Scientists Have Discovered New Air Pollution Sources Using “Roving Sentinels”
Scientists Have Discovered New Air Pollution Sources Using “Roving Sentinels” SciTechDaily
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A Report on Air Quality Monitoring and Source Identification in Salt Lake Valley
A pioneering study by University of Utah and EDF utilized Google Street View cars for detailed air quality monitoring in Salt Lake Valley. Revealing hyper-local pollution hotspots and highlighting environmental justice issues, the research marks a significant advancement in understanding and addressing urban air pollution’s uneven impact.
Introduction
In 2019, a team of atmospheric scientists from the University of Utah, in collaboration with the Environmental Defense Fund and other partners, introduced an innovative approach to air quality monitoring in the Salt Lake Valley. They equipped two Google Street View cars to function as mobile air pollution detectors, capable of identifying hyper-local pollution hotspots. The aim of this study was to gather highly detailed air quality data and accurately pinpoint the sources of pollution emissions.
Data Collection and Analysis
The researchers loaded the vehicles with air quality instrumentation and directed drivers to trawl through neighborhoods street by street, taking one air sample per second. This comprehensive sampling yielded a massive dataset of air pollutant concentrations in the Salt Lake Valley from May 2019 to March 2020. The observations provided the highest-resolution map yet of pollution hotspots at fine scales, capturing variability within 200 meters.
Using a novel atmospheric modeling technique developed by Professor John Lin, the researchers were able to trace pollutants back to their exact sources. This method combined wind-pattern modeling and statistical analysis, surpassing the broader methods of traditional air quality monitoring that assess air quality over entire urban areas.
Findings and Implications
The study revealed distinct variations in pollution levels within different local areas of the Salt Lake Valley. Higher pollution levels were observed around traffic and industrial areas, confirming the expected air quality patterns. Notably, neighborhoods with lower average incomes and a higher percentage of Black residents showed higher pollutant levels, highlighting environmental justice issues.
The legacy of redlining policies from a century ago was found to contribute to the uneven impact of air pollution. Redlined neighborhoods, which were historically labeled as “hazardous,” often had poor air quality due to industrial activities. The researchers emphasized the importance of addressing these environmental justice issues and investing in underprivileged neighborhoods to improve air quality.
Conclusion
The use of mobile air pollution detectors, such as Google Street View cars, combined with advanced atmospheric modeling techniques, provides a powerful tool for identifying pollution hotspots and understanding the sources of pollution emissions. This research contributes to the achievement of the Sustainable Development Goals (SDGs), particularly Goal 3 (Good Health and Well-Being) and Goal 11 (Sustainable Cities and Communities).
Further utilization of this method in other cities can help identify pollution sources and inform policy decisions to mitigate the impact of air pollution on citizens. The researchers also hope to utilize the atmospheric model for projects like Air Tracker, a web-based tool that helps users find the likely source of air pollution in their neighborhoods. By addressing environmental justice issues and promoting equitable access to clean air, we can create healthier and more sustainable communities.
SDGs, Targets, and Indicators
1. Which SDGs are addressed or connected to the issues highlighted in the article?
- SDG 3: Good Health and Well-being
- SDG 11: Sustainable Cities and Communities
- SDG 13: Climate Action
- SDG 15: Life on Land
2. What specific targets under those SDGs can be identified based on the article’s content?
- SDG 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water, and soil pollution and contamination.
- SDG 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management.
- SDG 13.2: Integrate climate change measures into national policies, strategies, and planning.
- SDG 15.1: By 2020, ensure the conservation, restoration, and sustainable use of terrestrial and inland freshwater ecosystems and their services.
3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?
- Ambient air pollutant concentrations (e.g., nitrous oxides, black carbon, fine particulate matter) measured using research-grade instrumentation in Google Street View cars.
- Variability of air pollution levels within different neighborhoods.
- Identification of pollution hotspots at fine scales (within 200 meters).
- Correlation between air pollution levels and demographic factors such as average incomes and percentage of Black residents.
Table: SDGs, Targets, and Indicators
| SDGs | Targets | Indicators |
|---|---|---|
| SDG 3: Good Health and Well-being | Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water, and soil pollution and contamination. | – Ambient air pollutant concentrations – Variability of air pollution levels within neighborhoods – Correlation between air pollution levels and demographic factors |
| SDG 11: Sustainable Cities and Communities | Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management. | – Ambient air pollutant concentrations – Variability of air pollution levels within neighborhoods – Correlation between air pollution levels and demographic factors |
| SDG 13: Climate Action | Target 13.2: Integrate climate change measures into national policies, strategies, and planning. | – Ambient air pollutant concentrations – Variability of air pollution levels within neighborhoods – Correlation between air pollution levels and demographic factors |
| SDG 15: Life on Land | Target 15.1: By 2020, ensure the conservation, restoration, and sustainable use of terrestrial and inland freshwater ecosystems and their services. | – Ambient air pollutant concentrations – Variability of air pollution levels within neighborhoods – Correlation between air pollution levels and demographic factors |
Note: The indicators mentioned in the table are based on the information provided in the article.
Behold! This splendid article springs forth from the wellspring of knowledge, shaped by a wondrous proprietary AI technology that delved into a vast ocean of data, illuminating the path towards the Sustainable Development Goals. Remember that all rights are reserved by SDG Investors LLC, empowering us to champion progress together.
Source: scitechdaily.com
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