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Abstract Background This meta-analysis evaluates the diagnostic and staging accuracy of [18F]F-FES PET/CT, its ability to detect estrogen receptor (ER) positivity, and its effectiveness in predicting response to endocrine therapy in ER-positive (ER+) breast cancer. A systematic search of PubMed, Embase (OVID), and Web of Science databases was conducted for studies published between 2013 and June 2024. Studies involving ER + breast cancer patients who underwent [18F]F-FES PET/CT were included. We analyzed the diagnostic accuracy, ER detection capability, and predictive ability for endocrine therapy response. Results Out of 189 studies initially identified, 21 met the inclusion criteria. For diagnosis and staging compared to [18F]F-FDG PET (10 studies), [18F]F-FES PET/CT demonstrated a sensitivity of 0.75 (95% CI: 0.62–0.85) and a false positive rate (FPR) of 0.27 (95% CI: 0.09–0.50). For ER detection (7 studies), sensitivity was 0.86 (95% CI: 0.71–0.94) with an FPR of 0.45 (95% CI: 0.19–0.73). For predicting response to endocrine therapy (12 studies), [18F]F-FES PET/CT showed a sensitivity of 0.79 (95% CI: 0.62–0.89) and an FPR of 0.58 (95% CI: 0.42–0.72). Conclusions [18F]F-FES PET/CT is valuable for diagnosing and staging ER + breast cancer, assessing ER status, and predicting response to endocrine therapy. Its implementation can improve treatment planning and patient outcomes in breast cancer management.

Vegetation phenology is a sensitive indicator of climate change, and the impact of large-scale meteorological seasonal variations on phenological patterns remains understudied because traditional seasonal divisions fail to capture the dynamics of rapid phenological change. Utilizing CN05 gridded temperature data, we applied a dynamic meteorological model to analyze the spatial distribution and trends of spring and autumn, revealing their influence on regional vegetation phenology. We revealed that the start of spring and end of spring advanced at rates of −0.19 d·yr−1 and −0.15 d·yr−1, respectively, affecting 92.57 % and 82.85 % of the study area. Conversely, the start and end of autumn were delayed by + 0.06 d·yr−1 and + 0.10 d·yr−1, impacting 54.05 % and 89.96 % of the region. The length of spring and length of autumn increased at rates of + 0.05 d·yr−1 and + 0.02 d·yr−1, respectively, across 55.93 % and 53.97 % of the area. These changes exhibited a clear latitudinal gradient, with a decreasing duration from south to north. Significant correlations were observed between seasonal variations and vegetation phenology; earlier spring onset corresponded to an earlier start of the growing season in 71.58 % of the study area, while a later end of autumn correlated with a delayed end of the growing season in 59.72 % of the region. This study systematically demonstrates, for the first time, the extensive influence of climate-driven seasonal changes on vegetation phenology, offering valuable insights for weather forecasting, climate zoning, and phenology management.

Net primary productivity (NPP) is a crucial component of the terrestrial carbon cycle and plays a crucial role in assessing ecological security. Although machine learning models have been widely used in research on ecosystem modelling, however, the performance of deep learning models with interpretability in predicting NPP are still very limited. In this study, we developed an interpretable deep learning predictive model to uncover the historical drivers and future changes of NPP in China using remote sensing data, climate data and topography. The results show that more than three quarters (88 %) of China’s regional NPP have shown an increasing trend over the past 20 years, with an overall trend of 2.46 gC/m2/yr. This extensive range of dynamic processes is a nonlinear response to climatic conditions and topographic factors. The constructed convolutional neural network (CNN) model showed good predictive skill for historical NPP, and revealed that temperature is the main controlling factor, highlighting its importance in vegetation growth in China. Compared to the historical period (2001–2020), in the context of future climate change, the risk of carbon sinks decreasing in China is highly likely in the imminent near term (2021–2039), especially under high emission scenarios. These results suggest that interpretable deep learning method is a useful tool for revealing vegetation productivity drivers and estimating vegetation productivity under a nonstationary climate background.

Study region: China Study focus: The Dryness/Wetness Index (DWI) data from China is widely utilized in palaeohydroclimate research. The initial part of this data, covering the years 1470–1979 (original DWI), is primarily generated from records of droughts/floods in historical documents. However, the extended data over 1980–2000 (precipitation-based DWI) is derived entirely from instrumental precipitation measurements. To date, there is no research on the regional differences in hydroclimatic representativeness of the original DWI. Moreover, when reconstructing precipitation using the combined 1470–2000 DWI data as a proxy and calibrating it with instrumental precipitation data post-1950, the overestimated reconstruction skill has not been evaluated. Therefore, utilizing data on crop yield reductions due to drought/flood disasters from 1978 to 2008, we establish the disaster-based DWI following the same method as the original DWI and explore its representativeness and reconstruction skill. New hydrological insights for the region: Disaster-based DWI is more sensitive to precipitation in East Central China, with the seasonal window primarily lasting for five months and distributed between April and September. In contrast, it reflects soil water in the Northeastern, Southeast coastal, and Western regions in China. Additionally, by comparing the average predicted R-Squared of summer precipitation reconstruction using precipitation-based DWI and disaster-based DWI (58.6 % and 45.0 %, respectively), we identify an average overestimation of 13.6 %. Even after excluding this inflated R-Squared, the disaster-based DWI remains a highly reliable proxy for precipitation.

Abstract Background The 70-gene signature (70-GS, MammaPrint) test has been recommended by the main guidelines to evaluate prognosis and chemotherapy benefit of hormonal receptor positive human epidermal receptor 2 negative (HR + /Her2−) early breast cancer (BC). However, this expensive assay is not always accessible and affordable worldwide. Based on our previous study, we established nomogram models to predict the binary and quartile categorized risk of 70-GS. Methods We retrospectively analyzed a consecutive cohort of 150 female patients with HR + /Her2− BC and eligible 70-GS test. Comparison of 40 parameters including the patients’ medical history risk factors, imaging features and clinicopathological characteristics was performed between patients with high risk (N = 62) and low risk (N = 88) of 70-GS test, whereas risk calculations from established models including Clinical Treatment Score Post-5 years (CTS5), Immunohistochemistry 3 (IHC3) and Nottingham Prognostic Index (NPI) were also compared between high vs low binary risk of 70-GS and among ultra-high (N = 12), high (N = 50), low (N = 65) and ultra-low (N = 23) quartile categorized risk of 70-GS. The data of 150 patients were randomly split by 4:1 ratio with training set of 120 patients and testing set 30 patients. Univariate analyses and multivariate logistic regression were performed to establish the two nomogram models to predict the the binary and quartile categorized risk of 70-GS. Results Compared to 70-GS low-risk patients, the high-risk patients had significantly less cardiovascular co-morbidity (p = 0.034), more grade 3 BC (p = 0.006), lower progesterone receptor (PR) positive percentage (p = 0.007), more Ki67 high BC (≥ 20%, p

ABSTRACTAccurate reconstructed series are crucial for studying the differences in regional hydroclimatic variations in Europe over the past millennium. Using hierarchical clustering analysis and stepwise regression methods, we reconstructed yearly time series of the summer standardized precipitation evapotranspiration index (SPEI) for six European regions over the past millennium. Our analysis also revealed prominent regional hydroclimatic differences in multidecadal signals over the past 500 years. For instance, in the 1500s–1570s (from the beginning of the 1500s to the end of the 1570s), drying trends were observed in northern and southeastern Europe, whereas southwestern Europe experienced a wetting trend. Moreover, drying trends were observed in northern and central Europe in the 1640s–1670s. Additionally, wetting trends were observed in western and central Europe during the 1830s–1850s, with drying trends in northern and southeastern Europe. Notably, the hydroclimatic variations in most European regions showed drying trends in the 1920s–1950s, especially in southern Europe. By utilizing large amounts of tree-ring samples and directly comparing regional hydroclimatic variations, our reconstructions provide a consistent and comprehensive dataset for further analysis. The reconstructed dataset is available at https://doi.org/10.57760/sciencedb.07215.

Abstract Lateral movement of soil organic carbon (SOC) induced by soil erosion and runoff changes spatial distributions of SOC, and further changes the land‐atmosphere CO2 exchange and terrestrial carbon budget. However, current ecosystem models do not or only poorly integrate the process of SOC lateral movement and cannot simulate the impacts of soil erosion on the carbon cycle. This study integrated SOC erosion and deposition processes into a process‐based ecosystem model (i.e., Integrated BIosphere Simulator (IBIS)), and separately simulated the lateral movements of dissolved organic carbon (DOC) and particulate organic carbon (POC). The model was evaluated in three river basins in Northeast China that are dominated by cropland, forest, and grassland. The results showed that the model reproduced well the production, erosion, and deposition of DOC and POC. The annual SOC lateral movement (1.34–7.22 g C m−2 yr−1) induced by erosion in the three tested basins was 0.27%–1.45% of the annual net primary production. The model developed in this study has great implications for simulating the lateral movements of SOC in terrestrial ecosystems, which can improve model performance in projecting the terrestrial carbon budget.

Abstract Hydroclimate reconstruction for the last millennium is essential to understand the differences in hydroclimate extremes and their causes under cold/warm conditions. In this study, the first gridded drought/flood grades (D/F grades) dataset in eastern China (EC) during the last millennium was generated. This D/F grades dataset mainly consisted of two components. The first section was created by interpolating drought/flood grades from 1500 to 2000 using the angular distance weight method. Sampling error estimates were employed to assess the effects of the interpolated dataset. The second section for the D/F grades dataset during 960–1500 was generated by constructing best subset regression models using selected tree-ring chronologies in the United States through atmospheric teleconnection. The validation parameters of the calibration equations were also derived, including the adjusted R 2 , predicted R 2 , RE, and CE. This dataset provides critical support for investigating the characteristics and causes of hydroclimate extremes in EC at various spatiotemporal scales, as well as the relationship with climate modes, such as El Niño-Southern Oscillation, Pacific Decadal Oscillation, and East Asia Summer Monsoon.

Water security is under threat worldwide from climate change. A warming climate would accelerate evaporation and cryosphere melting, leading to reduced water availability and unpredictable water supply. However, the water crisis in the Northern Slope of Tianshan Mountains (NSTM) faces dual challenges because water demands for fast-growing urban areas have put heavy pressure on water resources. The mountain-oasis-desert system features glacier-fed rivers that sustain intensive water use in the oasis and end in the desert as fragile terminal lakes. The complex balance between water conservation and economic development is subtle. This paper investigates changes in hydroclimatic variables and water security-related issues on the NSTM. The spatiotemporal variations in glaciers, climatic variables, rivers, lakes and reservoirs, groundwater, surface water, human water use, and streamflow were analyzed for the past four decades. The results show that temperature in the NSTM exhibited an apparent upward trend with a more significant warming rate in the higher altitude regions. Glacier mass loss and shrinkage was strong. The average annual streamflow increased from 1980-1989 to 2006–2011 at most hydrological stations. The monthly dynamics of surface water area showed notable variability at both inter-annual and seasonal scales, revealing the impacts of both natural and anthropogenic drivers on surface water availability in the region. The terrestrial water storage anomaly showed a decreasing trend, which might be related to groundwater pumping for irrigation. Human water use for agriculture and industry grew with the increase in cultivated land area and gross domestic product (GDP). The increased agricultural water use was strongly associated with the expansion of oases. It is unclear whether water availability would remain high under future climatic and hydrological uncertainties, posing challenges to water management. In the context of rapid urban growth and climate change, balancing water for humans and nature is vital in achieving the Sustainable Development Goals (SDGs) in NSTM. This study provides a baseline understanding of the interplay among water, climate change, and socio-economic development in NSTM. It would also shed light on wise water management under environmental changes for other rapidly developing mountain-oasis-desert systems worldwide.

The study of climate variability and trend provides important evidence for water resource management strategies in Xinjiang. The scientific community has systematically studied the ‘warming and wetting’ process in the Xinjiang region. However, significant controversy persists regarding whether this trend has stagnated, and there remains a gap in understanding the decadal climate variability across different seasons within the subregions of Xinjiang. Here, we analyzed the spatiotemporal characteristics of seasonal-to-annual climate variations in Southern and Northern Xinjiang over the past 60 years by the Standardized Precipitation Evapotranspiration Index (SPEI-3) and identified the change points of mean and trend changes in the SPEI series and further explored the atmospheric circulation patterns before and after the transition from dry/wet conditions. Specifically, although the mean change point test indicated a wetter climate after 1986 at both the annual and seasonal scales, the trend analysis showed a shift from wet to dry from 1996, which has persisted until the present. There were significant interdecadal features in the spatial distribution of SPEI. Xinjiang exhibited a predominantly dry pattern from 1961 to 1980, which changed to a wetter pattern from 1981 to 2000, Xinjiang experienced its wettest decade from 1991 to 2000, and the whole region returned to a drier pattern from 2001 to 2020. From the annual and seasonal variation, the rate of change is greater in the south, with stronger change amplitude in summer and autumn and a higher frequency of anomalous SPEI. The results of the atmospheric circulation analysis demonstrated that the net water vapor flux in the Xinjiang region increased by about 8.30 g·kg ^−1 ·m·s ^−1 in the period 1987–2020 compared to 1961–1986 due to the combined interaction of high-, mid-, and low-latitude systems with the Central Asian low-pressure system. The results indicated a sharp increase in aridification in Xinjiang, providing valuable insights for disaster prevention, mitigation, and risk management related to regional drought hazards.

BackgroundCyclin-dependent kinase 4/6 inhibitor (CDK4/6i) has become the commonest first-line treatment of hormonal receptor positive and human epidermal growth factor receptor 2 negative (HR+/HER2-) metastatic breast cancer (MBC). However, therapy is quite individualized after progression of disease (PD) when CDK4/6i fails. Estrogen receptor (ER) status of metastatic lesions of bone, lung or liver might be different from the primary tumor and biopsy of metastatic lesions was invasive and not always available. Prediction of treatment response after PD of CDK4/6i remains unsolved. 18F-fluoroestradiol (FES) PET/CT could non-invasively reveal ER expression both in primary and metastatic breast cancer and recognize heterogeneity of ER status.Case presentationA 70-year-old woman with Parkinson’s disease, osteoporosis and cardiovascular co-morbidity was diagnosed with HR+/HER2- breast cancer (pT2N2M0, stage IIIa). Three years later, she developed metastases in right lung and pleura with pleural effusion and received palbociclib + letrozole. After 8 months the disease progressed, and 18F-FES PET/CT revealed multiple ER-positive pleural lesions and ER-negative pulmonary nodules after PD and the progression-free survival (PFS) of first-line CDK4/6i was 8 months. Since most of the metastatic lesions were ER-positive, abemaciclib + fulvestrant were chosen as the second-line CDK4/6i treatment and the PFS was 15 months. Another 18F-FES PET/CT showed a new ER-positive pleural mass with multiple ER-negative pulmonary nodules. Since 18F-FES PET/CT revealed that the dominant lesions were still ER-positive, dalpiciclib + exemestane + fulvestrant were prescribed as the third-line CDK4/6i treatment. Currently the patient’s disease had been stable for 2 months.ConclusionThis case demonstrated that 18F-FES PET/CT could show ER heterogeneity non-invasively and reveal the treatment responses a predictive imaging tool of serial second- and third-line of CDK4/6i treatments when first-line CDK4/6i failed in HR+/HER2- MBC. So long as the dominant or newly-developed metastatic lesion was ER-positive on 18F-FES PET after first-line CDK4/6i, the patient might show certain therapeutic response towards endocrine-based treatment including second- and third-line of CDK4/6i, and thus increased the time to chemotherapy (TTC).

Abstract Purpose To develop and validate a machine learning model based on radiomic features derived from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) images to preoperatively predict the pathological grade in patients with pancreatic ductal adenocarcinoma (PDAC). Methods A total of 149 patients (83 men, 66 women, mean age 61 years old) with pathologically proven PDAC and a preoperative 18F-FDG PET/CT scan between May 2009 and January 2016 were included in this retrospective study. The cohort of patients was divided into two separate groups for the training (99 patients) and validation (50 patients) in chronological order. Radiomics features were extracted from PET/CT images using Pyradiomics implemented in Python, and the XGBoost algorithm was used to build a prediction model. Conventional PET parameters, including standardized uptake value, metabolic tumor volume, and total lesion glycolysis, were also measured. The quality of the proposed model was appraised by means of receiver operating characteristics (ROC) and areas under the ROC curve (AUC). Results The prediction model based on a twelve-feature-combined radiomics signature could stratify PDAC patients into grade 1 and grade 2/3 groups with AUC of 0.994 in the training set and 0.921 in the validation set. Conclusion The model developed is capable of predicting pathological differentiation grade of PDAC based on preoperative 18F-FDG PET/CT radiomics features.

Abstract Background 99mTc-PYP scintigraphy provides differential diagnosis of ATTR cardiomyopathy (ATTR-CM) from light chain cardiac amyloidosis and other myocardial disorders without biopsy. This study was aimed to assess the diagnostic feasibility and the operator reproducibility of 99mTc-PYP quantitative SPECT. Method Thirty-seven consecutive patients who underwent a 99mTc-PYP thorax planar scan followed by SPECT and CT scans to diagnose suspected ATTR-CM were enrolled. For the quantitative SPECT, phantom studies were initially performed to determine the image conversion factor (ICF) and partial volume correction (PVC) factor to recover 99mTc-PYP activity concentration in the myocardium for calculating the standardized uptake value (SUV) (unit: g/ml). SUVmax was compared among groups of ATTR-CM, AL cardiac amyloidosis, and other pathogens (others) and among categories of Perugini visual scores (grades 0–3). The intra- and inter-operator reproducibility of quantitative SPECT was verified, and the corresponded repeatability coefficient (RPC) was calculated. Results The ICF was 79,327 Bq/ml to convert count rate in pixel to 99mTc activity concentration. PVC factor as a function of the measured activity concentration ratio in the myocardium and blood-pool was [y = 1.424 × (1 − exp(− 0.759 × x)) + 0.104]. SUVmax of ATTR-CM (7.50 ± 2.68) was significantly higher than those of AL (1.96 ± 0.35) and others (2.00 ± 0.74) (all p < 0.05). SUVmax of grade 3 (8.95 ± 1.89) and grade 2 (4.71 ± 0.23) were also significantly higher than those of grade 1 (1.92 ± 0.31) and grade 0 (1.59 ± 0.39) (all p < 0.05). Correlation coefficient (R 2) of SUVmax reached 0.966 to 0.978 with only small systematic difference (intra = − 0.14; inter = − 0.23) between two repeated measurements. Intra- and inter-operator RPCs were 0.688 and 0.877. Conclusions 99mTc-PYP quantitative SPECT integrated with adjustable PVC factors is feasible to quantitatively and objectively assess the burden of cardiac amyloidosis for diagnosis of ATTR-CM.

Brown adipose tissue (BAT) is important in monitoring energy homeostasis and cancer cachexia. Different from white adipose tissue, BAT is characterized by the presence of a large number of mitochondria in adipocytes. Translocator protein 18 kDa (TSPO), a critical transporter, is expressed in the outer membrane of mitochondria. We speculated that [18F]DPA714, a specific TSPO tracer, may monitor BAT activity in tumor-bearing mice in vivo. We first analyzed the radioactive uptake of positron emission tomography (PET) tracers in BAT of CT26 xenograft mice with 18F-fluorodeoxyglucose ([18F]FDG) and [18F]DPA714. We also studied the BAT uptake of [18F]DPA714 in CT26, A549 and LLC tumor models. The dynamic distribution of [18F]FDG is quite variable among animals, even in mice of the same tumor model (%ID/g-mean: mean ± SDM, 8.61 ± 8.90, n = 16). Contrarily, [18F]DPA714 produced high-quality and stable BAT imaging in different tumor models and different animals of the same model. Interestingly, %ID/g-mean of [18F]DPA714 in BAT was significantly higher on day 26 than that on day 7 in CT26 xenograft model. Taken together, these results strongly indicate the potential feasibility of [18F]DPA714 PET imaging in investigating BAT and energy metabolism during tumor progression in preclinical and clinical study.

Introduction Cardiovascular diseases (CVDs) are the leading causes of death and disability worldwide. Reducing dietary salt consumption is a potentially cost-effective way to reduce blood pressure and the burden of CVD. To date, economic evidence has focused on sodium reduction in food industry or processed food with blood pressure as the primary outcome. This study protocol describes the planned within-trial economic evaluation of a low-sodium salt substitute intervention designed to reduce the risk of stroke in China.Methods and analyses The economic evaluation will be conducted alongside the Salt Substitute and Stroke Study: a 5-year large scale, cluster randomised controlled trial. The outcomes of interest are quality of life measured using the EuroQol-5-Dimensions and major adverse cardiovascular events. Costs will be estimated from a healthcare system perspective and will be sought from the routinely collected data available within the New Rural Cooperative Medical Scheme. Cost-effectiveness and cost-utility analyses will be conducted, resulting in the incremental cost-effectiveness ratio expressed as cost per cardiovascular event averted and cost per quality-adjusted life year gained, respectively.Ethics and dissemination The trial received ethics approval from the University of Sydney Ethics Committee (2013/888) and Peking University Institutional Review Board (IRB00001052-13069). Informed consent was obtained from each study participant. Findings of the economic evaluation will be published in a peer-reviewed journal and presented at international conferences.Trial registration number ClinicalTrials.gov Registry (NCT02092090).

We report a rare case of Cushing’s syndrome induced by an ectopic adrenocortical adenoma. A 57-year-old woman was diagnosed with adrenocorticotropic hormone (ACTH)-independent Cushing’s syndrome based on clinical manifestation and laboratory information. She was found to have a mass in the left renal hilum via contrast-enhanced computed tomography (CT). The mass was negative, as seen in somatostatin receptor imaging with 99mTc-hydrazinonicotinyl-Tyr3-octreotide (HYNIC-TOC), and showed mild fluorodeoxyglucose (FDG) activity via positron emission tomography (PET)/CT. The results of adrenal venous sampling suggested a left-side adrenal origin of hypercortisolism, possibly secreted by the mass in the renal hilum. Histopathology after surgical resection of the mass confirmed an ectopic adrenocortical adenoma, which was responsible for the patient’s Cushing’s syndrome. During the 8-month follow-up after surgery, no recurrence of Cushing’s syndrome was found.

Suitable planting areas for winter wheat in north China are expected to shift northwardly due to climate change, however, increasing extreme events and the deficient water supply are threatening the security of planting systems. Thus, based on predicted climate data for 2021–2050 under the Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5) emission scenarios, as well as historical data from 1961–1990, we use four critical parameters of percentages of extreme minimum temperature years (POEMTY), first day of the overwintering period (FD), sowing date (SD), and precipitation before winter (PBW), in order to determine the planting boundary of winter wheat. The results show that the frequency of extreme minimum temperature occurrences is expected to decrease in the North winter wheat area, which will result in a northward movement of the western part of northern boundary by 73, 94, and 114 km on average, in addition to FD delays ranging from 6.0 to 10.5 days. Moreover, agrometeorological conditions in the Huang-Huai winter wheat area are expected to exhibit more pronounced changes than the rest of the studied areas, especially near the southern boundary, which is expected to retreat by approximately 213, 215, and 233 km, northwardly. The north boundary is expected to move 90–140 km northward. Therefore, the change in southern and northern boundaries will lead the potential planting areas of the entire North winter wheat area to increase by 10,700 and 28,000 km2 on average in the SSP3-7.0 and SSP5-8.5 scenarios, respectively, but to decrease by 38,100 km2 in the SSP1-2.6 scenario; however, the lack of precipitation remains a limitation for extending planting areas in the future.

Climate changes and its influences on human society are of increasing concern in science communities. Based on the reconstructed climate data and CENTURY model, we simulated net primary productivity of grassland and the grain yield of highland barley during the pre-industrial millennium in Ali Prefecture, Tibet Autonomous Region. It showed that the variation of precipitation and temperature together affected the fluctuation of land productivity. Wavelet analysis results showed that the land productivity in Ali fluctuated within main periodic bands of 180 yr. We found that the rise and falls of the Guge Kingdom in Ali was synchronic with the fluctuation of land productivity, and the collapse of the Guge Kingdom was obviously related to the sudden change of climate in the 17th century, which turned dry and cold. By combining with historical studies, this study further proposes the mechanism of land productivity fluctuation under climate change on Guge Kingdom. Our findings are helpful to understand the relationship between climate change and social vulnerability, especially providing a typical case study of ancient plateau countries.

In this study, the hierarchical clustering algorithm was used to cluster the summer heat waves (HWs) in northern East Asia (NEA) into wave-train HW and blocking HW. In the past 38 years, the wave-train HWs have increased significantly, while the blocking HWs have not shown a visible trend. The wave-train index and the blocking index are proposed to objectively identify the HW type after capturing the circulation characteristics of two kinds of HWs. When a wave-train HW occurs in NEA, simultaneous HW will occur in Eastern Europe. However, when a blocking HW occurs in NEA, a negative temperature anomaly will take place in Eastern Europe. The results of numerical simulations using the linear baroclinic model indicate that the wave-train HWs and the blocking HWs are related to the heating anomaly over southern Greenland and the cooling anomaly over the Barents Sea, respectively.

Changes in climate extremes under 1.5 °C and 2 °C global warming may impact agricultural production across Central Asia. We used the simulated daily data of average temperature, maximum temperature, minimum temperature, and precipitation provided by the Inter-Sectoral Impact Model Intercomparison Project and analyzed the current climate status and future projected changes of a set of climate extreme indices related to agricultural production under 1.5 °C and 2 °C global warming. In addition, the possible impacts of climate change on agricultural production in Central Asia were discussed. The results show that the annual mean temperature in Central Asia will increase by 1.48 °C and 2.34 °C at 1.5 °C and 2 °C warming levels, respectively, compared to the base period (1986–2005), and the increasing trends are significant at the α = 0.01 level for all grids. The number of warm days and growing season length will increase. Under the 1.5 °C scenario, the mean annual total precipitation (PRCPTOT) and heavy precipitation (R95P) will experience increases of 7.68% and 26.55%, respectively, and the consecutive dry days (CDD) will be reduced by 1.1 days. However, the standardized precipitation evapotranspiration index (SPEI) shows significant drought conditions in most of Central Asia (more than 60%). Under the 2 °C scenario, there will be a 3.89% increase in PRCPTOT and a 24.78% increase in R95P. Nevertheless, accompanying the increase in CDD (0.8 day) and the decrease in SPEI, drought conditions will be further exacerbated. These results indicate that Central Asia is likely to face more severe ecological problems in the future, which will threaten the regional agricultural production and the food security. Therefore, adaptation strategies should be implemented immediately to mitigate the negative impacts of climate change on Central Asia’s agriculture.

Exploring the impacts of climate change on agriculture is one of important topics with respect to climate change. We quantitatively examined the impacts of climate change on winter wheat yield in Northern China using the Cobb–Douglas production function. Utilizing time-series data of agricultural production and meteorological observations from 1981 to 2016, the impacts of climatic factors on wheat production were assessed. It was found that the contribution of climatic factors to winter wheat yield per unit area (WYPA) was 0.762–1.921% in absolute terms. Growing season average temperature (GSAT) had a negative impact on WYPA for the period of 1981–2016. A 1% increase in GSAT could lead to a loss of 0.109% of WYPA when the other factors were constant. While growing season precipitation (GSP) had a positive impact on WYPA, as a 1% increase in GSP could result in 0.186% increase in WYPA, other factors kept constant. Then, the impacts on WYPA for the period 2021–2050 under two different emissions scenarios RCP4.5 and RCP8.5 were forecasted. For the whole study area, GSAT is projected to increase 1.37°C under RCP4.5 and 1.54°C under RCP8.5 for the period 2021–2050, which will lower the average WYPA by 1.75% and 1.97%, respectively. GSP is tended to increase by 17.31% under RCP4.5 and 22.22% under RCP8.5 and will give a rise of 3.22% and 4.13% in WYPA. The comprehensive effect of GSAT and GSP will increase WYPA by 1.47% under RCP4.5 and 2.16% under RCP8.5.

To limit global warming to well below 2°C in accord with the Paris Agreement, countries throughout the world have submitted their Intended Nationally Determined Contributions (INDCs) outlining their greenhouse gas (GHG) mitigation actions in the next few decades. However, it remains unclear what the resulting climate change is in response to the proposed INDCs and subsequent emission reductions. In this study, the global and regional warming under the updated INDC scenarios was estimated from a range of comprehensive Earth system models (CMIP5) and a simpler carbon-climate model (MAGICC), based on the relationship of climate response to cumulative emissions. The global GHG emissions under the updated INDC pledges are estimated to reach 14.2∼15.0 GtC/year in 2030, resulting in a global mean temperature increase of 1.29∼1.55°C (median of 1.41°C) above the preindustrial level. By extending the INDC scenarios to 2100, global GHG emissions are estimated to be around 6.4∼9.0 GtC/year in 2100, resulting in a global mean temperature increase by 2.67∼3.74°C (median of 3.17°C). The Arctic warming is projected to be most profound, exceeding the global average by a factor of three by the end of this century. Thus, climate warming under INDC scenarios is projected to greatly exceed the long-term Paris Agreement goal of stabilizing the global mean temperature at to a low level of 1.5‐2.0°C above the pre-industrial. Our study suggests that the INDC emission commitments need to be adjusted and strengthened to bridge this warming gap.

Volcanic eruptions, climate changes and their influences on crop harvests and social development are of increasing concern in science communities. Using a dataset of crop harvest scores of southwest China from 1730 to 1910, which was derived from the memorials to the emperors in the Qing Dynasty of China, reconstructed climate proxies and the chronology of large volcanic eruptions occurring between 10°S and 15°N, we analysed possible relationships between crop harvests, climate changes and volcanic eruptions. In addition, some archives of policies and measures related to crops and social development extracted from the chronicles were used to analyse social resilience when faced with poor harvests. The results show that crop harvests in the study area generally increased with fluctuations when there were less low-latitude large volcanic eruptions from 1730 to 1810. However, from 1811 to 1910, volcanoes at low latitudes erupted more frequently, which contributed to concurrent low temperature and drought. Meanwhile, the crop harvests showed a step-down decrease during the following periods of 1810s, 1850s, 1870s and 1890s. Though, the local social system was certainly resilient in facing of such climate and agriculture disasters, i.e. the local society remained stable without significant famine, large-scale migration or social unrest until 1911. The strong resilience of local social systems owed largely to various relieving measures, such as, building barns, exempting or reducing local taxes, allocating farmland to immigrants, and central government dominated grain purchasing and distribution to alleviate disasters.

Average sodium intake and stroke mortality in northern China are both among the highest in the world. An effective, low-cost strategy to reduce sodium intake in this population is urgently needed.We sought to determine the effects of a community-based sodium reduction program on salt consumption in rural northern China.This study was a cluster-randomized trial done over 18 months in 120 townships (one village from each township) from five provinces. Sixty control villages were compared to 60 intervention villages that were given access to a reduced-sodium, added-potassium salt substitute in conjunction with a community-based health education program focusing on sodium reduction. The primary outcome was the difference in 24-hour urinary sodium excretion between randomized groups.Among 1,903 people with valid 24-hour urine collections, mean urinary sodium excretion in intervention compared with control villages was reduced by 5.5% (-14mmol/day, 95% confidence interval -26 to -1; p = 0.03), potassium excretion was increased by 16% (+7mmol/day, +4 to +10; p

Based on observational data and Asian monsoon intensity datasets from China, the relationships between the East Asian winter monsoon index and winter temperature, the East Asian summer monsoon index and Meiyu precipitation over the middle and lower reaches of the Yangtze River, were analyzed. We found that the monsoon signals were reflected in the temperature and Meiyu precipitation variations. Thus, we used the reconstructed Meiyu precipitation and winter temperature series for the past 300 years and detected the summer/winter monsoon intensity signals using multi-taper spectral estimation method and wavelet analysis. The main periodicities of Meiyu precipitation and winter temperature, such as interannual cycle with 2-7-year, interdecadal-centennial cycles with 30-40-year and 50-100-year, were found. The good relationships between the East Asian summer and winter monsoons suggested that they were in phase at 31-year cycle, while out of phase at 100-year cycle, but with 20-year phase difference. In addition, the winter monsoon intensity may be regulated by the North Atlantic Oscillation, the Arctic Oscillation and the Atlantic Multidecadal Oscillation, and the summer monsoon is closely related to the signal intensities of the Pacific Decadal Oscillation.

We reconstructed the annual temperature anomaly series in Xinjiang during 1850-2001 based on three kinds of proxies, including 17 tree-ring width chronologies, one tree-ring δ13C series and two δ18O series of ice cores, and instrumental observation data. The low- and high-frequency signal decomposition for the raw temperature proxy data was obtained by a fast Fourier transform filter with a window size of 20 years, which was used to build a good relationship that explained the high variance between the temperature and the proxy data used for the reconstruction. The results showed that for 1850-2001, the temperature during most periods prior to the 1920s was lower than the mean temperature in the 20th century. Remarkable warming occurred in the 20th century at a rate of 0.85°C/100a, which was higher than that during the past 150 years. Two cold periods occurred before the 1870s and around the 1910s, and a relatively warm interval occurred around the 1940s. In addition, the temperature series showed a warming hiatus of approximately 20 years around the 1970s, and a rapid increase since the 1980s.

Depending on the descriptions of crop yield and social response to crop failure/harvest from Chinese historical documents, we classified the crop yield of North China during 601–900 AD into six categories and quantified each category to be the crop yield grades. We found that the regional mean crop yield had a significant (P

According to the written records and scores of grain harvest in the official historical documents of the Qing Dynasty in China, the spatial-temporal distribution of and the impact caused by the 1759 AD drought in Northwest China were reconstructed, and the response of Chinese society to the drought at that time was summarized. In the spring and summer of 1759, vast areas of northern China suffered from drought, of which that experienced in the northwest region was the most serious. Starting from 27 April 1759, droughts covered Zhili, Shanxi, Shaanxi, and Gansu provinces, and the droughts in Gansu and northern Shaanxi provinces lasted until 23 July 1759. This severe drought caused the worst crop failure in Northwest China in 1759 during the period 1730-1900. By implementing a series of disaster relief measures, the Qing government managed to ease the adverse societal impact of the drought in the summer of 1760. Among the relief measures, tax reduction and exemption in disaster-stricken areas, grain storage in the northwest region, and bumper agricultural harvests in Henan, Shandong, Jiangsu, and Anhui provinces in 1759 were the main reasons for the rapid recovery from the drought impacts. With better climatic conditions in the 18th century, China had higher agricultural harvest levels in the 18th century than in the 19th century. Favorable financial conditions increased drought relief efforts, which was the background for the greater societal adaptability to the climate disaster of 1759. [ABSTRACT FROM AUTHOR]