The Yangtze River Delta (YRD) port cluster is one of five major port clusters in China and is home to Shanghai port, the largest port worldwide. In this study, an automatic identification system-based model was built to estimate the ship exhaust emissions in the YRD and the East China Sea within 400 km of the coastline. In 2010, the total emissions of SO2, NOX, and PM2.5 were 3.8 × 10(5) tonnes/yr, 7.1 × 10(5) tonnes/yr, and 5.1 × 10(4) tonnes/yr, respectively. More than 60% and 85% of the ship emissions occurred within 100 km and 200 km of the coastline, respectively. Ship emissions also showed distinct seasonal variability. The emission of SO2 and NOX by ships in hot spots, such as ports and vessel traffic hubs was much higher than that on land, with maximum SO2 and NOX intensities from ships that were 36 times and 17 times greater, respectively, than the maximal land-based emissions. The potential impact of ship emissions at six hot spots on the surrounding atmospheric environment was estimated with the HYSPLIT model. Our study demonstrated that ship emissions have an important impact on both the entire YRD region and on greater East China.

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While the approach to multiple-attribute decision-making (MADM) is widely used in a variety of fields, including models with fuzzy sets and corresponding extensions, it cannot solve target-oriented decision problems with both selective and targeted alternatives. Therefore, this study provides the first description of a target-oriented MADM problem and proposes a novel decision framework. An attribute value function for target orientation is defined by integrating range and frequency values derived under cumulative prospect theory and range-frequency theory. A Choquet integral with discrete fuzzy measures is then used to integrate attribute values and determine comprehensive values for selective alternatives. In this determination of comprehensive values, a parameter estimation model is also established, with its input assumed to be the pairwise comparison judgment matrix with probabilistic linguistic preference relation. This model as well as its transformation aims at determining the parameters of both the attribute value function and fuzzy measures. Finally, the process of target-oriented MADM is summarized, and an illustrative example is provided to demonstrate the applicability of the proposed techniques.