Aerosol Optical Depth Values Research Articles

Evaluation of MODIS combined DT and DB AOD retrievals and their association with meteorological variables over Qena, Egypt

The purpose of this study is to validate the daily Terra-MODIS level 2 combined dark target (DT) and deep blue (DB) aerosol optical depth (AOD) retrievals with a spatial resolution of 10 km against the ground-based AERONET AOD data to be used in evaluating the air pollution and impact of meteorological variables over Qena, Egypt, in 2019. The regression analysis demonstrated an accepted agreement between the MODIS and AERONET AOD data with a correlation coefficient (R) of 0.7118 and 74.22% of the collocated points fall within the expected error (EE) limits. Quality flag filtering and spatial and temporal collocation were found to have a significant impact on the regression results. Quality flag filtering increased R by 0.2091 and % within EE by 17.97, spatial collocation increased R by 0.0143 and % within EE by 1.13, and temporal collocation increased R by 0.0089 and % within EE by 4.43. By validating the MODIS AOD data seasonally and analyzing the temporal distribution of the seasonal AOD data to show the retrieval accuracy variations between seasons, it was found that the MODIS AOD observations overestimated the AERONET AOD values in all seasons, and this may be because of underestimating the surface reflectance. Perhaps the main reason for the highest overestimation in summer and autumn is the transportation of aerosols from other regions, which changes the aerosol model in Qena, making accurate aerosol-type assumptions more difficult. Therefore, this study recommends necessary improvements regarding the aerosol model selection and the surface reflectance calculations. Temperature and relative humidity were found to have a strong negative relationship with a correlation of − 0.735, and both have a moderate association with AOD with a correlation of 0.451 and − 0.356, respectively. Because Qena is not a rainy city, precipitation was found to have no correlation with the other variables.

Seasonal evolution of aerosol loading and its vertical distribution in northeastern China from long-term satellite observations and model reanalysis

The vertical structure of aerosols plays an important role in regional air pollution and climate change. Using long-term data on aerosol optical properties obtained through satellite observations (MODIS/Terra, MODIS/Aqua, CALIOP) and reanalysis products (CAMS) during 2007–2021, we analysed the seasonal evolution and vertical distribution of aerosol loading in northeastern China (NEC). We also analysed the seasonal variation trends of aerosol optical depth (AOD) of aerosol species. The AODs during spring and summer were high and distributed in Liaoning (LN) with an average value of approximately 0.6, which was higher in central Jilin and southern Heilongjiang. Sulfate AOD (AOD_SO4) and organic matter AOD (AOD_OM) in NEC were higher during spring and summer (approximately 0.2), and the maximum value of dust AOD (AOD_DU) was approximately 0.1 obtained for western LN. During spring, the aerosol extinction coefficient (AEC) for NEC was high at heights below 2.0 km in LN, and its value was maximum (approximately 0.16 km−1) near the ground in LN during winter. The AEC was concentrated within 0–1 km during winter and higher within 1–3 km during spring and summer in NEC. During 2007–2021, AOD exhibited a decreasing trend, with higher average AOD during spring and summer and lower average AOD during autumn and winter. The seasonal trend of AOD in NEC exhibited a decreasing trend. BC_AOD showed the largest decline in spring, followed by DU_AOD and OM_AOD, and SO4_AOD showed a significant decline in summer. This paper presents accurate information on regional types and vertical distribution of aerosols. This information can be used for model improvement and satellite validation.

Estimating high-spatial-resolution daily PM2.5 mass concentration from satellite top-of-atmosphere reflectance based on an improved random forest model

The aerosol optical depth (AOD) has been widely used to estimate ground PM2.5 mass concentration in the field of remote sensing, but the current AOD retrieval results always contained invalid AOD values due to the limitations of different algorithms, which is not conducive to obtaining daily estimations of PM2.5 mass concentration. This study used the top-of-atmosphere (TOA) reflectance to establish a relationship with ground PM2.5 mass concentration instead of using traditional AOD product data. We developed an improved multiple-factor random forest model (IMFRFM) by integrating TOA reflectance, meteorological data, and land-use data to estimate high-spatial-resolution (1-km × 1-km) daily PM2.5 mass concentration in the Pearl River Delta (PRD) region. The simulation results showed that our model had excellent performance (test-R2 = 0.88, RMSE = 9.20 μg/m³, and MAE = 2.48 μg/m³) with city-based and time-based cross-validation (CV) test-R2 values of 0.82 and 0.88, respectively. The four-year (2017–2020) seasonal results showed that the PM2.5 mass concentration of the PRD region exhibited obvious seasonality, with the highest values in winter and lowest values in summer. The four-year annual results showed that the PM2.5 mass concentration in the PRD region decreased year by year. The annual average PM2.5 mass concentration in most cities in the PRD region were below 40 μg/m³, indicating that the atmospheric environment of the PRD region was gradually improving.

A Model of Mean Long-term Values of Atmospheric Aerosol Optical Depth at a 354 nm Wavelength in Russia in the Warm Season

A Model of Mean Long-term Values of Atmospheric Aerosol Optical Depth at a 354 nm Wavelength in Russia in the Warm Season

ОЦЕНКА СРЕДНИХ МНОГОЛЕТНИХ ЗНАЧЕНИЙ АЭРОЗОЛЬНОЙ ОПТИЧЕСКОЙ ТОЛЩИНЫ АТМОСФЕРЫ НА ДЛИНЕ ВОЛНЫ 354 НМ НА ТЕРРИТОРИИ РОССИИ В ТЕПЛЫЙ ПЕРИОД

Based on the results of satellite measurements using OMI instrumentation (NASA, USA) at 354 nm in 2005-2020 (http://avdc.gsfc.nasa.gov) over nine populated areas in Russia, after the exclusion of cases of the smoke and dust registration in the atmosphere, approximations were obtained for temporal variations in average long-term values of atmospheric aerosol optical depth (AOD) in April to September. The approximations obtained for four most spaced-apart areas made it possible to develop a spatiotemporal model of average long-term AOD in the ultraviolet band for the territory from 43° to 60° N and from 33° to 133° E for a warm season. A verification of the model using data for the other five areas that were not included in the model development and a comparison of the results with AERONET ground data confirmed a fairly good quality of the model. An analysis of the measurement data is indicative of significant negative annual linear trends in the mean April-September AOD for all analyzed areas.

Investigation of Spatiotemporal Variation and Drivers of Aerosol Optical Depth in China from 2010 to 2020

China has experienced rapid economic growth and serious control of aerosol emissions in the past decade. Thus, the spatiotemporal variations and driving factors of aerosol optical depth (AOD) are urgently needed to evaluate the effectiveness of aerosol control activities. The innovation of this study is a detailed spatial and temporal analysis of aerosol pollution in eight major regions of China from 2010 to 2020 using the MERRA-2 AOD reanalysis product and the driving mechanism based on the Granger causality test, sensitivity, and contribution analysis. The results show that the spatial distribution of AOD varied across the areas. Divided by the Hu Line, the AOD values of the Eastern areas were significantly higher than those of the Western areas. The temporal trend in the last eleven years was dominated by a continuous decline and moderate fluctuations at both annual and seasonal scales. The relationship between socioeconomic factors and AOD drivers was more significant in economically developed regions, suggesting that China pays more attention to haze control while developing its economy. The driving relationship between AOD and temperature was weak, while wind speed and relative humidity were more influential. For vegetation factors, Granger effects were mainly observed in the Northeast, Beijing-Tianjin-Hebei, Guangdong, Central China, and Southwest regions. In the Guangdong and Southwest regions, vegetation and economic factors were the more influential drivers. This study provides a scientific basis for the detection of aerosol changes, driving mechanisms and pollution management in China.

AOD Derivation from SDGSAT-1/GLI Dataset in Mega-City Area

Aerosol optical depth (AOD) is the key parameter for determining the aerosol radiative effects and air quality variation. It is important to quantify nighttime aerosols using satellite-based night light images to understand their diurnal variations. This study selected high-resolution low light images from the Glimmer Imager (GLI) aboard the SDGSAT-1 satellite to examine spatial–temporal changes in night light emitted from the urban surface of Beijing. The radiance observed by SDGSAT-1/GLI was used to discern the AOD changes using the radiance background method (RB) and standard deviation method (SD) based on the characterization of the radiance from artificial light sources. Cloud cleaning processes were conducted to reduce the influence of the cloud cover in the glimmer images of the derived AOD. The results showed that there are good consistencies between the derived AOD results from the remote sensing and nighttime site observations. The radiance background method is better than the standard deviation method for deriving AOD using SDGSAT-1/GLI with the RMSE of its RB (0.0984) being greater than that of the SD (0.7653). The influence of moonlight, atmospheric absorption, and positioning errors on the results is briefly discussed. This paper shows that SDGSAT-1 can obtain relatively reliable night AOD values based on our investigations using the available satellite images taken in winter and spring, and that it has the potential to provide the scientific products of nighttime AOD.

Intricate behavior of winter pollution in Hanoi over the 2006–2020 semi-climatic period

During the winter period (October to March), air quality in northern Vietnam is strongly impacted by the northeast monsoon cycles, that create periodic changes in the air masses pathways and the meteorological conditions. In this work, an original approach is proposed to identify the main sources contributing to the degradation of air quality in Hanoi and quantify the share of local and imported pollution under the influence of the northeast monsoon. Firstly, semi-climatic trends in particle emissions in East Asia and mainland Southeast Asia were studied using outputs from the NAAPS model, that assimilates space-borne Aerosol Optical Depth (AOD) observations. From winter 2006/07 to winter 2010/11, the pollution plumes were most frequently located over the Indochina Peninsula, and the smoke partial AOD showed biomass burning activities (natural and anthropogenic) to be responsible. From winter 2011/12 to winter 2019/20 however, the pollution plumes were mostly observed over eastern China and to a lesser extent, Northern Vietnam, and the sulfate partial AOD indicated they came from coal-based industrial activities. Secondly, the impact of the northeast monsoon on the air masses origin was studied using HYSPLIT back-trajectories with clustering over the 14 winter periods. During regular winters, northeastern air masses predominated, which can bring pollution from eastern China and the industrial region surrounding Hanoi (Red River Delta). However, the existence of El Niño perturbed the air masses trajectories during three winters (2014/15, 2015/16 and 2018/19), bringing more western air masses and thus, causing a temporary decrease of the sulfate AOD and simultaneous increase of the smoke AOD over Hanoi. Thirdly, a method to classify the winter days and highlight the influence of cold surges on PM2.5 variability was built, relying only on Hanoi local wind and NAAPS AOD value. This classification allowed to estimate that long-range transport from China during the onset of cold surges caused an average increase of around 30% of the PM2.5 level in Hanoi. Additionally, the contribution of local pollution to the most severe pollution episodes, occurring during the persistence of cold surges, was estimated to be around 40% of the average PM2.5.

Analysis of the urban turbidity island effect: a case study in Beijing City, China

The urban turbidity island (UTI) effect is an important research topic in urban climate studies. It is closely related to urban visibility and the health of urban residents; however, it has received little attention in previous research. This study analyzes the temporal and spatial distribution characteristics of the UTI effect through the combined use of satellite remote sensing and ground observation data. Specifically, absolute and relative urban turbidity island intensity (UTII_A and UTII_R) indices are proposed and calculated for 2000–2020 by using aerosol data products and atmospheric fine particle mass concentration inversion products, which are represented by aerosol optical depth (AOD), PM1, PM2.5, and PM10. The results show the following: (a) there has been a clear footprint of the UTI effect in Beijing since 2000, generally consistent with trends of urban sprawl; (b) there are great differences in the interannual distribution of AOD, normalized AOD and PM values in urban and suburban areas; and (c) there are seasonal differences in the UTI distribution and air pollutant concentrations. The differences among indices between urban and suburban areas are mainly caused by heat island-induced air convection, complex structures in urban areas and regional weather conditions. Importantly, the interannual distribution of AOD and UTII_A of PM values decreased from 2014 to 2020, indicating that the government’s air pollution control policy has significantly improved air quality. Analysis from this study could support the formulation of urban planning and control policies to guide human activities.

Aerosol Characterization of Northern China and Yangtze River Delta Based on Multi-Satellite Data: Spatiotemporal Variations and Policy Implications

Horizontal and vertical distributions of aerosol properties in the Taklimakan Desert (TD), North central region of China (NCR),North China Plain(NCP), and Yangtze River Delta (YRD) were investigated by statistical analysis using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) L3 data from 2007 to 2020, to identify the similarities and differences in atmospheric aerosols in different regions, and evaluate the impact of pollution control policies developed in China in 2013 on aerosol properties in the study area. The aerosol optical depth (AOD) distribution had substantial seasonal and spatial distribution characteristics. AOD had high annual averages in TD (0.38), NCP (0.49), and YRD (0.52). However, these rates showed a decline post-implementation of the long-term pollution control policies; AOD values declined by 5%, 13.8%, 15.5%, and 23.7% in TD, NCR, NCP, and YRD respectively when comparing 2014–2018 to 2007–2013, and by 7.8%, 11.5%, 16%, and 10.4% when comparing 2019–2020 to 2014–2018. The aerosol extinction coefficient showed a clear regional pattern and a tendency to decrease gradually as height increased. Dust and polluted dust were responsible for the changes in AOD and extinction coefficients between TD and NCR and NCP and YRD, respectively. In TD, with change of longitude, dust aerosol first increased and then decreased gradually, peaking in the middle. Similarly in NCP, polluted dust aerosol first increased and then decreased, with a maximum value in the middle. The elevated smoke aerosols of NCP and YRD were significantly higher than those observed in TD and NCR. The high aerosol extinction coefficient values (>0.1 km−1) were mainly distributed below 4 km, and the relatively weak aerosol extinction coefficients (>0.001 km−1) were mainly distributed between 5–8 km, indicating that the high-altitude long-range transport of TD and NCR dust aerosols affects NCP and YRD.

Improving aerosol optical depth retrievals from Himawari-8 with ensemble learning enhancement: Validation over Asia

The Advanced Himawari Imager (AHI) onboard the Himawari-8 spacecraft from the Japan Meteorological Agency (JMA) enables retrieval of aerosol optical depth (AOD) with high spatio-temporal resolution. This work demonstrates that the latest version of Level-3 AHI AOD product is affected by an overall underestimation against ground measurements from 98 sunphotometer sites over Asia, with site-average R2 and mean bias error (MBE) of 0.54 and − 0.10, respectively. The MBE varies from −0.23 to 0.03 over land, depending on site, and averages 0.06 over water. To correct these errors, an XGBoost model has been developed based on the AHI AOD, as well as meteorological quantities and geographic information from the ERA5 ECMWF reanalysis, a digital elevation model (DEM), and ground-based AOD measurements obtained in 2018. After application of this correction algorithm, the testing dataset indicates that R2 and the fraction of data included within the expected error (EE) envelope (±15%) are 0.86 and 74.7%, respectively, thus representing substantial improvement compared to the corresponding uncorrected results of 0.59 and 42.2%. The optimal XGBoost also demonstrates a good generalization ability because 69.5% of the corrected AOD falls within the EE envelope when applying the model to AHI data from 2019. The model's Feature Importance analysis shows that, besides the raw AHI AOD, geographic coordinates, surface albedo, and atmospheric water vapor contribute significantly to the correction model. The AOD difference map (corrected AOD minus raw AHI AOD) reveals that the XGBoost model improves AOD values considerably for land areas by 0.14, 0.10, 0.09, and 0.11 for MAM, JJA, SON and DJF, respectively.

ESTIMATING AIRBORNE PARTICULATE MATTER IN THE NATIONAL CAPITAL REGION, PHILIPPINES USING MULTIPLE LINEAR REGRESSION AND GRADIENT BOOSTING ALGORITHM ON MODIS MAIAC AEROSOL OPTICAL DEPTH

Abstract. The generation of air quality concentration data is imperative for the health and environment of highly urbanized regions. Through remote sensing, air pollutant concentrations can be obtained over large areas for a long time. In this study, particulate matter (PM2.5 and PM10) concentrations were estimated using satellite-derived Moderate Resolution Imaging Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Optical Depth (AOD) values observed in the National Capital Region (NCR), Philippines. Models were generated using multiple linear regression (MLR) and gradient boosting regression to determine the best models for the whole data from 2017 to 2020, dry season, and wet season with a 70–30 split for the train-test sets. Initial models resulted with the best coefficient of determination R2 values of 2.6% and 1.2% using MLR and 2.0% using gradient boosting regression. The results for PM2.5 and PM10 showed the lowest Root Mean Square Error (RMSE) values of 8.79 μg/m3 and 18.99 μg/m3 using MLR and 8.08 μg/m3 and 16.85 μg/m3 using gradient boosting, respectively. The preliminary results indicate the relatively poor performance of models in estimating particulate matter using satellite-derived AOD images. Improvements in the models will include the integration of more in-situ data from air quality monitoring stations and the addition of additional variables and features such as meteorological parameters and geographical layers.

HOTSPOT ANALYSIS AND COMPARISON BETWEEN SATELLITE-DERIVED AEROSOL OPTICAL DEPTH AND GROUND-BASED PARTICULATE MATTER MEASUREMENTS IN METRO MANILA

Abstract. Highly urbanized regions such as the Metro Manila area in the Philippines contribute to the deterioration of air quality through overpopulation, excessive vehicle emissions, and industrialization. However, the limited number of ground monitoring stations hinders the detailed estimation of the region’s overall air quality. Satellite-derived air pollutant concentrations have been used in several research studies as a substitute or supplementary to ground-based data due to their extensive spatial and temporal coverage. Using the aerosol optical depth (AOD) from the MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm and ground measurements of coarse particulate matter (PM10), this study explores the comparison between satellite-derived and ground-based air pollutant concentrations measured from 2017 to 2020 through trend analysis of monthly average values per city. With 16 stations located in different cities, the monthly average values of AOD vs PM10 showed inconsistent results due to significant gaps in the ground data. Through optimized hotspot analysis, it was found that 7.24% of the Metro Manila region are considered hotspots using the MAIAC AOD values from 2017 to 2019 (pre-pandemic). From 2018 to 2020 (pandemic), 23.86% of Metro Manila are counted as hotspots. The AOD derived from satellite imagery and hotspot analysis can be used for future studies that focus on the development of models to predict ground pollutant values and the designation of non-attainment areas.

Influence of the Long-Range Transport of Siberian Biomass Burnings on Air Quality in Northeast China in June 2017.

Biomass burning (BB) emits a large volume of trace gases and aerosols into the atmosphere, which can significantly affect the earth's radiative balance and climate and has negative impacts on air quality and even human health. In late June 2017, an intense BB case, dominated by forest and savanna fires, occurred in Siberia, and it affected the air quality of Northeast China through long-range transport. Here, multisatellite remote-sensing products and ground-based PM2.5 measurements are used to evaluate the influence of the Siberian smoky plume on Northeast China. The results show that the BB was intense at the early stage when the daily fire count and average fire radiative power exceeded 300 and 200 MW, respectively. The maximum daily fire count reached 1350 in Siberia, and the peak value of instantaneous fire radiative power was as high as 3091.5 MW. High concentrations of CO and aerosols were emitted into the atmosphere by the BB in Siberia. The maximum daily mean values of the CO column concentration and aerosol optical depth (AOD) increased by 3 × 1017 molec·cm2 and 0.5 compared with that during the initial BB stage. In addition, the BB released a large number of absorptive aerosols into the atmosphere, and the UV aerosol index (UVAI) increased by five times at the peak of the event in Siberia. Under the appropriate synoptic conditions and, combined with pyroconvection, the smoky plume was lifted into the upper air and transported to Northeast China, affecting the air quality of Northeast China. The daily mean values of CO concentration, AOD, and UVAI in Northeast China increased by 6 × 1017 molec·cm2, 0.5, and 1.4, respectively, after being affected. Moreover, the concentration of the surface PM2.5 in Northeast China approximately doubled after being affected by the plume. The results of this study indicate that the air quality of Northeast China can be significantly affected by Siberian BBs under favorable conditions.

June to October Aerosol Optical Depth over the Arctic at Various Spatial and Temporal Scales in MODIS, MAIAC, CALIOP and GOES Data

The accuracy of the cloud-aerosol lidar with orthogonal polarization (CALIOP), moderate resolution imaging spectroradiometer (MODIS), Multi-Angle Implementation of Atmospheric Correction (MAIAC), and Geostationary Operational Environmental Satellite (GOES) aerosol optical depth (AOD) products for the Arctic north of 59.75°N was examined by means of 35 aerosol robotic network (AERONET) AOD sites. The assessment for June to October 2006 to 2020 showed MAIAC AOD agreed the best with AERONET AOD; CALIOP AOD differed the strongest from the AERONET AOD. Cross-correlations of CALIOP AOD along the satellite path indicated that AOD-values 40 km up-and-down the path often failed to represent the AERONET AOD-values within ±30 min of the overpass in this region dominated by easterly winds. Typically, CALIOP AOD was lower than AERONET AOD and MAIAC AOD at the sites, especially, at sites with mean AOD below 0.1. Generally, MODIS AOD values exceeded those of MAIAC. Comparison of CALIOP, MAIAC, and MODIS products resampled on a 0.25° × 0.25° grid revealed differences among the products caused by their temporal and spatial resolution, sample habit and size. Typically, the MODIS AOD-product showed the most details in AOD distribution. Despite differences in AOD-values, all products provided similar temporal evolution of elevated and lower AOD.

Dynamic Characteristics of Aerosol Optical Properties over Dibrugarh City in the North-Eastern Indian Region during 2018–2021

Aerosols play an important role in the earth's environment across the globe through their involvement in various earth system cycles. The change in the aerosol properties may cause short and long-term impacts, the knowledge of such changes is useful in the estimation of the pollution sources of any region. We have carried out the analysis of the aerosols' optical and radiative properties using AERONET station data from 2018 to 2021 in Dibrugarh City. The higher Aerosol Optical Depth (AOD) values during winter and pre-monsoon months indicate high anthropogenic activities, and biomass burning in Dibrugarh. The impact of various sources and daily meteorological parameters help in understanding the diurnal variations of the AOD, Ångström Exponent (AE), and column water (CW). Fine aerosol fractions dominate the aerosol volume, but sometimes the long-range transport of dust affects aerosol properties during pre-monsoon months (MAM). MODIS-derived AOD and AERONET AOD values show a good correlation, with R2 = 0.68. The highest volume of the aerosols reaches up to 0.11 µm3 µm-2 during pre-monsoon months, whereas it lies below 0.05 µm3 µm-2 in other seasons. SSA values indicate the presence of scattering aerosols but in 2020, a sudden decline in the SSA values shows a strong rise in the absorbing aerosols. Throughout the study period (2018–2021), the positive radiative forcing indicates a rise in atmospheric heating.

Spatial-Temporal Analysis of the Relationship Between Aerosol Optical Depth and Seasonal Land and Ocean Temperature Around Shanghai

Few people use remote sensing data to simultaneously retrieve the seasonal changes in aerosol optical depth (AOD) on land and ocean, as well as its relationship with surface temperature. Aerosols, as one of the indicators of air pollution, directly or indirectly affect people's numerous activities. This article uses Terra satellite MODIS data as the data source and conducts AOD inversion work on the land and ocean areas around Shanghai, China based on IDL, 6S model, and dark pixel method. The results show that for land areas, the higher the surface temperature, the lower the AOD value, with summer being the most significant; On the ocean, the higher the ocean surface temperature, the greater the AOD value. This experiment provides a theoretical basis for the relationship between AOD and temperature, and confirms the possibility of retrieving ocean AOD from MODIS data.

气溶胶光学厚度与PM2.5浓度的时空分布特征及其关系——以京津冀大气污染传输通道城市群为例

PDF HTML阅读 XML下载 导出引用 引用提醒 气溶胶光学厚度与PM2.5浓度的时空分布特征及其关系——以京津冀大气污染传输通道城市群为例 DOI: 10.5846/stxb202204100936 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41771178，41671151）；辽宁省高等学校创新人才支持计划项目（LR2017017）；辽宁省教育厅项目（H201783628） Spatiotemporal distribution characteristics and relationship analysis of aerosol optical depth and PM2.5 concentration: Taking the “2+26” urban agglomeration as an example Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:城市人口和产业的聚集伴随化石能源消费的迅速增长，导致空气污染物排放量不断增加，对区域气候产生了不可逆的负面影响。以多源遥感数据为基础，对京津冀大气污染传输通道城市群（"2+26"城市群）2015-2019年气溶胶光学厚度（AOD）、PM2.5浓度的时空分布格局进行分析，从月份、季节、年份三个时间维度定量分析其时空变化规律，并通过计算相关性系数来分析气溶胶光学厚度对PM2.5浓度的影响。主要得出研究结论如下：（1） PM2.5浓度整体呈现冬季>春季>秋季>夏季的趋势，并且表现出高度空间自相关性，2015-2019年间，PM2.5浓度显著下降至40μg/m3以下；（2） AOD平均范围值在0-1之间，总体上呈现春夏季高，秋冬季低的分布特点，到2019年，春夏秋三季AOD浓度呈现明显降低，夏季下降趋势最为显著，AOD同样表现出高度空间自相关性；（3） AOD与PM2.5浓度存在显著的正相关关系。从季节变化上看，相关性呈现出：秋季>夏季>冬季>春季的特点。年均AOD与PM2.5浓度呈现中等正相关关系。因此，定量研究气溶胶光学厚度与PM2.5浓度在时空变化上的相似性以及相关性，可以证明气溶胶对大气污染存在影响关系，为未来城市空气质量管理提供科学思路和依据。 Abstract:The agglomeration of population and industries has led to the rapid growth of fossil energy consumption, resulting in the continuous increase of air pollutant emissions and irreversible negative impacts on the regional climate. Based on the multi-source remote sensing data, this paper analyzed the temporal and spatial distribution of Aerosol Optical Depth (AOD) and PM2.5 in the "2+26" urban agglomeration from 2015 to 2019, and the influence of aerosol optical thickness on PM2.5 concentration was analyzed by calculating the correlation coefficient. The main conclusions are as follows:(1) The overall change of PM2.5 concentration was winter > spring > autumn > summer, and it showed highly spatial autocorrelation. From 2015 to 2019, the PM2.5 concentration has dropped significantly to below 40 μg/m3. (2) The average range of AOD values was between 0 and 1, showing the distribution characteristics of high in spring and summer while low in autumn and winter. By 2019, the concentration of AOD in spring, summer and autumn showed a significant decrease, and was the most significant in summer. AOD also showed a high spatial autocorrelation. (3) There was a significantly positive correlation between AOD and PM2.5 concentration. From the perspective of seasonal changes, the correlation showed the characteristics of autumn>summer>winter>spring. And the annual average AOD and PM2.5 concentration showed a moderately positive correlation.Therefore, a quantitative study of the similarity and correlation between AOD and PM2.5 concentration in spatiotemporal changes can prove the influence of aerosols on air pollution, and provide scientific ideas and basis for future urban air quality management. 参考文献 相似文献 引证文献

Aerosol Optical Depth Spatial and Temporal Variability Using Satellite Data Over Indian Major Cities

Introduction: The study’s main aim is to investigate the long-term variation of Aerosol Optical Depth (AOD). It also aims to show the relationship between meteorological parameters. This study evaluates long-term (2010 to 2021) special and temporal changes over major Indian regions using satellite-based data from NASA’s Terra Satellite.
 Materials and Methods: This study was carried out during 2010-2021 using MODIS data for long-term analysis. Variation of AOD with meteorological parameters was also performed to show the impact of these parameters (Temperature and Relative Humidity) on AOD by the MERRA-II model.
 Results: Based on Terra AOD data, in all the studied regions, especially the eastern region (Kolkata), the mean AOD was high (0.9-1.2). In the western region (Mumbai, Ahmedabad, and Surat), the mean AOD was low to moderate during all seasons. Furthermore, the impact of meteorological parameters on AOD shows significant variation in average annual AOD in Kolkata (0.70 ± 0.09), while other regions reported lower than average AOD values during the study period. Mumbai and Surat had average AODs (0.44 ± 0.13), (0.45 ± 0.14), while Ahmedabad and Jaipur reported average AOD of 0.45 ± 0.14 and 0.23 ± 0.11 during the study period, respectively.
 Conclusion: Generally, AOD values vary from season to season due to aerosol’s optical and microphysical properties being affected by meteorological conditions and surface albedo. This study examined the spatial and temporal distribution of AOD over five major Indian cities.

Stratospheric Aerosol Characteristics from the 2017–2019 Volcanic Eruptions Using the SAGE III/ISS Observations

In recent years (2017–2019), several moderate volcanic eruptions and wildfires have perturbed the stratospheric composition and concentration with distinct implications on radiative forcing and climate. The Stratospheric Aerosol and Gas Experiment III instruments onboard the International Space Station (SAGE III/ISS) have been providing aerosol extinction coefficient (EC) profiles at multiple wavelengths since June 2017. In this study, a method to invert the spectral stratospheric aerosol optical depth (sAOD) or EC values from SAGE III/ISS (to retrieve the number/volume size distributions and other microphysical properties) is presented, and the sensitivity of these retrievals is evaluated. It was found that the retrievals are strongly dependent on the choices of wavelengths, which in turn determine the shapes of the calculated curves. Further, we examine the changes in stratospheric aerosol spectral behavior, size distribution properties, time evolution (growth/decay) characteristics associated with subsequent moderate volcanic eruptions, namely, Ambae (15∘S, 167∘E; April and July 2018), Raikoke (48∘N, 153∘E; June 2019), and Ulawun (5∘S, 151∘E; June and August 2019), in different spatial regions. The observational period was classified with reference to Ambae eruptions into four phases (pre-Ambae, Ambae1, Ambae2, and post-Ambae). The pre-Ambae and post-Ambe periods comprise the 2017 Canadian fires and 2019 Raikoke/Ulawun eruptions, respectively. The spectral dependence of sAOD was comparable and lowest during the pre-Ambae and Ambae1 periods in all regions. The number concentration at the principal mode radius (between 0.07 and 0.2 μm) was observed to be higher during the Ambae2 period over the Northern Hemisphere (NH). The rate of change (growth/decay) in the sAOD on a global scale resembled the changes in the Southern Hemisphere (SH), unlike the time-lag-associated changes in the NH. These differences could be attributed to the prevailing horizontal and vertical dispersion mechanisms in the respective regions. Lastly, the radiative forcing estimates of Ambae and Raikoke/Ulawun eruptions, as reported in recent studies, was discussed by taking clues from other major and moderate eruptions to gain insight on their role in climate change.