EURONEAR—Recovery, follow-up and discovery of NEAs and MBAs using large field 1–2 m telescopes

We report on the follow-up and recovery of 100 program NEAs, PHAs and VIs using the ESO/MPG 2.2 m, Swope 1 m and INT 2.5 m telescopes equipped with large field cameras. The 127 fields observed during 11 nights covered 29 square degrees. Using these data, we present the incidental survey work which includes 558 known MBAs and 628 unknown moving objects mostly consistent with MBAs from which 58 objects became official discoveries. We planned the runs using six criteria and four servers which focus mostly on faint and poorly observed objects in need of confirmation, follow-up and recovery. We followed 62 faint NEAs within one month after discovery and we recovered 10 faint NEAs having big uncertainties at their second or later opposition. Using the INT we eliminated four PHA candidates and VIs. We observed in total 1286 moving objects and we reported more than 10,000 positions. All data were reduced by the members of our network in a team effort, and reported promptly to the MPC. The positions of the program NEAs were published in 27 MPC and MPEC references and used to improve their orbits. The O−C residuals for known MBAs and program NEAs are smallest for the ESO/MPG and Swope and about four times larger for the INT whose field is more distorted. For the astrometric reduction, the UCAC-2 catalog is recommended instead of USNO-B1. The incidental survey allowed us to study statistics of the MBA and NEA populations observable today with 1–2 m facilities. We calculate preliminary orbits for all unknown objects, classifying them as official discoveries, later identifications and unknown outstanding objects. The orbital elements a, e, i calculated by FIND_ORB software for the official discoveries and later identified objects are very similar with the published elements which take into account longer observational arcs; thus preliminary orbits were used in statistics for the whole unknown dataset. We present a basic model which can be used to distinguish between MBAs and potential NEAs in any sky survey. Based on three evaluation methods, most of our unknown objects are consistent with MBAs, while up to 16 unknown objects could represent NEO candidates and four represent our best NEO candidates. We assessed the observability of the unknown MBA and NEA populations using 1 and 2 m surveys. Employing a 1 m facility, one can observe today fewer unknown objects than known MBAs and very few new NEOs. Using a 2 m facility, a slightly larger number of unknown than known asteroids could be detected in the main belt. Between 0.1 and 0.8 new NEO candidates per square degree could be discovered using a 2 m telescope.     

Mining the ESO WFI and INT WFC archives for known Near Earth Asteroids. Mega‐Precovery software

The ESO/MPG WFI and the INT WFC wide field archives comprising 330 000 images were mined to search for serendip‐itous encounters of known Near Earth Asteroids (NEAs) and Potentially Hazardous Asteroids (PHAs). A total of 152 as‐teroids (44 PHAs and 108 other NEAs) were identified using the PRECOVERY software, their astrometry being measured on 761 images and sent to the Minor Planet Centre. Both recoveries and precoveries were reported, including prolonged orbital arcs for 18 precovered objects and 10 recoveries. We analyze all new opposition data by comparing the orbits fitted before and after including our contributions. We conclude the paper presenting “Mega‐Precovery”, a new online service focused on data mining of many instrument archives simultaneously for one or a few given asteroids. A total of 28 instrument archives have been made available for mining using this tool, adding together about 2.5 million images forming the “Mega‐Archive”     

The EURONEAR Lightcurve Survey of Near Earth Asteroids

This data paper presents lightcurves of 101 near Earth asteroids (NEAs) observed mostly between 2014 and 2017 as part of the EURONEAR photometric survey using 11 telescopes with diameters between 0.4 and 4.2 m located in Spain, Chile, Slovakia and Romania. Most targets had no published data at the time of observing, but some objects were observed in the same period mainly by B. Warner, allowing us to confirm or improve the existing results. To plan the runs and select the targets, we developed the public Long Planning tool in PHP. For preliminary data reduction and rapid follow-up planning we developed the LiDAS pipeline in Python and IRAF. For final data reduction, flux calibration, night linkage and Fourier fitting, we used mainly MPO Canopus. Periods of 18 targets are presented for the first time, and we could solve or constrain rotation for 16 of them. We secured periods for 45 targets (\(U\sim 3\)), found candidate periods for other 16 targets (\(U\sim 2\)), and we propose tentative periods for other 32 targets (\(U\sim 1\)). We observed 7 known or candidate binary NEAs, fiting 3 of them (2102 Tantalus, 5143 Heracles and 68348). We observed 8 known or candidate tumbling NEAs, deriving primary periods for 3 objects (9400, 242708 and 470510). We evidenced rapid oscillations (few minutes) and could fit fast tentative periods TP2 for 5 large newly suggested tumbling or binary candidates (27346, 112985, 285625, 377732, 408980), probably discovering at least one new binary NEA (2011 WO41). We resolved periods of 4 special objects which include two proposed space mission targets (163249 and 101955 Bennu), one very fast rotator NEA discovered by EURONEAR (2014 NL52) and the “Halloween asteroid” (2015 TB145). Using Mercator in simultaneous 3 band MAIA imaging, we could evidence for the first time clear variation in the color lightcurves of 10 NEAs. The periods derived from the g–r color lightcurves are found to match individual band period fits for 4 NEAs (27346, 86067, 112985 and 275976).     

On climate change and economic analysis

Climatic change and its societal impacts have been a topic of considerable concern over the last decade. Economic analysis would seem to have much to contribute to society's understanding of the importance of this issue, yet the contributions of prior analyses have been limited. Consideration from a decision-analytic perspective suggests that more useful insights could be gained by evaluating the effects of a changing (rather than changed) climate and the potential adaptations of society to that changing climate. Linking physical and economic models of differing levels of aggregation can be useful in analyzing a changing climate.S. T. Sonka is Professor, Department of Agricultural Economics, University of Illinois at Urbana-Champaign, and Principal Scientist at the Illinois State Water Survey. P. J. Lamb is Principal Scientist and Head, Climate and Meteorology Section, Illinois State Water Survey, and Professor, Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign.