Seasonal variation of the transport of black carbon aerosol from the Asian continent to the Arctic during the ARCTAS aircraft campaign

Extensive measurements of black carbon (BC) aerosol were conducted in and near the North American Arctic during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) aircraft campaign in April and June-July 2008. We identify the pathways and mechanisms of transport of BC to the Arctic from the Asian continent using these data. The concentration, transport efficiency, and measured altitude of BC over the North American Arctic were highly dependent on season and origin of air parcels, e.g., biomass burning (BB) in Russia (Russian BB) and anthropogenic (AN) in East Asia (Asian AN). Russian BB air was mainly measured in the middle troposphere and caused maximum BC concentrations at this altitude in spring. The median BC concentration and transport efficiency of the Russian BB air were 270 ng m -3 (at STP) and 80% in spring and 20 ng m-3 and 4% in summer, respectively. Asian AN air was measured most frequently in the upper troposphere, with median values of 20 ng m-3 and 13% in spring and 5 ng m-3 and 0.8% in summer. These distinct differences are explained by differences in the transport mechanisms and accumulated precipitation along trajectories (APT), which is a measure of wet removal processes during transport. The transport of Russian BB air to the Arctic was nearly isentropic with slow ascent (low APT), while Asian AN air underwent strong uplift associated with warm conveyor belts (high APT). The APT values in summer were much larger than those in spring due to the increase in humidity in summer. These results show that the impact of BC emitted from AN sources in East Asia on the Arctic was very limited in both spring and summer. The BB emissions in Russia in spring are demonstrated to be the most important sources of BC transported to the North American Arctic. Copyright 2011 by the American Geophysical Union

Determining ground-level composition and concentration of particulate matter across regional areas using the Himawari-8 satellite

Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar orbiting imagers, which means that aerosol is only derived during the daytime, and only once or twice per day. Sub-hourly, infrared (IR), geostationary data, such as the ten-minute data from Himawari-8, are required to monitor these events to ensure that sporadic dust events can be continually observed and quantified. Newer quantification methods using geostationary data have focussed on detecting the presence, or absence, of a dust event. However, limited attention has been paid to the determination of composition, and particle size, using IR wavelengths exclusively. More appropriate IR methods are required to quantify and classify aerosol composition in order to improve the understanding of source impacts. The primary research objectives were investigated through a series of scientific papers centred on aspects deemed critical to successfully determining ground-level concentrations. A literature review of surface particulate monitoring of dust events using geostationary satellite remote sensing was undertaken to understand the theory and limitations in the current methodology. The review identified (amongst other findings) the reliance on visible wavelengths and the lack of temporal resolution in polar-orbiting satellite data. As a result of this, a duststorm was investigated to determine how rapidly the storm passed and what temporal data resolution is required to monitor these and other similar events. Various IR dust indices were investigated to determine which are optimum for determining spectral change. These indices were then used to qualify and quantitate dust events, and the methodology was validated against three severe air quality events of a dust storm; smoke from prescribed burns; and an ozone smog incident. The study identified that continuous geostationary temporal resolution is critical in the determination of concentration. The Himawari-8 spatial resolution of 2 km is slightly coarse and further spatial aggregation or cloud masking would be detrimental to determining concentrations. Five dual-band BTD combinations, using all IR wavelengths, maximises the identification of compositional differences, atmospheric stability, and cloud cover and this improves the estimated accuracy. Preliminary validation suggests that atmospheric stability, cloud height, relative humidity, PM2.5, PM10, NO, NO2, and O3 appear to produce plausible plumes but that aerosol speciation (soil, sea-spray, fires, vehicles, and secondary sulfates) and SO2 require further investigation. The research described in the thesis details the processes adopted for the development and implementation of an integrated approach to using geostationary remote sensing data to quantify population exposure (who), qualify the concentration and composition (what), assess the temporal (when) and spatial (where) concentration distributions, to determine the source (why) of aerosols contribution to resulting ground-level concentration

Investigating Aerosol Effects on Clouds, Precipitation and Regional Climate in US and China by Means of Ground-based and Satellite Observations and a Global Climate Model

Aerosols affect climate by scattering/absorbing radiation and by acting as cloud condensation nuclei (CCN) or ice nuclei (IN). One of the least understood but most significant aspects of climate change is the aerosol effect on cloud and precipitation. A hypothesis has recently been proposed that, in addition to reducing cloud effective radius and suppressing precipitation, aerosols may also modify the thermodynamic structure of deep convective clouds and lead to enhanced precipitation when complex thermodynamic processes are involved. Taking advantage of the long-term and extensive ground-based observations at the US Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, we thoroughly tested such a hypothesis and provide direct evidence of it. Moreover, the hypothesis is also supported by analysis of satellite-based observations over tropical regions from multiple sensors in the A-Train satellites constellation. Extensive analyses of the long-term ground-based and large-scale data reveal significant increases in rain rate or frequency and cloud top heights with increasing aerosol loading for mix-phase deep convective clouds, decreases rain frequency for low liquid clouds, but little impact on cloud height for liquid clouds. Rigorous tests are conducted to investigate any potential artifacts and influences of meteorological conditions. Large-scale circulation patterns and monsoon systems can be changed by scattering and absorption of solar radiation by aerosols. By means of model simulations with the National Center for Atmospheric Research Community Climate Model (NCAR/CCM3), we found that the increase of aerosol loading in China contributes to circulation changes, leading to more frequent occurrence of fog events in winter as observed from meteorological records. The increase in atmospheric aerosols over China heats the atmosphere and generates a cyclonic circulation anomaly over eastern-central China. This circulation anomaly leads to a reduction in the influx of dry and cold air over that area during winter. Weakening of the East Asian winter monsoon system may also contribute to these changes. All these changes favor the formation and maintenance of fog over this region. The MODerate resolution Imaging Spectroradiometer (MODIS) aerosol products used in the above studies are validated using ground-based measurements from the Chinese Sun Hazemeter Network (CSHNET). Overall, substantial improvement was found in the current version of aerosol products relative to the previous one. At individual sites, the improvement varies with surface and atmospheric conditions

APPLICATIONS OF MODERATE-RESOLUTION REMOTE SENSING TECHNOLOGIES FOR SURFACE AIR POLLUTION MONITORING IN SOUTHEAST ASIA

Retrievals from Earth observation satellites are widely used for many applications, including analyzing dynamic lands and measuring atmospheric components. This research aims to evaluate appropriateness of using satellite retrievals to facilitate understanding characteristics of Southeast Asian (SEA) surface air pollution, attributed to regional biomass burnings and urban activities. The studies in this dissertation focused on using satellite retrievals for 1) mapping potential SEA air pollution sources; which are forests, rice paddies, and urban areas, 2) understanding dynamic optical characteristics of SEA biomass-burning aerosols, and 3) inferring surface ozone level. Data used in this study were from three NASA\u27s Earth Observing System (EOS) satellites, which are Terra, Aqua, and Aura. These retrievals have spatial resolution ranging from hundred meters to ten kilometers. Algorithms used for the SEA land cover classification were developed using time-series analyses of surface reflectance in multiple wavelength bands from Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. Comparing the results to national statistical databases, good agreement was obtained for spatial estimation of forest areas after correction with plantation areas. For estimation of rice paddies areas, the agreement depended on the rice ecosystems. It was good for rainfed rice and poor for deepwater rice. Models for irrigated and upland rice areas showed overall high coefficients of determination, suggesting that they effectively simulated the spatial distribution of those rice paddies; but were prone to underestimate and overestimate, respectively. Estimated SEA regional rice area was 42×106 ha, which agrees with previous published values. Analysis of the satellite retrieval could identify large urban areas. However, the satellite-derived urban areas also incorrectly included large sandy beaches. Optical properties of SEA background aerosols were investigated through the multivariate analyses of long-term ground-based aerosol measurements acquired from Aerosol Robotic Network (AERONET). The results in this study showed that from mid-September to December, the aerosol had both fine size and high light scattering efficiency. It was assumed to be largely urban/industrial aerosols, possibly coming from eastern China. From January to April, the aerosol had fine size and had single scattering albedo (SSA at 440 nm) of approximately 0.9. It was assumed to be smoke from local biomass burning. From October to January, when seasonal winds are strongest, more SEA urban aerosol was observed. This aerosol had coarser size and had SSA of ~0.9 or less. The appropriateness of using Ozone Monitoring Instrument (OMI) aerosol retrieval to facilitate understanding SEA biomass-burning aerosol properties was evaluated through three lines of evidence. These are 1) comparisons between the results obtained from multivariate analyses of the OMI aerosol retrieval and those obtained from the ground-measured AERONET data, 2) from Atmospheric Infrared Sounder (AIRS) total column CO product, and 3) from MODIS active fire detections. The results showed that the OMI retrieval used for large-scale SEA biomass-burning aerosol characterization was consistent with these alternative measures only when 1 \u3c OMI aerosol optical depth (442 nm) \u3c 3. The OMI aerosol retrieval was then used for the study on dynamic characteristics of biomass burning aerosol. This study considered the aerosols from two forest-fire episodes, 2007 SEA continent and 2008 Indonesian fires. Dependence of the aerosol optical properties on four variables was investigated. These variables were 1) wind speed/direction, 2) relative humidity (RH), 3) land use/cover as a surrogate of fuel type estimated from time-series analysis of MODIS surface reflectance, and 4) age of aerosol estimated from spatial-temporal analysis of MODIS active fire and the wind characteristics. Results from Pearson Chi-square test for independence showed that the dependence between aerosol group memberships with different optical properties and the limiting variables was significant for most cases, except for Indonesian aerosol age factor. These results agree with prior knowledge on regional burning conditions (types of fuel and relative humidity) and aerosol chemical/physical properties (chemical composition related to aerosol optical properties and hygroscopicity). Using EOS-Aura tropospheric column ozone (TCO) to infer surface ozone level was evaluated through analyses of linear relationships between TCO estimated from OMI and Microwave Limb Sounder (MLS) retrievals and coincident TCO from balloon-based ozonesonde measurements. This evaluation was for different tropospheric ozone profile shapes and for different geographical regions (for low, mid, and high latitudes and for Pacific and Atlantic regions). Results indicate that inference on ozone level derived from the satellite-based TCO requires corresponding information about tropospheric ozone profile shape. The use of satellite-based TCO was more appropriate for polluted low-latitude locations where upper troposphere ozone is rare and surface enhanced ozone is high

Studying the Impact on Urban Health over the Greater Delta Region in Egypt Due to Aerosol Variability Using Optical Characteristics from Satellite Observations and Ground-Based AERONET Measurements

This research addresses the aerosol characteristics and variability over Cairo and the Greater Delta region over the last 20 years using an integrative multi-sensor approach of remotely sensed and PM10 ground data. The accuracy of these satellite aerosol products is also evaluated and compared through cross-validation against ground observations from the AErosol RObotic NETwork (AERONET) project measured at local stations. The results show the validity of using Multi-angle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms for quantitative aerosol optical depth (AOD) assessment as compared to Ozone Monitoring Instrument (OMI), Sea-viewingWide Field-of-view Sensor (SeaWiFS), and POLarization and Directionality of the Earth’s Reflectances (POLDER). In addition, extracted MISR-based aerosol products have been proven to be quite eective in investigating the characteristics of mixed aerosols. Daily AERONET AOD observations were collected and classified using K-means unsupervised machine learning algorithms, showing five typical patterns of aerosols in the region under investigation. Four seasonal aerosol emerging episodes are identified and analyzed using multiple indicators, including aerosol optical depth (AOD), size distribution, single scattering albedo (SSA), and Ångström exponent (AE). The movements and detailed aerosol composition of the aforementioned episodes are demonstrated using NASA’s Goddard Space Flight Center (GSFC) back trajectories model in collaboration with aerosol subtype products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission. These episodes indicate that during the spring, fall, and summer, most of the severe aerosol events are caused by dust or mixed related scenarios, whereas during winter, aerosols of finer size lead to severe heavy conditions. It also demonstrates the impacts of different aerosol sources on urban human health, which are presented by the variations of multiple parameters, including solar radiation, air temperature, humidity, and UV exposure. Scarce ground PM10 data were collected and compared against satellite products, yet owed to their discrete nature of availability, our approach made use of the Random Decision Forest (RDF) model to convert satellite-based AOD and other meteorological parameters to predict PM10. The RDF model with inputs from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) and Global Land Data Assimilation System (GLDAS) datasets improves the performance of using AOD products to estimate PM10 values. The connection between climate variability and aerosol intensity, as well as their impact on health-related PM2.5 over Egypt is also demonstrated

The potential of increasing man-made air pollution to reduce rainfall over southern West Africa

Southern West Africa has one of the fastest-growing populations worldwide. This has led to a higher water demand and lower air quality. Over the last 3 decades, most of the region has experienced decreasing rainfall during the little dry season (LDS; mid-July to end of August) and more recently also during the second rainy season (SRS; September-October), while trends during the first rainy season (FRS; mid-May to mid-July) are insignificant. Here we analyse spatio-temporal variations in precipitation, aerosol, radiation, cloud, and visibility observations from surface stations and from space to find indications for a potential contribution of anthropogenic air pollution to these rainfall trends. The proposed mechanism is that the dimming of incoming solar radiation by aerosol extinction contributes to reducing vertical instability and thus convective precipitation. To separate a potential aerosol influence from large-scale climatic drivers, a multilinear-regression model based on sea-surface temperature (SST) indices is used. During both LDS and SRS, weakly statistically significant but accelerating negative rainfall trends unrelated to known climatic factors are found. These are accompanied by a strong increase in pollution over the upstream tropical Atlantic caused by fire aerosol from Central Africa, particularly during the LDS. Over southern West Africa, no long-term aerosol records are available, inhibiting a direct quantification of the local manmade effect. However, significant decreases in horizontal visibility and incoming surface solar radiation are strong indicators for an increasing aerosol burden, in line with the hypothesized pollution impact on rainfall. The radiation trend is further enhanced by an increase in low-level cloudiness. The large spatial extent of potentially aerosol-related trends during the LDS is consistent with the stronger monsoon flow and less wet deposition during this season. Negligible aerosol impacts during the FRS are likely due to the high degree of convective organization, which makes rainfall less sensitive to surface radiation. The overall coherent picture and the accelerating trends - some of which are concealed by SST effects - should alarm policymakers in West Africa to prevent a further increase in air pollution as this could endanger water supply and food and energy production for a large and growing population

Effects of Meteorology Changes on Inter-Annual Variations of Aerosol Optical Depth and Surface PM2.5 in China—Implications for PM2.5 Remote Sensing

PM2.5 retrieval from satellite-observed aerosol optical depth (AOD) is still challenging due to the strong impact of meteorology. We investigate influences of meteorology changes on the inter-annual variations of AOD and surface PM2.5 in China between 2006 and 2017 using a nested 3D chemical transport model, GEOS-Chem, by fixing emissions at the 2006 level. We then identify major meteorological elements controlling the inter-annual variations of AOD and surface PM2.5 using multiple linear regression. We find larger influences of meteorology changes on trends of AOD than that of surface PM2.5. On the seasonal scale, meteorology changes are beneficial to AOD and surface PM2.5 reduction in spring (1–50%) but show an adverse effect on aerosol reduction in summer. In addition, major meteorological elements influencing variations of AOD and PM2.5 are similar between spring and fall. In winter, meteorology changes are favorable to AOD reduction (−0.007 yr−1, −1.2% yr−1; p < 0.05) but enhanced surface PM2.5 between 2006 and 2017. The difference in winter is mainly attributed to the stable boundary layer that isolates surface PM2.5 from aloft. The significant decrease in AOD over the years is related to the increase in meridional wind speed at 850 hPa in NCP (p < 0.05). The increase of surface PM2.5 in NCP in winter is possibly related to the increased temperature inversion and more stable stratification in the boundary layer. This suggests that previous estimates of wintertime surface PM2.5 using satellite measurements of AOD corrected by meteorological elements should be used with caution. Our findings provide potential meteorological elements that might improve the retrieval of surface PM2.5 from satellite-observed AOD on the seasonal scale

Examination of aerosol distributions and radiative effects over the Bay of Bengal and the Arabian Sea region during ICARB using satellite data and a general circulation model

In this paper we analyse aerosol loading and its direct radiative effects over the Bay of Bengal (BoB) and Arabian Sea (AS) regions for the Integrated Campaign on Aerosols, gases and Radiation Budget (ICARB) undertaken during 2006, using satellite data from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, the Aerosol Index from the Ozone Monitoring Instrument (OMI) on board the Aura satellite, and the European-Community Hamburg (ECHAM5.5) general circulation model extended by Hamburg Aerosol Module (HAM). By statistically comparing with large-scale satellite data sets, we firstly show that the aerosol properties measured during the ship-based ICARB campaign and simulated by the model are representative for the BoB and AS regions and the pre-monsoon season. In a second step, the modelled aerosol distributions were evaluated by a comparison with the measurements from the ship-based sunphotometer, and the satellite retrievals during ICARB. It is found that the model broadly reproduces the observed spatial and temporal variability in aerosol optical depth (AOD) over BoB and AS regions. However, AOD was systematically underestimated during high-pollution episodes, especially in the BoB leg. We show that this underprediction of AOD is mostly because of the deficiencies in the coarse mode, where the model shows that dust is the dominant component. The analysis of dust AOD along with the OMI Aerosol Index indicate that missing dust transport that results from too low dust emission fluxes over the Thar Desert region in the model caused this deficiency. Thirdly, we analysed the spatio-temporal variability of AOD comparing the ship-based observations to the large-scale satellite observations and simulations. It was found that most of the variability along the track was from geographical patterns, with a minor influence by single events. Aerosol fields were homogeneous enough to yield a good statistical agreement between satellite data at a 1&amp;deg; spatial, but only twice-daily temporal resolution, and the ship-based sunphotometer data at a much finer spatial, but daily-average temporal resolution. Examination of the satellite data further showed that the year 2006 is representative for the five-year period for which satellite data were available. Finally, we estimated the clear-sky solar direct aerosol radiative forcing (DARF). We found that the cruise represents well the regional-seasonal mean forcings. Constraining simulated forcings using the observed AOD distributions yields a robust estimate of regional-seasonal mean DARF of &amp;minus;8.6, &amp;minus;21.4 and +12.9 W m&lt;sup&gt;&amp;minus;2&lt;/sup&gt; at the top of the atmosphere (TOA), at the surface (SUR) and in the atmosphere (ATM), respectively, for the BoB region, and over the AS, of, &amp;minus;6.8, &amp;minus;12.8, and +6 W m&lt;sup&gt;&amp;minus;2&lt;/sup&gt; at TOA, SUR, and ATM, respectively

A HTAP Multi-Model Assessment of the Influence of Regional Anthropogenic Emission Reductions on Aerosol Direct Radiative Forcing and the Role of Intercontinental Transport

In this study, we assess changes of aerosol optical depth (AOD) and direct radiative forcing (DRF) in response to the reduction of anthropogenic emissions in four major pollution regions in the northern hemisphere by using results from 10 global chemical transport models in the framework of the Hemispheric Transport of Air Pollution (HTAP). The multi-model results show that on average, a 20% reduction of anthropogenic emissions in North America, Europe, East Asia and South Asia lowers the global mean AOD and DRF by about 9%, 4%, and 10% for sulfate, organic matter, and black carbon aerosol, respectively. The impacts of the regional emission reductions on AOD and DRF extend well beyond the source regions because of intercontinental transport. On an annual basis, intercontinental transport accounts for 10-30% of the overall AOD and DRF in a receptor region, with domestic emissions accounting for the remainder, depending on regions and species. While South Asia is most influenced by import of sulfate aerosol from Europe, North America is most influenced by import of black carbon from East Asia. Results show a large spread among models, highlighting the need to improve aerosol processes in models and evaluate and constrain models with observations