Reconciling discrepancies in the source characterization of VOCs between emission inventories and receptor modeling

Emission inventory (EI) and receptor model (RM) are two of the three source apportionment (SA) methods recommended by Ministry of Environment of China and used widely to provide independent views on emission source identifications. How to interpret the mixed results they provide, however, were less studied. In this study, a cross-validation study was conducted in one of China's fast-developing and highly populated city cluster- the Pearl River Delta (PRD) region. By utilizing a highly resolved speciated regional EI and a region-wide gridded volatile organic compounds (VOCs) speciation measurement campaign, we elucidated underlying factors for discrepancies between EI and RM and proposed ways for their interpretations with the aim to achieve a scientifically plausible source identification. Results showed that numbers of species, temporal and spatial resolutions used for comparison, photochemical loss of reactive species, potential missing sources in EI and tracers used in RM were important factors contributed to the discrepancies. Ensuring the consensus of species used in EIs and RMs, utilizing a larger spatial coverage and longer time span, addressing the impacts of photochemical losses, and supplementing emissions from missing sources could help reconcile the discrepancies in VOC source characterizations acquired using both approaches. By leveraging the advantages and circumventing the disadvantages in both methods, the EI and RM could play synergistic roles to obtain robust SAs to improve air quality management practices

Modeling inorganic nitrogen deposition in Guangdong province, China

Atmospheric nitrogen deposition is an essential component of acid deposition and serves as one of main sources of nitrogen of the ecosystem. Along with rapidly developed economy, it is expected that the nitrogen deposition in Guangdong province is considerably large, due to substantial anthropogenic reactive nitrogen lost to the Pearl River Delta (PRD) region, one of the most developed region in China. However, characterization of chemical compositions of inorganic nitrogen (IN) deposition and quantification of nitrogen deposition fluxes in time and space in Guangdong province were seldom conducted, especially using a numerical modeling approach. In this study, we established a WRF/SMOKE-PRD/CMAQ model system and expanded 2006-based PRD regional emission inventories to Guangdong provincial ones, including SO2, NOx, VOC, PM10, PM2.5, and NH3 emissions for modeling nitrogen deposition in Guangdong province. Observations, including meteorological observed data, rainfall data, ground-level criteria pollutant measurements, satellite-derived data, and nitrogen deposition fluxes from field measurements were employed in the evaluation of model performance. Results showed that annual nitrogen deposition fluxes in the PRD region and Guangdong province were 31.01 kg N hm(-1) a(-1) and 26.03 kg N hm(-1) a(-1), dominated by NHx (including NH3 and NH4+), with a percentage of 63% and 71% of the total deposition flux of IN, respectively. The ratio of dry deposition to wet deposition was approximately 2:1 in the PRD region and about 3:2 in the whole Guangdong province. IN deposition was mainly distributed in the PRD region, Chaozhou, and Maoming, which was similar to the spatial distributions of NOx and NH3 emissions. The spatial distributions of chemical compositions of IN deposition implied that NH3-N and NOx-N tended to deposit in places close to emission sources, while spatial distributions of aerosol NH4+ - N and NO3- - N usually exhibited broader deposition areas, along with long-range transport of fine particles. Distinct temporal trends were found in IN components, especially for wet depositions, with peak values in August. (C) 2015 Elsevier Ltd. All rights reserved

Uncovering the key mechanisms of how deep decarbonization benefits air pollution alleviation in China

Addressing climate change and air pollution goals in conjunction would be efficient and cost-effective. Dealing with these two challenges is a common issue for urban clusters pursuing sustainable development. Expected to become the fourth international first-class bay area, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) takes the lead in exploring a green and low-carbon transition path as a key element of being a pioneering economic reform demonstration zone. Based on an integrated modeling framework that couples an energy-economy model (IMED|CGE), decomposition analysis, and regression methods, the potential contribution of achieving the climate mitigation target to air pollutant reduction in the GBA by 2050 was quantified. The results showed that the transport sector has the most significant potential for carbon reduction. Energy intensity and structural transformations are the main contributors to reducing carbon emissions, with the latter becoming increasingly important over time. Climate policy can effectively reduce air pollutant emissions; however, this effect varies for different pollutants and sectors. Based on the assessment of the synergy index and cost of abatement, sectors with priority for synergic governance were identified. The regression results indicated that the carbon shadow price would be significantly more effective in reducing air pollutant emissions in the post-2030 period than before 2030, except for SO _2 and NH _3 , partially because of the existing actions that cause the synergistic effects to decline. In addition, end-of-pipe removal measures still play a relatively significant role in reducing air pollutants, particularly VOC, NH _3, and primary PM _2.5 . Thus, the findings suggest that priority should be given to sectors with huge synergistic benefits, such as transportation and power generation while paying attention to possible trade-offs

Decadal changes in emissions of volatile organic compounds (VOCs) from on-road vehicles with intensified automobile pollution control: Case study in a busy urban tunnel in south China

In the efforts at controlling automobile emissions, it is important to know in what extent air pollutants from on-road vehicles could be truly reduced. In 2014 we conducted tests in a heavily trafficked tunnel in south China to characterize emissions of volatile organic compounds (VOC) from on-road vehicle fleet and compared our results with those obtained in the same tunnel in 2004. Alkanes, aromatics, and alkenes had average emission factors (EFs) of 338, 63, and 42 mg km-1 in 2014 against that of 194, 129, and 160 mg km-1 in 2004, respectively. In 2014, LPG-related propane, n-butane and i-butane were the top three non-methane hydrocarbons (NMHCs) with EFs of 184 ± 21, 53 ± 6 and 31 ± 3 mg km-1; the gasoline evaporation marker i-pentane had an average EF of 17 ± 3 mg km-1; ethylene and propene were the top two alkenes with average EFs of 16 ± 1 and 9.7 ± 0.9 mg km-1, respectively; isoprene had no direct emission from vehicles; toluene showed the highest EF of 11 ± 2 mg km-1 among the aromatics; and acetylene had an average EF of 7 ± 1 mg km-1. While EFs of total NMHCs decreased only 9% from 493 ± 120 mg km-1 in 2004 to 449 ± 40 mg km-1 in 2014, their total ozone formation potential (OFP) decreased by 57% from 2.50 × 103 mg km-1 in 2004 to 1.10 × 103 mg km-1 in 2014, and their total secondary organic aerosol formation potential (SOAFP) decreased by 50% from 50 mg km-1 in 2004 to 25 mg km-1 in 2014. The large drop in ozone and SOA formation potentials could be explained by reduced emissions of reactive alkenes and aromatics, due largely to fuel transition from gasoline/diesel to LPG for taxis/buses and upgraded vehicle emission standards