Projections Of Future Change Research Articles

Future Impacts of Climate Change and Land Use on Multiple Ecosystem Services in a Rapidly Urbanizing Agricultural Basin, China

Ecosystem services (ESs) in rapidly urbanizing agricultural basins are vulnerable to environmental changes. Adequately understanding the driving forces and the dynamics of ESs related to water quantity and quality can provide a basis for making sound management decisions on the development of basins. Here, we explored the impacts of future land use and climate changes on four ESs: nitrogen and phosphorous purification, water supply, and soil retention services in the Taihu Basin region of eastern China. Spatially explicit methods, a cellular automata-Markov (CA-Markov) model and the delta downscaling method were used to quantify the ESs, simulate land use changes, and project future climate changes, respectively. We built a business-as-usual land use scenario, representative concentration pathways (RCPs) scenarios for climate change, as well as a combined land use and climate change scenario to analyze the changes in the drivers and the responses of ESs. The results showed the following: (1) future land use changes would significantly enhance the nitrogen purification service while reducing the phosphorus purification service compared to other services; (2) climate change would have substantial effects on water supply and soil retention, but these impacts would vary with different RCPs scenarios during three future periods; and (3) the combined scenarios of both drivers would obviously influence all ESs and lead to a nitrogen purification service that was different from the other three services. Moreover, the policy implications of the results were discussed. The findings can help guide the creation of policies for land structure and patterns, climate change adaptation, and ecosystem-based management to promote the sustainable development of watersheds at the regional scale.

A Statistical Assessment of Southern Hemisphere Tropical Cyclone Tracks in Climate Models

Reliable projections of future changes in tropical cyclone (TC) characteristics are highly dependent on the ability of global climate models (GCMs) to simulate the observed characteristics of TCs (i.e., their frequency, genesis locations, movement, and intensity). Here, we investigate the performance of a suite of GCMs from the U.S. CLIVAR Working Group on Hurricanes in simulating observed climatological features of TCs in the Southern Hemisphere. A subset of these GCMs is also explored under three idealized warming scenarios. Two types of simulated TC tracks are evaluated on the basis of a commonly applied cluster analysis: 1) explicitly simulated tracks, and 2) downscaled tracks, derived from a statistical–dynamical technique that depends on the models’ large-scale environmental fields. Climatological TC properties such as genesis locations, annual frequency, lifetime maximum intensity (LMI), and seasonality are evaluated for both track types. Future changes to annual frequency, LMI, and the latitude of LMI are evaluated using the downscaled tracks where large sample sizes allow for statistically robust results. An ensemble approach is used to assess future changes of explicit tracks owing to their small number of realizations. We show that the downscaled tracks generally outperform the explicit tracks in relation to many of the climatological features of Southern Hemisphere TCs, despite a few notable biases. Future changes to the frequency and intensity of TCs in the downscaled simulations are found to be highly dependent on the warming scenario and model, with the most robust result being an increase in the LMI under a uniform 2°C surface warming.

Developing climate model ensembles: A comparative case study

Projections of future changes in hydroclimatic variables are available through various general circulation models (GCMs) that are part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Assessment of the performance of these models in simulating past climate, both individually and as an ensemble, has received much attention and is commonly the first step in assessing their suitability of application. In this study, we have evaluated the ability of various ensemble models to simulate past temperature and precipitation in the Gulf Basin region of North America, chosen as an illustrative case study. We have developed ensembles from 34 CMIP5 GCMs using six diverse approaches, including random forest, support vector regression, neural networks, linear regression, and weighted k-nearest neighbors, and compared the performance of the ensembles with each other and the individual GCMs using a robust set of metrics and nonparametric tests. For temperature, random forest outperforms all other ensembles and the best-performing GCM by a statistically significant margin and is able to simulate temporal and spatial patterns in temperature well. None of the ensembles are able to adequately simulate observed precipitation patterns in the study area, likely due to spatial differences in precipitation drivers in the region, as well as the coarseness of the dataset itself. However, the random forest, support vector regression, neural network, and linear regression ensembles achieved statistically significant improvements to precipitation simulation, as compared to the individual GCMs and the simple arithmetic mean ensemble, which has been used in several studies.

Estimation of permafrost on the Tibetan Plateau under current and future climate conditions using the CMIP5 data

Permafrost has significant impacts on climate change through its strong interaction with the climate system. In order to better understand the permafrost variation and the role it plays in climate change, model outputs from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used in the present study to diagnose the near‐surface permafrost on the Tibetan Plateau (TP), assess the abilities of the models to simulate present‐day (1986–2005) permafrost and project future permafrost change on the TP under four different representative concentration pathways (RCPs). The results indicate that estimations of present‐day permafrost using the surface frost index (SFI) and the Kudryavtsev method (KUD) show a spatial distribution similar to that of the frozen soil map on the TP. However, the permafrost area calculated via the KUD is larger than that calculated via the SFI. The SFI produces a present‐day permafrost area of 127.2 × 104 km2. The results also indicate that the permafrost on the TP will undergo regional degradation, mainly at the eastern, southern and northeastern edges, during the 21st century. Furthermore, most of the sustainable permafrost will probably exist only in the northwestern TP by 2099. The SFI also indicates that the permafrost area will shrink by 13.3 × 104 km2 (9.7%) and 14.6 × 104 km2 (10.5%) under the RCP4.5 and RCP8.5 scenarios, respectively, in the next 20 years and by 36.7 × 104 km2 (26.6%) and 45.7 × 104 km2 (32.7%), respectively, in the next 50 years. The results are helpful for us to better understand the permafrost response to climate change over the TP, further investigate the physical mechanism of the freeze–thaw process and improve the model parameterization scheme.

The NUIST Earth System Model (NESM) version 3: description and preliminary evaluation

Abstract. The Nanjing University of Information Science and Technology Earth System Model version 3 (NESM v3) has been developed, aiming to provide a numerical modeling platform for cross-disciplinary Earth system studies, project future Earth climate and environment changes, and conduct subseasonal-to-seasonal prediction. While the previous model version NESM v1 simulates the internal modes of climate variability well, it has no vegetation dynamics and suffers considerable radiative energy imbalance at the top of the atmosphere and surface, resulting in large biases in the global mean surface air temperature, which limits its utility to simulate past and project future climate changes. The NESM v3 has upgraded atmospheric and land surface model components and improved physical parameterization and conservation of coupling variables. Here we describe the new version's basic features and how the major improvements were made. We demonstrate the v3 model's fidelity and suitability to address global climate variability and change issues. The 500-year preindustrial (PI) experiment shows negligible trends in the net heat flux at the top of atmosphere and the Earth surface. Consistently, the simulated global mean surface air temperature, land surface temperature, and sea surface temperature (SST) are all in a quasi-equilibrium state. The conservation of global water is demonstrated by the stable evolution of the global mean precipitation, sea surface salinity (SSS), and sea water salinity. The sea ice extents (SIEs), as a major indication of high-latitude climate, also maintain a balanced state. The simulated spatial patterns of the energy states, SST, precipitation, and SSS fields are realistic, but the model suffers from a cold bias in the North Atlantic, a warm bias in the Southern Ocean, and associated deficient Antarctic sea ice area, as well as a delicate sign of the double ITCZ syndrome. The estimated radiative forcing of quadrupling carbon dioxide is about 7.24 W m−2, yielding a climate sensitivity feedback parameter of −0.98 W m−2 K−1, and the equilibrium climate sensitivity is 3.69 K. The transient climate response from the 1 % yr−1 CO2 (1pctCO2) increase experiment is 2.16 K. The model's performance on internal modes and responses to external forcing during the historical period will be documented in an accompanying paper.

Hydrologic Response to Land Use Change in a Large Basin in Eastern Amazon

Accelerated land use changes in the Brazilian Amazonian region over the last four decades have raised questions about potential consequences for local hydrology. Under the hypothesis of a lack of frontier governance, projections of future changes in the Amazon basin suggest that 20–30% or more of this basin could be deforested in the next 40 years. This could trigger a cascade of negative impacts on water resources. In this study, we examined how a future conversion of the forest into pasture would influence streamflow and water balance components by using a conceptual and semi-distributed hydrological model in a large (142,000 km2) forested basin: specifically, the Iriri River basin in the Brazilian Amazon. The results showed that the land use change could substantially alter the water balance components of the originally forested basin. For example, an increase of over 57% in pasture areas increased a simulated annual streamflow by ~6.5% and had a significant impact on evapotranspiration, surface runoff, and percolation. Our findings emphasize the importance of protected areas for conservation strategies in the Brazilian Amazonian region.

유효가뭄지수(EDI)를 이용한 한반도 미래 가뭄 특성 전망

유효가뭄지수(EDI)를 이용한 한반도 미래 가뭄 특성 전망

The European mountain cryosphere: a review of its current state, trends, and future challenges

Abstract. The mountain cryosphere of mainland Europe is recognized to have important impacts on a range of environmental processes. In this paper, we provide an overview on the current knowledge on snow, glacier, and permafrost processes, as well as their past, current, and future evolution. We additionally provide an assessment of current cryosphere research in Europe and point to the different domains requiring further research. Emphasis is given to our understanding of climate–cryosphere interactions, cryosphere controls on physical and biological mountain systems, and related impacts. By the end of the century, Europe's mountain cryosphere will have changed to an extent that will impact the landscape, the hydrological regimes, the water resources, and the infrastructure. The impacts will not remain confined to the mountain area but also affect the downstream lowlands, entailing a wide range of socioeconomical consequences. European mountains will have a completely different visual appearance, in which low- and mid-range-altitude glaciers will have disappeared and even large valley glaciers will have experienced significant retreat and mass loss. Due to increased air temperatures and related shifts from solid to liquid precipitation, seasonal snow lines will be found at much higher altitudes, and the snow season will be much shorter than today. These changes in snow and ice melt will cause a shift in the timing of discharge maxima, as well as a transition of runoff regimes from glacial to nival and from nival to pluvial. This will entail significant impacts on the seasonality of high-altitude water availability, with consequences for water storage and management in reservoirs for drinking water, irrigation, and hydropower production. Whereas an upward shift of the tree line and expansion of vegetation can be expected into current periglacial areas, the disappearance of permafrost at lower altitudes and its warming at higher elevations will likely result in mass movements and process chains beyond historical experience. Future cryospheric research has the responsibility not only to foster awareness of these expected changes and to develop targeted strategies to precisely quantify their magnitude and rate of occurrence but also to help in the development of approaches to adapt to these changes and to mitigate their consequences. Major joint efforts are required in the domain of cryospheric monitoring, which will require coordination in terms of data availability and quality. In particular, we recognize the quantification of high-altitude precipitation as a key source of uncertainty in projections of future changes. Improvements in numerical modeling and a better understanding of process chains affecting high-altitude mass movements are the two further fields that – in our view – future cryospheric research should focus on.

Projection of Future Changes in Elephant Population in Amboseli under Representative Concentration Pathways

Within savanna environments, movements of elephant are influenced by changes in climate especially seasonal rainfall. In this study, we investigated the possible changes in elephant population based on projected rainfall changes using regional climate models (RCM) and Representative Concentration Pathways (RCPs). The relationship between elephant and rainfall was modelled against annual, wet season, dry season rainfall based on various time lags. Future relation between elephant and rainfall was projected based on three RCPs; 2.6, 4.5 and 8.5. There was a strong linear relationship between elephant and October-November-December (OND) rains with time lag of 13 years (Y = −4016.43 + 19.11x, r2 = 0.459, P = 0.006). The rainfall trends for RCP 2.6 and 4.5 showed a slight increase in annual rainfall for the period 2006-2100 but driven by OND increases. Rainfall increase for RCP 8.5 was significant and was driven by increase in both March-April-May (MAM) and OND. These rainfall dynamics had influence on the projected elephant population in the Amboseli ecosystem. For RCP 2.6 and 4.5 the elephant population increase was 2455 and 2814 respectively. RCP 8.5 elephant population doubled to an average of 3348 elephants. In all the RCPs there are seasonal and yearly variations and absolute number varies from the average. The range of variation is small in RCPs 2.6 and 4.5 compared to RCP 8.5. Evidently, elephant population will increase based on projected rainfall projections surpassing park capacity. It therefore, requires that the Park authority put in place measures that could contain these numbers including opening of blocked wildlife corridors, maintain the cross border movement of Amboseli elephant with Tanzania in that case ensure there is no poaching. Lastly, work with local communities so that they can benefit from tourism through setting up conservancies through which they could minimize the human elephant conflicts based on the projected elephant population.

Future changes in precipitation extremes over China using the NEX-GDDP high-resolution daily downscaled data-set

AbstractRecently, a new high-resolution daily downscaled data-set derived from 21 CMIP5 model simulations has been released by NASA, called ‘NASA Earth Exchange Global Daily Downscaled Projections’ (NEX-GDDP). In this study, the performance of this data-set in simulating precipitation extremes and long-term climate changes across China are evaluated and compared with CMIP5 GCMs. The results indicate that NEX-GDDP can successfully reproduce the spatial patterns of precipitation extremes over China, showing results that are much closer to observations than the GCMs, with increased Pearson correlation coefficients and decreased model relative error for most models. Furthermore, NEX-GDDP shows that precipitation extremes are projected to occur more frequently, with increased intensity, across China in the future. Especially at regional to local scales, more information for the projection of future changes in precipitation extremes can be obtained from this high-resolution data-set. Most importantly, the uncer...

Western Iberian offshore wind resources: More or less in a global warming climate?

Climate change is a major challenge for the energy sector, particularly for wind energy onshore and offshore. Climate models are the only tool which is able to produce physical-based projections of future changes in response to increasing greenhouse gas emissions. In the present study, the Western Iberian offshore wind resource is analysed for present and future climates, using a set of regional climate models (RCMs) simulations produced in the framework of the CORDEX experiment at 0.11° resolution (∼12km), and a regional climate simulation produced with the WRF model at higher resolution (9km). All these simulations are firstly, evaluated against wind buoy measurements and Cross-Calibrated Multi-Platform (CCMP) wind data, and used to generate two high quality multi-model ensembles based on the individual model’s performance. The results of the WRF simulation and of the two multi-model ensembles are then used to describe the wind resource both for the present and future climates, according to the RCP4.5 and RCP8.5 emission scenarios. This allows the assessment of the climate change signal on the offshore wind and to provide an uncertainty measure of these projections. The vast majority of climate models project reductions of wind speed and wind power for all seasons, with the exception of summer. For the RCP8.5 emission scenario the multi-model ensembles project reductions in power density of around 7% for winter, 4% for spring and 12% for autumn, and increases of 5% for summer. In the latter, and increase up to 20% in power density is forecasted for the Iberian northwest coast. This is sufficient to offset the yearly balance, in as much as no change is expected at a yearly scale for this area. For the remaining west Iberian coast, a yearly reduction of less than 5% is estimated. These results are shared by the two multi-model ensembles and by WRF higher resolution simulation (9km). The projected changes have the consequence of reducing the annual cycle of power density availability and of its yearly mean values. Finally, for the less aggressive scenario, RCP4.5, the changes have the same signal but with smaller values.

The impact of stochastic physics on tropical rainfall variability in global climate models on daily to weekly time scales

AbstractMany global atmospheric models have too little precipitation variability in the tropics on daily to weekly time scales and also a poor representation of tropical precipitation extremes associated with intense convection. Stochastic parameterizations have the potential to mitigate this problem by representing unpredictable subgrid variability that is left out of deterministic models. We evaluate the impact on the statistics of tropical rainfall of two stochastic schemes: the stochastically perturbed parameterization tendency scheme (SPPT) and stochastic kinetic energy backscatter scheme (SKEBS), in three climate models: EC‐Earth, the Met Office Unified Model, and the Community Atmosphere Model, version 4. The schemes generally improve the statistics of simulated tropical rainfall variability, particularly by increasing the frequency of heavy rainfall events, reducing its persistence and increasing the high‐frequency component of its variability. There is a large range in the size of the impact between models, with EC‐Earth showing the largest improvements. The improvements are greater than those obtained by increasing horizontal resolution to ∼20 km. Stochastic physics also strongly affects projections of future changes in the frequency of extreme tropical rainfall in EC‐Earth. This indicates that small‐scale variability that is unresolved and unpredictable in these models has an important role in determining tropical climate variability statistics. Using these schemes, and improved schemes currently under development, is therefore likely to be important for producing good simulations of tropical variability and extremes in the present day and future.

Erratum to: Projection of future changes in the frequency of intense tropical cyclones

Erratum to: Projection of future changes in the frequency of intense tropical cyclones

Past changes in the North Atlantic storm track driven by insolation and sea-ice forcing

Abstract Changes in the location of Northern Hemisphere storm tracks may cause significant societal and economic impacts under future climate change, but projections of future changes are highly uncertain and drivers of long-term changes are poorly understood. Here we develop a late Holocene storminess reconstruction from northwest Spain and combine this with an equivalent record from the Outer Hebrides, Scotland, to measure changes in the dominant latitudinal position of the storm track. The north-south index shows that storm tracks moved from a southern position to higher latitudes over the past 4000 yr, likely driven by a change from meridional to zonal atmospheric circulation, associated with a negative to positive North Atlantic Oscillation shift. We suggest that gradual polar cooling (caused by decreasing solar insolation in summer and amplified by sea-ice feedbacks) and mid-latitude warming (caused by increasing winter insolation) drove a steepening of the winter latitudinal temperature gradient through the late Holocene, resulting in the observed change to a more northern winter storm track. Our findings provide paleoclimate support for observational and modeling studies that link changes in the latitudinal temperature gradient and sea-ice extent to the strength and shape of the circumpolar vortex. Together this evidence now suggests that North Atlantic winter storm tracks may shift southward under future warming as sea-ice extent decreases and the mid- to high-latitude temperature gradient decreases, with storms increasingly affecting southern Europe.

Determining climate effects on US total agricultural productivity

The sensitivity of agricultural productivity to climate has not been sufficiently quantified. The total factor productivity (TFP) of the US agricultural economy has grown continuously for over half a century, with most of the growth typically attributed to technical change. Many studies have examined the effects of local climate on partial productivity measures such as crop yields and economic returns, but these measures cannot account for national-level impacts. Quantifying the relationships between TFP and climate is critical to understanding whether current US agricultural productivity growth will continue into the future. We analyze correlations between regional climate variations and national TFP changes, identify key climate indices, and build a multivariate regression model predicting the growth of agricultural TFP based on a physical understanding of its historical relationship with climate. We show that temperature and precipitation in distinct agricultural regions and seasons explain ∼70% of variations in TFP growth during 1981-2010. To date, the aggregate effects of these regional climate trends on TFP have been outweighed by improvements in technology. Should these relationships continue, however, the projected climate changes could cause TFP to drop by an average 2.84 to 4.34% per year under medium to high emissions scenarios. As a result, TFP could fall to pre-1980 levels by 2050 even when accounting for present rates of innovation. Our analysis provides an empirical foundation for integrated assessment by linking regional climate effects to national economic outcomes, offering a more objective resource for policy making.

Accounting for monogastric livestock as a driver in global land use and cover change assessments

ABSTRACTLand systems are described based on various characteristics, including land cover composition and agricultural production. However, it is uncertain to what extent livestock, particularly monogastric livestock, determines land systems. We included monogastrics in a land system classification, and statistically analyzed the land cover composition and agricultural production of otherwise similar land systems with and without monogastric livestock. The results indicate that land systems with monogastrics are statistically different from their counterparts in the classification without monogastrics in terms of grassland area and crop yields, but are less different in terms of tree area, crop area, and ruminant livestock production. We then used a land systems map that includes monogastrics in the classification and a similar map that does not include monogastrics to project future changes in a novel manner that integrates livestock as a determinant of land systems. The results show that including monogastrics in otherwise similar projections yields less cropland intensification and more cropland expansion in several world regions, including Northern Africa and the Middle East. Other regions, such as Europe and Australia, were characterized by less decrease or more increase in tree area in the application with monogastrics, mainly due to the occurrence of open forests with monogastrics. This study prompts a call for improved characterization of land systems for land use and cover change (LUCC) assessments in order to better represent LUCC driven by monogastric livestock.

Projections of future habitat use by Atlantic bluefin tuna: mechanistic vs. correlative distribution models

Climate change is likely to drive complex shifts in the distribution and ecology of marine species. Projections of future changes may vary, however, depending on the biological impact model used. In this study, we compared a correlative species distribution model and a simple mechanistic oxygen balance model for Atlantic bluefin tuna (Thunnus thynnus: ABFT) in the North Atlantic Ocean. Both models gave similar results for the recent historical time period, and suggested that ABFT generally occupy favourable metabolic habitats. Projections from an earth system model showed largely temperature-induced reductions in ABFT habitat in the tropical and sub-tropical Atlantic by 2100. However, the oxygen balance model showed more optimistic results in parts of the subpolar North Atlantic. This was partially due to an inherent ability to extrapolate beyond conditions currently encountered by pelagic longline fishing fleets. Projections included considerable uncertainty due to the simplicity of the biological models, and the coarse spatiotemporal resolution of the analyses. Despite these limitations, our results suggest that climate change is likely to increase metabolic stress on ABFT in sub-tropical habitats, but may improve habitat suitability in subpolar habitats, with implications for spawning and migratory behaviours, and availability to fishing fleets.

Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario.

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)—weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location.

Current and future levels of mercury atmospheric pollution on a global scale

Abstract. An assessment of current and future emissions, air concentrations, and atmospheric deposition of mercury worldwide is presented on the basis of results obtained during the performance of the EU GMOS (Global Mercury Observation System) project. Emission estimates for mercury were prepared with the main goal of applying them in models to assess current (2013) and future (2035) air concentrations and atmospheric deposition of this contaminant. The combustion of fossil fuels (mainly coal) for energy and heat production in power plants and in industrial and residential boilers, as well as artisanal and small-scale gold mining, is one of the major anthropogenic sources of Hg emissions to the atmosphere at present. These sources account for about 37 and 25 % of the total anthropogenic Hg emissions globally, estimated to be about 2000 t. Emissions in Asian countries, particularly in China and India, dominate the total emissions of Hg. The current estimates of mercury emissions from natural processes (primary mercury emissions and re-emissions), including mercury depletion events, were estimated to be 5207 t year−1, which represents nearly 70 % of the global mercury emission budget. Oceans are the most important sources (36 %), followed by biomass burning (9 %). A comparison of the 2035 anthropogenic emissions estimated for three different scenarios with current anthropogenic emissions indicates a reduction of these emissions in 2035 up to 85 % for the best-case scenario. Two global chemical transport models (GLEMOS and ECHMERIT) have been used for the evaluation of future mercury pollution levels considering future emission scenarios. Projections of future changes in mercury deposition on a global scale simulated by these models for three anthropogenic emissions scenarios of 2035 indicate a decrease in up to 50 % deposition in the Northern Hemisphere and up to 35 % in Southern Hemisphere for the best-case scenario. The EU GMOS project has proved to be a very important research instrument for supporting the scientific justification for the Minamata Convention and monitoring of the implementation of targets of this convention, as well as the EU Mercury Strategy. This project provided the state of the art with regard to the development of the latest emission inventories for mercury, future emission scenarios, dispersion modelling of atmospheric mercury on a global and regional scale, and source–receptor techniques for mercury emission apportionment on a global scale.

Reservoir operation using system dynamics under climate change impacts: a case study of Yamchi reservoir, Iran

This paper proposes a decision support system for Yamchi reservoir operation in semi-arid region of Iran. The paper consists of the following steps: Firstly, the potential impacts of climate change on the streamflow are predicted. The study then presents the projections of future changes in temperature and precipitation under A2 scenario using the LARS-WG downscaling model and under RCP2.6, RCP4.5, and RCP8.5 using the statistical downscaling model (SDSM) in the northwestern of Iran. To do so, a general circulation model of HadCM3 is downscaled by using the LARS-WG model. As a result, the average temperature, for the horizon 2030 (2011–2030), will increase by 0.77 °C and precipitation will decrease by 11 mm. Secondly, the downscaled variables are used as input to the artificial neural network to investigate the possible impact of climate change on the runoffs. Thirdly, the system dynamics model is employed to model different scenarios for reservoir operation using the Vensim software. System dynamics is an effective approach for understanding the behavior of complex systems. Simulation results demonstrate that the water shortage in different sectors (including agriculture, domestic, industry, and environmental users) will be enormously increased in the case of business-as-usual strategy. In this research, by providing innovative management strategies, including deficit irrigation, the vulnerability of reservoir operation is reduced. The methodology is evaluated by using different modeling tests which then motivates using the methodology for other arid/semi-arid regions.