Over the last few decades, China has seen a steep rise in diverse eco city and low carbon city policies. Recently, attention has begun to focus on the perceived shortcomings in the practical delivery of related initiatives, with several publications suggesting a gap between ambitious policy goals and the emerging realities of the newly built environment. To probe this further, M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPTin this article we examine -based on the policy network approach -how the gap between high-level national policies and local practice implementation can be explained in the current Chinese context. We develop a four-pronged typology of eco city projects based on differential involvement of key (policy) actor groups, followed by a mapping of what are salient policy network relations among these actors in each type. Our analysis suggests that, within the overall framework of national policy, a core axis in the network relations is that between local government and land developers. In some cases, central government agenciesoften with buy-in from international architecture, engineering and consulting firms -seek to influence local government planning through various incentives aimed at rendering sustainability a serious consideration. However, this is mostly done in a top-down manner, which overemphasizes a rational, technocratic planning mode while underemphasizing interrelationships among actors. This makes the emergence of a substantial implementation gap in eco city practice an almost predictable outcome. Consequently, we argue that special attention be paid in particular to the close interdependency between the interests of local government actors and those of land and real estate developers. Factoring in this aspect of the policy network is essential if eco city implementation is to gain proper traction on the ground.

Hourly average monitoring data for mass concentrations of PM1, PM2.5, PM10, and black carbon (BC) were measured in Wuhan from December 2013 to December 2014, which has a flourishing steel industry, to analyze the characteristics of PM and their relation to BC, using statistical methods. The results indicate that variations in the monthly average mass concentrations of PM have similar concave parabolic shapes, with the highest values occurring in January and the lowest values appearing in August or September. The correlation coefficient of the linear regression model between PM1 and PM2.5 is quite high, reaching 0.99. Furthermore, the proportion of PM1 contained within PM2.5 is roughly 90%, directly proving that ultrafine particles whose diameter less than 1 μm may be a primary component of PM2.5 in Wuhan. Additionally, better seasonal correlation between PM and BC occurs only in summer and autumn, due to multiple factors such as topography, temperature, and the atmosphere in winter and spring. Finally, analysis of the diurnal variation of PM and BC demonstrates that the traffic emissions during rush hour, exogenous pollutants, and the shallow PBLH with stagnant atmosphere, all contribute to the severe pollution of Wuhan in winter.

Active remote sensing of atmospheric XCO 2 has several advantages over existing passive remote sensors, including global coverage, a smaller footprint, improved penetration of aerosols, and night observation capabilities. China is planning to launch a multi-functional atmospheric observation satellite equipped with a CO 2 -IPDA (integrated path differential absorption Lidar) to measure columnar concentrations of atmospheric CO 2 globally. As space and power are limited on the satellite, compromises have been made to accommodate other passive sensors. In this study, we evaluated the sensitivity of the system's retrieval accuracy and precision to some critical parameters to determine whether the current configuration is adequate to obtain the desired results and whether any further compromises are possible. We then mapped the distribution of random errors across China and surrounding regions using pseudo-observations to explore the performance of the planned CO 2 -IPDA over these regions. We found that random errors of less than 0.3% can be expected for most regions of our study area, which will allow the provision of valuable data that will help researchers gain a deeper insight into carbon cycle processes and accurately estimate carbon uptake and emissions. However, in the areas where major anthropogenic carbon sources are located, and in coastal seas, random errors as high as 0.5% are predicted. This is predominantly due to the high concentrations of aerosols, which cause serious attenuation of returned signals. Novel retrieving methods must, therefore, be developed in the future to suppress interference from low surface reflectance and high aerosol loading.

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