Analysis of air quality in Dire Dawa,Ethiopia

Ambient air quality was monitored and analyzed to develop air quality index and its implications for livability and climate change in Dire Dawa, Ethiopia. Using survey research design, 16 georeferenced locations, representing different land uses, were randomly selected and assessed for sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon dioxide (CO₂), carbon monoxide (CO),volatile organic compounds (VOCs), and meteorological parameters (temperature and relative humidity). The study found mean concentrations across all land uses for SO₂ of 0.37 ± 0.08 ppm, NO₂ of 0.13 ± 0.17 ppm, CO₂ of 465.65 ± 28.63 ppm, CO of 3.35 ± 2.04 ppm, and VOCs of 1850.67 ± 402 ppm. An air quality index indicated that ambient air quality for SO₂ was very poor, NO₂ ranged from moderate to very poor, whereas CO rating was moderate. Significant positive correlations existed between temperature and NO₂, CO₂, and CO and between humidity and VOCs. Significant relationships were also recorded between CO₂ and NO₂ and between CO and CO₂. Poor urban planning, inadequate pollution control measure, and weak capacity to monitor air quality have implications for energy usage, air quality, and local meteorological parameters, with subsequent feedback into global climate change. Implementation of programs to monitor and control emissions in order to reduce air pollution will provide health, economic, and environmental benefits to the city.

Implications: The need to develop and implement emission control programs to reduce air pollution in Dire Dawa City is urgent. This will provide enormous economic, health, and environmental benefits. It is expected that economic effects of air quality improvement will offset the expenditures for pollution control. Also, strategies that focus on air quality and climate change present a unique opportunity to engage different stakeholders in providing inclusive and sustainable development agenda for Dire Dawa.     

Air quality in Yanbu,Saudi Arabia

Yanbu, on the Red Sea, is an affluent Saudi Arabian industrial city of modest size. Substantial effort has been spent to balance environmental quality, especially air pollution, and industrial development. We have analyzed six years of observations of criteria pollutants O₃, SO₂, particles (PM_2.5 and PM₁₀) and the known ozone precursors—volatile organic compounds (VOCs) and nitrogen oxides (NO_x). The results suggest frequent VOC-limited conditions in which ozone concentrations increase with decreasing NO_x and with increasing VOCs when NO_x is plentiful. For the remaining circumstances ozone has a complex non-linear relationship with the VOCs. The interactions between these factors at Yanbu cause measurable impacts on air pollution including the weekend effect in which ozone concentrations stay the same or even increase despite significantly lower emissions of the precursors on the weekends. Air pollution was lower during the Eids (al-Fitr and al-Adha), Ramadan and the Hajj periods. During Ramadan, there were substantial night time emissions as the cycle everyday living is almost reversed between night and day. The exceedances of air pollution standards were evaluated using criteria from the U.S. Environmental Protection Agency (EPA), World Health Organization (WHO), the Saudi Presidency of Meteorology and Environment (PME) and the Royal Commission Environmental Regulations (RCER). The latter are stricter standards set just for Yanbu and Jubail. For the fine particles (PM_2.5), an analysis of the winds showed a major impact from desert dust. This effect had to be taken into account but still left many occasions when standards were exceeded. Fewer exceedances were found for SO₂, and fewer still for ozone. The paper presents a comprehensive view of air quality at this isolated desert urban environment.

Implications: Frequent VOC-limited conditions are found at Yanbu in Saudi Arabia that increase ozone pollution if NO_x is are reduced. In this desert environment, increased nightlife produces the highest levels of VOCs and NO_x at night rather than the day. The effects increase during Ramadan. Fine particles peak twice a day—the morning peak is caused by traffic and increases with decreasing wind, potentially representing health concerns, but the larger afternoon peak is caused by the wind, and it increases with increasing wind speeds. These features suggest that exposure to pollutants must be redefined for such an environment.     

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.     

Field evaluations of newly available “interference-free” monitors for nitrogen dioxide and ozone at near-road and conventional National Ambient Air Quality Standards compliance sites

Long-standing measurement techniques for determining ground-level ozone (O₃) and nitrogen dioxide (NO₂) are known to be biased by interfering compounds that result in overestimates of high O₃ and NO₂ ambient concentrations under conducive conditions. An increasing near-ground O₃ gradient (NGOG) with increasing height above ground level is also known to exist. Both the interference bias and NGOG were investigated by comparing data from a conventional Federal Equivalent Method (FEM) O₃ photometer and an identical monitor upgraded with an “interference-free” nitric oxide O₃ scrubber that alternatively sampled at 2 m and 6.2 m inlet heights above ground level (AGL). Intercomparison was also made between a conventional nitrogen oxide (NO_x) chemiluminescence Federal Reference Method (FRM) monitor and a new “direct-measure” NO₂ NO_x 405 nm photometer at a near-road air quality measurement site. Results indicate that the O₃ monitor with the upgraded scrubber recorded lower regulatory-oriented concentrations than the deployed conventional metal oxide–scrubbed monitor and that O₃ concentrations 6.2 m AGL were higher than concentrations 2.0 m AGL, the nominal nose height of outdoor populations. Also, a new direct-measure NO₂ photometer recorded generally lower NO₂ regulatory-oriented concentrations than the conventional FRM chemiluminescence monitor, reporting lower daily maximum hourly average concentrations than the conventional monitor about 3 of every 5 days.

Implications: Employing bias-prone instruments for measurement of ambient ozone or nitrogen dioxide from inlets at inappropriate heights above ground level may result in collection of positively biased data. This paper discusses tests of new regulatory instruments, recent developments in bias-free ozone and nitrogen dioxide measurement technology, and the presence/extent of a near-ground O₃ gradient (NGOG). Collection of unbiased monitor inlet height–appropriate data is crucial for determining accurate design values and meeting National Ambient Air Quality Standards.     

A comparison of hourly with annual air pollutant emissions: Implications for estimating acute exposure and public health risk

Health risks from air pollutants are evaluated by comparing chronic (i.e., an average over 1 yr or greater) or acute (typically 1-hr) exposure estimates with chemical- and duration-specific reference values or standards. When estimating long-term pollutant concentrations via exposure modeling, facility-level annual average emission rates are readily available as model inputs for most air pollutants. In contrast, there are far fewer facility-level hour-by-hour emission rates available for many of these same pollutants. In this report, we first analyze hour-by-hour emission rates for total reduced sulfur (TRS) compounds from eight kraft pulp mill operations. This data set is used to demonstrate discrepancies between estimating exposure based on a single TRS emission rate that has been calculated as the mean of all operating hours of the year, as opposed to reported hourly emission rates. A similar analysis is then performed using reported hourly emission rates for sulfur dioxide (SO₂) and oxides of nitrogen (NO_x) from three power generating units from a U.S. power plant. Results demonstrate greater variability at kraft pulp mill operations, with ratios of reported hourly to average hourly TRS emissions ranging from less than 1 to greater than 160 during routine facility operations. Thus, if fluctuations in hourly emission rates are not accounted for, over- or underestimates of hourly exposure, and thus acute health risk, may occur. In addition to this analysis, we also demonstrate an additional challenge when assessing health risk based on hourly exposures: the lack of human health reference values based on 1-hr exposures.

Implications: Largely due to the lack of reported hourly emission rate data for many air pollutants, an hourly average emission rate (calculated from an annual emission rate) is often used when modeling the potential for acute health risk. We calculated ratios between reported hourly and hourly average emission rates from pulp and paper mills and a U.S. power plant to demonstrate that if not considered, hourly fluctuations in emissions could result in an over- or underestimation of exposure and risk. We also demonstrate the lack of 1-hr human health reference values meant to be protective of the general population, including children.     

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi,China

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM₁₀], sulfur dioxide [SO₂], and nitrogen oxides [NO_x]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants.

Implications: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality.

Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.     

Variability in the primary emissions and secondary gas and particle formation from vehicles using bioethanol mixtures

Bioethanol for use in vehicles is becoming a substantial part of global energy infrastructure because it is renewable and some emissions are reduced. Carbon monoxide (CO) emissions and total hydrocarbons (THC) are reduced, but there is still controversy regarding emissions of nitrogen oxides (NO_x), aldehydes, and ethanol; this may be a concern because all these compounds are precursors of ozone and secondary organic aerosol (SOA). The amount of emissions depends on the ethanol content, but it also may depend on the engine quality and ethanol origin. Thus, a photochemical chamber was used to study secondary gas and aerosol formation from two flex-fueled vehicles using different ethanol blends in gasoline. One vehicle and the fuel used were made in the United States, and the others were made in Brazil. Primary emissions of THC, CO, carbon dioxide (CO₂), and nonmethane hydrocarbons (NMHC) from both vehicles decreased as the amount of ethanol in gasoline increased. NO_x emissions in the U.S. and Brazilian cars decreased with ethanol content. However, emissions of THC, CO, and NO_x from the Brazilian car were markedly higher than those from the U.S. car, showing high variability between vehicle technologies. In the Brazilian car, formation of secondary nitrogen dioxide (NO₂) and ozone (O₃) was lower for higher ethanol content in the fuel. In the U.S. car, NO₂ and O₃ had a small increase. Secondary particle (particulate matter [PM]) formation in the chamber decreased for both vehicles as the fraction of ethanol in fuel increased, consistent with previous studies. Secondary to primary PM ratios for pure gasoline is 11, also consistent with previous studies. In addition, the time required to form secondary PM is longer for higher ethanol blends. These results indicate that using higher ethanol blends may have a positive impact on air quality.

Implications: The use of bioethanol can significantly reduce petroleum use and greenhouse gas emissions worldwide. Given the extent of its use, it is important to understand its effect on urban pollution. There is a controversy on whether there is a reduction or increase in PM emission when using ethanol blends. Primary emissions of THC, CO, CO₂, NO_x, and NMHC for both cars decreased as the fraction of ethanol in gasoline increased. Using a photochemical chamber, the authors have found a decrease in the formation of secondary particles and the time required to form secondary PM is longer when using higher ethanol blends.     

Assimilative capacity–based emission load management in a critically polluted industrial cluster

In the present study, a modified approach was adopted to quantify the assimilative capacity (i.e., the maximum emission an area can take without violating the permissible pollutant standards) of a major industrial cluster (Manali, India) and to assess the effectiveness of adopted air pollution control measures at the region. Seasonal analysis of assimilative capacity was carried out corresponding to critical, high, medium, and low pollution levels to know the best and worst conditions for industrial operations. Bottom-up approach was employed to quantify sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter (aerodynamic diameter <10 μm; PM₁₀) emissions at a fine spatial resolution of 500 × 500 m² in Manali industrial cluster. AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model), an U.S. Environmental Protection Agency (EPA) regulatory model, was used for estimating assimilative capacity. Results indicated that 22.8 tonnes/day of SO₂, 7.8 tonnes/day of NO₂, and 7.1 tonnes/day of PM₁₀ were emitted from the industries of Manali. The estimated assimilative capacities for SO₂, NO₂, and PM₁₀ were found to be 16.05, 17.36, and 19.78 tonnes/day, respectively. It was observed that the current SO₂ emissions were exceeding the estimated safe load by 6.7 tonnes/day, whereas PM₁₀ and NO₂ were within the safe limits. Seasonal analysis of assimilative capacity showed that post-monsoon had the lowest load-carrying capacity, followed by winter, summer, and monsoon seasons, and the allowable SO₂ emissions during post-monsoon and winter seasons were found to be 35% and 26% lower, respectively, when compared with monsoon season.

Implications: The authors present a modified approach for quantitative estimation of assimilative capacity of a critically polluted Indian industrial cluster. The authors developed a geo-coded fine-resolution PM₁₀, NO₂, and SO₂ emission inventory for Manali industrial area and further quantitatively estimated its season-wise assimilative capacities corresponding to various pollution levels. This quantitative representation of assimilative capacity (in terms of emissions), when compared with routine qualitative representation, provides better data for quantifying carrying capacity of an area. This information helps policy makers and regulatory authorities to develop an effective mitigation plan for air pollution abatement.     

Air quality mapping using GIS and economic evaluation of health impact for Mumbai City,India

Mumbai, a highly populated city in India, has been selected for air quality mapping and assessment of health impact using monitored air quality data. Air quality monitoring networks in Mumbai are operated by National Environment Engineering Research Institute (NEERI), Maharashtra Pollution Control Board (MPCB), and Brihanmumbai Municipal Corporation (BMC). A monitoring station represents air quality at a particular location, while we need spatial variation for air quality management. Here, air quality monitored data of NEERI and BMC were spatially interpolated using various inbuilt interpolation techniques of ArcGIS. Inverse distance weighting (IDW), Kriging (spherical and Gaussian), and spline techniques have been applied for spatial interpolation for this study. The interpolated results of air pollutants sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and suspended particulate matter (SPM) were compared with air quality data of MPCB in the same region. Comparison of results showed good agreement for predicted values using IDW and Kriging with observed data. Subsequently, health impact assessment of a ward was carried out based on total population of the ward and air quality monitored data within the ward. Finally, health cost within a ward was estimated on the basis of exposed population. This study helps to estimate the valuation of health damage due to air pollution.

Implications: Operating more air quality monitoring stations for measurement of air quality is highly resource intensive in terms of time and cost. The appropriate spatial interpolation techniques can be used to estimate concentration where air quality monitoring stations are not available. Further, health impact assessment for the population of the city and estimation of economic cost of health damage due to ambient air quality can help to make rational control strategies for environmental management. The total health cost for Mumbai city for the year 2012, with a population of 12.4 million, was estimated as USD8000 million.     

Quick vaporization of sprayed sodium hypochlorite (NaClO(aq)) for simultaneous removal of nitrogen oxides (NOx), sulfur dioxide (SO2), and mercury (Hg0)

Sodium hypochlorite (NaClO) has been widely used as a chemical additive for enhancing nitrogen oxide (NO_x; NO + NO₂), sulfur dioxide (SO₂), and mercury (Hg⁰) removals in a wet scrubber. However, they are each uniquely dependent on NaClO_(aq) pH, hence making the simultaneous control difficult. In order to overcome this weakness, we sprayed low liquid-to-gas (L/G) ratio (0.1 L/Nm³) of NaClO_(aq) to vaporize quickly at 165 °C. Results have shown that the maximized NO_x, SO₂, and Hg⁰ removals can be achieved at the pH range between 4.0 and 6.0. When NO_x and Hg⁰ coexist with SO₂, in addition, their removals are significantly enhanced by reactions with solid and gaseous by-products such as NaClO_(s), NaClO_2(s), OClO, ClO, and Cl species, originated from the reaction between SO₂ and NaClO_(aq). We have also demonstrated the feasibility of this approach in the real flue gases of a combustion plant and observed 50%, 80%, and 60% of NO_x, SO₂, and Hg⁰ removals, respectively. These findings led us to conclude that the spray of NaClO_(aq) at a relatively high temperature at which the sprayed solution can vaporize quickly makes the simultaneous control of NO_x, SO₂, and Hg⁰ possible.

Implications: The simple spray of NaClO_(aq) at temperatures above 165 °C can cause the simultaneous removal of gaseous NO_x, SO₂, and Hg⁰ by its quick vaporization. Their maximized removals are achieved at the pH range between 4.0 and 6.0. NO_x and Hg⁰ removals are also enhanced by gaseous and solid intermediate products generated from the reaction of SO₂ with NaClO_(aq). The feasibility of this approach has been demonstrated in the real flue gases of a combustion plant.     

Composition and secondary formation of fine particulate matter in the Salt Lake Valley: Winter 2009

Under the National Ambient Air Quality Standards (NAAQS), put in place as a result of the Clean Air Amendments of 1990, three regions in the state of Utah are in violation of the NAAQS for PM₁₀ and PM_2.5 (Salt Lake County, Ogden City, and Utah County). These regions are susceptible to strong inversions that can persist for days to weeks. This meteorology, coupled with the metropolitan nature of these regions, contributes to its violation of the NAAQS for PM during the winter. During January–February 2009, 1-hr averaged concentrations of PM_10-2.5, PM_2.5, NO_x, NO₂, NO, O₃, CO, and NH₃ were measured. Particulate-phase nitrate, nitrite, and sulfate and gas-phase HONO, HNO₃, and SO₂ were also measured on a 1-hr average basis. The results indicate that ammonium nitrate averages 40% of the total PM_2.5 mass in the absence of inversions and up to 69% during strong inversions. Also, the formation of ammonium nitrate is nitric acid limited. Overall, the lower boundary layer in the Salt Lake Valley appears to be oxidant and volatile organic carbon (VOC) limited with respect to ozone formation. The most effective way to reduce ammonium nitrate secondary particle formation during the inversions period is to reduce NO_x emissions. However, a decrease in NO_x will increase ozone concentrations. A better definition of the complete ozone isopleths would better inform this decision.

Implications: Monitoring of air pollution constituents in Salt Lake City, UT, during periods in which PM_2.5 concentrations exceeded the NAAQS, reveals that secondary aerosol formation for this region is NO_x limited. Therefore, NO_x emissions should be targeted in order to reduce secondary particle formation and PM_2.5. Data also indicate that the highest concentrations of sulfur dioxide are associated with winds from the north-northwest, the location of several small refineries.     

Probabilistic assessment of the potential indoor air impacts of vent-free gas heating appliances in energy-efficient homes in the United States

Use of vent-free gas heating appliances for supplemental heating in U.S. homes is increasing. However, there is currently a lack of information on the potential impact of these appliances on indoor air quality for homes constructed according to energy-efficient and green building standards. A probabilistic analysis was conducted to estimate the impact of vent-free gas heating appliances on indoor air concentrations of carbon monoxide (CO), nitrogen dioxide (NO₂), carbon dioxide (CO₂), water vapor, and oxygen in “tight” energy-efficient homes in the United States. A total of 20,000 simulations were conducted for each Department of Energy (DOE) heating region to capture a wide range of home sizes, appliance features, and conditions, by varying a number of parameters, e.g., room volume, house volume, outdoor humidity, air exchange rates, appliance input rates (Btu/hr), and house heat loss factors. Predicted airborne levels of CO were below the U.S. Environmental Protection Agency (EPA) standard of 9 ppm for all modeled cases. The airborne concentrations of NO₂ were below the U.S. Consumer Product Safety Commission (CPSC) guideline of 0.3 ppm and the Health Canada benchmark of 0.25 ppm in all cases and were below the World Health Organization (WHO) standard of 0.11 ppm in 99–100% of all cases. Predicted levels of CO₂ were below the Health Canada standard of 3500 ppm for all simulated cases. Oxygen levels in the room of vent-free heating appliance use were not significantly reduced. The great majority of cases in all DOE regions were associated with relative humidity (RH) levels from all indoor water vapor sources that were less than the EPA-recommended 70% RH maximum to avoid active mold and mildew growth. The conclusion of this investigation is that when installed in accordance with the manufacturer’s instructions, vent-free gas heating appliances maintain acceptable indoor air quality in tight energy-efficient homes, as defined by the standards referenced in this report.

Implications: Probabilistic modeling of indoor air concentrations of carbon monoxide (CO), nitrogen dioxide (NO₂), carbon dioxide (CO₂), water vapor, and oxygen associated with use of vent-free gas heating appliances provides new data indicating that uses of these devices are consistent with acceptable indoor air quality in “tight” energy-efficient homes in the United States. This study will provide authoritative bodies such as the International Code Council with definitive information that will assist in the development of future versions of national building codes, and will provide evaluation of the performance of unvented gas heating products in energy conservation homes.     

Synthesis and health-based evaluation of ambient air monitoring data for the Marcellus Shale region

In recent years, there has been a marked increase in the amount of ambient air quality data collected near Marcellus Shale oil and gas development (OGD) sites. We integrated air measurement data from over 30 datasets totaling approximately 200 sampling locations nearby to Marcellus Shale development sites, focusing on 11 air pollutants that can be associated with OGD operations: fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), acetaldehyde, benzene, ethylbenzene, formaldehyde, n-hexane, toluene, xylenes, and hydrogen sulfide (H₂S). We evaluated these data to determine whether there is evidence of community-level air quality impacts of potential health concern, making screening-level comparisons of air monitoring data with acute and chronic health-based air comparison values (HBACVs). Based on the available air monitoring data, we found that only a small fraction of measurements exceeded HBACVs, which is similar to findings from integrative air quality assessments for other shale gas plays. Therefore, the data indicate that air pollutant levels within the Marcellus Shale development region typically are below HBACV exceedance levels; however, the sporadic HBACV exceedances warrant further investigation to determine whether they may be related to specific site characteristics, or certain operations or sources. Like any air monitoring dataset, there is uncertainty as to how well the available Marcellus Shale air monitoring data characterize the range of potential exposures for people living nearby to OGD sites. Given the lesser amounts of air monitoring data available for locations within 1,000 feet of OGD sites as compared to locations between 0.2 and 1 miles, the presence of potential concentration hotspots cannot be ruled out. Additional air monitoring data, in particular more real-time data to further characterize short-term peak concentrations associated with episodic events, are needed to provide for more refined assessments of potential health risks from Marcellus Shale development.

Implications: While there is now a sizable amount of ambient air monitoring data collected nearby to OGD activities in the Marcellus Shale region, these data are currently scattered among different databases and studies. As part of an integrative assessment of Marcellus Shale air quality impacts, ambient air data are compiled for a subset of criteria air pollutants and hazardous air pollutants that have been associated with OGD activities, and compared to acute and chronic health-based air comparison values to help assess the air-related public health impacts of Marcellus Shale development.     

Detection of anomalous nitrogen dioxide (NO2) concentration in urban air of India using proximity and clustering methods

Owing to accurate future air quality estimates, need for detecting the anomalously high increase in concentration of pollutants cannot be adjourned. Plentiful approaches were proposed in the past to substantially determine the abnormal conditions, but most of the statistical approaches were computationally expensive and ignored the false alarm ratios. Thus, a hybrid of proximity- and clustering-based anomaly detection approaches to identify anomalies in the air quality data is suggested in this work. The Gaussian distribution property of the real-world data set is utilized further to segregate out anomalies. The results depicted twofold advantages of our approach, by efficient extraction of anomalies and with increased accuracy by reducing the number of false alarms. Specifically, the presence of NO₂ concentration in air is investigated in this work, considering its constant increase over decades as well as its inevitable health risks. Furthermore, spatiotemporal segments with anomalously high NO₂ concentrations for 14 residential, industrial, and commercial areas of five cities in India are extracted. To validate the results, a comparative analysis with existing approaches of anomaly detection and with two benchmark data sets is performed. Results showed that our method outperformed the existing methods of anomaly detection, when evaluated over metrics such as sensitivity, miss rate, and false alarms. Further, a detailed analysis of extracted anomalies and a detailed discussion about the factors responsible for such anomalies are presented in this work. This study is helpful in educating government and people about spatiotemporal, geographical, and economic conditions responsible for anomalously high NO₂ concentrations in air.

Implications: Using our methodology, days with extremely high concentration of any pollutant in air, at any particular location, can be extracted. The reasons for such extremely high pollutant concentration on particular days of a year can be studied and preventive measures can be taken by the government. Thus, by identification of causes of anomalies, future similar events can be avoided. This would also help in people’s decision making in case such events occur in the future.     

Air quality and health benefits from potential coal power plant closures in Texas

As power production from renewable energy and natural gas grows, closures of some coal-fired power plants in Texas become increasingly likely. In this study, the potential effects of such closures on air quality and human health were analyzed by linking a regional photochemical model with a health impacts assessment tool. The impacts varied significantly across 13 of the state’s largest coal-fired power plants, sometimes by more than an order of magnitude, even after normalizing by generation. While some power plants had negligible impacts on concentrations at important monitors, average impacts up to 0.5 parts per billion (ppb) and 0.2 µg/m³ and maximum impacts up to 3.3 ppb and 0.9 µg/m³ were seen for ozone and fine particulate matter (PM_2.5), respectively. Individual power plants impacted average visibility by up to 0.25 deciviews in Class I Areas. Health impacts arose mostly from PM_2.5 and were an order of magnitude higher for plants that lack scrubbers for SO₂. Rankings of health impacts were largely consistent across the base model results and two reduced form models. Carbon dioxide emissions were relatively uniform, ranging from 1.00 to 1.26 short tons/MWh, and can be monetized based on a social cost of carbon. Despite all of these unpaid externalities, estimated direct costs of each power plant exceeded wholesale power prices in 2016.

Implications: While their CO₂ emission rates are fairly similar, sharply different NO_x and SO₂ emission rates and spatial factors cause coal-fired power plants to vary by an order of magnitude in their impacts on ozone, particulate matter, and associated health and visibility outcomes. On a monetized basis, the air pollution health impacts often exceed the value of the electricity generated and are of similar magnitude to climate impacts. This suggests that both air pollution and climate should be considered if externalities are used to inform decision making about power-plant dispatch and retirement.     

Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formation

The U.S. Environmental Protection Agency (EPA), state and local agencies have focused their efforts in assessing secondary fine particulate matter (aerodynamic diameter ≤2.5 µm; PM_2.5) formation in prevention of significant deterioration (PSD) air dispersion modeling. The National Association of Clean Air Agencies (NACAA) developed a method to account for secondary PM_2.5 formation by using sulfur dioxide (SO₂) and nitrogen oxides (NO_x) offset ratios. These ratios are used to estimate the secondary formation of sulfate and nitrate PM_2.5. These ratios were first introduced by the EPA for nonattainment areas in the Implementation of the New Source Review (NSR) Program for Particulate Matter Less than 2.5 Micrometers (PM_2.5), 73 FR 28321, to offset emission increases of direct PM_2.5 emissions with reductions of PM_2.5 precursors and vice versa. Some regulatory agencies such as the Minnesota Pollution Control Agency (MPCA) have developed area-specific offset ratios for SO₂ and NO_x based on Comprehensive Air Quality Model with Extensions (CAMx) evaluations for air dispersion modeling analyses. The current study evaluates the effect on American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) predicted concentrations from the use of EPA and MPCA developed ratios. The study assesses the effect of these ratios on an electric generating utility (EGU), taconite mine, food processing plant, and a pulp and paper mill. The inputs used for these four scenarios are based on common stack parameters and emissions based on available data. The effect of background concentrations also evaluates these scenarios by presenting results based on uniform annual PM_2.5 background values. This evaluation study helps assess the viability of the offset ratio method developed by NACAA in estimating primary and secondary PM_2.5 concentrations. An alternative Tier 2 approach to combine modeled and monitored concentrations is also presented.

Implications:

On January 4, 2012, the EPA committed to engage in rulemaking to evaluate updates to the Guideline on Air Quality Models (Appendix W of 40 CFR 51) and, as appropriate, incorporate new analytical techniques or models for secondary PM_2.5. As a result, the National Association of Clean Air Agencies (NACAA) developed a screening method involving offset ratios to account for secondary PM_2.5 formation. The use of this method is promising to evaluate total (direct and indirect) PM_2.5 impacts for permitting purposes. Therefore, the evaluation of this method is important to determine its viability for widespread use.     

Evaluation of an explicit NOx chemistry method in AERMOD

An explicit NO_x chemistry method has been implemented in AERMOD version 15181, ADMSM. The scheme has been evaluated by comparison with the methodologies currently recommended by the U.S. EPA for Tier 3 NO₂ calculations, that is, OLM and PVMRM2. Four data sets have been used for NO₂ chemistry method evaluation. Overall, ADMSM-modeled NO₂ concentrations show the most consistency with the AERMOD calculations of NO_x and the highest Index of Agreement; they are also on average lower than those of both OLM and PVMRM2. OLM shows little consistency with modeled NO_x concentrations and markedly overpredicts NO₂. PVMRM2 shows performance closer to that of ADMSM than OLM; however, its behavior is inconsistent with modeled NO_x in some cases and it has less good statistics for NO₂. The trend in model performance can be explained by examining the features particular to each chemistry method: OLM can be considered as a screening model as it calculates the upper bound of conversion from NO to NO₂ possible with the background O₃ concentration; PVMRM2 includes a much-improved estimate of in-plume O₃ but is otherwise similar to OLM, assuming instantaneous reaction of NO with O₃; and ADMSM allows for the rate of this reaction and also the photolysis of NO₂. Evaluation with additional data sets is needed to further clarify the relative performance of ADMSM and PVMRM2.

Implications: Extensive evaluation of the current AERMOD Tier 3 chemistry methods OLM and PVMRM2, alongside a new scheme that explicitly calculates the oxidation of NO by O₃ and the reverse photolytic reaction, shows that OLM consistently overpredicts NO₂ concentrations. PVMRM2 performs well in general, but there are some cases where this method overpredicts NO₂. The new explicit NO_x chemistry scheme, ADMSM, predicts NO₂ concentrations that are more consistent with both the modeled NO_x concentrations and the observations.     

Air quality modeling for effective environmental management in the mining region

Air quality in the mining sector is a serious environmental concern and associated with many health issues. Air quality management in mining regions has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanisms. A modeling approach called the mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model takes into account the planet’s boundary conditions and assumes that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values for the predicted concentrations of PM₁₀, PM_2.5, TSP, NO₂, and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening in summer, and the minimum mixing height (380 m) is attained during the evening in winter. The dust fall (PM coarse) deposition flux is maximum during February and March with a deposition velocity of 4.67 cm/sec. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM_2.5, from 0.71 to 0.82 for PM₁₀, and from 0.71 to 0.89 for NO₂. The analyses illustrate that the presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. Comparisons of MADM and CALPUFF modeling values are made for four different pollutants (PM_2.5, PM₁₀, TSP, and NO₂) under three different atmospheric stability classes (stable, neutral, and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

Implications: The mathematical model (MADM) is developed by extending the Gaussian equation particularly when examining the settling process of important pollutants for the industrial region. Physical removal effects of air pollutants with field data have been considerred for the MADM development and for an extensive field case study. The model is well validated in the field of an open pit mine to assess the regional air quality. The MADA model helps to facilitate the management of the mining industry in doing estimation of emission rate around mining activities and predicting the resulted concentration of air pollutants together in one integrated approach.     

Total life cycle emissions of post-Panamax containerships powered by conventional fuel or natural gas

This study proposes an easy-to-apply method, the Total Life Cycle Emission Model (TLCEM), to calculate the total emissions from shipping and help ship management groups assess the impact on emissions caused by their capital investment or operation decisions. Using TLCEM, we present the total emissions of air pollutants and greenhouse gases (GHGs) during the 25-yr life cycle of 10 post-Panamax containerships under slow steaming conditions. The life cycle consists of steel production, shipbuilding, crude oil extraction and transportation, fuel refining, bunkering, and ship operation. We calculate total emissions from containerships and compare the effect of emission reduction by using various fuels. The results can be used to differentiate the emissions from various processes and to assess the effectiveness of various reduction approaches. Critical pollutants and GHGs emitted from each process are calculated. If the containerships use heavy fuel oil (HFO), emissions of CO₂ total 2.79 million tonnes (Mt), accounting for 95.37% of total emissions, followed by NO_x and SO_x emissions,which account for 2.25% and 1.30%, respectively.The most significant emissions are from the operation of the ship and originate from the main engine (ME).When fuel is switched to 100% natural gas (NG), SO_x, PM₁₀, and CO₂ emissions show remarkable reductions of 98.60%, 99.06%, and 21.70%, respectively. Determining the emission factor of each process is critical for estimating the total emissions. The estimated emission factors were compared with the values adopted by the International Maritime Organization (IMO).The proposed TLCEM may contribute to more accurate estimates of total life cycle emissions from global shipping.

Implications: We propose a total life cycle emissions model for 10 post-Panamax container ships. Using heavy fuel oil, emissions of CO₂ total 2.79 Mt, accounting for approximately 95% of emissions, followed by NO_x and SO_x emissions. Using 100% natural gas, SO_x, PM₁₀, and CO₂ emissions reduce by 98.6%, 99.1%, and 21.7%, respectively. NO_x emissions increase by 1.14% when running a dual fuel engine at low load in natural gas mode.