Pulsating aurora from electron scattering by chorus waves.

Auroral substorms, dynamic phenomena that occur in the upper atmosphere at night, are caused by global reconfiguration of the magnetosphere, which releases stored solar wind energy. These storms are characterized by auroral brightening from dusk to midnight, followed by violent motions of distinct auroral arcs that suddenly break up, and the subsequent emergence of diffuse, pulsating auroral patches at dawn. Pulsating aurorae, which are quasiperiodic, blinking patches of light tens to hundreds of kilometres across, appear at altitudes of about 100 kilometres in the high-latitude regions of both hemispheres, and multiple patches often cover the entire sky. This auroral pulsation, with periods of several to tens of seconds, is generated by the intermittent precipitation of energetic electrons (several to tens of kiloelectronvolts) arriving from the magnetosphere and colliding with the atoms and molecules of the upper atmosphere. A possible cause of this precipitation is the interaction between magnetospheric electrons and electromagnetic waves called whistler-mode chorus waves. However, no direct observational evidence of this interaction has been obtained so far. Here we report that energetic electrons are scattered by chorus waves, resulting in their precipitation. Our observations were made in March 2017 with a magnetospheric spacecraft equipped with a high-angular-resolution electron sensor and electromagnetic field instruments. The measured quasiperiodic precipitating electron flux was sufficiently intense to generate a pulsating aurora, which was indeed simultaneously observed by a ground auroral imager.

Characterizing Determinants of Near-Road Ambient Air Quality for an Urban Intersection and a Freeway Site.

INTRODUCTION: Near-road ambient air pollution concentrations that are affected by vehicle emissions are typically characterized by substantial spatial variability with respect to distance from the roadway and temporal variability based on the time of day, day of week, and season. The goal of this work is to identify variables that explain either temporal or spatial variability based on case studies for a freeway site and an urban intersection site. The key hypothesis is that dispersion modeling of near-road pollutant concentrations could be improved by adding estimates or indices for site-specific explanatory variables, particularly related to traffic. Based on case studies for a freeway site and an urban intersection site, the specific aims of this project are to (1) develop and test regression models that explain variability in traffic-related air pollutant (TRAP) ambient concentration at two near-roadway locations; (2) develop and test refined proxies for land use, traffic, emissions and dispersion; and (3) prioritize inputs according to their ability to explain variability in ambient concentrations to help focus efforts for future data collection and model development.The key pollutants that are the key focus of this work include nitrogen oxides (NOx), carbon monoxide (CO), black carbon (BC), fine particulate matter (PM2.5; PM ≤ 2.5 µm in aerodynamic diameter), ultrafine particles (UFPs; PM ≤ 0.1 µm in aerodynamic diameter), and ozone (O3). NOx, CO, and BC are tracers of vehicle emissions and dispersion. PM2.5 is influenced by vehicle table emissions and regional sources. UFPs are sensitive to primary vehicle emissions. Secondary particles can form near roadways and on regional scales, influencing both PM2.5 and UFP concentrations. O3 concentrations are influenced by interaction with NOx near the roadway. Nitrogen dioxide (NO2), CO, PM2.5, and O3 are regulated under the National Ambient Air Quality Standards (NAAQS) because of demonstrated health effects. BC and UFPs are of concern for their potential health effects. Therefore, these pollutants are the focus of this work. METHODS: The methodological approach includes case studies for which variables are identified and assesses their ability to explain either temporal or spatial variability in pollutant ambient concentrations. The case studies include one freeway location and one urban intersection. The case studies address (1) temporal variability at a fixed monitor 10 meters from a freeway; (2) downwind concentrations perpendicular to the same location; (3) variability in 24-hour average pollutant concentrations at five sites near an urban intersection; and (4) spatiotemporal variability along a walking path near that same intersection.The study boundary encompasses key factors in the continuum from vehicle emissions to near-road exposure concentrations. These factors include land use, transportation infrastructure and traffic control, vehicle mix, vehicle (traffic) flow, on-road emissions, meteorology, transport and evolution (transformation) of primary emissions, and production of secondary pollutants, and their resulting impact on measured concentrations in the near-road environment. We conducted field measurements of land use, traffic, vehicle emissions, and near-road ambient concentrations in the vicinity of two newly installed fixed-site monitors. One is a monitoring station jointly operated by the U.S. Environmental Protection Agency (U.S. EPA) and the North Carolina Department of Environmental Quality (NC DEQ) on I-40 between Airport Boulevard and I-540 in Wake County, North Carolina. The other is a fixed-site monitor for measuring PM2.5 at the North Carolina Central University (NCCU) campus on E. Lawson Street in Durham, North Carolina. We refer to these two locations as the freeway site and the urban site, respectively. We developed statistical models for the freeway and urban sites. RESULTS: We quantified land use metrics at each site, such as distances to the nearest bus stop. For the freeway site, we quantified lane-by-lane total vehicle count, heavy vehicle (HV) count, and several vehicle-activity indices that account for distance from each lane to the roadside monitor. For the urban site, we quantified vehicle counts for all 12 turning movements through the intersection. At each site, we measured microscale vehicle tailpipe emissions using a portable emission measurement system.At the freeway site, we measured the spatial gradient of NOx, BC, UFPs, and PM, quantified particle size distributions at selected distances from the roadway and assessed partitioning of particles as a function of evolving volatility. We also quantified fleet-average emission factors for several pollutants.At the urban site, we measured daily average concentrations of nitric oxide (NO), NOx, O3, and PM2.5 at five sites surrounding the intersection of interest; we also measured high resolution (1-second to 10-second averages) concentrations of O3, PM2.5, and UFPs along a pedestrian transect. At both sites, the Research LINE-source (R-LINE) dispersion model was applied to predict concentration gradients based on the physical dispersion of pollution.Statistical models were developed for each site for selected pollutants. With variables for local wind direction, heavy-vehicle index, temperature, and day type, the multiple coefficient of determination (R2) was 0.61 for hourly NOx concentrations at the freeway site. An interaction effect of the dispersion model and a real-time traffic index contributed only 24% of the response variance for NOx at the freeway site. Local wind direction, measured near the road, was typically more important than wind direction measured some distance away, and vehicle-activity metrics directly related to actual real-time traffic were important. At the urban site, variability in pollutant concentrations measured for a pedestrian walk-along route was explained primarily by real-time traffic metrics, meteorology, time of day, season, and real-world vehicle tailpipe emissions, depending on the pollutant. The regression models explained most of the variance in measured concentrations for BC, PM, UFPs, NO, and NOx at the freeway site and for UFPs and O3 at the urban site pedestrian transect. CONCLUSIONS: Among the set of candidate explanatory variables, typically only a few were needed to explain most of the variability in observed ambient concentrations. At the freeway site, the concentration gradients perpendicular to the road were influenced by dilution, season, time of day, and whether the pollutant underwent chemical or physical transformations. The explanatory variables that were useful in explaining temporal variability in measured ambient concentrations, as well as spatial variability at the urban site, were typically localized real-time traffic-volume indices and local wind direction. However, the specific set of useful explanatory variables was site, context (e.g., next to road, quadrants around an intersection, pedestrian transects), and pollutant specific. Among the most novel of the indicators, variability in real-time measured tailpipe exhaust emissions was found to help explain variability in pedestrian transect UFP concentrations. UFP particle counts were very sensitive to real-time traffic indicators at both the freeway and urban sites. Localized site-specific data on traffic and meteorology contributed to explaining variability in ambient concentrations. HV traffic influenced near-road air quality at the freeway site more so than at the urban site. The statistical models typically explained most of the observed variability but were relatively simple. The results here are site-specific and not generalizable, but they are illustrative that near-road air quality can be highly sensitive to localized real-time indicators of traffic and meteorology.

Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service.

Spatially varying diesel locomotive fuel use and emission rates (FUERs) are needed to accurately quantify local emission hotspots and their health impacts. However, existing locomotive FUER data are typically not spatially resolved or representative of real-world locomotive operation. Therefore, existing data are of limited use in quantifying the spatial variability in real-world FUERs. The objectives of this work are to quantify spatial variability in locomotive FUERs and identify factors differentiating hotspots from non-hotspots. FUERs were measured based on real-world measurements conducted for the Piedmont passenger rail service using a portable emission measurement system. FUERs were quantified based on 0.25 mile track segments on the Piedmont route. Hotspots were defined as segments in the top quintile of segment-average FUERs. On average, hotspots contributed 40-50% to trip fuel use and emissions. Hotspots were typically associated with low-to-medium speed, and high acceleration and grade. In contrast, non-hotspots were associated with high speed, and low acceleration and grade. Hotspots were typically located near populated areas and, thus, may exacerbate air pollutant exposure. The method demonstrated here can be applied to other passenger train services to assess key trends in hotspot locations and factors that explain the occurrence of hotspots.

Geospatial Variation of Real-World Tailpipe Emission Rates for Light-Duty Gasoline Vehicles.

Spatial variability in real-world on-road tailpipe light-duty gasoline vehicle nitrogen oxides, hydrocarbon, carbon monoxide, and carbon dioxide emission rates, the locations of emissions hotspots, and factors that explain spatial variability are quantified. A sample of 205 vehicles were measured on four predefined round-trip study routes using Portable Emission Measurement Systems. The trips on each route were divided into segments, averaging 1/4 mile in length. Segment-average emission rates were estimated based on measured 1 Hz emission rates. Emission hotspots are defined as segments with ≥90th percentile of segment-average emission rates. The hotspots have average emission rates 2-4 times greater, depending on the pollutant, than other segments. Hotspots are of heterogeneous characteristics including road attributes and vehicle activity metrics. For example, some hotspots were on arterial roads with an upstream signalized intersection and positive road grade, whereas some hotspots were on interstates with positive grade. Vehicle activity metrics, including average vehicle specific power and relative positive acceleration, help identify the hotspots. To reliably identify a fleet-average hotspot, data are needed for at least 36-130 vehicles, depending on the pollutant.

Indoor Exposure to Ambient Particles and Its Estimation Using Fixed Site Monitors.

Ambient PM2.5 concentrations measured at fixed site monitors (FSM) are often biased with respect to exposure concentrations because of spatial variability and infiltration. Based on comparison of ambient concentrations from 14 FSMs and of exposure concentrations measured indoors and outdoors at two schools in Hong Kong for winter and summer seasons, the magnitude and sources of exposure error based on using FSMs as a surrogate for exposure are quantified. An approach for bias correcting surrogate exposure estimates from FSMs is demonstrated. The approach is based on a proximity factor (PF) that accounts for differences in spatial locations, proximity to emissions and deviation from dominant wind direction, and an infiltration factor (IF) that varies by season. The combination of the PF and IF reduce bias in mean school exposure estimates from ±90% to ±20%. Bias in exposure estimates from using FSMs as surrogates tend to be smaller for which the exposure site and FSM are aligned with wind direction, have similar sampling height, and are in close proximity. The methodology demonstrated to assess concordance between FSMs and exposure measurement sites can be applied more broadly to help reduce exposure error, which may help to interpret seasonal variations in health estimates.

An evaluation of fetal heart rate characteristics associated with neonatal encephalopathy: a case-control study.

OBJECTIVE: We sought to identify fetal heart rate (FHR) characteristics that are associated with neonatal encephalopathy (NE). DESIGN: Retrospective case-control study. SETTING: A single medical centre in Shanghai, China, 2006-2015. SAMPLE: Women delivering a singleton, non-anomalous infant at ≥36 weeks' gestation diagnosed with NE (cases, n = 109) were compared with a group of women with unaffected infants (controls, n = 233). METHODS: Two physicians blinded to the outcome independently reviewed FHR tracings during the last 30 minutes of tracing prior to delivery. FHR characteristics were compared in the two groups and multivariable logistic regression was used to adjust for confounding. MAIN OUTCOME MEASURES: Adjusted odds ratio (aOR) and 95% confidence interval (CI) for the presence of specific FHR categories and characteristics. RESULTS: Category II FHR tracings were observed in 89% of women prior to delivery and were not independently associated with NE. Notably, a category III FHR was observed in 17.4% of women in the NE group compared with 0.9% of women in the control group (aOR 44.99, 95% CI 7.23-279.97). Bradycardia, minimal/absent variability, late decelerations and prolonged decelerations were independently associated with NE, whereas accelerations were protective. Similar findings were found when the cases were limited to NE with arterial cord pH <7.1 and in a subgroup analysis of women with category II tracings. CONCLUSIONS: Category III tracings, while infrequent, are not uncommon prior to delivery among fetuses who develop NE. In contrast, most FHR tracings are category II prior to delivery; however, individual FHR characteristics within this category are associated with NE. FUNDING: This research was supported by the Interdisciplinary Programme of Shanghai Jiao Tong University. TWEETABLE ABSTRACT: Category III tracings are not uncommon prior to delivery among fetuses who develop neonatal encephalopathy.

Factors affecting variability in PM2.5 exposure concentrations in a metro system.

The objectives of this study were to: (1) evaluate PM2.5 inflow to metro train cabins when doors open at stations; (2) assess the spatial and temporal variability in PM2.5 exposure concentration; and (3) quantify the relationship between in-cabin concentration versus outdoor and non-ambient PM2.5. We measured in-cabin PM2.5 concentrations using portable monitors at the door-side and center of a train cabin simultaneously on a Hong Kong metro line. In addition, platform and in-cabin pollutant concentrations near a train door were simultaneously measured. Short-term spikes in PM2.5 concentrations typically occur near train doors when doors open, related to inflow of ambient air aboveground and tunnel air underground. In-cabin PM2.5 exposure concentrations are typically lower away from the doors when the doors open. PM2.5 concentrations inside train cabins and on station platform operating above-ground are more influenced, compared to underground, by outdoor PM2.5. Moreover, non-ambient sources contribute approximately 50% of train in-cabin and station platform PM2.5 concentrations during underground operation. The results help more accurately quantify commuting PM2.5 exposure on a metro system, and can be used to improve population-based exposure simulation models.

Performance, body fat reserves and plasma metabolites in Brown Swiss dairy cows: Indoor feeding versus pasture-based feeding.

Feeding dairy cows indoors or on pasture affects not only labour, machinery and housing costs, but also animals' performance and metabolism. This study investigates the effects of indoor feeding (IF) with a partial-mixed ration (PMR) versus pasture-based feeding (PF) on milk production, fertility, backfat thickness (BFT), body weight (BW) loss and energy metabolism of Brown Swiss (BS) dairy cows with similar genetic production potential. The IF herd consisted of 13 cows fed a PMR composed of maize and grass silage plus protein concentrate according to each cow's requirements. The PF herd consisted of 14 cows offered barn-ventilated hay ad libitum after calving from January until March and grazed on semi-continuous pastures during the vegetation period. The IF cows produced more energy-corrected milk (ECM) per standard lactation (9,407 vs. 5,960 kg; p < .01), more milk fat (378 vs. 227 kg; p < .01) and milk protein (326 vs. 215 kg; p < .01). The calving interval (377 vs. 405 days; p < .01) and time empty (86 vs. 118 days; p < .01) were shorter in the PF compared to IF, possibly also due to different selection criteria for maintaining the respective seasonal calving rhythm. The empty body fat loss calculated according to BCS until its nadir was higher in IF cows (IF: 10.4 vs. PF: 4.8 MJ/day; p < .01), but no differences were noted in total body fat loss estimated via BFT (p = .24). However, PF had lower blood glucose concentration at all investigated time points, but no differences occurred in serum non-esterified fatty acid and ß-hydroxybutyrate concentrations post-partum. In conclusion, BS cows were equally well suited for the IF with PMR and the PF system investigated here without developing a prominent metabolic load despite differences in nutrient supply. As such, investigated BS dairy cows in our trial seem to have a high capacity for metabolic adaptation to different production systems.

Recent advances in the use of nanoparticles for allergen-specific immunotherapy.

The number of patients suffering from allergic asthma and rhinoconjunctivitis has increased dramatically within the last decades. Allergen-specific immunotherapy (AIT) is the only available cause-oriented therapy so far. AIT reduces symptoms, but has also a disease-modifying effect. Disadvantages are a long-lasting procedure, and in a few cases potential systemic adverse reactions. Encapsulation of allergens or DNA vaccines into nanostructures may provide advantages compared to the conventional AIT with noncapsulated allergen extracts: The protein/DNA molecule can be protected from degradation, higher local concentrations and targeted delivery to the site of action appear possible, and most importantly, recognition of encapsulated allergen by the immune system, especially by IgE antibodies, is prevented. AIT with nanoparticles (NPs) may offer a safer and potentially more efficient way of treatment for allergic diseases. In this review, we summarize the use of biodegradable NPs consisting of synthetic or natural polymers, liposomes, and virus-like particles as well as nonbiodegradable NPs like dendrimers, and carbon- or metal-based NPs for AIT. More or less successful applications of these NPs in prophylactic as well as therapeutic vaccination approaches in rodents or other animals as well as first human clinical trials are discussed in detail.

Sequential Measurement of Intermodal Variability in Public Transportation PM2.5 and CO Exposure Concentrations.

A sequential measurement method is demonstrated for quantifying the variability in exposure concentration during public transportation. This method was applied in Hong Kong by measuring PM2.5 and CO concentrations along a route connecting 13 transportation-related microenvironments within 3-4 h. The study design takes into account ventilation, proximity to local sources, area-wide air quality, and meteorological conditions. Portable instruments were compacted into a backpack to facilitate measurement under crowded transportation conditions and to quantify personal exposure by sampling at nose level. The route included stops next to three roadside monitors to enable comparison of fixed site and exposure concentrations. PM2.5 exposure concentrations were correlated with the roadside monitors, despite differences in averaging time, detection method, and sampling location. Although highly correlated in temporal trend, PM2.5 concentrations varied significantly among microenvironments, with mean concentration ratios versus roadside monitor ranging from 0.5 for MTR train to 1.3 for bus terminal. Measured inter-run variability provides insight regarding the sample size needed to discriminate between microenvironments with increased statistical significance. The study results illustrate the utility of sequential measurement of microenvironments and policy-relevant insights for exposure mitigation and management.

Effect of Biodiesel Fuels on Real-World Emissions of Passenger Locomotives.

Few data are available regarding the effect of biodiesel on exhaust emission rates of two-stroke engines used in many passenger locomotives. Using a portable emissions measurement system (PEMS), duty cycle average nitrogen oxides (NOx), hydrocarbons (HC), carbon monoxide (CO), particulate matter (PM), and carbon dioxide (CO2) emission rates were measured for three locomotives operating on ultra-low sulfur diesel (ULSD) and soy-based B10, B20, and B40 biodiesel blends. Measurements were conducted in the rail yard (RY) and over-the-rail (OTR) during passenger service. Compared to ULSD, B20 biodiesel had statistically significant average emission rate reductions in the RY of 58% for CO, 45% for PM, and 6% CO2 and OTR of 59% for HC, 50% for CO, 26% for PM, and 5% for CO2. The average differences in NOx emission rates for both the RY and OTR, and HC in the RY, were not statistically significant. The OTR findings typically agreed qualitatively with the RY findings; however, OTR provides a better basis for estimating the real-world impact of fuel switching. The results indicate substantial potential to reduce in-use locomotive emissions for existing older locomotives, with the exception of NOx.

Enhanced immunogenicity of multivalent MUC1 glycopeptide antitumour vaccines based on hyperbranched polymers.

Enhancing the immunogenicity of an antitumour vaccine still poses a major challenge. It depends upon the selected antigen and the mode of its presentation. We here describe a fully synthetic antitumour vaccine, which addresses both aspects. For the antigen, a tumour-associated MUC1 glycopeptide as B-cell epitope was synthesised and linked to the immunostimulating T-cell epitope P2 derived from tetanus toxoid. The MUC1-P2 conjugate is presented multivalently on a hyperbranched polyglycerol to the immune system. In comparison to a related vaccine of lower multivalency, this vaccine exposing more antigen structures on the hyperbranched polymer induced significantly stronger immune responses in mice and elicited IgG antibodies of distinctly higher affinity to epithelial tumour cells.

Comparison of Over-the-Rail and Rail Yard Measurements of Diesel Locomotives.

Locomotive prime mover engine emission rates are typically measured at steady-state for discrete throttle notches using an engine dynamometer weighted by a standard duty cycle. However, this method may not represent real-world locomotive emissions. A method for in-use measurement of passenger locomotives, using a portable emissions measurement system (PEMS), was developed to estimate duty cycle average emission rates. We conducted 48 measurements of one-way trips between Raleigh and Charlotte, NC, on 7 locomotives and 18 sets of measurements in the rail yard (RY). Real-world duty cycles differed from those used for regulatory analyses, leading to statistically significant lower cycle average NOx and HC emission rates. Compared to RY measurements, notch average NOx emission rates measured over-the-rail (OTR) at the highest two notch settings were, on average, 19% lower for four locomotives. At the highest notch, OTR CO2 emission rates were, on average, 12% lower than RY rates for five locomotives. For a more accurate representation of real-world emission rates, OTR measurements are preferred. However, using steady-state notch average RY emission rates and standard duty cycles may be tolerable for some applications. OTR versus RY cycle average emission rates typically differed by less than 10%.

Variability in Light-Duty Gasoline Vehicle Emission Factors from Trip-Based Real-World Measurements.

Using data obtained with portable emissions measurements systems (PEMS) on multiple routes for 100 gasoline vehicles, including passenger cars (PCs), passenger trucks (PTs), and hybrid electric vehicles (HEVs), variability in tailpipe emission rates was evaluated. Tier 2 emission standards are shown to be effective in lowering NOx, CO, and HC emission rates. Although PTs are larger, heavier vehicles that consume more fuel and produce more CO2 emissions, they do not necessarily produce more emissions of regulated pollutants compared to PCs. HEVs have very low emission rates compared to tier 2 vehicles under real-world driving. Emission factors vary with cycle average speed and road type, reflecting the combined impact of traffic control and traffic congestion. Compared to the slowest average speed and most congested cycles, optimal emission rates could be 50% lower for CO2, as much as 70% lower for NOx, 40% lower for CO, and 50% lower for HC. There is very high correlation among vehicles when comparing driving cycles. This has implications for how many cycles are needed to conduct comparisons between vehicles, such as when comparing fuels or technologies. Concordance between empirical and predicted emission rates using the U.S. Environmental Protection Agency's MOVES model was also assessed.

Comparison of sources of variability in school age children exposure to ambient PM2.5.

School age children are particularly susceptible to exposure to ambient fine particle (PM2.5). To provide insight into factors affecting variability in ambient PM2.5 exposure, distributions of daily PM2.5 exposures for school age children are estimated for four seasons in three climatic zones of the United States using a stochastic microenvironmental exposure model, based on ambient concentration, air exchange rate, penetration factor, deposition rate, census data, meteorological data, and time pattern data. Estimated daily individual exposure varies largely among seasons, regions, and individuals. The mean ratio of ambient exposure to ambient concentration (Ea/Ca) ranges from 0.46 to 0.61 among selected regions and seasons, resulting from differences in air exchange rate. The individual Ea/Ca varies by a factor of 2 to 3 over a 95% frequency range among simulated children, resulting from variability in children's time patterns. These patterns are similar among age groups, but vary with the day of the week and outdoor temperature. Variability in exposure is larger between individuals than between groups. The high end ratio of the Ea/Ca, at the 95th percentile of inter-individual variability, is 30% to 50% higher than the mean Ea/Ca ratio. Results can be used to intepret and adjust exposure errors in epidemiology and to assist in development of exposure mitigation strategies.

Loop electrosurgical excision procedure and risk of vaginal infections during pregnancy: an observational study.

OBJECTIVE: To investigate the risk for preterm birth associated with vaginal infections in pregnancies after a loop electrosurgical excision procedure (LEEP), compared with women with no prior LEEP. DESIGN: Multicentre retrospective cohort study. SETTING: USA. POPULATION: Women with LEEP between 1996 and 2006 were compared with two unexposed groups who had cervical biopsy or Pap test, without any other cervical procedure, in the same calendar year. METHODS: The first pregnancy progressing beyond 20 weeks of gestation in women with prior LEEP was compared with pregnancy in women without LEEP. Stratified analysis according to the presence or the absence of vaginal infection during pregnancy was used to investigate whether the risk for preterm birth differed according to the presence or the absence of infection. The interaction between LEEP and vaginal infection was investigated using multivariable logistic regression with interaction terms, as well as the Mantel-Haenszel test for homogeneity. MAIN OUTCOME MEASURES: Spontaneous preterm birth (<37 and <34 weeks of gestation). RESULTS: Of 1727 patients who met the inclusion criteria, 34.4% (n = 598) underwent LEEP prior to an index pregnancy. There was no increased risk for vaginal infections among women with LEEP compared with women without LEEP. Chlamydia infection and LEEP demonstrated significant interaction, suggesting that the presence of chlamydia infection in women with a history of LEEP augments the risk for preterm birth, compared with women with no history of LEEP. CONCLUSIONS: Vaginal infections during pregnancy in women with a history of LEEP may be associated with an increased risk for preterm birth, compared with women with no history of LEEP.

In-use activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks.

UNLABELLED: The objectives of this study were to quantify real-world activity, fuel use, and emissions for heavy duty diesel roll-off refuse trucks; evaluate the contribution of duty cycles and emissions controls to variability in cycle average fuel use and emission rates; quantify the effect of vehicle weight on fuel use and emission rates; and compare empirical cycle average emission rates with the U.S. Environmental Protection Agency's MOVES emission factor model predictions. Measurements were made at 1 Hz on six trucks of model years 2005 to 2012, using onboard systems. The trucks traveled 870 miles, had an average speed of 16 mph, and collected 165 tons of trash. The average fuel economy was 4.4 mpg, which is approximately twice previously reported values for residential trash collection trucks. On average, 50% of time is spent idling and about 58% of emissions occur in urban areas. Newer trucks with selective catalytic reduction and diesel particulate filter had NOx and PM cycle average emission rates that were 80% lower and 95% lower, respectively, compared to older trucks without. On average, the combined can and trash weight was about 55% of chassis weight. The marginal effect of vehicle weight on fuel use and emissions is highest at low loads and decreases as load increases. Among 36 cycle average rates (6 trucks×6 cycles), MOVES-predicted values and estimates based on real-world data have similar relative trends. MOVES-predicted CO2 emissions are similar to those of the real world, while NOx and PM emissions are, on average, 43% lower and 300% higher, respectively. The real-world data presented here can be used to estimate benefits of replacing old trucks with new trucks. Further, the data can be used to improve emission inventories and model predictions. IMPLICATIONS: In-use measurements of the real-world activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks can be used to improve the accuracy of predictive models, such as MOVES, and emissions inventories. Further, the activity data from this study can be used to generate more representative duty cycles for more accurate chassis dynamometer testing. Comparisons of old and new model year diesel trucks are useful in analyzing the effect of fleet turnover. The analysis of effect of haul weight on fuel use can be used by fleet managers to optimize operations to reduce fuel cost.

Method for modeling driving cycles, fuel use, and emissions for over snow vehicles.

As input to a winter use plan, activity, fuel use, and tailpipe exhaust emissions of over snow vehicles (OSV), including five snow coaches and one snowmobile, were measured on a designated route in Yellowstone National Park (YNP). Engine load was quantified in terms of vehicle specific power (VSP), which is a function of speed, acceleration, and road grade. Compared to highway vehicles, VSP for OSVs is more sensitive to rolling resistance and less sensitive to aerodynamic drag. Fuel use rates increased linearly (R2>0.96) with VSP. For gasoline-fueled OSVs, fuel-based emission rates of carbon monoxide (CO) and nitrogen oxides (NOx) typically increased with increasing fuel use rate, with some cases of very high CO emissions. For the diesel OSVs, which had selective catalytic reduction and diesel particulate filters, fuel-based NOx and particulate matter (PM) emission rates were not sensitive to fuel flow rate, and the emission controls were effective. Inter vehicle variability in cycle average fuel use and emissions rates for CO and NOx was substantial. However, there was relatively little inter-cycle variation in cycle average fuel use and emission rates when comparing driving cycles. Recommendations are made regarding how real-world OSV activity, fuel use, and emissions data can be improved.