Estimated Emission Factors Research Articles

Climate change impact of integrating a solar microgrid system into the Swedish electricity grid

Microgrids are small-scale electricity networks that integrate distributed electricity generation with consumers and, potentially, with storage devices. There is growing interest in these systems, as they can offer solutions for electrification of remote areas, deployment of distributed renewable energy resources, and decarbonization of electricity supply. However, the potential benefits of microgrids in terms of climate change mitigation have not yet been thoroughly assessed. In this study, Life Cycle Assessment was performed to determine the climate change impact of integrating a solar microgrid system in western Sweden into the Swedish electricity grid. To determine whether replacement of grid electricity with electricity from the microgrid can lower greenhouse gas (GHG) emissions, average and marginal GHG emission factors (EFs) for electricity use were estimated with explicit spatial and temporal resolution, using historical data on electricity generation and trade, and life cycle EFs for electricity generation technologies. The assessment, with both marginal and average EFs, showed that integration of the microgrid into the Swedish electricity grid did not provide GHG emissions abatements, as the electricity from the microgrid displaced grid electricity with lower carbon intensity. It was found that a microgrid without batteries would have lower climate change impact, but would still fail to lower overall GHG emissions. Moreover, it was demonstrated that the methodological approach used for estimation of EFs and the definition of spatial boundaries could influence the obtained results.

Integrated modelling to assess N pollution swapping in slurry amended soils

In the present work, it was hypothesized that through modelling it is possible to overcome the constraints that arise in the quantification of N pollution swapping associated to slurry application practices when using individual experimental data. For this, environmental N losses were assessed under two methods of dairy slurry application to a double cropping system (rainfed oats (Avena strigosa)/irrigated maize (Zea mays)) in two different soils. An integrated experimentation and modelling approach was applied using the RZWQM2 model. The model was first tested using four years of experimental data concerning N fluxes to/from different environmental compartments (soil mineralization, N gas emissions, and N leaching). The model estimated emissions with overall efficiencies of ~70% and r2 ~ 0.75. Total N losses were higher for surface band application (95.4 and 40.2 kg ha−1 for the sandy and sandy loam soils, respectively). However, when slurry was injected, nitrate leaching considerably increased (by 107 and 64% for the sandy and sandy loam soils, respectively), even though gas emissions were minimized. This N swapping among path losses requires targeting of the N mitigation measures to the environmental compartment showing the highest vulnerability. Generally, the estimated emission factors (EFs) were lower than or equal to (slurry injection in the sandy loam soil) the IPCC default. The values showed high variability, reinforcing the need to use agricultural system specific EFs. The methodologies used in this study, focused on scenario analysis, can support policy as they can be used to set up integral strategies to decrease N emissions from livestock farming systems, taking into account possible synergies and antagonisms produced by the measures among NH3 and N2O emissions and NO3− leaching.

Cookstove Smoke Impact on Ambient Air Quality and Probable Consequences for Human Health in Rural Locations of Southern Nepal.

Residential emission from traditional biomass cookstoves is a major source of indoor and outdoor air pollution in developing countries. However, exact quantification of the contribution of biomass cookstove emissions to outdoor air is still lacking. In order to address this gap, we designed a field study to estimate the emission factors of PM2.5 (particulate matter of less than 2.5 µ diameter) and BC (black carbon) indoors, from cookstove smoke using biomass fuel and with smoke escaping outdoors from the roof of the house. The field study was conducted in four randomly selected households in two rural locations of southern Nepal during April 2017. In addition, real-time measurement of ambient PM2.5 was performed for 20 days during the campaign in those two rural sites and one background location to quantify the contribution of cooking-related emissions to the ambient PM2.5. Emission factor estimates indicate that 66% of PM2.5 and 80% of BC emissions from biomass cookstoves directly escape into ambient air. During the cooking period, ambient PM2.5 concentrations in the rural sites were observed to be 37% higher than in the nearby background location. Based on the World Health Organization (WHO)’s AirQ+ model simulation, this 37% rise in ambient PM2.5 during cooking hours can lead to approximately 82 cases of annual premature deaths among the rural population of Chitwan district.

Estimation of Energy and Emissions Properties of Waste from Various Species of Mint in the Herbal Products Industry

The paper presents the results of research on the physicochemical properties of plant biomass consisting of four mint species, these being Mentha × piperita L. var. citrata Ehrh.—‘Bergamot’, Mentha × rotundifolia L., Mentha spicata L., and Mentha crispa L. The research conducted consisted of the technical analysis of biofuels—determining the heat of combustion and the calorific value of the material under study, and the content of ash, volatile compounds, and humidity. In addition, elemental analysis was carried out for the biomass under study by determining the content of carbon, hydrogen, nitrogen, and sulfur. The research demonstrated that Mentha × piperita L. var. citrata Ehrh.—‘Bergamot’ had the highest energy potential with a gross calorific value of 16.96 MJ·kg−1, and a net calorific value of 15.60 MJ·kg−1. Among the tested materials, Mentha × rotundifolia L. had the lowest content of ash at 7.23%, nitrogen at 0.23%, and sulfur at 0.03%, and at the same time had the highest content of volatile fraction at 70.36%. When compared to hard coal, the estimated emission factors indicated a CO reduction of 29–32%, CO2 reduction of 28–31%, NOx reduction of 40–80%, SO2 reduction of 92–98%, and dust reduction of 45–61%, depending on the type of biomass used.

Detecting nighttime fire combustion phase by hybrid application of visible and infrared radiation from Suomi NPP VIIRS

An accurate estimation of biomass burning emissions is partially limited by the lack of knowledge of fire burning phase (smoldering vs. flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in nighttime scenes. In contrast, VIIRS 4 μm moderate resolution band #13 (M13), though capable of detecting fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered by their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to the footprint of M-band pixels, accounting for onboard detector aggregation schemes and bowtie effect removals. The visible energy fraction (VEF) is subsequently introduced as an indicator of fire burning phase. VEF is calculated as the ratio of visible light power (VLP) to FRP for each fire pixel retrieved from the VIIRS 750 m active fire product. A global distribution of VEF values is quantitatively obtained, showing smaller VEF values in regions with mostly smoldering wildfires, such as peatland fires in Indonesia, larger VEF values in regions with flaming wildfires over grasslands and savannas in the sub-Sahelian region, and the largest VEF values associated with gas flaring in the Middle East. Mean VEF for different land cover types or regions is highly correlated with modified combustion efficiency (MCE). These results, together with a case study of the 2018 California Camp Fire, show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.

Estimation of greenhouse gas emission factors based on observed covariance of CO2, CH4, N2O and CO mole fractions

BackgroundCovariances among major anthropogenic greenhouse gases were studied during three cold-air pool episodes in the Pannonian Basin to better constrain their emission factors for Europe.ResultsOn the base of observed covariance between carbon dioxide, methane, carbon monoxide and nitrous oxide atmospheric dry air mole fraction in a region of the Pannonian (Carpathian) Basin during three cold-air pool episodes in January–February 2017, emission factors relative to carbon dioxide were determined. For the determination of the emission of carbon dioxide, a simple boundary-layer budget model was compiled. The model gave 6.3 g m−2 day−1 carbon dioxide emission for the footprint area of the measurements on average for the period of the episodes. The 6.7–13.8 nmol μmol−1, 0.15–0.31 nmol μmol−1 and 15.0–25.8 nmol μmol−1 ratios for CH4:CO2, N2O:CO2 and CO:CO2, respectively, correspond to 15.3–31.7 mg m−2 day−1 methane, 0.9–2.0 mg m−2 day−1 nitrous oxide and 60.0–103.4 mg m−2 day−1 carbon monoxide emissions for the region. These values are somewhat higher than the officially reported bottom-up annual national averages for Hungary, which are explained by the winter conditions and intensive domestic heating.ConclusionsThe study indicated the high share of biomass burning in residential heating in rural environment that results in high carbon monoxide emission relative to that of carbon dioxide. It also indicated that the actual emission factor for nitrous oxide may exceed the range given in the guidelines for inventory compilation, which should be taken into account in reporting. It is shown that even a simple boundary-layer budget model might give realistic emission estimation under cool-air pool episodes.

Energy and Emission Characteristics of Biowaste from the Corn Grain Drying Process

This paper presents the results of the evaluation of the energy potential of waste from the process of drying corn grain in the form of corn cobs, damaged grains, corn grain husks, and mixtures of starting materials. A technical and elementary analysis was performed for the biomass under investigation. The elemental composition of ash and the tendencies for slagging and boiler slagging were determined, and the emission factors were estimated based on the elemental analysis performed. The tests showed the highest calorific value among the starting materials for corn cobs (CCs) (14.94 MJ·kg−1) and for the mixture of corn cobs with corn husk (CC–CH) (13.70 MJ·kg−1). The estimated emission factors were within ranges of 38.26–63.26 kg·Mg−1 for CO, 936–1549 kg·Mg−1 for CO2, 0.85–4.32 kg·Mg−1 for NOx, 0.91–1.03 kg·Mg−1 for SO2, and 3.88–54.31 kg·Mg−1 for dust. The research showed that the creation of mixtures from starting materials leads to materials with lower potential for negative environmental impact as well as a reduced risk of slagging and fouling of biomass boilers. However, taking into account all the parameters determined for the biomass under study, the highest energy potential was characteristic for corn cobs and the mixture of corn cobs with corn husk.

Estimation of Carbon Dioxide from Transportation Sector Based on Urban Data Availability

One source of potential carbon dioxides in most developing countries is the transportation sector. The calculation of carbon dioxides is therefore, important as a part of policy making on carbon management in the region. The Intergovernmental Panel on Climate Change (IPCC) calculation method which were often used require large and complete data. This is a problematic for developing countries due to the availability of data are not in accordance or sufficient with the IPCC method. This study examined the alternative calculation methods that are tailored to the available data in most developing countries. Two alternative methods are proposed for calculating carbon dioxide emissions; the first method is based on data of the number and types of vehicles, and the second method is based on the data and the length of the road class. The results show that both alternative methods are reliable to estimate specific emission factor (SEF) and emission estimates that are close to the IPCC calculation methods. The alternative of second method provides results that are closer to the IPCC calculation method with the correlation value of 0.997 and the standard error of 2.8 ton CO2/years, as compared to the results of alternative first method (correlation value of 0.990 and the standard error of 4.7 ton CO2/years).

In-situ estimation of non-regulated pollutant emission factors in an urban area of Nantes, France, with fleet composition characterization

The purpose of this study is to estimate the in-situ emission factors of several pollutants (particle number [PN], black carbon [BC] and several volatile and semi-volatile organic compounds [VOCs and SVOCs]) in an urban area of Nantes, France, with real-world traffic conditions and characterization of the fleet composition. The fleet composition and driving conditions are characterized by the number of vehicles, their speeds and their types (passenger cars [PCs], light commercial vehicles [LCVs], heavy-duty vehicles [HDVs]) as well as their characteristics (make, model, fuel, engine, EURO emission standard, etc.). The number of vehicles passing on the boulevard is around 20,000 per day with about 44% of Euro 5 and Euro 6 vehicles. The impacts of fleet composition on emission were analyzed by ANOVA. The results show that the fleet composition has a significant impact on emissions for different pollutants. Higher percentage of gasoline PCs between Euro 4 to Euro 6 and Euro 4 diesel PCs induces more BC emission. Higher percentage of old gasoline and diesel vehicles (≤ Euro 3) induces higher emission of toluene, ethylbenzene and m + p- and o-xylene. Furthermore, emission factors estimated in this work were compared to those calculated in other in-situ studies that show a good agreement. For the chassis bench comparison, the in-situ PN and BC emission factors are in the same range as those measured for diesel vehicles without particle filter and gasoline vehicles with direct injection system. These EFs are also comparable with old heavy duty vehicles without particle filter (5 × 1013–2 × 1014 #/km).

How Many Trajectories Are Needed to Develop Facility- and Speed-Specific Vehicle-Specific Power Distributions for Emission Estimation? Case Study in Beijing

Vehicle-specific power (VSP) distributions, or operating mode (OpMode) distributions, are one of the most important parameters in VSP-based emission models, such as the motor vehicle emission simulator (MOVES) model. The collection of second-by-second vehicle activity data is required to develop facility- and speed-specific (FaSS) VSP distributions. This then raises the problem of how many trajectories are needed to develop FaSS VSP distributions for emission estimation. This study attempts to investigate the adaptive sample size for developing robust VSP distributions for emission estimations for light-duty vehicles. First, vehicle activity data are divided into trajectories and categorized into different trajectory pools. Then, the uncertainty of FaSS VSP distribution caused by sample size is analyzed. Further, the relationship between VSP distribution sample size and emission factor uncertainty is discussed. The case study indicates that error in developing FaSS VSP distributions decreases significantly with increased sample size. In different speed bins, the sample size required to develop robust FaSS VSP distributions and estimate emission factors is significantly different. In detail, in each speed bin, for a 90% confidence level, 30 trajectories (1,800 s) are enough to develop robust FaSS VSP distributions for light-duty vehicles with the root mean square errors (RMSEs) lower than 2%, which means errors in calculating fuel consumption and greenhouse gas (GHG) emissions are lower than 5%. However, 35 trajectories (2,100 s) are needed to estimate emissions of carbon monoxide (CO), nitrogen oxide (NOX), and hydrocarbons (HC) with an estimation error lower than 5%.

Size-resolved particle emission factors of vehicular traffic derived from urban eddy covariance measurements

Road traffic is one of the major sources of atmospheric particles in urban areas. Modelling the contribution of this source to urban pollution requires reliable estimates of emission factors possibly resolved in size. In this work, size-resolved particle emission factors (EFs) of the mixed vehicle fleet were measured in the urban area of Lecce (south-eastern Italy). The approach used is based on vertical fluxes measured with eddy-covariance, counting of vehicles, and estimation of footprints. Results show that the average EF in number (range 0.009–3 μm) was 2.2*1014 #/Veh km, being dominated by ultrafine particles (Dp < 0.25 μm) due to exhaust emissions. EF number size distribution decreases with particle size. A reduction of more than four orders of magnitude was observed at Dp ≅ 0.9 μm. EF mass size distribution reaches a maximum around Dp ≅ 0.3 μm then decreases until Dp ≅ 0.9 μm. For larger particles EF in mass increases for the influence of non-exhaust emissions. Average emission factor of PM1 was 56 mg/Veh Km and that of PM2.5 was 63 mg/Veh Km. A comparison of measurements taken in 2010 and 2015 in the same area shows a decreasing trend of the average total EF in number of about 56%, likely as a consequence of the increased use of new generation vehicles following more restrictive limits for particle emissions.

A Comparative Study of Stack Emissions from Straight-Line and Zigzag Brick Kilns in Nepal

Nepal has approximately 1000 operational brick kilns, which contribute significantly to ambient air pollution. They also account for 1.81% of the total bricks produced in the South Asian region. Little is known about their emissions, which are consequently not represented in regional/global emission inventories. This study compared emissions from seven brick kilns. Four were Fixed Chimney Bull’s Trench Kilns (FCBTKs) and three were Induced-Draught Zigzag Kilns (IDZKs). The concentrations of carbon dioxide (CO2), sulfur dioxide (SO2), black carbon (BC), and particulate matter (PM) with a diameter less than 2.5 µm (PM2.5) were measured. The respective emission factors (EFs) were estimated using the carbon mass balance method. The average fuel-based EF for CO2, SO2, PM2.5, and BC were estimated as 1633 ± 134, 22 ± 22, 3.8 ± 2.6 and 0.6 ± 0.2 g per kg, respectively, for all FCBTKs. Those for IDZKs were 1981 ± 232, 24 ± 22, 3.1 ± 1, and 0.4 ± 0.2 g per kg, respectively. Overall, the study found that converting the technology from straight-line kilns to zigzag kilns can reduce PM2.5 emissions by ~20% and BC emissions by ~30%, based on emission factor estimates of per kilogram of fuel. While considering per kilogram of fired brick, emission reductions were approximately 40% for PM2.5 and 55% for BC, but this definitely depends on proper stacking and firing procedures.

Emissions of pollutant gases, fine particulate matters and their significant tracers from biomass burning in an open-system combustion chamber

An open-system combustion chamber was designed and constructed for simulation of burning of various biomass types to estimate emission factors of pollutant gases, fine particulate matters and their composition to find out significant tracers. Rice straw (RS), maize residues (MR) and forest leaf litters (FLL) from mixed deciduous forest (MDF) and dry dipterocarp forest (DDF) were collected from various places in Northern Thailand based on land-use types. Approximately 1 kg of air-dried biomass sample was burned in the chamber, PM2.5 were collected. CO2 dominated during the flaming state while CO is predominant in the smoldering state. The highest EFPM2.5 was obtained from MDF burning (4.38 ± 2.99 g kg−1), while the lowest value was from MR burning (2.15 ± 0.95 g kg−1). Among water soluble ions, K+ (biomass burning (BB) tracer) was the most abundant species in PM2.5 followed by Cl− and SO42−. The average EFK+ from the burning of agricultural biomass was significantly higher than the burning of FLL. Scatter plot of K+/SO42− versus K+/Cl− can be used to distinguish between agricultural crop residues and FLL burning. Levoglucosan (BB tracer) was a dominant species among anhydrosugars and also a major component found in FLL burning. The ratios of levoglucosan/K+ and levoglucosan/mannosan obtained from forest and agricultural waste burnings were significantly different, therefore they can be used for BB source identification.

Estimating nitrogen flows of agricultural soils at a landscape level – A modelling study of the Upper Enns Valley, a long-term socio-ecological research region in Austria

This paper explores the fate of reactive nitrogen (Nr) on the landscape scale of present agricultural production practice on arable and grassland soils. We use the soil modelling tool LandscapeDNDC (landscape scale DeNitrification-DeComposition model) to quantify resulting flows of Nr distributed to the atmosphere, hydrosphere and the crops. Test area is a watershed in the Austrian Alps characterized by arable production in the low-lying areas and grassland in the mountains. The approach considers an overall budget of nitrogen, and determines the nitrogen use efficiency for individual crops and crop rotations, with average levels found at 85% for the arable area and 68–98% for the grassland areas. Modelled Nr flows are compared to the values resulting from the national emission factor (EF) method used for the Austrian emission inventory. For the arable part of the study region, the annual sum of released Nr emissions derived from LandscapeDNDC modelling is lower than the result of the EF method by about 13% (or 7 kg N ha−1). Model results are lower also for other Nr species, yet nitrate leaching rates as well as ammonia emissions contribute a major share. For grassland areas, nitrate leaching values estimated by LandscapeDNDC greatly depend on local specifics and substantially exceed EF estimates. All other modelled Nr species are lower than the EF results. The model set-up allows to characterize spatially explicit effects of mitigation measures. As an example, we identify nitrous oxide (N2O) hot spots in the study region, and we quantify the N2O emission saving potential if focusing reduction efforts to such hot spots. Reducing fertilization of hot spots by half could remove 14% of N2O emission for 5% less crop yield and a loss of grassland yield by <1% when extrapolated to the whole study area.

Speciated and total emission factors of particulate organics from burning western US wildland fuels and their dependence on combustion efficiency

Abstract. Western US wildlands experience frequent and large-scale wildfires which are predicted to increase in the future. As a result, wildfire smoke emissions are expected to play an increasing role in atmospheric chemistry while negatively impacting regional air quality and human health. Understanding the impacts of smoke on the environment is informed by identifying and quantifying the chemical compounds that are emitted during wildfires and by providing empirical relationships that describe how the amount and composition of the emissions change based upon different fire conditions and fuels. This study examined particulate organic compounds emitted from burning common western US wildland fuels at the US Forest Service Fire Science Laboratory. Thousands of intermediate and semi-volatile organic compounds (I/SVOCs) were separated and quantified into fire-integrated emission factors (EFs) using a thermal desorption, two-dimensional gas chromatograph with online derivatization coupled to an electron ionization/vacuum ultraviolet high-resolution time-of-flight mass spectrometer (TD-GC × GC-EI/VUV-HRToFMS). Mass spectra, EFs as a function of modified combustion efficiency (MCE), fuel source, and other defining characteristics for the separated compounds are provided in the accompanying mass spectral library. Results show that EFs for total organic carbon (OC), chemical families of I/SVOCs, and most individual I/SVOCs span 2–5 orders of magnitude, with higher EFs at smoldering conditions (low MCE) than flaming. Logarithmic fits applied to the observations showed that log (EFs) for particulate organic compounds were inversely proportional to MCE. These measurements and relationships provide useful estimates of EFs for OC, elemental carbon (EC), organic chemical families, and individual I/SVOCs as a function of fire conditions.

Estimating greenhouse gases emissions from horticultural peat soils using a DNDC modelling approach

Peat soils represent an important global carbon (C) sink, but can also provide a highly fertile medium for growing horticultural crops. Sustainable crop production on peat soils involves a trade-off between ensuring food security and mitigating typically high greenhouse gas (GHG) emissions and rates of soil C loss. An alternative approach to resource intensive field-based monitoring of GHG fluxes for all potential management scenarios is to use a process-based model driven by existing field data to estimate emissions. The aim of this study was to evaluate the suitability of the Denitrification-Decomposition (DNDC) model for estimating emissions of CO2, N2O and CH4 from horticultural peat soils. The model was parameterised using climatic, soil, and crop management data from two intensively cultivated sites on soils of contrasting soil organic matter (SOM) contents (∼35% and ∼70% SOM content). Simulated emissions of CO2, N2O and CH4, and simulated soil physical and crop output values, were compared to actual GHG, soil and crop measurements. Model performance was assessed using baseline parameterisation (i.e. model defaults), then calibrated using pre-simulation and sensitivity analysis processes. Under baseline parameterisation conditions, DNDC proved poor at predicting GHG emissions and soil/crop variables. Calibration and validation improved DNDC performance in estimating the annual magnitude of emissions, but model refinement is still required for reproducing seasonal GHG patterns in particular. Key constraints on model functioning appear to be its ability to reliably model soil moisture and some aspects of C and nitrogen dynamics, as well as the quality of input data relating to water table dynamics. In conclusion, our results suggest that the DNDC (v. 9.5) model cannot accurately reproduce or be used to replace actual field measurements for estimation of GHG emission factors under different management scenarios for horticultural peat soils, but may be able to do so with further modification.

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

ABSTRACTThis 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 NOx and SOx 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), SOx, 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 NOx and SOx emissions. Using 100% natural gas, SOx, PM10, and CO2 emissions reduce by 98.6%, 99.1%, and 21.7%, respectively. NOx emissions increase by 1.14% when running a dual fuel engine at low load in natural gas mode.

Assessing the impact of converting roundabouts to traffic signals on vehicle emissions along an urban arterial corridor in Qatar

ABSTRACTThe type of control at intersections has a major effect on the operation of any urban corridor. Different predefined procedures are available to calculate some of the main operational characteristics, such as capacity, delay, and level of service, in order to select the best type of control. However, there are other important factors that affect major arterials operational characteristics, factors that are not fully addressed, such as the impact of emissions. In this study, a microscopic simulation approach using VISSIM and MOVES was developed to assess the environmental effect of converting four three-lane roundabouts to signalized intersections along a heavily congested urban corridor in Qatar. A decision was made to switch all roundabouts to traffic signals for better operations. Preliminary results indicated that the signal control outperformed the roundabout in the range of 37% to 43% reduction in emissions. A more detailed analysis revealed that roundabout corridor operations’ effects on emission rates are divergent from those of signalized corridors, particularly upstream and downstream of the intersections. Immediate roundabout upstream approaches are driver behavior dependent, characterized by substantial coasting at lower speeds and subsequent re-accelerating with less idling, described as acceleration events, which resulted in high emission rates, while signalized corridors are signal timing dependent, characterized by ample idling with less coasting and re-acceleration, resulting in reduced emission rates. The results also revealed that there was no significant difference between emission rates in the vicinity of the two types of control. Both recorded nearly the same emission rate.Implications: A microscopic simulation approach using VISSIM and MOVES was developed to assess the environmental effect of converting four three-lane roundabouts to signalized intersections along a heavily congested urban corridor in Doha, Qatar. Intersection geometries along with the control type have significant impact on emission rates and play a major role in assessing environmental impacts. US EPA MOVES was calibrated to Qatar conditions which can be used to estimate emission factors and quantify vehicular emissions along other corridors in the country. The results can also be beneficial for other countries within the region.

Constraining the Emission of Particulate Matter From Indonesian Peatland Burning Using Continuous Observation Data

AbstractTropical peatland, which dominantly distributes in Indonesia and Malaysia, has experienced recurring fires in the last few decades. Constraining the enhancement ratios and emission factors of gas and particulate matter emitted by the wildfires is necessary to evaluate their environmental and climatic impacts. We analyzed continuous observation data at Pekanbaru in Indonesia and Muar in Malaysia to investigate the emissions of gas and particulate matter. The enhancement ratios of particulate matter to carbon monoxide (PM10/CO) of wildfires in Riau province in June 2013 and February–March 2014 were analyzed. The PM10/CO ratios of peatland burning plumes ranged from 77 to 97 μg mg−1 for the event in June 2013, whereas the corresponding value was 127 μg mg−1 in February–March 2014. These enhancement ratios were translated to the emission factors of particulate matter using previous data on the emission factors of CO, assuming that secondary formation was ignorable. The estimated emission factors for PM10 were 13 ± 2 g kg−1 (2013) and 19 ± 2 g kg−1 (2014). These values are comparable to those reported by recent field observations in Indonesia and Malaysia (17.3 ± 6.0 to 34.4 ± 18.8 g kg−1). The estimated emission factors from both the present study and recent field work are consistently higher than that used in the current emission inventory, which suggests that it should be updated. A caveat for this analysis is possible influence of secondary formation, which will still be needed to be investigated in future studies.

Uncertainty estimation of road-dust emissions via interval statistics

Particulate matter, a.k.a. particle pollution, is a complex mixture of small particles and liquid droplets that are present in the air. Once inhaled, these particles can affect the heart and lungs and cause serious health problems. A recent study, based on geographically referenced datasets of pollutant emissions has shown that non-exhaust related pollution is at present dominant and increasing. Emissions from paved roads are poorly estimated due to the lack of knowledge about the resuspension process. Recent literature works have attempted to provide a reliable framework for the estimation of emission factors. Estimations are obtained by linear regression with a single-valued discriminant for the acceptance/rejection of the experimental dataset based on the evaluation of the r-squared coefficient. In this paper, we explore alternative methods to evaluate the “quality” of the data and consequently discriminate whether a given sample can be accepted to provide estimation of the emission factors. Uncertainties are characterised both in the data and in the statistical model. Measurements are expressed with interval-valued datapoints to include the experiment precision directly within the estimation process. Alternative fitting techniques that avoid the use a single-valued discriminant are also explored for an inclusive estimation of the emission factors.