Natural-anthropogenic environment interactively causes the surface urban heat island intensity variations in global climate zones.

The inconstant climate change and rapid urbanization substantially disturb the global thermal balance and induce severe urban heat island (UHI) effect, adversely impacting human development and health. Existing literature has revealed the UHI characteristics and driving factors at an urban scale, but interactions between the main factors of a global grid scale assessment on the context of climate zones remain unclear. Therefore, based on the multidimensional climatic and socio-economic statistical datasets, the multi-time scale of surface urban heat island intensity (SUHI) characteristics was investigated in this study to analyze how natural-anthropogenic drivers affect the variance of SUHI and vary in their importance for the changes of other interaction factors. The results show that the mean value of SUHI in summer is higher than in winter, and in daytime is higher than in nighttime on a seasonal and daily scale. SUHIs in different global climate zones have significant differences. When analyzing drivers' contributions and interactions with LightGBM model and SHAP algorithm, we know that monthly precipitation (PREC), the estimated population (POP) and surface pressure (PRES) are the three major drivers of daytime SUHI. The nighttime SUHI is mainly PREC, POP and anthropogenic heat emission (AHE), the influence rules of the natural driversare mostly opposite to that of daytime. This study highlights the fundamental role of background climate for designing strategies. Irrigation or artificial rainfall will be effective to mitigate SUHI in low rainfall areas, while it is more effective to reduce AHE in high rainfall areas. In where greening can be difficult in the most developed cities, reducing AHE, increasing per capita GDP and controlling the population scale may also contribute to alleviating the SUHI. This study provides ideas for developing responsive urban heat island mitigation policies in a more realistic setting.

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.

The influence of local background climate on the dominant factors and threshold-size of the cooling effect of urban parks.

Urban parks can mitigate the urban heat island (UHI) by creating microclimates that lower in temperature than their surroundings, which are known as park cooling effect (PCE). The local background climate has a significant impact on the PCE, however the dominant factors and threshold value of efficiency (TVoE) of the PCE under different local background climates are still uncertain. Here, we selected 207 urban parks in 27 cities in East China with four different local background climates, warm temperate sub-humid monsoon (WTC), northern subtropical sub-humid monsoon (NSC), northern subtropical humid monsoon (NHC), and middle subtropical humid monsoon climate (MSC), for comparative studies. The relative contributions of multi-influencing factors to the PCE and TVoE of urban parks were quantified through a multivariate stepwise regression model and curve fitting. The results show that: (1) PCE increases from WTC, NSC, NHC to MSC, and urban parks at low latitudes have a greater cooling effect in general than those at high latitudes; (2) the area of the park is the dominant factor of PCE under four different local background climates (the explanation rate exceeds 50%) and water bodies within urban parks play a more significant role in the cooling effect in high latitudes, dry areas; (3) the TVoE of park on WTC, NSC, NHC, and MSC are 0.81, 0.71, 0.70, and 0.66 ha, respectively, revealing that the background climate significantly affects the TVoE. These findings are essential to decision-makers and can provide actionable knowledge for climate adaptation planning on a regional (climate) scale.

Health risk assessment of heavy metal(loid)s in park soils of the largest megacity in China by using Monte Carlo simulation coupled with Positive matrix factorization model.

Urban Parks are important places for residents to engage in outdoor activities, and whether heavy metal(loid)s (HMs) in park soils are harmful to human health has aroused people's concern. A total of 204 topsoil samples containing nine HMs were collected from 78 urban parks of Shanghai in China, and used to assess the health risks caused by HMs in soils. The results revealed that the Hg, Cd and Pb were the main enriched pollutants and posed higher ecological risks than the other HMs. Four HM sources (including natural sources, agricultural activities, industrial production and traffic emissions) were identified by combining the Positive matrix factorization model and Correlation analysis, with the contribution rate of 48.24%, 7.03%, 13.04% and 31.69%, respectively. The assessment of Probabilistic health risks indicated that the Non-carcinogenic risks for all populations were negligible. However, the Total carcinogenic risk cannot be negligible and children were more susceptible than adults. The assessment results of source-oriented health risks showed that industrial production and traffic emissions were estimated to be the most important anthropogenic sources of health risks for all populations. Our results provide scientific support needed for the prevention and control of HM pollution in urban parks.