Climate Change Threatens Micronutrient Density of European Winter Wheat.

Mental health and climate change: tackling invisible injustice

This paper evaluates the possible impacts of climate change and land use change and its combined effects on soil loss and net soil loss (erosion and deposition) in the Mae Nam Nan sub-catchment, Thailand. Future climate from two general circulation models (GCMs) and a regional circulation model (RCM) consisting of HadCM3, NCAR CSSM3 and PRECIS RCM ware downscaled using a delta change approach. Cellular Automata/Markov (CA_Markov) model was used to characterize future land use. Soil loss modeling using Revised Universal Soil Loss Equation (RUSLE) and sedimentation modeling in Idrisi software were employed to estimate soil loss and net soil loss under direct impact (climate change), indirect impact (land use change) and full range of impact (climate and land use change) to generate results at a 10 year interval between 2020 and 2040. Results indicate that soil erosion and deposition increase or decrease, depending on which climate and land use scenarios are considered. The potential for climate change to increase soil loss rate, soil erosion and deposition in future periods was established, whereas considerable decreases in erosion are projected when land use is increased from baseline periods. The combined climate and land use change analysis revealed that land use planning could be adopted to mitigate soil erosion and deposition in the future, in conjunction with the projected direct impact of climate change.

Although consensus exists among the scientific community that climate change could affect future air-quality through its linkages to weather meteorology, the evolution of the atmospheric composition in a changing climate needs to be further investigated. The objective of this study is to investigate the potential impact of future climate change on ozone air-quality in Europe. Simulations with the global chemical transport model GEOS-CHEM driven from the GISS III general circulation model are conducted for a present (1999–2001) and the future (2049–2051) 3-year period. To isolate the effects from changes in climate and anthropogenic emissions four types of simulations are performed: (1) present day climate and emissions (2) future climate following the IPCC SRES A1B scenario and present day anthropogenic emissions of ozone precursors (3) present day climate and future emissions and (4) future climate and emissions. Results indicate that the impact of climate change on its own leads to an increase of less than 3 ppb in western and central Europe. When both climate change and future emissions are implemented in the simulations higher changes in the ozone concentrations are evident reaching 12 ppb in the South west and east Mediterranean. Moreover, the ozone photochemical sensitivity to isoprene and nitrogen oxides (NOx) is also investigated.

Climate change impact assessment along with adaptation measures are key for reducing the impact of climate change on crop production. The impact of current and future climate change on maize production was investigated, and the adaptation role of shifting planting dates, different levels of nitrogen fertilizer rates, and choice of maize cultivar as possible climate change adaptation strategies were assessed. The study was conducted in three environmentally contrasting sites in Ethiopia, namely: Ambo, Bako, and Melkassa. Future climate data were obtained from seven general circulation models (GCMs), namely: CanESM2, CNRM-CM5, CSIRO-MK3-6-0, EC-EARTH, HadGEM2-ES, IPSL-CM5A-MR, and MIROC5 for the highest representative concentration pathway (RCP 8.5). GCMs were bias-corrected at site level using a quantile-quantile mapping method. APSIM, AquaCrop, and DSSAT crop models were used to simulate the baseline (1995–2017) and 2030s (2021–2050) maize yields. The result indicated that the average monthly maximum air temperature in the 2030s could increase by 0.3–1.7 °C, 0.7–2.2 °C, and 0.8–1.8 °C in Ambo, Bako, and Melkassa, respectively. For the same sites, the projected increase in average monthly minimum air temperature was 0.6–1.7 °C, 0.8–2.3 °C, and 0.6–2.7 °C in that order. While monthly total precipitation for the Kiremt season (June to September) is projected to increase by up to 55% (365 mm) for Ambo and 75% (241 mm) for Bako respectively, whereas a significant decrease in monthly total precipitation is projected for Melkassa by 2030. Climate change would reduce maize yield by an average of 4% and 16% for Ambo and Melkassa respectively, while it would increase by 2% for Bako in 2030 if current maize cultivars were grown with the same crop management practice as the baseline under the future climate. At higher altitudes, early planting of maize cultivars between 15 May and 1 June would result in improved relative yields in the future climate. Fertilizer levels increment between 23 and 150 kg ha−1 would result in progressive improvement of yields for all maize cultivars when combined with early planting for Ambo. For a mid-altitude, planting after 15 May has either no or negative effect on maize yield. Early planting combined with a nitrogen fertilizer level of 23–100 kg ha−1 provided higher relative yields under the future climate. Delayed planting has a negative influence on maize production for Bako under the future climate. For lower altitudes, late planting would have lower relative yields compared to early planting. Higher fertilizer levels (100–150 kg ha−1) would reduce yield reductions under the future climate, but this varied among maize cultivars studied. Generally, the future climate is expected to have a negative impact on maize yield and changes in crop management practices can alleviate the impacts on yield.

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] There is a need to raise our understanding of the impact of climate variability and change on hydrologic processes at the watershed scale. This is important, particularly for land managers and policymakers, in making better-informed decisions to assess adaptation strategies and to ensure that all sectors and populations can meet projected water demand. The Missouri Salt River Basin was chosen for this study due to its unique soil and agriculture-dominated land use. It is dominated by high clay content soils, making it sensitive to changes in the hydrologic condition. While numerous studies have examined hydrologic processes around this region, only a few have analyzed linkages between climate and the consequence of these changes to water allocation. One of the greatest potentials to maintain viable crop and livestock economies is to continue making gains in production efficiency, particularly in the area of rain-fed crops with the potential of increasing irrigation. Therefore, the objective of this study is to: (1) evaluate the impacts of potential climate and land use changes on the hydrologic components of the agriculturally dominated Salt River Basin; (2) evaluate the impact of climate change to agriculture management in this watershed, and determine if land use change can mitigate the climate change impacts on hydrological processes; (3) evaluate the impacts of potential climate changes on the water supply and demand of the Salt River Basin using integrated hydrological model and water allocation model approach; (4) determine if future water supply can meet the Salt River Basin catchment demands, and evaluate the future water competition among different sectors in the Salt River Basin using scenario based approach. Temperature and precipitation projections for two representative concentration pathways (RCP 4.5 moderate CO[2] level and RCP 8.5 high CO[2] level) were obtained from nineteen general circulation models statistically downscaled to better represent local conditions. These data, along with soils, land cover, land management, and topography, were input to the Soil and Water Assessment Tool (SWAT), a process-based hydrologic simulation model, to evaluate hydrologic impacts. Possible outcomes for the near (2020-2039) and far (2040-2059) future scenarios were determined. Combined climate and land use change scenarios showed distinct annual and seasonal variations in hydrological processes. Annual precipitation was projected to increase from 4% to 7%, which resulted in 14% more spring days with soil water content equal or exceeding field capacity in mid-century. However, 07 precipitation was projected to decrease -- a critical factor for crop growth. Higher temperatures led to increased potential vapotranspiration during the growing season, resulting in an increased need for irrigation by 38 mm. Analysis from multiple land use scenarios indicated that converting crop and pasture land to forest coverage can potentially mitigate the effects of climate change on streamflow, thus insuring future water availability. Using hydrologic output simulations from SWAT, evaluation of water allocation strategies was performed using the water evaluation and planning (WEAP) model. By selecting priority water use strategies, WEAP enabled review of potential conflicts among users through scenario-based approaches. Operating on the principle of water balance accounting, a range of inter-related water issues facing water users, including multiple water sources, sectoral demand analyses, water conservation, water allocation priorities, and general reservoir operations, were evaluated. For this study, scenarios with different rate of irrigation expansion for crop areas were evaluated. The Ag Census data from 1997, 2002, and 2007 were analyzed to obtain the historical reported numbers of livestock in each county within the watershed. The historical livestock numbers combined with USDA agricultural projections to 2027 were used to project inventory for 2060. The results indicated that future water shortages will become more prominent in the SRB under projected climate conditions. Without any change irrigation area, the future unmet could double as a consequence of climate change from 3 million m3 to 6 million m3. Increased irrigation equal 10% of crop land results in 38.5 million m3 of unmet water demand. If water from Mark Twain can be withdrawn for agriculture purposes, the unmet demand would lower by 30% compared with the baseline period. However, under prolonged drought period, the impact of the Mark Twain Lake is limited. Finally, under all considered scenarios public water supply is not a source of water vulnerability in this region.

Managing flood risks in a changing climate

Anthropogenic climate change and allergen exposure: The role of plant biology

The projected impact of climate and land use change on plant diversity: An example from West Africa

Evaluating the impact of future climate and forest cover change on the ability of Southeast (SE) Asia’s protected areas to provide coverage to the habitats of threatened avian species

Australia's political engagement on health and climate change: the MJA-Lancet Countdown indicator and implications for the future.

Malaria is a serious global health issue, resulting in an estimated 219 million cases and 660,000 deaths in 2010, many of them in Africa.1 Malaria transmission is tied closely to environmental variables such as rainfall and temperature—even when there’s plenty of rainfall to produce breeding pools for the Anopheles mosquitoes that spread malaria, hot temperatures can hamper mosquito development.2 Some early projections predicted that climate change would cause an increase in malaria cases,3 but more recent reports suggest it’s more likely that cases will shift in their distribution rather than rise overall.4 In this issue of EHP investigators at the Massachusetts Institute of Technology (MIT) report their projections, using a new modeling tool, that there probably will not be a significant increase in malaria prevalence in West Africa, even during a worst-case scenario of increased rainfall in the region.5 The authors used the Hydrology, Entomology, and Malaria Transmission Simulator (HYDREMATS) to estimate the impact of climate change on malaria transmission in West Africa. HYDREMATS is a combined hydrology and entomology model of malaria transmission developed at MIT by coauthor Elfatih A.B. Eltahir, a professor in the Department of Civil and Environmental Engineering, and former graduate student Arne Bomblies, now an assistant professor at the University of Vermont. The model uses high-resolution data on environmental variables including rainfall, temperature, topography, and soil conditions to model ephemeral breeding pools that form during intense rains. The model also tracks the simulated behavior of individual mosquitoes as they interact with their environment. The researchers used current climate data to model vectorial capacity, a measure of how efficiently mosquitoes spread malaria. They then looked at climate predictions for the time period 2080–2099 and determined which combination of temperature and rainfall changes corresponded to best- and worst-case scenarios in terms of malaria transmission. They conducted simulations using the best- and worst-case climate projections to predict vectorial capacity under each new scenario. The model did not include changes in malaria transmission due to interventions such as spraying, mosquito netting, and preventive medications. Figure 1 A child with malaria receives care in Sierra Leone. This country lies in a part of West Africa that is already saturated with malaria, and prevalence is not projected to increase with climate change. Figure 1 An ephemeral pool in Niger provides a perfect breeding site for Anopheles mosquitoes. This and other northern parts of West Africa could become too hot to sustain malaria. The northernmost areas studied are currently too dry and warm for effective malaria transmission. According to the model, they could become more suitable only if the climate becomes substantially wetter, but even then high temperatures likely would prohibit sustained transmission. The middle areas are expected to see a decrease in suitability for malaria transmission even under the wettest predictions of future climate. Southern areas could become even more suitable for transmission, but the persistent prevalence of malaria in these areas means a rise in cases is unlikely unless many people immigrate. Therefore, the investigators conclude, it appears unlikely, on the basis of this model, that climate change will increase malaria transmission in West Africa.5 “The main advantage of our malaria transmission model is that it provides a more detailed and direct relationship among environmental variables and malaria transmission than previous models,” says coauthor Teresa K. Yamana, a PhD student. “This is especially true for rainfall, because the timing of rain is just as important as the amount of rain. For example, more puddles form if there’s a big storm compared to if the same amount of rain falls over the course of several days.” Another strength of the study is its consideration of a wide range of climate predictions. Yamana explains that climate impact studies may be based on the climate predictions of a single model without knowing whether that model accurately represents the region of interest. Others average the predictions made by multiple models, but this is not a good strategy in the case of West Africa: “Half of the predictions say the climate will be wetter, half say it will be drier,6” she says, “so the average is something close to no change in rainfall—this could end up being very far from the truth.” Jonathan Patz, director of the Global Health Institute at the University of Wisconsin–Madison, is impressed by the researchers’ modeling because it “included a range of best- and worst-case scenarios to avoid bias. They also considered both temperature and rainfall, essential for malaria estimates.” He says, “Their findings are consistent with expectations that temperature projections alone explain only a part of malaria risk, and disease risk will considerably depend on rainfall and other environmental factors, particularly hydrological dynamics that vary by location.”

International audience

The impact of global climate change is a challenge to the sustainability of many ecosystems, including soil systems. However, the performance of soil properties under future climate was rarely assessed. Therefore, this study was carried out to evaluate selected soil processes under climate change using an agri-environmental modeling approach to Sri Lanka. The Agricultural Production Systems Simulator (APSIM) model was used to simulate soil and plant-related processes using recent past (1990–2019) and future (2041–2070) climates. Future climate data were obtained for a regional climate model (RCM) under representative concentrations pathway 4.5 scenarios. Rainfalls are going to be decreased in all the tested locations under future climate scenarios while the maximum temperature showcased rises. According to simulated results, the average yield reduction under climate change was 7.4%. The simulated nitrogen content in the storage organs of paddy declined in the locations (by 6.4–25.5%) as a reason for climate change. In general, extractable soil water relative to the permanent wilting point (total available water), infiltration, and biomass carbon lost to the atmosphere decreased while soil temperature increased in the future climate. This modeling approach provides a primary-level prediction of soil dynamics under climate change, which needs to be tested using fieldwork.

In climate change (CC) impact studies, various weather-dependent models (e.g. crop growth models or rainfall-runoff models) are employed to assess possible CC impacts on crop yields, river flows, as well as on various climatological and other indices. To perform such experiments, one has to decide what meteorological data (representing present & future climate) will be used as inputs. Two most commonly used approaches at hand are Regional Climate Models (RCMs) and Stochastic Weather Generators (WGs). While one might say, that these two approaches are the rivals which compete for getting the main role in providing the weather data for CC impact studies, we want to demonstrate that these two approaches could be rather allies  which could be very effective while being used together.In our presentation, we show three ways of such co-operation: (1) To produce weather series representing the future climate by the WG, WG parameters must be modified by CC scenarios, which may be derived by comparing RCM simulations of present vs. future climates. (2) To assess separate effects of changes (projected by RCMs) in individual weather variables (e.g. temperature or precipitation) and their statistical characteristics (means, variabilities, spatial and/or temporal correlations), WG may be used: only selected WG parameters representing chosen variable and its statistical characteristic may be modified before producing the synthetic series. (3) To assess statistical significance of the changes derived from a given RCM simulation, WG may be also used: the significancy of projected changes may be based on analyzing the spread of the changes derived by comparing multiple pairs of synthetic time series produced by WG calibrated with RCM simulations for future vs. present time slices.In the experiment, we use: (a) our multi-site multi-variate parametric weather generator SPAGETTA, (b) E-OBS data to calibrate the generator for the present climate conditions in 8 European regions, and (c) outputs from ensemble of 19 RCM simulations for present and future climate (CORDEX database) in these regions.Acknowledgement: The experiment was made within the frame of the PERUN project funded by the Technological Agency of the Czech Republic (project no. SS0203004000).

Integrating hydrology with climate is essential for a better understanding of the impact of present and future climate on hydrological extremes, which may cause frequent flooding, drought, and shortage of water supply. This study assessed the impact of future climate change on the hydrological extremes (peak and low flows) of the Zenne river basin (Belgium). The objectives were to assess how climate change impacts basin-wide extreme flows and to provide a detailed overview of the impacts of four future climate change scenarios compared to the control (baseline) values. The scenarios are high (wet) summer (projects a future with high storm rain in summer), high (wet) winter (predicts a future with high rainfall in winter), mean (considers a future with intermediate climate conditions), and low (dry) (projects a future with low rainfall during winter and summer). These scenarios were projected by using the Climate Change Impact on HYDRological extremes perturbation tool (CCI-HYDR), which was (primarily) developed for Belgium to study climate change. We used the Soil and Water Assessment Tool (SWAT) model to predict the impact of climate change on hydrological extremes by the 2050s (2036–2065) and the 2080s (2066–2095) by perturbing the historical daily data of 1961–1990. We found that the four climate change scenarios show quite different impacts on extreme peak and low flows. The extreme peak flows are expected to increase by as much as 109% under the wet summer scenario, which could increase adverse effects, such as flooding and disturbance of the riverine ecosystem functioning of the river. On the other hand, the low (dry) scenario is projected to cause a significant decrease in both daily extreme peak and low flows, by as much as 169% when compared to the control values, which would cause problems, such as droughts, reduction in agricultural crop productivity, and increase in drinking water and other water use demands. More importantly, larger negative changes in low flows are predicted in the downstream part of the basin where a higher groundwater contribution is expected, indicating the sensitivity of a basin to the impact of climate change may vary spatially and depend on basin characteristic. Overall, an amplified, as well as an earlier, occurrence of hydrological droughts is expected towards the end of this century, suggesting that water resources managers, planners, and decision makers should prepare appropriate mitigation measures for climate change for the Zenne and similar basins.