Coastal vulnerability to climate change in China's Bohai Economic Rim

Future sea level rise exacerbates compound floods induced by rainstorm and storm tide during super typhoon events: A case study from Zhuhai, China

Compound floods are becoming a growing threat in coastal cities against a background of global sea level rise (SLR), and may cause increasing impacts on societal safety and economy. How to quantify the impact of SLR and compound effects among various flood causes on compound flood have become important challenges. We propose a modeling framework which integrates atmospheric, storm tide and urban flood (IASTUF) models to characterize the various physical processes related to compound flood. Future SLR projections under various shared socioeconomic and respective concentration pathway emission scenarios are considered. Hengqin Island (Zhuhai City, China) frequently experiences typhoon conditions combined with rainstorm and storm surge events. Its population has increased more than sixfold during the past decade, stimulating urgent demands for assessments of the potential risks associated with future compound floods in the context of potential SLR. A compound flood event in northern Hengqin Island, caused by the super typhoon Mangkhut in 2018, is selected as a case study to verify the proposed modeling framework. Results show that the IASTUF modeling framework can capture well the combined processes of typhoon, rainstorm, storm tide and inland flooding and demonstrates good performance in quantifying compound flood magnitudes. Compared to the current scenario, the node flooding volume (from the drainage system) and the maximum inundation area (with inundation depths >1 m) in 2050 are projected to increase by 20-26 % and 41-85 %, respectively, and these increases rise to 46-84 % and 23-71 times by 2100. The inundation volumes and water depths due to compound events are larger than the sum of those caused by the corresponding single-cause events, indicating that concurrent rainstorm and storm surge induce positive compound effects on flood magnitude. These findings can provide guidance for the management and mitigation of future compound flood hazards driven by super typhoon events.

Spatial-temporal evolution of carbon emissions and spatial-temporal heterogeneity of influencing factors in the Bohai Rim Region, China

The total change in carbon emissions in the Bohai Rim Region (BRR) plays a guiding role in the policy formulation of carbon emission reduction in northern China. Taking the 43 cities in the BRR as an example, the spatial-temporal evolution of carbon emissions in the BRR was analyzed using kernel density estimation (KDE), map visualization, and standard deviation ellipses, and the spatial autocorrelation model was used to explore the spatial clustering of carbon emissions. On this basis, the spatial-temporal heterogeneity of the factors influencing carbon emissions is explained using a Geodetector. The results are as follows: (i) During the study period, the carbon emissions in the BRR were on the rise, the share of carbon emissions in the Beijing-Tianjin-Hebei region (BTHR) and Liaoning Province was decreasing, and the contribution of Shandong Province was gradually enhanced. The spatial distribution of carbon emissions shows a geographical pattern of "middle-high and low-outside." (ii) Carbon emissions from different regions show the characteristics of BTHR > Shandong Province > Liaoning Province. The high-value carbon emission area continues to move from the northwest of Beijing-Tianjin-Hebei to the southeast. (iii) Municipal carbon emissions showed a significant positive spatial correlation in the later part of the study. The high-high aggregation area is in Tianjin, and the low-low aggregation area is in Liaoning Province. (iv) The level of transport development contributes to carbon emissions with the highest growth rate, followed by industrial structure. There are also regional differences in the dominant influences on municipal carbon emission differences. Population size, urbanization, and economic development level are the core influencing factors of carbon emissions in the BTHR, Shandong Province, and Liaoning Province, respectively. In addition, the explanatory power of the interaction between the level of economic development and other factors on carbon emissions is at a high level.

A synthetic water-heat-vegetation biodiversity nexus approach to assess coastal vulnerability in eastern China

Climate change pressure and biodiversity degradation in coastal regions have caused an increase in urban vulnerability. Current coastal vulnerability studies fail to consider the interactions among the perturbations. Increases in such interactions contribute to the indeterminate changes in the ecosystem productivity and impact on human well-being. Therefore, by integrating water, heat, and vegetation biodiversity (WHB) indicators using catastrophe theory in the study, the interaction among subsystems was explored to expound on the multi-effect of the urban. The results showed that (1) the overall vulnerability of China's coastal cities has increased, and high-value areas were mainly distributed in the three southern provinces; (2) the spatial-temporal pattern of vulnerability was highly heterogeneous. As low-low clusters, Shanghai and its surrounding cities exhibited spatial aggregation characteristics; (3) social, physical and financial capitals were the first three main adaptive capacity factors. The distance-based linear model (DistLM) evidenced that per capita GDP, and road density explained about 30 % and 10 % of the difference in vulnerability variation. The proposed framework could help decision-makers detect how vulnerable coastal areas exposed to WHB impacts are, with crucial implications for future sustainable management.

Risk mapping of Indian coastal districts using IPCC-AR5 framework and multi-attribute decision-making approach

Strategic location of coastal areas across the world causes them to be prone to disaster risks. In the global south, the Indian coast is one of the most susceptible to oceanic extreme events, such as cyclones, storm surge and high tides. This study provides an understanding of the risk experienced (currently as well as back in 2001) by the districts along the Indian coastline by developing a quantitative risk index. In the process, it attempts to make a novel contribution to the risk literature by following the definition of risk as a function of hazard, exposure and vulnerability as stated in the most recent (Fifth) assessment report of the Intergovernmental Panel on Climate Change (IPCC). Indicators of bio-physical hazards (such as cyclones, storm surge, tides and precipitation), and socio-economic contributors of vulnerability (such as infrastructure, technology, finance and social nets) and exposure (space), are combined to develop an overall risk index at a fine administrative scale of district-level over the entire coastline. Further, the study employs a multi-attribute decision-making (MADM) method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to combine the contributing indicators and generate indices on hazard, exposure and vulnerability. The product of these three components is thereafter defined as risk. The results suggest that most districts of the eastern coast have higher risk indices compared to those in the west, and the risk has increased since 2001. The higher risk can be attributed to the higher hazard indices in the eastern districts which are aggravated by their higher vulnerability index values. This study is the first effort made to map risk for the entire coastline of India - which in turn has resulted in a new cartographic product at a district-scale. Such assessments and maps have implications for environmental and risk-managers as they can help identify the regions needing adaptive interventions.

Assessment of Regional Health Vulnerability to Extreme Heat - China, 2019

What is already known on this topic?

The health risk caused by high-temperatures depends on the interaction between high temperature exposure and the sensitivity and adaptability of the affected populations.

What is added by this report?

A comprehensive assessment model was established by principal component analysis using the data of 19 cities, 15 provincial-level administrative divisions and used to identify regional characteristics and major influencing factors of health vulnerability to extreme heat in China.

What are the implications for public health practice?

The results of the health vulnerability assessment could effectively identify the regions highly vulnerable to extreme heat in China and provide scientific evidence for the development of adaptive measures and resource allocation plans.

Association between ambient particulate matter exposure and platelet counts in adults: a retrospective cohort study

Associations between ambient particulate matter exposure and platelet counts are inconsistent in previous studies, and study on the effect of long-term exposure especially in Asian populations is limited. We explored the associations between long-term PM2.5 (particulate matter < 2.5 μm) exposure and platelet counts using a prospective cohort study in Northeast China. We used a logistic regression model to analyze the effects of different PM2.5 increments and platelet count elevation. Mixed linear models were used to analyze the association between PM2.5 concentration and platelet counts. Interaction and sub-group analyses were also conducted. Results showed that every 1 μg/m3 increment of PM2.5 exposure was associated with 0.29% (95%CI: 0.25-0.32%) increase in platelet counts and 10% (95%CI: 8-12%) higher risk of platelet elevation. Effects of long-term PM2.5 exposure on platelet elevation were stronger in male participants, of Han ethnicity, and without diabetes. Long-term PM2.5 exposure would increase platelet counts in adults in Northeast area of China, which might add more evidence to the potential biological mechanisms responsible for the effect of air pollution exposure on cardiovascular disease.