Growing shipping activities in port areas have generated negative impacts on climate, air quality and human health. To better evaluate the environmental impact of ship emissions, an experimental characterization of air pollution from ships was conducted in Shanghai Port in the summer of 2016. The ambient concentrations of gaseous NO, NO₂, SO₂ and O₃ in addition to fine particulate matter concentrations (PM_2.5), particle size distributions and the chemical composition of individual particles from ship emission were continuously monitored for 3 months. Ship emission plumes were visible at the port site in terms of clear peaks in the gaseous species and particulate matter concentrations. The SO₂ and vanadium particle numbers were found to correlate best with ship emissions in Shanghai Port. Single-particle data showed that ship emission particles at the port site mainly concentrated in a smaller size range (<0.4 µm), where their number contributions were more important than their mass contributions to ambient particulate matter. The composition of ship emission particles at the port site suggested that they were mostly freshly emitted particles: their mass spectra were dominated by peaks of sulfate, elemental carbon (EC), and trace metals such as V, Ni, Fe and Ca, in addition to displaying very low nitrate signals. The gaseous NO_x composition in some cases of plumes showed evidence of atmospheric transformation by ambient O₃, which subsequently resulted in O₃ depletion in the area. Quantitative estimations in this study showed that ship emissions contributed 36.4 % to SO₂, 0.7 % to NO, 5.1 % to NO₂, −0.9 % to O₃, 5.9 % to PM_2.5 and 49.5 % to vanadium particles in the port region if land-based emissions were included, and 57.2 % to SO₂, 71.9 % to NO, 30.4 % to NO₂, −16.6 % to O₃, 27.6 % to PM_2.5 and 77.0 % to vanadium particles if land-based emissions were excluded.

The Yangtze River Delta (YRD) and the megacity of Shanghai are host to one of the busiest port clusters in the world; the region also suffers from high levels of air pollution. The goal of this study was to estimate the contributions of shipping to regional emissions, air quality, and population exposure and to characterize the importance of the geographic spatiality of shipping lanes and different types of ship-related sources for the baseline year of 2015, which was prior to the implementation of China's Domestic Emission Control Areas (DECAs) in 2016. The WRF-CMAQ model, which combines the Weather Research and Forecasting model (WRF) and the Community Multi-scale Air Quality (CMAQ) model, was used to simulate the influence of coastal and inland-water shipping, port emissions and ship-related cargo transport on air quality and on the population-weighted concentrations (which is a measure of human exposure). Our results showed that the impact of shipping on air quality in the YRD was primarily attributable to shipping emissions within 12 NM (nautical miles) of shore, but emissions coming from the coastal area between 24 and 96 NM still contributed substantially to ship-related PM_2.5 concentrations in the YRD. The overall contribution of ships to the PM_2.5 concentration in the YRD could reach 4.62 µg m⁻³ in summer when monsoon winds transport shipping emissions onshore. In Shanghai city, inland-water going ships were major contributors (40 %–80 %) to the shipping impact on urban air quality. Given the proximity of inland-water ships to the urban populations of Shanghai, the emissions of inland-water ships contributed more to population-weighted concentrations. These research results provide scientific evidence to inform policies for controlling future shipping emissions; in particular, in the YRD region, expanding the boundary of 12 NM from shore in China's current DECA policy to around 100 NM from shore would include most of shipping emissions affecting air pollutant exposure, and stricter fuel standards could be considered for the ships on inland rivers and other waterways close to residential regions.

Hygroscopicity plays crucial roles in determining aerosol optical properties and aging processes in the atmosphere. We investigated submicron aerosol hygroscopicity and composition by connecting an aerosol time-of-flight mass spectrometer (ATOFMS) in series to a hygroscopic tandem differential mobility analyzer (HTDMA), to characterize hygroscopicity and composition of ambient aerosols in Shanghai, China. The HTDMA–ATOFMS data suggested that particle types, including biomass burning, elemental carbon (EC), dust/ash, organic particles, cooking particles and sea salt, were shown to have distinct hygroscopicity distributions. Peak intensities in particle spectra were found to be nonlinearly correlated with hygroscopicity, and the correlations were variant with particle types. Based on the measured hygroscopicity–composition relations, we developed a statistical method to estimate ambient particle hygroscopicity just from their mass spectra. The method was applied to another ambient ATOFMS dataset sampled from 12 to 28 September 2012 in Shanghai. The estimated hygroscopicity suggested that ambient particles were present in three apparent hygroscopicity modes, whose growth factors peaked at 1.05, 1.42 and 1.60 (85 % relative humidity, RH). The estimated growth factor (GF) were divided into four bins as 1.5 to represent the nearly hydrophobic (NH), less-hygroscopic (LH), more-hygroscopic (MH) and sea salt (SS) modes. Number contributions of particle types to hygroscopicity modes showed consistent results with the HTDMA–ATOFMS experiment. Based on the combined information on particle composition, hygroscopicity, air mass back trajectories and ambient pollutant concentrations, we inferred that the NH, LH, MH and SS modes were characterized by primary organic aerosol (POA) ∕ EC, secondary organic aerosol (SOA), secondary inorganic aerosol (SIA) and salt compositions, respectively. The proposed method would provide additional information to the study of particle mixing states, source identification and visibility variation.

In this study, typical haze pollution influenced by biomass burning (BB) activities in Changsha in the autumn of 2024 was investigated through the mixing state and evolution process of BB particles via the real-time measurement of single-particle aerosol mass spectrometry (SPAMS). From the clean period to the haze period, the PM_2.5 concentration increased from 25 μg·m⁻³ at 12:00 to 273 μg·m⁻³ at 21:00 on 12 October, and the proportion of total BB single particles in the total detected particles increased from 17.2% to 54%. This indicates that the rapid increase in PM_2.5 concentration was accompanied by a concurrent increase in the contribution of particles originating from BB sources. The detected BB particles were classified into two types based on their mixing states and temporal variations: BB1 and BB2, which accounted for 71.7% and 28.3% of the total BB particles, respectively. The analysis of backward trajectories and fire spots suggested that BB1 particles originated from straw burning emissions at northern Changsha, while BB2 particles were primarily related to local nighttime cooking emissions in Changsha. In addition, a special type of K-containing single particles without K cluster ions was found closely associated with BB1 type particles, which were designated as secondarily processed BB particles (BB-sec). The BB-sec particles contained abundant sulfate and ammonium signals and showed lagged appearance after the peak of BB1-type particles, which was possibly due to the aging and formation of ammonium sulfate on the freshly emitted particles. In all, this study provides insights into understanding the substantial impact of BB sources on regional air quality during the crop harvest season and the appropriate disposal of crop straw, including conversion into high-efficiency fuel through secondary processing or clean energy via biological fermentation, which is of great significance for the mitigation of local haze pollution.