Regions Of High Vulnerability Research Articles

Rising summer river water temperature across Canada: spatial patterns and hydroclimatic controls

Understanding the spatio-temporal variability of climate-induced river water temperature change is critical for identifying hotspots and assessing the impacts on ecological and socioeconomic systems. Here, we employ the air2stream model reconstructed river temperature records for 106 stations in Canada (Nash Sutcliffe coefficient goodness-of-fit: minimum = 0.79; median = 0.93; maximum = 0.97) to analyze summer temperature changes over the years 1980–2018. Results reveal widespread river temperature increases from June to September, with significantly increasing trends for about 40%–60% of stations. Additionally, we find significantly rising 7-day maximum temperature and increasing occurrences over the critical 18 and 20 °C thresholds for about 30%–65% of stations. Furthermore, by employing the Ward’s agglomerative hierarchical clustering machine learning (ML) method, we identify eight regions of spatially coherent variability and change. We find that the south-east, coast and northern prairies are the regions of high vulnerability because of the likely impacts of rising summer water temperatures on cold-water aquatic species. Additionally, by using the random forests ML method, we demonstrate that mean air temperature and its trends are the primary drivers of mean water temperature and trends, respectively. Thus, with the projected enhanced air temperature increase across Canada, an amplified future summer river warming can be expected, which could have severe consequences, particularly in already thermally-stressed river systems.

Estimating the impact of short-term sulfur dioxide exposure on the COVID-19 incidence: A spatiotemporal study in the continental United States

Numerous studies have investigated the association of short-term SO2 exposure with the incidence of COVID-19, but few studies have focused on the spatiotemporal heterogeneity in the associations, which are crucial for identifying high-vulnerability regions and periods of the epidemic and formulating cost-effective prevention policies. We used a recently proposed multi-stage approach to explore this issue, with the continental US serving as an example. Firstly, rough state-specific SO2-COVID-19 associations were independently estimated by time-series generalized additive model (GAMs). A Leroux-prior-based conditional autoregression (LCAR) was used to spatially smooth the estimations. A time-varying GAM-LCAR analytical process was used to obtain the temporal change of association. Finally, a spatiotemporal LCAR was used to explore whether vaccination rates and temperature were the effect modifiers. The results showed significant positive associations in the middle and northeastern regions with relative risks (RRs) varying from 1.10 to 1.25, weak positive associations in the western and middle-eastern regions with RRs less than 1.10, and insignificant associations in the southeastern regions. On average, a 1-ppb increase of SO2 corresponded to a 6.25% (95%CI: 3.71%–9.00%) increase in the cases of COVID-19. In the time dimension, the SO2-COVID-19 association exhibited no significance from April 2020 to the end of 2020, and then gradually rose from January 2021 to December 2021. The vaccination rate was recognized as a significant modifier with a stronger association at a higher rate. Such spatiotemporal pattern suggested that middle and northeastern regions and the post-pandemic era deserved more attention and targeted cost-effective policies.

Social Entrepreneurial Ecosystems in Upper-Middle-Income Countries: Social Policy and Sustainable Economic Development Implications

This study aims to explore how a region’s degree of vulnerability influences the perceived level of support toward social entrepreneurship from a social entrepreneurial ecosystem perspective. The study of social entrepreneurial ecosystems (SEEs) constitutes a promising area for its potential to support high-impact entrepreneurs, but they are currently underexplored in upper-middle-income countries. This study also combines a macro-level (countries) and a meso-level (vulnerability regions) analysis to better understand how national policies may affect the perceptions of different ‘regions’ and, consequently, sustainable economic development. This study follows principal component analysis and non-parametric statistics to compare the means of the countries and the levels of regions’ vulnerabilities based on the Global Entrepreneurship Monitor’s regional data from Chilean (n = 276) and Mexican (n = 188) experts. At the macro level, the results show that experts in Chile have a better perception of social policies for social entrepreneurship than their counterparts in Mexico. At the meso-level, experts in high-vulnerability regions have a better perception of the social ecosystem dynamism than those in the low-vulnerability regions. The results contribute to the urgent dialogue to set up strategies that allow upper-middle-income countries and their regions to achieve greater impact and sustainability.

Investigation of rivers planform change in a semi-arid region of high vulnerability to climate change: A case study of Tigris River and its tributaries in Iraq

In this paper, the planform changes of rivers in a semi-arid region, which are particularly vulnerable to the impacts of climate change, were investigated. This research provides valuable insights into the adaptation and mitigation efforts necessary for effective climate change risk management in this area. A comprehensive analysis was carried out using satellite images and GIS to investigate the changes in the planform of the Mosul-Makhool reach of the Tigris River and its Lesser Zab and Greater Zab tributaries as a case study. To date, no studies have examined the impact of dam construction and climate change on the planform changes of these rivers. A survey was conducted to analyze the channel planform from 1979 to 2021. Various channel planform features were computed, including sinuosity index, braiding index, erosion and accretion, migration rate, confluence point, and junction angle. Results demonstrated that the Tigris River has low meandering features, the Lesser Zab has moderate meandering features, and the Greater Zab has the highest sinuosity index value of 1.95, which indicates very high meandering features. The change in the sinuosity index was fairly small. Generally, the rivers tended slightly towards deposition rather than erosion. The migration rate of the meandering rivers was high, with the highest value recorded in the Tigris River and Greater Zab. The average movement rate of the Greater Zab-Tigris River confluence was 31.81 m/year, and the Lesser Zab-Tigris River confluence moved 20.2 m/year. The study results demonstrate that climate change and dam construction significantly impact the rivers' planform in semi-arid regions. This investigation holds significant importance in evaluating morphodynamic changes in river systems worldwide with great detail and accuracy using satellite data.

Coastal vulnerability assessment for the coast of Tamil Nadu, India-a geospatial approach.

A coastal region is a section of land that borders a significant body of water, often the sea or ocean. Despite their productivity, they are sensitive to even little alterations in the outside environment. This study aims to develop a spatial coastal vulnerability index (CVI) map for the Tamil Nadu coast of India, which has diverse coastal and marine environments that are ecologically fragile zones. Climate change is expected to increase the intensity and frequency of severe coastal hazards, such as rising sea levels, cyclones, storm surges, tsunamis, erosion, and accretion, severely impacting local environmental and socio-economic conditions. This research employed expert knowledge, weights, and scores from the analytical hierarchy process (AHP) to create vulnerability maps. The process includes the integration of various parameters such as geomorphology, Land use and land cover (LULC), significant wave height (SWH), rate of sea level rise (SLR), shoreline change (SLC), bathymetry, elevation, and coastal inundation. Based on the results, the very low, low, and moderate vulnerability regions comprise 17.26%, 30.77%, and 23.46%, respectively, whereas the high and very high vulnerability regions comprise 18.20% and 10.28%, respectively. The several locations tend to be high and very highdue to land-use patterns and coastal structures, but very few are contributed by geomorphological features. The results are validated by conducting a field survey in a few locations along the coast. Thus, this study establishes a framework for decision-makers to implement climate change adaptation and mitigation actions in coastal zones.

Refined assessment of flash flood vulnerability in Linzhi based on spatialization and GIS

Flash floods are one of the most serious mountain disasters in Linzhi, China, pose a grave threat to the lives and property of the residents. However, the current regional vulnerability research cannot meet the needs of refined disaster prevention and mitigation in mountainous areas. Therefore, to address this knowledge gap, this study presented a vulnerability assessment framework base on spatialization technique along with the triangular fuzzy number-based analytic hierarchy process (TFN-AHP) and random forest (RF) model. To achieve this goal, an assessment system containing 12 indicators was constructed from the three perspectives of exposure, susceptibility and coping capacity. Firstly, factor spatialization is introduced in data preprocessing. Then TFN-AHP and the RF model were used to calculate the exposure, susceptibility, and coping capacity. Finally, the spatial distribution of the vulnerability throughout Linzhi was obtained. According to the results, the exposure, susceptibility and coping capacity in most areas are extremely low and low, accounting for 74.1%, 99% and 99%, respectively. The vulnerability is similar to the exposure that most of the regions have extremely low vulnerability and low vulnerability, accounting for 83.5%. The moderate vulnerability regions account for 8.5%, and the high vulnerability regions account for only 1%. The assessment results show that high-exposure areas mainly exhibit a linear distribution, and mainly include river valleys, cultivated land, and residential areas. Obviously, these areas are mainly distributed in the population and economic agglomeration areas and on low-altitude terrain. The distribution of high and comparatively high vulnerability zones, where economic and human activities are considerably high, are closely to the topography of the catchment. Thus, the results of this study provide scientific and technological evidence for resettlement, population distribution adjustment, and prevention and mitigation of flash floods in Linzhi.

Comprehensive Vulnerability Assessment of Urban Areas Using an Integration of Fuzzy Logic Functions: Case Study of Nasiriyah City in South Iraq

Globally, urbanisation has been the most significant factor causing land use and land cover changes due to accelerated population growth and limited governmental regulation. Urban communities worldwide, particularly in Iraq, are on the frontline for dealing with threats associated with environmental degradation, climate change and social inequality. However, with respect to the effects of urbanization, most previous studies have overlooked ecological problems, and have disregarded strategic environmental assessment, which is an effective tool for ensuring sustainable development. This study aims to provide a comprehensive vulnerability assessment model for urban areas experiencing environmental degradation, rapid urbanisation and high population growth, to help formulate policies for urban communities and to support sustainable livelihoods in Iraq and other developing countries. The proposed model was developed by integrating three functions of fuzzy logic: the fuzzy analytic hierarchy process, fuzzy linear membership and fuzzy overlay gamma. Application of the model showed that 11 neighbourhoods in the study area, and more than 175,000 individuals, or 25% of the total population, were located in very high vulnerability regions. The proposed model offers a decision support system for allocating required financial resources and efficiently implementing mitigation processes for the most vulnerable urban areas.

Facilitating entrepreneurship in the failing Cuban economic model?

Purpose This study aims to understand the necessity of entrepreneurship in a poor emerging economy, where the supportive entrepreneurial ecosystem is not in place. Design/methodology/approach In the years 2015 and 2019, this study survey first-time small-scale emerging entrepreneurs within the new entrepreneurial ecosystem in Cuba. Findings The results suggest that the entrepreneurial environment has deteriorated and declined over this period. The study contributes to the understanding of high-vulnerability regions and poverty conditions as found in some emerging economies. This study contributes to the wider literature on policies that inhibit or stimulate necessity entrepreneurship in emerging economies. Originality/value The study responds to calls for a better understanding by offering new insights into necessity entrepreneurship in challenging contexts under poverty and crisis; and the ways for recovery. It provides insights into the underexplored Cuban economy.

Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using rangewide monitoring data.

Climate change is expected to alter the distribution and abundance of tree species, impacting ecosystem structure and function. Yet, anticipating where this will occur is often hampered by a lack of understanding of how demographic rates, most notably recruitment, vary in response to climate and competition across a species range. Using large-scale monitoring data on two dry woodland tree species (Pinus edulis and Juniperus osteosperma), we develop an approach to infer recruitment, survival, and growth of both species across their range. In doing so, we account for ecological and statistical dependencies inherent in large-scale monitoring data. We find that drying and warming conditions generally lead to declines in recruitment and survival, but the strength of responses varied between species. These climate conditions point to geographic regions of high vulnerability for particular species, such as Pinus edulis in northern Arizona, where both survival and recruitment are low. Our approach provides a path forward for leveraging emerging large-scale monitoring and remotely sensed data to anticipate the impacts of global change on species distributions.

Surface Subsidence in Urbanized Coastal Areas: PSI Methods Based on Sentinel-1 for Ho Chi Minh City

In Ho Chi Minh City (HCMC), Vietnam, though at present flooding is merely a recurring nuisance, there is increasing concern that a combination of impending climate change and rapid urbanization will significantly exacerbate the situation. Given the significant measures taken in HCMC to reduce groundwater extraction and sea-level rise (SLR) inundation since the most recent subsidence studies, we aim to update and contribute to the subsidence information of HCMC with continuous temporal coverage from 2017 to 2019. In this study, we use Persistent Scatterer Interferometry (PSI) with Copernicus Sentinel-1 data and open source tools to determine current subsidence rates within the urban center of HCMC. Additionally, the scalability of this method and use of freely accessible data allows for continuous updating and monitoring of this high-vulnerability region. The observed average subsidence rates were 3.3 mm per year with a maximum local subsidence of 5.3 cm per year. These results largely align with findings of previous studies and reflect similar spatial distributed subsidence patterns. Inundation risk awareness is enhanced by not only continued improved subsidence analysis, but also incorporating latest advancements in Digital Elevation Model (DEM) accuracy. This study compares local differences between traditionally used AW3D30 DEM with the CoastalDEM. Our findings indicate that although we identify lower than previously accepted elevations in the urban core, that stabilization of subsidence is observed in this same region.

Extreme climate variability weakens a major tropical agricultural hub

Abstract Agriculture is affected daily by climatic phenomena, but limited information is available on the impacts of extreme climate variability (ECV) in agricultural systems of tropical countries. Citrus was used as a model system to explore whether ECV scenarios cause severe impacts on the climatic suitability of the crop in the eastern plains of Colombia, a key agricultural hub for the country. Because this region is a national food basket, climate risks need to be identified across the territory. Our study developed species distribution modelling of citrus used to generate the first agro-climatic zonification for citrus in Colombia. We used this model to investigate the interannual ECV impacts based on the latest ensemble modelling approaches. The ECV scenarios in this study are unique and highly valuable because we analyze maximum and minimum interannual values recorded daily from 1980 to 2010 rather than monthly. Four citrus growing climatic zones were identified. In the worst-case scenarios, these zones experienced a loss of climatically suitable area by 50%. However, in some cases optimum areas remained unchanged and/or new suitable areas emerged. Strong rainfall and high temperatures triggered negative impacts in the most critically-affected zones, weakening a large proportion of the ideal climatic space for citrus growing. Our study provides new evidence that could be used to generate climate-based ecological indicators for regions of high vulnerability. Delimitation maps and modelling results may be used by citrus growers to develop more efficient citrus production systems in tropical conditions and ultimately increase resilience to climate variability.

Impact of climate change on vulnerability of freshwater resources: a case study of Mauritius

Freshwater resource availability in SIDS, including Mauritius, is on the verge of becoming a major constraint to socio-economic development. A freshwater vulnerability assessment was undertaken for the period of 2000–2015 to understand the present vulnerability of the water systems in Mauritius and a future vulnerability estimation. Currently, the freshwater sector has been classified as a moderately vulnerable sector with a Freshwater Vulnerability Index (FVI) of 0.36–0.38 derived from a resource availability of 1091–1184 m3/capita, a coefficient of rainfall variation of 0.206–0.220, a water exploitation rate of 72–76% and ecological degradation of 30–39% for the period of 2000–2015. For the period of 2020–2050 under a business as usual scenario, the freshwater sector remained in a moderate-vulnerability region whereby the water exploitation rate was found to be the most affected vulnerability parameter with an increase to 95% exploitation by 2050. Under the effects of climate change, the FVI increased to a range of 0.38–0.44 indicating a shift from moderate- to high-vulnerability region and the findings also indicate that the country is likely to enter into a water scarcity region (water availability of 100%) by 2040. For all three scenarios, the resource stress category showed the highest contribution on the calculated FVI with a share of contribution of 33–38% to the current FVI, 34–38% to the predicted FVI for a business as usual scenario and 40–43% to the predicted FVI under the effects of climate change.

Using virtual laboratories for disaster analysis – a case study of Taiwan

ABSTRACTDue to its geographic location, Taiwan frequently experiences severe natural disasters (for example earthquakes and typhoons) that significantly interrupt business operations and subsequently cause extensive financial losses. Prior work on economic losses resulting from such natural disasters in Taiwan has not considered regional and sectoral spillover effects. In this work, we estimate the economic impacts resulting from the 1999 Chichi earthquake, the 2009 typhoon Morakot, the 2016 Tainan earthquake, and the 2016 typhoon Megi. We do so in the new TaiwanLab, a collaborative virtual laboratory that is capable of generating a time-series of subnational multiregional input–output (MRIO) tables, capturing interregional transactions among 267 sectors across Taiwan’s 22 city-counties. We identify critical economic sectors in regions of high vulnerability to natural disasters. Our research is, thus, a credible reference to decision-making that determines regional and sectoral prioritisation for damage mitigation, improved resiliency, and faster recovery schedules.

Spatial Assessment of Urban Climate Change Vulnerability during Different Urbanization Phases

In urban areas, concentrated populations and societal changes intensify the influence of climate change. However, few studies have focused on vulnerability to climate-related risks on the scale of a single urban area. Against this backdrop, we reconstructed a spatial vulnerability framework based on the drivers-pressures-state-impact-response (DPSIR) model to reflect the complex interactions between urbanization and climate change and to integrate the natural and socio-economic factors of urban areas into this framework. Furthermore, to explore the relationship between rapid urbanization and climate change, we studied data from two years that represented different stages of urbanization. The results showed that the index framework was able to reconcile these two concepts to reflect the complex interactions between urbanization and climate change. The assessment results indicate that the overall degree of climate change vulnerability exhibits a generally increasing and dispersing trend after rapid urbanization. The increasing trend is influenced by an increase in low-vulnerability areas, and the dispersing trend is influenced by anthropogenic activities caused by rapid urbanization. The changes are reflected in the following observations: 1. The suburbs are affected by their own natural environmental characteristics and rapid urbanization; the vulnerability level has risen in most areas but has declined in certain inland areas. 2. High-vulnerability regions show minor changes during this stage due to the lasting impact of climate change. Finally, the main environmental problems faced by high-vulnerability areas are discussed based on existing research.

Object-based classification of cloudy coastal areas using medium-resolution optical and SAR images for vulnerability assessment of marine disaster

Efficient and accurate access to coastal land cover information is of great significance for marine disaster prevention and mitigation. Although the popular and common sensors of land resource satellites provide free and valuable images to map the land cover, coastal areas often encounter significant cloud cover, especially in tropical areas, which makes the classification in those areas non-ideal. To solve this problem, we proposed a framework of combining medium-resolution optical images and synthetic aperture radar (SAR) data with the recently popular object-based image analysis (OBIA) method and used the Landsat Operational Land Imager (OLI) and Phased Array type L-band Synthetic Aperture Radar (PALSAR) images acquired in Singapore in 2017 as a case study. We designed experiments to confirm two critical factors of this framework: one is the segmentation scale that determines the average object size, and the other is the classification feature. Accuracy assessments of the land cover indicated that the optimal segmentation scale was between 40 and 80, and the features of the combination of OLI and SAR resulted in higher accuracy than any individual features, especially in areas with cloud cover. Based on the land cover generated by this framework, we assessed the vulnerability of the marine disasters of Singapore in 2008 and 2017 and found that the high-vulnerability areas mainly located in the southeast and increased by 118.97 km 2 over the past decade. To clarify the disaster response plan for different geographical environments, we classified risk based on altitude and distance from shore. The newly increased high-vulnerability regions within 4 km offshore and below 30 m above sea level are at high risk; these regions may need to focus on strengthening disaster prevention construction. This study serves as a typical example of using remote sensing techniques for the vulnerability assessment of marine disasters, especially those in cloudy coastal areas.

Assessing the Vulnerability of Marine Fisheries in China: Towards an Inter-Provincial Perspective

China’s marine fisheries are undergoing large-scale environmental changes associated with climate change, marine pollution, and overfishing. The assessment of marine fisheries vulnerability has become extremely necessary for fisheries management and sustainable development. However, studies on China’s marine fisheries vulnerability remains sparse. This study aimed to provide an analysis of the inter-provincial level vulnerability of China’s marine fisheries under multiple disturbances. The vulnerability measure was composed of exposure, sensitivity, and adaptive capacity indicators specific to marine fisheries based on the Intergovernmental Panel on Climate Change (IPCC) definitions. Results showed that Liaoning, Hebei, Fujian, and Hainan provinces appeared to be the most vulnerable; Shanghai appeared to be less vulnerable among China’s 11 coastal provinces; and the key sources of vulnerability differed considerably among coastal regions. The high vulnerability regions could be divided into two different patterns according to the combination of exposure, sensitivity, and adaptive capacity, but they all had one thing in common: relatively low adaptive capacity. While some existing coercive measures to reduce dependence on fisheries were found to be helpful in China, the reality showed that appropriate adaptation measures such as improving fishermen’s education level and increasing vocational training may be helpful in enhancing the existing policy effectiveness.

Mapping the need for adaptation: assessing drought vulnerability using the livelihood vulnerability index approach in a mid-hill region of Nepal

ABSTRACTFor effective development and adaptation interventions in resource-poor regions to take place, it is critical to identify, at the highest spatial scale possible, regions of higher priority based on current needs and vulnerabilities. The index-based assessment of vulnerability to climate change and variability is typically used to identify administrative-level regions of high vulnerability using various socioeconomic and biophysical datasets. One method that combines both approaches at the community level consists of collecting highly resolved socio-economic data and using the livelihood vulnerability index (LVI) to assess population vulnerability to increased climate variability and shocks. We use this mixed-methods approach in mapping climate vulnerability of ten drought-prone villages in the central-east mid-hill region of Nepal. We integrate data from over 900 household surveys and national-level databases and identify spatial patterns in the different components of climate vulnerability. We assess to what extent climatic extremes or people's socioeconomic capacity contribute to vulnerability and may shape development needs at the sub-district scale. We find that the majority of our study area falls in the high vulnerability category with significant spatial variation. In some villages, there are different vulnerability classes in different wards, indicating that even within the lowest administrative units, there is a significant spatial variation in the level of vulnerability. Livelihood strategies, water availability, and topographic components played the most important role in determining overall vulnerability and we measure strong interconnections among different components. The interconnectedness nature of different vulnerability components is creating a self-reinforcing downward spiral of vulnerability that traps local communities in a state of heightened vulnerability. We conclude that adaptation strategies in highly vulnerable regions should include careful consideration of different livelihoods and environmental components, their fine-scale spatial variations, and interconnections.

Global vulnerability to agricultural drought and its spatial characteristics

As an important part of agricultural drought risk, agricultural drought vulnerability helps effectively prevent and alleviate drought impacts by quantifying the vulnerability as well as identifying its spatial distribution characteristics. In this study, global agricultural cultivation regions were chosen as the study area; six main crops (wheat, maize, rice, barley, soybean, sorghum) were selected as the hazard-affected body of agricultural drought. Then, global vulnerability to agricultural drought was assessed at a 0.5° resolution and finally, its distribution characteristics were revealed. The results indicated that the area percentages of different grades of global vulnerability to agricultural drought from low to very high were 38.96%, 28.41%, 25.37%, and 7.26%, respectively. This means that the total area percentage of high and very high vulnerability zones exceeded 30% of the study area. Although high and very high vulnerability zones were mainly distributed in arid and semi-arid regions, approximately 40% of those above were distributed in humid and semi-humid regions. In addition, only about 15% of the population in this study was located in the high vulnerability regions. Among the vulnerability factors, water deficit during the growing season and the irrigation area ratio are the key factors affecting regional vulnerability. Therefore, the vulnerability could be reduced by adjusting crop planting dates and structures as well as by improving irrigation level and capacity.

The spatial and temporal distribution of dendrite fragmentation in solidifying Al-Cu alloys under different conditions

The directional columnar solidification of Al-Cu alloy dendrites was studied in-situ by synchrotron X-ray radiography to investigate the spatial and temporal distribution of dendrite fragmentation, without and with an applied pulsed electromagnetic field (PEMF) and in different solidification directions. The differing arrangements had a strong and reproducible influence on fragmentation behaviour that was rationalised using a model of solute-driven re-melting of dendrite arms in microstructural regions of high vulnerability. Although absolute rates of fragmentation varied, all the fragmentation distributions had a characteristic peak in fragmentation rate at a distance of 500–800 μm into the mushy zone. Consistent with the need for solute-rich liquid flow for dendrite root re-melting, this peak was explained to occur under conditions where there was both comparatively steep liquid solute concentration gradients, measured directly from the radiographs, and relatively high permeability of the dendrite network to liquid flow.

An integrated methodology to develop a standard for landslide early warning systems

Abstract. Landslides are one of the most widespread and commonly occurring natural hazards. In regions of high vulnerability, these complex hazards can cause significant negative social and economic impacts. Considering the worldwide susceptibility to landslides, it is necessary to establish a standard for early warning systems specific to landslide disaster risk reduction. This standard would provide guidance in conducting landslide detection, prediction, interpretation, and response. This paper proposes a new standard consisting of seven sub-systems for landslide early warning. These include risk assessment and mapping, dissemination and communication, establishment of the disaster preparedness and response team, development of an evacuation map, standardized operating procedures, installation of monitoring and warning services, and the building of local commitment to the operation and maintenance of the entire program. This paper details the global standard with an example of its application from Central Java, one of 20 landslide-prone provinces in Indonesia that have used this standard since 2012.