Regional Monitoring Network Research Articles

Wetland Accretion Rates Along Coastal Louisiana: Spatial and Temporal Variability in Light of Hurricane Isaac’s Impacts

The wetlands of the southern Louisiana coast are disappearing due to a host of environmental stressors. Thus, it is imperative to analyze the spatial and temporal variability of wetland vertical accretion rates. A key question in accretion concerns the role of landfalling hurricanes as a land-building agent, due to their propensity to deposit significant volumes of inorganic sediments. Since 1996, thousands of accretion measurements have been made at 390 sites across coastal Louisiana as a result of a regional monitoring network, called the Coastal Reference Monitoring System (CRMS). We utilized this dataset to analyze the spatial and temporal patterns of accretion by mapping rates during time periods before, around, and after the landfall of Hurricane Isaac (2012). This analysis is vital for quantifying the role of hurricanes as a land-building agent and for understanding the main mechanism causing heightened wetland accretion. The results show that accretion rates averaged about 2.89 cm/year from stations sampled before Isaac, 4.04 cm/year during the period encompassing Isaac, and 2.38 cm/year from sites established and sampled after Isaac. Accretion rates attributable to Isaac’s effects were therefore 40% and 70% greater than before and after the event, respectively, indicating the event’s importance toward coastal land-building. Accretion associated with Isaac was highest at sites located 70 kilometers from the storm track, particularly those near the Mississippi River and its adjacent distributaries and lakes. This spatial pattern of elevated accretion rates indicates that freshwater flooding from fluvial channels, rather than storm surge from the sea per se, is the main mechanism responsible for increased wetland accretion. This significance of riverine flooding has implications toward future coastal restoration policies and practices.

Modeling of the chemical composition of fine particulate matter: Development and performance assessment of EASYWRF-Chem

The European emission Adaptation SYstem for the WRF-Chem model (EASYWRF-Chem) has been developed to generate chemical information supporting the WRF-Chem requirements from any emission inventory based on the CORINAIR methodology. Using RADM2 and RACM2 mechanisms, “emission species” are converted into “model species” thanks to the SAPRC methodology for gas phase pollutant and the PM10 and PM2.5 fractions. Furthermore, by adapting US EPA PM2.5 profiles, the processing of aerosol chemical speciation profiles separates the unspeciated PM2.5 emission into five chemical families: sulfates, nitrates, elemental carbon, organic aerosol and unspeciated aerosol. The evaluation of the model has been performed by separately comparing model outcomes with (i) meteorological measurements; (ii) NO2, O3, PM10 and PM2.5 mass concentrations from the regional air quality monitoring network; (iii) hourly-resolved data from four field campaign measurements, in winter and in summer, on two sites in the French northern region. In the latter, a High Resolution — Time of Flight — Aerosol Mass Spectrometer (HR-ToF-AMS) provided non-refractory PM1 concentrations of sulfate, nitrate and ammonium ions as well as organic matter (OM), while an aethalometer provided black carbon (BC) concentrations in the PM2.5 fraction.Meteorological data (temperature, wind, relative humidity) are well simulated for all the time series data except for specific events as wind direction changes or rainfall. For particulate matter, results are presented by considering firstly the total mass concentration of PM2.5 and PM10. EASYWRF-Chem simulations overestimated the PM10 mass concentrations by +22% and +4% for summer and winter periods respectively, whereas for the finer PM2.5 fraction, mass concentrations were overestimated by +20% in summer and underestimated by −13% in winter.Simulated sulfate concentrations were underestimated and nitrate concentrations were overestimated but hourly variations were well represented. Ammonium particulate matter was well simulated for all seasons. Although simulated particulate OM concentrations in PM2.5 were underestimated, their hourly variations were well reproduced by the model. At least BC measurements revealed that EASYWRF-Chem forecast performance was higher in winter than during summer when BC concentrations were very low.

Evaluation of a MISR-Based High-Resolution Aerosol Retrieval Method Using AERONET DRAGON Campaign Data

Satellite-retrieved aerosol optical depth (AOD) can potentially provide an effective way to complement the spatial coverage limitation of a ground particulate air-pollution monitoring network such as the U.S. Environment Protection Agency's regulatory monitoring network. One of the current state-of-the-art AOD retrieval methods is the National Aeronautics and Space Administration's Multiangle Imaging SpectroRadiometer (MISR) operational algorithm, which has a spatial resolution of 17.6 km $\times$ 17.6 km. Although the MISR's aerosol products lead to exciting research opportunities to study particle composition at a regional scale, its spatial resolution is too coarse for analyzing urban areas, where the air pollution has stronger spatial variations and can severely impact public health and the environment. Accordingly, a novel AOD retrieval algorithm with a resolution of 4.4 km $\times$ 4.4 km has been recently developed, which is based on hierarchical Bayesian modeling and the Monte Carlo Markov chain (MCMC) inference method. In this paper, we carry out detailed quantitative and qualitative evaluations of the new algorithm, which is called the HB-MCMC algorithm, using recent AErosol RObotic NETwork (AERONET) Distributed Regional Aerosol Gridded Observation Networks (DRAGON) campaign data obtained in the summer of 2011. These data, which were not available in a previous study, contain spatially dense ground measurements of the AOD and other aerosol particle characteristics from the Baltimore–Washington, DC region. Our results show that the HB-MCMC algorithm has 16.2% more AOD retrieval coverage and improves the root-mean-square error by 38.3% compared with the MISR operational algorithm. Our detailed analyses with various metrics show that the improvement of our scheme is coming from the novel modeling and inference method. Furthermore, the map overlay of the retrieval results qualitatively confirms the findings of the quantitative analyses.

SIMAC: Development and implementation of a coral reef monitoring network in Colombia

Significant coral reef decline has been observed in Colombia during the last three decades. However, due to the lack of monitoring activities, most of the information about health and changes was fragmentary or inadequate. To develop an expanded nation-wide reef-monitoring program, in 1998 INVEMAR (Instituto de Investigaciones Marinas y Costeras: "Colombian Institute of Marine and Coastal Research") designed and implemented SIMAC (Sistema Nacional de Monitorco de Arrecifes Coralinos en Colombia: "National Monitoring System of Coral Reefs in Colombia") with the participation of other institutions. By the end of 2003 the SIMAC network reached more than twice its initial size, covering ten reef areas (seven in the Caribbean and three in the Pacific), 63 reef sites and 263 permanent transects. SIMAC monitoring continued without interruption until 2008 and should persist in the long-term. The SIMAC has a large database and consists basically of water quality measurements (temperature, salinity, turbidity) and a yearly estimation of benthic reef cover, coral disease prevalence, gorgonian density, abundance of important mobile invertebrates, fish diversity and abundance of important fish species. A methods manual is available in the Internet. Data and results of SIMAC have been widely circulated through a summary report published annually since 2000 for the Colombian environmental agencies and the general public, as well as numerous national and international scientific papers and presentations at meetings. SIMAC information has contributed to support regional and global reef monitoring networks and databases (i.e. CARICOMP, GCRMN, ReefBase).

Top-down constraints on atmospheric mercury emissions and implications for global biogeochemical cycling

Abstract. We perform global-scale inverse modeling to constrain present-day atmospheric mercury emissions and relevant physiochemical parameters in the GEOS-Chem chemical transport model. We use Bayesian inversion methods combining simulations with GEOS-Chem and ground-based Hg0 observations from regional monitoring networks and individual sites in recent years. Using optimized emissions/parameters, GEOS-Chem better reproduces these ground-based observations and also matches regional over-water Hg0 and wet deposition measurements. The optimized global mercury emission to the atmosphere is ~ 5.8 Gg yr−1. The ocean accounts for 3.2 Gg yr−1 (55 % of the total), and the terrestrial ecosystem is neither a net source nor a net sink of Hg0. The optimized Asian anthropogenic emission of Hg0 (gas elemental mercury) is 650–1770 Mg yr−1, higher than its bottom-up estimates (550–800 Mg yr−1). The ocean parameter inversions suggest that dark oxidation of aqueous elemental mercury is faster, and less mercury is removed from the mixed layer through particle sinking, when compared with current simulations. Parameter changes affect the simulated global ocean mercury budget, particularly mass exchange between the mixed layer and subsurface waters. Based on our inversion results, we re-evaluate the long-term global biogeochemical cycle of mercury, and show that legacy mercury becomes more likely to reside in the terrestrial ecosystem than in the ocean. We estimate that primary anthropogenic mercury contributes up to 23 % of present-day atmospheric deposition.

A hydrologic assessment of a saline‐spring fen in the Athabasca oil sands region, Alberta, Canada – a potential analogue for oil sands reclamation

AbstractCanada's post‐mined oil sands will have a higher concentration of salts compared with freshwater peatlands that dominate the landscape. While rare, naturally occurring saline wetlands do exist in Alberta's Boreal Plains and may function as analogues for reclamation, however, little is known about their hydrology. This paper investigates the geochemical and hydrologic characteristics of a natural saline‐spring peatland in Alberta's oil sands region. The fen is located within a saline groundwater discharge area connected to the erosional edge of the Grand Rapids Formation. Na+(195–25,680 mgl−1) and Cl−(1785–56,249 mg l−1) were the dominant salts, and the fen transitioned sharply to freshwater along its margins because in part of subsurface mineral ridges that restricted shallow groundwater exchange. Salinity decreased from hypersaline to brackish along the local groundwater flow path but no active spring outlets were observed over the two‐year study. Vertical groundwater discharge was minimal because of the very low permeability of the underlying sediments. Subsurface storage was exceeded during periods of high flow, resulting in flooding and surface runoff that was enhanced by the ephemerally connected pond network. These findings have implications for reclamation, as mechanisms such as subsurface mineral ridges may function as effective saline groundwater‐control structures in the post‐mined environment. Incorporating saline wetlands into regional monitoring networks will help to better quantify natural discharge, which has implications for belowground wastewater storage related toin situbitumen extraction. Copyright © 2015 John Wiley & Sons, Ltd.

Field performance evaluation of Maxxam passive samplers for regional monitoring of ambient SO2, NO2 and O3 concentrations in Alberta, Canada

A field performance evaluation of Maxxam passive samplers was carried out for ambient concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2) and ground-level ozone (O3). Monthly passive and hourly continuous air monitoring data from four regional air monitoring networks in Alberta, Canada were evaluated over a 5-year period (2006–2010). Monthly concentrations were relatively low, ranging from 0.1 to 3.9 ppb, 0.2–18.1 ppb and 10.1–56.1 ppb for SO2, NO2 and O3, respectively. From duplicate passive sampling, geometric mean precision values were 17.9%, 14.8% and 4.7% for SO2, NO2 and O3, respectively. Geometric mean of the relative error (as a measure of accuracy) was 30% (median = 33%, interquartile range, IQR 15–63%) for SO2 and 32% (median = 40%, IQR = 25–64%) for NO2. O3 measurements had a better measure of accuracy with a geometic mean relative error of 12% (median = 17%, IQR = 8–27%) and met the acceptable level recommended by United States National Institute of Safety and Health (NIOSH) and the European Union (EU) Directive (±25%). From reduced major axis (RMA) analysis, bias (systematic error) is apparent in the Maxxam passive samplers in the field resulting in overestimation of ambient SO2 and O3 concentrations and underestimation of NO2 concentrations relative to continuous analyzers. Seasonal influences were observed for accuracy of passive SO2 and O3 measurements. A poor association was found between passive versus continuous concentrations for SO2 and O3 during the winter and the summer, respectively.

Active moss biomonitoring for extensive screening of urban air pollution: Magnetic and chemical analyses

In this study, active magnetic biomonitoring of moss for particulate air pollution and an assessment of heavy metals and polycyclic aromatic hydrocarbons (PAHs) were performed for the entire metropolitan area of Belgrade. Two mosses, Sphagnum girgensohnii (a species of the most recommended biomonitoring moss genus) and Hypnum cupressiforme (a common moss in the study area), were used. During the summer of 2013, moss bags were exposed at 153 sampling sites, forming a dense network of sites. A type II regression model was applied to test the interchangeable use of the two moss species. Significantly higher levels of all measured pollutants were recorded by S. girgensohnii in comparison with H. cupressiforme. Based on the results, the mosses could not be interchangeably used in urban areas, except for the biomonitoring of Cu. Nevertheless, according to the relative accumulation factors obtained for both moss species, similar city zones related to high, moderate and low levels of air pollution were distinguished. Moreover, new pollution hotspots, omitted by regulatory monitoring, were identified. The results demonstrate that moss magnetic analysis represents an effective first step for obtaining an overview of particulate air pollution before more expensive chemical analyses. Active moss biomonitoring could be applied as a pragmatic approach for optimizing the representativeness of regulatory monitoring networks.

Modeling of time-resolved light extinction and its applications to visibility management in the Lower Fraser Valley of British Columbia, Canada

Fine particulate matter (PM2.5) is the dominant cause of atmospheric visibility degradation in the Lower Fraser Valley (LFV) of British Columbia, where poor visibility due to air pollution is of concern. The spatial coverage of the current LFV visibility monitoring network is relatively low, with large parts of the airshed not being represented. Given the desire on the part of local and regional governments to manage visibility in the LFV airshed, the development of a method that allows near real-time estimation of 1-hr light extinction data from the dense network of PM measurements would be highly beneficial. This paper describes a simple linear algorithm, developed using the Hybrid method, to estimate near real-time 1-hr total light extinction at four monitoring sites in the LFV. Model inputs include ambient hourly PM2.5, NO2, relative humidity measurements, and historical monthly-averaged aerosol composition. The results indicate that the developed model can provide relatively accurate and time-resolved estimates of extinction in regions where visibility is not being monitored, thus extending the spatial coverage of the regional visibility monitoring network. The model was also applied to a number of policy-related scenarios to inform visual air quality management in the study area. Results indicated that in order to achieve a perceptible improvement (1.0 deciview) relative to baseline average visibility conditions in the LFV airshed, average ambient PM2.5 concentration would have to decrease by 17% from baseline conditions. Furthermore, to achieve a 20% increase in the number of daylight hours with “excellent” visibility, average PM2.5 would need to be reduced by 30%. Model simulations also indicated that “across-the-board” emission reduction policies would result in greater improvements for the “worst 20%” visibility conditions than for the “best 20%” conditions, suggesting that reducing the number of “poor” visibility days would be easier than improving the number of “excellent” visibility days.Implications: This study describes the development of a model using standard air quality monitoring data (PM2.5, NO2, relative humidity, and PM speciation profiles) to provide near real-time estimates of time-resolved extinction in regions where direct optical monitoring is not available. Applications of the model include extension of spatial coverage of a visibility network, testing various air quality scenarios to inform visibility management, and as a tool for setting visual air quality standards in impacted airsheds.

Integrating multidisciplinary science, modelling and impact data into evolving, syn-event volcanic hazard mapping and communication: A case study from the 2012 Tongariro eruption crisis, New Zealand

New Zealand's Tongariro National Park volcanoes produce hazardous eruptions every few years to decades. On 6 August 2012 the Te Maari vent of Tongariro Volcano erupted, producing a series of explosions and a fine ash of minor volume which was dispersed rapidly to the east. This manuscript presents a summary of the eruption impacts and the way these supported science communication during the crisis, particularly in terms of hazard map development. The most significant proximal impact was damage from pyroclastic surges and ballistics to the popular and economically-important Tongariro Alpine Crossing track. The only hazard to affect the medial impact zone was a few mms of ashfall with minor impacts. Field testing indicated that the Te Maari ash had extremely low resistivity when wetted, implying a very high potential to cause disruption to nationally-important power transmission networks via the mechanism of insulator flashover. This was not observed, presumably due to insufficient ash accumulation on insulators. Virtually no impacts from distal ashfall were reported. Post-event analysis of PM10 data demonstrates the additional value of regional air quality monitoring networks in quantifying population exposure to airborne respirable ash. While the eruption was minor, it generated a high level of public interest and a demand for information on volcanic hazards and impacts from emergency managers, the public, critical infrastructure managers, health officials, and the agriculture sector. Meeting this demand fully taxed available resources. We present here aspects of the New Zealand experience which may have wider applicability in moving towards improved integration of hazard impact information, mapping, and communication. These include wide use of a wiki technical clearinghouse and email listservs, a focus on multi-agency consistent messages, and a recently developed environment of collaboration and alignment of both research funding and technical science advice. Hazard maps were integral to science communication during the crisis, but there is limited international best practice information available on hazard maps as communication devices, as most volcanic hazard mapping literature is concerned with defining hazard zones. We propose that hazard maps are only as good as the communications framework and inter-agency relationships in which they are embedded, and we document in detail the crisis hazard map development process. We distinguish crisis hazard maps from background hazard maps and ashfall prediction maps, illustrating the complementary nature of these three distinct communication mechanisms. We highlight issues that arose and implications for the development of future maps.

An integrated approach for the evaluation of technological hazard impacts on air quality: the case of the Val d'Agri oil/gas plant

Abstract. The Val d'Agri area (southern Italy) hosts one of the biggest onshore European reservoir and the largest oil/gas pre-treatment plant, named Centro Olio Val d'Agri (COVA), located in a rural/anthropized context. Several hazards are associated with this plant. These are mainly represented by possible impacts of the COVA atmospheric emissions on the local air quality and human health. This work uses a novel approach based on the integration of air quality measurements from the regional monitoring network, additional experimental measurements (i.e. sub-micrometre particulate matter (PM1) and black carbon (BC)) and advanced statistical analyses to provide a preliminary evaluation of the Val d'Agri air quality state and give some indication of specific areas potentially affected by COVA hazards. Results show that the COVA plant emissions have a particular impact on the air quality of the area closest to it. In this area several pollutants specifically related to the COVA combustion processes (i.e. nitrogen oxides, benzene and toluene) show the highest concentration values and significant correlations. The proposed approach represents a first step in the assessment of the risks associated with oil/gas exploration and pre-treatment activities and a starting point for the development of effective and exportable air quality monitoring strategies.

Temporal variability in groundwater and surface water quality in humid agricultural catchments; driving processes and consequences for regional water quality monitoring

Considering the large temporal variability in surface water quality is essential for adequate water quality policy and management. Neglecting these dynamics may easily lead to decreased effectiveness of measures to improve water quality and to inefficient water quality monitoring. The objective of this paper is to summarise our understanding of temporal variability in surface water and upper groundwater quality and to discuss the consequences and opportunities for regional water quality monitoring. In regional monitoring networks, measurement frequencies are typically too low to capture the short-term temporal variations in solute concentrations. This causes large uncertainty in the assessment of (trends in) average concentrations and contaminant loads. The most important driver for short-term variations in water quality in most catchments is the variability in meteorological conditions, which induces changes in the relative discharge contributions of water from different flow routes and different chemical compositions. Various options exist for dealing with the transient behavior of water quality in regional water quality monitoring. Estimates of average concentrations and loads from low-frequency concentration data can be improved by using the explanatory strength of commonly available measurements of quantitative hydrological data like precipitation, discharge, and groundwater levels. This paper provides examples of the relationship between water quality and explanatory variables in conceptual, statistical, or process-based models. Another strategy for dealing with short-term variability in water quality monitoring is to measure long-term average solute concentrations using passive samplers. Similarly, on-site auto analyzers and ion specific electrodes provide opportunities for continuous water quality measurements.

FOCUS: A pilot study for national-scale critical loads development in the United States

Abstract The development and use of critical loads of air pollutant deposition in the U.S. is gaining momentum, and recent research efforts in the U.S. have produced valuable data for calculating critical loads. Critical loads are used to quantify the levels of air pollutants that are expected to impact forest health, soil fertility, aquatic biota condition, and other ecosystem responses. In addition, model refinements for improving critical loads estimates, and maps for illustrating critical loads for acidification and nitrogen saturation and eutrophication resulting from excess nutrient nitrogen, have been developed at various scales. However, prior to the effort described here, no cohesive process existed to provide a national-scale critical loads database and maps as a unified product representing all U.S. ecosystems. The FOCUS (Focal Center Utility Study) Project was initiated to coordinate the development and implementation of a clear, consistent, repeatable process for calculating and mapping critical loads within the U.S. In the FOCUS Phase I Pilot Study, empirical and calculated critical loads data for the U.S. were synthesized from dozens of regional and national-scale monitoring networks, research projects and publically available databases following an approach similar to that used in Europe. The United Nations Economic Commission for Europe (UNECE), through its International Cooperative Programme on Modelling and Mapping of Critical Levels & Loads and Air Pollution Effects, Risks and Trends (ICP-M&M) collects, analyzes and maps critical loads data. Countries participating in the Convention on Long-range Transboundary Air Pollution (CLRTAP) use a Critical Loads “Focal Center” in each country to serve as the point of contact for submitting regional and national-scale critical loads data to the ICP-M&M. One of the purposes of this study was to develop a foundation for interacting with other Focal Centers by assembling critical loads data, creating a database, establishing modeling protocols, and developing infrastructure within the U.S to report and update critical loads on a national scale. Because the U.S. does not currently have an officially designated Focal Center, critical loads data were provided as an informal, unofficial submission to the Coordination Center for Effects (CCE) of the ICP-M&M in March 2011, in the interest of international cooperation and exchange of information on the effects of atmospheric deposition of pollutants on ecosystems. We envision that these data will enable U.S. scientists, land managers, and environmental policymakers to enter into a productive and meaningful dialogue within the US, and also with the international scientific community on methods for estimating, calculating, mapping, interpreting, and refining critical loads for the effects of acidification and excess nutrient nitrogen on terrestrial and aquatic ecosystems. This paper describes the process used to develop national-scale critical loads in the U.S., summarizes the FOCUS Phase I approach and database development effort, and presents some initial national-scale critical loads mapping products.

Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean peninsula

Summary An understanding soil moisture spatio-temporal variability is essential for hydrological and meteorological research. This work aims at evaluating the spatio-temporal variability of near surface soil moisture and assessing dominant meteorological factors that influence spatial variability over the Korean peninsula from May 1 to September 29, 2011. The results of Kolmogorov–Smirnov tests for goodness of fit showed that all applied distributions (normal, log-normal and generalized extreme value: GEV) were appropriate for the datasets and the GEV distribution described best spatial soil moisture patterns. The relationship between the standard deviation and coefficient of variation (CV) of soil moisture with mean soil moisture contents showed an upper convex shape and an exponentially negative pattern, respectively. Skewness exhibited a decreasing pattern with increasing mean soil moisture contents and kurtosis exhibited the U-shaped relationship. In this regional scale (99,720 km2), we found that precipitation indicated temporally stable features through an ANOVA test considering the meteorological (i.e. precipitation, insolation, air temperature, ground temperature and wind speed) and physical (i.e. soil texture, elevation, topography, and land use) factors. Spatial variability of soil moisture affected by the meteorological forcing is shown as result of the relationship between the meteorological factors (precipitation, insolation, air temperature and ground temperature) and the standard deviation of relative difference of soil moisture contents (SDRDt) which implied the spatial variability of soil moisture. The SDRDt showed a positive relationship with the daily mean precipitation, while a negative relationship with insolation, air temperature and ground temperature. The variation of spatial soil moisture pattern is more sensitive to change in ground temperature rather than air temperature changes. Therefore, spatial variability of soil moisture is greatly affected by meteorological factors and each of the meteorological factors has certain duration of effect on soil moisture spatial variability in regional scale. The results provide an insight into the soil moisture spatio-temporal patterns affected by meteorological and physical factors simultaneously, as well as the design criteria of regional soil moisture monitoring network at regional scale.

Multiobjective Network Optimization for Soil Monitoring of the Loess Hilly Region in China

The soil monitoring network plays an important role in detecting the spatial distribution of soil attributes and facilitates sustainable land-use decision making. Reduced costs, higher speed, greater scope, and a loss of accuracy are necessary to design a regional monitoring network effectively. In this paper, we present a stochastic optimization design method for regional soil carbon and water content monitoring networks with a minimum sample size based on a modified particle swarm optimization algorithm equipped with multiobjective optimization technique. Our effort is to reconcile the conflicts between various objectives, that is, kriging variance, survey budget, spatial accessibility, spatial interval, and the amount of monitoring sites. We applied the method to optimize the soil monitoring networks in a semiarid loess hilly area located in northwest China. The results reveal that the proposed method is both effective and robust and outperforms the standard binary particle swarm optimization and spatial simulated annealing algorithm.

Fast increasing of surface ozone concentrations in Pearl River Delta characterized by a regional air quality monitoring network during 2006–2011

Based on the observation by a Regional Air Quality Monitoring Network including 16 monitoring stations, temporal and spatial variations of ozone (O3), NO2 and total oxidant (Ox) were analyzed by both linear regression and cluster analysis. A fast increase of regional O3 concentrations of 0.86 ppbV/yr was found for the annual averaged values from 2006 to 2011 in Guangdong, China. Such fast O3 increase is accompanied by a correspondingly fast NOx reduction as indicated by a fast NO2 reduction rate of 0.61 ppbV/yr. Based on a cluster analysis, the monitoring stations were classified into two major categories – rural stations (non-urban) and suburban/urban stations. The O3 concentrations at rural stations were relatively conserved while those at suburban/urban stations showed a fast increase rate of 2.0 ppbV/yr accompanied by a NO2 reduction rate of 1.2 ppbV/yr. Moreover, a rapid increase of the averaged O3 concentrations in springtime (13%/yr referred to 2006 level) was observed, which may result from the increase of solar duration, reduction of precipitation in Guangdong and transport from Eastern Central China. Application of smog production algorithm showed that the photochemical O3 production is mainly volatile organic compounds (VOC)-controlled. However, the photochemical O3 production is sensitive to both NOx and VOC for O3 pollution episode. Accordingly, it is expected that a combined NOx and VOC reduction will be helpful for the reduction of the O3 pollution episodes in Pearl River Delta while stringent VOC emission control is in general required for the regional O3 pollution control.

PRESAXIO regional air quality modelling system: validation and applications

Different operational air quality forecasts (ESSEM Cost Action 0602) are currently available in Europe. However, most of them are not suitable for regional application and, also, their coarse outputs do not fit well with air quality management needs. In this work, PRESAXIO regional air quality modelling system is validated and applied over Galicia (NW of Spain), including WRF and CHIMERE models. WRF validation is done by comparison with surface meteorological measurements; CHIMERE validation applies DELTA tool with AirBase data. PRESAXIO applications include an operational air quality forecast, design of a regional air quality monitoring network, and impact assessment of EMEP emissions changes in regional O 3 peaks.

Моніторинг якості вод басейнової геосистеми Полтви

The tasks of hydroecological monitoring of river-basin system have been justified. The analysis of the system of the monitoring studies in Poltva river basin has been made. The main problems in the functioning of the regional monitoring network have been determined. Key words: hydroecological monitoring, river-basin system, water quality.

A global assessment of precipitation chemistry and deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus

A global assessment of precipitation chemistry and deposition has been carried out under the direction of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) Scientific Advisory Group for Precipitation Chemistry (SAG-PC). The assessment addressed three questions: (1) what do measurements and model estimates of precipitation chemistry and wet, dry and total deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity, and phosphorus show globally and regionally? (2) has the wet deposition of major ions changed since 2000 (and, where information and data are available, since 1990) and (3) what are the major gaps and uncertainties in our knowledge? To that end, regionally-representative measurements for two 3-year-averaging periods, 2000–2002 and 2005–2007, were compiled worldwide. Data from the 2000–2002 averaging period were combined with 2001 ensemble-mean modeling results from 21 global chemical transport models produced in Phase 1 of the Coordinated Model Studies Activities of the Task Force on Hemispheric Transport of Air Pollution (TF HTAP). The measurement data and modeling results were used to generate global and regional maps of major ion concentrations in precipitation and deposition. A major product of the assessment is a database of quality assured ion concentration and wet deposition data gathered from regional and national monitoring networks. The database is available for download from the World Data Centre for Precipitation Chemistry (http://wdcpc.org/). The assessment concludes that global concentrations and deposition of sulfur and nitrogen are reasonably well characterized with levels generally highest near emission sources and more than an order of magnitude lower in areas largely free of anthropogenic influences. In many parts of the world, wet deposition of reduced nitrogen exceeds that of oxidized nitrogen and is increasing. Sulfur and nitrogen concentrations and deposition in North America and Europe have declined significantly in line with emission reduction policies. Major regions of the world, including South America, the more remote areas of North America, much of Asia, Africa, Oceania, polar regions, and all of the oceans, are inadequately sampled for all of the major ions in wet and dry deposition, and particularly so for phosphorus, organic forms of nitrogen, and weak acids including carbonates and organic acids. Measurement-based inferential estimates of dry deposition are limited to sulfur and some nitrogen in only a few regions of the world and methods are highly uncertain. The assessment concludes with recommendations to address major gaps and uncertainties in global ion concentration and deposition measurements.

Identifying influencing wells for gradient estimation in the confined portion of the Gulf Coast aquifer near Kingsville, TX

Hydraulic gradient is a fundamental aquifer characteristic required to estimate groundwater flow and quantify advective fluxes of pollutants. Graphical and local estimation schemes using potentiometric head information from three or four wells are used to compute hydraulic gradients but suffer from imprecision and subjectivity. The use of linear regression is recommended when hydraulic head data from a groundwater monitoring network consisting of several wells are available. In such cases, statistical influence analysis can be carried out to evaluate how each well within the network impacts the gradient estimate. A suite of five metrics, namely—(1) the hat-values, (2) studentized residuals, (3) Cook’s distance, (4) DFBETAs and (5) Covariance ratio (COVRATIO) are used in this study to identify influential wells within a regional groundwater monitoring network in Kleberg County, TX. The hat-values indicated that the groundwater network was reasonably well balanced and no well exerted an undue influence on the regression. The studentized residuals and Cook’s distance indicated the wells with the highest influence on the regression predictions were those that were close to high groundwater production centers or affected by coastal-aquifer interactions. However, the wells in the proximity of the production centers had the highest impact on the estimated gradient values as ascertained using DFBETAs. The covariance ratio which indicates the sensitivity of a monitoring well on the estimated standard error of regression was noted to be significant at most wells within the network. Therefore, networks seeking to address changes in groundwater gradients due to climate and anthropogenic influences need to be denser than those used to ascertain synoptic gradient estimates alone. The magnitude of the groundwater velocity was greatly underestimated when the influential wells were excluded from the network. The direction of flow was affected to a lesser extent, but a complete gradient reversal was noted when the network consisted of only four peripheral wells. The influence analysis therefore provides a valuable tool to assess the importance of individual wells within a monitoring network and can therefore be useful when existing networks are to be pruned due to fiscal constraints.