The building industry in China has huge potential capacity for energy/resources conservation and pollutants reduction to achieve sustainable development However, stakeholders are hardly able to reach a consensus on preferential needs and effective solutions, which was a difficulty faced by policy makers. To better identify the common interests on sustainable development in this field, the Sustainability Solutions Navigator (SSN) was adopted in China for the first time to assess the sustainability needs and practices. Based on the participation of stakeholders from the government, businesses, academia, and non-government organizations, prioritized needs and practices were identified using SSN, and gap analyses were conducted for comparison to global benchmarks. According to the results, the top needs were mainly focused on improving government efficiency and implementation, maintaining healthy indoor environments and obtaining adequate funds; priority practices were mainly focused on governmental action, renewable energy development and pollutant source reduction. The gap analysis indicated that the government efficiency and performance had the largest gap to the benchmark. By using a simple interactive tool to bring different stakeholders into policy making process, this study produces all-around information for decision makers. The results imply that the sustainability of the building industry in China has a much better expectation than governmental performance. (C) 2013 Elsevier Ltd. All rights reserved.
Lake Yilong in Southwestern China has been under serious eutrophication threat during the past decades; however, the lake water remained clear until sudden sharp increase in Chlorophyll a (Chl a) and turbidity in 2009 without apparent change in external loading levels. To investigate the causes as well as examining the underlying mechanism, a three-dimensional hydrodynamic and water quality model was developed, simulating the flow circulation, pollutant fate and transport, and the interactions between nutrients, phytoplankton and macrophytes. The calibrated and validated model was used to conduct three sets of scenarios for understanding the water quality responses to various load reduction intensities and ecological restoration measures. The results showed that (a) even if the nutrient loads is reduced by as much as 77%, the Chl a concentration decreased only by 50%; and (b) aquatic vegetation has strong interaction with phytoplankton, therefore requiring combined watershed and in-lake management for lake restoration. (c) 2013 Elsevier Ltd. All rights reserved.
Lake Dianchi, one of the main water sources for Kunming, China, experiences severe cyanobacterial blooms due to rapid urbanization and local industrial development. Scientific interest in the mechanisms that cause blooms has been increasing. An integrated model combining rough set theory with binary logistic regression was used to examine the correlation between weather conditions and cyanobacterial blooms in Lake Dianchi based on daily monitoring data. The binary logistic regression yielded quantitative correlations between cyanobacterial blooms and the assessed meteorological variables, including temperature, wind velocity, and wind direction. The rough decision process connected the weather conditions and cyanobacterial blooms, which were used to verify the binary regression model results. It was shown that by comparing the methods, the rough decision-adjusted binary logistic regression model significantly improved model accuracy. The integrated model of cyanobacterial blooms in Lake Dianchi may inform decision-makers at local water purification plants of the water quality in the lake and assist them in making more cost-effective decisions.
The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP) method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP) and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers' preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of ``low risk and high return efficiency'' in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.