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• We firstly applied the high forest thematic resolution land use to assess species distribution; • Firmiana danxiaensis was selected, as it is a rare tree species that is endemic to China; • Both future climate and land use change data are projections for the SSPs scenarios. The distribution of species is mostly influenced by climate synergistic effects and land use. The prediction of endangered species is dependent on fine-scale environmental features, especially in forests. The capture of fine-scale suitable habitats is bounded by low spatial resolution and coarse categorization. In this study, we improved the land use information and forest spatial detail through high forest thematic resolution land use data. To understand the relative influence of environmental factors, suitable habitat models for Chinese endangered tree species (Firmiana danxiaensis) under three climate and high forest thematic resolution land use conditions was constructed. We also assess F. danxiaensis 's response to climate and land use, and differential performance in land use on the suitable habitat. The area of suitable habitat for F. danxiaensis grows slowly under the SSP1-2.6 (shared social pathway scenario) scenario, decreases by 21.33% from the present to 2090 under the SSP2-4.5 scenario, and expands significantly under the SSP5-8.5 scenario. We conclude that high forest thematic resolution land use is beneficial in capturing species' requirements for specific habitats and especially necessary in predicting endangered species. At the same time, the distribution of suitable habitats for species is primarily driven by climate, and limited their development by land use. The study shows that the synthetic effects of climate and land use change on F. danxiaensis are positive, with a marked trend toward the northeast. As a consequence, some endangered species are able to benefit from future SSPs scenarios, in particular they respond more strongly to the SSP5-8.5 scenario than to the other scenarios. Assessing the role of changes in the climate and high forest thematic resolution land use on F. danxiaensis will help promote sustainable land use management and contribute to the conservation policy for Chinese endangered species. [ABSTRACT FROM AUTHOR]

[Display omitted] • Dust sources of central playas will increase under SSP1-2.6 and SSP5-8.5 scenarios. • The uncertainty of dust source prediction is minimized using an ensemble approach. • The Partial ROC criterion is suggested for analyzing algorithm performance. • Dirt roads were the most important controlling factor of dust emission. Monitoring and controlling dust sources under climate changes and developing suitable prediction approaches is very important, since they have direct impacts on the environment and human health. The current study was performed with the aim of predicting the dust emission of Yazd province, located in the central playas of Iran, by combining a machine learning ensemble model and the global climate model IPSL-CM6A-LR. The key variables of dust emission including physiographic characteristics, climatic variables and human factors were mapped in order to model occurrence data against background data. After removing 15 autocorrelated points, from 120 pixels located in dust sources, 75 % and 25 % of them were randomly selected as training and test datasets, respectively. To evaluate modeling, in addition to sensitivity, specificity, TSS and Kappa indices, the Partial ROC approach was used. For the final mapping of land susceptibility to dust emission, individual models based on the weighted average of AUC ratio values were used to create the ensemble model. The relative importance of dust emission controlling factors was obtained with the consensus of seven machine learning models: distance to dirt roads, altitude, distance to mines and mean temperature of driest quarter. MARS outperformed the other individual models, so that it showed no significant difference with the ensemble model at the thresholds of E = 10 and E = 5 (p-value < 0.05). Statistical analysis of the ensemble model with AUC ratio equal to 1.933 showed that currently 28.56 percent of the province, is prone to dust emission and it will increase linearly in the future for scenarios SSP1-2.6 and SSP5-8.5. In both time periods (2041–2070 and 2071–2100), dust emissions will be higher under the SSP5-8.5 scenario compared to the SSP1-2.6 scenario. The results can be used by policymakers for the sustainable management of deserts and thus reduce the impacts of dust on current and future ecosystem health. [ABSTRACT FROM AUTHOR]

The global climate has significantly changed primarily due to human-induced activities. The incidences of droughts and extreme floods followed by destruction have been appearing across the globe along with extensive effects on economic and public health sectors, including the human lives losses whereby, Africa is among the greatly affected regions. Several studies aver that weather-related extremes are likely to increase due to the rising impacts. This article aims to emerge the effects of a warning climate on temperature and precipitation patterns in African tropical regions for pre-emptive adaptation practices. It was conducted using nonparametric Mann-Kendall's test and Sen's slope estimator coupled with the downscaled global climate models (NEX-GDDP-CMIP6 GCMs). The study shows that the annual precipitation in Lusaka keeps decreasing though the rainfall season showed an increasing possibility. The projection under ssp245 showed a slight rainfall decrement but increased by the mid-century under ssp585. Besides, the rainfall in Kigali, presents an excess increment resulting in increased extreme events. The projection showed up to 40% annual rainfall increment by the end-century under ssp585. However, both the regions present a slight trend increment in maximum and minimum temperature. Henceforth, the results of this study may prove useful in climate change mitigation and adaptation practices on rainfed agriculture, hydroelectricity, water supply systems, and resilient hydraulic infrastructure provision in the region. • Climate variability and projection under ssp245 and ssp585 scenarios in Africa tropical urban region. • Mann-Kendall's and Sen's slope estimator test coupled with downscaled and bias corrected NEX-GDDP-CMIP6 GCM ensemble. • The climate in Lusaka, Zambia might experience increased dry days within the dry season. • The climate in Kigali, Rwanda, presents an excess precipitation increment which might result in increased extreme events. [ABSTRACT FROM AUTHOR]

Asia is recognized as one of the most vulnerable regions. This research aims to identify climate change effects on economic growth. It proposes a new and comprehensive perspective to examine the climate-economy nexus in this region and provides an underpinning for assessing the pathway of the growing Asian economy under the SSP climate scenario (CMIP6). We apply a macroeconomic-climate modeling approach with a climate damage function. The damage function, which is based on the temperature anomaly, was examined under three classes of damage severity. The climate change effect has been examined by including the direct effect on the output as the level effect and two more channels, including capital depreciation and productivity growth reduction. The augmented Solow growth model framework that considers different types of capital, including physical, human, social, and environmental capital, was applied. The labor productivity or technology is assumed to depend on trade-related variables, including trade openness, financial development, and foreign aid inflows. Also, in order to test the constant returns to scale assumption, the CES production function, which is the flexible production technology, was used. The study relied on the country-year panel of GDP per capita and other macroeconomic variables such as labor force, capital formation, financial development index, trade openness, and foreign aid gleaned for 1994–2017 to estimate production functions using the GMM estimation method. The climate data on the annual mean temperature and projections of future temperature are based on ICMP6 by 2100 for Asian countries. Based on the CES estimation results, constant returns to scale or Cobb-Douglas production function was adopted. The estimation results show that physical and environmental capital account for the highest contribution to the output per worker. However, the contribution of trade-related variables was found to be insignificant. The projected pathway by 2100 establishes that climate change would significantly reduce Asian output per worker, especially if severe damage function is examined, and climate change stays on the SSP scenario-anticipated trajectory. The output elasticity with respect to temperature under the most severe scenario was obtained −22.80, corresponding to the output per worker reduction of 46.7 percent in 2100. Among the three channels of the climate effect, productivity growth reduction showed the most adverse effect on output. The lower flexibility of the production function that restricts the environmental replacement with other inputs, may lead to a more binding role under growing scarcity conditions. It was also found that labor and technology could contribute dampening the capital damage induced by higher temperatures. From the research results, the findings suggest measures aiming at providing flexible production technology, development of capital-embodied technologies, and lower dependence on environmental capital. [ABSTRACT FROM AUTHOR]

A forward-looking approach that incorporates biodiversity and nature-based solutions is needed for climate change adaptation. In this research, we identified conservation priorities in 2050 for Southwest China (SWC) based on habitat suitability, climate stability, and carbon storage capacity and presented the results for 12 SSP-GCMs combinations. Our findings indicate that the mean temperature of the SWC may increase significantly, with the largest predicted rise being of 2.78 °C and the smallest being 1.36 °C. The carbon storage capacity of terrestrial ecosystems in 89.03 % of the SWC's protected areas (PAs) is forecast to increase by 2050. Among the 237 PAs, habitat suitability is expected to increase in 158 PAs. The climate change intensity in all PAs is expected to remain at a rate of the weakest 15 % in the entire SWC. Based on our research, areas with high habitat suitability, climate stability, and carbon storage capacity at the same time in 2050 would cover 23.80 % of the SWC, with an area of about 550,000 km2. The representation of the SWC's existing PAs network reveals that the PAs' overlap with conservation hotspots is only 13.71 %, with just 12.69 % of these hotspots being adequately protected. Thus we propose a stepwise post-2020 conservation plan for the SWC from now through to the mid-point of the century. By 2030, 25 % of the SWC is expected to be protected, with the target increasing to 33 % and 43 % by 2040 and 2050, respectively. To achieve these goals, significant efforts are required like developing a dynamic future planning mechanisms. • A nature-based climate adaptation conservation plan is needed for biodiversity. • The SWC's mean temperature may rise significantly with the largest increase of 2.78 °C till 2050. • Conservation priority areas is predicted to cover 23.80 % SWC, with only 3.02 % protected. • The existing PAs' overlap with hotspots is 13.71 %, only 12.69 % hotspots is adequately protected. • Stepwise SWC conservation plan: 25 % protected by 2030, 33 % by 2040, 43 % by 2050. [ABSTRACT FROM AUTHOR]

[Display omitted] • An ensemble of fifteen members combined by five bias-corrected GCMs and three empirical models were included. • Ensemble means of basin-wide rainfall erosivity would increase by 2.5%-31.0%. • Adverse impact of climate change on soil erosion might be minor in certain seasons and regions. Climate change is a driver of soil erosion, but the future projections of seasonal rainfall erosivity variability and spatial distribution over the Lancang-Mekong River Basin (LMRB) are still not well understood. Based on the bias-corrected precipitation data from five General Circulation Models (GCMs) in the sixth phase of the Coupled Model Intercomparison Project (CMIP6), the impacts of future climate change on the seasonal rainfall erosivity over the LMRB were assessed using three widely applied empirical daily rainfall erosivity models under three combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-RCP2.6, SSP3- RCP7.0 and SSP5- RCP8.5). The results show that rainfall erosivity would generally increase in the near term (2030–2060) and far term (2070–2100), and more ensemble members agree with the increase in rainfall erosivity, especially under the high emission scenarios in the far term. In the near term, the ensemble mean of basin-wide rainfall erosivity would increase by 2.5%-8.7% compared to the baseline period (1980–2010), while in the far term, the ensemble mean would increase by 12.2%-31.0%. Seasonal variations in rainfall erosivity show that summer rainfall erosivity from June to August accounts for more than two-thirds of the total annual rainfall erosivity. Although the projected basin-wide average summer rainfall erosivity would increase, the mid-southern basin in Thailand and southern Lao PDR would experience a decrease. For rainfall erosivity from March to May, large areas except for the mountainous part of China would also experience a decrease in seasonal rainfall erosivity. The projected changes in rainfall erosivity can contribute to a better understanding of soil erosion risk under climate change across the LMRB. [ABSTRACT FROM AUTHOR]

The effects of climate change (CC) have intensified in Ghana, especially in the Greater Accra region over the last two decades. CC assessment under the new IPCC scenarios and consistent local station data is limited. Consequently, CC assessment is becoming difficult in data-scarce regions in Ghana. This study utilizes six different Regional Climate Models under the 6th IPCC Report's Shared Socioeconomic Pathway scenarios (SSPs) of the CMIP6, which were bias-corrected with CMhyd over Greater Accra using ground station and PUGMF reanalysis data. The study reveals a reduction and potential shift in the intensity of precipitation in the region under the SSPs. Maximum temperature is expected to increase by 0.81–1.45 °C, 0.84–1.54 °C, 0.96–1.70 °C and 0.98–1.73 °C, while minimum temperature would likely increase by 1.33–2.02 °C, 1.49–2.22 °C, 1.71–4.75 °C and 1.75–4.83 °C under SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5 scenarios, respectively. Thus, temperature will likely increase, especially at night in the near future. Rising temperatures and changes in precipitation have impacts on all strata of society, from agricultural production to power generation and beyond. These findings can help inform Ghanaian policymaking on Sustainable Development Goals 11 and 13 as well as nationally determined contributions within the Paris Agreement. • The study utilizes six different Regional Climate Models to assess the Shared Socioeconomic Pathway scenarios (SSPs) of the CMIP6, over Greater Accra • The study reveals that Greater Accra is projected to be vulnerable to climate change in the future • The study reveals a reduction and potential shift in the intensity of precipitation in the region under the SSPs • Temperature will likely increase, especially at night in the near future. • These findings can help inform Ghanaian policymaking on Sustainable Development Goals 11 and 13 [ABSTRACT FROM AUTHOR]

GDP scenarios are major drivers of climate change and climate change mitigation assessment studies. In this paper, a major update of the SSP GDP projections is presented. By using the most recent economic data and short-term projections by the World Bank and International Monetary Fund, the update captures changes in the system of national accounting and purchasing power parities, as well as the impact of the Covid 19 pandemic. Harmonization between the data and the original end-of-the century SSP projections was carried out in terms of GDP per capita in order to preserve the underlying narrative of income convergence. The result is a set of projections compatible with the most recent data and the SSP narratives. A comparison of DICE models calibrated to the original and updated SSP2 GDP per capita projections illustrates how significant the impact of an update of income data on integrated assessment results can be. The estimated global social costs of carbon in 2015 and 2030 rose by almost 30%. [ABSTRACT FROM AUTHOR]

Projecting future air pollution and related health burdens remains challenging because of the complex interactions among future emissions, population, and climate change. In this study, we estimated the premature deaths attributed to ambient fine particulate matter (PM 2.5) and ozone (O 3) from 2015 to 2100 under four socioeconomic climate scenarios based on an age-stratified assessment method. We found that PM 2.5 will decrease in all shared socioeconomic pathway (SSP) scenarios and O 3 will decrease in the SSP1-2.6 and SSP2-4.5 scenarios, contributing to a decrease in premature mortality together with the declining total population in China. However, the benefits of a decline in population size and PM 2.5 and O 3 concentrations over time will be largely offset by population aging, and premature death caused by PM 2.5 and O 3 will continue to rise till 2060–2080. This impact was greater for the O 3 -related deaths than those for PM 2.5. Our study highlights the importance of future prevention strategies that must jointly improve air quality and susceptibility to aging. [ABSTRACT FROM AUTHOR]

Precipitation changes over the Tibetan Plateau (TP) substantially impact the downstream river runoff. However, future precipitation variation over the TP remains unclear. Here, we evaluated the historical (1961–2014) precipitation of 25 CMIP6 models based on the observations. The multi-model ensemble mean of the five best models (BMME) was in stronger agreement with observations than the single model. Then, seasonal precipitation changes in 2015–2099 were projected using the BMME under four Shared Socioeconomic Pathway (SSP) scenarios. The results showed that seasonal precipitation would increase over the TP in the 21st century, with a higher rate of precipitation increase under the higher emission scenarios. Precipitation is projected to increase by 29.3% (11.5%), 27.1% (12.7%), 23.2% (9.4%), and 16.7% (2.9%) in spring, summer, autumn, and winter by end of the 21st century relative to 1995–2014 under the high-emission SSP5‐8.5 (low-emission SSP1‐2.6) scenario, respectively. The largest precipitation increases in summer and autumn during 2040–2059 and 2080–2099 will occur in the southeastern TP, whereas the largest increases in winter and spring will appear in the Pamirs, where precipitation will increase by >40% during 2080–2099 relative to 1995–2014. The spatial discrepancy in seasonal precipitation changes indicates a potential glacier expansion over the Pamirs and increased flood risks over the southeastern TP. • Future precipitation changes over the Tibetan Plateau (TP) are predicted by CMIP6 models • Performances of 25 CMIP6 models in predicting precipitation variations are reported • Multi-model ensemble means of the five best models provided the highest accuracy • Results show seasonal precipitation will increase over the TP in the 21st century • Seasonal precipitation changes suggest glacier expansion over the Pamirs and increased flood risks over the southeastern TP [ABSTRACT FROM AUTHOR]

Scenario-based land use/land cover change (LUCC) simulation can explore different possibilities in the future for decision-making on city development. However, the current LUCC research in urban-rural areas still lacks support for local climate change research due to unmatched scenario settings and simplified land coverage classification. We thus adopt the local climate zone (LCZ) scheme, which includes more detailed 18 land types, to explore future LUCC in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) under the latest Intergovernmental Panel on Climate Change (IPCC) scenario, the shared socioeconomic pathways (SSPs), with different policy constraints. First, we produce a 100-m spatial resolution LCZ map of the GBA in 2020, which achieves an accuracy with Kappa = 0.876. Then, we carry out an LCZ simulation by adopting the Global Change Analysis Model (GCAM) and Future Land Use Simulation Model (FLUS) from 2020 to 2100 under the SSPs. The results show that LCZ projections appropriately reflect different land responses under different SPPs and the contrastive LCZ spatial changes among different cities even under the same scenario. Ecological protection is a crucial goal in the development plan of the Chinese government. Thus, we add the ecological control lines to protect ecological land under SSPs. This protection is pronouncedly reflected in ecological land within built-up areas in central cities and ecological land around urban areas in fringe cities. This study is the first test of LCZ projection under SSPs. The study findings could serve as an application potential for urban planning, urban climate and mega-city studies globally. • We simulate the future growth of the mega-urban Local climate Zone (LCZ) in 2020–2100. • LCZ projections appropriately reflect different land responses under SSP scenarios. • Spatial contrastive changes differ among LCZ types and cities under the same scenario. • In central cities, the ecological control effect is reflected inside built-up areas. • However, in fringe cities, this effect is pronounced around built-up areas. [ABSTRACT FROM AUTHOR]

Climate change and urbanization are converging to challenge the flood control in the Pearl River Delta (PRD) due to their adverse impacts on precipitation extremes and the urban areas environment. Previous studies have investigated temporal changes in flood risk with various single factor, few have considered the joint effects of climate change, urbanization and socio-economic development. Here, based on the representative concentration pathway (RCP) scenarios, we conducted a comprehensive assessment of future (2030–2050) flood risk over the PRD combined with a thorough investigation of climate change, urbanization and socio-economic development. Precipitation extremes were projected using the regional climate model RegCM4.6, and urbanization growth was projected based on the CA-Markov model. The economic and population development was estimated by the shared socio-economic pathways (SSPs). Flood risk mapping with different RCPs-urbanization-SSPs scenarios was developed for the PRD based on the set pair analyze theory. The results show that climate change and urbanization are expected to exacerbate flood risk in most parts of the PRD during the next few decades, concurrently with more intense extreme precipitation events. The high flood risk areas are projected mainly in the urban regions with unfavorable terrain and dense population. The highest flood risk areas are expected to increase by 8.72% and 19.80% under RCP4.5 and RCP8.5 scenarios, respectively. Reducing greenhouse gas emissions may effectively mitigate the flood risk over the PRD. This study highlight the links between flood risk and changing environment, suggesting that flood risk management and preventative actions should be included in regional adaptation strategies. Unlabelled Image • Predict future extreme precipitation changes using the RegCM4.6 downscaling outputs • Apply CA-Markov model to simulate and predict spatially explicit land use change • Joint the effects of climate change, urbanization, and socio-economic on flood risk • Unfavorable terrain and densely populated urban areas are at greatest risk • Reduce greenhouse gas emissions may effectively mitigate flood risk over the PRD [ABSTRACT FROM AUTHOR]