• Energy Research

Abstract Climate change is impacting marine ecosystems and their goods and services in diverse ways, which can directly hinder our ability to achieve the Sustainable Development Goals (SDGs), set out under the 2030 Agenda for Sustainable Development. Through expert elicitation and a literature review, we find that most climate change effects have a wide variety of negative consequences across marine ecosystem services, though most studies have highlighted impacts from warming and consequences of marine species. Climate change is expected to negatively influence marine ecosystem services through global stressors—such as ocean warming and acidification—but also by amplifying local and regional stressors such as freshwater runoff and pollution load. Experts indicated that all SDGs would be overwhelmingly negatively affected by these climate impacts on marine ecosystem services, with eliminating hunger being among the most directly negatively affected SDG. Despite these challenges, the SDGs aiming to transform our consumption and production practices and develop clean energy systems are found to be least affected by marine climate impacts. These findings represent a strategic point of entry for countries to achieve sustainable development, given that these two goals are relatively robust to climate impacts and that they are important pre‐requisite for other SDGs. Our results suggest that climate change impacts on marine ecosystems are set to make the SDGs a moving target travelling away from us. Effective and urgent action towards sustainable development, including mitigating and adapting to climate impacts on marine systems are important to achieve the SDGs, but the longer this action stalls the more distant these goals will become. A free Plain Language Summary can be found within the Supporting Information of this article.

Projected increases in weather variability due to climate change will have severe consequences on human health, increasing mortality, and disease rates. Among these, cardiovascular diseases (CVD), highly prevalent among the elderly, have been shown to be sensitive to extreme temperatures and heat waves.This study aimed to find out the relationship between daily temperature (and other weather parameters) and daily CVD hospital admissions among the elderly population in Thai Nguyen province, a northern province of Vietnam.Retrospective data of CVD cases were obtained from a data base of four hospitals in Thai Nguyen province for a period of 5 years from 2008 to 2012. CVD hospital admissions were aggregated by day and merged with daily weather data from this period. Distributed lag non-linear model (DLNM) was used to derive specific estimates of the effect of weather parameters on CVD hospital admissions of up to 30 days, adjusted for time trends using b-splines, day of the week, and public holidays.This study shows that the average point of minimum CVD admissions was at 26°C. Above and below this threshold, the cumulative CVD admission risk over 30 lag days tended to increase with both lower and higher temperatures. The cold effect was found to occur 4-15 days following exposure, peaking at a week's delay. The cumulative effect of cold exposure on CVD admissions was statistically significant with a relative risk of 1.12 (95% confidence interval: 1.01-1.25) for 1°C decrease below the threshold. The cumulative effect of hot temperature on CVD admissions was found to be non-significant and was estimated to be at a relative risk of 1.17 (95% confidence interval: 0.90-1.52) for 1°C increase in the temperature. No significant association was found between CVD admissions and the other weather variables.Exposure to cold temperature is associated with increasing CVD admission risk among the elderly population.

Dengue fever is a mosquito-borne viral disease estimated to cause about 230 million infections worldwide every year, of which 25,000 are fatal. Global incidence has risen rapidly in recent decades with some 3.6 billion people, over half of the world's population, now at risk, mainly in urban centres of the tropics and subtropics. Demographic and societal changes, in particular urbanization, globalization, and increased international travel, are major contributors to the rise in incidence and geographic expansion of dengue infections. Major research gaps continue to hamper the control of dengue. The European Commission launched a call under the 7th Framework Programme with the title of 'Comprehensive control of Dengue fever under changing climatic conditions'. Fourteen partners from several countries in Europe, Asia, and South America formed a consortium named 'DengueTools' to respond to the call to achieve better diagnosis, surveillance, prevention, and predictive models and improve our understanding of the spread of dengue to previously uninfected regions (including Europe) in the context of globalization and climate change.The consortium comprises 12 work packages to address a set of research questions in three areas:Research area 1: Develop a comprehensive early warning and surveillance system that has predictive capability for epidemic dengue and benefits from novel tools for laboratory diagnosis and vector monitoring.Research area 2: Develop novel strategies to prevent dengue in children.Research area 3: Understand and predict the risk of global spread of dengue, in particular the risk of introduction and establishment in Europe, within the context of parameters of vectorial capacity, global mobility, and climate change.In this paper, we report on the rationale and specific study objectives of 'DengueTools'. DengueTools is funded under the Health theme of the Seventh Framework Programme of the European Community, Grant Agreement Number: 282589 Dengue Tools.

Dengue fever is the most important viral vector-borne disease with ~50 million cases per year globally. Previous estimates of the potential effect of global climate change on the distribution of vector-borne disease have not incorporated the effect of socioeconomic factors, which may have biased the results. We describe an empirical model of the current geographic distribution of dengue, based on the independent effects of climate and gross domestic product per capita (GDPpc, a proxy for socioeconomic development). We use the model, along with scenario-based projections of future climate, economic development, and population, to estimate populations at risk of dengue in the year 2050. We find that both climate and GDPpc influence the distribution of dengue. If the global climate changes as projected but GDPpc remained constant, the population at risk of dengue is estimated to increase by about 0.28 billion in 2050. However, if both climate and GDPpc change as projected, we estimate a decrease of 0.12 billion in the population at risk of dengue in 2050. Empirically, the geographic distribution of dengue is strongly dependent on both climatic and socioeconomic variables. Under a scenario of constant GDPpc, global climate change results in a modest but important increase in the global population at risk of dengue. Under scenarios of high GDPpc, this adverse effect of climate change is counteracted by the beneficial effect of socioeconomic development.

In Singapore, the frequency and magnitude of dengue epidemics have increased significantly over the past 40 years. It is important to understand the main drivers for the rapid increase in dengue incidence. We studied the relative contributions of putative drivers for the rise of dengue in Singapore: population growth, climate parameters and international air passenger arrivals from dengue endemic countries, for the time period of 1974 until 2011. We used multivariable Poisson regression models with the following predictors: Annual Population Size; Aedes Premises Index; Mean Annual Temperature; Minimum and Maximum Temperature Recorded in each year; Annual Precipitation and Annual Number of Air Passengers arriving from dengue-endemic South-East Asia to Singapore. The relative risk (RR) of the increase in dengue incidence due to population growth over the study period was 42.7, while the climate variables (mean and minimum temperature) together explained an RR of 7.1 (RR defined as risk at the end of the time period relative to the beginning and goodness of fit associated with the model leading to these estimates assessed by pseudo-R2 equal to 0.83). Estimating the extent of the contribution of these individual factors on the increasing dengue incidence, we found that population growth contributed to 86% while the residual 14% was explained by increase in temperature. We found no correlation with incoming air passenger arrivals into Singapore from dengue endemic countries. Our findings have significant implications for predicting future trends of the dengue epidemics given the rapid urbanization with population growth in many dengue endemic countries. It is time for policy-makers and the scientific community alike to pay more attention to the negative impact of urbanization and urban climate on diseases such as dengue.