Mean Aerosol Optical Depth Values Research Articles

Aerosol in global oceanic regions: Four-decade trends, spatial patterns, and policy implications

High aerosol loadings are observed not only in megacities on continents but also in oceanic regions like the Bohai Sea. This work provides a comprehensive analysis of the spatial and temporal variations in Aerosol Optical Depth (AOD) across different ocean regions worldwide over the past four decades, using remote sensing reanalysis data. The mean AOD value across all oceanic grids is approximately 0.112, with higher levels recorded in the Central Atlantic (~0.206), followed by the North Indian Ocean (~0.201), and the Western North Pacific (~0.197). A latitudinal analysis reveals that high AOD values are predominantly found in the Northern Hemisphere's oceanic regions, especially between latitudes 0° and 70° N. Except for the Gulf of California and Hudson Bay, AOD values in the other fourteen surveyed inland seas surpass the mean levels found at similar latitudes in oceanic regions. Among which, the Bohai Sea stands out as the most polluted oceanic region with AOD value of 0.35. Over the last four decades, AOD trends have revealed a significant decrease across about 89.5 % of global oceanic grids, while an increase in AOD is observed in low-latitude oceanic areas (30° S–30° N). Investigation into inland seas shows that nearly two-thirds have experienced a declining AOD trend, while sharply upward trends in AOD are primarily found in Asia. The Bohai Sea shows the largest increase in AOD, with an annual growth rate of 1.4 %. The turning-points of the AOD in each inland sea confirm the success of regional emission control policies initiated on the adjacent continents. To improve air quality in inland seas like the Bohai Sea, adjusting industrial layouts, such as relocating heavy industries from the surrounding coastal cities' proximities to areas near open seas, could significantly benefit public health.

Analysis of Daytime and Night-Time Aerosol Optical Depth from Solar and Lunar Photometry in Valladolid (Spain)

Aerosol optical depth (AOD) at night-time has become a hot topic in recent years due to the development of new instruments recording accurate ground-based lunar irradiance measurements, and the development of calibration methods and extraterrestrial irradiance models adapted to lunar photometry. This study uses all daytime and night-time AOD data available at Valladolid (Spain) from October 2016 to March 2022 in order to analyze its behavior and the added contribution of night data. The annual, monthly and daily AOD evolution is studied comparing daytime and night-time values and checking the correlation between them. For this purpose, the daily averages are computed, showing an annual pattern, with low AOD values throughout the year (mean value of AOD at 440 nm: 0.122), where winter months have the lower and summer the higher values, as observed in previous studies. All these AOD values are modulated by frequent desert dust events over the Iberian Peninsula, with a strong influence on daily and monthly mean values in February and March, where the strongest desert outbreaks occurred. The added new data confirm these results and the good correlation between daytime and night-time data. Also, a complete daily evolution is shown, observing that AOD and Ångström exponent (AE) mean values vary by only ±0.02 in 24 h, with a maximum value at 06:00 UTC and minimum at 18:00 UTC for both parameters.

Spatio-temporal variations of aerosol optical depth over Ukraine under the Russia-Ukraine war

The ongoing Russia-Ukraine war has an impact on air quality in the contested region, but it is difficult to assess it during the war and to distinguish between weather conditions and anthropogenic impacts on air pollution. Aerosol optical depth (AOD) might be a way to indicate the regional air quality remotely. In this study, we analyze satellite-based MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD products to compare monthly mean AOD values before and during the war. By examining the spatial-temporal distribution of AOD in 2022 and comparing it with a baseline period from 2012 to 2021, we aim to assess the impact of the conflict. Our analysis employs a time series algorithm that decomposes long-term trends and seasonal variations, enabling us to identify AOD changes associated with the war-induced artificial perturbations. Additionally, we utilize satellite-based tropospheric NO2 data and nighttime lighting data as auxiliary sources to support the analysis of abnormal AOD changes resulting from the war. Furthermore, four parameters from Aerosol Robotic Network (AERONET) measurements in the Kyiv site, including angstrom exponent (AE), single scattering albedo (SSA), refractive index (RI), fine mode fraction (FMF) were exclusively discussed to explore the possible changes of aerosol physical-optical properties over Ukraine during the war. Results showed that air quality in Ukraine has been affected by the war in contradictory ways at different levels. At the national level, atmospheric pollution has dropped across Ukraine due to a decrease in the sources of air pollution emissions as a result of the suppression of economic and agricultural activities. Meanwhile, atmospheric air quality has deteriorated at the local scale where war is intense due to the large amounts of air pollutants emitted by explosions. Specifically, a significant decrease in AOD of 22.46% compared to the baseline period was observed across Ukraine in January and February 2022 before the war. Additionally, there was a column density reduction of over 10% for tropospheric NO2 compared to the same period in the previous year. Following the outbreak of the war on February 24, significant increases in AOD were observed in March when compared to the baseline period. Eastern Ukraine experienced a significant increase of 40.14%, while northern Ukraine and central Ukraine saw rises of 34.15% and 45.78%, respectively. In April, a wider distribution of areas with significantly high AOD values across Ukraine was observed compared to March. In July, widespread areas with anomalous low AOD appeared in northern and western Ukraine, likely due to a decrease in post-harvest agricultural burning caused by the war. In August, anomalous high AOD areas were observed in central Ukraine, possibly attributed to continued Russian long-range strikes and a new round of bombardments.

Spatial distribution of aerosols burden and evaluation of changes in aerosol optical depth using multi-approach observations in tropical region

Understanding of Aerosol optical depth (AOD) parameter is important for air quality assessment. This study aims to evaluate and validate AOD measurements from combine datasets to improve air quality for a period 2005–2020 using Aerosol Robotic Network (AERONET) at Ilorin site (8.320° N, 4.340° E) in Nigeria. AOD outputs from Community Atmosphere Model Version 6 with chemistry (CAM6-chem) at 1° horizontal resolution and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) are investigated in addition to validation of two satellites AOD retrievals: Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR). Result of spatial distribution of AOD shows high values > 1 in the North and Western Sahara compared to Central Africa. Desert dust shows largest contribution in the North and Western Africa that is up to 2 magnitude larger than other aerosol types. Primary organic matter (POM) and secondary organic aerosols (SOAs) both presents high burdens with later been dominant at around 10° band, and black carbon (BC) largest burden (2.6 × 10 − 5 kgm − 2) is seen in the model from oil and gas exploration site in Nigeria. Inter-comparison of MERRA/MISR/MODIS and AERONET AOD using linear correlation of the seasonal dependence demonstrated high correlation (r = 0.864 − 0.973) subjected to Root Mean Square Error (RMSE = 0.069 − 0.211), suggesting good agreement between the datasets. When compared to seasonal mean maximum AERONET AOD value of 0.978 MERRA is ∼5%, MISR ∼28% and MODIS ∼29% lower with stronger correlations observed in the wet and pre-harmattan seasons. Similarly, MODEL AOD at 550 nm and dust burden were found to be ∼34% and ∼67% lower in context to AERONET AOD annual mean value of 0.627. Positive relationships that indicate an upward slope exist between all the computed datasets with moderate value of AERONET/CAM-chem spearman partial correlation, and MERRA/MODIS and MODIS/MISR showing strong and significant relationship with p-value less than 0.05. Low variance is observed with all measurements except in MERRA.

Aerosol optical depth regime over megacities of the world

Abstract. Currently, 55 % of the world's population resides in urban areas and this number is projected to increase to 70 % by 2050. Urban agglomerations with a population over 10 million, characterized as megacities, are expected to be more than 100 by 2100. Such large concentrations of population could boost creativity and economic progress, but also raises several environmental challenges such as air quality degradation. In this study, we investigate the spatial and temporal variability of urban aerosol state of 81 cities with a population over 5 million, relying on daily satellite-based aerosol optical depth (AOD) retrievals, derived at fine spatial resolution (0.1∘×0.1∘), over an 18-year period spanning from 2003 to 2020. According to our results, the lowest long-term mean AOD values worldwide were found in European and American cities (from 0.08 to 0.20). For almost all African and Asian cities, mean AOD ranged from 0.25 up to 0.90, but a considerable dust aerosol contribution (up to 70 %) was found for some of them with associated mean dust optical depth (DOD) values reaching up to 0.4. Mostly Chinese and Indian cities tend to have higher mean AOD values in the areas surrounding their center, while the opposite was found for most of the cities in the rest of the world. High intraannual AOD variability was revealed for the eastern American cities, while lower values were found in Chinese, eastern Indian and the eastern Mediterranean cities. During the study period, statistically significant negative AOD decadal trends were found for East Asian, European and North American cities, with the greatest decrease of −0.1 to −0.3 per decade recorded for the Chinese cities, in which the maximum mean AODs (0.45–0.91) are observed. In most of the US cities, where low mean AOD <0.17 was recorded, considerable declining AOD trends were found (−30 % to −50 % per decade). For the rest of Asian, African and South American cities, statistically significant AOD increase was found, with the greatest values of +0.07 to +0.16 per decade recorded for Indian cities. In Bengaluru (India), it is reported the lowest mean AOD value (0.2) and the maximum AOD increase (+69 %), which may be partially attributed to the population growth over the study period. The agreement of the satellite-derived AOD trends against those obtained from ground-based AERONET measurements was examined. For ground-based stations within the geographical limits of the contiguous urban area of the examined cities, a 0.93 correlation for the long-term means of AOD was found and ∼75 % of the derived trends agreed in sign. It was found that the spatial homogeneity within the examined satellite domain and the location of the surface station were key factors that determined their agreement. The present study highlights the vital and essential contribution of spaceborne products to monitor aerosol burden over megacities of the planet towards fulfilling the United Nations Sustainable Development Goal of “sustainable cities and communities”, dealing with urban air quality.

Estimation of the Mass Concentration of Volcanic Ash Using Ceilometers: Study of Fresh and Transported Plumes from La Palma Volcano

This study presents a synergistic approach to the study of the aerosol optical and microphysical properties measured in La Palma, Spain, during the 2021 eruption of the Cumbre Vieja volcano (from 19 September to 13 December 2021). This study aims to characterize the different phases of the volcanic eruption using the spatio-temporal evolution of the event together with the mass concentration quantification of four different atmospheric layers. The impact of the plume’s pathway that reached the South of France is analyzed. Here, passive and active remote sensors were used, namely CL51 and CL61 ceilometers and AERONET sunphotometers. The attenuated backscattering ranged from 0.8 to 9.1 × 10−6 (msr)−1 and the volume depolarization ratio measured nearby the volcano was up to 0.3. The ash plume remained within the first 4 km agl, with intense episodes that reached mean aerosol optical depth values of up to 0.4. Thirteen study cases were selected where coarse mode was dominant over fine mode. For the data selection, the fine and coarse lidar ratios found were 3.9 ± 0.8 and 21.0 ± 3.8 sr in the north and 6.9 ± 1.8 and 30.1 ± 10.3 sr in the south. The ash mass concentration reached moderate levels with maximum values of up to 313.7 μgm−3.

Full-coverage 1-km estimates and spatiotemporal trends of aerosol optical depth over Taiwan from 2003 to 2019

Satellite-derived aerosol optical depth (AOD) provides an effective way to investigate global and regional variations in atmospheric aerosols. However, due to cloud cover and surface reflectance, AOD datasets derived from satellite instruments generally have non-random missing values, which introduces additional uncertainty into AOD data and limits its downstream. To remedy this problem, this study used a two-stage approach based on spatial interpolation and a random forest model to fill the gaps in data generated by the Multiangle Implementation of Atmospheric Correction (MAIAC) aerosol retrieval algorithm, which provides the best-available AOD product to the global public. The relationship between ground-level fine particulate matter concentrations and satellite AOD was considered in the modeling. By gap-filling daily 1-km MAIAC AOD data from 2003 to 2019 over Taiwan, the two-stage model achieved comparable accuracy (coefficient of determination = 0.52, root-mean-square error = 0.22) against ground-level AOD measurements to the accuracy that has been achieved by previous studies. Furthermore, it improved daily high-spatial-resolution AOD estimates to 100% of spatial coverage. Comparisons between the full-coverage estimates and MAIAC retrievals showed that the MAIAC AOD dataset generally underestimated monthly/seasonal/annual mean AOD values in Taiwan. We also used the long-term estimates of the daily 1-km AOD dataset with full coverage to explore the spatiotemporal trends in AOD in Taiwan. The practical approach developed in this study is suitable for application in long- and short-term studies of air pollution and its effects on public health.

Features of the Extreme Fire Season of 2021 in Yakutia (Eastern Siberia) and Heavy Air Pollution Caused by Biomass Burning

Yakutia (Eastern Siberia) is one of the most fire-prone regions of Russia, which is frequently affected by large-scale wildfires despite a relatively short warm period, which usually lasts from May to September. In 2021, Yakutia experienced the worst fire season over the last four decades. In this study, we investigate features of the extreme fire season, factors that promote extreme fire weather, and heavy air pollution caused by biomass burning in the region utilizing multiple satellite and ground-based observations along with reanalysis data and forward-trajectory modelling. The results demonstrate that the total number of hotspots (HS) in 2021 amounted to ~150,000, which is almost twice as much as the previous record year (2020). One of the main features of the 2021 fire season was the period of extensive growth of the number of HS, which occurred from 24 July to 12 August. High fire danger during the fire season was promoted by positive anomalies in monthly air temperature (August) and negative anomalies in monthly precipitation (May–July). August of 2021 in central Yakutia was the second most hot August (14.9 °C) during a 43-year NCEP-DOE Reanalysis record (1979–2021). In addition, the intensification of wildfires during August 2021 was associated with persistent high-pressure systems, which promoted dry weather conditions in the region by blocking the transport of moist air masses from the western part of Russia. The low wind speeds, observed in the center of a high-pressure system, led to the accumulation of wildfire emissions in the atmosphere, which significantly affect air quality in the region. The monthly mean aerosol optical depth values in July 2021 were 0.82 (MODIS MAIAC) and 1.37 (AERONET) which were 14.9 and 18.7 times higher than respective values of 2007 (the year with minimal wildfires in the Asian part of Russia and Yakutia). Based on aerosol index observations and forward trajectories, we demonstrate that smoke plumes originated from the study area were transported over long distances reaching the Ural Mountains in the west, Mongolia in the south, the North Pole in the north, and Alaska in the east, traveling the distances of ~2000–7000 km. Maximum spatial extent of the smoke plumes reached ~10–12 mln. km2.

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).

A study on the vertical distribution of dust transported from the Tigris–Euphrates basin to the Northwest Iran Plateau based on CALIOP/CALIPSO data

The space-borne CALIOP lidar data has been used to better understand the dust transport mechanism from the Mesopotamian region to the atmosphere of Zanjan, a city in the Northwest Iran Plateau. The level 2 aerosol profile data product of the CALIOP has been studied for 142 overpasses during 2006–2018. The mean values of aerosol optical depth (AOD) and particulate depolarization ratio (PDR) at 532 nm, extracted from 142 cases, are 0.23 and 0.17, respectively. Moreover, 32 dust events (23% of all) have been recorded. For these cases, the mean values of AOD and PDR reach 0.53 and 0.21, respectively. The monthly-mean values of AOD and PDR confirm previous studies that dust particles are the dominant type of aerosols in the atmosphere of Zanjan, and their concentrations are remarkably increased in dry and warm months, especially between April to August. Based on the vertical profiles of PDR and extinction coefficients, the altitude range of about 1–3.5 km AGL is the most probable range of dust layer distribution in the studied area. Also, some dust events have been studied in more detail using the CALIOP data, sunphotometer data, ECMWF and HYSPIT meteorological models, and AOD product of the MODIS. Based on the results, dust particles originated from the Tigris–Euphrates basin, rise from the surface of Mesopotamia, move eastward, pass above the Zagros Mountains (the barrier between Mesopotamia and Iran Plateau), and finally reach the atmosphere of the studied area and cause dust events. It seems that it is the most probable mechanism of dust transport to the Northwest Iran Plateau.

Aerosol Optical Depths during Two Harmattan Seasons in Ile-Ife, Nigeria

Aim: To quantify the atmospheric aerosol loading in order to predict the severity and accompanying consequences of aerosols at a tropical location in Ile-Ife, southwest Nigeria.
 Place and Duration of Study: Department of Physics and Engineering Physics, Obafemi Awolowo University, Ile-Ife, Nigeria, between November 2017 and March 2019.
 Methodology: Daily measurements of Aerosol Optical Depth (AOD) at about the local noon (12:30 pm–1:30 pm) for two consecutive Harmattan seasons (November 2017–March 2018; and November 2018 – March 2019) were carried out at three different wavelengths, 465 nm, 540 nm and 619 nm using a manually operated hand-held sun photometer (model Calitoo).
 Results: The mean values of AOD were 0.98, 0.87 and 0.83 in the 465 nm, 540 nm and 619 nm wavelengths respectively for November 2017 – March 2018; and 0.94, 0.83 and 0.78 in the 465 nm, 540 nm and 619 nm wavelengths respectively for November 2018 – March 2019. The values assume high levels of haziness at the study location. Intense Harmattan dust storm was experienced on some typical days with AOD values > 2. The resulting elevated level of atmospheric haziness led to visibility deterioration and visibility values greatly reduced to 1 km on such days. December, January and February months were the peak of the Harmattan. The distribution of the particle size indicated that the dominated aerosol is the coarse mode Harmattan dust during the period of study.
 Conclusion: The study location experiences a polluted atmosphere during the Harmattan season.

Space-Time Machine Learning Models to Analyze COVID-19 Pandemic Lockdown Effects on Aerosol Optical Depth over Europe

The recent COVID-19 pandemic affected various aspects of life. Several studies established the consequences of pandemic lockdown on air quality using satellite remote sensing. However, such studies have limitations, including low spatial resolution or incomplete spatial coverage. Therefore, in this paper, we propose a machine learning-based scheme to solve the pre-mentioned limitations by training an optimized space-time extra trees model for each year of the study period. The results have shown that our trained models reach a prediction accuracy up to 95% when predicting the missing values in the MODIS MCD19A2 Aerosol Optical Depth (AOD) product. The outcome of the mentioned scheme was a geo-harmonized atmospheric dataset for aerosol optical depth at 550 nm with 1 km spatial resolution and full coverage over Europe. As an application, we used the proposed machine learning based prediction approach in AOD levels analysis. We compared the mean AOD levels between the lockdown period from March to June in 2020 and the mean AOD values of the same period for the past 5 years. We found that AOD levels dropped over most European countries in 2020 but increased in several eastern and western countries. The Netherlands had the most significant average decrease in AOD levels (19%), while Spain had the highest average increase (10%). Moreover, we analyzed the relationship between the relative percentage difference of AOD and four meteorological variables. We found a positive correlation between AOD and relative humidity and a negative correlation between AOD and wind speed. The value of the proposed prediction scheme is further emphasized by taking into consideration that the reconstructed dataset can be used for future air quality studies concerning Europe.

Characterizing the long‐term dynamics of aerosol optical depth in the Yangtze River Middle‐Reach urban agglomeration, China

AbstractAlong with the rapid urbanization and economic development, the Yangtze River Middle‐Reach urban agglomeration (YRMR) has suffered from increasingly serious environmental problems. Characterizing the long‐term dynamics of aerosol optical depth (AOD) in YRMR is of important significance for scientific control of aerosol pollutants over this region. Previously, numerous researches have analysed the temporal and spatial characteristics of AOD in different regions through statistical values of AOD time series or using trend analysis methods based on linear regression models. It is challenging to approximate nonlinear trends and identify change points of AOD time series. This paper proposed a new methodology for investigating the dynamics of AOD over the YRMR region on a monthly basis by using the Terra MODIS Collection 6.1 Level 2 aerosol products (MOD04_L2) during 2001–2017. A three‐dimensional spatio‐temporal interpolation method was used to generate gap‐filled monthly AOD maps, and then a generic Bayesian time series decomposition algorithm was applied to analyse the trends and change points of monthly AOD time series. The results showed that the areas with high AOD values were mainly located in the core cities and the connecting belts. Strong positive AOD anomalies had been observed during 2006–2011, whereas the positive anomalies were typically intermingled with negative anomalies and it indicated that the evolution patterns of AOD for different regions were different and influenced by fluctuations. Trend analysis of the monthly mean AOD values indicated that AOD in YRMR increased first, then fluctuated, and finally decreased. Although it was difficult to separate the increasing and fluctuating periods from each other due to the fluctuation, the decreasing trend after 2011 was significant, and a significant drop of AOD had been observed since 2014. Long‐term AOD variations were closely related to national policies, and the results could provide useful references for regional environmental assessment and decision‐making.

Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua

This study provides characteristics of aerosol columnar properties, measured over ten countries in Eastern Europe from 2002 to 2019. Aerosol optical depth (AOD) and Ångström exponent (AE) were obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 merged Dark Target and Deep Blue aerosol product. The product is validated using ground-based Aerosol Robotic Network (AERONET) situated at Minsk, Belsk, Moldova and Kyiv. The results showed that 76.15% of retrieved AOD data are within the expected error. It was established that 64.2% of AOD points are between 0 and 0.2 and 79.3% of all AE points are over 1. Mean AOD values in the region vary from 0.130 ​± ​0.04 (Moldova) to 0.193 ​± ​0.03 (Czech Republic) with mean value in the region 0.162 ​± ​0.05. Seasonal mean AOD (AE) values were at the maximum during the summer from 0.231 ​± ​0.05 (1.482 ​± ​0.09 in winter) to minimum 0.087 ​± ​0.04 during the winter (1.363 ​± ​0.17 in summer). Gradual AOD reduction is observed in all countries with annual trend from −0.0050 (Belarus) to −0.0029 (Russia). Finally, the relationship between AOD and AE was studied to classify various aerosol types and showed seasonal non-uniformity of their contribution depending on variation in sources. The entire region is under significant impact of various aerosol types, including clean continental (СС), mixed (MX) and anthropogenic/burning (AB) aerosols types that are at 59.77%, 24.72%, and 12.97% respectively. These results form an important basis for further regional studies of air quality and distribution of sources of pollution.

SPATIAL-TEMPORAL CHARACTERISTICS OF THE AEROSOL OPTICAL DEPTH (AOD) DERIVED FROM LONGTERM (1980–2018) MERRA-2 OVER GUANGDONG

Abstract. This paper presents and compares the aerosol optical depth (AOD) spatial-temporal characteristics over five subsets in different locations of Guangdong, as well as Hong Kong and Macau (GDHM) since reform and opening-up. By means of GIS analysis tools and subset the onward MERRA-2 monthly mean value aerosol reanalysis dataset to the size of study area, the results reveal that the yearly mean AOD over the whole GDHM ranged from 0.18 to 0.69 during 1980 to 2018. The field average of AOD in five chosen areas approached to 0.40 and appeared linearly increased at 0.0077 per year. All the five selected areas reached their yearly mean AOD peaks at 2007. The field average AOD increased rapidly at 0.028 per year from 1997 till 2007 then appeared decreasing oscillation in a linear slope −0.0109 per year since 2007. But the average AOD of 2010–2018 is higher than the former three decadal averages. Comparing the former and the latter two decades, the high yearly mean AOD value clusters have moved from northern parts of Guangdong to central north Pearl River Delta, where also appeared more apparent AOD yearly change among the other three parts since late 1990s. Only six yearly mean AOD over southern cities of Pearl River estuary were lower than east or west comparing parts in 1980s. Eastern part of Guangdong stayed the lowest yearly mean AOD region in 21years of the past 39 years. Central, southern and western of GDHM had 36 years while northern and western of GDHM had 37 years their AOD values during February to April were the high values of the year.

Aerosol Optical Characteristics During the Biomass Burning Season in Southeastern Mexico

In this paper, we present a characterization of the optical properties of the aerosols emitted during biomass burning (BB) season in the period 2005–2009. Trends of aerosol optical depth (AOD), Angstrom exponent (α), and precipitable water (PW) were analyzed using a 5-year dataset from AErosol RObotic NETwork (AERONET) observations over Tuxtla Gutierrez (TG), Chiapas. The overall mean AOD (500 nm) during the 2005–2009 period was 0.26 ± 0.18. However, monthly mean values of AOD > 0.5 during the spring months (April and May) would indicate the high load of particles emitted by fires. The overall mean of α (440–870 nm) was 1.40 ± 0.21, which confirms the presence of fine aerosols. Additionally, the combined analysis of the α with its spectral curvature δα, and the results from the spectral de-convolution algorithm (SDA) shows that fine-mode aerosols dominated AOD variability in TG. In this paper, the trajectories of air masses (400 and 1500 m, a.s.l.) arriving at the TG site were classified by using backward trajectory cluster analysis. Trajectory clustering results indicate a BB regional transport from Central America that affects the atmosphere in southeastern Mexico. We use observations of fire radiative power (FRP) from the Moderate Resolution Imaging Spectroradiometer (MODIS) to study the incidence of wildfires and to estimate the BB emissions from 2005 to 2009 in southeastern Mexico. The results indicated a gradual decrease in fires throughout the years. Campeche and Yucatan are the states in southeastern Mexico where BB produces the highest emissions of carbon dioxide (CO2), carbon monoxide (CO), black carbon (BC), and particulate material PM2.5. However, the largest emissions come from wildfires in Guatemala. Finally, to put in context the aerosol optical properties over southeastern Mexico, the sun photometric measurements in TG are compared with those retrieved from AERONET stations located in other tropical biomass burning regions (Brazil and Zambia).

Temporal-Spatial Characteristics and Variability in Aerosol Optical Depth over China During 2001-2017

Based on the latest monthly data of moderate resolution imaging spectroradiometer (MODIS)/Terra C6.1 aerosol optical depth (AOD), the temporal-spatial distribution and variability trend in AOD over China during 2001-2017 are analyzed to explore the distribution and variation characteristics of AOD in China. Regarding the spatial characteristics, the first prominent high-value center of the annual mean AOD was located in the industrially and economically developed areas of the North China Plain, Central China, the Yangtze River Delta region, the Pearl River Delta region, and the Sichuan Basin. The second prominent high-value center of the annual mean AOD was located in the dust aerosol-dominated areas of Taklimakan Desert. Two low-value centers of the annual mean AOD were located in the eastern part of Inner Mongolia to the north of Northeast China and the Tibet Plateau. Regarding the temporal characteristics, the AOD value peaked in eight areas in spring and summer. The annual mean AOD values in the Taklimakan Desert, Sichuan Basin, and Pearl River Delta peaked from March to May, and those in the North China Plain, Central China, and Yangtze River Delta peaked from May to July. The trend characteristics showed that during 2001-2006, the AOD in Northwest China and Inner Mongolia showed a downtrend, and that in the east-central China and the eastern part of southwest China showed a growth trend. During 2007-2012, the trend of AOD in the Tibetan Plateau and the Taklimakan Desert changed from decreasing to increasing. The growth trend of AOD in the North China Plain and the Sichuan Basin was weakened, and the AOD in the Yangtze River Delta showed a weak downward trend. During 2013-2017, the AOD in most areas of China showed a significant downward trend.

Spatial-temporal Distribution of Aerosol Optical Depth and Its Main Influence Types in China During 1990-2017

In order to accurately understand the optical characteristics of aerosols in China, based on Mann-Kendall(MK) and Sen's slope trend analysis methods, the spatiotemporal variations of aerosol optical depth(AOD) derived from MERRA-2 reanalysis datasets were estimated in China for the period of 1990-2017. The results showed that ① for the interannual scale, there was a significant increasing trend in the annual mean AOD in China during 1990-2017. Besides, high aerosol loadings were observed in spring and summer, and the seasonal difference between the eastern and western regions was large. This was mainly due to the topographic and meteorological factors. ② At the spatial scale, the annual mean AOD values increased from the northwest to the southeast, with characteristically high AOD values occurring in Sichuan Pendi and the Tarim and Turpan basins and low values in the Qinghai-Xizang plateau region. Similarly, the AOD MK value and Sen's slope value showed significant decreasing trends from the southeast to the northwest, which was closely related to climate change and the human activity intensity. ③ In regard to black carbon aerosol, dust aerosol, organic carbon aerosol, sea salt aerosol, and SO4 aerosol, dust and SO4 aerosols were affected by the air humidity and human activity intensity, which have obvious regional differences in China.

Aerosol optical properties over Europe: an evaluation of the AQMEII Phase 3 simulations against satellite observations

Abstract. The main uncertainties regarding the estimation of changes in the Earth's energy budget are related to the role of atmospheric aerosols. These changes are caused by aerosol–radiation (ARIs) and aerosol–cloud interactions (ACIs), which heavily depend on aerosol properties. Since the 1980s, many international modeling initiatives have studied atmospheric aerosols and their climate effects. Phase 3 of the Air Quality Modelling Evaluation International Initiative (AQMEII) focuses on evaluating and intercomparing regional and linked global/regional modeling systems by collaborating with the Task Force on the Hemispheric Transport of Air Pollution Phase 2 (HTAP2) initiative. Within this framework, the main aim of this work is the assessment of the representation of aerosol optical depth (AOD) and the Ångström exponent (AE) in AQMEII Phase 3 simulations over Europe. The evaluation was made using remote-sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra and Aqua platforms, and the instruments belonging to the ground-based Aerosol Robotic Network (AERONET) and the Maritime Aerosol Network (MAN). Overall, the skills of AQMEII simulations when representing AOD (mean absolute errors from 0.05 to 0.30) produced lower errors than for the AE (mean absolute errors from 0.30 to 1). Regardless of the models or the emissions used, models were skillful at representing the low and mean AOD values observed (below 0.5). However, high values (around 1.0) were overpredicted for biomass burning episodes, due to an underestimation in the common fires' emissions, and were overestimated for coarse particles – principally desert dust – related to the boundary conditions. Despite this behavior, the spatial and temporal variability of AOD was better represented by all the models than AE variability, which was strongly underestimated in all the simulations. Noticeably, the impact of the model selection when representing aerosol optical properties is higher than the use of different emission inventories. On the other hand, the influence of ARIs and ACIs has a little visible impact compared to the impact of the model used.

Variation in MERRA-2 aerosol optical depth and absorption aerosol optical depth over China from 1980 to 2017

4258 instantaneous 550 nm Aerosol Optical Depth (AOD) values were compared between the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) and the Aerosol Robotic Network (AERONET) in four seasons at 12 AERONET sites across China. The correlation coefficients (R) in spring, summer, autumn and winter were 0.88, 0.92, 0.91 and 0.87, respectively. The MERRA-2 AOD was compared with the Moderate resolution Imaging Spectroradiometer (MODIS/Aqua) AOD over China from 2003 to 2017, and good agreement was obtained. 4501 daily AOD values were compared between MERRA-2 and MODIS at 16 sites over China. Spatial distribution and temporal variation of MERRA-2 AOD over China were analyzed from 1980 to 2017. Mean values of MERRA-2 AOD indicated that high AOD mainly appeared in the eastern, southeastern and central China, while low AOD mostly occurred in the western and northeastern China. Mean AOD values over China during this study period in each month was also discussed, and similar spatial distribution (high AOD in developed areas, low AOD in rural and less developed areas) was found in each month. Slight AOD increase could be observed in the 1980s and 1990s, and a rapid increase happened from 2001 to 2010, followed by an AOD decrease between 2011 and 2017. Annual variation of mean AOD of the whole China (the Yangtze River Delta) showed a slight increase of 0.0010 (0.0045) per year from 1980 to 1999, a rapid increase of 0.0096 (0.0271) per year between 2000 and 2009, and a decrease of −0.0089 (−0.0206) per year from 2010 to 2017. Annual AOD Variation in Jing-jin-ji and Pearl River Delta is similar to that in the Yangtze River Delta. In four seasons, AOD change was similar to the annual AOD variation except winter with a slight decrease of −0.0012 per year between 1980 and 1999. AOD variation over China before and after the Pinatubo volcanic eruption in the Philippines in June 1991 was analyzed to get a better understanding of the transport and the impact on the environment from volcanic pollutants. AOD variation trend over China was studied in two periods. The increasing trend appeared in most part of China from 1980 to 2009, while a decreasing trend could be found in almost the entire China between 2010 and 2017. Spatial and temporal variation of MERRA-2 Absorption Aerosol Optical Depth (AAOD), Black Carbon Absorption Aerosol Optical Depth (BCAAOD) and Dust Absorption Aerosol Optical Depth (DUAAOD) were analyzed during the period between 1980 and 2017. BCAAOD (66.30%) and DUAAOD (30.56%) offered the major contribution to total AAOD in China. 38 years of variation of AAOD over China is mainly due to the variation of BCAAOD. BCAAOD experienced an increase (1980–2007) and a decrease (2008–2017) during the 38 years in China.