Global scenarios of urban density and its impacts on building energy use through 2050.

Although the scale of impending urbanization is well-acknowledged, we have a limited understanding of how urban forms will change and what their impact will be on building energy use. Using both top-down and bottom-up approaches and scenarios, we examine building energy use for heating and cooling. Globally, the energy use for heating and cooling by the middle of the century will be between 45 and 59 exajoules per year (corresponding to an increase of 7-40% since 2010). Most of this variability is due to the uncertainty in future urban densities of rapidly growing cities in Asia and particularly China. Dense urban development leads to less urban energy use overall. Waiting to retrofit the existing built environment until markets are ready in about 5 years to widely deploy the most advanced renovation technologies leads to more savings in building energy use. Potential for savings in energy use is greatest in China when coupled with efficiency gains. Advanced efficiency makes the least difference compared with the business-as-usual scenario in South Asia and Sub-Saharan Africa but significantly contributes to energy savings in North America and Europe. Systemic efforts that focus on both urban form, of which urban density is an indicator, and energy-efficient technologies, but that also account for potential co-benefits and trade-offs with human well-being can contribute to both local and global sustainability. Particularly in growing cities in the developing world, such efforts can improve the well-being of billions of urban residents and contribute to mitigating climate change by reducing energy use in urban areas.

Response of vegetation phenology to urbanization in the conterminous United States.

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003-2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends later (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6-6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.

Effects of land use intensity on the natural attenuation capacity of urban soils in Beijing, China.

Urban soils are major sinks that provide the services of attenuating and detoxifying environmental pollutants. This significant ecosystem service of urban soil can be evaluated by the natural attenuation capacity (NAC). In this research, we develop a method to calculate the natural pollutant attenuation capacity of urban soils on the basis of 5 chemical and physical measurements. By selecting municipal parks soils for reference, we assessed the spatial and temporal changes of NAC in Beijing city soils under influences of rapid urbanization. Results indicated that NAC was increasingly impacted by land use in the order: parks

[Characteristics and drivers of vegetation temporal dynamics in Hunan Province of China during 2002-2020]. / 湖南省2002­2020å¹´æ¤è¢«åŠ¨æ€æ¼”å˜ç‰¹å¾åŠå½±å“å› å­.

Understanding the influences of climate change and human activities on vegetation change is the foundation for effective ecosystem management. Based on the 250 m MODIS-NDVI data from 2002 to 2020, we employed Theil-Sen Median trend analysis and the Mann-Kendall test to quantify vegetation change in Hunan Province. By combining with meteorological, nighttime light index, land cover and other data, residual analysis and correlation analysis, we examined the impacts of human activities and climate change on vegetation dynamics at both the pixel level and the county level. The results showed that the normalized difference vegetation index (NDVI) in Hunan Province exhibited a spatial pattern of "overall improvement with localized degradation" during 2002-2020. Approximately 64.9% of the study area experienced significant vegetation improvement, mainly occurring in the western and central-southern parts of Hunan Province. 1.4% of the study area experienced significant vegetation degradation, mostly in the newly developed urban areas and the farmland in the Dongting Lake Plain. Human activities and climate change jointly promoted vegetation improvement in 67.9% of the study area. Human activities and climate contributed to 96% and 4% of the NDVI change, respectively. At the county level, human activities contributed to over 80% of the NDVI change in each district or county. The impacts of human activities on vegetation change exhibited significant spatial heterogeneity. Urban expansion led to vegetation degradation in the newly developed areas, while vegetation growth appeared in the old developed urban areas. The ecological restoration projects promoted vegetation restoration in the western part of Hunan Province. This study could help us better understand the spatiotemporal variations of vegetation and their responses to climate change and human activities, which would offer scientific basis for effective ecological restoration policy.

Modeling soil conservation, water conservation and their tradeoffs: a case study in Beijing.

Natural ecosystems provide society with important goods and services. With the rapid increase in human populations and excessive utilization of natural resources, humans frequently enhance the production of some services at the expense of the others. Although the need for tradeoffs between conservation and development is urgent, the lack of efficient methods to assess such tradeoffs has impeded progress. Three land use strategy scenarios (development scenario, plan trend scenario and conservation scenario) were created to forecast potential changes in ecosystem services from 2007 to 2050 in Beijing, China. GIS-based techniques were used to map spatial and temporal distribution and changes in ecosystem services for each scenario. The provision of ecosystem services differed spatially, with significant changes being associated with different scenarios. Scenario analysis of water yield (as average annual yield) and soil retention (as retention rate per unit area) for the period 2007 to 2050 indicated that the highest values for these parameters were predicted for the forest habitat under all three scenarios. Annual yield/retention of forest, shrub, and grassland ranked the highest in the conservation scenario. Total water yield and soil retention increased in the conservation scenario and declined dramatically in the other two scenarios, especially the development scenario. The conservation scenario was the optimal land use strategy, resulting in the highest soil retention and water yield. Our study suggests that the evaluation and visualization of ecosystem services can effectively assist in understanding the tradeoffs between conservation and development. Results of this study have implications for planning and monitoring future management of natural capital and ecosystem services, which can be integrated into land use decision-making.

Dasymetric mapping of urban population in China based on radiance corrected DMSP-OLS nighttime light and land cover data.

High spatial resolution urban population dataset is increasingly required for sustainable urban planning and management. Dasymetric mapping is an effective approach to create such dataset. However, the created gridded total population datasets usually have limitation for urban analysis in developing countries as they usually underestimate urban population because of the strong urban-rural difference. In this study, we aimed to create a dataset of gridded urban population with 1 km resolution in China in year 2000 and 2010. We proposed an index of urban nighttime light (UNTL) by integrating radiance corrected DMSP nighttime light (RcNTL) and urban land, which is then used as weight to disaggregate county-level urban population. The validation using township population in Beijing as references shows reasonable accuracy with a mean relative error of 38% and a R2 of 68%. Using only two widely available datasets (RcNTL and urban land), the proposed method is simple and computing efficient compared with methods using multiple geospatial data (e.g., land use and land cover, distance to city center, slope) and that combined with remote sensing imagery. As the used two auxiliary datasets are accessible globally, the method has great potential to produce similar urban population dataset for other developing countries where fine scale census population datasets are scarce. The produced urban population dataset is valuable for enriching our understanding of the urbanization process and designing sustainable urban planning and management strategies in China.

A new method to quantify surface urban heat island intensity.

Reliable quantification of urban heat island (UHI) can contribute to the effective evaluation of potential heat risk. Traditional methods for the quantification of UHI intensity (UHII) using pairs-measurements are sensitive to the choice of stations or grids. In order to get rid of the limitation of urban/rural divisions, this paper proposes a new approach to quantify surface UHII (SUHII) using the relationship between MODIS land surface temperature (LST) and impervious surface areas (ISA). Given the footprint of LST measurement, the ISA was regionalized to include the information of neighborhood pixels using a Kernel Density Estimation (KDE) method. Considering the footprint improves the LST-ISA relationship. The LST shows highly positive correlation with the KDE regionalized ISA (ISAKDE). The linear functions of LST are well fitted by the ISAKDE in both annual and daily scales for the city of Berlin. The slope of the linear function represents the increase in LST from the natural surface in rural regions to the impervious surface in urban regions, and is defined as SUHII in this study. The calculated SUHII show high values in summer and during the day than in winter and at night. The new method is also verified using finer resolution Landset data, and the results further prove its reliability.

The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States.

Urban heat island (UHI), the phenomenon that urban areas experience higher temperatures compared to their surrounding rural areas, has significant socioeconomic and environmental impacts. With current and anticipated rapid urbanization, improved understanding of the response of UHI to urbanization is important for developing effective adaptation measures and mitigation strategies. Current studies mainly focus on a single or a few big cities and knowledge on the response of UHI to urbanization for large areas is limited. As a major indicator of urbanization, urban area size lends itself well for representation in prognostic models. However, we have little knowledge on how UHI responds to urban area size increase and its spatial and temporal variation over large areas. In this study, we investigated the relationship between surface UHI (SUHI) and urban area size in the climate and ecological context, and its spatial and temporal variations, based on a panel analysis of about 5000 urban areas of 10km2 or larger, in the conterminous U.S. We found statistically significant positive relationship between SUHI and urban area size, and doubling the urban area size led to a SUHI increase as high as 0.7°C. The response of SUHI to the increase of urban area size shows spatial and temporal variations, with stronger SUHI increase in Northern U.S., and during daytime and summer. Urban area size alone can explain as much as 87% of the variance of SUHI among cities studied, but with large spatial and temporal variations. Urban area size shows higher association with SUHI in regions where the thermal characteristics of land cover surrounding the urban area are more homogeneous, such as in Eastern U.S., and in the summer months. This study provides a practical approach for large-scale assessment and modeling of the impact of urbanization on SUHI, both spatially and temporally.

Effect of landscape pattern on insect species density within urban green spaces in Beijing, China.

Urban green space is an important refuge of biodiversity in urban areas. Therefore, it is crucial to understand the relationship between the landscape pattern of green spaces and biodiversity to mitigate the negative effects of urbanization. In this study, we collected insects from 45 green patches in Beijing during July 2012 using suction sampling. The green patches were dominated by managed lawns, mixed with scattered trees and shrubs. We examined the effects of landscape pattern on insect species density using hierarchical partitioning analysis and partial least squares regression. The results of the hierarchical partitioning analysis indicated that five explanatory variables, i.e., patch area (with 19.9% independent effects), connectivity (13.9%), distance to nearest patch (13.8%), diversity for patch types (11.0%), and patch shape (8.3%), significantly contributed to insect species density. With the partial least squares regression model, we found species density was negatively related to patch area, shape, connectivity, diversity for patch types and proportion of impervious surface at the significance level of p < 0.05 and positively related to proportion of vegetated land. Regression tree analysis further showed that the highest species density was found in green patches with an area <500 m2. Our results indicated that improvement in habitat quality, such as patch area and connectivity that are typically thought to be important for conservation, did not actually increase species density. However, increasing compactness (low-edge) of patch shape and landscape composition did have the expected effect. Therefore, it is recommended that the composition of the surrounding landscape should be considered simultaneously with planned improvements in local habitat quality.

Assessing the combined risks of PAHs and metals in urban soils by urbanization indicators.

We quantitatively describe the impacts of urbanization on the accumulation of polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) in urban soils as well as their health risks to residents. Residential building age, population density, road density, and distance from urban center were used as urbanization level indicators. Significant correlations were found between those urbanization indicators and the amounts of PAHs, Cu, Cd, Pb, Zn and As in residential soils. The exposure time of soils to urban air was the primary factor affecting soil pollution, followed by local road density and population density. Factor analysis suggested that 59.0% of the elevated pollutant concentrations were caused by citywide uniform deposition, and 15.3% were resulted from short-range deposition and/or non-combustion processes. The combined health risks posed by soil PAHs and HMs were aggravated with time and can be expressed as functions of residence age, road density, and other urbanization indicators.

[Selection of landscape metrics for urban forest based on simulated landscapes].

Based on the existing urban forest landscape of Shenyang, four landscape pattern gradients were simulated, and one existing landscape pattern gradient in accordance with the trend of these gradients was selected. By analyzing the responses of 28 landscape metrics for landscape fragmentation and patch shape complexity to various landscape pattern gradients, preference landscape metrics were selected for describing the degree of the two landscape pattern characteristics. The results showed that patch density (PD) and mean patch area (AREA_MN) regularly responded to the change of landscape fragmentation. The increase of landscape fragmentation resulted in an increase of PD value while a decrease of AREA_MN value. Patch shape complexity of area weighted mean perimeter area ratio (PARA_AM) coincided with the gradients of landscape pattern. PARA AM value increased with increasing patch shape complexity, which precisely characterized the degree of patch shape complexity.