Use of electron microscopy to determine presence of coal dust in a neighborhood bordering an open-air coal terminal in Curtis Bay, Baltimore, Maryland, USA.

BACKGROUND: Despite decreasing US consumption, over 90 million metric tons of coal were exported by the US in 2023, requiring significant infrastructure for transport, handling, and storage of coal at export terminals. Residents in Curtis Bay, Baltimore, Maryland, USA live at the fenceline of an open-air coal terminal and have, for decades, reported rapid accumulation of black dust at their homes. Community-level exposure to coal dust originating from coal handling and storage terminals has remained largely unexplored. OBJECTIVES: To investigate community-identified concerns and use a community-driven approach to determine the presence/absence of coal dust in Curtis Bay surfaces. METHODS: Passive settled dust samples were collected from two residential areas, 345 m and 1235 m from the coal terminal, using conductive carbon tape. Scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDX) of standard reference coal material and a positive control material from the coal terminal in Curtis Bay were used to optimize the morphological and elemental classification criteria for coal dust. A manual SEM-EDX protocol was developed to identify coal particles in settled dust collected on conductive carbon tape in community settings. RESULTS: SEM-EDX analysis confirmed presence of coal dust sampled at both residential locations. Estimated coal dust particle loading at the proximal and distal site were 13.2 and 3.4 coal particles/mm2, respectively. The coal dust particles identified met specific criteria, including size (>5 µm), morphology, and elemental composition (≥75 % carbon, ≤20 % oxygen). DISCUSSION: These findings are consistent with longstanding community concerns and lived experiences regarding the presence of coal dust in Curtis Bay, which neighbors a major open-air coal terminal. This approach has potential for other communities neighboring coal terminals to assess similar concerns with residential coal dust exposure.

Mobile laboratory measurements of air pollutants in Baltimore, MD elucidate issues of environmental justice.

The City of Baltimore, MD has a history of problems with environmental justice (EJ), air pollution, and the urban heat island (UHI) effect. Current chemical transport models lack the resolution to simulate concentrations on the scale needed, about 100 m, to identify the neighborhoods with anomalously high air pollution levels. In this paper we introduce the capabilities of a mobile laboratory and an initial survey of several pollutants in Baltimore to identify which communities are exposed to disproportionate concentrations of air pollution and to which species. High concentrations of black carbon (BC) stood out at some locations - near major highways, downtown, and in the Curtis Bay neighborhood of Baltimore. Results from the mobile lab are confirmed with longer-term, low-cost monitoring. In Curtis Bay, higher concentrations of BC were measured along Pennington Ave. (mean [5th to 95th percentiles] = 2.08 [2.0-10.9] µg m-3) than along Curtis Ave. just ~ 150 m away (0.67[0.1 - 1.8] µg m-3). Other species, including criteria pollutants ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5), showed little gradient. Observations with high spatial and temporal resolution help isolate the mechanisms leading to locally high pollutant concentrations. The difference in BC appears to result not from heavier truck traffic or slower dispersion but from the interruptions in traffic flow. Pennington Ave. has three stoplights while Curtis Ave. has none. As heavy-duty diesel-powered vehicles accelerate, they experience turbo-lag and the resulting rich air-fuel mixture exacerbates BC emissions. Immediate mediation might be achieved through smoother traffic flow, and the long-term solution through replacing heavy-duty trucks with electric vehicles.Implications: We present results documenting the locations within Baltimore of high concentrations of Black Carbon pollution and identify the likely source - diesel exhaust emissions exacerbated by stop-and-go traffic and associated turbo-lag. This suggests solutions (smoother traffic, retrofit particulate filters, replacement of diesel with electric vehicles) that would enhance Environmental Justice (EJ) and could be applied to other cities with EJ problems.Synopsis: This paper presents observations of atmospheric black carbon aerosol showing impacts on environmental justice, then identifies causes and suggests solutions.

Tracing sources of atmospheric methane using clumped isotopes.

We apply a recently developed measurement technique for methane (CH4) isotopologues* (isotopic variants of CH4-13CH4, 12CH3D, 13CH3D, and 12CH2D2) to identify contributions to the atmospheric burden from fossil fuel and microbial sources. The aim of this study is to constrain factors that ultimately control the concentration of this potent greenhouse gas on global, regional, and local levels. While predictions of atmospheric methane isotopologues have been modeled, we present direct measurements that point to a different atmospheric methane composition and to a microbial flux with less clumping (greater deficits relative to stochastic) in both 13CH3D and 12CH2D2 than had been previously assigned. These differences make atmospheric isotopologue data sufficiently sensitive to variations in microbial to fossil fuel fluxes to distinguish between emissions scenarios such as those generated by different versions of EDGAR (the Emissions Database for Global Atmospheric Research), even when existing constraints on the atmospheric CH4 concentration profile as well as traditional isotopes are kept constant.

Inferred vehicular emissions at a near-road site: Impacts of COVID-19 restrictions, traffic patterns, and ambient air temperature.

Vehicles are a major source of anthropogenic emissions of carbon monoxide (CO), nitrogen oxides (NOx), and black carbon (BC). CO and NOx are known to be harmful to human health and contribute to ozone formation, while BC absorbs solar radiation that contributes to global warming and also has negative impacts on human health and visibility. Travel restrictions implemented during the COVID-19 pandemic provide researchers the opportunity to study the impact of large, on-road traffic reductions on local air quality. Traffic counts collected along Interstate-95, a major eight-lane highway in Maryland (US), reveal a 60% decrease in passenger car totals and an 8.6% (combination-unit) and 21% (single-unit) decrease in truck traffic counts in April 2020 relative to prior Aprils. The decrease in total on-road vehicles led to the near-elimination in stop-and-go traffic and a 14% increase in the mean vehicle speed during April 2020. Ambient near-road (NR) BC, CO, NOx, and carbon dioxide (CO2) measurements were used to determine vehicular emission ratios (ΔBC/ΔCO, ΔBC/ΔCO2, ΔNOx/ΔCO, ΔNOx/ΔCO2, and ΔCO/ΔCO2), with each ratio defined as the slope value of a linear regression performed on the concentrations of two pollutants within an hour. A decrease of up to a factor of two in ΔBC/ΔCO, ΔBC/ΔCO2, ΔNOx/ΔCO2, and in the fraction of on-road diesel vehicles from weekdays to weekends shows diesel vehicles to be the dominant source of BC and NOx emissions at this NR site. We estimate up to a 70% reduction in BC emissions in April 2020 compared to earlier years, and attribute much of this to lower diesel BC emissions resulting from improvements in traffic flow and fewer instances of acceleration and braking. Future efforts to reduce vehicular BC emissions should focus on improving traffic flow or turbocharger lag within diesel engines. Inferred BC emissions from the NR site also depend on ambient temperature, with an increase of 54% in ΔBC/ΔCO from -5 to 20 °C during the cold season, similar to previous studies that reported increasing BC emissions with rising temperature. The default setting of MOVES3, the current version of the mobile emission model used by the US EPA, does not adjust hot-running BC emissions for ambient temperature. Future work will focus on improving the accuracy of mobile emissions in air quality modeling by incorporating the effects of temperature and traffic flow in the system used to generate mobile emissions input for commonly used air quality models.

Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence.

Nitrogen dioxide (NO2) at the ground level poses a serious threat to environmental quality and public health. This study developed a novel, artificial intelligence approach by integrating spatiotemporally weighted information into the missing extra-trees and deep forest models to first fill the satellite data gaps and increase data availability by 49% and then derive daily 1 km surface NO2 concentrations over mainland China with full spatial coverage (100%) for the period 2019-2020 by combining surface NO2 measurements, satellite tropospheric NO2 columns derived from TROPOMI and OMI, atmospheric reanalysis, and model simulations. Our daily surface NO2 estimates have an average out-of-sample (out-of-city) cross-validation coefficient of determination of 0.93 (0.71) and root-mean-square error of 4.89 (9.95) µg/m3. The daily seamless high-resolution and high-quality dataset "ChinaHighNO2" allows us to examine spatial patterns at fine scales such as the urban-rural contrast. We observed systematic large differences between urban and rural areas (28% on average) in surface NO2, especially in provincial capitals. Strong holiday effects were found, with average declines of 22 and 14% during the Spring Festival and the National Day in China, respectively. Unlike North America and Europe, there is little difference between weekdays and weekends (within ±1 µg/m3). During the COVID-19 pandemic, surface NO2 concentrations decreased considerably and then gradually returned to normal levels around the 72nd day after the Lunar New Year in China, which is about 3 weeks longer than the tropospheric NO2 column, implying that the former can better represent the changes in NOx emissions.

Carbon Monoxide Emissions from the Washington, DC, and Baltimore Metropolitan Area: Recent Trend and COVID-19 Anomaly.

We analyze airborne measurements of atmospheric CO concentration from 70 flights conducted over six years (2015-2020) using an inverse model to quantify the CO emissions from the Washington, DC, and Baltimore metropolitan areas. We found that CO emissions have been declining in the area at a rate of ≈-4.5 % a-1 since 2015 or ≈-3.1 % a-1 since 2016. In addition, we found that CO emissions show a "Sunday" effect, with emissions being lower, on average, than for the rest of the week and that the seasonal cycle is no larger than 16 %. Our results also show that the trend derived from the NEI agrees well with the observed trend, but that NEI daytime-adjusted emissions are ≈50 % larger than our estimated emissions. In 2020, measurements collected during the shutdown in activity related to the COVID-19 pandemic indicate a significant drop in CO emissions of 16 % relative to the expected emissions trend from the previous years, or 23 % relative to the mean of 2016 to February 2020. Our results also indicate a larger reduction in April than in May. Last, we show that this reduction in CO emissions was driven mainly by a reduction in traffic.

Volatile chemical product emissions enhance ozone and modulate urban chemistry.

Decades of air quality improvements have substantially reduced the motor vehicle emissions of volatile organic compounds (VOCs). Today, volatile chemical products (VCPs) are responsible for half of the petrochemical VOCs emitted in major urban areas. We show that VCP emissions are ubiquitous in US and European cities and scale with population density. We report significant VCP emissions for New York City (NYC), including a monoterpene flux of 14.7 to 24.4 kg ⋅ d-1 ⋅ km-2 from fragranced VCPs and other anthropogenic sources, which is comparable to that of a summertime forest. Photochemical modeling of an extreme heat event, with ozone well in excess of US standards, illustrates the significant impact of VCPs on air quality. In the most populated regions of NYC, ozone was sensitive to anthropogenic VOCs (AVOCs), even in the presence of biogenic sources. Within this VOC-sensitive regime, AVOCs contributed upwards of ∼20 ppb to maximum 8-h average ozone. VCPs accounted for more than 50% of this total AVOC contribution. Emissions from fragranced VCPs, including personal care and cleaning products, account for at least 50% of the ozone attributed to VCPs. We show that model simulations of ozone depend foremost on the magnitude of VCP emissions and that the addition of oxygenated VCP chemistry impacts simulations of key atmospheric oxidation products. NYC is a case study for developed megacities, and the impacts of VCPs on local ozone are likely similar for other major urban regions across North America or Europe.

Synergistic aircraft and ground observations of transported wildfire smoke and its impact on air quality in New York City during the 2018 LISTOS campaign.

Air pollution associated with wildfire smoke transport during the summer can significantly affect ozone (O3) and particulate matter (PM) concentrations, even in heavily populated areas like New York City (NYC). Here, we use observations from aircraft, ground-based lidar, in-situ analyzers and satellite to study and assess wildfire smoke transport, vertical distribution, optical properties, and potential impact on air quality in the NYC urban and coastal areas during the summer 2018 Long Island Sound Tropospheric Ozone Study (LISTOS). We investigate an episode of dense smoke transported and mixed into the planetary boundary layer (PBL) on August 15-17, 2018. The horizontal advection of the smoke is shown to be characterized with the prevailing northwest winds in the PBL (velocity > 10 m/s) based on Doppler wind lidar measurements. The wildfire sources and smoke transport paths from the northwest US/Canada to northeast US are identified from the NOAA hazard mapping system (HMS) fires and smoke product and NOAA-HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory analysis. The smoke particles are distinguished from the urban aerosols by showing larger lidar-ratio (70-sr at 532-nm) and smaller depolarization ratio (0.02) at 1064-nm using the NASA High Altitude Lidar Observatory (HALO) airborne high-spectral resolution lidar (HSRL) measurements. The extinction-related angstrom exponents in the near-infrared (IR at 1020-1640 nm) and Ultraviolet (UV at 340-440 nm) from NASA-Aerosol Robotic Network (AERONET) product show a reverse variation trend along the smoke loadings, and their absolute differences indicate strong correlation with the smoke-Aerosol Optical Depth (AOD) (R > 0.94). We show that the aloft smoke plumes can contribute as much as 60-70% to the column AOD and that concurrent high-loadings of O3, carbon monoxide (CO), and black carbon (BC) were found in the elevated smoke layers from the University of Maryland (UMD) aircraft in-situ observations. Meanwhile, the surface PM2.5 (PM with diameter ≤ 2.5 µm), organic carbon (OC) and CO measurements show coincident and sharp increase (e.g., PM2.5 from 5 µg/m3 before the plume intrusion to ~30 µg/m3) with the onset of the plume intrusions into the PBL along with hourly O3 exceedances in the NYC region. We further evaluate the NOAA-National Air Quality Forecasting Capability (NAQFC) model PBL-height, PM2.5, and O3 with the observations and demonstrate good consistency near the ground during the convective PBL period, but significant bias at other times. The aloft smoke layers are sometimes missed by the model.

Wintertime CO2, CH4, and CO Emissions Estimation for the Washington, DC-Baltimore Metropolitan Area Using an Inverse Modeling Technique.

Since greenhouse gas mitigation efforts are mostly being implemented in cities, the ability to quantify emission trends for urban environments is of paramount importance. However, previous aircraft work has indicated large daily variability in the results. Here we use measurements of CO2, CH4, and CO from aircraft over 5 days within an inverse model to estimate emissions from the DC-Baltimore region. Results show good agreement with previous estimates in the area for all three gases. However, aliasing caused by irregular spatiotemporal sampling of emissions is shown to significantly impact both the emissions estimates and their variability. Extensive sensitivity tests allow us to quantify the contributions of different sources of variability and indicate that daily variability in posterior emissions estimates is larger than the uncertainty attributed to the method itself (i.e., 17% for CO2, 24% for CH4, and 13% for CO). Analysis of hourly reported emissions from power plants and traffic counts shows that 97% of the daily variability in posterior emissions estimates is explained by accounting for the sampling in time and space of sources that have large hourly variability and, thus, caution must be taken in properly interpreting variability that is caused by irregular spatiotemporal sampling conditions.

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ.

Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42% in the control run and by 12% with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80% for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O3 datasets and observationally constrained box model simulations of OH and HO2. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29% for CO, 18% for ozone, 11% for HO2, and 27% for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O3, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO x controls, can improve ozone pollution over East Asia.

Evaluation of Thermal Optical Analysis (TOA) using an aqueous binary mixture.

Thermal-Optical Analysis (TOA), a commonly implemented technique used to measure the amount of particulate carbon in the atmosphere or deposited on a filter substrate, distinguishes organic carbon (OC) from elemental carbon (EC) through the monitoring of laser light, heating, and measuring evolved carbon. Here, we present a method to characterize the TOA transmission method with an aqueous binary mixture containing EC and OC that can easily be deposited onto a filter at low volumes. Known amounts of EC and OC were deposited onto a quartz-fiber filter and analyzed with different temperature protocols. Results with the NIST-EPA-C temperature protocol agreed with the reference values to better than 2 % for EC, OC, total carbon (TC), and EC/TC. Indicated TC for all temperature protocols was within 5 % of the reference value while all protocols reproduced EC/TC ratios with an uncertainty less than 10 %.

SO2 Emission Estimates Using OMI SO2 Retrievals for 2005-2017.

SO2 column densities from Ozone Monitoring Instrument provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three Ozone Monitoring Instrument SO2 retrieval products (National Aeronautics and Space Administration (NASA) standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO2 emissions. SO2 column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4D-Var/mass balance emission inversion to derive monthly SO2 emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in United States, India, and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO2 emissions increase from 2005 to 2016 by 35% (NASA)-48% (BIRA) in India, but decrease in China by 23% (NASA)-33% (BIRA) since 2008. Compared to in situ measurements, the posterior GEOS-Chem surface SO2 concentrations have reduced NMB in China, the United States, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO2 measurement in China and spatial variability of SO2 concentration in China, South Korea, and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO2 emissions using Ozone Monitoring Instrument observations.

Author Correction: India Is Overtaking China as the World's Largest Emitter of Anthropogenic Sulfur Dioxide.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

India Is Overtaking China as the World's Largest Emitter of Anthropogenic Sulfur Dioxide.

Severe haze is a major public health concern in China and India. Both countries rely heavily on coal for energy, and sulfur dioxide (SO2) emitted from coal-fired power plants and industry is a major pollutant contributing to their air quality problems. Timely, accurate information on SO2 sources is a required input to air quality models for pollution prediction and mitigation. However, such information has been difficult to obtain for these two countries, as fast-paced changes in economy and environmental regulations have often led to unforeseen emission changes. Here we use satellite observations to show that China and India are on opposite trajectories for sulfurous pollution. Since 2007, emissions in China have declined by 75% while those in India have increased by 50%. With these changes, India is now surpassing China as the world's largest emitter of anthropogenic SO2. This finding, not predicted by emission scenarios, suggests effective SO2 control in China and lack thereof in India. Despite this, haze remains severe in China, indicating the importance of reducing emissions of other pollutants. In India, ~33 million people now live in areas with substantial SO2 pollution. Continued growth in emissions will adversely affect more people and further exacerbate morbidity and mortality.

Methane emissions from the Marcellus Shale in southwestern Pennsylvania and northern West Virginia based on airborne measurements.

Natural gas production in the U.S. has increased rapidly over the past decade, along with concerns about methane (CH4) leakage (total fugitive emissions), and climate impacts. Quantification of CH4 emissions from oil and natural gas (O&NG) operations is important for establishing scientifically sound, cost-effective policies for mitigating greenhouse gases. We use aircraft measurements and a mass balance approach for three flight experiments in August and September 2015 to estimate CH4 emissions from O&NG operations in the southwestern Marcellus Shale region. We estimate the mean ± 1σ CH4 emission rate as 36.7 ± 1.9 kg CH4 s-1 (or 1.16 ± 0.06 Tg CH4 yr-1) with 59% coming from O&NG operations. We estimate the mean ± 1σ CH4 leak rate from O&NG operations as 3.9 ± 0.4% with a lower limit of 1.5% and an upper limit of 6.3%. This leak rate is broadly consistent with the results from several recent top-down studies but higher than the results from a few other observational studies as well as in the U.S. Environmental Protection Agency CH4 emission inventory. However, a substantial source of CH4 was found to contain little ethane (C2H6), possibly due to coalbed CH4 emitted either directly from coalmines or from wells drilled through coalbed layers. Although recent regulations requiring capture of gas from the completion venting step of the hydraulic fracturing appear to have reduced losses, our study suggests that for a 20 year time scale, energy derived from the combustion of natural gas extracted from this region will require further controls before it can exert a net climate benefit compared to coal.

Evaluation and environmental correction of ambient CO2 measurements from a low-cost NDIR sensor.

Non-dispersive infrared (NDIR) sensors are a low-cost way to observe carbon dioxide concentrations in air, but their specified accuracy and precision are not sufficient for some scientific applications. An initial evaluation of six SenseAir K30 carbon dioxide NDIR sensors in a lab setting showed that without any calibration or correction, the sensors have an individual root mean square error (RMSE) between ~5 and 21 parts per million (ppm) compared to a research-grade greenhouse gas analyzer using cavity enhanced laser absorption spectroscopy. Through further evaluation, after correcting for environmental variables with coefficients determined through a multivariate linear regression analysis, the calculated difference between the each of six individual K30 NDIR sensors and the higher-precision instrument had an RMSE of between 1.7 and 4.3 ppm for 1 min data. The median RMSE improved from 9.6 for off-the-shelf sensors to 1.9 ppm after correction and calibration, demonstrating the potential to provide useful information for ambient air monitoring.

Urban Emissions of Water Vapor in Winter.

Elevated water vapor (H2Ov) mole fractions were occassionally observed downwind of Indianapolis, IN, and the Washington, D.C.-Baltimore, MD, area during airborne mass balance experiments conducted during winter months between 2012 and 2015. On days when an urban H2Ov excess signal was observed, H2Ov emissions estimates range between 1.6 × 104 and 1.7 × 105 kg s-1, and account for up to 8.4% of the total (background + urban excess) advected flow of atmospheric boundary layer H2Ov from the urban study sites. Estimates of H2Ov emissions from combustion sources and electricity generation facility cooling towers are 1-2 orders of magnitude smaller than the urban H2Ov emission rates estimated from observations. Instances of urban H2Ov enhancement could be a result of differences in snowmelt and evaporation rates within the urban area, due in part to larger wintertime anthropogenic heat flux and land cover differences, relative to surrounding rural areas. More study is needed to understand why the urban H2Ov excess signal is observed on some days, and not others. Radiative transfer modeling indicates that the observed urban enhancements in H2Ov and other greenhouse gas mole fractions contribute only 0.1°C day-1 to the urban heat island at the surface. This integrated warming through the boundary layer is offset by longwave cooling by H2Ov at the top of the boundary layer. While the radiative impacts of urban H2Ov emissions do not meaningfully influence urban heat island intensity, urban H2Ov emissions may have the potential to alter downwind aerosol and cloud properties.

Expected ozone benefits of reducing nitrogen oxide (NOx) emissions from coal-fired electricity generating units in the eastern United States.

On hot summer days in the eastern United States, electricity demand rises, mainly because of increased use of air conditioning. Power plants must provide this additional energy, emitting additional pollutants when meteorological conditions are primed for poor air quality. To evaluate the impact of summertime NOx emissions from coal-fired electricity generating units (EGUs) on surface ozone formation, we performed a series of sensitivity modeling forecast scenarios utilizing EPA 2018 version 6.0 emissions (2011 base year) and CMAQ v5.0.2. Coal-fired EGU NOx emissions were adjusted to match the lowest NOx rates observed during the ozone seasons (April 1-October 31) of 2005-2012 (Scenario A), where ozone decreased by 3-4 ppb in affected areas. When compared to the highest emissions rates during the same time period (Scenario B), ozone increased ∼4-7 ppb. NOx emission rates adjusted to match the observed rates from 2011 (Scenario C) increased ozone by ∼4-5 ppb. Finally in Scenario D, the impact of additional NOx reductions was determined by assuming installation of selective catalytic reduction (SCR) controls on all units lacking postcombustion controls; this decreased ozone by an additional 2-4 ppb relative to Scenario A. Following the announcement of a stricter 8-hour ozone standard, this analysis outlines a strategy that would help bring coastal areas in the mid-Atlantic region closer to attainment, and would also provide profound benefits for upwind states where most of the regional EGU NOx originates, even if additional capital investments are not made (Scenario A). IMPLICATIONS: With the 8-hr maximum ozone National Ambient Air Quality Standard (NAAQS) decreasing from 75 to 70 ppb, modeling results indicate that use of postcombustion controls on coal-fired power plants in 2018 could help keep regions in attainment. By operating already existing nitrogen oxide (NOx) removal devices to their full potential, ozone could be significantly curtailed, achieving ozone reductions by up to 5 ppb in areas around the source of emission and immediately downwind. Ozone improvements are also significant (1-2 ppb) for areas affected by cross-state transport, especially Mid-Atlantic coast regions that had struggled to meet the 75 ppb standard.

Formaldehyde in the Tropical Western Pacific: Chemical sources and sinks, convective transport, and representation in CAM-Chem and the CCMI models.

Formaldehyde (HCHO) directly affects the atmospheric oxidative capacity through its effects on HOx. In remote marine environments, such as the Tropical Western Pacific (TWP), it is particularly important to understand the processes controlling the abundance of HCHO because model output from these regions is used to correct satellite retrievals of HCHO. Here, we have used observations from the CONTRAST field campaign, conducted during January and February 2014, to evaluate our understanding of the processes controlling the distribution of HCHO in the TWP as well as its representation in chemical transport/climate models. Observed HCHO mixing ratios varied from ~500 pptv near the surface to ~75 pptv in the upper troposphere. Recent convective transport of near surface HCHO and its precursors, acetaldehyde and possibly methyl hydroperoxide, increased upper tropospheric HCHO mixing ratios by ~33% (22 pptv); this air contained roughly 60% less NO than more aged air. Output from the CAM-Chem chemistry transport model (2014 meteorology) as well as nine chemistry climate models from the Chemistry-Climate Model Initiative (free-running meteorology) are found to uniformly underestimate HCHO columns derived from in situ observations by between 4 and 50%. This underestimate of HCHO likely results from a near factor of two underestimate of NO in most models, which strongly suggests errors in NOx emissions inventories and/or in the model chemical mechanisms. Likewise, the lack of oceanic acetaldehyde emissions and potential errors in the model acetaldehyde chemistry lead to additional underestimates in modeled HCHO of up to 75 pptv (~15%) in the lower troposphere.

Impacts of brown carbon from biomass burning on surface UV and ozone photochemistry in the Amazon Basin.

The spectral dependence of light absorption by atmospheric particulate matter has major implications for air quality and climate forcing, but remains uncertain especially in tropical areas with extensive biomass burning. In the September-October 2007 biomass-burning season in Santa Cruz, Bolivia, we studied light absorbing (chromophoric) organic or "brown" carbon (BrC) with surface and space-based remote sensing. We found that BrC has negligible absorption at visible wavelengths, but significant absorption and strong spectral dependence at UV wavelengths. Using the ground-based inversion of column effective imaginary refractive index in the range 305-368 nm, we quantified a strong spectral dependence of absorption by BrC in the UV and diminished ultraviolet B (UV-B) radiation reaching the surface. Reduced UV-B means less erythema, plant damage, and slower photolysis rates. We use a photochemical box model to show that relative to black carbon (BC) alone, the combined optical properties of BrC and BC slow the net rate of production of ozone by up to 18% and lead to reduced concentrations of radicals OH, HO2, and RO2 by up to 17%, 15%, and 14%, respectively. The optical properties of BrC aerosol change in subtle ways the generally adverse effects of smoke from biomass burning.