On thresholds for controlling negative particle (PM2.5) readings in air quality reporting.

Ambient PM2.5 (particles less than 2.5 µm in diameter) is monitored in many countries including Australia. Occasionally PM2.5 instruments may report negative measurements, although in realty the ambient air can never contain negative amounts of particles. Some negative readings are caused by instrument faults or procedural errors, thus can be simply invalidated from air quality reporting. There are occasions, however, when negative readings occur due to other factors including technological or procedural limitations. Treatment of such negative data requires consideration of factors such as measurement uncertainty, instrument noise and risk for significant bias in air quality reporting. There is very limited documentation on handling negative PM2.5 data in the literature. This paper demonstrates how a threshold is determined for controlling negative hourly PM2.5 readings in the New South Wales (NSW) air quality data system. The investigation involved a review of thresholds used in different data systems and an assessment of instrument measurement uncertainties, zero air test data and impacts on key reporting statistics when applying different thresholds to historical datasets. The results show that a threshold of -10.0 µg/m3 appears optimal for controlling negative PM2.5 data in public reporting. This choice is consistent with the measurement uncertainty estimates and the zero air test data statistics calculated for the NSW Air Quality Monitoring Network, and is expected not to have significant impacts on key compliance reporting statistics such as data availability and annual average pollution levels. The analysis can be useful for air quality monitoring in other Australian jurisdictions or wider context.

Evaluation of a New Chemical Mechanism for 2-Amino-2-methyl-1-propanol in a Reactive Environment from CSIRO Smog Chamber Experiments.

Amines are considered as an emerging class of atmospheric pollutants that are of great importance to atmospheric chemistry and new particle formation. As a typical amine, 2-amino-2-methyl-1-propanol (AMP) is one of the proposed solvents for capturing CO2 from flue gas streams in amine-based post-combustion CO2 capture plants, and it is expected to result in AMP emission and secondary product formation in the atmosphere. However, the current knowledge of its atmospheric chemistry and kinetics is poorly understood, particularly in a reactive environment. In this work, we used the CSIRO smog chamber to study the photo-oxidation of AMP in the presence of volatile organic compound (VOC)-NOx surrogate mixtures over a range of initial amine concentrations. O3 formation was significantly inhibited when AMP was added to the surrogate VOC-NOx mixtures, implying that AMP could alter known atmospheric chemical reaction pathways and the prevailing reactivity. Simultaneously, a large amount of AMP-derived secondary aerosol was formed, with a considerably high aerosol mass yield (i.e., ratio of aerosol formed to reacted AMP) of 1.06 ± 0.20. Based on updated knowledge of its kinetics, oxidation pathways, and product yields, we have developed a new mechanism (designated as CSIAMP-19), integrated it into the Carbon Bond 6 (CB6) chemical mechanism, and evaluated it against available smog chamber data. Compared with the existing AMP mechanism (designated as CarterAMP-08), the modified CB6 with CSIAMP-19 mechanism improves prediction against AMP-VOC-NOx experiments across a range of initial AMP concentrations, within ±10% model error for gross ozone production. Our results contribute to scientific understanding of AMP photochemistry and to the development of the chemical mechanism of other amines. Once some potential limitations are considered, the updated AMP reaction scheme can be further embedded into the chemical transport model for regional modeling scenarios where AMP-related emissions are of concern.

Characterization of a new smog chamber for evaluating SAPRC gas-phase chemical mechanism.

A new state-of-the-art indoor smog chamber facility (CAPS-ZJU) has been constructed and characterized at Zhejiang University, which is designed for chemical mechanism evaluation under well-controlled conditions. A series of characterization experiments were performed to validate the well-established experimental protocols, including temperature variation pattern, light spectrum and equivalent intensity (JNO2), injection and mixing performance, as well as gases and particle wall loss. In addition, based on some characterization experiments, the auxiliary wall mechanism has been setup and examined. Fifty chamber experiments were performed across a broad range of experimental scenarios, and we demonstrated the ability to utilize these chamber data for evaluating SAPRC chemical mechanism. It was found that the SAPRC-11 can well predict the O3 formation and NO oxidation for almost all propene runs, with 6 hr Δ(O3 - NO) model error of -3% ± 7%, while the final O3 was underestimated by ~20% for isoprene experiments. As for toluene and p-xylene experiments, it was confirmed that SAPRC-11 has significant improvement on aromatic chemistry than earlier version of SAPRC-07, although the aromatic decay rate was still underestimated to some extent. The model sensitivity test has been carried out, and the most sensitive parameters identified are the initial concentrations of reactants and the light intensity as well as HONO offgasing rate and O3 wall loss rate. All of which demonstrated that CAPS-ZJU smog chamber could derive high quality experimental data, and could provide insights on chamber studies and chemical mechanism development.

Smoke aerosols dispersion and transport from the 2013 New South Wales (Australia) bushfires.

Environmental monitoring and modelling, especially in the regional context, has seen significant progress with the widely usage of satellite measurement in conjunction with local meteorological and air quality monitoring to understand the atmospheric dispersion and transport of air pollutants. This paper studies the application of these data and modelling tools to understand the environment effects of a major bushfire period in the state of New South Wales (NSW), Australia, in 2013. The bushfires have caused high pollution episodes at many sites in the greater Sydney metropolitan areas. The potential long-range transport of aerosols produced by bushfires to other region and states has been seen by regulators as a major concern. Using data and images collected from satellites, in addition to the results obtained from different simulations carried out using HYSPLIT trajectory model and a regional meteorological model called Conformal Cubic Atmospheric Model (CCAM), we were able to identify at least 2 days on which the smoke aerosols from bush fires in NSW has been transported at high altitude to the northern state of Queensland and the Coral Sea. As a result, widespread high particle concentration in South East Queensland including the Brisbane area, as measured by nearly all the air quality monitoring stations in this region, occurred on the day when the smoke aerosols intruded to lower altitude as indicated by the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) Lidar measurements on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite. The use of meteorological or air quality modelling to connect the ground-based measurements with satellite observations as shown in this study is useful to understand the pollutant transport due to bushfires and its impact on regional air quality.

Evaluating the real changes of air quality due to clean air actions using a machine learning technique: Results from 12 Chinese mega-cities during 2013-2020.

China has implemented two national clean air actions in 2013-2017 and 2018-2020, respectively, with the aim of reducing primary emissions and hence improving air quality at a national level. It is important to examine the effectiveness of such emission reductions and assess the resulting changes in air quality. However, such evaluation is difficult as meteorological factors can amplify, or obscure the changes of air pollutants, in addition to the emission reduction. In this study, we applied the random forest machine learning technique to decouple meteorological influences from emissions changes, and examined the deweathered trends of air pollutants in 12 Chinese mega-cities during 2013-2020. The observed concentrations of all criteria pollutants except O3 showed significant declines from 2013 to 2020, with PM2.5 annual decline rates of 6-9% in most cities. In contrast, O3 concentrations increased with annual growth rates of 1-9%. Compared with the observed results, all the pollutants showed smoothed but similar variation in trend and annual rate-of-change after weather normalization. The response of O3 to NO2 concentrations indicated significant regional differences in photochemical regimes, and the differences between observed and deweathered results provided implications for volatile organic compound emission reductions in O3 pollution mitigation. We further evaluated the effectiveness of first and second clean air actions by removing the meteorological influence. We found that the meteorology can make negative or positive contribution in reducing pollutant concentrations from emission reduction, depending on type of pollutants, locations, and time period. Among the 12 mega-cities, only Beijing showed a positive meteorological contribution in amplifying reductions in main pollutants except O3 during both clean air action periods. Considering the large and variable impact of meteorological effects in changing air quality, we suggest that similar deweathered analysis is needed as a routine policy evaluation tool on a regional basis.

A hybrid approach to estimating long-term and short-term exposure levels of ozone at the national scale in China using land use regression and Bayesian maximum entropy.

Because ambient ozone (O3) has fine spatial scale variability in addition to a large scale regional distribution, accurate exposure predictions for population health studies need to also capture fine spatial scale differences in exposure. To address these needs, we developed a 3-year average land use regression (LUR) and combined LUR and Bayesian maximum entropy (BME) by incorporating a national area variability LUR model for China from 2015 to 2017 along with data that take into account incompleteness of O3 monitoring data into a BME framework. Spatio-temporal kriging models that either included or did not include "soft" data were used for comparison. The final LUR model included five predictor variables: road length within a 1000 m buffer, temperature, wind speed, industrial land area within a 3000 m buffer and altitude. The 1-year predicted O3 concentrations based on the ratio method moderately agreed with the measured concentration, and the regression R2 values were 0.53, 0.57 and 0.59 in the year of 2015, 2016 and 2017, respectively. The LUR/BME model performed better (R2 = 0.80, root mean squared error [RMSE] = 23.5 µg/m3) than the ordinary spatio-temporal kriging model that either included "soft" data (R2 = 0.57, RMSE = 49.2 µg/m3) or did not include the "soft" data (R2 = 0.52, RMSE = 58.5 µg/m3). We have demonstrated that a hybrid LUR/BME model can provide accurate predictions of O3 concentrations with high spatio-temporal resolution at the national scale in mainland China.

The Effect of Lockdown Period during the COVID-19 Pandemic on Air Quality in Sydney Region, Australia.

In early 2020 from April to early June, the metropolitan area of Sydney as well as the rest of New South Wales (NSW, Australia) experienced a period of lockdown to prevent the spread of COVID-19 virus in the community. The effect of reducing anthropogenic activities including transportation had an impact on the urban environment in terms of air quality which is shown to have improved for a number of pollutants, such as Nitrogen Dioxides (NO2) and Carbon Monoxide (CO), based on monitoring data on the ground and from a satellite. In addition to primary pollutants CO and NOx emitted from mobile sources, PM2.5 (primary and secondary) and secondary Ozone (O3) during the lockdown period will also be analyzed using both statistical methods on air quality data and the modelling method with emission and meteorological data input to an air quality model. By estimating the decrease in traffic volume in the Sydney region, the corresponding decrease in emission input to the Weather Research and Forecasting-Community Multiscale Air Quality Modelling System (WRF-CMAQ) air quality model is then used to estimate the effect of lockdown on the air quality especially CO, NO2, O3, and PM2.5 in the Greater Metropolitan Region (GMR) of Sydney. The results from both statistical and modelling methods show that NO2, CO, and PM2.5 levels decreased during the lockdown, but O3 instead increased. However, the change in the concentration levels are small considering the large reduction of ~30% in traffic volume.

The Summer 2019-2020 Wildfires in East Coast Australia and Their Impacts on Air Quality and Health in New South Wales, Australia.

The 2019-2020 summer wildfire event on the east coast of Australia was a series of major wildfires occurring from November 2019 to end of January 2020 across the states of Queensland, New South Wales (NSW), Victoria and South Australia. The wildfires were unprecedent in scope and the extensive character of the wildfires caused smoke pollutants to be transported not only to New Zealand, but also across the Pacific Ocean to South America. At the peak of the wildfires, smoke plumes were injected into the stratosphere at a height of up to 25 km and hence transported across the globe. The meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) model is used together with the air quality monitoring data collected during the bushfire period and remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites to determine the extent of the wildfires, the pollutant transport and their impacts on air quality and health of the exposed population in NSW. The results showed that the WRF-Chem model using Fire Emission Inventory (FINN) from National Center for Atmospheric Research (NCAR) to simulate the dispersion and transport of pollutants from wildfires predicted the daily concentration of PM2.5 having the correlation (R2) and index of agreement (IOA) from 0.6 to 0.75 and 0.61 to 0.86, respectively, when compared with the ground-based data. The impact on health endpoints such as mortality and respiratory and cardiovascular diseases hospitalizations across the modelling domain was then estimated. The estimated health impact on each of the Australian Bureau of Statistics (ABS) census districts (SA4) of New South Wales was calculated based on epidemiological assumptions of the impact function and incidence rate data from the 2016 ABS and NSW Department of Health statistical health records. Summing up all SA4 census district results over NSW, we estimated that there were 247 (CI: 89, 409) premature deaths, 437 (CI: 81, 984) cardiovascular diseases hospitalizations and 1535 (CI: 493, 2087) respiratory diseases hospitalizations in NSW over the period from 1 November 2019 to 8 January 2020. The results are comparable with a previous study based only on observation data, but the results in this study provide much more spatially and temporally detailed data with regard to the health impact from the summer 2019-2020 wildfires.

The effects of humidity and ammonia on the chemical composition of secondary aerosols from toluene/NOx photo-oxidation.

The secondary aerosol formation mechanism in the presence of ammonia (NH3), is poorly understood, especially under high relative humidity (RH) conditions. In this study, a total of seven experiments were conducted from toluene/NOx photo-oxidation in the presence/absence of NH3 under dry (~7% RH) and wet (>60% RH) conditions in a ~3 m3 smog chamber. A series of instruments including gas analysers, scanning mobility particle sizer (SMPS), aerosol mass spectrometry (HR-ToF-AMS) etc. were applied to measure the NOx and O3 concentrations, the mass concentration and chemical composition of secondary aerosol. It was found that NH3 could enhance the mass loading of secondary aerosol, especially under wet condition. However, the presence of NH3 or increasing RH did not have a significant influence on SOA yield. The organic aerosol mass spectrum from AMS showed that the most abundant fragment was at m/z = 44, which was mainly from the fragmentation of carboxylic acids. Compared to the absence of NH3, the fraction of fragment at m/z = 44 and O:C was higher in the presence of NH3, regardless of dry or wet conditions. The highest O:C value of 0.71-0.75 was observed in the presence of NH3 under wet condition, suggesting there could be a synergetic effect between the high RH and the presence of NH3, which jointly contributed to the photochemical aging process of SOA. The N:C increased in the presence of NH3 under both dry and wet conditions, which might be attributed to the carboxylates and organic nitrates formed from the reaction between NH3 and carboxylic acids. The results implied that SOA modelling should consider the role of NH3 and water vapour, which might fill the gap of O:C between laboratory studies and field measurements.

Meteorological and chemical impacts on PM2.5 during a haze episode in a heavily polluted basin city of eastern China.

Haze formation involves many interacting factors, such as secondary aerosol formation, unfavourable synoptic conditions and regional transport. The interaction between these factors complicates scientific understanding of the mechanism behind haze formation. In this study, we investigated the factors resulting in haze events in Longyou, a city located in a basin in China. Aerosol samples of PM2.5 were collected for subsequent chemical composition analysis between 11 January and 5 February 2018. The impacts of wind on PM2.5, SO2 and NO2 concentrations were analysed. Besides, the origin of air parcels and potential sources of PM2.5 were analysed by backward trajectory, potential source contribution function (PSCF) and concentration-weighted trajectories (CWT). Among the water-soluble ions identified, NO3- had the highest concentration, with further analysis demonstrating the haze evolution was mainly driven by the reactions involving NO3- formation. The dramatic increase of nitrate is mainly due to the homogeneous reaction of nitric acid with ammonia, while sulfate is likely due to heterogeneous reactions of NO2, SO2 and NH3. The average wind speed was less than 2 m/s during the aerosol sampling period, which could be considered as a stagnant state. Pollutants emitted by industrial area located in the northeast Longyou were probably brought to observation sites by continuous wind from northeast and accumulated gradually. Air parcels originating from the northeast of Zhejiang province also had large effects on haze pollution in Longyou. Together, our results showed that rapid secondary aerosol formation and unfavourable synoptic conditions are the main factors resulting in haze pollution in Longyou.

Estimation of health and economic benefits based on ozone exposure level with high spatial-temporal resolution by fusing satellite and station observations.

In recent years, ozone pollution has become more and more serious in China. Several epidemiological studies have demonstrated the correlation between short-term ozone exposure and several health risks including all-cause mortality, cardiovascular mortality, and respiratory mortality. In this study, the daily ozone exposure levels with 10 km × 10 km resolution were estimated based on satellite data derived from Ozone Monitoring Instrument (OMI) and the monitoring data. The health impacts for potential decrease in the daily ozone concentration and the corresponding economic benefits in 2016 were estimated by applying the environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. By reducing the daily maximum 8-h average concentration of ozone to 100 µg/m3, the estimated avoided all-cause mortalities were 120 × 103 (95% confidence interval (CI): 67 × 103, 160 × 103) cases and the correspondingly economic benefits ranged from 36 to 64 billion CNY using amended human capital (AHC) and willingness to pay (WTP) method in 2016. If the daily maximum 8-h average concentration of ozone were rolled back to 70 µg/m3, the estimated avoided all-cause mortalities were 160 × 103 (95% CI: 98 × 103, 230 × 103) cases and economic benefits ranged from 54 to 95 billion CNY based on AHC and WTP methods.

Smog chamber study of the role of NH3 in new particle formation from photo-oxidation of aromatic hydrocarbons.

Ammonia (NH3) is a major contributor to secondary aerosol in the atmosphere and can alter the kinetics of their formation. However, systematic studies related to the role of NH3 in aerosol nucleation processes and further particle size growth under complex scenarios are lacking. In this study, we conducted 16 experiments in the CSIRO smog chamber under dry conditions using aromatic hydrocarbons (toluene, o-/m-/p-xylene) and different concentrations of NH3. The presence of NH3 did not change the gas-phase chemistry or nucleation onset time, but slowed the nucleation rate (5%-94%) once it began. From the response of nitrogen oxides (NOx) measurement and mechanism modeling results, we hypothesised that the surface reaction between NH3 and nitric acid played a central role in aerosol nucleation and further growth. After nucleation, the subsequently formed ammonium nitrate and organic condensation vapours may partition together into the initial growth process of new particles, thus increasing the aerosol initial growth rate (8%-90%) and size growth potentials (7%-108%), and leading to high aerosol mass formation. Further investigation implied that the initial growth and further growth rate determine the aerosol mass concentration, rather than the nucleation rate. We conclude that both the initial NOx concentration and volatile organic compound (VOC)/NOx ratio are crucial for the initial and further growth, and aerosol mass of new particles, when NH3 levels are high. Our results provide crucial insights into the complex chemistry of VOC/NOx/NH3 in the atmosphere, and highlight the importance of NH3 reduction for particulate matter control.

Chemical characteristics and sources of PM1 during the 2016 summer in Hangzhou.

During the 2016 Hangzhou G20 Summit, the chemical composition of submicron particles (PM1) was measured by a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) along with a suite of collocated instruments. The campaign was undertaken between August 5 and September 23, 2016. The impacts of emission controls and meteorological conditions on PM1 chemical composition, diurnal cycles, organic aerosol (OA) source apportionment, size distribution and elemental ratios were characterized in detail. Excluding rainy days, the mean PM1 mass concentration during G20 was 30.3 µg/m3, similar to that observed before G20 (28.6 µg/m3), but much lower than that after G20 (42.7 µg/m3). The aerosol chemistry during the three periods was substantially different. Before G20, high PM1 loading mostly occurred at daytime, with OA accounting for 60.1% of PM1, followed by sulfate (15.6%) and ammonium (9.1%). During G20, the OA fraction decreased from 60.1% to 44.6%, whereas secondary inorganic aerosol (SIA) increased from 31.8% to 49.5%. After G20, SIA dominated high PM1 loading, especially at nighttime. Further analysis showed that the nighttime regional transport might play an unfavorable role in the slight increase of secondary PM1 during G20, while the strict emissions controls were implemented. The OA (O/C = 0.58) during G20 was more aged, 48.7% and 13.7% higher than that before and after G20 respectively. Our study highlighted that the emission controls during G20 were of great success in lowering locally produced aerosol and pollutants, despite of co-existence of nighttime regional transport containing aerosol high in low-volatile organics and sulfate. It was implied that not only are emissions controls on both local and regional scale important, but that the transport of pollutants needs to be sufficiently well accounted for, to ensure the successful implementation of air pollution mitigation campaigns in China.