[Research methods and progress on the reduction effects of vehicle emission pollutants by street canyon greening.] / è¡—è°·ç»¿åŒ–æ¶ˆå‡æœºåŠ¨è½¦æŽ’æ”¾æ±¡æŸ“ç‰©çš„ç ”ç©¶æ–¹æ³•ä¸Žè¿›å±•.

With the development of high-density and high-rise buildings on both sides of the street, widespread attention has been paid to the applicability of the traditional greening model of 'the more trees, the better atmospheric environment' in dealing with air pollution in urban street canyons. Clarifying the characteristics of street canyons greening and its planting design pattern on the reduction of emission pollutants by vehicles is an important prerequisite for the improvement of air quality in the street canyons. Based on literature review, we compared the applicability and limitations of the three methods, including field observation, wind tunnel test, and numerical simulation. We further analyzed the effects of roadside trees and hedges on the dispersion and deposition of air pollutants, and put forward a framework of adaptive greening design for air quality improvement. Finally, we proposed that future studies should address the creation of graphic languages for roadside greening design, the development of technical guidelines for evaluating the exposure of air pollution, and the optimization of parameterization schemes for the physical processes of greening effect in computational fluid dynamics models. Overall, our review could provide ideas and reference for the subsequent research.

[Planning approach of urban blue-green space based on local climate optimization: A review]. / åŸºäºŽå±€åœ°æ°”å€™ä¼˜åŒ–çš„åŸŽå¸‚è“ç»¿ç©ºé—´è§„åˆ’é€”å¾„ç ”ç©¶è¿›å±•.

Local climatic problems are widespread in cities under high-density and high-intensity construction mode in China, including heat island effect, poor ventilation, and frequent haze wea-ther. Urban blue-green space is vital for mitigating wind and heat, and for improving air quality, and therefore has become a hotspot of urban planning and design research dealing with climatic problems. Here, we reviewed the climate effects of urban blue-green space. In particular, we summarized the research progress of planning approaches to cool island landscape features optimization, cooling island configuration, ventilation corridor network connection and ventilation corridor interface control based on the levels of planning layout and network construction. We proposed a basic framework of urban blue-green space planning optimizing local climate by combining intelligent simulation platform, evaluation index system, planning and design guide, and guarantee mechanism for implement, aiming to provide key evidence for urban climate adaption and design.

[Research progress and development trend of quantitative assessment techniques for urban thermal environment.] / åŸŽå¸‚çƒ­çŽ¯å¢ƒå®šé‡è¯„ä»·æŠ€æœ¯ç ”ç©¶è¿›å±•åŠå‘å±•è¶‹åŠ¿.

Quantitative assessment of urban thermal environment has become a focus for urban climate and environmental science since the concept of urban heat island has been proposed. With the continual development of space information and computer simulation technology, substantial progresses have been made on quantitative assessment techniques and methods of urban thermal environment. The quantitative assessment techniques have been developed to dynamics simulation and forecast of thermal environment at various scales based on statistical analysis of thermal environment on urban-scale using the historical data of weather stations. This study reviewed the development progress of ground meteorological observation, thermal infrared remote sensing and numerical simulation. Moreover, the potential advantages and disadvantages, applicability and the development trends of these techniques were also summarized, aiming to add fundamental knowledge of understanding the urban thermal environment assessment and optimization.

[Quantitative estimation of vegetation cover and management factor in USLE and RUSLE models by using remote sensing data: a review].

Soil loss prediction models such as universal soil loss equation (USLE) and its revised universal soil loss equation (RUSLE) are the useful tools for risk assessment of soil erosion and planning of soil conservation at regional scale. To make a rational estimation of vegetation cover and management factor, the most important parameters in USLE or RUSLE, is particularly important for the accurate prediction of soil erosion. The traditional estimation based on field survey and measurement is time-consuming, laborious, and costly, and cannot rapidly extract the vegetation cover and management factor at macro-scale. In recent years, the development of remote sensing technology has provided both data and methods for the estimation of vegetation cover and management factor over broad geographic areas. This paper summarized the research findings on the quantitative estimation of vegetation cover and management factor by using remote sensing data, and analyzed the advantages and the disadvantages of various methods, aimed to provide reference for the further research and quantitative estimation of vegetation cover and management factor at large scale.

[Spatiotemporal distribution characteristics of rainfall erosivity in Three Gorges Reservoir Area].

Based on the 1976-2005 daily rainfall records from 25 weather stations in the Three Gorges Reservoir Area and its surrounding regions, this paper studied the spatiotemporal distribution characteristics of rainfall erosivity in the Area, with the focus on the annual and inter-annual trends of the rainfall erosivity around seven main weather stations. In 1976-2005, the average annual rainfall erosivity (R) in the Area was from 4389.0 to 8021.0 MJ x mm x hm(-2) x h(-1) x a(-1), being increased first from the northeast to the southwest, reached the peak in the central, and then decreased. The annual rainfall erosivity around the seven main weather stations mostly concentrated in the period from April to October, with the R value increased first from April, reached the highest in June or July, and then decreased. The maximum rainfall erosivity in consecutive three months around each of the seven weather stations accounted for 54.2%-60.7% of the total annual rainfall erosivity. In the study period, the coefficients of variation of the annual rainfall erosivity around the seven main weather stations varied moderately from 0.278 to 0.387, and the tendency rate ranged from -431.1 to 263.5 MJ x mm x hm(-2) x h(-1) x (10 a)(-1). However, the coefficients of tendency did not pass the confidence test with 5% level of significance, and the changes of annual rainfall erosivity showed random fluctuation. The variation degree of monthly rainfall erosivity was larger than the variation of annual rainfall erosivity, but only showed an obvious climate trend in a few months around parts of the weather stations.

[Spatial optimum allocation of shelter-forest types in Three Gorges Reservoir Area based on multiple objective grey situation decision].

Based on the 2007 Landsat TM images and the dominant environmental factors of shelter forest, the forest sites in the Three Gorges Reservoir Area were classified, and by using multiple objective grey situation decision model, three indices including water conservation amount, biomass, and stand productivity were selected to make the spatial optimum allocation of the present four kinds of shelter forest (coniferous forest, broadleaf forest, mixed coniferous-broadleaf forest, and shrub) in the Area. The forest sites in the Area in 2007 could be classified into 40 types, and after the optimization of spatial allocation, the proportion of coniferous forest, broadleaf forest, mixed coniferous-broadleaf forest, and shrub would be 32.55%, 29.43%, 34.95%, and 3.07%, respectively. Comparing with that before optimization, the proportion of coniferous forest and shrub after optimization was reduced by 8.79% and 28.55%, while that of broadleaf forest and mixed coniferous-broadleaf forest was increased by 10.23% and 27.11%, respectively. After the optimization of spatial allocation, the amount of water conservation, biomass, and stand productivity of the shelter forests in the area would be increased by 14.09 x 10(8) m3, 0.35 x 10(8) t, and 1.08 x 10(6) t, respectively.

[Evaluation of landscape connectivity based on least-cost model].

Landscape connectivity, as a dominant factor affecting species dispersal, reflects the degree to which the landscape facilitates or impedes organisms' movement among resources patches. It is also an important indicator in sustainable land use and biological conservation. Least-cost model originates from graph theory, and integrates the detailed geographical information with organisms' behavioral characteristics in the landscape. Through cost distance analysis, this model can describe the species connectivity in heterogeneous landscape intuitively and visually. Due to the simple algorithm performed in GIS packages and the demand of moderate data information, least-cost model has gained extensive attention in the evaluation of large-scale landscape connectivity. Based on the current studies of landscape connectivity, this paper elaborated the significance, principles, and operation processes of least-cost model in evaluating landscape connectivity, and discussed the existing problems of the model in its practical applications, which would benefit the further related studies and biodiversity conservation.