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Aerosol types have crucial and distinguished impacts on climate effects and cause the difference of air pollution. However, direct retrieval of aerosol type by satellite remote sensing is difficult, and the satellite products of aerosol type are seriously lacking. At present, the identification of aerosol type is mainly based on ground-based observation data, but the coverage area of ground-based stations is limited, and large-scale spatial continuous monitoring cannot be carried out. The existing aerosol type identification methods based on satellite data need to combine multiple satellites data (e.g. Moderate-resolution Imaging Spectroradiometer (MODIS), Ozone Monitoring Instrument (OMI), etc.) which leads to a low temporal resolution. The research about aerosol type identification only based on geostationary satellite data is lacking. Therefore, aerosol type identification based on the multi-parameter threshold method and the neural network method are proposed and compared in this paper. The neural network jointly using spectral and temporal information was trained and tested by the measurements from 26 sites of Aerosol Robotic Network (AERONET) and Sun-Sky Radiometer Observation Network (SONET). For the overall validation, the aerosol type identification based on the neural network is better than that based on the multi-parameter threshold method, and the accuracy reaches 71.44%. Atmospheric environment monitoring and quantitative remote sensing can be supported by this study. • Aerosol type, neural network, geostationary satellite [ABSTRACT FROM AUTHOR]

For regions where limited in-situ observations are available for use as a reference, such as in China, the understanding of how changes in the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol retrieval algorithm impact the data quality is limited. In this paper, the MODIS-Aqua Aerosol Optical Thickness (AOT) Collection 5 (C5) and 6 (C6) Dark-Target (DT) products are evaluated by comparison with similar products from the China Aerosol Remote Sensing NETwork (CARSNET) and the Aerosol Robotic Network (AERONET) in China for the year 2008. The validation data are analyzed for key factors affecting the results of the MODIS-DT aerosol retrieval algorithm, including surface type, aerosol loading and aerosol absorption. The impacts of the change from the C5 to the C6 versions of the MODIS AOT retrieval algorithm are discussed in detail. The main findings are: (1) The agreement from retrieval aspects between both MODIS C5/C6 and CARSNET-AERONET for most AOT values over distinct regions indicates that the conclusions obtained from C5 hold for C6; (2) MODIS-DT has an extended coverage (more retrievals) with good quality due to the change of upstream data (calibration, cloud masking, etc); (3) About 64% of the MODISDT C6 AOT data over China fall within the (±0.15 AOT ± 0.05) error envelope; (4) positive AOT differences between C6 and C5 over relatively dark surfaces and negative differences over relatively bright surfaces due to the change of surface parameterization have been observed; (5) the AOT difference between MODIS and CARSNET-AERONET relating to AOT loading is not significant, especially for large AOT; (6) MODIS-DT performs well for absorbing aerosol over relatively bright surfaces. • MODIS/Aqua AOT C5/C6 DT products are evaluated to understand the effects of different parameters on algorithm performance. • Both MODIS C5 and C6 DT show good quality over China under different surface and atmospheric conditions. • MODIS C6 DT aerosol product has an extended coverage with good quality over China. [ABSTRACT FROM AUTHOR]

In this paper, we report the results and analysis of a recent field campaign in August 2007 investigating the impacts of emissions from transportation on air quality and community concentrations in Beijing, China. We conducted measurements in three different environments, on-road, roadside and ambient. The carbon monoxide, black carbon and ultrafine particle number emission factors for on-road light-duty vehicles are derived to be 95gkg−1-fuel, 0.3gkg−1-fuel and 1.8×1015 particleskg−1-fuel, respectively. The emission factors for on-road heavy-duty vehicles are 50gkg−1-fuel, 1.3gkg−1-fuel and 1.1×1016 particleskg−1-fuel, respectively. The carbon monoxide emission factors from this study agree with those derived from remote sensing and on-board vehicle emission testing systems in China. The on-road black carbon and particle number emission factors for Chinese vehicles are reported for the first time in the literature. Strong traffic impacts can be observed from the concentrations measured in these different environments. Most clear is a reflection of diesel truck traffic activity in black carbon concentrations. The comparison of the particle size distributions measured at the three environments suggests that the traffic is a major source of ultrafine particles. A four-day traffic control experiment conducted by the Beijing Government as a pilot to test the effectiveness of proposed controls was found to be effective in reducing extreme concentrations that occurred at both on-road and ambient environments. [Copyright &y& Elsevier]

Aerosol is a critical trace component of the atmosphere. Many processes in the Earth's climate system are intimately related to aerosols via their direct and indirect radiative effects. Aerosol effects are not limited to these climatic aspects, however. They are also closely related to human health, photosynthesis, new energy, etc., which makes aerosol a central focus in many research fields. A fundamental requirement for improving our understanding of the diverse aerosol effects is to accumulate high-quality aerosol data by various measurement techniques. Sunphotometer remote sensing is one of the techniques that has been playing an increasingly important role in characterizing aerosols across the world. Much progress has been made on this aspect in China during the past decade, which is the work reviewed in this paper. Three sunphotometer networks have been established to provide high-quality observations of long-term aerosol optical properties across the country. Using this valuable dataset, our understanding of spatiotemporal variability and long-term trends of aerosol optical properties has been much improved. The radiative effects of aerosols both at the bottom and at the top of the atmosphere are comprehensively assessed. Substantial warming of the atmosphere by aerosol absorption is revealed. The long-range transport of dust from the Taklimakan Desert in Northwest China and anthropogenic aerosols from South Asia to the Tibetan Plateau is characterized based on ground-based and satellite remote sensing as well as model simulations. Effective methods to estimate chemical compositions from sunphotometer aerosol products are developed. Dozens of satellite and model aerosol products are validated, shedding new light on how to improve these products. These advances improve our understanding of the critical role played by aerosols in both the climate and environment. Finally, a perspective on future research is presented. • Development of ground-based sunphotometer networks in China is presented. • Advances in our understanding of aerosol optical properties and radiative effects are reviewed. • A perspective on possible directions for future research is discussed. [ABSTRACT FROM AUTHOR]

China experienced heavy aerosol pollution in recent years. The aerosol pollution changes surface solar radiation and affects the land terrestrial carbon and water cycles in China. However, there are still some uncertainties in evaluating aerosol effects on ecosystem. Therefore, we combined the MODIS Atmosphere and Land products with process-based model to examine the sensitivity of gross primary productivity (GPP) and water use efficiency (WUE) to AOD. We also evaluated the effects of aerosol loadings on GPP and WUE at China FLUX sites from 2002 to 2015. Our results indicated that the radiative effects of aerosols on GPP varied with the vegetation type, which is consistent with other studies. Aerosol enhances the GPP by 2% in forest and reduces the GPP by 7% in grass land during the study period. We also found that the radiative effects of aerosols on WUE varied with the vegetation type. The WUE was promoted by the aerosols for all surface types when AOD is lower than 2.3. This indicates that the aerosol could enhance the plants WUE in most cases. Cloud during the study period restrains aerosol effects on growth of plants and improves the aerosol effects on WUE. Aerosol loadings during the study period fertilized the growth in two forest growth and slightly impede the growth of grass. They also improve the WUE for all vegetation types. The WUE increases more that 4% in most of sites increases. The results in this paper could help to fully understand the influences of aerosol on land carbon and water cycle. • MODIS products and BESS model were used to evaluate aerosol effects on GPP and WUE. • Aerosol enhances the GPP by 2% in forest during the study period. • The WUE increases more than 4% in most of sites due to the aerosol effects. • Cloud restrains aerosol effects on GPP and improves aerosol effects on WUE. [ABSTRACT FROM AUTHOR]