Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications

Remote Sensing of Environment, Journal Year: 2020, Volume and Issue: 252, P. 112136 - 112136

Published: Oct. 30, 2020

Language: Английский

---

Improved 1 km resolution PM_2.5 estimates across China using enhanced space–time extremely randomized trees

Atmospheric chemistry and physics, Journal Year: 2020, Volume and Issue: 20(6), P. 3273 - 3289

Published: March 19, 2020

Abstract. Fine particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) has adverse effects on human health and the atmospheric environment. The estimation of surface PM2.5 concentrations made intensive use satellite-derived aerosol products. However, it been a great challenge to obtain high-quality high-resolution data from both ground satellite observations, which is essential monitor air pollution over small-scale areas such as metropolitan regions. Here, space–time extremely randomized trees (STET) model was enhanced by integrating updated spatiotemporal information additional auxiliary improve spatial resolution overall accuracy estimates across China. To this end, newly released Moderate Resolution Imaging Spectroradiometer Multi-Angle Implementation Atmospheric Correction AOD product, along meteorological, topographical land-use emissions, input STET model, daily 1 km maps for 2018 covering mainland China were produced. performed well, high out-of-sample (out-of-station) cross-validation coefficient determination (R2) 0.89 (0.88), low root-mean-square error 10.33 (10.93) µg m−3, small mean absolute 6.69 (7.15) m−3 relative 21.28 % (23.69 %). In particular, captured well at regional individual site scales. North Plain, Sichuan Basin Xinjiang Province always featured levels, especially in winter. outperformed most models presented previous related studies, strong predictive power (e.g., monthly R2=0.80), can be used estimate historical records. More importantly, study provides new approach obtaining dataset (i.e., ChinaHighPM2.5), important studies focused urban areas.

Language: Английский

---

Changing State of the Climate System

Cambridge University Press eBooks, Journal Year: 2023, Volume and Issue: unknown, P. 287 - 422

Published: June 29, 2023

A summary is not available for this content so a preview has been provided. As you have access to content, full PDF via the 'Save PDF' action button.

Language: Английский

---

Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

Remote Sensing of Environment, Journal Year: 2021, Volume and Issue: 270, P. 112775 - 112775

Published: Nov. 11, 2021

Language: Английский

---

The ChinaHighPM10 dataset: generation, validation, and spatiotemporal variations from 2015 to 2019 across China

Environment International, Journal Year: 2020, Volume and Issue: 146, P. 106290 - 106290

Published: Dec. 11, 2020

Respirable particles with aerodynamic diameters ≤ 10 µm (PM10) have important impacts on the atmospheric environment and human health. Available PM10 datasets coarse spatial resolutions, limiting their applications, especially at city level. A tree-based ensemble learning model, which accounts for spatiotemporal information (i.e., space-time extremely randomized trees, denoted as STET model), is designed to estimate near-surface concentrations. The 1-km resolution Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product auxiliary factors, including meteorology, land-use cover, surface elevation, population distribution, pollutant emissions, are used in model generate high-resolution (1 km) high-quality dataset China ChinaHighPM10) from 2015 2019. has an out-of-sample (out-of-station) cross-validation coefficient determination (CV-R2) 0.86 (0.82) a root-mean-square error (RMSE) 24.28 (27.07) μg/m3, outperforming most widely models previous related studies. High levels concentration occurred northwest (e.g., Tarim Basin) Northern Plain. Overall, concentrations had significant declining trend 5.81 μg/m3 per year (p < 0.001) over past five years China, three key urban agglomerations. ChinaHighPM10 potentially useful future small- medium-scale air pollution studies by virtue its higher overall accuracy.

Language: Английский

---

Satellite-Derived 1-km-Resolution PM₁ Concentrations from 2014 to 2018 across China

Environmental Science & Technology, Journal Year: 2019, Volume and Issue: 53(22), P. 13265 - 13274

Published: Oct. 14, 2019

Particulate matter with aerodynamic diameters ≤1 μm (PM1) has a greater impact on the human health but been less studied due to fewer ground observations. This study attempts improve retrieval accuracy and spatial resolution of satellite-based PM1 estimates using new ground-based monitoring network in China. Therefore, space-time extremely randomized trees (STET) model is first developed estimate concentrations at 1 km from 2014 2018 across mainland The STET can derive daily an average across-validation coefficient determination 0.77, low root-mean-square error 14.6 μg/m3, mean absolute 8.9 μg/m3. are generally most areas China, except for North China Plain Sichuan Basin where intense activities poor natural conditions prevalent, especially winter. Moreover, pollution greatly decreased over past 5 years, benefiting emission control model, incorporating spatiotemporal information, shows superior performance relative previous studies. high-resolution high-quality data set (i.e., ChinaHighPM1) be useful air studies medium- or small-scale areas.

Language: Английский

---

Merging regional and global aerosol optical depth records from major available satellite products

Atmospheric chemistry and physics, Journal Year: 2020, Volume and Issue: 20(4), P. 2031 - 2056

Published: Feb. 24, 2020

Abstract. Satellite instruments provide a vantage point for studying aerosol loading consistently over different regions of the world. However, typical lifetime single satellite platform is on order 5–15 years; thus, climate studies, use multiple sensors should be considered. Discrepancies exist between optical depth (AOD) products due to differences in their information content, spatial and temporal sampling, calibration, cloud masking, algorithmic assumptions. Users satellite-based AOD time-series are confronted with challenge choosing an appropriate dataset intended application. In this study, 16 monthly obtained from algorithms were inter-compared evaluated against Aerosol Robotic Network (AERONET) AOD. Global regional analyses indicate that tend agree qualitatively annual, seasonal timescales but may offset magnitude. Several approaches then investigated merge records satellites create optimised dataset. With few exceptions, all merging lead similar results, indicating robustness stability merged products. We introduce gridded product period 1995–2017. show quality as least good individual Optimal agreement AERONET further demonstrates advantage This provides long-term perspective changes world, users encouraged

Language: Английский

---

Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring

Earth system science data, Journal Year: 2020, Volume and Issue: 12(4), P. 3573 - 3620

Published: Dec. 22, 2020

Abstract. Proven by multiple theoretical and practical studies, multi-angular spectral polarimetry is ideal for comprehensive retrieval of properties aerosols. Furthermore, a large number advanced space polarimeters have been launched recently or planned to be deployed in the coming few years (Dubovik et al., 2019). Nevertheless, at present, utilization aerosol products from rather limited, due relatively small polarimetric compared photometric observations, as well challenges making full use extensive information content available these complex observations. Indeed, while recent several new algorithms developed provide enhanced retrievals satellite polarimetry, value yet remains proven. In this regard, paper presents analysis obtained Generalized Retrieval Atmosphere Surface Properties (GRASP) algorithm POLDER/PARASOL After about decade development, GRASP has adapted operational processing observations released. These updated PARASOL/GRASP are publicly (e.g., http://www.icare.univ-lille.fr, last access: 16 October 2018, http://www.grasp-open.com/products/, 28 March 2020); dataset used current study registered under https://doi.org/10.5281/zenodo.3887265 (Chen 2020). The objective comprehensively evaluate First, validation entire 2005–2013 archive was conducted comparing ground-based Aerosol Robotic Network (AERONET) data. subjects optical depth (AOD), absorption (AAOD) single-scattering albedo (SSA) six wavelengths, Ångström exponent (AE), fine-mode AOD (AODF) coarse-mode (AODC) interpolated reference wavelength 550 nm. Second, an inter-comparison with PARASOL/Operational, MODIS Dark Target (DT), Deep Blue (DB) Multi-Angle Implementation Atmospheric Correction (MAIAC) year 2008 performed. Over land both data validations inter-comparisons were separately different surface types, discriminated bins normalized difference vegetation index (NDVI): < 0.2, 0.2 ≤ 0.4, 0.4 0.6, ≥ 0.6. Three analyzed: GRASP/HP (“High Precision”), Optimized Models. consistent but using assumptions modeling accuracies atmospheric radiative transfer (RT) calculations. Specifically, when there direct size distribution refraction. When GRASP/Models, approximated mixture prescribed components, each their own fixed properties, only concentrations those components retrieved. employs most accurate RT calculations, GRASP/Optimized GRASP/Models optimized achieve best trade-off between accuracy speed. all three options, underlying reflectance retrieved simultaneously calculations performed “online” during retrieval. All results show solid quality characteristics. retrievals, however, provided products, e.g., (550 nm) unbiased highest correlation (R ∼ 0.92) fraction (∼ 55.3 %) satisfying requirements Global Climate Observing System (GCOS) AERONET non-negligible positive bias 0.07) low (< 0.2). On other hand, detailed microphysical characteristics (AE, AODF, AODC, SSA, etc.) correlate generally better than do GRASP/Models. Overall, demonstrates high versus AERONET. Evidently, approach more total AOD, limited models used. comparative showed that, based on against AERONET, product similar sometimes higher products. good agreement over ocean. land, especially bright surfaces, degrades differences increase. characteristics, such AE, AODF AODC PARASOL/GRASP, reliable, land. global robust agreement, though some patterns tendencies observed. ocean, PARASOL/Models MODIS/DT agree coefficient 0.92. lower, ranging 0.76 0.85. There no significant offset; surfaces tend values smaller moderate AODs. Seasonal means suggest that biomass burning loading central Africa dust Taklamakan Desert, less northern Sahara. It noticeable also sites somewhat higher, suggesting work rest globe. One potential reasons may general, rely climatology retrievals. shows like POLDER least comparable single-viewing MODIS-like imagers. At same time, AE), additional parameters AAOD SSA.

Language: Английский

---

Air pollution trends measured from Terra: CO and AOD over industrial, fire-prone, and background regions

Remote Sensing of Environment, Journal Year: 2021, Volume and Issue: 256, P. 112275 - 112275

Published: Jan. 26, 2021

Following past studies to quantify decadal trends in global carbon monoxide (CO) using satellite observations, we update estimates and find a CO trend column amounts of about −0.50 % per year between 2002 2018, which is deceleration compared analyses performed on shorter records that found −1 year. Aerosols are co-emitted with from both fires anthropogenic sources but lifetime than CO. A combined analysis aerosol optical depth (AOD) measurements space helps diagnose the drivers regional differences trend. We use long-term Measurements Pollution Troposphere (MOPITT) AOD Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Other instruments measuring thermal infrared, AIRS, TES, IASI, CrIS, show consistent hemispheric variability corroborate results MOPITT Trends examined by hemisphere regions for uncertainties quantified. The split into two sub-periods (2002 2010 2018) order assess changes over 16 years. focus four major population centers: Northeast China, North India, Europe, Eastern USA, as well fire-prone hemispheres. In general, declines faster first half record second half, while more across regions. evidence atmospheric impact air quality management policies. large decline China initially associated an improvement combustion efficiency, subsequent additional improvements onwards. Industrial minimal emission control measures such India become globally relevant weakens. also examine monthly percentile values understand seasonal implications local biomass burning sufficiently strong counteract downward CO, particularly late summer.

Language: Английский

---

ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set

Atmospheric measurement techniques, Journal Year: 2021, Volume and Issue: 14(1), P. 309 - 334

Published: Jan. 15, 2021

Abstract. Monitoring and describing the spatiotemporal variability in dust aerosols is crucial for understanding their multiple effects, related feedbacks, impacts within Earth system. This study describes development of ModIs Dust AeroSol (MIDAS) data set. MIDAS provides columnar daily optical depth (DOD) at 550 nm a global scale fine spatial resolution (0.1∘ × 0.1∘) over 15-year period (2003–2017). new set combines quality filtered satellite aerosol (AOD) retrievals from MODIS-Aqua swath level (Collection 6.1; Level 2), along with DOD-to-AOD ratios provided by Modern-Era Retrospective analysis Research Applications version 2 (MERRA-2) reanalysis to derive DOD on MODIS native grid. The uncertainties AOD MERRA-2 fraction, respect AEronet RObotic NETwork (AERONET) LIdar climatology vertical Aerosol Structure space-based lidar simulation (LIVAS), respectively, are taken into account estimation total uncertainty. fractions very good agreement those LIVAS across belt tropical Atlantic Ocean Arabian Sea; degrades North America Southern Hemisphere, where sources smaller. MIDAS, MERRA-2, DODs strongly agree when it comes annual seasonal patterns, colocated averages 0.033, 0.031, 0.029, respectively; however, deviations loading evident regionally dependent. Overall, well correlated AERONET-derived (R=0.89) only shows small positive bias (0.004 or 2.7 %). Among major areas planet, highest R values (>0.9) found sites Africa, Middle East, Asia. expands, complements, upgrades existing observational capabilities aerosols, suitable climatological studies, model evaluation, assimilation.

Language: Английский

---