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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1990

An eight-month climatology of marine stratocumulus cloud fraction, albedo, and integrated liquid water

As part of the FIRE/Extended Time Observations (ETO) program, extended time observations were made at San Nicolas Island (SNI) from March to October, 1987. Hourly averages of air temperature, relative humidity, wind speed and direction, solar irradiance, and downward longwave irradiance were recorded. The radiation sensors were standard Eppley pyranometers (shortwave) and pyrgeometers (longwave). The SNI data were processed in several ways to deduce properties of the stratocumulus covered marine boundary layer (MBL). For example, from the temperature and humidity the lifting condensation level, which is an estimate of the height of the cloud bottom, can be computed. A combination of longwave irradiance statistics can be used to estimate fractional cloud cover. An analysis technique used to estimate the integrated cloud liquid water content (W) and the cloud albedo from the measured solar irradiance is also described. In this approach, the cloud transmittance is computed by dividing the irradiance measured at some time by a clear sky value obtained at the same hour on a cloudless day. From the transmittance and the zenith angle, values of cloud albedo and W are computed using the radiative transfer parameterizations of Stephens (1978). These analysis algorithms were evaluated with 17 days of simultaneous and colocated mm-wave (20.6 and 31.65 GHz) radiometer measurements of W and lidar ceilometer measurements of cloud fraction and cloudbase height made during the FIRE IFO. The algorithms are then applied to the entire data set to produce a climatology of these cloud properties for the eight month period.

Fairall, C. W.↗
NASA NTRS1987

An Exponential Finite Difference Technique for Solving Partial Differential Equations

An exponential finite difference algorithm, as first presented by Bhattacharya for one-dimensianal steady-state, heat conduction in Cartesian coordinates, has been extended. The finite difference algorithm developed was used to solve the diffusion equation in one-dimensional cylindrical coordinates and applied to two- and three-dimensional problems in Cartesian coordinates. The method was also used to solve nonlinear partial differential equations in one (Burger's equation) and two (Boundary Layer equations) dimensional Cartesian coordinates. Predicted results were compared to exact solutions where available, or to results obtained by other numerical methods. It was found that the exponential finite difference method produced results that were more accurate than those obtained by other numerical methods, especially during the initial transient portion of the solution. Other applications made using the exponential finite difference technique included unsteady one-dimensional heat transfer with temperature varying thermal conductivity and the development of the temperature field in a laminar Couette flow.

Handschuh, Robert F.↗
NASA NTRS2007

Characterization of Polar Stratospheric Clouds With Spaceborne Lidar: CALIPSO and the 2006 Antarctic Season

The role of polar stratospheric clouds in polar ozone loss has been well documented. The CALIPSO satellite mission offers a new opportunity to characterize PSCs on spatial and temporal scales previously unavailable. A PSC detection algorithm based on a single wavelength threshold approach has been developed for CALIPSO. The method appears to accurately detect PSCs of all opacities, including tenuous clouds, with a very low rate of false positives and few missed clouds. We applied the algorithm to CALIPSO data acquired during the 2006 Antarctic winter season from 13 June through 31 October. The spatial and temporal distribution of CALIPSO PSC observations is illustrated with weekly maps of PSC occurrence. The evolution of the 2006 PSC season is depicted by time series of daily PSC frequency as a function of altitude. Comparisons with virtual solar occultation data indicate that CALIPSO provides a different view of the PSC season than attained with previous solar occultation satellites. Measurement-based time series of PSC areal coverage and vertically-integrated PSC volume are computed from the CALIPSO data. The observed area covered with PSCs is significantly smaller than would be inferred from a temperature-based proxy such as TNAT but is similar in magnitude to that inferred from TSTS. The potential of CALIPSO measurements for investigating PSC microphysics is illustrated using combinations of lidar backscatter coefficient and volume depolarization to infer composition for two CALIPSO PSC scenes.

Pitts, Michael C.↗
NASA NTRS1993

Passive microwave remote sensing of thin sea ice using principal component analysis

The possibility of developing a satellite-based sea-ice-concentration algorithm which solves for the presence of thinner ice is explored on the basis of time sequences of surface-based measurements of passive MW emission from growing saline ice reported by Wensnahan et al. (1993). It is shown that two classes of thinner ice can be distinguished from mixtures of open water, first-year ice, and multiyear ice. Newly formed ice appears to be optically thick at 37 and 90 GHz and has a relatively dry surface. The thin ice spectrum occurs when the ice is greater than 4 cm thick and appears to result from the accumulation of brine at the ice surface. Thin ice has a relatively stable spectrum characterized by high brightness temperatures, a near-zero spectral gradient at vertical polarization, and a large difference between vertical and horizontal polarizations. It is concluded that thin ice can be detected using satellite data.

Wensnahan, Mark↗
NASA NTRS2005

Bayesian Analysis of the Power Spectrum of the Cosmic Microwave Background

There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background. The sky, when viewed in the microwave, is very uniform, with a nearly perfect blackbody spectrum at 2.7 degrees. Very small amplitude brightness fluctuations (to one part in a million!!) trace small density perturbations in the early universe (roughly 300,000 years after the Big Bang), which later grow through gravitational instability to the large-scale structure seen in redshift surveys... In this talk, I will discuss a Bayesian formulation of this problem; discuss a Gibbs sampling approach to numerically sampling from the Bayesian posterior, and the application of this approach to the first-year data from the Wilkinson Microwave Anisotropy Probe. I will also comment on recent algorithmic developments for this approach to be tractable for the even more massive data set to be returned from the Planck satellite.

Bayesian inference↗
NASA NTRS1974

Application and sensitivity investigation of Fourier transforms for microwave radiometric inversions

Existing microwave radiometer technology now provides a suitable method for remote determination of the ocean surface's absolute brightness temperature. To extract the brightness temperature of the water from the antenna temperature equation, an unstable Fredholm integral equation of the first kind was solved. Fast Fourier Transform techniques were used to invert the integral after it is placed into a cross-correlation form. Application and verification of the methods to a two-dimensional modeling of a laboratory wave tank system were included. The instability of the Fredholm equation was then demonstrated and a restoration procedure was included which smooths the resulting oscillations. With the recent availability and advances of Fast Fourier Transform techniques, the method presented becomes very attractive in the evaluation of large quantities of data. Actual radiometric measurements of sea water are inverted using the restoration method, incorporating the advantages of the Fast Fourier Transform algorithm for computations.

Holmes, J. J.↗
NASA NTRSDate not supplied

Version 8 of the SMAP Level-4 Soil Moisture Data Assimilation Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 9-km resolution, 3-hourly surface (0-5 cm) and root-zone (0-100 cm) soil moisture from April 2015 to present with a mean latency of 2.5 days from the time of observation. The product is based on the assimilation of SMAP L-band (1.4 GHz) brightness temperature (Tb) observations into the NASA Catchment land surface model as the model is driven with observations-based precipitation forcing. This presentation discusses the improvements in the forthcoming Version 8 of L4_SM, including updates in the precipitation forcing, the Catchment model parameters, and the L-band microwave radiative transfer model (mwRTM). The precipitation observations used in L4_SM Version 8 outside of North America and the high latitudes are from the latest (Version 7) NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement mission (IMERG) products. Moreover, occasionally excessive precipitation rates in earlier versions of L4_SM along certain longitudes in North America were eliminated by a bug fix in the precipitation corrections algorithm. The Catchment model in L4_SM Version 8 uses climatological snow albedo values based on observations from the Moderate Resolution Imaging Spectroradiometer, replacing the look-up table parameterization of earlier versions. Additionally, corrected soil parameters were implemented for a small region in Argentina that had erroneously been classified as peat because of an error in the ancillary soil data. Finally, the mwRTM in L4_SM Version 8 uses the Mironov soil mixing approach and updated values of the L-band scattering albedo, soil roughness, and vegetation opacity climatology obtained from the latest (Release 19) SMAP Level-2 dual-channel soil moisture retrieval product. During the development of L4_SM Version 8, the change in the mwRTM parameterization resulted in a reduced unbiased RMSE of surface soil moisture when verified against in situ measurements. It also reduced the standard deviation of the Tb observation-minus-forecast residuals by ~0.15 K, highlighting the importance of the mwRTM for successful data assimilation. The bug fixes in the precipitation corrections algorithm and the Catchment model soil parameters in the Argentina region result in locally large improvements of the simulated land surface states. In summary, the ongoing refinements of the L4_SM product continue to improve its science quality and performance for global soil moisture monitoring

Rolf Reichle↗
NASA NTRS2008

Absorption and Attenuation Coefficients Using the WET Labs ac-s in the Mid-Atlantic Bight: Field Measurements and Data Analysis

Ocean color algorithms are based on the parameterization of apparent optical properties as a function of inherent optical properties. WET Labs underwater absorption and attenuation meters (ac-9 and ac-s) measure both the spectral beam attenuation [c (lambda)] and absorption coefficient [a (lambda)]. The ac-s reports in a continuous range of 390-750 nm with a band pass of 4 nm, totaling approximately 83 distinct wavelengths, while the ac-9 reports at 9 wavelengths. We performed the ac-s field measurements at nine stations in the Mid-Atlantic Bight from water calibrations to data analysis. Onboard the ship, the ac-s was calibrated daily using Milli Q-water. Corrections for the in situ temperature and salinity effects on optical properties of water were applied. Corrections for incomplete recovery of the scattered light in the ac-s absorption tube were performed. The fine scale of spectral and vertical distributions of c (lambda) and a (lambda) were described from the ac-s. The significant relationships between a (674) and that of spectrophotometric analysis and chlorophyll a concentration of discrete water samples were observed.

Ohi, Nobuaki↗
NASA NTRS2004

Polymorphic Electronic Circuits

Polymorphic electronics is a nascent technological discipline that involves, among other things, designing the same circuit to perform different analog and/or digital functions under different conditions. For example, a circuit can be designed to function as an OR gate or an AND gate, depending on the temperature (see figure). Polymorphic electronics can also be considered a subset of polytronics, which is a broader technological discipline in which optical and possibly other information- processing systems could also be designed to perform multiple functions. Polytronics is an outgrowth of evolvable hardware (EHW). The basic concepts and some specific implementations of EHW were described in a number of previous NASA Tech Briefs articles. To recapitulate: The essence of EHW is to design, construct, and test a sequence of populations of circuits that function as incrementally better solutions of a given design problem through the selective, repetitive connection and/or disconnection of capacitors, transistors, amplifiers, inverters, and/or other circuit building blocks. The evolution is guided by a search-and-optimization algorithm (in particular, a genetic algorithm) that operates in the space of possible circuits to find a circuit that exhibits an acceptably close approximation of the desired functionality. The evolved circuits can be tested by computational simulation (in which case the evolution is said to be extrinsic), tested in real hardware (in which case the evolution is said to be intrinsic), or tested in random sequences of computational simulation and real hardware (in which case the evolution is said to be mixtrinsic).

Stoica, Adrian↗
NASA NTRS2013

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations : Sensitivity Tests and Results - Part II

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Monte Carlo Bayesian inference↗
NASA NTRS2019

CoSMIR Performance During the GPM Olympex Campaign

The airborne Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) participated in the Global Precipitation Measurement (GPM) Olympic Mountains Experiment (OLYMPEX) from November to December 2015 with great success. With similar channels as the GPM Microwave Imager (GMI) at 89-183 GHz, CoSMIR served as a proxy for GMI by flying onboard the DC-8 aircraft for a total of 17 science flights, collecting over 72 hours of observations. The high-quality, calibrated brightness temperature dataset is the result of several improvements made to CoSMIR prior to OLYMPEX to make the instrument more reliable. This paper describes these improvements and gives a detailed summary of the CoSMIR measurements obtained from OLYMPEX. CoSMIR experienced minor performance issues during the campaign, most of which were not excessive and only resulted in a loss of approximately four hours of data for the entire campaign. Performance issues are discussed and shown how they were mitigated to achieve a quality dataset. Comparisons of CoSMIR and GMI observations are presented to show that the CoSMIR measurements agree well with GMI. The CoSMIR dataset is publicly available as part of the OLYMPEX data suite and can reliably be used in GPM algorithm development and related studies.

Airborne radiometer↗
NASA NTRS1988

Computations of vortical supersonic flows over a blunt-nose-cylinder at high angles of attack

Three-dimensional, viscous, and separated flows over a blunt-nose-cylinder at 20, 32, and 44-deg attack angles were computed. The approaching freestream was at a Mach number of 1.6 and a unit Reynolds number of 2 x 10 to the 6th/ft with a total temperature of 585 R. The cylinder used for the computations had a length-to-diameter ratio of 6.67 with a base diameter of 3 in. The flowfield was dominated by large-scale and multiple vortices generated by crossflow separation. The effect of turbulence on the flow structure of one case was modeled algebraically with modifications to correct the length and velocity scales in the regions of separation. The mass averaged Navier-Stokes equations were solved by an approximately factored, upwind-biased, implicit, finite volume scheme. The initialization of the flows was enhanced by a mesh sequencing strategy applied to the diagonalized form of the discretized equations. The convergence to steady-state was accelerated by a multigrid algorithm and using the block inversions for the discretized equations. Calculations were compared with experimental results.

Baysal, O.↗
NASA NTRS1994

Tomographic separation of composite spectra. 2: The components of 29 UW Canis Majoris

We have analyzed the UV photospheric lines of 29 CMa, a 4.39 day period, double-lined O-type spectroscopic binary. Archival data from International Ultraviolet Explorer (IUE)(28 spectra well distributed in oribital phase) were analyzed with several techniques. We find that the mass ratio is q = 1.20 +/- 0.16 (secondary more massive) based on three independent arguments. A tomography algorithm was used to produce the separate spectra of the two stars in six UV spectral regions. The MK spectral classifications of the primary and secondary, O7.5-8 Iab and O9.7 Ib, respectively, were estimated through a comparison of UV line ratios with those in spectral standard stars. The flux ratio of the stars in the UV is 0.36 +/- 0.07 (primary brighter). The primary has a strong P Cygni NIV wavelength 1718 feature, indicating a strong stellar wind. We also present tomographic reconstructions of visual spectral data in the range 4300-4950 A, based on seven observations of differing orbital phases, which confirm the UV classifications, and show that the primary is an Of star. From the spectral classifications, we estimate the temperatures of the stars to be 33,750 K and 29,000 K for primary and secondary, respectively. We then fit visual and UV light curves and show that reasonably good fits can be obtained with these temperatures, a semicontact configuration, an inclination of 74 deg. +/- 2 deg., and an intensity ratio r is less than 0.5.

Bagnuolo, William G., Jr.↗
NASA NTRS1999

Corals from Space

The goal of this research is to monitor the health and vigor of coral reef ecosystems, and their sensitivity to natural and anthropogenic climate changes. To achieve these lofty goals, this research is investigating the feasibility of using spaceborne high-resolution spectrometers (on the US Landsat, French Systeme Probatoire pour l'Observation de la Terre [SPOT] and/or the Indian Resources Satellite [IRS 1C & 1D] spacecraft) to first map the aerial extent of coral reef systems, and second separate the amount of particular corals. If this is successful, we could potentially provide a quantum leap in our understanding of coral reef systems, as well as provide much needed baseline data to measure future changes in global coral reef ecosystems. In collaboration with Tomas Tomascik, Yann Morel, and other colleagues, a series of experiments were planned to coordinate in situ coral observations, high-resolution spaceborne imagery (from Landsat, SPOT, and, possibly, IRS IC spacecraft), and NASA Space Shuttle photographs and digital images. Our eventual goal is to develop "coral health algorithms" that can be used to assess time series of imagery collected from satellite sensors (Landsat since 1972, SPOT since 1986) in concert with in situ observations. The bad news from last year was that from 1997 to mid- 1998, the extreme cloudiness over southeast Asia due to prolonged smoke from El Nino-related fires and the economic chaos in this region frustrated both our space and reef-based data collection activities. When this volatile situation stabilizes, we will restart these activities. The good news was that in collaboration with Al Strong at the National Oceanic and Atmospheric Administration (NOAA) we had an exciting year operationally using the NOAA's Advanced Very High Resolution Radiometer sensor derived sea surface temperature products to warn of coral "bleaching" at many locations throughout the tropics. Data from NOAA's satellites showed that during the El Nino of 1997 and the first half of 1998, more ocean area in the tropics experienced exceptionally high sea surface temperatures, or "hot spots," than have been observed in any fall year since the El Nino of 1982. From January to July, the coral bleaching events were concentrated in the Southern Hemisphere (during its warm season). Since July 1998, the reports of extensive coral bleaching have again spread into regions of the Northern Hemisphere following abnormally high sea surface temperatures, especially around the Philippines and throughout the Caribbean Basin, Bahamas, Bermuda and Florida Keys. These El Nino induced events clearly demonstrated that corals are the "canaries of the marine ecosystem," highly sensitive to short-term natural climate events (El Nino), and should be monitored as measures of longer-term environmental and climate change. Additional information is contained in the original.

Patzert, William C.↗
NASA NTRS2016

Assessment of the SMAP Passive Soil Moisture Product

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

passive↗
NASA NTRS2001

Spectral Data Assimilation for Merging Satellite Ocean Color Imagery

The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project was initiated 'to develop a methodology and operational capability to combine data products from various ocean color missions in a manner that ensures the best possible global coverage and best exploits the complementary missions of the sensors'. While the merging of data from multiple sources has already been implemented for sea surface temperature (SST), altimetry or clouds, this is a new topic in ocean color science. Merging ocean color data has obvious advantage in terms of spatial and temporal coverage of the global ocean but data merging should also result in new, more diverse and improved data products with lower uncertainties. The merging of ocean color satellite data is generally considered at the level of the global gridded products, i.e., NASA Level-3 and, more specifically, for the merging of chlorophyll a concentration data, [Ch1]. This approach limits computational issues and deals with a unique, simple quantity, [Ch1]. However, ocean color data merging can also be conducted at the level of water-leaving radiances, LwN(lamda), using either empirical or semi-analytical algorithms. Although more challenging, this latter approach is potentially extremely powerful as it can achieve good consistency in the final data products and can take advantage of both the specificities and differences of each source of data. The demonstration of the feasibility of such approach is the main objective of our SIMBIOS work. Here, we use a semi-analytical algorithm to merge Rrs (or, equivalently LwN) data from different sources to estimate [Ch1]. The model also allows for the retrieval of other quantities such as the combined absorption of colored detrital particulate and dissolved organic matter at 443 nm, a(sub cdm)(443) and the particulate backscattering, b(sub bp)(443).

Siegel, David A.↗
NASA NTRSDate not supplied

Surface Radiation Budget (SRB) Release 2.5 QC Longwave Monthly Data in Native Format (SRB_REL2.5_QCLW_MONTHLY)

The surface radiation budget data include downward and net longwave fluxes, as well as three meteorological parameters for the entire globe between 07/01/1983 and 06/30/2005. These parameters were derived within the Quality-Check LW (QCLW) algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=monthly; Temporal_Resolution_Range=monthly].

RADIATIVE FLUX↗
NASA NTRS2014

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗