Differences between magnitudes and health impacts of BC emissions across the United States using 12 km scale seasonal source apportionment

Demonstration of Hollow Fiber Membrane-Based Enclosed Space Air Remediation for Capture of an Aerosolized Synthetic SARS-CoV-2 Mimic and Pseudovirus Particles

Reduction of airborne viral particles in enclosed spaces is critical in controlling pandemics. Three different hollow fiber membrane (HFM) modules were investigated for viral aerosol separation in enclosed spaces. Pore structures were characterized by scanning electron microscopy, and air transport properties were measured. Particle removal efficiency was characterized using aerosols generated by a collision atomizer from a defined mixture of synthetic nanoparticles including SARS-CoV-2 mimics (protein-coated 100 nm polystyrene). HFM1 (polyvinylidene fluoride, ~50-1300 nm pores) demonstrated 96.5-100% efficiency for aerosols in the size range of 0.3-3 μm at a flow rate of 18.6 ± 0.3 SLPM (~1650 LMH), whereas HFM2 (polypropylene, ~40 nm pores) and HFM3 (hydrophilized polyether sulfone, ~140-750 nm pores) demonstrated 99.65-100% and 98.8-100% efficiency at flow rates of 19.7 ± 0.3 SLPM (~820 LMH) and 19.4 ± 0.2 SLPM (~4455 LMH), respectively. Additionally, lasting filtration with minimal fouling was demonstrated using ambient aerosols over 2 days. Finally, each module was evaluated with pseudovirus (vesicular stomatitis virus) aerosol, demonstrating 99.3% (HFM1), >99.8% (HFM2), and >99.8% (HFM3) reduction in active pseudovirus titer as a direct measure of viral particle removal. These results quantified the aerosol separation efficiency of HFMs and highlight the need for further development of this technology to aid the fight against airborne viruses and particulate matter concerning human health.

High-Resolution Modeling and Apportionment of Diesel-Related Contributions to Black Carbon Concentrations

Exposure to diesel-related air pollution, which includes black carbon (BC) as a major component of the particulate matter emitted in engine exhaust, is a known human health hazard. The resulting health burden falls heavily on vulnerable communities located close to major sources including highways, rail yards, and ports. Determination of source contributions to the overall pollution burden is challenging due to collinearity in the exhaust composition profiles for relevant sources including heavy-duty diesel trucks, railroad locomotives, cargo-handling equipment, and marine engines. Additionally, the impact of each source depends not just on the magnitude of emissions but on its location relative to receptors as well as on meteorology. We modeled source-resolved BC concentrations in West Oakland, California, at a high (150 m) spatial resolution using the Weather Research and Forecasting model. The ability of the model to predict hourly and 24 h average BC concentrations is evaluated for a 100-day period in summer 2017 when BC was measured at 100 sites within the community. We find that a community monitoring site is representative of population-weighted average BC exposure in the community. Major contributing sources to BC in West Oakland include on-road diesel trucks (44 ± 5%) and three off-road diesel sources: ocean-going vessels (19 ± 1%), railroad locomotives (16 ± 2%), and harbor craft such as tugboats and ferries (11 ± 1%).

Multipollutant impacts to U.S. receptors of regional on-road freight in Ontario, Canada

On-road freight is a significant source of air pollutant and greenhouse gas emissions. The resulting economic damages can cross borders through processes of atmospheric fate and transport, regardless of whether that freight serves local or regional demand. Understanding patterns of freight demand and atmospheric processes can thus inform inter-jurisdictional efforts to mitigate multipollutant damages. We quantify how different freight trips across 49 census divisions in the Province of Ontario, Canada create an economic burden on downwind US receptors. We apply an integrated modeling approach combining a travel demand model, a mobile emissions simulator, and marginal damages from emissions. Economic damages include the increased risk of premature death from PM_2.5 related to primary PM_2.5 (represented by damages from inert primary PM_2.5), NO_X, SO₂, and NH₃, and the global effects of climate change from greenhouse gases (CO₂, CH₄, N₂O). Over 90% of the $1.4 billion (2010USD) in transboundary air pollutant damages at US receptors result from regional freight demand across Ontario in 2012. A single major freight corridor, the ON-401 expressway, contributes more than half of all damages. Most of these damages impact the states situated to the south and east of the province. Mean estimates of annual damages range from millions to tens of millions (2010USD) across major eastern metropolitan areas including New York, Boston, Philadelphia, and D.C. Most of these damages result from NO_X, which constitutes 95% of inorganic PM_2.5-related pollutant emissions by mass. Thus, targeting NOx from freight movements along the ON-401 expressway could avoid millions to tens of millions of damages annually in eastern US cities. These results indicate that local green freight policies may be unable to address the environmental burden at cross-border receptors. Cooperation is needed among local, provincial, and federal governments to encourage policies targeting the most harmful emissions along routes servicing regional freight demands. Implications: On-road freight movement in Ontario can yield billions of dollars in annual economic damages to US residents through its effects on air pollution and climate change. We use an integrated modeling approach combining an on-road freight travel demand, mobile emissions, and marginal damages of emissions to quantify and study these economic damages. Regional freight contributes approximately 90% of damages, with one major freight corridor, the ON-401 expressway, contributing 59%. Most damages derive from emissions of NOx and amount to millions to tens of millions of dollars in annual damages across major Eastern US cities. Thus, targeting NOx from freight movements along the ON-401 expressway could avoid millions of damages annually in eastern US cities.

A multiphase CMAQ version 5.0 adjoint

We present the development of a multiphase adjoint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint model provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation, and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosol dynamics and thermodynamics, cloud chemistry and dynamics, diffusion, and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with algorithmic differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or finite-difference method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the complex variable method (CVM) is adopted where necessary. The adjoint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM and CVM. In an example application of the full multiphase adjoint model, we provide the first estimates of how emissions of particulate matter (PM2.5) affect public health across the US.

Direct Radiative Effect and Public Health Implications of Aerosol Emissions Associated with Shifting to Gasoline Direct Injection (GDI) Technologies in Light-Duty Vehicles in the United States

Due to their enhanced fuel economy, the market share of gasoline direct injection (GDI) vehicles has increased significantly over the past decade. However, GDI engines emit higher levels of black carbon (BC) aerosols compared to traditional port fuel injection (PFI) engines. Here, we performed coupled chemical transport and radiative transfer simulations to estimate the aerosol-induced public health and direct radiative effects of shifting the U.S. fleet from PFI to GDI technology. By comparing simulations with current emission profiles and emission profiles modified to reflect a shift from PFI to GDI, we calculated the change in aerosol (mostly BC) concentrations associated with the fleet change. Standard concentration-response calculations indicated that the total annual deaths in the U.S. attributed to particulate gasoline-vehicle emissions would increase from 855 to 1599 due to shifting from PFI to GDI. Furthermore, the increase in BC associated with the shift would lead to an annual average positive radiative effect over the U.S. of approximately +0.075 W/m², with values as large as +0.45 W/m² over urban regions. On the other hand, the reduction in CO₂ emissions associated with the enhanced fuel economy of GDI vehicles would yield a globally uniform negative radiative effect, estimated to be -0.013 W/m² over a 20 year time horizon. Therefore, the climate burden of the increase in BC emissions dominates over the U.S., especially over source regions.

State-level drivers of future fine particulate matter mortality in the United States

Future fine particulate matter (PM₂.₅) concentrations and resulting health impacts will be largely determined by factors such as energy use, fuel choices, emission controls, state and national policies, and demographcs. In this study, a human-earth system model is used to estimate PM_2.5 mortality costs (PMMC) due to air pollutant emissions from each US state over the period 2015 to 2050, considering current major air quality and energy regulations. Contributions of various socioeconomic and energy factors to PMMC are quantified using the Logarithmic Mean Divisia Index. National PMMC are estimated to decrease 25% from 2015 to 2050, driven by decreases in energy intensity and PMMC per unit consumption of electric sector coal and transportation liquids. These factors together contribute 68% of the decrease, primarily from technology improvements and air quality regulations. States with greater population and economic growth, but with fewer clean energy resources, are more likely to face significant challenges in reducing future PMMC from their emissions. In contrast, states with larger projected decreases in PMMC have smaller increases in population and per capita GDP, and greater decreases in electric sector coal share and PMMC per unit fuel consumption.

Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution

There are many technological pathways that can lead to reduced carbon dioxide emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessment model with state-level resolution of the energy system to compare environmental impacts of alternative low-carbon pathways for the United States. One set of pathways emphasizes nuclear energy and carbon capture and storage, while another set emphasizes renewable energy, including wind, solar, geothermal power, and bioenergy. These are compared with pathways in which all technologies are available. Air pollutant emissions, mortality costs attributable to particulate matter smaller than 2.5 μm in diameter, and energy-related water demands are evaluated for 50% and 80% carbon dioxide reduction targets in 2050. The renewable low-carbon pathways require less water withdrawal and consumption than the nuclear and carbon capture pathways. However, the renewable low-carbon pathways modeled in this study produce higher particulate matter-related mortality costs due to greater use of biomass in residential heating. Environmental co-benefits differ among states because of factors such as existing technology stock, resource availability, and environmental and energy policies.

High-resolution mapping of sources contributing to urban air pollution using adjoint sensitivity analysis: benzene and diesel black carbon

The adjoint of the Community Multiscale Air Quality (CMAQ) model at 1 km horizontal resolution is used to map emissions that contribute to ambient concentrations of benzene and diesel black carbon (BC) in the San Francisco Bay area. Model responses of interest include population-weighted average concentrations for three highly polluted receptor areas and the entire air basin. We consider both summer (July) and winter (December) conditions. We introduce a novel approach to evaluate adjoint sensitivity calculations that complements existing methods. Adjoint sensitivities to emissions are found to be accurate to within a few percent, except at some locations associated with large sensitivities to emissions. Sensitivity of model responses to emissions is larger in winter, reflecting weaker atmospheric transport and mixing. The contribution of sources located within each receptor area to the same receptor's air pollution burden increases from 38-74% in summer to 56-85% in winter. The contribution of local sources is higher for diesel BC (62-85%) than for benzene (38-71%), reflecting the difference in these pollutants' atmospheric lifetimes. Morning (6-9am) and afternoon (4-7 pm) commuting-related emissions dominate region-wide benzene levels in winter (14 and 25% of the total response, respectively). In contrast, afternoon rush hour emissions do not contribute significantly in summer. Similar morning and afternoon peaks in sensitivity to emissions are observed for the BC response; these peaks are shifted toward midday because most diesel truck traffic occurs during off-peak hours.