Large Asian Cities Research Articles

Aerosol characterization and peculiarities of source apportionment in Moscow, the largest and northernmost European megacity

High population and a wide range of activities in a megacity lead to large-scale ecological consequences which require the assessment with respect to distinct characteristics of climate, location, fuel consumption, and emission sources. In-depth study of aerosol characteristics was carried out in Moscow, the largest megacity in Europe, during the cold period (autumn and winter) and in spring. PM10 chemical speciation based on carbonaceous matter, water-soluble ions, and elements was carried out to reconstruct the PM mass and evaluate the primary and secondary aerosol contribution. For the whole study period organic matter, mineral dust, and secondary inorganic/organic accounted for 34, 24, and 16 % of PM10 mass, respectively. PM10, OC, and EC approached a maximum in spring and decreased in winter. Mineral dust seasonal fraction increased from spring (17 %) to autumn (32 %), and then decreased in winter (22 %). Secondary inorganic aerosols (SIA) in opposite showed the maximum 27 % in winter. K+ marked the residential biomass burning in the region surrounding a megacity in spring and autumn, agriculture fires in spring. In winter primary aerosol contribution dropped down 56 % while secondary approached practically equal 44 %. Source factors with the relative contributions are quantified, namely city dust (26 %), traffic (23 %), industrial (20 %), biomass burning (12 %), secondary (12 %), and de-icing salt (7 %); they were significantly varying between the cold heating period and springtime. The relevance of sources to meteorological parameters and mass transportation is investigated by using both bivariate polar plots and Lagrangian integrated trajectory (HYSPLIT) model. Trajectory clustering demonstrates regional sources being crucial contributors to PM10 pollution. Aerosol speciation and source apportion factors identify the differences of the Moscow urban background among large European and Asian cities due to northern climate conditions, fast construction, long-range transport from industrial-developing area surrounding a city, regional biomass burning preferably in spring and autumn, and winter road management.

Atmospheric Ultrafine Particulate Matter (PM0.1)-Bound Carbon Composition in Bangkok, Thailand

Seasonal variations in atmospheric ultrafine particulate matter (PM0.1) were monitored in Bangkok, Thailand, from 2016 to 2017. PM0.1-bound organic carbon (OC) and elemental carbon (EC) were collected by a cascade air sampler that can collect PM0.1 and were analyzed by a Thermal-Optical carbon analyzer following the IMPROVE-TOR protocol. The annual average PM0.1 in Bangkok was 14.5 ± 4.7 µg/m3, which is higher than in large Asian cities such as Shanghai and Hanoi. Biomass burning from neighboring areas was shown to increase the particle concentration. Apparent increases in carbon species such as OC and EC, and the OC/EC ratios in the wet and dry seasons were observed; the Char-EC/Soot-EC ratio revealed that the PM0.1 in the Bangkok atmosphere was influenced mainly by vehicle exhausts, even though the influence of biomass burning was greater during the dry season. The effective carbon ratio (ECR) shows that Bangkok’s carbonaceous aerosol is light-absorbing and -scattering. The higher SOC/OC in the dry season indicates the high level of secondary sources forming smaller particles from the combustion sources in Bangkok, increasing light scattering during these periods, and contributing to climate and air quality. The findings of this work are of great importance to air pollutant control policies in urban areas.

Proposal of LCZ categories and standards considering super high‐rise buildings suited for Asian cities based on the analysis of urban morphological properties of Tokyo

AbstractThe Local Climate Zone (LCZ) scheme is an urban classification system which classifies urban areas into discrete local climates by morphological and land cover characteristics, proposed based on urban heat island researches in 1970s to 2000s. However, while the original scheme defines high‐rise buildings as areas higher than 25 m on average, buildings over 100 m have become more common in Asia since the 2000s. With the heterogeneity of urban areas, directly applying the original LCZ scheme to Asian cities has become difficult. Studies to incorporate the heterogeneity of urban morphology into the scheme have been conducted by researchers, although the increase in the number of taller buildings is not explored. This study proposes, LCZ categories and standards considering the super high‐rise buildings in Asian cities for a detailed categorization of urban morphology. For this, the urban morphological characteristics of Tokyo Metropolis, with a wide range of morphologies that exist in Asian cities, were analyzed. The proposal was made based on this analysis in relation to the thermal characteristics. Then, the characteristics of land surface temperature in each LCZ category were investigated in Shanghai and Xi'an, which indicated the applicability of the proposed categories to mid to large scale Asian cities.

Quantifying social segregation in large-scale networks

We present a measure of social segregation which combines mobile phone data and income register data in Oslo, Norway. In addition to measuring the extent of social segregation, our study shows that social segregation is strong, robust, and that social networks are particularly clustered among the richest. Using location data on the areas where people work, we also examine whether exposure to other social strata weakens measured segregation. Lastly, we extend our analysis to a large South Asian city and show that our main results hold across two widely different societies.

An Efficient Simulation-Based Approach to Ambulance Fleet Allocation and Dynamic Redeployment

We present an efficient approach to ambulance fleet allocation and dynamic redeployment, where the goal is to position an entire fleet of ambulances to base locations to maximize the service level (or utility) of the Emergency Medical Services (EMS) system. We take a simulation-based approach, where the utility of an allocation is measured by directly simulating emergency requests. In both the static and dynamic settings, this modeling approach leads to an exponentially large action space (with respect to the number of ambulances). Futhermore, the utility of any particular allocation can only be measured via a seemingly “black box” simulator. Despite this complexity, we show that embedding our simulator within a simple and efficient greedy allocation algorithm produces good solutions. We derive data-driven performance guarantees which yield small optimality gap. Given its efficiency, we can repeatedly employ this approach in real-time for dynamic repositioning. We conduct simulation experiments based on real usage data of an EMS system from a large Asian city, and demonstrate significant improvement in the system’s service levels using static allocations and redeployment policies discovered by our approach.

Neo-Tokyo: Distopia Urbana e Cidades Genéricas

Em Akira (1988) temos uma representação da cidade de Tóquio (neste caso Neo Tokyo) que serve de valioso documento histórico no que diz respeito ao imaginário relativo às transformações pelas quais a cultura, tecnologia e as cidades japonesas passaram durante a segunda metade do século XX. Por lidar com reflexões relativas ao caldeirão do pensamento sócio-econômico-cultural das megacidades asiáticas, a película dialoga com as reflexões de Rem Koolhaas acerca da formação e características das “Cidades Genéricas”, expostas em S,M,L,XL, de 1995. A perda da identidade das grandes cidades asiáticas é discutida neste artigo traçando-se um paralelo entre os textos de Koolhaas e a visão de Katsuhiro Otomo, roteirista e diretor do longa. A primeira parte deste artigo trata da importância de Akira na formulação de um imaginário contemporâneo relativo à cidade de Tóquio, bem como da capacidade que esta obra tem ao capturar e representar questões relativas ao Japão urbano do período. Na segunda parte há um breve comentário sobre a cultura e sociedade japonesas deste período. A cidade de Neo Tokyo, em si, é o objeto da terceira parte, sendo esta distopia comparada em diversos aspectos à utopia apresentada por Kenzo Tange em 1961, em seu plano para a ocupação da Baía de Tóquio. Também nesta terceira parte são observados mais detalhadamente os aspectos que aproximam a representação distópica da mega metrópole asiática àqueles explorados por Koolhaas. Na quarta e última parte, há um comentário final sobre as razões pelas quais o cyberpunk japonês tem tanto apelo ao público ocidental e sua capacidade de síntese e expressão dos problemas enfrentados pelas grandes cidades asiáticas.

Agricultural permanence in large Asian cities: a case study of Nanjing, China

ABSTRACT Nanjing, the capital of China's Jiangsu Province, has grown rapidly during the post-reform era and the pace of change placed tremendous pressure on the city's arable land resources. This case study of land use/land cover change (LU/LC) in Nanjing's Jiangning district assesses changes in agricultural land, production, and labor within the ten 2016-era jiedao (sub-district political units) of Jiangning from 2000 to 2015. This case study provides an opportunity to assess an important component of the Ginsburg-McGee desakota hypothesis predicting that Asian extended metropolis regions, unlike similar large cities in Western nations, will consistently maintain agricultural land and labor supplies within metropolitan boundaries. The study is based on field visits combined with time-series LU/LC analyses of a GIS database joining archived agricultural and agro-economic data with additional LU/LC data layers derived from satellite imagery including Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM) imagery. Results show Jiangning continues to retain high, if decreasing, proportions of agricultural land and employment. After significant decreases for all ten jiedao from 2000 to 2010, government policies appear to have helped stabilize arable land losses from 2010 to 2015. Jiedao in the closest proximity to Nanjing's central business districts lost arable land at greater rates than those in the periphery. OLS linear multiple regression analyses identified factors that are the most effective predictors of arable land persistence including lower mean annual income, higher percentage of men in the farm workforce, higher reliance on traditional double-cropped rice-wheat, and less vegetable production.

MICS-Asia III: multi-model comparison and evaluation of aerosol over East Asia

Abstract. A total of 14 chemical transport models (CTMs) participated in the first topic of the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. These model results are compared with each other and an extensive set of measurements, aiming to evaluate the current CTMs' ability in simulating aerosol concentrations, to document the similarities and differences among model performance, and to reveal the characteristics of aerosol components in large cities over East Asia. In general, these CTMs can well reproduce the spatial–temporal distributions of aerosols in East Asia during the year 2010. The multi-model ensemble mean (MMEM) shows better performance than most single-model predictions, with correlation coefficients (between MMEM and measurements) ranging from 0.65 (nitrate, NO3-) to 0.83 (PM2.5). The concentrations of black carbon (BC), sulfate (SO42-), and PM10 are underestimated by MMEM, with normalized mean biases (NMBs) of −17.0 %, −19.1 %, and −32.6 %, respectively. Positive biases are simulated for NO3- (NMB = 4.9 %), ammonium (NH4+) (NMB = 14.0 %), and PM2.5 (NMB = 4.4 %). In comparison with the statistics calculated from MICS-Asia phase II, frequent updates of chemical mechanisms in CTMs during recent years make the intermodel variability of simulated aerosol concentrations smaller, and better performance can be found in reproducing the temporal variations of observations. However, a large variation (about a factor of 2) in the ratios of SNA (sulfate, nitrate, and ammonium) to PM2.5 is calculated among participant models. A more intense secondary formation of SO42- is simulated by Community Multi-scale Air Quality (CMAQ) models, because of the higher SOR (sulfur oxidation ratio) than other models (0.51 versus 0.39). The NOR (nitric oxidation ratio) calculated by all CTMs has larger values (∼0.20) than the observations, indicating that overmuch NO3- is simulated by current models. NH3-limited condition (the mole ratio of ammonium to sulfate and nitrate is smaller than 1) can be successfully reproduced by all participant models, which indicates that a small reduction in ammonia may improve the air quality. A large coefficient of variation (CV > 1.0) is calculated for simulated coarse particles, especially over arid and semi-arid regions, which means that current CTMs have difficulty producing similar dust emissions by using different dust schemes. According to the simulation results of MMEM in six large Asian cities, different air-pollution control plans should be taken due to their different major air pollutants in different seasons. The MICS-Asia project gives an opportunity to discuss the similarities and differences of simulation results among CTMs in East Asian applications. In order to acquire a better understanding of aerosol properties and their impacts, more experiments should be designed to reduce the diversities among air quality models.

Fast methods for finding significant motifs on labelled multi-relational networks

Abstract A labelled multi-relational network (or labelled multigraph, for short) is one in which nodes have labels and a pair of nodes may be connected by an edge with one or more labels. For example, in an airline route database, ‘large European city’ may be the label on the Paris node and ‘large Asian city’ may be the label on the New Delhi node and the edge between the two cities may be labelled by several carriers. This article presents an analytical method to compute the p-values of labelled subgraph (sub-network) motifs in such labelled multi-relational networks (multigraphs). The method (and a fast approximation to the method) works for both directed and undirected graphs and extends to large subgraphs. We have validated these methods on a dataset of medium size real networks (up to tens of thousands of nodes and hundreds of thousands of edges) of different types (biological, infrastructural and collaboration networks). The pure analytical model is faster than a randomized simulation model by a factor of approximately 1000 in most of our experiments. This improvement in performance is greater for larger graphs. The approximate analytical model avoids the calculations of statistical variance and achieves nearly the same precision and recall as the pure analytical model while being several times faster. To test the scalability of our methods, we run our algorithms on synthetic and real datasets from protein–protein interaction networks, airline flight paths, the internet infrastructural network and the IMDB movie network. We also illustrate a use case of this form of analysis on a large relationship network of people involved in the Panama papers scandal, retrieving frequently used money laundering patterns. labelled multigraphs motif enumeration; motif statistical significance; random network models; multi-relational networks; multigraphs.

Publisher's Note: Generic patterns in the evolution of urban water networks: Evidence from a large Asian city [Phys. Rev. E 95 , 032312 (2017)

This corrects the article DOI: 10.1103/PhysRevE.95.032312.

Urban Transport and Eco-Urbanism: A Global Comparative Study of Cities with a Special Focus on Five Larger Swedish Urban Regions

Urban transport is critical in shaping the form and function of cities, particularly the level of automobile dependence and sustainability. This paper presents a detailed study of the urban transport eco-urbanism characteristics of the Stockholm, Malmö, Göteborg, Linköping, and Helsingborg urban regions in southern Sweden. It compares these cities to those in the USA, Australia, Canada, and two large wealthy Asian cities (Singapore and Hong Kong). It finds that while density is critical in determining many features of eco-urbanism, especially mobility patterns and particularly how much public transport, walking, and cycling are used, Swedish cities maintain healthy levels of all these more sustainable modes and only moderate levels of car use, while having less than half the density of other European cities. Swedish settlement patterns and urban transport policies mean they also enjoy, globally, the lowest level of transport emissions and transport deaths per capita and similar levels of energy use in private passenger transport as other European cities, and a fraction of that used in lower density North American and Australian cities. Swedish urban public transport systems are generally well provided for and form an integral part of the way their cities function, considering their lower densities. Their use of walking and cycling is high, though not as high as in other European cities and together with public transport cater for nearly 50% of the total daily trip making, compared to auto-dependent regions with between about 75% and 85% car trips. The paper explores these and other patterns in some detail. It provides a clear depiction of the strengths and weaknesses of Swedish cities in urban transport, some key policy directions to improve them and posits possible explanations for some of the atypical patterns observed.

Strategiczne węzły miejskie w wielkich miastach Azji Południowo-Wschodniej

Celem pracy – jest charakterystyka przestrzeni publicznej w ośrodkach Azji Południowo -Wschodniej1 na tle współczesnych problemów rozwoju wielkich miast. Poprzez węzły miejskie autor dokonuje analizy centrum w strategicznych ośrodkach tego regionu. W dzisiejszych czasach tworzenie nowych trendów miastotwórczych uległo ograniczeniu na kontynencie europejskim (tu wiodącym pozostaje – proces rewitalizacji) przenosząc się do Azji i Afryki, gdzie na naszych oczach kreowane są ogromne nowe kwartały i miasta (często w sposób gwałtowny i niezmiernie szybki). Poruszane problemy w artykule odnoszą się do sposobu kształtowania struktury przestrzeni publicznych wielkich miast, obejmującej nowe zjawiska urbanistyczne, które funkcjonują na tle znanych i zdiagnozowanych zjawisk jak metropolizacja czy globalizacja. Strategiczne elementy struktury metropolitarnej wielkich miast azjatyckich są niejednokrotnie przyczynkiem do tworzenia nowych niezależnych dzielnic – regionów wpływających na podziały i fragmentaryzację samej przestrzeni publicznej, a w konsekwencji na wyodrębnienie niezależnych ośrodków.

A Methodology of Health Effects Estimation from Air Pollution in Large Asian Cities

The increase of health effects caused by air pollution seems to be a growing concern in Asian cities with increasing motorization. This paper discusses methods of estimating the health effects of air pollution in large Asian cities. Due to the absence of statistical data in Asia, this paper carefully chooses the methodology using data of the Japanese compensation system. A basic idea of health effects will be captured from simple indicators, such as population and air quality, in a correlation model. This correlation model enables more estimation results of respiratory mortality caused by air pollution to be yielded than by using the relative model. The correlation model could be an alternative method to estimate mortality besides the relative risk model since the results of the correlation model are comparable with those of the relative model by city and by time series. The classification of respiratory diseases is not known from the statistical yearbooks in many countries. Estimation results could support policy decision-making with respect to public health in a cost-effective way.

Generic patterns in the evolution of urban water networks: Evidence from a large Asian city.

We examine high-resolution urban infrastructure data using every pipe for the water distribution network (WDN) and sanitary sewer network (SSN) in a large Asian city (≈4 million residents) to explore the structure as well as the spatial and temporal evolution of these infrastructure networks. Network data were spatially disaggregated into multiple subnets to examine intracity topological differences for functional zones of the WDN and SSN, and time-stamped SSN data were examined to understand network evolution over several decades as the city expanded. Graphs were generated using a dual-mapping technique (Hierarchical Intersection Continuity Negotiation), which emphasizes the functional attributes of these networks. Network graphs for WDNs and SSNs are characterized by several network topological metrics, and a double Pareto (power-law) model approximates the node-degree distributions of both water infrastructure networks (WDN and SSN), across spatial and hierarchical scales relevant to urban settings, and throughout their temporal evolution over several decades. These results indicate that generic mechanisms govern the networks' evolution, similar to those of scale-free networks found in nature. Deviations from the general topological patterns are indicative of (1) incomplete establishment of network hierarchies and functional network evolution, (2) capacity for growth (expansion) or densification (e.g., in-fill), and (3) likely network vulnerabilities. We discuss the implications of our findings for the (re-)design of urban infrastructure networks to enhance their resilience to external and internal threats.

Equivalent full-load hours for assessing climate change impact on building cooling and heating energy consumption in large Asian cities

Estimating cooling and heating energy requirements is an integral part of designing and managing buildings. Further, as buildings are among the largest energy consumers in cities, the estimates are important for formulating effective energy conservation strategies. Where complex hourly simulation models are not favored, such estimates may be derived by simplified methods that are less computationally intensive but still provide results that are reasonably close to those obtained from the more complicated approach. The equivalent full load hours (EFLH) method is a simplified energy estimation method that has recently gained popularity. It offers a straightforward means of evaluating energy efficiency programs. However, to date, easily accessible EFLH data exist only for a very limited number of countries in North America and Europe, but not Asia. This current work provides previously unavailable monthly EFLH data for building cooling and heating in three large Asian cities, viz. Hong Kong, Seoul and Tokyo. To assess the effects of changing temperature over the course of decades on building cooling and heating energy consumption, EFLH data are calculated for three time periods: past (1983–2005), present (2006–2014) and future (2015–2044). The projections for the future time period are based on the climate scenarios Representative Concentration Pathways (RCPs) 4.5 and 8.5 of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report. RCP-4.5 assumes a stabilization of future greenhouse gas (GHG) emissions followed by a reduction, while RCP-8.5 assumes their further increase. From the EFLH data, considering just the effects of ambient temperature changes, it is projected the total energy required to heat and/or cool residential dwellings in Hong Kong, Seoul and Tokyo to increase by 18.3%, 4% and 10.4%, respectively over 62years from 1983 to 2044 in the case of RCP-4.5, and by 23.3%, 9.3% and 15.8%, respectively in the case of RCP-8.5. This shows that even with future stabilization and reduction of GHG emissions, as per scenario RCP-4.5, the energy needs of the three cities for building heating and cooling combined can be expected to increase over the next few decades. This has significant implications, namely increased demands for additional primary energy, which will result in further GHG emissions. These effects, however, can be controlled with adjustments to the electricity fuel mix of each location, and also by use of more efficient heating, ventilation and air-conditioning (HVAC) devices.

Learning Individual Behavior Using Sensor Data: The Case of GPS Traces and Taxi Drivers

The ubiquitous deployment of mobile and sensor technologies has led to both the capacity to observe human behavior in physical (offline) settings as well as to record it. This provides researchers with a new lens to study and better understand the individual decision processes that were previously unobserved. In this paper, we study decision making behavior of 11,196 taxi drivers in a large Asian city using a rich data set consisting of 10.6 million fine-grained GPS trip records. These records include detailed taxi GPS trajectories, taxi occupancy data (i.e., whether a taxi was occupied with a passenger or was vacant) and taxi drivers’ daily incomes. This capacity to use data where occupancy of the taxi is known is a distinctive feature of our data set and sets this work apart from prior work which has attempted to study driver behavior. The specific decision we focus on pertains to actions drivers take to find new passengers after they have dropped off their current passengers. In particular, we study the role of information derivable from the GPS trace data (e.g., where passengers are dropped off, where passengers are picked up, longitudinal taxicab travel history with fine-grained time stamps) observable by or made available to drivers in enabling them to learn the distribution of demand for their services over space and time. We conduct our study using a heterogeneous Bayesian learning model. We find strong heterogeneity in individual learning behavior and driving decisions, which is significantly associated with individual economic outcomes. Drivers with higher incomes benefit significantly from their ability to learn from not only demand information directly observable in the local market, but also aggregate information on demand flows across markets. Interestingly, our policy simulations indicate information that is noisy at the individual level becomes valuable after being aggregated across various spatial and temporal dimensions. Moreover, the value of information does not increase monotonically with the scale and frequency of information sharing. Finally, our study has important welfare implications in that efficient information sharing leads to an income increase among all drivers, instead of a redistribution of income between different types of drivers. Our work allows us not only to explain driver decision making behavior using these detailed behavioral traces, but also to prescribe information sharing strategy for the firm in order to improve the overall market efficiency.

Strategic Planning for Setting Up Base Stations in Emergency Medical Systems

Emergency Medical Systems (EMSs) are an important component of public health-care services. Improving infrastructure for EMS and specifically the construction of base stations at the ”right” locations to reduce response times is the main focus of this paper. This is a computationally challenging task because of the: (a) exponentially large action space arising from having to consider combinations of potential base locations, which themselves can be significant; and (b) direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that maximises the service level of EMS. Using the properties of submodular optimisation we show that our greedy algorithm provides quality guaranteed solutions for one of the objectives employed in real EMSs. Furthermore, we validate our derived policy by employing a real-life event driven simulator that incorporates the real dynamics of EMS. Finally, we show the utility of our approaches on a real-world dataset from a large asian city and demonstrate significant improvement over the best known approaches from literature.

Characterizing street hierarchies through network analysis and large-scale taxi traffic flow: a case study of Wuhan, China

Hierarchy is an important property of a street network, which suggests that only a small number of streets are prominent. A previous empirical study of a European city has identified four levels of scale in a street network, namely the top 1%, top 20%, bottom 80%, and bottom 20%. This paper investigates such street hierarchies in a large Asian city, Wuhan, with a complicated network of streets. Based on network analysis, we find that street hierarchies in this case study are slightly different so that the fourth scale is adjusted from the initial 20 to 25%. The detected street hierarchies are further compared to the intensity of large-scale traffic flows at different time scales. We find that distributions of both daily and hourly traffic conform well to the street hierarchies. More specifically, the 20% of top streets accommodate about 98% of traffic flow, and the 1% of top streets account for more than 60% of traffic flow. Moreover, this finding indicates that the current street network of Wuhan needs to be improved because the top 20% of streets are rather overburdened leading to traffic congestion. Our study not only provides new quantitative evidence as to the emergence of street hierarchies but also highlights the possible traffic congestion.

High burden of prediabetes and diabetes in three large cities in South Asia: The Center for cArdio-metabolic Risk Reduction in South Asia (CARRS) Study

AimTo estimate the prevalence of, and assess factors associated with, diabetes and prediabetes in three South Asian cities. MethodsUsing a multi-stage cluster random sample representative of each city, 16,288 subjects aged ≥20 years (Chennai: 6906, Delhi: 5365 and Karachi: 4017) were recruited to the Centre for cArdio-metabolic Risk Reduction in South-Asia (CARRS) Study. Fasting plasma glucose (FPG) and glycosylated hemoglobin (HbA1c) were measured in 13720 subjects. Prediabetes was defined as FPG 100–125mg/dl (5.6–6.9mmol/l) and/or HbA1c 5.7–6.4% (39–46mmol/mol) and diabetes as self-report and/or drug treatment for diabetes and/or FPG≥126mg/dl (≥7.0mmol/l) and/or HbA1c≥6.5% (48mmol/mol). We assessed factors associated with diabetes and prediabetes using polytomous logistic regression models. ResultsOverall 47.3–73.1% of the population had either diabetes or prediabetes: Chennai 60.7% [95%CI: 59.0–62.4%] (diabetes – 22.8% [21.5–24.1%], prediabetes – 37.9% [36.1–39.7%]); Delhi 72.7% [70.6–74.9%] (diabetes – 25.2% [23.6–26.8%], prediabetes – 47.6% [45.6–49.5%]); and Karachi 47.4% [45.7–49.1%]; (diabetes – 16.3% [15.2–17.3%], prediabetes – 31.1% [29.5–32.8%], respectively). Proportions of self-reported diabetes were 55.1%, 39.0%, and 48.0% in Chennai, Delhi, and Karachi, respectively. City, age, family history of diabetes, generalized obesity, abdominal obesity, body fat, high cholesterol, high triglyceride, and low HDL cholesterol levels were each independently associated with prediabetes, while the same factors plus waist-to-height ratio and hypertension were associated with diabetes. ConclusionSix in ten adults in large South Asian cities have either diabetes or prediabetes. These data call for urgent action to prevent diabetes in South Asia.

Non-Myopic Adaptive Route Planning in Uncertain Congestion Environments

We consider the problem of adaptively routing a fleet of cooperative vehicles within a road network in the presence of uncertain and dynamic congestion conditions. To tackle this problem, we first propose a Gaussian process dynamic congestion model that can effectively characterize both the dynamics and the uncertainty of congestion conditions. Our model is efficient and thus facilitates real-time adaptive routing in the face of uncertainty. Using this congestion model, we develop efficient algorithms for non-myopic adaptive routing to minimize the collective travel time of all vehicles in the system. A key property of our approach is the ability to efficiently reason about the long-term value of exploration, which enables collectively balancing the exploration/exploitation trade-off for entire fleets of vehicles. Our approach is validated by traffic data from two large Asian cities. Our congestion model is shown to be effective in modeling dynamic congestion conditions. Our routing algorithms also generate significantly faster routes compared to standard baselines, and achieve near-optimal performance compared to an omniscient routing algorithm. We also present the results from a preliminary field study, which showcases the efficacy of our approach.