Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region

Site Selection of Urban Parks Based on Fuzzy-Analytic Hierarchy Process (F-AHP): A Case Study of Nanjing, China

The scientific siting of urban parks is critical for sustainable urban environment development, and this study aimed to identify suitable areas for future urban parks in Nanjing, China. This study has integrated geographic information systems (GIS) and fuzzy hierarchical analysis (F-AHP) in order to evaluate the suitability of the site selection of urban parks in Nanjing, China. Different physical, natural, environmental, accessibility, and human activity factors were evaluated in order to assess the suitability of a park site. The results revealed that 5% were highly suitable for urban park site selection, 36% were more suitable, 32% were moderately suitable, 19% were less suitable, and 8% were unsuitable for urban park site selection. The findings suggest that the areas that are highly suitable for urban park placement are located in the western and eastern parts of Nanjing. Carbon storage was the most important factor in the suitability of urban park site selection, followed by the normalized difference vegetation index (NDVI) and the heat-island effect. The methodology that has been adopted in this study helps to improve the methodological framework of combining F-AHP and GIS; in addition, generating urban park site selection maps assists planners and decision-makers in making scientific site selection decisions.

Evaluating the Spatial Risk of Bacterial Foodborne Diseases Using Vulnerability Assessment and Geographically Weighted Logistic Regression

Foodborne diseases are an increasing concern to public health; climate and socioeconomic factors influence bacterial foodborne disease outbreaks. We developed an “exposure–sensitivity–adaptability” vulnerability assessment framework to explore the spatial characteristics of multiple climatic and socioeconomic environments, and analyzed the risk of foodborne disease outbreaks in different vulnerable environments of Zhejiang Province, China. Global logistic regression (GLR) and geographically weighted logistic regression (GWLR) models were combined to quantify the influence of selected variables on regional bacterial foodborne diseases and evaluate the potential risk. GLR results suggested that temperature, total precipitation, road density, construction area proportions, and gross domestic product (GDP) were positively correlated with foodborne diseases. GWLR results indicated that the strength and significance of these relationships varied locally, and the predicted risk map revealed that the risk of foodborne diseases caused by Vibrio parahaemolyticus was higher in urban areas (60.6%) than rural areas (20.1%). Finally, distance from the coastline was negatively correlated with predicted regional risks. This study provides a spatial perspective for the relevant departments to prevent and control foodborne diseases.

Fuzzy-Based Ecological Vulnerability Assessment Driven by Human Impacts in China

Human activities have a significant impact on global ecosystems. Assessing and quantifying ecological vulnerability is a fundamental challenge in the study of the ecosystem’s capacity to respond to anthropogenic disturbances. However, little research has been conducted on EVA’s existing fuzzy uncertainties. In this paper, an ecological vulnerability assessment (EVA) framework that integrated the Exposure-Sensitivity-Adaptive Capacity (ESC) framework, fuzzy method, and multiple-criteria decision analysis (MCDA), and took into account human impacts, was developed to address the uncertainties in the assessment process. For the first time, we conducted a provincial-scale case study in China to illustrate our proposed methodology. Our findings imply that China’s ecological vulnerability is spatially heterogeneous due to regional differences in exposure, sensitivity, and adaptive capacity indices. The results of our ecological vulnerability assessment and cause analysis can provide guidance for further decision-making and facilitate the protection of ecological quality over the medium to long term. The developed EVA framework can also be duplicated at multiple spatial and temporal dimensions utilizing context-specific datasets to assist environmental managers in making informed decisions.

A Cost Allocation Decision Model for Air Pollution Control

Air pollution control as the background of a cost allocation method is based on the Shapley value to determine the core stakeholder, so fair pollution control projects and the establishment of the atmospheric pollution of governance cost allocation model are put forward for the solution of air pollution coordinated by the government supervision and the atmospheric pollution control collaborative group. The results show that the cost allocation model of air pollution control based on Shapley value is more reasonable, and the cost of stakeholders is reduced to a certain extent, and the risk of the participants is reduced so that it maximizes social benefits.

Urban agglomeration worsens spatial disparities in climate adaptation

Many countries promote urban agglomeration to enhance economic competitiveness, but the impacts of this strategy on local climate adaptation remain poorly understood. Here, we use variation in greenspaces to test the effectiveness of climate adaptation policy across climate impacts and vulnerability dimensions. Using satellite imagery and logistic regression, we analyze spatiotemporal correlation between greenspace and climate vulnerability in the Guangdong-Hong Kong-Macau Greater Bay Area, an area comprising ~ 70 million people and 11 cities, making it a useful natural experiment for our study. We find that while greenspace increases proportionally with climate exposure and sensitivity, many cities exhibit discrepancies between greenspace variation and climate vulnerability. Green adaptation funnels into wealthier, less vulnerable areas while bypassing more vulnerable ones, increasing their climate vulnerability and undermining the benefits of urban agglomeration. The results suggest that centrally-planned climate adaptation policy must accommodate local heterogeneity to improve urban sustainability. By neglecting local heterogeneity, urban agglomeration policy risks exacerbating spatial inequalities in climate adaptation.

Assessing the Effects of Desertification Control Projects from the Farmers' Perspective: A Case Study of Yanchi County, Northern China

Desertification has inflicted severe damage on the natural environment and social economy for decades, particularly in the arid and semi-arid regions of northern China. In Yanchi County, a series of projects were implemented to combat desertification after 2000. To assess the effects of these Desertification Control Projects from the farmers’ perspective, we divided Yanchi County into two regions (the northern and southern regions) according to their different environmental conditions. We collected data including basic family information, farmers’ perceptions and attitudes, and farmers’ suggestions, in a questionnaire investigation following the Participatory Rural Appraisal approach. Data analysis using the Mann–Whitney U test and Fisher’s exact test revealed that the Desertification Control Projects were generally successful, as the local environment and farmers’ incomes were both improved. Farmers were all satisfied with the effects of the projects, but the farmers in the southern region had a higher acceptance of the projects than those in the northern region. In addition, three problems with the Desertification Control Projects were noted: the farmers had a low degree of participation in the projects, the farmer’s low incomes affected the sustainability of the projects, and the implementation of the complete grazing ban had several adverse effects. We provided suggestions for solving these problems. Our findings have important implications for assessing the effects of environmental conservation projects, especially from a participant’s perspective.

Livelihood Vulnerability of Marine Fishermen to Multi-Stresses under the Vessel Buyback and Fishermen Transfer Programs in China: The Case of Zhoushan City, Zhejiang Province

In the context of vessel buyback and fishermen transfer, some traditional marine fishermen changed their profession and turned to other related industries such as mariculture, fish processing, and recreational fishery. Studying the livelihood vulnerability of different types of fishermen is an important basis to help fishermen rebuild sustainable livelihoods. This paper developed a framework of a fishermen’s livelihood vulnerability assessment under multi-stresses, and then conducted an empirical analysis based on a survey in Zhoushan City, Zhejiang Province, China. Finally, the determinants of livelihood vulnerability were analyzed by a regression tree model. Results showed that fishermen with a high level of vulnerability accounted for about 37.35%, and they had some unique characteristics such as advanced age, low education levels. Although converted fishermen faced fewer exposure risks than non-converted fishermen, they eventually showed higher vulnerability due to poor adaptive ability. The livelihood vulnerability of fishermen engaged in recreational fisheries was relatively low, while that of fishermen engaged in non-fisheries was quite different from each other. The results of the regression tree analysis showed that the number of household income sources, whether they converted or not, impacts of disturbances, and whether they were equipped with fishery facilities could influence the fishermen’s livelihood vulnerability. The government should pay more attention to the fishermen whose family income source was single, and the converted fishermen whose productive physical capital was scare.