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The Coupled Climate-Economy-Biosphere (CoCEB) model described herein takes an integrated assessment approach to simulating global change. By using an endogenous economic growth module with physical and human capital accumulation, this paper considers the sustainability of economic growth, as economic activity intensifies greenhouse gas emissions that in turn cause economic damage due to climate change. Different types of fossil fuels and different technologies produce different volumes of carbon dioxide in combustion. The shares of different fuels and their future evolution are not known. We assume that the dynamics of hydrocarbon-based energy share and their replacement with renewable energy sources in the global energy balance can be modeled into the 21st century by use of logistic functions. Various climate change mitigation policy measures are considered. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, we consider abatement activities also as an investment in overall energy eficiency of the economy and decrease of overall carbon intensity of the energy system. The paper shows that these efforts help to reduce the volume of industrial carbon dioxide emissions, lower temperature deviations, and lead to positive effects in economic growth. [ABSTRACT FROM AUTHOR]

Building on the richness of recent contributions in the field, this paper presents a state-of-the-art CNN analysis method for automating the recognition of standardised building components in modern heritage buildings. At the turn of the twentieth century manufactured building components became widely advertised for specification by architects. Consequently, a form of standardisation across various typologies began to take place. During this era of rapid economic and industrialised growth, many forms of public building were erected. This paper seeks to demonstrate a method for informing the recognition of such elements using deep learning to recognise 'families' of elements across a range of buildings in order to retrieve and recognise their technical specifications from the contemporary trade literature. The method is illustrated through the case of Carnegie Public Libraries in the UK, which provides a unique but ubiquitous platform from which to explore the potential for the automated recognition of manufactured standard architectural components. The aim of enhancing this knowledge base is to use the degree to which these were standardised originally as a means to inform and so support their ongoing care but also that of many other contemporary buildings. Although these libraries are numerous, they are maintained at a local level and as such, their shared challenges for maintenance remain unknown to one another. Additionally, this paper presents a methodology to indirectly retrieve useful indicators and semantics, relating to emerging HBIM families, by applying deep learning to a varied range of architectural imagery. [ABSTRACT FROM AUTHOR]

The Yangtze Economic Belt (hereafter, the Belt) is one of the most dynamic regions in China in terms of population growth, economic progress, industrialization, and urbanization. It faces many resource constraints (land, food, energy) and environmental challenges (pollution, biodiversity loss) under rapid population growth and economic development. Interactions between human and natural systems are at the heart of the challenges facing the sustainable development of the Belt. By adopting systematic thinking and the methodology of system dynamics simulation, an integrated system-dynamics-based simulation model for the Belt, named ANEMI_Yangtze, has been developed based on the third version of ANEMI3. The nine sectors of population, economy, land, food, energy, water, carbon, nutrients, and fish are currently included in ANEMI_Yangtze. This paper presents the ANEMI_Yangtze model description, which includes (i) the identification of the cross-sectoral interactions and feedbacks involved in shaping the Belt's system behavior over time; (ii) the identification of the feedbacks within each sector that drive the state variables in that sector; and (iii) the description of a new fish sector and modifications to the population, food, energy, and water sectors, including the underlying theoretical basis for model equations. The validation and robustness tests confirm that the ANEMI_Yangtze model can be used to support scenario development, policy assessment, and decision-making. This study aims to improve the understanding of the complex interactions among coupled human–natural systems in the Belt to provide the foundation for science-based policies for the sustainable development of the Belt. [ABSTRACT FROM AUTHOR]

Timely and accurate socioeconomic indicators are the prerequisite for smart social governance. For example, the level of economic development and the structure of population are important statistics for regional or national policy-making. However, the collection of these characteristics usually depends on demographic and social surveys, which are time- and labor-intensive. To address these issues, we propose a machine learning-based approach to estimate and map the economic development from multi-source open available geospatial data, including remote sensing imagery and OpenStreetMap road networks. Specifically, we first extract knowledge-based features from different data sources; then the multi-view graphs are constructed through different perspectives of spatial adjacency and feature similarity; and a multi-view graph neural network (MVGNN) model is built on them and trained in a self-supervised learning manner. Then, the handcrafted features and the learned graph representations are combined to estimate the regional economic development indicators via random forest models. Taking China's county-level gross domestic product (GDP) as an example, extensive experiments have been conducted and the results demonstrate the effectiveness of the proposed method, and the combination of the knowledge-based and learning-based features can significantly outperform baseline methods. Our proposed approach can advance the goal of acquiring timely and accurate socioeconomic variables through widely accessible geospatial data, which has the potential to extend to more social indicators and other geographic regions to support smart governance and policy-making in the future. [ABSTRACT FROM AUTHOR]

Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations. [ABSTRACT FROM AUTHOR]

Space technology and resources are used around the world to address societal challenges. Space provides valuable satellite services, unique scientific discoveries, surprising technology applications and new economic opportunities. Venezuela formally recognizes the advantages of space resources and pursues national level activity to harness them. Venezuela space cooperation has grown in the past several years, contributing to debates over Venezuela's rising influence in the Latin America. This paper summarizes the establishment and current development of space activities in the Bolivarian Republic of Venezuela, these activities are focused on the areas of telecommunications, Earth observation, research and development space and has as a primary goal the satisfaction of social needs. This analysis offers the elements most important of the Venezuelan space policy: technological transfer, capacity building and human training and international cooperation including the new participation of Venezuela in the international charter on space and major disasters. Our analysis shows that Venezuela has the potential to become a space leadership country, promoting the social welfare, integration, and sustainable development of Latin American countries. [ABSTRACT FROM AUTHOR]

This paper presents a historical analysis from socio-hydrological perspectives of the coupled human- groundwater system of the Cangzhou region in the North China Plain (NCP). The history of the "pendulum swing" for water allocation between the economic development and aquifer environmental health of the system is divided into five eras (i.e., natural, exploitation, degradation and restoration, drought-triggered deterioration, and returning to equilibrium). The system's evolution was interpreted using the Taiji-Tire model. Over-exploitation was considered as the main cause of aquifer depletion, and the groundwater utilization pattern was affected by the varying groundwater table. The aquifer depletion enhanced community sensitivity toward environmental issues, and upgraded the social productive force for restoration. The evolution of the system was substantially impacted by two droughts. The drought in 1965 induced the system from natural conditions to groundwater exploiting. The drought from 1997 to 2002 resulted in a surge in further groundwater abstraction and dramatic aquifer deterioration, and community sensitivity increased rapidly and induced the social productive force to a tipping point. From then on, the system returns to equilibrium through new policies and water-saving technologies. Along with the establishment of a strict water resource management strategy and the launch of the South-to-North Water Diversion Project, further restoration of groundwater environment was implemented. However, a comprehensive and coordinated drought management plan should be devised to avoid irreversible change in the system. [ABSTRACT FROM AUTHOR]

In the present Part 1 of a two-part paper, we formulate and study a simple Coupled Climate–Economy–Biosphere (CoCEB) model. This highly idealized model constitutes the basis of our integrated assessment approach to understanding the various feedbacks involved in the system. CoCEB is composed of a physical climate module, based on Earth's energy balance, and an economy module that uses endogenous economic growth with physical and human capital accumulation. We concentrate on the interactions between the two subsystems: the effect of climate on the economy, via damage functions, and the effect of the economy on climate, via control of greenhouse gas emissions. Simple functional forms of the relation between the two subsystems permit simple interpretations of the coupled effects. The CoCEB model is used to evaluate hypotheses on the long-term effect of investment in emission abatement, and on the comparative efficacy of different approaches to abatement. In this paper, we consider investments in low-carbon technologies. Carbon capture and storage (CCS), along with deforestation reduction, will be dealt with in Part 2. The CoCEB model is highly flexible and transparent; as such, it allows one to easily formulate and compare different functional representations of climate change mitigation policies. Using different mitigation measures and their cost estimates, as found in the literature, one is able to compare these measures in a coherent way. While many studies in the climate–economic literature treat abatement costs merely as an unproductive loss of income, this paper shows that mitigation costs do slow down economic growth over the next few decades, but only up to the mid-21st century or even earlier; growth reduction is compensated later on by having avoided negative impacts of climate change on the economy. [ABSTRACT FROM AUTHOR]

Yangtze Economic Belt is one of the most dynamic regions in China in terms of population growth, economic progress, industrialization, and urbanization. It faces many resource constraints (food, energy) and environmental challenges (pollution, biodiversity loss) under rapid population growth and economic development. Interactions between human and natural systems are at the heart of the challenges facing the sustainable development of the Yangtze Economic Belt. Understanding these interactions poses challenges because human and natural systems evolve in response to a wide range of influences. Accounting for these complex dynamics requires a system tool that can represent the fundamental drivers of change and responses of the individual system as well as how different systems interact and co-evolve. By adopting the system thinking and the methodology of system dynamics simulation, an integrated assessment model for the Yangtze Economic Belt, named ANEMI_Yangtze, is developed based on the third version of the global integrated assessment model, ANEMI. Nine sectors of population, economy, land, food, energy, water, carbon, nutrients, and fish are currently included in ANEMI_Yangtze. This paper identifies the opportunities and challenges facing the Yangtze Economic Belt and presents the ANEMI_Yangtze model structure. It also includes: (i) the identification of the cross-sectoral interactions and feedbacks involved in shaping Yangtze Economic Belt's system behaviour over time; (ii) the identification of the feedbacks within each sector that drive the state variables in that sector; and (iii) the explanation of the theoretical and mathematical basis for those feedbacks. ANEMI_Yangtze was developed and calibrated sector by sector before coupling them together into complete ANEMI_Yangtze model. After the validation and robustness test, the ANEMI_Yangtze model can be used to support decision making, policy assessment, and scenario development. This study aims to improve the understanding of the complex interactions among human and natural systems in the Yangtze Economic Belt to provide foundation for science-based policies for the sustainable development of the economic belt. [ABSTRACT FROM AUTHOR]

Karst rocky desertification occurs after vegetation deteriorates as a result of intensive land use, which leads to severe water loss and soil erosion and exposes basement rocks, creating a rocky landscape. Karst rocky desertification is found in humid areas in southwest China, the region most seriously affected by rocky desertification in the world. In order to promote ecological restoration and help peasants out of poverty, the Chinese government carried out the first phase of a rocky desertification control project from 2006 to 2015, which initially contained the expansion of rocky desertification. Currently, the Chinese government is prepared to implement the second phase of the rocky desertification control project, and therefore it is essential to summarise the lessons learned over the last 10 years of the first phase. In this paper, we analyse the driving social and economic factors behind rocky desertification, summarise the scientific research on rocky desertification in the region, and finally identify the main problems facing rocky desertification control. In addition, we put forward several policy suggestions that take into account the perspective of local peasants, scientific research, and China's economic development and urbanisation process. These suggestions include promoting the non-agriculturalization of household livelihoods, improving ecological compensation, strengthening the evaluation of rocky desertification control and dynamic monitoring, and strengthening research on key ecological function recovery technologies and supporting technologies. [ABSTRACT FROM AUTHOR]

This paper discusses the increasing interest in the territorial dimension of rural development in the Global South. Adapting the local development approach of the 1970s to the changing context of globalization and to the competitiveness discourse, mainstream development agencies and scholars currently see territorial development (TD) as an attractive model for the integration of rural regions into globalization dynamics. However, territory serves not only conventional mainstream ideologies, but also post-development thinking. It is shown that territory has turned out to be a crucial element for social movements in the defense of alternative visions of modernity and in the constitution of life worlds outside the conventional development path. The analysis of the meaning development actors give the term territory and the focus on the purposes for which it is mobilized allows a variety of possible development paths for the rural South to be identified, thus going beyond the prevailing modernist vision. [ABSTRACT FROM AUTHOR]

Based on the data of China's fourth, fifth and sixth population census, taking the seven geographical zone as research units, the Changing Spatial Patterns of China's Migration in 1985-2010 is studied by the means of spatial analysis and mathematical statistics. The empirical results show that: 1 The migration population in China was increasing a lot in 1985-2010, and the main part of it is Provincial migration. 2 The total number of migration, immigration and emigration, the relative proportion of inter provincial and provincial migration have been positively correlated to the regional economic development level. 3 The emigrations from Hong Kong, Macao, Taiwan and overseas mainly moved to East and North China. 4 Central and west of China are the main area where people outflowed from, and most migration population moved to south-eastern coastal areas. The migration in Northeast and northwest of China is still relatively small. The main direction of population migration and flowing is from west to east and from north to south. [ABSTRACT FROM AUTHOR]

The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) night-time light imagery has been proved to be a powerful tool to monitor economic development with its relatively high spatial resolution at large scales. Night-time lights caused by human activities derived from DMSP-OLS satellite imagery are widely used in socioeconomic parameter estimations and urbanization monitoring. In this paper, DMSP-OLS night-time stable light data from 1999 to 2012 are utilized to analyze inter-annual variation in GDP of per unit light intensity (RGDP) in China. Furthermore, RGDP was compared with statistical data of the tertiary industry structure for 28 provincial regions. The results show that the provincial RGDP decreased abruptly in 2001-2002, 2008-2009 and 2011-2012, which is consistent with the proportional growth of the tertiary industry in GDP. These results indicate that the changes in RGDP can reflect tertiary industry structural changes in China's province-level regions. [ABSTRACT FROM AUTHOR]

The assessment of natural hazards such as floods and droughts is a complex issue demanding integrated approaches and high quality data. Especially in African developing countries, where information is limited, the assessment of floods and droughts, though an overarching issue influencing economic and social development, is even more challenging. This paper presents an integrated approach to assess crucial aspects of floods and droughts in the transboundary Mekrou River basin (a portion of the Niger basin in West Africa) combining climatic trends analysis and the findings of a household survey. The multi-variables trend analysis estimates at the biophysical level the climate variability and the occurrence of floods and droughts. These results are coupled with the analysis of household survey data that reveal behaviors and opinions of the local residents regarding the observed climate variability and occurrence of flood and drought events, household mitigation measures and impacts of floods and droughts. Furthermore, two econometric models are set up to estimate the costs of floods and droughts of impacted households during a two years period (2014-2015) resulting into an average cost of approximately 495 euro per household for floods and 391 euro per household for droughts. [ABSTRACT FROM AUTHOR]

"The dragon and the elephant" between China and India is an important manifestation of global multipolarization in the 21st century. As an engine of global economic growth, China and India have similar development processes, different development models as well as differences in urban development, which have attracted widespread attention from scholars. Based on the 1992-2012 consecutive annual nighttime lighting data (DMSP-OLS), this paper uses the Gini coefficient, the Getis-Ord Gi* index and the Compounded Night Light Index (CNLI) to conduct a multi-scale comparative analysis of the differences in urban development between China and India from the perspective of geospatial. The results show that: (1) The space of urban land in the two countries expanded rapidly, with an average annual expansion rate of 5.24% and 3.85% respectively. China's urban land expansion rate is 1.36 times that of India. Among them, the arid resource towns in northwest China and the resource towns in central India have recently developed rapidly. (2) India's imbalance in development is more prominent than China's. China's regional and provincial imbalances are narrowing, while the regional differences in India are gradually widening. (3) The spatial pattern of land use in both countries shows a certain degree of coastal and inland differences. The main spatial pattern of China's regional development is the difference between East-Central-West, while the spatial pattern of regional development in India is North-South difference. (4) The strength of the expansion of the core cities of the two countries is quite different. From 1997 to 2007, China's core urban expansion intensity remained at a relatively high level while India was at a relatively low level. But from 2007 to 2012, India's core cities expanded at a relatively high level while China was at a relatively low level. [ABSTRACT FROM AUTHOR]

Enterprises organized in clusters are often efficient in stimulating urban development, productivity and profit outflows. Identifying clusters of economic activities (EAs) thus becomes an important step in devising regional development policies, aimed at facilitating regional economic development. However, a major problem with cluster identification stems from limited reporting of specific EAs by individual countries and administrative entities. Even Eurostat, which maintains most advances regional databases, provides data for less than 50% of all regional subdivisions of the 3rd tier of the Nomenclature of Territorial Units for Statistics (NUTS3). Such poor reporting impedes identification of EA clusters and economic forces behind them. In this study, we test a possibility that missing data on geographic concentrations of EAs can be reconstructed using Light-at-Night (LAN) satellite measurements, and that such reconstructed data can then be used for the identification of EA clusters. As we hypothesize, LAN, captured by satellite sensors, is characterized by different intensity, depending on its source - production facilities, services, etc., - and this information can be used for EA identification. The study was carried out in three stages. First, using nighttime satellite images, we determined what types of EAs can be identified, with a sufficient degree of accuracy, by LAN they emit. Second, we calculated multivariate statistical models, linking EAs concentrations with LAN intensities and several locational and development attributes of NUTS3 regions in Europe. Next, using the obtained statistical models, we restored missing data on EAs across NUTS3 regions in Europe and identified clusters of EAs, using spatial analysis tools. [ABSTRACT FROM AUTHOR]

In 2019 the ICA commission on map production and geoinformation management, together with the research group of cartography of the Vienna University of Technology, some schools and the publisher Jobstmedia, have started an initiative to collect the generation´s view on SDG and its expression with maps. The aim is a continuous edited book atlas in print and digital form, which illustrates the range of perspectives on the SDGs and their motivations for establishing a sustainable world (http://sdggeneration.cartography.at/). [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) are responsible for devastating impact and mass losses. Consequently, it is essential to diagnose all components of risk in order to quantitatively estimate how the TC-induced direct economic losses (DELs) respond to the changes in hazard, exposure and vulnerability. The probability distribution of TC-induced DEL records over the period 2000−2015 for the mainland of China appears to be a negative binomial. This paper quantifies the relationship between TC-induced DELs (L), maximum sustained wind (MSW), asset value (K) and per capita GDP (I) based on the economic concept of elasticity by the generalized linear model. The coefficients on three terms indicate that a doubling in MSW increases the DEL by 303%, a doubling in asset value exposure increases the DEL by 65%, while a doubling in per capita GDP leads to a 53% decrease in DEL. The results can be used for loss assessment of disasters that occur afterwards. The elasticity values suggest that continuing economic growth will take a heavy toll on TC-prone regions assuming no changes in mitigation and adaptation efforts. From another perspective, the results emphasize that human behavior matters to the formation of disasters and disaster risk reduction. [ABSTRACT FROM AUTHOR]

Sustainable Development Goals (SDGs) proposed by the United Nations (UN) General Assembly in September 2015, provided a global development agenda for all countries to use as a blueprint for progress on economic, social, and environmental sustainability. There are 17 Goals, 169 Targets and 230+ Indicators in SDGs, which specifically depends on multi-source data for monitoring and reporting on progress towards the associated targets and indicators. The existing evaluation methods are mainly based on statistic and survey data with lower spatiotemporal resolution, longer evaluation cycle, and higher cost. To monitor indicators of the SDGs quickly and accurately, it required us to explore new data sources and technology. In this paper, firstly, we reviewed comprehensively all indicators information (concepts and definitions, computation method, and data sources) in three Goals (SDG6, SDG11, and SDG15). Then, we analyzed the feasibility of monitoring accurately and quickly the above indicators on basis of available multi-source data (statistics, remote sensing, ground-based observations and internet data). Finally, a series of integration methods are developed to monitor several specific indicators with multi-source data. The methodology of this study provided experience for monitoring SDGs indicators in developing countries and filled the gap for the assessment of SDGs indicators at fine scale. [ABSTRACT FROM AUTHOR]

Both climate-change damages and climate-change mitigation will incur economic costs. While the risk of severe damages increases with the level of global warming (Dell et al., 2014; IPCC, 2014b, 2018; Lenton et al., 2008), mitigating costs increase steeply with more stringent warming limits (IPCC, 2014a; Luderer et al., 2013; Rogelj et al., 2015). Here, we show that the global warming limit that minimizes this century's total economic costs of climate change lies between 1.9 and 2 ∘ C, if temperature changes continue to impact national economic growth rates as observed in the past and if instantaneous growth effects are neither compensated nor amplified by additional growth effects in the following years. The result is robust across a wide range of normative assumptions on the valuation of future welfare and inequality aversion. We combine estimates of climate-change impacts on economic growth for 186 countries (applying an empirical damage function from Burke et al., 2015) with mitigation costs derived from a state-of-the-art energy–economy–climate model with a wide range of highly resolved mitigation options (Kriegler et al., 2017; Luderer et al., 2013, 2015). Our purely economic assessment, even though it omits non-market damages, provides support for the international Paris Agreement on climate change. The political goal of limiting global warming to "well below 2 degrees" is thus also an economically optimal goal given above assumptions on adaptation and damage persistence. [ABSTRACT FROM AUTHOR]

In the field of cultural tourism, slow routes, especially pedestrian and cycle routes, are considered important resources for sustainable, social and economic development of the territories. The cultural routes, defined by the Council of Europe, have extended the notion of conservation and valorization of cultural heritage to a wider territorial perspective, that allow to join tangible and intangible heritage dimensions, natural and built heritage, in a whole. In this framework, cultural routes, mainly used to rediscover the territory through slow-travel experience, need to be documented and ranked as a system of cultural heritage spread over the territory, by innovative and effective tools. The SQISR method (Spatial Quality Index of Slow Routes), at territorial level, allows to analyze the spatial features of slow routes through GIS-based mapping techniques, but also to compare alternative routes on the base of a set of heterogeneous indicators. The SQIRS method has been applied to evaluate two alternative itineraries of the Monks Route, that cross the agricultural landscape in southern Milan, with aim to document their spatial features and rank them in relation to their spatial quality. The SQISR method, that is based on a quantitative approach, allows to visualize the outcomes by different ways: graded GPS tracks, graphs, diagrams. [ABSTRACT FROM AUTHOR]

Culture heritage provides us an automatic sense of unity and belonging, which allows us to better understand previous generation and history of where we come from. The preservation of heritage is closely linked to the culture of society where culture plays a vital role in urban, economic and social development. The research aim is to overview the main principles of green architecture and identify the main heritage conservation approaches as a theoretical approach to identify the most suitable conservation approach that applies all the principles of the green architecture. The chosen approach will be applied on our case study "Vancouver city in Canada" to verity our conclusion from the theoretical study. [ABSTRACT FROM AUTHOR]

The Indus, Ganges, and Brahmaputra (IGB) river basins provide about 900 million people with water resources used for agricultural, domestic, and industrial purposes. These river basins are marked as "climate change hotspots", where climate change is expected to affect monsoon dynamics and the amount of meltwater from snow and ice, and thus the amount of water available. Simultaneously, rapid and continuous population growth as well as strong economic development will likely result in a rapid increase in water demand. Since quantification of these future trends is missing, it is rather uncertain how the future South Asian water gap will develop. To this end, we assess the combined impacts of climate change and socio-economic development on the future "blue" water gap in the IGB until the end of the 21st century. We apply a coupled modelling approach consisting of the distributed cryospheric–hydrological model SPHY, which simulates current and future upstream water supply, and the hydrology and crop production model LPJmL, which simulates current and future downstream water supply and demand. We force the coupled models with an ensemble of eight representative downscaled general circulation models (GCMs) that are selected from the RCP4.5 and RCP8.5 scenarios, and a set of land use and socio-economic scenarios that are consistent with the shared socio-economic pathway (SSP) marker scenarios 1 and 3. The simulation outputs are used to analyse changes in the water availability, supply, demand, and gap. The outcomes show an increase in surface water availability towards the end of the 21st century, which can mainly be attributed to increases in monsoon precipitation. However, despite the increase in surface water availability, the strong socio-economic development and associated increase in water demand will likely lead to an increase in the water gap during the 21st century. This indicates that socio-economic development is the key driver in the evolution of the future South Asian water gap. The transgression of future environmental flows will likely be limited, with sustained environmental flow requirements during the monsoon season and unmet environmental flow requirements during the low-flow season in the Indus and Ganges river basins. [ABSTRACT FROM AUTHOR]

Gross domestic product (GDP) represents a widely used metric to compare economic development across time and space. GDP estimates have been routinely assembled only since the beginning of the second half of the 20th century, making comparisons with prior periods cumbersome or even impossible. In recent years various efforts have been put forward to re-estimate national GDP for specific years in the past centuries and even millennia, providing new insights into past economic development on a snapshot basis. In order to make this wealth of data utilizable across research disciplines, we here present a first continuous and consistent data set of GDP time series for 195 countries from 1850 to 2009, based mainly on data from the Maddison Project and other population and GDP sources. The GDP data are consistent with Penn World Tables v8.1 and future GDP projections from the Shared Socio-economic Pathways (SSPs), and are freely available at http://doi.org/10. 5880/pik.2018.010 (Geiger and Frieler, 2018). To ease usability, we additionally provide GDP per capita data and further supplementary and data description files in the online archive. We utilize various methods to handle missing data and discuss the advantages and limitations of our methodology. Despite known shortcomings this data set provides valuable input, e.g., for climate impact research, in order to consistently analyze economic impacts from pre-industrial times to the future. [ABSTRACT FROM AUTHOR]

Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a mediumsized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change.We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a timevarying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment. [ABSTRACT FROM AUTHOR]

The unprecedented use of Earth's resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human-natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human-natural systems, the following eight lessons were identified that if taken into account by future coupled human-natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together. [ABSTRACT FROM AUTHOR]

The North China Plain (NCP) has become one of the most polluted regions in China, with the rapidly increasing economic growth in the past decades. High concentrations of ambient O3 and aerosol have been observed at urban as well as rural sites in the NCP. Most of the in situ observations of air pollutants have been conducted near the ground so that current knowledge about the vertical distributions of tropospheric O3 and aerosol over the NCP region is still limited. In this study, vertical profiles of O3 and size-resolved aerosol concentrations below 2.5 km were measured in summer 2014 over a rural site in the NCP, using an unmanned aerial vehicle (UAV) equipped with miniature analyzers. In addition, vertical profiles of aerosol scattering property in the lower troposphere and vertical profiles of O3 below 1 km were also observed at the site using a lidar and tethered balloon, respectively. The depths of the mixed layer and residual layer were determined according to the vertical gradients of lidar particle extinction and aerosol number concentration. Average O3 and size-resolved aerosol number concentration in both the mixed and residual layer were obtained from the data observed in seven UAV flights. The results show that during most of the flights the O3 levels above the top of mixed layer were higher than those below. Such a positive gradient in the vertical distribution of O3 makes the residual layer an important source of O3 in the mixed layer, particularly during the morning when the top of mixed layer is rapidly elevated. In contrast to O3, aerosol number concentration was normally higher in the mixed layer than in the residual layer, particularly in the early morning. Aerosol particles were overwhelmingly distributed in the size range<1 µm, showing slight differences between the mixed and residual layers. Our measurements confirm that the lower troposphere over the rural area of the NCP is largely impacted by anthropogenic pollutants locally emitted or transported from urban areas. Compared with the historic O3 vertical profiles over Beijing from the Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft (MOZAIC), a strong increase in O3 can be found at all heights below 2.5 km in the decade from 2004 to 2014, with the largest enhancement of about 41.6 ppb. This indicates that the lower troposphere over the northern part of the NCP has experienced rapidly worsening photochemical pollution. This worsening trend in photochemical pollution deserves more attention in the future. [ABSTRACT FROM AUTHOR]

The North China Plain (NCP) has been experiencing severe air pollution problems with rapid economic growth and urbanisation. Many field and model studies have examined the distribution of air pollutants in the NCP, but convincing results have not been achieved, mainly due to a lack of direct measurements of pollutants over large areas. Here, we employed a mobile laboratory to observe the main air pollutants in a large part of the NCP from 11 June to 15 July 2013. High median concentrations of sulfur dioxide (SO2) (12 ppb), nitrogen oxides (NOx) (NOCNO2; 452 ppb), carbon monoxide (CO) (956 ppb), black carbon (BC; 5.5 μgm-3) and ultrafine particles (28 350 cm-3) were measured. Most of the high values, i.e. 95 percentile concentrations, were distributed near large cities, suggesting the influence of local emissions. In addition, we analysed the regional transport of SO2 and CO, relatively long-lived pollutants, based on our mobile observations together with wind field and satellite data analyses. Our results suggested that, for border areas of the NCP, wind from outside this area would have a diluting effect on pollutants, while south winds would bring in pollutants that have accumulated during transport through other parts of the NCP. For the central NCP, the concentrations of pollutants were likely to remain at high levels, partly due to the influence of regional transport by prevalent south-north winds over the NCP and partly by local emissions. [ABSTRACT FROM AUTHOR]

To sustain growing food demand and increasing standard of living, global water use increased by nearly 6 times during the last 100 years, and continues to grow. As water demands get closer and closer to the water availability in many regions, each drop of water becomes increasingly valuable and water must be managed more efficiently and intensively. However, soaring water use worsens water scarcity conditions already prevalent in semi-arid and arid regions, increasing uncertainty for sustainable food production and economic development. Planning for future development and investments requires that we prepare water projections for the future. However, estimations are complicated because the future of the world's waters will be influenced by a combination of environmental, social, economic, and political factors, and there is only limited knowledge and data available about freshwater resources and how they are being used. TheWater Futures and Solutions (WFaS) initiative coordinates its work with other ongoing scenario efforts for the sake of establishing a consistent set of new global water scenarios based on the shared socio-economic pathways (SSPs) and the representative concentration pathways (RCPs). The WFaS "fasttrack" assessment uses three global water models, namely H08, PCR-GLOBWB, and WaterGAP. This study assesses the state of the art for estimating and projecting water use regionally and globally in a consistent manner. It provides an overview of different approaches, the uncertainty, strengths and weaknesses of the various estimation methods, types of management and policy decisions for which the current estimation methods are useful. We also discuss additional information most needed to be able to improve water use estimates and be able to assess a greater range of management options across the water-energy-climate nexus. [ABSTRACT FROM AUTHOR]

With the rapid growth in population and economic development, emissions of greenhouse gases (GHGs) from the Indian subcontinent have sharply increased during recent decades. However, evaluation of regional fluxes of GHGs and characterization of their spatial and temporal variations by atmospheric inversions remain uncertain due to a sparse regional atmospheric observation network. As a result of an Indo-French collaboration, three new atmospheric stations were established in India at Hanle (HLE), Pondicherry (PON) and Port Blair (PBL), with the objective of monitoring the atmospheric concentrations of GHGs and other trace gases. Here we present the results of the measurements of CO2, CH4, N2O, SF6, CO, and H2 from regular flask sampling at these three stations over the period 2007-2011. For each species, annual means, seasonal cycles and gradients between stations were calculated and related to variations in natural GHG fluxes, anthropogenic emissions, and monsoon circulations. Covariances between species at the synoptic scale were analyzed to investigate the likely source(s) of emissions. The flask measurements of various trace gases at the three stations have the potential to constrain the inversions of fluxes over southern and northeastern India. However, this network of ground stations needs further extension to other parts of India to better constrain the GHG budgets at regional and continental scales. [ABSTRACT FROM AUTHOR]

The combined effect of climate change and accelerated economic development in Northern regions increases the threat of permafrost related surface deformation to buildings and transportation infrastructure. Satellite based InSAR provides a means for monitoring infrastructure that may be both remote and spatially extensive. However, permafrost poses challenges for InSAR monitoring due to the complex temporal deformation patterns caused by both seasonal active layer fluctuations and long-term changes in permafrost thickness. These dynamics suggest a need for increasing the temporal resolution of multi-temporal InSAR methods. To address this issue we have developed a method that combines and jointly processes two or more same side geometry InSAR stacks to provide a high-temporal resolution estimate of surface deformation. The method allows for combining stacks from more than a single SAR sensor and for a combination of frequency bands. Data for this work have been collected and analysed for an area near the community of Umiujaq, Quebec in Northern Canada and include scenes from RADARSAT-2, TerraSAR-X and COSMO-SkyMed. Multiple stack based surface deformation estimates are compared for several cases including results from the three sensors individually and for all sensors combined. The test cases show substantially similar surface deformation results which correlate well with surficial geology. The best spatial coverage of coherent targets was achieved when data from all sensors were combined. The proposed multiple stack method is demonstrated to improve the estimation of surface deformation in permafrost affected areas and shows potential for deriving InSAR based permafrost classification maps to aid in the monitoring of Northern infrastructure. [ABSTRACT FROM AUTHOR]