Greenhouse Gas and Air Pollutant Emissions from Composting.

Composting can divert organic waste from landfills, reduce landfill methane emissions, and recycle nutrients back to soils. However, the composting process is also a source of greenhouse gas and air pollutant emissions. Researchers, regulators, and policy decision-makers all rely on emissions estimates to develop local emissions inventories and weigh competing waste diversion options, yet reported emission factors are difficult to interpret and highly variable. This review explores the impacts of waste characteristics, pretreatment processes, and composting conditions on CO2, CH4, N2O, NH3, and VOC emissions by critically reviewing and analyzing 388 emission factors from 46 studies. The values reported to date suggest that CH4 is the single largest contributor to 100-year global warming potential (GWP100) for yard waste composting, comprising approximately 80% of the total GWP100. For nitrogen-rich wastes including manure, mixed municipal organic waste, and wastewater treatment sludge, N2O is the largest contributor to GWP100, accounting for half to as much as 90% of the total GWP100. If waste is anaerobically digested prior to composting, N2O, NH3, and VOC emissions tend to decrease relative to composting the untreated waste. Effective pile management and aeration are key to minimizing CH4 emissions. However, forced aeration can increase NH3 emissions in some cases.

In-Use Passenger Vessel Emission Rates of Black Carbon and Nitrogen Oxides.

This study quantified emission factors of black carbon (BC) and nitrogen oxides (NOx) from 21 engines on in-use excursion vessels and ferries operating in California's San Francisco Bay, including EPA uncertified and Tier 1-4 engines and across engine operating modes. On average, ∼60 fuel-based emission factors per engine were measured using a novel combination of exhaust plume capture combined with GPS location and speed data that can be more readily deployed than common portable emissions measurement systems. BC and NOx emission factors (g kg-1) were lowest and least variable during fast cruising and highest during maneuvering and docked operation. Selective catalytic reduction (SCR) reduced NOx emissions by ∼80% when functional. However, elevated NOx emissions that exceeded corresponding exhaust standards were measured on most Tier 3 and Tier 4 engines sampled, which can be attributed to inactive SCR during frequent low engine load operation. In contrast, BC emissions exceeded the PM emission standard for only one engine, and SCR systems employed as a NOx reduction technology also reduced emitted BC. Using these measured emission factors to compare commuting options, we show that the CO2-equivalent emissions per passenger-kilometer are comparable when commuting by car and ferry, but BC and NOx emissions can be several to more than ten times larger when commuting by ferry.

Measured influence of overhead HVAC on exposure to airborne contaminants from simulated speaking in a meeting and a classroom.

Tracer gas experiments were conducted in a 158 m3 room with overhead supply diffusers to study dispersion of contaminants from simulated speaking in physically distanced meeting and classroom configurations. The room was contained within a 237 m3 cell with open plenum return to the HVAC system. Heated manikins at desks and a researcher operating the tracer release apparatus presented 8-9 thermal plumes. Experiments were conducted under conditions of no forced air and neutral, cooled, or heated air supplied at 980-1100 cmh, and with/out 20% outdoor air. CO2 was released at the head of one manikin in each experiment to simulate small (<5 µm diameter) respiratory aerosols. The metric of exposure relative to perfectly mixed (ERM) is introduced to quantify impacts, based on measurements at manikin heads and at three heights in the center and corners of the room. Chilled or neutral supply air provided good mixing with ERMs close to one. Thermal stratification during heating produced higher ERMs at most manikins: 25% were ≥2.5 and the highest were >5× perfectly mixed conditions. Operation of two within-zone air cleaners together moving ≥400 cmh vertically in the room provided enough mixing to mitigate elevated exposure variations.

Insights from Application of a Hierarchical Spatio-Temporal Model to an Intensive Urban Black Carbon Monitoring Dataset.

Existing regulatory pollutant monitoring networks rely on a small number of centrally located measurement sites that are purposefully sited away from major emission sources. While informative of general air quality trends regionally, these networks often do not fully capture the local variability of air pollution exposure within a community. Recent technological advancements have reduced the cost of sensors, allowing air quality monitoring campaigns with high spatial resolution. The 100×100 black carbon (BC) monitoring network deployed 100 low-cost BC sensors across the 15 km2 West Oakland, CA community for 100 days in the summer of 2017, producing a nearly continuous site-specific time series of BC concentrations which we aggregated to one-hour averages. Leveraging this dataset, we employed a hierarchical spatio-temporal model to accurately predict local spatio-temporal concentration patterns throughout West Oakland, at locations without monitors (average cross-validated hourly temporal R 2=0.60). Using our model, we identified spatially varying temporal pollution patterns associated with small-scale geographic features and proximity to local sources. In a sub-sampling analysis, we demonstrated that fine scale predictions of nearly comparable accuracy can be obtained with our modeling approach by using ~30% of the 100×100 BC network supplemented by a shorter-term high-density campaign.

Air Pollutant Emission Rates for Dry Anaerobic Digestion and Composting of Organic Municipal Solid Waste.

Dry anaerobic digestion (AD) of organic municipal solid waste (MSW) followed by composting of the residual digestate is a waste diversion strategy that generates biogas and soil amendment products. The AD-composting process avoids methane (CH4) emissions from landfilling, but emissions of other greenhouse gases, odorous/toxic species, and reactive compounds can affect net climate and air quality impacts. In situ measurements of key sources at two large-scale industrial facilities in California were conducted to quantify pollutant emission rates across the AD-composting process. These measurements established a strong relationship between flared biogas ammonia (NH3) content and emitted nitrogen oxides (NOx), indicating that fuel NOx formation is significant and dominates over the thermal or prompt NOx pathways when biogas NH3 concentration exceeds ∼200 ppm. Composting is the largest source of CH4, carbon dioxide (CO2), nitrous oxide (N2O), and carbon monoxide (CO) emissions (∼60-70%), and dominate NH3, hydrogen sulfide (H2S), and volatile organic compounds (VOC) emissions (>90%). The high CH4 contribution to CO2-equivalent emissions demonstrates that composting can be an important CH4 source, which could be reduced with improved aeration. Controlling greenhouse gas and toxic/odorous emissions from composting offers the greatest mitigation opportunities for reducing the climate and air quality impacts of the AD-composting process.

Life-Cycle Greenhouse Gas Emissions and Human Health Trade-Offs of Organic Waste Management Strategies.

Waste-to-energy systems can play an important role in diverting organic waste from landfills. However, real-world waste management can differ from idealized practices, and emissions driven by microbial communities and complex chemical processes are poorly understood. This study presents a comprehensive life-cycle assessment, using reported and measured data, of competing management alternatives for organic municipal solid waste including landfilling, composting, dry anaerobic digestion (AD) for the production of renewable natural gas (RNG), and dry AD with electricity generation. Landfilling is the most greenhouse gas (GHG)-intensive option, emitting nearly 400 kg CO2e per tonne of organic waste. Composting raw organics resulted in the lowest GHG emissions, at -41 kg CO2e per tonne of waste, while upgrading biogas to RNG after dry AD resulted in -36 to -2 kg CO2e per tonne. Monetizing the results based on social costs of carbon and other air pollutant emissions highlights the importance of ground-level NH3 emissions from composting nitrogen-rich organic waste or post-AD solids. However, better characterization of material-specific NH3 emissions from landfills and land-application of digestate is essential to fully understand the trade-offs between alternatives.

Comparison of Mobile and Fixed-Site Black Carbon Measurements for High-Resolution Urban Pollution Mapping.

Urban concentrations of black carbon (BC) and other primary pollutants vary on small spatial scales (<100m). Mobile air pollution measurements can provide information on fine-scale spatial variation, thereby informing exposure assessment and mitigation efforts. However, the temporal sparsity of these measurements presents a challenge for estimating representative long-term concentrations. We evaluate the capabilities of mobile monitoring in the represention of time-stable spatial patterns by comparing against a large set of continuous fixed-site measurements from a sampling campaign in West Oakland, California. Custom-built, low-cost aerosol black carbon detectors (ABCDs) provided 100 days of continuous measurements at 97 near-road and 3 background fixed sites during summer 2017; two concurrently operated mobile laboratories collected over 300 h of in-motion measurements using a photoacoustic extinctiometer. The spatial coverage from mobile monitoring reveals patterns missed by the fixed-site network. Time-integrated measurements from mobile lab visits to fixed-site monitors reveal modest correlation (spatial R2 = 0.51) with medians of full daytime fixed-site measurements. Aggregation of mobile monitoring data in space and time can mitigate high levels of uncertainty associated with measurements at precise locations or points in time. However, concentrations estimated by mobile monitoring show a loss of spatial fidelity at spatial aggregations greater than 100 m.

Comparing the Use of High- to Low-Cost Black Carbon and Carbon Dioxide Sensors for Characterizing On-Road Diesel Truck Emissions.

The exhaust plume capture method is a commonly used approach to measure pollutants emitted by in-use heavy-duty diesel trucks. Lower cost sensors, if used in place of traditional research-grade analyzers, could enable wider application of this method, including use as a monitoring tool to identify high-emitting trucks that may warrant inspection and maintenance. However, low-cost sensors have for the most part only been evaluated under ambient conditions as opposed to source-influenced environments with rapidly changing pollutant concentrations. This study compared black carbon (BC) emission factors determined using different BC and carbon dioxide (CO2) sensors that range in cost from $200 to $20,000. Controlled laboratory experiments show that traditional zero and span steady-state calibration checks are not robust indicators of sensor performance when sampling short duration concentration peaks. Fleet BC emission factor distributions measured at two locations at the Port of Oakland in California with 16 BC/CO2 sensor pairs were similar, but unique sensor pairs identified different high-emitting trucks. At one location, the low-cost PP Systems SBA-5 agreed on the classification of 90% of the high emitters identified by the LI-COR LI-7000 when both were paired with the Magee Scientific AE33. Conversely, lower cost BC sensors when paired with the LI-7000 misclassified more than 50% of high emitters when compared to the AE33/LI-7000. Confidence in emission factor quantification and high-emitter identification improves with larger integrated peak areas of CO2 and especially BC. This work highlights that sensor evaluation should be conducted under application-specific conditions, whether that be for ambient air monitoring or source characterization.

Control Technology-Driven Changes to In-Use Heavy-Duty Diesel Truck Emissions of Nitrogenous Species and Related Environmental Impacts.

Emissions from thousands of in-use heavy-duty diesel trucks were sampled at a highway and an arterial street location in the San Francisco Bay Area, spanning a time period when use of diesel particle filters (DPFs) and selective catalytic reduction (SCR) increased rapidly. At the highway site where a diverse mix of trucks is observed, SCR systems on 2010 and newer engines reduce emitted nitrogen oxides (NOx) by 87 ± 5% relative to pre-2004 engines. SCR also mitigates DPF-related increases in nitrogen dioxide (NO2) emissions. However, a majority of trucks had in-use NOx emission rates that exceeded applicable emission standards. SCR systems increase emissions of nitrous oxide (N2O) and ammonia (NH3) from near-zero levels to 0.93 ± 0.13 and 0.18 ± 0.07 g kg-1, respectively. Emissions of all nitrogenous species and especially NH3 are skewed; 10% of trucks contribute 95% of the on-road fleet's total NH3 emissions. Similar emission changes are observed at the arterial street site where exclusively drayage trucks operate. The environmental effects of decreased black carbon, NOx, and carbon dioxide (CO2) emissions and increased N2O and NH3 emissions due to the rapid adoption of DPF and SCR systems by the California truck fleet are: (1) a 65% net decrease in the social cost of statewide exposure to diesel truck emissions (-3.3 billion 2018 US dollars per year), and (2) a 3% net decrease in the global warming potential-weighted emission factor (-27 g CO2-eq km-1).

A Distributed Network of 100 Black Carbon Sensors for 100 Days of Air Quality Monitoring in West Oakland, California.

Ambient particulate matter (PM) pollution is a major environmental health risk in urban areas. Dense networks of low-cost air quality sensors are emerging to characterize the spatially heterogeneous concentrations that are typical of urban settings, but are not adequately captured using traditional regulatory monitors at central sites. In this study, we present the 100×100 BC Network, a 100-day deployment of low-cost black carbon (BC) sensors across 100 locations in West Oakland, California. This 15 km2 community is surrounded by freeways and affected by emissions associated with local port and industrial activities. We assess the reliability of the sensor hardware and data collection systems, and identify modes of failure to both quantify and qualify network performance. We illustrate how dynamic, local emission sources build upon background BC concentrations. BC concentrations varied sharply over short distances (∼100 m) and timespans (∼1 hour), depending on surrounding land use, traffic patterns, and downwind distance from pollution sources. Strong BC concentration fluctuations were periodically observed over the diurnal and weekly cycles, reflecting the impact of localized traffic emissions and industrial facilities in the neighborhood. Overall, the results demonstrate how distributed sensor networks can reveal the complex spatiotemporal dynamics of combustion-related air pollution within urban neighborhoods.

In-Use Performance and Durability of Particle Filters on Heavy-Duty Diesel Trucks.

Diesel particle filters (DPFs) are standard equipment on heavy-duty diesel trucks with 2007 and newer engines in the U.S. This study evaluates the performance and durability of these filters. Black carbon (BC) emission rates from several thousand heavy-duty trucks were measured at the Port of Oakland and Caldecott Tunnel over multiple years as California regulations accelerated the adoption of DPFs. As DPF use increased, fleet-average BC emissions decreased, and emission factor distributions became more skewed. Relative to 2004-2006 engines without filters, DPFs reduced BC emission rates by 65-70% for 2007-2009 engines and by >90% for 2010+ engines. Average BC emission rates for 2007-2009 engines increased by 50-67% in 2015 relative to measurements made 1-2 years earlier. Some trucks in this cohort have become high-emitters, indicating that some DPFs are no longer working well. At the Port, where DPFs were universal in 2015, high-emitting 2007-2009 engines (defined here as emitting >1 g BC kg-1) comprised 7% of the fleet but were responsible for 65% of the total BC emitted. These observations raise concerns about DPF durability and the prospects for fully mitigating adverse effects of diesel particulate matter on human health and the environment.

Accelerating the Deployment of Anaerobic Digestion to Meet Zero Waste Goals.

The U.S. places approximately 53% of its total municipal solid waste (MSW) in landfills, but state and local governments across the country are now setting ambitious environmental and waste diversion policies requiring, among other things, diversion and utilization of organics. Municipalities across the U.S. are employing anaerobic digestion (AD) as part of their strategy to divert organic MSW from landfills, produce biogas, and yield other beneficial coproducts such as compost and fertilizer. However, AD faces many technical, regulatory, and economic barriers to greater deployment, including upstream waste contamination, local odor and air pollution concerns, lengthy siting and permitting processes, and requirements and sizable costs for interconnecting to the electric grid. We identify a combination of scientific, operational, and policy advancements that are needed to address these barriers.

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).

High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data.

Air pollution affects billions of people worldwide, yet ambient pollution measurements are limited for much of the world. Urban air pollution concentrations vary sharply over short distances (≪1 km) owing to unevenly distributed emission sources, dilution, and physicochemical transformations. Accordingly, even where present, conventional fixed-site pollution monitoring methods lack the spatial resolution needed to characterize heterogeneous human exposures and localized pollution hotspots. Here, we demonstrate a measurement approach to reveal urban air pollution patterns at 4-5 orders of magnitude greater spatial precision than possible with current central-site ambient monitoring. We equipped Google Street View vehicles with a fast-response pollution measurement platform and repeatedly sampled every street in a 30-km2 area of Oakland, CA, developing the largest urban air quality data set of its type. Resulting maps of annual daytime NO, NO2, and black carbon at 30 m-scale reveal stable, persistent pollution patterns with surprisingly sharp small-scale variability attributable to local sources, up to 5-8× within individual city blocks. Since local variation in air quality profoundly impacts public health and environmental equity, our results have important implications for how air pollution is measured and managed. If validated elsewhere, this readily scalable measurement approach could address major air quality data gaps worldwide.

Effects of Particle Filters and Selective Catalytic Reduction on Heavy-Duty Diesel Drayage Truck Emissions at the Port of Oakland.

Effects of fleet modernization and use of diesel particle filters (DPF) and selective catalytic reduction (SCR) on heavy-duty diesel truck emissions were studied at the Port of Oakland in California. Nitrogen oxides (NOx), black carbon (BC), particle number (PN), and size distributions were measured in the exhaust plumes of ∼1400 drayage trucks. Average NOx, BC, and PN emission factors for newer engines (2010-2013 model years) equipped with both DPF and SCR were 69 ± 15%, 92 ± 32%, and 66 ± 35% lower, respectively, than 2004-2006 engines without these technologies. Intentional oxidation of NO to NO2 for DPF regeneration increased tailpipe NO2 emissions, especially from older (1994-2006) engines with retrofit DPFs. Increased deployment of advanced controls has further skewed emission factor distributions; a small number of trucks emit a disproportionately large fraction of total BC and NOx. The fraction of DPF-equipped drayage trucks increased from 2 to 99% and the median engine age decreased from 11 to 6 years between 2009 and 2013. Over this period, fleet-average BC and NOx emission factors decreased by 76 ± 22% and 53 ± 8%, respectively. Emission changes occurred rapidly compared to what would have been observed due to natural (i.e., unforced) turnover of the Port truck fleet. These results provide a preview of more widespread emission changes expected statewide and nationally in the coming years.

Changes to the chemical composition of soot from heterogeneous oxidation reactions.

The atmospheric aging of soot particles, in which various atmospheric processes alter the particles' chemical and physical properties, is poorly understood and consequently is not well-represented in models. In this work, soot aging via heterogeneous oxidation by OH and ozone is investigated using an aerosol flow reactor coupled to a new high-resolution aerosol mass spectrometric technique that utilizes infrared vaporization and single-photon vacuum ultraviolet ionization. This analytical technique simultaneously measures the elemental and organic carbon components of soot, allowing for the composition of both fractions to be monitored. At oxidant exposures relevant to the particles' atmospheric lifetimes (the equivalent of several days of oxidation), the elemental carbon portion of the soot, which makes up the majority of the particle mass, undergoes no discernible changes in mass or composition. In contrast, the organic carbon (which in the case of methane flame soot is dominated by aliphatic species) is highly reactive, undergoing first the addition of oxygen-containing functional groups and ultimately the loss of organic carbon mass from fragmentation reactions that form volatile products. These changes occur on time scales comparable to those of other nonoxidative aging processes such as condensation, suggesting that further research into the combined effects of heterogeneous and condensational aging is needed to improve our ability to accurately predict the climate and health impacts of soot particles.

Chemical compositions of black carbon particle cores and coatings via soot particle aerosol mass spectrometry with photoionization and electron ionization.

Black carbon is an important constituent of atmospheric aerosol particle matter (PM) with significant effects on the global radiation budget and on human health. The soot particle aerosol mass spectrometer (SP-AMS) has been developed and deployed for real-time ambient measurements of refractory carbon particles. In the SP-AMS, black carbon or metallic particles are vaporized through absorption of 1064 nm light from a CW Nd:YAG laser. This scheme allows for continuous "soft" vaporization of both core and coating materials. The main focus of this work is to characterize the extent to which this vaporization scheme provides enhanced chemical composition information about aerosol particles. This information is difficult to extract from standard SP-AMS mass spectra because they are complicated by extensive fragmentation from the harsh 70 eV EI ionization scheme that is typically used in these instruments. Thus, in this work synchotron-generated vacuum ultraviolet (VUV) light in the 8-14 eV range is used to measure VUV-SP-AMS spectra with minimal fragmentation. VUV-SP-AMS spectra of commercially available carbon black, fullerene black, and laboratory generated flame soots were obtained. Small carbon cluster cations (C(+)-C5(+)) were found to dominate the VUV-SP-AMS spectra of all the samples, indicating that the corresponding neutral clusters are key products of the SP vaporization process. Intercomparisons of carbon cluster ratios observed in VUV-SP-AMS and SP-AMS spectra are used to confirm spectral features that could be used to distinguish between different types of refractory carbon particles. VUV-SP-AMS spectra of oxidized organic species adsorbed on absorbing cores are also examined and found to display less thermally induced decomposition and fragmentation than spectra obtained with thermal vaporization at 200 °C (the minimum temperature needed to quantitatively vaporize ambient oxidized organic aerosol with a continuously heated surface). The particle cores tested in these studies include black carbon, silver, gold, and platinum nanoparticles. These results demonstrate that SP vaporization is capable of providing enhanced organic chemical composition information for a wide range of organic coating materials and IR absorbing particle cores. The potential of using this technique to study organic species of interest in seeded laboratory chamber or flow reactor studies is discussed.

Emissions and climate-relevant optical properties of pollutants emitted from a three-stone fire and the Berkeley-Darfur stove tested under laboratory conditions.

Cooking in the developing world generates pollutants that endanger the health of billions of people and contribute to climate change. This study quantified pollutants emitted when cooking with a three-stone fire (TSF) and the Berkeley-Darfur Stove (BDS), the latter of which encloses the fire to increase fuel efficiency. The stoves were operated at the Lawrence Berkeley National Laboratory testing facility with a narrow range of fuel feed rates to minimize performance variability. Fast (1 Hz) measurements of pollutants enabled discrimination between the stoves' emission profiles and development of woodsmoke-specific calibrations for the aethalometer (black carbon, BC) and DustTrak (fine particles, PM2.5). The BDS used 65±5% (average±95% confidence interval) of the wood consumed by the TSF and emitted 50±5% of the carbon monoxide emitted by the TSF for an equivalent cooking task, indicating its higher thermal efficiency and a modest improvement in combustion efficiency. The BDS reduced total PM2.5 by 50% but achieved only a 30% reduction in BC emissions. The BDS-emitted particles were, therefore, more sunlight-absorbing: the average single scattering albedo at 532 nm was 0.36 for the BDS and 0.47 for the TSF. Mass emissions of PM2.5 and BC varied more than emissions of CO and wood consumption over all tests, and emissions and wood consumption varied more among TSF than BDS tests. The international community and the Global Alliance for Clean Cookstoves have proposed performance targets for the highest tier of cookstoves that correspond to greater reductions in fuel consumption and PM2.5 emissions of approximately 65% and 95%, respectively, compared to baseline cooking with the TSF. Given the accompanying decrease in BC emissions for stoves that achieve this stretch goal and BC's extremely high global warming potential, the short-term climate change mitigation from avoided BC emissions could exceed that from avoided CO2 emissions.

Lubricating oil dominates primary organic aerosol emissions from motor vehicles.

Motor vehicles are major sources of primary organic aerosol (POA), which is a mixture of a large number of organic compounds that have not been comprehensively characterized. In this work, we apply a recently developed gas chromatography mass spectrometry approach utilizing "soft" vacuum ultraviolet photoionization to achieve unprecedented chemical characterization of motor vehicle POA emissions in a roadway tunnel with a mass closure of >60%. The observed POA was characterized by number of carbon atoms (NC), number of double bond equivalents (NDBE) and degree of molecular branching. Vehicular POA was observed to predominantly contain cycloalkanes with one or more rings and one or more branched alkyl side chains (≥80%) with low abundances of n-alkanes and aromatics (<5%), similar to "fresh" lubricating oil. The gas chromatography retention time data indicates that the cycloalkane ring structures are most likely dominated by cyclohexane and cyclopentane rings and not larger cycloalkanes. High molecular weight combustion byproducts, that is, alkenes, oxygenates, and aromatics, were not present in significant amounts. The observed carbon number and chemical composition of motor vehicle POA was consistent with lubricating oil being the dominant source from both gasoline and diesel-powered vehicles, with an additional smaller contribution from unburned diesel fuel and a negligible contribution from unburned gasoline.

Quantifying on-road emissions from gasoline-powered motor vehicles: accounting for the presence of medium- and heavy-duty diesel trucks.

Vehicle emissions of nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM2.5), organic aerosol (OA), and black carbon (BC) were measured at the Caldecott tunnel in the San Francisco Bay Area. Measurements were made in bore 2 of the tunnel, where light-duty (LD) vehicles accounted for >99% of total traffic and heavy-duty trucks were not allowed. Prior emission studies conducted in North America have often assumed that route- or weekend-specific prohibitions on heavy-duty truck traffic imply that diesel contributions to pollutant concentrations measured in on-road settings can be neglected. However, as light-duty vehicle emissions have declined, this assumption can lead to biased results, especially for pollutants such as NOx, OA, and BC, for which diesel-engine emission rates are high compared to corresponding values for gasoline engines. In this study, diesel vehicles (mostly medium-duty delivery trucks with two axles and six tires) accounted for <1% of all vehicles observed in the tunnel but were nevertheless responsible for (18 ± 3)%, (22 ± 6)%, and (45 ± 8)% of measured NOx, OA, and BC concentrations. Fleet-average OA and BC emission factors for light-duty vehicles are, respectively, 10 and 50 times lower than for heavy-duty diesel trucks. Using measured emission factors from this study and publicly available data on taxable fuel sales, as of 2010, LD gasoline vehicles were estimated to be responsible for 85%, 18%, 18%, and 6% of emissions of CO, NOx, OA, and BC, respectively, from on-road motor vehicles in the United States.