Air quality effects of alternative fuels. Final report

To support the Alternative Fuels Utilization Program, a comparison of potential air quality effects of alternative transportation fuels is being performed. This report presents the results of Phase 1 of this program, focusing on reformulated gasoline (RFG), methanol blended with 15 percent gasoline (M85), and compressed natural gas (CNG). The fuels are compared in terms of effects on simulated future concentrations of ozone and mobile source air toxics in a photochemical grid model. The fuel comparisons were carried out for the future year 2020 and assumed complete replacement of gasoline in the projected light-duty gasoline fleet by each of the candidate fuels. The model simulations were carried out for the areas surrounding Los Angeles and Baltimore/DC, and other (non-mobile) sources of atmospheric emissions were projected according to published estimates of economic and population growth, and planned emission control measures specific to each modeling domain. The future-year results are compared to a future-year run with all gasoline vehicle emissions removed. The results of the comparison indicate that the use of M85 is likely to produce similar ozone and air toxics levels as those projected from the use of RFG. Substitution of CNG is projected to produce significantly lower levels of ozone and the mobile source air toxics than those projected for RFG or M85. The relative benefits of CNG substitution are consistent in both modeling domains. The projection methodologies used for the comparison are subject to a large uncertainty, and modeled concentration distributions depend on meteorological conditions. The quantitative comparison of fuel effects is thus likely to be sensitive to alternative assumptions. The consistency of the results for two very different modeling domains, using very different base assumptions, lends credibility to the qualitative differentiation among these fuels. 32 refs., 42 figs., 47 tabs

A Double machine learning trend model for citizen science data

Funding: This work was funded by The Leon Levy Foundation, The Wolf Creek Foundation and the National Science Foundation (ABI sustaining: DBI-1939187). This work used Bridges2 at Pittsburgh Supercomputing Center and Anvil at Rosen Center for Advanced Computing at Purdue University through allocation DEB200010 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603 and #2138296. Our research was also funded through the 2017–2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND program, with financial support from the Academy of Finland (AKA, Univ. Turku: 326327, Univ. Helsinki: 326338), the Swedish Research Council (Formas, SLU: 2018-02440, Lund Univ.: 2018-02441), the Research Council of Norway (Forskningsrådet, NINA: 295767) and the U.S. National Science Foundation (NSF, Cornell Univ.: ICER-1927646).1. Citizen and community science datasets are typically collected using flexible protocols. These protocols enable large volumes of data to be collected globally every year; however, the consequence is that these protocols typically lack the structure necessary to maintain consistent sampling across years. This can result in complex and pronounced interannual changes in the observation process, which can complicate the estimation of population trends because population changes over time are confounded with changes in the observation process. 2. Here we describe a novel modelling approach designed to estimate spatially explicit species population trends while controlling for the interannual confounding common in citizen science data. The approach is based on Double machine learning, a statistical framework that uses machine learning (ML) methods to estimate population change and the propensity scores used to adjust for confounding discovered in the data. ML makes it possible to use large sets of features to control for confounding and to model spatial heterogeneity in trends. Additionally, we present a simulation method to identify and adjust for residual confounding missed by the propensity scores. 3. To illustrate the approach, we estimated species trends using data from the citizen science project eBird. We used a simulation study to assess the ability of the method to estimate spatially varying trends when faced with realistic confounding and temporal correlation. Results demonstrated the ability to distinguish between spatially constant and spatially varying trends. There were low error rates on the estimated direction of population change (increasing/decreasing) at each location and high correlations on the estimated magnitude of population change. 4. The ability to estimate spatially explicit trends while accounting for confounding inherent in citizen science data has the potential to fill important information gaps, helping to estimate population trends for species and/or regions lacking rigorous monitoring data.Peer reviewe

Chemical reactivity and long-range transport potential of polycyclic aromatic hydrocarbons – a review

Polycyclic aromatic hydrocarbons (PAHs) are of considerable concern due to their well-recognised toxicity and especially due to the carcinogenic hazard which they present. PAHs are semi-volatile and therefore partition between vapour and condensed phases in the atmosphere and both the vapour and particulate forms undergo chemical reactions. This article briefly reviews the current understanding of vapour-particle partitioning of PAHs and the PAH deposition processes, and in greater detail, their chemical reactions. PAHs are reactive towards a number of atmospheric oxidants, most notably the hydroxyl radical, ozone, the nitrate radical (NO3) and nitrogen dioxide. Rate coefficient data are reviewed for reactions of lower molecular weight PAH vapour with these species as well as for heterogeneous reactions of higher molecular weight compounds. Whereas the data for reactions of the 2-3-ring PAH vapour are quite extensive and generally consistent, such data are mostly lacking for the 4-ring PAHs and the heterogeneous rate data (5 and more rings), which are dependent on the substrate type and reaction conditions, are less comprehensive. The atmospheric reactions of PAH lead to the formation of oxy and nitro derivatives, reviewed here, too. Finally, the capacity of PAHs for long range transport and the results of numerical model studies are described. Research needs are identified

Egg weight effects on hatchability of african ostrich

Ocenę wylęgowości przeprowadzono na 133 jajach strusich, które w zależności od masy podzielono na 3 grupy: I – jaja o masie od 1300 do 1450 g, II – jaja o masie od 1451 do 1600 g, III – jaja o masie od 1601 do 1750 g. Największy odsetek zarodków zamarłych (30%) stwierdzono w grupie I, natomiast w pozostałych dwóch wskaźnik ten był mniejszy, odpowiednio o 22,6 i 12,4%. Najwyższe wskaźniki wylęgowości zarówno z jaj nałożonych, jak i zapłodnionych stwierdzono w grupie II, odpowiednio 66,6 i 88,8%. Optimum masy strusich jaj wylęgowych winno mieścić się w przedziale 1451–1600 g.Hatchability evaluation was performed on 133 ostrich eggs which, according to their weight, were divided into 3 groups: group I – with eggs weighing 1300 to 1450 g, group II – with eggs weighing 1451 to 1600 g, and group III – with eggs weighing 1601 to 1750 g. The largest percentage of dead embryos (30%) was found in group I, whereas this rate in two other ones was smaller by 22.6 and 12.4%, respectively. Largest hatchability rates both from set and ferilised eggs were found in group II, i.e. 66.6 and 88.8%, respectively. The optimum of ostrich egg weight should be within the range of 1451–1600 g

Wykorzystanie mniszka lekarskiego (Taraxacum officinale) do oceny antropogenicznego zanieczyszczenia środowiska metalami toksycznymi

The common dandelion (Taraxacum officinale) is a widely distributed plant, not only geographically but also in terms of diverse, often extremely polluted habitats. It is therefore potentially an ideal plant to study accumulation of anthropogenic pollution. The aim of the study was to determine the suitability of common dandelion to assess the environmental contamination of Cd, Cr, Cu, Fe, Mn, Ni, Pb, Ti, Zn, V. The plants were collected from sites initially identified as significantly polluted as well as habitats presumably hardly contaminated. Analyses were made using inductively coupled plasma optical emission spectrometry (ICP OES) in argon, following decomposition of the organic matrix of samples using a mixture of 65% HNO3 and 30% H2O2 in a microwave digestion system. Elevated levels of Cd, Cr, Cu, Fe, Ni and Ti were found both in the leaves and roots of dandelion collected from more polluted sites. The results show that the common dandelion can be a good bio-indicator of environmental contamination for these elements. For the other studied metals, the results were not so unequivocal. In the case of Cd, Cr, Mn, and Ni, statistically significant correlation was found in the concentrations of these elements between the dry matter of leaves and roots.Mniszek pospolity (Taraxacum officinale) jest rośliną bardzo rozpowszechnioną nie tylko geograficznie, lecz także pod względem różnorodności siedlisk, często niezwykle silnie zanieczyszczonych. Jest zatem rośliną potencjalnie idealną do badań nad kumulacją zanieczyszczeń antropogenicznych. Celem badań było ustalenie przydatności mniszka pospolitego do oceny skażenia środowiska naturalnego Cd, Cr, Cu, Fe, Mn, Ni, Pb, Ti, Zn, V. Rośliny pobrano z miejsc wstępnie uznanych za znacznie skażone oraz z siedlisk przypuszczalnie mało zanieczyszczonych. Analizy wykonano metodą spektrometrii emisyjnej ze wzbudzeniem w indukcyjnie sprzężonej plazmie argonowej (ICP OES), po dekompozycji osnowy organicznej próbek mieszaniną 65% HNO3 i 30% H2O2 w mineralizatorze mikrofalowym. Zarówno w liściach, jak i w korzeniach mniszka pobranego z miejsc bardziej zanieczyszczanych stwierdzono podwyższony poziom Cd, Cr, Cu, Fe, Ni i Ti. Uzyskane wyniki wskazują, że mniszek pospolity może być dobrym bioindykatorem skażenia środowiska tymi pierwiastkami. W odniesieniu do pozostałych badanych metali wyniki nie okazały się tak jednoznaczne. W przypadku Cd, Cr, Mn, i Ni wykazano występowanie statystycznie istotnych korelacji między zawartością tych pierwiastków w suchej masie liści i korzeni