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Shrivastava, Manish

Publications and source records attributed to Shrivastava, Manish.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Formation of secondary organic aerosol from wildfire emissions enhanced by long-time ageing

Wildfire smoke, consisting primarily of organic aerosols, has profound impacts on air quality, climate and human health. Wildfire organic aerosol evolves over long-time photochemical oxidation due to the formation and ageing of secondary organic aerosol, which substantially changes its magnitude and properties. However, there are large uncertainties in the long-time ageing of wildfire organic aerosol because of the distinct ageing behaviours of the complex organic emissions. Here we developed an oxidation model that simulates the ageing of wildfire organic emissions in the full volatility range on a precursor level and integrated insights from single-species ageing and wildfire emissions ageing experiments and field plume observations to constrain the long-time ageing of wildfire organic aerosol. The model captured the enhancement of organic aerosol mass (2–8 times) and oxygen-to-carbon ratio (1–4 times) in the wildfire ageing experiments. It also reconciled a long-standing discrepancy between field and laboratory observations of the magnitude of secondary organic aerosol formation. The model indicated large emissions-driven variations in precursor contributions to secondary organic aerosol, which further evolve with long-time ageing. In conclusion, the estimated global wildfire secondary organic aerosol production (139 ± 34 Tg per year) was much higher than previous studies omitting or under-constraining long-time ageing.

58 GEOSCIENCES↗
DOE OSTI2024

Data associated with the manuscript “Radiative impact of record-breaking wildfires from integrated ground-based data” collected in Richland, Washington in September 2020

This data package is associated with the publication “Radiative impact of record-breaking wildfires from integrated ground-based data” submitted to Nature Scientific Reports (Kassianov et al., 2024). Data from ground-based measurements of shortwave and spectrally resolved irradiance and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges were assessed to quantify the radiative impact of the September 2020 wildfires that occurred in the Western United States. Data were collected in September 2020 by several ground-based instruments at the Atmospheric Measurements Laboratory (AML) located in Richland, Washington (46.3451, -119.2792). These data include (1) Aerosol Optical Depth (AOD); (2) spectrally resolved and shortwave (SW) irradiances; (3) backscatter profiles; (4) total sky images; and (5) near-surface ambient air temperatures.The data package consists of five sub-directories: (1) “AML_Ceilometer_”; (2)” AML_CSPHOT_”; (3) “AML_MFRSR_irradiances_”; (4) “AML_SW_irradiances_and_Temp_”; (5) “AML_TSI_images_”; and 6 files stored at the directory level, including the readme, file-level metadata file, and data dictionary. The file-level metadata file (the file ending in “_flmd.csv”) lists all files contained in this data package and descriptions for each. The data dictionary (the file ending in “_dd.csv”) describes each tabular column header’s unit, definition, and structure. Below are descriptions of each sub-directory:“AML_Ceilometer_” includes ceilometer data collected at the AML. These files contain the corresponding narratives of data. Details related to the ceilometer data can be found in Morris (2016). “AML_CSPHOT_” includes ascii files with high-temporal resolution (about 10-15 min) AML CSPHOT data and their daily-averaged counterparts. These two files contain the corresponding narratives of data. Details related to the CSPHOT data can be found in Gregory (2011). “AML_MFRSR_irradiances_” includes ascii files with the AML MFRSR-measured diffuse, normal, and total spectrally resolved irradiance. Details related to the MFRSR data can be found in Hodges and Michalsky (2016) and Koontz et al. (2013). “AML_SW_irradiances_+_Temp_” includes near-surface ambient air temperature and SW irradiances, namely direct normal, diffuse hemispherical, and total hemispheric (global), measured at the AML. These files also incorporate the corresponding narratives of data. Details related to the SW irradiances can be found in Andreas et al. (2018). “AML_TSI_images_” includes Total Sky Images (TSIs) collected at the AML. Details related to the TSI data can be found in Morris (2005).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Shift in Peaks of PAH-Associated Health Risks From East Asia to South Asia and Africa in the Future

Lung cancer risk from exposure to ambient polycyclic aromatic hydrocarbons (PAHs) is expected to change significantly by 2050 compared to 2008 due to changes in climate and emissions. Integrating a global atmospheric chemistry model, a lung cancer risk model, and plausible future emissions trajectories of PAHs, we assess how global PAHs and their associated lung cancer risk will likely change in the future. Benzo(a)pyrene (BaP) is used as an indicator of cancer risk from PAH mixtures. From 2008 to 2050, the population-weighted global average BaP concentrations under all RCPs consistently exceeded the WHO-recommended limits, primarily attributed to residential biofuel use. Peaks in PAH-associated incremental lifetime cancer risk shift from East Asia (4 × 10 –5 ) in 2008 to South Asia (mostly India, 2–4 × 10 –5 ) and Africa (1–2 × 10 –5 ) by 2050. In the developing regions of Africa and South Asia, PAH-associated lung cancer risk increased by 30–64% from 2008 to 2050, due to increasing residential energy demand in households for cooking, heating, and lighting, the continued use of traditional biomass use, increases in agricultural waste burning, and forest fires, accompanied by rapid population growth in these regions. Due to more stringent air quality policies in developed countries, their PAH lung cancer risk substantially decreased by ~80% from 2008 to 2050. Climate change is likely to have minor effects on PAH lung cancer risk compared to the impact of emissions. Future policies, therefore, need to consider efficient combustion technologies that reduce air pollutant emissions, including incomplete combustion products such as PAH.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Physics informed deep neural network embedded in a chemical transport model for the Amazon rainforest

Secondary organic aerosols (SOA) are fine particles in the atmosphere, which interact with clouds, radiation and affect the Earth’s energy budget. SOA formation involves chemistry in gas phase, aqueous aerosols, and clouds. Simulating these chemical processes involve solving a stiff set of differential equations, which are computationally expensive steps for three-dimensional chemical transport models. Deep neural networks (DNNs) are universal function approximators that could be used to represent the complex nonlinear changes in aerosol physical and chemical processes; however, key challenges such as generalizability to extended time periods, preservation of mass balance, simulating sparse model outputs, and maintaining physical constraints have limited their use in atmospheric chemistry. Here, we develop an approach of using a physics-informed DNN that overcomes previous such challenges and demonstrates its applicability for the chemical formation processes of isoprene epoxydiol SOA (IEPOX-SOA) over the Amazon rainforest. The DNN is trained with data generated by simulating IEPOX-SOA over the entire atmospheric column, using the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). The trained DNN is then embedded within WRF-Chem to replace the computationally expensive default solver of IEPOX-SOA formation. The trained DNN predictions generalizes well with the default model simulation of the IEPOX-SOA mass concentrations and its size distribution (20 size bins) over several days of simulations in both dry and wet seasons. The embedded DNN reduces the computational expense of WRF-Chem by a factor of 2. Our approach shows promise in terms of application to other computationally expensive chemistry solvers in climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Observationally Constrained Modeling of the Reactive Uptake of Isoprene-Derived Epoxydiols under Elevated Relative Humidity and Varying Acidity of Seed Aerosol Conditions

Isoprene is the non-methane volatile organic compound (VOC) emitted in largest amounts to the atmosphere, and it is a significant source of secondary organic aerosol (SOA) mass. The uptake of isoprene oxidation products followed by multiphase chemistry in fine particles is the key pathway to form isoprene epoxydiol-derived SOA (IEPOX-SOA). However, many parameters that relate to diffusion and reaction of IEPOX in the particle phase remain uncertain, since reaction kinetics previously measured in bulk aqueous phase solutions might be different from atmospheric aerosols. Here, we use simultaneous environmental chamber measurements of multiple parameters governing IEPOX-SOA formation at timescales of ~hours: particle size distribution, composition, and volatility of IEPOX-SOA to constrain the key parameters governing IE-POX-SOA formation under humid (i.e., 50% relative humidity, RH) and varying seed aerosol acidity conditions. Reducing the 2-methyltetrol (tetrol) reaction rate constants by a factor of 4 brings the model predictions in agreement with the IEPOX-SOA measurements with acidified ammonium bisulfate seed aerosols. For less acidic ammonium sulfate aerosols both the organo-sulfate (OS) and tetrol reaction rate constants need to be reduced to bring model predictions closer to chamber observations. Using the measured non-volatile content of IEPOX-SOA we constrain the oligomerization timescale of 2-methyltetrols. We find that the oligomerization timescale is 4 hours with acidified seed aerosols, but a much longer time scale of 24 hours is needed for non-acidified seed aerosols, indicating that the aerosol acidity greatly affects the oligomerization rate of tetrols. Here we show that the actual kinetics of IEPOX-SOA formation rate on aerosol seeds consisting of both ammonium bisulfate and ammonium sulfate are a factor of 4~5 slower under 50-60% RH conditions compared to their application in previous models, which were based on bulk aqueous solution measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Formation Process of Particles and Cloud Condensation Nuclei Over the Amazon Rainforest: The Role of Local and Remote New-Particle Formation

Understanding the formation processes of particles and cloud condensation nuclei (CCN) in pristine environments is a major challenge in accurately assessing anthropogenic radiative forcing. Here, using a state-of-the-art model that systematically simulates the chemical processes controlling new-particle formation (NPF) and multi-scale chemical transport, we find that NPF contributes ~90% of the particle number and ~80% of the CCN at 0.5% supersaturation (CCN0.5%) in the pristine Amazon boundary layer during the wet season. The corresponding contributions are only ~30% and ~20% during the dry season because of prevalent biomass burning. In both seasons, about half of the NPF-induced particles and ~85% of the NPF-induced CCN0.5% in the boundary layer originate from the long-range transport of new particles formed hundreds to thousands of kilometers away. Moreover, about 50–65% of the NPF-induced particles and 35–50% of the NPF induced CCN0.5% originate from the downward transport of new particles formed in the free troposphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Notable impact of wildfires in the western United States on weather hazards in the central United States

Increased wildfire events constitute a significant threat to life and property in the United States. Wildfire impact on severe storms and weather hazards is another pathway that threatens society, and our understanding of which is very limited. Here, we use unique modeling developments to explore the effects of wildfires in the western US (mainly California and Oregon) on precipitation and hail in the central US. We find that the western US wildfires notably increase the occurrences of heavy precipitation rates by 38% and significant severe hail (≥2 in.) by 34% in the central United States. Both heat and aerosols from wildfires play an important role. By enhancing surface high pressure and increasing westerly and southwesterly winds, wildfires in the western United States produce ( 1 ) stronger moisture and aerosol transport to the central United States and ( 2 ) larger wind shear and storm-relative helicity in the central United States. Both the meteorological environment more conducive to severe convective storms and increased aerosols contribute to the enhancements of heavy precipitation rates and large hail. Moreover, the local wildfires in the central US also enhance the severity of storms, but their impact is notably smaller than the impact of remote wildfires in California and Oregon because of the lessened severity of the local wildfires. As wildfires are projected to be more frequent and severe in a warmer climate, the influence of wildfires on severe weather in downwind regions may become increasingly important.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Airborne flux measurements of ammonia over the Southern Great Plains using chemical ionization mass spectrometry

Ammonia (NH 3 ) is an abundant trace gas in the atmosphere and an important player in atmospheric chemistry, aerosol formation and the atmosphere-surface exchange of nitrogen. It is recognized as a major source of aerosol pollution, and it may limit the formation of cloud nuclei in remote or cold parts of the atmosphere. For soil and plants, NH 3 -mediated nitrogen can act as a harmful pollutant or as a desirable nutrient, mostly in natural and agricultural settings, respectively. Agriculture is also the main source of atmospheric NH 3 via volatilization from fertilizers and manure processing in livestock farming. The accurate determination of NH 3 emission rates remains a challenge, partly due to the propensity of NH 3 to interact with instrument surfaces leading to high detection limits and slow response times. In this paper, we present a new method for quantifying ambient NH 3 , using chemical ionization mass spectrometry (CIMS) with deuterated benzene cations as reagents. The setup aimed at limiting sample-surface interactions and achieved a 1-σ precision of 10–20 pptv and an immediate 1/e response rate < 0.4 s, which compares favorably to the existing state of the art. The sensitivity exhibited an inverse humidity dependence, in particular in relatively dry conditions. Background of up to 10 % of the total signal required consideration as well, as it responded on the order of a few minutes. To showcase the method’s capabilities, we quantified NH3 mixing ratios from measurements obtained during deployment on a Gulfstream I aircraft during the HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems) field campaign in rural Oklahoma during May 2016. Typical mixing ratios were 1–10 parts per billion by volume (ppbv) for the boundary layer and 0.1–1 ppbv in the lower free troposphere. Sharp plumes of up to 10s of ppbv of NH3 were encountered as well. We identified two of their sources as a large fertilizer plant and a cattle farm, and our mixing ratio measurements yielded upper bounds of 350 ± 50 and 0.6 kg NH 3 h –1 for their respective momentary source rates. The fast response of the CIMS also allowed us to derive vertical NH 3 fluxes within the turbulent boundary layer via eddy covariance, for which we chiefly used the continuous wavelet transform technique. As expected for a region dominated by agriculture, we observed predominantly upward fluxes, implying net NH 3 emissions from surface. The corresponding analysis focused on the most suitable flight, which contained two straight-and-level legs at ~300 m above ground. We derived NH 3 fluxes between –4 and 18 mol km –2 h –1 for these legs, at an effective spatial resolution of 1–2 km. The analysis demonstrated how flux measurements benefit from suitably arranged flight tracks with sufficiently long straight-and-level legs, and explores the detrimental effect of measurement discontinuities. Following flux footprint estimations, comparison to the NH 3 area emissions inventory provided by the US Environmental Protection Agency indicated overall agreement, but also the absence of some sources, for instance the identified cattle farm. Our study concludes that high-precision CIMS measurements are a powerful tool for in-situ measurements of ambient NH 3 mixing ratios, and even allow for the airborne mapping of the air-surface exchange of NH 3 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effective radiative forcing of anthropogenic aerosols in E3SMv1: historical changes, causality, decomposition, and parameterization sensitivities

The effective radiative forcing of anthropogenic aerosols (ERF aer ) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERF aer simulated by the E3SMv1 atmosphere model using both century-long free-running atmosphere-land simulations and short nudged simulations. We relate the simulated ERF aer to characteristics of the aerosol composition and optical properties, and evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. Consequently, although the global mean anthropogenic aerosol burden and optical depth increase from 1870 to 2014, the ERF aer magnitude does not increase after around year 1970. The relationships between key aerosol and cloud properties (relative changes between preindustrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period from 1870 to 2014. The ERF aer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol-cloud interactions). Compared to other models, E3SMv1 features a stronger sensitivity of the cloud droplet effective radius to changes in the cloud droplet number concentration. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds. The ERF aer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-atmosphere forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERF aer , it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Novel Application of Machine Learning Techniques for Rapid Source Apportionment of Aerosol Mass Spectrometer Datasets

In this work, we apply machine learning approaches sparse multinomial logistic regression to classify aerosol mass spectrometer (AMS) unit mass resolution (UMR) data followed by an ensemble regression technique for source apportionment of organic aerosols (OA). The classifier was trained on 60 well characterized laboratory and positive matrix factorization (PMF) deconvolved reference spectra to identify eight OA types. These include four laboratory-derived secondary organic aerosol (SOA) spectra, which include isoprene photooxidation SOA, isoprene epoxydiols (IEPOX) SOA, a monoterpene SOA type that includes a-pinene and ß-pinene SOA, and aromatic SOA from oxidation of naphthalene and m-xylene precursors, as well as PMF deconvolved spectra for three primary organic aerosol (POA) types, namely, hydrocarbon-like organic aerosol (HOA), biomass burning organic aerosol (BBOA), and cooking OA (COA), and a more oxidized oxygenated OA type (MO-OOA). A 5-fold cross-validation strategy, repeated 10 times, was used to assess the classifier’s performance. The classifier had high classification accuracy for COA, aromatic SOA, and isoprene SOA spectra but incorrectly classified ~9% by number of MO-OOA spectra as BBOA, 12% of BBOA spectra as HOA (and vice versa), and 18% of IEPOX-SOA spectra as aromatic SOA. Next, an ensemble regression model was trained on an artificially generated dataset consisting of mixtures of different OA types to assess its ability to predict fractional mass abundances from classification probabilities of various OA species obtained from the multinomial logistic regression classifier trained on the reference spectra. Ultimately, the proposed approach was applied for source apportionment of aircraft-based AMS measurements of OA UMR spectra during the HI-SCALE field campaign. On two representative days (May 6th and 18th, 2016), the algorithm determined that ~50-60% of OA by mass was MO-OOA, which represented a highly aged organic aerosol mixture from different sources. On both days, BBOA was determined to contribute less than 10% to OA by mass. However, on May 18th, the aromatic SOA fraction was higher compared to that on May 6th. The proposed approach is capable of rapidly analyzing AMS data in real time, making it suitable for applications where rapid source apportionment of AMS OA spectra is desirable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud life cycle in the Amazon rainforest

Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Anthropogenic–biogenic interaction amplifies warming from emission reduction over the southeastern US

A decline of surface biogenic secondary organic aerosols through the mediation of reduced anthropogenic aerosols has been recognized as an air quality co-benefit of anthropogenic emission control over the southeastern US. However, the climate impacts of this anthropogenic–biogenic interaction remain poorly understood. Here, we identified a substantial decline of summertime aerosol loading aloft over the southeastern US in recent decades through the interaction, which leads to a stronger decline in column-integrated aerosol optical depth and a greater increase in radiative fluxes over the southeastern than northeastern US, different from trends of anthropogenic emissions and near-surface aerosol loading. The anthropogenic–biogenic interaction is shown to explain more than 60% of the coherent increasing trend of 5.3 Wm -2 decade -1 in clear-sky surface downward radiative fluxes. We show that current climate models fail to represent this interaction. The interaction is further projected to amplify the positive radiative forcing from emission control by 42.3% regionally over the southeastern US and globally by 5.4% in 2050 under RCP4.5 compared to 2005. This amplification effect implies greater challenges to achieving the Paris Agreement temperature targets with continuous emission control in future.

54 ENVIRONMENTAL SCIENCES↗