International progress and evaluation on interactive coupling effects between urbanization and the eco-environment

Fang, Chuanglin; Liu, Haimeng; Li, Guangdong

doi:10.1007/s11442-016-1317-9

Cited by 209 publications

(87 citation statements)

References 239 publications

(219 reference statements)

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“…Ambient (outdoor) air pollution usually refers to the phenomenon that due to human activities or natural processes, some substances enter the air and endanger the comfort, health, and welfare of the human body when they remain in the air at a high concentration for a long time [1,2]. With the continuous acceleration of the urbanization process, PM 2.5 has become one of the major pollutants of smog outbreaks [3,4].…”

Section: Introductionmentioning

confidence: 99%

Estimates of Daily PM2.5 Exposure in Beijing Using Spatio-Temporal Kriging Model

et al. 2018

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Excessive exposure to ambient (outdoor) air pollution may greatly increase the incidences of respiratory and cardiovascular diseases. Accurate reports of the spatial-temporal distribution characteristics of daily PM2.5 exposure can effectively prevent and reduce the harm caused to humans. Based on the daily average concentration data of PM2.5 in Beijing in May 2014 and the spatio-temporal kriging (STK) theory, we selected the optimal STK fitting model and compared the spatial-temporal prediction accuracy of PM2.5 using the STK method and ordinary kriging (OK) method. We also reveal the spatial-temporal distribution characteristics of the daily PM2.5 exposure in Beijing. The results show the following: (1) The fitting error of the Bilonick model (BM) model which is the smallest (0.00648), and the fitting effect of the prediction model of STK is the best for daily PM2.5 exposure. (2) The cross-examination results show that the STK model (RMSE = 8.90) has significantly lower fitting errors than the OK model (RMSE = 10.70), so its simulation prediction accuracy is higher. (3) According to the interpolation of the STK model, the daily exposure of PM2.5 in Beijing in May 2014 has good continuity in both time and space. The overall air quality is good, and overall the spatial distribution is low in the north and high in the south, with the highest concentration in the southwestern region. (4) There is a certain degree of spatial heterogeneity in the cumulative duration at the good, moderate, and polluted grades of China National Standard. The areas with the longest cumulative duration at the good, moderate and polluted grades are in the north, southeast, and southwest of the study area, respectively.

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Section: Introductionmentioning

confidence: 99%

Estimates of Daily PM2.5 Exposure in Beijing Using Spatio-Temporal Kriging Model

et al. 2018

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“…For example, various environmental pollution and serious destruction of resources often occur in or around cities with concentrated population [4]. This may be the stress effect of urbanization on the ecological environment as demonstrated by many previous studies [10,11]. With the increase of a terrain gradient, the ecosystem health condition gradually improved.…”

Section: Temporal-spatial Relationship Between Esh and Himentioning

confidence: 96%

“…Therefore, the research on urbanization and the ecological environment system has become a hot topic in the academic field. Fang et al [10] created the theoretical framework of the interaction coupling effect between urbanization and the ecological environment. Liu et al [11] revealed the stress effect of urbanization by human activities on the ecological environment and the constraint effect of the ecological environment on urbanization.…”

Section: Introductionmentioning

confidence: 99%

Temporal–Spatial Distribution of Ecosystem Health and Its Response to Human Interference Based on Different Terrain Gradients: A Case Study in Gannan, China

2020

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The exploitation, utilization, and protection of land resources are some of the great social problems during the process of rapid urbanization in China. The status of land use directly affects ecosystem health (ESH). The evaluation of ESH and the spatial correlations between urbanization caused by human interference help us to analyze the influence of urbanization on ecosystems and also provide new insight into reasonable and scientific resource management. In this study, we evaluated the ESH of Gannan, in Jiangxi Province, China, based on ecosystem service values (ESV) and selected a series of indicators to detect the impact of urbanization on ecosystem health in 1990, 1995, 2000, 2005, 2010. and 2015. Remote sensing (RS) and the Geographic Information System (GIS) were used as processing tools to calculate basic data and to map the results based on different terrain gradients. The results show that ecosystem health suffered a downward trend from 1990 to 2015. Especially, the area proportion at an unhealthy level and average health (ave-health) level increased prominently, and the area of a well state decreased. Further, the results indicate that urbanization had a negative impact on ESH. The degree of a negative correlation increases with the process of urban sprawl. In addition, we found that from 1990 to 2015, the area proportion of a degraded level and unhealthy level was the highest on the first terrain gradient, and as the terrain gradient increased, this area proportion also decreased. However, the high interference region occupies a higher proportion in the lower terrain gradient. Consequently, the results could reveal the impact of urbanization on ecosystem health and could provide an even more effective service for a sustainable development.

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“…[4]. The impact of human activities is mainly reflected through land use change [5]. Current changes in river runoff vary on different scales and the report of IPCC (Intergovernmental Panel on Climate Change) in 2013 predicted that global climate change is likely to exert substantial impacts on surface water resource across the world [6].…”

Section: Introductionmentioning

confidence: 99%

Trends of Runoff Variation and Effects of Main Causal Factors in Mun River, Thailand During 1980–2018

Huang

et al. 2020

Water

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Mun River is the largest tributary of the Mekong River in Thailand and provides abundant water resources not only for an important agricultural area in Thailand but also for the lower Mekong River. To understand how the runoff of Mun River responds to climate change and human activities in recent decades, this study performed a detailed examination of the characteristics of runoff variation based on measurements at two hydrological gauging stations on the main stem of Mun River during 1980–2018. Using the Mann-Kendall test, Morlet wavelet transform and Double Cumulative Curve methods, this study identifies that the variation of annual runoff of Mun River encountered an abruption in 1999/2000, with an increased trend taking place since then. Furthermore, a detailed assessment of the effects of the variations in rainfall, temperature, evaporation, and land use types extracted from remote sensing images at the basin scale reveals that a significant reduction in forest area and slight reductions in evaporation and farmland area taking place since 1999 can lead to an increase in the runoff of Mun River, while the dramatic increase in garden area since 1999 tends to make the runoff decrease.

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International progress and evaluation on interactive coupling effects between urbanization and the eco-environment

Cited by 209 publications

References 239 publications

Estimates of Daily PM2.5 Exposure in Beijing Using Spatio-Temporal Kriging Model

Estimates of Daily PM2.5 Exposure in Beijing Using Spatio-Temporal Kriging Model

Temporal–Spatial Distribution of Ecosystem Health and Its Response to Human Interference Based on Different Terrain Gradients: A Case Study in Gannan, China

Trends of Runoff Variation and Effects of Main Causal Factors in Mun River, Thailand During 1980–2018

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