Secondary Particulate Matter Research Articles

Characteristics of Atmospheric Compounds based on Regional Multicorrelation Analysis in Honam Area

Particulate Matter (PM) in the atmosphere has serious impacts on human health and the global environmental systems. To reduce anthropogenic PM emissions is of importance to protect public health. In this study, the variation of concentrations in PM<sub>2.5</sub>, NO<sub>2</sub>, and O<sub>3</sub> of Honam region over the past 6 years (2016-2021) was investigated. A statistical approach (i.e., hierarchical cluster analysis) was performed to present their spatial relationships. As a result, the high concentration of PM<sub>2.5</sub> in Iksan-si was found in sources of primary pollutants emitted from industrial complexes and ammonia from large-scale livestock complexes. The high concentration periods of PM<sub>2.5</sub> with lower concentrations of NO<sub>2</sub> and O<sub>3</sub> can be seasonal and secondary PM product contributions. In addition, the concentration of O<sub>3</sub> in Buan-gun and Wanju-gun with lower PM levels can be the effect of emission of volatile organic compounds (VOC<sub>S</sub>) from sources. It is necessary to strengthen management for reducing emissions by sources and to establish a policy to control precursors of the atmospheric contaminants.

Comparison of total PM emissions emitted from electric and internal combustion engine vehicles: An experimental analysis

Electric vehicles (EVs) are regarded as zero emission vehicles due to the absence of exhaust emissions. However, they still contribute non-exhaust particulate matter (PM) emissions, generated by brake wear, tire wear, road wear, and resuspended road dust. In fact, because EVs are heavier than internal combustion engine vehicles (ICEVs), their non-exhaust emissions are like to be even higher. While total PM emissions, including exhaust and non-exhaust PM emissions, from ICEVs and EVs have been compared based on the emission factors (EFs) listed in national emission inventories, there have been no comparisons based on experimental determinations.In this study, exhaust and non-exhaust emissions generated from a gasoline ICEV, diesel ICEV, and EV were experimentally investigated. The results showed that the EFs for the total PM emissions of ICEVs and EV were dependent on the inclusion of secondary exhaust PM, the brake pad type, and the regenerative braking intensity of the EV. When only primary exhaust PM emissions were considered in vehicles equipped with non-asbestos organic (NAO) brake pads, the total PM10 EF of the EV (47.7–49.3 mg/V·km) was 10–17 % higher than those of the gasoline ICEV (42.3 mg/V·km) and diesel ICEV (43.2 mg/V·km). However, in vehicles equipped with low-metallic (LM) brake pads, the total PM10 EF of the EV (49.2–57.7 mg/V·km) was comparable or lower than those of the gasoline ICEV (56.3 mg/V·km) and diesel ICEV (57.2 mg/V·km). When secondary PM emissions were included, the EF was always significantly lower for the EV than ICEVs. The total PM10 EF of the EV (47.7–57.7 mg/V·km) was lower than those of the gasoline ICEV (56.5–70.5 mg/V·km) and diesel ICEV (58.0–72.0 mg/V·km). Since secondary PM particles are mostly of submicron size, the EFs of the PM2.5 fraction of the ICEVs (28.7–33.0 mg/V·km) were two times higher than those of the EV (13.9–17.4 mg/V·km).

Formation and evolution of secondary particulate matter during heavy haze pollution episodes in winter in a severe cold climate region of Northeast China.

The formation and evolution of sulfate (SO42-) and nitrate (NO3-) secondary contaminants under different stages of pollution episodes and different meteorological and emission conditions were compared, based on the simultaneous observation of fine particulate matter (PM2.5) and its chemical components in four heavy haze pollution episodes at 14 sampling sites in a severe cold climate region of Northeast China in winter from 2017 to 2019. The results yielded two main findings. (1) Nitrate formation during the day was mainly due to the combination of high emissions and high relative humidity (RH, 50-90%), high temperature (T, 0 to 5°C), high atmospheric oxidizability (ozone (O3) and nitrous acid (HONO) concentrations), and high ammonia (NH3) concentrations. Nitrate was formed by a gas-phase homogeneous reaction of the hydroxyl radical (OH·) with nitrogen dioxide (NO2), sulfur dioxide (SO2), and ammonia (NH3). (2) The main differences in SO42- formation between Northeast China and other regions were that the gas-phase oxidation process played an important role. This was mainly a result of the promotion of the gas-phase oxidation of SO42- due to the high oxidizing ability and the suppression of the aqueous reaction due to the low Ts in winter and low-sulfur coal emissions. Sulfate formation mostly occurred through an aqueous phase reaction in winter, but the highest yield and the fastest production capacity were produced by the gas-phase reaction.

Does Ambient Secondary Conversion or the Prolonged Fast Conversion in Combustion Plumes Cause Severe PM2.5 Air Pollution in China?

The ambient formation of secondary particulate matter (ambient FSPM) is commonly recognized as the major cause of severe PM2.5 air pollution in China. We present observational evidence showing that the ambient FSPM was too weak to yield a detectable contribution to extreme PM2.5 pollution events that swept northern China between 11 and 14 January 2019. Although the Community Multiscale Air Quality (CMAQ) model (v5.2) reasonably reproduced the observations in January 2019, it largely underestimated the concentrations of the PM2.5 during the episode. We propose a novel mechanism, called the “in-fresh-stack-plume non-precipitation-cloud processing of aerosols” followed by the evaporation of semi-volatile components from the aerosols, to generate PM2.5 at extremely high concentrations because of highly concentrated gaseous precursors and large amounts of water droplets in fresh cooling combustion plumes under poor dispersion conditions, low ambient temperature, and high relative humidity. The recorded non-precipitation-cloud processing of the aerosols in fresh stack combustion plumes normally lasts 20–30 s, but it prolongs as long as 2–5 min under cold, humid, and stagnant meteorological conditions and expectedly causes severe PM2.5 pollution events. Regardless of the presence of the natural cloud in the planetary boundary layer during the extreme events, the fast conversion of air pollutants in water droplets and the generation of the PM2.5 through the non-precipitation-cloud processing of aerosols always occur in fresh combustion plumes. The processing of aerosols is detectable using a nano-scan particle sizer assembled on an unmanned aerial vehicle to monitor the particle formation in stack plumes. In-fresh-stack-plume processed aerosols under varying meteorological conditions need to be studied urgently.

Evaluation of modelled LOTOS-EUROS with observational based PM10 source attribution

Due to its serious health impact particulate matter is one of the air pollutants subject to abatement policies. Information on the main sources responsible for high concentrations of pollutants is therefore crucial to enable effective policy measures. In this study we compared two different methods for attribution of particulate matter concentrations to different sources: A tagging approach within the regional chemistry transport model LOTOS-EUROS and an observational method using speciated particulate matter observations and Positive Matrix Factorisation (PMF). The methods have been applied for winter 2016/2017 over Eastern Germany where in wintertime high woodburning emissions, cold temperatures and regular easterly winds can lead to a build-up of pollutant concentrations. The comparison allows the validation of the modelled source attribution for a selection of source categories. The contributions for biomass and total combustion compare well between both methods providing trust in the determined contributions, applied emissions including their timing. The total contribution from combustion is estimated between 3.3-7.7 μg/m3 (PMF) and 3.3-7.2 μg/m3 (LOTOS-EUROS) for the 9 stations incorporated in the study. The temporal Pearson correlation coefficient ranges between 0.3-0.64 for total combustion and 0.34 and 0.7 for biomass combustion. The mean absolute contributions for traffic at background stations also compare well with most values between 1.5-2.0 μg/m3 for PMF and 1–1.6 μg/m3 for LOTOS-EUROS. A lack of correlation for this contribution however suggests that the model has difficulty in representing the source category traffic in a time consistent manner and developments are needed to improve the temporal distribution of the traffic emissions within the model. The modelled particulate matter concentrations displayed a 20–40% underestimation of the observed concentrations with an increasing bias during high pollution events. The underestimation showed a high correlation with the observed contribution from combustion and secondary particulate matter including ammonium sulfate and organic carbon suggesting that at least a part of the missing mass in LOTOS-EUROS is related to transformation of volatile combustion emissions, likely from solid fuels, to secondary particle mass and missing enhanced formation of sulfate. Implementation of these missing processes would help to improve the source attribution of particulate matter with the LOTOS-EUROS model.

Significant contribution of secondary particulate matter to recurrent air pollution: Evidence from in situ observation in the most polluted city of Fen-Wei Plain of China

Particulate matter (PM) pollution in high emission regions will affect air quality, human health and climate change on both local and regional scales, and thus attract worldwide attention. In this study, a comprehensive study on PM2.5 and its chemical composition were performed in Yuncheng (the most polluted city of Fen-Wei Plain of China) from November 28, 2020 to January 24, 2021. The average concentration of PM2.5 was 87.8 ± 52.0 μg/m3, which were apparently lower than those observed during the same periods of past five years, attributable to the clean air action plan implemented in this region. NO3− and organic carbon (OC) were the dominant particulate components, which on average contributed 22.6% and 16.5% to PM2.5, respectively. The fractions of NO3−, NH4+, OC and trace metals increased while those of crustal materials and elemental carbon decreased with the degradation of PM2.5 pollution. Six types of PM2.5 sources were identified by the PMF model, including secondary inorganic aerosol (35.3%), coal combustion (28.7%), vehicular emission (20.7%), electroplating industry (8.6%), smelt industry (3.9%) and dust (2.8%). Locations of each identified source were pinpointed based on conditional probability function, potential source contribution function and concentration weighted trajectory, which showed that the geographical distribution of the sources of PM2.5 roughly agreed with the areas of high emission. Overall, this study provides valuable information on atmospheric pollution and deems beneficial for policymakers to take informed action to sustainably improve air quality in highly polluted region.

Research on the Growth Mechanism of PM2.5 in Central and Eastern China during Autumn and Winter from 2013–2020

Haze is a majorly disastrous type of weather in China, especially central and eastern of China. The development of haze is mainly caused by highly concentrated fine particles (PM2.5) on a regional scale. Here, we present the results from an autumn and winter study conducted from 2013 to 2020 in seven highly polluted areas (27 representative stations) in central and eastern China to analyze the growth mechanism of PM2.5. At the same time, taking Beijing Station as an example, the characteristics of aerosol composition and particle size in the growth phase are analyzed. Taking into account the regional and inter-annual differences of fine particles (PM2.5) distribution, the local average PM2.5 growth value of the year is used as the boundary value for dividing slow, rapid, and explosive growth (only focuses on the hourly growth rate greater than 0). The average value of PM2.5 in the autumn and winter of each regional representative station shows a decreasing trend as a whole, especially after 2017, whereby the decreasing trend was significant. The distribution value of +ΔPM2.5 (PM2.5 hourly growth rate) in the north of the Huai River is lower than that in the south of the Huai River, and both of the +ΔPM2.5 after 2017 showed a significant decreasing trend. The average PM2.5 threshold before the explosive growth is 70.8 µg m−3, and the threshold that is extremely prone to explosive growth is 156 µg m−3 to 277 µg m−3 in north of the Huai River. For the area south of the Huai River, the threshold for PM2.5 explosive growth is relatively low, as a more stringent threshold also puts forward stricter requirements on atmospheric environmental governance. For example, in Beijing, the peak diameters gradually shift to larger sizes when the growth rate increases. The number concentration increasing mainly distributed in Aitken mode (AIM) and Accumulation mode (ACM) during explosive growth. Among the various components of submicron particulate matter (PM1), organic aerosol (OA), especially primary OA (POA), have become one of the most critical components for the PM2.5 explosive growth in Beijing. During the growth period, the contribution of secondary particulate matter (SPM) to the accumulated pollutants is significantly higher than that of primary particulate matter (PPM). However, the proportion of SPM gradually decreases when the growth rate increases. The contribution of the PPM can reach 48% in explosive growth. Compared to slow and rapid growth, explosive growth mainly occurs in the stable atmosphere of higher humidity, lower pressure, lower temperature, small winds, and low mixed layers.

Effect of GNWs/NiO-WO3/GNWs Heterostructure for NO2 Gas Sensing at Room Temperature.

Recently, as air pollution and particulate matter worsen, the importance of a platform that can monitor the air environment is emerging. Especially, among air pollutants, nitrogen dioxide (NO2) is a toxic gas that can not only generate secondary particulate matter, but can also derive numerous toxic gases. To detect such NO2 gas at low concentration, we fabricated a GNWs/NiO-WO3/GNWs heterostructure-based gas sensor using microwave plasma-enhanced chemical vapor deposition (MPECVD) and sputter, and we confirmed the NO2 detection characteristics between 10 and 50 ppm at room temperature. The morphology and carbon lattice characteristics of the sensing layer were investigated using field emission scanning electron microscopy (FESEM) and Raman spectroscopy. In the gas detection measurement, the resistance negative change according to the NO2 gas concentration was recorded. Moreover, it reacted even at low concentrations such as 5–7 ppm, and showed excellent recovery characteristics of more than 98%. Furthermore, it also showed a change in which the reactivity decreased with respect to humidity of 33% and 66%.

Measurements of nitrous oxide and ammonia emissions from diesel automobile under the real-world driving conditions using laser absorption spectrometer

Nitrous oxide (N2O) is a greenhouse gas and contributes to ozone depletion, and ammonia (NH3) contributes to the formation of secondary particulate matter. To reduce global warming and particulate matter, the real-world levels of N2O and NH3 emitted from automobiles is required to be examined. However, there are a few studies on the measurements of N2O and NH3 in automobile exhaust under the real-world conditions. In this study, we have measured the real-world emissions of N2O and NH3 from the latest diesel vehicle equipped with an urea-SCR system. N2O was measured by an on-board system using mid-IR laser spectroscopy and NH3 was measured using a sensor-based measurement technique. As a result, NH3 was not emitted, while N2O was emitted intermittently when vehicle was running.

Chemical and physical characterization of oil shale combustion emissions in Estonia

In this study, oil shale combustion emission measurements were conducted in a 60 kW th Circulating Fluidized Bed combustion test facility located in a laboratory-type environment. A comprehensive set of instruments including a nitrate-ion-based Chemical Ionization Atmospheric Pressure interface Time-of-Flight Mass Spectrometer, a Soot-Particle Aerosol Mass Spectrometer, and a Potential Aerosol Mass (PAM) chamber was utilized to investigate the chemical composition and concentrations of primary and secondary emissions in oil shale combustion. In addition, the size distribution of particles (2.5–414 nm) as well as concentration and composition of gaseous precursors were characterized. Altogether 12 different experiments were conducted. Primary emissions were studied in seven experiments and aged emissions using PAM chamber in five experiments. Combustion temperatures and solid fuel circulation rates varied between different experiments, and it was found that the burning conditions had a large impact on gaseous and particulate emissions. The majority of the combustion particles were below 10 nm in size during good burning whereas in poor burning conditions the emitted particles were larger and size distributions with 2–3 particle modes were detected. The main submicron particle chemical component was particulate organic matter (POM), followed by sulfate, chloride, nitrate, and ammonium. The secondary particulate matter formed in the PAM chamber was mostly POM and the concentration of POM was many orders of magnitude higher in aged aerosol compared to primary emissions. A significant amount of aromatic volatile organic compounds (VOCs) was measured as well. VOCs have the potential to go through gas-to-particle conversion during the oxidation process, explaining the observed high concentrations of aged POM. During good combustion, when VOC emissions were lower, over 80% of SO 2 was oxidized either to gaseous H 2 SO 4 (37%) or particulate sulfate (46%) in the PAM chamber, which mimic the atmospheric processes taken place in the ambient air after few days of emission. • Oil Shale was combusted in a 60-kW th laboratory facility. • Combustion temperature had a large influence on exhaust emissions. • Poor burning produced larger particles and hence larger mass concentrations. • High amount of secondary particle matter was formed during ageing experiments. • SO 2 , sulfuric acid clusters and particulate sulfate were determined.

Probabilistic total PM2.5 emissions from vehicular sources in Australian perspective.

Motor vehicles operating on the road are a significant source of Particulate Matter (PM) emissions depending on the fuels used in the vehicles. Gasoline and Diesel vehicles are directly responsible for the tailpipe PM emissions (specifically PM2.5: particles ≤ 2.5µm), known as primary PM2.5 emissions. The other major direct emissions from the vehicles, which include volatile organic compounds (VOCs), and nitrogen oxides (NOx) contribute to the formation of secondary organic PM, also known as secondary organic aerosols (SOA), through some inter-related chemical reactions. The SOAs are highly toxic and contribute to a portion of total PM emissions. In this research, emission scenarios of both primary PM2.5 and SOA for a car-dependent expanding Australian city (Adelaide) were analyzed. The variability of traffic characteristics on road was considered and conducted a probabilistic emissions inventory for tailpipe primary PM2.5 and precursors, while statistical analysis of the probable chemical conversion ratios was considered for the SOA inventory. It was found that the tailpipe emissions from the vehicles were higher than the air quality standard, while the SOA contribution from the vehicles was not significantly high but contributed to the increase of total PM concentration. The analysis of the chemical transformation of SOA precursors justified the importance of conducting more detailed emissions modelling for sustainable urban air quality planning.

Mapping pollution exposure and chemistry during an extreme air quality event (the 2018 Kīlauea eruption) using a low-cost sensor network

Extreme air quality episodes represent a major threat to human health worldwide but are highly dynamic and exceedingly challenging to monitor. The 2018 Kīlauea Lower East Rift Zone eruption (May to August 2018) blanketed much of Hawai'i Island in "vog" (volcanic smog), a mixture of primary volcanic sulfur dioxide (SO2) gas and secondary particulate matter (PM). This episode was captured by several monitoring platforms, including a low-cost sensor (LCS) network consisting of 30 nodes designed and deployed specifically to monitor PM and SO2 during the event. Downwind of the eruption, network stations measured peak hourly PM2.5 and SO2 concentrations that exceeded 75 μg m-3 and 1,200 parts per billion (ppb), respectively. The LCS network's high spatial density enabled highly granular estimates of human exposure to both pollutants during the eruption, which was not possible using preexisting air quality measurements. Because of overlaps in population distribution and plume dynamics, a much larger proportion of the island's population was exposed to elevated levels of fine PM than to SO2 Additionally, the spatially distributed network was able to resolve the volcanic plume's chemical evolution downwind of the eruption. Measurements find a mean SO2 conversion time of ∼36 h, demonstrating the ability of distributed LCS networks to observe reaction kinetics and quantify chemical transformations of air pollutants in a real-world setting. This work also highlights the utility of LCS networks for emergency response during extreme episodes to complement existing air quality monitoring approaches.

Reactive nitrogen compounds and their influence on human health: an overview.

Nitrogen (N)is a critical component of food security, economy and planetary health. Human production of reactive nitrogen (Nr) via Haber-Bosch process and cultivation-induced biological N2 fixation (BNF) has doubled global N cycling over the last century. The most important beneficial effect of Nr is augmenting global food supplies due to increased crop yields. However, increased circulation of Nr in the environment is responsible for serious human health effects such as methemoglobinemia ("blue baby syndrome") and eutrophication of coastal andinland waters. Furthermore, ammonia (NH3) emission mainly from farming and animal husbandary impacts not only human health causing chronic lung disease, inflammation of human airways and irritation of eyes, sinuses and skin but is also involved in the formation of secondary particulate matter (PM) that plays a critical role in environment and human health. Nr also affects human health via global warming, depletion of stratospheric ozone layer resulting in greater intensity of ultra violet B rays (UVB) on the Earth's surface, and creation of ground-level ozone (through reaction of NO2 with O2). The consequential indirect human health effects of Nr include the spread of vector-borne pathogens, increased incidence of skin cancer, development of cataracts, and serious respiratory diseases, besides land degradation. Evidently, the strategies to reduce Nr and mitigate adverse environmental and human health impacts include plugging pathways of nitrogen transport and loss through runoff, leaching and emissions of NH3, nitrogen oxides (NO x ), and other N compounds; improving fertilizer N use efficiency; reducing regional disparity in access to N fertilizers; enhancing BNF to decrease dependence on chemical fertilizers; replacing animal-based proteins with plant-based proteins; adopting improved methods of livestock raising and manure management; reducing air pollution and secondary PM formation; and subjecting industrial and vehicular NO x emission to pollution control laws. Strategic implementation of all these presents a major challenge across the fields of agriculture, ecology and public health. Recent observations on the reduction of air pollution in the COVID-19 lockdown period in several world regions provide an insight into the achievability of long-term air quality improvement. In this review, we focus on complex relationships between Nr and human health, highlighting a wide range of beneficial and detrimental effects.

Analysis of the air pollution climate of a central urban roadside supersite: London, Marylebone Road

The London Marylebone Road monitoring site is a roadside supersite adjacent to a highway carrying 80–90,000 vehicles per day on six lanes in a street canyon. Data from the Automatic Urban and Rural Network (AURN), Black Carbon Network, Automatic Hydrocarbon Network, Heavy Metal Network, Particle Size and Number and Particle Composition Network covering the period from 2009 to 2018 were analysed to determine short-term (diurnal, weekly and seasonal) and long-term variations and geographic source attribution. The contribution of roadside emissions relative to background sites (roadside increment) to the pollution climate was also investigated. The long-term trend analysis shows significant decline in regulated pollutants such as the particulate matter fractions (−4.0%; −3.93%/yr for PM2.5 and PM10 respectively) and gas phase pollutants associated with vehicular emissions (−5.5%; −1.22% and −2.1%/yr for CO, NOx and NO2 respectively), although concentrations of SO2 and O3 have remained relatively constant over the years. Equivalent Black carbon (eBC) and total particle number count have also declined over the years whereas the heavy metals show mixed results (only Cu, Ni and V shows significant downward trends). The inorganic ionic components of the PM10 fraction, elemental (EC) and organic carbon (OC) and the volatile organic compounds all generally show declining trends over the period. Assessment of the diurnal variations shows elevated concentrations of the particulate matter fractions, the nitrogen oxides, CO and SO2 at periods corresponding to the traffic rush hours, whereas O3 peaked in the afternoon when there is less titration due to lower NO concentrations. The diurnal pattern of eBC and Total Particle Number Count are similar to NOx and show strong traffic influence. Cl, Mg, K and Na levels show no systematic pattern throughout, with their presence likely controlled by meteorological conditions, and Ca showing high concentrations in the afternoon because of resuspension of deposited dust resulting from turbulence created by vehicular movement, and eroded road-surface material. Ammonium and nitrate show their lowest concentrations during the day when the temperature is high, probably reflective of their semi-volatile nature, with sulphate producing a peak around mid-day. The VOCs, with the exception of ethane, give the bimodal peaks typical of traffic related emission in the diurnal plots and their pattern is more similar to CO than the other traffic emitted gaseous pollutants. Ethane is associated with leakages from gas supply pipes. The weekday plots show weekday (Monday – Friday) increases in traffic-related pollutants and a decline over the weekends due to lower traffic volumes, with the reverse observed for O3. K and the marine aerosol components show relatively similar concentrations on all days of the week, while Ca, NH4+, NO3− and SO42− all show a weekday maximum and decline over the weekend. The pollutants show seasonal variations; O3 shows a springtime maximum, with the traffic-emitted pollutants (NO, NOx, CO, EC, OC etc) giving a winter maximum due to increase in emission, lower mixing depth and poor dispersion. Particulate matter fractions and total particle count show lower concentrations in summertime reflective of the semi-volatile nature of some components. Ca shows less seasonal variability, with marine aerosol components showing a maximum winter concentration driven by higher wind speed conditions. NH4+, NO3− and SO42− show lowest levels in summer and maximum springtime concentrations. The traffic-related VOCs show a summertime minimum and wintertime maximum, while isoprene shows increased concentrations during summertime. The street canyon circulation causes the sampling of North London air on northerly winds, but enhanced traffic pollution when winds have a southerly component. There is a sizeable roadside increment above the local background for both exhaust (particulate matter mass fractions, particle number and eBC) and non-exhaust emissions (heavy metals). However, roadside increments of inorganic species, which include Ca, marine aerosol components and the secondary particulate matter components, are not significant, indicating that they are mainly controlled by regional transport of the pollutants. Polar plots show strong local contributions for the regulated gas phase pollutants and the carbon components (EC and OC), with O3 concentrations enhanced mainly from the northerly direction. The long-range contribution from mainland Europe to the particulate matter fractions is significant and occurs mainly as secondary aerosol. Ratios of OC/EC in particles have shown a steady increase due to a more rapid reduction of EC than OC.

Volatile organic compound and particulate matter emissions from an ultrasonic essential oil diffuser.

Ultrasonic essential oil diffusers (EODs) are a popular type of indoor scenting source. We performed a chamber study in which we measured the emissions from EODs used with lemon, lavender, eucalyptus, and grapeseed oils. Over the course of 15min, the most abundant VOCs released from lemon, lavender, eucalyptus, and grapeseed oils were 2.6±0.7mg of d-limonene, 3.5±0.4mg of eucalyptol, 1.0±0.1mg of linalyl acetate, and 0.2±0.02mg of linalyl acetate, respectively. Each oil had a unique particulate matter (PM) emission profile in terms of size, number density, and rate. The dominant size ranges of the PM were 10-100nm for lemon oil, 50-100nm for lavender oil, 10-50nm for lemon oil, and above 200nm for grapeseed oil. PM1 emission rates of approximately 2mg/h, 0.1mg/h, and 3mg/h, were observed for lemon, lavender/eucalyptus, and grapeseed oils, respectively. A fivefold increase in PM1 emission was measured when the EOD with eucalyptus oil was filled with tap water as opposed to deionized water. Modeling suggests that reasonable use cases of EODs can contribute substantially to primary and secondary PM in indoor environments, but this potential varies depending on the oil and water types used.

Mitigation of Acute Ammonia Emissions With Biochar During Swine Manure Agitation Before Pump-Out: Proof-of-the-Concept

Ammonia (NH3) emissions from animal agriculture can cause eutrophication of water ecosystems and are precursors to secondary particulate matter (PM2.5). NH3 emissions from stored swine manure represent nutrient loss affecting the fertilizing value of manure. The short-term emission bursts occur when farmers agitate manure before emptying storage and fertilizing fields. There is no proven technology to mitigate gaseous emissions during agitation, while the hazards of acute releases (e.g., H2S) are well-known. Biochar mitigates NH3 emissions from manure over the long-term. The objective of this research was to evaluate the mitigation of acute NH3 emissions during/after agitation. Two biochars, highly alkaline and porous (HAP from corn stover) and red oak (RO), were tested. The 6 and 12 mm-thick layers of biochar powder were surficial applied followed by 3 min agitation. NH3 concentrations were measured before/during/after agitation. Mitigation was assessed by comparing: (i) the maximum (peak) flux, (ii) total emission (from agitation start till NH3 concentration returned to the before-agitation), and (iii) the total emissions during agitation. The 12 mm HAP significantly (p < 0.05) reduced (i–iii) by 63, 70, and 85%, respectively. The 6 mm HAP significantly reduced (i–iii) by 76, 75, and 78%, respectively. The 12 mm RO significantly reduced (i–iii) by 9, 53, and 57%, respectively. The 6 mm RO significantly reduced (i–iii) by 61, 86, and 63%, respectively. The NH3 emission kinetics model confirmed that a 6 mm dose was just as effective as the larger dose. More research is needed to optimize and scale-up mitigating emissions and retention of nutrients in manure with biochar.

A review of the potentiality of biochar technology to abate emissions of particulate matter originating from agriculture

Agricultural operations and processes generate copious quantities of particulate matter (PM) both directly and indirectly through emissions of PM precursor gases with dire consequences for human health, environment and climate. PM emissions from agricultural activities are projected to continually rise in the light of soaring food demand driven by a ballooning global population, and thus, plausible measures are needed to combat them. Recently, interest in using biochar to attenuate PM emissions of agricultural origin, especially the secondary PM precursors, has gained traction and this review study is purposed to examine the capacity of the technology to curb the agricultural-related PM emissions basing on observations made in the previously concluded studies. The study gives a brief overview of the effects of PM and delineates its weighty agricultural sources plus detailing whether and how the pyrolysis technology and biochar as its product can help to alleviate the emissions. Additional discussions address the looming dilemma of biochar applications becoming a PM emission problem and the techniques that should be applied to ensure its sustainable usage. It is overwhelmingly clear from the studies reviewed that pyrolysis and resultant biochar have an enormous potential to attenuate PM from agriculture if adequately utilised.

NO2 levels as a contributing factor to COVID-19 deaths: The first empirical estimate of threshold values

This study represents the first empirical estimation of threshold values between nitrogen dioxide (NO2) concentrations and COVID-19-related deaths in France. The concentration of NO2 linked to COVID-19-related deaths in three major French cities were determined using Artificial Neural Networks experiments and a Causal Direction from Dependency (D2C) algorithm. The aim of the study was to evaluate the potential effects of NO2 in spreading the epidemic. The underlying hypothesis is that NO2, as a precursor to secondary particulate matter formation, can foster COVID-19 and make the respiratory system more susceptible to this infection. Three different neural networks for the cities of Paris, Lyon and Marseille were built in this work, followed by the application of an innovative tool of cutting the signal from the inputs to the selected target. The results show that the threshold levels of NO2 connected to COVID-19 range between 15.8 μg/m3 for Lyon, 21.8 μg/m3 for Marseille and 22.9 μg/m3 for Paris, which were significantly lower than the average annual concentration limit of 40 μg/m³ imposed by Directive 2008/50/EC of the European Parliament.

Size-segregated particle number and mass concentrations from different emission sources in urban Beijing

Abstract. Although secondary particulate matter is reported to be the main contributor of PM2.5 during haze in Chinese megacities, primary particle emissions also affect particle concentrations. In order to improve estimates of the contribution of primary sources to the particle number and mass concentrations, we performed source apportionment analyses using both chemical fingerprints and particle size distributions measured at the same site in urban Beijing from April to July 2018. Both methods resolved factors related to primary emissions, including vehicular emissions and cooking emissions, which together make up 76 % and 24 % of total particle number and organic aerosol (OA) mass, respectively. Similar source types, including particles related to vehicular emissions (1.6±1.1 µg m−3; 2.4±1.8×103 cm−3 and 5.5±2.8×103 cm−3 for two traffic-related components), cooking emissions (2.6±1.9 µg m−3 and 5.5±3.3×103 cm−3) and secondary aerosols (51±41 µg m−3 and 4.2±3.0×103 cm−3), were resolved by both methods. Converted mass concentrations from particle size distributions components were comparable with those from chemical fingerprints. Size distribution source apportionment separated vehicular emissions into a component with a mode diameter of 20 nm (“traffic-ultrafine”) and a component with a mode diameter of 100 nm (“traffic-fine”). Consistent with similar day- and nighttime diesel vehicle PM2.5 emissions estimated for the Beijing area, traffic-fine particles, hydrocarbon-like OA (HOA, traffic-related factor resulting from source apportionment using chemical fingerprints) and black carbon (BC) showed similar diurnal patterns, with higher concentrations during the night and morning than during the afternoon when the boundary layer is higher. Traffic-ultrafine particles showed the highest concentrations during the rush-hour period, suggesting a prominent role of local gasoline vehicle emissions. In the absence of new particle formation, our results show that vehicular-related emissions (14 % and 30 % for ultrafine and fine particles, respectively) and cooking-activity-related emissions (32 %) dominate the particle number concentration, while secondary particulate matter (over 80 %) governs PM2.5 mass during the non-heating season in Beijing.

Vertical transport of PM2.5 and PM10 and its source identification in the street canyons of Chennai metropolitan city, India

Chemical characterization of particulate matter (PM) measured along trafficked roads in Chennai city was performed during the winter season. Several heights, from 3 m to about 38 m above the ground level, and road geometries were taken into account. The daily average coarse (PM10) and fine (PM2.5) particles concentrations were in the range 72–110 (for PM10) and 34–57 μg/m3 (for PM2.5), depending on the site. Samples were analyzed in terms of inorganic ions using Ion Chromatography (IC) and elements by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Results indicated the dominance of SO42− followed by Na+,Ca2+,NO3− and Cl− ions in the coarse fraction; similarly, in the fine fraction ion concentrations decreased in the following order: SO42−, NH4+, K+ and Ca2+. Among the elements, crustal element (Al, Fe) and Zn concentrations were much higher (accounting about 90% of the total elemental concentration) than other toxic elements (Cr, Cu, Mn, Ni, Pb, Sn, Ti and V). No element showed a significant dependence on height, expect for calcium at site ‘Velachery’ which contributed significantly to the abundance of the coarse fraction mass. In order to identify the major sources of air pollution, the collected data were analyzed using Positive Matrix Factorization (PMF), allowing to highlight five dominant pollution sources/factors: secondary PM, road traffic, biomass burning, sea spray and crustal erosion. Overall, the present study provided a new insight for the source apportionment of monitored pollutants in the Chennai city.