Hurricane Michael in 2018 was one of the strongest storms to impact the coastal U.S. and was unusual given that it occurred in October (i.e., late in the hurricane season) and intensified over the continental shelf. A potential contributor to this extreme event was thought to be anomalously high heat content on the shelf of the Mississippi Bight, a shelf region significantly impacted by freshwater discharge. Using available long-term time series of regional meteorological and oceanic measurements, water column conditions during the run-up to the rapid intensification of Hurricane Michael were compared to historical conditions in the region. Data for the water column heat content in the western Mississippi Bight were available at a mooring site on the 20 m isobath (Site CP) during August-October of 2018. Unusually high heat content was observed, relative to the typical summer conditions of previous years (N = 13), which resulted from the compounding effects of atmospheric events in the preceding months (August and September): a series of smaller mixing events (e.g., passage of Tropical Storm Gordon) in conjunction with a regional heatwave during most of September. Tropical Storm Gordon traveled across the shelf of the Mississippi Bight, disrupting the stratified water column as observed at Site CP. The stratification breakdown mixed the upper water column heat content deeper into the water column and subsequently allowed for the anomalously warm atmospheric conditions in September to effectively transfer heat deeper into the water column. While the mooring site was significantly distant (250 km) from the center of Hurricane Michael, these processes observed in the western Mississippi Bight likely occurred in the eastern portion of the basin as well. As a result of these compounding atmospheric effects, the shelf water column was primed to support the intensification of following tropical storms, which highlights the need for coupled oceanic-atmospheric forecast models to capture the interaction between the ocean and atmosphere and its effect on water column conditions on the shelf.

Smoke influence in urban areas is relatively easy to detect at high concentrations, but more challenging to detect at low concentrations. For this reason, we have evaluated an approach using thermal desorption gas chromatography mass spectrometry (TD-GC-MS) to detect volatile organic compounds (VOCs) in particular oxygenated VOCs in urban areas. The goal of this work is to develop a method that can reliably quantify smoke tracers in an urban environment at relatively low cost and complexity. We present here the development and validation of a double-bedded thermal desorption tube with an auto sampler to collect continuous samples of VOCs. To evaluate the method performance, we have tested stability during storage, interferences (e.g., water and O3), and reproducibility for six VOCs, namely, acetonitrile, acetone, pentane, iso-pentane, benzene, and toluene. The results demonstrate that these can be quantified reproducibly with an error ≤ 20% between the collection and analysis with a storage time of up to 21 days. For acetone, similar results were obtained until day 14. Calibration experiments performed over a dynamic range of 10–150 ng loaded over thermal desorption tubes at different relative humidity showed excellent linearity (r2 ≥ 0.91). At this time, we are utilizing this method during the summer 2019 FIREX-AQ intensive experiment at the Boise ground site in Idaho. These results will be presented along with the quality control data.

The Bureau of Reclamation serves water to 31 million people and 20 percent of irrigators in the western United States. Reclamation generates large amounts of data and information describing reservoir operations, hydropower generation, environmental compliance, invasive mussels, infrastructure, and other aspects of Reclamation’s mission activities. Much of these data are currently accessed on a program-specific basis via legacy information management & technology (IMT) systems, often without modern features such as machine-readable data formats and web-services. The Department of the Interior’s Open Water Data Initiative addresses these issues, and Reclamation is striving to improve its data-publishing efforts, making its data more easily found, accessed, and applied to support public and private sector activities. This presentation provides an overview of two IMT systems that Reclamation has developed under OWDI: the Reclamation Water Information System (RWIS, water.usbr.gov) and the Reclamation Information Sharing Environment (RISE). RWIS was developed first as a pilot, demonstrating how multiple programs’ water data could be combined into a modernized data-publishing system. It provides free access to reservoir and water time series data from Reclamation’s five regions, includes map and query interfaces for data discovery and access, and web-services for automated retrieval. Based on the success of the RWIS pilot, Reclamation has more recently focused on developing RISE, which will envelop RWIS and feature a much larger collection of Reclamation data, including water quality as it pertains to Reclamation water management activities, invasive mussels, hydropower, and infrastructure, and more. RISE will also serve a mix of data types, going beyond RWIS’ scope of time series data to also include geospatial and documents data. This presentation summarizes RISE development approach, architecture and previews the upcoming release in Winter 2019.

The state of the practice for large area land cover mapping is based on the application of supervised classifiers to multi-temporal multi-spectral optical wavelength data. Deep learning approaches have been developed but are typically applied to individual images with less research on their application to satellite time series. The recent availability of 30 m Landsat analysis ready data (ARD) has significantly increased the ease of using Landsat data. Irregular gaps in the Landsat image time series reduce the easy application of deep learning to time series. This study proposes a novel solution based on a two dimensional (2-D) array (one spectral dimension and one temporal dimension) derived at each ARD pixel time series and using the 2-D convolutional neural network (CNN) deep learning algorithm. Classification results are presented for all of the Conterminous United States (CONUS) considering a year of Landsat 5 and 7 data. The 30 m USGS National Land Cover Database (NLCD) (15 classes after filtering) and USDA Crop Data Layer (CDL) (22 classes after filtering) products are filtered conservatively across the CONUS and sampled to construct >3.31 and >0.48 million training pixels respectively defined with reliable accuracy and reduced spatial autocorrelation. The CNN and a conventional Random Forest (RF) classifier are trained using 10%, 50% and 90% of the training samples, and used to classify the remaining samples. Classification experiments are undertaken independently using the NLCD and CDL training data. Different CNN structures with different learnable coefficients are used and the accuracy results compared with conventional RF results. The main findings were (1) application of the CNN with different structures provided only about 1% accuracy difference, the optimal CNN structure was dependent on the number of training samples, and increasing the number of CNN learnable coefficients beyond the number of training samples was not helpful; (2) although the CNN training time was up to two orders of magnitude slower than the RF, the classification time was an order of magnitude faster, (3) the CNN provided 2-5% higher accuracy than the RF which is notable given the large number of classes and that the overall classification accuracies were >80%.

The Achankovil Shear Zone (AKSZ) is a NW-SE trending ductile shear zone passing through the Southern Granulite Terrain (SGT) has remained enigmatic among scientific community for the perspective of shear zone status and extension. While some consider the AKSZ to represent a Pan African terrain boundary between the Trivandrum block (TB) in the Kerala Khondalite Belt (KKB) and Madurai block (MB) of the SGT (Drury et al. 1984; Santosh, 1987; Harris and Santosh 1994; Santosh et al. 1992, 2005, 2006; Guru Rajesh and Chetty, 2006; Sreejith and Ravindra Kumar, 2013) that can be traced in to now- dispersed crustal fragments of Madagascar and Sri Lanka (Braun and Kriegsman, 2003; Guru Rajesh and Chetty, 2006; Santosh et al. 2009, Sreejith and Ravindra Kumar, 2013). Others consider MB and TB evolved coherently and AKSZ to be a high strain zone (MB is the continuation of TB) within the SGT (Ghosh et al 2004). Detailed structural field work across the SGT suggests that MB and TB are two different blocks and the lineament occurs between these two blocks is the Achankovil Shear Zone (AKSZ). Tracing the paleo-sutures across the rifted crustal fragments is an important method for the reconstruction of the pre-drift crustal assembly. For tracing paleo-sutures detailed structural evolutionary studies are necessary. Available data suggest that the middle and central crustal domains of the present day landmass of Madagascar was with India vis-à-vis East Gondwanaland (comprising India, Australia and Antarctica) that accreted with the West Gondwanaland (comprising Africa), during Late Neoproterozoic and Early Paleozoic (Tucker et al., 1999; Sommer et al., 2003; Collins, 2006). Geologists correlated the AKSZ of India with different major and minor shear zones present in the southern Madagascar, for example Ranotsara shear zone (RSZ), Tranomaro shear zone (TSZ), Angavo shear zone (ASZ) etc. (Tucker et al., 1999; Raharimahefa and Kusky, 2006, 2010; Sajeev et al., 2009; Tucker et al., 2011a, b). Monazites analyzed from the Antananarivo block maintained Neoproterozoic age of 796Ma (Cenki Tok et al, 2016) and also the Imorona–Itsindro Suite of central Madagascar represents 850–750 Ma magmatism (Zhou et al, 2015; Archibald et al, 2016) which is similar to the chronology of Madurai block, SGT. Age of Androyan group (Southern Madagascar) ranges from 560-530 Ma (Jons & Schenk, 2011) obtained from monazites which is similar to the chronology of Trivandrum block, SGT. Taking the arguments a step further, we argue the extension of AKSZ of SGT towards the RSZ of Madagascar which is consistant with the suggestion by Windley et al. 1994; Markl et al. 2000; Cenki et al. 2004; Jons & Schenk, 2011; Zhou et al, 2015; Archibald et al, 2016 based on structural studies and chronology.

Deep convective storms assume many intensities, sizes and morphologies in Earth’s atmosphere, reflecting varying balances of the competing forces that arise in the diverse atmospheric conditions that promote and support such storms. The understanding of how these forces compete with each other lends itself only with great difficulty to observational study, but much more easily to idealized parameter space studies using numerical models. A parameter space study was recently designed and executed using an eight-dimensional framework, with 2-h experiments run using all possible combinations of reasonably chosen high and low values of the eight independent parameters. The basic parameters are those needed to build an idealized vertical profile of temperature, moisture and wind: bulk convective available potential energy (CAPE), radius of an assumed semicircular hodograph, shape of the buoyancy profile, shape of the shear profile, lifting condensation level, level of free convection, cloud-base temperature (roughly equivalent to total precipitable water), and free tropospheric relative humidity. Each of the parameters is found to exert noteworthy independent impacts on the intensity and morphology of the convection, with drastic differences in updraft overturning efficiency (the ratio of simulated peak updraft speed to that predicted from pseudoadiabatic parcel theory), updraft rotation, updraft steadiness and precipitation efficiency. Storm rotational efficiency relative to ambient vertical shear, and its steadiness, may also be examined. Results will be shown that demonstrate the strongly patterned convective response within this large parameter space, for both updraft overturning and rotational efficiency and their temporal steadiness. For example, in experiments having CAPE = 2000 J/kg, peak updraft efficiency reaches 94% in some cases, while in others with unfavorable combinations of parameters, that peak is less than 20%. While the eight basic parameters used in this study cover most of the variability of the vertical meteorological structure of the convective atmosphere, the framework can easily be expanded by adding new dimensions to deal with other physical effects, such as varying types and distributions of aerosols and other tracers that influence atmospheric chemistry.

Over-pumping and extended drought events have raised awareness on groundwater resources management within the Mediterranean Basin. As groundwater often has an important role in sustaining certain types of aquatic, terrestrial and coastal ecosystems, water policy makers should pay special concern to maintain groundwater contribution to the environmental flow. To this aim, the present study focuses on the assessment of a newly introduced groundwater management tool, the Groundwater Footprint (GWF) (Gleeson et al., 2012). GWF represents a water balance between aquifer inflows and outflows, focusing on environmental flow requirements and expresses the area required to sustain groundwater use and groundwater dependent ecosystem services. GWF is applied to a pilot aquifer in the Mediterranean Basin, crossed by an intermittent river. Total abstraction, natural and artificial recharge, groundwater contribution to environmental stream flow are the critical parameters related to GWF estimation. In order to estimate groundwater contribution to the environmental stream flow, the assumption that groundwater contributes to the environmental flow to the same percentage as baseflow contributes to the natural flow has been made. However, the main constraint met in GWF estimation has been the estimation of the environmental flow in non-perennial river, as the quantification of the environmental flow requirements has been mainly studied for perennial rivers. For this reason, the available to the literature studies referring to environmental flow requirements have been assessed and the most appropriate method for the specific pilot area has been applied. The ratio GWF to the actual area of the aquifer (A) can be used to assess groundwater management, as GWF/A>1 indicates unsustainable groundwater consumption. Consequently, GWF/A may consist a comprehensible to the general public groundwater stress indicator and can be used to raise awareness.

The core argument is that there may be a right to some of the knowledge that astrobiology can supply about the origins of life, and specifically about our human origins. Such a right might be appealed to in international agreements and declarations by bodies such as the UN.

Himalaya is one of the most seismically active and earthquake-prone regions of the world. Recently an Earthquake Early Warning System (EEWS) for Northern India has been developed which includes around 165 strong ground motion accelerometers installed in Uttarakhand (India). A timely earthquake early warning of few seconds can save people’s lives and thus the development of an improved Warning Dissemination System (WDS) component of EEWS is much required. For this purpose, an improved WDS has been developed. This system currently uses newly designed low-cost public sirens and smartphone apps to alert people in case of an earthquake. The developed sirens have been currently installed in two major cities of Uttarakhand (India) and in all district emergency operations centers for the last 2 years. On 4th August 2021, the newly developed app “Uttarakhand Bhookamp Alert” for WDS has been officially launched by the Uttarakhand State Disaster Management Authority for operational use. Further, a GIS-based maintenance system is also developed for the maintenance of the complete system, which automatically checks the health and keeps records of the sirens along with the smartphone users. This app gives the facility to the users for sharing their current location with disaster rescue teams after the earthquake early warning alert. Detailed scientific principles and working mechanism of newly developed dissemination system along with its applicability to disseminate the real-time information in case of an earthquake will be presented.

Polygonal Fault Systems (PFS) are an enigmatic class of small non-tectonic extensional faults. PFS are predominantly hosted in fine-grained sedimentary tiers and are prevalent along many continental margin basins. The genesis of PFS is widely debated and little is known about the timeframe for polygonal fault growth. We present the first measurements of throw rates for polygonal faults by measuring the vertical offset of seven age-calibrated horizons mapped using three-dimensional seismic reflection data from the Norwegian Sea. Individual polygonal faults exhibit a range of throw rate profiles through time, ranging from near linear to singly or multiply stepped. The stepped profiles have a range of short-term throw rates ranging from 0 to 18 m/Ma. Time-averaged throw rates of 180 polygonal faults over the entire 2.61-0 Ma interval are normally distributed and range between 1.4-10.9 m/Ma. We convert our PFS throw rates to displacement rates and compare these to published displacement rates for gravity driven and tectonic normal faults. We find that the displacement rates of polygonal faults mark the lower limit of a continuous spectrum of extensional fault displacement rates; they are up to two orders-of-magnitude slower than gravity-driven faults, and up to three orders-of-magnitude slower than the fastest growing tectonic faults. We attribute the ultra-slow kinematic behaviour to the non-tectonic nature of polygonal faults where throw accumulates primarily through dewatering of the largely fine-grained sediments comprising the host layers for the PFS, and differential volumetric strain between the fault footwalls and hangingwalls.

Sand production is the process in which formation sand and gravel would migrate into the wellbore by the flow of reservoir fluids. This is a problem that endangers the safety of hydrate exploitation. The aim of this study is to understand sand production in during hydrate exploitation. A novel experimental apparatus was constructed to examine sand production in the hydrate-bearing sediments by applying the depressurization method. The maximum pressure of apparatus is 30 MPa, the temperature could be controlled from -253.15 to 313.15 K. The pore pressure, crustal stress, production pressure, gas flow rate, water production volume and subsidence rates could be measured. The vertical wellbore comprised liner 1 (ø32 mm × 135 mm, 3 mm holes, arrangement: 36°, holes row gap: 10 mm) and liner 3 (ø24 mm × 135 mm, 2.5 mm holes, arrangement: 36°, hole row gap: 10 mm) with a sand screen. Besides gas in from top, the sediment chamber (ø158 mm × 120 mm) had a middle mesh screen that allowed gas and water enter or vacuumize the chamber circumferentially around the sediments (ø158 mm × 100 mm). Sand production situation was recorded by HD camera through the visual window on the gas-solid-liquid separator. Hydrate production was divided into three periods: water, gas with water drops, and gas. We found fine sand production in the first period and sand grains production in the second. The sand production behaviours through the different gas production rates in two production method - depletion gas production curve and stable gas production curve were discussed. The grain sizes of sand production were increasing in the production period with hydrate saturation decreasing. The temperature related characteristics of the hydrate layers differed during different stages of hydrate production. The unique sputtering occurring owing to the decomposition of the hydrate might have provided the driving force for sand migration, and water gas bubbles or gaseous water drops from the decomposed hydrate might have enhanced sand carrying capacity. The subsidence of hydrate-bearing sediments was influenced by sand production, whereas the maintenance of crustal stress possibly influenced the rate and magnitude of subsidence. The stimulation at late production in low hydrate saturation might conduct the subsidence and sand production increased dramatically.

Over the last decade, the opportunistic use of broadband Ocean Bottom Seismometer (OBS) recordings has been extremely beneficial for baleen whales studies as they regularly record their stereotyped calls ([10-40] Hz). Often deployed in remote areas, OBSs offer additional and often unprecedented locations for acoustic data collection. The long-term, widespread networks are then ideal for passive acoustic monitoring. Therefore OBS-recorded data are crucial to conservation purposes from monitoring their post-exploitation recovery to improving our understanding of these endangered species and threats. As an example of the potential of OBSs for baleen whale studies, this work exploits data collected by the RHUM-RUM (Réunion Hotspot and Upper Mantle - Réunions Unterer Mantel) seismic network. It aimed initially at imaging the mantle structure beneath the Western Indian Ocean and the dynamics of La Réunion volcanic hotspot. To that extent, 57 OBSs were deployed on the ocean floor, covering an area of 2000x2000 km2 (Lat. 16-34°S, Long. 048-070°E), from October 2012 to November 2013. The RHUM-RUM data provides the second opportunity to record species-specific or regionally-distinct signals of Blue Whales (BWs; Antarctic and Madagascar Pygmy BW) within the Western Indian Ocean Sanctuary. BW calls can propagate from tens to hundreds of kilometers. Consequently, results show that recordings from a single OBS are sufficient to determine the acoustic presence of a species and estimate the range of a calling individual. However, the data analysis benefits from the use of automatic and reliable detection processes. Additional information arises from increasing the number of sensors: a small array of the RHUM-RUM network (20km inter-sensor distance) is used for localization and tracking, essential for animal counting. Besides, the broader configuration showed repartition and migration patterns of the studied species. These recordings from the bottom of the ocean shed new light on the study of BWs and, more generally, low-frequency sounds in this area.

Volcanic aerosol forcing has been reported in the literature to be less effective in changing the earth’s surface temperature than CO2 forcing. This implies a different feedback strength, and therefore different contributions from individual feedback mechanisms. We employ the CMIP6 version of MPI-ESM to understand the reasons for these apparent differences in the ability to change the surface air temperature. Using a highly idealized eruption scenario and comparing it to a doubling and a halving of CO2 concentration, we identify key reasons for changes in the magnitude of the feedback parameter. We show that the “efficacy” [Hansen et al. 2005] of volcanic aerosol forcing depends strongly on the method and the time scale used to calculate it. We argue that the seemingly established result of a lower-than-unity efficacy of volcanic aerosol forcing might only hold under the specific methodological choices other authors have made, but not in general. Furthermore, we find qualitative differences between the cooling and warming simulations, but strong similarities between the 0.5xCO2 and the idealized eruption cases. This hints towards processes, which are not forcing agent-specific, but specific to the sign of the forcing. A pronounced curvature in the N(T) plot (“Gregory plot”) for the cooling scenarios makes the computation of feedback through regression even more sensitive to subjective choices than in the 2xCO2 case. We disentangle the role of ocean heat uptake efficacy and atmospheric feedback processes in the framework of the pattern effect.

NOAA/National Ocean Service’s (NOS) Center for Operational Oceanographic Products and Services (CO-OPS) provides users with real-time currents at more than sixty stations, currents predictions at thousands of historic and active stations, and operational currents nowcast and near-term forecast information in navigable estuaries, harbors, rivers, and coastal regions of the United States as an integral part of its safe navigation mission. CO-OPS performs at least one current survey each year to update currents predictions in regions of particular interest to stakeholders. NOS’ Operational Forecast Systems (OFS) operate and maintain fully 3-D hydrodynamic models that provide regional nowcast and forecast (48-60 hours) guidance for water levels, currents, salinity, and temperature. By combining the information available from real-time observations, current surveys, historic current predictions, and OFS output, both the tidal current predictions and the OFS forecast products can be improved. Tidal current predictions are traditionally generated based on analysis of at least one month of six-minute observation data obtained from a physically deployed current meter using harmonic least squares techniques to resolve tidal constituents. By using longer time series and traditional techniques combined with additional statistical methods, a more accurate representation of the tidal flow and a more exact match to the shape of the tidal current curve is obtained. By applying these methods to long-term OFS output at locations where long-term physical observations also exist, tidal current predictions based on model data within the model domain can be verified. Once verified, the number of available “virtual stations” exponentially increases the repository of tidal current predictions. Users can choose any location of interest and receive tidal current predictions that can be incorporated into integrated, user-friendly navigation products and tools. We will evaluate this technique in the lower Chesapeake Bay using output from the Chesapeake Bay Operational Forecast System (CBOFS) and real-time currents data.

Departures from standard spherically symmetric solar models, in the form of perturbations such as global and local-scale flows and structural asphericities, result in the splitting of eigenfrequencies in the observed solar spectrum. Here we describe new theoretical developments that enable the computation of sensitivity kernels for frequency splittings (a coefficients) due to general Lorentz stresses in the Sun. We draw from theoretical ideas prevalent in normal-mode coupling theory in geophysical literature to build these kernels. We plot the Lorentz-stress kernels and estimate the a-coefficients arising from a combination of deep-toroidal and surface-dipolar fields (although we note that this could equally well be substituted by another choice of Lorentz stresses). These results pave the way to formally pose an inverse problem, and infer magnetic fields from the measured even a-coefficients.

Areas of Jupiter’s moon, Europa, contain irregular ice floes that are illustrative of the massive disruption, reorientation, and refreezing experienced on Europa’s surface as Jupiter’s gravity imparts immense tidal forces that heat the moon. In recent years, various machine learning programs have been used to detect surface features on planetary bodies. Most commonly, such software works to count craters for estimating planetary surface age or to map sand-filled dune fields whose shapes may indicate wind or weather patterns. Creating software to automatically detect Europa’s jigsaw-like ice floes will accelerate scientific analysis of such terrains once higher resolution images of the moon arrive in the fall of 2022 from the Juno spacecraft and later from the forthcoming Europa Clipper mission. In this project, a U-net, a deep learning semantic segmentation model, was applied to images of the surface of Jupiter’s moon Europa taken by the Galileo spacecraft to detect ice floes in the moon’s Chaos Terrains. To measure the quality of the program developed, the Intersection over Union (IoU), a metric that measures the goodness of fit for semantic segmentation, was calculated. Throughout the course of the project, the IoU increased from a value of 0.0012 to 0.286 by adjusting hyperparameters including learning rate and epochs. Adjusting how the data was labeled also improved performance, functioning best when ice floes were hand-labeled using loose-fitting polygons rather than exact edge-mapping. As Galileo faced transmission issues, the usable dataset was limited to 23 images, 19 of which were used for training and 4 for testing. In the coming months, higher quality augmented data should provide additional training images that should further improve the performance of the U-net. Once the algorithm is sufficiently capable of identifying floes in the Chaos Terrains, it may later assist in selection of regions of interest for further study on Europa or even landing sites for a future proposed lander.

Over the past 60+ years, an enormous amount of exploration geophysics survey data has been collected around the globe, the majority of which is high-quality 2D and 3D seismic data acquired by the petroleum energy industry. Much of this ‘legacy’ data still has significant commercial value today and in the future, for hydrocarbon exploration, gas storage (methane, helium, hydrogen…), groundwater, minerals, CO2 sequestration, geothermal, and other purposes. However, there is likely a subset of this exploration data that is of little further commercial value, but may be of immense value to academic, government and industry researchers, for example. This may include very long 2D seismic lines recorded in frontier exploration areas which turned out to be non-prospective; for example along convergent margin subduction zones or major continental tectonic fault zones, which are absent of major sedimentary basins. Shared access to this subset of legacy data would provide an extremely useful opportunity and resource for academic researchers and others, much as shared earthquake data via the IRIS network has revolutionized our understanding of earthquakes, faults and tectonics. There are several challenges that would need to be overcome before such legacy data can be shared widely among the broader geophysical community. Much of this legacy data is archived on old magnetic tape media that is now physically degrading, making it difficult to recover the data. The data would need to be collected, recovered, QC’ed, archived with associated metadata, and stored on modern digital data storage systems like the IRIS DMC, newer cloud-based systems like OSDU, or other options. The data archival, maintenance and support for a shared data distribution system would require a sustainable business model and funding from all of the data stakeholders, including government agencies like NSF, academic universities, and industry users. Data use agreements would need to be structured to ensure that data is used for non-commercial purposes as appropriate, data users respect various legal terms and conditions, and data is not shared freely among individual recipients without the approval of the host data center.

The dithiothreitol (DTT) assay is widely used to characterize the Oxidation Potential (OP) of atmospheric particulate matter (PM), which can cause adverse effects on human health. However, it’s under debate which chemical species determines the consumption rate of DTT. During January and April 2018, we measured the improved DTT assay of daily PM2.5 samples collected in Guangzhou, China with complimentary measurements of water-soluble ions, organic/elemental carbon (OC/EC) and metal elements. The average sampled air volume normalized consumption rate of DTT (DTTv) was 4.67 ±1.06 and 4.45 ± 1.02 nmol min-1 m-3, in January and April, respectively while the average PM2.5 mass normalized consumption rate of DTT (DTTm) was 13.47 ± 3.86 and 14.66 ± 4.49 pmol min-1 μg-1. Good correlations were found between DTTv and concentration of PM2.5, OC, and EC while no correlation was found between DTTm and concentrations of water-soluble ions, OC, EC or metal element, which is consistent with most early observations. We also evaluated the contribution of soluble metals to DTT assay by addition of EDTA, a strong metal chelator. We found that nearly 90% of DTTv and DTTm were reduced by EDTA, suggesting a dominant role of soluble metals in determining the response of DTT to ambient PM2.5. Based on responses of DTT to soluble metals in literature, we found that Cu(II) and Mn(II) are the major contributors to OP of PM2.5 in Guangzhou. The correlation coefficient between DTTm and OC shows a clear increase after addition of EDTA, implying that the response of DTT to quinones is not strongly suppressed by EDTA.