Suchergebnisse

The reservoir-related tourism industry has been developed for leisure purposes since the 1970s and has gained popularity worldwide. To promote reservoir-related tourism in China, the Chinese government launched a "top-down" project titled "Water Conservation Scenic Spot" (WCSS) in 2001. However, because of the lack of reasonable planning, innovative ideas, and effective governance, there are some problems with WCSS constraining its development. To deal with those problems, it is necessary to have a holistic understanding of the WCSS situation. This study analyses the origin, status, opportunities, and challenges of WCSS development in China. The results show a trend of periodic increase in the number of WCSSs between 2001 and 2016, and WCSS development is unbalanced regarding regions and types. Moreover, the main issues for the WCSS include the failure to follow WCSS guidelines in practice, weak awareness of the scientific educational function, monotonous planning and construction, a lack of cultural preservation, insufficient funding, weak marketing, damaging of natural resources, destruction of clusters of animals and plants, land surface erosion, and landscape pollution. These adverse effects can be alleviated by strengthening supervision and fostering balanced development, promoting education and protecting cultural resources, distributing funding and enlarging popularity, controlling the amount of tourism, and avoiding overexpansion. Overall, the findings of this study can encourage the development of WCSSs in the future and are of significance in supporting the reservoir-related tourism industry.

Urban overheating can result in serious environmental, social and economic problems such as a poor outdoor thermal environment, heat stress, heat-related morbidity and mortality, increased peak electricity demand, and economic productivity loss. Extensive effort has been made by local governments to mitigate urban overheating, cool streetscapes and cities, and protect vulnerable people. However, there is uncertainty about which urban heat mitigation strategies (UHMSs) can provide better solutions for a specific urban context. Also, there is a compelling need for local governments to automate the decision-making process and optimise the combination of UHMSs to maximise the mitigation outcomes for their cities.This research aims to fill the gap by developing a novel decision-making framework that integrates artificial intelligence techniques with urban heat mitigation in the built environment. The novel decision-making framework comprises: the ontology-based knowledge representation of UHMSs and their relationships with urban contexts and performance assessment; sensitivity analysis of the environmental, social and economic performance of UHMSs; and genetic algorithm-based multi-objective optimisation of UHMSs. The novel decision-making framework enables an automated process of identifying appropriate UHMSs tailored to a specific urban context and generating the optimal combination of UHMSs to support decision making by local governments. The utilisation of the decision-making framework was investigated through Leppington and Green Square development cases in Sydney, Australia. The results showed that a set of optimal combinations of UHMSs with key planning and design variables was obtained automatically. For example, an optimum combination of 7 m Koelreuteria paniculata on street sides, greyish-white concrete on driveways, white concrete on roofs, and grey concrete on walls was automatically obtained for urban heat mitigation in Leppington. The most key planning and design variables are related to albedo since albedo had significant impacts on environmental, social, and economic performance in Leppington. The optimised combination of UHMSs led to the optimal environmental, social and economic performance, for example, an air temperature reduction of 0.9°C, land surface temperature reduction of 8.9°C, a heat-related mortality rate reduction of 6.4%, a UTCI improvement of 0.5°C, a reduction in the economic productivity loss of 2.2%, a reduction in electricity energy bills of 6.1%, and a reduced implementation cost of 22.8% for the Leppington case.This research incorporates artificial intelligence techniques into urban heat mitigation in the built environment to enable an automated process of decision making. The decision-making framework and its application in two urban development cases demonstrate a novel approach for local governments to automatically identify optimal combinations of UHMSs to tackle urban heat challenges in the local context. The research outcomes will advance interdisciplinary knowledge about the use of artificial intelligence techniques in the decision-making process for urban heat mitigation.

Air pollution has become a critical issue in the urban areas of southeastern China in recent years. A complete understanding of the tempo-spatial characteristics of air pollution can help the public and governmental bodies manage their lives and work better. In this study, data for six criteria air pollutants (including particulate matter (PM2.5, PM10), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) from 37 sites in nine major cities within Fujian Province, China were collected between January 2015 to December 2016, and analyzed. We analyzed the spatial and temporal variations of these six criteria pollutants, as well as the attainment rates, and identified what were the major pollutants. Our results show that: (1) the two-year mean values of PM2.5 and PM10 exceeded the Chinese National Ambient Air Quality Standard (CAAQS) standard I levels, whereas other air pollutants were below the CAAQS standard I ; (2) the six criteria air pollutants show spatial variations (i.e. most air pollutants were higher in the city center areas, followed by suburban areas and exurban areas, except for O3 ; and the concentrations of PM10, PM2.5, NO2, O3 were higher in coastal cities than in inland cities) ; (3) seasonal variations and the no attainment rates of air pollutants were found to be higher in cold seasons and lower in warm seasons, except for O3 ; (4) the most frequently present air pollutant was PM10, with PM2.5 and O3 being the second and third most frequent, respectively ; (5) all the air pollutants, except O3, showed positive correlations with each other. These results provide additional information for the effective control of air pollution in the province of Fujian.

Air pollution has become a critical issue in the urban areas of southeastern China in recent years. A complete understanding of the tempo-spatial characteristics of air pollution can help the public and governmental bodies manage their lives and work better. In this study, data for six criteria air pollutants (including particulate matter (PM₂.₅, PM₁₀), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and ozone (O₃)) from 37 sites in nine major cities within Fujian Province, China were collected between January 2015 to December 2016, and analyzed. We analyzed the spatial and temporal variations of these six criteria pollutants, as well as the attainment rates, and identified what were the major pollutants. Our results show that: (1) the two-year mean values of PM₂.₅ and PM₁₀ exceeded the Chinese National Ambient Air Quality Standard (CAAQS) standard I levels, whereas other air pollutants were below the CAAQS standard I; (2) the six criteria air pollutants show spatial variations (i.e. most air pollutants were higher in the city center areas, followed by suburban areas and exurban areas, except for O₃; and the concentrations of PM₁₀, PM₂.₅, NO₂, O₃ were higher in coastal cities than in inland cities); (3) seasonal variations and the no attainment rates of air pollutants were found to be higher in cold seasons and lower in warm seasons, except for O₃; (4) the most frequently present air pollutant was PM₁₀, with PM₂.₅ and O₃ being the second and third most frequent, respectively; (5) all the air pollutants, except O₃, showed positive correlations with each other. These results provide additional information for the effective control of air pollution in the province of Fujian. ; Forestry, Faculty of ; Other UBC ; Non UBC ; Reviewed ; Faculty

Air pollution has become a critical issue in the urban areas of southeastern China in recent years. A complete understanding of the tempo-spatial characteristics of air pollution can help the public and governmental bodies manage their lives and work better. In this study, data for six criteria air pollutants (including particulate matter (PM(2.5), PM(10)), carbon monoxide (CO), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)) and ozone (O(3))) from 37 sites in nine major cities within Fujian Province, China were collected between January 2015 to December 2016, and analyzed. We analyzed the spatial and temporal variations of these six criteria pollutants, as well as the attainment rates, and identified what were the major pollutants. Our results show that: (1) the two-year mean values of PM(2.5) and PM(10) exceeded the Chinese National Ambient Air Quality Standard (CAAQS) standard I levels, whereas other air pollutants were below the CAAQS standard I; (2) the six criteria air pollutants show spatial variations (i.e. most air pollutants were higher in the city center areas, followed by suburban areas and exurban areas, except for O(3); and the concentrations of PM(10), PM(2.5), NO(2), O(3) were higher in coastal cities than in inland cities); (3) seasonal variations and the no attainment rates of air pollutants were found to be higher in cold seasons and lower in warm seasons, except for O(3); (4) the most frequently present air pollutant was PM(10), with PM(2.5) and O(3) being the second and third most frequent, respectively; (5) all the air pollutants, except O(3), showed positive correlations with each other. These results provide additional information for the effective control of air pollution in the province of Fujian.