A multi-objective assessment of an air quality monitoring network using environmental,economic, and social indicators and GIS-based models

In the United States, air pollution is primarily measured by Air Quality Monitoring Networks (AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns, protecting the public health, and determining compliance with air quality standards. In 2006, the U.S. Environmental Protection Agency issued a directive that air pollution agencies assess the performance of their AQMNs. Although various methods to design and assess AQMNs exist, here we demonstrate a geographic information system (GIS)-based approach that combines environmental, economic, and social indicators through the assessment of the ozone (O₃) and particulate matter (PM10) networks in Maricopa County, Arizona. The assessment was conducted in three phases: (1) to evaluate the performance of the existing networks, (2) to identify areas that would benefit from the addition of new monitoring stations, and (3) to recommend changes to the AQMN. A comprehensive set of indicators was created for evaluating differing aspects of the AQMNs’ objectives, and weights were applied to emphasize important indicators. Indicators were also classified according to their sustainable development goal. Our results showed that O₃ was well represented in the county with some redundancy in terms of the urban monitors. The addition of weights to the indicators only had a minimal effect on the results. For O₃, urban monitors had greater social scores, while rural monitors had greater environmental scores. The results did not suggest a need for adding more O₃ monitoring sites. For PM10, clustered urban monitors were redundant, and weights also had a minimal effect on the results. The clustered urban monitors had overall low scores; sites near point sources had high environmental scores. Several areas were identified as needing additional PM10 monitors. This study demonstrates the usefulness of a multi-indicator approach to assess AQMNs. Network managers and planners may use this method to assess the performance of air quality monitoring networks in urban regions.

Implications:The U.S. Environmental Protection Agency issued a directive in 2006 that air pollution agencies assess the performance of their AQMNs; as a result, we developed a GIS-based, multi-objective assessment approach that integrates environmental, economic, and social indicators, and demonstrates its use through assessing the O₃ and PM₁₀ monitoring networks in the Phoenix metropolitan area. We exhibit a method of assessing network performance and identifying areas that would benefit from new monitoring stations; also, we demonstrate the effect of adding weights to the indicators. Our study shows that using a multi-indicator approach gave detailed assessment results for the Phoenix AQMN.     

Long-term trends in airborne SO2 in an air quality monitoring station in Seoul,Korea, from 1987 to 2013

Atmospheric concentration of sulfur dioxide (SO₂) was intermittently measured at an air quality monitoring (AQM) station in the Yong-san district of Seoul, Korea, between 1987 and 2013. The SO₂ level was compared with other important pollutants concurrently measured, including methane (CH₄), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), ozone (O₃), and particulate matter (PM₁₀). If split into three different periods (period 1, 1987–1988, period 2, 1999–2000, and period 3, 2004–2013), the respective mean [SO₂] values (6.57 ± 4.29, 6.30 ± 2.44, and 5.29 ± 0.63 ppb) showed a slight reduction across the entire study period. The concentrations of SO₂ are found to be strongly correlated with other pollutants such as CO (r = 0.614, p = 0.02), which tracked reductions in reported emissions due to tighter emissions standards enacted by the South Korean government. There was also a clear seasonal trend in the SO₂ level, especially in periods 2 and 3, reflecting the combined effects of domestic heating by coal briquettes and meteorological conditions. Although only a 16% concentration reduction was achieved during the 27-year study duration, this is significant if one considers rapid urbanization, an 83.2% increase in population, and rapid industrialization that took place during that period.

Implications: Since 1970, a network of air quality monitoring (AQM) stations has been operated by the Korean Ministry of Environment (KMOE) for routine nationwide monitoring of air pollutant concentrations in urban/suburban areas. To date, the information obtained from these stations has provided a platform for analyzing long-term trends of major pollutant species. In this study, we examined the long-term trends of SO₂ levels and relevant environmental parameters monitored continuously in the Yong-san district of Seoul between 1987 and 2013. The data were analyzed over various time scales (i.e., monthly, seasonal, and annual intervals). The results obtained from this study will allow us to assess the effectiveness of abatement strategy and to predict future concentrations trends in association with future abatement strategies and technologies.     

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial,California, USA

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R² for converted hourly averaged Dylos mass measurements versus a PM_2.5 BAM was 0.79 and that versus a PM₁₀ BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM_2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R² = 0.35–0.81).

Implications: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.     

Removal of SO2 from flue gas using blast furnace dust as an adsorbent

Environmental Science and Pollution Research - To control the SO2 emission and achieve the target of “waste controlled by waste”, a novel desulfurization method with blast furnace dust...     

Carbon catalysis in the aqueous oxidation of SO2 by NO2 and air

Sulfur Dioxide and an oxidant gas — air or NO₂ — were bubbled through aqueous suspensions of both washed and unwashed carbon black as well as through samples of wash water, which contained whatever soluble species were originally present on the carbon, and high-purity water. The sulfate yields obtained showed the washed and unwashed carbon to be equally catalytic for the oxidation of SO₂ to sulfate by both oxidants whereas little sulfate was generated in either the wash water or high-purity water in the absence of carbon. These results indicate that the sulfate yields produced in aqueous suspensions of the carbon studied are due to catalysis by the carbon particles rather than by soluble species dissolved from them.     

再生水补水人工湖水域聚类划分及水质指标时空分布特征

以天津临港生态湿地公园人工湖水质和水文的调查数据为依据,运用相关性分析和聚类分析将研究水体划分为3类水域。研究了不同聚类水域水温、DO、pH、氮磷营养元素以及Chla的时空分布特征。结果显示,DO、硝态氮、TN、TP与流速呈显著正相关,水温、SS与流速呈显著负相关。Chla与水深呈显著正相关,TN、硝态氮与水深呈显著负相关。断面宽度与所有理化指标均没有显著相关性。3种水域在监测期间N/P比(TN/TP)显示湖泊正在从氮营养元素限制型(N/P<7)向适宜藻类生长的营养类型过渡。富营养化评价显示,再生水为补水的临港人工湖在监测期间水质已处于中度富营养,主要贡献因子为COD和TP。     

Evaluation of air quality by passive and active sampling in an urban city in Turkey: current status and spatial analysis of air pollution exposure

Concentrations of air pollutants, nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ozone (O(3)), particulate matter (PM(2.5) and PM(10)), trace metals, and polycyclic aromatic hydrocarbons (PAHs) were measured in 2008 and 2009 in the city of Eski?ehir, central Turkey. Spatial distributions of NO(2), SO(2), and ozone were determined by passive sampling campaigns carried out during two different seasons with fairly large spatial coverage. A basic population exposure assessment was carried out employing Geographical Information System techniques by combining population density maps with pollutant distribution maps of NO(2) and SO(2). It was found that 95 % of the population is exposed to NO(2) levels close to the World Health Organization guideline value. Regarding SO(2), a large proportion of the population (83 %) is exposed to levels above the WHO second interim target value. Concentrations of all the pollutants showed a seasonal pattern increasing in winter period, except for ozone having higher concentrations in summer season. Daily PM(10) and PM(2.5) concentrations exceeded European Union limit values almost every sampling day. Toxic fractions of the measured PAHs were calculated and approximately fourfold increase was observed in winter period. Copper, Pb, Sn, As, Cd, Zn, Sb, and Se were found to be moderately to highly enriched in PM(10) fraction, indicating anthropogenic input to those elements measured. Exposure assessment results indicate the need for action to reduce pollutant emissions especially in the city center. Passive sampling turns out to be a practical and economical tool for air quality assessment with large spatial coverage.     

Analysis of temporal and spatial dichotomous PM air samples in the El Paso-Cd. Juarez air quality basin.

This paper presents and discusses the results obtained from the gravimetric and chemical analyses of the 24-hr average dichotomous samples collected from five sites in the El Paso-Cd. Juarez air quality basin between August 1999 and March 2000. Gravimetric analysis was performed to determine the temporal and spatial variations of PM2.5 (particulate matter less than 2.5 microm in diameter) and PM25-10 (particulate matter less than 10 pm but greater than 2.5 microm in diameter) mass concentrations. The results indicate that approximately 25% of the PM10 (i.e., PM25 + PM25-10) concentration is composed of PM2.5. Concurrent measurements of hourly PM concentrations and wind speed showed strong diurnal patterns of the regional PM pollution. Results of X-ray fluorescence (XRF) elemental analyses were compared to similar but limited studies performed by the Texas Natural Resource Conservation Commission (TNRCC) in 1990 and 1997. Major elements from geologic sources-Al, Si, Ca, Na, K, Fe, and Ti-accounted for 35% of the total mass concentrations in the PM2.5-10 fraction, indicating that geologic sources in the area are the dominant PM sources. Levels of toxic trace elements, mainly considered as products of anthropogenic activities, have decreased significantly from those observed in 1990 and 1997.     

Control of ozone precursors in a complex industrial terrain by using multiscale-nested air quality models with fine spatial resolution (1 km2)

The location of the northeastern Iberian Peninsula (NEIP) in the northwestern Mediterranean basin, the presence of the Pyrenees mountain range (with altitudes > 3000 m), and the influence of the Mediterranean Sea and the large valley canalization of Ebro river induce an extremely complicated structure for the dispersion of photochemical pollutants. Air pollution studies in very complex terrains such as the NEIP require high-resolution modeling for resolving the very complex dynamics of flows. To deal with the influence of larger-scale transport, however, high-resolution models have to be nested in larger models to generate appropriate initial and boundary conditions for the finer resolution domains. This article shows the results obtained through the utilization of the MM5-EMICAT2000-CMAQ multiscale-nested air quality model relating the sensitivity regimes for ozone (O3)-nitrogen oxides (NOx)-volatile organic compounds (VOCs) in an area of high geographical complexity, like the industrial area of Tarragona, located in the NEIP. The model was applied with fine temporal (one-hour) and spatial resolution (cells of 24 km, 2 km, and 1 km) to represent the chemistry and transport of tropospheric O3 and other photochemical species with respect to different hypothetical scenarios of emission controls and to quantify the influence of different emission sources in the area. Results indicate that O3 chemistry in the industrial domain of Tarragona is strongly sensitive to VOCs; the higher percentages of reduction for ground-level O3 are achieved when reducing by 25% the emissions of industrial VOCs. On the contrary, reductions in the industrial emissions of NOx contribute to a strong increase in hourly peak levels of O3. At the same time, the contribution of on-road traffic and biogenic emissions to ground-level O3 concentrations in the area is negligible with respect to the pervasive weight of industrial sources. This analysis provides an assessment of the effectiveness of different policies for the control of emission of precursors by comparing the modeled results for different scenarios.     

GIS-based air quality modelling: spatial prediction of PM10 for Selangor State,Malaysia using machine learning algorithms

Environmental Science and Pollution Research - Rapid urbanization has caused severe deterioration of air quality globally, leading to increased hospitalization and premature deaths. Therefore,...     

A prediction-based approach to modelling temporal and spatial variability of traffic-related air pollution in Montreal, Canada

Concentrations of traffic-related air pollution can be highly variable at the local scale and can have substantial seasonal variability. This study was designed to provide estimates of intra-urban concentrations of ambient nitrogen dioxide (NO₂) in Montreal, Canada, that would be used subsequently in health studies of chronic diseases and long-term exposures to traffic-related air pollution. We measured concentrations of NO₂ at 133 locations in Montreal with passive diffusion samplers in three seasons during 2005 and 2006. We then used land use regression, a proven statistical prediction method for describing spatial patterns of air pollution, to develop separate estimates of spatial variability across the city by regressing NO₂ against available land-use variables in each of these three periods. We also developed a “pooled” model across these sampling periods to provide an estimate of an annual average. Our modelling strategy was to develop a predictive model that maximized the model R². This strategy is different from other strategies whose goal is to identify causal relationships between predictors and concentrations of NO₂.Observed concentrations of NO₂ ranged from 2.6 ppb to 31.5 ppb, with mean values of 12.6 ppb in December 2005, 14.0 ppb in May 2006, and 8.9 ppb in August 2006. The greatest variability was observed during May. Concentrations of NO₂ were highest downtown and near major highways, and they were lowest in the western part of the city. Our pooled model explained approximately 80% of the variability in concentrations of NO₂. Although there were differences in concentrations of NO₂ between the three sampling periods, we found that the spatial variability did not vary significantly across the three sampling periods and that the pooled model was representative of mean annual spatial patterns.     

Statistical and diagnostic evaluation of the ADMS-Urban model compared with an urban air quality monitoring network

The present study examines the behaviour of the ADMS-Urban air quality forecasting model in predicting dispersion of traffic-related pollutants in urban areas. The study has been carried out in Ravenna (NE Italy), a medium-sized town where pollution produced by vehicle traffic accounts for most of the emissions. ADMS-Urban performances have been assessed through statistical analysis, by comparing carbon monoxide concentrations (vehicle traffic tracing pollutant) estimated by the model with concentrations measured by stations of the air quality monitoring network. Although the correspondence of values estimated by ADMS-Urban with measured values turns out to be satisfactory, the study shows that the model tends to produce an underestimated value compared with the actual situation, and identifies a corrective method that makes it possible to improve the relevant performances. Furthermore, the diagnostic analysis highlights that the model performances depend upon some meteorological parameters.     

Analysis of air quality within a street canyon using statistical and dispersion modelling techniques

The dispersion model, ADMS-Urban, alongside the statistical modelling technique, generalized additive modelling, have been used to predict hourly NO_x and nitrogen dioxide (NO₂) concentrations at a busy street canyon location and the results compared with measurements. Generalized additive models (GAMs) were constructed for NO₂ and NO_x concentrations using input data required to run ADMS-Urban. Bivariate polar plots have been produced from the wind flow (speed and direction) and pollution data (measured and predicted concentrations) to provide further information regarding the complex wind-pollutant interactions in an urban street canyon. The predictions made with the GAMs show excellent agreement with measured concentrations at this location, reproducing both the magnitude of NO_x and NO₂ concentrations and also the wind speed-wind direction dependence of pollutant sources within the canyon. However, the predictions made with ADMS-Urban under-estimated the measured NO_x by 11% and NO₂ by 21% and there are clear differences in the bivariate polar plots. Several sensitivity tests were carried out with ADMS-Urban in an attempt to produce predictions in closer agreement to those measured at Gillygate. Increasing the primary NO₂ fraction in ADMS-Urban (from 10% to 20%) had a considerable effect on the predictions made with this model, increasing NO₂ predictions by ∼20%. However, the bivariate plots still showed major differences to those of the measurements. This work illustrates that generalized additive modelling is a useful tool for investigating complex wind-pollutant interactions within a street canyon.     

Confidence limits for air quality model evaluations,as estimated by bootstrap and jackknife resampling methods

Air quality models are used to make decisions regarding the construction of industrial plants, the types of fuel that will be burnt and the types of pollution control devices that will be used. It is important to know the uncertainties that are associated with these model predictions. Standard analytical methods found in elementary statistics textbooks for estimating uncertainties are generally not applicable since the distributions of performance measures related to air quality concentrations are not easily transformed to a Gaussian shape. This paper suggests several possible resampling procedures that can be used to calculate uncertainties or confidence limits on air quality model performance. In these resampling methods, many new data sets are drawn from the original data set using an empirical set of rules. A few alternate forms of the socalled bootstrap and jackknife resampling procedures are tested using a concocted data set with a Gaussian parent distributions, with the result that the jackknife is the most efficient procedure to apply, although its confidence bounds are slightly overestimated. The resampling procedures are then applied to predictions by seven air quality models for the Carpinteria coastal dispersion experiment. Confidence intervals on the fractional mean bias and the normalized mean square error are calculated for each model and for differences between models. It is concluded that these uncertainties are sometimes so large for data sets consisting of about 20 elements that it cannot be stated with 95% confidence that the performance measure for the ‘best’ model is significantly different from that for another model.     

Simultaneous sampling of NH3, HNO3, HC1, SO2 and H2O2 in ambient air by a wet annular denuder system

A new sampling device is described for the simultaneous collection of NH₃, HNO₃, HCl, SO₂ and H₂O₂ in ambient air. The apparatus is based on air sampling by two parallel annular denuder tubes. The gases are collected by absorption in solutions present in the annulus of the denuder tubes. After a sampling time of 30 min at flow rate of 32 ℓ min⁻¹ the solutions are extracted from the denuders and analyzed off-line. The detection limits of NH₃, HNO₃, HCL and SO₂ are in the order of 0.1–0.5 μm⁻³. For H₂O₂ the detection limit is 0.01 μm⁻³. The reproducibility is 5–10% at the level of ambient air concentrations. Comparison of this novel technique with existing methods gives satisfactory results. The compact set-up offers the possibility of field experiments without the need of extensive equipment.     

Assessing seasonal and spatial trends of persistent organic pollutants (POPs) in Indian agricultural regions using PUF disk passive air samplers

The first survey of persistent organic pollutant (POP) concentrations in air across several Indian agricultural regions was conducted in 2006-2007. Passive samplers comprising polyurethane foam (PUF) disks were deployed on a quarterly basis at seven stations in agricultural regions, one urban site and one background site. The project was conducted as a sub-project of the Global Atmospheric Passive Sampling (GAPS) Network. In addition to revealing new information on air concentrations of several organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs), the study has demonstrated the feasibility of conducting regional-scale monitoring for POPs in India using PUF disk samplers. The following analytes were detected with relatively high concentrations in air (mean for 2006 and 2007, pg/m³): α- and γ-hexachlorocyclohexane (HCH) (292 and 812, respectively); endosulfan I and II (2770 and 902, respectively); p,p′-DDE and p,p′-DDT (247 and 931, respectively); and for the sum of 48 PCBs, 12,100 (including a site with extremely high air concentrations in 2007) and 972 (when excluding data for this site).     

Assessment of emissions data for the Toronto region using aircraft-based measurements and an air quality model

An aircraft-based measurement campaign was conducted during the summer of 1996 in the vicinity of Toronto, Canada. The objective of the campaign was to assess the errors in a particular emission inventory used by three-dimensional air quality models. Measurements of NO₂ and hydrocarbons were made both upwind and downwind of Toronto, on days with strong synoptic-scale flow from a west to northerly direction. The chemical composition of the background airmass on these days was typical of unpolluted continental air. Measurements have been compared with the output from an on-line air quality model (MC2-AQ) run at 5 km resolution and suggest that emissions of NO_x from Toronto are well described in the emission database, though evidence that NO_x emissions are underestimated for suburban regions surrounding Toronto was found. In general, no significant underestimation of hydrocarbon emissions was found, though emissions of the model propane species, which includes acetylene and benzene, was underestimated by at least a factor of two.     

Ammonia emission, deposition and impact assessment at the field scale: a case study of sub-grid spatial variability

A local ammonia (NH3) inventory for a 5x5 km area in central England was developed, to investigate the variability of emissions, deposition and impacts of NH3 at a field scale, as well as to assess the validity of the UK 5-km grid inventory. Input data were available for the study area for 1993 and 1996 on a field by field basis, allowing NH3 emissions to be calculated for each individual field, separately for livestock grazing, livestock housing and manure storage, landspreading of manures and fertiliser N application to crops and grassland. An existing atmospheric transport model was modified and applied to model air concentrations and deposition of NH3 at a fine spatial resolution (50 m grid). From the mapped deposition estimates and land cover information, critical loads and exceedances were derived. to study the implications of local variability for regional NH3 impacts assessments. The results show that the most extreme local variability in NH3 emissions, deposition and impacts is linked to housing and storage losses. However, landspreading of manures and intensive cattle grazing are other important area sources, which vary substantially in the landscape. Overall, the range of predicted emissions from agricultural land within the study area is 0-2000 kg N ha(-1) year(-1) in 1993 and 0-8000 kg N ha(-1) year(-1) in 1996, respectively, with the peak at a poultry farm located in the study area. On average, the estimated field level NH3 emissions over the study area closely match the emission for the equivalent 5-km grid square in the national inventory for 1996. Deposition and expected impacts are highly spatially variable, with the edges of woodland and small "islands" of semi-natural vegetation in intensive agricultural areas being most at risk from enhanced deposition. Conversely the centres of larger nature reserves receive less deposition than average. As a consequence of this local variability it is concluded that national assessments at the 5 km grid level underestimate the occurrence of critical loads exceedances due to NH3 in agricultural landscapes.