Atmospheric Dispersion Conditions Research Articles

Temporal characteristics and vertical profiles of atmospheric CH4 at the northern foot of the Qinling Mountains in China

A two-year (March 2021 to February 2023) continuous in-situ atmospheric CH4 measurements and periodic vertical CH4 measurements (<2000 m) in July and November 2021 were conducted at the northern foot of the Qinling Mountains in Xi'an, China, aiming to study the temporal and vertical variations in atmospheric CH4 and the influence of air mass transport. The two-year average CH4 concentration at this site was 2119.6 ± 108.8 ppb. Seasonal CH4 concentrations were the highest in winter (2177.6 ± 121.5 ppb) and lower in summer (2079.1 ± 77.6 ppb) and spring (2073.9 ± 68.4 ppb). Diurnal CH4 peaked at 10:00–11:00. Atmospheric CH4 there was mainly from local source emissions from Xi'an and short distance transport from the southern Qinling Mountains through the valleys. On the July sampling days, vertical CH4 concentrations increased in the morning (08:00) and at mid-night (23:30), while they decreased in the early afternoon (13:00) and late afternoon (18:00) from near the surface (20 m) to 200 m, increased at 200–500 m, and then decreased at 500–1000 m. During the heating period in November, vertical CH4 concentrations increased by 20.0–86.8 ppb at 20–200 m due to horizontal transport and poor atmospheric dispersion conditions, and then decreased up to 2000 m, with the fastest decrease rate (−44.4 ± 51.4 ∼ −17.6 ± 19.3 ppb/100 m) at 500–1000 m. Vertical CH4 concentrations increased at all heights especially below 500 m in serve haze, mainly attributed to horizontal transport from the northwestern and southeastern polluted regions. Vertical observations further confirmed the important influence of transport on CH4 levels at this site.

Assessing the role of atmospheric dispersion vs. emission strength in the southern Po Valley (Italy) using dispersion-normalised multi-time receptor modelling

In this paper, we applied the Dispersion Normalised Positive Matrix Factorisation (DN-PMF) approach recently proposed in the literature to provide a more realistic picture of the relative importance of emission strength vs. atmospheric dispersion conditions. The disentanglement of such effects is of great concern in pollution hot spots like the Po Valley (Italy), where particulate matter limit values are exceeded despite the existing abatement measures. To explore the potentiality of the DN-PMF approach – still scarcely applied in the literature – a well-chemically characterised PM1 (atmospheric particles with aerodynamic diameter <1 μm) dataset comprising samples collected at different time resolutions at an urban background site (Bologna) in the southern Po Valley was used. Indeed, it is well known that shallow mixing layers promote pollutant accumulation but this observation is not enough to exclude an enhancement of emission strength which could be tackled by appropriate abatement strategies.The source apportionment of sub-micron sized aerosols having a quite long atmospheric residence time in a complex environment like the Po Valley - which is also strongly impacted by secondary aerosol formation on a basin-scale - is generally quite challenging when using receptor models. Due to the availability of a huge dataset with variables having multiple time resolutions, in this work the DN-PMF was implemented in a multi-time resolution approach (MT) to achieve a better source identification and to gain knowledge about the relative importance of atmospheric dilution vs. emissions. A comparison between results obtained by the application of the regular multi time resolution (REG-MT) vs. the DN-MT approach is presented here for the five factors identified (nitrate-dominated, sulphate-dominated, biomass burning, mineral dust, and urban aerosol). The first interesting outcome is that REG-MT and DN-MT results do not point at significant differences in temporal patterns for aerosol components and sources impacting at the basin-scale (i.e. sulphate- and nitrate-dominated aerosol, biomass burning) thus suggesting that the diel modulation of these PM1 emissions is somehow masked by the stronger variability of the mixing layer. Conversely, contributions from local sources with more pronounced diel variation like traffic are quite well reproduced by DN-MT and the ambient concentrations are enhanced compared to REG-MT. This is an important piece of information highlighting that PM1 concentrations from local sources have been likely underestimated by REG-MT assessments.To our knowledge, this is one of the very few applications of DN-MT and the first one at a European site where the huge effort made to implement air pollution containment measures is still not very much effective in reducing PM levels; moreover, in this paper a detailed discussion about the possible interpretation of the output of DN-MT in terms of temporal patterns is reported.

Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes

Abstract. Super-resolution atmospheric modelling can be used to interpret and optimize environmental observations during top-down emission rate retrieval campaigns (e.g. aircraft-based) by providing complementary data that closely correspond to real-world atmospheric pollution transport and dispersion conditions. For this work, super-resolution model simulations with large-eddy-simulation sub-grid-scale parameterization were developed and implemented using WRF-ARW (Weather Research and Forecasting - Advanced Research WRF). We demonstrate a series of best practices for improved (realistic) modelling of atmospheric pollutant dispersion at super-resolutions. These include careful considerations for grid quality over complex terrain, sub-grid turbulence parameterization at the scale of large eddies, and ensuring local and global tracer mass conservation. The study objective was to resolve small dynamical processes inclusive of spatio-temporal scales of high-speed (e.g. 100 m s−1) airborne measurements. This was achieved by downscaling of reanalysis data from 31.25 km to 50 m through multi-domain model nesting in the horizontal and grid-refining in the vertical. Further, WRF dynamical-solver source code was modified to simulate the release of passive tracers within the finest-resolution domain. Different meteorological case studies and several tracer source emission scenarios were considered. Model-generated fields were evaluated against observational data (surface monitoring network and aircraft campaign data) and also in terms of tracer mass conservation. Results indicated agreement between modelled and observed values within 5 ∘C for temperature, 1 %–25 % for relative humidity, and 1–2 standard deviations for wind fields. Model performance in terms of (global and local) tracer mass conservation was within 2 % to 5 % of model input emissions. We found that, to ensure mass conservation within the modelling domain, tracers should be released on a regular-resolution grid (vertical and horizontal). Further, using our super-resolution modelling products, we investigated emission rate estimations based on flux calculation and mass-balancing. Our results indicate that retrievals under weak advection conditions (horizontal wind speeds &lt; 5 m s−1) are not reliable due to weak correlation between the source emission rate and the downwind tracer mass flux. In this work we demonstrate the development of accurate super-resolution model simulations useful for planning, interpreting, and optimizing top-down retrievals, and we discuss favourable conditions (e.g. meteorological) for reliable mass-balance emission rate estimations.

Discordant future climate-driven changes in winter PM2.5 pollution across India under a warming climate

India’s megacities have been suffering from frequent winter particulate matter (PM2.5) pollution episodes, and how impacts of meteorology on air quality will evolve with time under a warming climate remains a concern. In this study, we identified conducive meteorological weather conditions in 5 megacities across India and found that quantile regression models can better describe the meteorological impacts under high pollution level and capture more observed high PM2.5 events than linear regression. The future climate-driven changes in winter PM2.5 pollution in India were offered with quantile regression models using Coupled Model Intercomparison Project 6 simulations under the SSP585 and SSP245 scenarios. Under SSP585 scenario, northern Indian megacities are likely to suffer from a stagnant weather condition in the near future, and higher boundary layer height and more atmospheric dispersion conditions during the second half of 21st century. Compared with the mean levels over 1990–2019, New Delhi and Kolkata would experience 6.1 and 5.7 more PM2.5 exceedances per season over 2030–2059 and 4.1 and 2.5 fewer exceedances per season during 2070–2099, respectively. Owing to increasing surface humidity and boundary layer height, air quality is projected to improve in Mumbai and Hyderabad with more than 6.1 and 1.2 fewer exceedances per season over 2050–2099. However, more than 6 exceedances will occur in Chennai due to enhanced lower-tropospheric stability. The negative impact of future meteorology on PM2.5 exceedances would become weak under SSP245. Our results can provide references for the Indian government to optimize their emission control plans to minimize adverse impacts of air quality on health, ecosystem, and climate.

Rapid decline of carbon monoxide emissions in the Fenwei Plain in China during the three-year Action Plan on defending the blue sky

The Fenwei Plain is one of China's most polluted regions, with poor atmospheric dispersion conditions and an outdated energy structure. After implementing multiple policies in recent years, significant reductions in air pollutant concentrations were observed. In this study, based on the Lagrangian-Bayesian inversion framework FLEXINVERT, we constructed a variable resolution inversion system focusing on the Fenwei Plain and inferred the carbon monoxide (CO) emissions using in-situ atmospheric CO observations from April 2014 to March 2020. We analyzed the spatiotemporal variations of the CO emissions and discussed their causes, especially the effect of the “Three-year Action Plan on Defending the Blue Sky” (TAPDBS). Before the policy, CO emissions temporarily increased, and the overall decrease in CO emissions per unit of Gross Domestic Product (GDP) slowed down. When the policy was implemented, CO emission fluxes declined sharply, with an average drop of 28%, accompanied by an even higher 37% decrease of CO emission per GDP. The reasons for the decline in CO emissions in Shanxi, Shaanxi and Henan are diverse. The decrease in energy intensity is the reason for CO emission reduction in Shannxi and Henan province but not in Shanxi province. This research fills the gap in emission information in recent years and confirms that TAPDBS has brought a breakthrough in both economic development and air quality protection in the Fenwei Plain.

Comparative Study of Source Inversion Under Multiple Atmospheric Pollutant Emission Scenarios

Source inversion is an effective approach for estimating air pollutant source parameters (e.g., source emission or source strength [Q0], source horizontal location [x0, y0], and release height [z0]) in industrial activities or accidents. Air pollution events in the real world generally correspond to complex application scenarios arising from unknown source parameters (i.e., Q0, [Q0, z0], [Q0, x0, y0], and [Q0, x0, y0, z0]) and atmospheric dispersion conditions. However, the source inversion characteristic law of these complex practical scenarios and the interaction mechanism between source location prior information and source strength inversion have not been revealed. In this study, the source inversion performance (accuracy and robustness) under the aforementioned scenarios was evaluated based on the Prairie Grass field experiments. Results indicated that the estimation accuracy of source strength was worse with an increase in the number of unknown source parameters with absolute relative deviations of 34.4, 46.0, 80.1, and 83.6% for a single parameter and double, triple, and quadruple parameters, respectively. Source strength inversion performance was obviously affected by location parameters; robustness was markedly reduced when source height was unknown, whereas accuracy was obviously reduced when source horizontal locations were unknown. Impacts of atmospheric conditions on different source parameters were distinct. Extreme atmospheric conditions (stability A and F) can obviously reduce the estimation accuracy of source strength for single and double parameter inversion scenarios, whereas unstable conditions (stability A, B, and C) can reduce the estimation accuracy of source strength for triple and quadruple parameter scenarios. Source inversion accuracy and robustness were generally poor under extremely stable conditions. This study can fill the knowledge gap in characteristic laws of source inversion under complex application scenarios and the interaction relationship between different unknown source parameters. The results of the influence law of location prior information on source strength inversion have important guiding significance to further improve the inversion accuracy of source strength in practical environmental managements.

Assessment of the link between atmospheric dispersion and chemical composition of PM10 at 2-h time resolution

The concentration of air pollutants is governed by both emission rate and atmospheric dispersion conditions. The role played by the atmospheric mixing height in determining the daily time pattern of PM components at the time resolution of 2 h was studied during 21 days of observation selected from a 2-month field campaign carried out in the urban area of Rome, Italy.Natural radioactivity was used to obtain information about the mixing properties of the lower atmosphere throughout the day and allowed the identification of advection and stability periods. PM10 composition was determined by X-ray fluorescence, ion chromatography, inductively coupled plasma-mass spectrometry and thermo-optical analysis. A satisfactory mass closure was obtained on a 2-h basis, and the time pattern of the PM10 macro-sources (soil, sea, secondary inorganics, organics, traffic exhaust) was acquired at the same time scale.After a complete quality control procedure, 27 main components and source tracers were selected for further elaboration. On this database, we identified some groups of co-varying species related to the main sources of PM. Each group showed a peculiar behaviour in relation to the mixing depth. PM components released by soil, biomass burning and traffic exhaust, and, particularly, ammonium nitrate, showed a clear dependence on the mixing properties of the lower atmosphere. Biomass burning components and organics peaked during the night hours (around midnight), following the atmospheric stabilization and increased emission rate. Traffic exhausts and non-exhausts species also peaked in the evening, but they showed a second, minor increase between 6:00 and 10:00 when the strengthening of the emission rate (morning rush hour) was counterbalanced by the dilution of the atmosphere (increasing mixing depth). In the case of ammonium nitrate, high concentrations were kept during the whole night and morning.

Clustering diurnal cycles of day-to-day temperature change to understand their impacts on air quality forecasting in mountain-basin areas

Abstract. Air pollution is substantially modulated by meteorological conditions, and especially their diurnal variations may play a key role in air quality evolution. However, the behaviors of temperature diurnal cycles along with the associated atmospheric condition and their effects on air quality in China remain poorly understood. Here, for the first time, we examine the diurnal cycles of day-to-day temperature change and reveal their impacts on winter air quality forecasting in mountain-basin areas. Three different diurnal cycles of the preceding day-to-day temperature change are identified and exhibit notably distinct effects on the day-to-day changes in atmospheric-dispersion conditions and air quality. The diurnal cycle with increasing temperature obviously enhances the atmospheric stability in the lower troposphere and suppresses the development of the planetary boundary layer, thus deteriorating the air quality on the following day. By contrast, the diurnal cycle with decreasing temperature in the morning is accompanied by a worse dispersion condition with more stable atmosphere stratification and weaker surface wind speed, thereby substantially worsening the air quality. Conversely, the diurnal cycle with decreasing temperature in the afternoon seems to improve air quality on the following day by enhancing the atmospheric-dispersion conditions on the following day. The findings reported here are critical to improve the understanding of air pollution in mountain-basin areas and exhibit promising potential for air quality forecasting.

Improving source inversion performance of airborne pollutant emissions by modifying atmospheric dispersion scheme through sensitivity analysis combined with optimization model

Estimating accurately airborne pollutant emissions source information (source strength and location) is important for achieving effective air pollution management or adequate emergency responses to accidents. Inversion method is one of the useful tools to identify the source parameters. The atmospheric dispersion scheme has been proven to be the key to determining the source inversion performance by influencing the accuracy of the dispersion models. Modifying the atmospheric dispersion scheme is an important potential method to improve the inversion performance, but this has not been studied previously. To fill this gap, a novel approach for parameter sensitivity analysis combined with an optimization method was proposed to improve the source inversion performance by optimizing empirical scheme. The dispersion coefficients σy and σz of the typical BRIGGS scheme under different atmospheric dispersion conditions were optimized and used for air pollutant dispersion and source inversion. The results showed that the prediction performance of the air pollutant concentrations was greatly improved with statistical indices |FB| and NMSE decreased by 0.22 and 2.07, respectively; FAC2 and R increased by 0.10, and 0.08, respectively. For source inversion, the results of the significance analysis suggested that the accuracy in the source strength and location parameter (x0) were both significantly improved by ∼271% (relative deviation reduced from 60.0% to 16.2%) and ∼121% (absolute deviation reduced from 27.6 to 12.5 m). The improvement of source strength inversion accuracy was more significant under unstable atmospheric conditions (stability class A, B, and C); the mean absolute relative deviation was reduced by 97.5%. These results can help to obtain more accurate source information and to provide reliable reference for air pollution managements or emergency response to accidents. This study provides a novel and versatile approach to improve estimation performance of pollutant emission sources and enhances our understanding of source inversion.

Effectiveness of airborne radon progeny assessment for atmospheric studies

In this paper, measurements of short- and long-lived Radon progeny attached to atmospheric fine aerosols are reported.Hourly measurements of 222Rn short-lived decay products (i.e. 214Bi via on-line alpha spectrometry on 214Po) in the atmosphere were carried out in Milan (Italy) from 1999 to 2016; 214Bi mean concentrations ranged from 0.2 to 38.1 Bq m−3. It is noteworthy that minima occurred in springtime although the strongest convective turbulence can be expected in summer, when the highest solar radiation is available; one order of magnitude higher values were observed in winter when the Po valley experienced poor atmospheric dilution. The Theil-Sen method was applied to investigate the long-time trend in de-seasonalised data series. Results showed that - although inter/intra-annual variations in 214Bi concentrations were observed in connection with differences in atmospheric dispersion conditions – no statistically significant trend over the investigated period was detected.On a sub-set of these samples, also weekly 210Pb concentrations were determined via off-line alpha spectrometry on 210Po; atmospheric activity concentration values ranged between 0.13 and 3.05 mBq m−3. The seasonal behaviour of 210Pb concentrations followed fairly well the 214Bi temporal pattern, showing that mixing layer dynamics is paramount in determining short- and long-lived Radon progeny levels in the atmosphere.From 210Pb/214Bi activity ratio, the residence time τres of fine aerosols in the atmosphere was estimated to be on average 1 day, ranging from 11.0 to 55.3 h without any evident temporal trend. By exploiting the availability of mixing layer height data at our site, an alternative approach to estimate aerosol residence time was tested; this was based on a simple relationship relying on deposition velocity (from literature data) and mixing layer height (available at our monitoring station). Mean experimental τres resulted in 1.2 days which was comprised in the 0.6–2.0 days range estimated by the alternative method. This result brings a noteworthy contribution to the scientific debate about differences among aerosol residence time estimates obtained by different radioactive parent-daughter couple; our results show that the 210Pb/214Bi (or equivalently 210Pb/222Rn) couple provides reliable estimates.

PM2.5-bound PAHs during a winter haze episode in a typical mining city, central China: Characteristics, influencing parameters, and sources

Huangshi City in Hubei Province, Central China is one of the most important mineral cities in the middle reaches of the Yangtze River, where haze occurred frequently in recent years due to coal-based metalsmelting. A haze was observed from January 13 to January 25, 2018 in Huangshi. To understand the levels, compositions, influencing parameters, and sources of PAHs during a process of haze generation and elimination, fine particulate matter (PM2.5) -bound polycyclic aromatic hydrocarbons (PAHs) were high-time-resolution measured (four samples per day) by gas chromatograph-mass spectrometry (GC-MS). The episode divided into three periods including before haze episode (BHE, 10 samples), during haze episode (DHE, 33 samples) and after haze episode (AHE, 4 samples) based on PM2.5 concentration. The average concentrations of Σ15PAHs at three different periods decreased as follows: DHE (30.52 ng m−3) > BHE (29.99 ng m−3) > AHE (14.24 ng m−3). 4- and 5-ring PAHs were the dominant species, and the proportion of 5- and 6-ring PAHs significantly increased DHE probably due to the local emissions (e.g., vehicle emissions) and the poor atmospheric dispersion conditions. PM2.5-bound PAHs were affected by gaseous pollutants (NO2, SO2, O3, and CO) and meteorological parameters (pressure, temperature, wind speed, wind direction, and relative humidity). Results of source apportionment indicated that PM2.5-bound PAHs were similar for three stages of this haze, mainly including vehicle exhaust emission, coal/biomass combustion, industrial process, and coke oven.

Surveillance of SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; and NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; from ship emissions by MAX-DOAS measurements and the implications regarding fuel sulfur content compliance

Abstract. Due to increased concerns regarding air pollutants emitted from shipping, feasible technology for the surveillance of these pollutants is in high demand. Here, we present shore-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of SO2 and NO2 emitted from ships under different traffic conditions in China's ship emission control areas (ECAs) in Shanghai and Shenzhen, China. Three typical measurement sites were selected in these two regions to represent the following emission scenarios: ships docked at berth, ships navigating in an inland waterway and inbound/outbound ships in a deep-water port. Using 2-D scanning, the observations show that SO2 and NO2 hot spots can be quickly and easily located from multiple berths. Although MAX-DOAS measurements can not distinguish plumes from specific ships in the busy shipping lanes of the inland waterway area, they certify that variations in the SO2 and NO2 levels are mainly impacted by the ship traffic density and the atmospheric dispersion conditions. In the open water area, which has a lower vessel density, MAX-DOAS measurements can capture the pulse signal of ship-emitted SO2 and NO2 very well; they can also characterize the peak's altitude and the insistent duration of the individual ship plumes. Combined with the ship activity data, information on the rated power of the engine and the fuel sulfur content, it was found that the SO2∕NO2 ratio in a single plume is usually low (&lt; 1.5) for inbound vessels due to the usage of the auxiliary engine, which has less power and uses “clean” fuel with a low sulfur content. Thus, an unexpectedly high SO2∕NO2 ratio implies the use of fuel with a sulfur content exceeding the regulation limits. Therefore, the observed SO2∕NO2 ratio in the plume of a single ship can be used as an index to indicate compliance (or noncompliance) with respect to the fuel sulfur content, and the suspicious ship can then be flagged for further enforcement. Combining the ship emissions estimated by actual operation parameters and the logical sulfur content, shore-based MAX-DOAS measurements will provide a fast and more accurate way to surveil ship emissions.

Radon-based estimates of equivalent mixing layer heights: A long-term assessment

Air pollution events at urban locations are driven by both emissions and atmospheric dispersion conditions. Atmospheric dispersion is not routinely assessed at monitoring networks thus preventing the possibility of understanding if high pollution events are due to increasing emissions or to the occurrence of atmospheric stability conditions. In principle, this piece of information would be very useful to implement effective strategies for pollution abatement. In this work, an 18-year long dataset of radon (222Rn) progeny measurements was used to estimate equivalent mixing layer heights (hereafter referred to as MH) with hourly resolution by means of a box model. Mean MH obtained by more conventional modelling approaches based on turbulence variables on a 5-year long dataset agreed very well with results obtained by the box model. It is noteworthy that in the literature there are scarce MH data for such long periods and comparisons between estimates by radioactive tracers and other approaches are often limited to a few days/weeks. Results suggested that relatively simple methods like the one here proposed could be implemented at pollution monitoring stations in order to improve available information and better understand the evolution of pollution events on 1-h timescale. In addition, the long-term assessment here presented provides useful data to pursue MH climatological studies.

Seasonal and Spatial Variation of Particulate Aerosols and Carbonaceous Species in PM2.5 in the Periphery of Chandigarh, India

Present study highlights the seasonal and spatial variation of particulate aerosols (PM10 and PM2.5) and carbonaceous species (organic tarry matter, organic and elemental carbon) in PM2.5. The ambient air samples for particulate aerosols were collected from tricity of Chandigarh, Mohali and Panchkula in India during summer (April’15–May’15) and winter (December’15–January’16). The mass levels of particulate aerosols and carbonaceous species show significant variation both seasonally and spatially. Average mass levels reported as higher in winter than summer were attributed to stagnant atmospheric and poor dispersion conditions. The mass levels were also found to be higher in industrial area as compared to residential and commercial areas. Average mass levels varying from 107.6 to 137.8 µg m−3 for PM10 and 46.6–59.5 µg m−3 for PM2.5 during the study period indicate alarming situation of particulate aerosols in this tricity. Carbonaceous species contributing as 42.5–47.5% OTM, 25.4–29.9% OC and 3.4–4.7% EC in PM2.5 indicate larger in fraction at all sites during both summer and winter.

Atmospheric pollution over the eastern Mediterranean during summer – a review

Abstract. The eastern Mediterranean (EM) is one of the regions in the world where elevated concentrations of primary and secondary gaseous air pollutants have been reported frequently, mainly in summer. This review discusses published studies of the atmospheric dispersion and transport conditions characterizing this region during the summer, followed by a description of some essential studies dealing with the corresponding concentrations of air pollutants such as ozone, carbon monoxide, total reactive nitrogen, methane, and sulfate aerosols observed there. The interlaced relationship between the downward motion of the subsiding air aloft induced by global circulation systems affecting the EM and the depth of the Persian Trough, a low-pressure trough that extends from the Asian monsoon at the surface controlling the spatiotemporal distribution of the mixed boundary layer during summer, is discussed. The strength of the wind flow within the mixed layer and its depth affect much the amount of pollutants transported and determine the potential of the atmosphere to disperse contaminants off their origins in the EM. The reduced mixed layer and the accompanying weak westerlies, characterizing the summer in this region, led to reduced ventilation rates, preventing an effective dilution of the contaminants. Several studies pointing at specific local (e.g., ventilation rates) and regional peculiarities (long-range transport) enhancing the build-up of air pollutant concentrations are presented. Tropospheric ozone (O3) concentrations observed in the summer over the EM are among the highest over the Northern Hemisphere. The three essential processes controlling its formation (i.e., long-range transport of polluted air masses, dynamic subsidence at mid-tropospheric levels, and stratosphere-to-troposphere exchange) are reviewed. Airborne campaigns and satellite-borne initiatives have indicated that the concentration values of reactive nitrogen identified as precursors in the formation of O3 over the EM were found to be 2 to 10 times higher than in the hemispheric background troposphere. Several factors favor sulfate particulate abundance over the EM. Models, aircraft measurements, and satellite-derived data have clearly shown that sulfate has a maximum during spring and summer over the EM. The carbon monoxide (CO) seasonal cycle, as obtained from global background monitoring sites in the EM, is mostly controlled by the tropospheric concentration of the hydroxyl radical (OH) and therefore demonstrates high concentrations over winter months and the lowest concentrations during summer when photochemistry is active. Modeling studies have shown that the diurnal variations in CO concentration during the summer result from long-range CO transport from European anthropogenic sources, contributing 60 to 80 % of the boundary-layer CO over the EM. The values retrieved from satellite data enable us to derive the spatial distribution of methane (CH4), identifying August as the month with the highest levels over the EM. The outcomes of a recent extensive examination of the distribution of methane over the tropospheric Mediterranean Basin, as part of the Chemistry-Aerosol Mediterranean Experiment (ChArMEx) program, using model simulations and satellite measurements, are coherent with other previous studies. Moreover, this methane study provides some insight into the role of the Asian monsoon anticyclone in controlling the variability of CH4 pollutant within mid-to-upper tropospheric levels above the EM in summer.

Causative impact of air pollution on evapotranspiration in the North China Plain

Atmospheric dispersion conditions strongly impact air pollution under identical surface emissions. The degree of air pollution in the Jing-Jin-Ji region is so severe that it may impose feedback on local climate. Reference evapotranspiration (ET0) plays a significant role in the estimation of crop water requirements, as well as in studies on climate variation and change. Since the traditional correlation analysis cannot capture the causality, we apply the convergent cross mapping method (CCM) in this study to observationally investigate whether the air pollution impacts ET0. The results indicate that southwest regions of Jing-Jin-Ji always suffer higher PM2.5 concentration than north regions through the whole year, and correlation analysis suggests that PM2.5 concentration has a significant negative effect on ET0 in most cities. The causality detection with CCM quantitatively demonstrates the significantly causative influence of PM2.5 concentration on ET0, higher PM2.5 concentration decreasing ET0. However, CCM analysis suggests that PM2.5 concentration has a relatively weak causal influence on ET0 while the correlation analysis gives the near zero correlation coefficient in Zhangjiakou city, indicating that the causative influence of PM2.5 concentration on ET0 is better revealed with CCM method than the correlation analysis. Considering that ET0 is strongly associated with crop water requirement, the amount of water for agricultural irrigation could be reduced at high PM2.5 concentrations. These findings can be utilized to improve the efficiency of water resources utilization, and reduce the exploiting amount of groundwater in the Jing-Jin-Ji region, although PM2.5 is detrimental to human health.

Evaluation of Accidental Atmospheric Releases of Chlorine and Butane from a Mobile Source Using ALOHA and MARPLOT

The purpose of this paper is to evaluate the extend of the threat zone of two mobile accidental atmospheric releases of chlorine and butane on the I-95 Highway by estimating the downwind dispersion of the chemical plumes using the numerical model ALOHA (Area Locations of Hazardous Atmospheres) and by graphing the boundaries of the threat zone using MARPLOT (Mapping Application for Response, Planning, and Local Operational Tasks). In addition, to assess the risk of exposure at two points of interest from the chlorine accident, and to measure the extent of the flammable zone; the area where a flash fire or a vapor cloud explosion could occur at some point after the release begins, resulting from the butane accident. Moreover, the aim is to study the stability class effect on indoor and outdoor concentrations and its effect on distance of the flammable zones. The paper conclude that the stability class has a significant effect on the prediction of the size of the toxic threat zone under different atmospheric dispersion conditions. In addition, the size of the area impacted after a chemical release depends on the characteristics of the chemical along with the meteorological and atmospheric conditions.

Characterization of hydrocarbons in aerosols at a Mediterranean city with a high density of palm groves.

Samples of PM1 and PM10 were collected for 1year at an urban background station in the city of Elche (southeastern Spain) and analyzed to determine the content of n-alkanes and polycyclic aromatic hydrocarbons (PAHs). A few samples were also gathered at a second sampling point established at one of the several palm tree gardens of the city in order to evaluate the influence of biogenic emissions on the urban levels of n-alkanes. Diagnostic parameters obtained for aliphatic hydrocarbons (carbon maximum number (C max), carbon preference index (CPI), and wax n-alkane content (%WNA)) revealed a higher contribution of biogenic n-alkanes in PM10 than in PM1. Moreover, the values of %WNA indicated that the levels of n-alkanes in Elche were more affected by emissions from terrestrial vegetation than in other urban areas, particularly in the palm tree grove location (%WNA=29 for PM10). PAH diagnostic ratios pointed to traffic as the main anthropogenic source of hydrocarbons in Elche, with predominance of diesel versus gasoline vehicle emissions. The average levels of total PAHs (~1ngm(-3)) were noticeably lower than the values registered at other urban areas in Europe, most likely because emissions from other sources are scarce. Both aliphatic and aromatic hydrocarbons showed higher levels in the cold season due to the lower atmospheric dispersion conditions, the increase in traffic exhaust emissions, and the lower ambient temperatures that reduce the evaporation of semivolatile species.

Evaluation of atmospheric dispersion conditions for siting and designing an NPP using aerological data

An important step in special research on the climatic conditions of atmospheric dispersion is statistical processing of the data from observations performed at the principal aerological station. The software package for statistical analysis of aerological data used to evaluate the atmospheric dispersal conditions at the future site of a nuclear power plant is described. It is noted that the software package provides preliminary preparation of the working database of the principal aerological station. As an example, a calculation of the field of the meteorological dilution factor for the impurities at the site of the Nizhegorodskaya NPP, currently under construction, is presented.

Integrated modeling of urban–scale pollutant transport: application in a semi–arid urban valley, Northwestern China

Air pollution in urban areas is related not only to emission sources but also to atmospheric dispersion and transport conditions. Knowledge of pollutant transport pathways, potential source regions and their relative contribution to pollution levels in a city is thus very useful for urban planning and development of effective regulatory and mitigation strategies. In this study, the Hybrid Single–Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by high resolution (1km × 1km) meteorological fields from the Weather Research & Forecasting (WRF) model was used to identify the relationship between atmospheric transport patterns and daily pollutant concentrations on urban scale, with a case study in Lanzhou–an urban valley in Northwestern China. Trajectories calculated by HYSPLIT model for winter months (December, January and February) of 2002–2008 were analyzed using Ward’s hierarchical method to identify dominant transport pathways leading to elevated pollutant concentrations in urban Lanzhou. Potential source locations and their relative contribution to pollution levels were evaluated with the help of potential source contribution function (PSCF) analysis and the concentration–weighted trajectory (CWT) method. The transport pathways from the northeast of the urban center and from the west and the east county were identified as the most important pathways leading to high pollutant concentrations in urban Lanzhou, with potential source areas located in the west and the east to the urban center. The contribution of potential source regions was more than 200 µg m–3, 120 µg m–3 and 60–80 µg m–3 to the PM10, SO2 and NO2 loadings, respectively, which is closely related to emission source characteristics in the study area.