Projections of future temperature-related cardiovascular mortality under climate change, urbanization and population aging in Beijing, China

The synergistic effect of high temperature and relative humidity on non-accidental deaths at different urbanization levels

Numerous studies have examined the impact of temperature on mortality, yet research on the combined effect of temperature and humidity on non-accidental deaths remains limited. This study investigates the synergistic impact of high temperature and humidity on non-accidental deaths in China, assessing the influence of urban development and urbanization level. Utilizing the distributed lag nonlinear model (DLNM) of quasi-Poisson regression, we analyzed the relationship between Wet Bulb Globe Temperature (WBGT) and non-accidental deaths in 30 Chinese cities from 2010 to 2016, including Guangzhou during 2012-2016. We stratified temperature and humidity across these cities to evaluate the influence of varying humidity levels on deaths under high temperatures. Then, we graded the duration of heat and humidity in these cities to assess the impact of deaths with different durations. Additionally, the cities were categorized based on gross domestic product (GDP), and a vulnerability index was calculated to examine the impact of urban development and urbanization level on non-accidental deaths. Our findings reveal a pronounced synergistic effect of high temperature and humidity on non-accidental deaths, particularly at elevated humidity levels. The synergies of high temperature and humidity are extremely complex. Moreover, the longer the duration of high temperature and humidity, the higher the risk of non-accidental death. Furthermore, areas with higher urbanization exhibited lower relative risks (RR) associated with the synergistic effects of heat and humidity. Consequently, it is imperative to focus on damp-heat related mortality among vulnerable populations in less developed regions.

Association between ambient temperature and cause-specific mortality: An individual-level case-crossover study in Suzhou, China

The changing climate poses a growing challenge to the population health. The objective of this study was to assess the association between ambient temperature and cause-specific mortality in Suzhou. Based on the non-accidental mortality data collected during 2008-2022 in Suzhou, China, this study utilized an individual-level case-crossover design to evaluate the associations of temperature with cause-specific mortality. We applied a distributed lag nonlinear model with a maximum lag of 14 days to account for lag effects. Mortality risk due to extreme cold (<2.5th percentile) and extreme heat (>97.5th percentile) was analyzed. A total of 634,530 non-accidental deaths were analyzed in this study. An inverse J-shaped exposure-response relationship was observed between ambient temperature and non-accidental mortality, with the minimum mortality temperature (MMT) at 29.1℃. The relative risk (RR) of mortality associated with extreme cold (2.5th percentile) was 1.37 [95 % confidence interval (CI): 1.30, 1.44], higher than estimate of 1.09 (95 %CI: 1.07, 1.11) for extreme heat (97.5th percentile) relative to the MMT. Heat effect lasted for 2-3 days, while cold effect could persist for almost 14 days. Higher mortality risk estimates were observed for cardiorespiratory deaths compared to total deaths, with statistically significant between-group differences. Consequently, this study provides first-hand evidence on the associations between ambient temperatures and mortality risks from various causes, which could help local government and policy-makers in designing targeted strategies and public health measures against the menace of climate change.

Modifying temperature-related cardiovascular mortality through green-blue space exposure

Green-blue spaces (GBS) are pivotal in mitigating thermal discomfort. However, their management lacks guidelines rooted in epidemiological evidence for specific planning and design. Here we show how various GBS types modify the link between non-optimal temperatures and cardiovascular mortality across different thermal extremes. We merged fine-scale population density and GBS data to create novel GBS exposure index. A case time series approach was employed to analyse temperature-cardiovascular mortality association and the effect modifications of type-specific GBSs across 1085 subdistricts in south-eastern China. Our findings indicate that both green and blue spaces may significantly reduce high-temperature-related cardiovascular mortality risks (e.g., for low (5%) vs. high (95%) level of overall green spaces at 99th vs. minimum mortality temperature (MMT), Ratio of relative risk (RRR) = 1.14 (95% CI: 1.07, 1.21); for overall blue spaces, RRR = 1.20 (95% CI: 1.12, 1.29)), while specific blue space types offer protection against cold temperatures (e.g., for the rivers at 1st vs MMT, RRR = 1.17 (95% CI: 1.07, 1.28)). Notably, forests, parks, nature reserves, street greenery, and lakes are linked with lower heat-related cardiovascular mortality, whereas rivers and coasts mitigate cold-related cardiovascular mortality. Blue spaces provide greater benefits than green spaces. The severity of temperature extremes further amplifies GBS's protective effects. This study enhances our understanding of how type-specific GBS influences health risks associated with non-optimal temperatures, offering valuable insights for integrating GBS into climate adaptation strategies for maximal health benefits.

Optimal decision-making in relieving global high temperature-related disease burden by data-driven simulation

The rapid acceleration of global warming has led to an increased burden of high temperature-related diseases (HTDs), highlighting the need for advanced evidence-based management strategies. We have developed a conceptual framework aimed at alleviating the global burden of HTDs, grounded in the One Health concept. This framework refines the impact pathway and establishes systematic data-driven models to inform the adoption of evidence-based decision-making, tailored to distinct contexts. We collected extensive national-level data from authoritative public databases for the years 2010-2019. The burdens of five categories of disease causes - cardiovascular diseases, infectious respiratory diseases, injuries, metabolic diseases, and non-infectious respiratory diseases - were designated as intermediate outcome variables. The cumulative burden of these five categories, referred to as the total HTD burden, was the final outcome variable. We evaluated the predictive performance of eight models and subsequently introduced twelve intervention measures, allowing us to explore optimal decision-making strategies and assess their corresponding contributions. Our model selection results demonstrated the superior performance of the Graph Neural Network (GNN) model across various metrics. Utilizing simulations driven by the GNN model, we identified a set of optimal intervention strategies for reducing disease burden, specifically tailored to the seven major regions: East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa. Sectoral mitigation and adaptation measures, acting upon our categories of Infrastructure & Community, Ecosystem Resilience, and Health System Capacity, exhibited particularly strong performance for various regions and diseases. Seven out of twelve interventions were included in the optimal intervention package for each region, including raising low-carbon energy use, increasing energy intensity, improving livestock feed, expanding basic health care delivery coverage, enhancing health financing, addressing air pollution, and improving road infrastructure. The outcome of this study is a global decision-making tool, offering a systematic methodology for policymakers to develop targeted intervention strategies to address the increasingly severe challenge of HTDs in the context of global warming.

Using a Leroux-prior-based conditional autoregression-based strategy to map the short-term association between temperature and bacillary dysentery and its attributable burden in China

Background

In China, bacillary dysentery (BD) is the third most frequently reported infectious disease, with the greatest annual incidence rate of 38.03 cases per 10,000 person-years. It is well acknowledged that temperature is associated with BD and the previous studies of temperature-BD association in different provinces of China present a considerable heterogeneity, which may lead to an inaccurate estimation for a region-specific association and incorrect attributable burdens. Meanwhile, the common methods for multi-city studies, such as stratified strategy and meta-analysis, have their own limitations in handling the heterogeneity. Therefore, it is necessary to adopt an appropriate method considering the spatial autocorrelation to accurately characterize the spatial distribution of temperature-BD association and obtain its attributable burden in 31 provinces of China.

Methods

A novel three-stage strategy was adopted. In the first stage, we used the generalized additive model (GAM) model to independently estimate the province-specific association between monthly average temperature (MAT) and BD. In the second stage, the Leroux-prior-based conditional autoregression (LCAR) was used to spatially smooth the association and characterize its spatial distribution. In the third stage, we calculate the attribute BD cases based on a more accurate estimation of association.

Results

The smoothed association curves generally show a higher relative risk with a higher MAT, but some of them have an inverted "V" shape. Meanwhile, the spatial distribution of association indicates that western provinces have a higher relative risk of MAT than eastern provinces with 0.695 and 0.645 on average, respectively. The maximum and minimum total attributable number of cases are 224,257 in Beijing and 88,906 in Hainan, respectively. The average values of each province in the eastern, western, and central areas are approximately 40,991, 42,025, and 26,947, respectively.

Conclusion

Based on the LCAR-based three-stage strategy, we can obtain a more accurate spatial distribution of temperature-BD association and attributable BD cases. Furthermore, the results can help relevant institutions to prevent and control the epidemic of BD efficiently.

Projection of future heat-related morbidity in three metropolitan prefectures of Japan based on large ensemble simulations of climate change under 2 °C global warming scenarios

Recently, global warming has become a prominent topic, including its impacts on human health. The number of heat illness cases requiring ambulance transport has been strongly linked to increasing temperature and the frequency of heat waves. Thus, a potential increase in the number of cases in the future is a concern for medical resource management. In this study, we estimated the number of heat illness cases in three prefectures of Japan under 2 °C global warming scenarios, approximately corresponding to the 2040s. Based on the population composition, a regression model was used to estimate the number of heat illness cases with an input parameter of time-dependent meteorological ambient temperature or computed thermophysiological response of test subjects in large-scale computation. We generated 504 weather patterns using 2 °C global warming scenarios. The large-scale computational results show that daily amount of sweating increased twice and the core temperature increased by maximum 0.168 °C, suggesting significant heat strain. According to the regression model, the estimated number of heat illness cases in the 2040s of the three prefectures was 1.90 (95%CI: 1.35-2.38) times higher than that in the 2010s. These computational results suggest the need to manage ambulance services and medical resource allocation, including intervention for public awareness of heat illnesses. This issue will be important in other aging societies in near future.

The coupling coordination characteristics of China's health production efficiency and new urbanization and its influencing factors

Urbanization leads to dramatic changes in habitat quality, which significantly affects population health. Research on the coupling coordination relationship between new urbanization and health production efficiency is conducive to improving residents' well-being and urban sustainable development. In this article, we adopted the super-efficient SBM model and entropy value method separately to evaluate the spatiotemporal variation characteristics of health production efficiency and new urbanization in China. Then, we used the coupling coordination degree model to investigate the interactive coercing relationship between new urbanization and health production efficiency. Finally, the panel Tobit model is used to analyze the factors influencing the coupled coordination of the two systems. The results showed that the new urbanization levels of 31 provinces in China have all steadily increased from 2003 to 2018. Health production efficiency exhibited a fluctuating but increasing trend, and its regional differences are gradually narrowing. Health production efficiency and new urbanization have developed in a more coordinated direction, with a spatial pattern of "high in the southeast and low in the northwest." Meanwhile, the relative development characteristics between the two systems have constantly changed, from the new urbanization lagged type to the two systems synchronized type and the health production efficiency lagged type. Population density, economic development level, government financial investment, and government health investment positively impact the coupling coordination degree of the two systems. In comparison, individual health investment harms the harmonization of the two systems.

Patterns in acute aortic dissection and a connection to meteorological conditions in Germany

Acute type A aortic dissection (ATAAD) is a dramatic emergency exhibiting a mortality of 50% within the first 48 hours if not operated. This study found an absolute value of cosine-like seasonal variation pattern for Germany with significantly fewer ATAAD events (Wilcoxon test) for the warm months of June, July, and August from 2005 to 2015. Many studies suspect a connection between ATAAD events and weather conditions. Using ERA5 reanalysis data and an objective weather type classification in a contingency table approach showed that for Germany, significantly more ATAAD events occurred during lower temperatures (by about 4.8 K), lower water vapor pressure (by about 2.6 hPa), and prevailing wind patterns from the northeast. In addition, we used data from a classification scheme for human-biometeorological weather conditions which was not used before in ATAAD studies. For the German region of Berlin and Brandenburg, for 2006 to 2019, the proportion of days with ATAAD events during weather conditions favoring hypertension (cold air advection, in the center of a cyclone, conditions with cold stress or thermal comfort) was significantly increased by 13% (Chi-squared test for difference of proportions). In contrast, the proportion was decreased by 19% for conditions associated with a higher risk for patients with hypotension and therefore a lower risk for patients with hypertension (warm air advection ahead of warm fronts, conditions with no thermal stress or heat stress, in the center of a cyclone with thermal stress). As many studies have shown that hypertension is a risk factor for ATAAD, our findings support the hypothesized relation between ATAAD and hypertension-favoring weather conditions.

Heat exposure assessment based on high-resolution spatio-temporal data of population dynamics and temperature variations

Urban heat waves pose a significant risk to the health and safety of city dwellers, with urbanization potentially amplifying the health impact of extreme heat. Accurate assessments of population heat exposure hinge on the interplay between temperature, population spatial dynamics, and the epidemiological effects of temperature on health. Yet, many past studies have over-simplified the matter by assuming static populations, leading to substantial inaccuracies in heat exposure assessments. To address these issues, this study integrates dynamic population data, fluctuating temperature, and the exposure-response relationship between temperature and health to construct an advanced heat exposure assessment framework predicated on a population dynamic model. We analyzed urban heat island characteristics, population dynamics, and heat exposure during heat wave conditions in Beijing, a major city in China. Our findings highlight significant intra-day population movement between urban and suburban areas during heat wave conditions, with spatial population flow patterns showing clear scale-dependent characteristics. These population flow dynamics intensify heat exposure levels, and the disparity between dynamic population-weighted temperature and average temperature is most pronounced at night. Our research provides a more comprehensive understanding of real urban population heat exposure levels and can furnish city administrators with more scientifically rigorous evidence.

Anticipating older populations' health risk exacerbated by compound disasters based on mortality caused by heart diseases and strokes

The health of older populations in the Southeastern U.S. receives threats from recurrent tropical cyclones and extreme heat, which may exacerbate the mortality caused by heart diseases and strokes. Such threats can escalate when these extremes form compound disasters, which may be more frequent under climate change. However, a paucity of empirical evidence exists concerning the health threats of compound disasters, and anticipations regarding the health risks of older populations under future compound disaster scenarios are lacking. Focusing on Florida, which has 67 counties and the second-largest proportion of older populations among U.S. states, we calibrate Poisson regression models to explore older populations' mortality caused by heart diseases and strokes under single and compound disasters. The models are utilized to estimate the mortality across future disaster scenarios, the changing climate, and the growing population. We identify that under multiple hurricanes or heat, current-month hurricanes or heat can affect mortality more heavily than previous-month hurricanes or heat. Under future scenarios, co-occurring hurricanes and extreme heat can exacerbate the mortality more severely than other disaster scenarios. The same types of compound disasters can coincide with an average of 20.5% higher mortality under RCP8.5-SSP5 than under RCP4.5-SSP2. We assess older populations' future health risks, alerting health agencies to enhance preparedness for future "worst-case" scenarios of compound disasters and proactively adapt to climate change.

Impacts of exposure to humidex on cardiovascular mortality: a multi-city study in Southwest China

BACKGROUND

Many studies have reported the association between ambient temperature and mortality from cardiovascular disease (CVD). However, the health effects of humidity are still unclear, much less the combined effects of temperature and humidity. In this study, we used humidex to quantify the effect of temperature and humidity combined on CVD mortality.

METHODS

Daily meteorological, air pollution, and CVD mortality data were collected in four cities in southwest China. We used a distributed lag non-linear model (DLNM) in the first stage to assess the exposure-response association between humidex and city-specific CVD mortality. A multivariate meta-analysis was conducted in the second stage to pool these effects at the overall level. To evaluate the mortality burden of high and low humidex, we determined the attributable fraction (AF). According to the abovementioned processes, stratified analyses were conducted based on various demographic factors.

RESULTS

Humidex and the CVD exposure-response curve showed an inverted "J" shape, the minimum mortality humidex (MMH) was 31.7 (77th percentile), and the cumulative relative risk (CRR) was 2.27 (95% confidence interval [CI], 1.76-2.91). At extremely high and low humidex, CRRs were 1.19 (95% CI, 0.98-1.44) and 2.52 (95% CI, 1.88-3.38), respectively. The burden of CVD mortality attributed to non-optimal humidex was 21.59% (95% empirical CI [eCI], 18.12-24.59%), most of which was due to low humidex, with an AF of 20.16% (95% eCI, 16.72-23.23%).

CONCLUSIONS

Low humidex could significantly increase the risk of CVD mortality, and vulnerability to humidex differed across populations with different demographic characteristics. The elderly (> 64 years old), unmarried people, and those with a limited level of education (1-9 years) were especially susceptible to low humidex. Therefore, humidex is appropriate as a predictor in a CVD early-warning system.

Assessing future heat stress across China: combined effects of heat and relative humidity on mortality

This study utilizes China's records of non-accidental mortality along with twenty-five simulations from the NASA Earth Exchange Global Daily Downscaled Projections to evaluate forthcoming heat stress and heat-related mortality across China across four distinct scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The findings demonstrate a projected escalation in the heat stress index (HSI) throughout China from 2031 to 2100. The most substantial increments compared to the baseline (1995-2014) are observed under SSP5-8.5, indicating a rise of 7.96°C by the year 2100, while under SSP1-2.6, the increase is relatively modest at 1.54°C. Disparities in HSI growth are evident among different subregions, with South China encountering the most significant elevation, whereas Northwest China exhibits the lowest increment. Projected future temperatures align closely with HSI patterns, while relative humidity is anticipated to decrease across the majority of areas. The study's projections indicate that China's heat-related mortality is poised to surpass present levels over the forthcoming decades, spanning a range from 215% to 380% from 2031 to 2100. Notably, higher emission scenarios correspond to heightened heat-related mortality. Additionally, the investigation delves into the respective contributions of humidity and temperature to shifts in heat-related mortality. At present, humidity exerts a greater impact on fluctuations in heat-related mortality within China and its subregions. However, with the projected increase in emissions and global warming, temperature is expected to assume a dominant role in shaping these outcomes. In summary, this study underscores the anticipated escalation of heat stress and heat-related mortality across China in the future. It highlights the imperative of emission reduction as a means to mitigate these risks and underscores the variances in susceptibility to heat stress across different regions.

Future temperature-related excess mortality under climate change and population aging scenarios in Canada

OBJECTIVE

Climate change is expected to increase global temperatures. How temperature-related mortality risk will change is not completely understood, and how future demographic changes will affect temperature-related mortality needs to be clarified. We evaluate temperature-related mortality across Canada until 2099, accounting for age groups and scenarios of population growth.

METHODS

We used daily counts of non-accidental mortality for 2000 to 2015 for all 111 health regions across Canada, incorporating in the study both urban and rural areas. A two-part time series analysis was used to estimate associations between mean daily temperatures and mortality. First, current and future daily mean temperature time series simulations were developed from Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from past and projected climate change scenarios under Shared Socioeconomic Pathways (SSPs). Next, excess mortality due to heat and cold and the net difference were projected to 2099, also accounting for different regional and population aging scenarios.

RESULTS

For 2000 to 2015, we identified 3,343,311 non-accidental deaths. On average, a net increase of 17.31% (95% eCI: 13.99, 20.62) in temperature-related excess mortality under a higher greenhouse gas emission scenario is expected for Canada in 2090-2099, which represents a greater burden than a scenario that assumed strong levels of greenhouse gas mitigation policies (net increase of 3.29%; 95% eCI: 1.41, 5.17). The highest net increase was observed among people aged 65 and over, and the largest increases in both net and heat- and cold-related mortality were observed in population scenarios that incorporated the highest rates of aging.

CONCLUSION

Canada may expect net increases in temperature-related mortality under a higher emissions climate change scenario, compared to one assuming sustainable development. Urgent action is needed to mitigate future climate change impacts.

Effects of pollen concentration on allergic rhinitis in children: A retrospective study from Beijing, a Chinese megacity

With global climate change and rapid urbanization, the prevalence of allergic diseases caused by pollen is rising dramatically worldwide with unprecedented complexity and severity, especially for children in mega-cities. However, because of the lack of long time-series pollen concentrations data, the accurate evaluation of the impact of pollen on allergic rhinitis (AR) was scarce in the Chinese metropolis. A generalized additive model was used to assess the effect of pollen concentration on pediatric AR outpatient visits in Beijing from 2014 to 2019. A stratified analysis of 10 pollen species and age-gender-specific groups was also conducted during the spring and summer-autumn peak pollen periods separately. Positive associations between pollen concentration and pediatric AR varied with the season and pollen species were detected. Although the average daily pollen concentration is higher during the spring tree pollen peak, the influence was stronger at the summer-autumn weed pollen peak with the maximum relative risk 1.010 (95% CI 1.009, 1.011), which was higher than the greatest relative risk, 1.003 (95% CI 1.002, 1.004) in the spring peak. The significant adverse effects can be sustained to lag10 during the study period, and longer in the summer-autumn peak (lag13) than in the spring peak (lag8). There are thresholds for the health effects and they varied between seasons. The significant effect appeared when the pollen concentration was higher than 3.74 × 105 grain·m-2·d-1 during the spring tree pollen peaks and 4.70 × 104 grain·m-2·d-1 during the summer-autumn weed pollen peaks. The stratified results suggested that the species-specific effects were heterogeneous. It further highlights that enough attention should be paid to the problem of pollen allergy in children, especially school-aged children aged 7-18 years and weed pollen in the summer-autumn peak pollen period. These findings provide a more accurate reference for the rational coordination of medical resources and improvement of public health.

Projections of temperature-associated mortality risks under the changing climate in an ageing society

OBJECTIVES

This study aimed to project future temperature-associated mortality risk and additional deaths among Taiwan's elderly (aged >65 years) population.

STUDY DESIGN

This study investigated retrospective temperature-mortality risk associations and future mortality projections.

METHODS

A distributed lag non-linear model and random effect meta-analyses were employed to assess the risk of daily temperature-associated deaths in all-cause, circulatory, and respiratory diseases. Using the statistical downscaling temperature projections of the Representative Concentration Pathways (RCPs; i.e. RCP2.6, RCP6.0 and RCP8.5), future risk of mortalities were projected among the elderly for 2030-2039, 2060-2069 and 2090-2099, with a 30%, 40% and 50% expected increase in elderly population proportions, respectively.

RESULTS

The baseline analysis from 2005 to 2018 identified that Taiwan's population is more vulnerable to cold effects than heat, with the highest cold-related mortality risk being attributed to circulatory diseases, followed by all-cause and respiratory diseases. However, future projections suggest a declining trend in cold-related mortalities and a significant rise in heat-related mortalities under different RCP scenarios. Heat-attributable mortalities under the RCP8.5 scenario by 2090-2099 would account for almost 170,360, 36,557 and 29,386 additional annual deaths among the elderly due to all-cause, circulatory and respiratory diseases, respectively. Heat-attributable all-cause mortalities among the elderly would increase by 3%, 11% and 30% under RCP2.6, RCP6.0 and RCP8.5, respectively, by 2090-2099.

CONCLUSIONS

The findings of this study provide predictions on future temperature-related mortality among the elderly in a developed, ageing society with a hot and humid climate. The results from this study can guide public health interventions and policies for climate change and ageing society-associated health risks.

How does 2D and 3D of urban morphology affect the seasonal land surface temperature in Island City? A block-scale perspective

The global climate warming caused by urbanization has significantly affected the urban environment. Whilst land surface temperature (LST) is an important factor reflecting urban temperature, previous research on LST mostly focused on two-dimensional (2D) factors and rarely mentioned about the role of three-dimensional (3D) factors, particularly the LST variation characteristics of island cities. Therefore, this study examined the seasonal variation characteristics of urban LST by analyzing the impact of 2D and 3D urban morphology factors of different urban block types on LST in Xiamen Island. The main results are as follows. First, compact low layer (CL), a block type with a higher density of low-rise buildings, has a higher LST in any season. Under the same block density (BD), the higher the block average height (BH), the lower the LST. Second, among the 2D urban morphology factors, normalized difference vegetation index (NDVI) was the main factor for cities to reduce urban LST, especially in summer, while normalized difference built-up index (NDBI) was the opposite. Different from land cities, we found a positive correlation between modified normalized difference water body index (MNDWI) and LST in autumn and winter. Third, in the 3D urban morphology factors, sky view factor (SVF) was significantly positively correlated with LST, while building fluctuation (BF) was negatively correlated. The higher the SVF, the worse the radiation shielding effect between buildings. On the contrary, the higher the BF, the higher the building undulation, and the better the building radiation shielding. These findings should provide some quantitative insights for the future construction and planning of island cities, which can be used to improve the thermal environment of island cities and support the sustainable development of cities.

The influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza activity in China

Previous research has extensively studied the seasonalities of human influenza infections and the effect of specific climatic factors in different regions. However, there is limited understanding of the influences of monsoons. This study applied generalized additive model with monthly surveillance data from mainland China to explore the influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza in China. The results suggested two influenza active periods in northern China and three active periods in southern China. The study found that the northerly advancement of East Asian Summer Monsoon (EASM) influences the summer influenza spatio-temporal patterns in both southern and northern China. At the interannual scale, the north-south converse effect of EASM on influenza activity is mainly due to the converse effect of EASM on humidity and precipitation. Within the annual scale, influenza activity in southern China gradually reaches its maximum during the summer exacerbated by the northerly advancement of EASM. Furthermore, the winter epidemic in China is related to the low temperature and humidity influenced by the East Asian Winter Monsoon (EAWM). Moreover, the active period in transition season is related partially to the large rapid temperature change influenced by the transition of EAWM and EASM. Despite the delayed onset and instability, the climatic condition influenced by the East Asian Monsoon is one of the potential key drivers of influenza activity.

Peaking Global and G20 Countries' CO2 Emissions under the Shared Socio-Economic Pathways

Mitigating climate change requires long-term global efforts. The aim of this study is to simulate the possible paths of CO₂ emissions in G20 countries and the world from 2020 to 2050, by using the STIRPAT model and SSP scenarios with different constraints (SSP baseline, SSP-3.4). The results show that: (1) the world's CO₂ emissions cannot peak in the SSP baseline scenarios, but can peak in the SSP-3.4 scenarios through four paths other than the high fossil energy consumption path; (2) for G20 countries, in the SSP baseline scenarios, 13 countries such as China, the United States, and the United Kingdom can achieve the peak, while six countries such as Argentina, India, and Saudi Arabia cannot. In the SSP-3.4 scenarios, Saudi Arabia cannot achieve the peak, while other countries can achieve the peak, and most of them are likely to achieve significant CO₂ emission reductions by 2050; (3) climate goals have a crowding-out effect on other sustainable development goals, with less impact on developed countries and a greater impact on developing countries; and (4) the optimization of the energy structure and a low energy intensity can greatly advance the peak time of CO₂ emissions.

Characterizing Spatial Patterns of the Response Rate of Vegetation Green-Up Dates to Land Surface Temperature in Beijing, China (2001–2019)

The phenology indicator of vegetation green-up dates (GUD) is prone to being affected by changes in temperature. However, the influencing degree of urbanization-induced temperature warming on vegetation GUDs among different vegetation species along the urban-rural gradient remains inadequately described. In this study, based on the long-term (2001–2019) satellite-derived vegetation GUDs and nighttime land surface temperature (LST) of forests, grasslands, and croplands along the urban-rural gradient with Beijing (China) as a case study area, the responses of vegetation GUDs to temperature changes were quantitatively analyzed, taking into account the vegetation types and distances away from the urban domain. The results show that (1) long-term GUDs and LST are significantly negatively correlated, characterized by a weaker significant correlation near the urban area when compared with its surrounding areas, with the greatest absolute linear correlation coefficients (r) happening at rings 32 km (rmax = −0.93, forests), 20 km and 48 km (rmax = −0.83, grasslands), and 34 km (rmax = −0.82, croplands), respectively; (2) the magnitude of change in GUDs over the past 19 year (2001–2019) are significantly positively correlated with these in LST near the urban area, demonstrating a distance-decay trend, with the greatest advance in GUDs occurring at the ring nearest the urban area, by about 20 days (forests), 24.5 days (grasslands), and 15.6 days (croplands), respectively; (3) the spatial pattern of the response rate of GUDs change to LST change (days K−1) also showed a declining trend with distance, with GUD advanced by 6.8 days K−1 (forests), 7.5 days K−1 (grasslands), and 4.9 days K−1 (croplands) at the closest ring to the urban, decreasing to about 2.3 days K−1 (48 km), 4.1 days K−1 (18 km), and 1 day K−1 (18 km), respectively, indicating a notable influence of temperature warming on vegetation GUDs near the urban domains.