Yaoqiu Kuang

Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery

Abstract Studies of urbanization and urban thermal environment are now attracting wide interests among scientists all over the world. This study investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Guangzhou, China utilizing three dates of Landsat TM/ETM+ images acquired in 1990, 2000, and 2005, respectively. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban enlargement. As a key parameter for studying urban thermal characteristics, the land surface temperature (LST) was also retrieved from thermal infrared band of each TM/ETM+ dataset. Based on these parameters, the urban expansion, urban heat island effect and the relationships of LSTs to other biophysical parameters were then analyzed. Results indicated that the area ratio of impervious surface in Guangzhou increased significantly, which grew from 20.56% in 1990, to 34.72% in 2000, and further to 41.12% in 2005, however, the intensity of urban heat island was not always enlarged in observed years. In addition, Geostatistical analyses showed that the mean-centre of the impervious surface was moving towards the northwest during 1990–2005. And correlation analyses revealed that, at the pixel-scale, the association of LSTs to other two variables (vegetation abundance and percent impervious surface) was not straightforward, while LSTs possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional-scale, respectively. This study provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Water pollution and degradation in Pearl River Delta, South China

Abstract The Pearl River Delta Economic Zone is the most dynamic economic area in South China. One of the major problems in the region is the sustainable utilization of the water resources. On the basis of analysis of the water environment status and pollution sources, it is suggested that domestic sewage is the primary cause of pollution. Two new concepts “degradation coefficient” and “degradation volume” of water resources, due to pollution, which may be used to assess macroscopically the carrying capacity of the water resources and sustainability of the water environment, are proposed by the authors. The results calculated indicate that the volumes of degraded water resources will be up to 204, 352, and 537 million m3 in 2002, 2010, and 2020. It is suggested that water for daily consumption and domestic sewage must be controlled more effectively and there should be cross-regional coordination in tackling problems of water environment.

Water shortage: a serious problem in sustainable development of China

SUMMARY Water crises have occurred in more than 400 cities in China at the beginning of 2000. Investigation and statistical data suggest that there are five main problems in the management and utilization of water resources in China. These are (1) insufficient capacity and inhomogeneous space-time distribution of natural resources, (2) outdated construction of water conservancy projects and supply engineering, (3) unreasonable industrial water consumption, (4) increased water pollution and (5) incomplete management of the river basin and waterworks in city. It is necessary to take steps corresponding to the above-mentioned reasons to mitigate and even dispel the pressure on water resources for sustainable development of China as quickly as possible.

CO2 emission from cement manufacturing and its driving forces in China

In China, cement manufacturing has contributed 1788.78 million metric tons of CO2 (carbon equivalent) into atmosphere in the past 35 years (1969-2003). Its driving forces were analysed by a stochastic regression model (STIRPAT), which showed that population was a key driving force and its pressure was higher than the global average level. On the other hand, economic growth had less impact, but a doubling in economic growth might result in nearly doubling in CO2 emissions. In three STIRPAT models, evidence for the existence of the Environmental Kuznets Curve (EKC) was found, with a turning point well beyond the present value.

Empirical research on decoupling relationship between energy-related carbon emission and economic growth in Guangdong province based on extended Kaya identity.

The decoupling elasticity decomposition quantitative model of energy-related carbon emission in Guangdong is established based on the extended Kaya identity and Tapio decoupling model for the first time, to explore the decoupling relationship and its internal mechanism between energy-related carbon emission and economic growth in Guangdong. Main results are as follows. (1) Total production energy-related carbon emissions in Guangdong increase from 4128 × 104 tC in 1995 to 14396 × 104 tC in 2011. Decoupling elasticity values of energy-related carbon emission and economic growth increase from 0.53 in 1996 to 0.85 in 2011, and its decoupling state turns from weak decoupling in 1996–2004 to expansive coupling in 2005–2011. (2) Land economic output and energy intensity are the first inhibiting factor and the first promoting factor to energy-related carbon emission decoupling from economic growth, respectively. The development speeds of land urbanization and population urbanization, especially land urbanization, play decisive roles in the change of total decoupling elasticity values. (3) Guangdong can realize decoupling of energy-related carbon emission from economic growth effectively by adjusting the energy mix and industrial structure, coordinating the development speed of land urbanization and population urbanization effectively, and strengthening the construction of carbon sink.

The Long-Term Relationship between Population Growth and Vegetation Cover: An Empirical Analysis Based on the Panel Data of 21 Cities in Guangdong Province, China

It is generally believed that there is an inverse relationship between population growth and vegetation cover. However, reports about vegetation protection and reforestation around the World have been continuously increasing in recent decades, which seems to indicate that this relationship may not be true. In this paper, we have taken 21 cities in Guangdong Province, China as the study area to test the long-term relationship between population growth and vegetation cover, using an AVHRR NDVI data set and the panel cointegrated regression method. The results show that there is a long-term inverted N-shaped curve relationship between population growth and vegetation cover in the region where there are frequent human activities and the influence of climate change on vegetation cover changes is relatively small. The two turning points of the inverted N-shaped curve for the case of Guangdong Province correspond to 2,200 persons·km−2 and 3,820 persons·km−2, and they can provide a reference range for similar regions of the World. It also states that the population urbanization may have a negative impact on the vegetation cover at the early stage, but have a positive impact at the later stage. In addition, the Panel Error Correction Model (PECM) is used to investigate the causality direction between population growth and vegetation cover. The results show that not only will the consuming destruction effect and planting construction effect induced by the population growth have a great impact on vegetation cover changes, but vegetation cover changes in turn will also affect the population growth in the long term.

Environmental quality and its impact on the local economy: A case study from Dongguan, South China

Industries that pollute the environment developed in the early 1990s in Dongguan City, especially those in the middle and lower valley of the Dongjiang River (waterside area) have seriously affected water and air quality and hence have affected soil quality through polluted water irrigation and precipitation. Investigation of the economic growth and environmental pollution in the 32 township units in the City from 1990 to 2000 also reveals that environmental pollution has affected the history of the development of the towns or townships in the waterside region in the delta of the River Dongjiang, especially the towns near the river mouth, and has prevented their industry from upgrading and hence has slowed down their economic growth. The impact of environmental pollution on economic growth is most severe in the towns along the lower valley, or in down-wind regions. In contrast, economic development in the protected area of the upper valley of the waterside region indicates that environmental protection that strictly controls the discharge of pollutants does not restrict the development of the local economy.

Numerical study of urban expansion and its influence on urban environment using Landsat TM/ETM+ images

Multi-temporal Landsat TM/ETM+ imagery of 1990, 2000, and 2005 were used in this study. And the vegetation abundances, percent impervious surface, normalized difference impervious surface index(NDISI) and brightness temperature were retrieved from each TM/ETM+ dataset. Then the urban expansion, urban heat island and the relationships between LST and other variables which relate to urban environment were investigated. Results indicated that the percentage of urban area in Guangzhou increased significantly, which grew from 18.35% in 1990, to 24.16% in 2000, and further to 33.29% in 2005. But the intensity of urban heat island was not always enlarged during 1990–2005. And the regression analyses showed that, at the pixel-scale, the relationships between LST and other two variables (vegetation abundances and percent impervious surface) were relatively more complicated and could not be described by using the linear regression model. However, LST had a strong positive and negative correlation with percent impervious area and vegetation abundance in the region-scale, respectively. These results may be very useful for moderate- or large-scale ecological modeling and climate modeling.