2.5 and BC trends (time series plot) and correlation / R² (scatter plot).
  • A strong correlation between PM2.5 and BC suggests fresh combustion emissions played a major role in air quality.
  • If PM2.5 and BC are not strongly correlated, this suggests there may significant non-combustion sources of PM2.5