The fast-growing urbanization has contributed to the construction sector be- coming one of the major sectors traded in the world stock market. In general, non- stationarity is highly related to most of the stock market price pattern. Even though stationarity transformation is a common approach, yet this may prompt to originality loss of the data. Hence, the non-transformation technique using a generalized dynamic principal component (GDPC) were considered for this study. Comparison of GDPC was performed with two transformed principal component techniques. This is pertinent as to observe a larger perspective of both techniques. Thus, the latest weekly two-years observations of nine constructions stock market price from seven different countries were applied. The data was tested for stationarity before performing the analysis. As a re- sult, the mean squared error in the non-transformed technique shows eight lowest values. Similarly, eight construction stock market prices had the highest percentage of explained variance. In conclusion, a non-transformed technique can also present a better result outcome without the stationarity transformation.
The pace of urbanization in Peninsular Malaysia was slower in the most recent intercensal interval, 1957 to 1970, than in the previous period, 1947 to 1957. Most of the small change in the rural-urban balance from 1957 to 1970 appears due to the growth of towns into the urban classification rather than to a redistribution of population into the previous urban settlements. A number of towns in Peninsular Malaysia do show exceptional growth from 1957 to 1970, but there seems to be no clear relationship between a city's size and its subsequent growth. The rural areas on the outskirts of the largest cities do show rapid growth, especially the periphery of the capital city. It appears that neither the classic model of urbanization based upon Western experience nor the over-urbanization thesis explain the urbanization process in Peninsular Malaysia.
Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs. Given the proliferation of different water quality models and the promise they have shown, it is timely to assess the state-of-the-art in this field, to identify potential challenges and suggest future research directions. In this review, model types, modeled quality parameters, modeling purpose, data availability, type of case studies and model performance evaluation are critically analyzed and discussed based on a review of 110 papers published between 2010 and 2019. The review identified that applications of empirical and kinetic models dominate those of data-driven models for addressing water quality issues. The majority of models are developed for prediction and process understanding using experimental or field sampled data. While many models have been applied to real problems, the corresponding prediction accuracies are overall moderate or, in some cases, low, especially when dealing with larger SNs. The review also identified the most common issues associated with water quality modeling of SNs and based on these proposed several future research directions. These include the identification of appropriate data resolutions for the development of different SN models, the need and opportunity to develop hybrid SN models and the improvement of SN model transferability.
In Oceania, a region challenged by rapid urbanisation and climate change, integrative frameworks are required to enable effective actions on health and sustainability. The Ecohealth approach provides a framework for practice that acknowledges human health is intrinsically linked to ecosystem health. This research communication reports on a study involving interviews with twenty-seven leading health and sustainability thinkers from Oceania and across the globe. In examining their ideas for action, the report presents the study findings in relation to the guiding principles of Ecohealth: systems thinking, transdisciplinarity, participation, sustainability, equity and knowledge-to-action. Implications for Ecohealth practitioners working in Oceania are considered.
The current disconnection between access to increasing amounts of data about urbanization, health, and other global changes and the conflicting meanings and values of that data has created uncertainty and reduced the ability of people to act upon available information which they do not necessarily understand. We see a disconnection between increasing data availability and data processing capability and capacity. In response to this disconnection, modeling has been attributed an important role in international and national research programs in order to predict the future based on past and recent trends. Predictive models are often data heavy and founded on assumptions which are difficult to verify, especially regarding urban health issues in specific contexts. Producing large volumes of data warrants debate about what data are prerequisites for better understanding human health in changing urban environments. Another concern is how data and information can be used to apply knowledge. Making sense of empirical knowledge requires a new transdisciplinary knowledge domain created by a commitment to convergence between researchers in multiple academic disciplines and other actors and institutions in cities. Disciplinary-based researchers are no longer the sole producers of empirical knowledge. Today, diverse kinds of knowledge are becoming an emergent product of multiple societal stakeholders acting collectively to address challenges that impact on their habitat, their livelihood, and their health. Insights from complexity science also require a fundamental rethinking of the role and responsibility of human agency while admitting rather than denying complexity and radical uncertainty.
The study aims to analyze two objectives: first is to explore the non-linear relationship between tourism development, economic growth, urbanization, and environmental degradation, and also to analyze the threshold level of the contribution of tourism development on environmental degradation in top tourist arrival destinations. We applied the newly proposed econometric method panel smooth transition regression (PSTR) framework with two regimes on yearly panel data from 1995 to 2017. Findings suggest that the relationship between tourism development and environmental degradation is non-linear and regime dependent. Furthermore, the findings indicated that the relationship above the threshold level is negative and significant, while below the threshold, tourism development is positive and significant effect on environmental degradation. Tourism development and environmental degradation also exhibit the inverted U-shape relationship meaning that at a particular point, increase in tourism development increases in environmental degradation but after a particular point, increase in tourism development decreases the environmental degradation. The economic growth and urbanization also portray a non-linear and regime-dependent relationship with environmental degradation. The study assists policies and empirical information.
Global climate change and rapid urbanization, mainly driven by anthropogenic activities, lead to urban flood vulnerability and uncertainty in sustainable stormwater management. This study projected the temporal and spatial variation in urban flood susceptibility during the period 2020-2050 on the basis of shared socioeconomic pathways (SSPs). A case study in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was conducted for verifying the feasibility and applicability of this approach. GBA is predicted to encounter the increase in extreme precipitation with high intensity and frequency, along with rapid expansion of constructed areas, resulting in exacerbating of urban flood susceptibility. The areas with medium and high flood susceptibility will be expected to increase continuously from 2020 to 2050, by 9.5 %, 12.0 %, and 14.4 % under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively. In terms of the assessment of spatial-temporal flooding pattern, the areas with high flood susceptibility are overlapped with that in the populated urban center in GBA, surrounding the existing risk areas, which is consistent with the tendency of construction land expansion. The approach in the present study will provide comprehensive insights into the reliable and accurate assessment of urban flooding susceptibility in response to climate change and urbanization.
China can effectively promote urban-rural integration and economic and social modernization through new urbanization, which also serves as a strong driver and supporter of the growth of rural tourism. This paper examines the new urbanization and the growth of the rural tourism industry based on the rural revitalization strategy. It does so by using the techniques of literature research, field investigation, information technology retrieval, and excavation. We list the accomplishments of the rural tourism sector at its current stage of development and identify the issues and factors that will affect the sector's future growth. In addition, a coordinated development evaluation index system is built based on a theoretical analysis of rural revitalization strategies and new urbanization, and the corresponding comprehensive score is obtained using the entropy method for research. The index weight of the subsystem for rural revitalization in province A is computed using the entropy weight method. According to the findings, the wealth of life has the smallest weight (0.1117), followed by the prosperity of industry (0.2618), which is the largest on a criterion level. The effective weight of governance is the largest, at 0.2801. This study can serve as a useful resource for fostering rural tourism and advancing rural business.
There is a shred of evidence of environmental degradation in the form of carbon emissions to behave differently when tested with different macroeconomic variables. This paper aims to examine the long-run and short-run association between natural resource rent, financial development, and urbanization on carbon emission from the context of the USA during 1995-2015 with the help of a contemporary and innovative approach named quantile autoregressive distributed lagged model (QARDL). The stated approach is applied due to the fact that non-linearity is observed for the study variables. The findings indicated that the higher financial development (0.304), natural resource rent (0.102), and urbanization (0.489) have a positive impact on the environmental degradation in the region of USA during long-run estimation in the stated quantiles of the study. This would indicate that higher financial development, urbanization, and natural resources are putting more environmental pressure on the economy of the USA. Similarly, the findings under short-run estimation confirm that past and lagged values of carbon emission, financial development, natural resource rent, and urbanization are significantly determining the current values of the carbon emission. For this reason, it is suggested that the government requires some immediate steps of the USA to control the harmful effect of such financial development, more urbanization, and higher natural resource rent as well. This would indicate the reflection of some green strategies in all three explanatory variables to generate some fruitful environmental outcomes.
With climate change and urbanization, flood disasters have significantly affected urban development worldwide. In this study, we developed a paradigm to assess flood economic vulnerability and risk at the urban mesoscale, focusing on urban land use. A hydrological simulation was used to evaluate flood hazards through inundation analyses, and a hazard-vulnerability matrix was applied to assess flood risk, enhancing the economic vulnerability assessment by quantifying the differing economic value and flood losses associated with different land types. The case study of Wangchengpo, Changsha, China, found average total economic losses of 126.94 USD/m2, with the highest risk in the settlement core. Residential areas had the highest flood hazard, vulnerability, and losses (61.10% of the total loss); transportation areas accounted for 27.87% of the total economic losses due to their high flooding depth. Despite low inundation, industrial land showed greater economic vulnerability due to higher overall economic value (10.52% of the total). Our findings highlight the influence of land types and industry differences on flood vulnerability and the effectiveness of land-use inclusion in urban-mesoscale analyses of spatial flood characteristics. We identify critical areas with hazard and economic vulnerability for urban land and disaster prevention management and planning, helping to offer targeted flood control strategies to enhance urban resilience.
In the current context of rapid development and urbanization, land use and land cover (LULC) types have undergone unprecedented changes, globally and nationally, leading to significant effects on the surrounding ecological environment quality (EEQ). The urban agglomeration in North Slope of Tianshan (UANST) is in the core area of the Silk Road Economic Belt of China. This area has experienced rapid development and urbanization with equally rapid LULC changes which affect the EEQ. Hence, this study quantified and assessed the spatial-temporal changes of LULC on the UANST from 2001 to 2018 based on remote sensing analysis. Combining five remote sensing ecological factors (WET, NDVI, IBI, TVDI, LST) that met the pressure-state-response(PSR) framework, the spatial-temporal distribution characteristics of EEQ were evaluated by synthesizing a new Remote Sensing Ecological Index (RSEI), with the interaction between land use change and EEQ subsequently analyzed. The results showed that LULC change dominated EEQ change on the UANST: (1) From 2001 to 2018, the temporal and spatial pattern of the landscape on the UANST has undergone tremendous changes. The main types of LULC in the UANST are Barren land and Grassland. (2) During the study period, RSEI values in the study area were all lower than 0.5 and were at the [good] levels, reaching 0.31, 0.213, 0.362, and 0346, respectively. In terms of time and space, the overall EEQ on the UANST experienced three stages of decline-rise-decrease. (3) The estimated changes in RSEI were highly related to the changes of LULC. During the period 2001 to 2018, the RSEI value of cropland showed a trend of gradual increase. However, the rest of the LULC type's RSEI values behave differently at different times. As the UANST is the core area of Xinjiang's urbanization and economic development, understanding and balancing the relationship between LULC and EEQ in the context of urbanization is of practical application in the planning and realization of sustainable ecological, environmental, urban, and social development in the UANST.
Urbanization may influence physical activity (PA) levels, although little evidence is available for low- and middle- income countries where urbanization is occurring fastest. We evaluated associations between urbanization and total PA, as well as work-, leisure-, home-, and transport-specific PA, for 138,206 adults living in 698 communities across 22 countries within the Prospective Urban and Rural Epidemiology (PURE) study. The 1-week long-form International PA Questionnaire was administered at baseline (2003-2015). We used satellite-derived population density and impervious surface area estimates to quantify baseline urbanization levels for study communities, as well as change measures for 5- and 10-years prior to PA surveys. We used generalized linear mixed effects models to examine associations between urbanization measures and PA levels, controlling for individual, household and community factors. Higher community baseline levels of population density (- 12.4% per IQR, 95% CI - 16.0, - 8.7) and impervious surface area (- 29.2% per IQR, 95% CI - 37.5, - 19.7), as well as the rate of change in 5-year population density (- 17.2% per IQR, 95% CI - 25.7, - 7.7), were associated with lower total PA levels. Important differences in the associations between urbanization and PA were observed between PA domains, country-income levels, urban/rural status, and sex. These findings provide new information on the complex associations between urbanization and PA.
In terms of achieving sustainable development goals (SDGs), the developing economies are facing many issues, and one of the key issues is environmental degradation. Being a developing economy, Pakistan is also experiencing thought-provoking impacts of global warming and still far away from the ideal track of sustainable development. For addressing environment-related issue and achieving the targets of SDGs, a policy-level reorientation might be necessary. In this view, this study investigates the impact of economic growth, transport infrastructure, urbanization, financial development, and renewable energy consumption on CO2 emissions by using the data of Pakistan during 1990-2020. For this purpose, we use novel wavelet quantile correlation approach. The empirical results of wavelet quantile correlation approach demonstrate that economic growth, transport infrastructure, urbanization, and financial development are responsible for environmental pollution. Whereas, result also claims that renewable energy consumption is a useful tool for reducing environmental pollution in Pakistan. Moreover, the results of FMOLS approach show that 1% increase in economic growth, transportation infrastructure, urbanization, and financial development increases CO2 emissions by 0.240, 0.010, 0.478, and 0.102%, respectively. However, 1% increase in renewable energy usage reduces CO2 emission by 1.083%. Based on the empirical outcomes, this study proposes comprehensive policy framework for achieving the targets of SDG 7 (clean energy), SDG 8 (economic growth), SDG 11 (sustainable cities and communities), and SDG 13 (climate action).
Many species of birds gradually adapt to urbanization and colonize cities successfully. However, their nest site selection and competitive relationship in an urban community remain little known. Understanding the impact of urbanization on birds and the competitive relationship has important implications for the conservation and management of wildlife in urban ecosystems. Here, we undertook a systematic study to quantify nests in all species of birds in an urbanizing area of Nanchang, China. A total of 363 nests were detected in surveys including 340 nests of 16 bird species and 23 unidentified species nests. We mainly analyzed 5 dominant breeding birds with a sample size of >10 during the two breeding seasons (From April to July in 2016 and 2017), which included the light-vented bulbul, Chinese blackbird, scaly-breasted munia, spotted dove and grey-capped greenfinch. Most birds (93.66%) nested in the tree of artificial green belts, which seems to be the best breeding habitat for urban birds. Our results suggested that birds' breeding success relies on the trade-off between the benefit and the expense of specific stresses from habitats. The nest site selection of birds is also affected by the life habit of urban predators. Furthermore, competition among species can influence their distributions and utilization of environmental resources when birds nest in cities. We confirmed that the niche differentiation of five bird species in an urban environment makes them coexist successfully by utilizing various resources.
Urbanization has made tremendous contributions to China's economic development since its economic reforms and opening up. At the same time, population agglomeration has aggravated environmental pollution and posed serious challenges to China's environment. This article empirically investigates the impacts of China's urbanization on eco-efficiency, comprehensively reflecting economic growth, resource input, and waste discharge. We first measured the provincial eco-efficiency in China from 2005 to 2015 using the Super Slack-Based model (Super-SBM). We then constructed a spatial model to empirically analyze the effects of urbanization on eco-efficiency at the national level, and at four regional levels. The results indicated that the regional eco-efficiency in China has fluctuated, but is generally improving, and that a gap between regions was evident, with a trend toward further gap expansion. We observed an effect of spatial spillover in eco-efficiency, which was significant and positive for the whole country, except for the western region. The influence of urbanization on China's eco-efficiency exhibited a U-curve relationship. The changing trend in the eastern, central, and western regions was the same as that in the whole country; however, the trend exhibited an inverted U-curve relationship in the northeastern region. To the best of our knowledge, covering a time period of 2005-2015, this article is the first of its kind to study the impact of urbanization on eco-efficiency in China at both the national and regional levels. This study may help policy-makers to create sustainable policies that could be helpful in balancing urbanization and the ecological environment.
The objective of this paper is to examine the dynamic impact of urbanization, economic growth, energy consumption, and trade openness on CO 2 emissions in Nigeria based on autoregressive distributed lags (ARDL) approach for the period of 1971-2011. The result shows that variables were cointegrated as null hypothesis was rejected at 1 % level of significance. The coefficients of long-run result reveal that urbanization does not have any significant impact on CO 2 emissions in Nigeria, economic growth, and energy consumption has a positive and significant impact on CO 2 emissions. However, trade openness has negative and significant impact on CO 2 emissions. Consumption of energy is among the main determinant of CO 2 emissions which is directly linked to the level of income. Despite the high level of urbanization in the country, consumption of energy still remains low due to lower income of the majority populace and this might be among the reasons why urbanization does not influence emissions of CO 2 in the country. Initiating more open economy policies will be welcoming in the Nigerian economy as the openness leads to the reduction of pollutants from the environment particularly CO 2 emissions which is the major gases that deteriorate physical environment.