Economic and Climate Benefits of Electric Vehicles in China, the United States, and Germany.

Mass adoption of electric vehicles (EVs) is widely viewed as essential to address climate change and requires a compelling case for ownership worldwide. While the manufacturing costs and technical capabilities of EVs are similar across regions, customer needs and economic contexts vary widely. Assessments of the all-electric-range required to cover day-to-day driving demand, and the climate and economic benefits of EVs, need to account for differences in regional characteristics and individual travel patterns. To meet this need travel profiles for 1681 light-duty passenger vehicles in China, the U.S., and Germany were used to make the first consistent multiregional comparison of customer and greenhouse gas (GHG) emission benefits of EVs. We show that despite differences in fuel prices, driving patterns, and subsidies, the economic benefits/challenges of EVs are generally similar across regions. Individuals who are economically most likely to adopt EVs have GHG benefits that are substantially greater than for average drivers. Such "priority" EV customers have large (32%-63%) reductions in cradle-to-grave GHG emissions. It is shown that low battery costs (below approximately $100/kWh) and a portfolio of EV offerings are required for mass adoption of electric vehicles.

On-Road Chemical Transformation as an Important Mechanism of NO2 Formation.

Nitrogen dioxide (NO2) not only is linked to adverse effects on the respiratory system but also contributes to the formation of ground-level ozone (O3) and fine particulate matter (PM2.5). Our curbside monitoring data analysis in Detroit, MI, and Atlanta, GA, strongly suggests that a large fraction of NO2 is produced during the "tailpipe-to-road" stage. To substantiate this finding, we designed and carried out a field campaign to measure the same exhaust plumes at the tailpipe-level by a portable emissions measurement system (PEMS) and at the on-road level by an electric vehicle-based mobile platform. Furthermore, we employed a turbulent reacting flow model, CTAG, to simulate the on-road chemistry behind a single vehicle. We found that a three-reaction (NO-NO2-O3) system can largely capture the rapid NO to NO2 conversion (with time scale ≈ seconds) observed in the field studies. To distinguish the contributions from different mechanisms to near-road NO2, we clearly defined a set of NO2/NO x ratios at different plume evolution stages, namely tailpipe, on-road, curbside, near-road, and ambient background. Our findings from curbside monitoring, on-road experiments, and simulations imply the on-road oxidation of NO by ambient O3 is a significant, but so far ignored, contributor to curbside and near-road NO2.

A cost-benefit analysis of a pellet boiler with electrostatic precipitator versus conventional biomass technology: A case study of an institutional boiler in Syracuse, New York.

BACKGROUND: Biomass facilities have received increasing attention as a strategy to increase the use of renewable fuels and decrease greenhouse gas emissions from the electric generation and heating sectors, but these facilities can potentially increase local air pollution and associated health effects. Comparing the economic costs and public health benefits of alternative biomass fuel, heating technology, and pollution control technology options provides decision-makers with the necessary information to make optimal choices in a given location. METHODS: For a case study of a combined heat and power biomass facility in Syracuse, New York, we used stack testing to estimate emissions of fine particulate matter (PM2.5) for both the deployed technology (staged combustion pellet boiler with an electrostatic precipitator) and a conventional alternative (wood chip stoker boiler with a multicyclone). We used the atmospheric dispersion model AERMOD to calculate the contribution of either fuel-technology configuration to ambient primary PM2.5 in a 10km×10km region surrounding the facility, and we quantified the incremental contribution to population mortality and morbidity. We assigned economic values to health outcomes and compared the health benefits of the lower-emitting technology with the incremental costs. RESULTS: In total, the incremental annualized cost of the lower-emitting pellet boiler was $190,000 greater, driven by a greater cost of the pellet fuel and pollution control technology, offset in part by reduced fuel storage costs. PM2.5 emissions were a factor of 23 lower with the pellet boiler with electrostatic precipitator, with corresponding differences in contributions to ambient primary PM2.5 concentrations. The monetary value of the public health benefits of selecting the pellet-fired boiler technology with electrostatic precipitator was $1.7 million annually, greatly exceeding the differential costs even when accounting for uncertainties. Our analyses also showed complex spatial patterns of health benefits given non-uniform age distributions and air pollution levels. CONCLUSIONS: The incremental investment in a lower-emitting staged combustion pellet boiler with an electrostatic precipitator was well justified by the population health improvements over the conventional wood chip technology with a multicyclone, even given the focus on only primary PM2.5 within a small spatial domain. Our analytical framework could be generalized to other settings to inform optimal strategies for proposed new facilities or populations.

Demand response, behind-the-meter generation and air quality.

We investigated the implications of behind-the-meter (BTM) generation participating in demand response (DR) programs. Specifically, we evaluated the impacts of NOx emissions from BTM generators enrolled in the New York Independent System Operator (NYISO)'s reliability-based DR programs. Through analyzing the DR program enrollment data, DR event records, ozone air quality monitoring data, and emission characteristics of the generators, we found that the emissions from BTM generators very likely contribute to exceedingly high ozone concentrations in the Northeast Corridor region, and very likely account for a substantial fraction of total NOx emissions from electricity generation. In addition, a companion study showed that the emissions from BTM generators could also form near-source particulate matter (PM) hotspots. The important policy implications are that the absence of up-to-date regulations on BTM generators may offset the current efforts to reduce the emissions from peaking power plants, and that there is a need to quantify the environmental impacts of DR programs in designing sound policies related to demand-side resources. Furthermore, we proposed the concept of "Green" DR resources, referring to those that not only provide power systems reliability services, but also have verifiable environmental benefits or minimal negative environmental impacts. We argue that Green DR resources that are able to maintain resource adequacy and reduce emissions at the same time are key to achieving the cobenefits of power system reliability and protecting public health during periods with peak electricity demand.

Near-road modeling and measurement of cerium-containing particles generated by nanoparticle diesel fuel additive use.

Cerium oxide nanoparticles (nCe) are used as a fuel-borne catalyst in diesel engines to reduce particulate emissions, yet the environmental and human health impacts of the exhaust particles are not well understood. To bridge the gap between emission measurements and ambient impacts, size-resolved measurements of particle composition and mass concentration have been performed in Newcastle-upon-Tyne, United Kingdom, where buses have used an nCe additive since 2005. These observations show that the noncrustal cerium fraction thought to be associated with the use of nCe has a mass concentration ∼ 0.3 ng m(-3) with a size distribution peaking at 100-320 nm in aerodynamic diameter. Simulations with a near-roadway multicomponent sectional aerosol dynamic model predict that the use of nCe additives increases the number concentration of nuclei mode particles (<50 nm in diameter) while decreasing the total mass concentration. The near-road model predicts a downwind mass size distribution of cerium-containing particles peaking at 150 nm in aerodynamic diameter, a value similar to that measured for noncrustal cerium in Newcastle. This work shows that both the emission and atmospheric transformation of cerium-containing particles needs to be taken into account by regional modelers, exposure scientists, and policymakers when determining potential environmental and human health impacts.

Resolving the effect of roadside vegetation barriers as a near-road air pollution mitigation strategy.

Communities located in near-road environments experience elevated levels of traffic-related air pollution. Near-road air pollution is a major public health concern, and an environmental justice issue. Roadside green infrastructure such as trees, hedges, and bushes may help reduce pollution levels through enhanced deposition and mixing. Gaussian-based dispersion models are widely used by policymakers to evaluate mitigation strategies and develop regulatory actions. However, vegetation barriers are not included in those models, hindering air quality improvement at the community level. The main modeling challenge is the complexity of the deposition and mixing process within and downwind of the vegetation barrier. We propose a novel multi-regime Gaussian-based model that describes the parameters of the standard Gaussian equations in each regime to account for the physical mechanisms by which the vegetation barrier deposits and disperses pollutants. The four regimes include vegetation, a downwind wake, a transition, and a recovery zone. For each regime, we fit the relevant Gaussian plume equation parameters as a function of the vegetation properties and the local wind speed. Furthermore, the model captures particle deposition, a major factor in pollutant reduction by vegetation barriers. We parameterized the multi-regime model using data generated from a fields-validated computational fluid dynamics (CFD) model, covering a wide range of vegetation properties and meteorological conditions. The proposed multi-regime Gaussian-based model was evaluated across 9 particle sizes and a tracer gas to assess its capability of capturing dispersion and deposition. The multi-regime model's normalized mean error (NME) ranged between 0.18 and 0.3, the fractional bias (FB) ranged between -0.12 and 0.09, and R 2 value ranged from 0.47 to 0.75 across all particle sizes and the tracer gas for ground level concentrations, which are within acceptable ranges for air quality dispersion modeling. Even though the multi-regime model is parameterized for coniferous trees, our sensitivity study indicates that it can provide useful predictions for hedges/bushes vegetative barriers as well.

Analyses of turbulent flow fields and aerosol dynamics of diesel engine exhaust inside two dilution sampling tunnels using the CTAG model.

Experimental results from laboratory emission testing have indicated that particulate emission measurements are sensitive to the dilution process of exhaust using fabricated dilution systems. In this paper, we first categorize the dilution parameters into two groups: (1) aerodynamics (e.g., mixing types, mixing enhancers, dilution ratios, residence time); and (2) mixture properties (e.g., temperature, relative humidity, particle size distributions of both raw exhaust and dilution gas). Then we employ the Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model to investigate the effects of those parameters on a set of particulate emission measurements comparing two dilution tunnels, i.e., a T-mixing lab dilution tunnel and a portable field dilution tunnel with a type of coaxial mixing. The turbulent flow fields and aerosol dynamics of particles are simulated inside two dilution tunnels. Particle size distributions under various dilution conditions predicted by CTAG are evaluated against the experimental data. It is found that in the area adjacent to the injection of exhaust, turbulence plays a crucial role in mixing the exhaust with the dilution air, and the strength of nucleation dominates the level of particle number concentrations. Further downstream, nucleation terminates and the growth of particles by condensation and coagulation continues. Sensitivity studies reveal that a potential unifying parameter for aerodynamics, i.e., the dilution rate of exhaust, plays an important role in new particle formation. The T-mixing lab tunnel tends to favor the nucleation due to a larger dilution rate of the exhaust than the coaxial mixing field tunnel. Our study indicates that numerical simulation tools can be potentially utilized to develop strategies to reduce the uncertainties associated with dilution samplings of emission sources.

Modeling spatial variations of black carbon particles in an urban highway-building environment.

Highway-building environments are prevalent in metropolitan areas. This paper presents our findings in investigating pollutant transport in a highway-building environment by combing field measurement and numerical simulations. We employ and improve the Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model to simulate the spatial variations of black carbon (BC) concentrations near highway I-87 and an urban school in the South Bronx, New York. The results of CTAG simulations are evaluated against and agree adequately with the measurements of wind speed, wind directions, and BC concentrations. Our analysis suggests that the BC concentration at the measurement point of the urban school could decrease by 43-54% if roadside buildings were absent. Furthermore, we characterize two generalized conditions in a highway-building environment, i.e., highway-building canyon and highway viaduct-building. The former refers to the canyon between solid highway embankment and roadside buildings, where the spatial profiles of BC depend on the equivalent canyon aspect ratio and flow recirculation. The latter refers to the area between a highway viaduct (i.e., elevated highway with open space underneath) and roadside buildings, where strong flow recirculation is absent and the spatial profiles of BC are determined by the relative heights of the highway and buildings. The two configurations may occur at different locations or in the same location with different wind directions when highway geometry is complex. Our study demonstrates the importance of incorporating highway-building interaction into the assessment of human exposure to near-road air pollution. It also calls for active roles of building and highway designs in mitigating near-road exposure of urban population.

Uncertainty investigation of plume-chasing method for measuring on-road NOx emission factors of heavy-duty diesel vehicles.

The plume-chasing method has shown great advantages in measuring on-road emission factors (EFs) compared with regulatory methods like dynamometer and portable emission measurement systems (PEMS). In this study, a new on-board measurement system incorporating ultrasonic anemometers and solid-state Lidar was developed to investigate the uncertainties of on-road emission factors measured by plume-chasing method due to variables such as on-road wind velocity, chasing speed, chasing distance, and turbulent kinetic energy (TKE). A series of PEMS-chasing experiments for heavy-duty diesel vehicles (HDDVs) were conducted on both highways and local roadways in Beijing, China. Our analysis demonstrated that the differences in EF estimations between concurrent plume-chasing and PEMS measurement decreased with increasing chasing speed as a result of greater vehicle-induced TKE in the wake between HDDV and the mobile platform, whereas the effect of chasing distance on EF estimations appeared insignificant within the tested distance range (12-22 m). In the case of strong crosswinds, overprediction of chasing-based EFs was observed due to convective plume mixing from surrounding vehicular sources. The findings of this study contribute greatly to interpret emission factors measured by the plume-chasing method, and also calls for a future study to develop real-time EF correction algorithms for large-scale mobile chasing measurements.

Ambient sampling of real-world residential wood combustion plumes.

Wood smoke contains large quantities of carbonaceous aerosols known to increase climate forcing and be detrimental to human health. This paper reports the findings from our ambient sampling of fresh residential wood combustion (RWC) plumes in two heating seasons (2015-2016, 2016-2017) in Upstate New York. An Aethalometer (AE33) and a pDR-1500 were employed to monitor residential wood smoke plumes in Ithaca, NY through a hybrid mobile-stationary method. Fresh wood smoke plumes were captured and characterized at 13 different RWC sources in the city, all without significant influence from other combustion sources or atmospheric aging. Wood smoke absorption Ångström exponent (AAE) was estimated using both a one-component model, AAEWB, and a two-component model, AAEBrC (assuming AAEBC = 1.0). Consistent with the recent laboratory studies, our results show that AAEs were highly variable for residential wood smoke for the same source and across different sources, with AAEWB values ranging from 1.3 to 5.0 and AAEBrC values ranging from 2.2 to 7.4. This finding challenges the use of using a single AAE wood smoke value within the range of 1 to 2.5 for source apportionment studies. Furthermore, the PM2.5/BC ratio measured using optical instruments was demonstrated to be potentially useful to characterize burning conditions. Different wood smoke sources can be distinguished by their PM2.5/BC ratio, which range between 15 and 150. This shows promise as an in-situ, cost-effective, ambient sampling-based method to characterize wood burning conditions.Implications: There are two main implications from this paper. First, the large variability in wood smoke absorption Ångström exponent (AAE) values revealed from our real-world, ambient sampling of residential wood combustion plumes indicated that it is not appropriate to use a single AAE wood smoke value for source apportionment studies. Second, the PM2.5/BC ratio has been shown to serve as a promising in-situ, cost-effective, ambient sampling-based indicator to characterize wood burning conditions. This has the potential to greatly reduce the costs of insitu wood smoke surveillance.