Less Than 2 °C Warming by 2100 Unlikely.

The recently published Intergovernmental Panel on Climate Change (IPCC) projections to 2100 give likely ranges of global temperature increase in four scenarios for population, economic growth and carbon use1. However these projections are not based on a fully statistical approach. Here we use a country-specific version of Kaya's identity to develop a statistically-based probabilistic forecast of CO2 emissions and temperature change to 2100. Using data for 1960-2010, including the UN's probabilistic population projections for all countries2-4, we develop a joint Bayesian hierarchical model for GDP per capita and carbon intensity. We find that the 90% interval for cumulative CO2 emissions includes the IPCC's two middle scenarios but not the extreme ones. The likely range of global temperature increase is 2.0-4.9°C, with median 3.2°C and a 5% (1%) chance that it will be less than 2°C (1.5°C). Population growth is not a major contributing factor. Our model is not a "business as usual" scenario, but rather is based on data which already show the effect of emission mitigation policies. Achieving the goal of less than 1.5°C warming will require carbon intensity to decline much faster than in the recent past

Design of a Two-Level Underground Parking Garage for Swarthmore College

This report contains the complete design of a two-level underground parking garage located at Swarthmore College in Swarthmore, Pennsylvania, underneath the North\ud Campus Athletic Field. This report contains full architectural, structural, mechanical, and\ud detail drawings and could, if presented to a contractor, be used to actually build the garage.\ud We have designed a garage that is efficient, structurally sound, aesthetically pleasing, and\ud has minimal impact on the surrounding environment. The garage is designed with post-tensioned\ud concrete for the roof slabs, floor slabs, beams, joists and girders, and cast-in-place\ud normally reinforced concrete for the columns and slab-on-grade. Post-tensioned\ud concrete proved to be, overall, the most cost effective structural system given our design\ud parameters. Reasons behind the choice of post-tensioned concrete can be found in section\ud 4.1. MultiFrame 3D, MiniCAD, PCACOL, and Microsoft Excel were used for the primary\ud design work.\ud The geotechnical, structural, electrical and mechanical designs are each discussed\ud in-depth in their own sections, and while smaller diagrams can be found throughout the\ud report, complete CAD drawings are located in the appendices

Rutabaga Project and Arrowhead Grown Virginia, MN

The Iron Range of Minnesota is known for mining, and, before that for logging. But its forgotten history of food self-sufficiency, both by its indigenous population and its more recent immigrants, is deeply buried. This project put in place a three-part "Grown on the Range" effort with these focus areas: 1) a robust eat-and-grow-local campaign, expanded to “Arrowhead Grown” to more fully encompass the region, 2) an Iron Range Local Food Trail tourism attraction, and, 3) a regular newspaper column highlighting past and current regional farming and food production. This project is putting the Iron Range and all of Northeast Minnesota back on the track towards food self-sufficiency with all of the economic and health benefits that will bring

Less Than 2 °C Warming by 2100 Unlikely.

The recently published Intergovernmental Panel on Climate Change (IPCC) projections to 2100 give likely ranges of global temperature increase in four scenarios for population, economic growth and carbon use1. However these projections are not based on a fully statistical approach. Here we use a country-specific version of Kaya's identity to develop a statistically-based probabilistic forecast of CO2 emissions and temperature change to 2100. Using data for 1960-2010, including the UN's probabilistic population projections for all countries2-4, we develop a joint Bayesian hierarchical model for GDP per capita and carbon intensity. We find that the 90% interval for cumulative CO2 emissions includes the IPCC's two middle scenarios but not the extreme ones. The likely range of global temperature increase is 2.0-4.9°C, with median 3.2°C and a 5% (1%) chance that it will be less than 2°C (1.5°C). Population growth is not a major contributing factor. Our model is not a "business as usual" scenario, but rather is based on data which already show the effect of emission mitigation policies. Achieving the goal of less than 1.5°C warming will require carbon intensity to decline much faster than in the recent past

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future