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In an effort to gauge the global pandemic's impact on social thoughts and behavior, it is important to answer the following questions: (1) What kinds of topics are individuals and groups vocalizing in relation to the pandemic? (2) Are there any noticeable topic trends and if so how do these topics change over time and in response to major events? In this paper, through the advanced Sequential Latent Dirichlet Allocation model, we identified twelve of the most popular topics present in a Twitter dataset collected over the period spanning April 3rd to April 13th, 2020 in the United States and discussed their growth and changes over time. These topics were both robust, in that they covered specific domains, not simply events, and dynamic, in that they were able to change over time in response to rising trends in our dataset. They spanned politics, healthcare, community, and the economy, and experienced macro-level growth over time, while also exhibiting micro-level changes in topic composition. Our approach differentiated itself in both scale and scope to study the emerging topics concerning COVID-19 at a scale that few works have been able to achieve. We contributed to the cross-sectional field of urban studies and big data. Whereas we are optimistic towards the future, we also understand that this is an unprecedented time that will have lasting impacts on individuals and society at large, impacting not only the economy or geo-politics, but human behavior and psychology. Therefore, in more ways than one, this research is just beginning to scratch the surface of what will be a concerted research effort into studying the history and repercussions of COVID-19. [ABSTRACT FROM AUTHOR]

The rationality and efficiency of the spatial structure of an urban park system are critical in building a livable urban environment. Fractal theory is currently treated as the frontier theory for exploring the law of complex systems; however, it has rarely been applied to urban park systems. This study applied the aggregation, grid and correlation dimension models of fractal theory in Fuzhou, China. The spatial structure and driving factors of the urban park system were analyzed and an innovative model was proposed. The evidence shows that the spatial structure of the park system has fractal characteristics, although self-organization and optimization have not yet been fully formed, revealing a multi-core nesting pattern. Moreover, the core is cluster of four popular parks with weakening adsorption, and the emerging Baima River Park is located at the geometric center, which is likely to be further developed. The system structure is primarily driven by geographical conditions, planning policies, and transportation networks. Against this backdrop, an innovative model for the park system was proposed. The central park has heterogeneity and synergistic development, relying on the kinds of flow which can lead to the formation of a park city, a variation of a garden city. At the regional scale, relying on the geographical lines, the formation of a regional park zone could be realized. These findings provide new perspectives to reveal the spatial structure of urban park systems. The information derived can assist policy makers and planners in formulating more scientific plans, and may contribute to building a balanced and efficient urban park system. [ABSTRACT FROM AUTHOR]

China is facing both serious water scarcity and climate change challenges simultaneously. There is an urgent need to identify the synergies between water conservation and greenhouse gas (GHG) emission mitigation. This paper aims to trace the embodied water uses and GHG emissions (i.e., CO 2 , CH 4 and N 2 O) via China's domestic supply chains in 2012 and to explore their common important paths for driving the water withdrawals and the emissions of GHGs using the environmentally-extended input-output analysis and the structural path analysis. The results show a significant coupling between the embodied water uses and the embodied emissions of CO 2 , CH 4 and N 2 O in the supply chains on a national scale. The water-GHG nexus relationships from the consumption-side are systematically revealed in terms of industrial sectors, final demands and supply chain paths. The top 20 nexus paths ranked by water together accounted for 37.40% of the national total water withdrawals. Ranked by GHGs, the proportions were 22.46% of the total GHG emissions. Synergies in saving water resources and mitigating the emissions of CO 2 , CH 4 and N 2 O can be achieved through controlling important supply chain paths and critical transmission sectors. The highly interlinked nature of water and climate change issues requires comprehensive solutions to reduce future freshwater and GHG emission needs to maintain sustained economic growth in China. Image 1 • We trace embodied water uses and GHG emissions in 2012 Chinese supply chains. • We develop Sankey diagrams to illustrate the water-GHG nexus relationships. • The top 20 paths ranked by water contributed 37.40% of the total water uses. • The top 20 paths ranked by GHG contributed 22.46% of the total GHG emissions. • Critical nexus sectors and paths are potential water and climate policy targets. [ABSTRACT FROM AUTHOR]

This study investigated the urban growth dynamics of urban regions. The study area was the Marmara Region, one of the most densely populated and ecologically diverse areas in Turkey. Using CORINE land cover data for 2006, 2012, and 2018, the study utilized multiple correspondence analyses and cluster analyses, to analyze land cover changes. The resulting maps, visualized in GIS, revealed the rapid urban transformation of the regional structure, formerly comprised of four distinct areas, into a more complex structure, in which densification and sprawl occur simultaneously. Our findings demonstrated a dissonance between the spatial dynamics of the Marmara Region during the study period, and the capacity and scope of the simultaneously initiated regional policies and mega-projects. This uncoordinated approach has endangered the region's sustainable development. The paper, therefore, discusses the importance of land use planning and transboundary collaboration for sustainable regional development. Beyond the local case, the results contribute to critical theories in regional planning by linking theory and practice. [ABSTRACT FROM AUTHOR]

With the availability of computational resources, geographical information systems, and remote sensing data, urban growth modeling has become a viable tool for predicting urbanization of cities and towns, regions, and nations around the world. This information allows policy makers, urban planners, environmental and civil organizations to make investments, design infrastructure, extend public utility networks, plan housing solutions, and mitigate adverse environmental impacts. Despite its importance, urban growth models often discard the spatiotemporal uncertainties in their prediction estimates. In this paper, we analyzed the uncertainty in the urban land predictions by comparing the outcomes of two different growth models, one based on a widely applied cellular automata model known as the SLEUTH CA and the other one based on a previously published machine learning framework. We selected these two models because they are complementary, the first is based on human knowledge and pre-defined and understandable policies while the second is more data-driven and might be less influenced by any a priori knowledge or bias. To test our methodology, we chose the cities of Jiaxing and Lishui in China because they are representative of new town planning policies and have different characteristics in terms of land extension, geographical conditions, growth rates, and economic drivers. We focused on the spatiotemporal uncertainty, understood as the inherent doubt in the predictions of where and when will a piece of land become urban, using the concepts of certainty area in space and certainty area in time. The proposed analyses in this paper aim to contribute to better urban planning exercises, and they can be extended to other cities worldwide. [ABSTRACT FROM AUTHOR]

Globalization drives anthropogenic methane (CH 4) emissions from upstream to downstream agents through global supply chains. However, previous studies have overlooked the indirect CH 4 emissions enabled by primary suppliers. In this study, we use the Ghosh Multi-Regional Input-Output (MRIO) model and Structural Decomposition Analysis (SDA) to explore the temporal changes in global income-based CH 4 emissions and decompose the socioeconomic drivers. Our results show that global income-based CH 4 emissions increased by 17.21% from 2001 to 2014, with per capita primary inputs and technology being the two key drivers. Specifically, in China and India, income-based CH 4 emissions were mainly from agriculture, and input structure was responsible for restraining the growth in CH 4 emissions from their agricultural activities. On the other hand, service activities dominated the United States and the European Union, and production output structure was accountable for their emission growth related to service activities. To achieve global CH 4 emission mitigation, key sectors of major economies with high income-based CH 4 emissions should optimize their primary input structures, production output structure, and production technologies from the supply-side. It is crucial to reduce enabled CH 4 emissions in emerging economies, particularly in Asia, through the adjustment of primary input activities. [Display omitted] • Per capita primary inputs and technology dominated global CH 4 emission changes. • Income-based emissions decreased in West & Central Europe and the United States. • Agriculture and mining contributed to the high emissions in most emerging economies. • Production output structure accounted for the growth in service-enabled emissions. • Spatial heterogeneity of drivers of income-based CH 4 emissions was discussed. [ABSTRACT FROM AUTHOR]

With the rapid development of computer technology, urban informatics, as a new discipline in the field of urban planning, has gradually attracted academic attention. The rise of urban informatics puts new pressures on urban planning, but it also provides a new perspective of analysis. This paper is a summary of a panel discussion among scholars in urban informatics held at the 2020 International Association for China Planning(IACP).In this context, the panel outlines the definition of urban informatics, and the difference between urban informatics and urban analytic and computing, and found that urban informatics pays more attention to end user. This indicates that urban informatics has been more than a supporting role in urban planning or design, and is increasingly integrated with urban planning. The panel also discusses the connotation of urban informatics and its wide application in practice, and illustrates with examples. At the same time, the team identifies the difficulties of its development mainly reflected in the two aspects of resources and talents, and the learners of urban planning discipline have natural advantage in learning urban informatics. Finally, the panel discusses how to improve teaching, and concludes that the promotion of good cases, discipline integration, training data thinking rather than focusing too much on methods and other concepts. All in all, this panel's report contributes to the wider discussion about the role of urban informatics plays in urban planning. [ABSTRACT FROM AUTHOR]

Abstract Reducing CH 4 emissions is a major global challenge, owing to the world-wide rise in emissions and concentration of CH 4 in the atmosphere, especially in the past decade. China has been the greatest contributor to global anthropogenic CH 4 emissions for a long time, but current understanding towards its growing emissions is insufficient. This paper aims to link China's CH 4 emissions during 2005–2012 to their socioeconomic determinants by combining input-output models with structural decomposition analysis from both the consumption and income perspectives. Results show that changes in household consumption and income were the leading drivers of the CH 4 growth in China, while changes in efficiency remained the strongest factor offsetting CH 4 emissions. After 2007, with the global financial crisis and economic stimulus plans, embodied emissions from exports plunged but those from capital formation increased rapidly. The enabled emissions in employee compensation increased steadily over time, whereas emissions induced from firms' net surplus decreased gradually, reflecting the reform on income distribution. In addition, at the sectoral level, consumption and capital formation respectively were the greatest drivers of embodied CH 4 emission changes from agriculture and manufacturing, while employee compensation largely determined the enabled emission changes across all industrial sectors. The growth of CH 4 emissions in China was profoundly affected by the macroeconomic situation and the changes of economic structure. Examining economic drivers of anthropogenic CH 4 emissions can help formulate comprehensive mitigation policies and actions associated with economic production, supply and consumption. Highlights • We explore the socioeconomic determinants of China's growing CH 4 emissions. • Supply-side and demand-side structures in the economy affected CH 4 emission growth. • Key sectors and driving forces for embodied and enabled emissions are identified. • Adjusting economic structures could be more effective in mitigating CH 4 emissions. [ABSTRACT FROM AUTHOR]

Globalization has characterized geo-economic integrations of world regions via South-South, North-North, and South-North trades, which play a critical role in displacing global greenhouse gas emissions. Based on the global CH 4 emission inventories from the EDGAR database and the global multi-region input-output accounts from the EORA database, this study explores the trade-induced CH 4 emission transfers of 20 geographical regions of the world from 1990 to 2015. Global total CH 4 emissions increased by 19.13% in 2015 compared to 1990, while trade-related emissions increased by 46.28% over the same period. Western Europe, the USA, Japan, Other East Asia, and Mainland China were the largest five importers of embodied CH 4 emissions, while Sub-Saharan Africa, Russia, Middle East, Mainland China, and Southeast Asia were the largest five export regions of embodied CH 4 emissions. Substantial agriculture- and energy-related CH 4 emissions were transferred from developed regions to developing regions. The trade between economies from the global south and the global north had undergone positive changes, with the trade structure and transfer path showing a trend of divergence. Among the total CH 4 emissions embodied in international trade, the CH 4 emissions embodied in South-North trade accounted for more than half (55.94–62.72 Tg, 71%–55%) from 1990 to 2015. The CH 4 emissions embodied in the South-South trade accounted for 19%–34% (14.62–39.46 Tg), and the proportion of CH 4 emissions embodied in the North-North trade appeared to be relatively small (10%–11%, 8.05–12.82 Tg) during the period. It is imperative to strengthen South-South, South-North, and North-North cooperation in multilateral trade to jointly cut down the CH 4 emissions among world regions. [Display omitted] • The spatial and temporal evolution of global CH 4 emissions is studied. • The role of geo-economic integration in displacing regional emissions is revealed. • Agriculture- and energy-related CH 4 emission transfer is calculated. • South-South trade of CH 4 emissions rose from 19% to 34% from 1990 to 2015. • South-North trade of CH 4 emissions declined from 71% to 55% during the period. [ABSTRACT FROM AUTHOR]

Abstract Agriculture is one of the most important sectors for global anthropogenic methane (CH 4) and nitrous oxide (N 2 O) emissions. While much attention has been paid to production-side agricultural non-CO 2 greenhouse gas (ANGHG) emissions, less is known about the emissions from the consumption-based perspective. This paper aims to explore the characteristics of agricultural CH 4 and N 2 O emissions of global major economies by using the latest emission data from the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) and the recently available global multi-regional input-output model from the World Input-Output Database (WIOD). The results show that in 2014, the 42 major economies together accounted for 60.7% and 65.0% of global total direct and embodied ANGHG emissions, respectively. The consumption-based ANGHG emissions in the US, Japan, and the EU were much higher than their production-based emissions, while the converse was true for Brazil, Australia, and India. The global-average embodied ANGHG emissions per capita was 0.7 t CO 2 -eq, but major developing countries such as China, India, Indonesia and Mexico were all below this average value. We find that the total transfer of embodied ANGHG emissions via international trade was 622.4 Mt CO 2 -eq, 11.9% of the global total. China was the largest exporter of embodied ANGHG emissions, while the US was the largest importer. Most developed economies were net importers of embodied emissions. Mexico-US, China-US, China-EU, China-Japan, China-Russia, Brazil-EU, India-EU and India-US formed the main bilateral trading pairs of embodied emission flows. Examining consumption-based inventories can be useful for understanding the impacts of final demand and international trade on agricultural GHG emissions and identifying appropriate mitigation potentials along global supply chains. Highlights • We explore agricultural CH 4 and N 2 O emission characteristics of 42 major economies. • Impacts of final demand and international trade on ANGHG emissions are evaluated. • 622.4 Mt CO 2 eq CH 4 and N 2 O emissions in 2014 were embodied in international trade. • Developed economies as net importers had high per capita emission requirements. [ABSTRACT FROM AUTHOR]