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| 基于粤港澳大湾区市域尺度的绿地空间格局、局地大气因素与居民呼吸健康三者之
间的作用机制研究 |
| 冯娴慧,何慕 |
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| 作者简介：冯娴慧
1977年生/女/云南曲靖人/博士/华南理工大学建筑学院教授/研究
方向为绿地对微气候作用机制、绿地的健康作用/本刊特约编辑
(广州 510640) |
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| 摘要: |
| 绿地空间格局、局地大气因素、居民呼吸健康是风景园林研究的重要领域，前人大多研究已证实三者中任两者之间存在相关性。分析了三者之间的直接
或间接作用机制及影响路径。选取粤港澳大湾区的7个城市，采用表征植被的NDVI、LAI，以及表征景观格局的COHESION等12项绿地空间格局指标，采用气
温、风速等4项气候指标和4项大气污染指标表征局地大气因素，采用肺癌发病率、死亡率表征居民呼吸健康，通过多元线性回归模型分析三者之间的相关性，通
过偏最小二乘结构方程模型(PLS-SEM)、Bootstrap自助法研究三者之间的中介效应和调节效应。结果表明，绿地空间格局、大气因素、肺癌三者之间在一些指
标中存在相关性。中介效应表现为NDVI通过影响空气污染，间接影响肺癌状况，当CONTIG、SHAPE、SHDI指数作为调节变量时，显著增强了风速对发病率
的负相关性影响；当气温作为调节变量时，显著增强COHESION、LPI、AI、PLAND指数对发病率的负相关性影响。因此，提升绿地聚集度、形态多样性，不
仅影响气温和风速，还能构建出直接或间接路径以降低肺癌发病率和死亡率。 |
| 关键词: 风景园林 绿地空间格局 大气因素 呼吸健康 中介效应 调节效应 |
| DOI：10.19775/j.cla.2025.01.0015 |
| 投稿时间：2023-11-17修订日期：2024-06-25 |
| 基金项目:国家自然科学基金面上项目(51978276) |
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| Research on the Mechanism of Green Space Patterns, Local Atmospheric Factors, and Residents'Respiratory Health Based on the City Scale of Guangdong-Hong Kong-Macao Greater Bay Area |
| FENG Xianhui,HE Mu |
| Abstract: |
| Green space patterns, local atmospheric factors, and residents' respiratory
health are three essential research areas in Landscape Architecture. Respiratory health
is influenced by a multitude of complex factors, including environmental, genetic,
lifestyle, and socioeconomic conditions, with green spaces and atmospheric conditions
have a particularly impactful influence. The effects of environmental factors on
health can be modified through public policy, especially by enhancing respiratory
health through the planning and design of green spaces. Most of the research focuses
on the correlation between any two of the three, and it has been verified that there
exist various correlations such as positive correlation or negative correlation among
each pair. This study investigates the comprehension chain relationship between
the three, i.e., the complex interactions between the three directly or indirectly,
to explore the mechanism of interaction between the three as well as the path of
influence, for providing scientific evidence for the optimization of the green space
pattern, the improvement of the atmospheric environment, and the construction of a
green space planning that is conducive to the respiratory health of the residents. The
research was conducted in the Guangdong-Hong Kong-Macao Greater Bay Area,
globally recognized as a pivotal hub for urban development on China's southern coast.
Characterized by an urbanization rate of over 80% and a South Asian subtropical
monsoon climate, the area is perennially warm and humid. Specifically, the study
encompassed seven cities within the Bay Area: Guangzhou, Shenzhen, Zhuhai,
Zhongshan, Jiangmen, Hong Kong, and Macao. Twelve indicators, including that
representing the coverage degree (NDVI), green biomass (LAI), and the landscape
pattern morphology (COHESIN, LPI, SHDI) and other 12 indicators as green space
spatial pattern indicators; four climatic indicators, including air temperature, wind
speed, precipitation and relative humidity, and four atmospheric pollution indicators,
including SO2, NO? were used to characterize the local atmospheric factors; and two
indicators, namely, the lung cancer incidence rate and mortality rate, were used to
describe the respiratory health of the residents. The multivariate linear regression
model was used to analyze the relationship between green space pattern, respiratory
health, and atmospheric factors. The correlation between spatial pattern of green
space, atmospheric factors, and lung cancer status was analyzed by multiple linear
regression model; the pathways, mediating effects, and moderating effects among the
three were studied by Partial Least Squares structural equation model (PLS-SEM)
and Bootstrap method. The results show correlations between the spatial pattern of
green space, atmospheric factors, and lung cancer in some indicators. Associations
have been identified between green space configurations, atmospheric conditions, and
respiratory health outcomes involving mediating and moderating effects. Key green
space indexes, such as LAI, SHAPE, and SHDI, exhibit a strong negative correlation
with both the incidence and mortality rates of lung cancer. In contrast, elevated
concentrations of atmospheric pollutants like SO? and NO? show a robust positive
correlation with these rates, suggesting that higher levels of air pollution contribute
to increased lung cancer risks. Notably, the NDVI index, representing green space
extent, indirectly influences lung cancer outcomes by modulating air pollution levels,
confirming its role as a mediator in this relationship. Using the PLS-SEM model,
the study tested the moderating effects of various index combinations. The results
confirmed that wind speed and temperature are the only variables that effectively
serve as independent and moderating variables, respectively, in the moderation effect
models. When CONTIG, SHAPE, and SHDI indices are used as moderating variables
to characterize spatial aggregation, heterogeneity, and diversity of green space, it
was found that there is a significantly enhanced negative correlation between wind
speed among atmospheric factors on the incidence rate. From this finding, it can be
inferred that increasing the fragmentation of green spaces might reduce the beneficial
effects of wind speed on respiratory health. Conversely, enhancing the morphological
diversity of green spaces strengthens the negative association between wind speed
and incidence rates. When air temperature was used as a moderating variable, it
significantly enhanced the negative correlation effect of the COHESION, LPI, AI,
and PLAND indices, which characterize the spatial aggregation and heterogeneity of
green spaces on morbidity. The research suggests that in green space planning, while
increasing total area is important, prioritizing the development of larger, cohesive
green spaces over fragmented layouts is more effective. Effective green space
construction requires not only tree planting but the maintenance of diverse, healthy
vegetation to maximize health and environmental benefits. Enhancing vegetation
density and structure, reducing green space fragmentation, and promoting spatial
aggregation and morphological diversity can influence atmospheric conditions, such
as wind speed and temperature, while directly or indirectly reducing lung cancer
incidence and mortality. These changes not only help mitigate air pollution but also
establish pathways supporting respiratory health among residents by addressing both
environmental and health outcomes. |
| Key words: landscape architecture green space pattern atmospheric factors respiratory health mediating effect moderating effect |
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