VOC emission caps constrained by air quality targets based on response surface model: A case study in the Pearl River Delta Region, China

Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds (VOCs), VOC emission control has become a major concern in China. In response, emission caps to control VOC have been stipulated in recent policies, but few of them were constrained by the co-control target of PM_2.5 and ozone, and discussed the factor that influence the emission cap formulation. Herein, we proposed a framework for quantification of VOC emission caps constrained by targets for PM_2.5 and ozone via a new response surface modeling (RSM) technique, achieving 50% computational cost savings of the quantification. In the Pearl River Delta (PRD) region, the VOC emission caps constrained by air quality targets varied greatly with the NO_x emission reduction level. If control measures in the surrounding areas of the PRD region were not considered, there could be two feasible strategies for VOC emission caps to meet air quality targets (160 µg/m³ for the maximum 8-hr-average 90th-percentile (MDA8-90%) ozone and 25 µg/m³ for the annual average of PM_2.5): a moderate VOC emission cap with <20% NOx emission reductions or a notable VOC emission cap with >60% NO_x emission reductions. If the ozone concentration target were reduced to 155 µg/m³, deep NO_x emission reductions is the only feasible ozone control measure in PRD. Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions. If VOC emissions were further reduced in autumn, MDA8-90% ozone could be lowered by 0.3-1.5 µg/m³, equaling the ozone benefits of 10% VOC emission reduction measures. The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM_2.5 and O₃ pollution in China.     

Variability of PM2.5 and O3 concentrations and their driving forces over Chinese megacities during 2018-2020

Recently,air pollution especially?ne particulate matters (PM_2.5) and ozone (O₃) has become a severe issue in China.In this study,we?rst characterized the temporal trends of PM_2.5and O₃for Beijing,Guangzhou,Shanghai,and Wuhan respectively during 2018-2020.The annual mean PM_2.5has decreased by 7.82%-33.92%,while O₃concentration showed insigni?cant variations by-6.77%-4.65%during 2018-2020.The generalized additive models (GAMs) were ...     

Studies on relationships between air pollutants and allergenicity of Humulus Scandens pollen collected from different areas of Shanghai

Pollen pollution and allergy are becoming prominent issues in China. However, few studies on pollinosis have been reported. As an allergen in the atmosphere, allergenic Humulus scandens pollen was collected from four districts of Shanghai, including Wusong (WS), Jiading (JD), Xujiahui (XJH) and Songjiang (SJ). The mass concentrations of SO₂, NO₂, O₃, PM_10, and PM_2.5 (particulate matter with air dynamic diameter less than 10 and 2.5 µm, respectively) near the four sampling sites were also recorded during Humulus scandens pollen season. The allergenicity of the Humulus scandens pollen was assessed by using of a rat model and enzyme linked immunosorbent assay (ELISA). Relationships between the allergenicity and air pollutants were correlated. Our results demonstrated that the biological viability of the pollens collected from the four districts exhibited no significant differences. ELISA and dot blotting results further demonstrated that the serum of sensitized rats exhibited much higher immune-reactive response than that of control groups. Western blotting showed that the 15 KD (1KD = 1000 dalton) proteins of Humulus pollen led to the allergic response. The allergenic intensity of Humulus pollen protein from different samples followed the pattern: WS > JD > XJ > SJ. There was a negative relationship between the allergenicity of Humulus pollens and PM₁₀ (R = -0.99) / PM_2.5 (R = -0.73), and a positive relationship with O₃ (R = 0.92). These data clearly showed that PM₁₀ and PM_2.5 could enhance Humulus pollen protein release, and O₃ could aggravate the allergenicity of the Humulus pollen.     

Deciphering urban traffic impacts on air quality by deep learning and emission inventory

Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep learning model, iDeepAir, to predict surface-level PM_2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air quality. Our model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355 µg/m³ to 12.283 µg/m³ compared with other models. And identifies the ranking of major factors, local meteorological conditions have become a nonnegligible factor. Layer-wise relevance propagation (LRP) is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM_2.5 concentration in various regions of Shanghai. Meanwhile, As the strict and effective industrial emission reduction measurements implementing in China, the contribution of urban traffic to PM_2.5 formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03% in 2011 to 24.37% in 2017 in Shanghai, and the impact of traffic emissions would be ever-prominent in 2030 according to our prediction. We also infer that the promotion of vehicular electrification would achieve further alleviation of PM_2.5 about 8.45% by 2030 gradually. These insights are of great significance to provide the decision-making basis for accurate and high-efficient traffic management and urban pollution control, and eventually benefit people's lives and high-quality sustainable developments of cities.     

上海市浦东城区二次气溶胶生成的估算

利用2010年5～10月不同日最高O3小时浓度(O3,max)下PM10浓度变化评估不同O3浓度水平下二次气溶胶生成量.CO作为一次颗粒物的标志物,O3作为光化学反应水平的指示物种.结果表明不同光化学水平条件下,PM10中一次与二次气溶胶浓度及比例存在较大差异.随着光化学水平的增加,PM10中一次气溶胶排放浓度增长不大(0.036～0.044 mg.m-3),二次气溶胶的生成量却呈数倍增长(0.018～0.055 mg.m-3);二次与一次气溶胶浓度的比例也从49.8%增加到124.5%.O3,max出现的时间也随着光化学水平的增强由13:00推迟到14:00,二次气溶胶生成的主要时段也从11:00～20:00增加到09:00～20:00;此外,PM2.5中主要组分SO24-、NO3-、OC等比例随着光化学水平(即O3,max浓度)的不同而存在一定差异,当O3,max<0.10 mg.m-3时,PM2.5主要由12.0%有机碳(OC)、18.7%硫酸盐、13.1%硝酸盐和4.5%元素碳(EC)组成,而O3,max>0.20mg.m-3时,PM2.5主要由20.0%有机碳(OC)、22.9%硫酸盐、23.1%硝酸盐和4.7%元素碳(EC)组成.说明SO24-、NO3-、OC受光化学水平影响较大.     

Distribution and chemical speciation of arsenic in different sized atmospheric particulate matters

The distribution and chemical speciation of arsenic (As) in different sized atmospheric particulate matters (PMs), including total suspended particles (TSP), PM₁₀, and PM_2.5, collected from Baoding, China were analyzed. The average total mass concentrations of As in TSP, PM₁₀, and PM_2.5 were 31.5, 35.3, and 54.1 µg/g, respectively, with an order of PM_2.5 >PM ₁₀ > TSP, revealing that As is prone to accumulate on fine particles. Due to the divergent toxicities of different As species, speciation analysis of As in PMs is further conducted. Most of previous studies mainly focused on inorganic arsenite (iAs^III), inorganic arsenate (iAs^V), monomethylarsonate (MMA), and dimethylarsinate (DMA) in PMs, while the identification and sensitive quantification of trimethylarsine oxide (TMAO) were rarely reported. In this study, a high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry system was optimized for As speciation including TMAO in PMs. An anion exchange column was used to separate MMA, DMA and iAs^V, while a cation exchange column to separate TMAO and iAs^III. Results showed that iAs^V was the dominate component in all the samples, corresponding to a portion of 79.2% ± 9.3% of the total extractable species, while iAs^III, TMAO and DMA made up the remaining 21%. Our study demonstrated that iAs^III accounted for about 14.4% ± 11.4% of the total extracted species, with an average concentration of 1.7 ± 1.6 ng/m³. It is worth noting that TMAO was widely present in the samples (84 out of 97 samples), which supported the assumption that TMAO was ubiquitous in atmospheric particles.     

Spatial and temporal variation of particulate matter and gaseous pollutants in 26 cities in China

O3and PM2.5were introduced into the newly revised air quality standard system in February 2012, representing a milestone in the history of air pollution control, and China's urban air quality will be evaluated using six factors(SO2, NO2, O3, CO, PM2.5and PM10) from the beginning of 2013. To achieve the new air quality standard, it is extremely important to have a primary understanding of the current pollution status in various cities. The spatial and temporal variations of the air pollutants were investigated in 26 pilot cities in China from August 2011 to February 2012, just before the new standard was executed. Hourly averaged SO2, NO2and PM10were observed in 26 cities, and the pollutants O3, CO and PM2.5were measured in 15 of the 26 cities. The concentrations of SO2and CO were much higher in the cities in north China than those in the south. As for O3and NO2, however, there was no significant diference between northern and southern cities. Fine particles were found to account for a large proportion of airborne particles, with the ratio of PM2.5to PM10ranging from 55% to 77%. The concentrations of PM2.5(57.5 μg/m3) and PM10(91.2 μg/m3) were much higher than the values(PM2.5: 11.2 μg/m3; PM10 : 35.6 μg/m3) recommended by the World Health Organization. The attainment of the new urban air quality standard in the investigated cities is decreased by 20% in comparison with the older standard without considering O3, CO and PM2.5, suggesting a great challenge in urban air quality improvement, and more eforts will to be taken to control air pollution in China.     

Evaluating the influence of air pollution on solar radiation observations over the coastal region of Alicante (Southeastern Spain)

The present study evaluates ground-based downward surface shortwave radiation (R_s) over the coastal region of Alicante (Southeastern Spain). Hourly measurements collected over the eleven-year period 2010-2020 are used. Two weather stations located over the region capital, Alicante, have been selected as representative of urban and suburban typologies. Two additional weather stations far from the city have been selected representing rural typologies. R_s is significantly reduced over the urban station during the morning hours within the winter season compared to the observations recorded over the suburban and rural stations, with a global mean difference of -81 and -120 W/m² at 10 LT, respectively. However, no significant differences are obtained during the midday sun, with a global mean difference of -20 W/m² between the urban and rural stations. With the aim of explaining these differences, the current paper investigates the relationship between R_s and different air pollutants: NO_x, SO₂, and fine particulate matter (PM_2.5 and PM₁₀) as well as the wind field measured at the urban and suburban stations. The results found in this work point towards a close relationship between R_s and NO_x concentrations annual cycles, which are also influenced by the prevailing wind circulations observed over the study area. A global mean NO_x concentration of 107 µg/m³ is observed over the urban station at 10 LT during the winter season. In contrast, these high concentrations are significantly reduced over the suburban station, with global mean value of 40 µg/m³ at 10 LT, for this period of the year.     

河北农居环境颗粒态汞污染特征及健康评估研究

近年来,我国农村环境问题日渐加重,大气颗粒态汞对人体健康的危害逐渐凸现出来,而已有研究对我国农居环境中的汞污染状况关注较少. 以颗粒态汞为研究对象,于2009年7、8月及2010年10~12月,对河北省6个村庄中的34个典型农居环境进行PM₁₀和PM_2.5膜采样,采用冷原子荧光法测定颗粒态汞质量浓度. 结果表明,同一季节时,厨房PM₁₀中汞质量浓度约是庭院PM₁₀中汞质量浓度的2倍; 在同一空间内,PM₁₀中汞质量浓度大小依次是冬季(3.004 ng·m^-3)>秋季(1.550 ng·m^-3)>夏季(1.127 ng·m^-3); 同一季节时,PM_2.5中汞质量浓度大小依次是厨房(0.795 ng·m^-3±0.337 ng·m^-3)>客厅(0.398 ng·m^-3±0.159 ng·m^-3)>庭院(0.321 ng·m^-3±0.143 ng·m^-3); PM_2.5中的汞质量浓度占PM₁₀中汞质量浓度的百分比为(52.4±13.5)%. 对农居环境PM_2.5中汞的健康风险度水平进行评价,不同人群中儿童的暴露水平最高,其年均超额危险度<10^-8. 可知农居环境PM_2.5中汞对农户的健康风险在可以忽略的水平.     

Short-term impacts of air pollution on the platelet-lymphocyte ratio and neutrophil-lymphocyte ratio among urban adults in China

The short-term impacts of urban air pollution on the platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) remain obscure.In this study,we included 3487 urban adults from the Wuhan-Zhuhai cohort.Individual inhalation exposure to air pollutants was estimated by combining participants’daily breath volume and ambient concentrations of six air pollutants (includingfine particulate matter (PM_2.5),inhalable particulate matter(PM₁₀),nitrogen dioxide (NO₂...     

成都市降水对大气污染物的清除效果分析

成都市受特殊地形和气候条件影响,地面风速小,静风比例高,空气湿度大,大气污染物扩散缓慢,主要靠降水的冲刷和清除作用去除大气污染物.利用2014年5月13日-2017年12月31日成都市逐小时ρ（PM_2.5）、ρ（PM₁₀）、ρ（NO₂）、ρ（O₃）、ρ（CO）、ρ（SO₂）监测数据和同期地面降水量观测数据,分析了降水前污染物质量浓度、小时最大降水量、降水持续时间及累积降水量对大气污染物清除效果的影响.结果表明:①降水对6种大气污染物的清除率随降水前污染物质量浓度的增加而增大,并且汛期降水对大气污染物的清除率大于非汛期降水.②降水对大气污染物起正清除作用,清除率随降水持续时间的增加而增大.③不同降水量对不同污染物的清除效果不同,对PM_2.5、PM₁₀、NO₂、CO和SO₂的清除率随降水量的增加而逐渐增大,对O₃的清除效果相差不大且清除率均较大;小时最大降水量对PM_2.5、PM₁₀、NO₂、O₃、CO、SO₂的清除率平均值分别为29.48%、26.95%、22.02%、26.87%、11.94%、28.75%,累积降水量的清除率平均值分别为31.64%、30.66%、24.38%、26.31%、13.89%、32.91%,其中CO不易溶于水,降水对其清除作用明显小于其他几种污染物.研究显示,降水对大气污染物的清除作用显著,对SO₂、PM_2.5和PM₁₀的清除效果较好,而对CO的清除效果较差.      

Physicochemical and toxicological characteristics of nanoparticles in aerosols in southern Thailand during recent haze episodes in lower southeast Asia

Transboundary haze from biomass burning is one of the most important air pollutions in Southeast Asia. The most recent serious haze episode occurred in 2015. Southern Thailand was affected by the haze during September to October when the particulate matter concentration hit a record high. We investigated physical and chemical characteristics of aerosols, including concentration and aerosol size distribution down to sub-micron sizes during haze episodes in 2013 and 2015 and, for reference, an insignificant haze period in 2017. The highest total suspended particulates and PM₁₀ levels in Hat Yai city were 340.1 and 322.5 µg/m³. The mass fractions were nanoparticles (< 100 nm) 3.1%-14.8% and fine particles (< 1 µm) 54.6%-59.1%. Polycyclic aromatic hydrocarbon size distributions in haze periods peaked at 0.75 µm and the concentrations are 2-30 times higher than the normal period. High molecular weight (4-6 ring) PAHs during the haze episode contribute to about 56.7%-88.0% for nanoparticles. The average values of benzo(a)pyrene toxic equivalency quotient were 3.34±2.54ng/m³ in the 2015 haze period but only 0.89±0.17 ng/m³ in 2017. It is clear that particles smaller than 1 µm, were highly toxic. Nanoparticles contributed 19.4%-26.0% of total BaP-TEQ, whereas the mass fraction is 13.1%-14.8%. Thus the nanoparticles were more carcinogenic and can cause greater health effect than larger particles. The fraction of BaP-TEQ for nanoparticles during 2017 non-haze period was nearly the same, while the mass fraction was lower. This indicates that nanoparticles are the significant source of carcinogenic aerosols both during haze and non-haze periods.     

Observations of N2O5 and NO3 at a suburban environment in Yangtze river delta in China: Estimating heterogeneous N2O5 uptake coefficients

The nitrate radical (NO₃) and dinitrogen pentoxide (N₂O₅) play an important role in the nocturnal atmosphere chemistry. Observations of NO₃ radicals and N₂O₅ were performed in a semirural ground site at Tai'Zhou in polluted southern China using cavity ring down spectroscopy (CRDS) from 23 May to 15 June 2018. The observed NO₃ and N₂O₅ concentrations were relatively low, with 1 min average value of 4.4 ± 2.2 and 26.0 ± 35.7 pptV, respectively. The N₂O₅ uptake coefficient was determined to be from 0.027 to 0.107 based on steady state lifetime method. Fast N₂O₅ hydrolysis was the largest contributor to the loss of NO₃ and contributed to substantial nitrate formation, with an average value of 14.83 ± 6.01 µg/m³. Further analysis shows that the N₂O₅ heterogeneous reactions dominated the nocturnal NO_x loss and the nocturnal NO_x loss rate is 0.14 ± 0.02 over this region.     

Progressively narrow the gap of PM2.5 pollution characteristics at urban and suburban sites in a megacity of Sichuan Basin, China

Nowadays, the fine particle pollution is still severe in some megacities of China, especially in the Sichuan Basin, southwestern China. In order to understand the causes, sources, and impacts of fine particles, we collected PM_2.5 samples and analyzed their chemical composition in typical months from July 2018 to May 2019 at an urban and a suburban (background) site of Chengdu, a megacity in this region. The daily average concentrations of PM_2.5 ranged from 5.6-102.3 µg/m³ and 4.3-110.4 µg/m³ at each site. Secondary inorganics and organic matters were the major components in PM_2.5 at both sites. The proportion of nitrate in PM_2.5 has exceeded sulfate and become the primary inorganic component. SO₂ was easier to transform into sulfate in urban areas because of Mn-catalytic heterogeneous reactions. In contrast, NO₂ was easily converted in suburbs with high aerosol water content. Furthermore, organic carbon in urban was much greater than that in rural, other than elemental carbon. Element Cr and As were the key cancer risk drivers. The main sources of PM_2.5 in urban and suburban areas were all secondary aerosols (42.9%, 32.1%), combustion (16.0%, 25.2%) and vehicle emission (15.2%, 19.2%). From clean period to pollution period, the contributions from combustion and secondary aerosols increased markedly. In addition to tightening vehicle controls, urban areas need to restrict emissions from steel smelters, and suburbs need to minimize coal and biomass combustion in autumn and winter.     

2014—2016年海口市空气质量概况及预报效果检验

本文主要基于CUACE模式在海口市的预报产品,结合2014年3月—2017年2月海口市AQI、PM_2.5、PM₁₀和O₃的实况资料进行预报效果检验.结果表明,①近3年海口市空气质量等级主要以优和良为主,但仍有少部分天数以PM₁₀、PM_2.5和O₃为首要污染物,分别占所有首要污染物天数的27.6%、29.5%和42.9%,其中O₃上升幅度较快.②CUACE模式能较好的模拟出AQI和3类污染物浓度的变化特征,其中PM_2.5的预报值与实测值最为接近,而PM₁₀和O₃普遍偏低.③日平均浓度的预报效果检验表明,PM_2.5的标准误差（RMSE）最小,AQI和PM₁₀次之,O₃最大.3个时次预报平均偏差（MB）和归一化偏差（MNB）均为负值,表明CUACE模式预报的污染要素浓度均偏低于实测值.④海口市空气质量为优等级时,TS评分最高;无首要污染物时,首要污染物预报的TS评分最高,但首要污染物为PM_2.5、PM₁₀或O₃时,TS评分均偏低.     

奥运前期与奥运期间北京市大气细颗粒物特征比较分析

利用城市生态系统研究站对北京市奥运前后(2008年6～9月)大气中细颗粒物(PM2.5)进行连续监测,获得不同阶段PM2.5日平均浓度的动态特征,分析气象因素、人为控制管理措施对颗粒物浓度的影响.结果表明,近北五环的生态中心站点(RCEES)颗粒物日均浓度平均值为0.067 mg.m-3,奥运期间的颗粒物浓度(0.060 mg.m-3)比奥运前期(0.081 mg.m-3)减少了约26%.而位于南二环市中心的教学植物园站点(JX)颗粒物浓度平均含量为0.078 mg.m-3.JX站点奥运期间的颗粒物浓度(0.069 mg.m-3)比奥运前期(0.095 mg.m-3)减少了约27%.各个阶段PM2.5的日变化都基本呈现双峰态势.第一个峰值出现在08:00～10:00左右,RCEES站点颗粒物浓度为0.068 mg.m-3,JX站点浓度值为0.089 mg.m-3;另一个峰值出现在晚20:00～22:00左右,RCEES和JX站点颗粒物浓度为0.079 mg.m-3和0.083 mg.m-3,这主要与上班交通高峰导致的尾气排放污染和道路扬尘污染等有关.研究气象参数发现奥运期间与奥运前期气象条件无显著差异,属于高温高湿风力不大的典型北京夏季天气条件.奥运期间颗粒物浓度与温度呈显著正相关(P<0.01),而与风速、相对湿度及降水相关性不显著(P>0.05).而连续多年大气污染综合治理措施和奥运空气质量保障措施的实施,产生了显著环境效益.在自然因素相差不大的条件下,人为控制因素对奥运期间颗粒物的下降起到主导作用.     

基于无人机的大气细颗粒物与臭氧污染探测与溯源研究进展

近年来,中国大气细颗粒物(PM_2.5)污染的治理已取得阶段性成效,但臭氧(O₃)污染快速上升,实现PM_2.5和O₃协同控制的基础与关键是针对大气污染物的精细化探测和污染溯源.随着无人机技术和传感器技术的迅速发展,基于无人机平台的大气污染探测可以有效获得近地层的PM_2.5和O₃结构特征,并结合计算机算法对大气污染事件进行精准溯源,具有高时效性、高灵活性和高时空分辨率的特征,有助于研究人员了解区域污染物的分布、变化以及来源,为大气复合污染的协同控制提供科学依据.通过回顾传统的大气污染探测方法,总结了污染探测领域常用的无人机飞行平台类型和探测仪器,归纳了基于无人机的PM_2.5和O₃污染探测应用与相关溯源算法,并展望了无人机大气探测的未来研究方向.     

兰州市PM2.5中多环芳烃的污染特征和来源解析

为了明确兰州市PM_2.5中16种多环芳烃（PAHs）的污染特征和来源,采集了兰州市4个季节的PM_2.5样品,运用气相色谱-质谱联用仪（GC-MS）对PAHs的浓度进行了分析,利用正定矩因子分解法（PMF）、聚类分析和潜在源因子分析法（PSCF）对PAHs的来源进行解析.结果表明,兰州市PM_2.5中ρ（PAHs）均值为：冬季［（118±16.2） ng·m^-3］>秋季［（50.8±21.6） ng·m^-3］>春季［（22.2±8.87） ng·m^-3］>夏季［（4.65±1.32） ng·m^-3］.相关性分析表明,兰州市PM_2.5和TPAHs均与温度呈现极显著的负相关性,与气压呈现极显著的正相关性,与风向、风速和相对湿度的相关性较差.各环PAHs在4个季节的占比相似,其中4环和5环的PAHs占比为最大,其次为6环和2~3环.兰州市PM_2.5中PAHs的主要来源在春夏季为工业排放和生物质及天然气燃烧,秋季工业排放占主导地位,冬季主要为燃煤排放,交通排放在4个季节的贡献比较稳定.聚类分析和PSCF计算结果表明,来自蒙古国、新疆东北部和青海等地的气流对兰州市环境空气质量有重要的影响.     

太原市2014年春节期间常规大气污染物浓度变化及聚类分析

为了探寻太原市春节期间不同监测站点各常规大气污染物的质量浓度变化规律及相互之间的关系,记录和收集了太原市上兰、南寨、涧河、尖草坪、桃园、坞城、小店、金胜、晋源9个监测点2014年农历小年至元宵节(2014-01-23—2014-02-14)期间的大气PM2.5、PM10、CO、NO2、O3、SO2小时浓度值以及相应的气温、气压、湿度、风级、能见度等气象数据,采用相关分析、小波分析、单因子污染指数评价和系统聚类等方法进行研究,发现:1该时段内就太原市总体而言,PM2.5超标倍数最大,其次是PM10、SO2、CO、NO2,O3污染最小.2农历小年、除夕、正月初八、元宵节大气PM2.5和PM10的浓度迅速增加,与自然气象因子基本无关,说明烟花爆竹的集中燃放对大气颗粒物尤其是细颗粒物产生较大影响.3SO2、NO2、CO与PM2.5和PM10浓度变化的波动趋势相似、主周期相同,反映了部分PM2.5和PM10与SO2、NO2、CO有共同的来源;O3的波动趋势及主周期与上述污染物完全不同,显示出它来源的特殊性.4按PM2.5聚类,南寨、涧河、尖草坪、桃园4个点聚为一类,小店和坞城2个点聚为一类,金胜和晋源聚为一类,位于太原市最北端作为清洁对照的上兰监测点自成一类,与它们的地理位置有较好的相符性,同时,聚类分析结果与各监测点的单因子污染指数评价结果相一致.本文提示小波分析与聚类分析相结合可以较好地反映城市大气污染物浓度变化的时间与空间分布规律.     

餐饮行业细颗粒物(PM2.5)排放测算方法:以上海市为例

以上海市餐饮企业为例,研究了餐饮企业PM_(2.5)排放特征以及排放测算方法.按照单位灶头、单位时间、单位就餐人次这3种计算基准,获得了不同类型餐饮企业PM_(2.5)的排放因子,并在此基础上结合2014年上海市餐饮企业活动水平测算了PM_(2.5)的排放清单.结果表明,餐饮企业排放PM_(2.5)的浓度范围0.1~1.8 mg·m~(-3),甚至超过国家饮食业标准中关于油烟1mg·m~(-3)的排放限值;PM_(2.5)中OC质量贡献超过50%,OC/EC比值的变化范围为58.8~752.3,平均值为128.4,可作为餐饮排放的示踪特征.企业规模是影响餐饮企业PM_(2.5)排放因子的重要因素.按照灶头活动、餐饮作业时间以及就餐人次这3种方法计算得出的餐饮企业PM_(2.5)排放因子均表明,大型、中型企业明显高于小型和微型企业(食堂、快餐).基于上述3种排放因子,计算2014年上海PM_(2.5)排放量相对一致,表明本研究获得基于3种活动水平的排放因子比较可靠,未来可应用于其他城市餐饮企业排放清单的核算.