Impact of Diwali celebrations on urban air and noise quality in Delhi City,India

A study was conducted in the residential areas of Delhi, India, to assess the variation in ambient air quality and ambient noise levels during pre-Diwali month (DM), Diwali day (DD) and post-Diwali month during the period 2006 to 2008. The use of fireworks during DD showed 1.3 to 4.0 times increase in concentration of respirable particulate matter (PM₁₀) and 1.6 to 2.5 times increase in concentration of total suspended particulate matter (TSP) than the concentration during DM. There was a significant increase in sulfur dioxide (SO₂) concentration but the concentration of nitrogen dioxide (NO₂) did not show any considerable variation. Ambient noise level were 1.2 to 1.3 times higher than normal day. The study also showed a strong correlation between PM₁₀ and TSP (R ² ≥ 0.9) and SO₂ and NO₂ (R ² ≥ 0.9) on DD. The correlation between noise level and gaseous pollutant were moderate (R ² ≥ 0.5). The average concentration of the pollutants during DD was found higher in 2007 which could be due to adverse meteorological conditions. The statistical interpretation of data indicated that the celebration of Diwali festival affects the ambient air and noise quality. The study would provide public awareness about the health risks associated with the celebrations of Diwali festival so as to take proper precautions.     

Ambient air quality of Lucknow City (India) during use of fireworks on Diwali Festival

The present study deals with the effect of fireworks on ambient air quality during Diwali Festival in Lucknow City. In this study, PM₁₀, SO₂, NO _x and 10 trace metals associated with PM₁₀ were estimated at four representative locations, during day and night times for Pre Diwali (day before Diwali) and Diwali day. On Diwali day 24 h average concentration of PM₁₀, SO₂, and NO _x was found to be 753.3, 139.1, and 107.3 μg m⁻³, respectively, and these concentrations were found to be higher at 2.49 and 5.67 times for PM₁₀, 1.95 and 6.59 times for SO₂ and 1.79 and 2.69 for NO _x , when compared with the respective concentration of Pre Diwali and normal day, respectively. On Diwali day, 24 h values for PM₁₀, SO₂, and NO _x were found to be higher than prescribed limit of National Ambient Air Quality Standard (NAAQS), and exceptionally high (7.53 times) for PM₁₀. On Diwali night (12 h) mean level of PM₁₀, SO₂ and NO _x was 1,206.2, 205.4 and 149.0 μg m⁻³, respectively, which was 4.02, 2.82 and 2.27 times higher than their respective daytime concentrations and showed strong correlations (p < 0.01) with each other. The 24 h mean concentration of metals associated with PM₁₀ was found to be in the order of Ca (3,169.44) > Fe (747.23) > Zn (542.62) > Cu (454.03), > Pb (307.54) > Mn (83.90) > Co (78.69) > Cr (42.10) > Ni (41.47) > Cd (34.69) in ng m⁻³ and all these values were found to be higher than the Pre Diwali (except Fe) and normal day. The metal concentrations on Diwali day were found to be significantly different than normal day (except Fe & Cu). The concentrations of Co, Ni, Cr and Cd on Diwali night were found to be significantly higher than daytime concentrations for Pre Diwali (control). The inter correlation of metals between Ca with Pb, Zn with Ni and Cr, Cu with Co, Co with Mn, Ni with Cd, Mn with Cd, Ni with Cd and Cr, and Cr with Cd showed significant relation either at p < 0.05 or P < 0.01 levels, which indicated that their sources were the same. The metals Cu, Co, Ni, Cr and Cd showed significant (p < 0.01) association with PM₁₀. These results indicate that fireworks during Diwali festival affected the ambient air quality adversely due to emission and accumulation of PM₁₀, SO₂, NO _x and trace metals. ITRC Communication Number 2538     

Short-term variation in air quality associated with firework events: a case study

The effect of fireworks on air quality was assessed from the ambient concentrations of various air pollutants (SO2, NO2, PM10 and TSP) during Diwali festival in Hisar city (India), in November 1999. The extensive use of fireworks was found to be related to short-term variation in air quality. During the festival the concentration of SO2 was observed to be increased approximately 10-fold at few sites, whereas the concentrations of NO2, PM10 and TSP increased 2-3 times, compared to the data collected on a typical winter day in December 1999. The maximum NO2 concentration was observed a day after the festival. The diurnal pattern of the above pollutants showed a slight increase in the night. The levels of these pollutants observed during Diwali were found to be moderately high, which can be associated with serious health impacts.     

烟花爆竹禁燃对春节期间东北地区空气质量影响评估

利用2015—2017年春节期间东北地区主要大气污染物(PM_(10)、PM_(2.5)、SO_2、NO_2、CO和O3)质量浓度监测资料及相应气象因子(温度、湿度、风速和气压)观测资料,分析了春节期间烟花爆竹禁燃对东北地区空气质量的影响。结果表明:随着东北地区主要城市禁燃力度的增强,空气质量逐年提升,PM_(2.5)和SO_2浓度逐年大幅度下降。禁燃可明显降低城区PM_(2.5)浓度,而由于春节期间污染源整体减少,城区和城郊监测点PM_(2.5)浓度值差异减小。烟花爆竹对PM_(10)和PM_(2.5)浓度影响高于对气体污染物SO_2、NO_2和CO的影响。此外,气象条件对东北地区春节期间禁燃改善空气质量的效果也有明显影响。因此,结合春节期间的气象条件,在东北地区实施禁燃政策动态调整非常必要。     

The impact assessment of Diwali fireworks emissions on the air quality of a tropical urban site, Hyderabad, India, during three consecutive years

Diwali is one of the largest festivals for Hindu religion which falls in the period October–November every year. During the festival days, extensive burning of firecrackers takes place, especially in the evening hours, constituting a significant source of aerosols, black carbon (BC), organics, and trace gases. The widespread use of sparklers was found to be associated with short-term air quality degradation events. The present study focuses on the influence of Diwali fireworks emissions on surface ozone (O₃), nitrogen oxides (NO _x ), and BC aerosol concentration over the tropical urban region of Hyderabad, India during three consecutive years (2009–2011). The trace gases are analyzed for pre-Diwali, Diwali, and post-Diwali days in order to reveal the festivity’s contribution to the ambient air quality over the city. A twofold to threefold increase is observed in O₃, NO _x , and BC concentrations during the festival period compared to control days for 2009–2011, which is mainly attributed to firecrackers burning. The high correlation coefficient (~0.74) between NO _x and SO₂ concentrations and higher SO₂/NO _x (S/N) index suggested air quality degradation due to firecrackers burning. Furthermore, the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation-derived aerosol subtyping map also confirmed the presence of smoke aerosols emitted from firecrackers burning over the region. Nevertheless, the concentration level of pollutants exhibited substantial decline over the region during the years 2010 and 2011 compared to 2009 ascribed to various awareness campaigns and increased cost of firecrackers.     

Assessment of Air Quality After the Implementation of Compressed Natural Gas (CNG) as Fuel in Public Transport in Delhi, India

Public transport in Delhi was amended by the Supreme Court of India to use Compressed Natural Gas (CNG) instead of diesel or petrol. After the implementation of CNG since April 2001, Delhi has the highest fraction of CNG-run public vehicles in the world and most of them were introduced within 20 months. In the present study, the concentrations of various criteria air pollutants (SPM, PM₁₀, CO, SO₂ and NO_x) and organic pollutants such as benzene, toluene, xylene (BTX) and polycyclic aromatic hydrocarbons (PAHs) were assessed before and after the implementation of CNG. A decreasing trend was found for PAHs, SO₂ and CO concentrations, while the NO_x level was increased in comparison to those before the implementation of CNG. Further, SPM, PM₁₀, and BTX concentrations showed no significant change after the implementation of CNG. However, the BTX concentration demonstrated a clear relation with the benzene content of gasoline. In addition to the impact of the introduction of CNG the daily variation in PAHs levels was also studied and the PAHs concentrations were observed to be relatively high between 10 pm to 6 am, which gives a proof of a relation with the limited day entry and movement of heavy vehicles in Delhi.     

临汾市大气污染物的时间分布特征与源区分析

多年来，临汾市多次名列我国生态环境部公布的空气质量最差的重点城市之列，对其大气污染的时间分布特征和潜在源区进行分析对其环境管理与污染防治具有重要意义。利用2015—2019年临汾市5个国控空气环境质量监测站点的6种空气污染物(SO₂、NO₂、CO、O₃、PM_2.5和PM₁₀)浓度数据和气象观测数据，使用HYSPLIT模型研究了该市空气污染物的时间变化特征、轨迹输送特征和可能的来源。结果表明，PM_2.5和PM₁₀的年均浓度均超过了《环境空气质量标准》(GB 3095—2012)Ⅱ级标准，SO₂仅在2016—2017年超过该标准，其余3种污染物的年均浓度均低于该标准。6种污染物2015—2019年的月均浓度的变化特征表现为O₃浓度呈以6、7月为中心的近似正态分布，SO₂、NO₂和CO以及PM_2.5和PM₁₀浓...     

2016年长沙市环境空气质量的“周末效应”及“假日效应”

通过获取2016年长沙市连续在线观测得到的PM₁₀、PM_2.5、NO₂、O₃、CO和 SO₂逐时浓度资料，对工作日、周末、节假日（尤其是春节）的空气质量优良天数、污染物浓度变化特征进行对比分析，长沙市2016年6项污染物均表现出一定的"周末效应"现象，周末日平均浓度均低于工作日及全年的日平均浓度，其中PM_2.5最为明显；PM₁₀和PM_2.5浓度均星期一最高，星期六最低，CO和 SO₂浓度周末也均处于相对最低水平，NO₂和O₃在周末的平均浓度略低于工作日水平或与其持平。国庆假期，由于城区人口、车辆减少，长沙大气环境质量相对较好，而春节假期，由于受到烟花爆竹集中燃放的影响，PM₁₀、PM_2.5和SO₂浓度远超过全年平均水平，这在一定程度上说明人类活动对污染物浓度及大气环境质量变化具有一定的影响力。     

Estimation of air pollutant emission loads from construction and operational activities of a port and harbour in Mumbai, India

Port causes environmental and health concerns in coastal cities if its operation and development are not made environmentally compatible and sustainable. An emission inventory is necessary to assess the impact of port projects or growth in marine activity as well as to plan mitigation strategies. In this study, a detailed emission inventory of total suspended particulate (TSP) matter, respirable particulate matter (PM₁₀), sulphur dioxide (SO₂) and oxides of nitrogen (NO_x) for a port having operation and construction activities in parallel is compiled. The study has been done for 1 year. Results show that the maximum contribution of emission of air pollutants in the port area was from TSP (68.5%) and the minimum was from SO₂ (5.3%) to the total pollutants considered in this study. Total TSP emission from all activities of the port was 4,452 tyr^???1 and PM₁₀ emission was 903 tyr^???1 in the year 2006. Re-suspension of dust from paved roads was the major contributor of TSP and PM₁₀ in the road transport sector. Construction activities of the port had contributed 3.9% of TSP and 7.4% of PM₁₀ to total emission of particulate matter. Of the total particulate emissions from various port activities approximately 20% of TSP could be attributed to PM₁₀. The sectoral composition indicates that major contribution of SO₂ emission in the port was from maritime sector and major contribution of NO_x was from road transport sector.     

Variation in spatial pattern of criteria air pollutants before and during initial rain of monsoon

Spatial patterns of various criteria air pollutants,like SO₂, NO₂, O₃, and TSP were studied atShahdara National Ambient Air Quality Monitoring stationin Delhi (India) in July 1999. The minimum pollutantconcentrations were observed during morning hours,whereas the highest concentrations were found during thelate night hours, which seem to be related with thevehicular emission. Pre-monsoon daily ambient airquality spatial pattern was compared with the spatialpattern during initial and subsequent rain shower ofmonsoon. These spatial patterns were found to beessentially the same before and during rain, however asignificant decrease in SO₂, NO₂ and TSPconcentrations (40-45%) was observed after initial andsubsequent rains of the monsoon, demonstrating theimportance of rainfall in the scavenging of thesecriteria air pollutants.     

The impact of ground-level fireworks (13?km long) display on the air quality during the traditional Yanshui Lantern Festival in Taiwan

In this study, the concentrations of CO, non-methane hydrocarbons, NO_X, SO₂, benzene, toluene, ethylbenzene, xylene (BTEX), PM₁₀, and PM_2.5 were continuously monitored before and after the fireworks display during the traditional Lantern Festival from March 2?C7, 2007 in Yanshui Town, Taiwan. Major roads in Yanshui Town were surrounded by fireworks 13 km in length, with the display lasting for 45 min. More than 200 small firecracker towers popped up randomly in town, resulting in exceedingly inhomogeneous air quality until the end of display at 03:00 the next day, March 5. During the fireworks display, the hourly concentration of PM₁₀ and PM_2.5 at Yanshui Primary School reached about 429 and 250 ??g m^???3, respectively, which is 10 times the normal level, and 6 s values even went as high as 1,046 and 842 ??g m^???3, respectively. Similarly, BTEX concentration went up to about five to 10 times its normal value during the fireworks display. As indicated by the distribution of submicron particle sizes, the number of particles with a diameter less than 100 nm increased abruptly during the event period. Metal components with concentrations of more than 10 times higher than the normal value at Yanshui Primary School were Sr, K, Ba, Pb, Al, Mg, and Cu, in sequence. Among water-soluble ions, the content of K^?+?, Mg^2?+?, and Cl^??? increased the most, all of which were related to the materials used in the fireworks. The results of this study indicate that fireworks can cause an abrupt increase in the concentration of trace substances in the air within a short period. Although the risks of these trace substances on public health remain to be further assessed, the study results can be utilized in the management of folk events.     

2001年～2008年及奥运会期间天津市大气污染特征分析

根据天津市大气质量监测数据,对2001年～2008年及奥运会期间天津市大气污染特征和主要大气污染物的变化规律进行了分析。结果表明,2001年～2008年天津市的PM10、SO2和NO2污染总体呈下降趋势,但质量浓度仍相对较高。2008年8月奥运会期间天津市PM10和SO2质量浓度达到国家空气质量二级标准,NO2质量浓度达到国家空气质量一级标准,空气质量良好。天津市PM10污染相对稳定,SO2和NO2的污染分布呈现明显的季节性,时间上表现为冬强夏弱。气象条件对污染物浓度影响明显,沙尘、大雾等天气可使污染物浓度急剧升高。     

2001—2020年合肥市空气质量变化趋势研究

为系统分析合肥市长时间序列空气质量变化特征,对合肥市2001—2020年SO₂、NO₂和PM₁₀,以及2013—2020年CO、O₃和PM_2.5的浓度特征开展研究。采用Mann-Kendall(M-K)时间趋势检验法分析了6项污染物的时间变化规律,同时考虑了人为活动对污染物小时浓度的影响。结果表明,PM_2.5和O₃是目前影响合肥市空气质量的首要污染物。2014年以来,合肥市PM₁₀、PM_2.5、CO和SO₂年均浓度均呈逐年下降趋势,但NO₂和O₃污染有加剧趋势。合肥市SO₂和颗粒物浓度表现为冬春季节高、夏秋季节低;O₃浓度变化趋势与之相反;NO₂和CO浓度呈秋冬季节高、春夏季节低。     

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.     

杭州市大气污染物排放清单及特征

以杭州市区为研究区域,通过调查整合多套污染源数据库及其他统计资料,研究文献报道及模型计算的各种污染源排放因子,获得杭州市区各行业PM10、PM2.5、SO2、NOx、CO、VOCs、NH3等污染物的排放量,建立了杭州市区2010年1 km×1 km大气污染物排放清单。结果表明,2010年杭州市区PM10、PM2.5、SO2、NOx、CO、VOCs和NH3的排放总量分别为7.96×104、4.02×104、7.23×104、8.98×104、73.90×104、39.56×104、3.32×104t。从排放源的行业分布来看,机动车尾气排放是杭州市区大气污染物最重要排放源之一,对PM10、PM2.5、NOx、CO和VOCs的贡献分别达到14.4%、27.1%、40.3%、21.4%、31.1%。道路扬尘、电厂锅炉、工业炉窑、植被、畜禽养殖对不同污染物分别有着重要贡献,道路扬尘对PM10和PM2.5的贡献分别为44.6%和20.0%、电厂锅炉对SO2和NOx的贡献分别为37.0%和25.7%、工业炉窑对CO的贡献为41.5%、植被排放对VOCs的贡献为27.1%、畜禽养殖对NH3的贡献为76.5%。从空间分布来看,萧山区和余杭区对SO2、NH3和植被排放BVOC的贡献要显著高于主城区;而主城区机动车对PM2.5、NOx和VOCs的贡献分别达到36.3%、56.0%和47.4%,较市区范围内显著增加,表明机动车尾气排放已成为杭州主城区大气污染最重要的来源之一。     

哈大绥城市“十三五”期间大气环境容量分析

根据2016—2020年哈尔滨市、大庆市、绥化市(以下称哈大绥)国控环境空气自动监测站的SO₂、NO₂、PM_2.5监测资料,统计年鉴中行政区划、污染物排放及气象等监测数据,分析哈大绥区域环境空气质量的变化趋势和测算因子,采用A值法核定了哈大绥区域SO₂、NO₂、PM_2.5的大气环境容量。结果表明:哈大绥SO₂、NO₂、PM_2.5 3项污染物采暖季的大气环境容量均呈逐年递增趋势。通过计算环境承载能力发现,哈大绥SO₂、NO₂、PM_2.5 3项污染物在非采暖季均具有高承载能力,哈大绥非采暖季环境容量高于采暖季。哈尔滨的个别污染物仍然处于临界超载状态,为减少重污染天气,应进一步削减采暖季污染物排放量。     

深圳市大气能见度特征分析及其与主要污染物因子相关性分析

近些年,随着深圳市大气污染防治举措的加强,空气质量不断趋好。文章汇总了深圳市2006～2009年大气能见度特征数据,分析了深圳市能见度的年度、季度和月度变化,发现近些年深圳市大气能见度具有向好的发展趋势。探讨了大气能见度与空气主要污染物PM10、NO2、SO2的相关关系,计算了PEARSON相关系数和偏相关系数,发现PM10浓度与能见度具有显著相关性。在此基础上总结了各个主要污染物与能见度的回归曲线。利用多元线性回归法建立了大气能见度与空气主要污染物PM10、NO2、SO2之间的回归方程。     

Change of air quality and its impact on atmospheric visibility in central-western Pearl River Delta

Ambient air quality data, including atmospheric visibility, of Foshan city, a highly polluted city in the Pearl River Delta (PRD), and data obtained by the On-line Air Pollutant Exhaust Monitoring Network (OAPEMN), recently established by the National Emission Monitoring and Control Network for major industrial enterprises, were analyzed and are reported here for the first time, revealing the change in air pollution patterns and its impact on visibility degradation in the last decade. Reduced visibility of less than 8 km (after elimination of rainy and foggy periods) was found 22% of the time from 1998 to 2008, accompanied by elevated levels of pollutants, especially SO₂ and PM₁₀, in comparison with that of other developed cities. However, PM₁₀ showed a steady decreasing trend (0.004 mg m^???3 year^???1) during 2001?C2008, in contrast to the noticeable increase in ambient NO₂ concentrations from ~0.020 mg m^???3 before 2005 to above 0.050 mg m^???3 afterward. Multiple regression analysis revealed that the percentage of reduced visibility strongly correlated with PM₁₀ concentration, suggesting that visibility degradation was directly proportional to the loading of particles. Moreover, the fairly significant correlation between reduced visibility and NO₂ concentration also implied that the impact of primary emissions of NO₂ and enhanced secondary pollutants, formed via photochemical processes in the atmosphere, could not be ignored. The decreased PM₁₀ levels were obviously the predominant factor for the improvement in visibility (5.0% per 0.01 mg m^???3) and were likely due to the implementation of stricter air pollution control measures for industrial exhaust, which also resulted in reduced SO₂ pollution levels in the recent 2 years. In particular, the OAPEMN records showed an overall enhanced SO₂ removal by 64% in major industrial sectors. The continuous increase in road traffic and lack of efficient NO _x control strategies in the PRD region, however, caused an increase in ambient NO₂ concentrations.     

黑龙江省“十三五”时期生态环境质量变化及趋势预测

以黑龙江省生态环境监测网监测结果为基础,总结归纳了"十三五"期间黑龙江省生态环境质量变化特征,并采用随机森林和GM(1,1)预测模型对"十四五"期间黑龙江省生态环境质量状况进行了预测。结果表明:"十三五"期间,黑龙江省环境空气、水环境和声环境质量全面好转。其中,环境空气主要污染物PM_2.5、PM₁₀、SO₂、NO₂和CO的年均质量浓度均呈现出明显下降的趋势,"哈大绥"重点区域PM₁₀、SO₂、NO₂和CO年均质量浓度呈现下降趋势。地表水水质总体呈波动变化趋势,水质状况均为轻度污染。"十四五"期间,黑龙江省生态环境质量将处于稳中向好的趋势。环境空气主要污染物及地表水主要污染指标年均质量浓度均呈现明显的下降趋势,道路交通声环境质量也将得到进一步改善。     

Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.