Air pollution is an important environmental threat to the health of New York City residents. Exposures to two common air pollutants, fine particulate matter (PM2.5) and ozone (O3), can worsen respiratory illness and heart conditions and contribute to premature deaths. Older adults, children and people with existing heart and lung disease are especially affected. This site provides estimates of the impact of air pollution on the health of NYC residents as measured by the numbers of emergency department visits, hospitalizations, and deaths attributable to PM2.5 and ozone.

About PM2.5, Ozone and Health

Fine particulate matter, also known as (PM2.5), are small airborne particles that can be inhaled deep into the lungs. Major sources of PM2.5 include trucks, buses and cars, and the burning of fossil fuel to generate electric power and heat buildings. Exposure to particulate matter has been linked to breathing problems, reduced lung function, heart disease and premature death. Ozone, also called smog, causes irritation and inflammation of the lungs and worsening of asthma.

About the Data and Indicators

PM2.5 and ozone attributable health events are estimated using well established health impact methods often used to estimate the changes in the number of illnesses and deaths that could occur in a population if air pollution concentrations were reduced by a specified amount. This method:

• Uses air quality monitoring data from EPA’s Air Quality System to characterize current or baseline air pollution levels
• Specifies comparison of air quality conditions, such as background levels of air pollution without any man-made emissions, also called modeled natural background level
• Computes change in air pollution levels as the difference between the current level and the comparison level for each neighborhood
• Uses the change in air pollution levels, concentration-response functions from epidemiological studies, and information about the local population and baseline emergency room visits, hospitalization and death rates to calculate the health impact associated with the change in air quality in each neighborhood.

See report for detailed descriptions of health impact methodologies.

Prevention

To help improve air quality and reduce the risk of health effects from air pollution:

• Choose a cleaner commute - walk, bike or use mass transit instead of a car, especially during rush hour.
• Support policies that promote public transportation and energy conservation.
• Spend less time outdoors and in strenuous physical activity on poor air quality days. Avoid being outdoors in the middle of the day when pollution levels are highest.
• Know how sensitive you are to air pollution, and plan outdoor activities when and where pollution levels are lower. Local TV and radio stations report air quality forecasts, and you can track the Air Quality Index.

Key Messages

Air pollution is an important environmental threat to the health of New York City residents, even small improvements in air quality can lead to large public health benefits. Many contributors to poor air quality in NYC are targeted for improvements in the City’s long-term planning and sustainability plan, OneNYC Air Quality. Continuing and expanding these and other efforts at the State and Federal level can result in large benefits to the health of New York City residents.

There are many schemes of neighborhood boundaries (or geographies) available for different datasets. These include:

• Citywide
• Borough
• United Hospital Fund 42 (UHF42) and United Hospital Fund 34 (UHF34) neighborhoods
• Community Districts (CD), and, related, Community District Tabulation Areas (CDTA)
• Public Use Microdata Areas (PUMA)
• Neighborhood Tabulation Areas (NTA)

We try to make data available at as fine a geographic resolution as we can. Read more about different geographies at this data story.

It would be convenient if each dataset could be made available at the same geography, but this is not always possible. The neighborhood boundaries available depend on the specifics of the underlying dataset.

When we have multiple years of data, we show the data as trend charts.

Trends for individual neighborhoods tend to be very unstable (or "bouncy"), due to small counts for outcomes in individual neighborhoods. To show clearer trends, we usually aggregate up and show trend data by Borough.

Options on some indicators let you compare this indicator to other similar indicators.

We try to make data available as soon as we can.

Many datasets take a long time to reach us — a "lag" of several years, during which data are gathered from different entities to try to create a complete dataset; data are processed (cleaned, deduplicated, etc), and analyzed. It can take several years to prepare a dataset — so a dataset that is several years old is sometimes the most up-to-date information available. Still, this data continues to show us valuable trends and insights.

We also try to display datasets that have been available for many years. Some datasets (like those that are asked on surveys) are not asked every year of the survey, which means that we cannot provide annual data.

For some datasets, we have to aggregate time periods in order to break down data by borough or neighborhood.

Measures are the numeric ways that a dataset (or indicator) are expressed. Examples of different measures might be: number, percent or rate.

A number tells us how much of an outcome is in a certain area. But a rate (usually expressed as, for example, 40 per 100,000) tells us how much of an outcome there is, relative to the population of the area in question. This lets us compare neighborhoods of different sizes.

On this site, we try to show how environmental factors might be connected to health outcomes. One way we do this is with Correlates. We choose potentially-related datasets and display them on a scatterplot so you can see how these two datasets are correlated.

The Disparities view displays neighborhoods by poverty category to show underlying disparities in the data.

Read more about correlation here.