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Oral Presentations

AS42 - Remote Sensing of Fires, Aerosols, Surface Pm2.5, and Aerosol Precursors
Friday, August 11, 2017 | 308 | 08:30-10:30
AS42-D5-AM1-308-001 (AS42-A011)
The GaoFen-5 Satellite Mission for Air Quality Monitoring in China
Liangfu CHEN#+
Chinese Academy of Sciences, China
#Corresponding author: +Presenter

The Chinese government has developed GaoFen series of satellites to observe the Earth, with GaoFen-5 for air quality monitoring specially. There are four main instruments onboard GaoFen-5, Directional Polarization Camera (DPC), Environment Monitoring Instrument (EMI), Atmospheric Infrared Ultraspectral (AIUS), and Greenhouse-gases Monitoring Instrument (GMI). DPC is similar as PARASOL, which mainly measures scattering properties of aerosol and clouds with polarization. The EMI with spectrum range in 270-790 nm can obtain information of trace gases such as NO2, SO2, and O3 as OMI. At the same time, AIUS can provide vertical profiles of trace gases such as O3, H­­2O with occultation observation. GMI measures information of greenhouse gases of CO2 and CH4 with shortwave infrared bands. The integrated observation of these instruments can provide a comprehensive insights into the air pollution in China. As all the instrument test and algorithms reached the end, the GaoFen-5 satellite is expected to be launched later in 2017.

AS42-D5-AM1-308-002 (AS42-A001)
An Operational Method for Aerosol Optical Depth Retrieval Using High Temporal-Spatial Resolution Data of Geostationary Satellite Gaofen-4
Xingfeng CHEN1+, Zhengqiang LI1#, Weizhen HOU1, Ying ZHANG1, Shaoshuai ZHAO2
1 Chinese Academy of Sciences, China, 2 Henan Polytechnic University, China
#Corresponding author: +Presenter

Geostationary satellite is useful and important for monitoring the aerosol temporal and spatial changes, especially in China. The Chinese Gaofen-4 satellite is a new generation geostationary satellite which has both more spectral bands (6 bands: 1 Panchromatic, 4 Visible and near infrared and 1 Medium-wave infrared) and high temporal and spatial (50m) resolution. Gaofen-4 grabs images in staring and scanning observation modes. Utilizing the ultra-high temporal-spatial resolution satellite data acquired by Gaofen-4, we designed the operational method and software system to retrieve aerosol optical depth. The characteristics of Gaofen-4 observation modes and the band sensibility were investigated. We developed the retrieval algorithm of aerosol optical depth using ultra-high temporal-spatial resolution data, with a core idea of “surface and atmosphere varies differently” special for geostationary satellite. And, a cloud masking method was developed using only four visible and near infrared bands considering the NDVI and WT indexes. The AOD retrieval algorithm is being used for GOCI sensor and has been improved for Gaofen-4 data. In the improved algorithm, the earth-atmosphere signals could be decoupled automatically by the self-updating reflectance using time series data. Then, an operational software system was developed, which has the capabilities of multithreading calculation and automatic operation, which meet the demands of satellite data operational processing. A series of Gaofen-4 satellite data were processed and validated by the ground-based experimental data, which can get from AERONET and SONET. Preliminary results (R2>0.76) were obtained and indicate that the system has good reliability and stability. This remote sensing software system could monitor temporal-spatial changes of the haze pollutions in China.

AS42-D5-AM1-308-003 (AS42-A009)
Remote Sensing Observation of Dust Storms and Thier Association with Kawasaki Disease Outbreaks
Hesham EL-ASKARY1#+, Nick LAHYE2, Eric LINSTEAD1, William SPRIGG3, Magdi YACOUB4
1 Chapman University, United States, 2 Jet Propulsion Laboratory, California Institute of Technology, United States, 3 University of Arizona, United States, 4 Imprerial College of London, United Kingdom
#Corresponding author: +Presenter

Kawasaki disease (KD) is a rare vascular disease that, if left untreated, can result in irreparable cardiac damage in children. While the symptoms of KD are well-known, as are best practices for treatment, the etiology of the disease and the factors contributing to KD outbreaks remain puzzling to both medical practitioners and scientists alike. Recently, a fungus known as Candida, originating in the farmlands of China, has been blamed for outbreaks in China and Japan, with the hypothesis that it can be transported over long ranges via different wind mechanisms. This paper provides evidence to understand the transport mechanisms of dust at different geographic locations and the cause of the annual spike of KD in Japan. The particle in question is Candida that is carried along with many other dusts, particles or aerosols, of various sizes in major seasonal wind currents. The evidence is based upon particle categorization using the Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD), Fine Mode Fraction (FMF) and Ångström Exponent (AE), the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) attenuated backscatter and aerosol subtype, and the Aerosol Robotic Network’s (AERONET) derived volume concentration. We found that seasonality associated with aerosol size distribution at different geographic locations plays a role in identifying dominant abundance at each location. Knowing the typical size of the Candida fungus, and analyzing aerosol characteristics using AERONET data reveals possible particle transport association with KD events at different locations. Thus, understanding transport mechanisms and accurate identification of aerosol sources is important in order to understand possible triggers to outbreaks of KD. This work provides future opportunities to leverage machine learning, including state-of-the-art deep architectures, to build predictive models of KD outbreaks, with the ultimate goal of early forecasting and intervention within a nascent global health early-warning system.

AS42-D5-AM1-308-004 (AS42-A012)
Estimating Regional PM2.5 Through Sophisticated Correction on Satellite AOD: An Attempt of Combining Chemical Model and In Situ Meteorological Observations
Zifeng WANG#+, Liangfu CHEN, Minghui TAO, Jinhua TAO, Li SU
Chinese Academy of Sciences, China
#Corresponding author: +Presenter

Fine particulate matters with aerodynamic radius less than 2.5 μm (PM2.5) is one of the primary pollutants in most regions of China, which induces substantial adverse impact on public health and ecological safety. The estimation of regional PM2.5 using satellite derived aerosol optical depth (AOD) faces two major sources of uncertainty, namely the vertical distributions and hygroscopic characteristics of aerosols. This study follows a clear pathway of “physical correction on AOD” by integrating chemical model simulations and in situ observations, aiming at reduce the impact of these problems.

Firstly, the aerosol vertical profiles from models are compared with collocated in situ profiles observed by LIDAR or radiosonde. Model profiles will be adjusted based on the constraint of observed profiles as well as local weather conditions, so as to extract and accurate extinction contribution of ground-level aerosols to AOD. We use 0.25° GEOS-Chem to provide regional vertical profiles of aerosols, and after appropriate adjustment these data are used to conduct vertical correction on MODIS AOD to obtain the regional distribution of surface aerosol extinction. Secondly, this study develops an empirical method of dynamically deriving aerosol hygroscopicity over different time and space. Not relying on detailed information of aerosol chemical and microphysical properties, this method simply uses the in-situ observations of visibility (VIS), RH and PM2.5 concentrations to approximate aerosol hygroscopic growth under ambient conditions. The applicability of this method to the routine measurements from meteorological and air quality network guarantees enough spatial and temporal coverages to support the satellite estimation of PM2.5.

Preliminary attempt was conducted over Zhejiang Province in East China based on one year of dataset in 2014. Our results showed that this method effectively improves the AOD-PM2.5 correlation after implementing the vertical and hygroscopic correction, and especially can achieve a satisfactory accuracy in daily satellite estimation of PM2.5.

AS42-D5-AM1-308-005 (AS42-A020)
Analysis of Aerosol Information Content in Simulated CAPI/TanSat Observation Over Land
Xi CHEN1#+, Jun WANG2, Yi LIU1, Xiaoguang XU2, Zhaonan CAI1, Dongxu YANG1
1 Chinese Academy of Sciences, China, 2 The University of Iowa, United States
#Corresponding author: +Presenter

Aerosols affect the radiative transfer in the absorption bands of carbon dioxide (CO2), thereby contributing to the uncertainties in the retrieval of CO2 from space. A Cloud and Aerosol Polarimetric Imager (CAPI) has been designed to fly on the Chinese Carbon Dioxide Observation Satellite (TanSat) and provide aerosol and cloud information to facilitate the measurements of CO2. This study aims to assess the information content about aerosol properties that can be obtained from CAPI’s observations of radiance and polarization. We simulate synthetic CAPI observations using the UNified Linearized Vector Radiative Transfer Model (UNL-VRTM), from which the degree of freedom for signal (DFS) and a posteriori error are calculated using optimal estimation theory. It is found that CAPI can provide 3 to 4.5 independent pieces of information about aerosol parameters, mainly related to aerosol total volume (or aerosol optical depth), fine mode fraction (fmfv) of aerosol volume, and imaginary part of refractive index for coarse mode aerosols. At directions around back-scattering, aerosol information content is smaller due in part to the large directional surface reflectance. In addition, due to weaker scattering of coarse aerosol, the information content of large particle is relatively less. Therefore, as fmfv decreases, DFS remains large for fine aerosol and increases for coarse aerosol. Furthermore, the degree of linear polarization (DOLP) is shown to be more sensitive to aerosol properties than reflectance, hence improves CAPI’s aerosol retrieval accuracy. The additional information content from DOLP measurements ranges from 1 to 1.8 in terms of DFS and reaches the largest in conditions of 0.2 < fmfv < 0.4 at SZA < 60o. If AOD is known as a priori (for example, from other A-Train satellites), total DFS for aerosol information content can be improved by 0.8 to 1.6 in most cases, and could exceed 2.0 for AOD < 0.2.

AS42-D5-AM1-308-006 (AS42-A021)
A Multi-Platform System for Understanding, Monitoring and Forecasting the Impact of Aerosol Pollutants in South-East Asia
National University of Singapore, Singapore
#Corresponding author: +Presenter

In the South-EAST Asia (SEA) region, smokeemissions from biomass burning has become an ever increasing problem that affects the region's major cities and especially Singapore. Trans-boundary smoke episodes triggered by fire events are occurring more frequently and with increasing intensity e.g. 1997, 2006, 2010, 2013 and more recently 2015. These fire events are the result of small and large scale land clearance occurring specially during the region's dry season and periods of severe draught. Satellite observations suggest a strong impact of the Asian summer monsoon on the local and regional tropospheric environment. Such a impact influences surface sources of emission such as local pollution and trans-boundary emissions (biomass burning). Unfortunately, the lack of extensive and reliable measurements, in most parts of the region, makes it difficult to assess and quantify the monsoonal effect. Satellite remote sensing has the capability of delivering non-intrusive, regional wide means of understanding and studying the local and regional sources of aerosol emission. However, the extraction of aerosol physical and optical properties from remote sensing satellites as well as inferring its transport and evolution posses substantial challenges as the region host one the highest cloud fraction in the world. In this work, we will discuss the challenges that the local and regional meteorology imposes on ground and satellite remote sensing observations as well as proposing a framework to overcome these limitations. Such a framework will allow for rapid measurement response during pollution events as well as to study the different aspects of the local and regional aerosol environment. Such an arrangement is crucial andnecessary in order to establish rigorous correlations between tropospheric aerosols and local air quality indicators.

AS42-D5-AM1-308-007 (AS42-A010)
Aerosol Microphysical Properties Retrievals from High Spectral Resolution Lidar Data
Xu LIU#+
NASA Langley Research Center, United States
#Corresponding author: +Presenter

An Optimal Estimation (OE) inversion method has been developed to retrieve aerosol effective size, volume concentration, and complex refractive indices using three wavelengths backscattering (3β) and two wavelengths of extinction (2α) lidar measurements. The algorithm is capable of retrieving multiple aerosol modes and can retrieve vertical profiles simultaneously using altitude resolved HSRL data. The algorithm is designed in such as way that it can include additional measurements (e.g. polarimeter or Sun photometer) for improved aerosol microphysical property retrievals. In a traditional aerosol retrieval algorithm, one solves for aerosol size distributions under various parameter space (rmin, rmax, real and imaginary refractive index) using Tikhonov (or other) regularization and then selects physically and mathematically meaningful solutions from hundreds of thousand retrievals. In an attempt to speed up the retrieval and to provide retrieval error estimates, the OE method solves for all related aerosol microphysical parameters (e.g. number concentrations, particle size distribution, real and imaginary part of refractive indices) simultaneously in a maximum-likelihood sense by fitting the observed data. Other quantities such as effective particle radius, surface area concentration, volume concentration, and single scattering albedo are also derived from the retrieved size distribution and the number concentrations. Preliminary results using both simulated data and airborne measurements from HSRL-2. Coincident airborne in-situ and surface remote sensing datasets will be used to evaluate the performance of the new OE algorithm.

AS42 - Remote Sensing of Fires, Aerosols, Surface Pm2.5, and Aerosol Precursors
Friday, August 11, 2017 | 308 | 11:00-12:30
AS42-D5-AM2-308-008 (AS42-A005)
Improving Nocturnal Fire Detection with the VIIRS Day-Night Band
Jun WANG#+
The University of Iowa, United States
#Corresponding author: +Presenter

Building on existing techniques for satellite remote sensing of fires, this paper takes advantage of the day–night band (DNB) aboard the Visible Infrared Imaging Radiometer Suite (VIIRS) to develop the Firelight Detection Algorithm (FILDA), which characterizes fire pixels based on both visible-light and infrared (IR) signatures at night. By adjusting fire pixel selection criteria to include visible-light signatures, FILDA allows for sig- nificantly improved detection of pixels with smaller and/or cooler subpixel hotspots than the operational Interface Data Processing System (IDPS) algorithm. VIIRS scenes with near-coincident Ad- vanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified “candidate fire pixel selection” approach from FILDA that lowers the 4-μm brightness temperature (BT) threshold but includes a minimum DNB radi- ance. FILDA is shown to be effective in detecting gas flares and characterizing fire lines during large forest fires (such as the Rim Fire in California and High Park fire in Colorado). Compared with the operational VIIRS fire algorithm for the study period, FILDA shows a large increase (up to 90%) in the number of detected fire pixels that can be verified with the finer resolution ASTER data (90 m). Part (30%) of this increase is likely due to a combined use of DNB and lower 4-μm BT thresholds for fire detection in FILDA. Although further studies are needed, quantitative use of the DNB to improve fire detection could lead to reduced response times to wildfires and better estimate of fire characteristics (smoldering and flaming) at night.

AS42-D5-AM2-308-009 (AS42-A004)
Predicting Pollutant Emissions from Agricultural Waste Burning in Guangdong Province Using Neural Network
Xu FENG+, Tzung-May FU#, Hansen CAO
Peking University, China
#Corresponding author: +Presenter

The trace gases and aerosols emitted from agricultural waste burning have large impacts on air quality in many parts of China, including in particular the Pearl River Delta. These seasonal emissions are variable in space and time, posing a challenge for air quality forecasts. Here, we used the back-propagation neural network (BPNN) technique to predict the daily variability of agricultural waste burning. We applied hierarchical clustering and K-means clustering techniques to objectively determine spatially-coherent areas for individual BPNNs. The BPNNs were constructed and trained using a decade (2003 to 2012) of daily assimilated meteorological data from NCEP FNL and fire pixels from the Moderate Resolution Imaging Spectroradiometer (MODIS). The data from the year 2013 were used for validation. In forecast mode, we drove the BPNNs with NCEP FNL forecast to obtain daily fire pixel forecasts, which were in turn used to scale the Fire Inventory from NCAR (FINN). We compared air quality forecasts driven by our daily-variable emission inventory, as well as forecasts driven by the monthly mean FINN. We showed that our daily-variable inventory led to significant improvements in the forecasts of PM2.5 and trace gas concentrations in the Guangdong Province.

AS42-D5-AM2-308-010 (AS42-A013)
Understanding Sources of Elemental Composition of Particulate Matter in the South China Sea During the 2011 Vasco Cruise
Miguel Ricardo HILARIO1#+, Gabrielle Frances LEUNG1, Annelle Raphayette CHUA1, Melliza CRUZ2, Maria Obiminda CAMBALIZA1,2, Jeffrey REID3, James SIMPAS2, Nofel LAGROSAS2,4, Donald BLAKE5, Sherdon Niño UY2
1 Ateneo de Manila University, Philippines, 2 Manila Observatory, Philippines, 3 Naval Research Laboratory, United States, 4 Chiba University, Japan, 5 University of California, Irvine, United States
#Corresponding author: +Presenter

The South China Sea is a receptor of various natural and anthropogenic aerosols. However, current understanding of their sources is limited. In September 2011, a 2-week research cruise was conducted near Palawan, Philippines. Size-segregated aerosol data was collected using a Davis Rotating-drum Uniform size-cut Monitor sampler, and analyzed for 28 selected elements. Whole air samples were also collected and analyzed for over 60 trace gases.  Positive Matrix Factorization was performed on the PM2.5 size range to determine possible sources and their contributions to the fine particulate matter mass. Additionally, size distribution plots, time series plots, PM1:PM10 ratio slope values and correlation matrix were used in interpreting factors. In the PM2.5 size range, initial results identify five sources: ferrous metal source (2.4%), biomass burning (26.1%), sea spray (36.5%), oil combustion (4.3%), and coal combustion (30.7%). Vanadium was solely apportioned to the oil combustion factor. Furthermore, 91.3% of V was found in the PM0.75 size range, suggesting anthropogenic origins. Nearly 85% of K and 62% of S were apportioned to the biomass burning factor. Spikes in the biomass burning contribution coincided with the arrival of plumes during the cruise, further suggesting the presence of biomass burning emissions in the SCS. Biomass burning tracers (ethane, benzene, CH3I) tracked the time series plot of carbon monoxide. These results coincide well with known biomass burning activity in the region. However, the high contribution of coal combustion was unexpected and our analysis showed it to be ubiquitous throughout the cruise. Selenium, a tracer of coal combustion, displayed a slight increase towards the end of the cruise, possibly due to a coal-fired power plant near Manila Bay. Understanding sources is key to characterizing the aerosol environment in the SCS and its relationship with cloud behavior and precipitation patterns in the region.

AS42-D5-AM2-308-011 (AS42-A019)
Impact of Crop Residue Burning on Air Quality Over China Based on Satellite Data and Field Observations
Meng FAN#+, Liangfu CHEN, Shenshen LI, Mingmin ZOU, Jinhua TAO
Chinese Academy of Sciences, China
#Corresponding author: +Presenter

Emissions of fine aerosol particles and gaseous pollutants from biomass burning, including forest/savanna fires and crop residue burning, significantly contribute to the severe degradation of regional air quality, the change of global climate, as well as human health. As a large agricultural country, China faces large-scale burning of crop stubble in the field during the harvesting, post-harvesting and pre-harvesting periods. In China, especially in recent decades, straw burning played a noticeable role in the sudden and extreme haze episodes that combined with the primary and secondary pollutants derived from the industry pollution, engine exhausts and coal combustion. In this study, MODIS and VIIRS data were used to derive crop residue burning spots. And the spatio-temporal variation characteristics of crop residue burning over China for a long time were investigated. Because air quality data in China began to be monitored in 2012 only in important regions,such as the Jing-Jin-Ji region, the Yangtze River Delta Region, the Pearl River Delta Region and provincial capitals. Daily air quality data since 2012, including PM2.5, PM10, O3, NO2, SO2 and CO, were obtained from China's National Environmental Monitoring Center (CNEMC). The Kriging method was applied for analyzing the spatial distribution of PM2.5, PM10, O3, NO2, SO2 and CO during the period from 2012 to 2016. Finally, the daily crop residue burning and air quality data were used to analyze their spatial and temporal relationships. Our results showed that crop residue burning is close related to PM2.5 change in summer, China's middle-east and autumn-winter, China's northeast, they showed a spatial consistency during these two periods. In autumn-winter, crop residue burning can effectively induce the PM2.5 increase in China's northeast, and it is more obvious than summer crop residue burning because of the special weather condition, different crop residue and other sources of PM2.5.

AS42-D5-AM2-308-012 (AS42-A026)
The Utilization of Satellite Observations for Improving Global Aerosol Forecasting
Sarah LU1#+, Shih-Wei WEI1, Xiaoyang ZHANG2, Shobha KONDRAGUNTA3, Sheng-Po CHEN1, Qiang ZHAO3, Jun WANG3, Partha BHATTACHARJEE3, Jeff MCQUEEN3
1 University at Albany, State University of New York, United States, 2 South Dakota State University, United States, 3 National Oceanic and Atmospheric Administration, United States
#Corresponding author: +Presenter

Aerosol modeling, traditionally serving regional air quality and climate communities, has seen rapid development at several operational and research NWP centers in the last few years. The development of global aerosol forecasting capability allows aerosol impact on weather forecasts and climate prediction to be considered. In addition, it enables the NWP centers to provide quality atmospheric constituent products, serving the stakeholders such as health professional, policy makers, climate scientists, and solar energy plant managers.

Satellite observations have been utilized extensively to improve aerosol forecasts. This includes: (1) routine monitoring of model performance, (2) the use of near-real-time biomass burning emissions from satellites, and (3) data assimilation of satellite aerosol observations. This study compared model results with versus without using near-real-time smoke emissions and document the performance gain resulted from satellite emissions information. We then investigate the effects of aerosol data assimilation on improving the initial conditions for aerosol forecast. The model we use is NOAA global aerosol system, NEMS GFS Aerosol Component (NGAC). Real-real-time smoke emissions are blended from MODIS and multiple geostationary satellites. Satellite products we assimilated are VIIRS aerosol optical depth.

Poster Presentations

  AS42-D3-PM1-P-013 (AS42-A003)
Information Content Analysis of Space-Borne Polarization Measurements for Aerosol Retrievals
Weizhen HOU+, Zhengqiang LI#, Xingfeng CHEN, Lili QIE
Chinese Academy of Sciences, China
#Corresponding author: +Presenter

Based on the optimal estimation (OE) theory and corresponding framework of inversion algorithm, the information content of multispectral polarization measurements are assessed for retrieving the aerosol properties. Following the setting of multispectral polarized bands, the synthetic data at the top of atmosphere (TOA) and Jacobians of TOA reflectance with respect to the aerosol parameters are calculated by the forward model UNL-VRTM for various aerosol scenarios and surface types. In the information content analysis, 5 polarized bands including 490, 670, 865, 1610 and 2250nm are considered, and the coarse-mode particle size distribution and refractive index are assumed have been known with a priori error, as well as the predefinition of bidirectional polarization distribution function (BPDF). It is found that at least 4 degrees of freedom for signal (DFS) of retrieved aerosol parameters could be obtained. For the fine-dominated aerosol model, the information content could well satisfy the retrieval of fine-mode volume concentration, effective radius, effective deviation and the real part of refractive index. While for the coarse-dominated aerosol, except for those 4 fine-mode parameters, the coarse-mode volume concentration also could be retrieved. Besides, if the dart target (DT) algorithm is integrated with the polarized measurements by TOA radiance measurements over dark target for aerosol retrieval, the fine-mode imaginary part also could be retrieved with enough information content for fine-dominated aerosol case. The findings of this study have important implication of our development of aerosol retrieval algorithm for further-launched Space-borne sensors with polarization measurements.

  AS42-D3-PM1-P-014 (AS42-A008)
Air Particulate Matter (APM) Emissions from Agricultural Waste (Rice Straw) Burning in the Philippines: Emission Factor Testing and Estimation of Nationwide PM2.5 Emissions
Hezron GIBE#+, Mylene CAYETANO
University of the Philippines Diliman, Philippines
#Corresponding author: +Presenter

The practice of burning agricultural waste material, such as rice straw and other residue from the harvesting process, is a common method of farmland management in the Philippines. While other methods exist such as incorporation of biomaterial into the soil between planting seasons, burning is a common enough practice that it requires attention. Rice straw burning is a considerable source of air pollutants such as organic carbon, greenhouse gases (carbon dioxide and methane), as well as particulate matter. Initiatives have been made by local research institutions to encourage farmers to avoid rice straw burning and adopt more environmentally sound approaches to agricultural waste management. This study presents a view of the current situation of particulate emissions generated by burning of rice straw as agricultural biomass waste in the Philippines. A component of this study is the laboratory testing of emission factors. The amount of PM2.5 generated from burning of rice straw was measured in a wind tunnel setup with a Minivol sampler. Samples were ran through gravimetric and elemental analysis to determine their mass and composition. In addition, this measured emission factor was used as a component with other factors, such as the amount of rice straw produced in the various regions of the country, and reduction factors involving other non-burning methods of agricultural waste management. They were used to estimate the amount of possible PM2.5 emissions generated by this activity across different regions of the Philippines using a spatial approach by mapping emissions across several provinces and regions. The results of this study are expected to be a reference for local research and government institutions to facilitate further developments in the reduction of air pollution generated from burning of agricultural waste, and to promote awareness of the importance of air quality management in smaller cities.

  AS42-D3-PM1-P-015 (AS42-A014)
Volatile Organic Compound Emissions in South China Sea/East Sea During the 2011 Vasco Cruise: Emission Ratios and Source Apportionment
Gabrielle Frances LEUNG1#+, Annelle Raphayette CHUA1, Maria Obiminda CAMBALIZA1,2, Melliza CRUZ2, Jeffrey REID3, James SIMPAS2, Nofel LAGROSAS2,4, Donald BLAKE5, Sherdon Niño UY2
1 Ateneo de Manila University, Philippines, 2 Manila Observatory, Philippines, 3 Naval Research Laboratory, United States, 4 Chiba University, Japan, 5 University of California, Irvine, United States
#Corresponding author: +Presenter

As part of the Seven Southeast Asian Studies (7SEAS) program, a two-week cruise in the Northern Palawan region of South China Sea/East Sea (SCS/ES) was conducted in late September of 2011 to observe the behavior of atmospheric aerosols. The region has complex meteorology and is known to be a receptor of biomass burning and various anthropogenic sources nearby, which makes emission sources difficult to identify directly. During the field campaign, whole air samples were collected and later analyzed for more than 60 trace gases, including volatile organic compounds (VOCs). In this paper, emission ratios with respect to carbon monoxide (CO) are determined via regression analysis.  Using this method, the emission ratios for eight VOCs (ethane, ethyne, benzene, CH3Cl, CH3I, BuONO2, 3-ONO2, 3-Methyl-2-BuONO2) are found to have significant correlation (R2 > 0.6) with CO. Positive Matrix Factorization (PMF) is applied on the collected VOC data to identify the sources contributing to the observed aerosol emissions. Overall, six factors are identified from the PMF analysis: biomass burning (19.2%), urban emissions (48.4%), industrial emissions (8.48%), ships (7.94%), marine emissions (10.6%), and a mixed source (5.35%). HYSPLIT ensemble backtrajectories of sampling  points within identified biomass burning plumes suggest a source around the island of Kalimantan. However, some backtrajectories outside the plumes show sampled air masses originating above the boundary layer, which suggests other long range transport sources. Emission ratios with CO as initially calculated from measured data are compared to emission ratios calculated from the PMF-reconstructed biomass burning factor contribution. The latter method captures the former to within 12%. This noteworthy agreement between independent approaches increases our confidence in identifying and characterizing important aerosol sources in the region.

  AS42-D3-PM1-P-016 (AS42-A018)
Fine Particulate Matter During New Year from 2003 to 2017 Around Marikina Valley, Metro Manila
Genevieve LORENZO1#+, James SIMPAS1, Nofel LAGROSAS1,2, Melliza CRUZ1, Maria Obiminda CAMBALIZA1,3, Paola Angela BANAGA3, Jose Ramon VILLARIN3
1 Manila Observatory, Philippines, 2 Chiba University, Japan, 3 Ateneo de Manila University, Philippines
#Corresponding author: +Presenter

Fine particulate matter (PM2.5) levels have been observed during the New Year celebrations in Metro Manila to be maximum, hazardous to health, and almost six times the average PM2.5 concentrations. Twenty-four hour PM2.5 samples were collected on air filters using low volume MiniVol air samplers from 2003 to 2017 from five sites in and around an air basin (80 km2), the Marikina Valley, in Metro Manila that ranged from 43-567 ug/m3. The highest PM2.5 concentrations (4.7 times the background sites, which are located ~30 kilometers from the Marikina Valley) were measured in the northernmost site, Nangka, Marikina (6 out of 15 years) which is located in an area with the lowest elevation (18 m) in the valley, and upwind of the other sites. Prevailing wind directions, during the sampling period, from weather stations in and around Marikina Valley were from the north from 2013 to 2017. Hourly PM2.5 concentrations from 2012 to 2017 from continuous air samplers (Beta Attenuation Monitor, DustTrak, and Airbox Air Samplers) in Manila Observatory, Quezon City (7 kilometers downwind of Nangka, Marikina, and with 75 m elevation) show peak fine particulate concentrations (356 - >1000 ug/m3) one to three hours after the end of the fireworks and firecracker activities during the New Year revelry, when wind speeds were lowest, temperatures were decreasing and relative humidity levels were highest. Knowledge of the timing of emissions and contributory meteorological conditions, such as the case for New Year, will help in the forecasting of air pollution episodes in Metro Manila, where average fine particulate levels are already unhealthy.

  AS42-D3-PM1-P-017 (AS42-A024)
Global Evaluation of MODIS 10km Aerosol Product Over Land
Qingxin WANG+, Yanfang MING#, Lin SUN, Jing WEI, Ruibo LI, Yikun YANG
Shandong University of Science and Technology, China
#Corresponding author: +Presenter

The operational MODIS aerosol products (MOD04) provide global dairy distribution of aerosol optical depth (AOD) at 10 km spatial resolution and have been widely used in air pollution research from local to global scales. The Dark Target (DT) and Deep Blue (DB) algorithms are two main aerosol retrieval algorithms. MOD04 has been updated to the latest Collection 6 (C6) version with improvements on the retrieval algorithm and quality controls and provides both DT and DB AOD datasets. Thus, quantitative analysis and evaluation of MODIS AOD products have great significance for the users to make a reasonable choice of different aerosol products in different research fields. In this study, accuracy of the MOD04 aerosol products were validated using the AERONET ground-based AOD measurements from a total of 172 sites over the land surfaces. The AOD retrievals under different surface reflectance ranges and aerosol types are also validated. Results showed that showed that 1) Both DT and DB AOD retrievals are well correlated with AERONET AOD measurements with 61.27% and 67.94% of the AOD collections falling within the Expected Error (0.05±0.15*AERONET), however, the DB retrievals show approximately less 18.7% of overestimation uncertainly than DT retrievals. 2) The accuracy of DT and DB algorithms decreases obviously with the increasing surface reflectance. 3) Both DT and BD algorithms show high accuracy in the weakly absorbing aerosol regions, whereas show poor accuracy in the continental and dust aerosol regions.