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Abstract To investigate the unmet needs for rehabilitation services among middle-aged and older adults in Chengdu, Sichuan, China, and identify the associated factors. This cross-sectional study was conducted on middle-aged and older adults in Chengdu, Sichuan, China, between 2015 and 2016. The questionnaire included demographic data and questions about rehabilitation needs. Multivariable logistic regression analysis was used to identify the associated factors of unmet needs for rehabilitation services. Among 663 participants, 91.70% needed medical rehabilitation (608/663), 26.55% of who need auxiliary equipment (176/663), 77.07% of who need daily care and social participation (511/663), and 79.34% of who need recreational therapy activities (526/663), while

Abstract To prepare for implementation of a new aerosol retrieval specifically designed for dust aerosol over ocean in the operational Dark‐Target (DT) algorithms for the Moderate‐resolution Imaging Spectrometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensors, we focus on the challenge of detecting dust. We first survey the literature on existing dust detection algorithms and then develop an innovative algorithm that combines near‐UV (deep blue), visible, and thermal infrared (TIR) wavelength spectral tests. The new detection algorithm is applied to Terra and Aqua MODIS granules and compared with other dust detection possibilities from existing MODIS products. Quantitative evaluation of the new dust detection algorithm is conducted using both a collocated AERONET‐MODIS data set and collocated Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)‐MODIS data set. From comparison with both AERONET and CALIOP measurements, we estimate the new dust detection algorithm detects about 30% of weakly dusty pixels and more than 80% of heavily dusty pixels, with false detections in the range of 1–2%. The very low false detection rate is particularly noteworthy in comparison with existing literature. Compared with the dust flag currently available as part of the MODIS cloud mask product (MOD35/MYD35), and dust classification based on commonly used thresholds with aerosol optical depth (AOD) and Angstrom exponent (AE), the new dust detection algorithm finds more dusty pixels and fewer false detections.

The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.

For reflected sunlight observed from space at visible and near-infrared wavelengths, particles suspended in Earth’s atmosphere provide contrast with vegetation or dark water at the surface. This is the physical motivation for the Dark Target (DT) aerosol retrieval algorithm developed for the Moderate Resolution Imaging Spectrometer (MODIS). To extend the data record of aerosol optical depth (AOD) beyond the expected 20-year lifespan of the MODIS sensors, DT must be adapted for other sensors. A version of the DT AOD retrieval for the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar-Orbiting Partnership (SNPP) is now mature enough to be released as a standard data product, and includes some upgraded features from the MODIS version. Differences between MODIS Aqua and VIIRS SNPP lead to some inevitable disagreement between their respective AOD measurements, but the offset between the VIIRS SNPP and MODIS Aqua records is smaller than the offset between those of MODIS Aqua and MODIS Terra. The VIIRS SNPP retrieval shows good agreement with ground-based measurements. For most purposes, DT for VIIRS SNPP is consistent enough and in close enough agreement with MODIS to continue the record of satellite AOD. The reasons for the offset from MODIS Aqua, and its spatial and temporal variability, are investigated in this study.

This study characterizes a massive African dust intrusion into the Caribbean Basin and southern U.S. in June 2020, which is nicknamed the Godzilla dust plume, using a comprehensive set of satellite and ground-based observations (including MODIS, CALIOP, SEVIRI, AERONET, and EPA Air Quality network) and the NASA GEOS global aerosol transport model. The MODIS data record registered this massive dust intrusion event as the most intense episode over the past two decades. During this event, the aerosol optical depth observed by AERONET and MODIS peaked at 3.5 off the coast of West Africa and 1.8 in the Caribbean Basin. CALIOP observations show that the top of dust plume reached altitudes of 6-8 km in West Africa and descended to about 4 km altitude over the Caribbean Basin and 2 km over the U.S. Gulf coast. The dust plume degraded the air quality in Puerto Rico to the hazardous level, with maximum daily PM10 concentration of 453 μg m-3 recorded on June 23. The dust intrusion into the U.S. raised the PM2.5 concentration on June 27 to a level exceeding the EPA air quality standard in about 40 % of the stations in the southern U.S. Satellite observations reveal that dust emissions from convection-generated haboobs and other sources in West Africa were large albeit not extreme on a daily basis. However, the anomalous strength and northern shift of the North Atlantic Subtropical High (NASH) together with the Azores low formed a closed circulation pattern that allowed for accumulation of the dust near the African coast for about four days. When the NASH was weakened and wandered back to south, the dust outflow region was dominated by a strong African Easterly Jet that rapidly transported the accumulated dust from the coastal region toward the Caribbean Basin, resulting in the record-breaking African dust intrusion. In comparison to satellite observations, the GEOS model well reproduced the MODIS observed tracks of the meandering dust plume as it was carried by the wind systems. However, the model substantially underestimated dust emissions from haboobs and did not lift up enough dust to the middle troposphere for ensuing long-range transport. Consequently, the model largely missed the satellite-observed elevated dust plume along the cross-ocean track and underestimated the dust intrusion into the Caribbean Basin by a factor of more than 4. Modeling improvements need to focus on developing more realistic representations of moist convection, haboobs, and the vertical transport of dust. [ABSTRACT FROM AUTHOR]

Emissions and long-range transport of mineral dust and combustion-related aerosol from burning fossil fuels and biomass vary from year to year, driven by the evolution of the economy and changes in meteorological conditions and environmental regulations. This study offers both satellite and model perspectives of interannual variability and possible trend of combustion aerosol and dust in major continental outflow regions over the past 15 years (2003–2017). The decade-long record of aerosol optical depth (AOD, denoted as τ), separately for combustion aerosol (τc) and dust (τd), over global oceans is derived from the Collection 6 aerosol products of the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard both Terra and Aqua. These MODIS/Aqua datasets, complemented by aerosol source-tagged simulations using the Community Atmospheric Model Version 5 (CAM5), are then analyzed to understand the interannual variability and potential trend of τc and τd in the major continental outflows. Both MODIS and CAM5 consistently yield a similar decreasing trend of −0.017 to −0.020 decade−1 for τc over the North Atlantic Ocean and the Mediterranean Sea that is attributable to reduced emissions from North America and Europe, respectively. On the contrary, both MODIS and CAM5 display an increasing trend of +0.017 to +0.036 decade−1 for τc over the tropical Indian Ocean, the Bay of Bengal, and the Arabian Sea, which reflects the influence of increased anthropogenic emissions from South Asia and Middle East in the last two decades. Over the northwestern Pacific Ocean that is often affected by East Asian emissions of pollution and dust, the MODIS retrievals show a decreasing trend of −0.021 decade−1 for τc and −0.012 decade−1 for τd, which is however not reproduced by the CAM5 model. In other outflow regions strongly influenced by biomass burning smoke or dust, both MODIS retrievals and CAM5 simulations show no statistically significant trends; and the MODIS observed interannual variability is usually larger than that of the CAM5 simulation. [ABSTRACT FROM AUTHOR]

While stand alone satellite and model aerosol products see wide utilization, there is a significant need in numerous atmospheric and climate applications for a fused product on a regular grid. Aerosol data assimilation is an operational reality at numerous centers, and like meteorological reanalyses, aerosol reanalyses will see significant use in the near future. Here we present a standardized 2003-2013 global 1×1° and 6-hourly modal aerosol optical thickness (AOT) reanalysis product. This data set can be applied to basic and applied Earth system science studies of significant aerosol events, aerosol impacts on numerical weather prediction, and electro-optical propagation and sensor performance, among other uses. This paper describes the science of how to develop and score an aerosol reanalysis product. This reanalysis utilizes a modified Navy Aerosol Analysis and Prediction System (NAAPS) at its core and assimilates quality controlled retrievals of AOT from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Multi-angle Imaging SpectroRadiometer (MISR) on Terra. The aerosol source functions, including dust and smoke, were regionally tuned to obtain the best match between the model fine- and coarse-mode AOTs and the Aerosol Robotic Network (AERONET) AOTs. Other model processes, including deposition, were tuned to minimize the AOT difference between the model and satellite AOT. Aerosol wet deposition in the tropics is driven with satellite-retrieved precipitation, rather than the model field. The final reanalyzed fine- and coarse-mode AOT at 550 nm is shown to have good agreement with AERONET observations, with global mean root mean square error around 0.1 for both fine- and coarse-mode AOTs. This paper includes a discussion of issues particular to aerosol reanalyses that make them distinct from standard meteorological reanalyses, considerations for extending such a reanalysis outside of the NASA A-Train era, and examples of how the aerosol reanalysis can be applied or fused with other model or remote sensing products. Finally, the reanalysis is evaluated in comparison with other available studies of aerosol trends, and the implications of this comparison are discussed. [ABSTRACT FROM AUTHOR]