Emission Factors Research Articles

Beyond the average: Emissions from electricity and the implications of decarbonization policies in Guangdong

Various policy interventions have been proposed to decarbonize the Chinese economy through the electricity sector. This study is the first to use generation-by-plant data to analyze the emissions from the electricity sector in a Chinese region and evaluate the environmental impacts of various policy interventions. Using regression techniques, the average emission factor, marginal emission factor, and marginal displacement factor, are estimated for different pollutants of Guangdong, the most affluent and populous province in China. Results reveal a decline in average emission factors over the sample period of 2017–2021, owing to the expansion of renewable energy. This study also finds a less pronounced disparity between marginal emission factors and average emission factors compared with that in developed countries, probably due to the prevalence of coal-burning plants and lower renewable energy penetration in Guangdong. Using the estimated emission factors, this study also examines the environmental effect of time-of-use tariffs, indirect emissions of electric vehicles, and carbon displacement effect of wind energy. The conclusions reveals that the time-of-use tariffs moderately reduced CO2 emissions, and the extensive adoption of electric vehicles and wind energy substantially reduces carbon emissions, indicating that decarbonizing the economy needs the coordination of various policies.

Applying trade mechanisms to quantify dynamic GHG emissions of electricity consumption in an open economy - The case of Switzerland

Quantifying greenhouse gas (GHG) emissions from electricity consumption presents a significant challenge due to the variable nature of the generation mix throughout the year and the complex dynamics of cross-border electricity trade. In this paper, we introduce an innovative methodology designed to accurately capture the hourly GHG emissions linked to electricity imports, and thus electricity consumption. Contrary to conventional approaches, our methodology identifies the relevant generation technologies in exporting countries which are activated for export. This selection is based on (i) the classification of the technologies according to their dispatch cost (merit order), and (ii) considers trade mechanisms from economic theory.We apply this methodology to Switzerland, a country characterized by a low-carbon electricity generation mix, which however heavily relies on imports from neighbouring countries, particularly during the winter months. Over the period from 2017 to 2021, we find that 88 % of Switzerland's domestic electricity demand is met by its own generation—primarily hydro and nuclear—while the remaining 12 % is imported, mainly from fossil-fuel-based sources. Consequently, the average annual GHG emission factor for electricity consumption in Switzerland is 98 g-CO2eq/kWh, with 29 % attributed to domestic generation and 71 % to imports. This figure is 40 % higher than the 70 g-CO2eq/kWh estimated using a conventional approach, which typically underestimates the specific impacts of electricity imports.The disparity between these approaches becomes even more pronounced when considering the seasonal and hourly variations in the electricity mix and the resulting emission factors. These insights are particularly crucial in the context of emerging electricity demands, such as heat pumps and electric vehicles, where accurate GHG accounting can significantly influence policy and investment decisions.

Developing Specific Emission Factors for Natural Gas Driven Pneumatic Devices.

A measurement study was conducted in 2023 to derive operator-specific emission factors for natural gas driven pneumatic devices at onshore production facilities in the United States. A total of 369 intermittent bleed and 26 continuous low-bleed pneumatic devices were measured using a high-volume sampler. Considering all intermittent bleed devices, the emission factor from this study was statistically lower than the factor in the revised Greenhouse Gas Reporting Rule (GHGRP) issued May 6, 2024. Intermittent devices were classified by inspection with an optical gas imaging camera as functioning or malfunctioning. Measurements of functioning intermittent bleed devices were statistically higher while measurements of malfunctioning intermittent bleed devices were statistically lower than the corresponding emission factor in the final revisions to the GHGRP. Measurements of continuous low-bleed pneumatic devices were statistically lower than the updated factor in the final revisions to GHGRP. Additionally, a Monte Carlo analysis was conducted to investigate the potential impact of measurement duration and sample size on emission factors derived for intermittent bleed devices. We conclude that while a short measurement duration may miss actuations of properly operating devices with low vent frequencies, potentially resulting in an emission factor with low bias, the sample size of greater than 300 measurements each greater than 3 min in duration, as included in this study, is unlikely to be biased low in a statistically significant manner, particularly when one considers the material contribution of malfunctioning devices.

Greenhouse gas emission from prescribed fires is influenced by vegetation types in West African Savannas

Greenhouse gas (GHG) emissions from prescribed fires are poorly investigated, resulting in a high uncertainty in GHG budgets. Using, a carbon mass balance approach and experimental prescribed fires in 80 plots, this study assessed carbon emissions and established emission factors (EFs) for carbon dioxides (CO2), carbon monoxide (CO), and methane (CH4) across climate zones and vegetation types. In grass and shrub savannas, fires could burn intensely due to the lower moisture content and continuous spatial distribution of biomass fuel, causing greater carbon emissions with 1.61 ± 0.13 t C ha−1 and 1.01 ± 0.13 t C ha−1, respectively. Despite their low carbon emissions, tree savannas (1658.17 ± 11.13 g kg−1) and woodlands (1629.94 ± 12.23 g kg−1) have the highest EFs, which can be attribute to the high carbon content of biomass fuel in these vegetation types. Vegetation types and their interaction with climate zones have a substantial impact on carbon emissions and carbon species EFs, and should therefore be considered in assessing GHG emissions from fires. The findings from this study provide a useful basis for improving the national measurement, reporting, and verification of GHG emissions and for improving the measurement of the global balance of GHG emissions from fires.

Onboard test-based exhaust emission factors for marine diesel engines on anchor handling tug supply vessels

In order to accurately assess China’s port air pollution caused by AHTS (Anchor Handling Tug Supply Vessels) ships, 46 diesel engines on 27 AHTS ships were tested for onboard emissions using a large gas analyzer to statistically analyze their fuel-based and power-based emission factors. The results show that fuel-based NOx-emission factors for MEs, SEs and AEs before and after the use of the SCR system are 45.4, 38.24,33.04 g/kg and 6.35, 4.98, 5.82 g/kg, CO-emission factors are 7.95, 6.30, 7.96 g/kg and 6.90, 6.93, 8.32 g/kg, THC-emission factors are 0.49, 0.64, 0.25 g/kg and 0.42, 0.47, 0.22 g/kg, and CO2-emission factors are 3121.62, 3121.34, 3093.12 g/kg and 3088.14,3091.40, 3085.21 g/kg, respectively. Power-based NOx-emission factors for MEs, SEs and AEs before and after the use of the SCR system are 9.71, 8.61, 7.58 g/(kW·h) and 1.37, 1.23, 1.33 g/(kW·h), CO-emission factors are 1.71, 2.08, 1.84 g/(kW·h) and 1.47, 1.53, 1.93 g/(kW·h), THC-emission factors are 0.10, 0.14, 0.05 g/(kW·h) and 0.09, 0.13, 0.06 g/(kW·h), and CO2-emission factors are 671.73, 700.58, 718.46 g/(kW·h) and 664.42, 694.16, 716.92 g/(kW·h), respectively. The power-based emission factor is closely related to the diesel engine load, and the relationship between different exhaust emissions and diesel engine load shows different patterns. In addition, it was found that the NOx emissions of the ship decreased significantly to meet the IMO Tier III requirements after running SCR. The emission factors of CO, HC and CO2 have no obvious change whether SCR systems were operated or not. The AHTS marine engine emission factors obtained in this paper are highly relevant and can provide reliable data for establishing a suitable emission inventory for medium and high speed engineering support vessels.

Source Profiles of VOCs for Different Types of Industrial Boilers in Sichuan, China

Seven different types of industrial boilers in Sichuan Province were selected to determine the VOC emission components and the source profiles of VOCs containing 115 components were established using Teflon sampling and GC-MS/FID analysis. The ozone formation potential （OFP） and emission factors of VOCs from different types of industrial boilers were analyzed. The results showed that the VOC components emitted from different types of industrial boilers were different. Oxygenated volatile organic compounds （OVOCs） and halogenated hydrocarbons were the major components of biomass boilers, with a total contribution rate of more than 60%. The primary VOC emission species included dichloromethane, ethylene, acetone, acetaldehyde, acetylene, and toluene. Halogenated hydrocarbons （50.7%） were the chief emission components of coal-fired boilers, followed by aromatic hydrocarbons and OVOCs. Dichloromethane, ethylene, acetaldehyde, ethyl acetate, and benzene hydrocarbon were the major VOC emission species. The emission of alkanes （59.7%） in natural gas boilers was prominent, particularly ethane and isopentane. The OFP values of VOC emissions from coal-fired, biomass, and natural gas industrial boilers were 6.1, 28.7, and 4.7 mg·m-3, respectively. Alkenes were the primary OFP contributors （35.1%-59.5%） in different types of industrial boilers. OVOCs （32.8%） in biomass boilers and aromatic hydrocarbons （43.0%） in coal-fired boilers also contributed significantly to OFP. The VOC emission factors of coal-fired, biomass, and natural gas industrial boilers in Sichuan Province were （17.3 ± 10.7） g·t-1, （90.6 ± 42.1） g·t-1, and 0.10 g·m-3, respectively. The VOC emission level of biomass boilers was higher than that of coal-fired boilers and VOC emission control could not be ignored.

Coarse bubble mixing in anoxic zone greatly stimulates nitrous oxide emissions from biological nitrogen removal process

The biological nitrogen removal process in wastewater treatment inevitably produces nitrous oxide (N2O), a potent greenhouse gas. Coarse bubble mixing is widely employed in wastewater treatment processes to mix anoxic tanks; however, its impacts on N2O emissions are rarely reported. This study investigates the effects of coarse bubble mixing on N2O emissions in a pilot-scale mainstream nitrite shunt reactor over a 50-day steady-state period. Online and offline N2O monitoring campaigns show that coarse bubble mixing in the anoxic zones significantly elevates N2O emissions, yielding an extremely high emission factor of 15.5 ± 3.5 %. Intensive sampling and isotopic analyses suggest that the elevated emissions are primarily due to the inhibition of the N2O denitrification process by oxygen in the anoxic phase introduced by coarse bubbling. Substituting coarse bubble mixing with submersible pump mixing resulted in a substantial reduction of N2O emissions, decreasing the emission factor by an order of magnitude to 1.2 ± 0.8 %. The findings reveal that a previously overlooked factor, coarse bubble mixing, can significantly stimulate N2O emissions. The use of coarse bubble mixing in anoxic tanks of biological nitrogen removal warrants caution.

In-situ online investigation of biogenic volatile organic compounds emissions from tropical rainforests in Hainan, China

Biogenic volatile organic compounds (BVOCs) emitted by tropical plants represent a significant proportion of global emissions, but the in-situ BVOC measurements in tropical rainforests are extremely sparse. Herein, a vehicle-mounted mobile monitoring system was developed for in-situ online investigations of BVOC emissions from thirty representative tree species in the tropical rainforests of Hainan Island, southern China. The results showed that monoterpenes were the primary BVOCs emitted from most broadleaf trees. Isoprene, sabinene, γ-terpinene and β-ocimene were the most abundant BVOCs. Localized canopy-scale emission factors (EFs) exhibited notable discrepancies with the defaults in the Model of Emissions of Gases and Aerosols from Nature (MEGAN), specifically with isoprene EFs being slightly lower than the model, while the EFs for monoterpenes and sesquiterpenes were 1 to 27 times higher than those in MEGAN. The BVOC emission inventory for the predominant mature forest species in Hainan Island in 2023 was further estimated to be 244.43 Gg C·yr−1, with isoprene and monoterpenes accounting for 74 % and 16 %, respectively. Additionally, unimodal monthly variation patterns were revealed, with BVOC emissions peaked in July (30.08 Gg C·yr−1) and bottomed in January (8.84 Gg C·yr−1). This study demonstrates the potential and versatility of the applied mobile platform for in-situ online measurements of plant volatiles. Our findings provide important data support for reducing uncertainties in BVOC emission estimations in tropical rainforests and for evaluating their health benefits in the context of forest therapy.

Fuel consumption and exhaust emissions from Euro 6d vehicles fueled by innovative LPG/DME blend

The aim of this research was to investigate the exhaust emissions from vehicles when fueled by a new and fully renewable fuel if made of bio-LPG and renewable dimethyl ether (DME), in comparison with standard gasoline. For this purpose, DME was mixed with liquefied petroleum gas (LPG) and used to fuel three bi-fuel LPG/gasoline spark-ignition engines light-duty vehicles. The suitable fuel blend was selected based on several octane tests using CFR engines. Exhaust emissions were tested over the WLTC and over the hot-start CADC cycles, as well as on the road. All Euro 6 standards were well fully met over the WLTC with both fuels. Switching from gasoline to LPG/DME fueling, the CO and NOx emission factors increased for two vehicles, whereas THC and NMHC decreased. Regarding particulates, for two vehicles the emission factors decreased, too. Generally, when the vehicles were driven on the CADC, lower gaseous emissions were observed compared to WLTC: excluding one vehicle, when switching from gasoline to LPG/DME fueling, the overall emission profiles reflected those of the same vehicles run on the WLTC. The unregulated particulate emissions measured over both testing cycles reflect what was detected for the regulated ones. Except for PN10, which was not measured, all regulated emissions were found to meet the (most severe) Euro 7 standards proposed at first by the European Commission. RDE tests showed that all vehicle emissions obtained from on-road tests were also found to meet the RDE standards, regardless of the fueling. Concerning CO2 emissions, LPG/DME fueling guaranteed a systematic decrease for all vehicles and cycles, both on road and in the laboratory. The present investigation aims at demonstrating that the innovative LPG/DME 80 %/20 % (m/m) blend not only can be deemed as potentially suitable for GHG emissions reduction, as long as both DME and propane are obtained from renewable sources, but even compliant with EN 589 and both Euro 6 and part of preliminary Euro 7 exhaust emission proposal.

Computation of Particulate Emission Load from Vehicular Traffic on Road Network

The present study on traffic volume monitoring aims to compute total particulate emission load from urban road vehicular traffic and to find average emission factor. An industrial area Pandesara was selected as study area for its commercial and industrial activity, the contribution of public and private vehicle emissions in this area were high. Vehicle emissions include tailpipe emissions and road dust resuspensions. Tailpipe emission was the highest in off- road vehicles even their traffic volume was the least of all. Road dust resuspension due to vehicular speed was highest in 2 wheelers. Road dust resuspension concentrations due to silt fraction was found to be maximum in heavy motor vehicles. Total particulate matters concentrations emitted from vehicles and average emission factor were found to be 251616 gm/hr and 0.79 gm/Veh/Km respectively for entire Pandesara zone. Road dust resuspension plays a significant role in vehicular emission, still having less awareness among people worldwide. Keywords: Particulate Matter, Tailpipe Emission, Traffic Volume, Speed, Road Dust Resuspension, Turbulent Wake Height

The Environmental Impacts of Future Global Sales of Hydrogen Fuel Cell Vehicles

During the last decade, developing more sustainable transportation modes has become a primary objective for car manufacturers and governments around the world to mitigate environmental issues, such as climate change, the continuous increase in greenhouse gas (GHG) emissions, and energy depletion. The use of hydrogen fuel cell technology as a source of energy in electric vehicles is considered an emerging and promising technology that could contribute significantly to addressing these environmental issues. In this study, the effects of Hydrogen Fuel Cell Battery Electric Vehicles (HFCBEVs) on global GHG emissions compared to other technologies, such as BEVs, were determined based on different relevant factors, such as predicted sales for 2050 (the result of the developed prediction model), estimated daily traveling distance, estimated future average global electricity emission factors, future average Battery Electric Vehicle (BEV) emission factors, future global hydrogen production emission factors, and future average HFCBEV emission factors. As a result, the annual GHG emissions produced by passenger cars that are expected to be sold in 2050 were determined by considering BEV sales in the first scenario and HFCBEV replacement in the second scenario. The results indicate that the environmental benefits of HFCBEVs are expected to increase over time compared to those of BEVs, due to the eco-friendly methods that are expected to be used in hydrogen production in the future. For instance, in 2021, HFCBEVs could produce more GHG emissions than BEVs by 54.9% per km of travel, whereas in 2050, BEVs could produce more GHG emissions than HFCBEVs by 225% per km of travel.

A Review of Cradle-to-Gate Greenhouse Gas Emission Factors for Canada’s Harvested Wood Products

Abstract With the previous decade’s (2010 through 2019) greenhouse gas emissions remaining the highest on record, focus on emissions mitigation efforts is paramount. Harvested wood products (HWPs) can store carbon for various timespans depending on the product and its end uses. Life cycle inventories (LCIs) are the base for life cycle analyses (LCAs), as they represent a comprehensive catalogue of the raw data essential to complete an LCA. However, most LCI documentation is in the form of case studies of different types of HWPs, with varying LCI results that reflect varied system boundaries, case-specific conditions, and assumptions. Our goal was to conduct a systematic literature review to evaluate, analyze, and synthesize previously reported Canadian HWP data and to initiate a Canadian database based on reported cradle-to-gate HWP emission factors. HWPs were categorized as lumber, traditional structural panels, mass timber, nonstructural panels, and wood pellets. Based on our analysis, we found that softwood lumber produced the lowest cradle-to-gate emission factor (61.99 kg of CO2 equivalent [CO2eq] per m3 HWP) while I-joists produced the highest (218.55 kg of CO2eq per m3 HWP). Resource extraction emissions accounted for most of the overall emissions for softwood lumber, oriented strand board, cross-laminated timber, and glue-laminated timber. Meanwhile, manufacturing accounted for most of the emissions for plywood, I-joists, cellulosic fiberboard, particleboard, and wood pellets. Substantial gaps exist in published LCI data and, when possible, publishing detailed LCI data is encouraged to support additional HWP life cycle analyses.

Emission inventory of IVOCs from diesel engine emissions in China based on real-world measured data

Intermediate volatility organic compounds (IVOCs), recognized as significant precursors of secondary organic aerosols, play a pivotal role in environmental pollution. This study utilized measured real-world emission factors to construct an inventory of IVOC emissions from diesel engines and to analyze their spatial distribution across China in 2022. Furthermore, the emission inventory derived from this approach was compared with that obtained through the IVOC/primary organic aerosol (POA) ratio method. The following findings were observed: (1) In 2022, the total IVOC emissions from diesel engines in China amounted to approximately 430 Gg, surpassing those emitted by gasoline engines and residential solid fuel combustion. Specifically, the IVOC emissions attributed to on-road diesel vehicles, inland vessels, agricultural machinery, and non-road construction machinery were recorded at 377, 39.3, 10.4 and 3 Gg, respectively. (2) In terms of geographical distribution in 2022, IVOC emissions from diesel engines were predominantly concentrated in Eastern, Southern and Northern China; on-road diesel vehicle emissions were primarily located within logistics hubs or regions characterized by extensive national and arterial road networks; while non-road construction and agricultural machinery emissions were largely confined to Eastern and Central China. Emissions from inland vessels exhibited a more distinct regional pattern concentrated mainly within the Yangtze River Delta, Pearl River Delta, and Bohai Rim areas. (3) A comparative analysis between the inventory established using real-world measured emission factors and that derived via IVOC/POA ratios indicated that the latter methodology may have overestimated emissions associated with inland vessels and non-road construction machinery. Moving forward, reducing IVOC emissions from diesel engines is crucial for enhancing air quality and safeguarding human health-particularly concerning heavy-duty vehicles, light-duty vehicles, and inland vessels.

Online characterization of primary and secondary emissions of particulate matter and acidic molecules from a modern fleet of city buses

Abstract. The potential impact of transitioning from conventional fossil fuel to a non-fossil-fuel vehicle fleet was investigated by measuring primary emissions via extractive sampling of bus plumes and assessing secondary mass formation using the Gothenburg Potential Aerosol Mass (Go:PAM) reactor from 76 in-use transit buses. Online chemical characterization of gaseous and particulate emissions from these buses was conducted using chemical ionization mass spectrometry (CIMS) with acetate as the reagent ion, coupled with the Filter Inlet for Gases and AEROsols (FIGAERO). Acetate reagent ion chemistry selectively ionizes acidic compounds, including organic and inorganic acids, as well as nitrated and sulfated organics. A significant reduction (48 %–98 %) in fresh particle emissions was observed in buses utilizing compressed natural gas (CNG), biodiesels like rapeseed methyl ester (RME) and hydrotreated vegetable oil (HVO), and hybrid-electric HVO (HVOHEV) compared to diesel (DSL). However, secondary particle formation from photooxidation of emissions was substantial across all the fuel types. The median ratio of particle mass emission factors of aged to fresh emissions increased in the following order: DSL buses at 4.0, HVO buses at 6.7, HVOHEV buses at 10.5, RME buses at 10.8, and CNG buses at 84. Of the compounds that can be identified by CIMS, fresh gaseous emissions from all Euro V/EEV (Enhanced Environmentally friendly Vehicle) buses, regardless of fuel type, were dominated by nitrogen-containing compounds such as nitrous acid (HONO), nitric acid (HNO3), and isocyanic acid (HNCO), alongside small monoacids (C1−C3). Notably, the emission of nitrogen-containing compounds was lower in Euro VI buses equipped with more advanced emission control technologies. Secondary gaseous organic acids correlated strongly with gaseous HNO3 signals (R2=0.85–0.99) in Go:PAM, but their moderate to weak correlations with post-photooxidation secondary particle mass suggest that they are not reliable tracers of secondary organic aerosol formation from bus exhaust. Our study highlights that non-regulated compounds and secondary pollutant formation, not currently addressed in legislation, are crucial considerations in the evaluation of environmental impacts of future fuel and engine technology shifts.

Transforming the feeding regime towards low-input increases the environmental impact of organic milk production on a case study farm in central germany

Abstract Purpose Despite the direct effect of the feeding regime on the environmental impacts of dairy farming systems, its level of intensity, particularly in organic systems, has rarely been investigated. This study compares the environmental impact of a high-input feeding regime with a grassland-based, low-input feeding regime scenario within an organic milk production system conducted on Gladbacherhof, the research farm of Justus Liebig University Giessen, in Central Germany. Methods An integrated Life Cycle Assessment (LCA) analysis was performed from a cradle-to-farm gate perspective to quantify five environmental impacts, namely Global Warming (GW), Non-Renewable Energy Use (NREU), Land Use (LU), Terrestrial Acidification (TA), and Freshwater Eutrophication (FE). All agronomic data of the Gladbacherhof research farm, averaged over the years 2010–2017, were included. When not directly measured on the farm, ecoinvent data were included. Results and discussion Contrary to our hypothesis, the results suggest that a grassland-based low-input system has a higher environmental impact as compared to a high-input system for each of the five impact categories when using fat and protein-corrected milk (FPCM) as the functional unit. A 50% reduction in concentrates and exclusion of maize silage from the feed ration in the modelled low-input production system lead to a 20% drop in milk yield. To balance the energy content in low-input feeding ration, longer grazing period and higher amount of hay, alfalfa, and grass silage are required. This in turn results in higher emissions from enteric fermentation, manure management, and feed production and hence in higher environmental impact, particularly for GW, TA, and FE. Conclusions This study is one of the few that directly explores the environmental impact of feeding intensity in an organic milk production system. Nevertheless, there is a lack of research on consolidated emission factors for several greenhouse gas (GHG) sources in organic livestock and cropping systems to perform more robust carbon footprint calculations that comply with the Intergovernmental Panel on Climate Change (IPCC) Tier 3 GHG reporting guidelines. To generalize the results at the regional or national scale, direct comparisons with a larger number of organic farms representative of high-input and low-input intensities are still essential.

Air Pollutant Emission Factors of Inland River Ships under Compliance

Inland river ships (IRSs) use diesel with a lower sulfur content and emit relatively low emissions, making it challenging to monitor their emissions. Sniffer monitoring equipment was installed from August 2020 to June 2022 at the Gezhou Dam of the Yangtze River and monitored emissions from 8,238 IRSs passing through the lock. We partnered with the maritime department to select 100 ships passing through the lock to extract fuel oil samples for direct fuel sulfur content (FSC) detection, which determined the actual FSC of the passing ships. The monitoring data from these 100 ships indicated that the relative error of the SO2 emission factors (EFs) and FSC results is significant at the 10-parts-per-million level. The monitoring data from the remaining 8,138 ships showed that the EFs of NO, NO2, PM2.5, and PM10 were 24.02 ± 16.92 g kg−1, 10.30 ± 18.08 g kg−1, 0.72 ± 0.60 g kg−1, and 0.92 ± 0.70 g kg−1, respectively. The NOx EFs of container ships are higher than those of other ship types, while the PM EFs for different ship types do not significantly differ. Based on these EFs, we calculated the average emission rates for different types of ships passing through locks, which is a real-time measurement method for estimating ship emissions. In addition, a comparison of ship EF measurements over the past 20 years revealed that EF values for SO2, NOx, and PM exhibited a downward trend, with the calculated results of the current study determined to be the lowest numerical level.

P-phenylenediamines (PPDs) and 6PPD-quinone in tunnel PM2.5: From the perspective of characterization, emission factors, and health risks

P-phenylenediamines (PPDs) and a quinone derivative (6PPD-Q), as antioxidants added to tires, can inevitably enter into the environment during tire wear emission, posing potential health and ecological risks. However, investigation on their pollution characteristics in PM2.5 is still lacking, especially for high-pollution scenarios, such as tunnels. Herein, we investigated the pollution characteristics and emission factors, as well as the correlation analysis and daily intakes of PM2.5-bound PPDs and 6PPD-Q in tunnel. The results indicated heavy PPDs and 6PPD-Q pollution were observed in tunnel PM2.5, with the concentration at the two tunnel sites being 3.83 and 8.73 times higher than those at the urban site, respectively. PPDs were negatively correlated to relative humidity and positively to temperature. Emission factors of 6PPD and 6PPD-Q were 3013.54 and 1466.67 ng·veh−1·km−1 for large vehicles. PPDs and 6PPD-Q were most harmful to children, and annual exposure dosages at the tunnel sites were 4.64 times higher than those at the urban site. This study conducted a comparison of PPDs and 6PPD-Q in urban and tunnel environments for the first time. Our findings clarified the key factors to reduce the pollution of PPDs in tunnel and supported policy-making for emission reduction of PPDs and 6PPD-Q.

Exploring ultrafine particle emission characteristics from in-use light-duty diesel trucks in China using a portable measurement system

Diesel vehicle exhaust is one of the major contributors to ultrafine particles (UFPs) in urban areas in China. However, there is still a lack of knowledge about UFPs emission characteristics from current in-use diesel vehicles. This study has carried out an on-road test of 10 in-use Light-duty Diesel Trucks (LDDTs) with different emission control standards in China using a self-established portable measurement system based on the Electronic Low-pressure Impactor (ELPI) and characterized the ultrafine particle number (PN) concentration, particle size distribution and metal element contents. The results revealed a significant reduction of 93.37% in the average PN0.1 emission factor of LDDTs from China IV to China VI. Notably, LDDTs compliant with the China VI vehicle emission control standard exhibited the lowest PN0.1 and PM0.1 emission factors, measuring 4.991×1014 #/km and 0.627 g/km, respectively. By taking into account emissions under real driving conditions, we found that the PN emission rates grow with the increase of the Vehicle Specific Power (VSP). The cold-start phase had higher PN emissions than the hot-start phase, with 8590, 1890, 477, and 22 times higher than those of the ambient air (1.18×105 #/cm3), respectively. The installation of Diesel Particulate Filter (DPF) can decrease UFPs by more than 99.8%, while the PN emission factor during the DPF regeneration stage (1.85×1016 #/km) increased by 5 orders of magnitude that of the DPF normal works (7.51×1011 #/km). Metal element contents analysis shows that Fe, Ca, Al and Mg are the dominant elements in UFPs of LDDT exhaust gas, but the element of Ni is slightly increasing in a China VI, possibly due to the new automotive engine exhaust manifolds being made of Ni instead of cast iron for the purpose of having more high-temperature resistance. Our study demonstrates the importance of monitoring and routine maintenance of exhaust after-treatment systems.

Assessing the influence of actual LNG emission factors within the EU emissions trading system

The shipping sector has been incorporated into the European Union Emissions Trading System (EU-ETS). Undoubtedly, the carbon emission factor is a critical consideration when determining carbon allowances in the EU-ETS, known as EU Allowances (EUAs). In this study, an all-performance carbon emission test was conducted on a marine LNG engine to investigate the differences between the actual carbon emission factor and the reference value. It was observed that the actual carbon emission factor is smaller than the reference value. The test results indicate a discrepancy of approximately 3%, resulting in potential savings of 10,000 to 20,000 dollars in EUAs for a ship consuming 2000 tonnes of LNG fuel annually. Furthermore, variations in the carbon emission factor were observed under different engine operational conditions, fluctuating by around 2% at constant revolutions per minute (RPM). This suggests the need for more suitable emission testing methods to accurately reflect actual emissions and better achieve emission control goals.

Energy consumption modeling in industrial sewing operations: A case study on carbon footprint measurement in the apparel industry

In the textile supply chain, the apparel manufacturing industry heavily relies on energy consumption (EC), contributing to greenhouse gas emissions. Understanding and optimizing energy usage in apparel manufacturing is crucial for sustainable and energy-efficient manufacturing. The EC in the industrial sewing operations is directly linked with sewing parameters, including fabric seam length, standard sewing speed, and stitching time. In general, the carbon footprint of an apparel industry is measured by considering the standard minute value (SMV) and specific energy consumption (SEC). However, these metrics include non-productive time and do not accurately measure actual EC or assess the industry’s carbon footprint. To address these limitations, this case study tackles this technical issue by calculating the stitching time of an industrial sewing machine based on its actual EC derived from the sewing machine’s motor power. This study employs EC modeling for industrial sewing parameters, including fabric seam length, standard sewing speed, and stitching time. This proposed model utilizes real-time data collected during the garment-making process, including fabric spreading, cutting, sewing, and ironing. The study allocates eleven sewing machines for a specific garment style to stitch a basic knit fabric t-shirt. The total EC for the entire garment-making (t-shirt) process at a single line is 0.1052 kWh, equivalent to 59.97 g of CO2 emissions (Bangladesh’s CO2/kWh emission factor). This study explores that a direct-drive servo motor consumes approximately five times less than its maximum motor load power, making it more energy-efficient than other sewing machines. Therefore, this study demonstrates the effectiveness of EC modeling by incorporating industrial sewing parameters and selecting energy-efficient sewing machines to reduce carbon footprints and enhance environmental sustainability in the apparel manufacturing industry.