Dataset associated with "Unequal airborne exposure burden to toxic metals is associated with race, ethnicity, and segregation"

This dataset contains annual and county-level mean concentrations and mass proportions of fine particulate metals (aggregated from the EPA's CSN/IMPROVE networks), associated minimum detectable limit for each monitor, as well as racial and ethnic demographic population data. This dataset is aggregated from publicly available air pollutant data from the EPA (http://views.cira.colostate.edu/fed/QueryWizard/Default.aspx) and the US Census Bureau (https://data.census.gov/cedsci/). This dataset is used to examine the association of racial residential segregation with fine particulate metal concentrations. The time period ranges from year 2009 to 2019.- Columns labeled "XX_concentration" report the annual and county-level mean concentration in ug m-3 - Columns labeled 'XX_content" report the mass proportion of fine particulate metals relative to PM2.5 mass - Columns labeled "XX_mdl" report the minimum detectable limit for that species at that monitor. In the case of more than one monitor in the county, this column reports the average. - Columns labeled "DI_XX" report the dissimilarity index for the racial/ethnic group using the non-Hispanic White population as the reference population (see associated manuscript for details), where "NHB" corresponds to non-Hispanic Black and "native_amer" to "Native American". - Columns labeled "XX_pop_county" report the county population of the respective racial/ethnic group. These groupings reflect the identification made by individuals in US Census Bureau data. "NHW" refers to "non-Hispanic White". - "CountyFIPS" refers to the county FIPS code. - "Latitude" and "Longitude" reflect the coordinates of the monitor in degrees. In the case of more than one monitor per county, these columns averages.Communities of color have been exposed to a disproportionate burden of air pollution across the United States for decades. Yet, the inequality in exposure to known toxic elements of air pollution is unclear. Here, we find that populations living in racially segregated communities are exposed to a form of fine particulate matter with over three times higher mass proportions of known toxic and carcinogenic metals. While concentrations of total fine particulate matter are two times higher in racially segregated communities, concentrations of metals from anthropogenic sources are nearly ten times higher. Populations living in racially segregated communities have been disproportionately exposed to these environmental stressors throughout the past decade. We find evidence, however, that these disproportionate exposures may be abated though targeted regulatory action. For example, recent regulations on marine fuel oil not only reduced vanadium concentrations in coastal cities, but also sharply lessened differences in vanadium exposure by segregation.This work was supported financially by grants from the Health Effects Institute under grant number 4953- RFA14-3/16-4 awarded to FD, National Institute of Health under grant numbers DP2MD012722 and P50MD010428 awarded to FD, National Institute of Health and National Institute of Environmental Health Sciences under grant number R01 ES028033 awarded to FD, National Institute of Health and Columbia University under grant number 1R01ES030616 awarded to FD, the National Institute On Minority Health And Health Disparities of the National Institutes of Health under award number R01MD012769 awarded to MLB and FD, the Environmental Protection Agency under grant number 83587201-0 awarded to FD and grant number RD83587101 awarded to MLB, The Climate Change Solutions Fund, and the Harvard Star Friedman Award. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Environmental Protection Agency

Improved estimates of preindustrial biomass burning reduce the magnitude of aerosol climate forcing in the Southern Hemisphere.

Fire plays a pivotal role in shaping terrestrial ecosystems and the chemical composition of the atmosphere and thus influences Earth's climate. The trend and magnitude of fire activity over the past few centuries are controversial, which hinders understanding of preindustrial to present-day aerosol radiative forcing. Here, we present evidence from records of 14 Antarctic ice cores and 1 central Andean ice core, suggesting that historical fire activity in the Southern Hemisphere (SH) exceeded present-day levels. To understand this observation, we use a global fire model to show that overall SH fire emissions could have declined by 30% over the 20th century, possibly because of the rapid expansion of land use for agriculture and animal production in middle to high latitudes. Radiative forcing calculations suggest that the decreasing trend in SH fire emissions over the past century largely compensates for the cooling effect of increasing aerosols from fossil fuel and biofuel sources

Improved estimates of preindustrial biomass burning reduce the magnitude of aerosol climate forcing in the Southern Hemisphere.

Fire plays a pivotal role in shaping terrestrial ecosystems and the chemical composition of the atmosphere and thus influences Earth's climate. The trend and magnitude of fire activity over the past few centuries are controversial, which hinders understanding of preindustrial to present-day aerosol radiative forcing. Here, we present evidence from records of 14 Antarctic ice cores and 1 central Andean ice core, suggesting that historical fire activity in the Southern Hemisphere (SH) exceeded present-day levels. To understand this observation, we use a global fire model to show that overall SH fire emissions could have declined by 30% over the 20th century, possibly because of the rapid expansion of land use for agriculture and animal production in middle to high latitudes. Radiative forcing calculations suggest that the decreasing trend in SH fire emissions over the past century largely compensates for the cooling effect of increasing aerosols from fossil fuel and biofuel sources

The potential role of methanesulfonic acid (MSA) in aerosol formation and growth and the associated radiative forcings

Atmospheric marine aerosol particles impact Earth's albedo and climate. These particles can be primary or secondary and come from a variety of sources, including sea salt, dissolved organic matter, volatile organic compounds, and sulfur-containing compounds. Dimethylsulfide (DMS) marine emissions contribute greatly to the global biogenic sulfur budget, and its oxidation products can contribute to aerosol mass, specifically as sulfuric acid and methanesulfonic acid (MSA). Further, sulfuric acid is a known nucleating compound, and MSA may be able to participate in nucleation when bases are available. As DMS emissions, and thus MSA and sulfuric acid from DMS oxidation, may have changed since pre-industrial times and may change in a warming climate, it is important to characterize and constrain the climate impacts of both species. Currently, global models that simulate aerosol size distributions include contributions of sulfate and sulfuric acid from DMS oxidation, but to our knowledge, global models typically neglect the impact of MSA on size distributions. In this study, we use the GEOS-Chem-TOMAS (GC-TOMAS) global aerosol microphysics model to determine the impact on aerosol size distributions and subsequent aerosol radiative effects from including MSA in the size-resolved portion of the model. The effective equilibrium vapor pressure of MSA is currently uncertain, and we use the Extended Aerosol Inorganics Model (E-AIM) to build a parameterization for GC-TOMAS of MSA's effective volatility as a function of temperature, relative humidity, and available gas-phase bases, allowing MSA to condense as an ideally nonvolatile or semivolatile species or too volatile to condense. We also present two limiting cases for MSA's volatility, assuming that MSA is always ideally nonvolatile (irreversible condensation) or that MSA is always ideally semivolatile (quasi-equilibrium condensation but still irreversible condensation). We further present simulations in which MSA participates in binary and ternary nucleation with the same efficacy as sulfuric acid whenever MSA is treated as ideally nonvolatile. When using the volatility parameterization described above (both with and without nucleation), including MSA in the model changes the global annual averages at 900&thinsp;hPa of submicron aerosol mass by 1.2&thinsp;%, N3 (number concentration of particles greater than 3&thinsp;nm in diameter) by &minus;3.9&thinsp;% (non-nucleating) or 112.5&thinsp;% (nucleating), N80 by 0.8&thinsp;% (non-nucleating) or 2.1&thinsp;% (nucleating), the cloud-albedo aerosol indirect effect (AIE) by &minus;8.6&thinsp;mW&thinsp;m&minus;2 (non-nucleating) or &minus;26&thinsp;mW&thinsp;m&minus;2 (nucleating), and the direct radiative effect (DRE) by &minus;15&thinsp;mW&thinsp;m&minus;2 (non-nucleating) or &minus;14&thinsp;mW&thinsp;m&minus;2 (nucleating). The sulfate and sulfuric acid from DMS oxidation produces 4&ndash;6 times more submicron mass than MSA does, leading to an &sim;10 times stronger cooling effect in the DRE. But the changes in N80 are comparable between the contributions from MSA and from DMS-derived sulfate/sulfuric acid, leading to comparable changes in the cloud-albedo AIE. Model&ndash;measurement comparisons with the Heintzenberg et al.&nbsp;(2000) dataset over the Southern Ocean indicate that the default model has a missing source or sources of ultrafine particles: the cases in which MSA participates in nucleation (thus increasing ultrafine number) most closely match the Heintzenberg distributions, but we cannot conclude nucleation from MSA is the correct reason for improvement. Model&ndash;measurement comparisons with particle-phase MSA observed with a customized Aerodyne high-resolution time-of-flight aerosol mass spectrometer (AMS) from the ATom campaign show that cases with the MSA volatility parameterizations (both with and without nucleation) tend to fit the measurements the best (as this is the first use of MSA measurements from ATom, we provide a detailed description of these measurements and their calibration). However, no one model sensitivity case shows the best model&ndash;measurement agreement for both Heintzenberg and the ATom campaigns. As there are uncertainties in both MSA's behavior (nucleation and condensation) and the DMS emissions inventory, further studies on both fronts are needed to better constrain MSA's past, current, and future impacts upon the global aerosol size distribution and radiative forcing. </div

Vertical profiles of light absorption and scattering associated with black carbon particle fractions in the springtime Arctic above 79◦ N

Despite the potential importance of black carbon (BC) for radiative forcing of the Arctic atmosphere, ver- tically resolved measurements of the particle light scatter- ing coefficient (σsp ) and light absorption coefficient (σap ) in the springtime Arctic atmosphere are infrequent, espe- cially measurements at latitudes at or above 80◦ N. Here, re- lationships among vertically distributed aerosol optical prop- erties (σap, σsp and single scattering albedo or SSA), par- ticle microphysics and particle chemistry are examined for a region of the Canadian archipelago between 79.9 and 83.4◦ N from near the surface to 500 hPa. Airborne data collected during April 2015 are combined with ground- based observations from the observatory at Alert, Nunavut and simulations from the Goddard Earth Observing Sys- tem (GEOS) model, GEOS-Chem, coupled with the TwO- Moment Aerosol Sectional (TOMAS) model (collectively GEOS-Chem–TOMAS; Kodros et al., 2018) to further our knowledge of the effects of BC on light absorption in the Arctic troposphere. The results are constrained for σsp less than 15 Mm−1, which represent 98 % of the observed σsp, be- cause the single scattering albedo (SSA) has a tendency to be lower at lower σsp, resulting in a larger relative contribution to Arctic warming. At 18.4 m2 g−1, the average BC mass ab- sorption coefficient (MAC) from the combined airborne and Alert observations is substantially higher than the two aver- aged modelled MAC values (13.6 and 9.1 m2 g−1) for two different internal mixing assumptions, the latter of which is based on previous observations. The higher observed MAC value may be explained by an underestimation of BC, the presence of small amounts of dust and/or possible differences in BC microphysics and morphologies between the obser- vations and model. In comparing the observations and simulations, we present σap and SSA, as measured, and σap/2 and the corresponding SSA to encompass the lower modelled MAC that is more consistent with accepted MAC values. Me- dian values of the measured σap, rBC and the organic com- ponent of particles all increase by a factor of 1.8 ± 0.1, going from near-surface to 750 hPa, and values higher than the sur- face persist to 600 hPa. Modelled BC, organics and σap agree with the near-surface measurements but do not reproduce the higher values observed between 900 and 600 hPa. The dif- ferences between modelled and observed optical properties follow the same trend as the differences between the mod- elled and observed concentrations of the carbonaceous com- ponents (black and organic). Model-observation discrepan- cies may be mostly due to the modelled ejection of biomass burning particles only into the boundary layer at the sources. For the assumption of the observed MAC value, the SSA range between 0.88 and 0.94, which is significantly lower than other recent estimates for the Arctic, in part reflecting the constraint of σsp < 15 Mm−1. The large uncertainties in measuring optical properties and BC, and the large differ- ences between measured and modelled values here and in the literature, argue for improved measurements of BC and light absorption by BC and more vertical profiles of aerosol chemistry, microphysics and other optical properties in the Arctic

Size-resolved mixing state of black carbon in the Canadian high Arctic and implications for simulated direct radiative effect

Transport of anthropogenic aerosol into the Arc- tic in the spring months has the potential to affect regional climate; however, modeling estimates of the aerosol direct radiative effect (DRE) are sensitive to uncertainties in the mixing state of black carbon (BC). A common approach in previous modeling studies is to assume an entirely exter- nal mixture (all primarily scattering species are in separate particles from BC) or internal mixture (all primarily scat- tering species are mixed in the same particles as BC). To provide constraints on the size-resolved mixing state of BC, we use airborne single-particle soot photometer (SP2) and ultrahigh-sensitivity aerosol spectrometer (UHSAS) mea- surements from the Alfred Wegener Institute (AWI) Polar 6 flights from the NETCARE/PAMARCMIP2015 campaign to estimate coating thickness as a function of refractory BC (rBC) core diameter and the fraction of particles contain- ing rBC in the springtime Canadian high Arctic. For rBC core diameters in the range of 140 to 220 nm, we find av- erage coating thicknesses of approximately 45 to 40 nm, re- spectively, resulting in ratios of total particle diameter to rBC core diameters ranging from 1.6 to 1.4. For total par- ticle diameters ranging from 175 to 730 nm, rBC-containing particle number fractions range from 16% to 3%, respec- tively. We combine the observed mixing-state constraints with simulated size-resolved aerosol mass and number dis- tributions from GEOS-Chem–TOMAS to estimate the DRE with observed bounds on mixing state as opposed to assuming an entirely external or internal mixture. We find that the pan-Arctic average springtime DRE ranges fro

Characterization of organic aerosol across the global remote troposphere: A comparison of ATom measurements and global chemistry models

The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of nonrefractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 μgsm-3). Lower concentrations (~ 0:1 0.3 μgsm-3) are observed in the northern middle and high latitudes and very low concentrations (< 0:1 μgsm-3) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the sec-ondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA= OC) ratios of ~ 2.2 2.8, and is 30 % 60% more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations. © 2020 IEEE Computer Society. All rights reserved

Chemical transport models often underestimate aerosol acidity in remote regions of the atmosphere

The inorganic fraction of fine particles affects numerous physicochemical processes in the atmosphere. However, there is large uncertainty in its burden and composition due to limited global measurements. Here, we present observations from eleven different aircraft campaigns from around the globe and investigate how aerosol pH and ammonium balance change from polluted to remote regions, such as over the oceans. Both parameters show increasing acidity with remoteness, at all altitudes, with pH decreasing from about 3 to about −1 and ammonium balance decreasing from almost 1 to nearly 0. We compare these observations against nine widely used chemical transport models and find that the simulations show more scatter (generally R2 \u3c 0.50) and typically predict less acidic aerosol in the most remote regions. These differences in observations and predictions are likely to result in underestimating the model-predicted direct radiative cooling effect for sulfate, nitrate, and ammonium aerosol by 15–39%

Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24 % and -35 % for particles with dry diameters > 50 and > 120 nm, as well as -36 % and -34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N-3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N-3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13 % and -22 % for updraft velocities 0.3 and 0.6 m s(-1), respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (partial derivative N-d/partial derivative N-a) and to updraft velocity (partial derivative N-d/partial derivative w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities partial derivative N-d/partial derivative N-a and partial derivative N-d/partial derivative w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain intermodel biases on the aerosol indirect effect.Peer reviewe

Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer