2.1.

Background

The MISR instrument³³ was launched into polar, sun-synchronous orbit aboard NASA’s Terra spacecraft on December 18, 1999. Routine Earth observations began on February 24, 2000. MISR uses nine separate cameras to image the Earth at nine discrete view angles: 0 deg (nadir) and 26.1 deg, 45.6 deg, 60.0 deg, and 70.5 deg forward and backward of nadir. Pushbroom imagery at 275-m- to 1.1-km spatial resolution over a 400-km-wide swath is acquired in four visible/near-infrared (VNIR) spectral bands (446, 558, 672, and 866 nm) in each camera by making use of spacecraft motion and linear detector arrays. MISR was designed to improve our understanding of the Earth’s climate, ecology, and environment. The suite of validated geophysical data products³⁸ is generated and archived for public distribution at the NASA Langley Atmospheric Science Data Center (ASDC). An extensive bibliography of peer-reviewed publications describing, applying, and validating MISR data for studies of aerosol climate, air quality, and health impacts, radiation and cloud–climate interactions, cloud-tracked winds, and surface biospheric and cryospheric science is available on the MISR website.³⁹

2.2.

Aerosol Data Product Generation

Among the objectives of the MISR investigation is global mapping of aerosols. Direct radiative effects of aerosols, both in magnitude and sign, depend principally on the aerosol optical depth (AOD), single scattering albedo, scattering phase function, and the albedo of the underlying surface. Aerosols also have indirect climate and hydrological impacts through their effects on the albedos, lifetimes, and microphysical properties of clouds, and play a major role in human and environmental health.

Multiangle radiance observations are valuable for enhancing the aerosol signal relative to surface reflection and providing sensitivity to the aerosol scattering phase functions, which are governed by particle size, shape, and composition.^40–42 Radiative-transfer-based algorithms are applied to radiometrically calibrated, georectified, and cloud-screened MISR multiangle, multispectral imagery to generate the aerosol product. Over land, two main algorithms work together. The first, known as heterogeneous land, utilizes spatial contrasts to derive an empirical orthogonal function representation of the surface contribution to the measured multiangle radiances.⁴³ The second, known as homogeneous land, uses similarity in the angular shape of surface bidirectional reflectance factors (BRFs) among the four spectral bands as a constraint on the aerosol retrievals.⁴⁴ Both algorithms make use of the multiangular nature of the MISR observations. By employing a lookup table consisting of 74 mixtures of aerosol particles having prescribed microphysical and optical properties and using several goodness-of-fit metrics to compare modeled top-of-atmosphere radiances to the MISR observations, the retrieval algorithm provides sensitivity to both AOD and aerosol types.³⁵

2.3.

Application to Air Quality and Human Health

Comparisons of MISR AODs with independent ground-based sunphotometer AODs from the Aerosol Robotic Network (AERONET)⁴⁵ show a high positive correlation,^46,47 including over arid land and urban areas.^48–50 As a result, MISR is one of several satellite instruments contributing to widely used global maps of ${\mathrm{PM}}_{2.5}$.^24,25,51 MISR’s sensitivity to particle type enables separation of anthropogenic aerosols from dust, which has led to improved estimates of ground-level ${\mathrm{PM}}_{2.5}$ concentrations in the arid western United States compared with single-angle approaches.^52,53 These multivariate regression models were initially developed to explore MISR’s ability to quantitatively characterize ground-level concentrations of ${\mathrm{PM}}_{2.5}$ components such as sulfate, nitrate, organic carbon (OC), and elemental carbon (EC). Later, a more flexible generalized additive model (GAM) using MISR fractional AOD (partitioned by particle properties) scaled by vertical profiles of aerosol loading from the GEOS-Chem transport model was able to explain 70% of the variability in sulfate concentrations measured by surface monitors.⁵⁴ Particle size and shape information from MISR retrievals has been used to associate anthropogenic pollution with significant decadal rise in AOD and ground-level ${\mathrm{PM}}_{2.5}$ over urban centers and densely populated rural areas in India.^55,56

Validation of MISR aerosol retrievals using the operational 17.6-km resolution product demonstrated high accuracy over land for AOD $<0.5$ and systematic underestimation (though high correlation) at high aerosol loading.^46–50 Hierarchical Bayesian modeling and statistical analysis of this product suggested potential benefits of going to higher spatial resolution.^57,58 Given the value of finer spatial detail for studies of urban air quality, the MISR retrieval algorithm was recently adapted to operate on a 4.4-km spatial grid, and prototyping of the updated code demonstrated significant improvements in terms of accuracy, coverage, and mapping of spatial gradients.⁵⁹ Consequently, the operational aerosol product was upgraded from 17.6-km (version 22) to 4.4-km spatial resolution (version 23), and the V23 product was made publicly available in late 2017. An example of the improvement in spatial resolution and coverage is shown in Fig. 1. These data are from a Terra overpass of southeastern Texas and western Louisiana on February 14, 2013. The 4.4-km resolution product does a superior job in pinpointing elevated AODs over Houston and the Red River Valley.

Fig. 1

Example comparison of 17.6-km (V22) and 4.4-km (V23) MISR AOD retrieval.

Prototype versions of MISR’s 4.4-km aerosol product have been used over parts of southern and central California to estimate daily-averaged ${\mathrm{PM}}_{2.5}$, ${\mathrm{PM}}_{10}$, and speciated ${\mathrm{PM}}_{2.5}$ concentrations. Through leave-one-out cross-validation against the EPA’s federal reference method measurements, the product was shown to capture ${\mathrm{PM}}_{2.5}$ spatial variability at the grid scale and to separate ${\mathrm{PM}}_{2.5}$ and ${\mathrm{PM}}_{10}$ size modes in the greater Los Angeles area.⁶⁰ Another recent study applied GAMs to 15 years of the prototype 4.4-km product, and showed that the GAMs are able to explain 66%, 62%, 55%, and 58% of the variability in daily-averaged ${\mathrm{PM}}_{2.5}$ sulfate, nitrate, OC, and EC concentrations.⁶¹

3.1.

Background

NASA selected the MAIA investigation in 2016 as part of its Earth Venture Instrument program. The MAIA instrument builds upon MISR’s legacy and adds new measurement capabilities for determining concentrations of total fine (${\mathrm{PM}}_{2.5}$) and coarse (${\mathrm{PM}}_{10}-{\mathrm{PM}}_{2.5}$) particles, along with the amounts of hydrated nonorganics, OC, black carbon (BC) or EC, and mineral dust in the fine particle mixtures. An integrated satellite/surface-level data and modeling strategy⁶² is used to generate daily mean PM values on a 1-km grid. This approach enables further separating the nonorganics into sulfate and nitrate contributions. The main challenges that MAIA aims to address are to demonstrate that current satellite-based strategies for mapping total ${\mathrm{PM}}_{2.5}$ mass can be extended to include speciation, and that the approach can be implemented on an operational basis.

MAIA’s primary objective is to assess the impacts of different types of airborne PM on human health. The planned investigation consists of several elements: (1) the MAIA satellite instrument, (2) algorithms and software to generate PM maps using data from the MAIA instrument, surface monitors, and CTMs, and (3) epidemiological studies using the MAIA PM maps and geocoded health data to associate different types of PMs with adverse health outcomes. By increasing the density of spatial sampling and the coverage of PM in the targeted regions, MAIA overcomes a major impediment faced by prior studies that have examined the health impacts of specific PM types,^63–67 namely their limited ability to accurately assess exposure due to the small number of ground-based speciated PM monitors. To support other atmospheric science research, MAIA plans to collect measurements over areas that are of value for studying aerosol and cloud impacts on Earth’s climate, and over extreme events such as wildfires, dust storms, and erupting volcanoes. Demonstration in Earth orbit of the new imaging technologies used in the MAIA instrument will also benefit NASA’s planning for future missions.

3.2.

Instrument Design

The MAIA instrument is designed to combine multispectral, polarimetric, and multiangular capabilities into a single, integrated imaging system capable of mapping total and speciated PM at the neighborhood scale. At the heart of the instrument is a pushbroom camera mounted on a two-axis gimbal.

3.2.3.

Multiangle imaging, areal coverage, and spatial resolution

The MAIA camera is a four-mirror $f/5.6$ optical system with cross-track and along-track focal lengths at the center of the optical field of view of 57 and 61 mm, respectively. As the MAIA orbit is not yet known, this design accommodates any orbit altitude between 600 and 850 km. Unlike MISR, which contains multiple cameras pointed at discrete along-track view angles, MAIA’s single camera is mounted on a biaxial gimbal assembly that can point the camera field of view to any along-track and cross-track position within a bidirectional field of regard. A mini dual-drive actuator (MDDA) drives each gimbal axis. The MDDA has been used on MISR and other satellite instruments, and provides each gimbal axis with 100% redundancy and resilience to single-point mechanical or electrical faults.

The targeting nature of the MAIA instrument enables routine multiangle observations of a globally distributed set of study sites. The along-track (scan) gimbal has a $\pm 58\text{-}\mathrm{deg}$ range of motion, while the cross-track (pan) gimbal has a $\pm 39\text{-}\mathrm{deg}$ range of motion, which when added to the $\pm 9\text{-}\mathrm{deg}$ cross-track field of view provides a $\pm 48\text{-}\mathrm{deg}$ cross-track field of regard. The pan capability permits access to targets that are not directly situated on the subspacecraft track, making it possible to observe each target, on average, at least three times per week. Images of the same area can be observed at a set of discrete view angles in a “step-and-stare” sequence. A “sweep” mode of operation in which the scan gimbal moves continuously over its accessible range is also possible.

For most targets, images would be acquired using the step-and-stare mode (Fig. 2). In this mode, the gimbals orient the camera to view the target’s leading edge, beginning at the most oblique forward view angle. Pushbroom imagery is acquired while the camera remains fixed at this angle, after which the scan gimbal moves to the next (smaller) forward view angle and imagery of the same area is reacquired. This sequence repeats until observations are acquired at all commanded angles. The pan actuator compensates for Earth rotation between views. Observing at five view angles would yield target lengths $>330\mathrm{km}$ from a 600-km orbit and $>420\mathrm{km}$ from an 850-km orbit. The number of view angles is selectable, with more angles resulting in a shorter along-track distance seen in common by all views. At nadir, the camera design covers a cross-track swath width of 192 km for an orbit altitude of 600 km, increasing to 272 km at 850-km altitude. Even at the lowest altitude, the target dimensions cover major metropolitan areas. Footprint sizes are on the order of 200 m at nadir and increase with view angle, particularly in the along-track direction. At the highest orbit altitude and most oblique view angle, the along-track footprint size remains below 1100 m, and is oversampled by a factor of 4.5 as a result of the pushbroom frame rate.

Fig. 2

Example MAIA step-and-stare sequence, showing the case of five discrete view angles.

3.2.4.

Instrument system

A conceptual layout of the MAIA instrument is shown in Fig. 3. A cylindrical barrel serves as a radiator to dissipate heat from the camera electronics. Another radiator, positioned to view deep space, dissipates heat from the focal plane, which is passively cooled to 225 K to limit dark current in the SWIR detectors. Other parts of the instrument include the structural supports, the biaxial gimbal assembly, the instrument electronics, an onboard calibrator (OBC), and a dark target (DT). The OBC consists of a glass diffuser and an array of wiregrid polarizers, and is illuminated by sunlight as the spacecraft traverses one of the orbital poles. The DT is a light-shielded cavity for measurement of dark levels. The biaxial gimbal enables periodically pointing the camera at these calibrators, and the data acquired are used in ground data processing to update the polarimetric and dark offset calibrations.

Fig. 3

Conceptual layout of the MAIA instrument.

3.3.

Science Operations

MAIA is to be launched into a low-Earth, sun-synchronous, polar orbit at an altitude in the 600- to 850-km range. The orbit altitude and mean local time of equator crossing will be established once the host spacecraft has been selected. Mid- to late-morning overpass time is preferred to allow for fog burn-off and boundary layer mixing and because fewer clouds are expected in the morning than in the afternoon.⁸³ In addition, because the accessible area within the instrument field of regard increases with orbit altitude, target revisit frequencies generally increase as orbit altitude increases. NASA is planning to select the host spacecraft in late 2018, and launch is expected to occur no earlier than mid-2021. The baseline mission duration is 3 years.

Science data would be collected, on average, over one target per orbit, resulting in about 100 acquisitions per week. Typical volume per target of the instrument data is estimated at 29 Gbit, slightly larger than the volume generated in one orbit by MISR, despite the fact that MAIA observes discrete targets, while MISR observes the illuminated side of the Earth continuously. This is a result of the larger number of spectral bands in MAIA, the collection of polarimetric data, and the use of onboard spatial averaging in MISR. Primary target areas (PTAs) are major population centers designated for conducting epidemiological investigations by the MAIA Science Team. PTAs would be observed in a step-and-stare mode and are selected to include major population centers covering a range of PM concentrations and particle types; surface-based aerosol sunphotometers (e.g., from AERONET⁴⁵) for aerosol retrieval validation; PM mass, size discrimination, and chemical speciation monitors associated with various measurement networks^84,85 to enable development of statistical and machine learning regression models that relate retrieved column-integrated aerosol properties to near-surface PM; and health data geocoded by home addresses, zip codes, census block groups, or similar locations of study subjects. Secondary target areas (STAs) are regions of interest for air quality or other aerosol and cloud research (e.g., climate science) and would make use of either the step-and-stare or sweep mode, depending on the measurement objective. STAs do not have the same requirements on surface monitor availability as PTAs and the feasibility of higher-level data processing beyond generation of calibrated and georectified imagery (see § 3.4.1) would be assessed on a case-by-case basis. Calibration/validation target areas (CVTAs) would be observed routinely for instrument calibration and stability monitoring, and aerosol/PM validation. As the MAIA instrument does not contain an absolute radiometric calibrator, the prelaunch camera calibration will be routinely updated via vicarious calibrations over Railroad Valley, Nevada. The vicarious calibration technique has been widely adopted by many satellite sensor investigations and uses surface and atmospheric measurements acquired at the time of satellite overpass to compute top-of-atmosphere radiance and to update the instrument radiometric response. MAIA observations of noninstrumented but stable Earth targets, such as the Libya-4 desert site, will also be used to maintain the radiometric calibration uncertainty to within $\pm 4\%$ over bright targets ($\pm 6\%$ over dark targets). A candidate set of PTAs, STAs, and CVTAs is shown in Fig. 4. Specialized acquisitions over targets of opportunity may be acquired over episodic events, such as volcanic eruptions, major wildfires, or dust storms.

Fig. 4

Candidate set of PTAs, STAs, and CVTAs and representative cities.

The candidate PTAs and STAs shown in Fig. 4 include historically understudied areas (e.g., Africa). The list is subject to future updates, as observability of some targets will depend on the orbit altitude of the host spacecraft and negotiations for access to the requisite surface monitors and health data are still in process.

3.4.

Data Processing and Products

MAIA data products follow the NASA hierarchy from level 0 (raw instrument data) to level 1 (calibrated and georectified imagery), level 2 (geophysical products at the same location as level 1 source data), and level 4 (integration of measured and modeled results). As spatial gridding and map projection are incorporated into level 1 processing in a similar manner as is done for MISR,⁸⁶ MAIA does not identify separate level 3 products. Data processing software developed at the MAIA science computing facility at JPL (with algorithmic approaches and software partially inherited from the MISR and AirMSPI projects) will be delivered to the NASA Langley ASDC for product generation.

3.5.

Science Investigation

Various epidemiological studies are planned for the different MAIA PTAs depending on the predominant PM species present, the type of health records available, and previous studies of the effects of air pollution in each area. Well-established epidemiological methodologies, such as time-series, case-crossover, and cohort-study designs^107–109 will be used.

Information about the candidate set of PTAs (see Fig. 4) is shown in Table 2. The MAIA science team plans to focus on health effects associated with a range of PM concentrations and different time scales of exposure. Acute exposure takes place over a period of several days and is generally associated with premature mortality and increased hospital visits due to both cardiovascular and respiratory diseases. These studies are conducted by analyzing vital statistics records (e.g., death certificates) and records of hospital admissions or emergency room visits. Subchronic exposure studies are primarily aimed at birth outcomes and pregnancy complications, such as low birth weight and preeclampsia. These outcomes are usually investigated by analyzing birth records contained in an area’s vital statistics data, or by establishing a birth cohort. Chronic exposure studies usually track individual-level health effects over multiple years, and are important as they document morbidity and mortality risk increases and are often used in GBD estimates. These are generally done with an established cohort or by analyzing existing health records combined with long-term residency data.¹¹¹

Table 2

Characteristics of the candidate PTAs.

As noted earlier, the baseline MAIA mission is 3 years in duration. Many epidemiological studies conducted around the world have reported associations between acute (daily) PM exposure and mortality, hospital admissions, and emergency department visits using $<3$ years of data in densely populated regions.^112–115 Adverse impacts on prenatal or neonatal development, e.g., restricted intrauterine growth, preterm delivery, low birth weight, congenital heart defects, and infant mortality,^5,116,117 have been associated with PM exposure during specific pregnancy trimesters.^118,119 Hence, investigations into birth outcomes targeting trimester specific effects can even utilize $<1$ year of data if the population of pregnant women residing in the area is large enough.^120–122 Long-term studies relating chronic exposure to cardiovascular disease have also benefited from only 2 to 3 years of data, and several have obtained statistically significant results using only a single year.^65,123–128 Although this may seem surprising, PM spatial patterns and the rank order tend to be fairly stable from year to year, and results show that the inferred health impacts from shorter-term exposures are consistent with studies using longer exposure periods.⁶⁵ These epidemiological studies targeting chronic health outcomes typically make use of large cohorts (groups of people, who have been exposed to air pollutants at different levels or compositions over long periods of time).

Health studies with geocoded subject locations at high spatial resolution (address level) enable the most accurate estimation of PM exposure-related health effects. MAIA’s resolution enables PM retrievals on a 1-km grid for sampling within the neighborhood scale. Although sulfate has relatively low spatial variability at urban-to-regional scales,¹²⁹ nitrate and primary OC vary over smaller spatial scales. BC aerosols are very heterogeneous due to their generation from traffic fuel combustion and biomass burning.^129,130 Recent research highlights the value of 1-km satellite-based aerosol data for health effect studies.^96,131–133