近年来，长春市细颗粒物（PM_2.5）浓度水平显著下降，但臭氧（O₃）污染问题日益凸显。臭氧与其前体物（NOx和VOCs）呈现高度非线性关系，控制单一的NOx或VOCs污染物可能无法有效改善臭氧污染，甚至可能使臭氧浓度升高。为了有效防治臭氧污染，长春市出台了一系列相关政策，但由于对臭氧污染形成机制缺乏足够的认识，而臭氧的生成又具有区域差异性和时间变化特征，政府对臭氧污染的管控仍处于起步阶段。因此有必要对长春市臭氧污染进行机理探究，科学制定减排方案并量化控制效果，以期为长春市夏季臭氧污染控制提供建议。本研究利用监测数据探究了长春市2019年夏季臭氧污染特征，整合多种清单，采用“自上而下”和“自下而上”相结合方式，编制了长春市2019年大气污染源排放清单。通过构建WRF-ISAT-CMAQ网格空气质量模型，采用情景分析和源解析技术手段，对长春市臭氧污染过程、来源以及控制效果进行时间和空间的定量化研究。主要研究内容与结果如下：

（1）分析长春市2019年臭氧污染污染特征

利用空气质量站点监测数据分析评价臭氧污染浓度的季度、月、小时分布特征，并结合气象要素分析对臭氧浓度的影响，结果为1)长春市臭氧污染平均浓度表现为夏季>春季>秋季>冬季。2）月变化趋势呈现“中间高，两端低，夏峰值”， 5～7月臭氧最大八小时浓度在100～160 μg/m³出现的频率较高，7月和8月臭氧是唯一的首要污染物3）臭氧浓度日变化趋势呈现 “单峰型”，夜间低于白天，低谷值在6～7时，峰值在16～17时。4）湿度10%～70%、温度25℃～33℃，风速大于4 m/s有助于臭氧浓度的累积和西南区域的输送。

基于“自上而下”和“自下而上”相结合方式整合多种清单编制了长春市2019年大气污染源排放清单，从行业和空间分布分析臭氧前体物污染排放特征。排放清单统计表明，主要污染物年排放量SO₂为37626.9吨、NOx为86814.2 吨、VOC为75937.6 吨、PM_2.5为51791.8 吨、PM₁₀为60796.1吨、CO为818454.1 吨、NH₃为59979.2吨。VOC排放主要来源于交通和居民源，集中分布在人口密集的主城区和各郊区县的居民聚集区；NOx排放主要来源于电厂、工业锅炉和交通源，集中分布在主城区、郊区县居民聚集区和交通干道沿线。

（2）评估验证WRF模式及CMAQ模式的模拟效果

应用WRF模式和CMAQ模式模拟2019年5～7月长春市三维气象场和臭氧时均浓度，选用R、MFB、MFE、NMB和NME等评估指标对模拟效果进行验证。夏季各点位臭氧小时模拟值对照监测值相关性平均值为0.62，平均相对偏差MFB平均值为0.1%，平均相对误差MFE平均值为0.04%。总体统计结果表明，WRF-ISAT-CMAQ能够满足模型性能标准，并且部分指标表现优秀水平，可用于臭氧污染的后续研究。

（3）解析长春市夏季臭氧污染来源

应用CMAQ中ISAM模块污染物源解析功能分析全源项、边界源和本地源在时间和空间上对臭氧污染浓度的贡献。源解析模拟表明，长春市夏季臭氧月均浓度约在35～101 μg/m³之间，城区交接位置浓度最低，郊区臭氧月均浓度比城区高。远距离传输占臭氧模拟值的72.39%～87.10%，边界源夏季对臭氧污染程度为7月>5月>6月，郊区农安县、德惠和九台受边界臭氧污染影响较大。本地源贡献约占臭氧模拟值的6%～15%，其中交通源占本地源臭氧浓度贡献的49.85%~59.55%；本地源夏季对臭氧污染程度为7月>6月>5月；城区中的二道区和宽城区，郊区中的德惠市、九台区和榆树市对长春市臭氧污染贡献较大。

（4）模拟长春市臭氧对前体物的减排响应与控制方案

以臭氧污染最严重的7月份为研究时段，设置38种减排情景模拟长春市臭氧对前体物减排响应，分析不同区域前体物最佳减排比例。模拟表明，2019年长春市城区属于VOC控制区，仅减排VOC对臭氧污染控制效果最佳；郊区属VOC和NOx协同控制区，臭氧前体物按VOC：NOx=1:2减排效果最佳，即当VOC减排20%时，对应 NOx减排40%效果最好。

基于最佳减排比例和臭氧污染来源，结合各行业十四五减排潜力，设置高、中、低三种减排方案。模拟表明，长春市夏季臭氧在高减排方案下控制效果最好。高减排方案为城区只削减VOC，电力、工业锅炉、水泥减排30%，居民、交通、溶剂使用、化工原料生产、石油开采及原油加工、其他工艺过程减排40%；郊区则协同减排，各行业VOC减排30%，NO_x减排60%。高、中、低减排方案在按照前体物最佳控制比例削减的情形下，长春市各点位夏季臭氧最大8小时浓度变化均值分别降低0.46 μg/m³、0.39 μg/m³和0.35 μg/m³。6月和7月高、中、低减排方案在按照前体物最佳控制比例削减的情形下，臭氧浓度均呈现较为一致的下降趋势，源削减得越多，臭氧浓度下降幅度越大，控制效果越好。

In recent years, the concentration level of fine particulate matter (PM_2.5) has decreased significantly in Changchun, but the problem of ozone (O₃) pollution is becoming more and more prominent. Ozone shows a highly non-linear relationship with its precursors (NOx and VOCs), and controlling a single NOx or VOCs pollutant may not be effective in ameliorating ozone pollution, and may even increase ozone concentrations. In order to effectively prevent and control ozone pollution, Changchun City has introduced a series of relevant policies, but due to the lack of sufficient knowledge about the formation mechanism of ozone pollution, and the regional variability and time-varying characteristics of ozone generation, the government's control of ozone pollution is still in its infancy. Therefore, it is necessary to explore the mechanism of ozone pollution in Changchun, scientifically formulate emission reduction programmers and quantify the control effects, with a view to providing recommendations for the control of ozone pollution in Changchun in summer. In this study, we used monitoring data to investigate the characteristics of summer ozone pollution in Changchun City in 2019, integrated multiple inventories, and compiled an inventory of air pollution sources in Changchun City in 2019 based on a combination of ‘top-down’ and ‘bottom-up’ approaches. By constructing the WRF-ISAT-CMAQ gridded air quality model, scenario analysis and source analysis techniques were used to quantify the ozone pollution process, sources, and control effects in Changchun City in time and space. The main research contents and results are as follows:

Analyse the pollution characteristics of ozone pollution in Changchun City in 2019

Using air quality station monitoring data to analyse and evaluate the quarterly monthly and hourly distribution characteristics of ozone pollution in 2019, and combining with meteorological factors to analyse the impact on ozone concentration. the results are l) the average concentration of ozone pollution in Changchun City is summer>spring>autumn>winter 2) the monthly trend shows "high in the middle, low at the ends, and peak in summer，From May to July, the maximum eight-hour ozone concentration appears more frequently at 100 to160 μg/m³, July and August ozone is the only primary pollutant 3) The daily trend of ozone concentration showed a "single-peak type", with nighttime lower than daytime, the trough value at 6 to 7 o'clock and the peak value at 16 to 17 o'clock.4) At humidity from 10% to 70%, temperature from 25°C to 33°C, wind speed greater than 4 m/s contributes to the accumulation of ozone concentration and transport from the southwest region.

Based on the combination of "top-down" and "bottom-up" approaches, the 2019 air pollution source emission inventory of Changchun City was compiled by combining a variety of inventories, with industry and spatial distribution analyses of ozone precursor pollution emission characteristics. The emission inventory statistics show that the annual emissions of major pollutants are 37626.9 tonnes of SO₂, 86814.2 tonnes of NOx, 75937.6 tonnes of VOC, 51791.8 tonnes of PM_2.5, 60796.1 tonnes of PM₁₀, 818454.1 tonnes of CO, and 59979.2 tonnes of NH₃. VOC emissions mainly come from traffic and residential sources, concentrated in densely populated main urban areas and residential areas in suburban counties; NOx emissions mainly come from power plants, industrial boilers and traffic sources, concentrated in the main urban areas, residential areas in suburban counties and along the main traffic roads.

Evaluate and verify the simulation effect of WRF model and CMAQ model

The WRF model and CMAQ model were applied to simulate the three-dimensional meteorological field and the hourly mean ozone concentration in Changchun City from May to July 2019, and the assessment indexes such as R, MFB, MFE, NMB, and NME were selected to verify the simulation effect. The mean value of the correlation of the hourly simulated ozone values against the monitoring values at each point in summer was 0.62, the mean value of the average relative deviation MFB was 0.1%, and the mean value of the average relative error MFE was 0.04%. The overall statistical results show that WRF-ISAT-CMAQ is able to meet the model performance criteria and performs at an excellent level in some of the indicators, which can be used in the follow-up study of ozone pollution.

Analysis of the sources of summer ozone pollution in Changchun City

Apply the pollutant source analysis function of the ISAM module in CMAQ to analyse the contribution of all-source items, boundary sources and local sources to ozone pollution concentrations in time and space. The source analysis simulation showed that the monthly average ozone concentrations in Changchun city in summer ranged from about 35 to 101 μg/m³, with the lowest concentrations in the urban area at the intersection location, and the monthly average ozone concentrations in the suburban area were higher than those in the urban area. Long-range transport accounted for 72.39% to 87.10% of the simulated ozone values, and the degree of ozone pollution from boundary sources in summer was July>May>June, with the suburban areas of Nong'an County, Dewei, and Jiutai being more affected by boundary ozone pollution. Local sources contribute about 6% to 15% of the simulated ozone values, with traffic sources accounting for 49.85% to 59.55% of the contribution to ozone concentrations from local sources; the degree of ozone pollution from local sources in summer is July>June>May; Erdao and Kuangcheng districts in the urban areas, and Dewei, Jiutai and Yushu in the suburbs contribute more to the ozone pollution in Changchun City.

Simulation of Ozone Emission Reduction Response to Precursors and Control Options in Changchun City

Taking July, the most serious month for ozone pollution, as the study period, 38 emission reduction scenarios were set up to simulate the abatement response of ozone to precursors in Changchun, and to analyse the optimal abatement ratios of precursors in different regions. The simulation shows that the urban area of Changchun City is a VOC control area in 2019, and only reducing VOC emissions has the best effect on ozone pollution control ; the suburban area belongs to the synergistic control area of VOC and NOx, and ozone precursors are best abated according to the ratio of VOC:NOx=1:2, e.g., when VOC abatement is 20%, the corresponding NOx abatement of 40% is the best effect.

Based on the optimal emission reduction ratio and ozone pollution sources, combined with the 14th Five-Year Plan emission reduction potential of each industry, three emission reduction scenarios are set up: high, medium and low. The simulation shows that Changchun summer ozone is best controlled under the high reduction scenario. The high abatement scenario is to reduce only VOC in urban areas, 30% for electricity, industrial boilers, cement, 40% for residents, traffic, solvent use, chemical raw material production, petroleum extraction and crude oil processing, and other processes; while in suburban areas, the synergistic abatement is to reduce VOC by 30% for each industry and NOx by 60%. Under the scenarios of high, medium and low emission reduction in accordance with the optimal control ratio of precursors, the maximum 8-hour ozone concentration changes in Changchun were reduced by 0.46 μg/m³, 0.39 μg/m³, and 0.35 μg/m³, respectively, and the ozone concentration showed a relatively consistent decrease in June and July under the scenarios of high, medium and low emission reduction in accordance with the optimal control ratio of precursors. The higher the source reduction, the larger the decrease in ozone concentration and the better the control effect.