• A diff-in-diff model estimates the effect of London traffic policies on NO 2 levels. • Toxicity Charge (TC) and Ultra Low Emission Zone (ULEZ) improve air quality. • These two traffic policies reduce NO 2 in the city centre and, also, in nearby areas. • No border effects due to the TC or the ULEZ are observed. • Ultra Low Emission Zone leads to larger cuts in NO 2 levels than Toxicity Charge.
<p>Record-breaking natural hazards occur regularly throughout the world, leading to a variety of impacts [1]. According to the WMO, since 1970 there were more than 11000 reported disasters attributed to these hazards globally, with just over 2 million deaths and US$ 3.64 trillion in losses [2]. From 1970 to 2019, weather, climate and water hazards accounted for 50% of all disasters, 45% of all reported deaths and 74% of all reported economic losses [2]. Droughts and heatwaves are both included in the top 4 disasters in terms of human losses [2], with uneven impacts throughout the world and a high likelihood that anthropogenic climate forcing will increase economic inequality between countries [3].</p><p>Nowadays there is strong evidence that droughts and heatwaves are at times synergetic and that their combined occurrence is largely caused by land-atmosphere feedbacks [4]. In fact, increasing trends of Compound Dry and Hot (CDH) events have been observed in both South America [5,6] and Europe [7,8], some of them with aggravated impacts. Specifically, the severe 2020 Pantanal extreme fire season (Brazil) resulted from the interplay between extreme and persistent temperatures (maximum temperatures 6 &#186;C above-average) and long-term soil dryness conditions [6]. Similarly, in the Iberian Peninsula, CDH events were shown to have an influence on the dramatic 2017 fire season [9] and also on crop losses [8]. Moreover, future climate projections suggest that CDH conditions are expected to become more common in a warming climate [4]. Therefore, it is very important to address weather events in a compound manner, identifying synergies, driving mechanisms and dominant atmospheric modes controlling single and combined hazards.</p><p>[1] IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of WGI to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte &#160;V. et al., (eds.)]. Cambridge University Press.&#160;</p><p>[2] WHO, 2021. Weather-related disasters increase over past 50 years, causing more damage but fewer deaths, https://public.wmo.int/en/media/press-release/weather-related-disasters-increase-over-past-50-years-causing-more-damage-fewer</p><p>[3] Diffenbaugh N.S., Burke M. (2019) Global warming has increased global economic inequality, PNAS, 116, 20, 9808-9813</p><p>[4] Zscheischler J. et al. (2018). Future climate risk from compound events. Nat. Clim. Change, 8, 469&#8211;477.</p><p>[5] Geirinhas J.L. et al. (2021). Recent increasing frequency of compound summer drought and heatwaves in Southeast Brazil. Environ. Res.&#160; Lett., 16(3).</p><p>[6] Libonati R. <em>et al</em> (2022) Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal,<em> Environ. </em><em>Res. Lett.</em> <strong>17</strong> 015005.</p><p>[7] Geirinhas J.L. et al. (2020) Heat-related mortality at the beginning of the twenty-first century in Rio de Janeiro, Brazil. Int. J. Biometeorol., 64, 1319&#8211;1332</p><p>[8] Russo A. et al. (2019) The synergy between drought and extremely hot summers in the Mediterranean. Environ. Res. Lett., 14, 014011</p><p>[9] Ribeiro A.F.S. et al. (2020) Risk of crop failure due to compound dry and hot extremes estimated with nested copulas. Biogeosciences, 17, 4815&#8211;4830</p><p>[10] Turco M. et al. (2019) Climate drivers of the 2017 devastating fires in Portugal. Sci. Rep., 9, 1</p><p>&#160;</p><p><em>This work was supported by Funda&#231;&#227;o para a Ci&#234;ncia e a Tecnologia (Portugal) under projects PTDC/CTA-CLI/28902/2017, PTDC/CTA-CLI/28902/2017 and FCT- UIDB/50019/2020 &#8211;IDL. </em></p><p><em>&#160;</em></p><p>&#160;</p>
In the past 40 years, marine heatwaves (MHWs) have experienced a worldwide increase in duration, intensity, frequency and spatial extent. This trend has been particularly evident in the Mediterranean, where exceptional events were observed during the summers of 2022, 2018 and 2003. This study proposes a twofold analysis of MHWs in the Mediterranean, focusing on their statistical characteristics and physical causes. A satellite dataset is utilized to analyze MHWs via an index, called activity, which aggregates the occurrence, duration, intensity and spatial extent of events. Our results show that the trend toward more active summers for MHWs is strongest in the western Mediterranean basin and long-term warming is the main driver in the whole Mediterranean basin. We also show that in the western and Adriatic Mediterranean region, the increase of SST variability contributes about a third to the MHW activity long-term trend whereas in the central, eastern and Aegean basins, the variability of SST mostly acts to diminish this trend. Through principal component analysis (PCA) of MHW activity, we found that the three most severe summer MHW events in the Mediterranean occur at the same location where the overall trend is highest. Interannual variability increased MHW activity in 2022 around the Balearic Sea, in 2018 in the eastern basins and in 2003 in the central basins. A joint PCA revealed that the long-term trend in MHW activity co-varies with a positive geopotential height anomaly over the Mediterranean, which is consistent with the generation of atmospheric-driven MHWs and which, at the North Atlantic scale, resembles the positive phase of the summer East Atlantic. The additional interannual variability contribution to these three severe summers was associated with western warming and projected onto the positive phase of the summer North Atlantic Oscillation. The increase in MHW over the last 40 years is also associated in the western, central and Adriatic regions with increased downward short-wave radiation and in the eastern Mediterranean with decreased upward long-wave radiation. Increased upward latent heat flux partly compensated for the MHW long-term increase over the whole Mediterranean basin. The interannual variability of MHW activity is related in the western, central and Adriatic basins to increased downward sensible and decreased upward latent heat flux possibly due to warm and humid air intrusion. A.S., A.R. and C.P. thank Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES http://doi.org/10.54499/JPIOCEANS/0001/2019 (ROADMAP), T.L.F. thank the Swiss National Science Foundation (Grant P00P2_198897), A.R and C.P thanks the national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). A.S. was supported by ANR and France 2030 through the project CLIMArcTIC (grant ANR-22-POCE-0005). A.R. was supported by FCT through https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006.
Abstract. Drought and heat events are becoming more frequent in Europe due to human-induced climate change, affecting many aspects of human well-being and ecosystem functioning. However, the intensity of these drought and heat events is not spatially and temporally uniform. Understanding the spatial variability of drought impacts is important information for decision makers, supporting both planning and preparations to cope with the changing climatic conditions. Currently, data relating to the damage caused by extended drought episodes is scattered across languages and sources such as scientific publications, governmental reports and the media. In this review paper, we compiled data of damages caused by the drought and heat of 2018 until 2022 in forest ecosystems and relate it to large European data sets, providing support for decision making both on the regional and European levels. We partitioned data from 16 European countries to the following regions: Northern, Central, Alpine, and South. We focused on drought and heat damage to forests, and categorized them as (1) physiological (2) pest, and (3) fire damage. We were able to identify the following key trends: (1) Relative defoliation rates of broadleaves is higher than of conifers in every country with the exception of Czech Republic (2) the incidence of wood destroyed by insects is extremely high in Central Europe and Sweden (3) Although forest fires can be related to heat and drought, they are superimposed by other anthropogenic influences (4) In this period (2018–2022), forests in central Europe are particularly affected, while forests in the Northern and Alpine zones are less affected, and adaptations to heat and drought can still be observed in the Southern zone. (5) Although in several regions 2021 was an average year still high levels of damages were observed indicating strong legacy effects of 2018–2020. We note that the inventory should be continuously updated as new data appear.
We present a simple neural network and data pre–selection framework, discriminating the most essential input data for accurately forecasting the concentrations of PM10, based on observations for the years between 2002 and 2006 in the metropolitan region of Lisbon, Portugal. Starting from a broad panoply of different data sets collected at several air quality and meteorological stations, a forward stepwise regression procedure is applied enabling to automatically identify the most important variables for predicting the pollutant and also to rank them in order of importance. The importance of this variable ranking is discussed, showing that it is very sensitive to the urban location where measurements are obtained. Additionally, the importance of Circulation Weather Types is highlighted, characterizing synoptic scale circulation patterns and the concentration of pollutants. We then quantify the performance of linear and non–linear neural network models when applied to PM10 concentrations. In the light of contradictory results of previous studies, our results show no clear superiority for the case studied of non–linear models over linear models. While all models show similar predictive performances, we find important differences in false alarm rates and demonstrate the importance of removing weekly cycles from input variables.
Abstract As a result of warming and precipitation deficits, the increasing shortage of water resources, droughts have become one of the main drivers of desertification, land degradation and food insecurity with direct impacts on ecosystems and society, especially in fragile communities. Over the Iberian Peninsula, a known climate change hotspot, the occurrence of droughts varies in intensity and severity, being its assessment under present and future conditions an important tool for adaptation measures. Here, for the first time, we present a comprehensive analysis of different plausible evolutions of droughts throughout the twenty-first century over Iberia on a monthly basis, featuring three different emission scenarios (RCP2.6, RCP4.5, RCP8.5). A multi-variable, multi-model EURO-CORDEX weighted ensemble is used to assess future drought conditions using the SPI (Standardized Precipitation Index) and SPEI (Standardized Precipitation Evapotranspiration Index). All indexes were computed by considering the full period, from 1971 to 2000 merged with 2011–2100 from each RCP scenario. The results clearly show that the Iberian Peninsula is highly vulnerable to climate change, indicating a significant increase in the intensity and severity of drought occurrences, even for the low-end RCP2.6 scenario. For the RCP4.5 and RCP8.5 scenarios, the increases are more pronounced and enhanced throughout the twenty-first century, from 3 up to 12 more severe droughts for the shorter timescales with increases in mean duration above 30 months for the longer accumulation periods. The use of all the RCPs data pooled together with a multi-variable weighted ensemble approach allows not only a more accurate and robust projection of future droughts but also ensures comparability among the projections from the three RCP scenarios. The future drought evolution aspires to assist the new Portuguese national roadmap for adaptation for the twenty-first century, bridging the water sector challenges from mitigation to adaptation in a dynamic way.
<p>Crop health and favourable yields depend strongly on precipitation and temperature patterns during the crop&#8217;s growing season. Compound events, such as co-occurring drought and heat can lead to extreme crop failure and cause larger damages than the impacts of the individual drought or heat alone.</p><p>Here we assess the relative role of hot and dry conditions (HDC) in crop yields and evaluate in what manner compound HDC enhance the probability of failure in rainfed cropping systems in the Iberian Peninsula. We use annual wheat yield data at the province level and cluster provinces with similar sensitivities of yields to climate conditions. Copula theory was applied to model the trivariate dependence between 3-monthly means of maximum temperature, 3-monthly means of precipitation and wheat yields. The climate variables and averaging periods have been chosen to maximize the dependence between the driver climate conditions during growing season and the annual yields. Copulas enable for the estimation of conditional probabilities of crop-loss under different hot and dry severity levels based on their trivariate joint distribution.</p><p>Our results demonstrate that the probability of wheat loss increases with the severity of the compound HDC and that losses are significantly larger during co-occurring drought and heat compared to individual water- or heat-stress. Moreover, the difference between heat impacts and compound heat and drought related impacts is larger than the difference between drought impacts and compound heat and drought related impacts, suggesting that water-stress is the major driver of wheat losses. These findings can help contribute to design management options to mitigate climate-related crop impacts and guide the decision-making process in agricultural practices.</p><p><strong>Acknowledgements</strong>: A.F.S.Ribeiro would like to acknowledge the financial support through FCT (Funda&#231;&#227;o para a Ci&#234;ncia e a Tecnologia, Portugal) under the projects UIDB/50019/2020 &#8211; IDL and PTDC/CTA-CLI/28902/201 (IMPECAF). A.F.S.Ribeiro is also thankful to FCT for the grant PD/BD/114481/2016 and to the COST Action CA17109 for a Short Term Scientific Mission (STSM) grant to develop the present work.</p>
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