Nitrogen dioxide (NO2) is a key component of urban air pollution. The nitrogen oxides ("NOx" of which NO2 is one component) are emitted from any combustion process. Coal- and gas-fired power plants and vehicles constitute the major anthropogenic (human-produced) sources. Forest fires and lightning are natural sources of NO2, but globally it is clear that anthropogenic sources dominate.
High levels of NO2 are significant as they are associated with: 1) haze that reduces visibility; 2) irritation of the eyes, nose, throat, and lungs; 3) acid rain; 4) reduced terrestrial plant growth; 5) oxygen-depleting algal blooms; and 6) corrosion of building materials.
Because of the importance of trace pollutants such as NO2 for air quality and human health around the world, instruments have been developed and installed on research satellites to measure NO2 on Earth. Collaborative teams from space agencies around the world build the sensors and retrieval algorithms to make these space-based images available to the world scientific and policy-making communities.
This animation shows a time series of NO2 measured from such satellites from October 2004 to December 2009. These particular images were captured by the Dutch-Finnish Ozone Monitoring Instrument (OMI) on NASA's Earth Observing System AURA satellite. One of the objectives of the AURA mission is to measure trace pollutants such as NO2, ozone, carbon monoxide, and aerosols by their interaction with light of visible and non-visible wavelengths. These data have been converted to false-color images so the viewer can "see" hot spots in NO2 concentration around the globe.
NO2 is a pollutant with a relatively short atmospheric lifetime, so it does not get transported far from its source. Thus, these satellite images provide a direct indication of where NO2 sources are located. In remote, unpolluted regions of the globe, NO2 will be uniformly low.
Several striking observations can be made from this global view of the NO2 air pollutant.
First, the dominant NO2 source regions correspond primarily to areas with high population and large industry, for example, eastern China, northern Europe, and the eastern United States. Because most electricity is produced by burning fossil fuels in power plants that emit NO2, these hot spots are strongly correlated with electricity usage and fuel sources.
Second, urban centers show up as smaller hot spots. High vehicle traffic leads to elevated NO2. For example, Mexico City, Tokyo, and Los Angeles are all clearly marked by their NO2 plume. If one zooms in to California, the north-south transit corridor of the I-5 freeway is actually visible from space via its NO2 signature.
Third, a clear seasonal pattern is apparent. In the northern hemisphere winter, peak NO2 is much higher in all the northern hemisphere hot spots. This is attributed both to heavier use of combustion power plants for wintertime home heating, as well as the fact that NO2 stays in the air longer in the winter. The atmospheric lifetime of NO2 is driven primarily by reactions initiated by sunlight. With less sunlight in the wintertime, reactions that break down NO2 are not easily initiated, and the NO2 is removed more slowly from the atmosphere. Urban areas report NO2 air quality standard "exceedance" events, when the level of this pollutant is higher than deemed safe by environmental agencies. This happens most frequently during the cold winter months.
Similarly, one sees hot spots over urban centers in the southern hemisphere during their local winter (June - September). In addition, some years see spread out elevated regional NO2 over southern Brazil and sub-Saharan Africa, typically peaking in September. This is the signature of "biomass burning," when large swathes of forest burn in those regions. Some seasonal burning is apparent in northern Australia as well. These are significant contributions to southern hemisphere NO2 but are dwarfed in comparison to northern hemisphere industry.
Finally, we can look for evidence of a long-term trend in regional NO2 emissions. Comparing December 2009 to December 2004, there is higher regional NO2 in China compared to North America or Northern Europe in 2009. This correlates with China's booming economy in recent years. In December of 2004 the relative amounts of NO2 over these regions was more consistent. This can be attributed both to economic activity as well as to effective policy efforts to reduce NOx emissions in some countries.
These satellite datasets provide a rich basis for interpretation of urban/rural, seasonal, and decadal (long-term) trends in air quality.
C1 Patterns. Students identify similarities and differences in order to sort and classify natural objects and designed products. They identify patterns related to time, including simple rates of change and cycles, and to use these patterns to make predictions.
C3 Scale Proportion and Quantity. Students recognize natural objects and observable phenomena exist from the very small to the immensely large. They use standard units to measure and describe physical quantities such as weight, time, temperature, and volume.
C4 Systems and System Models. Students understand that a system is a group of related parts that make up a whole and can carry out functions its individual parts cannot. They can also describe a system in terms of its components and their interactions.
C1 Patterns. Students recognize that macroscopic patterns are related to the nature of microscopic and atomic-level structure. They identify patterns in rates of change and other numerical relationships that provide information about natural and human designed systems. They use patterns to identify cause and effect relationships, and use graphs and charts to identify patterns in data.
C3 Scale Proportion and Quantity. Students observe time, space, and energy phenomena at various scales using models to study systems that are too large or too small. They understand phenomena observed at one scale may not be observable at another scale, and the function of natural and designed systems may change with scale. They use proportional relationships (e.g., speed as the ratio of distance traveled to time taken) to gather information about the magnitude of properties and processes. They represent scientific relationships through the use of algebraic expressions and equations
C6 Structures and Functions. Students model complex and microscopic structures and systems and visualize how their function depends on the shapes, composition, and relationships among its parts. They analyze many complex natural and designed structures and systems to determine how they function. They design structures to serve particular functions by taking into account properties of different materials, and how materials can be shaped and used.
C1 Patterns. Students observe patterns in systems at different scales and cite patterns as empirical evidence for causality in supporting their explanations of phenomena. They recognize classifications or explanations used at one scale may not be useful or need revision using a different scale; thus requiring improved investigations and experiments. They use mathematical representations to identify certain patterns and analyze patterns of performance in order to re-engineer and improve a designed system.
C3 Scale Proportion and Quantity. Students understand the significance of a phenomenon is dependent on the scale, proportion, and quantity at which it occurs. They recognize patterns observable at one scale may not be observable or exist at other scales, and some systems can only be studied indirectly as they are too small, too large, too fast, or too slow to observe directly. Students use orders of magnitude to understand how a model at one scale relates to a model at another scale. They use algebraic thinking to examine scientific data and predict the effect of a change in one variable on another (e.g., linear growth vs. exponential growth).
C4 Systems and System Models. Students can investigate or analyze a system by defining its boundaries and initial conditions, as well as its inputs and outputs. They can use models (e.g., physical, mathematical, computer models) to simulate the flow of energy, matter, and interactions within and between systems at different scales. They can also use models and simulations to predict the behavior of a system, and recognize that these predictions have limited precision and reliability due to the assumptions and approximations inherent in the models. They can also design systems to do specific tasks.
ESS2.D Weather & Climate. Weather is the combination of sunlight, wind, snow or rain, and temperature in a particular region and time. People record weather patterns over time
ESS3.C Human Impact on Earth systems. Societal activities have had major effects on the land, ocean, atmosphere, and even outer space. Societal activities can also help protect Earth’s resources and environments.
PS1.A Structure of Matter. Because matter exists as particles that are too small to see, matter is always conserved even if it seems to disappear. Measurements of a variety of observable properties can be used to identify particular materials.
PS1.B Chemical Reactions. Chemical reactions that occur when substances are mixed can be identified by the emergence of substances with different properties; the total mass remains the same.
ESS2.D Weather & Climate. Complex interactions determine local weather patterns and influence climate, including the role of the ocean.
ESS3.C Human Impact on Earth systems. Human activities have altered the biosphere, sometimes damaging it, although changes to environments can have different impacts for different living things. Activities and technologies can be engineered to reduce people’s impacts on Earth.
LS2.A Interdependent Relationships in Ecosystems. Organisms and populations are dependent on their environmental interactions both with other living things and with nonliving factors, any of which can limit their growth. Competitive, predatory, and mutually beneficial interactions vary across ecosystems but the patterns are shared.
PS1.A Structure of Matter. The fact that matter is composed of atoms and molecules can be used to explain the properties of substances, diversity of materials, states of matter, phase changes, and conservation of matter.
PS1.B Chemical Reactions. Reacting substances rearrange to form different molecules, but the number of atoms is conserved. Some reactions release energy and others absorb energy.
ESS2.D Weather & Climate. The role of radiation from the sun and its interactions with the atmosphere, ocean, and land are the foundation for the global climate system. Global climate models are used to predict future changes, including changes influenced by human behavior and natural factors
ESS3.C Human Impact on Earth systems. Sustainability of human societies and the biodiversity that supports them requires responsible management of natural resources, including the development of technologies that produce less pollution and waste and that preclude ecosystem degradation.
LS2.A Interdependent Relationships in Ecosystems. Ecosystems have carrying capacities resulting from biotic and abiotic factors. The fundamental tension between resource availability and organism populations affects the abundance of species in any given ecosystem.
PS1.A Structure of Matter. The sub-atomic structural model and interactions between electric charges at the atomic scale can be used to explain the structure and interactions of matter, including chemical reactions and nuclear processes. Repeating patterns of the periodic table reflect patterns of outer electrons. A stable molecule has less energy than the same set of atoms separated; one must provide at least this energy to take the molecule apart
PS1.B Chemical Reactions. Chemical processes are understood in terms of collisions of molecules, rearrangement of atoms, and changes in energy as determined by properties of elements involved.
PS2.C Stability & Instability in Physical Systems. Systems often change in predictable ways; understanding the forces that drive the transformations and cycles within a system, as well as the forces imposed on the system from the outside, helps predict its behavior under a variety of conditions. When a system has a great number of component pieces, one may not be able to predict much about its precise future. For such systems (e.g., with very many colliding molecules), one can often predict average but not detailed properties and behaviors (e.g., average temperature, motion, and rates of chemical change but not the trajectories or other changes of particular molecules). Systems may evolve in unpredictable ways when the outcome depends sensitively on the starting condition and the starting condition cannot be specified precisely enough to distinguish between different possible outcomes.
Boersma, K.F., H.J. Eskes, J.P. Veefkind, E.J. Brinksma, R.J. van der A, M. Sneep, G.H.J. van den Oord, P.F. Levelt, P. Stammes, J.F. Gleason and E.J. Bucsela, Near-real time retrieval of tropospheric NO2 from OMI, Atm. Chem. Phys., 2013-2128, sref:1680-7