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A 'lane change crash' is defined as a family of collisions that occurred when a driver attempts to change lane and strikes or is struck by a vehicle in the adjacent lane. One type of maneuver that is commonly used to avert a lane change crash involved aborting the intended lane change, and returning the vehicle to the original lane of the subject vehicle.
Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, De- CAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.
As the world enters the Anthropocene, the planet's environment is changing rapidly, putting critical ecosystem services at risk. Understanding and forecasting how ecosystems will change over the coming decades requires understanding the sensitivity of species to environmental change. The extant distribution of species and functional groups contains valuable information about the performance of different species in different environments. However, with high rates of environmental change, information inherent in ranges of many species will disappear, since that information exists only under quasi-equilibrium conditions. The information content of distributional data obtained now is greater than data obtained in the future. New remote sensing technologies can map chemical and structural traits of plant canopies and allow inference of trait and in many cases, species ranges. Current satellite remote sensing data can only produce relatively simple classifications, but new techniques have dramatically higher biological information content.
South Asia encompasses a wide and highly varied geographic region, and includes climate zones ranging from the mountainous Himalayan territory to the tropical lowland and coastal zones along alluvial floodplains. The region's climate is dominated by a monsoonal circulation that heralds the arrival of seasonal rainfall, upon which much of the regional agriculture relies. The spatial and temporal distribution of this rainfall is, however, not uniform over the region. Northern South Asia, central India, and the west coast receive much of their rainfall during the southwest monsoon season, between June and September. These rains partly result from the moisture transport accompanying the monsoonal winds, which move in the southwesterly direction from the equatorial Indian Ocean. Regions further south, such as south/southeast India and Sri Lanka, may receive rains from both the southwest monsoon, and also during the northeast monsoon season between October and December (with northeasterly monsoon wind flow and moisture flux), which results in a bi- or multi-modal rainfall distribution. In addition, rainfall across South Asia displays a large amount of intraseasonal and interannual variability. Interannual variability is influenced by many drivers, both natural (e.g., El Ni-Southern Oscillation; ENSO) and man-made (e.g., rising temperatures due to increasing greenhouse gas concentrations), and it is challenging to obtaining accurate time-series of annual rainfall, even amongst various observed data products, which display inconsistencies amongst themselves. These climatic and rainfall variations can further complicate South Asia's agricultural and water management. Agriculture employs at least 65 of the workforce in most South Asian countries, and nearly 80 of South Asia's poor inhabit rural areas. Understanding the response of current agricultural production to climate variability and future climate change is of utmost importance in securing food and livelihoods for South Asia's growing population. In order to assess the future of food and livelihood security across South Asia, the Agricultural Model Intercomparison and Improvement Project (AgMIP) has undertaken integrated climate-crop-economic assessments of the impact of climate change on food security and poverty in South Asia, encompassing Bangladesh, India, Nepal, Pakistan, and Sri Lanka. AgMIP has funded, on a competitive basis, four South Asian regional research teams (RRTs) and one South Asian coordination team (CT) to undertake climate-crop-economic integrated assessments of food security for many districts in each of these countries, with the goal of characterizing the state of food security and poverty across the region, and projecting how these are subject to change under future climate change conditions.
Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.
As countries take action to mitigate global warming, both by ratifying theUNFCCCParis Agreement and enacting the Kigali Amendment to the Montreal Protocol to manage hydrofluorocarbons (HFCs), it is important to consider the relative importance of the pertinent greenhouse gases and the distinct structure of their atmospheric impacts, and how the timing of potential greenhouse gas regulations would affect future changes in atmospheric temperature and ozone. HFCs should be explicitly considered in upcoming climate and ozone assessments, since chemistry-climate model simulations demonstrate that HFCs could contribute substantially to anthropogenic climate change by the mid- 21st century, particularly in the upper troposphere and lower stratosphere i.e., global average warming up to 0.19 Kat 80 hPa. The HFCmitigation scenarios described in this study demonstrate the benefits of taking early action in avoiding future atmospheric change: more than 90% of the climate change impacts of HFCs can be avoided if emissions stop by 2030.
Various land use changes driven by urbanization, conversion of grasslands and woodlands into farmlands, intensification of agricultural practices, deforestation, land fragmentation and degradation are taking place in Africa. In Kenya, agriculture is the main driver of land use conversions. The impacts of these land use changes are observable in land cover maps, and eventually in the hydrological systems. Reduction or change of natural vegetation cover types increases the speed of surface runoff and reduces water and nutrient retention capacities. This can lead to high nutrient inputs into lakes, resulting in eutrophication, siltation and infestation of floating aquatic vegetation. To assess if changes in land use could be contributing to increased phytoplankton blooms and sediment loads into Lake Victoria, we analyzed land use land cover data from Landsat, as well as surface chlorophyll-a and total suspended matter from MODIS-Aqua sensor.
Increased concentrations of ozone and fine particulate matter (PM2.5) since preindustrial times reflect increased emissions, but also contributions of past climate change. Here we use modeled concentrations from an ensemble of chemistry–climate models to estimate the global burden of anthropogenic outdoor air pollution on present-day premature human mortality, and the component of that burden attributable to past climate change. Using simulated concentrations for 2000 and 1850 and concentration–response functions (CRFs), we estimate that, at present, 470 000 (95% confidence interval, 140 000 to 900 000) premature respiratory deaths are associated globally and annually with anthropogenic ozone, and 2.1 (1.3 to 3.0) million deaths with anthropogenic PM2.5-related cardiopulmonary diseases (93%) and lung cancer (7%). These estimates are smaller than ones from previous studies because we use modeled 1850 air pollution rather than a counterfactual low concentration, and because of different emissions. Uncertainty in CRFs contributes more to overall uncertainty than the spread of model results. Mortality attributed to the effects of past climate change on air quality is considerably smaller than the global burden: 1500 (−20 000 to 27 000) deaths yr (exp -1) due to ozone and 2200 (−350 000 to 140 000) due to PM2.5. The small multi-model means are coincidental, as there are larger ranges of results for individual models, reflected in the large uncertainties, with some models suggesting that past climate change has reduced air pollution mortality.
The proliferation of vector-borne diseases are predicted to increase in a changing climate and Leishmaniases, as a vector-borne diseases, are re-emerging diseases in several regions of the world. In Morocco, during the last decade, a sharp increase in cutaneous leishmaniases cases has been reported. Nevertheless, in Morocco, leishmaniases are a major public health problem, and little interest was given to climate change impacts on the distribution and spread of these diseases. As insect-borne diseases, the incidence and distribution of leishmaniases are influenced by environmental changes, but also by several socio-economic and cultural factors. From a biological point of view, environmental variables have effects on the survival of insect vectors and mammalian reservoirs, which, in turn, affects transmission. Here, we highlight the effects of climate change in Morocco and discuss its consequences on the epidemiology of leishmaniases to identify challenges and define targeted recommendations to fight this disease.
In this study we use three different methodologies to document and compare temperature and precipitation projections for the city of Rio de Janeiro (RJ) over the 21st century. It aims to explore in what way the differences and similarities of those methodologies and their outcomes support the incorporation of climate risks in urban planning and improve effective urban climate change governance. We compared the projections for RJ from the Eta Regional Climate Model from the Brazilian National Institute for Space Research nested in two Hadley Center Global Climate Models (GCMs) (Eta-HadCM3 method and Eta-HadGEM2-ES method) and 33 GCMs from the Coupled Model Intercomparison Project Phase 5 multi-model dataset (Urban Climate Change Research Network - UCCRN method). The three methods showed increasing temperatures for RJ at the end of the century. Precipitation projections span a 13% decrease to a 12% increase when using the UCCRN method or are reduced between 0.4 and 0.5%, when using the Eta-HadGEM2-ES method. However, the middle range of the projections from UCCRN and Eta-HadGEM2-ES is similar. The three methods project an increase of warm days and nights and a decrease of cold days and nights. Nevertheless, although the directions of change are the same applying the three methods, the magnitude differs when considering warm and cold nights. Hence, city stakeholders are better informed when we apply different projection methods as it gives them the opportunity to consider the level of risk they are willing to bear in the future. We observed that defining climate change projections on the city scale based on clear communication and an interactive process between scientists and stakeholders can be used to inform citywide adaptation strategies and sector-specific uses, as well as promote urban climate risk governance.
(1) Temperate forests are shaped by late spring freezes after budburst—false springs—which may shift with climate change. Research to date has generated conflicting results, potentially because few studies focus on the multiple underlying drivers of false spring risk. (2) Here, we assessed the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six tree species across 11648 sites in Europe, to determine which were the strongest predictors of false spring risk and how these predictors shifted with climate change. (3) All predictors influenced false spring risk before recent warming, but their effects have shifted in both magnitude and direction with warming. These shifts have potentially magnified the variation in false spring risk among species with an increase in risk for early‐leafout species (i.e., Aesculus hippocastanum , Alnus glutinosa , Betula pendula ) versus a decline or no change in risk among late‐leafout species (i.e., Fagus sylvatica , Fraxinus excelsior , Quercus robur ). (4) Our results show how climate change has reshaped the drivers of false spring risk, complicating forecasts of future false springs, and potentially reshaping plant community dynamics given uneven shifts in risk across species.
During long-term space missions, microbial cultures accumulate the effects of low-dose radiation, microgravity, and other factors; altered growth and metabolic activity may occur before viability effects. This could affect functionality of bioreactors or other bio-enabled mission systems, as well as shed light on human health. Spaceflight microbiology studies beyond the low Earth orbit exposure afforded by the ISS have been limited. Nanosatellites offer an increasingly popular alternative for deep space missions. However, the communications delay requires biofluidic automation of a pre-defined experimental protocol, and the lack of sample return (reliance on sensors in flight) can significantly limit feasible investigations. Previous biological CubeSats (PharmaSat, O/OREOS, EcAMSat) have used alamarBlue, an off-the-shelf formulation of the redox indicator dye resazurin, to track metabolic activity, as will BioSentinel, the upcoming interplanetary microbiology experiment. A series of ground experiments (see abstracts by Liddell, Santa Maria, and A. Kim) were conducted using a microbial culture system outfitted with an electrochemical sensor array (electrical conductivity, pH, oxidation-reduction potential, and dissolved oxygen) with alamarBlue and the same strain of Saccharomyces cerevisiae as BioSentinel. By improving mapping of measured changes in alamarBlue kinetics to physicochemical changes, and ultimately to biological alterations such as shifted metabolic pathways, this work supplements data analyses from past missions and planning for future missions using alamarBlue to characterize space radiation effects. Initial results indicate that alamarBlue acts like a redox buffer; its presence significantly changes redox kinetics in otherwise identical cultures. The initial color change (blue resazurin reduced to red/pink resorufin) appears as a redox plateau. A second plateau, likely corresponding to the second color transition (resorufin to the colorless hydroresorufin), occurs at a lower redox value. The relationship to carbon source exhaustion, dissolved oxygen depletion, cell death, and measured redox potential is complex and still under study.
Salt marshes provide ecosystem services such as carbon sequestration, coastal protection, sea-level-rise (SLR) adaptation and recreation. SLR, storm events, drainage and mangrove encroachment are known drivers of salt marsh loss. However, the global magnitude and location of changes in salt marsh extent remains uncertain. Here we conduct a global and systematic change analysis of Landsat satellite imagery from the years 2000–2019 to quantify the loss, gain and recovery of salt marsh ecosystems and then estimate the impact of these changes on blue carbon stocks. We show a net salt marsh loss globally, equivalent to an area double the size of Singapore (719 km^2), with a loss rate of 0.28% year^(−1) from 2000 to 2019. Net global losses resulted in 16.3 (0.4–33.2, 90% confidence interval) Tg CO_2 e year^(−1) emissions from 2000 to 2019 and a 0.045 (−0.14–0.115) Tg CO_2 e year^(−1) reduction of carbon burial. Russia and the USA accounted for 64% of salt marsh losses, driven by hurricanes and coastal erosion. Our findings highlight the vulnerability of salt marsh systems to climatic changes such as SLR and intensification of storms and cyclones.
Awareness of the significant benefits of mangroves to human lives and their role in regulating environmental processes has increased during the recent decades. Yet there remains significant uncertainty about the mangrove change trajectories and the drivers of change at national scales. In Colombia, the absence of historical satellite imagery and persistent cloud cover have impeded the accurate mapping of mangrove extent and change over time. We create a temporally consistent Landsat-derived dataset using the LandTrendr algorithm to track the historical land cover and mangrove conversion from 1984-2020 across Colombia. Over this period, mangrove extent decreased by ~48.000ha (14% of total mangrove area). We find a gradual reduction of mangrove extent along the Pacific coast since 2004, whereas, in the Caribbean, mangrove cover declined around during 1984-1988 and also after 2012. Our time-series analysis matches with drivers of mangrove change at three local sites. For instance, hydroclimatic events, dredging activities, and high sediment loads transported by the rivers have collectively improved mangrove recovery in some sites. In contrast, human activities pressure linked to agricultural expansion and road construction have degraded mangroves. The transition from dense mangrove to other vegetation types is the most significant conversion affecting mangrove cover in Colombia, impacting an area of 38,469 ± 2,829 ha. We anticipate increased mangrove loss, especially along the Pacific coast, resulting from intensified human activity. Prioritization of conservation areas is needed to support local institutions, maintain currently protected areas, and develop strategies (e.g. payment for ecosystem services) to preserve one of the most pristine mangrove regions in the Western Hemisphere.
Cities in the poorest countries of the world are rapidly urbanizing. In fact, some of the fastest growing cities on the planet are found in sub-Saharan Africa. Many people benefit from economic, educational, and health opportunities that exist in cities and, as a result, city-dwellers often face less risk of poverty and disease in the context of climate change than their rural-dwelling counterparts. However, rapid urbanization, resulting from a large and constant influx of migrants from rural areas, can put pressure on existing social, economic, and health systems. For poor cities, they face a challenge to support existing residents while also expanding to support the needs of migrants, many of whom are deeply impoverished. Additionally, in a climate change, linked to heat waves, floods, droughts, and other related events, can add stress to complex urban food, health, hygiene, and housing systems. In this project we investigate urban expansion, climate change, and health in four major African cities – Ouagadougou, Addis Ababa, Nairobi, and Kigali. We consider different scenarios of urban expansion using historic and contemporary maps of urban extent, combined with climate (temperature, rainfall, and vegetation) and land cover combined with spatially referenced health information from the Demographic and Health Surveys (DHS) to investigate the relationships between urban dwelling, climate change and health. Temperature and rainfall scenarios are developed under different urban land use futures (expanding agricultural areas versus reducing agricultural areas) to examine the ways that individual health outcomes related to malnutrition vary under different potential future conditions. Preliminary results of the research highlight the importance of temperature for health, in particular, and suggest that while urban conditions related to urban infrastructure (e.g., educational attainment, electricity access, and improved hygiene) cannot reduce health risks to counter the impacts of high temperatures and reduced agricultural land. As cities in poor countries urbanize, city-dwellers face unique risks when droughts, heat waves, and other extreme weather events occur. In this project we explore urban land use conditions, climate conditions and health using future scenarios. Specifically we evaluate health outcomes in the future while considering different land use practices, urban expansion, temperature, and rainfall conditions to identify individual-level risk and protective factors. We compare results across four major cities in sub Saharan Africa.
The Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB) has been developed as an integral part of Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model to analyze greenhouse gas (GHG) emissions from land use change (LUC) and land management change (LMC) in the context of overall biofuel life-cycle analysis (LCA).
Thermal diodes are passive systems that modulate their thermal resistance depending on the direction of temperature gradient, thereby allowing preferential directional heat flow. A dual phase thermal diode consists of a junction between two phase change materials that have opposing temperature-dependent thermal conductivity trends, and whose performance (i.e., rectification ratio) is related to the ratio of the thermal conductivities of the different phases. In this work, a dual phase change diode with a rectification ratio of ~3.5 for an applied temperature bias of ~40 K is presented, which is among the highest-performing junction diodes based on phase change materials at the macroscale for near room temperature applications. The diode is composed of an aqueous solution of poly(N-isopropylacrylamide), a thermo-responsive polymer, and calcium chloride hexahydrate -- a solid-liquid phase change material. Experimental insights are provided into the contributions of different heat transfer mechanisms, conduction, and convection, and the effect of concentration of the thermo-responsive polymer.
Abstract We developed spatial Bayesian hierarchical models to assess potential climate change impacts on suitable habitat for five important tree species in the Pacific northwestern United States (California, Oregon, and Washington). Individual‐species models were fit with presence–absence data from forest inventory field plots and spatial relationships were specified through a conditional autoregressive model. This modeling approach allowed us to visualize uncertainty in response curves, map current and future prediction uncertainty, and provide interval estimates for change. Upward elevational or northward latitudinal shifts in climatically suitable habitat were projected for all species. Climate change impacts were the most damaging for noble fir ( Abies procera ), for which 79%–100% of the current range was projected to become climatically unsuitable by the 2080s. Although coastal Douglas‐fir ( Pseudotsuga menziesii var. menziesii ) has been projected by others to gain habitat in Canada, within our study area we projected a net loss of climatically suitable habitat (ca. 8000–31,400 km 2 ) under three of four future climate scenarios. A net loss in habitat was also projected for Oregon white oak ( Quercus garryana ) under three of four scenarios, with 40%–60% of the current range becoming unsuitable. Although there was no net loss of habitat for forest land blue oak under any scenario, other factors like competition may inhibit blue oak ( Quercus douglasii ) and white oak from occupying areas projected to increase in climatic suitability. Additionally, between 13% and 32% of blue oak's current range was projected to become unsuitable; some of these areas aligned with dieback following the 2012–2015 California drought, which our data set predates. Unlike the other four species, we projected a 17%–25% increase in climatically suitable habitat for California black oak ( Quercus kelloggii ), although 1%–20% of the current range was still projected to become unsuitable. Our findings indicate that, although some species will face more pressure in tracking climatically suitable habitat than others, climate change will impact the location of suitable habitat for many species.