Introduction: Climate change, decolonization, global Blackness

Quantitatively projecting the impact of future climate change on the socio-economy and exploring its internal mechanism are of great practical significance to adapt to climate change and prevent climate risks. Based on the economy-climate (C-D-C) model, this paper introduces a yield impact of climate change (YICC) model that can quantitatively project the climate change impact. The model is based on the YICC as its core concept and uses the impact ratio of climate change (IRCC) indicator to assess the response of the economic system to climate change over a long period of time. The YICC is defined as the difference between the economic output under changing climate condition and that under assumed invariant climate condition. The IRCC not only reflects the sensitivity of economic output to climate change but also reveals the mechanism of the nonlinear interaction between climate change and non-climatic factors on the socio-economic system. Using the main grain-producing areas in China as a case study, we use the data of the ensemble average of 5 GCMs in CMIP6 to project the possible impact of climate change on grain production in the next 15–30 years under three future scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). The results indicate that the long-term climate change in the future will have a restraining effect on production in North region and enhance production in South region. From 2021 to 2035, climate change will reduce production by 0.60–2.09% in North region, and increase production by 1.80–9.01% in South region under three future scenarios. From 2021 to 2050, compared with the climate change impact in 2021–2035, the negative impact of climate change on production in North region will weaken, and the positive impact on production in South region will enhance with the increase in emission concentration. Among them, climate change will reduce grain output in North region by 0.52–1.99%, and increase output in South region by 1.35–9.56% under the three future scenarios. The combination of economic results and climate change research is expected to provide scientific support for further revealing the economic mechanism of climate change impacts.

Impact of climate change on farms in smallholder farming systems: Yield impacts, economic implications and distributional effects

78.2 Impact of Climate Change on the Health and Well-Being of Indigenous Communities in Australia

Future climate change is expected to impact the extent, frequency, and magnitude of soil erosion in a variety of ways. The most direct of these impacts is the projected increase in the erosive power of rainfall owing to an increase in the moisture-holding capacity of the atmosphere, but other more indirect impacts include changes in plant biomass and shifts in land use to accommodate the new climatic regime. Given the potential for climate change to increase soil erosion and its associated adverse impacts, modelling future rates of erosion is a crucial step in its assessment as a potential future environmental problem, and as a basis to help advise future conservation strategies. In this study, the Water Erosion Prediction Project (WEPP) model is used to simulate the impacts of climate change on future rates of soil erosion for a case study hillslope in Northern Ireland for three future time periods centered on the 2020s, 2050s and 2080s. Despite the wide range of previous modelling studies, in the majority of cases a number of limitations are apparent with respect to their treatment of the direct impacts (changed climate data), and their failure to factor in the indirect impacts (changing land use and management). In addressing the need for site-specific climate change impacts, for example, many previous studies have attempted to downscale future climate change output from general circulation models (GCMs). The most popular downscaling approach in future soil erosion studies is the change factor method, yet this approach possesses severe limitations with respect to modelling future erosion rates since it incorporates only changes in the mean climate and fails to account for climate variability. In order to address this limitation, statistical downscaling methods are used in this study to downscale future climate change projections using three GCMs and two emissions scenarios, providing daily site-specific climate inputs to WEPP in a manner that incorporates both changes in the mean climate and its variability. The temporal scale of climate change projections is also a key limitation with respect to modelling future erosion rates. The most severe soil losses often occur in high intensity rainfall events that occur over very short time intervals, yet input to soil erosion models tends to be at a daily resolution. Given the decreasing confidence of future climate change projections at a sub-daily temporal resolution, a sensitivity analysis approach is used in this study to perturb the sub-daily rainfall intensity parameter in WEPP. In addition, most previous studies fail to account for the indirect impacts of climate change on soil erosion, with no change in land use and management often assumed. Here, a scenarios-based approach is employed to examine the impacts of changing crop cover and management on future rates of soil erosion. Results indicate a mix of soil erosion increases and decreases, depending on which scenarios are considered. Downscaled climate change projections in isolation generally result in erosion decreases, whereas large increases are projected when land use is changed from the current cover of grass to a row crop which requires annual tillage, and/or where large changes in sub-daily rainfall intensity are applied. The overall findings illustrate the potential for increased soil erosion under future climate change, and illuminate the need to address key limitations in previous studies with respect to the treatment of future climate change projections, and crucially, the factoring in of future land use and management.

Climate Change and Health: Strengthening the Evidence Base for Policy

Purpose The purpose of this study is to analyze the impact of climate change and variability on agricultural production in Middle East and North Africa region (MENA) where the deleterious impacts of climate change are generally projected to be greatest. Design/methodology/approach The study used a production function model using Fixed Effect Regression (FER) analysis and then using marginal impact analysis to assess the impact of climate change and variability on agricultural production. Therefore, the study utilized panel data for the period 1961-2009 pooled from 20 countries in MENA region. Findings Results showed that 1 per cent increase in temperature during winter resulted in 1.12 per cent decrease in agricultural production. It was also observed that 1 per cent increase in temperature variability during winter and spring resulted in 0.09 and 0.14 per cent decrease in agricultural production, respectively. Results also indicated that increasing precipitation during winter and fall season and precipitation variability during winter and summer seasons had negative impact. The estimated parameters of square temperature and precipitation indicated that climate change has significant nonlinear impacts on agricultural production in MENA region. Originality/value Despite there are many studies on the impact of climate change on agricultural production, there is a lack of publications to address the economic impact of both climate change and variability on agricultural production in MENA region. Thus, these results are more comprehensive and more informative to policymakers than the results from field trials.

Introduction There is a substantial literature about the future impacts of climate change (Nordhaus 1991; Cline 1992b; Fankhauser 1995; Mendelsohn et al . 2000; Tol 2002a); see Tol (2009b) for an overview. Less is known, however, about the impacts of climate change in the past. While there is no immediate policy relevance of estimates of past effects – as liability is yet to be established (Tol and Verheyen 2004) – such estimates would serve to validate models of future impacts – and thus help to improve these models and build confidence. In this chapter, I turn this question on its head. I use a model to backcast past impacts, thus generating hypotheses to be tested against observations. Unfortunately, there are no direct observations of the economic impact of past climate change. Note that the cause of climate change, past or future, is irrelevant for its impacts. There are, however, some studies that estimate particular aspects of the impact of past climate change, typically focussing on biophysical impacts.

Rapid change in climate is set to alter the delicate balance that exists between man and nature. The literature to this effect points out that the poorest countries and communities are likely to suffer the most because of their geographic locations, low income and low institutional capacity, as well as their greater reliance on climate-sensitive sectors like agriculture. Even if climate mitigations plans are implemented properly there will be some degree of warming due to inertia of emissions already released. As such, there is a strong consensus about the need of adaptation to changing climatic conditions. Adaptation to climate change is given increasing international attention as the confidence in climate change projections is getting higher. Developing countries have specific needs for adaptation due to high vulnerabilities, and they will in this way carry a great part of the global costs of climate change although the rising atmospheric greenhouse gas concentrations are mainly the responsibility of industrialized countries. Adaptation is believed to enhance the resilience against increasing climate variability. In this backdrop, the objective of the present paper is, therefore, to systematically and critically review the existing literature on the impacts of climate change and choice of adaptations across countries and draw insights for suggesting a comprehensive policy framework particularly for developing countries in this regard. The paper finds that the role of government and civil society is crucial for enabling efficient adaptation methods. Development policies and programs having synergy effect with climate change initiatives help adapt with the changing climate better. However, the availability of clean technology in developing countries will play the decisive role in controlling their growth rate of emission.

A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.

The impact of climate change on the territory and population is only increasing every year. Extreme weather events are expected to be repetitive and difficult to predict. New research shows that the effects of global warming are felt in large cities, at least twice as strong as in rural areas. That is why taking the necessary precautionary measures becomes an urgent task. The key, according to researchers, is adaptation and prevention. The authors of the article, analyzing the prerequisites and consequences of climate change, propose a scheme of organizational and economic mechanisms to counteract climate change in complex urban environments. Long-term goals include reducing urban heat islands through urban planning and climate-friendly home design to create a conducive, non-air-conditioned environment. In order to maximize the effectiveness of such adaptation measures, active multidisciplinary collaboration is required with the involvement of professionals in many industries. The assessment of the impact of climate change on the environment and human health has identified a number of gaps in knowledge and problems in the implementation of appropriate health measures. The article substantiates the relevance of climate change research in Ukraine. In addition, the main results of the research on population safety in the global climate change are summarized. Factors of the impact of global climate change on the environment, man, society, economy and complex agglomerations are highlighted. The consequences of climate change of natural, economic and social nature are presented. Directions and measures to adapt natural and socio-economic systems to global climate change are substantiated. The classification of the mechanisms of counteraction and mitigation of the negative effects of global climate change is given.

Water related issues are prominent amongst the commonly identified impacts of climate change. The issue of uncertainty remains highly pertinent, particularly for projections of changes in climate and the subsequent impact on hydrological extremes. An alternative to the traditional top-down impact studies are the bottom-up, vulnerability-based, approaches, which focus on sensitivity testing and adaptation options rather than climate change projections. A case study of such an approach to inform climate change policy development for flood management in Great Britain is described in this chapter. To assess the impact of climate change on hydrological droughts a multi-model experiment was undertaken, including seven global impact models (GIMs) driven by climate data from five global climate models (GCMs). This study demonstrates that different representations of terrestrial water cycle processes in GIMs can be responsible for considerable uncertainty in the response of hydrological drought to climate change.

The main objective of this study was to understand the impacts of climate variability and change on coastal resource governance, communities’ vulnerability and livelihoods security in the district. Specifically, the study aimed to assess the effects of rainfall and temperature variability and change on coastal resource distribution and management, to examine the vulnerabilities of socio-economic activities along the coastal areas to the impacts of climate variability and change and to establish the adaptive measures that the community and other stakeholders adapted to address the impacts of climate change and variability. The research was conducted in three purposively selected villages in Pangani District. A random sample of 60 respondents participated in the study. The study employed a mixture of quantitative and qualitative methods. Findings from this study demonstrate that climate change has happened and is still happening in the study area. The notable impacts of climate change include decrease of rainfall and change of rainfall seasons and patterns, emergence of new crop diseases and pests, decrease of fish catch, intrusion of salinity in the rivers and inland and general decline of crop productivity. The findings reveal that the impacts of climate change have been increasing over time between 1980 and 2014.

The Heat is On: Imperative for Midwifery Engagement in Climate Change.

Reviews on Impacts of Climate Change on Livestock Health and Production

Urban residents face increasing risk of heat stress due to the combined impact of climate change and intensification of the urban heat island (UHI) associated with urban growth. Considering the combined effect of urban growth and climate change is vital to understanding how temperatures in urban areas will change in the future. This study investigated the impact of urban growth and climate change on the UHI and heat stress in a subtropical city (Brisbane, Australia) in the present day (1991–2000) and medium term (2041–2050; RCP8.5) during summer. A control and urban growth scenario was used to compare the temperature increase from climate change alone with the temperature increase from climate change and urban growth. Average and minimum temperatures increased more with climate change and urban growth combined than with climate change alone, indicating that if urban growth is ignored, future urban temperatures could be underestimated. Under climate change alone, rural temperatures increased more than urban temperatures, decreasing the effect of the UHI by 0.4 °C at night and increasing the urban cool island by 0.8 °C during the day. With climate change, the number of hot days and nights doubled in urban and rural areas in 2041–2050 as compared to 1991–2000. The number of hot nights was higher in urban areas and with urban growth. Dangerous heat stress, defined as apparent temperature above 40 °C, increased with climate change and occurred on average 1–2 days every summer during 2041–2050, even in shaded conditions. There was higher temperature increases with urban growth and climate change than with climate change alone, indicating that reducing the effect of the UHI is vital to ensuring urban growth does not increase the heat stress risks that urban residents will face in the future.