953 resultados para climate change impact
Resumo:
Effective public policy to mitigate climate change footprints should build on data-driven analysis of firm-level strategies. This article’s conceptual approach augments the resource-based view (RBV) of the firm and identifies investments in four firm-level resource domains (Governance, Information management, Systems, and Technology [GISTe]) to develop capabilities in climate change impact mitigation. The authors denote the resulting framework as the GISTe model, which frames their analysis and public policy recommendations. This research uses the 2008 Carbon Disclosure Project (CDP) database, with high-quality information on firm-level climate change strategies for 552 companies from North America and Europe. In contrast to the widely accepted myth that European firms are performing better than North American ones, the authors find a different result. Many firms, whether European or North American, do not just “talk” about climate change impact mitigation, but actually do “walk the talk.” European firms appear to be better than their North American counterparts in “walk I,” denoting attention to governance, information management, and systems. But when it comes down to “walk II,” meaning actual Technology-related investments, North American firms’ performance is equal or superior to that of the European companies. The authors formulate public policy recommendations to accelerate firm-level, sector-level, and cluster-level implementation of climate change strategies.
Resumo:
The agricultural sector could be one of the most vulnerable economic sectors to the impacts of climate change in the coming decades. Climate change impacts are related to changes in the growth period, extreme weather events, and changes in temperature and recipitation patterns, among others. All of these impacts may have significant consequences on agricultural production(Bates, et al.2008. A main issue regarding climate change impacts is related to the uncertainty associated with their occurrence. Climate change impacts can bestimated with simulation models based on several assumptions, among which the future patterns of emissions of greenhouse g asses are quite likely the most relevant, driving the development of future scenarios, i.e. plausible visions of how the future may unfold. Those scenarios are developed as storylines associated with different assumptions about climate and socioeconomic conditions and emissions, with reference figures, such as demographic projections, average global temperatures, etc.(Intergovernmental Panel on Climate Change 2000). Within this context, climate change impact assessment is forced to consider multiple and interconnected sources of uncertainty in order to produce valuable information for policymakers.
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La possibilité d’estimer l’impact du changement climatique en cours sur le comportement hydrologique des hydro-systèmes est une nécessité pour anticiper les adaptations inévitables et nécessaires que doivent envisager nos sociétés. Dans ce contexte, ce projet doctoral présente une étude sur l’évaluation de la sensibilité des projections hydrologiques futures à : (i) La non-robustesse de l’identification des paramètres des modèles hydrologiques, (ii) l’utilisation de plusieurs jeux de paramètres équifinaux et (iii) l’utilisation de différentes structures de modèles hydrologiques. Pour quantifier l’impact de la première source d’incertitude sur les sorties des modèles, quatre sous-périodes climatiquement contrastées sont tout d’abord identifiées au sein des chroniques observées. Les modèles sont calés sur chacune de ces quatre périodes et les sorties engendrées sont analysées en calage et en validation en suivant les quatre configurations du Different Splitsample Tests (Klemeš, 1986;Wilby, 2005; Seiller et al. (2012);Refsgaard et al. (2014)). Afin d’étudier la seconde source d’incertitude liée à la structure du modèle, l’équifinalité des jeux de paramètres est ensuite prise en compte en considérant pour chaque type de calage les sorties associées à des jeux de paramètres équifinaux. Enfin, pour évaluer la troisième source d’incertitude, cinq modèles hydrologiques de différents niveaux de complexité sont appliqués (GR4J, MORDOR, HSAMI, SWAT et HYDROTEL) sur le bassin versant québécois de la rivière Au Saumon. Les trois sources d’incertitude sont évaluées à la fois dans conditions climatiques observées passées et dans les conditions climatiques futures. Les résultats montrent que, en tenant compte de la méthode d’évaluation suivie dans ce doctorat, l’utilisation de différents niveaux de complexité des modèles hydrologiques est la principale source de variabilité dans les projections de débits dans des conditions climatiques futures. Ceci est suivi par le manque de robustesse de l’identification des paramètres. Les projections hydrologiques générées par un ensemble de jeux de paramètres équifinaux sont proches de celles associées au jeu de paramètres optimal. Par conséquent, plus d’efforts devraient être investis dans l’amélioration de la robustesse des modèles pour les études d’impact sur le changement climatique, notamment en développant les structures des modèles plus appropriés et en proposant des procédures de calage qui augmentent leur robustesse. Ces travaux permettent d’apporter une réponse détaillée sur notre capacité à réaliser un diagnostic des impacts des changements climatiques sur les ressources hydriques du bassin Au Saumon et de proposer une démarche méthodologique originale d’analyse pouvant être directement appliquée ou adaptée à d’autres contextes hydro-climatiques.
Resumo:
Summary: Climate change has a potential to impact rainfall, temperature and air humidity, which have relation to plant evapotranspiration and crop water requirement. The purpose of this research is to assess climate change impacts on irrigation water demand, based on future scenarios derived from the PRECIS (Providing Regional Climates for Impacts Studies), using boundary conditions of the HadCM3 submitted to a dynamic downscaling nested to the Hadley Centre regional circulation model HadRM3P. Monthly time series for average temperature and rainfall were generated for 1961-90 (baseline) and the future (2040). The reference evapotranspiration was estimated using monthly average temperature. Projected climate change impact on irrigation water demand demonstrated to be a result of evapotranspiration and rainfall trend. Impacts were mapped over the target region by using geostatistical methods. An increase of the average crop water needs was estimated to be 18.7% and 22.2% higher for 2040 A2 and B2 scenarios, respectively. Objective ? To analyze the climate change impacts on irrigation water requirements, using downscaling techniques of a climate change model, at the river basin scale. Method: The study area was delimited between 4º39?30? and 5º40?00? South and 37º35?30? and 38º27?00? West. The crop pattern in the target area was characterized, regarding type of irrigated crops, respective areas and cropping schedules, as well as the area and type of irrigation systems adopted. The PRECIS (Providing Regional Climates for Impacts Studies) system (Jones et al., 2004) was used for generating climate predictions for the target area, using the boundary conditions of the Hadley Centre model HadCM3 (Johns et al., 2003). The considered time scale of interest for climate change impacts evaluation was the year of 2040, representing the period of 2025 to 2055. The output data from the climate model was interpolated, considering latitude/longitude, by applying ordinary kriging tools available at a Geographic Information System, in order to produce thematic maps.
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The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of climate change on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since most of building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. In this paper, the methods used to prepare future weather data for the study of the impact of climate change are reviewed. The advantages and disadvantages of each method are discussed. The inherent relationship between these methods is also illustrated. Based on these discussions and the analysis of Australian historic climatic data, an effective framework and procedure to generate future hourly weather data is presented. It is shown that this method is not only able to deal with different levels of available information regarding the climate change, but also can retain the key characters of a “typical” year weather data for a desired period.
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Urban traffic and climate change are two phenomena that have the potential to degrade urban water quality by influencing the build-up and wash-off of pollutants, respectively. However, limited knowledge has made it difficult to establish any link between pollutant buildup and wash-off under such dynamic conditions. In order to safeguard urban water quality, adaptive water quality mitigation measures are required. In this research, pollutant build-up and wash-off have been investigated from a dynamic point of view which incorporated the impacts of changed urban traffic as well as changes in the rainfall characteristics induced by climate change. The study has developed a dynamic object classification system and thereby, conceptualised the study of pollutant build-up and wash-off under future changes in urban traffic and rainfall characteristics. This study has also characterised the buildup and wash-off processes of traffic generated heavy metals, volatile, semi-volatile and non-volatile hydrocarbons under dynamic conditions which enables the development of adaptive mitigation measures for water quality. Additionally, predictive frameworks for the build-up and wash-off of some pollutants have also been developed.
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Climate change presents risks to health that must be addressed by both decision-makers and public health researchers. Within the application of Environmental Health Impact Assessment (EHIA), there have been few attempts to incorporate climate change-related health risks as an input to the framework. This study used a focus group design to examine the perceptions of government, industry and academic specialists about the suitability of assessing the health consequences of climate change within an EHIA framework. Practitioners expressed concern over a number of factors relating to the current EHIA methodology and the inclusion of climate change-related health risks. These concerns related to the broad scope of issues that would need to be considered, problems with identifying appropriate health indicators, the lack of relevant qualitative information that is currently incorporated in assessment and persistent issues surrounding stakeholder participation. It was suggested that improvements are needed in data collection processes, particularly in terms of adequate communication between environmental and health practitioners. Concerns were raised surrounding data privacy and usage, and how these could impact on the assessment process. These findings may provide guidance for government and industry bodies to improve the assessment of climate change-related health risks.
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Dengue fever (DF) is a serious public health concern in many parts of the world. An increase in DF incidence has been observed globally over the past decades. Multiple factors including urbanisation, increased international travels and global climate change are thought to be responsible for increased DF. However, little research has been conducted in the Asia-Pacific region about the impact of these changes on dengue transmission. The overarching aim of this thesis is to explore the spatiotemporal pattern of DF transmission in the Asia-Pacific region and project the future risk of DF attributable to climate change. Annual data of DF outbreaks for sixteen countries in the Asia-Pacific region over the last fifty years were used in this study. The results show that the geographic range of DF in this region increased significantly over the study period. Thailand, Vietnam and Laos were identified as the highest risk areas and there was a southward expansion observed in the transmission pattern of DF which might have originated from Philippines or Thailand. Additionally, the detailed DF data were obtained and the space-time clustering of DF transmission was examined in Bangladesh. Monthly DF data were used for the entire country at the district level during 2000-2009. Dhaka district was identified as the most likely DF cluster in Bangladesh and several districts of the southern part of Bangladesh were identified as secondary clusters in the years 2000-2002. In order to examine the association between meteorological factors and DF transmission and to project the future risk of DF using different climate change scenarios, the climate-DF relationship was examined in Dhaka, Bangladesh. The results show that climate variability (particularly maximum temperature and relative humidity) was positively associated with DF transmission in Dhaka. The effects of climate variability were observed at a lag of four months which might help to potentially control and prevent DF outbreaks through effective vector management and community education. Based on the quantitative assessment of the climate-DF relationship, projected climate change will likely increase mosquito abundance and activity and DF in this area. Assuming a temperature increase of 3.3oC without any adaptation measures and significant changes in socio-economic conditions, the consequence will be devastating, with a projected annual increase of 16,030 cases in Dhaka, Bangladesh by the end of this century. Therefore, public health authorities need to be prepared for likely increase of DF transmission in this region. This study adds to the literature on the recent trends of DF and impacts of climate change on DF transmission. These findings may have significant public health implications for the control and prevention of DF, particularly in the Asia- Pacific region.
Resumo:
Weather variables, mainly temperature and humidity influence vectors, viruses, human biology, ecology and consequently the intensity and distribution of the vector-borne diseases. There is evidence that warmer temperature due to climate change will influence the dengue transmission. However, long term scenario-based projections are yet to be developed. Here, we assessed the impact of weather variability on dengue transmission in a megacity of Dhaka, Bangladesh and projected the future dengue risk attributable to climate change. Our results show that weather variables particularly temperature and humidity were positively associated with dengue transmission. The effects of weather variables were observed at a lag of four months. We projected that assuming a temperature increase of 3.3 °C without any adaptation measure and changes in socio-economic condition, there will be a projected increase of 16,030 dengue cases in Dhaka by the end of this century. This information might be helpful for the public health authorities to prepare for the likely increase of dengue due to climate change. The modelling framework used in this study may be applicable to dengue projection in other cities.
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Ross River virus (RRV) is the most common vector-borne disease in Australia. It is vitally important to make appropriate projections on the future spread of RRV under various climate change scenarios because such information is essential for policy-makers to identify vulnerable communities and to better manage RRV epidemics. However, there are many methodological challenges in projecting the impact of climate change on the transmission of RRV disease. This study critically examined the methodological issues and proposed possible solutions. A literature search was conducted between January and October 2012, using the electronic databases Medline, Web of Science and PubMed. Nineteen relevant papers were identified. These studies demonstrate that key challenges for projecting future climate change on RRV disease include: (1) a complex ecology (e.g. many mosquito vectors, immunity, heterogeneous in both time and space); (2) unclear interactions between social and environmental factors; and (3) uncertainty in climate change modelling and socioeconomic development scenarios. Future risk assessments of climate change will ultimately need to better understand the ecology of RRV disease and to integrate climate change scenarios with local socioeconomic and environmental factors, in order to develop effective adaptation strategies to prevent or reduce RRV transmission.
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Climate change and solar ultraviolet radiation may affect vaccine-preventable infectious diseases (VPID), the human immune response process and the immunization service delivery system. We systematically reviewed the scientific literature and identified 37 relevant publications. Our study shows that climate variability and ultraviolet radiation may potentially affect VPID and the immunization delivery system through modulating vector reproduction and vaccination effectiveness, possibly influencing human immune response systems to the vaccination, and disturbing immunization service delivery. Further research is needed to determine these affects on climate-sensitive VPID and on human immune response to common vaccines. Such research will facilitate the development and delivery of optimal vaccination programs for target populations, to meet the goal of disease control and elimination.
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The eucalypt leaf beetle, Paropsis atomaria Olivier, is an increasingly important pest of eucalypt plantations in subtropical eastern Australia. A process-based model, ParopSys, was developed using DYMEXTM and was found to accurately predict the beetle populations. Climate change scenarios within the latest Australian climate model forecast range were run in ParopSys at three locations to predict changes in beetle performance. Relative population peaks of early generations did not change but shifted to earlier in the season. Temperature increases of 1.0 to 1.5 ºC or greater predicted an extra generation of adults at Gympie and Canberra, but not for Lowmead, where increased populations of late season adults were observed under all scenarios. Furthermore, an additional generation of late-larval stages was predicted at temperature increases of greater than 1.0 ºC at Lowmead. Management strategies to address these changes are discussed, as are requirements to improve the predictive capacity of the model.