Atmospheric Environment: X最新文献

Nitrous oxide (N₂O) emissions from organic waste and animal slurry contribute to climate change and endanger our ecosystems. For the development of efficient mitigation technologies, in-depth knowledge of emission processes is needed. This can be obtained by non-destructive, temporal measurements of in-situ soil profiles and the transformation of ammonium (NH₄⁺) during events of emissions. Planar optode imaging is a non-destructive measuring method that can be used to visualize spatiotemporal changes of ammonia (NH₃) and pH in soil systems. In this study, soil amended with dairy processing sludge (DPS) was incubated in static chambers for 23 days, and GHG emissions, NH₃ concentrations and pH in the soil were measured simultaneously over time. The aim was to investigate the potential of applying different planar optodes to provide information that gives insight into processes of N₂O emissions. The DPS was applied to the soil as a surface layer (SL), with untreated soil as a control (CK). We were able to measure N₂O emissions while monitoring spatiotemporal changes of soil pH and NH₃ concentrations. The visualized microscale heterogeneity of the soil contributed to a better understanding of N₂O emission processes. While technical challenges (e.g., humidity sensitivity of the NH₃ optode and airtightness of the chambers) still need to be overcome, the method is a promising non-destructive method to study soil processes after application of different types of soil amendments.

PAHs have been recognised as a major menace to living-beings as well as environment. Several researchers have extensively claimed regarding death-defying nature of PAHs and its derivatives. However, these studies have only considered the ambient air which is a composition of automobile exhausts, industrial emissions etc. as major source of harmful air pollutants. Indoor air quality (IAQ) is an overlooked area since, although many researchers in recent times have been working on the chemistry and composition of IAQ, yet, source determination and nature of pollutants is still a comprehensive area to be explored. With the above stated objective, the present study emphases on 16 USEPA specified PAHs which are allied with particulate matter. Both PM as well as PAHs are some very common and treacherous chemical contaminant accountable for more than a million death globally. PAHs are organic compound which are either attached to PM of various sizes or can exist in gaseous form. Current work precises the concentration of PAHs associated with fine PM i.e., PM_2.5 in indoor environment of south Asian precinct, further, using receptor modelling technique for determination indoor sources responsible for the emanation of specific PAHs. The toxicity equivalent quotient i.e., TEQ evaluated in the study demonstrations that the highest toxicity among all PAHs is exhibited by BaP followed by InP, BKF, BbF. Seasonal variations in the concentration of PAHs and their respective sources were also established using PMF models, which depicted the domination of 3-ring PAHs in winter with 42% contribution in outdoors, whereas, four-ring PAHs dominion in indoors. Similarly, in summer two-ring accounted for 35% in outdoors, and three-ring PAHs contributed highest with 26.8% in indoors. In monsoon PAHs with two-ring contributed highest with 45.2% in outdoors, whereas, 2-ring PAHs contributed 38.3% in indoors. Also, IDW mapping and molecular diagnostic ratio were assessed for an intense study on distribution of PAHs in the locality and the source apportionment purpose respectively. To the best of our knowledge, the study is first of its kind in this part of the world where, majority of the countries are either developing or under-developed and hence at greater risk to the noxious effects which are often overlooked. The study will provide a clear picture regarding the indoor sources of the PAHs and further help the further professionals to build a credible and pragmatic mitigation technique accordingly.

Benzene as one type of hazardous air pollutants (HAPs) is produced by industrial production processes and/or emitted during upset events caused by man-made or natural accidents. Although upset emissions of benzene can be a significant contributor to the total emission, it is still challenging to quantify. This study first develops a fast modeling framework using obstacle-resolving computational fluid dynamics modeling to compare the modeled within-facility-scale passive pollutant dispersion with the observed levels based on self-reported emissions for fourteen facilities in Texas, United States. Results of numerical simulations demonstrate that neglecting the obstacle effect can underpredict (overpredict) the near-(far-)field concentrations for a low source. For a source located above obstacles, underprediction occurs at all distances. The diagnostic framework is applied to 107 self-reported upset emission events for fourteen petroleum refineries in Texas from year 2019–2022. Considering different metrics across all events, it can be concluded that the modeled concentrations based on self-reported emissions likely underpredict the observed concentration increments. Depending on the possible source height, the median factor of underprediction ranges from 3 to 95 based on the average-plume metric. The agreement between model and observation is better for events characterized by high emission amounts and rates, which also correspond to high observed concentration increments. Overall, the research highlights the importance of considering obstacles and demonstrates the potential application of the current approach as an efficient diagnostic method for self-reported upset emissions using fenceline observations of HAPs.

In order to evaluate the impact of traffic emissions on urban air quality, an increasing number of cities have established near-road air quality monitoring stations (hereafter referred to as roadside stations). This study reviews the system of roadside stations, the data application, and the evolution of air pollutant concentrations in the traffic environment in typical cities, and proposes optimization suggestions roadside stations in the future. The results show a steady increase in publications on roadside stations over the years, with the annual average number of publications after 2020 being approximately 10 times the annual mean during 1994–2001. The literature mainly focused on ‘air pollution’, ‘particulate matter’, ‘emission’, etc., highlighting the impact of traffic emissions on urban air quality and human health. The purpose and principles of setting up roadside stations vary from country to country, but they are mainly used to assess the impact of vehicle emissions on air quality and to protect human health in the vicinity of roads. Over the past decade, near-road NO₂ concentrations in typical cities have decreased by 30%–50%, although they remain higher than those observed in the urban atmosphere. The comprehensive analysis based on long-term data from roadside stations can provide insight into the effectiveness of vehicle emission control measures, and serve as a scientific basis for the formulation of future public health protection policies.

Emissions from wood-burning stoves contribute to local air pollution. However, it is difficult to determine the real emissions from such stoves, especially due to unknown user behaviour, which can have a large impact on emissions. In this study, the low-cost emission reduction measure “user training” was evaluated to determine its emission reduction potential on firewood stoves. Two sets of tests were carried out. First, a field measurement campaign was conducted in Styria (Austria) with four wood stoves, where gaseous and particulate emissions were measured before and after a user training on optimised heating behaviour (e.g. ignition mode, fuel properties and placement in the combustion chamber, air supply). Gaseous emissions (carbon monoxide – CO, organic gaseous compounds – OGC) were measured continuously, while particulates were measured in batches, in undiluted and hot as well as in diluted and cooled flue gas in parallel with a specific field measurement setup. In addition, particle filters were analysed to quantify the concentration of the carcinogenic compound benzo(a)pyrene (BaP). Second, user training workshops were conducted. These tests had a simple measurement setup in order to increase the number of tests. Thus, only CO emissions were evaluated.

The results show that real life emissions in the field are high and have a high variability compared to laboratory tests and official type test results. However, user training showed a significant reduction of CO, OGC, TSP and BaP emissions of 42%, 57%, 45% and 76% (median), respectively. In addition, TSP_sum (sum of hot and cooled particle emission samples) emissions decreased by 39% (median) after user training. The relative reduction rates of all batches show that the highest emission reduction potential was identified for BaP, with a reduction rate of up to 97%. The results of the workshop tests confirmed the high variability in user behavior and the range for the emission reduction potentials, with a median CO reduction of 41%.

The emission reduction potential of the user training measure is comparable to state-of-the-art technological measures such as electrostatic precipitators and catalysts. However, these measures are costly and require a high level of technical sophistication. User training, on the other hand, is relatively cheap, easy to implement and suitable for all users. Of course, there is some risk that trained end-users will revert to their old habits, leading to higher emissions again. Therefore, regular training may be necessary to maintain the higher level of performance. As we did not assess this aspect in our work, further research would be needed to prove this theory.

The identification and reduction of methane sources is considered an important part of the fight to stem greenhouse gas (GHG) emissions to the atmosphere. One of the largest industrial contributors to national GHG emissions in Canada is the Alberta Oil Sands Region. To quantify and investigate the spatial distribution and temporal variability of methane emissions from this region, airborne measurements were conducted in 2017 and 2018 with three aircraft. 59 flights were conducted in total to assess emissions for both open-pit and in-situ facilities, in both cold and warm seasons. Derived emission rates were higher than those reported in national inventories by 30%–96% depending on the facility. In-situ facilities had emission rates an order of magnitude lower than surface mining operations and differed significantly from inventory estimates. No statistical differences in CH₄ emissions between cold and warm seasons were observed, substantiating the use of simple upscaling to annual emissions within inventories. Rather than confirming a reported decrease in emissions between 2013 and 2018, the measurements suggest essentially no change from the 18 t h⁻¹ for the region observed in 2013. Overall, the results suggest that current methods of CH₄ emission determination within the oil sands region, for use in reporting, require improvement.

Air quality in cities with large maritime ports is considerably impacted by emissions from shipping activity which is of a growing relevance due to an increasing relative contribution. To explore the extent of shipping emissions to ambient air quality, simulations with the chemical transport model LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog model) were performed for the year 2018 at an approximate 1 × 1 km resolution for six European cities with large ports, i.e., Rotterdam, Antwerp, Hamburg, Amsterdam, Le Havre, and London. It was found that depending on the investigated city, 6.5%–62% of the nitrogen dioxide (NO₂) concentration in the city centres is attributable to shipping activities. This corresponds to contributions of 1.8–11.5 μg/m³ to the ambient air NO₂ concentrations. The average NO₂ contribution of shipping in these six cities was 28% (7.1 μg/m³). The largest relative contribution was found for Le Havre where 62% (10.8 μg/m³) of the annual average NO₂ concentration was caused by shipping emissions. The largest absolute contribution is found for the city centre of Hamburg with 11.5 μg/m³ (41%). The lowest absolute and relative contribution (respectively 1.8 μg/m³ and 6.5%) are found for London, also having the smallest port in terms of tonnage throughput, which is one of the influential factors that determine emission totals, investigated in this study. For the other investigated pollutants, i.e., PM_2.5, PM₁₀ and SO₂, contributions from shipping were less pronounced with average contribution for all cities of 10% (1.2 μg/m³) 7% (1.5 μg/m³) and 4% (0.16 μg/m³) respectively. To assess the effect of model choices on these results, this study also looked into the choice of simulation resolution and relations between meteorological parameters and NO₂ concentrations. Following simulations with varying chemical transport model resolutions (1 × 1 km to 24 × 24 km), it is found that a decrease in ambient air pollutant concentrations away from localized emission sources is more pronounced at higher (1 × 1 km) model resolutions and source contributions are influenced more significantly than total concentrations. Considering meteorology, generally low wind speeds (1–2 m/s) lead to high NO₂ concentration in city centres. For the cities where the port is much closer to the city centre (e.g., London, Le Havre, Hamburg and Antwerp) the absolute NO₂ concentrations as well as the contributions from shipping emissions become highest for windless conditions. The high concentrations (>60 μg/m³ NO₂) only occur when wind speeds fall below 6 m/s.

Thailand experiences severe air quality issues, predominantly due to PM_2.5 pollution that surpasses WHO guidelines. The main sources are attributed to energy production, industrial activities, vehicular emissions, agricultural burning, and transboundary transport of pollutants. Understanding the transport and transformation of these pollutants is necessary for addressing air quality issues. The Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) provides information about meteorology, chemical reactions, and transport of trace gases and aerosols. The accuracy of WRF-Chem simulations greatly depends on the choice of anthropogenic and biomass burning emissions inventories. This study provides a detailed evaluation of these inventories to model PM_2.5 concentrations in Thailand during both haze and off-haze seasons in 2019. We evaluated WRF-Chem using four anthropogenic emission inventories—CAMS-GLOB-ANT, ECLIPSE, HTAP, and REAS—and four biomass burning emissions inventories—FINN1.5, FINN2.5 MOD, FINN2.5 MODVAR, and QFED—using data from ground-based air quality stations, MODIS AOD, and MOPITT CO satellite data. Our findings suggest CAMS-GLOB-ANT performs optimally for North Thailand, while HTAP and REAS are more effective in Eastern Thailand. For biomass burning, FINN1.5 shows superior performance. The study also highlights the challenge in capturing PM_2.5 diurnal variability, particularly due to inaccuracies in simulating the planetary boundary layer height during nighttime in complex terrains. Moreover, our analysis exhibits moderate model performances during the off-haze season while using global and regional anthropogenic emissions in Thailand, emphasizing the need for improving anthropogenic inventories for reliable air quality prediction. For biomass burning emissions, updating emission factors to reflect Thailand's specific vegetation types is recommended to improve WRF-Chem's representation of PM_2.5 levels.

Liquefied natural gas (LNG) use as shipping fuel has increased in recent years. While LNG results in lower carbon dioxide (CO₂) emissions as well as benefits in terms of air pollutants, the slip of unburned methane, the main component of LNG, has remained a concern. In this study, methane together with other climate warming agents, CO₂ and black carbon (BC), as well as other emission compounds were characterized from 4-stroke low-pressure dual fuel engine on-board a newly build cruise ship utilizing LNG as well as marine gas oil (MGO). The brake specific methane slip was found to vary according to engine load, being 2.3–3.0 g/kWh at 54–80% loads, but increasing to 10 g/kWh at 25% load and 21 g/kWh at 12% load. The LNG combustion also resulted in higher formaldehyde emissions compared to MGO, but reduction in formaldehyde levels was observed over the SCR catalyst present in the exhaust line of the dual-fuel engine, without urea injection, suggesting it may provide a pathway for formaldehyde mitigation. In terms of particle emissions, LNG use reduced particle mass (PM) by 87–93% and BC by 94–99% compared to MGO combustion. Non-volatile particle number above 23 nm (PN_nv,>23nm) and 10 nm (PN_nv,>10nm) were reduced by 88–97% and 97–99%, except at lowest engine load where PN_nv,>10nm increased by 26% compared to MGO utilization. When total greenhouse gas (GHG) emissions including CO₂ and BC were considered, LNG use resulted in 13–15% lower GHG at high loads, but the benefit was undermined by the escaping methane at low load conditions. Following the engine activity profile during 8-months of vessel operation on the Mediterranean suggested, however, that in a diesel-electric cruise ship, low load conditions are used mainly during arrivals and departures from harbors, as the engine was operated at loads above 40% for 90% of the operation time. Weighted emission factor, representing the actual engine operation, resulted in methane slip of 2.8 g/kWh or 1.7% of the fuel use, which is below the value considered in the FuelEU Maritime. The results suggest that load specific methane slip, together with engine load profile should be considered when evaluating methane slip on vessel or fleet level.