Mining and Tourism: Comparing Spatial Patterns, Socioeconomic Contributions, and Environmental Impacts in China

ABSTRACT This dissertation examines the environmental and socioeconomic impacts of mining and tourism industries in China with a goal of understanding whether or not these two sectors are mutually compatible in achieving sustainable developme nt. Yunnan, a province in southwest China was selected as the study area because of its high potential for growth in both sectors. A macro-level Geographic Information System (GIS) analysis and a case study were employed to understand patterns of change and linkages. Paper 1 addresses the spatial patterns of mining and tourism activities by a GIS analysis. Spatial cluster analysis of major tourism attractions and mining sites concludes that 1) mining sites tend to be clustered, whereas locations of tourism attractions do not exhibit any significant evidence of aggregation. 2) Mining and tourism sites tend to cluster at the scale of 25 kilometers to 45 kilometers. However, 3) mining/tourism sites relatively far away from each other attain more economic income. Incorporating the social context and development history of the study area, the results imply that although mining activities may have some negative impact on tourism attractions making those nearby a mining site earn less income; some factors tie the two industries together such as investing capacity of and policy support from local government. Paper 2 considers the environmental health and socioeconomic status of the areas where mining or tourism activities cluster. Statistical analysis on prefecture level and county level detects no significant difference between areas of mining and tourism in terms of economic status (GDP and poverty rate) and social development (ratio of researchers, agricultural technicians, teachers and doctors, and access to pipe water, major roads and telephone). For environmental indicators, the air pollution and soil erosion index perform better in tourism areas than mining areas, while other variables including forestry coverage, water quality and an overall ecological health index detect little difference between mining and tourism areas. The paper concludes that sector difference in economic and environmental performances may be over-emphasized. How mining and tourism contribute to or impact the sustainability of regional development needs to be further studied within the local context. Paper 3 develops a case study of a Tibet village called Jisha in northwest Yunnan to explore management as a factor influencing tourism impacts on environment and local economic productivity. Jisha village experiences two types of tourism development. A community based small-scale tourism development project, initiated by a local nongovernment organization, aims to partner with Jisha residents to build a Tibetan style hostel which will bring tourism income to the villagers. An external company plans to construct a hotel, golf course and chair- lift by making a large investment in the community. Although some aspects of this project are likely to benefit the local community better than others, local residents are resisting all development efforts. Results of the ethnographic study show organization- led projects work better in benefiting local people and conserving environment than corporation businesses. However, such ventures may not have the multiplier effect on the local economy as external corporate businesses because of the moderate size of the investment

Integrated assessment of atmospheric environmental management in China

China is facing severe challenges of air pollution and greenhouse gas (GHG) emissions with rapid economic development, industrialization and urbanization. Continued reductions in air pollutants and GHG emissions are critical, as they pose serious threats to human health and the environment. Air pollution and climate change are largely affected by similar sources and may interact with each other through atmospheric chemical reactions. This study developed a methodology to analyse the integrated impacts of atmospheric environmental policies on human health and climate change in China. Emission estimation, air quality modelling, health impact assessment, and economic evaluation are synthesized following the full-chain impact pathway from sources of emissions via environmental quality changes to physical and economic impacts. A quantitative assessment of the economic health and climatic benefits from emission reduction of air pollutants and GHG under different present and future scenarios in China is presented. Sensitivity and uncertainty analyses are conducted to provide information on the robustness of the results. The modelling results show that the years of life lost (YOLL) attributable to PM2.5 exposure are 8.2 and 13.4 million in 2010 and 2030 considering current legislation in China. The corresponding damage costs amount to about 3.9 and 5.2% of China’s gross domestic product (GDP) in 2010 and 2030, respectively. Aggressive control policies will lead to significant benefits in the aspects of health and climate change mitigation. The integrated benefits of the three investigated policy scenarios are estimated to be 239.9 (95% CI: 41.5, 1387.8), 353.1 (32.9, 3789.4), and 619.5 (87.2, 4403.5) billion EUR2010 in 2030, respectively. Clear provincial disparities on emissions, concentration levels, and attainable benefits from policy measures exist in China. Higher per capita benefits from policy measures are estimated for provinces with high population density and energy intensity. The integrated assessment methodology developed in this study enables simultaneous consideration of air pollution induced health effects and GHG related climatic effects in the process of environmental policy development in China. The reduction potential and integrated benefits from policy measures estimated in this study provide valuable policy insights for China and other developing countries

Adversarial Label Poisoning Attack on Graph Neural Networks via Label Propagation

Graph neural networks (GNNs) have achieved outstanding performance in semi-supervised learning tasks with partially labeled graph structured data. However, labeling graph data for training is a challenging task, and inaccurate labels may mislead the training process to erroneous GNN models for node classification. In this paper, we consider label poisoning attacks on training data, where the labels of input data are modified by an adversary before training, to understand to what extent the state-of-the-art GNN models are resistant/vulnerable to such attacks. Specifically, we propose a label poisoning attack framework for graph convolutional networks (GCNs), inspired by the equivalence between label propagation and decoupled GCNs that separate message passing from neural networks. Instead of attacking the entire GCN models, we propose to attack solely label propagation for message passing. It turns out that a gradient-based attack on label propagation is effective and efficient towards the misleading of GCN training. More remarkably, such label attack can be topology-agnostic in the sense that the labels to be attacked can be efficiently chosen without knowing graph structures. Extensive experimental results demonstrate the effectiveness of the proposed method against state-of-the-art GCN-like models

Heat-Related Mortality Projections for Cardiovascular and Respiratory Disease Under the Changing Climate in Beijing, China

Because heat-related health effects tend to become more serious at higher temperatures, there is an urgent need to determine the mortality projection of specific heat-sensitive diseases to provide more detailed information regarding the variation of the sensitivity of such diseases. In this study, the specific mortality of cardiovascular and respiratory disease in Beijing was initially projected under five different global-scale General Circulation Models (GCMs) and two Representative Concentration Pathways scenarios (RCPs) in the 2020s, 2050s, and 2080s compared to the 1980s. Multi-model ensembles indicated cardiovascular mortality could increase by an average percentage of 18.4 percent, 47.8 percent, and 69.0 percent in the 2020s, 2050s, and 2080s under RCP 4.5, respectively, and by 16.6 percent, 73.8 percent and 134 percent in different decades respectively, under RCP 8.5 compared to the baseline range. The same increasing pattern was also observed in respiratory mortality. The heat-related deaths under the RCP 8.5 scenario were found to reach a higher number and to increase more rapidly during the 21st century compared to the RCP4.5 scenario, especially in the 2050s and the 2080s. The projection results show potential trends in cause-specific mortality in the context of climate change, and provide support for public health interventions tailored to specific climate-related future health risks

Cumulative Environmental Vulnerability and Environmental Justice in California’s San Joaquin Valley

The identification of “environmental justice (EJ) communities” is an increasingly common element in environmental planning, policy, and regulation. As a result, the choice of methods to define and identify these communities is a critical and often contentious process. This contentiousness is, in turn, a factor of the lack of a commonly accepted method, the concern among many EJ advocates and some regulators that existing frameworks are inadequate, and ultimately, the significant consequences of such designations for both public policy and community residents. With the aim of assisting regulators and advocates to more strategically focus their efforts, the authors developed a Cumulative Environmental Vulnerability Assessment (CEVA). This CEVA is composed of a Cumulative Environmental Hazard Index and a Social Vulnerability Index, with a Health Index as a reference. Applying CEVA produces spatial analysis that identifies the places that are subject to both the highest concentrations of cumulative environmental hazards and the fewest social, economic and political resources to prevent, mitigate, or adapt to these conditions. We recommended that these areas receive special consideration in permitting, monitoring, and enforcement actions, as well as investments in public participation, capacity building, and community economic development

Public health impacts of city policies to reduce climate change:Findings from the URGENCHE EU-China project

Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments.; Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys.; There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied.; The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries

Cumulative Environmental Vulnerability and Environmental Justice in California’s San Joaquin Valley

The identification of “environmental justice (EJ) communities” is an increasingly common element in environmental planning, policy, and regulation. As a result, the choice of methods to define and identify these communities is a critical and often contentious process. This contentiousness is, in turn, a factor of the lack of a commonly accepted method, the concern among many EJ advocates and some regulators that existing frameworks are inadequate, and ultimately, the significant consequences of such designations for both public policy and community residents. With the aim of assisting regulators and advocates to more strategically focus their efforts, the authors developed a Cumulative Environmental Vulnerability Assessment (CEVA). This CEVA is composed of a Cumulative Environmental Hazard Index and a Social Vulnerability Index, with a Health Index as a reference. Applying CEVA produces spatial analysis that identifies the places that are subject to both the highest concentrations of cumulative environmental hazards and the fewest social, economic and political resources to prevent, mitigate, or adapt to these conditions. We recommended that these areas receive special consideration in permitting, monitoring, and enforcement actions, as well as investments in public participation, capacity building, and community economic development

Urbanization and Socioeconomic Development in Inner Mongolia in 2000 and 2010: A GIS Analysis

Economic indicators and other indices measuring overall development describe local development trajectories differently. In this paper, we illustrated this difference and explored how urbanization is related to development by a case study in Inner Mongolia, China. We calculated the human development index (HDI) and compared the temporal and spatial dynamics of the overall development (represented by the HDI) and economic growth (represented by the GDP) in 2000 and 2010. We conducted partial correlation analysis between the HDI and urbanization rate whilst controlling for the effects of the GDP. Our results showed that the spatial pattern of the HDI was little in 2000 and became clearer in 2010 when the western part tended to have higher values and the northeastern part tended to have lower values. The spatial trend for the GDP was obvious in 2000 as the high values clustered in the northwest and the low values clustered in the southeast but became less obvious in 2010 when high values clustered in several counties in the southwest and low values took up almost the entire northeast and some counties in the middle. Furthermore, we found that the HDI of all the city districts were significantly higher than their surrounding rural counties in both 2000 and 2010. Urbanization rates are found to be positively correlated with the HDI even when we controlled the effects of the GDP (p < 0.001). This study illustrated that the HDI and GDP told different stories on local performance in development at the county level. Translating the fast economic growth into an improvement in education and health relies on many other factors and our results seem to suggest that urbanization is one of these factors

Urbanization and Socioeconomic Development in Inner Mongolia in 2000 and 2010: A GIS Analysis

Economic indicators and other indices measuring overall development describe local development trajectories differently. In this paper, we illustrated this difference and explored how urbanization is related to development by a case study in Inner Mongolia, China. We calculated the human development index (HDI) and compared the temporal and spatial dynamics of the overall development (represented by the HDI) and economic growth (represented by the GDP) in 2000 and 2010. We conducted partial correlation analysis between the HDI and urbanization rate whilst controlling for the effects of the GDP. Our results showed that the spatial pattern of the HDI was little in 2000 and became clearer in 2010 when the western part tended to have higher values and the northeastern part tended to have lower values. The spatial trend for the GDP was obvious in 2000 as the high values clustered in the northwest and the low values clustered in the southeast but became less obvious in 2010 when high values clustered in several counties in the southwest and low values took up almost the entire northeast and some counties in the middle. Furthermore, we found that the HDI of all the city districts were significantly higher than their surrounding rural counties in both 2000 and 2010. Urbanization rates are found to be positively correlated with the HDI even when we controlled the effects of the GDP (p < 0.001). This study illustrated that the HDI and GDP told different stories on local performance in development at the county level. Translating the fast economic growth into an improvement in education and health relies on many other factors and our results seem to suggest that urbanization is one of these factors