China is the world's largest carbon emitter and suffers from severe air pollution. About one million deaths in China were attributable to air pollution in 2017. Alternative energy vehicles (AEVs), e.g. electric, hydrogen fuel cell, and natural gas vehicles, can help achieve both carbon emission mitigation and air quality improvement. However, climate, air quality and health co-benefit of AEVs powered by deeply decarbonized electricity generation remain poorly quantified. Here, we conduct a quantitative integrated assessment of the air quality, health, carbon emission mitigation and economic benefits of AEV deployment as the electricity grid decarbonizes in China. We find population-weighted annual PM2.5 and summer O3 concentration can decrease as large as 5.7μgm−3 and 4.9ppb. Annual avoided premature mortalities and years of life lost resulting from improved ambient air pollution can be as large as ~329,000 persons and ~1,611,000 years. We thus show that maximizing climate, air quality and health benefits of AEV deployment in China requires rapid decarbonization of the power system.
This setup mimics ice lying above the drainage system. In the experiment, a fluid-filled blister is generated via liquid injection into the interface between a transparent elastic layer and a porous substrate. After injection of liquid, the fluid permeates from the blister through the porous substrate, the blister volume V(t) relaxes exponentially with time. Our lab experiments show that varying the permeability of the porous substrate k significantly impacts the relaxation timescale in the experiments.
The carbon isotopic (δ13C) composition of shallow-water carbonates often is interpreted to reflect the δ13C of the global ocean and is used as a proxy for changes in the global carbon cycle. However, local platform processes, in addition to meteoric and marine diagenesis, may decouple carbonate δ13C from that of the global ocean. To shed light on the extent to which changing sediment grain composition may produce δ13C shifts in the stratigraphic record, we present new δ13C measurements of benthic foraminifera, solitary corals, calcifying green algae, ooids, coated grains, and lime mud from the modern Great Bahama Bank (GBB). This survey of a modern carbonate environment reveals δ13C variability comparable to the largest δ13C excursions in the last two billion years of Earth history.
The history of organismal evolution, seawater chemistry, and paleoclimate is recorded in layers of carbonate sedimentary rock. Meter-scale cyclic stacking patterns in these carbonates often are interpreted as representing sea level change. A reliable sedimentary proxy for eustasy would be profoundly useful for reconstructing paleoclimate, since sea level responds to changes in temperature and ice volume. However, the translation from water depth to carbonate layering has proven difficult, with recent surveys of modern shallow water platforms revealing little correlation between carbonate facies (i.e., grain size, sedimentary bed forms, ecology) and water depth. We train a convolutional neural network with satellite imagery and new field observations from a 3,000 km2 region northwest of Andros Island (Bahamas) to generate a facies map with 5 m resolution. Leveraging a newly-published bathymetry for the same region, we test the hypothesis that one can extract a signal of water depth change, not simply from individual facies, but from sequences of facies transitions analogous to vertically stacked carbonate strata. Our Hidden Markov Model (HMM) can distinguish relative sea level fall from random variability with ∼90% accuracy. Finally, since shallowing-upward patterns can result from local (autogenic) processes in addition to forced mechanisms such as eustasy, we search for statistical tools to diagnose the presence or absence of external forcings on relative sea level. With a new data-driven forward model that simulates how modern facies mosaics evolve to stack strata, we show how different sea level forcings generate characteristic patterns of cycle thicknesses in shallow carbonates, providing a new tool for quantitative reconstruction of ancient sea level conditions from the geologic record.
This dataset includes information about approximately 6,000 books and other items with bibliographic data as well as summary information about when the item circulated in the Shakespeare and Company lending library and the number of times an item was borrowed or purchased.
The Shakespeare and Company Project: Lending Library Events dataset includes information about approximately 35,000 lending library events including membership activities such as subscriptions, renewals and reimbursements and book-related activities such as borrowing and purchasing. For events related to lending library cards that are available as digital surrogates, IIIF links are provided.
The Shakespeare and Company Project: Lending Library Members dataset includes information about approximately 5,600 members of Sylvia Beach's Shakespeare and Company lending library.
The Shakespeare and Company Project makes three datasets available to download in CSV and JSON formats. The datasets provide information about lending library members; the books that circulated in the lending library; and lending library events, including borrows, purchases, memberships, and renewals. The datasets may be used individually or in combination site URLs are consistent identifiers across all three. The DOIs for each dataset are as follows: Members (https://doi.org/10.34770/nsa4-3t76); Books (https://doi.org/10.34770/079z-h206); Events (https://doi.org/10.34770/rtbp-kv40).
