Shipping emissions have aroused wide concern in the world. In order to promote the implementation of emission regulations, this study develop a ship based sniffing technique to perform remote measurement of the SO₂, NO_x and CO₂ from ships entering and leaving Shanghai port at the open sea. The ship emission prediction model, Smoke diffusion model and source identification model were developed to automatically analyze the emission data and screen the object ship source based on Automatic Identification System (AIS) system. The fueling documents of the detected ship were obtained from maritime sector and the results precision of the sniffer technique was evaluated by comparing the measured Fuel sulfur content (FSC) with actual value deduced from fueling documents. The influences of wind speed and direction, object ship parameters and monitoring distance on the identification of object ship and accuracy of the calculated FSC were thoroughly investigated and the corresponding correction factors under different conditions were deduced. The modified emission factor ratio of CO₂ to NOx were proposed in order to improve the accuracy. It is demonstrated that with wind speed higher than 2 m/s and test distance shorter than 400m, the sniffer technique exhibit high efficiency and accuracy for the remote emissions measurement of ship upwind with detection rate higher than 90% and test error of FSC below 15%. To reduce the influence of the wind direction, at least two sniffer systems were required to guarantee that at least one station is in the downwind of the ship lane. Based on the results and discussion, a novel sniffer monitoring system with two buoy based sniffing stations placed close to each side of the ship lane far off shore was proposed to realize the remote monitoring of ship emissions.

At present, the energy consumption and carbon emissions of maritime transportation have raised concerns about environmental issues. A potential way to reduce carbon emissions from vessels is the use of chemical-based carbon capture and storage (CCS) technology. However, this technology faces challenges such as high energy consumption, large space occupation, and high processing costs. Therefore, the development of a technology with low energy consumption and compact CO₂ storage is crucial to promote the advancement of CCS technology. This paper introduces a magnesium CO₂ battery system that converts CO₂ into new energy, in the form of hydrogen, while storing CO₂. By preparing highly efficient catalytic electrodes and testing the electrolyte and CO₂ flow rate on the battery performance, the optimal process parameters were determined to be Pd/CeO₂-oct for the electrodes, a 0.5 mol/L NaOH solution for the electrolyte, and a CO₂ flow rate of 1 L/h. The battery system demonstrated high cycling stability and conversion efficiency at a current density of 8 mA·cm⁻², with a stable cycling time of 600 min (20 cycles), a cathode hydrogen production of 10.135 mL, and a Faraday efficiency of 97.03%.