Geography, including climatic factors, have long been considered potentially important elements in shaping socio-economic activities, alongside other determinants, such as institutions. Here we ...demonstrate that geography and climate variables satisfactorily explain the worldwide economic activity as measured by the per capita Gross Cell Product (GCP-PC) at a fine geographical resolution, typically much higher than country average. A 1° by 1° GCP-PC dataset has been key for establishing and testing a direct relationship between 'local' geography/climate and GCP-PC. Not only have we tested the geography and climate hypothesis using many possible explanatory variables, importantly we have also predicted and reconstructed GCP-PC worldwide by retaining the most significant predictors. While this study confirms that latitude is the most important predictor for GCP-PC when taken in isolation, the accuracy of the GCP-PC prediction is greatly improved when other factors mainly related to variations in climatic variables, rather than average climatic conditions as typically used, are considered. However, latitude diminishes in importance when only the wealthier parts of the globe are considered. This work points to specific features of the climate system which explain economic activity, such as the variability in air pressure. Implications of these findings range from an improved understanding of why socio-economically better-off societies are geographically placed where they are in the present, past and future to informing where new economic activities could be established in order to yield favourable economic outcomes based on geography and climate conditions.
The importance of energy transition was underlined at COP28 in Dubai, where governments committed to tripling renewables capacities and doubling the rate of energy efficiency by 2030. However, the ...power generated by climate-dependent energy sources exhibits greater vulnerability to potential climate changes in the long term. Therefore, climate models play a pivotal role in estimating the effects of climate change on renewables in the context of strategic planning for the development and operation of new renewable power plants. In this context, the World Meteorological Organization (WMO) developed a Global Energy Resilience Atlas aimed at providing insights into the climate change risks for the hydropower sector, the largest renewable electricity source for most countries, generating over 4300 TWh globally. This study focuses on defining four Hydro Climate Risk indices (HCRIs) using historical and climate projection precipitation data for three climate scenarios. The final product is a freely available and interactive tool. The developed methodology and tool address how climate changes have historically affected hydropower generation and how they will impact the future at national scales. The final product also addresses the needs of policymakers at national, regional, and global levels in crafting long-term planning for a more secure energy sector, accelerating the energy transition to more sustainable and reliable energies.
Over recent years there has been an increasing deployment of renewable energy generation technologies, particularly large-scale wind farms. As wind farm deployment increases, it is vital to gain a ...good understanding of how the energy produced is affected by climate variations, over a wide range of time-scales, from short (hours to weeks) to long (months to decades) periods.
By relating wind speed at specific sites in the UK to a large-scale climate pattern (the North Atlantic Oscillation or “NAO”), the power generated by a modelled wind turbine under three different NAO states is calculated. It was found that the wind conditions under these NAO states may yield a difference in the mean wind power output of up to 10%. A simple model is used to demonstrate that forecasts of future NAO states can potentially be used to improve month-ahead statistical forecasts of monthly-mean wind power generation.
The results confirm that the NAO has a significant impact on the hourly-, daily- and monthly-mean power output distributions from the turbine with important implications for (a) the use of meteorological data (e.g. their relationship to large-scale climate patterns) in wind farm site assessment and, (b) the utilisation of seasonal-to-decadal climate forecasts to estimate future wind farm power output. This suggests that further research into the links between large-scale climate variability and wind power generation is both necessary and valuable.
► Power output from wind turbines is sensitive to wind speed. ► The affect of large-scale atmospheric circulation (NAO) on UK wind is investigated. ► Slow (monthly) changes in NAO state are shown to affect turbine output by up to 10%. ► Monthly turbine power output forecasts are improved using simple NAO predictions.
Understanding how entomopathogenic nematodes respond to temperature changes and have adapted to the local environment is crucial to improve their potential as biocontrol agents. In order to improve ...understanding of
Heterorhabditis bacteriophora
’s potential adaptability to future climate changes, full-length cDNA and the corresponding gene of heat shock protein 90 (Hsp90) were isolated and fully characterized. The reproductive potential of the Apulian strain of
H. bacteriophora
increased when the temperature rose from 23 to 30°C, but no reproduction was found at 12°C. Expression analyses revealed that
Hb-hsp
90-1 was differentially expressed in Infective Juveniles (IJs) and adults (hermaphrodites, females and males). Up-regulation of
Hb-hsp
90-1 was higher during the recovery process in
Galleria mellonella
larvae than adults, thus confirming the protective role of
Hb-hsp
90-1 in coping with the host environment. Silencing of
Hb-hsp
90-1 resulted in a significant reduction (76%) in the expression level. Silenced IJs took longer than untreated nematodes to infect
G. mellonella
, showing that
Hb-hsp
90-1 could be also involved in chemosensation. Furthermore, the number of adults and IJs recovered from
G. mellonella
infected with silenced nematodes and incubated at 30°C was higher than that obtained from
G. mellonella
infected with untreated nematodes. These data confirm the crucial role of
Hb-hsp
90-1 allowing acclimation to increased temperatures and modulation of the recovery process.
The nematicidal activity of garlic extracts is known on root-knot nematodes but never investigated on the grapevine nematode
. In this study, the nematicidal activity of a commercial garlic extract ...formulate (GEF) was assessed on
, both in vitro and in a pot assay. In the in vitro assays, mixed specimens of
were exposed to a 0-4 mL L
range of GEF concentrations, checking nematode immotility and mortality after 2, 4 or 8 h. In the experiments on potted grapevines, plants cultivated in soil infested by
were irrigated twice at a 15-day interval with 0.05, 0.2 and 0.5 mL L
solutions of GEF, including nontreated soil as a control. An almost complete mortality of
specimens occurred after a 2 h exposure to a 2 mL L
GEF concentration, while an 8 h exposure to even the 0.0312 and 0.0156 mL L
solutions resulted in about 50% and 30% mortality, respectively. Soil treatment with a 0.5 mL L
GEF solution significantly reduced the population of
and increased the grapevine root growth compared to nontreated soil or soil treated with the lower dosages. Results of this study indicated that garlic-based nematicides could be an effective tool for
management in organic and integrated vineyards.
Seasonal climate predictions can assist with timely preparations for extreme episodes, such as dry or wet periods that have associated additional risks of droughts, fires and challenges for water ...management. Timely warnings for extreme warm summers or cold winters can aid in preparing for increased energy demand. We analyse seasonal forecasts produced by three different methods: (1) a multi-linear statistical forecasting system based on observations only; (2) a non-linear random forest model based on observations only; and (3) process-based dynamical forecast models. The statistical model is an empirical system based on multiple linear regression that is extended to include the trend over the previous 3 months in the predictors, and overfitting is further reduced by using an intermediate multiple linear regression model. This results in a significantly improved El Niño forecast skill, specifically in spring. Also, the Indian Ocean dipole (IOD) index forecast skill shows improvements, specifically in the summer and autumn months. A hybrid multi-model ensemble is constructed by combining the three forecasting methods. The different methods are used to produce seasonal forecasts (three-month means) for near-surface air temperature and monthly accumulated precipitation seasonal forecast with a lead time of one month. We find numerous regions with added value compared with multi-model ensembles based on dynamical models only. For instance, for June, July and August temperatures, added value is observed in extensive parts of both Northern and Southern America, as well as Europe.
Noise from industrial plants, wind farms, ports, and airports ranges long distances and merges with noise from linear transport infrastructures (
roads and railways). A straightforward description of ...people’s long-term noise exposure is usually performed using simplified algorithms implemented in software packages. However, when focusing on the worst-case scenario in favourable sound propagation conditions, the prediction needs to be more accurate and requires the model’s calibration through actual measurements. In these cases, where the noise source under investigation, the concurrent sources, or all of them may be far away from the receivers, the correct choice of the temporal and meteorological windows to perform the measurements demands specific knowledge of weather-related phenomena. Such an approach is also essential in developing technically and economically sustainable mitigation strategies when required. This article first introduces some of the meteorological principles underpinning these phenomena. Within this framework, three of the most commonly used road-traffic noise calculation methods have been applied to identical scenarios, and their performances in accounting for weather-related effects on sound propagation have been analysed. The chosen methodological approach can be used for other environmental noise sources.
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