Major Source Of Air Pollution Research Articles

Simultaneous determination of carcinogenic PAHs and levoglucosan bound to PM2.5 for assessment of health risk and pollution sources during a smoke haze period

Carcinogenic polycyclic aromatic hydrocarbons (cPAHs) in ambient PM2.5 and a specific molecular marker of biomass burning, levoglucosan, are used to investigate the influence on public health of biomass burning. In this work, we present an effective method for one-time analysis of cPAHs and levoglucosan by GC-MS without derivatization. The method was applied for the analysis of PM2.5 samples (64.3 ± 17.6 μg m−3, n = 57) collected during a smoke haze period in Chiang Mai, Thailand. Levoglucosan was analyzed by using both the developed method (GC-MS) and a reference method (HPAEC-PAD) for comparison. Its average concentration obtained from GC-MS (0.31 ± 0.21 μg m−3) was about 4 times less than the concentration obtained from the reference method (1.22 ± 0.76 μg m−3). Therefore, a correcting factor (CF = 4) was used as a multiplying factor, to obtain a comparative value (1.23 ± 0.86 μg m−3). The average concentration of cPAHs found in PM2.5 samples was 5.88 ± 1.97 ng m−3 with the highest value of 10.86 ng m−3 indicating medium to high cancer risk due to PAHs exposure when referring to values of toxicity equivalence and inhalation cancer risk. Diagnostic ratios of BaA/(BaA + CHR) (0.48 ± 0.04) and IND/(IND + BPER) (0.58 ± 0.04) and strong correlations between PM2.5, levoglucosan and cPAHs concentrations implied that the major source of air pollution in the study period was biomass burning. PM2.5 concentration as a pollution indicator was labelled as BB-low, BB-medium, BB-high or BB-extreme; <50, 50–75, 75–100 and > 100 μg m−3, respectively. The levoglucosan and cPAHs concentration during BB-extreme pollution was 4.3 times and 2.34 times, respectively, that during BB-low pollution, and the correlation coefficient (r) between the concentrations of levoglucosan and cPAHs was as high as 0.987, indicating that the more intense the burning of biomass, the higher the carcinogenic risk in the urban air.

Primary Air Pollutants Emissions Variation Characteristics and Future Control Strategies for Transportation Sector in Beijing, China

Air pollutant emissions from vehicles, railways, and aircraft for freight and passenger transportation are major sources of air pollution, and strongly impact the air quality of Beijing, China. To better understand the variation characteristics of these emissions, we used the emission factor method to quantitatively determine the air pollutant emissions from the transportation sector. The emission intensity of different modes of transportation was estimated, and measures are proposed to prevent and control air pollutants emitted from the transportation sector. The results showed that air pollutant emissions from the transportation sector have been decreasing year by year as a result of the reduction in emissions from motor vehicles, benefiting from the structural adjustment of motor vehicles. A comparison of the emission intensity of primary air pollutants from different modes of transportation showed that the emission level of railway transportation was much lower than that of road transportation. However, Beijing relies heavily on road transportation, with road freight transportation accounting for 96% of freight transportation, whereas the proportion of railway transportation was low. Primary air pollutants from the transportation sector contributed significantly to the total emissions in Beijing. The proportion of NOX emissions increased from 54% in 2013 to 58% in 2018. To reduce air pollutant emissions from the transportation sector, further adjustments and optimization of the structure of transportation in Beijing are needed. As for the control of motor vehicle pollutant emissions, vehicle composition must be adjusted and the development of clean energy must be promoted, as well as the replacement of diesel vehicles with electric vehicles for passenger and freight transportation.

A Four-Electrode Mixed-Potential Sensor Array for Simultaneous Decoding of Hazardous Multi-Gas Mixtures

The development of sensors is necessary to provide controls to work with harmful gases required in many industrial processes and scientific endeavors. However, industrial growth especially in agriculture, power generation and transportation industries has become a major source of air pollution resulting in ozone depletion, eutrophication, smog and global warming.1, 2 As a result, the goalpost for sensor requirements is constantly changing due to increasingly tighter regulations on pollutants.3 Despite significant advancements, the need for fast, durable and highly selective sensors for monitoring air pollutants in various applications is constantly increasing. This is further complicated in environments where multiple gases with varying toxicity are present due to cross-sensitivity towards non-target chemical species within a given environment. Mixed-potential sensors, whose sensitivity depends on the kinetics of electrochemical reactions at the electrode-electrolyte interface, are shown to have higher sensitivity and durability towards a variety of gases although cross-sensitivity towards non-target gases remains a challenge.4 Recently mixed potential sensor arrays coupled with modeling have been evaluated for addressing this issue.5 Previously our group studied the role of varying bias currents of 0, -1.5, -3.5 and -6 µA on an Au|YSZ|Pt sensor that was exposed to different target gases such as NH3, NO, NO2, and C3H6, and analyzed the results through a Bayesian model where two and three gas mixtures were successfully decoded with increased selectivity.6 We recently tested a total of four mixed potential sensors connected in series where the four SEs, one AuPd, two La0.8Sr0.2CrO3 and another In doped SnO2, all with varying selectivity and sensitivity towards target gases such as NO, NO2, NH3 and C3H8, and decoded gas mixtures containing two and three analyte gases with less than 3% error in predicting the absolute concentration values of individual gases present in the mixture using a Bayesian algorithm.7, 8 In this presentation, we will discuss our latest results using a four electrode single platform mixed potential sensor array towards decoding two and three gas mixtures. The four electrodes of choice where a Pt quasi-reference electrode, one AuPd and two La0.8Sr0.2CrO3 electrodes (Figure 1). The target gases utilized in this work are NO, NO2, NH3 and C3H8. We will also elaborate results obtained with our sensors in a simulated poultry house environment for tracking ammonia concentrations in the presence of hydrocarbons such as ethane and propane.

Technology and the Effectiveness of Regulatory Programs over Time: Vehicle Emissions and Smog Checks with a Changing Fleet

Personal automobile emissions are a major source of urban air pollution. Many U.S. states control emissions through mandated vehicle inspections and repairs. But there is little empirical evidence directly linking mandated inspections, maintenance, and local air pollution levels. To test for a link, we estimate the contemporaneous effect of inspections on local air quality. We use day-to-day, within-county variation in the number of vehicles repaired and recertified after failing an initial emissions inspection, with individual-level data from 1998–2012 from California’s inspection program. Additional re-inspections of pre-1985 model year vehicles reduce local carbon monoxide, nitrogen oxide, and particulate matter levels, while re-inspections of newer vehicles with more modern engine technology have no economically significant effect on air pollution. This suggests emissions inspections have become less effective at reducing local air pollution as more high-polluting vehicles from the 1970s and 1980s leave the road, and provides an example of how the social efficiency of programs can change under improving technologies. We also estimate the importance of station quality, using a metric devised for California’s new STAR certification program. We show re-inspections of older vehicles conducted by low quality inspection stations do not change air pollution, while inspections at high quality stations have a moderate effect on pollution concentrations, which suggests the potential for ineffective monitoring at low quality inspection stations. We find little effect on ambient ozone levels, regardless of station quality or vehicle age.

Cooking with biomass fuel and cardiovascular disease: a cross-sectional study among rural villagers in Phitsanulok, Thailand.

Background: Burning biomass fuel is a major source of indoor air pollution; about 40% of Thai people still use biomass for cooking. There is increasing evidence of the association between biomass smoke exposure and serious health effects including cardiovascular disease. The object of this cross-sectional study was to investigate the association between biomass use for household cooking and cardiovascular outcome, including coronary heart disease, hypertension, high cholesterol, diabetes mellitus, and stroke among rural villagers in Phitsanulok, Thailand. Methods: Data from 1078 households were collected using a face-to-face interview questionnaire. Results: After being adjusted for gender, age, cigarette smoke, secondhand smoke, and exposure to other sources of air pollution, it was found that the family members of cooks using biomass fuel were at risk of coronary heart disease (CHD; OR=4.35; 95%CI 0.10-18.97), high blood pressure (HBP; OR=1.61; 95%CI 1.10-2.35), high cholesterol (HC; OR=2.74; 95%CI 1.66-4.53), and diabetes (OR= 1.88; 95%CI 1.03-3.46). Compared to LPG use, using wood was associated with stroke (OR=7.64; 95%CI 1.18-49.61), and using charcoal was associated with HC (OR=1.52; 95%CI 1.04-2.24). Compared to never user, household cooks who sometimes use charcoal had an increased risk of HBP (OR=2.04; 95%CI 1.32-3.15), HC (OR=2.61; 95%CI 1.63-4.18), and diabetes (OR=2.09; 95%CI 1.17-3.73); and cooks who often use charcoal had an elevated risk of stroke (OR=3.17; 95%CI 1.04-9.71), and HC (OR=1.52; 95%CI 1.02-2.27) to their family members. Conclusions: The study results were consistent with those found in studies from other parts of the world, and supports that exposure to biomass smoke increase cardiovascular diseases. The issue should receive more attention, and promotion of clean fuel use is a prominent action.

Hazardous air pollutant emissions implications under 2018 guidance on U.S. Clean Air Act requirements for major sources

ABSTRACT On January 25, 2018, the United States Environmental Protection Agency withdrew a 1995 policy that mandates the use of maximum achievable control technology (MACT) to regulate emissions from major sources of hazardous air pollutants (HAPs), a category of toxic chemicals that may be carcinogenic, mutagenic, or cause other adverse health effects. To better understand the implications and scope of the change in regulatory guidance for HAP emissions of major sources that may reclassify as area sources, the increase in emissions that could legally occur under the new policy is assessed here. Based on facility-level data from a 2014 HAP national emissions inventory, it is estimated that 70% of major sources of HAPs qualify for reclassification as area sources, which could result in a maximum of 35,030 tons per year (tpy) of additional HAP emissions if all sources successfully reclassified. This amount would nearly triple the total volume of HAPs that qualifying major sources emitted in 2014. On average, qualifying sources could emit individually an additional 18.4 tpy. In the 21 states and territories that follow only federal guidelines for controlling HAPs, it is more likely that the estimates presented here could materialize compared to states that have additional guidelines for area sources of HAPs. The quantitative analysis of the potential emission changes resulting from regulatory change is instructive for industry, state and federal decisionmakers, and interested members of the public looking to understand and anticipate how relevant stakeholders will be affected by this policy change. Implications: Withdrawal of a U.S. Environmental Protection Agency policy that mandates the use of maximum achievable control technology (MACT) to regulate emissions from major sources of hazardous air pollutants (HAPs) could result in higher emissions of toxic chemicals that may be carcinogenic, mutagenic, or cause other adverse health effects. Analysis of potential emission changes resulting from regulatory change is instructive for industry, state, and federal decisionmakers, and interested members of the public looking to understand and anticipate how relevant stakeholders will be affected by this policy change.

PM2.5 Inversion Using Remote Sensing Data in Eastern China Based on Deep Learning

PM2.5, which is a major source of air pollution, has a considerable impact on human health. In this study, a multi-element joint PM2.5 inversion method based on a deep learning model is proposed. With PM2.5 concentration as the ground truth, 10 elements including the Himawari-AOD daily data products, temperature, relative humidity, and pressure, were introduced as inversion elements. To verify the effectiveness of the method, the experiment was carried out by season using remote sensing data in Eastern China during 2016-2018. The results demonstrate that PM2.5 concentrations were positively correlated with AOD, precipitation, wind speed, and high vegetation cover index and negatively correlated with dwarf vegetation cover index. The correlation with temperature, humidity, pressure, and DEM changed with seasons. Comparative experiments indicated that the accuracy of PM2.5 inversion based on the deep neural network is higher than that of traditional linear and nonlinear models. R2 was above 0.5, and the error was small in each season. The R2 value for autumn, which showed the best inversion, was 0.86, that for summer was 0.75, that for winter was 0.613, and that for spring was 0.566. The visualization of the model illustrates that the inversion result of the DNN model is closer to the PM2.5 concentration distribution interpolated by the ground monitoring station, and the resolution is higher and more accurate.

Assessment of Major Air Pollution Sources in Efforts of Long Term Air Quality Improvement in İstanbul

Air pollution affected quality of life and public health due to high concentration levels of air pollutants in Istanbul, especially in 1990s. Major air pollution sources in Istanbul caused elevation of the air pollutants in ambient air of the megacity. To protect human health, the levels of PM10 and SO2 were reduced by taking effective actions such as the reduction of utilization of coal, fuel oil, wood combustion for residential heating, expending natural gas network and improving the quality of diesel and gasoline. Intelligent Traffic Systems (ITS) were applied to reduce the air pollutant emission from transportation by reducing travelling time. Overall, this study evaluates air pollution sources in Istanbul based on previous source apportionment studies that guide the emission reduction strategies. The improvement on PM10 and SO2 demonstrated as 50% and 98% reduction respectively since 1990s to 2014.

Effects of Trans, Trans-2,4-decadienal on the Ions Currents of Cardiomyocytes: Possible Mechanisms of Arrhythmogenesis Induced by Cooking-oil Fumes

Household air pollution has adverse effects on cardiovascular health. One of the major sources of household air pollutants is the combustion of cooking oils during cooking. Trans, trans-2,4-decadienal (tt-DDE) is a type of dienaldehyde that is present in a wide range of food and food products. It is a byproduct of the peroxidation of linoleic acid following the heating of oil during cooking. The mechanisms of the associations between household air pollution and cardiac arrhythmias are currently unclear. The purpose of this study was to determine effects of tt-DDE on the ion currents in H9c2 cells. The IK and ICa,L in H9c2 cells treated with and without tt-DDE were measured using the whole-cell patch clamp method. Expressions of Kv2.1 and Cav1.2 in H9c2 cells treated with and without tt-DDE were measured by western blot analysis. After the H9c2 cells had been exposed to tt-DDE, the IK and ICa,L were significantly decreased. The expression of Kv2.1, unlike that of Cav1.2, was also significantly decreased in these cells. These changes in IK and ICa,L that were induced by tt-DDE may help to explain the association between cardiac arrhythmogenesis and cooking-oil fumes.

Non-invasive biomonitoring of mercury in birds near thermal power plants: lessons from Maharashtra, India.

Thermal power plants (TPPs) have emerged as a major source of air, water, and soil pollution because of the presence of many toxic metals. The presence of mercury (Hg) in fly ash has proven to be toxic in nature because of its tendency to get bioaccumulated and biomagnified in the food chain. The aim of the present study was to understand the presence of toxic Hg in the feathers of wetland birds undertaking the study around a TPP located in Nagpur, India. Local wetland birds especially cattle egrets, heron, and Moorhen were commonly observed dwelling close to fly ash ponds for various purposes (roosting, breeding, feeding, etc.). Samples of fly ash, soil, water, plants, and bird feather were collected, cleaned, and processed for Hg analysis. A mercury analyzer was used to assess the concentration of toxic levels of Hg in samples. Our results reflect leaching of Hg in soil and uptake by plant samples, whereas in water, ash, and bird feather samples concentrations of Hg were fairly below the prescribed limits (World Health Organization). A non-invasive method for understanding the mercury concentration in wetland birds has been established as a potential important monitoring tool to track the fate of toxic metal Hg in the food chain. In summary, our results indicate fairly low Hg levels in feather samples projecting non-invasive biomonitoring as a promising strategy. The study also suggests that a comprehensive monitoring action plan in place for Hg and other toxic metals in the food chain that comes from TPP will be efficient to avoid any pitfalls. Graphical abstract.

Synthesis of multi-walled carbon nanotubes (MWCNTs) from plastic waste &amp; analysis of garlic coated gelatin/MWCNTs nanocomposite films as food packaging material

Plastic waste is considered as major source of air, water and soil pollution, due to its non-biodegradable nature. Its direct disposal has negative impact on the environment. So here we present nanotechnological aid to solve the problem of plastic waste. As carbon nanotubes offer wide range of applications, conversion of plastic waste into high value carbon nanotubes (CNTs) could be a beneficial option. Multi-walled carbon nanotubes (MWCNTs) were synthesized from waste plastic bottles using T-CVD method. Synthesized MWCNTs were characterized using XRD, SEM and EDAX. The CNTs were found to be of 30–45 nm in diameter. Garlic microparticles were successfully synthesized using planetary ball milling and characterized using SEM. Gelatin/MWCNT nanocomposite films with varying concentration of MWCNTs (1%, 2% and 3%) were prepared. The improved water and oil resistance as well as antibacterial study suggest that the prepared nanocomposite films can be used as potential food packaging material. Coating these nanocomposite films with garlic microparticles not only enhances their antibacterial activity but also can avoid the interaction of food with MWCNTs and solve the problem of the migration.

Design and dynamic behaviour investigation of a novel VOC recovery system based on a deep condensation process

Emission of volatile organic compounds (VOCs) is a major source of air pollution, and condensation is an ideal method for VOC recovery. However, with the increasingly strict regulations on VOC emissions, the traditional condensation method cannot meet the requirements of the existing VOC emission standards due to its restriction of the refrigeration temperature. In this paper, a novel VOC deep condensation recovery system (VOC-DCR system) is designed to overcome the shortcomings of the traditional condensation recovery system, and its steady-state simulation shows that the VOC recovery rate is 99.97% and the energy consumption is 35.67 kW. In addition, the VOC emission concentration after the treatment of the novel system is 45.17 mg/Nm3, which is far below the emission limit. Moreover, to verify the security and effectiveness of the actual running of the system, the dynamic model of the system is established to study its dynamic behaviours under external disturbances. The dynamic simulation results show that the novel system can overcome some disturbances and operate in a stable state. On this basis, this paper also predicts the operational risk of the system under extreme disturbances of −50% to 50%. The prediction results show that in order to ensure the safe and effective operation of the system, the disturbance of feed temperature and flow rate should be controlled within −33% to 8% and −2% to 8% respectively. Moreover, the disturbance of feed pressure and concentration should be controlled within −8% to 50% and −50% to 18% respectively. The conclusions of this study are of great significance for promoting the industrial application of the VOC-DCR system and guiding its safe operation.

Room temperature oxidation of acetone by ozone over alumina-supported manganese and cobalt mixed oxides

Volatile organic compounds (VOCs) are among the major sources of air pollution. Catalytic ozonation is an efficient process for removing VOCs at lower reaction temperature compared to catalytic oxidation. In this study, a series of alumina supported single and mixed manganese and cobalt oxides catalysts were used for ozonation of acetone at room temperature. The influence of augmenting the single Mn and Co catalysts were investigated on the performance and structure of the catalyst. The manganese and cobalt single and mixed oxides catalysts of the formula Mn10%-CoX and Co10%-MnX (where X = 0, 2.5%, 5%, or 10%) were prepared. It was found that addition of Mn and Co at lower loading levels (2.5% or 5%) to single metal oxide catalysts enhanced the catalytic activity. The mixed oxides catalysts of (Mn10%-Co2.5%) and (Mn10%-Co5%) led to acetone conversion of about 84%. It is concluded that lower oxidation state of the secondary metal improves ozone decomposition and oxidation of acetone.

Vehicle Emission Inventory and Scenario Analysis in Liaoning from 2000 to 2030

Vehicle emissions have become a major source of air pollution in urban cities. The vehicle emission inventory of the Liaoning province from 2000 to 2030 was established based on the COPERT model and ArcGIS, and the temporal and spatial distribution characteristics of six pollutants (CO, NMVOC, NOx, PM10, SO2, and CO2) were analyzed. Taking 2016 as the base year, eight scenarios of control measures were designed based on scenario analysis, and the effects of different scenarios on emission reduction were assessed. Results showed that during 2000-2016, CO, NMVOC, NOx, and PM10 emissions at first exhibited increasing trends, after which they decreased. Emissions of SO2 exhibited fluctuating trends, while the emissions of CO2 showed a continuous increase. Passenger cars and motorcycles were the main contributors of CO and NMVOC emissions. Heavy-duty trucks and buses were the main sources of NOx and PM10 emissions. Passenger cars were the major contributors to SO2 and CO2 emissions. Vehicle emissions were significantly higher in the central and southern in Liaoning Province. At the city level, vehicle emissions were mainly concentrated in Shenyang and Dalian. The scenario analysis showed that the implementation of stricter vehicle emission standards can enhance the emission reduction effect. Moreover, accelerating the implementation of new emission standards was beneficial to reduce emissions. The integrated scenario would achieve the maximum emission reduction, with reduction rates of CO, NMVOC, NOx, PM10, CO2, and SO2 at 30.7%, 14.3%, 81.7%, 29.4%, 12.3%, and 12.1%, respectively.

Oxide Catalysts with Ultrastrong Resistance to SO2 Deactivation for Removing Nitric Oxide at Low Temperature.

Nitrogen oxides are one of the major sources of air pollution. To remove these pollutants originating from combustion of fossil fuels remains challenging in steel, cement, and glass industries as the catalysts are severely deactivated by SO2 during the low-temperature selective catalytic reduction (SCR) process. Here, a MnOX /CeO2 nanorod catalyst with outstanding resistance to SO2 deactivation is reported, which is designed based on critical information obtained from in situ transmission electron microscopy (TEM) experiments under reaction conditions and theoretical calculations. The catalysts show almost no activity loss (apparent NOX reaction rate kept unchanged at 1800 µmol g-1 h-1 ) for 1000 h test at 523 K in the presence of 200 ppm SO2 . This unprecedented performance is achieved by establishing a dynamic equilibrium between sulfates formation and decomposition over the CeO2 surface during the reactions and preventing the MnOX cluster from the steric hindrance induced by SO2 , which minimized the deactivation of the active sites of MnOX /CeO2 . This work presents the ultralong lifetime of catalysts in the presence of SO2 , along with decent activity, marking a milestone in practical applications in low-temperature selective catalytic reduction (SCR) of NOX .

Pollutant measurements at near road and urban background sites in New York, USA

Due to the potential for heightened exposure to vehicle exhaust pollutants, air monitoring has been required at near roadway (NR) locations within large urban centers in the United States since 2010. In this paper pollutant measurements at two urban NR locations, Rochester and New York City, Queens are discussed. Pollutants measured at these sites include PM2.5 mass, nitrogen oxides (NO, NO2, NOx), ultrafine particles (UFP), black carbon (BC) and carbon monoxide (CO). Measurements at NR sites are made in conjunction with existing urban background (UB) sites. Although pollutant concentrations at Rochester and Queens are elevated at the NR sites compared to the UB sites particularly during the daytime hours, all pollutants are below the level of the National Ambient Air Quality Standards (NAAQS). At Rochester, BC at the NR site is elevated by a factor of 2–3 between 7 a.m. and 3 p.m. and drops to near uniform concentrations at both sites at night. The enhancement or increment in BC is highest in summer and lowest in winter. Other co-pollutants including NOx and CO are also elevated at the Rochester NR site by varying degrees during daytime hours. Similarly, enhanced pollutant concentrations are observed at the Queens NR site. At both locations small increments are observed for PM2.5 mass. For example, an annual increment of 0.27 μg/m3 and a daily increment of 0.80 μg/m3 was observed at the Rochester NR site. At Queens NR annual PM2.5 mass increments of 0.92 and 1.0 μg/m3 were observed in 2017 and 2018. In addition, a NR daily increment of 1.4 μg/m3 was observed at Queens in 2018. The data are analyzed for diurnal, weekday vs weekend and seasonal patterns. Nonparametric wind regression identified the roadways as the major source of traffic related air pollutants.

Using system dynamics to assess the environmental management of cement industry in streaming data context.

The cement industry can be regarded as one of the major sources of anthropogenic air pollution. It uses a significant amount of energy while creating substantial amount of potentially health-threatening carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx) and dust particles. Hence, the cement industry can be regarded as a primary area for study in the development of green manufacturing. In this study, an urban cement factory is analyzed. The major contribution of the article is the development of a holistic approach to identify the variables impacting cement production and environmental factors creating air pollution in the area, a system dynamics model has been developed incorporating streaming data. To understand the effect of a cement factory on an urban area, some strategic level decisions are also analyzed with the study in order to reveal their impact on environment. The impact of cement production on air pollution cannot be evaluated separately from other air quality factors; therefore, the contribution of each factor has to be identified in order to understand the specific issues affecting a region. With the use of the model, future implications of various air quality factors on environmental sustainability can be assessed. According to the results, PM10 value, which is currently above the World Health Organization (WHO) air pollution critical level of 50μg/m3 for 30% of the days in a year, will climb to more than 50% in 2023. Moreover, governments can also recognize the severe impacts of location selection for cement industries, unplanned and excessive building licensing, and uncontrolled immigration on environment of an urban living. Therefore, output of the study is potentially beneficial in guiding governmental decisions to ensure the sustainability of air quality.

Evolution of Indoor Cooking Emissions Captured by Using Secondary Electrospray Ionization High-Resolution Mass Spectrometry

Cooking emissions represent a major source of air pollution in the indoor environment and exhibit adverse health effects caused by particulate matter together with volatile organic compounds (VOCs)...

Mitigation of PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; and ozone pollution in Delhi: a sensitivity study during the pre-monsoon period

Abstract. Fine particulate matter (PM2.5) and surface ozone (O3) are major air pollutants in megacities such as Delhi, but the design of suitable mitigation strategies is challenging. Some strategies for reducing PM2.5 may have the notable side effect of increasing O3. Here, we demonstrate a numerical framework for investigating the impacts of mitigation strategies on both PM2.5 and O3 in Delhi. We use Gaussian process emulation to generate a computationally efficient surrogate for a regional air quality model (WRF-Chem). This allows us to perform global sensitivity analysis to identify the major sources of air pollution and to generate emission-sector-based pollutant response surfaces to inform mitigation policy development. Based on more than 100 000 emulation runs during the pre-monsoon period (peak O3 season), our global sensitivity analysis shows that local traffic emissions from the Delhi city region and regional transport of pollution emitted from the National Capital Region (NCR) surrounding Delhi are dominant factors influencing PM2.5 and O3 in Delhi. They together govern the O3 peak and PM2.5 concentration during daytime. Regional transport contributes about 80% of the PM2.5 variation during the night. Reducing traffic emissions in Delhi alone (e.g. by 50 %) would reduce PM2.5 by 15 %–20 % but lead to a 20 %–25 % increase in O3. However, we show that reducing NCR regional emissions by 25 %–30 % at the same time would further reduce PM2.5 by 5 %–10 % in Delhi and avoid the O3 increase. This study provides scientific evidence to support the need for joint coordination of controls on local and regional scales to achieve effective reduction in PM2.5 whilst minimising the risk of O3 increase in Delhi.

Estimation of Idle Emissions from the On-Road Vehicles in Dhaka

Vehicle emission is a major source of air pollution in Dhaka. Old fleet, lack of maintenance, improper traffic and parking management, overloading, fuel adulteration etc. are responsible for high emissions from the vehicle sector. In this study, vehicle emissions have been measured on-road in Dhaka using an Automotive Gas Analyzer and Smoke Opacity Meter to determine the existing vehicle emission scenario in the city. Concentrations of carbon monoxide (CO) and hydrocarbons (HC) in the emissions from CNG/gasoline vehicles, and opacity of the emissions from diesel vehicles were measured. The results were compared with the corresponding national limit values. It was found that all types of CNG vehicles performed very well with more than 80% satisfying the corresponding limit values. Private cars ranked at the top in performance among the CNG/gasoline vehicles. Diesel vehicles were found as the worst polluters in the vehicle sector; emissions from about 75% of the diesel vehicles had opacity more than 65 HSU, the national limit value for emissions from diesel vehicles. Motor cycles were also highly polluting; 60% of the motor cycles emitted CO and HC concentrations higher than the respective national emission limit values.