Urban heat island (UHI) is an increasingly important public health problem which could be even more severe in a near future due to global warming. Air conditioning (A/C) is a key parameter for health problems in case of heat waves since, on one hand, it reduces mortality but, on the other hand, depending on the heat rejection management, it can increase the street temperature.
This communication, based on simulations, addresses the influence of A/C management on the street temperatures of Paris in the case of the severe heat wave which occurred in August 2003. Results show that A/C affects the UHI depending on its management. A detailed analysis on selected districts shows that the local temperature variation resulting from heat island is proportional to the sensible heat rejected locally by A/C, indicating that a clever A/C management is all the more important to provide comfort and to mitigate heat island. Moreover, the incidence of the sky view factor is also discussed.

This study addresses the use of classical regression techniques for predicting the monthly average global solar radiation in the city of Al-Ain, UAE. The mean daily recorded data used were supplied by the National Center of Meteorology and Seismology (NCMS) in Abu Dhabi , UAE or the years of 1995 till 2007. Available weather data included the mean air temperature (⁰C), mean wind speed (knots), daily sunshine hours, and percent relative humidity in addition to the daily global solar radiation (kWh/m²). The data was divided into two groups: one data group from 1995-2004 for the prediction model and the second group (2005-2007) for testing the model. The correlation between mean daily global solar radiation (GSR) and the other four variables suggested using all four variables for building the prediction model, although the GSR is highly correlated to the mean temperature and sunshine-hours variations.
The resulting model was tested using the three-year data of the period 2005-2007 yielding a deterministic coefficient R² = 90.77 % and RMSE= 0.417 as well as low MBE values. The model was also tested with Artificial Neural Network (ANN) model data yielding very favorable results.

Climate change will influence not only mean but also climate variability, in particular the frequency, intensity and the spatial distribution of droughts. The main objective of this paper is to project the extent to which future climate-change will induce changes in drought characteristics in Romania for the middle and the end of the 21st century. We use monthly precipitation data simulated by the regional climatic model ICTP_RegCM3 over Romania to calculate the Standardized Precipitation Index (SPI) at time scale of 1, 3 and 6 months. The simulations have been conducted at a horizontal resolution of 10 km in the framework of EU-FP6 project – CECILIA. The reference period of the control run is 1961-1990 and, the scenario runs were conducted for SRES A1B scenario for the periods 2021-2050 and 2071-2100. Considerable uncertainty in model skill in reproducing summer precipitation is observed when it is driven by ECHAM GCM. Future projections show increase in seasonal drought conditions over Romania, especially in the south and south-eastern part of the country, more pronounced for the end of the 21st century. The frequency of severe and extremely dry conditions of 3 and 6 months in duration is projected to slightly increase in comparison with severe and extremely wet conditions.

Earth's climate change is not a new phenomenon; it has occurred on all time scales throughout the Earth's history. However, climate change phenomena since the time of the mid eighteenth century are quite different from the changes occurred in the time of paleoclimatic and antiquity periods. The present day anthropogenically caused climate change is unique from its precedents in many respects and it has been bringing a serious challenge on life in different apocalyptic forms. This has a serious implication to Ethiopia since its economy is predominantly based on rain-fed agriculture. In this paper, climate change signals are detected at local scale in the country from analyses of precipitation data. Precipitation records from in-situ rain gauge measurements from over 190 stations are employed in the analysis which involves reconstruction of missing values, homogenization and gridding onto 0.5 x 0.5 degree. The monthly time series of girdded data are subjected to harmonic and singular spectrum analyses to see the seasonal cycles and trend components that predominantly account for the variability in the dataset. Harmonic analysis (HA) of the dataset reveals that the annual cycle accounts for 50 to 80% of the seasonal rainfall variability over northwestern and western parts as well as central and southeastern highlands of Ethiopia while the semiannual cycle accounts for 40% of seasonal rainfall variability over southern part of the country. A slow varying monotonic rainfall trend is detected using singular spectrum analysis (SSA). Mann- Kendall test is applied to determine statistical significance of the detected trend. The results reveal that almost all of the grid points show either significant increasing or decreasing trend at both 95% and 99% significant levels. Spatially, parts of southern Ethiopia with a bimodal rain type and some parts of western half of the country, which has a monomodal type long rainy season, have shown decreasing rainfall trend. Southeastern highlands and most of the southeastern lowlands have also exhibited long term decline in rainfall. The north and northeastern part of the country and very localized places of western Ethiopia have exhibited an increase in rainfall for the last 30 years. The rainfall over the central rift valley areas has been deceasing whereas it has been increasing over the southern rift valley areas.

Global warming, caused by increasing temperature of the Earth is a reality. Thus, the objective is to expose and analyze the various forms of cohabitation with in the variability of climates on the river basin Bridget, plus to create an analysis of climate variability and temperature for the year 2020. The analysis area has a semiarid climate and is located in northeastern region of Brazil, in the state of Pernambuco. Recent studies have shown noticeable changes in temperature, rainfall, water resources, surface runoff and agriculture, with severe consequences for populations. However, as water is poorly distributed and the intensification of droughts will worsen the situation increasingly reaching the point of entire families will migrate to other areas. Thus, the region will become an environment highly susceptible to changes in climate. The most vulnerable area of the basin is the northern portion, where the land use occurs in a disorganized and unprepared. While the southern portion is less vulnerable because it is more likely to receive higher rainfall. Thus, living with the climate changes like for example: capturing rainwater and agroecology are required options for the northen region.

Ongoing climate change is already affecting distributions of many species. Future impacts of climate change are expected to be even greater. Conservation planning methodologies are usually based on the assumption that species distributions change relatively slowly unless they are directly affected by human activities, but this assumption is inappropriate under climate change. To address this problem we develop a model that, assuming a fixed budget limiting the selection of areas devoted to conservation, selects areas for each of different periods of time, and indicates how species disperse between selected areas on successive periods. These areas are termed dispersal pathways. Their effectiveness is assessed based on the performance to retain species suitable climates over time, and on the ability of species to disperse between the areas. The model identifies maximum effective dispersal pathways, limited to some given budget. We applied the model to nine Iberian species and considered four climate change and budgetary scenarios. Climate change scenarios assuming reductions of greenhouse gas emissions had relatively modest gains in species retention areas. But larger budgets for area selection translate in significantly better retention levels. Nevertheless, our model identified species that, regardless the high conservation investment attained with unlimited budget, have a very limited ability to disperse to climatically suitable areas. Connectivity enhancement and assisted colonization could be considered for such cases.

Mediterranean evergreen oak woodlands are scattered trees ecosystems threatened by global warming scenarios and experiencing processes of loss and fragmentation. In representative areas of oak evergreen woodlands, over a 50-year period (1958 ­ 2007), quantitative information on the woodland’s shifting mosaic, comprising its three main patch-types: forest, farmland and shrubland, was obtained. This information included rates of: woodlands loss; core area loss and; edge high-contrast length expansion. Evergreen oak woodlands loss rates sharply increased in recent decades under current management systems. In some areas these ecosystems would be lost in approximately 90-180 years. However it was not clear if the loss of these ecosystems was sensitive to climate change, namely to extreme weather events like precipitation with enlarged below-mean values periods, as particular combinations of socio-economic factors and biophysical conditions seems to affect its dynamics, mainly impacting tree long-term persistence by natural regeneration failure and by shrubland encroachment. Also, the existing environmental financial support programmes for these landscapes, which focus on increasing recruitment, may not reverse this trend.
Perpetuating these ecosystems requires a strategy that keeps both, low tree mortality and tree recruitment, encompassing: i) the identification and protection of areas with natural regeneration; ii) the exploitation of soil conservation techniques for oak woodland recovery; and iii) considering the effects of different fragmentation patterns on the ecosystem functioning. Further work is been carried out, with a more precise approach, to have a more clear relationship between oak woodland patterns of loss and fragmentation and global warming extreme weather events.

Global temperatures are increasing at an unprecedented rate, promoting important shifts on plant communities and contributing to the global loss of biodiversity. Of the biological responses to global warming, changes in the timing of phenological events such as flowering are among the most sensitive and important, both from a biological and economical point of view. The most reliable data sources to monitor life-cycle events are datasets systematically compiled by phenological stations. Although these are relatively abundant in Central and Northern Europe, they are scarce in Portugal. The lack of phenological observations can, however, be filled up by biological collections in herbariums and museums. These specimens are potential sources of long-term data to detect changes in flowering phenology, as long as some correction procedure is applied to overcome differences in sampling locations. In this study, we examined herbarium specimens of Narcissus bulbocodium L., an early flowering species with a short flowering period, collected between 1882 and 2006 and, more or less, equally distributed by the whole of the Portuguese territory. The main objective of this work is to find a model that can be used to correct for the geographical differences among the collection sites, allowing for the use of the abundant specimens held in the Portuguese herbaria for the study of the effect of the rise of temperature on plant phenology.

Climate change has the potential to greatly impact nearly every form of agriculture. However, history has shown that the narrow climatic zones for growing winegrapes are especially prone to variations in climate and long-term climate change. The observed warming over the last fifty years in wine regions worldwide has benefited some by creating more suitable conditions while others have been challenged by increased heat and water stress. Projections of future warming at the global, continent, and wine region scales will likely continue to have both beneficial and detrimental impacts through opening new areas to viticulture and increasing viability, or severely challenging the ability to adequately grow grapes and produce quality wine. This paper will detail the observed and projected changes in wine regions worldwide and discuss the impacts on vine growth, fruit composition, yield, and wine quality. Furthermore, this paper will discuss the opportunities and challenges inherent in regional assessments of climate change with particular attention on the Douro Valley of Portugal.

A range of analytical and methodological approaches are used to assess the potential impacts of and vulnerability to climate change. Conventional approaches tend to utilize top-down scenario-based analysis to assess the impacts of a particular stressor or its effects on a particular sector. Alternative methodologies such as bottom-up approaches focus on the underlying processes and factors affecting people’s vulnerability to climate. Both approaches are perceived as complimentary and instrumental to our understanding of climate change vulnerability particularly regarding assessments to inform and develop local adaptation policy. However, the application of methods and tools deriving from such approaches is often limited by the lack of suitable and accessible data. Focusing on the farming sector, this paper will reflect on the challenges encountered in performing an integrated vulnerability assessment framework that brings together these two different approaches and considers some of the key conceptual and methodological problems posed by this type of holistic approach to climate change vulnerability assessments. It concludes by suggesting that there is a need for more explicit debate about the nature and quality of the data required to perform climate change vulnerability assessments.

The threat to biodiversity and the intensity of the Anthropocene Extinction Event depend on the value of climate sensitivity. In addition to initiating the process of global warming, the anthropogenic disturbance of the climate system has also triggered the action of a complex web of interconnected feedback mechanisms which amplify the effect of the original disturbance. The value of the amplification factor determines the eventual increase in average surface temperature required to re-balance the dynamic thermal equilibrium of the planet. Using new visualisation techniques, this presentation offers a trans-disciplinary re-evaluation of climate sensitivity with profound implications for our current strategic approach to the mitigation of climate change. The most significant boundary in climate dynamics is the strength of feedback at which the system behaviour crosses the critical threshold between equilibrium-seeking and self-amplifying outcomes. This is the tipping point at the boundary of runaway climate change. The second part of this paper will explore current state of knowledge about this boundary, and indicate policy implications.

Turkey is a Mediterranean country and it is a transcontinental European and Asian country. Its geographical location is important for different climatic transition regions. In this study, daily maximum and minimum air temperature data from 165 stations were used to study the temperature fluctuation in the period of 1961-2008 in Turkey. Homogeneity for data quality and non-parametric Mann-Kendall correlation statistical tests for statistically significant increasing or decreasing trends have been assessed in the 48-year period. The results show that there is increasing trend in all seasonal maximum temperature but only the summer and autumn is significant. There is also a significant increasing trend in the summer minimum temperature..

Climate change is expected to affect lakes which are the important freshwater resource. Eight largest lakes contain about 96% of water resources of all lakes over Russia territory. Modern environmental and climate change, caused by natural and man-made factors, drives to important changes in hydrological regime of lakes. The response of the individual lakes to these changes depends on the magnitude of regional climate change. Water balance, lake level, thermal characteristics, ice events and ice thickness have been studied for largest Russian Lakes Baikal, Ladoga, Onega, Ilmen, Chudsko-Pskovskoe, Chany, Taimyr and Khanka based on the data of observation.
The lakes’ level is a reliable moisture integrator, reflecting water resource within a vast territory, and that is why it can be used as indicator of modern climate change. Three of studied lakes show negative water level trends (Ladoga, Onega and Chudsko-Pskovskoe) and Lake Chany manifests a positive one. Important consequences for aquatic ecosystems and human activities on lakes have modern changes in lake ice with progress of warming. All studied lakes show the tendencies to earlier date of ice cover break-up and decrease in duration of ice cover on lakes. Maximal ice cover thickness had the most pronounced response to climate warming during the last decades.

We examine here daily minimum and maximum temperatures recorded at 7 climatic stations all located in Lazio region, Italy. These 14 time series were provided by the Italian “Agro-meteorological National Data Base” (BDAN) of the National Agricultural Information System (SIAN) and cover the second half of the XX century. The purposes of the signal processing were, first, to extract the linear trend and the two main seasonal cycles present in the series, second, after their subtraction from the signal, to assess the relative importance of the residual stochastic component and, finally, identifying a stochastic model for the latter, in order to arrive at an artificial simulation of the original series. After retrieving and filling the data gaps, we obtained uninterrupted series of daily data. Then, after detrending and filterinfg away the seasonal components (with 6-month and 12-month periods), it was possible to determine correlograms and power spectra of the residual zero-mean stochastic component. Also, a successful attempt was carried out to model this stochastic residual by means of an AR(1) process, thus yielding an efficient representation of the time variability of each of the 14 temperature series. In all cases the residual white noise obtained is definitely non gaussian. This model including the trend, the seasonal oscillation and the AR(1) process permitted a fairly good artificial reconstruction of the given temperature series via computer simulations specific for each given climatic station. This reconstruction, on capturing the essential features of each given series, represents a useful tool to describe and understand the recurrence of weather patterns and the possible occurrences of weather-linked phenomena interesting the local vegetation and the related biological processes. As a by-product, the analysis has permitted to evaluate the relative incidence of the two main seasonal components, and their importance with respect to the residual variability associated to purely stochastic fluctuations. From a comparison with the results of other similar studies, carried out in other countries of Europe and Oceania, it appears that the trends found by us for both minimum and maximum temperature daily series, when statistically significant, are generally lower than the corresponding values reported by the last IPCC (2007) for those areas that, at least from a geographical viewpoint, appear similar to ours.

Global climate change has generally been linked with species extinctions, while a possible evolutionary effect of the new environmental conditions was seldom considered. Further, the overwhelming majority of speciation studies focus on population divergence under allopatry, a process resulting from the spatial separation of a group of individuals, that under different selection pressures, later give rise to a new species. Nevertheless, speciation may also take place under sympatry, when some individuals within the population genetically diverge, in spite of remaining in the same, originally occupied area. The very rarely observed process of sympatric speciation, also called adaptive speciation, is here documented through an ongoing study of two populations of a forest insect, the pine processionary moth, Thaumetopoea pityocampa (Lepidopter, Notodontidae), between which gene flow has ceased. One of the populations has undergone a shift of its annual cycle and succeeded to adjust to different, generally warmer, climatic conditions. This population already shows both ecological adaptations, such as a higher temperature niche, as well as some divergence at genetic level. Such findings draw attention to the need of considering the role of species plasticity and of speciation processes, in response to climate change. A thorough interdisciplinary approach is clearly needed, when planning mitigation strategies for biological communities under different scenarios.

Ambient concentrations of C2-C12 volatile organic compounds (VOCs) were hourly measured in Bursa which is the fourth largest city of Turkey. Two measurement campaigns were performed between September 14- November 6, 2005 and March 17 - May 10, 2006. A total 1667 chromatograms were generated during the study and 51 VOCs were determined in each chromatogram. However, only BTEX compounds were examined in this study.
In this study, BTEX concentrations increased from 05:00 am in the morning. The high concentration peaks were observed at 9:00-11:00 am. In the afternoon probably due to high mixing layer height, good dilution was occurred and lower BTEX concentrations were observed and peaks were delayed to 3 pm. Until the evening rush hour traffic, lower values were monitored. That is to say, diurnal pattern of the BTEX compounds were followed the traffic rush hours.
In the present study, correlations and ratios among the BTEX compounds were also investigated. High correlations observed for the BTEX suggest a common source. However, for benzene at the first campaign, other sources were found effective, apart from the traffic. Still, in the second campaign, benzene emissions were found consistent with the vehicular emissions.

This work presents a summary of the results obtained from the impact of the African dust on levels of atmospheric suspended particulate matter registered among different monitoring sites in the Madrid Air Basin, in the centre of the Iberian Peninsula. African dust outbreaks were identified over the period 2001-2008. Lidar measurements helped to assess the temporal evolution of the dust layers and its impact on surface boundary layer. Monthly trend was analyzed resulting in a late spring-summer maximum occurrence of episodes and the most common synoptic meteorological situations causing the transport of the African dusty air masses were identified over the seasons. Time series of particulate matter daily concentrations recorded across Air Quality Network monitoring stations and sampling campaigns were collected and analysed. The contribution of mineral dust source in airborne particulates was estimated at the sampling campaign sites by means of receptor modelling analyses. Our results have shown that the contribution of mineral dust to PM10 (particulate matter lower than 10 µm, aerodynamic diameter) during African dust outbreaks is highly significant at rural and urban sites of the Madrid Air Basin, giving rise to exceedances of the PM10 daily limit value (50 µg/m3). Quantification of the emissions of mineral dust would help to establish efficient abatement strategies to reduce the concentration of PM10 with origin in anthropogenic sources, during African dust episodic days in which the PM10 DLV was exceeded in Madrid sites.

Airborne particulate matters with particles ≤ 10 µm in aerodynamic diameter (PM10) were collected on quartz-fibre filters from 7 August 2008 to 18 June 2009 at Pico Mountain, Azores Island (Portugal). The samples were analyzed by the k0-based instrumental neutron activation analysis (k0-INAA) technique at the Portuguese research reactor. A total of 21 elements: As, Ba, Br, Ce, Co, Cr, Eu, Fe, Hf, K, La, Mo, Na, Sb, Se, Sc, Sm, Th, U, Yb and Zn were determined in the airborne PM10’s and used as independent variables in the problem of factor analysis by the positive matrix factorization (PMF) method. The backward trajectory analysis using HYSPLIT (atmospheric modeling software) and the calculation of enrichment factors associated with the PMF were performed to identify the PM sources and to estimate their contributions to the particle mass concentrations. The results based on the data set in the studied period indicated that major sources contributed to airborne PMs at the Pico Mountain were soil, sea-salt, combustion and dust. The best solutions were found to be five factors for elemental compositions of the particulate matters. The comparison of the results in the present studied period with the previous obtained ones at the same sampling site has been presented and discussed to which the results have again confirmed that the Pico Mountain is a valuable sampling site for studies of long-range impact of source regions, particularly, the north and central American regions.

Considering particulate matter among the health-damaging air pollutants, the objective of this work was to evaluate the influence of road transport on levels of fine (PM_2.5) and coarse (PM_2.5-10) particles in urban area and to assess its polycyclic aromatic hydrocarbon content and the associated health risks. Samples were collected for period of 40 days during 2007 at an urban site situated in Oporto metropolitan area in Portugal; 17 PAHs recommend by U.S. EPA as priority pollutants were quantified using microwave assisted extraction combined with liquid chromatography. The results showed that PM_2.5 and PM_2.5-10 daily means were 28.7 ± 9.8 µg m-3 and 13.9 ± 7.9 µg m^-3, respectively. The mean concentration of 17 particulate-bound PAHs (∑PAHs) was 13.3 ± 10.0 ng m^-3 in PM_2.5 and 1.0 ± 0.3 ng m^-3 in PM_2.5-10; PAHs with 5-6 aromatic rings were the most abundant compounds in PM_2.5 accounting for 70% of ∑PAHs. The estimated values of lifetime lung cancer risks considerably exceeded (220 and 44 times) the health-based guideline level. Finally, the results showed that evaluation of benzo[a]pyrene (regarded as a marker of the genotoxic and carcinogenic PAH) alone would underestimate the carcinogenic potential of the studied PAH mixtures.

Nine years (2000-2009) of MODIS aerosol data are analyzed in order to study the spatial and temporal variability of aerosol optical properties over the Iberian Peninsula. The focus is mainly on the aerosol optical depth at 550 nm, but also the Ångström exponent between 470 and 660 nm is analyzed. Based on a principal components analysis, three regions with similar aerosol properties variability are indentified. Among these regions, that corresponding to the western part of the Iberian Peninsula has been found to rule the global behaviour of the aerosol optical depth at 550 nm over the entire region. In this area a clear seasonal cycle, with maxima in summer and minima in winter, is observed. A similar behaviour is found for the whole region. The Ångström exponent shows an opposite variability cycle. In the other two regions, the seasonal cycle varies slightly and a displacement of the maxima and minima is observed. The analysis of temporal variability shows a decreasing and statistically significant trend in the aerosol optical depth along the nine studied years.