A review of polychlorinated biphenyls (PCBs) pollution in indoor air environment

Polychlorinated biphenyls (PCBs) were widely used in industrial production due to the unique physical and chemical properties. As a kind of persistent organic pollutants, the PCBs would lead to environment pollution and cause serious problems for human health. Thus, they have been banned since the 1980s due to the environment pollution in the past years. Indoor air is the most direct and important environment medium to human beings; thus, the PCBs pollution research in indoor air is important for the protection of human health. This paper introduces the industrial application and potential harm of PCBs, summarizes the sampling, extracting, and analytical methods of environment monitoring, and compares the indoor air levels of urban areas with those of industrial areas in different countries according to various reports. This paper can provide a basic summary for PCBs pollution control in the indoor air environment.

Implications: The review of PCBs pollution in indoor air in China is still limited. In this paper, we introduce the industrial application and potential harm of PCBs, summarize the sampling, extracting, and analytical methods of environment monitoring, and compare the indoor air levels of urban areas with industrial areas in different countries according to various reports.     

The influence of wind speed on airflow and fine particle transport within different building layouts of an industrial city

In atmospheric environment, the layout difference of urban buildings has a powerful influence on accelerating or inhibiting the dispersion of particle matters (PM). In industrial cities, buildings of variable heights can obstruct the diffusion of PM from industrial stacks. In this study, PM dispersed within building groups was simulated by Reynolds-averaged Navier-Stokes equations coupled Lagrangian approach. Four typical street building arrangements were used: (a) a low-rise building block with Height/base H/b = 1 (b = 20 m); (b) step-up building layout (H/b = 1, 2, 3, 4); (c) step-down building layout (H/b = 4, 3, 2, 1); (d) high-rise building block (H/b = 5). Profiles of stream functions and turbulence intensity were used to examine the effect of various building layouts on atmospheric airflow. Here, concepts of particle suspension fraction and concentration distribution were used to evaluate the effect of wind speed on fine particle transport. These parameters showed that step-up building layouts accelerated top airflow and diffused more particles into street canyons, likely having adverse effects on resident health. In renewal old industry areas, the step-down building arrangement which can hinder PM dispersion from high-level stacks should be constructed preferentially. High turbulent intensity results in formation of a strong vortex that hinders particles into the street canyons. It is found that an increase in wind speed enhanced particle transport and reduced local particle concentrations, however, it did not affect the relative location of high particle concentration zones, which are related to building height and layout.

Implications: This study has demonstrated the height variation and layout of urban architecture affect the local concentration distribution of particulate matter (PM) in the atmosphere and for the first time that wind velocity has particular effects on PM transport in various building groups. The findings may have general implications in optimization the building layout based on particle transport characteristics during the renewal of industrial cities. For city planners, the results and conclusions are useful for improving the local air quality. The study method also can be used to calculate the explosion risk of industrial dust for people who live in industrial cities.     

Ambient air concentrations exceeded health-based standards for fine particulate matter and benzene during the Deepwater Horizon oil spill

The Deepwater Horizon oil spill is considered one of the largest marine oil spills in the history of the United States. Air emissions associated with the oil spill caused concern among residents of Southeast Louisiana. The purpose of this study was to assess ambient concentrations of benzene (n=3,887) and fine particulate matter (n=102,682) during the oil spill and to evaluate potential exposure disparities in the region. Benzene and fine particulate matter (PM2.5) concentrations in the targeted parishes were generally higher following the oil spill, as expected. Benzene concentrations reached 2 to 19 times higher than background, and daily exceedances of PM2.5 were 10 to 45 times higher than background. Both benzene and PM2.5 concentrations were considered high enough to exceed public health criteria, with measurable exposure disparities in the coastal areas closer to the spill and clean-up activities. These findings raise questions about public disclosure of environmental health risks associated with the oil spill. The findings also provide a science-based rationale for establishing health-based action levels in future disasters.

Implications: Benzene and particulate matter monitoring during the Deepwater Horizon oil spill revealed that ambient air quality was a likely threat to public health and that residents in coastal Louisiana experienced significantly greater exposures than urban residents. Threshold air pollution levels established for the oil spill apparently were not used as a basis for informing the public about these potential health impacts. Also, despite carrying out the most comprehensive air monitoring ever conducted in the region, none of the agencies involved provided integrated analysis of the data or conclusive statements about public health risk. Better information about real-time risk is needed in future environmental disasters.     

In-vehicle carbon dioxide concentration in commuting cars in Bangkok,Thailand

It is known that in-vehicle carbon dioxide (CO₂) concentration tends to increase due to occupant exhalation when the HVAC (heating, ventilation, and air conditioning) air is in recirculation mode. Field experiments were conducted to measure CO₂ concentration during typical commute in Bangkok, Thailand. The measured concentrations agreed with the concentration predicted using first-order mass balance equation, in both recirculating and outside air modes. The long-term transient decay of the concentration when the vehicle was parked and the HVAC system was turned off was also studied. This decay was found to follow Fickian diffusion process. The paper also provides useful operational details of the automotive HVAC system and fresh air ventilation exchange between cabin interior and exterior.

Implications: Drivers in tropical Asian countries typically use HVAC recirculation mode in their automobiles. This behavior leads to excessive buildup of cabin CO₂ concentration levels. The paper describes the CO₂ buildup in a typical commute in Bangkok, Thailand. Auto manufacturers can potentially take measures to alleviate such high concentration levels. The paper also discusses the diffusion of CO₂ through the vehicle envelope, an area that has never been investigated before.     

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.     

Emissions of organic compounds from produced water ponds II: Evaluation of flux chamber measurements with inverse-modeling techniques

In this study, the authors apply two different dispersion models to evaluate flux chamber measurements of emissions of 58 organic compounds, including C2–C11 hydrocarbons and methanol, ethanol, and isopropanol from oil- and gas-produced water ponds in the Uintah Basin. Field measurement campaigns using the flux chamber technique were performed at a limited number of produced water ponds in the basin throughout 2013–2016. Inverse-modeling results showed significantly higher emissions than were measured by the flux chamber. Discrepancies between the two methods vary across hydrocarbon compounds and are largest in alcohols due to their physical chemistries. This finding, in combination with findings in a related study using the WATER9 wastewater emission model, suggests that the flux chamber technique may underestimate organic compound emissions, especially alcohols, due to its limited coverage of the pond area and alteration of environmental conditions, especially wind speed. Comparisons of inverse-model estimations with flux chamber measurements varied significantly with the complexity of pond facilities and geometries. Both model results and flux chamber measurements suggest significant contributions from produced water ponds to total organic compound emission from oil and gas productions in the basin.

Implications: This research is a component of an extensive study that showed significant amount of hydrocarbon emissions from produced water ponds in the Uintah Basin, Utah. Such findings have important meanings to air quality management agencies in developing control strategies for air pollution in oil and gas fields, especially for the Uintah Basin in which ozone pollutions frequently occurred in winter seasons.     

Impacts of prescribed fires and benefits from their reduction for air quality,health, and visibility in the Pacific Northwest of the United States

Using a WRF-SMOKE-CMAQ modeling framework, we investigate the impacts of smoke from prescribed fires on model performance, regional and loc al air quality, health impacts, and visibility in protected natural environments using three different prescribed fire emission scenarios: 100% fire, no fire, and 30% fire. The 30% fire case reflects a 70% reduction in fire activities due to harvesting of logging residues for use as a feedstock for a potential aviation biofuel supply chain. Overall model performance improves for several performance metrics when fire emissions are included, especially for organic carbon, irrespective of the model goals and criteria used. This effect on model performance is more pronounced for the rural and remote IMPROVE sites for organic carbon and total PM_2.5. A reduction in prescribed fire emissions (30% fire case) results in significant improvement in air quality in areas in western Oregon, northern Idaho, and western Montana, where most prescribed fires occur. Prescribed burning contributes to visibility impairment, and a relatively large portion of protected class I areas will benefit from a reduced emission scenario. For the haziest 20% days, prescribed burning is an important source of visibility impairment, and approximately 50% of IMPROVE sites in the model domain show a significant improvement in visibility for the reduced fire case. Using BenMAP, a health impact assessment tool, we show that several hundred additional deaths, several thousand upper and lower respiratory symptom cases, several hundred bronchitis cases, and more than 35,000 workday losses can be attributed to prescribed fires, and these health impacts decrease by 25–30% when a 30% fire emission scenario is considered.

Implications: This study assesses the potential regional and local air quality, public health, and visibility impacts from prescribed burning activities, as well as benefits that can be achieved by a potential reduction in emissions for a scenario where biomass is harvested for conversion to biofuel. As prescribed burning activities become more frequent, they can be more detrimental for air quality and health. Forest residue-based biofuel industry can be source of cleaner fuel with co-benefits of improved air quality, reduction in health impacts, and improved visibility.     

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.     

BTEX exposures in an area impacted by industrial and mobile sources: Source attribution and impact of averaging time

The impacts of emissions plumes from major industrial sources on black carbon (BC) and BTEX (benzene, toluene, ethyl benzene, xylene isomers) exposures in communities located >10 km from the industrial source areas were identified with a combination of stationary measurements, source identification using positive matrix factorization (PMF), and dispersion modeling. The industrial emissions create multihour plume events of BC and BTEX at the measurement sites. PMF source apportionment, along with wind patterns, indicates that the observed pollutant plumes are the result of transport of industrial emissions under conditions of low boundary layer height. PMF indicates that industrial emissions contribute >50% of outdoor exposures of BC and BTEX species at the receptor sites. Dispersion modeling of BTEX emissions from known industrial sources predicts numerous overnight plumes and overall qualitative agreement with PMF analysis, but predicts industrial impacts at the measurement sites a factor of 10 lower than PMF. Nonetheless, exposures associated with pollutant plumes occur mostly at night, when residents are expected to be home but are perhaps unaware of the elevated exposure. Averaging data samples over long times typical of public health interventions (e.g., weekly or biweekly passive sampling) misapportions the exposure, reducing the impact of industrial plumes at the expense of traffic emissions, because the longer samples cannot resolve subdaily plumes. Suggestions are made for ways for future distributed pollutant mapping or intervention studies to incorporate high time resolution tools to better understand the potential impacts of industrial plumes.

Implications: Emissions from industrial or other stationary sources can dominate air toxics exposures in communities both near the source and in downwind areas in the form of multihour plume events. Common measurement strategies that use highly aggregated samples, such as weekly or biweekly averages, are insensitive to such plume events and can lead to significant under apportionment of exposures from these sources.     

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.     

NOx emission calculations for bulk carriers by using engine power probabilities as weighting factors

An important marine pollution issue identified by the International Maritime Organization (IMO) is NO_x emissions; however, the stipulated method for determining the NO_x certification value does not reflect the actual high emission factors of slow-speed two-stroke diesel engines over long-term slow steaming. In this study, an accurate method is presented for calculating the NO_x emission factors and total amount of NO_x emissions by using the actual power probabilities of the diesel engines in four types of bulk carriers. The proposed method is suitable for all types and purposes of diesel engines, is not restricted to any operating modes, and is highly accurate. Moreover, it is recommended that the IMO-stipulated certification value calculation method be modified accordingly to genuinely reduce the amount of NO_x emissions. The successful achievement of this level of reduction will help improve the air quality, especially in coastal and port areas, and the health of local residents.

Implications: As per the IMO, the NO_x emission certification value of marine diesel engines having a rated power over 130 kW must be obtained using specified weighting factor (WF)-based calculation. However, this calculation fails to represent the current actual situation. Effective emission reductions of 6.91% (at sea) and 31.9% (in ports) were achieved using a mathematical model of power probability functions. Thus, we strongly recommend amending the certification value of NO_x Technical Code 2008 (NTC 2008) by removing the WF constraints, such that the NO_x emissions of diesel engines is lower than the Tier-limits at any load level to obtain genuine NO_x emission reductions.     

The effects of deterioration and technological levels on pollutant emission factors for gasoline light-duty trucks

Vehicle deterioration and technological change influence emission factors (EFs). In this study, the impacts of vehicle deterioration and emission standards on EFs of regulated pollutants (carbon monoxide [CO], hydrocarbon [HC], and nitrogen oxides [NO_x]) for gasoline light-duty trucks (LDTs) were investigated according to the inspection and maintenance (I/M) data using a chassis dynamometer method. Pollutant EFs for LDTs markedly varied with accumulated mileages and emission standards, and the trends of EFs are associated with accumulated mileages. In addition, the study also found that in most cases, the median EFs of CO, HC, and NO_x are higher than those of basic EFs in the International Vehicle Emissions (IVE) model; therefore, the present study provides correction factors for the IVE model relative to the corresponding emission standards and mileages.

Implications: Currently, vehicle emissions are great contributors to air pollution in cities, especially in developing countries. Emission factors play a key role in creating emission inventory and estimating emissions. Deterioration represented by vehicle age and accumulated mileage and changes of emission standards markedly influence emission factors. In addition, the results provide collection factors for implication in the IVE model in the region levels.     

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.     

Development of operating mode distributions for different types of roadways under different congestion levels for vehicle emission assessment using MOVES

The Motor Vehicle Emission Simulator (MOVES) quantifies emissions as a function of vehicle modal activities. Hence, the vehicle operating mode distribution is the most vital input for running MOVES at the project level. The preparation of operating mode distributions requires significant efforts with respect to data collection and processing. This study is to develop operating mode distributions for both freeway and arterial facilities under different traffic conditions. For this purpose, in this study, we (1) collected/processed geographic information system (GIS) data, (2) developed a model of CO₂ emissions and congestion from observations, (3) implemented the model to evaluate potential emission changes from a hypothetical roadway accident scenario. This study presents a framework by which practitioners can assess emission levels in the development of different strategies for traffic management and congestion mitigation.

Implications: This paper prepared the primary input, that is, the operating mode ID distribution, required for running MOVES and developed models for estimating emissions for different types of roadways under different congestion levels. The results of this study will provide transportation planners or environmental analysts with the methods for qualitatively assessing the air quality impacts of different transportation operation and demand management strategies.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

On ground truth in cross-border ozone transport

Cross-border transport of ozone is one of the most contentious issues of air pollution management in the U.S. Yet, both the modeling and observational studies are lacking. Models are normally validated by comparing predicted and observed ozone concentrations. However, proper validation of cross-border transport model requires a comparison of predictions against observation-based benchmarks of cross-border ozone transport. Such benchmarks are unavailable, as published observation-based studies always deal only with a combination of local production and cross-border transport, not a cross-border transport itself. We show how to extract necessary benchmarks from observations of rural monitoring sites near state borders. On example of the western border of New York, we find that in about two-thirds of the most polluted days all the ozone came in a steady cross-border inflow after previously passing over one or more large urban areas to the west. In all the enumerated days with direct cross-border inflow, daily maximum 8-hr concentrations of ozone just upwind of the border were over 60 ppb, with an average value of 68 ppb, just short of the 70 ppb ozone regulatory threshold, information also useful to state air pollution authorities.

Implications: The purpose of the cross-border ozone pollution models is to predict cross-border transport of ozone, so the ability of the model to accurately represent observed ozone concentrations is necessary but not sufficient for model validation. The accuracy of predicted ozone concentrations is not necessarily the same as the accuracy of the predictions of ozone transport. Proper model validation requires comparisons against observation-based benchmarks of cross-border transport. Such observations, so far absent, can be obtained from rural monitoring sites near state borders, as illustrated by the example of western New York.     

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.     

The relationship between atmospheric pollutant emissions and fuel qualities of inland vessels in Jiangsu Province,China

Air pollution caused by ship exhaust emission is receiving more and more attention. The physical and chemical properties of fuels, such as sulfur content and PAHs content, potentially had a significant influence on air pollutant emissions from inland vessels. In order to investigate the effects of fuel qualities on atmospheric pollutant emissions systematically, a series of experiments was conducted based on the method of actual ship testing. As a result, SO2, PM and NOx emission rates all increased with the increase of main engine rotating speed under cruise mode, while PM and NOx emission factors were inversely proportional to the main engine rotating speed. Moreover, SO2 emission factor changed little with the increase of the main engine rotating speed. In summary, the fuel-dependent specific emission of SO2 was a direct reflection of the sulfur content in fuel. The PM emission increased with the increase of sulfur content and PAHs content in fuel. However, fuel qualities impacted little on NOx emissions from inland vessels because of NOx formation mechanisms and conditions.

Implications: Ship activity is considered to be the third largest source of air pollution in China. In particular, air pollutants emitted from ships in river ports and waterways have a direct impact on regional air quality and pose threat on the health of local residents owing to high pollutants concentration and poor air diffusion. The study on the relationship between air pollutant emissions and fuel quality of inland vessels can provide foundational data for local authority to formulate reasonable and appropriate policies for reducing atmospheric pollution due to inland vessels.