Quantification of Methane Emissions from Cold Heavy Oil Production with Sand Extraction in Alberta and Saskatchewan, Canada.

Cold heavy oil production with sand (CHOPS) is an extraction process for heavy oil in Canada, with the potential to lead to higher CH4 venting than conventional oil sites, that have not been adequately characterized. In order to quantify CH4 emissions from CHOPS activities, a focused aerial measurement campaign was conducted in the Canadian provinces of Alberta and Saskatchewan in June 2018. Total CH4 emissions from each of 10 clusters of CHOPS wells (containing 22-167 well sites per cluster) were derived using a mass balance computation algorithm that uses in situ wind data measurement on board aircraft. Results show that there is no statistically significant difference in CH4 emissions from CHOPS wells between the two provinces. Cluster-aggregated emission factors (EF) were determined using correspondingly aggregated production volumes. The average CH4 EF was 70.4 ± 36.9 kg/m3 produced oil for the Alberta wells and 55.1 ± 13.7 kg/m3 produced oil for the Saskatchewan wells. Using these EF and heavy oil production volumes reported to provincial regulators, the annual CH4 emissions from CHOPS were estimated to be 121% larger than CHOPS emissions extracted from Canada's National Inventory Report (NIR) for Saskatchewan. The EF were found to be positively correlated with the percentage of nonpiped production volumes in each cluster, indicating higher emissions for nonpiped wells while suggesting an avenue for methane emission reductions. A comparison with recent measurements indicates relatively limited effectiveness of regulations for Saskatchewan compared to those in Alberta. The results of this study indicate the substantial contribution of CHOPS operations to the underreporting observed in the NIR and provide measurement-based EF that can be used to develop improved emissions inventories for this sector and mitigate CH4 emissions from CHOPS operations.

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.

Quantifying Methane Influx from Sewer into Wastewater Treatment Processes.

Wastewater treatment contributes substantially to methane (CH4) emissions, yet monitoring and tracing face challenges because the treatment processes are often treated as a "black box". Particularly, despite growing interest, the amount of CH4 carryover and influx from the sewer and its impacts on overall emissions remain unclear. This study quantified CH4 emissions from six wastewater treatment plants (WWTPs) across China, utilizing existing multizonal odor control systems, with a focus on Beijing and Guiyang WWTPs. In the Beijing WWTP, almost 90% of CH4 emissions from the wastewater treatment process were conveyed through sewer pipes, affecting emissions even in the aerobic zone of biological treatment. In the Guiyang WWTP, where most CH4 from the sewer was released at the inlet well, a 24 h online monitoring revealed CH4 fluctuations linked to neighborhood water consumption and a strong correlation to influent COD inputs. CH4 emission factors monitored in six WWTPs range from 1.5 to 13.4 gCH4/kgCODrem, higher than those observed in previous studies using A2O technology. This underscores the importance of considering CH4 influx from sewer systems to avoid underestimation. The odor control system in WWTPs demonstrates its potential as a cost-effective approach for tracing, monitoring, and mitigating CH4.

Reevaluating the Drivers of Fertilizer-Induced N2O Emission: Insights from Interpretable Machine Learning.

Direct nitrous oxide (N2O) emissions from fertilizer application are the largest anthropogenic source of global N2O, but the factors influencing these emissions remain debated. Here, we compile 1134 observations of fertilizer-induced N2O emission factor (EF) from 229 publications, covering various regions and crops globally. We then employ an interpretable machine learning model to investigate the driving factors of fertilizer-induced N2O emissions. Our results reveal that pH, soil organic carbon, precipitation, and temperature are the most influential factors, overweighing the impacts of management practices. Nitrogen application rate has a positive impact on the EF, but the effect diminishes as nitrogen application rate increases, which has been overestimated in previous studies. Soil pH has three-stage influence on EF: positive when 7.3 ≤ pH ≤ 8.7, significantly negative between 6.8 and 7.3, and insignificant at lower pH levels (4.7 ≤ pH ≤ 6.8). Moreover, we confirm the nonlinear contributions of temperature and precipitation to EF, which may cause an unexpected increase in N2O emission under climate change. Our research provides crucial insights for global N2O modeling and mitigation strategies.

Direct and indirect monitoring methods for nitrous oxide emissions in full-scale wastewater treatment plants: A critical review.

Mitigation of nitrous oxide (N2O) emissions in full-scale wastewater treatment plant (WWTP) has become an irreversible trend to adapt the climate change. Monitoring of N2O emissions plays a fundamental role in understanding and mitigating N2O emissions. This paper provides a comprehensive review of direct and indirect N2O monitoring methods. The techniques, strengths, limitations, and applicable scenarios of various methods are discussed. We conclude that the floating chamber technique is suitable for capturing and interpreting the spatiotemporal variability of real-time N2O emissions, due to its long-term in-situ monitoring capability and high data acquisition frequency. The monitoring duration, location, and frequency should be emphasized to guarantee the accuracy and comparability of acquired data. Calculation by default emission factors (EFs) is efficient when there is a need for ambiguous historical N2O emission accounts of national-scale or regional-scale WWTPs. Using process-specific EFs is beneficial in promoting mitigation pathways that are primarily focused on low-emission process upgrades. Machine learning models exhibit exemplary performance in the prediction of N2O emissions. Integrating mechanistic models with machine learning models can improve their explanatory power and sharpen their predictive precision. The implementation of the synergy of nutrient removal and N2O mitigation strategies necessitates the calibration and validation of multi-path mechanistic models, supported by long-term continuous direct monitoring campaigns.

Experimental assessment of pollutant emissions from residential fuel cells and comparative benchmark analysis.

Energy transition currently brings focus on fuel cell micro-combined heat and power (mCHP) systems for residential uses. The two main technologies already commercialized are the Proton Exchange Membrane Fuel Cells (PEMFCs) and Solid Oxide Fuel Cells (SOFCs). The pollutant emissions of one system of each technology have been tested with a portable probe both in laboratory and field-test configurations. In this paper, the nitrogen oxides (NOx), sulphur dioxide (SO2), and carbon monoxide (CO) emission levels are compared to other combustion technologies such as a recent Euro 6 diesel automotive vehicle, a classical gas condensing boiler, and a gas absorption heat pump. At last, a method of converting the concentration of pollutants (in ppm) measured by the sensors into pollutant intensity per unit of energy (in mg/kWh) is documented and reported. This allows for comparing the pollutant emissions levels with relevant literature, especially other studies conducted with other measuring sensors. Both tested residential fuel cell technologies fed by natural gas can be considered clean regarding SO2 and NOx emissions. The CO emissions can be considered quite low for the tested SOFC and even nil for the tested PEMFC. The biggest issue of natural gas fuel cell technologies still lies in the carbon dioxide (CO2) emissions associated with the fossil fuel they consume. The gas absorption heat pump however shows worse NOx and CO levels than the classical gas condensing boiler. At last, this study illustrates that the high level of hybridization between a fuel cell and a gas boiler may be responsible for unexpected ON/OFF cycling behaviours and therefore prevent both sub-systems from operating as optimally and reliably as they would have as standalone units.

Complete long-term monitoring of greenhouse gas emissions from a full-scale industrial wastewater treatment plant with different cover configurations.

The greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs), consisting mainly of methane (CH4) and nitrous oxide (N2O), have been constantly increasing and become a non-negligible contributor towards carbon neutrality. The precise evaluation of plant-specific GHG emissions, however, remains challenging. The current assessment approach is based on the product of influent load and emission factor (EF), of which the latter is quite often a single value with huge uncertainty. In particular, the latest default Tier 1 value of N2O EF, 0.016 ± 0.012 kgN2O-N kgTN-1, is estimated based on the measurement of 30 municipal WWTPs only, without involving any industrial wastewater. Therefore, to resolve the pattern of GHG emissions from industrial WWTPs, this work conducted a 14-month monitoring campaign covering all the process units at a full-scale industrial WWTP in Shanghai, China. The total CH4 and N2O emissions from the whole plant were, on average, 447.7 ± 224.5 kgCO2-eq d-1 and 1605.3 ± 2491.0 kgCO2-eq d-1, respectively, exhibiting a 5.2- or 3.9-times more significant deviation than the influent loads of chemical oxygen demand (COD) or total nitrogen (TN). The resulting EFs, 0.00072 kgCH4 kgCOD-1 and 0.00211 kgN2O-N kgTN-1, were just 0.36% of the IPCC recommended value for CH4, and 13.2% for N2O. Besides, the parallel anoxic-oxic (A/O) lines of this industrial WWTP were covered in two configurations, allowing the comparison of GHG emissions from different odor control setup. Unit-specific analysis showed that the replacement of enclosed A/open O with enclosed A/O reduced the CH4 EF by three times, from 0.00159 to 0.00051 kgCH4 kgCOD-1, and dramatically decreased the N2O EF by an order of magnitude, from 0.00376 to 0.00032 kgN2O-N kgTN-1, which was among the lowest of all full-scale WWTPs.

Urbanization can accelerate climate change by increasing soil N2 O emission while reducing CH4 uptake.

Urban land-use change has the potential to affect local to global biogeochemical carbon (C) and nitrogen (N) cycles and associated greenhouse gas (GHG) fluxes. We conducted a meta-analysis to (1) assess the effects of urbanization-induced land-use conversion on soil nitrous oxide (N2 O) and methane (CH4 ) fluxes, (2) quantify direct N2 O emission factors (EFd ) of fertilized urban soils used, for example, as lawns or forests, and (3) identify the key drivers leading to flux changes associated with urbanization. On average, urbanization increases soil N2 O emissions by 153%, to 3.0 kg N ha-1  year-1 , while rates of soil CH4 uptake are reduced by 50%, to 2.0 kg C ha-1  year-1 . The global mean annual N2 O EFd of fertilized lawns and urban forests is 1.4%, suggesting that urban soils can be regional hotspots of N2 O emissions. On a global basis, conversion of land to urban greenspaces has increased soil N2 O emission by 0.46 Tg N2 O-N year-1 and decreased soil CH4 uptake by 0.58 Tg CH4 -C year-1 . Urbanization driven changes in soil N2 O emission and CH4 uptake are associated with changes in soil properties (bulk density, pH, total N content, and C/N ratio), increased temperature, and management practices, especially fertilizer use. Overall, our meta-analysis shows that urbanization increases soil N2 O emissions and reduces the role of soils as a sink for atmospheric CH4 . These effects can be mitigated by avoiding soil compaction, reducing fertilization of lawns, and by restoring native ecosystems in urban landscapes.

Sub-23 nm Particles Dominate Non-Volatile Particle Number Emissions of Road Traffic.

Ultrafine particles (<100 nm) in urban air are a serious health hazard not yet fully understood. Therefore, particle number concentration monitoring was recently included in the WHO air quality guidelines. At present, e.g., the EU regulates particle number only regarding the emissions of solid particles larger than 23 nm emitted by vehicles. The aim of this study was to examine the non-volatile fraction of sub-23 nm particles in a traffic-influenced urban environment. We measured the number concentration of particles larger than 1.4, 3, 10, and 23 nm in May 2018. Volatile compounds were thermally removed in the sampling line and the line losses were carefully determined. According to our results, the sub-23 nm particles dominated the non-volatile number concentrations. Additionally, based on the determined particle number emission factors, the traffic emissions of non-volatile sub-10 nm particles can be even 3 times higher than those of particles larger than 10 nm. Yet, only a fraction of urban sub-10 nm particles consisted of non-volatiles. Thus, while the results highlight the role of ultrafine particles in the traffic-influenced urban air, a careful consideration is needed in terms of future particle number standards to cover the varying factors affecting measured concentrations.

Tracer-Gas-Integrated Measurements of Brake-Wear Particulate Matter Emissions from Heavy-Duty Vehicles.

Automotive brake-wear emissions are increasingly important in on-road particulate matter (PM) emission inventory. Previous studies reported a high level of PM emissions from the friction materials of light/medium-duty vehicles, but there are few data available from heavy-duty (HD) vehicles equipped with drum brakes despite their popularity (∼85% in HD vehicle fleet). This study developed a novel tracer-gas-integrated method for brake-wear PM emission measurements and evaluated four HD vehicles on a chassis dynamometer that complied with regulatory exhaust emission testing requirements. Three class-6 vehicles with a similar test weight demonstrated repeatability, with the coefficient of variation in the range of 9-36%. Braking events increased PM concentrations by 3 orders of magnitude above the background level. Resuspension of brake-wear PM also occurred during acceleration and contributed to 8-31% of the total PM2.5 mass. The class-6 vehicles had PM2.5 emissions from a single brake (0.7-1.5 mg/km/brake), generally similar to the level of tail-pipe exhaust PM emissions (0.7-1.5 mg/km/vehicle) of each vehicle. A class-8 vehicle exhibited brake-wear PM2.5 emissions (2.4-3.4 mg/km/brake) significantly higher than the tail-pipe exhaust PM emissions (∼1.3 mg/km/vehicle). This article reports an exceptionally high level of brake-wear PM emissions measured directly from the drum brakes of HD vehicles.

Present Knowledge and Future Perspectives of Atmospheric Emission Inventories of Toxic Trace Elements: A Critical Review.

Toxic trace elements (TEs) can pose serious risks to ecosystems and human health. However, a comprehensive understanding of atmospheric emission inventories for several concerning TEs has not yet been developed. In this study, we systematically reviewed the status and progress of existing research in developing atmospheric emission inventories of TEs focusing on global, regional, and sectoral scales. Multiple studies have strengthened our understanding of the global emission of TEs, despite attention being mainly focused on Hg and source classification in different studies showing large discrepancies. In contrast to those of developed countries and regions, the officially published emission inventory is still lacking in developing countries, despite the fact that studies on evaluating the emissions of TEs on a national scale or one specific source category have been numerous in recent years. Additionally, emissions of TEs emitted from waste incineration and traffic-related sources have produced growing concern with worldwide rapid urbanization. Although several studies attempt to estimate the emissions of TEs based on PM emissions and its source-specific chemical profiles, the emission factor approach is still the universal method. We call for more extensive and in-depth studies to establish a precise localization national emission inventory of TEs based on adequate field measurements and comprehensive investigation to reduce uncertainty.

Comparative Assessment of Methane Emissions from Onshore LNG Facilities Measured Using Differential Absorption Lidar.

This study provides results from measurements of methane emissions from three onshore LNG liquefaction facilities and two regasification facilities across different regions using the Differential Absorption Lidar (DIAL) technique. The measurement approach was to quantify, at each facility, emissions from the key functional elements (FEs), defined as spatially separable areas related to different identified processes. The DIAL technique enabled quantification of emissions at the FE level, allowing emission factors (EFs) to be determined for each FE using activity data. The comprehensive data set presented here should not be used for annualization, however shows the potential of what could be achieved with a larger sample size in terms of potential methane reduction and improving inventory accuracy. Among the benefits in obtaining data with this level of granularity is the possibility to compare the emissions of similar FEs on different plants including FEs present in both liquefaction and regasification facilities. Emissions from noncontinuous sources and superemitters can also be identified and quantified enabling more accurate inventory reporting and targeted maintenance and repair. Site throughput during the measurement periods was used to characterize total site EF; on average the methane losses were 0.018% and 0.070% of throughput at the regasification and liquefaction facilities, respectively.

Release Behavior of Liquid Crystal Monomers from Waste Smartphone Screens: Occurrence, Distribution, and Mechanistic Modeling.

Liquid crystal display (LCD) screens can release many organic pollutants into the indoor environment, including liquid crystal monomers (LCMs), which have been proposed as a novel class of emerging pollutants. Knowing the release pathways and mechanisms of LCMs from various components of LCD screens is important to accurately assess the LCM release and reveal their environmental transport behavior and fate in the ambient environment. A total of 47, 43, and 33 out of 64 target LCMs were detected in three disassembled parts of waste smartphone screens, including the LCM layer (LL), light guide plate (LGP), and screen protector (SP), respectively. Correlation analysis confirmed LL was the source of LCMs detected in LGP and SP. The emission factors of LCMs from waste screen, SP, and LGP parts were estimated as 2.38 × 10-3, 1.36 × 10-3, and 1.02 × 10-3, respectively. A mechanism model was developed to describe the release behaviors of LCMs from waste screens, where three characteristics parameters of released LCMs, including average mass proportion (AP), predicted subcooled vapor pressures (PL), and octanol-air partitioning coefficients (Koa), involving coexistence of absorption and adsorption mechanisms, could control the diffusion-partitioning. The released LCMs in LGP could reach diffusion-partition equilibrium more quickly than those in SP, indicating that LCM release could be mainly governed through SP diffusions.

Identification and Parametrization of Key Factors Affecting Levoglucosan Emission During Solid Fuel Burning.

Levoglucosan (LG) is a pyrolysis product of cellulose and hemicellulose at low combustion temperatures. However, LG release cannot be determined only by considering the contents of cellulose and hemicellulose exclusively due to the complexity of combustion processes and the physical-chemical properties of the fuel. This study detected the emission factors (EFs) of LG from 22 different solid fuel samples (including coal and biomass) by considering 18 different fuel properties and five combustion parameters. The average LGEFs during solid fuel burning varied in a range of 0.03-136 mg kg-1, with a magnitude difference of 1-4 orders. While the variations in cellulose (59.5-368 mg g-1) and hemicellulose (73.5-165 mg g-1) contents of fuel samples were only one- to 6-fold. A short combustion duration (<150 min) and a medium combustion temperature (200-400 °C) influenced by volatile and ash contents are crucial for the generation and accumulation of LG. A random forest coupled with the Akaike information criterion stepwise regression model successfully explained 96% of the total LG emission variation using three variables (ash content, cellulose content, and modified combustion efficiency). The ash content promoted coke formation and LG chain cracking by increasing the pyrolysis temperature and is considered the most important factor. The alkali metal in ash can reduce the energy barrier of intramolecular ring contraction reactions and inhibit the dehydration reactions, which led to additional heat being utilized by the competitive pathways of LG formation. This study provided a method to address the parametrization and release mechanisms of combustion source emissions.

Real-World Emission Characteristics of Full-Volatility Organics Originating from Nonroad Agricultural Machinery during Agricultural Activities.

Nonroad agricultural machinery (NRAM) emissions constitute a significant source of air pollution in China. Full-volatility organics originating from 19 machines under 6 agricultural activities were measured synchronously. The diesel-based emission factors (EFs) for full-volatility organics were 4.71 ± 2.78 g/kg fuel (average ± standard deviation), including 91.58 ± 8.42% volatile organic compounds (VOCs), 7.94 ± 8.16% intermediate-volatility organic compounds (IVOCs), 0.28 ± 0.20% semivolatile organic compounds (SVOCs), and 0.20 ± 0.16% low-volatility organic compounds (LVOCs). Full-volatility organic EFs were significantly reduced by stricter emission standards and were the highest under pesticide spraying activity. Our results also demonstrated that combustion efficiency was a potential factor influencing full-volatility organic emissions. Gas-particle partitioning in full-volatility organics could be affected by multiple factors. Furthermore, the estimated secondary organic aerosol formation potential based on measured full-volatility organics was 143.79 ± 216.80 mg/kg fuel and could be primarily attributed to higher-volatility-interval IVOCs (bin12-bin16 contributed 52.81 ± 11.58%). Finally, the estimated emissions of full-volatility organics from NRAM in China (2021) were 94.23 Gg. This study provides first-hand data on full-volatility organic EFs originating from NRAM to facilitate the improvement of emission inventories and atmospheric chemistry models.

Air Pollutant Emission Inventory of Waste-to-Energy Plants in China and Prediction by the Artificial Neural Network Approach.

The waste-to-energy (WTE) plant has been deployed in 205 cities in China. However, it always faces public resistance to be built because of the great concerns on flue gas pollutants (FGPs). There are limited studies on the socioeconomic heterogeneity analysis and prediction models of WTE capacity/ FGP emission inventories (EIs) based on big data. In this study, the incinerator level emission factors (EFs) in 2020 of PM, SO2, NOx, CO, HCl, dioxins, Hg, Cd + Tl, and Sb + As+ Pb + Cr + Co + Cu + Mn + Ni were calculated based on 322,926 monitoring values of all the 481 WTE plants (1140 processing lines) operating in China, with uncertainties in the range of ±34.70%. The EFs were significantly 45-96% lower than the national standard (GB18485-2014) and had negative relationships with local socioeconomic elements, while WTE capacity and FGP EIs had significantly positive correlations. Gross domestic product, area of built district, and municipal solid waste generation were the main driving forces of WTE capacity. The WTE capacity increased by 150% from 2015 to 2020, while the total emission of PM, SO2, CO, dioxins, Hg, and Sb + As + Pb + Cr + Co + Cu + Mn + Ni decreased by 42.46-88.24%. The artificial neural network models were established to predict WTE capacity and FGP EIs in the city level, with the mean square errors ranging from 0.003 to 0.19 within the model validation limits. This study provides data and model support for the formulation of appropriate WTE plans and a pollutant emission control scheme in different economic regions.

Characterizing emission factors and oxidative potential of motorcycle emissions in a real-world tunnel environment.

Transportation emissions significantly affect human health, air quality, and climate in urban areas. This study conducted experiments in an urban tunnel in Taipei, Taiwan, to characterize vehicle emissions under real driving conditions, providing emission factors of PM2.5, eBC, CO, and CO2. By applying multiple linear regression, it derives individual emission factors for heavy-duty vehicles (HDVs), light-duty vehicles (LDVs), and motorcycles (MCs). Additionally, the oxidative potential using dithiothreitol assay (OPDTT) was established to understand PM2.5 toxicity. Results showed HDVs dominated PM2.5 and eBC concentrations, while LDVs and MCs influenced CO and CO2 levels. The CO emission factor for transportation inside the tunnel was found to be higher than those in previous studies, likely owing to the increased fraction of MCs, which generally emit higher CO levels. Among the three vehicle types, HDVs exhibited the highest PM2.5 and eBC emission factors, while CO and CO2 levels were relatively higher for LDVs and MCs. The OPDTTm demonstrated that fresh traffic emissions were less toxic than aged aerosols, but higher OPDTTv indicated the impact on human health cannot be ignored. This study updates emission factors for various vehicle types, aiding in accurate assessment of transportation emissions' effects on air quality and human health, and providing a guideline for formulating mitigation strategies.

Complex temperature dependence of vehicular emissions: Evidence from a global meta-analysis.

The significant impact of low ambient temperature, which was less regulated, on vehicle exhaust emissions had garnered considerable attention. This study investigated the impact of ambient temperature on exhaust emissions based on the global meta-analysis. The estimated sizes (mean difference, MDt) of 11 exhaust pollutants were quantified with 1795 observations at low ambient temperatures (LATs, -18 °C to -7 °C) versus warm ambient temperatures (WATs, 20 °C-30 °C). The results indicated a strong and positive effect of LATs on vehicular emissions, with the average ratio of vehicular emission factors at LATs to those at WATs (EFLAT/EFWAT) ranging from 1.14 to 3.84. Oil-based subgroup analysis indicated a quite large MDt [NOx] of diesel engines (12.42-15.10 mg km-1·k-1). Particulate emissions were 0.22-1.41 mg km-1·k-1 enhanced during cold-start tests at LATs. The application of particulate filters on motor vehicles greatly reduced the impact of ambient temperature on tailpipe particulate emissions, at the expense of induced NOx emissions. During the Federal Test Procedure (FTP-75), exhaust emissions showed higher temperature dependence compared to the averaged levels (1.31-39.31 times). Locally weighted regression was used to determine exhaust temperature profiles, revealing that gasoline vehicles emitted more particulates at LATs, while diesel vehicles showed the opposite trend. Given the widespread use of motor vehicles worldwide, future motor vehicle emission standards should include tighter limits on exhaust emissions at LATs.

Emission characteristics and light absorption apportionment of carbonaceous aerosols: A tunnel test conducted in an urban with fully enclosed use of E10 petrol.

To reduce the heavy dependence on petroleum, bioethanol has been increasingly employed as an alternative and sustainable transportation fuel. However, the characteristics of black carbon (BC) emissions from E10 petrol vehicles (i.e., ethanol-gasoline containing 10% ethanol) are still unclear, especially under real driving conditions. Here, a tunnel test was conducted during a cold winter. This tunnel was characterized by heavy traffic comprising more than 98% E10-fueled gasoline vehicles (GVs). Real-time BC concentrations, traffic parameters and meteorological conditions were recorded during the sampling campaign. The average BC concentration inside the tunnel (10.94 ± 5.02 µg m-3) was almost twice the background concentration. Based on aethalometer AE33 in situ measurements and the minimum R-squared (MRS) method, real-time aerosol light absorption was apportioned. The light absorption proportions of BC, primary brown carbon (BrC1) and secondary brown carbon (BrC2) were 79.86%, 2.78% and 17.36%, respectively, at 370 nm. The BC emission factor (EFBC) of the E10-fueled vehicles was 1.09 ± 0.49 mg km-1·veh-1 and 15.24 ± 6.85 mg·(kg fuel)-1, lower than those of traditional gasoline fueled vehicles in previous studies. This study can support the compilation of vehicular BC emission inventories, provide recommendations for biofuel policies and contribute to comprehensively understanding the climatic impact of E10 petrol.

Characteristics of annual NH3 emissions from a conventional vegetable field under various nitrogen management strategies.

High N-fertilizer applications to conventional vegetable production systems are associated with substantial emissions of NH3, a key substance that triggers haze pollution and ecosystem eutrophication and thus, causing considerable damage to human and ecosystem health. While N fertilization effects on NH3 volatilization from cereal crops have been relatively well studied, little is known about the magnitude and yield-scaled emissions of NH3 from vegetable systems. Here we report on a 2-year field study investigating the effect of various types and rates of fertilizer application on NH3 emissions and crop yields for a pepper-lettuce-cabbage rotation system in southwest China. Our results show that both NH3 emissions and direct emission factors of applied N varied largely across seasons over the 2-year period, highlighting the importance of measurements spanning entire cropping years. Across all treatments varying from solely applying urea fertilizers to only using organic manures, annual NH3 emissions ranged from 0.64 to 92.4 kg N ha-1 yr-1 (or 0.07-6.84 g N kg-1 dry matter), equivalent to 0.05-5.99% of the applied N. At annual scale, NH3 emissions correlated positively with soil δ15N values, indicating that soil δ15N may be used as an indicator for NH3 losses. NH3 emissions from treatments fertilized partially or fully with manure were significantly lower compared with the urea fertilized treatment, while vegetable yields remained unaffected. Moreover, full substitution of urea by manure as compared to the partial substitution further reduced the yield-scaled annual NH3 emissions by 79.0-92.4%. Across all vegetable seasons, there is a significant negative relationship between yield-scaled NH3 emissions and crop N use efficiency. Overall, our results suggest that substituting urea by manure and reducing total N inputs by 30-50% allows to reduce NH3 emissions without jeopardizing yields. Such a change in management provides a feasible option to achieve environmental sustainability and food security in conventional vegetable systems.