OECD Regional Development Working Papers

doi:10.1787/20737009

Cited by 54 publications

(25 citation statements)

References 7 publications

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“…That is, there is a strong spatial autocorrelation of air pollutants in adjacent areas. However, most previous studies lack consideration of this factor and use classical statistical methods, such as ordinary least squares (OLS) [18,19] and correlation coefficients [59], which assume independent distribution, leading to estimation bias. Second, the resolution at which pollutant data are mapped in aggregate studies is usually 10 km × 10 km [60,61], which is too imprecise to identify the effect of the built environment at the scale of a city.…”

Section: Theoretical Hypothesismentioning

confidence: 99%

Impact of Population Density on PM2.5 Concentrations: A Case Study in Shanghai, China

Han

Sun

2019

Sustainability

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We examine the effects of the urban built environment on PM2.5 (fine particulate matter with diameters equal or smaller than 2.5 μm) concentrations by using an improved region-wide database, a spatial econometric model, and five built environment attributes: Density, design, diversity, distance to transit, and destination accessibility (the 5Ds). Our study uses Shanghai as a relevant case study and focuses on the role of density at the jiedao scale, the smallest administrative unit in China. The results suggest that population density is positively associated with PM2.5 concentrations, pointing to pollution centralization and congestion effects dominating the mitigating effects of mode-shifting associated with density. Other built environment variables, such as the proportion of road intersections, degree of mixed land use, and density of bus stops, are all positively associated with PM2.5 concentrations while distance to nearest primary or sub-center is negatively associated. Regional heterogeneity shows that suburban jiedao have lower PM2.5 concentrations when a subway station is present.

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Section: Theoretical Hypothesismentioning

confidence: 99%

Impact of Population Density on PM2.5 Concentrations: A Case Study in Shanghai, China

Han

Sun

2019

Sustainability

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“…Burke et al, 2015), (iii) there is a direct relationship between the type of cargo, volume of goods and handling technique (e.g. Merk & Dang, 2012;Walsh et al, 2017), and (iv) relative sea-level rise can be offset by raising port areas (e.g. Dronkers et al, 1990;Esteban et al, 2019).…”

Section: Approachmentioning

confidence: 99%

Demand for Ports to 2050: Climate Policy, Growing Trade and the Impacts of Sea‐Level Rise

Hanson

Nicholls

2020

Earth's Future

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Port infrastructure is critical to the world's economy and has seen major expansion over the last few decades. In the future there are likely to be further demands for port capacity which will require additional port area while existing ports will need upgrading in response to sea‐level rise to maintain current levels of operability. This analysis considers potential changes to 2050 under four climate‐based scenarios which aim to explore changes in international maritime trade consistent with global temperature increases of 2 °C and 4 °C and the implications of associated sea‐level rise. All scenarios anticipate a significant increase in trade, and a change in distribution across commodities. The demand for port handling areas in 2050 is roughly double to quadruple that of the baseline (2010) across scenarios. The maximum demand occurs under an unmitigated climate and high intensity in commodity movement with a maximum area in 2050 of 5,054km2. The minimum demand (2,510km2) occurs under a scenario of regionalized green energy production and lower material intensity. The total global investment costs for port adaptation to sea‐level rise and provision of new areas are between 223 and 768 billion USD to 2050. These are dominated by the need for new area construction with the adaptation of base year areas to relative sea‐level rise representing a maximum of 6% of total costs globally. Therefore, in addition to adapting existing port areas to sea‐level rise, it is equally or more important to consider provision of new ports.

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“…In 2010, Eurostat introduced a new regional typology which originated from a method developed by OECD (Brezzi, Dijkstra, & Ruiz, 2011). The method was based on grid square cells of 1 km 2 which in combination with the results of another Urban Audit provided an opportunity to revise the definition, borders and number of cities according to the idea of a densely populated area used in the degree of urbanisation classification.…”

Section: Literature Reviewmentioning

confidence: 99%

The statistical picture of population aging in towns of Wielkopolskie Province: TERYT and DE-GURBA perspectives

Klimanek¹,

Filas-Przybył²

2020

JEM

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Aim/purpose-The aim of the paper is to compare the statistical picture of aging of the urban population of the Wielkopolskie Province in terms of two typologies: TERYT and DEGURBA. Design/methodology/approach-Selected demographic aging measures for years 2010 and 2016 were calculated for 112 towns according to TERYT typology and for 53 urban areas according to DEGURBA classification. The demographic aging measures were the following: median age, parent support ratio, aging index, elderly dependency ratio, proportion of population aged 65 and over and total dependency ratio. Findings-TERYT classification using the formal and legal status of the city gives a slightly different picture in relation to urban areas defined based on the DEGURBA classification. The results obtained showed that the population aging process was slightly less intense in urban areas in 2016 according to the DEGURBA typology, compared with the indicators for the city group separated on the basis of the TERYT register identifier. Research implications/limitations-The results obtained are promising. The implications of the approach presented are at least twofold. At the methodological level, the paper presents an alternative possibility of distinguishing urban areas based on the DEGURBA classification in relation to the TERYT classification. However, in the cognitive layer, it shows differences in the aging of urban areas distinguished on the basis of these two classifications. These implications are limited only to the so-called traditional demographic aging measures and to urban population in the Wielkopolskie Province. To overcome these limitations further analysis should include, first of all, extending the research to the whole country.

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OECD Regional Development Working Papers

Cited by 54 publications

References 7 publications

Impact of Population Density on PM2.5 Concentrations: A Case Study in Shanghai, China

Impact of Population Density on PM2.5 Concentrations: A Case Study in Shanghai, China

Demand for Ports to 2050: Climate Policy, Growing Trade and the Impacts of Sea‐Level Rise

The statistical picture of population aging in towns of Wielkopolskie Province: TERYT and DE-GURBA perspectives

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