Meghan Hodges
Air pollution hot spots are areas where air pollution emissions expose individuals to increased negative health effects. These are particularly common in highly populated, urban areas, where there may be a combination of stationary sources (e.g. industrial facilities) and mobile sources (e.g. cars and trucks) of pollution. To identify these hot spots, researchers and policymakers have developed various tools, such as the EPA's Risk-Screening Environmental Indicators (RSEI) model, which identifies hot spots from a score of 3 to 15, with higher scores indicating closer proximity to hazards. Other methods include using 3D maps and space-time cubes to identify hot spots and cold spots of pollution.
| Characteristics | Values |
|---|---|
| Tools to identify air pollution hotspots | Risk-Screening Environmental Indicators (RSEI) model, Emerging Hot Spot Analysis tool |
| Common locations of air pollution hotspots | Highly populated, urban areas with industrial facilities, old factories, waste storage sites, and heavy traffic |
| Effects of air pollution hotspots | Respiratory disease, childhood asthma, cancer, and other health problems |
| Strategies to improve air quality in pollution hotspots | Activist campaigns, government plans, and meeting targets |
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What You'll Learn
- Utilise tools like the Emerging Hot Spot Analysis tool to find pollution hot spots
- Understand the data landscape and use datasets like RSEI to identify toxic air pollution hot spots
- Identify areas with high traffic and stationary sources of pollution, like engines left running in traffic
- Look for industrial facilities, old factories, waste storage sites, and other major sources of air pollution
- Monitor and collect emission data from specific sources, such as Chevron's refineries in Richmond
Utilise tools like the Emerging Hot Spot Analysis tool to find pollution hot spots
The Emerging Hot Spot Analysis tool is a useful resource for finding pollution hot spots. This tool is part of the Space Time Pattern Mining toolbox and can be used to identify trends in data, such as new, intensifying, diminishing, and sporadic hot and cold spots.
To utilise this tool, you will need to first create a space-time netCDF cube using the various tools in the Space Time Pattern Mining toolbox. This cube will serve as the input for the Emerging Hot Spot Analysis tool. The tool then uses the Conceptualization of Spatial Relationships values that you provide to calculate the Getis-Ord Gi* statistic for each bin, employing an FDR correction.
The Emerging Hot Spot Analysis tool can detect eight specific hot or cold spot trends: new, consecutive, intensifying, persistent, diminishing, sporadic, oscillating, and historical. For instance, an Intensifying Hot Spot is a location that has been a statistically significant hot spot for 90% of the time-step intervals, including the final time step.
After running the analysis, each bin in the input netCDF cube will have an associated z-score, p-value, and hot spot bin classification. These hot and cold spot trends are then evaluated using the Mann-Kendall trend test.
Visualising the data in 2D and 3D can greatly aid in interpreting the results of the Emerging Hot Spot Analysis tool. The 2D map provides the most prominent output, and messages summarising the analysis results are written at the bottom of the Geoprocessing pane.
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Understand the data landscape and use datasets like RSEI to identify toxic air pollution hot spots
The Risk-Screening Environmental Indicators (RSEI) model is a powerful tool that can be used to identify toxic air pollution hot spots. The RSEI tool, developed by the US Environmental Protection Agency (EPA), provides a screening measure of risks to human health by estimating the concentrations of individual industrial chemicals in the air in areas less than half a kilometre wide. This allows for a detailed understanding of pollution levels at a very local level, which is particularly useful in rural areas where emissions can vary widely.
The RSEI dataset is vast, with seven billion rows of data, and requires a supercomputer to analyse. The dataset is organised into a grid of 810m by 810m grid cells, with facilities assigned to a specific cell according to their latitude and longitude coordinates. The RSEI data incorporates information on toxicity, fate and transport, and population densities, providing a robust measure of human health risks.
However, it's important to note that the RSEI data is not perfect and has some limitations. For example, it does not include some bulk pollutants such as sulfur dioxide, nitrogen oxides, ozone, carbon monoxide, particulate matter, and carbon dioxide. Additionally, there may be incorrect or imprecise data submitted by facilities, which can impact the accuracy of the RSEI scores.
To identify toxic air pollution hot spots, ProPublica analysed five years of data from the RSEI model to identify hot spots of cancer-causing industrial air pollution. They derived cancer risk estimates from the concentration numbers in the model's grid cells and averaged them over a five-year period. Toxic hot spots were then identified as contiguous grid cells with an estimated incremental lifetime cancer risk greater than or equal to 1 in 100,000.
Other tools and techniques can also be used to identify pollution hot spots, such as the Emerging Hot Spot Analysis tool from the Space Time Pattern Mining toolbox, which allows for the visualisation and analysis of space-time data to identify hot and cold spots of pollution.
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Identify areas with high traffic and stationary sources of pollution, like engines left running in traffic
Vehicle traffic is a significant source of air pollution in urban areas. Mobile sources, such as cars, trucks, and buses, account for more than half of all air pollution in the United States, according to the Environmental Protection Agency. The concentration of these pollutants is often highest near major roadways, with a sharp decline in concentration as the distance from the road increases. Therefore, areas with high traffic, such as highways or busy city centres, are likely to be pollution hotspots.
To identify these areas, mobile monitoring can be used to measure pollutant concentrations at various locations. For example, in a study conducted in Kansas City, mobile monitoring was employed to measure nitrogen dioxide (NO2), black carbon (BC), and ultrafine particulate matter (UFP) concentrations across different zones in the city. Zone 1, with a high number of distribution centres and truck traffic, had generally higher pollutant concentrations than Zone 3, which was further from these sources.
Another method to identify high-traffic pollution hotspots is through dispersion modelling. This approach uses simulations to predict pollutant concentrations and their dispersion over time and space. For instance, the NEXUS study utilized a hybrid modelling system to estimate hourly, daily, and long-term pollutant concentrations, specifically focusing on PM2.5 and NOx levels in Detroit. By employing dispersion modelling, researchers can identify areas with high pollution concentrations, even without physical monitoring at fixed sites.
Additionally, stationary sources, such as idling engines, also contribute to pollution hotspots. In the Kansas City study, a stationary SUV was used to measure air quality parameters such as CO2, nitric oxide (NO), NO2, BC, and UFP. These stationary measurements provided insights into the temporal variability of pollutant concentrations. By combining mobile and stationary monitoring, a more comprehensive understanding of pollution hotspots can be achieved.
Identifying areas with high traffic and stationary sources of pollution is crucial for implementing effective pollution mitigation strategies. By understanding the spatial distribution of pollutants, environmental and public health officials can prioritize areas for intervention, such as implementing regulations or technological advancements to reduce emissions and improve air quality, ultimately reducing the health risks associated with exposure to these pollutants.
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Look for industrial facilities, old factories, waste storage sites, and other major sources of air pollution
When looking for runoff pollution hotspots, it is crucial to focus on industrial facilities, old factories, waste storage sites, and other significant sources of air pollution. These sites can contribute significantly to environmental contamination, including air, water, and soil pollution, through their manufacturing, processing, and extraction processes.
Industrial facilities, such as refineries, steel mills, and petrochemical plants, release various airborne pollutants. Refineries, for instance, transform raw materials like crude oil and natural gas into fuels, chemicals, and other products, emitting pollutants such as PM2.5, sulfur dioxide, nitrogen oxides, volatile organic compounds, and hazardous air pollutants. Similarly, petrochemical plants process hydrocarbons from crude oil and natural gas into petrochemicals used in everyday products, releasing pollutants like PM2.5, sulfur dioxide, nitrogen oxides, VOCs, and HAPs.
Old factories and abandoned industrial sites can also be major pollution sources. These sites may have left behind contaminated land and groundwater, which can lead to runoff pollution. Additionally, waste storage sites, particularly those dealing with hazardous waste, can create significant air pollution if not properly managed. Improper waste disposal methods, such as waste incineration, can further contribute to air pollution and impact nearby communities.
To identify these hotspots, one can utilize tools such as the Emerging Hot Spot Analysis tool from the Space Time Pattern Mining toolbox. This tool allows for the identification of both hot and cold spots of pollution by analyzing pollution data in 2D and 3D visualizations. Additionally, datasets like the Risk-Screening Environmental Indicators (RSEI) model can provide valuable insights into pollution hotspots. By partnering with local communities, journalists, and organizations like the Clean Air Council, efforts can be made to advocate for improved waste disposal methods, stricter regulations, and the adoption of cleaner practices to reduce pollution from these sources.
By actively seeking out these industrial facilities, old factories, and waste storage sites, and utilizing available tools and datasets, we can better identify and address runoff pollution hotspots, thereby mitigating their environmental and health impacts on surrounding areas.
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Monitor and collect emission data from specific sources, such as Chevron's refineries in Richmond
To monitor and collect emission data from Chevron's refineries in Richmond, several methods and tools can be employed:
Firstly, it is essential to utilise point monitors at specific locations near the refinery. Point monitors are more accurate than open-path equipment in detecting pollution from nearby sources. In the case of Chevron's Richmond refinery, point monitors are already in place for Atchison Village, Point Richmond, and North Richmond. However, Chevron should install additional point monitors at strategic locations to ensure comprehensive data collection.
Secondly, fence-line monitoring is crucial for refineries, as hazardous chemicals are often emitted from the refinery perimeter. Despite regulations, Chevron's Richmond refinery currently lacks sufficient fence-line monitors. Installing and maintaining fence-line monitors will provide more precise data on the emissions directly impacting the surrounding communities.
Thirdly, to ensure transparency and public access to information, Chevron should make its fence-line pollution data easily downloadable and include historical data. This will enable the public and researchers to analyse long-term trends and identify any persistent issues. Chevron has agreed to file quarterly pollution reports, which is a positive step towards transparency.
Additionally, Chevron should engage with the local community to understand their concerns and incorporate their feedback. The company can utilise tools such as the Community Warning System to alert residents about Level 1 events, including localized flares, which have been a frequent source of violation notices. By actively involving the community, Chevron can address specific issues and work collaboratively to find solutions.
Furthermore, Chevron can benefit from partnerships and collaborations with media organisations and environmental justice groups. For example, ProPublica has produced valuable investigations and mappings of toxic air pollution hotspots, including areas near Chevron's refineries. By working with such organisations, Chevron can gain insights into data analysis and identification of pollution hotspots.
Finally, Chevron should adhere to regulatory standards and expert recommendations. This includes implementing the suggestions made by the expert panel convened in 2013, such as collecting measurements at 5-minute intervals and providing real-time data to the public. By following these guidelines, Chevron can improve the accuracy and frequency of its emission data collection.
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Frequently asked questions
Runoff pollution is water that flows over surfaces in urban and rural areas and drains directly into natural water sources. It is polluted by contaminants such as trash, oil, grease, pesticides, metals, bacteria, and toxic chemicals.
Runoff pollution has various effects on the environment and human health. It can cause flooding, erosion, and reshaping of waterways. It also endangers aquatic life by blocking sunlight from reaching underwater grasses and smothering aquatic habitats. In addition, it can contaminate drinking water sources, making treatment more challenging and expensive.
You can identify a runoff pollution hotspot by observing the presence of trash, oil, or other contaminants in natural water sources. You can also refer to water quality assessments and maps provided by organizations such as the Washington State Department of Ecology. Additionally, you can contact local nonpoint staff or use reporting tools like the Environmental Tracking System (ERTS) to learn about specific regions.
The sources of runoff pollution vary and include atmospheric deposition, transportation-related activities, and metallic building materials. In agricultural areas, runoff pollution comes from manure storage areas, animal confinement areas, and fields where manure has been applied. Urban areas contribute through stormwater runoff, which carries pollutants from streets, parking lots, and other hard surfaces directly into natural water bodies.
Reducing runoff pollution requires collective action and individual efforts. Individuals can properly maintain their vehicles, recycle used oils and fluids, fix oil leaks, and opt for commercial car washes or wash their cars on lawns to prevent polluted water from entering storm drains. Communities can create "green infrastructure" by planting rain gardens, using rain barrels, and replacing old pavement with pervious pavement to slow down and absorb polluted runoff.
