Passive and active hybrid approach to buildings design in Saudi Arabia

The building sector is one of the highest consumers of energy in the world. This has led to high dependency on using fossil fuel to supply energy without due consideration to its environmental impact. Saudi Arabia has been through rapid development accompanied by population growth, which in turn has increased the demand for construction. However, this fast development has been met without considering sustainable building design. General design practices rely on using international design approaches and features without considering the local climate and aspects of traditional passive design. This is by constructing buildings with a large amount of glass fully exposed to solar radiation. The aim of this paper is to investigate the development of sustainability in passive design and vernacular architecture. Furthermore, it compares them with current building in Saudi Arabia in terms of making the most of the climate. Moreover, it will explore the most sustainable renewable energy that can be used to reduce the environmental impact on modern building in Saudi Arabia. This will be carried out using case studies demonstrating the performance of vernacular design in Saudi Arabia and thus its benefits in terms of environmental, economic and social sustainability. It argues that the adoption of a hybrid approach can improve the energy efficiency as well as reduce the carbon footprint of buildings. This is by combining passive design, learning from the vernacular architecture and implementing innovative sustainable technologies.

The influence of ozone precursor emissions from four world regions on tropospheric composition and radiative climate forcing

Ozone (O3) precursor emissions influence regional and global climate and air quality through changes in tropospheric O3 and oxidants, which also influence methane (CH4) and sulfate aerosols (SO42−). We examine changes in the tropospheric composition of O3, CH4, SO42− and global net radiative forcing (RF) for 20% reductions in global CH4 burden and in anthropogenic O3 precursor emissions (NOx, NMVOC, and CO) from four regions (East Asia, Europe and Northern Africa, North America, and South Asia) using the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model (CTM) simulations, assessing uncertainty (mean ± 1 standard deviation) across multiple CTMs. We evaluate steady state O3 responses, including long-term feedbacks via CH4. With a radiative transfer model that includes greenhouse gases and the aerosol direct effect, we find that regional NOx reductions produce global, annually averaged positive net RFs (0.2 ± 0.6 to 1.7 ± 2 mWm−2/Tg N yr−1), with some variation among models. Negative net RFs result from reductions in global CH4 (−162.6 ± 2 mWm−2 for a change from 1760 to 1408 ppbv CH4) and regional NMVOC (−0.4 ± 0.2 to −0.7 ± 0.2 mWm−2/Tg C yr−1) and CO emissions (−0.13 ± 0.02 to −0.15 ± 0.02 mWm−2/Tg CO yr−1). Including the effect of O3 on CO2 uptake by vegetation likely makes these net RFs more negative by −1.9 to −5.2 mWm−2/Tg N yr−1, −0.2 to −0.7 mWm−2/Tg C yr−1, and −0.02 to −0.05 mWm−2/Tg CO yr−1. Net RF impacts reflect the distribution of concentration changes, where RF is affected locally by changes in SO42−, regionally to hemispherically by O3, and globally by CH4. Global annual average SO42− responses to oxidant changes range from 0.4 ± 2.6 to −1.9 ± 1.3 Gg for NOx reductions, 0.1 ± 1.2 to −0.9 ± 0.8 Gg for NMVOC reductions, and −0.09 ± 0.5 to −0.9 ± 0.8 Gg for CO reductions, suggesting additional research is needed. The 100-year global warming potentials (GWP100) are calculated for the global CH4 reduction (20.9 ± 3.7 without stratospheric O3 or water vapor, 24.2 ± 4.2 including those components), and for the regional NOx, NMVOC, and CO reductions (−18.7 ± 25.9 to −1.9 ± 8.7 for NOx, 4.8 ± 1.7 to 8.3 ± 1.9 for NMVOC, and 1.5 ± 0.4 to 1.7 ± 0.5 for CO). Variation in GWP100 for NOx, NMVOC, and CO suggests that regionally specific GWPs may be necessary and could support the inclusion of O3 precursors in future policies that address air quality and climate change simultaneously. Both global net RF and GWP100 are more sensitive to NOx and NMVOC reductions from South Asia than the other three regions.

Review of the formulation of present‐generation stratospheric chemistry‐climate models and associated external forcings

The goal of the Chemistry‐Climate Model Validation (CCMVal) activity is to improve understanding of chemistry‐climate models (CCMs) through process‐oriented evaluation and to provide reliable projections of stratospheric ozone and its impact on climate. An appreciation of the details of model formulations is essential for understanding how models respond to the changing external forcings of greenhouse gases and ozonedepleting substances, and hence for understanding the ozone and climate forecasts produced by the models participating in this activity. Here we introduce and review the models used for the second round (CCMVal‐2) of this intercomparison, regarding the implementation of chemical, transport, radiative, and dynamical processes in these models. In particular, we review the advantages and problems associated with approaches used to model processes of relevance to stratospheric dynamics and chemistry. Furthermore, we state the definitions of the reference simulations performed, and describe the forcing data used in these simulations. We identify some developments in chemistry‐climate modeling that make models more physically based or more comprehensive, including the introduction of an interactive ocean, online photolysis, troposphere‐stratosphere chemistry, and non‐orographic gravity‐wave deposition as linked to tropospheric convection. The relatively new developments indicate that stratospheric CCM modeling is becoming more consistent with our physically based understanding of the atmosphere.

Insights into the molecular architecture of a peptide nanotube using FTIR and solid-state NMR spectroscopic measurements on an aligned sample

The self-assembly of proteins and peptides into b-sheet-rich amyloid fibers is a process that has gained notoriety because of its association with human diseases and disorders. Spontaneous self-assembly of peptides into nonfibrillar supramolecular structures can also provide a versatile and convenient mechanism for the bottom-up design of biocompatible materials with functional properties favoring a wide range of practical applications.[1] One subset of these fascinating and potentially useful nanoscale constructions are the peptide nanotubes, elongated cylindrical structures with a hollow center bounded by a thin wall of peptide molecules.[2] A formidable challenge in optimizing and harnessing the properties of nanotube assemblies is to gain atomistic insight into their architecture, and to elucidate precisely how the tubular morphology is constructed from the peptide building blocks. Some of these fine details have been elucidated recently with the use of magic-angle-spinning (MAS) solidstate NMR (SSNMR) spectroscopy.[3] MAS SSNMR measurements of chemical shifts and through-space interatomic distances provide constraints on peptide conformation (e.g., b-strands and turns) and quaternary packing. We describe here a new application of a straightforward SSNMR technique which, when combined with FTIR spectroscopy, reports quantitatively on the orientation of the peptide molecules within the nanotube structure, thereby providing an additional structural constraint not accessible to MAS SSNMR.

Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations.

The global vegetation response to climate and atmospheric CO2 changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought-tolerant biomes in the tropics. These features are broadly consistent with pollen-based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO2 concentration and the presence of large continental ice sheets. The extent of drought-tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low-latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO2 concentration on C3 photosynthesis, suggest an important additional role of low CO2 concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO2 concentration were included. This result suggests that both CO2 effects and climate effects were important in determining glacial-interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.

A simple framework for assessing the trade-off between the climate impact of aviation carbon dioxide emissions and contrails for a single flight

Persistent contrails are an important climate impact of aviation which could potentially be reduced by re-routing aircraft to avoid contrailing; however this generally increases both the flight length and its corresponding CO emissions. Here, we provide a simple framework to assess the trade-off between the climate impact of CO emissions and contrails for a single flight, in terms of the absolute global warming potential and absolute global temperature potential metrics for time horizons of 20, 50 and 100 years. We use the framework to illustrate the maximum extra distance (with no altitude changes) that can be added to a flight and still reduce its overall climate impact. Small aircraft can fly up to four times further to avoid contrailing than large aircraft. The results have a strong dependence on the applied metric and time horizon. Applying a conservative estimate of the uncertainty in the contrail radiative forcing and climate efficacy leads to a factor of 20 difference in the maximum extra distance that could be flown to avoid a contrail. The impact of re-routing on other climatically-important aviation emissions could also be considered in this framework.

Evaluating adjusted forcing and model spread for historical and future scenarios in the CMIP5 generation of climate models

We utilize energy budget diagnostics from the Coupled Model Intercomparison Project phase 5 (CMIP5) to evaluate the models' climate forcing since preindustrial times employing an established regression technique. The climate forcing evaluated this way, termed the adjusted forcing (AF), includes a rapid adjustment term associated with cloud changes and other tropospheric and land-surface changes. We estimate a 2010 total anthropogenic and natural AF from CMIP5 models of 1.9 ± 0.9 W m−2 (5–95% range). The projected AF of the Representative Concentration Pathway simulations are lower than their expected radiative forcing (RF) in 2095 but agree well with efficacy weighted forcings from integrated assessment models. The smaller AF, compared to RF, is likely due to cloud adjustment. Multimodel time series of temperature change and AF from 1850 to 2100 have large intermodel spreads throughout the period. The intermodel spread of temperature change is principally driven by forcing differences in the present day and climate feedback differences in 2095, although forcing differences are still important for model spread at 2095. We find no significant relationship between the equilibrium climate sensitivity (ECS) of a model and its 2003 AF, in contrast to that found in older models where higher ECS models generally had less forcing. Given the large present-day model spread, there is no indication of any tendency by modelling groups to adjust their aerosol forcing in order to produce observed trends. Instead, some CMIP5 models have a relatively large positive forcing and overestimate the observed temperature change.

Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models.

Climate change and infectious disease: time for a new normal?

At present, there is a clarion call for action on climate change across the global health landscape. At the recent WHO-sponsored conference on health and climate (held in Geneva, Switzerland, on Aug 27–29, 2014) and the UN Climate Summit (New York, USA, on Sept 23, 2014), participants were encouraged to act decisively to change the current trajectory of climate disruption. Health inequalities, including those related to infectious diseases, have now been pushed to centre stage. This approach represents a step-change in thinking. But as we are urged toward collective action, is it time to rethink our approach to research, especially in relation to climate change and infectious disease?

Climate change and water in the UK: past changes and future prospects

Climate change is expected to modify rainfall, temperature and catchment hydrological responses across the world, and adapting to these water-related changes is a pressing challenge. This paper reviews the impact of anthropogenic climate change on water in the UK and looks at projections of future change. The natural variability of the UK climate makes change hard to detect; only historical increases in air temperature can be attributed to anthropogenic climate forcing, but over the last 50 years more winter rainfall has been falling in intense events. Future changes in rainfall and evapotranspiration could lead to changed flow regimes and impacts on water quality, aquatic ecosystems and water availability. Summer flows may decrease on average, but floods may become larger and more frequent. River and lake water quality may decline as a result of higher water temperatures, lower river flows and increased algal blooms in summer, and because of higher flows in the winter. In communicating this important work, researchers should pay particular attention to explaining confidence and uncertainty clearly. Much of the relevant research is either global or highly localized: decision-makers would benefit from more studies that address water and climate change at a spatial and temporal scale appropriate for the decisions they make

The climate and environment of Byzantine Anatolia: integrating science, history, and archaeology

The integration of high-resolution archaeological, textual, and environmental data with longer-term, low-resolution data affords greater precision in identifying some of the causal relationships underlying societal change. Regional and microregional case studies about the Byzantine world—in particular, Anatolia, which for several centuries was the heart of that world—reveal many of the difficulties that researchers face when attempting to assess the influence of environmental factors on human society. The Anatolian case challenges a number of assumptions about the impact of climatic factors on socio-political organization and medium-term historical evolution, highlighting the importance of further collaboration between historians, archaeologists, and climate scientists.

Climate change modelling and its roles to chinese crops yield

Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10% for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out

Simple measures of climate, soil properties and plant traits predict national scale grassland soil carbon stocks

1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0-7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50-250 µm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45-50 µm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250-4000 µm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and Applications: Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1-100,000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Global patterns of plant root colonization intensity by mycorrhizal fungi explained by climate and soil chemistry

Aim Most vascular plants on Earth form mycorrhizae, a symbiotic relationship between plants and fungi. Despite the broad recognition of the importance of mycorrhizae for global carbon and nutrient cycling, we do not know how soil and climate variables relate to the intensity of colonization of plant roots by mycorrhizal fungi. Here we quantify the global patterns of these relationships. Location Global. Methods Data on plant root colonization intensities by the two dominant types of mycorrhizal fungi world-wide, arbuscular (4887 plant species in 233 sites) and ectomycorrhizal fungi (125 plant species in 92 sites), were compiled from published studies. Data for climatic and soil factors were extracted from global datasets. For a given mycorrhizal type, we calculated at each site the mean root colonization intensity by mycorrhizal fungi across all potentially mycorrhizal plant species found at the site, and subjected these data to generalized additive model regression analysis with environmental factors as predictor variables. Results We show for the first time that at the global scale the intensity of plant root colonization by arbuscular mycorrhizal fungi strongly relates to warm-season temperature, frost periods and soil carbon-to-nitrogen ratio, and is highest at sites featuring continental climates with mild summers and a high availability of soil nitrogen. In contrast, the intensity of ectomycorrhizal infection in plant roots is related to soil acidity, soil carbon-to-nitrogen ratio and seasonality of precipitation, and is highest at sites with acidic soils and relatively constant precipitation levels. Main conclusions We provide the first quantitative global maps of intensity of mycorrhizal colonization based on environmental drivers, and suggest that environmental changes will affect distinct types of mycorrhizae differently. Future analyses of the potential effects of environmental change on global carbon and nutrient cycling via mycorrhizal pathways will need to take into account the relationships discovered in this study.