A field sampling campaign of volatile organic compounds (VOCs) was conducted during ozone polluted days at three sites of botanic gardens (HP), industrial areas (XS), and traffic residential mixed areas (ZH) in Hangzhou. The sampling was performed using stainless steel canisters from 6:00 to 20:00 synchronously with a time interval of 2 h on 17 May, 26 June, 20 July, 24 August, and 26 September 2018. A total of 107 species of VOCs for each sample were quantified using two standard gases with a pre-concentrator coupled by GC/MS. The Positive Matrix Factorization (PMF) model was used to identify the major VOC sources and assess their contribution to VOC concentrations. The effects of VOCs on O₃ formation were investigated, based on propylene-equivalent concentrations (Prop-E), ozone formation potential (OFP), and Smog Production Model (SPM). It was found that the concentration of ozone during the sampling days tended to be highest in the downwind area while the concentrations of VOCs and NO₂ in HP were rather low. The most reactive species were isoprene, ethylene, m-xylene, toluene, and propylene. The average total VOC volume mixing ratios in HP, XS, and ZH were 32.00, 36.63, and 50.34 ppbv, respectively. Bimodal profiles of propane and n-butane were exhibited in ZH while unimodal diurnal variation of isoprene was performed in HP. Liquefied petroleum gas/natural gas (LPG/NG) usage, aged background, and secondary source were identified as the major contributors to total VOCs in Hangzhou, accounting for 19.65%, 15.53%, and 18.93%, respectively.

A measurement program designed to evaluate health impacts or benefits of using ethanol blend petrol examined exhaust and evaporative emissions from 21 vehicles representative of the current Australian light duty petrol (gasoline) vehicle fleet using a composite urban emissions drive cycle. The fuels used were unleaded petrol (ULP), ULP blended with either 5% ethanol (E5) or 10% ethanol (E10). The resulting data were combined with inventory data for Sydney to determine the expected fleet emissions for different uptakes of ethanol blended fuel. Fleet ethanol compatibility was estimated to be 60% for 2006, and for the air quality modelling it was assumed that in 2011 over 95% of the fleet would be ethanol compatible. Secondary organic aerosol (SOA) formation from ULP, E5 and E10 emissions was studied under controlled conditions by the use of a smog chamber. This was combined with meteorological data from Sydney for February 2004 and the emission data (both measured and inventory data) to model pollutant concentrations in Sydney’s airshed for 2006 and 2011. These concentrations were combined with the population distribution to evaluate population exposure to the pollutant. There is a health benefit to the Sydney population arising from a move from ULP to ethanol blends in spark-ignition vehicles. Potential health cost savings for Urban Australia (Sydney, Melbourne, Brisbane and Perth) are estimated to be A$39 million (in 2007 dollars) for a 50% uptake (by ethanol compatible vehicles) of E10 in 2006 and $42 million per annum for a 100% take up of E10 in 2011. Over 97% of the estimated health savings are due to reduced emissions of PM_2.5 and consequent reduced impacts on mortality and morbidity (e.g., asthma, cardiovascular disease). Despite more petrol-driven vehicles predicted for 2011, the quantified health impact differential between ULP and ethanol fuelled vehicles drops from 2006 to 2011. This is because modern petrol vehicles, with lower emissions than their older counterparts, will make up a higher proportion of the fleet in the future. Hence the beneficial effects of reductions in particulate matter become less significant as the fleet as a whole produces lower emissions.

Emissions from power plants constitute a major part of air pollution and should be adequately estimated. In this paper, we consider the problem of estimating nitrogen dioxide (NO$_X$) emission of power plants by developing an inverse method to integrate satellite observations of atmospheric pollutant column concentrations with species concentrations and direct sensitivities predicted by a regional air quality model, in order to discern biases in the emissions of the pollutant precursors. Using this method, the emission fields are analyzed using a “bottom-up” approach, with an inversion performed by an unscented Kalman filter (UKF) to improve estimation profiles from emissions inventories data for the Sydney metropolitan area. The idea is to integrate information from the original inventories with tropospheric nitrogen dioxide (NO$_2$) emissions estimated during one month from the air pollution model-chemical transport model, and then, for validation, to compare the resulting model with satellite retrievals from the ozone monitoring instrument (OMI) above the region. The UKF-based estimation of NO$_2$ emissions shows better agreement with OMI observations, implying a significant improvement in accuracy as compared with the original inventories. Therefore, the proposed method is a promising tool for estimation of air emissions in urban areas.