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基于CALPUFF模型的山東省獨立焦化行業大氣污染物分析與預測

Analysis and prediction of air pollutants in the independent coking industry in Shandong Province based on the CALPUFF model

  • 摘要: 基于已建立的2018年山東省高分辨率獨立焦化行業排放清單,結合焦化行業制定的相關政策,本研究設置了基準情景(BAU-2018、BAU-2025、BAU-2035)和減排優化情景(ERO-2025、ERO-2035),使用CALPUFF模型模擬了各情景下山東省獨立焦化行業SO2、NOx、PM10及PM2.5的污染情況及各污染物的減排潛力. 研究結果表明,在BAU-2018情景中,山東省各市SO2、NOx、PM10和PM2.5的年均貢獻比例的范圍分別為0.06%~0.84%、0.01%~0.63%、0.04%~0.19%和0.07%~0.21%;在各階段中,ERO-2025情景較于現狀(BAU-2018)的各污染物排放與貢獻濃度降低幅度最大;最優情景ERO-2035較于BAU-2018,SO2、NOx、PM10、PM2.5和CO2的排放量分別為減少了60.12%、78.24%、75.07%、74.20%和37.47%,SO2、NOx、PM10和PM2.5年均貢獻濃度降幅分別為60.74%、78.56%、75.00%和74.53%. 全面執行超低排放標準對污染物減排具有顯著效果,同時顯示出巨大的污染物與CO2的協同減排潛力.

     

    Abstract: Since 2018, Shandong Province has successively issued a series of pollution prevention and control programs for air pollutants from the coking industry, which plays a key role in coke production in China. However, a comprehensive assessment of the effectiveness of these measures is lacking. For a better understanding of this issue, based on the published air pollutant emission inventory for the independent coking industry and related policies formulated in Shandong in 2018, this study developed business-as-usual scenarios (BAU-2018, BAU-2025, and BAU-2035) and emission reduction optimization scenarios (ERO-2025 and ERO-2035). The emission reduction potential of PM10, SO2, NOx, PM2.5, and CO2 and their corresponding contributions to Shandong’s air quality with the air quality model (CALPUFF) were assessed under different scenarios. In terms of scenario settings, the gross domestic product of the secondary industry and the coke output of independent coking enterprises were used for linear regression to predict the coke output in 2025 and 2035. The mesoscale atmospheric data model, Weather Research and Forecasting, provided simulated three-dimensional meteorological field data for this study. Regional terrain data (90 m) were obtained from the United States Geological Survey. The resolution of the land use type data was 30 m, according to our previous research results. We adopted the MESOPUFF II chemical mechanism to simulate SO2, NOx, SO42?, NO3?, HNO3, PM10, and PM2.5 pollutants. To ensure the accuracy of the enterprise location information, we examined the enterprise latitude and longitude information one by one using Google Earth location recognition and manual visual inspection. The results showed that in the BAU-2018 scenario, the annual contribution ratios of SO2, NOx, PM10, and PM2.5 in Shandong Province were 0.06%–0.84%, 0.01%–0.63%, 0.04%–0.19%, and 0.07%–0.21%, respectively. Linyi has the highest contribution of SO2 and NOx concentrations to air quality, whereas Jining has the highest contribution of PM10 and PM2.5 concentrations to air quality. Compared with the current scenario (BAU-2018), the emission and contribution concentration of each pollutant showed an alarming decrease in the ERO-2025 scenario. Under the ERO-2035 scenario, the results showed that SO2, NOx, PM10, PM2.5, and CO2 emissions would be reduced by 60.12%, 78.24%, 75.07%, 74.20%, and 37.47%, respectively, compared with those under the BAU-2018 scenario. In the ERO-2035 scenario, the average contribution concentrations of SO2, NOx, PM10, and PM2.5 decreased by 60.74%, 78.56%, 75.00%, and 74.53%, respectively. Moreover, the results of this study showed that the comprehensive implementation of ultralow emission standards in Shandong Province had a considerable impact on air pollutant reduction in the independent coking industry, and the synergistic reduction of air pollutants and carbon dioxide showed huge potential.

     

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