首都国际机场航空器排放清单的计算分析

基于微脉冲激光雷达提取的混合层高度与首都机场的实际运行数据,采用美国EPA方法,更准确的估算了2016年首都国际机场航空器排放清单.结果表明：在航空器起飞着陆（LTO）循环排放的各种污染物中,NO_x和CO排放量最多,分别占排放总量的53.3%和38.5%.滑行阶段和爬升阶段的排放总量较多,占排放总量的49.7%和25.7%.滑行阶段是航空器排放CO、SO_x、HC和PM的主要阶段.在滑行阶段的主要排放物是CO和NO_x,分别占滑行阶段排放总量的71.7%和17.2%.混合层高度变化对航空器排放的NO_x与CO影响最大,对SO_x、HC与PM影响较小.在所有的起降航班机型中,A320对排放影响最小,B77W影响最大.航空器场面滑行时间是影响污染物排放量的一个非常重要的因素.优化航空器滑行效率,减少滑行时间,对减少机场排放量会有非常积极的作用.     

首都国际机场飞机排放清单的建立

将基于标准起飞着陆（LTO）循环各阶段工作时间的飞机排放量计算方法加以改进,利用AMDAR资料计算飞机的有效排放高度,进而准确计算出基于逐架飞机的大气污染物排放总量.结果表明,首都国际机场2013年飞机NO_x、CO、HC、SO₂和PM_2.5排放总量分别为7042.1t、3189.9t、295.3t、429.4t和150.4t.与传统的基于LTO循环的方法相比,修正后的首都机场飞机NO_x、CO、HC和SO₂排放增加了23.5%、2.3%、2.1%和18.1%.飞机排放的CO、HC、SO₂和PM_2.5月变化较小,NO_x排放受飞机有效排放高度影响月波动较大.1～2月飞机污染物排放量处于全年最低水平,8月各污染物排放达到峰值.此外,飞机在爬升和滑行/慢车两种模式下污染物排放比例最大,分别占排放总量的37.7%与36.8%.     

Numerical simulation study on air quality in aircraft cabins

Air pollution is one of the main factors that affect the air quality in aircraft cabins, and the use of different air supply modes could influence the distribution of air pollutants in cabins. Based on the traditional ceiling air supply mode used on the B737NG, this study investigated another 3 different kinds of air supply modes for comparison: luggage rack air supply mode, joint mode combining ceiling and luggage rack air supply, and joint mode combining ceiling and individual air supply. Under the above 4 air supply modes, the air velocity, temperature and distribution of air pollutants in a cabin full of passengers were studied using computational fluid dynamics (CFD), and carbon dioxide (CO₂) and formaldehyde were selected as 2 kinds of representative air pollutants. The simulation results show that the joint mode combining ceiling and individual air supply can create a more uniform distribution of air velocity and temperature, has a better effect on the removal of CO₂ and formaldehyde, and can provide better air quality in cabins than the other 3 modes.     

Evidence of aircraft activity impact on local air quality: A study in the context of uncommon airport operation

Wuhan Tianhe International Airport (WUH) was suspended to contain the spread of COVID-19, while Shanghai Hongqiao International Airport (SHA) saw a tremendous flight reduction. Closure of a major international airport is extremely rare and thus represents a unique opportunity to straightforwardly observe the impact of airport emissions on local air quality. In this study, a series of statistical tools were applied to analyze the variations in air pollutant levels in the vicinity of WUH and SHA. The results of bivariate polar plots show that airport SHA and WUH are a major source of nitrogen oxides. NO_x, NO₂ and NO diminished by 55.8%, 44.1%, 76.9%, and 40.4%, 33.3% and 59.4% during the COVID-19 lockdown compared to those in the same period of 2018 and 2019, under a reduction in aircraft activities by 58.6% and 61.4%. The concentration of NO₂, SO₂ and PM_2.5 decreased by 77.3%, 8.2%, 29.5%, right after the closure of airport WUH on 23 January 2020. The average concentrations of NO, NO₂ and NO_x scatter plots at downwind of SHA after the lockdown were 78.0%, 47.9%, 57.4% and 62.3%, 34.8%, 41.8% lower than those during the same period in 2018 and 2019. However, a significant increase in O₃ levels by 50.0% and 25.9% at WUH and SHA was observed, respectively. These results evidently show decreased nitrogen oxides concentrations in the airport vicinity due to reduced aircraft activities, while amplified O₃ pollution due to a lower titration by NO under strong reduction in NO_x emissions.     

Effect of current emission abatement strategies on air quality improvement in China: A case study of Baotou, a typical industrial city in Inner Mongolia

The nationalAirPollutionPreventionandControlActionPlanrequiredsignificant decreases inPM2.5 levels overChina.Toexploremoreeffectiveemissionabatement strategies inindustrialcities,acasestudywasconductedinBaotoutoevaluatethecurrent national controlmeasures.ThetotalemissionsofSO2, NOX, PM2.5 and NMVOC (non-methanevolatileorganiccompounds)inBaotouwere211.2Gg,156.1Gg,28.8Gg, and 48.5Gg,respectivelyin2013,andtheywouldexperienceareductionof30.4%,26.6%, 15.1%, and8.7%,respectivelyin2017and39.0%,32.0%,24.4%,and12.9%,respectivelyin 2020. TheSO2, NOX and PM2.5 emissionsfromtheindustrialsectorwouldexperiencea greater decrease,withreductionsof37%,32.7and24.3%,respectively.From2013to2020, the concentrationsofSO2, NO2, andPM2.5 are expectedtodeclinebyapproximately30%, 10% and14.5%,respectively.ThereductionrateofSNA(sulfate,nitrateandammonium) concentrationswassignificantlyhigherthanthatofPM2.5 in 2017,implyingthatthecurrent key strategytowardcontrollingairpollutantsfromtheindustrialsectorismorepowerful for SNA.Althoughairpollutioncontrolmeasuresimplementedintheindustrialsector could greatlyreducetotalemissions,constrainingtheemissionsfromlowersourcessuch as residentialcoalcombustionwouldbemoreeffectiveindecreasingtheconcentrationof PM2.5 from 2017to2020.Theseresultssuggestthatevenforatypicalindustrialcity,the reduction ofPM2.5 concentrationsnotonlyrequiresdecreasesinemissionsfromthe industrial sector,butalsofromthelowemissionsources.Theseasonalvariationinsulfate concentrationalsoshowedthatemissionfromcoal-burningisthekeyfactortocontrol during theheatingseason.     

Influence of agricultural activities, forest fires and agro-industries on air quality in Thailand

Annual and monthly-based emission inventories in northern, central and north-eastern provinces in Thailand, where agriculture and related agro-industries are very intensive, were estimated to evaluate the contribution of agricultural activity, including crop residue burning, forest fires and related agro-industries on air quality monitored in corresponding provinces. The monthly-based emission inventories of air pollutants, or, particulate matter (PM), NOx and SO₂, for various agricultural crops were estimated based on information on the level of production of typical crops: rice, corn, sugarcane, cassava, soybeans and potatoes using emission factors and other parameters related to country-specific values taking into account crop type and the local residue burning period. The estimated monthly emission inventory was compared with air monitoring data obtained at monitoring stations operated by the Pollution Control Department, Thailand (PCD) for validating the estimated emission inventory. The agro-industry that has the greatest impact on the regions being evaluated, is the sugar processing industry, which uses sugarcane as a raw material and its residue as fuel for the boiler. The backward trajectory analysis of the air mass arriving at the PCD station was calculated to confirm this influence. For the provinces being evaluated which are located in the upper northern, lower northern and northeast in Thailand, agricultural activities and forest fires were shown to be closely correlated to the ambient PM concentration while their contribution to the production of gaseous pollutants is much less.     

Baosteel emission control significantly benefited air quality in Shanghai

As the largest iron and steel producer in China, a part of Baosteel moved out of Shanghai deserves close attention due to its environmental impact. To understand the effect of Baosteel emission control on air quality in Shanghai, daily PM_(10), PM_(2.5), SO_2, NO_2 and CO were measured from 2010 to 2016. Concentrations of pollutants in Baoshan District presented a decreased trend during 2010–2016, with a reduction rate of 28.6% for PM_(10), 67.3% for SO_2, 8.6% for NO_2 and 42.0% for CO. However, fine particle pollution in Baoshan District during 2012–2016 seems to become more prominent, with PM_(2.5) concentration of 47 ± 28,45 ± 33, 38 ± 24, 54 ± 41 and 51 ± 34 μg/m3, respectively, indicating a slight increase of 8.5%in PM_(2.5). Concentrations of PM_(10) and CO decreased by 12.5% and 33.8% in the second half year in 2016(compared with that in 2015) probably due to closure of blast furnace of Baosteel. Baosteel was identified as the largest pollution source in Baoshan District.Emission from Baosteel accounted for 58.0% of SO_2, 43.6% of NO_2 and 79.3% of dust in total emission from Baoshan District during 2010–2015. Meanwhile, pollutant emission and coal consumption from Baosteel decreased by 52.0% for SO_2, 40.1% for NO_2, 15.7% for dust and22% for coal consumption. Energy consumption in Baoshan District reduced by 31% from2011 to 2015. Air quality improvement in Shanghai was attributed to local emission reduction, together with regional air quality improvement.     

Estimating emissions from crop residue open burning in China based on statistics and MODIS fire products

With the objective of reducing the large uncertainties in the estimations of emissions from crop residue open burning, an improved method for establishing emission inventories of crop residue open burning at a high spatial resolution of 0.25°× 0.25° and a temporal resolution of1 month was established based on the moderate resolution imaging spectroradiometer(MODIS) Thermal Anomalies/Fire Daily Level3 Global Product(MOD/MYD14A1). Agriculture mechanization ratios and regional crop-specific grain-to-straw ratios were introduced to improve the accuracy of related activity data. Locally observed emission factors were used to calculate the primary pollutant emissions. MODIS satellite data were modified by combining them with county-level agricultural statistical data, which reduced the influence of missing fire counts caused by their small size and cloud cover. The annual emissions of CO_2, CO, CH_4,nonmethane volatile organic compounds(NMVOCs), N_2O, NO_x, NH_3, SO_2, fine particles(PM2.5),organic carbon(OC), and black carbon(BC) were 150.40, 6.70, 0.51, 0.88, 0.01, 0.13, 0.07, 0.43,1.09, 0.34, and 0.06 Tg, respectively, in 2012. Crop residue open burning emissions displayed typical seasonal and spatial variation. The highest emission regions were the Yellow-Huai River and Yangtse-Huai River areas, and the monthly emissions were highest in June(37%).Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of within ±126% for N_2O to a high of within ± 169% for NH_3.     

Design and demonstration of a next-generation air quality attainment assessment system for PM2.5 and O3

Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test—Community Edition (SMAT-CE) is developed for demonstrating attainment of air quality standards of O₃ and PM_2.5. SMAT-CE improves computational efficiency and provides a number of advanced visualization and analytical functionalities on an integrated GIS platform. SMAT-CE incorporates historical measurements of air quality parameters and simulated air pollutant concentrations under a number of emission inventory scenarios to project the level of compliance to air quality standards in a targeted future year. An application case study of the software based on the U.S. National Ambient Air Quality Standards (NAAQS) shows that SMAT-CE is capable of demonstrating the air quality attainment of annual PM_2.5 and 8-hour O₃ for a proposed emission control policy.     

Design and demonstration of a next-generation air quality attainment assessment system for PM2.5 and O3

Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test—Community Edition (SMAT-CE) is developed for demonstrating attainment of air quality standards of O₃ and PM_2.5. SMAT-CE improves computational efficiency and provides a number of advanced visualization and analytical functionalities on an integrated GIS platform. SMAT-CE incorporates historical measurements of air quality parameters and simulated air pollutant concentrations under a number of emission inventory scenarios to project the level of compliance to air quality standards in a targeted future year. An application case study of the software based on the U.S. National Ambient Air Quality Standards (NAAQS) shows that SMAT-CE is capable of demonstrating the air quality attainment of annual PM_2.5 and 8-hour O₃ for a proposed emission control policy.     

Accurate prediction of air quality response to emissions for effective control policy design

Designing effective control policy requires accurate quantification of the relationship between the ambient concentrations of O₃and PM_2.5and the emissions of their precursors.However,the challenge is that precursor reduction does not necessarily lead to decreases in the concentrations of O₃and PM_2.5,which are formed by multiple precursors under complex physical and chemical processes;this calls for the development of advanced model technologies to prov...     

北京市能源利用对空气质量的影响分析和预测

为评价能源消耗对未来北京市空气质量的影响,以2000年为基准年,2008年为目标年,建立了北京市城八区能源利用相关的一次PM₁₀、SO₂和Nox的排放清单,采用空气质量模型,模拟城八区内各污染物浓度的时空分布,分析其排放和浓度分布特征及行业分担率,并预测2008年的空气质量.结果表明,对于能源消耗排放的一次PM₁₀和SO₂,工业排放对其浓度的贡献率在40%以上;机动车排放对Nox浓度的贡献率在65%左右;按照现行的政策和发展趋势,2008年北京市城八区的空气质量将有所好转,与能源利用相关的一次PM₁₀、SO₂和NO₂在各监测点的年日均浓度分别约为25,50,51μg/m³.     

Analysis and prediction of the influence of energy utilization on air quality in Beijing

This work evaluates the influence of energy consumption on the future air quality in Beijing, using 2000 as the base year and 2008 as the target year. It establishes the emission inventory of primary PM₁₀, SO₂ and NO_x related to energy utilization in eight areas of Beijing. The air quality model was adopted to simulate the temporal and spatial distribution of each pollutant concentration in the eight urban areas. Their emission, concentration distribution, and sectoral share responsibility rate were analyzed, and air quality in 2008 was predicted. The industrial sector contributed above 40% of primary PM₁₀ and SO₂ resulting from energy consumption, while vehicles accounted for about 65% of NO_x. According to the current policy and development trend, air quality in the eight urban areas could become better in 2008 when the average concentrations of primary PM₁₀, SO₂ and NO₂ related to energy utilization at each monitored site are predicted to be about 25, 50 and 51 μg/m³, respectively. Translated from China Environmental Science, 2005, 25(6): 746–750 [译自: 中国环境科学]     

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling (RSM) methodology and serves as a visualization and analysis tool (VAT) for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S. demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias < 2% and assisting in air quality policy making in near real time.     

全国火电行业大气污染物排放对空气质量的影响

基于WRF-CAMx空气质量模型,定量模拟了火电行业主要大气污染物排放对全国城市环境空气质量的影响.结果表明,火电行业对全国城市SO₂、NO₂、PM_2.5、硫酸盐、硝酸盐及一次PM_2.5年均浓度平均贡献率分别为15.6%、19.6%、8.5%、11.7%、12.0%和5.2%,并呈现空气污染越重地区,火电行业污染贡献率越低的总体特征.其中,京津冀鲁豫、长三角、以武汉城市群及长株潭城市群为中心的两湖平原地区、成渝地区中大部分空气污染最为严重的区域,火电行业对PM_2.5年均浓度的贡献率低于8%.因此,火电行业对环境空气质量的影响总体较小,在深化火电行业污染减排的同时,必须强化非电力行业多污染物协同控制.     

典型石化企业排放空气质量影响模拟研究

基于惠州市大亚湾区2017年大气污染源排放清单,利用WRF-CMAQ模型系统量化评估了大亚湾区某典型石化企业在关停和增产排放情景下对周边空气质量的影响.清单结果显示该企业2017年SO₂、NO_x、PM₁₀、PM_2.5、CO和VOCs的排放量分别为212 、1744 、455 、359 、1458 和6446 t,在严格落实等量替代及减排措施后,该石化企业虽然产能翻倍,但VOCs排放量同比2017年显著减少了30%,其它污染物排放量增加了6%~19%.模拟结果显示2017年该石化企业排放对大亚湾区NO₂、PM₁₀、PM_2.5和O₃的浓度贡献分别为0.91、0.64、0.54和-0.08 μg·m^-3,完全关闭该企业排放后对周边站点NO₂改善效果最大（可使邻近管委会子站NO₂浓度下降1.24 μg·m^-3,下降百分比为5.10%）,但由于NO的滴定效应,该企业NO_x减排对周边管委会子站和霞涌子站的O₃浓度均有轻微负贡献;该石化企业的增产改造对周边O₃浓度降低影响明显,周边站点中O₃浓度最高可下降2.45 μg·m^-3（下降幅度为1.72%）,大亚湾区O₃浓度整体也可下降1.45 μg·m^-3.此外,受秋冬季不利扩散条件以及主导上风向污染传输影响,该企业在1月和10月对管委会子站NO₂、PM₁₀和PM_2.5的浓度贡献较大,由于冬季低温导致光化学反应自由基活性降低,该企业在1月对管委会子站O₃浓度负贡献显著.     

铁岭市空气日报及预报的相关性研究

本文采用了空气污染指数进行评价空气质量,确定铁岭市空气质量日报、预报。根据空气污染指数值确定空气质量污染程度,最后采用数据统计方法对日报、预报的结果进行检验,检查两个样本均值之间是否有显著性差异。     

2015年海南省火电行业大气环境影响研究

基于火电企业在线监测数据、环境统计数据、排污许可及火电排放清单等，分析各统计口径下的海南火电大气污染物排放量差异，并基于在线监测数据分析海南省火电排放时间变化规律.分别设置现状、排污许可及超低排放3种情景，采用CALPUFF模型分析3种情景下火电厂对海南大气环境的影响.结果显示，不同统计口径下火电厂各污染物排放量差异较大，最大差值可达到5.65倍；在时间维度上，海南省火电行业污染物排放量月际分布较平稳，每月污染物排放量约占全年的7%~10%，24h变化呈现明显“两峰两谷”特征.在大气环境影响方面，火电企业大气SO₂、NO_x、PM_2.5、PM₁₀浓度分布总体呈现西部高东部低的趋势.现状情景下火电企业对各城市年均浓度影响范围为SO₂ 0.001~0.015μg/m³、NO_x 0~0.01μg/m³、PM₁₀ 0.001~0.006μg/m³、PM_2.5 0~0.003μg/m³，最高浓度基本出现在东方市、临高县.火电厂对大气环境的影响程度为许可情景>现状情景>超低情景，执行排污许可时火电厂排放PM₁₀和NO_x对各城市均值年均浓度较现状情景分别增加50%和38%；全面实施超低排放后，火电厂对大气环境影响有明显改善，SO₂和PM_2.5对各城市均值年均浓度较现状情景分别降低57%和69%.     

Overview of current regional and local scale air quality modelling practices: Assessment and planning tools in the EU

The 2008 European Air Quality Directive (AQD) (2008/50/EC) encourages the use of models in combination with monitoring in a range of applications. It also requires Member States to design appropriate air quality plans for zones where the air quality does not comply with the AQD limit values. In order to cope with these various elements, a wide range of different modeling methods have been developed and applied by EU Member States in the last decade to assess the effects of local and regional emission abatement policy options on air quality and human health. However, an overall review of the methodologies that are used in different countries to compile local and regional air quality plans has not been performed so far. Such a review has been the objective of the APPRAISAL EU FP7 project with the main goal to identify methodologies and their limitations and to propose possible key areas to be addressed by research and innovation on the basis of this review. To fulfill these objectives, a structured online database of methodologies has been developed in collaboration with experts involved in the design of air quality plans (AQP). The current work relies on the APPRAISAL database which currently totals 59 contributions from 13 Member States. In this paper we summarize the outcome of the APPRAISAL project with respect to the review of current Integrated Assessment Modeling practices.     

北京市与呼和浩特市空气质量对比分析

为了对比北京市和呼和浩特市空气质量,探讨其差异性成因及防治对策,收集2市2014—2019年的空气质量常规监测数据,对空气污染物浓度、首要污染物变化及空气质量指数等特征进行分析。结果表明：北京和呼和浩特2市空气中PM₁₀、PM_2.5、SO₂、NO₂、CO这5种污染物浓度表现出相似的季节变化特征,空气质量冬季最差,夏季最好;2市空气中污染物都是以颗粒物为主,其中北京市以PM_2.5为主,呼和浩特市以PM₁₀为主;长期监测数据显示,2市在经济社会快速发展的同时,污染物浓度大多呈持续下降的趋势,但O₃浓度有所增加。从2市各经济指标和污染物浓度变化的相关性看出,城市高质量发展越来越受到城市空气质量的约束,而改善城市经济结构在空气污染防治中具有极大作用。