Evaluating property buyouts and disaster recovery assistance (Rebuild) options in Canada: A comparative analysis of Constance Bay,Ontario and Pointe Gatineau,Quebec

Natural Hazards - How have property buyouts and disaster recovery assistance programs been implemented in Canadian communities? This paper compares contrasting policies and programs in two Canadian...     

China’s national carbon emissions trading scheme: lessons from the pilot emission trading schemes,academic literature,and known policy details

Upon completion, China’s national emissions trading scheme (C-ETS) will be the largest carbon market in the world. Recent research has evaluated China’s seven pilot ETSs launched from 2013 on, and academic literature on design aspects of the C-ETS abounds. Yet little is known about the specific details of the upcoming C-ETS. This article combines currently understood details of China’s national carbon market with lessons learned in the pilot schemes as well as from the academic literature. Our review follows the taxonomy of Emissions Trading in Practice: A Handbook on Design and Implementation (Partnership for Market Readiness & International Carbon Action Partnership. (2016). Retrieved from www.worldbank.org): The 10 categories are: scope, cap, distribution of allowances, use of offsets, temporal flexibility, price predictability, compliance and oversight, stakeholder engagement and capacity building, linking, implementation and improvements.

Key policy insights

• Accurate emissions data is paramount for both design and implementation, and its availability dictates the scope of the C-ETS.

• The stakeholder consultative process is critical for effective design, and China is able to build on its extensive experience through the pilot ETSs.

• Current policies and positions on intensity targets and Clean Development Mechanism (CDM) credits constrain the market design of the C-ETS.

• Most critical is the nature of the cap. The currently discussed rate-based cap with ex post adjustment is risky. Instead, an absolute, mass-based emissions cap coupled with the conditional use of permits would allow China to maintain flexibility in the carbon market while ensuring a limit on CO₂ emissions.

     

High-frequency climate oscillations drive ice-off variability for Northern Hemisphere lakes and rivers

Climatic Change - This study examines the climatic drivers of ice-off dates for lakes and rivers across the Northern Hemisphere. Most lakes and rivers have trended toward earlier ice-off dates over...     

Sediment routing in the Zagros foreland basin: Drainage reorganization and a shift from axial to transverse sediment dispersal in the Kurdistan region of Iraq

In the northwestern sector of the Zagros foreland basin, axial fluvial systems initially delivered fine-grained sediments from northwestern source regions into a contiguous basin, and later transverse fluvial systems delivered coarse-grained sediments from northeastern sources into a structurally partitioned basin by fold-thrust deformation. Here we integrate sedimentologic, stratigraphic, palaeomagnetic and geochronologic data from the northwestern Zagros foreland basin to define the Neogene history of deposition and sediment routing in response to progressive advance of the Zagros fold-thrust belt. This study constrains the depositional environments, timing of deposition and provenance of nonmarine clastic deposits of the Injana (Upper Fars), Mukdadiya (Lower Bakhtiari) and Bai-Hasan (Upper Bakhtiari) Formations in the Kurdistan region of Iraq. Sediments of the Injana Formation (~12.4–7.75 Ma) were transported axially (orogen-parallel) from northwest to southeast by meandering and low-sinuosity channel belt system. In contrast, during deposition of the Mukdadiya Formation (~7.75–5 Ma), sediments were delivered transversely (orogen-perpendicular) from northeast to southwest by braided and low-sinuosity channel belt system in distributive fluvial megafans. By ~5 Ma, the northwestern Zagros foreland basin became partitioned by growth of the Mountain Front Flexure and considerable gravel was introduced in localized alluvial fans derived from growing topographic highs. Foredeep accumulation rates during deposition of the Injana, Mukdadiya and Bai-Hasan Formations averaged 350, 400 and 600 m/Myr respectively, suggesting accelerated accommodation generation in a rapidly subsiding basin governed by flexural subsidence. Detrital zircon U-Pb age spectra show that in addition to sources of Mesozoic-Cenozoic cover strata, the Injana Formation was derived chiefly from Palaeozoic-Precambrian (including Carboniferous and latest Neoproterozoic) strata in an axial position to the northwest, likely from the Bitlis-Puturge Massif and broader Eastern Anatolia. In contrast, the Mukdadiya and Bai-Hasan Formations yield distinctive Palaeogene U-Pb age peaks, particularly in the southeastern sector of the study region, consistent with transverse delivery from the arc-related terranes of the Walash and Naopurdan volcano-sedimentary groups (Gaveh-Rud domain?) and Urumieh-Dokhtar magmatic arc to the northeast. These temporal and spatial variations in stratigraphic framework, depositional environments, sediment routing and compositional provenance reveal a major drainage reorganization during Neogene shortening in the Zagros fold-thrust belt. Whereas axial fluvial systems initially dominated the foreland basin during early orogenesis in the Kurdistan region of Iraq, transverse fluvial systems were subsequently established and delivered major sediment volumes to the foreland as a consequence of the abrupt deformation advance and associated topographic growth in the Zagros.     

A probabilistic framework for improving reverse geocoding output

Reverse geocoding, which transforms machine‐readable GPS coordinates into human‐readable location information, is widely used in a variety of location‐based services and analysis. The output quality of reverse geocoding is critical because it can greatly impact these services provided to end‐users. We argue that the output of reverse geocoding should be spatially close to and topologically correct with respect to the input coordinates, contain multiple suggestions ranked by a uniform standard, and incorporate GPS uncertainties. However, existing reverse geocoding systems often fail to fulfill these aims. To further improve the reverse geocoding process, we propose a probabilistic framework that includes: (1) a new workflow that can adapt all existing address models and unitizes distance and topology relations among retrieved reference data for candidate selections; (2) an advanced scoring mechanism that quantifies characteristics of the entire workflow and orders candidates according to their likelihood of being the best candidate; and (3) a novel algorithm that derives statistical surfaces for input GPS uncertainties and propagates such uncertainties into final output lists. The efficiency of the proposed approaches is demonstrated through comparisons to the four commercial reverse geocoding systems and through human judgments. We envision that more advanced reverse geocoding output ranking algorithms specific to different application scenarios can be built upon this work.     

Spatially explicit models for exploring COVID‐19 lockdown strategies

This article describes two spatially explicit models created to allow experimentation with different societal responses to the COVID‐19 pandemic. We outline the work to date on modeling spatially explicit infective diseases and show that there are gaps that remain important to fill. We demonstrate how geographical regions, rather than a single, national approach, are likely to lead to better outcomes for the population. We provide a full account of how our models function, and how they can be used to explore many different aspects of contagion, including: experimenting with different lockdown measures, with connectivity between places, with the tracing of disease clusters, and the use of improved contact tracing and isolation. We provide comprehensive results showing the use of these models in given scenarios, and conclude that explicitly regionalized models for mitigation provide significant advantages over a “one‐size‐fits‐all” approach. We have made our models, and their data, publicly available for others to use in their own locales, with the hope of providing the tools needed for geographers to have a voice during this difficult time.     

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

ABSTRACT

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in distributed computing frameworks. To efficiently process big geospatial data, this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System (HDFS) from the following aspects: (1) improve I/O efficiency by adopting the chunking data structure; (2) keep the workload balance and high data locality by building the global index (k-d tree); (3) enable Spark and HDFS to natively support geospatial raster data formats (e.g., HDF4, NetCDF4, GeoTiff) by building the local index (hash table); (4) index the in-memory data to further improve geospatial data queries; (5) develop a data repartition strategy to tune the query parallelism while keeping high data locality. The above strategies are implemented by developing the customized RDDs, and evaluated by comparing the performance with that of Spark SQL and SciSpark. The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency.     

Network analysis to inform invasive species spread among lakes

Often facilitated by human-mediated pathways,aquatic invasive species are a threat to the health and biodiversity of global ecosystems.We present a novel approach incorporating survey data of watercraft movement in a social network analysis to reconstruct potential pathways of aquatic invasive species spread between lakes.As an example,we use the green alga Nitellopsis obtusa,also known as starry stonewort,an aquatic invasive species affecting the Great Lakes region in the United States and Canada.The movement of algal fragments via human-mediated pathways(i.e.,watercraft)has been hypothesized as the primary driver of starry stonewort invasion.We used survey data collected at boat ramps during the 2013 and 2014 openwater seasons to describe the flow of watercraft from Lake Koronis,where N.obtusa was first detected in Minnesota,to other lakes in the state.Our results suggest that the risk of N.obtusa expansion is not highly constrained by geographic proximity and management efforts should consider highly connected lakes.Estimating human movement via network analysis may help to explain past and future routes of aquatic invasive species infestation between lakes and can improve evidence-based prevention and control efforts.     

Network analysis to inform invasive species spread among lakes

Often facilitated by human-mediated pathways,aquatic invasive species are a threat to the health and biodiversity of global ecosystems.We present a novel approach incorporating survey data of watercraft movement in a social network analysis to reconstruct potential pathways of aquatic invasive species spread between lakes.As an example,we use the green alga Nitellopsis obtusa,also known as starry stonewort,an aquatic invasive species affecting the Great Lakes region in the United States and Canada.The movement of algal fragments via human-mediated pathways(i.e.,watercraft)has been hypothesized as the primary driver of starry stonewort invasion.We used survey data collected at boat ramps during the 2013 and 2014 openwater seasons to describe the flow of watercraft from Lake Koronis,where N.obtusa was first detected in Minnesota,to other lakes in the state.Our results suggest that the risk of N.obtusa expansion is not highly constrained by geographic proximity and management efforts should consider highly connected lakes.Estimating human movement via network analysis may help to explain past and future routes of aquatic invasive species infestation between lakes and can improve evidence-based prevention and control efforts.     

Effect of polychromatic X‐ray microtomography imaging on the amino acid content of the Murchison CM chondrite

X‐ray microcomputed tomography (μCT) is a useful means of characterizing cosmochemical samples such as meteorites or robotically returned samples. However, there are occasional concerns that the use of μCT may be detrimental to the organic components of a chondrite. Small organic compounds such as amino acids comprise up to ~10% of the total solvent extractable carbon in CM carbonaceous chondrites. We irradiated three samples of the Murchison CM carbonaceous chondrite under conditions akin to and harsher than those typically used during typical benchtop X‐ray μCT imaging experiments to determine if detectable changes in the amino acid abundance and distribution relative to a nonexposed Murchison control sample occurred. After subjecting three meteorite samples to ionizing radiation dosages between ~300 Gray (Gy) and 3 kGy with bremstrahlung X‐rays, we analyzed the amino acid content of each sample. Within sampling and analytical errors, we cannot discern differences in the amino acid abundances and amino acid enantiomeric ratios when comparing the control samples (nonexposed Murchison) and the irradiated samples. We conclude that a polychromatic X‐ray μCT experiment does not alter the abundances of amino acids to a degree greater than how well those abundances are measured with our techniques and therefore any damage to amino acids is minimal.