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Abstract A permanent automated continuous seismic CO2 geosequestration monitoring system for was installed at CO2CRC Otway Project site (Victoria, Australia) in early 2020. The system is composed of five deviated ∼1600 m deep wells equipped with distributed acoustic sensing (DAS) acting as seismic receivers and nine seismic orbital vibrators (SOV) as seismic sources. DAS recording is performed continuously by three iDASv3 units. Each SOV operates for 2.5 h at a time, and hence all SOVs operating sequentially (during daytime only) produce in a single vintage every two days. Each vintage consists of 45 offset VSP transects covering predicted CO2 plume migration paths over ∼0.7 km2 area. An automated data processing implemented on-site reduces data size from ∼1.3 TB/day to ∼500 MB/day with the results transmitted to the office daily. The repeatability analysis based on pre-injection data (acquired from May to October 2020 before the injection start in December 2020) shows that variability of SOV performance is the main source of non-repeatability while borehole measurements are stable. An SOV waveform could reach NRMS value from 20 to 100 % within a few days. However, deconvolution of the seismograms with the waveform of the direct wave reduces the repeatability to within 10–15 % NRMS.

Data Center Energy Benchmarking: Part 5 - Case Studies on a Corporate Data Center (No. 22) Final Report August 2007 Final Report Prepared by Tengfang Xu and Steve Greenberg Lawrence Berkeley National Laboratory (LBNL) Berkeley CA 94720 Draft provided by EYP Mission Critical Facilities Los Angeles, CA 90064 and Landsberg Engineering, P.C. Clifton Park, NY 12065

The overarching goal of this work is to develop and demonstrate methods that support effective agro-pastoral risk management in a changing climate. Disaster mitigation strategies, such as the Sendai Framework for Disaster Risk Reduction (SFDRR), emphasize the need to address underlying causes of disaster risk and to prevent the emergence of new risks. Such assessments can be difficult, because they require transforming changes in meteorological outcomes into sector-specific impact. While it is common to examine trends in seasonal precipitation and precipitation extremes, it is much less common to study how these trends interact with crop and pasture water needs. Here, we show that the Water Requirement (WR) component of the widely used Water Requirement Satisfaction Index (WRSI) can be used to enhance the interpretation of precipitation changes. The WR helps answer a key question: was the amount of rainfall received in a given season enough to satisfy a crop or pasture's water needs? Our first results section focuses on analyzing spatial patterns of climate change. We show how WR values can be used to translate east African rainfall declines into estimates of crop and rangeland water deficits. We also show that increases in WR, during recent droughts, has intensified aridity in arid regions. In addition, using the PWB, we also show that precipitation increases in humid areas of western east Africa have been producing increasingly frequent excessive rainfall seasons. The second portion of our paper focuses on assessing temporal outcomes for a fixed location (Kenya) to support drought-management scenario development. Kenyan rainfall is decreasing and population is increasing. How can we translate this data into actionable information? The United Nations and World Meteorological Organization advise nations to proactively plan for agro-hydrologic shocks by setting aside sufficient grain and financial resources to help buffer inevitable low-crop production years. We show how precipitation, WR, crop statistics, and population data can be used to help guide 1-in-10 and 1-in-25-year low crop yield scenarios, which could be used to guide Kenya's drought management planning and development. The first and second research components share a common objective: using the PWB to translate rainfall data into more actionable information that can inform disaster risk management and development planning.

Concerns have been raised about attribution of species range shifts to anthropogenic climate change. Species paleo-range projections are emerging as a means to broaden understanding of range shifts and could be applied to assist in attribution. Apparent recent range contraction in the Quiver Tree (Aloidendron dichotomum (Masson) Klopper and Gideon F.Sm) has been attributed to anthropogenic climate change, but this has been challenged. We simulated the paleo- and future geographic range of A. dichotomum under changing climate using species distribution models (SDMs) to provide a broader perspective on its range dynamics. Ensemble modelling of the Last Glacial Maximum (LGM), mid-Holocene, current, and projected 2070 time periods simulates a paleo-historical poleward expansion of suitable bioclimatic space for this species under natural climate change post-LGM, and projects an eastward shift towards 2070. During the LGM, suitable bioclimatic space for A. dichotomum was simulated to be restricted to the equatorward part of its current range. During the Pleistocene/mid-Holocene climate transition period, the species’ range is predicted to have expanded significantly polewards at an average rate of 0.4 km per decade, assuming constant tracking of its optimal climatic niche. By 2070, suitable bioclimatic space is projected to expand further eastward into the summer rainfall region of South Africa, and contract in its equatorward reaches. Simulated post-LGM shifts roughly match expectations based on preliminary phylogenetic information, further supporting the attribution of current population declines to anthropogenic climate change drivers. Equatorward populations are required to migrate south-eastwards at a rate roughly 15 times faster than that calculated for the LGM/mid-Holocene climate transition period to avoid local extirpation. A preliminary analysis of range-wide genetic variation reveals a cline of variation, with generally higher levels in the central and more northerly part of the species distribution, as expected from the proposed paleo-range of the species. A more detailed analysis of the species’ phylogeographic history could be used to test the proposed paleo-range dynamics presented here, and if confirmed, would provide strong support for the use of this species as an indicator of anthropogenic climate change and a powerful case study for testing the implementation of conservation actions.

This paper provides a meta-analysis of a broad set of recent studies of the economic impacts of climate change mitigation policies. It evaluates the influences of the impacts of causal factors, key economic assumptions and macroeconomic linkages on the outcome of these studies. A quantile regression analysis is also performed on the meta sample, to evaluate the robustness of those key factors throughout the full range of macro findings. Results of these analyses suggest that study results are strongly driven by data inputs, economic assumptions and modeling approaches. However, they are sometimes affected in counterintuitive ways.

Abstract Desalination powered by renewable energy sources is an attractive solution to address the worldwide water-shortage problem without contributing significant to greenhouse gas emissions. A promising system for renewable energy desalination is the utilization of low-temperature direct contact membrane distillation (DCMD) driven by a thermal solar energy system, such as a salt-gradient solar pond (SGSP). This investigation presents the first experimental study of fresh water production in a coupled DCMD/SGSP system. The objectives of this work are to determine the experimental fresh water production rates and the energetic requirements of the different components of the system. From the laboratory results, it was found that the coupled DCMD/SGSP system treats approximately six times the water flow treated by a similar system that consisted of an air–gap membrane distillation unit driven by an SGSP. In terms of the energetic requirements, approximately 70% of the heat extracted from the SGSP was utilized to drive thermal desalination and the rest was lost in different locations of the system. In the membrane module, only half of the useful heat was actually used to transport water across the membrane and the remainder was lost by conduction in the membrane. It was also found that by reducing heat losses throughout the system would yield higher water fluxes, pointing out the need to improve the efficiency throughout the DCMD/SGSP coupled system. Therefore, further investigation of membrane properties, insulation of the system, or optimal design of the solar pond must be addressed in the future.

AbstractXylella fastidiosais a bacterium that infects crops like grapevines, coffee, almonds, citrus and olives, causing economically devastating damage. There is, however, little understanding of the genes that contribute to resistance, the genomic architecture of resistance, and the potential role of climate in shaping resistance, in part because major crops like grapevines (V. vinifera) are not resistant to the bacterium. Here we studied a wild grapevine species,Vitis arizonica, that segregates for resistance toX. fastidiosa. Using genome-wide association, we identified candidate genes that mediate the host response toX. fastidiosainfection. We uncovered evidence that resistance requires genes from multiple genomic regions, based on data from breeding populations and from additionalVitisspecies. We also inferred that resistance evolved more than once in the wild, suggesting that wildVitisspecies may be a rich source for resistance alleles and mechanisms. Finally, resistance inV. arizonicawas climate dependent, because individuals from low (< 10°C) temperature locations in the wettest quarter were typically susceptible to infection, likely reflecting a lack of pathogen pressure in these climates. Surprisingly, climate was nearly as effective a predictor of resistance phenotypes as some genetic markers. This work underscores that pathogen pressure is likely to increase with climate, but it also provides genetic insight and tools for breeding and transforming resistant crops.