Evaluation of the Air Quality and Greenhouse Gas Benefits of an Advanced Low-NOx Compressed Natural Gas (CNG) Engine in Medium and Heavy-Duty Vehicles in California

UC-ITS-2017-35The goal of this research is to assess the greenhouse gas (GHG) emissions and air quality (AQ) impacts of transitions to advanced low\u2010NOx Compressed Natural Gas (CNG) engines in medium-duty vehicle (MDV) and heavy-duty vehicle (HDV) applications in California with a particular emphasis on renewable natural gas (RNG) as a fueling pathway. To evaluate regional AQ impacts in 2035, pollutant emissions from all end-use sectors are projected from current levels and spatially and temporally resolved. Scenarios are constructed beginning with both a conservative (Base Case) and more optimistic (SIP) case regarding advanced vehicle technology and fuels integration to provide spanning of potential impacts. To capture the impact of seasonal dynamics on pollutant formation and fate, two modeling periods are conducted including a winter and summer episode. To estimate the potential GHG impacts of transitions to advanced CNG engines in HDV and MDV, scenarios are evaluated under various assumptions regarding fuel pathways to meet CNG demand from a life cycle perspective. Scenarios are compared to the baseline cases assuming (1) all CNG is provided from conventional fossil natural gas and (2) under a range of possible resource availabilities associated with RNG and renewable synthetic natural gas (RSNG) from in-state resources. Key findings include: i) expanding the deployment of advanced CNG MDV and HDV can reduce summer ground-level ozone concentrations and ground-level PM2.5 in key regions of California; ii) the largest AQ benefits are associated with reducing emissions from HDV; iii) in-state RNG pathways can meet the CNG demand estimated for both baseline cases; iv) in-state resources are unable to entirely meet CNG demand for the high total CNG demand estimated for the majority of Base alternative cases, and v) advanced CNG HDV and MDV can moderately reduce GHG emissions if fossil natural gas is used (14 to 26%)

A Parsimonious Approach to Modeling Animal Movement Data

Animal tracking is a growing field in ecology and previous work has shown that simple speed filtering of tracking data is not sufficient and that improvement of tracking location estimates are possible. To date, this has required methods that are complicated and often time-consuming (state-space models), resulting in limited application of this technique and the potential for analysis errors due to poor understanding of the fundamental framework behind the approach. We describe and test an alternative and intuitive approach consisting of bootstrapping random walks biased by forward particles. The model uses recorded data accuracy estimates, and can assimilate other sources of data such as sea-surface temperature, bathymetry and/or physical boundaries. We tested our model using ARGOS and geolocation tracks of elephant seals that also carried GPS tags in addition to PTTs, enabling true validation. Among pinnipeds, elephant seals are extreme divers that spend little time at the surface, which considerably impact the quality of both ARGOS and light-based geolocation tracks. Despite such low overall quality tracks, our model provided location estimates within 4.0, 5.5 and 12.0 km of true location 50% of the time, and within 9, 10.5 and 20.0 km 90% of the time, for above, equal or below average elephant seal ARGOS track qualities, respectively. With geolocation data, 50% of errors were less than 104.8 km (<0.94°), and 90% were less than 199.8 km (<1.80°). Larger errors were due to lack of sea-surface temperature gradients. In addition we show that our model is flexible enough to solve the obstacle avoidance problem by assimilating high resolution coastline data. This reduced the number of invalid on-land location by almost an order of magnitude. The method is intuitive, flexible and efficient, promising extensive utilization in future research

Lumbar segmental mobility disorders: comparison of two methods of defining abnormal displacement kinematics in a cohort of patients with non-specific mechanical low back pain

BACKGROUND: Lumbar segmental rigidity (LSR) and lumbar segmental instability (LSI) are believed to be associated with low back pain (LBP), and identification of these disorders is believed to be useful for directing intervention choices. Previous studies have focussed on lumbar segmental rotation and translation, but have used widely varying methodologies. Cut-off points for the diagnosis of LSR & LSI are largely arbitrary. Prevalence of these lumbar segmental mobility disorders (LSMDs) in a non-surgical, primary care LBP population has not been established. METHODS: A cohort of 138 consecutive patients with recurrent or chronic low back pain (RCLBP) were recruited in this prospective, pragmatic, multi-centre study. Consenting patients completed pain and disability rating instruments, and were referred for flexion-extension radiographs. Sagittal angular rotation and sagittal translation of each lumbar spinal motion segment was measured from the radiographs, and compared to a reference range derived from a study of 30 asymptomatic volunteers. In order to define reference intervals for normal motion, and define LSR and LSI, we approached the kinematic data using two different models. The first model used a conventional Gaussian definition, with motion beyond two standard deviations (2sd) from the reference mean at each segment considered diagnostic of rotational LSMD and translational LSMD. The second model used a novel normalised within-subjects approach, based on mean normalised contribution-to-total-lumbar-motion. An LSMD was then defined as present in any segment that contributed motion beyond 2sd from the reference mean contribution-to-normalised-total-lumbar-motion. We described reference intervals for normal segmental mobility, prevalence of LSMDs under each model, and the association of LSMDs with pain and disability. RESULTS: With the exception of the conventional Gaussian definition of rotational LSI, LSMDs were found in statistically significant prevalences in patients with RCLBP. Prevalences at both the segmental and patient level were generally higher using the normalised within-subjects model (2.8 to 16.8% of segments; 23.3 to 35.5% of individuals) compared to the conventional Gaussian model (0 to 15.8%; 4.7 to 19.6%). LSMDs are associated with presence of LBP, however LSMDs do not appear to be strongly associated with higher levels of pain or disability compared to other forms of non-specific LBP. CONCLUSION: LSMDs are a valid means of defining sub-groups within non-specific LBP, in a conservative care population of patients with RCLBP. Prevalence was higher using the normalised within-subjects contribution-to-total-lumbar-motion approach

Mismatches in Scale Between Highly Mobile Marine Megafauna and Marine Protected Areas

Marine protected areas (MPAs), particularly large MPAs, are increasing in number and size around the globe in part to facilitate the conservation of marine megafauna under the assumption that large-scale MPAs better align with vagile life histories; however, this alignment is not well established. Using a global tracking dataset from 36 species across five taxa, chosen to reflect the span of home range size in highly mobile marine megafauna, we show most MPAs are too small to encompass complete home ranges of most species. Based on size alone, 40% of existing MPAs could encompass the home ranges of the smallest ranged species, while only \u3c 1% of existing MPAs could encompass those of the largest ranged species. Further, where home ranges and MPAs overlapped in real geographic space, MPAs encompassed \u3c 5% of core areas used by all species. Despite most home ranges of mobile marine megafauna being much larger than existing MPAs, we demonstrate how benefits from MPAs are still likely to accrue by targeting seasonal aggregations and critical life history stages and through other management techniques

Mismatches in Scale Between Highly Mobile Marine Megafauna and Marine Protected Areas

Marine protected areas (MPAs), particularly large MPAs, are increasing in number and size around the globe in part to facilitate the conservation of marine megafauna under the assumption that large-scale MPAs better align with vagile life histories; however, this alignment is not well established. Using a global tracking dataset from 36 species across five taxa, chosen to reflect the span of home range size in highly mobile marine megafauna, we show most MPAs are too small to encompass complete home ranges of most species. Based on size alone, 40% of existing MPAs could encompass the home ranges of the smallest ranged species, while only \u3c 1% of existing MPAs could encompass those of the largest ranged species. Further, where home ranges and MPAs overlapped in real geographic space, MPAs encompassed \u3c 5% of core areas used by all species. Despite most home ranges of mobile marine megafauna being much larger than existing MPAs, we demonstrate how benefits from MPAs are still likely to accrue by targeting seasonal aggregations and critical life history stages and through other management techniques

Latitude dictates plant diversity effects on instream decomposition

Running waters contribute substantially to global carbon fluxes through decomposition of terrestrial plant litter by aquatic microorganisms and detritivores. Diversity of this litter may influence instream decomposition globally in ways that are not yet understood. We investigated latitudinal differences in decomposition of litter mixtures of low and high functional diversity in 40 streams on 6 continents and spanning 113 degrees of latitude. Despite important variability in our dataset, we found latitudinal differences in the effect of litter functional diversity on decomposition, which we explained as evolutionary adaptations of litter-consuming detritivores to resource availability. Specifically, a balanced diet effect appears to operate at lower latitudes versus a resource concentration effect at higher latitudes. The latitudinal pattern indicates that loss of plant functional diversity will have different consequences on carbon fluxes across the globe, with greater repercussions likely at low latitudes

Loci influencing blood pressure identified using a cardiovascular gene-centric array

Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped 50 000 single-nucleotide polymorphisms (SNPs) that capture variation in 2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P 2.4 10(6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.</p

Air quality impacts of fuel cell electric hydrogen vehicles with high levels of renewable power generation

The introduction of fuel cell electric vehicles (FCEV) operating on hydrogen is a key strategy to mitigate pollutant emissions from the light duty vehicle (LDV) transportation sector in pursuit of air quality (AQ) improvements. Further, concomitant increases in renewable power generation could assist in achieving benefits via electrolysis-provided hydrogen as a vehicle fuel. However, it is unclear (1) reductions in emissions translate to changes in primary and secondary pollutant concentrations and (2) how effects compare to those from emissions in other transport sectors including heavy duty vehicles (HDV). This work assesses how the adoption of FCEVs in counties expected to support alternative LDV technologies affect atmospheric concentrations of ozone and fine particulate matter (PM2.5) throughout California (CA) in the year 2055 relative to a gasoline vehicle baseline. Further, impacts of reducing HDV emissions are explored to facilitate comparison among technology classes. A base year emissions inventory is grown to 2055 representing a business-as-usual progression of economic sectors, including primarily petroleum fuel consumption by LDV and HDVs. Emissions are spatially and temporally resolved and used in simulations of atmospheric chemistry and transport to evaluate distributions of primary and secondary pollutants respective to baseline. Results indicate that light-duty FCEV Cases achieve significant reductions in ozone and PM2.5 when LDV market shares reach 50–100% in early adoption counties, including areas distant from deployment sites. Reflecting a cleaner LDV baseline fleet in 2055, emissions from HDVs impact ozone and PM2.5 at comparable or greater levels than light duty FCEVs. Additionally, the importance of emissions from petroleum fuel infrastructure (PFI) activity is demonstrated in impacts on ozone and PM2.5 burdens, with large refinery complexes representing a key source of air pollution in 2055. Results presented provide insight into light duty FCEV deployment strategies that can achieve maximum reductions in ozone and PM2.5 and will assist decision makers in developing effective transportation sector AQ mitigation strategies