Average Aerosol Optical Depth Research Articles

Coupling Coordination Degree of AOD and Air Pollutants in Shandong Province from 2015 to 2020

In order to reveal the correlation between aerosols and pollution indicators, the MODIS aerosol optical depth (AOD) was used to investigate the distribution of AOD in 16 prefecture-level cities in Shandong Province from 2015 to 2020. This study quantitatively analyzed the coupling degree and the coupling coordination degree between AOD and pollution indicators based on the coupling coordination model. The results showed that: (1) The annual average AOD in Shandong Province showed a rapid downward trend with a mean value of 0.615. The seasonal AOD of Shandong Province and prefecture-level cities was characterized by spring and summer > autumn and winter. The distribution of AOD in Shandong Province showed a spatial pattern of high in the west and low in the east, and high in the surrounding area and low in the middle. The decreasing rate of AOD was high in the west and low in the east. (2) The annual average AOD and Air Quality Index (AQI) were in a highly coupled and coordinated state. Their spatial distribution pattern decreased from west to east. There were certain fluctuations with seasonal changes, with the largest fluctuation in winter. (3) Except for O3, the overall coupling and coordination level between AOD and each pollutant was relatively high. The coupling coordination effect was as follows: C (PM2.5, AOD) and C (PM10, AOD) > C (NO2, AOD) > C (SO2, AOD), and C (CO, AOD) > C (O3, AOD). Except for the O3, its distribution was characterized by highs in the west and lows in the east. The degree of coupling between each pollution indicator and the seasonal average AOD was high. The study showed that there was a high degree of coupling and coordination between pollutant concentration indicators and AOD, and remote sensing AOD data can be used as an effective supplement to regional pollutant monitoring indicators.

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.

Investigation of COVID-19 Impact on Aerosol Optical Depth Over Malaysia and Indonesia

Abstract Lockdown or movement control order (MCO) was implemented all over the world, including Malaysia and Indonesia, during the coronavirus disease 2019 (COVID-19) pandemic. During the lockdown period, human activities were restricted. The restriction led to the reduction of human-made particulate matter released to the atmosphere. One of the indicators that could be used to estimate the concentration of particulate matter in the atmosphere is aerosol optical depth (AOD). The aim of this study is to investigate the variation in AOD level over the Malaysia and Indonesia region during this restriction period. This study has utilized monthly and daily Moderate Resolution Imaging Spectroradiometer (MODIS) Terra AOD product that can be accessed through National Aeronautics and Space Administration (NASA)’s Geospatial Interactive Online Visualization and Analysis Infrastructure (GIOVANNI) system. The developed long-term time-averaged map showed a high AOD level over Sumatera and South Kalimantan, with the maximum value being 0.4. The comparison among during, pre- and post-lockdown periods showed a reduction in the AOD level. The maximum AOD level decreased to 0.3 during the lockdown period compared to 0.4 in the pre- (2019) and post-lockdown periods (2021 and 2022). Average monthly time series showed no spike in the AOD level in 2020 and 2021. Hovmöller diagram showed low AOD throughout the latitude and longitude during lockdown compared to the pre- and post-lockdown periods. Analyses of the yearly AOD level showed reduction in the AOD level from +11.31% in 2019 to −18.17% and −18.01% in 2020 and 2021, respectively. The result also showed that the average daily AOD percentage during the lockdown period in 2020 had decreased to −5.34% from −3.18% in 2019 and had increased to +1.26 in 2021.

Optical characteristics of aerosol and its potential sources over Nam Co in the Tibetan Plateau during Asian summer monsoon period

Aerosols over the Tibetan Plateau (TP) play an important role in the regional and global climate change and ecological environment. The Second Tibetan Plateau Scientific Expedition and Research Program (STEP) carried out observation experiment at the Nam Co Station for Multisphere Observation and Research, Chinese Academy of Sciences (Nam Co Station, 30°46′N, 90°59′E, 4730 m) in the central TP from August 5 to September 11, 2020. This paper investigated the aerosol optical properties and its potential sources over Nam Co region. The main results are as follow: the average aerosol optical depth was 0.025 during the observation period; the average black carbon (BC) concentration and aerosol number concentration was 37 ng/m3 and 129 N/cm3, respectively; the diurnal variation and vertical distribution of aerosol were affected by the local meteorological elements. Frequent southerly winds during the summer monsoon led to a certain contribution of South Asia to the BC concentration in Nam Co region. And particles from the Taklimakan Desert led to dramatic increasing of aerosol number concentration over Nam Co region. The aerosol optical characteristics and influencing factors over the central TP were analyzed, which is beneficial to further study the influence of aerosols over the TP on regional and global weather and climate.

Multi-spatiotemporal AOD trends and association with land use changes over the Guangdong-Hong Kong-Macao Greater Bay Area during 2001-2021.

Analyzing long-term variations of aerosol optical depth (AOD) is beneficial for determining high-pollutant-risk areas and formulating mitigation policies. In this study, multi-spatiotemporal trends and periodicity of AOD, as well as the persistence over the Guangdong-Hong Kong-Macao Greater Bay Area from 2001 to 2021, were investigated by the extreme-point symmetric mode decomposition (ESMD), Theil-Sen Median trend analysis and Hurst exponent. The results elucidate that AOD exhibits fluctuant variations during the 21-year period with the year 2012 as the turning point. There is a slight upward tendency (0.009year-1) in the pre-2012 period but a pronounced downward trend (- 0.03year-1) in the post-2012 period, suggesting an overall declining trend in the study area. The northern cities in the area present an increasing-stable-decreasing trend of monthly average AOD, whereas other cities have an increasing-fluctuating-decreasing trend over the study period. The decreasing rate in the western parts is higher than that in the eastern parts, like Zhaoqing, Jiangmen and Foshan city. A continuous decline of AOD is dominated over the study area, whereas an anti-persistence tendency is accumulated in the northeastern parts. Additionally, elevated AOD can be observed in unused land, water bodies and construction land, while grassland, cropland and woodland have lower AOD. The decreasing rate is larger when land-use types with high AOD are converted to those with low AOD; otherwise, the decreasing rate is smaller. The results have a great significance for improving the understanding of long-term variations of AOD, as well as providing a scientific basis to formulate environmental protection and mitigation practices.

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

Analyzing aerosol variation during the COVID-19 pandemic lockdown using satellite data

The COVID-19 pandemic caused lockdowns worldwide throughout many cities, implementing numerous restrictions on human activity. Previous studies have shown that various anthropogenic pollutants have decreased in many regions from these lockdowns, which should translate into aerosol levels, measured by aerosol optical depth (AOD), also having a large reduction. However, AOD levels over metropolitan areas during the lockdown periods have not been sufficiently documented. Using NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) AOD data, we analyzed AOD level variances during the pandemic over 13 selected metropolitan areas in Europe, India, and China. We hypothesized that reduced human activities from the pandemic lockdowns would also result in a large decrease in AOD levels in metropolitan areas. So, we compared the average AOD levels during the lockdown to the previous five-year average during the city’s corresponding lockdown dates in order to investigate the statistical significance of variations. For European cities, there were few changes in AOD levels observed during the pandemic lockdown periods. As for the Indian cities, three showed slight decreases in AOD levels (~0.5%–7.4%) and one showed an 11% increase. However, compared to Indian and European cities, all of the cities in China showed noticeable reductions in AOD levels during the lockdown (~11%–30%). Statistical analysis did not show statistical significance for most of the cities due to the large variation of AOD, suggesting that the AOD level decrease attributed to the reduction of human activities does not exceed the range of natural AOD level variation.

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.

Retrieval and validation of long-term aerosol optical depth from AVHRR data over China

ABSTRACT Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) satellites can provide over 40 years of global remote sensing observations, which can be used to retrieve long-term aerosol optical depth (AOD). This is of great significance to the study of global climate change. In this paper, we proposed an algorithm to jointly calculate AOD and land surface properties from AVHRR observations. With assumptions that AOD doesn’t vary in adjacent space and earth surface property doesn’t vary in two days, the algorithm considered non-Lambertian surface reflection based on the shape of bidirectional reflectance distribution function (BRDF shape) and obtained AOD and surface property by optimal estimation (OE) method. The algorithm has been applied to NOAA-7, 9, 11, 14, 16, 18, and 19 satellites and AVHRR-retrieved AOD with 5 × 10 km over China (15°–60° N, 70°–140°E) has been obtained from 1982 to 2016. Comparisons of AVHRR-retrieved AOD against AErosol RObotic NETwork (AERONET) (in and around China) and China Aerosol Remote Sensing Network (CARSNET) AOD show good consistency with 62.62% points within the uncertainty of Δτ = ± (0.05 + 0.25τ) and root-mean-square error (RMSE) of 0.26. Further comparison of the monthly mean AOD of multiple AOD datasets in the ‘Beijing’, ‘Dalanzadgad’, ‘NCU_Taiwan’ and ‘Kanpur’ stations shows that the results of the algorithm are stable. The yearly averaged AOD data also has similar agreements with MERRA-2 (The Modern-Era Retrospective analysis for Research and Applications, Version 2) and AVHRRDB data (AVHRR ‘Deep Blue’ aerosol data set). The multi-year mean correlation coefficient is 0.70 and 0.61 and the percentages within the uncertainty are 80.01% and 67.29% compared with MERRA-2 AOD and AVHRRDB AOD respectively.

Nanomaterials pollutant's emission influencing outdoor recreation in China: Analytical strategies proceeding to sustainable environment

The global demand for bioenergy and nanomaterial utilization has significantly contributed to their source depletion. The impact of outdoor pollutant emissions on residents' health, behavior, physical activity, and sleeping behavior is much less explored. Producing biofuels from organic waste has the potential to unite budget-friendliness and long-term sustainability. Primary biofuels are produced specifically to mitigate environmental problems, and secondary biofuels are produced specifically to mitigate other environmental problems. The high level of pollutants ina certain area can severely restrict human activities and ultimately influence their whole life. The study aims to empirically evaluate the influence of nanomaterials pollutants emissions influencing outdoor recreation in China because its economy is based on fast-paced industrialization and urbanization. Various datasets were collected, including domestic and international tourists from the annual statistics for 2011–2020 from the National Bureau of Statistics of China. Ten years of annual METAR data of visibility (VR), temperature (T), relative humidity (Demirhan), and wind speed (WS) from 30 metrological stations at international airports. Annual average AOD (Aerosol's Optical Depth), O3 (Ozone), CO (Carbon Monoxide), SO4 (Sulphate), and PM2.5 (Particulate Matter) satellite imageries from 2011 to 2020 were obtained from NASA's official portal. The overall picture of satellite observations of pollutants over China describes that the highest level of AOD was observed in regions with greater population concentration than in other areas. We computed a statistical summary, correlation matrix, and Autoregressive Distributed Lag (ARDL) approach. Certain analyses were performed, like Unrestricted Error Correction Models (UECM) and Restricted Error Correction Model (RECM)), bound tests for cointegration, and multiplier estimations for short-term and long-term impacts. UECM and RECM models produced R2 > 0.90 with good F statistics and a p-value of <0.05. A bounds F-test for no cointegration on the ARDL model was performed, and the results show that the p-value = 1e-06 and F = 8.516 with alternative hypothesis = Possible cointegration. Bounds t-test for no cointegration was also performed on UECM model and the results show that t = −2.9066, Lower-bound I(0) = −3.43, Upper-bound I(1) = −5.37, p-value = 0.6138 and alternative hypothesis = Possible cointegration. The study's findings may help Chinese policymakers and stakeholders design effective information strategies to combat air pollution. Effective measures can help alleviate this devastating air quality factor, thus benefiting the tourism industry and enhancing the local inhabitants' welfare.

The Spatial-Temporal Differentiation of Aerosol Optical Properties and Types in the Beijing–Tianjin–Hebei Region Based on the Ecological Functional Zones

Atmospheric aerosol pollution has seriously affected the ecological environment and human health in recent years. There are great differences in aerosol optical properties and types due to the influence of environmental conditions, meteorology, industrial and agricultural activities, and other factors of each ecological functional zones. Using MODIS aerosol products (including MCD19A2 and MOD04_3K), this study discussed the temporal and spatial distribution of aerosol optical depth (AOD), Ångström wavelength index (AE) and aerosol types in the Beijing–Tianjin–Hebei region (BTH region) based on the ecological functional zones from 2015 to 2020. The results showed as follows: (1) The AOD in BTH region showed an obviously spatial pattern of low in the north and high in the south, while the spatial pattern of AE was opposite to that of AOD. In addition, the dominant aerosol type of the north part was clean aerosol, the dominant aerosol type of the middle part was biomass burning or urban-industrial aerosol, while that of the other part was mixed aerosols. (2) The seasonal changes of AOD and AE indexes in each ecological functional area had obvious seasonal changes, and the AOD and AE values were highest in summer. At the same time, the proportion of biomass combustion or urban industrial aerosol was the highest in summer. (3) The ecological functional areas with fewer human activities were dominated by clean aerosols, with lower AOD and higher AE value. The ecological functional areas dominated by cities were dominated by mixed aerosols, with higher AOD. The ecological functional areas dominated by agriculture and heavy industry were dominated by biomass combustion or urban industrial aerosols, with the largest AOD. (4) Compared with 2015, the average AOD of each ecological functional area decreased significantly to 2020, and biomass combustion or urban industrial aerosols changed to mixed aerosols.

Climatology and model prediction of aerosol optical properties over the Indo-Gangetic Basin in north India.

The current research focuses on the use of different simulation techniques in the future prediction of the crucial aerosol optical properties over the highly polluted Indo-Gangetic Basin in the northern part of India. The time series model was used to make an accurate forecast of aerosol optical depth (AOD) and angstrom exponent (AE), and the statistical variability of both cases was compared in order to evaluate the effectiveness of the model (training and validation). For this, different models were used to simulate the monthly average AOD and AE over Jaipur, Kanpur and Ballia during the period from 2003 to 2018. Further, the study was aimed to construct a comparative model that will be used for time series statistical analysis of MODIS-derived AOD550 and AE412-470. This will provide a more comprehensive information aboutthe levels of AOD and AE that will exist in the future. To test the validity and applicability of the developed models, root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percent error (MAPE), fractional bias (FB), and Pearson coefficient (r) were used to show adequate accuracy in model performance. From the observation, themonthly mean values of AOD and AE were found to be nearly similar at Kanpur and Ballia (0.62 and 1.26) and different at Jaipur (0.25 and 1.14). Jaipur indicates that during the pre-monsoon season, the AOD mean value was found to be highest (0.32 ± 0.15), while Kanpur and Ballia display higher AOD mean values during the winter season (0.72 ± 0.26 and 0.83 ± 0.32, respectively). Among the different methods, the autoregressive integrated moving average (ARIMA) model was found to be the best-suited model for AOD prediction at Ballia based on fitted error (RMSE (0.22), MAE (0.15), MAPE (24.55), FB (0.05)) and Pearson coefficient r (0.83). However, for AE, best prediction was found at Kanpur based on RMSE (0.24), MAE (0.21), MAPE (22.54), FB (-0.09) and Pearson coefficient r (0.82).

Land Use and Land Cover Influence on Sentinel-2 Aerosol Optical Depth below City Scales over Beijing

Atmospheric aerosols can impact human health, necessitating the understanding of their distribution determinants, especially in urban areas. The study discusses the relationships between five major land cover types and aerosol optical depth (AOD) within a city combining the high-resolution satellite-derived AOD products (derived from Sentinel-2) and land cover products (60 m and 100 m, respectively) for Beijing and its surroundings from 2017 to 2019. Contribution analysis is performed to quantitatively evaluate the influences of land cover on regional AOD over the study area. Patterns of aerosol distribution remarkably vary in time and space. Statistics of seasonal average AOD peak in spring and then progressively decline from summer through autumn to winter. High AOD values coincide with a low normalized difference vegetation index (NDVI) and a high normalized difference built-up index (NDBI). Urban and built-up land is a major contributor to regional AOD in the study area, especially in spring; forest and grassland always reduce AOD. Anthropogenic activities have a non-negligible influence on AOD and can even reverse the contribution of a land cover type to aerosols. Insights of the study promote the comprehension of the impacts of land cover on aerosols and air pollution and contribute to the planning of land use within a city.

Aerosol Property Analysis Based on Ground-Based Lidar in Sansha, China

Marine aerosol is one of the most important natural aerosols. It has a significant impact on marine climate change, biochemical cycling and marine ecosystems. Previous studies on marine aerosols, especially in the South China Sea, were carried out by satellite and shipborne measurements. The above methods have drawbacks, such as low temporal–spatial resolution and signal interference. However, lidar has high accuracy and high temporal–spatial resolution, so it is suitable for high-precision long-term observations. In this work, we obtain marine aerosol data using Mie Lidar in Sansha, an island in the South Chain Sea. Firstly, by comparing boundary layer height (BLH) between Sansha and Hefei, we found that Sansha’s boundary layer height has significant differences with that of inland China. Secondly, we compare the aerosol extinction coefficients and their variation with height in Sansha and Hefei. Finally, we obtain hourly averaged aerosol optical depth at Sansha and explore its relation with weather. To analyze the AOD–weather relation, we select three meteorological factors (sea surface temperature, mean sea level pressure and 10 m u-component of wind) based on their feature importance, which is determined by random forest regression. We also analyze the relationship between AOD and the above meteorological factors in each season separately. The results show that there is a strong relation between the meteorological factors and AOD in spring and summer, while there is no clear correlation in fall and winter. These analyses can provide valid data for future researches on marine aerosols in the South China Sea.

The influence and contribution of fine mode particles to aerosol optical properties during haze events at the foothills of Himalaya-Karakorum region

In the last decade, the regional haze is considered as one of the most devastating weathers which causes serious impacts on air quality, human health, and transportation over the Indo-Gangetic Plain, particularly the eastern part of Pakistan. In this paper for the first time, the long-term characterization of aerosols optical properties during haze events were carried out using ground-based Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite over Lahore and Faisalabad for the period of 2009–2018. Firstly, the MODIS Aerosol Optical Depth (AOD) was correlated with AERONET AOD and reported a high degree of R-squared correlation of value 0.78 between two datasets for the months of October, November and December during the study period (2009–2018). After validation of data, the daily averaged AOD and Angstrom Exponent (AE) values exceeding 1 were selected as heavy haze events. Then the aerosol optical properties such as AOD, AE, Volume Size Distribution (VSD), and Fine Mode Fraction (FMF) of AOD were retrieved from AERONET and MODIS for further analysis. The distribution of AOD and AE showed that most of the values were greater than 1.3 and 1.1, respectively, during haze events over both study sites. The daily averaged profile of aerosol VSD exhibited a bimodal lognormal distribution having dominant fine mode peaks at radius between 0.19 and 0.25 μm as compared to coarse modes peaks. Furthermore, the contribution of fine-mode AOD to the total AOD was quite higher (i.e., 86–98%) during haze events showing the greater contribution of fine mode aerosol particles. The correlation of AE with AOD and FMF revealed that the pronounced aerosol types were fine mode aerosol particles originated due to biomass burning and urban/industrial emissions during haze events. These types of fine mode aerosol particles were also confirmed with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) subtype measurements. Furthermore, the back trajectories revealed that most air masses were received from the local/regional aerosol sources, showing the contribution of fine mode aerosol particles to haze events whilst some of the trajectories were from Afghanistan, Iran, and India showing long range transportation of air masses to the receptor sites.

Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties

Abstract. Aerosol particles can be emitted, transported, removed, or transformed, leading to aerosol variability at scales impacting the climate (days to years and over hundreds of kilometers) or the air quality (hours to days and from meters to hundreds of kilometers). We present the temporal and spatial scales of changes in AOD (aerosol optical depth) and aerosol size (using Ångström exponent – AE; fine-mode fraction – FMF) over Korea during the 2016 KORUS-AQ (KORea–US Air Quality) atmospheric experiment. We use measurements and retrievals of aerosol optical properties from airborne instruments for remote sensing (4STAR; Spectrometers for Sky-Scanning Sun-Tracking Atmospheric Research) and in situ (LARGE; NASA Langley Aerosol Research Group Experiment) on board the NASA DC-8 and geostationary satellites (GOCI; Geostationary Ocean Color Imager; Yonsei aerosol retrieval – YAER, version 2) as well as from reanalysis (MERRA-2; Modern-Era Retrospective Analysis for Research and Applications, version 2). Measurements from 4STAR when flying below 1000 m show an average AOD at 501 nm of 0.36 and an average AE of 1.11 with large standard deviation (0.12 and 0.15 for AOD and AE, respectively), likely due to mixing of different aerosol types (fine and coarse mode). The majority of AOD due to fine-mode aerosol is observed at altitudes lower than 2 km. Even though there are large variations, for 18 out of the 20 flight days, the column AOD measurements by 4STAR along the NASA DC-8 flight trajectories match the South Korean regional average derived from GOCI. GOCI-derived FMF, which was found to be slightly low compared to AErosol RObotic NETwork (AERONET) sites (Choi et al., 2018), is lower than 4STAR's observations during KORUS-AQ. Understanding the variability of aerosols helps reduce uncertainties in the aerosol direct radiative effect by quantifying the errors due to interpolating between sparse aerosol observation sites or modeled pixels, potentially reducing uncertainties in the upcoming observational capabilities. We observed that, contrary to the prevalent understanding, AE and FMF are more spatially variable than AOD during KORUS-AQ, even when accounting for potential sampling biases by using Monte Carlo resampling. Averaging between measurements and models for the entire KORUS-AQ period, the reduction in correlation by 15 % is 65.0 km for AOD and shorter at 22.7 km for AE. While there are observational and model differences, the predominant factor influencing spatial–temporal homogeneity is the meteorological period. High spatiotemporal variability occurs during the dynamic period (25–31 May), and low spatiotemporal variability occurs during the blocking pattern (1–7 June). While AOD and FMF / AE are interrelated, the spatial variability and relative variability of these parameters in this study indicate that microphysical processes vary at scales shorter than aerosol concentration processes at which microphysical processes such as aerosol particle formation, growth, and coagulation mostly impact the dominant aerosol size (characterized by, e.g., FMF / AE) and to some degree AOD. In addition to impacting aerosol size, aerosol concentration processes such as aerosol emission, transport, and removal mostly impact the AOD.

Preliminary Assessment and Verification of the Langley Plots Calibration of the Sun Photometer at Mt Foyeding Observatory, Beijing

An assessment and verification of the Langley calibration method of the Sun photometer at Mt Foyeding (MFYD) Observatory in Beijing was performed. We explored whether the Langley plot calibration is practicable for this mountainous site by analyzing the aerosol climatology and carrying out a case study. Then, the aerosol optical depth (AOD) results were verified under the reference of AERONET AOD. The results showed that satisfactory atmospheric conditions are present on winter mornings, characterized by a smaller average AOD (~0.09–0.14) and a lower range ratio (~36.97–63.38%) than in the afternoons and over a whole day. The six days selected as the case study all showed stable atmospheric conditions characterized by daily average triplets of &lt;2% for all wavelengths. The residual sum of squares for V0λ at all wavelengths was &lt;0.0002 and the residual standard deviation was &lt;0.2%. A large improvement was found in the linear regression at morning relative to the statistics obtained over the whole day, when the coefficient of determination and residual standard deviation were promoted by 0.22–2.90% and ~2.76–23.32, respectively. The final V0λ value was derived from 31 days of observation and the deviations from the reference V0λ were about −1.69, −1.29, −0.81, −0.42, −0.34, −0.22, −0.63 and −0.36% at 340, 380, 440, 500, 675, 870, 1020 and 1640 nm, respectively. The regression analysis of the AOD validation showed a perfect AOD performance, with 100% of the retrievals lying within the expected error (0.05 ± 10%) from 380 to 1640 nm and 99.99% for the 340 nm band. Good AOD agreement (correlation coefficients &gt; 0.998) and residual standard deviation values ranging from ~0.006 to 0.011 were observed, with the relative mean bias varying from 0.999 to 1.066. The mean biases were concentrated within ±0.02 for the ultraviolet bands and within ±0.01 for the other bands; therefore, the results of this preliminary assessment and verification indicated that the Langley plots method is suitable for photometer calibration at the MFYD Observatory.

Comparison and evaluation of multiple satellite aerosol products over China in different scenarios under a unified criterion: Preparation for consistent and high-quality dataset construction

Aerosol optical depth (AOD) products provided by satellite sensors are widely used in climate modeling and climate change research. However, inconsistencies between products can cause large biases. It is necessary to integrate multiple satellite aerosol products to produce a consistent and high-quality aerosol record that satisfies the requirements of climate research users. To effectively combine the advantages of different datasets, their performance under different conditions needs to be compared during overlapping periods using uniform methods and criteria. Based on Aerosol Robotic Network (AERONET) measurements from 2019 to 2021, this study is the first to systematically compare the accuracy of 16 publicly released products from multiple satellite sensors in China under various scenarios using the same criteria to support the construction of a harmonized and high-quality dataset. Compared with AERONET AOD, the average retrieval percentage of 16 products satisfying the Global Climate Observing System (GCOS) accuracy requirement is 26.51%, with MISR and VIIRS Deep Blue (DB) products exceeding 40%, while MODIS 3 km Dark Target (DT), VIIRS DT, VIIRS Enterprise Processing System (EPS), and Sentinel-3 products are below 20%. By quantifying the accuracy of the products under different surface conditions, aerosol loadings, and particle size types, the accuracy ranking matrix of 16 products under different scenarios is established to provide a priori knowledge for the construction of a merged dataset. Finally, AOD products from October 2020 are merged based on the accuracy ranking matrix. The merged results show that, compared to the commonly used MODIS DT product, the percentage of retrievals satisfying GCOS requirement is improved by 22.55%, the correlation coefficient and mean absolute error are also improved, and the national average AOD coverage increases from 22.18% to 47.73%. These results are expected to provide guidance for the construction of high-quality datasets and the application of satellite aerosol products in climate research.

Decade-low aerosol levels over the Bohai and Yellow Seas amid the COVID-19 lockdown.

Coronavirus disease 2019 (COVID-19) has crucially influenced anthropogenic activities, which in turn impacts upon the environment. In this study, we investigated the variations on aerosol optical depth (AOD) at 550 nm over the Bohai Sea and Yellow Sea during the COVID-19 lockdown (from February to March in 2020) of China mainland based on Moderate-resolution Imaging Spectroradiometer (MODIS) observation by comparing with historical AOD records (2011–2019). Our results show that with the lockdown implementation, the decade-low AOD levels are achieved in February and March 2020 (0.39 ± 0.18 and 0.37 ± 0.19, respectively), which are 22% and 28% (p < 0.01) lower than the average AOD between 2011 and 2019 (0.50 ± 0.08 and 0.52 ± 0.05, respectively). After the lockdown restrictions were relaxed and industrial production gradually resumed, the AOD in April 2020 rebounded to the historical average level. Besides, compared with historical observations (2011–2019), the AOD temporal variability from February to April 2020 showed different pattern, with the decade-high increase from March to April (+0.11) and decade-low increase from February to March (-0.01). Independent observations and simulation, including fine particulate matter (PM2.5) from ground-based measurements, wind field from Cross-Calibrated Multi-Platform, satellite-derived aerosol type, and back trajectories calculation by Hybird Single Paricle Lagrangian Intergrated Trajectory (HYSPLIT) model, indicated that the above abnormal AOD variation can be attributed to reduction of anthropogenic emissions during the COVID-19 lockdown period. The results of this paper, therefore, indicate that aerosols over the Bohai and Yellow Seas are strongly influenced by human activities, and the public health events such as the epidemic may alter the intensity of human activities and thus the spatio-temporal pattern of aerosol over ocean. With the global spread of the epidemic and the corresponding significant changes in human behavior patterns (restrictions on human activities, etc.), more studies should be carried out in the future about the aerosol variability and its potential impact on the marine environment.

Characteristics of the Spatio-Temporal Dynamics of Aerosols in Central Asia and Their Influencing Factors

Aerosols are an important component of the atmospheric system. Long time-series observations for aerosols are essential for examining global climate change and the ecological environment. Based on Google Earth Engine and MODIS MCD19A2 data, we monitored the spatio-temporal dynamic characteristics of the aerosol optical depth (AOD) in Central Asia from 2001 to 2020. The effects of six environmental factors on the AOD distribution were explored using a geographic detector model and analysed in combination with the land-use/land-cover change (LUCC) and desertification in different periods. The results showed that the average multi-year AOD in Central Asia was 0.1442, with insignificant interannual variations. The high-value areas were mainly distributed in the Aral Sea and surrounding areas of the Tarim Basin in Xinjiang, with notable seasonal variations. The evaluation results for the influencing factors showed that the relative humidity and precipitation had a large effect on the spatial distribution of the AOD. The LUCC directly affected contributions to the AOD. Desertification of land provides rich dust sources, which are the main aerosol sources in Central Asia, thus exacerbating dust aerosol pollution. This study investigated the temporal and spatial characteristics and influencing factors of the AOD in Central Asia, providing a theoretical basis for the prevention and control of air pollution.