Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments

Aerosol Optical Depth (AOD) data derived from satellites is crucial for estimating spatially-resolved PM concentrations, but existing AOD data over land remain affected by several limitations (e.g., data gaps, coarser resolution, higher uncertainty or lack of size fraction data), which weakens the AOD-PM relationship. We developed a 0.1° resolution daily AOD data set over Europe over the period 2003-2020, based on two-stage Quantile Machine Learning (QML) frameworks. Our approach first fills gaps in satellite AOD data and then constructs three components' models to obtain reliable full-coverage AOD along with Fine-mode AOD (fAOD) and Coarse-mode AOD (cAOD). These models are based on AERONET (AErosol RObotic NETwork) observations, Gap-filled satellite AOD, climate and atmospheric composition reanalyses. Our QML AOD products exhibit better quality with an out-of-sample R2 equal to 0.68 for AOD, 0.66 for fAOD and 0.65 for cAOD, which is 23-92 %, 11-13 % and 115-132 % higher than the corresponding satellite or reanalysis products, respectively. Over 91.6 %, 81.6 %, and 88.9 % of QML AOD, fAOD and cAOD predictions fall within ±20 % Expected Error (EE) envelopes, respectively. Previous studies reported that a weak satellite AOD-PM correlation across Europe (Pearson correlation coefficient (PCC) around 0.1). Our QML products exhibit higher correlations with ground-level PMs, particularly when broadly matched by size: AOD with PM10, fAOD with PM2.5, cAOD with PM coarse (R = 0.41, 0.45 and 0.26, respectively). Different AOD fractions more effectively distinct PM size fractions, than total AOD. Our QML aerosol dataset and models pioneer full-coverage, daily high-resolution monitoring of fine-mode and coarse-mode aerosols, effectively addressing existing AOD challenges for further PMs exposures' estimations. This dataset opens avenues for more in-depth exploration of the impacts of aerosols on human health, climate, visibility, and biogeochemical processes, offering valuable insights for air quality management and environmental health risk assessment.

Evaluation of MERRA-2 and CAMS reanalysis for black carbon aerosol in China

Black carbon (BC) constitutes a pivotal component of atmospheric aerosols, significantly impacting regional and global radiation balance, climate, and human health. In this study, we evaluated BC data in two prominent atmospheric composition reanalysis datasets: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and the Copernicus Atmosphere Monitoring Service (CAMS), and analyzed the causes of their deviations. This assessment is based on observational data collected from 34 monitoring stations across China from 2006 to 2022. Our research reveals a significant and consistent decline in BC concentrations within China, amounting to a reduction exceeding 67.33%. However, both MERRA-2 and CAMS reanalysis data fail to capture this declining trend. The average annual decrease of BC in MERRA-2 from 2006 to 2022 is only 0.06 μg/m3 per year, while the BC concentration in CAMS even increased with an average annual value of 0.014 μg/m3 per year. In 2022, MERRA-2 had overestimated BC concentration by 20% compared to observational data, while CAMS had overestimated it by approximately 66%. In the regional BC concentration analysis, the data quality of the reanalysis data is better in the South China (RM = 0.59, RC = 0.53), followed by the North China (RM = 0.50, RC = 0.42). Reanalysis BC data in Northwest China and the Tibetan Plateau are difficult to use for practical analysis due to their big difference with observation. In a comparison of the anthropogenic BC emissions inventory used in the two atmospheric composition reanalysis datasets with the Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) emissions inventory, we found that: Despite the significant decline in China's BC emissions, MERRA-2 still relies on the 2006 emissions inventory, while CAMS utilizes emission inventories that even show an increasing trend. These factors will undoubtedly lead to greater deviations between reanalysis and observational data.

Critical Review on Radiative Forcing and Climate Models for Global Climate Change since 1970

This review identifies a critical problem in the fundamental physics of current climate models. The large greenhouse effect of rising CO2 assumed in climate models is assessed by six key observations from ground- and satellite-based measurements. This assessment is enhanced by statistical analyses and model calculations of global or regional mean surface temperature changes by conventional climate models and by a conceptual quantum physical model of global warming due to halogen-containing greenhouse gases (halo-GHGs). The postulated large radiative forcing of CO2 in conventional climate models does not agree with satellite observations. Satellite-observed warming pattern resembles closely the atmospheric distribution of chlorofluorocarbons (CFCs). This review helps understand recent remarkable observations of reversals from cooling to warming in the lower stratosphere over most continents and in the upper stratosphere at high latitudes, surface warming cessations in the Antarctic, North America, UK, and Northern-Hemisphere (NH) extratropics, and the stabilization in NH or North America snow cover, since the turn of the century. The complementary observation of surface temperature changes in 3 representative regions (Central England, the Antarctic, and the Arctic) sheds new light on the primary mechanism of global warming. These observations agree well with not CO2-based climate models but the CFC-warming quantum physical model. The latter offers parameter-free analytical calculations of surface temperature changes, exhibiting remarkable agreement with observations. These observations overwhelmingly support an emerging picture that halo-GHGs made the dominant contribution to global warming in the late 20th century and that a gradual reversal in warming has occurred since ~2005 due to the phasing out of halo-GHGs. Advances and insights from this review may help humans make rational policies to reverse the past warming and maintain a healthy economy and ecosystem.

Long-term spatiotemporal trends in aerosol optical depth and its relationship with enhanced vegetation index and meteorological parameters over South Asia

Satellite-based aerosol optical depth (AOD) is columnar light extinction by aerosol absorption and scattering and has become the most important variable for the assessment of the spatiotemporal distribution of aerosols at a regional and global level. In this paper, we have used AOD observations of multiangle imaging spectroradiometer (MISR) from September 2002 to May 2017, moderate resolution imaging spectroradiometer (MODIS) from September 2002 to December 2020, and sea-viewing wide field-of-view sensor (SeaWiFS) from September 2002 to December 2010 over South Asia. We have observed the association of AOD with enhanced vegetation index (EVI) and meteorological variables (temperature (TEMP), wind speed (WS), and relative humidity (RH)) acquired from Giovanni during the period September 2002-December 2020. The satellite observations of Terra-, MISR-, and SeaWiFS-AOD were also compared with Aqua-AOD. The findings show that AOD in eastern Pakistan is higher than in the western Pakistan due to increase in population density and biomass burning. Mean annual peak AOD (˃ 0.7) has been observed over the IGB region because of the significant increase in economical, industrial, and agricultural activities while AOD of ˃ 0.6 is observed over Bangladesh. The lowest mean annual AOD of ˂ 0.3 is observed over northeastern Afghanistan, western Nepal, and Bhutan whereas the AOD of 0.3 is seen over Sri Lanka. The highest seasonal mean AOD of 0.8 has been seen over Bihar, India, and AOD of ~ 0.7 is observed over Bangladesh while the lowest AOD is observed over Afghanistan, Sri Lanka, Nepal, and Bhutan during the winter season. However, the mean AOD over eastern Pakistan is maximum in both monsoon and post-monsoon season but relatively low in pre-monsoon and winter. The highest positive seasonal AOD anomalies were observed over South Asia in winter season followed by post-monsoon, pre-monsoon, and least being monsoon. The higher mean AOD anomaly value is found to be 0.2 over eastern Pakistan and western India. In northeastern Pakistan and central India, AOD and RH are positively correlated (r ˃ 0.54) while negatively correlated over Afghanistan, southwestern region of Pakistan, eastern India, Nepal, Bhutan, and Bangladesh. AOD is negatively correlated (r =  ~  - 0.3) with EVI over eastern Pakistan and western India. The highest correlation coefficient (r) obtained among Terra and Aqua is 0.97, MISR and Aqua is 0.93, and SeaWiFS and Aqua is 0.58 over South Asia.

Impact Assessment of Aerosol Optical Depth on Rainfall in Indian Rural Areas

Aerosol significantly influences the life cycle of clouds and their formation. Many studies reported worldwide on anthropogenic aerosols and their impact on clouds and their optical properties. Atmospheric remote sensing provides the best way to estimate indirectly air quality surveillance and management in megacities of developing countries like India where many cities have elevated concentration profiles of air pollutants with inadequate coverage of spatial and temporal monitoring. The results of the study highlighted the impact on rainfall patterns due to aerosol optical depth (AOD) and fine particulate matter (PM2.5) for a total of 7 years (2015–2021) over five different Indian rural sites by using MODerate Resolution Imaging Spectroradiometer (MODIS). The AOD (550 nm) and PM2.5 were retrieved from the MODIS sensor Terra satellites and the MEERA 2 model, respectively. Also, we have analyzed in this study the relationship of AOD (550 nm) with PM2.5 and meteorological variables (temperature relative humidity and precipitation) over Indian rural sites during 2015–2021. The maximum concentration of AOD (550 nm) has been measured for Gandhi college (2.94 ± 0.44) and minimum for ARM college (0.01 ± 0.28), while the maximum concentration of PM2.5 has been measured for ARM College 296.37 (µg m⁻³) and minimum for Karunya University 0.02 (µg m⁻³). Also, the relation between AOD (550 nm) with total precipitation is measured positively for all locations except Gandhi college whereby PM2.5 associated with total precipitation is measured negatively for all locations except ARM college. Finally, the relationship between PM2.5 and AOD (550 nm) is measured positively in all selected locations except Singhad Institute. The maximum rainfall has been observed for monsoon months (June–August) and post-monsoon months (October) for all locations during the study period. The maximum total precipitation has been measured for Singhad 11,674.7 (mm) and the minimum for Karunya University 4563.41 (mm). However, the results of the study indicated that there was no direct trend observed in AOD in five different selected rural Indian sites.

Comparison of Aerosol Optical Depth from MODIS Product Collection 6.1 and AERONET in the Western United States

Recent observations reveal that dust storms are increasing in the western USA, posing imminent risks to public health, safety, and the economy. Much of the observational evidence has been obtained from ground-based platforms and the visual interpretation of satellite imagery from limited regions. Comprehensive satellite-based observations of long-term aerosol records are still lacking. In an effort to develop such a satellite aerosol dataset, we compared and evaluated the Aerosol Optical Depth (AOD) from Deep Blue (DB) and Dark Target (DT) product collection 6.1 with the Aerosol Robotic Network (AERONET) program in the western USA. We examined the seasonal and monthly average number of Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua DB AOD retrievals per 0.1∘×0.1∘ from January 2003 to December 2017 across the region’s different topographic, climatic, and land cover conditions. The number of retrievals in the southwest United States was on average greater than 37 days per 90 days for all seasons except summer. Springtime saw the highest number of AOD retrievals across the southwest, consistent with the peak season for synoptic-scale dust events. The majority of Arizona, New Mexico, and western Texas showed the lowest number of retrievals during the monsoon season. The majority of collocating domains of AOD from the Aqua sensor showed a better correlation with AERONET AOD than AOD from Terra, and the correlation coefficients exhibited large regional variability across the study area. The correlation coefficient between the couplings Aqua DB AOD-AERONET AOD and Terra DB AOD-AERONET AOD ranges from 0.1 to 0.94 and 0.001 to 0.94, respectively. In the majority of the sites that exhibited less than a 0.6 correlation coefficient and few matched data points at the nearest single pixel, the correlations gradually improved when the spatial domain increased to a 50 km × 50 km box averaging domain. In general, the majority of the stations revealed significant correlation between MODIS and AERONET AOD at all spatiotemporal aggregating domains, although MODIS generally overestimated AOD compared to AERONET. However, the correlation coefficient in the southwest United States was the lowest and in stations from a higher latitude was the highest. The difference in the brightness of the land surface and the latitudinal differences in the aerosol inputs from the forest fires and solar zenith angles are some of the factors that manifested the latitudinal correlation differences.

Sensitivity of PM2.5 to NOx emissions and meteorology in North China based on observations

This study examines the sensitivity of daily PM_2.5 to NO_x emissions and meteorology using in situ observations from main cities of North China (NC). NC cities are divided into low-, medium-, and high-emission groups by the ranking of their 4-year mean NO₂. For each emission group, daily NO₂ levels are used to divide the days into good-, medium-, and bad-meteorological conditions. Regardless of their emission levels, all cities reveal significant decreases (96%-172%) in daily PM_2.5 levels from bad to good meteorological conditions. The largest difference in PM_2.5 concentrations between the emissions groups is found under bad meteorological conditions, with 56% higher PM_2.5 in high-emission cities than low-emission cities, indicating PM_2.5 under bad meteorological conditions has the largest sensitivity to emissions. The high-emission, bad-meteorology group saw a 24% decrease in mean daily PM_2.5 levels from 2017, a high-emission year, to 2019, a low-emission year. However, under good meteorological conditions, the high-emissions group shows an increase of 8.8 μg/m³ in mean daily PM_2.5 from 2017 to 2019 with a 2.6% increase in the possibility of high PM_2.5. These results suggest the current emission reduction measures are more effective in controlling PM_2.5 in high-emission cities under bad meteorological conditions than under other meteorological conditions.

Understanding global changes in fine-mode aerosols during 2008-2017 using statistical methods and deep learning approach

Despite their extremely small size, fine-mode aerosols have significant impacts on the environment, climate, and human health. However, current understandings of global changes in fine-mode aerosols are limited. In this study, we employed newly developed satellite retrieval data and an attentive interpretable deep learning model to explore the status, changes, and association factors of the global fine-mode aerosol optical depth (fAOD) and aerosol fine-mode fraction (FMF) from 2008 to 2017. At the global scale, the results show a significant increasing trend in land FMF (2.34 × 10^-3/year); however, the FMF over the ocean and the fAOD over land and ocean did not reveal significant trends. Between 2008 and 2017, high levels of both fAOD (>0.30) and FMF (>0.75) were identified over China, southeastern Asia, India, and Africa. Seasonally, global land FMF showed high values in summer (>0.70) and low values in spring (<0.65), while land fAOD was high in summer (>0.15) but low in winter (<0.13). Importantly, Australia and Mexico experienced significant increasing trends in FMF during all four seasons. At the regional scale, a significant decline in fAOD was identified in China, which indicates that government emission controls and reductions have been effective in recent decades. The deep learning model was used to interpret the result and showed that O₃ was significantly associated with changes in both the FMF and fAOD. This finding suggests the importance of synergizing the regulations for both O₃ and fine particles. Our work comprehensively examined global spatial and seasonal fAOD and FMF changes and provides a holistic understanding of global anthropogenic impacts.

Spatio-Temporal Characteristics of PM2.5, PM10, and AOD over the Central Line Project of China’s South-North Water Diversion in Henan Province (China)

The spatio-temporal characteristics of particulate matter with a particle size less than or equal to 2.5 μm (PM2.5), particulate matter with a particle size less than or equal to 10 μm (PM10), meteorological parameters from September 2018 to September 2019, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) aerosol optical depth (AOD) from 2007 to 2019 were investigated over the Central Line Project of China’s South-North Water Diversion (CSNWD) in Henan Province. To better understand the characteristics of the atmospheric environment over the CSNWD, air quality monitoring stations were installed in Nanyang (in the upper reaches), Zhengzhou (in the middle reaches), and Anyang (in the lower reaches). In this study, daily, monthly, and seasonal statistical analyses of PM2.5 and PM10 concentrations were performed and their relationship with meteorological parameters was investigated. The results show extremely poor air quality conditions over the Zhengzhou Station compared with the Nanyang and Anyang Stations. The annual average PM2.5 concentration did not meet China’s ambient air secondary standard (35 μg/m3 annual mean) over all the stations, while the annual average PM10 concentration satisfied China’s ambient air secondary standard (100 μg/m3 annual mean) over the Anyang and Nanyang Stations, except for the Zhengzhou Station. The highest PM2.5 and PM10 concentrations were observed during winter compared with the other seasons. The results show that PM2.5 and PM10 concentrations were negatively correlated with wind speed and temperature at the Nanyang and Zhengzhou Stations, but positively correlated with relative humidity. However, no significant negative or positive correlation was observed at Anyang Station. There is a strong linear positive correlation between PM2.5 and PM10 (R = 0.99), which indicates that the particulate matter at the three stations was mainly caused by local emissions. Additionally, the AOD values at the three stations were the highest in summer, which may be related to the residues of crops burned in Henan Province in summer.

Theoretical Uncertainty Analysis of Satellite Retrieved Aerosol Optical Depth Associated with Surface Albedo and Aerosol Optical Properties

Deriving aerosol optical depth (AOD) from space-borne observations is still challenging due to uncertainties associated with sensor calibration drift, cloud screening, aerosol type classification, and surface reflectance characterization. As an initial step to understanding the physical processes impacting these uncertainties in satellite AOD retrievals, this study outlines a theoretical approach to estimate biases in the satellite aerosol retrieval algorithm affected by surface albedo and prescribed aerosol optical properties using a simplified radiative transfer model with a traditional error propagation approach. We expand the critical surface reflectance concept to obtain the critical surface albedo (CSA), critical single scattering albedo (CSSA), and critical asymmetry parameter (CAP). The top-of-atmosphere (TOA) reflectance is not sensitive to significant variability in aerosol loading (AOD) at the critical value; thus, the AOD cannot be determined. Results show that 5% bias in surface albedo (A), single scattering albedo (SSA), or asymmetry parameter (g) lead to large retrieved AOD errors, especially high under conditions when A, SSA, or g are close to their critical values. The results can be useful for future research related to improvements of satellite aerosol retrieval algorithms and provide a preliminary framework to analytically quantify AOD uncertainties from satellite retrievals.

Atmospheric particulate matter and potentially hazardous compounds around residential/road side soil in an urban area

Exposure to ambient coarse and fine particulate matter (PM₁₀ and PM_2.5) causes premature death worldwide due to the nature of their particle size. It contains potentially hazardous elements (PHEs) and polycyclic aromatic hydrocarbons (PAHs). This study aims to quantify the particulate matter (PM) loads on the surface of soil in twenty-five different locations including residential and roadside areas of an urban area in Northeast India. This study shows that the 24h mean concentration of PM (121 ± 49 μg/m³ for PM_2.5 and 153 ± 45 μg/m³ for PM₁₀) exceeded more than three times the WHO's air quality standard limit for both PM_2.5 (25 μg/m³) and PM₁₀ (50 μg/m³) indicating poor air quality in the urban area during monsoon season. The health risk assessment of PAHs and PHEs including mutagenic or carcinogenic potency was observed to be higher as compared to other studies carried out on road traffic emissions in a similar type of urban area. This study also provides a brief database on the deposition of PM on the soil surfaces due to wet-deposition that would help to increase public awareness in such type of urban area for the control of PM pollution and further remediation.

The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future

The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.

Aerosols and Clouds Interactions in an Urban Atmosphere

Aerosols create great uncertainties in studying climate change under global warming and atmospheric dynamics. To understand the impacts of aerosols on cloud properties in Madurai, we have analyzed an extensive collection of aerosol and cloud properties, obtained from the Moderate resolution Imaging Spectroradiometer (MODIS) data, over the study site during 2012-2013. Monthly, seasonal and annual variations of aerosols and clouds studied along their interactions and impacts on climate. Considering annual averages for all these parameters, most often the year 2012 was dominated with a higher presence of AOD, COD, CER, CTT, CTP whereas rainfall and CF were found to be dominated in 2013. The presence of higher CF in 2013 may be a cause for the higher rainfall and the lower level of CF in 2012 may be a cause for less rainfall. High aerosol loading in this area is due to biomass burning and urban air pollution which may significantly suppress precipitation. Increased aerosols and the local aerosol emissions may reduce the precipitation efficiency, which is responsible for the precipitation reduction and vice-versa.

Deriving Aerosol Absorption Properties from Solar Ultraviolet Radiation Spectral Measurements at Thessaloniki, Greece

The gap in knowledge regarding the radiative effects of aerosols in the UV region of the solar spectrum is large, mainly due to the lack of systematic measurements of the aerosol single scattering albedo (SSA) and absorption optical depth (AAOD). In the present study, spectral UV measurements performed in Thessaloniki, Greece by a double monochromator Brewer spectrophotometer in the period 1998–2017 are used for the calculation of the aforementioned optical properties. The main uncertainty factors have been described and there is an effort to quantify the overall uncertainties in SSA and AAOD. Analysis of the results suggests that the absorption by aerosols is much stronger in the UV relative to the visible. SSA follows a clear annual pattern ranging from ~0.7 in winter to ~0.85 in summer at wavelengths 320–360 nm, while AAOD peaks in summer and winter. The average AAOD for 2009–2011 is ~50% above the 2003–2006 average, possibly due to increased emissions of absorbing aerosols related to the economic crisis and the metro-railway construction works in the city center.

Characteristics of Fine Particulate Matter (PM2.5) over Urban, Suburban, and Rural Areas of Hong Kong

In urban areas, fine particulate matter (PM2.5) associated with local vehicle emissions can cause respiratory and cardiorespiratory disease and increased mortality rates, but less so in rural areas. However, Hong Kong may be a special case, since the whole territory often suffers from regional haze from nearby mainland China, as well as local sources. Therefore, to understand which areas of Hong Kong may be affected by damaging levels of fine particulates, PM2.5 data were obtained from March 2005 to February 2009 for urban, suburban, and rural air quality monitoring stations; namely Central (city area, commercial area, and urban populated area), Tsuen Wan (city area, commercial area, urban populated, and residential area), Tung Chung (suburban and residential area), Yuen Long (urban and residential area), and Tap Mun (remote rural area). To evaluate the relative contributions of regional and local pollution sources, the study aimed to test the influence of weather conditions on PM2.5 concentrations. Thus, meteorological parameters including temperature, relative humidity, wind speed, and wind directions were obtained from the Hong Kong Observatory. The results showed that Hong Kong’s air quality is mainly affected by regional aerosol emissions, either transported from the land or ocean, as similar patterns of variations in PM2.5 concentrations were observed over urban, suburban, and rural areas of Hong Kong. Only slightly higher PM2.5 concentrations were observed over urban sites, such as Central, compared to suburban and rural sites, which could be attributed to local automobile emissions. Results showed that meteorological parameters have the potential to explain 80% of the variability in daily mean PM2.5 concentrations—at Yuen Long, 77% at Tung Chung, 72% at Central, 71% at Tsuen Wan, and 67% at Tap Mun, during the spring to summer part of the year. The results provide not only a better understanding of the impact of regional long-distance transport of air pollutants on Hong Kong’s air quality but also a reference for future regional-scale collaboration on air quality management.

Emission of Air Pollutants from Rice Residue Open Burning in Thailand, 2018

Crop residue burning negatively impacts both the environment and human health, whether in the aspect of air pollution, regional and global climate change, or transboundary air pollution. Accordingly, this study aims to assess the level of air pollutant emissions caused by the rice residue open burning activities in 2018, by analyzing the remote sensing information and country specific data. This research also aims to analyze the trend of particulate matter 10 microns or less in diameter (PM10) concentration air quality sites in provinces with large paddy rice planting areas from 2010–2017. According to the results, 61.87 megaton (Mt) of rice residue were generated, comprising 21.35 Mt generated from the irrigated fields and 40.53 Mt generated from the rain-fed field. Only 23.0% of the total rice residue generated were subject to open burning—of which nearly 32% were actually burned in the fields. The emissions from such rice residue burning consisted of: 5.34 ± 2.33 megaton (Mt) of CO2, 44 ± 14 kiloton (kt) of CH4, 422 ± 179 kt of CO, 2 ± 2 kt of NOX, 2 ± 2 kt of SO2, 38 ± 22 kt of PM2.5, 43 ± 29 kt of PM10, 2 ± 1 kt of black carbon (BC), and 14 ± 5 kt of organic carbon (OC). According to the air quality trends, the results shows the higher level of PM10 concentration was due to the agricultural burning activities, as reflected in the higher monthly averages of the months with the agricultural burning, by around 1.9–2.1 times. The result also shows the effect of government’s policy for farmers on the crop burning activities and air quality trends.

Exploring systematic offsets between aerosol products from the two MODIS sensors

Long-term measurements of global aerosol loading and optical properties are essential for assessing climate-related questions. Using observations of spectral reflectance and radiance, the dark-target (DT) aerosol retrieval algorithm is applied to Moderate-resolution Imaging Spectroradiometer sensors on both Terra (MODIS-T) and Aqua (MODIS-A) satellites, deriving products (known as MOD04 and MYD04, respectively) of global aerosol optical depth (AOD at 0.55 μm) over both land and ocean, and Angstrom Exponent (AE derived from 0.55 and 0.86 μm) over ocean. Here, we analyse the overlapping time series (since mid-2002) of the Collection 6 (C6) aerosol products. Global monthly mean AOD from MOD04 (Terra with morning overpass) is consistently higher than MYD04 (Aqua with afternoon overpass) by ~13% (~0.02 over land and ~0.015 over ocean), and this offset (MOD04 - MYD04), has seasonal as well as long-term variability. Focusing on 2008, and deriving yearly gridded mean AOD and AE, we find that over ocean, the MOD04 (morning) AOD is higher and the AE is lower. Over land, there is more variability, but only biomass-burning regions tend to have AOD lower for MOD04. Using simulated aerosol fields from the Goddard Earth Observing System (GEOS-5) Earth system model, and sampling separately (in time and space) along each MODIS-observed swath during 2008, the magnitudes of morning versus afternoon offsets of AOD and AE are smaller than those in the C6 products. Since the differences are not easily attributed to either aerosol diurnal cycles or sampling issues, we test additional corrections to the input reflectance data. The first, known as C6+, corrects for long-term changes to each sensors' polarization sensitivity, response-versus-scan angle, and to cross-calibration from MODIS-T to MODIS-A. A second convolves the de-trending and cross-calibration into scaling factors. Each method was applied upstream of the aerosol retrieval, using 2008 data. While both methods reduced the overall AOD offset over land from 0.02 to 0.01, neither significantly reduced the AOD offset over ocean. The overall negative AE offset was reduced. A Collection (C6.1) of all MODIS-atmosphere products was released, but we expect that the C6.1 aerosol products will maintain similar overall AOD and AE offsets. We conclude that: a) users should not interpret global differences between Terra and Aqua aerosol products as representing a true diurnal signal in the aerosol. b) Because the MODIS-A product appears to have overall smaller bias compared to ground-truth, it may be more suitable for some applications, however c) since the AOD offset is only ~0.02 and within noise level for single retrievals, both MODIS products may be adequate for most applications.

Limononic Acid Oxidation by Hydroxyl Radicals and Ozone in the Aqueous Phase

Kinetics and mechanism of limononic acid (3-isopropenyl-6-oxoheptanoic acid, LA) oxidation by hydroxyl radicals (OH) and ozone (O₃) were studied in the aqueous phase at 298 ± 2 K. These reactions were investigated using liquid chromatography coupled to the electrospray ionization and quadrupole tandem mass spectrometry (LC-ESI/MS/MS). The rate coefficients determined for LA + OH reaction were: 1.3 ± 0.3 × 10¹⁰ M^-1 s^-1 at pH = 2 and 5.7 ± 0.6 × 10⁹ M^-1 s^-1 at pH = 10. The rate coefficient determined for LA ozonolysis was 4.2 ± 0.2 × 10⁴ M^-1 s^-1 at pH = 2. The calculated Henry's law constant (H) for LA was ca. 6.3 × 10⁶ M × atm^-1, thereby indicating that in fogs and clouds with LWC = 0.3-0.5 g × m^-3 LA will reside entirely in the aqueous phase. Calculated atmospheric lifetimes due to reaction with OH and O₃ strongly indicate that aqueous-phase oxidation can be important for LA under realistic atmospheric conditions. Under acidic conditions, the aqueous-phase oxidation of LA by OH will dominate over reaction with O₃, whereas the opposite is more likely when pH ≥ 4.5. The aqueous-phase oxidation of LA produced keto-limononic acid and a number of low-volatility products, such as hydroperoxy-LA and α-hydroxyhydroperoxides.

Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top-down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error.

Occupational exposure to indoor air pollution among bakery workers in Ethiopia; A comparison of electric and biomass cookstoves

The indoor air pollution (IAP) produced by the domestic combustion of solid fuels is responsible for up to 4 million deaths annually, especially among low and middle income countries. Occupational exposure within the food preparation industries of these nations remains underexplored. We investigated occupational exposure to the IAP produced during the commercial production of injera, a staple of the Ethiopian diet, from bakeries in Addis Ababa, Ethiopia. Measurements of PM_2.5, black carbon (via the proxy measure PM_2.5 absorbance) and CO were collected from 30 bakeries and their employees for an average of 4-h per working day. Measurements were compared between bakeries using biomass and electric cookstoves. Further, the respiratory health data of 35 bakery employees were collected by interview-based questionnaire. Personal exposure to PM2.5 from biomass cookstoves was double that of electric cookstoves (430 μg/m3 vs. 216 μg/m3), black carbon exposure was four times higher among biomass users (67 × 10-5m-1 vs. 15 × 10-5m-1), and CO exposure was twenty times higher among biomass users (22 ppm vs. 1 ppm). Mixed effect models indicated that the number of stoves in use and additional solid fuel usage (e.g. coffee brewing) also contributed to exposure levels. These findings indicate that the use of biomass powered cookstoves during commercial injera production significantly contributes to IAP and self-reported respiratory symptoms. As injera is the staple foodstuff of Ethiopia, a widespread conversion to electric cookstoves is likely to have a significant impact. However, as high levels of IAP were also observed within the electric bakeries, further identification of pollution sources is required.

Importance of aerosol non-sphericity in estimating aerosol radiative forcing in Indo-Gangetic Basin

Aerosols are usually presumed spherical in shape while estimating the direct radiative forcing (DRF) using observations or in the models. In the Indo-Gangetic Basin (IGB), a regional aerosol hotspot where dust is a major aerosol species and has been observed to be non-spherical in shape, it is important to test the validity of this assumption. We address this issue using measured chemical composition at megacity Delhi, a representative site of the western IGB. Based on the observation, we choose three non-spherical shapes - spheroid, cylinder and chebyshev, and compute their optical properties. Non-spherical dust enhances aerosol extinction coefficient (β_ext) and single scattering albedo (SSA) at visible wavelengths by >0.05km^-1 and >0.04 respectively, while it decreases asymmetry parameter (g) by ~0.1. Accounting non-sphericity leads top-of-the-atmosphere (TOA) dust DRF to more cooling due to enhanced backscattering and increases surface dimming due to enhanced β_ext. Outgoing shortwave flux at TOA increases by up to 3.3% for composite aerosols with non-spherical dust externally mixed with other spherical species. Our results show that while non-sphericity needs to be accounted for, choice of shape may not be important in estimating aerosol DRF in the IGB.

Mixing states of aerosols over four environmentally distinct atmospheric regimes in Asia: coastal, urban, and industrial locations influenced by dust

Mixing can influence the optical, physical, and chemical characteristics of aerosols, which in turn can modify their life cycle and radiative effects. Assumptions on the mixing state can lead to uncertain estimates of aerosol radiative effects. To examine the effect of mixing on the aerosol characteristics, and their influence on radiative effects, aerosol mixing states are determined over four environmentally distinct locations (Karachi, Gwangju, Osaka, and Singapore) in Asia, an aerosol hot spot region, using measured spectral aerosol optical properties and optical properties model. Aerosol optical depth (AOD), single scattering albedo (SSA), and asymmetry parameter (g) exhibit spectral, spatial, and temporal variations. Aerosol mixing states exhibit large spatial and temporal variations consistent with aerosol characteristics and aerosol type over each location. External mixing of aerosol species is unable to reproduce measured SSA over Asia, thus providing a strong evidence that aerosols exist in mixed state. Mineral dust (MD) (core)-Black carbon (BC) (shell) is one of the most preferred aerosol mixing states. Over locations influenced by biomass burning aerosols, BC (core)-water soluble (WS, shell) is a preferred mixing state, while dust gets coated by anthropogenic aerosols (BC, WS) over urban regions influenced by dust. MD (core)-sea salt (shell) mixing is found over Gwangju corroborating the observations. Aerosol radiative forcing exhibits large seasonal and spatial variations consistent with features seen in aerosol optical properties and mixing states. TOA forcing is less negative/positive for external mixing scenario because of lower SSA. Aerosol radiative forcing in Karachi is a factor of 2 higher when compared to Gwangju, Osaka, and Singapore. The influence of g on aerosol radiative forcing is insignificant. Results emphasize that rather than prescribing one single aerosol mixing state in global climate models regionally and temporally varying aerosol mixing states should be included for more accurate assessment of aerosol radiative effects.

Utilization of O4 slant column density to derive aerosol layer height from a spaceborne UV-Visible hyperspectral sensor: Sensitivity and case study

The sensitivities of oxygen-dimer (O₄) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the Linearlized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O₄ SCD by 10⁴⁰ molecules²cm^-5, to aerosol types and optical properties are also evaluated and compared. Among the O₄ absorption bands at 340, 360, 380, and 477 nm, the O₄ absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80% of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Direct radiative forcing of urban aerosols over Pretoria (25.75°S, 28.28°E) using AERONET Sunphotometer data: first scientific results and environmental impact

The present study uses the data collected from Cimel Sunphotometer of Aerosol Robotic Network (AERONET) for the period from January to December, 2012 over an urban site, Pretoria (PTR; 25.75°S, 28.28°E, 1449 m above sea level), South Africa. We found that monthly mean aerosol optical depth (AOD, τ(a)) exhibits two maxima that occurred in summer (February) and winter (August) having values of 0.36 ± 0.19 and 0.25 ± 0.14, respectively, high-to-moderate values in spring and thereafter, decreases from autumn with a minima in early winter (June) 0.12 ± 0.07. The Angstrom exponents (α440-870) likewise, have its peak in summer (January) 1.70 ± 0.21 and lowest in early winter (June) 1.38 ± 0.26, while the columnar water vapor (CWV) followed AOD pattern with high values (summer) at the beginning of the year (February, 2.10 ± 0.37 cm) and low values (winter) in the middle of the year (July, 0.66 ± 0.21 cm). The volume size distribution (VSD) in the fine-mode is higher in the summer and spring seasons, whereas in the coarse mode the VSD is higher in the winter and lower in the summer due to the hygroscopic growth of aerosol particles. The single scattering albedo (SSA) ranged from 0.85 to 0.96 at 440 nm over PTR for the entire study period. The averaged aerosol radiative forcing (ARF) computed using SBDART model at the top of the atmosphere (TOA) was -8.78 ± 3.1 W/m², while at the surface it was -25.69 ± 8.1 W/m² leading to an atmospheric forcing of +16.91 ± 6.8 W/m², indicating significant heating of the atmosphere with a mean of 0.47K/day.

Urban impacts on regional carbonaceous aerosols: case study in central Texas

Rural and background sites provide valuable information on the concentration and optical properties of organic, elemental, and water-soluble organic carbon (OC, EC, and WSOC), which are relevant for understanding the climate forcing potential of regional atmospheric aerosols. To quantify climate- and air quality-relevant characteristics of carbonaceous aerosol in the central United States, a regional background site in central Texas was chosen for long-term measurement. Back trajectory (BT) analysis, ambient OC, EC, and WSOC concentrations and absorption parameters are reported for the first 15 months of a long-term campaign (May 2011-August 2012). BT analysis indicates consistent north-south airflow connecting central Texas to the Central Plains. Central Texas aerosols exhibited seasonal trends with increased fine particulate matter (< 2.5 microm aerodynamic diameter, PM2.5) and OC during the summer (PM2.5 = 10.9 microg m(-3) and OC = 3.0 microg m(-3)) and elevated EC during the winter (0.22 microg m(-3)). When compared to measurements in Dallas and Houston, TX, central Texas OC appears to have mixed urban and rural sources. However central Texas EC appears to be dominated by transport of urban emissions. WSOC averaged 63% of the annual OC, with little seasonal variability in this ratio. To monitor brown carbon (BrC), absorption was measured for the aqueous WSOC extracts. Light absorption coefficients for EC and BrC were highest during summer (EC MAC = 11 m2 g(-1) and BRC MAE365 = 0.15 m2 g(-1)). Results from optical analysis indicate that regional aerosol absorption is mostly due to EC with summertime peaks in BrC attenuation. This study represents the first reported values of WSOC absorption, MAE365, for the central United States. Implications: Background concentration and absorption measurements are essential in determining regional potential radiative forcing due to atmospheric aerosols. Back trajectory, chemical, and optical analysis of PM2.5 was used to determine climatic and air quality implications of urban outflow to a regional receptor site, representative of the central United States. Results indicate that central Texas organic carbon has mixed urban and rural sources, while elemental carbon is controlled by the transport of urban emissions. Analysis of aerosol absorption showed black carbon as the dominant absorber, with less brown carbon absorption than regional studies in California and the southeastern United States.

A review on black carbon emissions, worldwide and in China

Black carbon (BC) produced from open burning (OB) and controlled combustion (CC) is a range of carbonaceous products of incomplete combustion of biomass and fossil fuel, and is deemed as one of the major contributors to impact global environment and human health. BC has a strong relationship with POPs, in waste combustion, BC promotes the formation of POPs, and then the transport of POPs in the environment is highly influenced by BC. However less is known about BC formation, measurement and emissions estimation especially in developing countries such as China. Different forms of BC are produced both in CC and OB. BC emission characteristics and combustion parameters which determine BC emissions from CC and OB are discussed. Recent studies showed a lack of common methodology and the resulting data for describing the mechanisms related to BC formation during combustion processes. Because BC is a continuum carbonaceous combustion product, different sampling and measuring methods are used for measuring their emissions with great quantitative uncertainty. We discuss the commonly used BC sampling and measuring methods along with the causes for uncertainty and measures to minimizing the uncertainty. Then, we discuss the estimations of BC emission factors and emission inventory for CC and OB sources. The total emissions of BC from CC and OB in China are also estimated and compared with previous BC emission inventories in this review and we find the inventories tend to be overestimated. As China becomes the largest contributor to global BC emissions, studies for characterizing BC emissions from OB and CC sources are absent in China. Finally, we comment on the current state of BC emission research and identify major deficiencies that need to overcome. Moreover, the advancement in research tools, measuring technique in particular, as discussed in this review is critical for researchers in developing countries to improve their capability to study BC emissions for addressing the growing climate change and public health concerns.

Black carbon aerosol characterization in a remote area of Qinghai-Tibetan Plateau, western China

The concentrations, size distributions, and mixing states of refractory black carbon (rBC) aerosols were measured with a ground-based Single Particle Soot Photometer (SP2), and aerosol absorption was measured with an Aethalometer at Qinghai Lake (QHL), a rural area in the Northeastern Tibetan Plateau of China in October 2011. The area was not pristine, with an average rBC mass concentration of 0.36 μg STP-m(-3) during the two-week campaign period. The rBC concentration peaked at night and reached the minimal in the afternoon. This diurnal cycle of concentration is negatively correlated with the mixed layer depth and ventilation. When air masses from the west of QHL were sampled in late afternoon to early evening, the average rBC concentration of 0.21 μg STP-m(-3) was observed, representing the rBC level in a larger Tibetan Plateau region because of the highest mixed layer depth. A lognormal primary mode with mass median diameter (MMD) of ~175 nm, and a small secondary lognormal mode with MMD of 470-500 nm of rBC were observed. Relative reduction in the secondary mode during a snow event supports recent work that suggested size dependent removal of rBC by precipitation. About 50% of the observed rBC cores were identified as thickly coated by non-BC material. A comparison of the Aethalometer and SP2 measurements suggests that non-BC species significantly affect the Aethalometer measurements in this region. A scaling factor for the Aethalometer data at a wavelength of 880 nm is therefore calculated based on the measurements, which may be used to correct other Aethalometer datasets collected in this region for a more accurate estimate of the rBC loading. The results present here significantly improve our understanding of the characteristics of rBC aerosol in the less studied Tibetan Plateau region and further highlight the size dependent removal of BC via precipitation.

The black carbon story: early history and new perspectives

A number of recent studies have suggested that black carbon (BC), the light-absorbing fraction of soot, is next to CO2 one of the strongest contributors to the global climate change. BC heats the air, darkens the snow and ice surfaces and could contribute to the melting of Arctic ice, snowpacks, and glaciers. Although soot is the oldest known pollutant its importance in climate modification has only been recently recognized. In this article, we trace the historical developments over about three decades that changed the view of the role of BC in the environment, from a pollutant of marginal importance to one of the main climate change agents. We also discuss some of the reasons for the initial lack of interest in BC and the subsequent rigorous research activity on the role of aerosols in climate change.

BICAR: a new algorithm for multiresolution spatiotemporal data fusion

We introduce a method for spatiotemporal data fusion and demonstrate its performance on three constructed data sets: one entirely simulated, one with temporal speech signals and simulated spatial images, and another with recorded music time series and astronomical images defining the spatial patterns. Each case study is constructed to present specific challenges to test the method and demonstrate its capabilities. Our algorithm, BICAR (Bidirectional Independent Component Averaged Representation), is based on independent component analysis (ICA) and extracts pairs of temporal and spatial sources from two data matrices with arbitrarily different spatiotemporal resolution. We pair the temporal and spatial sources using a physical transfer function that connects the dynamics of the two. BICAR produces a hierarchy of sources ranked according to reproducibility; we show that sources which are more reproducible are more similar to true (known) sources. BICAR is robust to added noise, even in a "worst case" scenario where all physical sources are equally noisy. BICAR is also relatively robust to misspecification of the transfer function. BICAR holds promise as a useful data-driven assimilation method in neuroscience, earth science, astronomy, and other signal processing domains.

Global air quality and climate

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.

Observationally constrained estimates of carbonaceous aerosol radiative forcing

Carbonaceous aerosols (CA) emitted by fossil and biomass fuels consist of black carbon (BC), a strong absorber of solar radiation, and organic matter (OM). OM scatters as well as absorbs solar radiation. The absorbing component of OM, which is ignored in most climate models, is referred to as brown carbon (BrC). Model estimates of the global CA radiative forcing range from 0 to 0.7 Wm(-2), to be compared with the Intergovernmental Panel on Climate Change's estimate for the pre-Industrial to the present net radiative forcing of about 1.6 Wm(-2). This study provides a model-independent, observationally based estimate of the CA direct radiative forcing. Ground-based aerosol network data is integrated with field data and satellite-based aerosol observations to provide a decadal (2001 through 2009) global view of the CA optical properties and direct radiative forcing. The estimated global CA direct radiative effect is about 0.75 Wm(-2) (0.5 to 1.0). This study identifies the global importance of BrC, which is shown to contribute about 20% to 550-nm CA solar absorption globally. Because of the inclusion of BrC, the net effect of OM is close to zero and the CA forcing is nearly equal to that of BC. The CA direct radiative forcing is estimated to be about 0.65 (0.5 to about 0.8) Wm(-2), thus comparable to or exceeding that by methane. Caused in part by BrC absorption, CAs have a net warming effect even over open biomass-burning regions in Africa and the Amazon.

Contribution of anthropogenic aerosols in direct radiative forcing and atmospheric heating rate over Delhi in the Indo-Gangetic Basin

INTRODUCTION

The present work is aimed to understand direct radiation effects due to aerosols over Delhi in the Indo-Gangetic Basin (IGB) region, using detailed chemical analysis of surface measured aerosols during the year 2007.

METHODS

An optically equivalent aerosol model was formulated on the basis of measured aerosol chemical compositions along with the ambient meteorological parameters to derive radiatively important aerosol optical parameters. The derived aerosol parameters were then used to estimate the aerosol direct radiative forcing at the top of the atmosphere, surface, and in the atmosphere.

RESULTS

The anthropogenic components measured at Delhi were found to be contributing ∼ 72% to the composite aerosol optical depth (AOD(0.5) ∼ 0.84). The estimated mean surface and atmospheric forcing for composite aerosols over Delhi were found to be about -69, -85, and -78 W m(-2) and about +78, +98, and +79 W m(-2) during the winter, summer, and post-monsoon periods, respectively. The anthropogenic aerosols contribute ∼ 90%, 53%, and 84% to the total aerosol surface forcing and ∼ 93%, 54%, and 88% to the total aerosol atmospheric forcing during the above respective periods. The mean (± SD) surface and atmospheric forcing for composite aerosols was about -79 (± 15) and +87 (± 26) W m(-2) over Delhi with respective anthropogenic contributions of ∼ 71% and 75% during the overall period of observation.

CONCLUSIONS

Aerosol induced large surface cooling, which was relatively higher during summer as compared to the winter suggesting an increase in dust loading over the station. The total atmospheric heating rate at Delhi averaged during the observation was found to be 2.42  ±  0.72 K day(-1), of which the anthropogenic fraction contributed as much as ∼ 73%.

Aerosol size distributions in urban Jinan: seasonal characteristics and variations between weekdays and weekends in a heavily polluted atmosphere

Aerosol size distributions, trace gas, and PM(2.5) concentrations have been measured in urban Jinan, China, over 6 months in 2007 and 2008, covering spring, summer, fall, and winter time periods. Number concentrations of particles (10-2,500 nm) were 16,200, 13,900, 11,200, and 21,600 cm( -3) in spring, summer, fall, and winter, respectively. Compared with other urban studies, Jinan has higher number concentrations of accumulation-mode particles (100-500 nm) and particles (10-2,500 nm), but lower concentrations of ultrafine particles (10-100 nm). The number, surface and volume concentrations, and size distributions of particles showed obvious seasonal variation and are also influenced by traffic emissions. Through correlation analysis, traffic emissions are proposed to be a more important contributor to Atkien-mode and accumulation-mode particles than coal firing. Around midday, the presence of nanoparticles and new particle formation is limited to pre-existing particles from traffic emissions and the mass transport of particles from suburban and rural areas. Compared with other studies in urban areas of Europe and the USA, the variation of particle number concentration and related gas concentration in Jinan between weekdays and weekends is smaller and the reasons has been deduced.

Consistency between satellite-derived and modeled estimates of the direct aerosol effect

In the Intergovernmental Panel on Climate Change Fourth Assessment Report, the direct aerosol effect is reported to have a radiative forcing estimate of -0.5 Watt per square meter (W m(-2)), offsetting the warming from CO2 by almost one-third. The uncertainty, however, ranges from -0.9 to -0.1 W m(-2), which is largely due to differences between estimates from global aerosol models and observation-based estimates, with the latter tending to have stronger (more negative) radiative forcing. This study demonstrates consistency between a global aerosol model and adjustment to an observation-based method, producing a global and annual mean radiative forcing that is weaker than -0.5 W m(-2), with a best estimate of -0.3 W m(-2). The physical explanation for the earlier discrepancy is that the relative increase in anthropogenic black carbon (absorbing aerosols) is much larger than the overall increase in the anthropogenic abundance of aerosols.