Means Of Aerosol Optical Depth Research Articles

Aerosols Optical Properties Over Different Regions Over Iraq

investigating the spatial and temporal distribution of aerosols is crucial to the knowledge of their impact on air quality. In present work, the spatiotemporal variation of aerosol over different sites in Iraq was examined using aerosol Optical Depth (AOD) and Angstrom Exponent (AE) from the Moderate Resolution Imaging Spectroradiometer (MODIS) during 2003–2021, and Aerosols Index (AI) retrieved from the Ozone Monitoring Instrument 2005-2021. Satellite retrieval data is divided into three periods include, (2003–2007), (2008–2013) and (2014–2021). The results of the linear regression analysis of aerosol optical properties demonstrate that the second period (monthly mean AOD and AE) has distinct trends in all considered cities when compared with the first and third periods. Between 2008 and 2014, there was a tendency toward increased monthly mean AOD levels whereas monthly mean AE values shows decreasing. The annual mean of AOD is greater than 0.5. This indicates a high aerosol loading with a moderate intensity when equivalent to 0.4. Haditha and Basra experienced the highest annual mean of AOD (lowest AE) during the summer and spring months, while Duhook and Sulaymaniyah had significantly lower values. The results revealed considerable variability of the AOD, AE, and AI monthly mean on both spatial and temporal scales, having the highest AOD, AI, and AE decrease levels in the northwest and southern regions. While there was the lowest AOD, AI, and maximum AE over the northern parts of Iraq. Throughout the study period, the monthly temporal mean of AOD and AI peaked from May to July. These months have the highest aerosol activity, affecting the northwestern, southwest, and southern parts of Iraq. Minimum values of AOD, AI with maximum AE observed in the winter season, having the lowest aerosol activity effect over Iraq.

The observational evidence of association between types of aerosol mode-cloud-precipitation interaction over Iran

The present study quantifies for the first time the statistical relationship between aerosol properties with Cloud microphysical Properties (CPs), and consequently effect on precipitation over Iran. The daily means of Aerosol Optical Depth (AOD), Angstrom Exponent (AE), and CP including Cloud Fraction (CF), Cloud Top Temperature (CTT), Cloud Top Pressure (CTP), Cloud Optical Thickness (COT), and Cloud Effective Radius (CER) were obtained from the MODerate resolution Imaging Spectroradiometer (MODIS). The precipitation was retrieved from Tropical Rainfall Measuring Mission (TRMM) during 2003–2019 for 156 1 × 1 geographical degree grid-points over Iran. The different types of aerosols including the dust and fine aerosols were separated using the AOD and AE values for each season. We identified grid points, which had statistically significant correlation (at the 5% level) between aerosol modes and at least one of CPs, the precipitation and one of CPs, and between the precipitation and aerosols modes, at the same time. With this approach, we identified 10 points showing a statistically significant relationship between AOD, CPs, and precipitation, stimulatingly. For instance, at a point in the southwest of Iran, the correlation coefficient between the AOD with precipitation (r = 0.54), AOD with CTP (r = −0.51), and precipitation with CTP (r = −0.61) were statistically significant simultaneously. Based on statistical calculations, the relationship between precipitation and AOD (for 10 points) is often positive, which indicates the positive effect of aerosols on precipitation. However, in two points, the relationship between precipitation and AOD is negative, and subsequently significant. In addition, a negative correlation coefficient is also observed between CTT and CTP with AOD, as well as a positive relationship between AOD and COT for both fine (black carbon) and coarse mode (desert dust) of aerosols over Iran. Due to the lack of ground station data in Iran, this study can serve as a starting point to better understanding the complex, and uncertain response to cloud, radiation and precipitation to aerosol over arid region of Iran.

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.

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).

Spatial distribution and temporal variation of aerosol optical depth in the Western Pacific Ocean

The temporal and spatial characteristics of the aerosol optical depth (AOD) in the Western Pacific Ocean are analyzed using the field observation data and AVHRR remote sensing data. The observation AOD shows a significant north-south difference with a boundary of 25°N. In the north, the AOD spectral distribution shows a feature of decrease with the increase of wavelength in the range of 440–870 nm. In the south, the AOD maximum is at 500 nm. The average AOD (440) in the north is 0.177 larger than that in the south. The northern average Ångström exponent (α) is 3.2 times as large as that of the south. In terms of climatology, as the subtropical high ridge moves northward up to 12° from February to August, the location of AOD(630) maximum around 35°N moves northward by 10.5°. In addition to the northern maximum, the zonal mean of AOD(630) from AVHRR shows another maximum, located at 10°N. The AOD(630) at 35°N reaches its maximum in April, while the AOD(630) at 10°N reaches its maximum in March. The multi-year variation of AOD(630) at 35°N is consistent with that at 10°N with a correlation coefficient of 0.77. Research on the month of the climatological AOD(630) maximum at around 10°N shows that it is attributed to the joint action of aerosols from the sea south of 10°N and East Asia.

Improved Clear Sky Model from In Situ Observations and Spatial Distribution of Aerosol Optical Depth for Satellite-Derived Solar Irradiance over the Korean Peninsula

In solar resource assessment, the climatological environment of the target area is objectively quantified by the cloudiness or clear sky index, which is defined as the ratio of global horizontal irradiance to clear sky solar insolation. The clear sky model calculates incoming solar irradiance on the ground surface considering several atmospheric parameters such as water vapor and aerosol optical depth. This study investigated the importance of aerosol optical depth for deriving clear sky irradiance in radiative transfer models and examined its viability in a universal or community model for public use. The evaluation was conducted based on ground observations at the Korea Institute of Energy Research (KIER) station from January to December 2021. The original simulation was performed using the monthly mean of aerosol optical depth obtained from the Aerosol Robotic Network station; the mean absolute error was 29.9 W m−2. When the daily mean of in situ observations at KIER was incorporated into the clear sky model, the mean absolute error was reduced to 9.7 W m−2. Our results confirm that the clear sky model using gridded datasets of aerosol optical depth is suitable for use as a universal or community model.

The relationship between PM2.5 pollution and aerosol radiative forcing in a heavy industrial city, Taiyuan, in China

Rapid economic development had an important impact on the concentration of air pollutants and the aerosol properties in Taiyuan City, one of China's most important energy and heavy industry bases. Therefore, the long-term measurements of the optical and radiation properties of aerosols and air pollutants monitored by several urban sites in Taiyuan from 2013 to 2019 were analyzed. During the observation period, the multi-year mean concentrations of PM2.5, PM10, SO2, NO2 and CO were 65 ± 7 μg/m3, 129 ± 14 μg/m3, 57 ± 21 μg/m3, 45 ± 6 μg/m3, 1.45 ± 0.31 mg/m3, respectively. The concentrations of various pollutants were highest in winter (PM2.5: 90 μg/m3; PM10: 149 μg/m3; SO2: 109 μg/m3; NO2: 49 μg/m3; CO: 2.03 mg/m3). After the implementation of air pollution control in 2013, the annual mean concentrations of PM2.5, PM10, SO2 and CO in 2019 had been reduced by 28%, 29%, 73% and 47% respectively compared with those in 2013. But aerosol optical depth (AOD) and radiative forcing had no remarkable downtrend. Annual mean of AOD at 500 nm varied from 0.43 to 0.60 with high single scattering albedo (SSA), all above 0.91. Multi-year average radiative forcing at the top of atmosphere (TOA), interior of atmosphere (ATM), and bottom of the atmosphere (SFC) were − 2.68 ± 2.12 W/m2, 45.02 ± 3.14 W/m2, and − 47.46 ± 3.72 W/m2, respectively. And radiative forcing effects were strongest in winter (TOA: -5.74 ± 3.20 W/m2; ATM: 49.15 ± 3.85 W/m2; SFC: -54.83 ± 5.31 W/m2) due to the stronger anthropogenic emissions. The increase in humidity would increase the concentration of particulate matter and the extinction of the atmosphere. The increase of absorbing aerosols and scattering aerosols during the heating period in winter increased the aerosol radiative forcing, which would warm atmosphere and cool surface and then increase the stability of the atmosphere. Pollutants were difficult to diffuse and gradually accumulated thereby, and the radiative forcing effect continued to increase, forming positive feedback and making continuous pollution.

Evaluating temporal and spatial variability and trend of aerosol optical depth (550 nm) over Iran using data from MODIS on board the Terra and Aqua satellites

Our knowledge of the temporal-spatial variations of atmospheric aerosols is necessary because they can affect public health and air quality. This paper studied Collection 6, the product of Aerosol Optical Depth (AOD 550 nm), using the Deep Blue algorithm of moderate-resolution imaging spectroradiometer (MODIS) on board the Terra and Aqua satellites over Iran from 2003 to 2017. Long-term data of the dust using synoptic stations were also used. The results showed that the southwestern Iran, the Persian Gulf coast from Bushehr to Bandar Abbas, and the Makran coastal area in southeastern Iran have the highest seasonal means of Aerosol optical depth (AOD > 0.3) and that they are among the aerosol hotspot areas in southwestern Asia. Other regions in Iran, especially the northwest and the Zagros Mountains, have the lowest aerosol optical depth (AOD < 0.04). The highest AOD amount of Terra (0.144) and Aqua (0.156) occurs in the spring, and the lowest amount occurs in the autumn season (0.094 and 0.101 Terra and Aqua, respectively). The heights act as a barrier on the particle transport pathway and, as a result, will affect the release of dust on local and regional scales. AOD increase in Iran is more related to aerosol loading in deserts and arid areas around the country. The AOD increase during the cold period of the year in industrial cities is due to the combustion of fossil fuels and the reduction of the boundary layer height (BLH). It is because most atmospheric pollutants are released in the boundary layer and are homogenized through turbulent mixed layer processes. The most prominent active dust sources around Iran, which are the main source of aerosol increase, can be categorized into four sources: (1) Mesopotamian, (2) Northern Arabian Peninsula, (3) Elrob Elkhali desert, and (4) East Arabian Peninsula. The AOD seasonal trend showed that the most significant increasing trend occurs in autumn on the TERRA (42.82%) and Aqua (32.32%) satellites. The largest decreasing trend of AOD in Iran is observed in winter in Kermanshah province (− 0.0011 year−1) in western Iran and in other seasons in southeastern Iran for which meteorological changes play a major role.

Air quality investigation over Moundou Chad

The air quality over Moundou-Chad was examined using satellite dataset. Fifteen years aerosol optical depth (AOD) was obtained from the Multi-angle Imaging Spectro-Radiometer (MISR). The AOD dataset is statisticaly stable for further prediction. The highest AOD mean was observed in 2008. The standard deviation, average deviation and coefficient of variation all agrees that the AOD dataset is reliable. It is shown that the aerosol loading over Moundou is high and the size of the aerosol is very tiny to deposit in the human lungs.

Influence of biomass burning on local air pollution in mainland Southeast Asia from 2001 to 2016

In this study, various remote sensing data, modeling data and emission inventories were integrated to analyze the tempo-spatial distribution of biomass burning in mainland Southeast Asia and its effects on the local ambient air quality from 2001 to 2016. Land cover changes have been considered in dividing the biomass burning into four types: forest fires, shrubland fires, crop residue burning and other fires. The results show that the monthly average number of fire spots peaked at 34,512 in March and that the monthly variation followed a seasonal pattern, which was closely related to precipitation and farming activities. The four types of biomass burning fires presented different tempo-spatial distributions. Moreover, the monthly Aerosol Optical Depth (AOD), concentration of particulate matter with a diameter less than 2.5 μm (PM2.5) and carbon monoxide (CO) total column also peaked in March with values of 0.62, 45 μg/m3 and 3.25 × 1018 molecules/cm2, respectively. There are significant correlations between the monthly means of AOD (r = 0.74, P < 0.001), PM2.5 concentration (r = 0.88, P < 0.001), and CO total column (r = 0.82, P < 0.001) and the number of fire spots in the fire season. We used Positive Matrix Factorization (PMF) model to resolve the sources of PM2.5 into 3 factors. The result indicated that the largest contribution (48%) to annual average concentration of PM2.5 was from Factor 1 (dominated by biomass burning), followed by 27% from Factor 3 (dominated by anthropogenic emission), and 25% from Factor 2 (long-range transport/local nature source). The annually anthropogenic emission of CO and PM2.5 from 2001 to 2012 and the monthly emission from the Emission Database for Global Atmosphere Research (EDGAR) were consistent with PMF analysis and further prove that biomass burning is the dominant cause of the variation in the local air quality in mainland Southeast Asia.

Monitoring temporal–spatial variations of AOD over the Yangtze River Delta, China

Aerosol can induce visibility reduction, affect radiation balance and modify cloud property on the environmental effect, and show the harmful effects on human health. Insight of aerosol becomes an integral task in the process of control measures for environmental pollution. The present study provided an analysis of temporal–spatial variations of aerosol optical depth (AOD) using the MOD04 level-2 in collection 6 (C6) with the deep blue retrieval algorithm from January 2005 to December 2015 over Yangtze River Delta (YRD) in China. The AOD validations between MODIS and Aerosol Robotic Network (AERONET) were estimated by the methods of regression, correlation. Then, the periodic features and trends of AOD and angstrom exponent (AE) were explored with the wavelet transformation (WT) procedure. Further, the variations of AOD and AE spatial distribution on multi-time scales (annual, monthly and season) were demonstrated. Meantime, the sources of AOD are discussed. It was found that the daily AOD from MODIS has a strong correlation relationship (slope = 0.9838, r = 0.84) with AERONET over YRD. The variations of both AOD and AE on time series have been distinct temporal periodic (12, 6 and 4 months) characteristics, and show the decreasing trends on annual and semi-annual periods. On annual, the AOD on spatial distribution is slowly declining from the northwest towards the southeast, and the AE on spatial distribution is gradually decreasing from the northwest to the southeast and from the land to the coast. The variations both inter-annual AOD and AE on spatial distribution show the inverse trends, respectively. On monthly, the means of AOD range from minimum 0.46 in January to maximum 0.90 in July, and the variations of spatial distribution mainly occur in the north parts of Yangtze River and some scattered areas with high terrain and south coast. The means of AE range from minimum 1.13 in October to maximum 1.58 in April, and the variations of spatial distribution are mainly found in the south of Henan, the north of Jiangsu, the coast belt and the riverside of Yangtze River and the high terrain regions. On seasonality, the means of AOD reaches its maximum 0.68 in summer and minimum 0.50 in winter, and the variations of spatial distribution mainly occur in the coast belt, the north parts of Hongze Lake and the south parts with high terrain. The means of AE reaches its maximum 1.48 in spring and minimum 1.25 in autumn, and the variations of spatial distribution were shown the similarity with that of monthly.

The CU 2-D-MAX-DOAS instrument – Part 2: Raman scattering probability measurements and retrieval of aerosol optical properties

Abstract. The multiannual global mean of aerosol optical depth at 550 nm (AOD550) over land is ∼ 0.19, and that over oceans is ∼ 0.13. About 45 % of the Earth surface shows AOD550 smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity. We employ radiative transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 &lt; AOD430 &lt; 0.6) and (2) near-molecular scattering conditions (22 July, AOD430 &lt; 0.13) we compare RSP-based retrievals of AOD430 and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD430 is +0.012 ± 0.023 (CIMEL), −0.012 ± 0.024 (MFRSR), −0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMELAOD − MFRSRAOD) and yields the following expressions for correlations between different instruments: DOASAOD = −(0.019 ± 0.006) + (1.03 ± 0.02) × CIMELAOD (R2 = 0.98), DOASAOD = −(0.006 ± 0.005) + (1.08 ± 0.02) × MFRSRAOD (R2 = 0.98), and CIMELAOD = (0.013 ± 0.004) + (1.05 ± 0.01) × MFRSRAOD (R2 = 0.99). The average g measured by DOAS on both days was 0.66 ± 0.03, with a difference of 0.014 ± 0.05 compared to CIMEL. Active steps to minimize the error in the RSP help to reduce the uncertainty in retrievals of AOD and g. As AOD decreases and SZA increases, the RSP signal-to-noise ratio increases. At AOD430 ∼ 0.4 and 0.10 the absolute AOD errors are ∼ 0.014 and 0.003 at 70° SZA and 0.02 and 0.004 at 35° SZA. Inherently calibrated, precise AOD and g measurements are useful to better characterize the aerosol direct effect in urban polluted and remote pristine environments.

The empirical correlations between PM2.5, PM10 and AOD in the Beijing metropolitan region and the PM2.5, PM10 distributions retrieved by MODIS

We observed PM2.5, PM10 concentration, aerosol optical depth (AOD), and Ångström exponents (α) in three typical stations, the Beijing city, the Xianghe suburban and the Xinglong background station in the Beijing metropolitan region, from 2009 to 2010, synchronously. The annual means of PM2.5 (PM10) were 62 ± 45 (130 ± 88) μg m−3 and 79 ± 61 (142 ± 96) μg m−3 in the city and suburban region, which were much higher than the regional background (PM2.5: 36 ± 29 μg m−3). The annual means of AOD were 0.53 ± 0.47 and 0.54 ± 0.46 and 0.24 ± 0.22 in the city, suburban and the background region, respectively. The annual means of Ångström exponents were 1.11 ± 0.31, 1.09 ± 0.31 and 1.02 ± 0.31 in three typical stations. Meanwhile, the rates of PM2.5 accounting for PM10 were 44%–54% and 46%–70% in the city and suburban region during four seasons. The pollution of fine particulate was more serious in winter than other seasons. The linear regression functions of PM2.5 (y) and ground-observed AOD (x) were similarly with high correlation coefficient in the three typical areas, which were y = 74x + 18 (R2 = 0.58, N = 337, in the City), y = 80x + 25 (R2 = 0.55, N = 306, in the suburban) and y = 87x + 9 (R2 = 0.64, N = 350, in the background). The functions of PM10 (y) and ground-observed AOD (x) were y = 112x + 57 (R2 = 0.54, N = 337, in the city) and y = 114x + 68 (R2 = 0.47, N = 304, in the suburban). But the functions had large differences in four seasons. The correlations between PM2.5, PM10 and MODIS AOD were similar with the correlations between PM2.5, PM10 and the ground-observed AOD. With MODIS C6 AOD, the distributions of PM2.5 and PM10 concentration were retrieved by the seasonal functions. The absolute retrieval errors of seasonal PM2.5 distribution were less than 5 μg m−3 in the pollutant city and suburb, and less than 7 μg m−3 in the clean background.

Aerosol Direct Radiative Forcing over Shandong Peninsula in East Asia from 2004 to 2011

AbstractRecent vigorous industrialization and urbanization in Shandong Peninsula, China, have resulted in the emission of heavy anthropogenic aerosols over the region. The annual means of aerosol optical depth (AOD), Angstrom exponent (∝), single-scattering albedo (SSA), aerosol direct radiative forcing (ARF), surface radiative forcing (SRF), and top-of-the atmospheric radiative forcing (TOA) recorded during 2004–2011 were respectively 0.67±0.19, 1.25±0.24, 0.93±0.03, 47±9 W m-2, 61±9 W m-2, and −14±8 W m -2, The aerosol optical properties and ARF characteristics showed remarkable seasonal variations due to cycle changes in the aerosol components and dominance type. The atmosphere-surface system was cooled by ARF in all years of the study due to anthropogenic sulfate and nitrate emission and sea salt aerosols. The magnitude of TOA cooling was larger in summer (−15±17 W m-2) and autumn (−12±7 W m-2) than that in spring (−8±4 W m-2) and winter (−9±10 W m-2).

Observation of aerosol optical properties and particulate pollution at background station in the Pearl River Delta region

Measurements of fine particles (PM2.5), coarse particles (PM10) and aerosol optical properties were carried out at a background station-Dinghushan in the Pearl River Delta (PRD) region from 2009 to 2012. It showed that the long-term mean concentrations of PM2.5 and PM10 were as high as (51±31) μg/m3 and (76±43) μg/m3, respectively. Particulate pollution in the PRD region was mitigated over the last four years, and the annual mean concentrations of PM2.5 was decreased to (39±25) μg/m3 in 2012 from (65±33) μg/m3 in 2009. The concentrations of PM2.5 and PM10 were low in summer and high in the other three seasons. The correlation between the daily concentrations of PM2.5 and PM10 was generally high (R>0.90). The long-term mean PM2.5/PM10 ratio reached up to 0.67, the ratio was high in autumn (0.71) and low in summer (0.57). Atmospheric visibility was poor, the long-term mean of aerosol optical depth (AOD) at 500nm was 0.91±0.40, and Ångström exponent was 0.97±0.36. The values of AOD were low in winter and summer, and high in spring and autumn. The correlation between particulate matter (PM) concentrations and AOD was high. The correlation coefficient in dry season (October–next March) was better than that was in wet season (April–September). In addition, the correlation also demonstrated great differences for different air masses.

The empirical relationship between the PM2.5 concentration and aerosol optical depth over the background of North China from 2009 to 2011

Satellite observation has shown great promise in estimating the concentration of particulate matter at the surface. It is necessary to investigate the relationships between PM2.5 concentration and aerosol optical depth (AOD) to promote the accuracy of satellite remote sensing, especially in the high aerosol emitting region in North China. The annual concentration of PM2.5 was 33±10μg/m3 in the background of North China from 2009 to 2011, while the annual mean of AOD at 550nm was 0.23±0.10; there was a high correlation between the PM2.5 concentration and AOD in the region. The linear regression functions of the daily PM2.5 concentration (y) with the ground-observed AOD (x) and the MODIS AOD (x) were y=96.98x+6.61 (R2=0.58) and y=100.10x+12.13 (R2=0.57), respectively. The linear regression functions of the monthly PM2.5 concentration (y) with the ground-observed AOD (x) and the MODIS AOD (x) were y=91.66x+12.60 (R2=0.75) and y=79.33x+16.33 (R2=0.75), respectively. In addition, the results also demonstrated significant differences in the slopes and intercepts of the linear regression functions for different seasons. A large error resulted when any single function was used to retrieve the PM2.5 concentration using AOD.

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Objetivos: Determinar el espesor optico de los aerosoles (EOA) durante los meses de enero 2007 y 2008 y febrero de 2013 en la Estacion Cientifica Antartica Machu Picchu (ECAMP). Metodos: La investigacion fue descriptiva comparativa. Se utilizo el fotometro solar SP02-L para mediciones directas del sol con 4 sensores centrados en las longitudes de onda 412, 500, 675 y 862 nm. Se utilizo registros con un angulo cenital solar inferior a 80° y con cero de cobertura nubosa 30° alrededor del Sol. Estas mediciones fueron comparadas, a traves de la prueba de Pearson, con EOA a 550 nm de los sensores satelitales MODIS (Moderate Resolution Imaging Spectroradiometer). Resultados: Se determino una maxima y minima media de EOA de 0,1061 y 0,0616, respectivamente. Reporto un coeficiente de correlacion con el sensor MODIS, tanto del satelite Aqua y Terra, siendo 0,0284 y 0,0059 (p<0,05), respectivamente. La misma correlacion fue evaluada con el Indice de Aerosol del sensor OMI (Ozone Monitoring Instrument) resultando una mayor correlacion, 0,3606 (p<0,05). Comparando el EOA resultante en la ECAMP con las demas estaciones antarticas se encontraron valores similares alrededor de 0,06, en las zonas costeras como Neumayer y Aboa. Conclusiones: Los datos obtenidos en la ECAMP en los anos 2007, 2008 y 2013 no evidencian una variacion significativa respecto al espesor optico de aerosoles. Los altos valores obtenidos en la ECAMP comparados con las estaciones de Aboa y Neumayer pueden tener su explicacion en las mediciones manuales realizadas en comparacion con las automaticas de las otras estaciones.

Validation of MODIS aerosol optical depth product over China using CARSNET measurements

Abstract This study evaluates Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) retrievals with ground measurements collected by the China Aerosol Remote Sensing NETwork (CARSNET). In current stage, the MODIS Collection 5 (C5) AODs are retrieved by two distinct algorithms: the Dark Target (DT) and the Deep Blue (DB). The CARSNET AODs are derived with measurements of Cimel Electronique CE-318, the same instrument deployed by the AEROsol Robotic Network (AEROENT). The collocation is performed by matching each MODIS AOD pixel (10 × 10 km 2 ) to CARSNET AOD mean within 7.5 min of satellite overpass. Four-year comparisons (2005–2008) of MODIS/CARSNET at ten sites show the performance of MODIS AOD retrieval is highly dependent on the underlying land surface. The MODIS DT AODs are on average lower than the CARSNET AODs by 6–30% over forest and grassland areas, but can be higher by up to 54% over urban area and 95% over desert-like area. More than 50% of the MODIS DT AODs fall within the expected error envelope over forest and grassland areas. The MODIS DT tends to overestimate for small AOD at urban area. At high vegetated area it underestimates for small AOD and overestimates for large AOD. Generally, its quality reduces with the decreasing AOD value. The MODIS DB is capable of retrieving AOD over desert but with a significant underestimation at CARSNET sites. The best retrieval of the MODIS DB is over grassland area with about 70% retrievals within the expected error. The uncertainties of MODIS AOD retrieval from spatial–temporal collocation and instrument calibration are discussed briefly.

Improving the CALIOP aerosol optical depth using combined MODIS-CALIOP observations and CALIOP integrated attenuated total color ratio

[1] This paper aims to evaluate CALIOP aerosol optical depth (AOD) retrieval using MODIS AOD with the goal of improving the CALIOP selection of the lidar ratio leveraging the vertical resolved CALIOP and multispectral MODIS observations. Comparing the MODIS fine mode ratio to CALIOP, we find that the CALIOP integrated attenuated total color ratio provides sensitivity to the aerosol size and type. This finding can be used to better constrain the lidar ratio and improve the CALIOP AOD independent from MODIS.To retrieve the aerosol optical depth from CALIOP requires knowledge of the aerosol lidar ratio that varies significantly as a function of aerosol type. For most CALIOP retrievals the lidar ratio is estimated by correlating CALIOP observables (depolarization and backscatter) with precomputed lidar ratio climatologies. Applying a lidar ratio not representative of the observed aerosols can result in significant AOD biases and is one of the primary sources of uncertainty in the current CALIOP AOD. We demonstrate that over ocean the MODIS sensitivity to the fine- and coarse-mode aerosol mixing ratios provides additional constraints to the aerosol lidar ratio. When MODIS fine-mode retrievals are collocated with CALIOP, the improved lidar ratio significantly reduces the CALIOP AOD mean biases from ∣0.064∣ to ∣0.020∣ when compared to MODIS. In addition, we demonstrate that the CALIOP integrated attenuated total color ratio is correlated with the MODIS fine and coarse mixing ratios in marine environments. This finding suggests that for a CALIOP-only AOD retrieval the integrated attenuated total color ratio can be used to better constrain the lidar ratio. Using the CALIOP integrated attenuated total color ratio, the CALIOP-only AOD retrieval improves the AOD mean biases (∣0.064∣ to ∣0.007∣) when compared to the MODIS AOD.

Aerosol optical properties of regional background atmosphere in Northeast China

Aerosol optical properties from 2005 to 2008 at the Longfengshan regional background station in Northeast China were measured and analyzed. The annual mean of aerosol optical depth (AOD) at 440 nm for the four years was about 0.27 ± 0.25, 0.39 ± 0.37, 0.35 ± 0.34, and 0.38 ± 0.38, respectively, and the corresponding annual mean for the Angstrom exponent between 440 nm and 870 nm was about 1.43 ± 0.48, 1.23 ± 0.37, 1.53 ± 0.47, and 1.55 ± 0.42. The average monthly AOD 440nm showed similar seasonal variation with a maximum in spring and a minimum in autumn. The monthly means of AOD at 440, 675, 870 and 1020 nm increase from the January to March with the maxima about 0.77 ± 0.04, 0.65 ± 0.04, 0.58 ± 0.06, 0.57 ± 0.07, respectively and decrease from September to February with the minima about 0.32 ± 0.12, 0.22 ± 0.09, 0.15 ± 0.08, and 0.13 ± 0.07 in January. The monthly mean of Angstrom exponent shows a minimum in March (0.97 ± 0.52) and a maximum in September (1.66 ± 0.29). Both the AOD and Angstrom exponent presents single peak distributions of occurrence frequencies. The Longfenshan data showed high AODs (>1.00) both clustering in the fine mode growth wing and the coarse mode. Two typical cases under dust and haze conditions showed that the AOD under dusty day decreased from 2.20 to 1.20 and the Angstrom exponent increased from 0.10 to 1.00. On the contrast, the AOD under haze day remained relatively stable about 0.90 and the Angstrom exponent was around 1.40. The 3-day backtrajectory analysis at Longfengshan illustrated that the air-masses near ground on the dust day were from Bohai Sea and passed through Liaodong Peninsula and Northeast plain in China. But the air-masses on 500 m AGL were originated from western Mongolia and crossed Gobi deserts, Otindag Sand Land and Horqin Sand Land in Northeast China. The air-masses at Longfengshan near ground 500 m and 1000 m AGL on the haze days were from North China Region and passed through Northeast Heavy Industrial Base in Northeast China.