Quantifying instantaneous nitrogen oxides emissions from power plants based on space observations.

Thermal power plants are significant contributors to nitrogen oxides (NOx), impacting global atmospheric conditions and human health. Satellite observations, known for their continuity and global coverage, have become an effective means of quantifying power plant emissions. Previous studies, often accumulating long temporal data into integrated plumes, resulted in substantial errors in annual emissions at the individual power plant level due to neglecting variations in emissions and diffusion conditions. This study presents, for the first time, the quantification of instantaneous NOx emissions based on single overpass observations from the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite. By addressing the temporal variability of power plant emissions, it effectively reduces annual estimation errors. Comparative analysis between the Exponentially-Modified Gaussian (EMG) and Gaussian Plume Model (GPM) simulations demonstrates the capability of EMG to provide instantaneous emission estimates based on actual plumes, exhibiting closer proximity to actual monitoring values than GPM. Applying the EMG method, we quantify the instantaneous emission rates of six power plants in the United States. Comparing annual emission estimations at individual power plants with traditional integrated plume results, our method demonstrates a 63.7 % improvement in annual emission estimations. This study offers more detailed data on power plant emissions, providing a new avenue for better understanding the emission behavior of thermal power plants.

Spatiotemporally continuous PM2.5 dataset in the Mekong River Basin from 2015 to 2022 using a stacking model.

With the potential to cause millions of deaths, PM2.5 pollution has become a global concern. In Southeast Asia, the Mekong River Basin (MRB) is experiencing heavy PM2.5 pollution and the existing PM2.5 studies in the MRB are limited in terms of accuracy and spatiotemporal coverage. To achieve high-accuracy and long-term PM2.5 monitoring of the MRB, fused aerosol optical depth (AOD) data and multi-source auxiliary data are fed into a stacking model to estimate PM2.5 concentrations. The proposed stacking model takes advantage of convolutional neural network (CNN) and Light Gradient Boosting Machine (LightGBM) models and can well represent the spatiotemporal heterogeneity of the PM2.5-AOD relationship. In the cross-validation (CV), comparison with CNN and LightGBM models shows that the stacking model can better suppress overfitting, with a higher coefficient of determination (R2) of 0.92, a lower root mean square error (RMSE) of 5.58 µg/m3, and a lower mean absolute error (MAE) of 3.44 µg/m3. For the first time, the high-accuracy PM2.5 dataset reveals spatially and temporally continuous PM2.5 pollution and variations in the MRB from 2015 to 2022. Moreover, the spatiotemporal variations of annual and monthly PM2.5 pollution are also investigated at the regional and national scales. The dataset will contribute to the analysis of the causes of PM2.5 pollution and the development of mitigation policies in the MRB.

Spatio-Temporal Changes in Ecosystem Quality across the Belt and Road Region.

The Silk Road Economic Belt and the 21st Century Maritime Silk Road Initiative (BRI) proposed in 2013 by China has greatly accelerated the social and economic development of the countries along the Belt and Road (B&R) region. However, the international community has questioned its impact on the ecological environment and a comprehensive assessment of ecosystem quality changes is lacking. Therefore, this study proposes an objective and automatic method to assess ecosystem quality and analyzes the spatiotemporal changes in the B&R region. First, an ecosystem quality index (EQI) is established by integrating the vegetation status derived from three remote sensing ecological parameters including the leaf area index, fractional vegetation cover and gross primary productivity. Then, the EQI values are automatically categorized into five ecosystem quality levels including excellent, good, moderate, low and poor to illustrate their spatiotemporal changes from the years 2016 to 2020. The results indicate that the spatial distributions of the EQIs across the B&R region exhibited similar patterns in the years 2016 and 2020. The regions with excellent levels accounted for the lowest proportion of less than 12%, while regions with moderate, low and poor levels accounted for more than 68% of the study area. Moreover, based on the EQI pattern analysis between the years 2016 and 2020, the regions with no significant EQI change accounted for up to 99.33% and approximately 0.45% experienced a significantly decreased EQI. Therefore, this study indicates that the ecosystem quality of the B&R region was relatively poor and experienced no significant change in the five years after the implementation of the "Vision and Action to Promote the Joint Construction of the Silk Road Economic Belt and the 21st Century Maritime Silk Road". This study can provide useful information for decision support on the future ecological environment management and sustainable development of the B&R region.

Impact of satellite AOD data on top-down estimation of biomass burning particulate matter emission.

Particulate matter emitted from open biomass burning affects climate, air quality and public health. In the development of remote sensing techniques, top-down methods using satellite observations have become an effective way to estimate particulate matter emissions, but different spatial resolution and coverage of satellite aerosol optical depth (AOD) products introduce great uncertainties. In this work, we assess the differences in total particulate matter (TPM) emission when calculated using different satellite AOD data. To do this, we derive top-down biomass burning TPM emission coefficients (Ce) of Australia based on 1 km and 10 km MODIS AOD products, and compare the results of emission estimation. Using high spatial resolution AOD data, a 90 % decrease of Ce mean value is found in Australia, and the quality of Ce improves by 290 %. When we use 1 km AOD data in place of 10 km AOD data, the estimation of biomass burning TPM emissions in Australia during 2012-2020 drops from 1.08Tg to 0.11Tg; the temporal trends of the two products remain the same. The TPM emission estimates for biome based on higher spatial resolution AOD data in this study are lower than Fire Energetics and Emissions Research (FEERv1) inventories by factors of 0.08-0.2. Our work shows that using satellite AOD products of higher spatial resolution avoids overestimation of biomass burning TPM emissions, and improves the quality of final estimates, providing a possible way to understand biomass burning emission more accurately.

Evaluating the impacts of burning biomass on PM2.5 regional transport under various emission conditions.

The fine particulate matter (PM2.5) emitted by burning biomass has become the main source of pollution in cities; this pollution seriously threatens the ecosystem and inhabitants' health. A major challenge in dealing with this issue is the uncertainty regarding the influence of burning biomass on PM2.5 regional transport. In this study, Harbin-Changchun Megalopolis is the research area. Using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model combined with satellite data and PM2.5 monitoring data, we quantitatively analyzed the regional transport of PM2.5 from burning biomass upwind of each city under different emission conditions. Conditions at burn sites, especially emission intensity and meteorological factors, as well as transport distance play significant roles in the regional transport of PM2.5. Higher emission intensity aggravated the concentration of downwind PM2.5, at most 19.7 µg ⋅ m-3. Shorter transport distance strengthened the impact of biomass burning on downstream PM2.5 by weakening elimination, which could be up to 96.8 µg ⋅ m-3. Moreover, meteorological factors at fire points were closely related to the transport of PM2.5. First, lower planetary boundary layer height could enhance the transport of PM2.5 from the burning biomass by inhibiting vertical diffusion, and the enhancement could be up to 46.1 µg ⋅ m-3. Second, compared to strong wind, light wind caused the weaker dilution, enhancing PM2.5 regional transport by as much as 32.5 µg ⋅ m-3. Third, relatively humidity at 30%-40% had the strongest effect in facilitating the transport of PM2.5 from burning biomass. We conclude that comprehensively considering these three factors, namely the emission intensity, transport distance and meteorological factors at burn sites can facilitate the cross-regional development of accurate prediction models and effective pollution control measures.

Probing the dynamic characteristics of aerosol originated from South Asia biomass burning using POLDER/GRASP satellite data with relevant accessory technique design.

The dynamic characteristics of biomass burning aerosol originated from South Asia are investigated in this research using nearly 9 years of POLDER/GRASP satellite aerosol dataset. The POLDER/GRASP remote sensing data can provide global, repeatable, various, and sufficient real-world aerosol information even in the remote ocean region, which can't be offered by the ground measurement, laboratory observation or model simulation. The MODIS thermal anomalies/fire dataset and HYSPLIT backward trajectory are applied to search the aerosol originated from South Asia biomass burning. The biomass burning aerosol originated from South Asia could transport to and influence the north part of Indian Ocean (including Bay of Bengal and Arabian Sea), the north part of Indo-China Peninsula, South China, and even far to the Pacific Ocean (including part of East China Sea and South China Sea). The chemical, physical and optical characteristics of biomass burning aerosol over land and over ocean show different features and evolution patterns. Such difference is caused by the different ambient environment and different mixed aerosol during the transport process (urban/industrial aerosol over land and sea salt over ocean). During the 48-hours aging process, the volume fraction of black carbon, AAOD and Angstrom Exponent decrease. Meanwhile, the aerosol sphere fraction and SSA increase. The biomass burning aerosol over land shows a more obvious evolution trend than that over ocean. The biomass burning aerosol over ocean generally have higher SSA and lower volume fraction of black carbon, aerosol sphere fraction, AAOD and Angstrom Exponent. The aerosol radiative forcing efficiency also varies between land and ocean, due to their different features of aerosol and surface properties. In general, a negative clear-sky aerosol radiative forcing efficiency (cooling effect) at the TOA is observed. The aerosol cooling effect at the TOA over ocean (-82 W/m2 on average) is much stronger than that over land (-36 W/m2 on average). During the 48-hours aging process, a significant enhancement of the negative radiative forcing efficiency at the TOA is found over land. Over ocean, the enhancement of the negative radiative forcing efficiency at the TOA is weaker.

Estimating the Columnar Concentrations of Black Carbon Aerosols in China Using MODIS Products.

Black carbon (BC), the strongest light-absorbing particle, is believed to play substantial roles in regional air quality and global climate change. In this study, taking advantage of the high quality of moderate resolution imaging spectroradiometer products, we developed a new algorithm to estimate the BC columnar concentrations over China by simulating the BC and non-BC aerosol mixing states in detail. The results show that our new algorithm produces a reliable estimation of BC aerosols, in which BC columnar concentrations and their related parameters (aerosol absorption and BC surface concentration) show reasonable agreements and low biases compared with ground-based measurements. The uncertainties of BC retrievals are mainly associated with the surface and aerosol assumptions used in the algorithm, ranging from -14 to 44% at higher aerosol optical depth (AOD > 0.5). The proposed algorithm can improve the capability of space-borne aerosol remote sensing by successfully distinguishing BC from other aerosols. The acquired BC columnar concentrations enable the spatial pattern of serious BC aerosol pollution over East China to be characterized, showing that it exhibits higher levels in winter. These nationwide results are beneficial for estimating BC emissions, proposing mitigation strategies for air pollution, and potentially reducing the uncertainties of climate change studies.

The role of biomass burning states in light absorption enhancement of carbonaceous aerosols.

Carbonaceous aerosols, which are emitted from biomass burning, significantly contribute to the Earth's radiation balance. Radiative forcing caused by biomass burning has been poorly qualified, which is largely attributed to uncertain absorption enhancement values (Eabs) of black carbon (BC) aerosols. Laboratory measurements and theoretical modelling indicate a significant value of Eabs; but this enhancement is observed to be negligible in the ambient environment, implying that models may overestimate global warming due to BC. Here, we present an aggregate model integrating BC aerosol ensembles with different morphologies and mixing states and report a quantitative analysis of the BC Eabs from different combustion states during biomass burning. We show that the BC Eabs produced by flaming combustion may be up to two times more than those produced by smouldering combustion, suggesting that the particle morphology and mixing state of freshly emitted BC aerosols is an important source of the contrasting values of Eabs. The particle morphology of freshly emitted BC aerosols is widely assumed to be bare in models, which is rare in the ambient environment and leads to small estimates of Eabs by field observations. We conclude that the exact description of freshly emitted carbonaceous aerosols plays an important role in constraining aerosol radiative forcing.

Study on the characteristics of black carbon during atmospheric pollution conditions in Beijing.

Black carbon (BC), not only has a negative impact on human health, but also contributes to visibility degradation and the attenuation of solar radiation due to light absorption. In this paper, we investigated the variations of BC concentration, BC optical characteristics and its effects on the physical and optical properties of atmospheric aerosols based on AERONET data during atmospheric pollution conditions in Beijing from 2012 to 2017. The results indicated that the average annual ground-level BC concentration and BC/PM2.5 were 8.9 µg m-3 and 6.7%, respectively, from 2012 to 2017 during atmospheric pollution conditions in Beijing. The annual mean ground-level BC concentration showed weak variation, but the monthly variation was pronounced during atmospheric pollution conditions. Moreover, the BC column concentration had a higher correlation with absorptive aerosol optical thickness (AAOT) at 870 nm (R2 = 0.93) than 440 nm (R2 = 0.73). The difference in AAOT between 440 nm and 870 nm was more significant under high BC column concentration. The seasonal variation of the BC column concentration that contributed to the AAOT at 870 nm displayed a consistent monthly average variation tendency. The BC column concentrations were divided into three segments of low, moderate, and high according to the results of the approximately normal distribution of the BC column concentration. Compared with high BC concentration, the single scattering albedo (SSA) and asymmetry parameter were enhanced by 0.05 and 0.04 in low BC concentrations, respectively. On the contrary, the fine mode fraction (FMF) was dropped by 12.5% in low BC concentrations. A higher BC concentration contributed to the enhancement in the AAOT and the extinction ratio of the fine mode aerosol. Meanwhile, the atmospheric particles' forward scattering ability was also attenuated under a high BC concentration.

Does the prohibition on open burning of straw mitigate air pollution? An empirical study in Jilin Province of China in the post-harvest season.

Straw open burning is common practice in agricultural production, and has been identified as highly relevant to regional haze. A variety of control measures for straw open burning have been adopted in agricultural areas to mitigate air pollution, but their contribution to air quality improvement is difficult to estimate, and has been addressed by few studies. Using Jilin Province during the post-harvest season (PHS) as a study area, we empirically evaluated the contribution of the Straw Open Burning Prohibition Plan (SOBP) to air quality improvement by response surface methodology (RMS) modeling combined with scenario analysis, and constructed and introduced a stagnant index to the RMS model. The results indicated that the adoption of the SOBP by Jilin Province in the 2018 PHS mitigated air pollution effectively. The contribution of the plan to air quality improvement was also evaluated under two scenarios: if the SOBP had been implemented during the 2015 PHS, 2016 PHS, and 2017 PHS, the cumulative PM2.5 concentration would have declined in these years by 23%, 15%, and 22%, respectively, compared with their actual values; if the SOBP had not been implemented in the 2018 PHS, the cumulative PM2.5 concentration would have increased by 10%-14% compared with the actual value. The results can provide decision makers with a reference to assess the environmental performance of the SOBP, and guidance for establishing scientific environmental regulations for cleaner agricultural production and sustainable development.

[Spatial and Temporal Characteristics of Air Quality and Cause Analysis of Heavy Pollution in Northeast China].

Northeastern China experiences severe atmospheric pollution, with an increasing occurrence of heavy haze episodes. Based on ground monitoring data, satellite products and meteorological products of atmospheric pollutants in northeast China from 2013 to 2017, the characteristics of spatial and temporal distribution of air quality and the causes of heavy haze events in northeast China were discussed. It was found that the "Shenyang-Changchun-Harbin" city belt was the most polluted area in the region on an annual scale. The spatial distribution of air quality index (AQI) values had a clear seasonality, with the worst pollution occurring in winter, an approximately oval-shaped polluted area around western Jilin Province in spring, and the best air quality occurring in summer and most of autumn. The three periods that typically experienced intense haze events were Period I from late-October to early-November (i. e., late autumn and early winter), Period Ⅱ from late-December to January (i. e., the coldest time in winter), and Period Ⅲ from April to mid-May (i. e., spring). During Period I, strong PM2.5 emissions from seasonal crop residue burning and coal burning for winter heating were the dominant reasons for the occurrence of extreme haze events (AQI>300). Period Ⅱ had frequent heavy haze events (200 < AQI < 300) in the coldest months of January and February(200 < AQI < 300), which were due to high PM2.5 emissions from coal burning and vehicle fuel consumption, a lower atmospheric boundary layer, and stagnant atmospheric conditions. Haze events in Period Ⅲ, with high PM10 concentrations, were primarily caused by the regional transportation of windblown dust from degraded grassland in central Inner Mongolia and bare soil in western Jilin Province. Local agricultural tilling could also release PM10 and enhance the levels of windblown dust from tilled soil.

Biomass burning aerosol characteristics for different vegetation types in different aging periods.

Eighteen years of sun/sky photometer measurements at seven worldwide AErosol RObotic NETwork (AERONET) sites in typical biomass burning regions were used in this research. The AERONET measurements were analyzed with the help of Moderate-resolution Imaging Spectroradiometer (MODIS) fire products and the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The variation in the physicochemical and optical properties of biomass burning aerosols (BBAs), as well as their shortwave radiative forcing, was revealed for different vegetation types in different aging periods. The result indicated that, with aerosol aging, the BBA characteristics have a non-negligible evolution trend with obvious clustering features for different burning vegetation types. During the aging process, the volume fraction of black carbon (BC) declined (with a maximum drop of 38%) accompanied by particle size growth (with a maximum increment of 0.017 µm). Driven by the change in physicochemical properties, the Single Scattering Albedo (SSA) and the asymmetry factor increased as the aerosol aged (with maximum increments of 0.026 and 0.018 for the SSA and asymmetry factor respectively). The grass and shrub type had a higher volume fraction of BC (2.5 times higher than that in the forest and peat type) and a smaller fine mode volume median radius (with a difference of 0.037 µm from that of the forest and peat type). Such a phenomenon results in a lower SSA (with a difference of 0.103) and asymmetry factor (with a difference of 0.035) in the grass and shrub type when compared to the forest and peat type. Negative (-74 to -30 W/m2) clear-sky top of atmosphere (TOA) shortwave radiative forcing, strengthened during the aging process, was generally found for BBA. The BBA in the forest and peat region usually had stronger negative radiative forcing efficiency.

Contribution of meteorological factors to particulate pollution during winters in Beijing.

Associated with its modernization, Beijing has experienced significant fine particulate matter (PM2.5) pollution, especially in winter. In 2016, severe PM2.5 pollution (PM2.5 > 250 µg/m3) lasted over 6 days and affected over 23 million people. A major challenge in dealing with this issue is the uncertainty regarding the influence of individual meteorological factors to the overall PM2.5 concentration in Beijing. Thus, applying an empirical regression method to long-term ground-based PM2.5 data and meteorological sounding measurements, we attempted to analyze the influence of individual meteorological factors on PM2.5 pollution during winters in Beijing. We found that horizontal dilution and vertical aggregation plays a major role in PM2.5 pollution during the winter of 2016. The impact of horizontal wind on PM2.5 concentration in Beijing was mainly from its dilution, the dilution of northerly wind contributed 27.8% in 2016, far below its contribution in 2015 (32.2%). The contribution from the growing vertical aggregation observed in 2016 was mainly the result of both the lower height of the planetary boundary layer and the greater depth of the temperature inversion. The dilution of the planetary boundary layer height contributed 9.8% to PM2.5 pollution in 2016, 5.4% lower than that in 2017. Compared with the temperature difference of the inversion layer, the temperature inversion depth better reflects the aggregated impact of temperature inversions to PM2.5, which was 10.9% in 2015, and the ratio rose to 14.3% in 2016. Relative humidity is also an important impacting factor, which contributed 41.0%, far higher than the ratio in 2017 (26.7%). Such results imply that we should focus on not only local emission control, but also horizontal atmospheric transport and meteorological conditions in order to provide a more accurate analysis of pollution mechanisms, conductive to air pollution governance in Beijing.

Light Absorption Enhancement of Black Carbon Aerosol Constrained by Particle Morphology.

The radiative forcing of black carbon aerosol (BC) is one of the largest sources of uncertainty in climate change assessments. Contrasting results of BC absorption enhancement ( Eabs) after aging are estimated by field measurements and modeling studies, causing ambiguous parametrizations of BC solar absorption in climate models. Here we quantify Eabs using a theoretical model parametrized by the complex particle morphology of BC in different aging scales. We show that Eabs continuously increases with aging and stabilizes with a maximum of ∼3.5, suggesting that previous seemingly contrast results of Eabs can be explicitly described by BC aging with corresponding particle morphology. We also report that current climate models using Mie Core-Shell model may overestimate Eabs at a certain aging stage with a rapid rise of Eabs, which is commonly observed in the ambient. A correction coefficient for this overestimation is suggested to improve model predictions of BC climate impact.

The impacts of regional transport and meteorological factors on aerosol optical depth over Beijing, 1980-2014.

Understanding the role of different sources that contribute to the aerosol extinction coefficient is an important aspect toward analyzing climate change and regional air quality. In Beijing specifically, the region has suffered severe air quality deterioration over the past three decades, but the magnitude of extraneous contributions to aerosol variation has remained uncertain. Therefore, we estimated trends of contributions to aerosol optical depth (AOD) for Beijing from 1980 to 2014 and built a seasonal regression model to decouple the extraneous contribution from the total emitted using ground-based aerosol and meteorological measurements, extended to the emissions of man-made and natural contribution. The variation of AOD over Beijing was significantly affected by the anthropogenic aerosol emissions, which experienced slight augmentation by 15.3% from 1980 to 2000, rapid inflation by 36.9% from 2000 to 2006, and a gradual decrease by 10.0% from 2006 to 2014. The extraneous contribution from wind and its associated languishing patterns explain the historical increase of regional AOD, which experienced about a 10% enhancement over the three stages. Other meteorological contributions show no significant trends over 35 years, except for the temperature inversion, which despite the weakened hygroscopic growth after 2006, still experiences a significant enhancement.

Assessing Spatial and Temporal Patterns of Observed Ground-level Ozone in China.

Elevated ground-level ozone (O3), which is an important aspect of air quality related to public health, has been causing increasing concern. This study investigated the spatiotemporal distribution of ground-level O3 concentrations in China using a dataset from the Chinese national air quality monitoring network during 2013-2015. This research analyzed the diurnal, monthly and yearly variation of O3 concentrations in both sparsely and densely populated regions. In particular, 6 major Chinese cities were selected to allow a discussion of variations in O3 levels in detail, Beijing, Chengdu, Guangzhou, Lanzhou, Shanghai, and Urumchi, located on both sides of the Heihe-Tengchong line. Data showed that the nationwide 3-year MDA8 of ground-level O3 was 80.26 µg/m3. Ground-level O3 concentrations exhibited monthly variability peaking in summer and reaching the lowest levels in winter. The diurnal cycle reached a minimum in morning and peaked in the afternoon. Yearly average O3 MDA8 concentrations in Beijing, Chengdu, Lanzhou, and Shanghai in 2015 increased 12%, 25%, 34%, 22%, respectively, when compared with those in 2013. Compared with World Health Organization O3 guidelines, Beijing, Chengdu, Guangzhou, and Shanghai suffered O3 pollution in excess of the 8-hour O3 standard for more than 30% of the days in 2013 to 2015.

Assessment of PM2.5 concentrations and exposure throughout China using ground observations.

Exposure to PM2.5 results in negative effects on human health. However, PM2.5 exposure at the national scale is poorly known for China owing to limited spatial and temporal PM2.5 concentration data. In this study, we present analyses of PM2.5 exposure throughout China using high-resolution temporal and spatial ground-level PM2.5 data from 2015. Our results indicated that the annual mean PM2.5 concentration was 52.81µg/m3, and that the highest annual mean PM2.5 concentrations primarily appeared in the North China Plain. We also found the lowest and highest monthly mean PM2.5 concentrations appeared in August and January, respectively, while the lowest and highest diurnal mean PM2.5 concentrations occurred at 16:00 and 10:00, respectively. Moreover, comparisons to data from 2013 indicated that the annual mean PM2.5 concentrations decreased by 12.31% from 2013 to 2015, which was likely due to the implementation of environmental protection laws in early 2015. Our findings provide new insights, for not only studies of PM2.5 exposure and human health, but also to inform the implementation of national and regional air pollution reduction policies.

Black carbon radiative forcing at TOA decreased during aging.

During aging processing, black carbon (also called soot) particles may tend to be mixed with other aerosols, and highly influence their radiative forcing. In this study, freshly emitted soot particles were simulated as fractal aggregates composed of small spherical primary monomers. After aging in the atmosphere, soot monomers were coated by a thinly layer of sulfate as thinly coated soot particles. These soot particles were entirely embedded into large sulfate particle by further aging, and becoming heavily coated soot particles. In clear-sky conditions, black carbon radiative forcing with different aging states were investigated for the bottom and top of atmosphere (BOA and TOA). The simulations showed that black carbon radiative forcing increased at BOA and decreased at TOA after their aging processes. Thinly and heavily coated states increased up to ~12% and ~35% black carbon radiative forcing at BOA, and black carbon radiative forcing at TOA can reach to ~20% and ~100% smaller for thinly and heavily coated states than those of freshly emitted states, respectively. The effect of aging states of black carbon radiative forcing was varied with surface albedo, aerosol optical depth and solar zenith angles. These findings would be helpful for the assessments of climate change.

Comparison of Four Ground-Level PM2.5 Estimation Models Using PARASOL Aerosol Optical Depth Data from China.

Satellite remote sensing is of considerable importance for estimating ground-level PM2.5 concentrations to support environmental agencies monitoring air quality. However, most current studies have focused mainly on the application of MODIS aerosol optical depth (AOD) to predict PM2.5 concentrations, while PARASOL AOD, which is sensitive to fine-mode aerosols over land surfaces, has received little attention. In this study, we compared a linear regression model, a quadratic regression model, a power regression model and a logarithmic regression model, which were developed using PARASOL level 2 AOD collected in China from 18 January 2013 to 10 October 2013. We obtained R (correlation coefficient) values of 0.64, 0.63, 0.62, and 0.57 for the four models when they were cross validated with the observed values. Furthermore, after all the data were classified into six levels according to the Air Quality Index (AQI), a low level of statistical significance between the four empirical models was found when the ground-level PM2.5 concentrations were greater than 75 µg/m³. The maximum R value was 0.44 (for the logarithmic regression model and the power model), and the minimum R value was 0.28 (for the logarithmic regression model and the power model) when the PM2.5 concentrations were less than 75 µg/m³. We also discussed uncertainty sources and possible improvements.

Effects of mixing states on the multiple-scattering properties of soot aerosols.

The radiative properties of soot aerosols are highly sensitive to the mixing states of black carbon particles and other aerosol components. Light absorption properties are enhanced by the mixing state of soot aerosols. Quantification of the effects of mixing states on the scattering properties of soot aerosol are still not completely resolved, especially for multiple-scattering properties. This study focuses on the effects of the mixing state on the multiple scattering of soot aerosols using the vector radiative transfer model. Two types of soot aerosols with different mixing states such as external mixture soot aerosols and internal mixture soot aerosols are studied. Upward radiance/polarization and hemispheric flux are studied with variable soot aerosol loadings for clear and haze scenarios. Our study showed dramatic changes in upward radiance/polarization due to the effects of the mixing state on the multiple scattering of soot aerosols. The relative difference in upward radiance due to the different mixing states can reach 16%, whereas the relative difference of upward polarization can reach 200%. The effects of the mixing state on the multiple-scattering properties of soot aerosols increase with increasing soot aerosol loading. The effects of the soot aerosol mixing state on upwelling hemispheric flux are much smaller than in upward radiance/polarization, which increase with increasing solar zenith angle. The relative difference in upwelling hemispheric flux due to the different soot aerosol mixing states can reach 18% when the solar zenith angle is 75°. The findings should improve our understanding of the effects of mixing states on the optical properties of soot aerosols and their effects on climate. The mixing mechanism of soot aerosols is of critical importance in evaluating the climate effects of soot aerosols, which should be explicitly included in radiative forcing models and aerosol remote sensing.