机构地区:[1]北京化工大学化学工程学院,北京100029 [2]首都经济贸易大学管理工程学院,北京100070
出 处:《工程科学学报》2024年第7期1311-1323,共13页Chinese Journal of Engineering
基 金:国家自然科学基金资助项目(72174125);中央高校基本科研业务费资助项目(buctrc202133);国家重点实验室开放基金课题资助项目(22K07ESPCT)。
摘 要:基于已建立的2018年山东省高分辨率独立焦化行业排放清单,结合焦化行业制定的相关政策,本研究设置了基准情景(BAU-2018、BAU-2025、BAU-2035)和减排优化情景(ERO-2025、ERO-2035),使用CALPUFF模型模拟了各情景下山东省独立焦化行业SO_(2)、NO_x、PM_(10)及PM_(2.5)的污染情况及各污染物的减排潜力.研究结果表明,在BAU-2018情景中,山东省各市SO_(2)、NO_x、PM_(10)和PM_(2.5)的年均贡献比例的范围分别为0.06%~0.84%、0.01%~0.63%、0.04%~0.19%和0.07%~0.21%;在各阶段中,ERO-2025情景较于现状(BAU-2018)的各污染物排放与贡献浓度降低幅度最大;最优情景ERO-2035较于BAU-2018,SO_(2)、NO_x、PM_(10)、PM_(2.5)和CO_(2)的排放量分别为减少了60.12%、78.24%、75.07%、74.20%和37.47%,SO_(2)、NO_x、PM_(10)和PM_(2.5)年均贡献浓度降幅分别为60.74%、78.56%、75.00%和74.53%.全面执行超低排放标准对污染物减排具有显著效果,同时显示出巨大的污染物与CO_(2)的协同减排潜力.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,SO_(2),NOx,PM_(2.5),and CO_(2) 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 SO_(2),NOx,SO42−,NO3−,HNO3,PM10,and PM_(2.5) 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 SO_(2),NOx,PM10,and PM_(2.5) 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 SO_(2) and NOx concentrations to air quality,whereas Jining has the highest contribution of PM10 and PM_(2.
关 键 词:焦化 CALPUFF 环境影响 超低排放 CO_(2)
分 类 号:X51[环境科学与工程—环境工程]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...