| 其他摘要 | With the rapid economic development of China in recent years, the problem of air pollution has become increasingly prominent, especially in economically developed areas such as Beijing-Tianjin-Hebei, where fine particulate matter (PM2.5) pollution appears frequently. The Bohai Rim has many industrial provinces and megacities, making it one of the regions with the most serious haze problem in China. Under the vigorous control of our country, sources of PM2.5 pollution have been controlled to a certain extent. However, the proportion of secondary particulate in PM2.5 is increasing, of which nitrate (NO3-) has comprised a significant proportion. Identifying the sources of PM2.5 is the key to formulating pollution control strategies, so it is necessary to apportion the secondary components in PM2.5 reasonably. In this study, the stable nitrogen isotope (δ15N) characteristic was used to explore the source of NO3- in PM2.5 based on δ15N-nitrogen oxides (NOx) of the local emissions and further applied to the reapportionment of the secondary particulate source identified by Positive Matrix Factorization (PMF) as a constraint condition. The purpose of this study is to deeply identify the source of atmospheric pollution in the Bohai Rim from the perspective of the stable isotope, and provide reference for the NOx and PM2.5 emission reduction control measures.In order to make up for the deficiency of δ15N-NOx from local source emissions, four typical sources of residential coal combustion, biomass burning, road vehicle emissions and ship emissions were selected as the main sources of atmospheric NOx in Bohai Rim and the measurement of δ15N-NOx source value was conducted. The average values of δ15N-NOx from residential coal combustion and biomass burning were +5.46±1.80‰ and +6.27±4.98‰, respectively, which were affected by different bituminous coal volatiles and biomass types. Values of δ15N-NOx from road vehicle emissions had a wide range (-18.8 ~ +6.43‰) and tended to be negative, with an average value of -8.66±5.34‰. The average value of δ15N-NOx from LPG vehicle emissions was observably higher than that from gasoline and diesel vehicle emissions, and emissions of light diesel vehicles had higher δ15N-NOx than heavy diesel vehicles; the average δ15N-NOx value emitted during driving was higher than that when starting; in addition, the δ15N-NOx value increased dramatically with the improvement of emission standards and the equipment of denitrification measures. The δ15N-NOx values of ship emissions were basically negative, ranging from -35.5‰ to +6.50‰, and the average δ15N-NOx of all samples was -18.4±12.0‰, which was much lower than samples of vehicle emission. The average value of δ15N-NOx emitted by bulk carriers was higher than that by fishing vessels, and low rated speeds as well as high rated powers were likely to bring higher δ15N-NOx values; ships using fuel oil as energy sources emitted the highest δ15N-NOx values, followed by light diesel and heavy diesel ships; in the different load conditions of the main engine, the average δ15N-NOx values under the maneuvering and cruising condition were relatively close, which were higher than the low-speed cruise and parking condition; the average δ15N-NOx value of the auxiliary engine was higher than that of the main engine.In this study, long-term observation of PM2.5 in Beihuangcheng Island was carried out from the summer of 2014 to the spring of 2018. During the period, the mass concentration of PM2.5 averaged 77.0±52.3 μg/m3 and the daily average concentration varied from 11.6 μg/m3 to 328 μg/m3. It showed obvious seasonal characteristics of high in spring and winter and low in summer and autumn. Accounting for 8.70±16.2% and 6.38±4.89% of PM2.5 concentration, respectively, Organic carbon (OC) and elemental carbon (EC) had the highest concentration in winter and the lowest in summer, which was consistent with the seasonal characteristic of PM2.5 concentration. Water-soluble ions accounted for 40.7±24.9% of PM2.5 concentration, of which the average concentration of NO3- during the sampling period ranked first. The higher NO3-/nss-SO42- ratio in summer indicated that motor vehicles and ships contributed a lot at that time. The source apportionment results of PMF showed that the secondary particulate source contributed the most to PM2.5 in Beihuangcheng Island during the sampling period and occupied a clear dominant position (28.4%), followed by vehicle emissions (23.3%) and biomass burning (18.8%). The cumulative contribution of the first three sources reached more than 70%. Contributions of ship emissions (12.1%), coal combustion (9.13%), industrial pollution sources (4.97%), sea salt (2.80%) and chromium industry (0.455%) was low.The δ15N-NO3- value in PM2.5 in Beihuangcheng Island ranged from -3.09‰ to +50.9‰, with an average value of +8.64±6.28‰; the level of δ15N-NO3- varied with seasons and the higher δ15N-NO3- value in winter may be related to temperature and coal-fired heating. The δ18O-NO3- value averaged +75.9±10.9‰ and the highest and lowest values also appeared in winter and summer, respectively. According to Bayesian mixing model, coal combustion contributed the most to NO3- in Beihuangcheng Island (42.5±11.3%), followed by biomass burning (17.8±9.61%), ship emissions (14.7±7.37%) and vehicle emissions (14.0±5.64%); while the contribution of biogenic soil emissions was the lowest (6.44±2.55%). In terms of seasonal variation, the contribution of coal combustion increased significantly in winter due to the central heating in the Bohai Rim, causing the decrease of other sources; biomass burning and biogenic soil emissions showed seasonal characteristics of high in summer and low in winter, and contributions of mobile sources were similar in four seasons.Based on the linear regression method, the regression coefficients of the secondary particulate source with fossil fuel combustion, vehicle emissions, ship emissions and agriculture-related sources were 0.292, 0.293, 0.226 and 0.588 respectively. After that, the secondary particulate source was apportioned to the other six sources identified by PMF except sea salt. In the end, PM2.5 was reasonably re-apportioned into 7 sources: coal combustion, biomass burning, sea salt, ship emissions, chromium industry, vehicle emissions, and industrial sources, with contribution rates of 14.7%, 30.7%, 2.80%, 16.7%, 0.556%, 29.3% and 5.25% respectively. Slightly overtaking vehicle emissions, biomass burning became the largest contribution source of PM2.5; and the contribution order of other sources was not changed. |
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