Implications of limiting CO2 concentrations for land use and energy

Trade-offs in land-based carbon removal measures under 1.5 °C and 2 °C futures

Land-based carbon removals, specifically afforestation/reforestation and bioenergy with carbon capture and storage (BECCS), vary widely in 1.5 °C and 2 °C scenarios generated by integrated assessment models. Because underlying drivers are difficult to assess, we use a well-known integrated assessment model, GCAM, to demonstrate that land-based carbon removals are sensitive to the strength and scope of land-based mitigation policies. We find that while cumulative afforestation/reforestation and BECCS deployment are inversely related, they are both typically part of cost-effective mitigation pathways, with forestry options deployed earlier. While the CO2 removal intensity (removal per unit land) of BECCS is typically higher than afforestation/reforestation over long time horizons, the BECCS removal intensity is sensitive to feedstock and technology choices whereas the afforestation/reforestation removal intensity is sensitive to land policy choices. Finally, we find a generally positive relationship between agricultural prices and removal effectiveness of land-based mitigation, suggesting that some trade-offs may be difficult to avoid.

Cover crop performance under a changing climate in continuous corn system over Nebraska

Fall-planted cover crop (CC) within a continuous corn (Zea mays L.) system offers potential agroecosystem benefits, including mitigating the impacts of increased temperature and variability in precipitation patterns. A long-term simulation using the Decision Support System for Agrotechnology Transfer model was made to assess the effects of cereal rye (Secale cereale L.) on no-till continuous corn yield and soil properties under historical (1991-2020) and projected climate (2041-2070) in eastern Nebraska. Local weather data during the historical period were used, while climate change projections were based on the Canadian Earth System Model 2 dynamically downscaled using the Canadian Centre for Climate Modelling and Analysis Regional Climate Model 4 under two representative concentration pathways (RCP), namely, RCP4.5 and RCP8.5. Simulations results indicated that CC impacts on corn yield were nonsignificant under historical and climate change conditions. Climate change created favorable conditions for CC growth, resulting in an increase in biomass. CC reduced N leaching under climate change scenarios compared to an average reduction of 60% (7 kg ha- 1 ) during the historical period. CC resulted in a 6% (27 mm) reduction in total water in soil profile (140 cm) and 22% (27 mm) reduction in plant available water compared to no cover crop during historical period. CC reduced cumulative seasonal surface runoff/soil evaporation and increased the rate of soil organic carbon buildup. This research provides valuable information on how changes in climate can impact the performance of cereal rye CC in continuous corn production and should be scaled to wider locations and CC species.

Economic valuation of selected ecosystem services in Islamabad Capital Territory (ICT), Pakistan

Abstract Payment for ecosystem services (PES) is a mechanism where a consumer is able and ready to pay for the protection of the precise ecosystem service and there must be a provider such as local societies receiving an economic resource, who in return, must have the ability to maintain that ecosystem service. Economic valuation provides basis for payment for ecosystem services. Therefore, objective of this study was to evaluate tourism and carbon stock services of the Islamabad Capital Territory (ICT), Pakistan. Two forest zones (Chirpine and Scrub) of Islamabad capital territory (ICT) were selected for estimation of carbon stock and their carbon credits and carbon worth, a questionnaire-based survey was conducted for tourism as a payment for ecosystem services. The method for carbon stock assessment was systematic sampling for Chirpine forest whereas random sampling was done for scrub forest. The size of sampling plot was 17.84 m radius, and a total of 93 plots (49 Scrub zone and 44 Chirpine zone) was taken in the study area. The carbon stock of both zones (Chirpine and Scrub zone) is 22556.75 ton/ha (Chirpine 20105.79, Scrub 2450.96) and total carbon dioxide sequestered by both zone is 82557.72 ton/ha (Chirpine 73587.2, Scrub 8970.52), total carbon credits of both zone is 302160.87 (Chirpine 269328.97, Scrub 32831.9) and the carbon worth of both Chirpine and scrub zone is 4532418.92 $ (Chirpine 4039937.09$, Scrub 492481.83$). Similarly, from tourism point of view, in Shakar Parian, 94% tourists were agreed for PES whereas 6% were disagreed for the PES (the 6% tourist were disagreed to contribute for PES, 40% were agreed for Rs.5 contribution and 54% for Rs.10.). moreover, in Lake view Park, 97% tourists were agreed and 3% are disagreed (In Lake View Park 5% tourists were disagreed for the PES contribution whereas 32% were agreed for Rs.5 and 63% were for Rs.10). In Damen e Koh, around 87% tourist were agreed and 13% were disagreed, (24% were agreed for the contribution of Rs.5 and 63% tourists were agreed for the contribution of Rs.10). In Marghazar Zoo, 93% tourists were agreed (22% were agreed for contribution of Rs.5 and 71% tourist were agreed for contribution of Rs.10) and 7% are disagreed for PES whereas 7% tourists were not agreed for contribution. PES may implement to compensate forest and parks manager to ensure better management of the forests and parks. Due to prime location and scenic beauty of the ICT, it has huge potential for implementation of PES mechanism for sustainable forest management and conservation. Therefore, it is recommended that Capital Development Authority (CDA) Islamabad should devise a plan for implementation of PES in forests and parks of ICT for its sustainable management of recreational and forest resources.

The allometric relationship between carbon emission and economic development in Yangtze River Delta: fusion of multi-source remote sensing nighttime light data

Exploring the allometric relationship between carbon emission and economic development can provide guidance for policy-makers who hope to accelerate carbon emission reduction and achieve high-quality development. First, based on the established DMSP/OLS and NPP/VIIRS nighttime light datasets, this study simulated the carbon emissions of the Yangtze River Delta from 2000 to 2020. Second, our research analyzed the spatiotemporal evolution characteristics of carbon emissions. Third, adopting allometric growth model, we explored the allometric relationship between economic development and carbon emissions in Yangtze River Delta. The main conclusions are as follows. First, four prediction models, namely, linear fitting, support vector machine, random forest, and CNN-BiLSTM deep learning, were compared to simulate the accuracy of carbon emissions. Consequently, the CNN-BiLSTM deep learning estimation model presented the best accuracy. Second, both the carbon emissions in YRD as a whole showed an increasing trend, with the largest growth rate appearing in Shanghai and the smallest growth rate occurring in Lishui. Moreover, the high-carbon emission areas were mainly distributed in the core city cluster, which are enclosed by Shanghai, Nanjing, and Hangzhou. Finally, the allometric relationship between economic development and carbon emissions was dominated by one-level negative during the sample period, and the relative growth rate of carbon emissions is lower than that of the economic development, which made the YRD at a basic coordinate stage of weak expansion of economy.

Geographic distribution and impacts of climate change on the suitable habitats of Rhamnus utilis Decne in China

BACKGROUND

Rhamnus utilis Decne (Rhamnaceae) is an ecologically and economically important tree species. The growing market demands and recent anthropogenic impacts to R. utilis forests has negatively impacted its populations severely. However, little is known about the potential distribution of this species and environmental factors that affect habitat suitability for this species. By using 219 occurrence records along with 51 environmental factors, present and future suitable habitats were estimated for R. utilis using Maxent modeling; the important environmental factors affecting its distribution were analyzed.

RESULTS

January water vapor pressure, normalized difference vegetation index, mean diurnal range, and precipitation of the warmest quarter represented the critical factors explaining the environmental requirements of R. utilis. The potential habitat of R. utilis included most provinces from central to southeast China. Under the climate change scenario SSP 245, Maxent predicted a cumulative loss of ca. 0.73 × 105 km2 in suitable habitat for R. utilis during 2041-2060 while an increase of ca. 0.65 × 105 km2 occurred during 2081-2100. Furthermore, under this climate change scenario, the suitable habitat will geographically expand to higher elevations.

CONCLUSIONS

The findings of our study provide a foundation for targeted conservation efforts and inform future research on R. utilis. By considering the identified environmental factors and anticipating the potential impacts of climate change, conservation strategies can be developed to preserve and restore suitable habitats for R. utilis. Protecting this species is not only crucial for maintaining biodiversity but also for sustaining the economic benefits associated with its ecological services.

Nitrogen addition delays the emergence of an aridity-induced threshold for plant biomass

Crossing certain aridity thresholds in global drylands can lead to abrupt decays of ecosystem attributes such as plant productivity, potentially causing land degradation and desertification. It is largely unknown, however, whether these thresholds can be altered by other key global change drivers known to affect the water-use efficiency and productivity of vegetation, such as elevated CO2 and nitrogen (N). Using >5000 empirical measurements of plant biomass, we showed that crossing an aridity (1-precipitation/potential evapotranspiration) threshold of ∼0.50, which marks the transition from dry sub-humid to semi-arid climates, led to abrupt declines in aboveground biomass (AGB) and progressive increases in root:shoot ratios, thus importantly affecting carbon stocks and their distribution. N addition significantly increased AGB and delayed the emergence of its aridity threshold from 0.49 to 0.55 (P < 0.05). By coupling remote sensing estimates of leaf area index with simulations from multiple models, we found that CO2 enrichment did not alter the observed aridity threshold. By 2100, and under the RCP 8.5 scenario, we forecast a 0.3% net increase in the global land area exceeding the aridity threshold detected under a scenario that includes N deposition, in comparison to a 2.9% net increase if the N effect is not considered. Our study thus indicates that N addition could mitigate to a great extent the negative impact of increasing aridity on plant biomass in drylands. These findings are critical for improving forecasts of abrupt vegetation changes in response to ongoing global environmental change.

Spatial-temporal dynamics of land use carbon emissions and drivers in 20 urban agglomerations in China from 1990 to 2019

Urban agglomerations (UAs) are the largest carbon emitters; thus, the emissions must be controlled to achieve carbon peak and carbon neutrality. We use long time series land-use and energy consumption data to estimate the carbon emissions in UAs. The standard deviational ellipse (SDE) and spatial autocorrelation analysis are used to reveal the spatiotemporal evolution of carbon emissions, and the geodetector, geographically and temporally weighted regression (GTWR), and boosted regression trees (BRTs) are used to analyze the driving factors. The results show the following: (1) Construction land and forest land are the main carbon sources and sinks, accounting for 93% and 94% of the total carbon sources and sinks, respectively. (2) The total carbon emissions of different UAs differ substantially, showing a spatial pattern of high emissions in the east and north and low emissions in the west and south. The carbon emissions of all UAs increase over time, with faster growth in UAs with lower carbon emissions. (3) The center of gravity of carbon emissions shifts to the south (except for North China, where it shifts to the west), and carbon emissions in UAs show a positive spatial correlation, with a predominantly high-high and low-low spatial aggregation pattern. (4) Population, GDP, and the annual number of cabs are the main factors influencing carbon emissions in most UAs, whereas other factors show significant differences. Most exhibit an increasing trend over time in their impact on carbon emissions. In general, China still faces substantial challenges in achieving the dual carbon goal. The carbon control measures of different UAs should be targeted in terms of energy utilization, green and low-carbon production, and consumption modes to achieve the low-carbon and green development goals of the United Nations' sustainable cities and beautiful China's urban construction as soon as possible.

Topographic information improves simulated patterns of post-fire conifer regeneration in the southwest United States

The western United States is projected to experience more frequent and severe wildfires in the future due to drier and hotter climate conditions, exacerbating destructive wildfire impacts on forest ecosystems such as tree mortality and unsuccessful post-fire regeneration. While empirical studies have revealed strong relationships between topographical information and plant regeneration, ecological processes in ecosystem models have either not fully addressed topography-mediated effects on the probability of plant regeneration, or the probability is only controlled by climate-related factors, for example, water and light stresses. In this study, we incorporated seedling survival data based on a planting experiment in the footprint of the 2011 Las Conchas Fire into the Photosynthesis and EvapoTranspiration (PnET) extension of the LANDIS-II model by adding topographic and an additional climatic variable to the probability of regeneration. The modified algorithm included topographic parameters such as heat load index and ground slope and spring precipitation. We ran simulations on the Las Conchas Fire landscape for 2012-2099 using observed and projected climate data (i.e., Representative Concentration Pathway 4.5 and 8.5). Our modification significantly reduced the number of regeneration events of three common southwestern conifer tree species (piñon, ponderosa pine, and Douglas-fir), leading to decreases in aboveground biomass, regardless of climate scenario. The modified algorithm decreased regeneration at higher elevations and increased regeneration at lower elevations relative to the original algorithm. Regenerations of three species also decreased in eastern aspects. Our findings suggest that ecosystem models may overestimate post-fire regeneration events in the southwest United States. To better represent regeneration processes following wildfire, ecosystem models need refinement to better account for the range of factors that influence tree seedling establishment. This will improve model utility for projecting the combined effects of climate and wildfire on tree species distributions.

Simulation-based assessment of the soil organic carbon sequestration in grasslands in relation to management and climate change scenarios

Soil organic carbon (SOC) is crucial for the quality and productivity of terrestrial ecosystems and its sequestration plays an important role in mitigating climate change. Understanding the effects of agricultural management under future climate on the SOC balance helps decision making in environmental policies. Thereby, grasslands will play a key role, since future climate change may prolong the vegetation period. We used 24 representative grassland sites in Germany to assess the SOC balance obtained from the CANDY model in relation to ten management regimes, 18 future climate change scenarios and different soil types. Simulations were conducted over a period of 110 years. For most of the selected grassland sites an increase in both air temperature and precipitation was observed in the future climate. The effect of management on the SOC balance largely exceeded the effect of soil type and climate. An increasing management intensity (i.e. three to five cuts) generally increased the SOC balance, while extensive management (i.e. two or fewer cuts) lead to SOC losses. The seasonal variation of precipitation was the most important climate metric, with increased SOC sequestration rates being observed with increasing growing season precipitation. Clay soils had the potential for both highest gains and highest losses depending on management and precipitation. Given an overall lower SOC storage potential in sands and loams, the SOC balance in those soil types varied the least in response to climate change. We conclude that fostering SOC sequestration is possible in grassland soils by increasing management intensity, which involves increased fertilizer input and field traffic. This however may stand in conflict with other policy aims, such as preserving biodiversity. Multicriterial assessments are required to estimate the nett greenhouse gas balance and other aspects associated with these management practices at a farm scale.

Machine Learning Modeling of Aedes albopictus Habitat Suitability in the 21st Century

The Asian tiger mosquito, Aedes albopictus, is an important vector of arboviruses that cause diseases such as dengue, chikungunya, and zika. The vector is highly invasive and adapted to survive in temperate northern territories outside its native tropical and sub-tropical range. Climate and socio-economic change are expected to facilitate its range expansion and exacerbate the global vector-borne disease burden. To project shifts in the global habitat suitability of the vector, we developed an ensemble machine learning model, incorporating a combination of a Random Forest and XGBoost binary classifiers, trained with a global collection of vector surveillance data and an extensive set of climate and environmental constraints. We demonstrate the reliable performance and wide applicability of the ensemble model in comparison to the known global presence of the vector, and project that suitable habitats will expand globally, most significantly in the northern hemisphere, putting at least an additional billion people at risk of vector-borne diseases by the middle of the 21st century. We project several highly populated areas of the world will be suitable for Ae. albopictus populations, such as the northern parts of the USA, Europe, and India by the end of the century, which highlights the need for coordinated preventive surveillance efforts of potential entry points by local authorities and stakeholders.

Predicting of the current and future geographical distribution of Laurus nobilis L. under the effects of climate change

Today, climate change affects all living things on earth. It also leads to serious losses in terms of biodiversity, ecosystem services, and human welfare. In this context, Laurus nobilis L. is a very important species for Turkey, and the Mediterranean countries. This research aimed to simulate the current distribution of the suitable habitat for L. nobilis in Turkey and to predict its possible range shifts in future climate scenarios. To predict the geographical distribution of L. nobilis, the study used the maximum-entropy algorithm-based MaxEnt 3.4.1 with seven bioclimatic variables created using the Community Climate System Model 4.0 (CCSM4) and the prediction models RCP4.5-8.5 for the years 2050-2070. The results indicated that the most important bioclimatic variables that shape the distribution of L. nobilis are BIO11-mean temperature of coldest quarter, and BIO7-annual temperature range. Two climate change scenarios predicted that the geographical distribution of L. nobilis would increase slightly and then decrease in the future. However, the spatial change analysis showed that the general geographical distribution area of L. nobilis did not change significantly, but the "moderate," "high," and "very high" suitable habitats changed towards "low" suitable habitats. These changes were particularly effective in Turkey's Mediterranean region, which shows that climate change is instrumental in determining the future of the Mediterranean ecosystem. Therefore, suitability mapping and change analysis of potential future bioclimatic habitats can help in planning for land use, conservation, and ecological restoration of L. nobilis.

Methane emissions from California dairies estimated using novel climate metric Global Warming Potential Star show improved agreement with modeled warming dynamics

Introduction

Carbon dioxide (CO2) and methane (CH4) are two of the primary greenhouse gases (GHG) responsible for global warming. The “stock gas” CO2 accumulates in the atmosphere even if rates of CO2 emission decline. In contrast, the “flow gas” CH4 has an e-folding time of about 12 years and is removed from the atmosphere in a relatively short period of time. The climate impacts of cumulative pollutants such as CO2 and short-lived climate pollutants (SLCP) such as CH4 are often compared using Global Warming Potential (GWP), a metric that converts non-CO2 GHG into CO2-equivalent emissions. However, GWP has been criticized for overestimating the heating effects of declining SLCP emissions and conversely underestimating the heating impact of increasing SLCP emissions. Accurate quantification of the temperature effects of different CH4 emissions scenarios is particularly important to fully understanding the climate impacts of animal agriculture, whose GHG emissions are dominated by CH4.

Methods

A modified GWP metric known as Global Warming Potential Star (GWP*) has been developed to directly quantify the relationship between SLCP emissions and temperature change, which GWP cannot do. In this California dairy sector case study, we contrasted GWP- versus GWP*-based estimates of historical warming dynamics of enteric and manure CH4 from lactating dairy cattle. We predicted future dairy CH4 emissions under business-as-usual and reduction scenarios and modeled the warming effects of these various emission scenarios.

Results

We found that average CO2 warming equivalent emissions given by GWP* were greater than those given by GWP under increasing annual CH4 emissions rates, but were lower under decreasing CH4 emissions rates. We also found that cumulative CO2 warming equivalent emissions given by GWP* matched modeled warming driven by decreasing CH4 emissions more accurately than those given by GWP.

Discussion

These results suggest that GWP* may provide a more accurate tool for quantifying SLCP emissions in temperature goal and emissions reduction-specific policy contexts.

Dependence of column ozone on future ODSs and GHGs in the variability of 500-ensemble members

State-of-the-art chemistry-climate models (CCMs) have indicated that a future decrease in ozone-depleting substances (ODSs) combined with an increase in greenhouse gases (GHGs) would increase the column ozone amount in most regions except the tropics and Antarctic. However, large Arctic ozone losses have occurred at a frequency of approximately once per decade since the 1990s (1997, 2011 and 2020), despite the ODS concentration peaking in the mid-1990s. To understand this, CCMs were used to conduct 24 experiments with ODS and GHG concentrations set based on predicted values for future years; each experiment consisted of 500-member ensembles. The 50 ensemble members with the lowest column ozone in the mid- and high latitudes of the Northern Hemisphere showed a clear ODS dependence associated with low temperatures and a strong westerly zonal mean zonal wind. Even with high GHG concentrations, several ensemble members showed extremely low spring column ozone in the Arctic when ODS concentration remained above the 1980-1985 level. Hence, ODS concentrations should be reduced to avoid large ozone losses in the presence of a stable Arctic polar vortex. The average of the lowest 50 members indicates that GHG increase towards the end of the twenty-first century will not cause worse Arctic ozone depletion.

Trajectories of wildfire behavior under climate change. Can forest management mitigate the increasing hazard?

Mediterranean forests and fire regimes are closely intertwined. Global change is likely to alter both forest dynamics and wildfire activity, ultimately threatening the provision of ecosystem services and posing greater risks to society. In this paper we evaluate future wildfire behavior by coupling climate projections with simulation models of forest dynamics and wildfire hazard. To do so, we explore different forest management scenarios reflecting different narratives related to EU forestry (promotion of carbon stocks, reduction of water vulnerability, biomass production and business-as-usual) under the RCP 4.5 and RCP 8.5 climate pathways in the period 2020-2100. We used as a study model pure submediterranean Pinus nigra forests of central Catalonia (NE Spain). Forest dynamics were simulated from the 3rd National Forest Inventory (143 stands) using SORTIE-nd software based on climate projections under RCPs 4.5 and 8.5. The climate products were also used to estimate fuel moisture conditions (both live and dead) and wind speed. Fuel parameters and fire behavior were then simulated, selecting crown fire initiation potential and rate of spread as key indicators. The results revealed consistent trade-offs between forest dynamics, climate and wildfire. Despite the clear influence exerted by climate, forest management modulates fire behavior, resulting in different trends depending on the climatic pathway. In general, the maintenance of current practices would result in the highest rates of crown fire activity, while management for water vulnerability reduction is postulated as the best alternative to surmount the increasingly hazardous conditions envisaged in RCP 8.5.

Ratcheting of climate pledges needed to limit peak global warming

The new and updated emission reduction pledges submitted by countries ahead of COP26 represent a meaningful strengthening of global ambition compared to the 2015 Paris pledges1,2. Yet, limiting global warming below 1.5°C this century will require countries to ratchet ambition for 2030 and beyond2-6. We explore a suite of emissions pathways in which countries ratchet and achieve ambition through a combination of increasing near-term ambition through 2030, accelerating post-2030 decarbonization, and advancing the dates for national net-zero pledges. We show that ratcheting near-term ambition through 2030 will be crucial to limiting peak temperature changes. Delaying ratcheting ambition to beyond 2030 could still deliver end-of-century temperature change of less than 1.5°C, but that would result in higher temperature overshoot over many decades with the potential for adverse consequences. Ratcheting near-term ambition would also deliver benefits from enhanced non-CO2 mitigation and facilitate faster transitions to net-zero emissions systems in major economies.

Agroclimatic zoning for bananas under climate change in Brazil

BACKGROUND

Climate change is the main cause of biotic and abiotic stresses in plants and affects yield. Therefore, we sought to carry out a study on future changes in the agroclimatic conditions of banana cultivation in Brazil. The current agroclimatic zoning was carried out with data obtained from the National Institute of Meteorology related to mean air temperature, annual rainfall, and soil texture data in Brazil. The global climate model BCC-CSM1.1 (Beijing Climate Center-Climate System Model, version 1.1), adopted by the Intergovernmental Panel on Climate Change, corresponding to Representative Concentration Pathways (RCPs) 2.6, 4.5, 6.0, and 8.5 for the period 2050 (2041-2060) and 2070 (2061-2080), obtained through the CHELSA V1.2 platform, was chosen for the climate projections of the Coupled Model Intercomparison Project 5. Matrix images at a depth of 5-15 cm, obtained through the product of the SoilGrids system, were used for the texture data. ArcGIS version 10.8 was used to construct the maps.

RESULTS

Areas favorable to the crop plantation were classified as suitable when air temperature T_AIR was between 20 and 29 °C, annual rainfall R_ANNUAL between 1200 and 1900 mm, and soil clay content C_SOIL between 30 and 55%. Subsequently, the information was reclassified, summarizing the classes into preferential, recommended, little recommended, and not recommended. The current scenario shows a preferential class of 8.1%, recommended of 44.6%, little recommended of 47.1%, and not recommended of 0.1% for the Brazilian territory.

CONCLUSION

The results show no drastic changes in the total area regarding the classes, but there is a migration from these zones; that is, from tropical to subtropical and temperate regions. RCP 8.5-2070 (2061-2080) showed trends with negative impacts on arable areas for banana cultivation at the end of the century. © 2022 Society of Chemical Industry.

Predicting the distributional range shifts of Rhizocarpon geographicum (L.) DC. in Indian Himalayan Region under future climate scenarios

Himalaya, the highest mountain system in the world and house of important biodiversity hotspot, is sensitive to projected warming by climate change. Rhizocarpon geographicum (map lichen), a crustose lichen, grows in high mountain ranges, is a potential indicator species of climate change. In the present study, MaxEnt species distribution modeling algorithm was used to predict the suitable habitat for R. geographicum in current and future climate scenarios. Nineteen bioclimatic variables from WorldClim database, along with elevation, were used to predict the current distribution and three representative concentration pathway (RCP) scenarios by integrating three general circulation models (GCMs) for future distribution of species covering years 2050 and 2070. Furthermore, we performed change analysis to identify the precise difference between the current and future distribution of suitable areas of the species for delineating habitat range expansion (gain), habitat contraction (loss), and stable habitats. The final ensemble model obtained had average test value 0.968, and its predicted ~ 27.5% of the geographical area in the Indian Himalayan Region is presently climatically suitable for the species. The predicted highly suitable area for R. geographicum is observed to be declining in Northwestern Himalaya, and it is shifting towards the higher elevation areas of the Eastern Himalaya. The projected distribution in future under the RCP scenarios (RCP 4.5, 6.0, and 8.5) showed the range expansion towards higher elevations, and it is more pronounced for the extreme future scenarios (RCP 8.5) than for the moderate and intermediate climate scenarios (RCP 4.5 and RCP 6.0). However, assuming that species can migrate to previously unoccupied areas, the model forecasts a habitat loss of 10.86-16.51% for R. geographicum, which is expected due to increase in mean annual temperature by 1.5-3.7 °C. The predictive MaxEnt modeling approach for mapping lichen will contribute significantly to the understanding of the impact of climate change in Himalayan ecosystems with wide implications for drawing suitable conservation plans and to take adaptation and mitigation measures.

Research Progress on Preparation Methods of Skutterudites

Thermoelectric material is a new energy material that can realize the direct conversion of thermal energy and electric energy. It has important and wide applications in the fields of the recycling of industrial waste heat and automobile exhaust, efficient refrigeration of the next generation of integrated circuits and full spectrum solar power generation. Skutterudites have attracted much attention because of their excellent electrical trGiovanna Latronicoansport performance in the medium temperature region. In order to obtain skutterudites with excellent properties, it is indispensable to choose an appropriate preparation method. This review summarizes some traditional and advanced preparation methods of skutterudites in recent years. The basic principles of these preparation methods are briefly introduced. Single-phase skutterudites can be successfully obtained by these preparation methods. The study of these preparation methods also provides technical support for the rapid, low-cost and large-scale preparation of high-performance thermoelectric materials.

Managing for the unexpected: Building resilient forest landscapes to cope with global change

Natural disturbances exacerbated by novel climate regimes are increasing worldwide, threatening the ability of forest ecosystems to mitigate global warming through carbon sequestration and to provide other key ecosystem services. One way to cope with unknown disturbance events is to promote the ecological resilience of the forest by increasing both functional trait and structural diversity and by fostering functional connectivity of the landscape to ensure a rapid and efficient self-reorganization of the system. We investigated how expected and unexpected variations in climate and biotic disturbances affect ecological resilience and carbon storage in a forested region in southeastern Canada. Using a process-based forest landscape model (LANDIS-II), we simulated ecosystem responses to climate change and insect outbreaks under different forest policy scenarios-including a novel approach based on functional diversification and network analysis-and tested how the potentially most damaging insect pests interact with changes in forest composition and structure due to changing climate and management. We found that climate warming, lengthening the vegetation season, will increase forest productivity and carbon storage, but unexpected impacts of drought and insect outbreaks will drastically reduce such variables. Generalist, non-native insects feeding on hardwood are the most damaging biotic agents for our region, and their monitoring and early detection should be a priority for forest authorities. Higher forest diversity driven by climate-smart management and fostered by climate change that promotes warm-adapted species, might increase disturbance severity. However, alternative forest policy scenarios led to a higher functional and structural diversity as well as functional connectivity-and thus to higher ecological resilience-than conventional management. Our results demonstrate that adopting a landscape-scale perspective by planning interventions strategically in space and adopting a functional trait approach to diversify forests is promising for enhancing ecological resilience under unexpected global change stressors.

Climate predictors and climate change projections for avian haemosporidian prevalence in Mexico

Long-term, inter-annual and seasonal variation in temperature and precipitation influence the distribution and prevalence of intraerythrocytic haemosporidian parasites. We characterized the climatic niche behind the prevalence of the three main haemosporidian genera (Haemoproteus, Plasmodium and Leucocytozoon) in central-eastern Mexico, to understand their main climate drivers. Then, we projected the influence of climate change over prevalence distribution in the region. Using the MaxEnt modelling algorithm, we assessed the relative contribution of bioclimatic predictor variables to identify those most influential to haemosporidian prevalence in different avian communities within the region. Two contrasting climate change scenarios for 2070 were used to create distribution models to explain spatial turnover in prevalence caused by climate change. We assigned our study sites into polygonal operational climatic units (OCUs) and used the general haemosporidian prevalence for each OCU to indirectly measure environmental suitability for these parasites. A high statistical association between global prevalence and the bioclimatic variables ‘mean diurnal temperature range’ and ‘annual temperature range’ was found. Climate change projections for 2070 showed a significant modification of the current distribution of suitable climate areas for haemosporidians in the study region.

Impact of climate change on future precipitation amounts, seasonal distribution, and streamflow in the Omo-Gibe basin, Ethiopia

This study projected the impact of climate change on the amount of precipitation, seasonal distribution, and streamflow of the Omo-gibe basin, Ethiopia. Projections of climate change using the results of high-resolution multimodal ensembles from fifteen regional climate models (RCMs) of the Coordinated Regional Climate Reduction Experiment (CORDEX)-Africa were statistically downscaled and bias-adjusted using a quantile mapping approach. Precipitation and temperature were projected under RCP 8.5 and RCP 4.5 emission scenarios. Climate and streamflow projections from a mean ensemble of RCMs in the near future (2025–2050), medium future (2051–2075), and far future (2076–2100) were compared to the reference (1989–2019). Mann-Kendall (MK) trend testing was used to determine if a change is statistically significant and to detect trends in temperature, precipitation, and streamflow. The Soil and Water Assessment Tool (SWAT) hydrological model was used to project the impact of climate change on the streamflow. According to RCP4.5 and RCP8.5, the emission scenarios predicted significant positive (rising) temperature, but significant negative (decreasing) precipitation and streamflow. The average temperature projected increases range from 2.40-3.34 °C under the RCP 4.5 emission scenarios and 2.6–4.54 °C under the RCP 8.5 emission scenarios. Annual average precipitation projected decreases range between 10.77-13.11% under the RCP 4.5 emission scenario, while the RCP 8.5 emission scenarios decrease range between 11.10-13.86% in the rainy summer season (June–August) and the irregular rain season (March–May). Projected annual average streamflow decrease range between 7.08-10.99% under the RCP 4.5 emission scenarios and 10.98–12.88% under the RCP 8.5 emission scenarios. Results on projected temperature increases and reductions in precipitation and streamflow will help to develop effective adaptation measures to reduce the ongoing impacts of climate change and draw up long-term water resource management plans in the river basin. Both the results and the multidisciplinary approach will be vital to irrigation and hydropower project planners.

Visual Analysis of Global Carbon Mitigation Research Based on Scientific Knowledge Graphs

Global temperature change is related to the destiny of all mankind, and carbon mitigation, as well as greenhouse gases control, are key points. In order to explore the basic knowledge, research hotspots and trends in global carbon mitigation research, this paper, based on 15,304 carbon mitigation articles from Web of Science, from 1991 to 2021, conducts spatio-temporal distribution, country distribution, research hotspots and cooperation network analysis, and draws frontier knowledge graphs of carbon mitigation by using CiteSpace, Gephi and other scientific knowledge mapping and literature analysis software. The key scholars, important literature, main contribution institutions and countries/regions in the field of carbon mitigation research were extracted, and the research basis and evolution law were displayed. The study found that: (1) The research on carbon mitigation is increasing every year, which can be roughly divided into four stages: germination, low-speed development, medium-speed development and high-speed development. (2) The spatial distribution of carbon mitigation research is unbalanced, mainly showing a characteristic of "one super and many strong" centered on the United States. (3) The research hotspots of carbon mitigation have gradually evolved from phenomenon analysis, policy guidance, method exploration to mechanism improvement. Further research might focus on ocean carbon sink, carbon trading and carbon-negative technology.

Choices in land representation materially affect modeled biofuel carbon intensity estimates

Estimates of biofuel carbon intensity are uncertain and depend on modeled land use change (LUC) emissions. While analysts have focused on economic and agronomic assumptions affecting the quantity of land converted, researchers have paid less attention to how models classify land into broad categories and designate some categories as ineligible for LUC. To explore the effect of these land representation attributes, we use three versions of a global human and Earth systems model, GCAM, and compute the "carbon intensity of land-use change" (CI-LUC) from increased U.S. corn ethanol production. We consider uncertainty in model parameters along with the choice of land representation and find the latter is one of the most influential parameters on estimated CI-LUC. A version of the model that protects 90% of non-commercial land reduced estimated CI-LUC by an average of 32% across Monte Carlo trials compared to our baseline model. Another version that mimics the GTAP-BIO-ADV land representation, which protects all non-commercial land, reduced CI-LUC by an average of 19%. The results of this experiment demonstrate that land representation in biofuel LUC models is an important determinant of CI-LUC.

Implication of imposing fertilizer limitations on energy, agriculture, and land systems

Since the 1950's, global fertilizer usage has increased by more than 800% resulting in detrimental impacts to the environment. The projected increase in crop production due to increasing demands for food, feed, biofuel, and other uses, may further increase fertilizer usage. Studies have examined achieving agricultural intensification in environmentally sustainable ways, however, they have not focused on the whole-system economic aspects of changes in fertilizer usage over the long term. We utilize the Global Change Analysis Model (GCAM) to explore the impact of reducing global fertilizer usage on land use change, agricultural commodity price and production, energy production, and greenhouse gas emissions. We find that constrained fertilizer availability results in reduced global cropland area, particularly land used for bioenergy production, and expanded forested area. These results are driven by price impacts which lead to shifts in agricultural production between commodity types, regions, and technologies, and which lead to decreased agricultural commodity demands.

Land-based climate change mitigation measures can affect agricultural markets and food security

Earlier studies have noted potential adverse impacts of land-related emissions mitigation strategies on food security, particularly due to food price increases-but without distinguishing these strategies' individual effects under different conditions. Using six global agroeconomic models, we show the extent to which three factors-non-CO2 emissions reduction, bioenergy production and afforestation-may change food security and agricultural market conditions under 2 °C climate-stabilization scenarios. Results show that afforestation (often simulated in the models by imposing carbon prices on land carbon stocks) could have a large impact on food security relative to non-CO2 emissions policies (generally implemented as emissions taxes). Respectively, these measures put an additional 41.9 million and 26.7 million people at risk of hunger in 2050 compared with the current trend scenario baseline. This highlights the need for better coordination in emissions reduction and agricultural market management policies as well as better representation of land use and associated greenhouse gas emissions in modelling.

Europe's Climate Target for 2050: An Assessment

Decarbonisation is harder for transport, heating, industry and agriculture. That is, a doubling of the decarbonisation rate requires much more than a doubling of the policy effort. The low-hanging fruit has been picked.

Modifications on Promoting the Proton Conductivity of Polybenzimidazole-Based Polymer Electrolyte Membranes in Fuel Cells

Hydrogen-air proton exchange membrane fuel cells (PEMFCs) and direct methanol fuel cells (DMFCs) are excellent fuel cells with high limits of energy density. However, the low carbon monoxide (CO) tolerance of the Pt electrode catalyst in hydrogen-air PEMFCs and methanol permanent in DMFCs greatly hindered their extensive use. Applying polybenzimidazole (PBI) membranes can avoid these problems. The high thermal stability allows PBI membranes to work at elevated temperatures when the CO tolerance can be significantly improved; the excellent methanol resistance also makes it suitable for DMFCs. However, the poor proton conductivity of pristine PBI makes it hard to be directly applied in fuel cells. In the past decades, researchers have made great efforts to promote the proton conductivity of PBI membranes, and various effective modification methods have been proposed. To provide engineers and researchers with a basis to further promote the properties of fuel cells with PBI membranes, this paper reviews critical researches on the modification of PBI membranes in both hydrogen-air PEMFCs and DMFCs aiming at promoting the proton conductivity. The modification methods have been classified and the obtained properties have been included. A guide for designing modifications on PBI membranes for high-performance fuel cells is provided.

A mixed-effect model approach for assessing land-based mitigation in integrated assessment models: A regional perspective

Given the prospects of low short-term emissions reduction, carbon removals (CDRs) are expected to play an important role in achieving ambitious mitigation targets in future scenarios of integrated assessment models (IAMs), particularly Bioenergy with Carbon Capture and Storage (BECCS). In this paper, we explore the IAMC 1.5℃ database to depict the characteristics of the two main CDR options present in mitigation scenarios: BECCS and afforestation/reforestation. We apply a linear mixed-effect model to capture the specific regional and cross-IAM effects. Results reveal that the distribution of BECCS and afforestation deployment differs across IAMs and regions and, to a second extent, time. BECCS is preferred in the scenarios not for its ability to expand energy use but actually because it appears as an alternative to afforestation, which is associated with a decrease in energy use. However, the regional distribution of CDR deployment does not show a common pattern across scenarios and IAMs. Therefore, a more comprehensive investigation is needed before it can support policy proposals.

Increasingly expanded future risk of dengue fever in the Pearl River Delta, China

BACKGROUND

In recent years, frequent outbreaks of dengue fever (DF) have become an increasingly serious public health issue in China, especially in the Pearl River Delta (PRD) with fast socioeconomic developments. Previous studies mainly focused on the historic DF epidemics, their influencing factors, and the prediction of DF risks. However, the future risks of this disease under both different socioeconomic development and representative concentration pathways (RCPs) scenarios remain little understood.

METHODOLOGY AND PRINCIPAL FINDINGS

In this study, a spatial dataset of gross domestic product (GDP), population density, and land use and land coverage (LULC) in 2050 and 2070 was obtained by simulation based on the different shared socioeconomic pathways (SSPs), and the future climatic data derived from the RCP scenarios were integrated into the Maxent models for predicting the future DF risk in the PRD region. Among all the variables included in this study, socioeconomics factors made the dominant contribution (83% or so) during simulating the current spatial distribution of the DF epidemics in the PRD region. Moreover, the spatial distribution of future DF risk identified by the climatic and socioeconomic (C&S) variables models was more detailed than that of the climatic variables models. Along with global warming and socioeconomic development, the zones with DF high and moderate risk will continue to increase, and the population at high and moderate risk will reach a maximum of 48.47 million (i.e., 63.78% of the whole PRD) under the RCP 4.5/SSP2 in 2070.

CONCLUSIONS

The increasing DF risk may be an inevitable public health threat in the PRD region with rapid socioeconomic developments and global warming in the future. Our results suggest that curbs in emissions and more sustainable socioeconomic growth targets offer hope for limiting the future impact of dengue, and effective prevention and control need to continue to be strengthened at the junction of Guangzhou-Foshan, north-central Zhongshan city, and central-western Dongguan city. Our study provides useful clues for relevant hygienic authorities making targeted adapting strategies for this disease.

Short-term effects of land consolidation of dryland-to-paddy conversion on soil CO2 flux

To improve grain production capacity, many areas in the world are shifting from rainfed agriculture to irrigated agriculture. One example of such land consolidation is dryland-to-paddy conversion. The conversion of land use pattern largely affects the stability of farmland soil, especially the soil carbon cycle. However, the mutual feedback mechanisms between carbon flux variation and environmental factors during the farmland consolidation process are still poorly known. Located in the Huang-Huai-Hai Plain China, Xuzhou is a typical area where dryland-to-paddy conversion are most widely distributed. Therefore, in this study, we have carried out dryland-to-paddy conversion by setting up two isolated rectangular fields one group planting corn in dryland (DL) and another group planting in paddy field (PF) in Xuzhou. Here, we determined the effect of dryland-to-paddy consolidation on soil CO₂ flux in two isolated rectangular fields - the dryland (DL) cultivated with corn and the paddy field (PF) cultivated with rice. Our results showed that the soil carbon flux and temperature followed similar unimodal curves with greater soil CO₂ flux of in PF than in DL. Surprisingly, the land conversion significantly reduced soil microbial biomass carbon and easily oxidized organic carbon by 28.55% and 29.09%, respectively. The structural equation modeling results demonstrated that the changes in soil environmental factors, including temperature, and fungal OTU numbers, were the primary drivers for the soil CO₂ flux and soil carbon pool (P < 0.05). Overall, this study improves the understanding of the ecological impact of dryland-to-paddy conversion, providing insights into low-carbon agriculture and climate mitigation.

Climate Change Projections of Dry and Wet Events in Iberia Based on the WASP-Index

The Weighted Anomaly of Standardized Precipitation Index (WASP-Index) was computed over Iberia for three monthly timescales (3-month, 6-month and 12-month) in 1961–2020, based on an observational gridded precipitation dataset (E-OBS), and between 2021 and 2070, based on bias-corrected precipitation generated by a six-member climate model ensemble from EURO-CORDEX, under two Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5. The area-mean values revealed an upward trend in the frequency of occurrence of intermediate-to-severe dry events over Iberia, which will be strengthened in the future, particularly for the 12-month WASP (12m-WASP) intermediate dry events under RCP8.5. Besides, the number of 3-month WASP (3m-WASP) intermediate-to-severe wet events is projected to increase (mostly the severest events under RCP4.5) but no evidence was found for an increase in the number of more persistent 12m-WASP wet events under both RCPs. Despite important spatial heterogeneities, an increase/decrease of the intensity, duration and frequency of occurrence of the 12m-WASP intermediate-to-severe dry/wet events was found under both scenarios, mainly in the southernmost regions of Iberia (mainly Comunidad Valenciana, Región de Murcia, Andalucía in Spain, Alentejo, and Algarve in Portugal), thus becoming more exposed to prolonged and severe droughts in the future. This finding corroborates the results of previous studies.

Heating and Cooling Degree-Days Climate Change Projections for Portugal

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating (HDD) and cooling (CDD) degree-days along with HDD + CDD were computed from an ensemble of seven high-resolution bias-corrected simulations attained from EURO-CORDEX under two Representative Concentration Pathways (RCP4.5 and RCP8.5). These three indicators were analyzed for 1971–2000 (from E-OBS) and 2011–2040, and 2041–2070, under both RCPs. Results predict a decrease in HDDs most significant under RCP8.5. Conversely, it is projected an increase of CDD values for both scenarios. The decrease in HDDs is projected to be higher than the increase in CDDs hinting to an increase in the energy demand to cool internal environments in Portugal. Statistically significant linear CDD trends were only found for 2041–2070 under RCP4.5. Towards 2070, higher(lower) CDD (HDD and HDD + CDD) anomaly amplitudes are depicted, mainly under RCP8.5. Within the five NUTS II regions projections revealed for 2041–2070 a decrease in heating requirements for Algarve and Lisbon Area higher in Faro, Lisboa and Setúbal whereas for North and Center regions results predicts an increase in cooling energy demand mainly in Bragança, Vila Real, Braga, Viana do Castelo, Porto and Guarda, higher under RCP8.5.

Impact of climate change on wetland ecosystems: A critical review of experimental wetlands

Climate change is identified as a major threat to wetlands. Altered hydrology and rising temperature can change the biogeochemistry and function of a wetland to the degree that some important services might be turned into disservices. This means that they will, for example, no longer provide a water purification service and adversely they may start to decompose and release nutrients to the surface water. Moreover, a higher rate of decomposition than primary production (photosynthesis) may lead to a shift of their function from being a sink of carbon to a source. This review paper assesses the potential response of natural wetlands (peatlands) and constructed wetlands to climate change in terms of gas emission and nutrients release. In addition, the impact of key climatic factors such as temperature and water availability on wetlands has been reviewed. The authors identified the methodological gaps and weaknesses in the literature and then introduced a new framework for conducting a comprehensive mesocosm experiment to address the existing gaps in literature to support future climate change research on wetland ecosystems. In the future, higher temperatures resulting in drought might shift the role of both constructed wetland and peatland from a sink to a source of carbon. However, higher temperatures accompanied by more precipitation can promote photosynthesis to a degree that might exceed the respiration and maintain the carbon sink role of the wetland. There might be a critical water level at which the wetland can preserve most of its services. In order to find that level, a study of the key factors of climate change and their interactions using an appropriate experimental method is necessary. Some contradictory results of past experiments can be associated with different methodologies, designs, time periods, climates, and natural variability. Hence a long-term simulation of climate change for wetlands according to the proposed framework is recommended. This framework provides relatively more accurate and realistic simulations, valid comparative results, comprehensive understanding and supports coordination between researchers. This can help to find a sustainable management strategy for wetlands to be resilient to climate change.

A coupled human-natural system analysis of freshwater security under climate and population change

Jordan is facing an unfolding water crisis, exacerbated by climate change and conflict-induced refugee influxes. We present a freshwater security analysis for the country, enabled by an integrated systems model that combines simulation of Jordan’s natural and built water environment with thousands of representative human agents determining water allocation and use decisions. Our analysis points to severe, potentially destabilizing, declines in Jordan’s freshwater security. Without intervening measures, over 90% of Jordan’s low-income population will be experiencing critical water insecurity by the end of the century. To gain a foothold on its water future, Jordan must enact an ambitious portfolio of interventions that span supply- and demand-side measures, including large-scale desalinization and comprehensive water-sector reform.

Limited water availability, population growth, and climate change have resulted in freshwater crises in many countries. Jordan’s situation is emblematic, compounded by conflict-induced population shocks. Integrating knowledge across hydrology, climatology, agriculture, political science, geography, and economics, we present the Jordan Water Model, a nationwide coupled human–natural-engineered systems model that is used to evaluate Jordan’s freshwater security under climate and socioeconomic changes. The complex systems model simulates the trajectory of Jordan’s water system, representing dynamic interactions between a hierarchy of actors and the natural and engineered water environment. A multiagent modeling approach enables the quantification of impacts at the level of thousands of representative agents across sectors, allowing for the evaluation of both systemwide and distributional outcomes translated into a suite of water-security metrics (vulnerability, equity, shortage duration, and economic well-being). Model results indicate severe, potentially destabilizing, declines in freshwater security. Per capita water availability decreases by approximately 50% by the end of the century. Without intervening measures, >90% of the low-income household population experiences critical insecurity by the end of the century, receiving <40 L per capita per day. Widening disparity in freshwater use, lengthening shortage durations, and declining economic welfare are prevalent across narratives. To gain a foothold on its freshwater future, Jordan must enact a sweeping portfolio of ambitious interventions that include large-scale desalinization and comprehensive water sector reform, with model results revealing exponential improvements in water security through the coordination of supply- and demand-side measures.

Precipitation and temperature response to sea salt injection into low marine clouds over West Africa

Sea salt injection into the tropical marine clouds is evaluated for its potentials to reduce the negative impact of the prevailing global warming over West Africa. Radiative forcing is determined as the intercept of the regression of response of radiation parameter to that of surface air temperature. The seasonal responses of temperature and precipitation to geoengineering over West Africa are analysed using temperature and precipitation outputs from IPSL-M5A-LR with three different forcing scenarios. The three scenarios are historical greenhouse gas concentrations, Representative Concentration Pathway 4.5 W/m2 scenario (RCP4.5) and combination of RCP4.5 and geoengineering forcing (sea salt climate engineering, G5). 20-year means in the middle of G5 (2045–2064) are considered for the future period, and the historical climatology from 1986 to 2005 is used. Net downward flux and top of atmosphere outgoing shortwave radiation have negative forcing only at the western Sahel. The G5 reduces the warming in the RCP4.5 scenario over the whole of West Africa. It also shifts ITCZ northward with respect to RCP4.5, thereby increasing wetness over most of the land areas. The areas with wetness response have anomalous westerly with respect to RCP 4.5 and latitudinal location below anomalous easterly wind. Results show that G5 is effective in reducing the RCP4.5 projected warming up to 1.2 K and increasing wetness over most land areas. The G5 has a damaging effect on the temperature pattern at the southern ocean and coastal areas, while it has damaging effect on precipitation patterns at some parts of the Sahel.

The potential land requirements and related land use change emissions of solar energy

Although the transition to renewable energies will intensify the global competition for land, the potential impacts driven by solar energy remain unexplored. In this work, the potential solar land requirements and related land use change emissions are computed for the EU, India, Japan and South Korea. A novel method is developed within an integrated assessment model which links socioeconomic, energy, land and climate systems. At 25-80% penetration in the electricity mix of those regions by 2050, we find that solar energy may occupy 0.5-5% of total land. The resulting land cover changes, including indirect effects, will likely cause a net release of carbon ranging from 0 to 50 gCO₂/kWh, depending on the region, scale of expansion, solar technology efficiency and land management practices in solar parks. Hence, a coordinated planning and regulation of new solar energy infrastructures should be enforced to avoid a significant increase in their life cycle emissions through terrestrial carbon losses.

Global emissions of NH3, NOx, and N2O from biomass burning and the impact of climate change

Emissions of ammonia (NH₃), oxides of nitrogen (NO_x; NO +NO₂), and nitrous oxide (N₂O) from biomass burning were quantified on a global scale for 2001 to 2015. On average biomass burning emissions at a global scale over the period were as follows: 4.53 ± 0.51 Tg NH₃ year^-1, 14.65 ± 1.60 Tg NO_x year^-1, and 0.97 ± 0.11 Tg N₂O year^-1. Emissions were comparable to other emissions databases. Statistical regression models were developed to project NH₃, NO_x, and N₂O emissions from biomass burning as a function of burn area. Two future climate scenarios (RCP 4.5 and RCP 8.5) were analyzed for 2050-2055 ("mid-century") and 2090-2095 ("end of century"). Under the assumptions made in this study, the results indicate emissions of all species are projected to increase under both the RCP 4.5 and RCP 8.5 climate scenarios. Implications: This manuscript quantifies emissions of NH₃, NO_x, and N₂O on a global scale from biomass burning from 2001-2015 then creates regression models to predict emissions based on climate change. Because reactive nitrogen emissions have such an important role in the global nitrogen cycle, changes in these emissions could lead to a number of health and environmental impacts.

Evaluation of the Impact of Climate Change on Runoff Generation in an Andean Glacier Watershed

Excluding Antarctica and Greenland, 3.8% of the world’s glacier area is concentrated in Chile. The country has been strongly affected by the mega drought, which affects the south-central area and has produced an increase in dependence on water resources from snow and glacier melting in dry periods. Recent climate change has led to an elevation of the zero-degree isotherm, a decrease in solid-state precipitation amounts and an accelerated loss of glacier and snow storage in the Chilean Andes. This situation calls for a better understanding of future water discharge in Andean headwater catchments in order to improve water resources management in glacier-fed populated areas. The present study uses hydrological modeling to characterize the hydrological processes occurring in a glacio-nival watershed of the central Andes and to examine the impact of different climate change scenarios on discharge. The study site is the upper sub-watershed of the Tinguiririca River (area: 141 km2), of which nearly 20% is covered by Universidad Glacier. The semi-distributed Snowmelt Runoff Model + Glacier (SRM+G) was forced with local meteorological data to simulate catchment runoff. The model was calibrated on even years and validated on odd years during the 2008–2014 period and found to correctly reproduce daily runoff. The model was then forced with downscaled ensemble projected precipitation and temperature series under the RCP 4.5 and RCP 8.5 scenarios, and the glacier adjusted using a volume-area scaling relationship. The results obtained for 2050 indicate a decrease in mean annual discharge (MAD) of 18.1% for the lowest emission scenario and 43.3% for the most pessimistic emission scenario, while for 2100 the MAD decreases by 31.4 and 54.2%, respectively, for each emission scenario. Results show that decreasing precipitation lead to reduced rainfall and snowmelt contributions to discharge. Glacier melt thus partly buffers the drying climate trend, but our results show that the peak water occurs near 2040, after which glacier depletion leads to reducing discharge, threatening the long-term water resource availability in this region.

Modeling impacts of future climate change on reservoir storages and irrigation water demands in a Mediterranean basin

Water storage requirements in the Mediterranean region vary in time and are strongly affected by the local geography and climate conditions. The objective of this study is to assess the implications of climate change on the water balance of an agricultural reservoir in a Mediterranean-climate basin in Turkey throughout the 21st century. A monthly dynamic water balance model is developed to simulate the historical and future water availability in the reservoir. The model is driven by the fine-resolution dynamically downscaled climate data from four GCMs from the CMIP5 archive, namely CCSM4, GFDL-ESM2M, HadGEM2-ES, and MIROC5, under two different representative concentration pathway scenarios (RCP4.5 and RCP8.5), and the hydrologic data projected under the same scenarios. The reservoir outflows, including the reservoir evaporation and downstream irrigation water demands, are also modeled using the projected climate variables. The net irrigation water requirement of the crops in the irrigation system, seasonal evapotranspiration rates, and reservoir evaporation rates are estimated based on the Penman-Monteith Evapotranspiration method (FAO-56 Method). The study investigates whether the future water supply in the reservoir will be sufficient to meet the future irrigation water demands for the years from 2017 to 2100. The results show that under all eight modeled climate change projections, statistically significant increasing trends for the annual irrigation water demands are expected throughout the 21st century. Moreover, higher evapotranspiration rates are predicted under the ensemble average of the RCP8.5 projections, compared to those of the RCP4.5 projections. Ultimately, seven out of eight projections projected insufficient reservoir water levels during the 21st century, especially during the irrigation seasons when higher water demands are expected. These impacts indicate the importance of sustainable water resources management in the region to provide irrigation water from reservoirs, and to sustain agricultural productivity under projected water limitations due to climate change.

Predicting the Water Requirement for Rice Production as Affected by Projected Climate Change in Bihar, India

Climate change is a well-known phenomenon all over the globe. The influence of projected climate change on agricultural production, either positive or negative, can be assessed for various locations. The present study was conducted to investigate the impact of projected climate change on rice’s production, water demand and phenology for the state of Bihar, India. Furthermore, this study assessed the irrigation water requirement to increase the rice production by 60%, for the existing current climate scenario and all the four IPCC climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) by the 2050s (2050–2059). Various management practices were used as adaptation methods to analyze the requirement of irrigation water for a 60% increase in rice production. The climate data obtained from the four General Circulation Models (GCMs) (bcc_csm1.1, csiro_mk3_6_0, ipsl_cm5a_mr and miroc_miroc5) were used in the crop growth model, with the Decision Support System for Agrotechnology Transfer (DSSAT) used to simulate the rice yield, phenological days and water demand under all four climate change scenarios. The results obtained from the CERES-Rice model in the DSSAT, corresponding to all four GCMs, were ensembled together to obtain the overall change in yield, phenology and water demand for 10 years of interval from 2020 to 2059. We investigated several strategies: increasing the rice’s yield by 60% with current agronomic practice; increasing the yield by 60% with conservation agricultural practice; and increasing the rice yield by 30% with current agronomic practice as well as with conservation agricultural practices (assuming that the other 30% increase in yield would be achieved by reducing post-harvest losses by 30%). The average increase in precipitation between 2020 and 2059 was observed to be 5.23%, 13.96%, 9.30% and 9.29%, respectively, for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5. The decrease in yield during the 2050s, from the baseline period (1980–2004), was observed to be 2.94%, 3.87%, 4.02% and 5.84% for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5, respectively. The irrigation requirement was predicted to increase by a range of 39% to 45% for a 60% increase in yield using the current agronomic practice in current climate scenario and by 2050s with all the four climate change scenarios from the baseline period (1980–2004). We found that if we combine both conservation agriculture and removal of 30% of the post-harvest losses, the irrigation requirement would be reduced by 26% (45 to 19%), 20% (44 to 24%), 21% (43 to 22%), 22% (39 to 17%) and 20% (41 to 21%) with current climate scenario, RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 conditions, respectively. This combination of conservation practices suggests that the irrigation water requirement can be reduced by a large percentage, even if we produce 60% more food under the projected climate change conditions.

Synergistic effects of nitrogen and CO2 enrichment on alpine grassland biomass and community structure

Global environmental change is altering the Earth's ecosystems. However, much research has focused on ecosystem-level responses, and we know substantially less about community-level responses to global change stressors. Here we conducted a 6-yr field experiment in a high-altitude (4600 m asl) alpine grassland on the Tibetan Plateau to explore the effects of nitrogen (N) addition and rising atmospheric CO₂ concentration on plant communities. Our results showed that N and CO₂ enrichment had synergistic effects on alpine grassland communities. Adding nitrogen or CO₂ alone did not alter total community biomass, species diversity or community composition, whereas adding both resources together increased community biomass, reduced species diversity and altered community composition. The observed decline in species diversity under simultaneous N and CO₂ enrichment was associated with greater community biomass and lower soil water content, and driven by the loss of species characterised simultaneously by tall stature and small specific leaf area. Our findings point to the co-limitation of alpine plant community biomass and structure by nitrogen and CO₂ , emphasising the need for future studies to consider multiple aspects of global environmental change together to gain a more complete understanding of their ecological consequences.

Observed and projected changes in the climate based decay hazard of timber in the United Kingdom

Current climate projections suggest that the UK will experience warmer and wetter winters and warmer and dryer summers. This change in the climate could affect the incidence or severity of microbiological attack on exposed timber and have significant impact on buildings and construction. One method of assessing the geographical climate based hazard is to use the Scheffer Climate index, which relates temperature and rain variables. There was a considerable increase in the Scheffer climate indices for various locations of the UK from 1990 to 2019. The highest index values are seen in the Northern and western areas of the United Kingdom, but increases are seen across the country. The paper also uses representative concentration pathway (RCP) scenarios to project future climate decay indices for the United Kingdom until the end of the twenty-first century. The projections show an increase in the Scheffer index even in the lowest RCP scenario, with indices in all regions of the UK increasing to indicate very high hazard of decay. The major implication is that to ensure serviceability of wood and wooden structures exposed to the environment the use of good design, durable woods and properly treated or modified woods will be paramount.

Susceptibility of Water Resources and Hydropower Production to Climate Change in the Tropics: The Case of Lake Malawi and Shire River Basins, SE Africa

The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021–2050 and 2071–2100 are used. An annual temperature increase of 1 °C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi’s water budget. Meanwhile, a +5% (−5%) deviation in annual rainfall changes mean lake level by +0.7 m (−0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 °C (3.5 °C) and −20% (−15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021–2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071–2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced.

Evaluating Water Balance Variables under Land Use and Climate Projections in the Upper Choctawhatchee River Watershed, in Southeast US

Changes in water balance variables are essential in planning and management. Two major factors affecting these variables are climate change and land use change. Few researches have been done to investigate the combined effect of the land use change and climate change using projections. In this study the hydrological processes in Upper Choctawhatchee River Watershed were modeled using the Soil and Water Assessment Tool (SWAT) to investigate the impacts of climate and land use change. We integrated land use projection based in the Shared Socioeconomic Pathways with future climate data to study the combined effects on Hydrological response of the watershed. Future rainfall and temperature, for two time periods, were obtained using General Climate Models to provide SWAT with the climatic forcing in order to project water balance variables. The simulation was carried out under two radiative forcing pathways of RCP4.5 and RCP6.0. Land use change focused on urbanization dominated the climate changes. Impacts on water balance variables differed seasonally. Results showed surface runoff experienced major changes under both emissions scenarios in some months up to 5 times increase. Among the water balance variables, evapotranspiration (ET) as the least dominant pathway for water loss showed the modest changes with the largest decrease during fall and summer. Projection indicated more frequent extreme behavior regarding water balance during midcentury. Discharge was estimated to increase through the year and the highest changes were projected during summer and fall with 186.3% increase in November under RCP6.0. Relying on rainfall for farming along with reduced agricultural landuse (11.8%) and increased urban area (47%) and population growth would likely make the water use efficiency critical. The model demonstrated satisfactory performance, capturing the hydrologic parameters. It thus can be used for further modelling of water quality to determine the sustainable conservation practices and extreme weather events such as hurricane and tropical storms.