A model for the maximum credible hourly impact on any ground receptor from point sources with momentumdominated plume rise

A pollutant dispersion model is developed, allowing rapid evaluation of the maximum credible one-hour-average concentration on any given ground-level receptor, along with the corresponding critical meteorological conditions (wind speed and stability class) for stacks with momentum-dominated plume rise in urban or rural areas under buoyancy or no buoyancy induced dispersion. Site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class, and mixing height.The analysis is based on the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings respectively, the buoyancy induced dispersion correlation of Pasquill, the wind profile exponent values suggested by Irwin, the momentum plume rise relations of Briggs, as well as the Benkley and Schulman's model for the minimum mixing heights.The model is particularly suited for air pollution management studies, as it allows fast screening of the maximum impact on any selected receptor and evaluation of the ways to have this impact reduced. Also, for regulatory purposes, as it allows accurate setting of minimum stack height requirements as function of the exit gas volume and velocity, the pollutant emission rates and their hourly concentration standards, as well as the source location relative to sensitive receptors.     

An automated monitoring of atmospheric mixing height from routine radiosonde profiles over South Korea using a web-based data transfer method

This study describes an effort to estimate atmospheric mixing height using vertical profiles of thermodynamic variables measured operationally at radiosonde sites in South Korea. We focus on mixing height at 06UTC (15LST) when vigorous daytime convection is expected with clear skies. For this purpose, we developed a simple numerical algorithm using a new data transfer tool, known as cURL, to determine mixing height and applied it to radiosonde data at Osan and Gwangju for 2010. Emphasis was placed on automating as much as possible the process of determining mixing height. According to the preliminary results, the estimation algorithm performed successfully for most cases with clear sky conditions and was useful in diagnosing and monitoring daytime mixing heights more effectively on a near-real-time basis. With the developed algorithm, it is possible to estimate mixing heights from radiosonde data within a few hours of the development of the convective boundary layer. Application to radiosonde sites in other countries is straightforward and continued modifications of the algorithm are anticipated in the near future.     

平流层臭氧深度侵入对典型城区的影响过程分析

中纬度平流层臭氧深度侵入是造成对流层至近地面臭氧浓度突增的原因之一。筛选春夏季臭氧浓度升高时段的高分辨率大气再分析数据ERA5,以位涡值的下沉趋势分析了对流层顶折叠位置及变化过程;以AIRS数据反演了臭氧浓度、一氧化碳浓度和相对湿度的垂直廓线,并估计了其分布及相关性;以近地表污染物浓度变化、HYSPLIT模型后向轨迹分析结果证实了臭氧侵入气团的运移轨迹和局地效应;通过激光雷达监测结果观测臭氧垂直浓度分布,确定了臭氧浓度最大值所处高度,判定了受影响近地点的浓度升高时刻;以边界层高度变化、气象条件分析结果及当地与周边城市地面监测数据的逐小时变化情况等综合信息,进行了区域确认和近地面影响判定。通过以上数值综合分析,对城市地区受平流层臭氧深度侵入影响的过程和具体时间进行了详细再现,可为排除非人为排放因素导致的近地表臭氧浓度增加提供回溯分析,为臭氧污染防控决策提供依据。     

Spatial and temporal distribution of gaseous elemental mercury in Chongqing, China

In order to investigate the spatial and temporal variability of atmospheric mercury (Hg) in Chongqing, China, gaseous elemental mercury (GEM) was measured from August 2006 to September 2007, using Lumex multifunctional mercury analyzer RA-915(+) (Lumex Ltd., Russia). The mean GEM concentration was 6.74 +/- 0.37 ng m(-3) in Chongqing, much higher than the accepted global background values (1.5-2 ng m(-3)). The GEM concentrations were different in different function areas. GEM in transport, industrial and commercial areas were 7.07 +/- 1.04, 7.05 +/- 0.96 and 6.71 +/- 1.10 ng m(-3), respectively, while GEM was 6.14 +/- 1.30 and 4.32 +/- 1.04 in the educational/recreational and nature conservation areas, suggesting that Hg emissions from mobile vehicles and industrial sources (specially coal combustion) were the most important contributors to atmospheric Hg in Chongqing. Mean Hg concentrations also had monthly variations with highest in November (8.24 +/- 0.50 ng m(-3)) and lowest values in August (5.36 +/- 0.70 ng m(-3)). Additionally, the diurnal variation of GEM concentrations was dependent on the local/regional atmospheric conditions. At Jinyun Mountain site (natural conservation area), hourly GEM concentrations had much higher values in daytime than at night. At Power Plant site, however, the hourly GEM concentrations were lower in daytime than at night. GEM concentrations in the air were correlated significantly with meteorological parameters except for barometric pressure.     

北京市大气气态汞变化特征

采用Tekran 2537X大气汞分析仪在线测量北京市城区大气中气态元素汞(GEM,简称大气汞) 浓度,研究大气汞浓度随不同气象条件的变化特征。通过分析2016年10月—2017年9月大气汞监测数据发现,该监测点全年大气汞浓度为0.48～16.25 ng/m³,均值为(3.41±1.79)ng/m³。春季、夏季、秋季和冬季大气汞浓度均值依次为2.93 、2.95、4.27、3.37 ng/m³,其中,秋季大气汞浓度明显高于其他季节 。秋季大气汞浓度显著偏高可能由不利的大气扩散条件导致。大气汞夜间浓度显著高于白天浓度。同时,将大气汞与SO₂、CO及PM_2.5进行相关性分析,发现大气汞浓度变化趋势与SO₂、CO和PM_2.5呈显著正相关。结合风向和风速进行污染来源分析,得到该点位大气汞在西南和东北方向上受人为排放源影响较大。污染源类型分析表明,冬季大气汞与CO同源性强,主要来自本地供暖用煤。     

The Relationship between Extreme Nitrogen Oxide (NOx) Concentrations in Dublin's Atmosphere and Meteorological Conditions

A study was carried out to investigate the effects of meteorological conditions on atmospheric Nitrogen Oxide (NOx (Nitrogen Oxide and Nitrogen Dioxide)) concentrations at a site in Dublin. Data used in the study (meteorological conditions and hourly NOx concentrations) were compiled from hourly records for the years 1988-1992. The research identified wind speed, air pressure and wind direction as the most important meteorological parameters for understanding the behaviour of extreme NOx concentrations in Dublin's air. Daily, weekly and seasonal variation in NOx concentrations were observed. This work also highlighted the importance of the role played by general synoptic weather conditions over local climatic effects in extreme events.     

Diurnal trends in coarse particulate matter composition in the Los Angeles Basin

To investigate the diurnal profile of the concentration and composition of ambient coarse particles, three sampling sites were set up in the Los Angeles Basin to collect coarse particulate matter (CPM) in four different time periods of the day (morning, midday, afternoon and overnight) in summer and winter. The samples were analyzed for total and water-soluble elements, inorganic ions and water-soluble organic carbon (WSOC). In summer, highest concentrations of CPM gravimetric mass, mineral and road dust, and WSOC were observed in midday and afternoon, when the prevailing onshore wind was stronger. In general, atmospheric dilution was lower in winter, contributing to the accumulation of air pollutants during stagnation conditions. Turbulences induced by traffic become a significant particle re-suspension mechanism, particularly during winter night time, when mixing height was lowest. This is evident by the high levels of CPM mass, mineral and road dust in winter overnight at the near-freeway sites located in urban Los Angeles, and to a lesser extent in Riverside. WSOC levels were higher in summer, with a similar diurnal profile with mineral and road dust, indicating that they either share common sources, or that WSOC may be adsorbed or absorbed onto the surfaces of these dust particles. In general, the contribution of inorganic ions to CPM mass was greater in the overnight sampling period at all sampling sites, suggesting that the prevailing meteorological conditions (lower temperature and higher relative humidity) favor the formation of these ions in the coarse mode. Nitrate, the most abundant CPM-bound inorganic species in this basin, is found to be predominantly formed by reactions with sea salt particles in summer. When the sea salt concentrations were low, the reaction with mineral dust particles and the condensation of ammonium nitrate on CPM surfaces also contributes to the formation of nitrate in the coarse mode.     

长株潭区域一次重度污染过程气象成因

利用PM_2.5质量浓度、地面气象要素、NCEP、ERSST＿V3、GBL等资料,研究了2021年12月7—11日长株潭地区一次重度空气污染过程的特征及成因。结果表明,高空平直环流、无明显槽脊影响,地面弱冷空气活跃是本次重度空气污染过程的主要环流形势特征;地面均压场、小风和升温增湿是此次重度空气污染过程的主要气象要素特征。污染物浓度变化与主导风向和污染通道密切相关,本地风速对混合层的高度、污染物水平扩散影响较大,600～700 hPa逆温层有利于污染物在主导风作用下近距离传输及在低层交换积累。我国中东部污染物积聚是长株潭区域重要的污染来源,长株潭地区存在区域性同步污染现象。低层流入长株潭区域气流轨迹差异及地理条件是长株潭污染物空间分布差异的重要因素。     

秸秆焚烧对哈尔滨市灰霾天气的影响

2015年11月1—4日,哈尔滨市及周边地区发生了连续的灰霾天气,颗粒物浓度急剧升高。污染发生时,监测仪器均布设在哈尔滨市区上风向30 km处(哈尔滨市双城区)并开展了连续96 h的监测分析。综合利用气象观测资料,3D可视激光雷达监测资料及地面空气污染监测资料分析了灰霾天气发生的气象条件和污染边界层特征,根据哈尔滨市双城区大气污染物排放源谱库对主要成分进行来源解析,结合颗粒物质量浓度和气象条件研究了秸秆焚烧对灰霾天气的影响。结果表明,灰霾天气持续期间,夜间生物质燃烧源成为该地区颗粒物的第二大源;秸秆焚烧产生的大气污染物,由于地面长时间静风,污染边界层降低等原因,致使本地污染物累积、不易扩散,加剧了本次污染。     

杭州秋季大气VOCs变化特征及化学反应活性研究

2017年9月1日至11月30日采用Syntech Spectras GC955在线气相色谱仪对杭州市不同功能区大气环境中的挥发性有机化合物(VOCs)进行了在线连续监测,分析了不同功能区VOCs及各组分的体积分数、日变化规律及大气化学反应活性。结果显示,下沙周边工业区总VOCs浓度整体高于朝晖周边居民区,其中夜间更为显著。烷烃和芳香烃浓度在夜间时段工业区较居民区高得更为明显,其中芳香烃组分表现尤为突出,2个功能区烯烃体积分数相差不大。杭州市主要VOCs体积分数总体上在国内处于中间水平。不同功能区烷烃和芳香烃均呈现夜间浓度高于白天的日变化特征,居民区各VOCs组分日变化基本呈现双峰结构,工业区烷烃和芳香烃体积分数日变化呈现单峰结构,烯烃体积分数没有明显的日变化特征。不同功能区中芳香烃对臭氧生成潜势贡献最大,烯烃次之,烷烃贡献最小。下沙周边工业区大气化学活性(尤其是芳香烃组分)较朝晖周边居民区强。同种VOCs物质在不同功能区对臭氧生成潜势的贡献大小不同,但关键贡献物质均为低碳烷烃、低碳烯烃及苯系物。     

Simulation of mixing depths incorporating the urban heat island effect

The main objective of this paper was to establish the effect of anthropogenic heat flux on the formation of mixing depth specially in urban areas. In this study an energy balance mixing depth model was developed for the simulation of mixing depth incorporating the heat island effect. To demonstrate the effect of heat island, mixing depths were simulated under two conditions. Under the first condition, hourly gridded anthropogenic heat flux and variant surface characteristics were considered, while under the second condition anthropogenic heat flux term was ignored and constant surface characteristics were considered throughout the modelling domain. The release of anthropogenic heat flux in the urban environment was found to be responsible for the growth of the unstable layer in the lower atmosphere even during the night. This resulted in higher mixing depth values in urban areas compared to the surrounding countryside. The maximum differential surfaces sensible heat flux between urban and rural areas was estimated as 130 W/m². From the simulation of mixing depth, it was revealed that the maximum increment in mixing depth in urban areas was 300 m due to the heat island effect. This increment in mixing depth in urban areas can provide an extra space for dilution and mixing of pollutants.     

基于自动站资料的深圳灰霾特征对比分析

利用深圳自动气象站的气象要素和深圳大气成分监测系统采集的大气成分数据,分析了深圳城区和郊区灰霾季节变化、日变化差异和不同风向下污染物浓度差异,结果表明,城区由于人类活动频繁导致灰霾日比郊区多,以轻微灰霾偏多为主。秋、冬季城区冷空气活动频繁、能源消耗大,灰霾出现频率是郊区的1~2倍;春季冷空气和海上暖湿气流容易形成对峙,沿海颗粒物更容易吸湿增长,郊区灰霾频率反而比城区高25%;夏季对流强、降水频密,城郊差异最小。城区灰霾频率受早晚交通高峰期影响,日变化呈双峰型。而郊区受太阳辐射和光化学反应影响大,呈单峰型。偏北风条件下污染物浓度明显升高,偏南风带来的清洁空气使得颗粒物浓度降幅明显。     

上海市郊春季PM10 污染的观测研究

利用上海市郊金山环境监测站2007年春季的逐时PM10和气象参数的观测数据,分析了PM10日平均质量浓度和最大质量浓度的时间变化规律,小时平均质量浓度的分布规律,气象条件对PM10质量浓度的影响,并利用HYSPLIT轨迹模型结合气象观测数据对一次最严重的PM10污染过程进行了分析.结果表明,PM10在春季有11日出现超标,污染比较严重;风和降雨对PM10质量浓度均有较为明显的影响;4月2日监测点PM10日平均和最高质量浓度分别达到0.78 mg/m3和1.0 mg/m3,均为全年最高值,这与北方冷空气携带沙尘南下的影响有关.     

Study of atmospheric stagnation, recirculation and ventilation potential at Narora Atomic Power Station NPP site

The atmosphere is an important pathway to be considered in assessment of the environmental impact of radioactivity releases from nuclear facilities. The estimation of concentration of released effluents in air and possible ground contamination needs an understanding of relevant atmospheric dispersion. This paper describes the meteorological characteristics of Narora Atomic Power Station (NAPS) Nuclear Power Project site by using the integral parameters developed by Allwine and Whiteman (Atmospheric Environment 28(4):713–721, 1994). Meteorological data measured during the period 2006–2010 were analysed. The integral quantities related to the occurrence of stagnation, recirculation and ventilation characteristics were studied for the NAPS site to assess the dilution potential of the atmosphere. Wind run and recirculation factors were calculated for a 24-h transport time using 5 years of hourly surface measurements of wind speed and direction. The occurrence of stagnation, recirculation and ventilation characteristics during 2006–2010 at the NAPS site is observed to be 33.8, 19.5 and 34.7 % of the time, respectively. The presence of strong winds with predominant wind direction NW and WNW during winter and summer seasons leads to higher ventilation (48.1 and 44.3 %) and recirculation (32.6 % of the summer season). The presence of more dispersed light winds during pre-winter season with predominant wind directions W and WNW results in more stagnation (59.7 % of the pre-winter season). Thus, this study will serve as an essential meteorological tool to understand the transport mechanism of atmospheric radioactive effluent release from any nuclear industry during the pre-operational as well as operational phase.     

Input strategy analysis for an air quality data modelling procedure at a local scale based on neural network

In recent years, a significant part of the studies on air pollutants has been devoted to improve statistical techniques for forecasting the values of their concentrations in the atmosphere. Reliable predictions of pollutant trends are essential not only for setting up preventive measures able to avoid risks for human health but also for helping stakeholders to take decision about traffic limitations. In this paper, we present an operating procedure, including both pollutant concentration measurements (CO, SO₂, NO₂, O₃, PM10) and meteorological parameters (hourly data of atmospheric pressure, relative humidity, wind speed), which improves the simple use of neural network for the prediction of pollutant concentration trends by means of the integration of multivariate statistical analysis. In particular, we used principal component analysis in order to define an unconstrained mix of variables able to improve the performance of the model. The developed procedure is particularly suitable for characterizing the investigated phenomena at a local scale.     

Vertical ozone characteristics in urban boundary layer in Beijing

Vertical ozone and meteorological parameters were measured by tethered balloon in the boundary layer in the summer of 2009 in Beijing, China. A total of 77 tethersonde soundings were taken during the 27-day campaign. The surface ozone concentrations measured by ozonesondes and TEI 49C showed good agreement, albeit with temporal difference between the two instruments. Two case studies of nocturnal secondary ozone maxima are discussed in detail. The development of the low-level jet played a critical role leading to the observed ozone peak concentrations in nocturnal boundary layer (NBL). The maximum of surface ozone was 161.7 ppbv during the campaign, which could be attributed to abundant precursors storage near surface layer at nighttime. Vertical distribution of ozone was also measured utilizing conventional continuous analyzers on 325-m meteorological observation tower. The results showed the NBL height was between 47 and 280 m, which were consistent with the balloon data. Southerly air flow could bring ozone-rich air to Beijing, and the ozone concentrations exceeded the China’s hourly ozone standard (approximately 100 ppb) above 600 m for more than 12 h.     

Short-Term Forecasting of Nitrogen Dioxide (NO<Subscript>2</Subscript>) Levels Using a Hybrid Statistical and Air Mass History Modelling Approach

A novel hybrid model has been developed to support the provision of real-time air quality forecasts. Statistical techniques have been applied in parallel with air mass history modelling to provide an efficient and accurate forecasting system with the ability to identify high NO₂ events, which tend to be the episodes of most significance in Ireland. Air mass history modelling and k-means clustering are used to identify air mass types that lead to high NO₂ levels in Ireland. Trajectory matching techniques allow data associated with these air masses to be partitioned during model development. Non-parametric regression (NPR) has been applied to describe nonlinear variations in concentration levels with wind speed, direction and season and produce a set of linearized factors which, together with other meteorological variables, are employed as inputs to a multiple linear regression. The model uses an innovative integrated approach to combine the NPR with the air mass history modelling results. On validation, a correlation coefficient of 0.75 was obtained, and 91 % of daily maximum (hourly averaged) NO₂ predictions were within a factor of two of the measured value. High pollution events were well captured, as indicated by strong agreement between measured and modelled high percentile values. The model requires only simple input data, does not require an emission inventory and utilises very low computational resources. It represents an accurate and efficient means of producing real-time air quality forecasts and, when used in combination with forecaster experience, is a useful tool for identifying periods of poor air quality 24 h in advance. The hybrid approach outlined in this paper can easily be applied to produce high-quality forecasts of both NO₂ and additional pollutants at new locations/countries where historical monitoring data are available.     

Monitoring of ocean surface algal blooms in coastal and oceanic waters around India

The National Aeronautics and Space Administration’s (NASA) sensor MODIS-Aqua provides an important tool for reliable observations of the changing ocean surface algal bloom paradigms in coastal and oceanic waters around India. A time series of the MODIS-Aqua-derived OSABI (ocean surface algal bloom index) and its seasonal composite images report new information and comprehensive pictures of these blooms and their evolution stages in a wide variety of events occurred at different times of the years from 2003 to 2011, providing the first large area survey of such phenomena around India. For most of the years, the results show a strong seasonal pattern of surface algal blooms elucidated by certain physical and meteorological conditions. The extent of these blooms reaches a maximum in winter (November–February) and a minimum in summer (June–September), especially in the northern Arabian Sea. Their spatial distribution and retention period are also significantly increased in the recent years. The increased spatial distribution and intensity of these blooms in the northern Arabian Sea in winter are likely caused by enhanced cooling, increased convective mixing, favorable winds, and atmospheric deposition of the mineral aerosols (from surrounding deserts) of the post-southwest monsoon period. The southward Oman coastal current and southwestward winds become apparently responsible for their extension up to the central Arabian Sea. Strong upwelling along this coast further triggers their initiation and growth. Though there is a warming condition associated with increased sea surface height anomalies along the coasts of India and Sri Lanka in winter, surface algal bloom patches are still persistent along these coasts due to northeast monsoonal winds, enhanced precipitation, and subsequent nutrient enrichment in these areas. The occurrence of the surface algal blooms in the northern Bay of Bengal coincides with a region of the well-known Ganges–Brahmaputra Estuarine Frontal (GBEF) system, which increases supply of nutrients in addition to the land-derived inputs triggering surface algal blooms in this region. Low density (initiation stage) of such blooms observed in clear oceanic waters southeast and northeast of Sri Lanka may be caused by the vertical mixing processes (strong monsoonal winds) and the occurrence of Indian Ocean Dipole events. Findings based on the analyses of time series satellite data indicate that the new information on surface algal blooms will have important bearing on regional fisheries, ecosystem and environmental studies, and implications of climate change scenarios.     

Characteristics of black carbon aerosol mass concentration over the East Baltic region from two-year measurements

Continuous measurements of black carbon (BC) aerosol mass concentration were performed at a background site Preila (55°55'N, 21°00'E, 5 m a.s.l., Lithuania) during the period 2008-2009. The data were used to characterize the BC mass concentration distribution over the East Baltic region. High increase in aerosol BC concentration was associated with the change in air mass characteristics and biomass burning during the winter heating season and spring wildfires. Monthly means of BC concentration ranged from 212 to 1268 ng m(-3) and the highest hourly means of concentration were from 4800 to 6300 ng m(-3), predominantly in spring and winter months. During the October-April period the BC mass concentrations were about twice as high as those in the summertime. The BC diurnal pattern in winter was typically different from that in spring indicating the seasonal variation of the atmospheric boundary layer height. The weekday/weekend difference was not strongly pronounced because the BC concentrations in Preila are mainly affected by long-range transport or local sources. Typical periodicities caused by anthropogenic and meteorological influences have been identified using Fourier analysis. It was shown that domestic heating appears as a 365 day periodicity; traffic slightly contributes 5-7 day peaks in the spectrum and elevated long-range BC can be identified as characteristic peaks with periodicities in the range from 16 to 29 days.Temporal evolution and transport of BC aerosols were interpreted by the air mass backward trajectory analysis in conjunction with the examination of the wavelength dependence on the aethalometer data. Air masses originated from the North Atlantic Ocean and Scandinavia were favourable for lower BC concentrations (350 ng m(-3)), while the BC level associated with the Western Europe airflows was significantly higher (970 ng m(-3)). The mean values of ?ngstr?m exponent of the absorption coefficient (monthly means 1.45 ± 0.25 and 0.84 ± 0.50 over January and June, respectively) revealed that the BC concentration observed over the East Baltic is influenced by submicron sized particles as a result of incomplete biomass combustion during the winter season.     

Detecting and correcting sensor drifts in long-term weather data

Quality control of long-term monitoring data of thousands and millions of individual records as present in meteorological data is cumbersome. In such data series, sensor drifts, stalled values, and scale shifts may occur and potentially result in flawed conclusions if not noticed and handled properly. However, there is no established standard procedure to perform quality control of high-frequency meteorological data. In this paper, we outline a procedure to remove sensor drift in high-frequency data series using the example of 15-year-long sets of hourly relative humidity (RH) data from 28 stations subdivided into 202 individual sensor operation periods. The procedure involves basic quality control, relative homogeneity testing, and drift removal. Significant sensor drifts were observed in 40.6 % of all sensor operation periods. The drifts varied between data series and depended in a complex, usually inconsistent way on absolute RH values; within single series for instance, a drift could be negative in the lower RH range and positive in the upper RH range. Detrending changed RH values by, on average, 1.96 %. For one fifth of the detrended data, adjustments were 2.75 % and more of the measured value, and in one tenth 4.75 % and more. Overall, drifts were strongest for RH values close to 100 %. The detrending procedure proved to effectively remove sensor drifts. The principles of the procedure also apply to other meteorological parameters and more generally to any time series of data for which comparable reference data are available.