Air quality in New York City is an essential public health concern that impacts millions of residents. My objective was to analyze particulate matter (PM2.5) concentration and its correlation with traffic volume and building emissions using data provided by the NYC Open Data platform. This comprehensive dataset enables an examination of air pollution at a granular neighborhood level.

Reference: NYC Open Data Air Quality.

Process Documentationon

The project utilized air quality surveillance data and spatial files containing New York City Neighborhood Tabulation Area (NTA) codes. Tableau software facilitated merging these datasets, aligning NTA codes with their corresponding air quality data points to construct accurate geographic representations of PM2.5 distribution.

For mapping methodology, see Tableau’s Guide on Maps with Shapefiles.

Results and Discussion

The Particle Matter Average Map utilizes a dark map base to starkly delineate areas of higher particulate matter (PM2.5) concentrations. This visualization method effectively highlights regions with medium and high PM2.5 levels against the dark backdrop, ensuring they command attention. In contrast, areas with low PM2.5 levels merge seamlessly with the map’s dark tones, suggesting a less immediate health concern. This approach prioritizes areas needing intervention and offers a stark visualization of the health disparities within the urban landscape.

In contrast, the Traffic Tertiles and Building Emissions maps utilize a qualitative color gradient to delineate low, medium, and high categories. This approach offers an immediate visual cue of relative emissions and traffic density but lacks the numerical specificity present in the PM Average map.

The Traffic Tertiles Map is presented on a street map base, facilitating a direct visual correlation between traffic volume and air quality. By utilizing color gradations—low (unmarked), medium (light shade), and high (dark shade)—the map reflects the density of vehicular movement. Streets with heavier traffic are distinctly marked, underscoring their potential contribution to air pollution. This method serves a dual purpose: it highlights areas where traffic management could improve air quality and provides a clear, at-a-glance understanding of traffic distribution throughout the city.

In the Building Emissions Map, the choice of a satellite base map emphasizes the physical presence of buildings in correlation to emissions data. Buildings, especially those in densely populated areas, stand out against the satellite imagery, aligning with the marked emissions levels on the map. The high-resolution imagery provides a tangible context to the abstract concept of emissions, anchoring the data in the lived environment of the city. This map underscores the link between urban infrastructure and environmental impact, offering insights into how urban planning could mitigate pollution.

A unified map encapsulates three main elements: Traffic Tertiles, Building Emissions, and Particulate Matter (PM) Average, illustrating the complex interplay between human activity and air quality.

The Traffic Tertiles section uses shades of brown to indicate traffic density, visually correlating higher traffic with increased pollution levels. Similarly, the Building Emissions segment employs the same brown hues to differentiate emission levels from buildings, highlighting urban infrastructure’s significant role in environmental health. This color synchronization not only unifies the presentation but also aids in drawing clearer connections between traffic, building emissions, and their cumulative effect on particulate matter levels, which are vividly depicted in the Particulate Matter Average section. Through this integrated approach, the map educates viewers about the critical areas where concerted efforts can mitigate air pollution, thus enhancing public health and urban livability

Reflection

Reflecting on the current state of “Mapping the Air We Breathe: NYC’s Pollution Tapestry,” the visualization has successfully integrated traffic, building emissions, and particulate matter data to illustrate the environmental challenges across New York City. However, there is substantial potential for expanding this research to include more dimensions that could influence policy decisions and public understanding.

Integrating socioeconomic data, specifically neighborhood wealth indicators would be a pivotal enhancement. By overlaying economic data such as average income levels, housing values, or economic disparity indices, the map could offer insights into how wealth distribution correlates with exposure to pollutants. This addition would highlight areas where lower-income communities might be disproportionately affected by poor air quality, addressing environmental justice concerns.

Furthermore, incorporating health outcome data, such as rates of respiratory illnesses or other conditions linked to poor air quality, could provide a more comprehensive view of pollution’s impact on public health. This could empower policymakers with the information needed to target interventions more effectively and allocate resources where they are most needed.

Explore the Environment and Health Data Portal and Indicator Public Reporting to dive deeper into the data.

Advanced Visualization Techniques

To realize these enhancements, advanced visualization techniques could be employed:

Interactive Layering: Allowing users to add or remove data layers (e.g., pollution levels, socio-economic status, health outcomes) would enable customized analysis, making the tool more versatile and informative.

Temporal Sliders: Introducing features that display changes over time could help track the progress of air quality improvement initiatives or worsening conditions, providing a dynamic timeline of environmental health.

Correlation Heatmaps: These could visually represent the strength of correlation between air quality and socio-economic factors, highlighting areas with significant overlaps between high pollution levels and low economic status.

Conclusion

This report presents an analytical view of New York City’s air quality, focusing on particulate matter. The visualizations created serve as tools for public awareness and as a foundation for policy development and urban health initiatives. Future work will aim to refine these visual tools, incorporating a broader range of data and developing interactive features for enhanced user engagement.