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.     

河北省火电企业吨煤烟气排放量测定及污染动态预测

火电企业大气污染动态预测是大气污染控制的基础。采用现场实测法,对河北省36家火电企业101台机组锅炉进行现场监测,经统计分析给出不同装机容量吨煤烟气排放量,并与其他方法进行了比较,发现实测结果更为合理。在此基础上,建立吨煤SO₂、NO_x,烟尘排放量和烟气浓度的关系,为火电企业大气污染动态预测提供新的公式,对定量测定火电企业污染物排放提供参考。     

Estimation of shipping emissions in Candarli Gulf, Turkey

Ships are significant air pollution sources as their high powered main engines often use heavy fuels. The major atmospheric components emitted are nitrogen oxides, particulate matter (PM), sulfur oxide gases, carbon oxides, and toxic air pollutants. Shipping emissions cause severe impacts on health and environment. These effects of emissions are emerged especially in territorial waters, inland seas, canals, straits, bays, and port regions. Candarli Gulf is one of the major industrial regions on the Aegean side of Turkey. The marine environment of the region is affected by emissions from ships calling to ten different ports. In this study, NO _x , SO₂, CO₂, hydrocarbons (HC), and PM emissions from 7,520 ships are estimated during the year of 2007. These emissions are classified regarding operation modes and types of ships. Annual shipping emissions are estimated as 631.2 t year^???1 for NO _x , 573.6 t year^???1 for SO₂, 33,848.9 t year^???1 for CO₂, 32.3 t year^???1 for HC, and 57.4 t year^???1 for PM.     

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.     

2018年大连海域船舶大气污染物排放特征及影响分析

船舶废气已成为大气污染物的重要来源之一。为掌握大连周边海域船舶大气污染物排放特征,以及大连海域船舶排放对大连市大气环境的影响,基于船舶自动识别系统监测数据,采用基于功率的动力法估算出2018年大连海域船舶排放清单,并利用WRF、SMOKE、CMAQ空气质量数值模拟系统,研究了1月、4月、7月、10月船舶排放对大连市大气环境的影响。研究结果表明,2018年大连海域船舶共排放SO₂ 7 606.23 t、NO_x 30 990.13 t、PM₁₀ 1 212.02 t、PM_2.5 969.58 t、CO 3 339.10 t、HC 1 414.63 t、CO₂ 2 546 299.67 t。其中,客船、散货船、油船和多用途船的排放占比较大,排放区域主要集中在大连湾、大窑湾附近及周边航道。受气候因素影响,不同月份的船舶排放对大连市大气环境的影响不同,其中,1月、4月和10月受影响较大的区域主要是旅顺口区和金州区,而7月受影响较大的区域主要是甘井子区。     

Assessment of Urban Air Quality in South Estonia by Simple Measures

In countries having limited resources, it is difficult to assess urban air quality on contemporaneously, due to the absence of on-line information about air pollution levels and emission rates. An alternative approach is recommended for smaller cities with lower demands of resources. The applied scheme consists of a database of air pollution sources (NO _x and CO from industry, traffic, and domestic heating), the simple Gaussian-plume model AEROPOL and a series of measurements by passive monitors. This method was used in Tartu, a small city situated in the valley of the river Emajõgi, within a landscape with noteworthy topographical variations. Simulations of annual average and maximal concentrations were performed, and a fair agreement obtained with NO₂ monitoring results from passive Palmes monitors. Inventories of pollution sources in 1998 revealed that official statistics of stationary sources covered 64% of SO₂,36% of CO, 37% of NO _x and 32% of total particulate matter emissions. Recommendations for measures for reducing air pollution levels and for further investigations towards improving air quality assessment and management, are given.     

Evaluation of relationship between meteorological parameters and air pollutant concentrations during winter season in Elazığ, Turkey

In recent years, due to the rapid increase in population density, building density and energy consumption, the outdoor air quality has deteriorated in the crowded urban areas of Turkey. Elaz?? city, which is located in the east Anatolia region of Turkey, is also influenced by air pollutants. In the present study, relationship between monitored air pollutant concentrations such as SO₂ and the total suspended particles (TSP) data and meteorological factors such as wind speed, temperature, relative humidity, solar radiation and atmospheric pressure was investigated in months of October, November, December, January, February, and March during the period of 3 years (2003, 2004 and 2005) for Elaz?? city. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elaz?? city. The correlation between the previous day’s SO₂, TSP concentrations and actual concentrations of these pollutants on that day was investigated and the coefficient of determination R² was found to be 0.64 and 0.54, respectively. The statistical models of SO₂ and TSP including all of meteorological parameters gave R² of 0.20 and 0.12, respectively. Further, in order to develop this model, previous day’s SO₂ and TSP concentrations were added to the equations. The new model for SO₂ and TSP was improved considerably with R²?=?0.74 and 0.61, respectively.     

Investigating the impacts of some meteorological parameters on air pollution in Balikesir, Turkey

Air pollution is one of the most important environmental problems in Balikesir, situated in the western part of Turkey, during the winter periods. The unfavorable climate as well as the city’s topography, and inappropriate fuel usage cause serious air pollution problems. The air pollutant concentrations in the city have a close relationship with meteorological parameters. In the present study, the relationship between daily average total suspended particulate (TSP) and sulphur dioxide (SO₂) concentrations measured between 1999–2005 winter seasons were correlated with meteorological factors, such as wind speed, temperature, relative humidity and pressure. This statistical analysis was achieved using the stepwise multiple linear regression method. According to the results obtained through the analysis, higher TSP and SO₂ concentrations are strongly related to colder temperatures, lower wind speed, higher atmospheric pressure and higher relative humidity. The statistical models of SO₂ and TSP gave correlation coefficient values (R ²) of 0.735 and 0.656, respectively.     

常州市工业大气污染物排放特征研究

通过调查企业生产情况,采用现场实测、模型、排放因子等方法,获得了常州市工业大气污染物的排放量,从行业、排放口高度、空间、时间及重点源所占比例等方面,分析了常州市工业大气污染物的分布特征。结果显示:常州市工业PM、PM_(10)、PM_(2.5)、SO_2、NO_x、CO、NH_3、VOCs排放量分别为3.089、1.348、0.695、5.380、7.077、14.459、0.030、0.848万t;钢铁、水泥、热电、金属制品、化工是常州市大气污染物产生的主要行业;高架源、中架源、低架源排放比例依次增加;11.5%的企业占据了全市排放量的86%以上;SO2等污染物各月排放量基本稳定,PM2.5等上半年排放量波动较大;市区企业的集中排放在不利气象条件下易造成大气污染。     

新疆克孜勒苏河喀什市段入河污染物估算及特征分析

依据污染源调查资料,采用距离法对克孜勒苏河喀什市段污染物的入河量进行估算。结果表明:污水处理厂排放口是克孜勒苏河喀什市段最主要的污染源,COD、NH3-N、TN、TP的排放量占研究区域总量的61%~83%;其次是豆腐厂总排口,4项指标占研究区域总排放量的17%~37%,也是该河段的主要污染源。两者各指标排放量之和均超过区域总量的98%。不同类型的污染源中,生活源COD、NH3-N、TN、TP的贡献率分别是工业源的2、5、4和1.6倍。     

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。     

Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

Preparation and Validation of Gridded Emission Inventory of Criteria Air Pollutants and Identification of Emission Hotspots for Megacity Delhi

Delhi is one of the many megacities struggling with punishing levels of pollution from industrial, residential, and transportation sources. Over the years, pollution abatement in Delhi has become an important constituent of state policies. In the past one decade a lot of policies and regulations have been implemented which have had a noticeable effect on pollution levels. In this context, air quality models provide a powerful tool to study the impact of development plans on the expected air pollution levels and thus aid the regulating and planning authorities in decision-making process. In air quality modeling, emissions in the modeling domain at regular interval are one of the most important inputs. From the annual emission data of over a decade (1990–2000), emission inventory is prepared for the megacity Delhi. Four criteria pollutants namely, CO, SO₂, PM, and NO _x are considered and a gridded emission inventory over Delhi has been prepared taking into account land use pattern, population density, traffic density, industrial areas, etc. A top down approach is used for this purpose. Emission isopleths are drawn and annual emission patterns are discussed mainly for the years 1990, 1996 and 2000. Primary and secondary areas of emission hotspots are identified and emission variations discussed during the study period. Validation of estimated values is desired from the available data. There is a direct relationship of pollution levels and emission strength in a given area. Hence, an attempt has been made to validate the emission inventory for all criteria pollutants by analyzing emissions in various sampling zones with the ambient pollution levels. For validation purpose, the geographical region encompassing the study area (Delhi) has been divided into seven emission zones as per the air quality monitoring stations using Voronoi polygon concept. Dispersion modeling is also used for continuous elevated sources to have the contributing emissions at the ground level to facilitate validation. A good correlation between emission estimates and concentration has been found. Correlation coefficient of 0.82, 0.77, 0.58 and 0.68 for CO, SO₂, PM and NO _x respectively shows a reasonably satisfactory performance of the present estimates.     

A Method for Locating Influential Pollution Sources and Estimating Their Contributions

This work develops a source-oriented approach to locate the influential pollution sources and estimate their contributions to pollutant concentrations observed at a receptor site. The domain containing possible influential pollution sources is divided into systematic grid cells, and the influential grid sources are determined based on the locations of the segment endpoints of air trajectories arriving at the receptors. The contribution of each grid source is initially calculated using a formula derived from a Lagrangian box model and including the effects of source emissions, atmospheric dilution, and chemical transformation and deposition. The formula is described in detail in this study. Finally, the average contribution of each grid source is determined based on numerous analyzed events. The proposed approach was used to locate influential pollution sources and determine their contributions to a rural monitoring station during periods of high SO₂ pollution in southern Taiwan. The contributions of sources in various 2 km by 2 km grid cells, five districts, three source categories, 8 industrial areas, and a power plant were evaluated. The results show that the major influential sources were in the northwestern region of south Taiwan, and belonged to three district and point sources. Furthermore, two industrial areas close to the evaluated stations were also very significant, and contributed about 30% of the total pollution.     

The Valuation of Health Effects Caused by Stationary Sources–Related SO2 Emissions: The Adaptation of Impact Pathway Approach in Taiwan

This paper presents the externalities of sulfur dioxide (SO₂) in the Taichung metropolitan, Taiwan. The human effects of SO₂ from stationary sources are a key element for local air quality management. A methodology to evaluate those effects in monetary term had been adapted and applied. This method was modified from the EU-based impact pathway approach link to the skill of geographic information systems. The studied area was divided into 66 districts and the quantity of SO₂ was allocated to each district. Then, the ambient concentration of SO₂ was estimated by using the ordinary kriging method. A risk analysis was employed to characterize the health impacts caused by SO₂. Finally, a monetary transfer approach based on the European data was conducted to estimate local damage costs per ton of SO₂. Health impacts, especially acute mortality, dominate in term of costs. The calculation showed that damage costs ranged from 0.56 to 7.38 USD/kg SO₂ based on the 2002 emission data. The results could be used in the internalization of SO₂ externalities and management of the stationary sources in the studied area. This paper also concludes that the externalities caused by stationary-related SO₂ emissions are some 28.5 million US dollars in Taichung metropolitan (Taiwan) in 2002.     

Use of a MM5–CAMx–PSAT Modeling System to Study SO2 Source Apportionment in the Beijing Metropolitan Region

A coupled MM5–CAMx air quality modeling system was used to simulate SO₂ concentrations in Beijing, China during the heating season. Particulate matter source apportionment technology was employed to investigate the apportionment of SO₂ sources in the study area. Comprehensive analysis of the industry and region revealed that the most important SO₂ contributors were publicly and privately supplied heating emission sources and other industry emission sources from the urban areas of Beijing, with 66.1?% of the emission source contribution ratio. Four SO₂ emission reduction scenarios based on our SO₂ source apportionment research were established to assess the potential for improving the SO₂ air quality in Beijing during the heating season. By weighing the desired SO₂ improvement, the availability of technology, and economic considerations, a suitable SO₂ reduction plan was able to be recommended for Beijing city.     

Spatio-Temporal Variations of Sulphur Dioxide Patterns with Wind Conditions in Central Taiwan

Sulphur dioxide (SO₂) is one of the main atmospheric pollutants in central Taiwan. This article analyses the SO₂ concentration seasonal variations and spatial distribution using data obtained from ten air quality monitoring stations and the Taiwan Weather Bureau. It reveals that SO₂ concentration is high in winter and low in summer and that high concentration centers are located south of the Taichung coal-fired power plant, the main source of SO₂ emissions in the region.The location of high concentration centers changeswith different prevailing winds. SO₂ variations due towind direction are not unique. During short periods,when meteorological conditions are constant, variationin the pollution sources cause variations in thespatial distribution. This has been deduced byappreciation of Intervention analysis to time seriesof hourly data.     

某石化化工行业聚集区室内外PM2.5中多环芳烃分布特征及来源

于非采暖季和采暖季分别采集某石化化工行业聚集城市中心城区室内外PM_(2.5)样品,采用高效液相色谱法分析PM_(2.5)上载带的16种PAHs,对其分布特征、来源以及室外PAHs污染对室内污染的贡献进行了初步探讨。结果表明,研究区域非采暖季和采暖季室外PM_(2.5)中ΣPAHs浓度日均值分别为36.3、294 ng/m~3,室内PM_(2.5)中ΣPAHs浓度分别为14.8、84.6 ng/m~3,均以4、5环PAHs为主;室内PAHs主要来自室外渗透污染,但同时明显存在室内排放源贡献;PAHs来源分析进一步证实研究区域PAHs主要来自煤炭、石油等不完全燃烧,采暖季煤炭燃烧源贡献更突出。     

A Statistical Analysis of Particulate Data Sets for Jawaharlal Nehru Port and Surrounding Harbour Region in India

The concentrations of total suspended particulate matter (TSP) and particulate matter less than 10 microns (PM10) were measured at various locations in a Jawaharlal Nehru port and surrounding harbour region. Meteorological data was also collected to establish the correlation with air pollutant concentration. The results are analysed from the standpoint of monthly and seasonal variations, annual trends as well as meteorological effects. The monthly mean concentration of TSP was in the range of 88.2 to 199.3 microg m(-3). The maximum and minimum-recorded value of PM10 was 135.8 and 20.3 microg m(-3), respectively. The annual average concentration of PM10 was 66.1 microg m(-3). There are clear associations between TSP and PM10 data set at all the measured three sites with a correlation coefficient of 0.89, 0.69 and 0.81, respectively. PM10 data appears to be a constant fraction of the TSP data throughout the year, indicating common influences of meteorology and sources. Particle size analysis showed PM10 to be 47% of the total TSP concentration, which is lower than reported for industrial area and traffic junctions in Mumbai. Anthropogenic sources contribute significantly to the PM10 fraction in an industrial region, while contributions from natural sources are more in a port and harbour area. Statistical analysis of air quality data shows that TSP is strongly correlated with wind speed but weakly correlated with temperature. There appears to be a simple inverse relationship between TSP and wind speed data, indicating the dilution and transport by winds.     

北京市建筑施工裸地的空间分布及扬尘效应

北京市作为中国典型的快速城市化大城市之一,大规模的城市建设使得城市内部存在大量的建筑施工裸地,工地扬尘效应造成了严重的大气颗粒物污染。以北京市平原区为研究区,首先利用高分辨率卫星数据反演了建筑施工裸地的空间分布格局,在此基础上,结合建筑施工裸地的扬尘排放因子,在空间上定量分析建筑施工裸地的扬尘效应。结果显示,2012年全市平原区建筑施工裸地总面积为140.77 km2,主要分布在城市核心区向外拓展的城乡过渡带。建筑施工裸地的扬尘效应分析中发现北京市平原区建筑施工裸地中TSP、PM10和PM2.5的排放量分别是31.53、16.66、9.16万吨,并且这些污染物的排放量在城市发展新区与功能拓展区中较高,生态涵养发展区较小。以北京市的建筑施工裸地为例,示范了以遥感为技术手段结合污染排放因子的城市内部典型面源污染的监测和污染排放定量化,为今后面源污染的快速准确监测开辟了新的研究思路。