Real-world greenhouse gas emission characteristics from in-use light-duty diesel trucks in China.

The transportation sector is a significant contributor to greenhouse gas (GHG) emissions in China. However, real-world GHG emissions from in-use light-duty diesel trucks (LDDTs) are largely uncertain due to data paucity. In this study, we have conducted real driving emission (RDE) tests of real-world CO2, N2O, and CH4 emissions from 12 in-use LDDTs in China. Results reveal that China's CH4 emission rates from LDDTs are overestimated by 57.71 ± 39.15 % if using the previous ratio method of CO2:CH4. Notably, under real-world driving conditions, such as speeds exceeding 60 km/h, maximum exhaust gas temperatures are reached, potentially impacting urea decomposition catalyst temperatures and subsequently influencing N2O production, which is highly sensitive to system temperature. Moreover, uphill roads can increase CO2 emissions by 51.93 % compared to downhill roads. Despite the tightening of vehicle emission standards, CO2 and N2O emissions from the LDDTs have not decreased linearly. However, LDDTs meeting the China VI standard exhibit the lowest average CO2, N2O and CH4 emission factors (EFs) of 335.26 ± 21.72 g/km, 2.7 ± 0.69 mg/km and 3.50 ± 0.70 mg/km, respectively. At last, the uncertainties in the GHG EFs for the tested LDDTs through RDE tests were (-39 %, 82 %) in our study, while a significantly higher uncertainty (-85 %, 182 %) for GHG EFs of LDDTs were found in our study and other reported literature in China, largely due to the application of different non-native vehicle emission factor models and testing methods, as well as different vehicles of control emission standards. Our study highlights more urgent needs for direct RDE tests and the importance of considering real driving conditions, such as road grades, in special geographical regions when undertaking carbon accounting work in the transportation sector.

Developing a model-ready highly resolved HONO emission inventory in Guangdong using domestic measured emission factors.

Nitrous acid (HONO) plays an important role in the budget of hydroxyl radical (OH) in the atmosphere. However, current chemical transport models (CTMs) typically underestimate ambient concentrations of HONO due to a dearth of high resolution primary HONO emission inventories. To address this issue, we have established a highly resolved bottom-up HONO emission inventory for CTMs in Guangdong province, utilizing the best available domestic measured emission factors and newly obtained activity data. Our results indicate that emissions from various sources in 2020, including soil, on-road traffic, non-road traffic, biomass burning, and stationary combustion, were estimated at 21.5, 10.0, 8.2, 2.5, and 0.7 kt, respectively. Notably, the HONO emissions structure differed between the Pearl River Delta (PRD) and the non-PRD regions. Specifically, traffic sources were the dominant contributors (62 %) to HONO emissions in the PRD, whereas soil sources accounted for the majority (65 %) of those in the non-PRD. Among on-road traffic sources, diesel vehicles played a significant role, contributing 99.7 %. Comparisons with previous methods suggest that HONO emissions from diesel vehicles are underestimated by approximately 2.5 times. Higher HONO emissions, dominated by soil emissions, were observed in summer months, particularly in August. Furthermore, diesel vehicle emissions were pronounced at night, likely contributing to the nighttime accumulation of HONO and the morning peak of OH. The emission inventories developed in this study can be directly applied to widely used CTMs, such as CMAQ, CAMx, WRF-Chem, and NAQPMS, to support the simulation of OH formation and secondary air pollution.

Characterizing Operating Condition-Based Formaldehyde Emissions of Light-Duty Diesel Trucks in China Using a PEMS-HCHO System.

Formaldehyde (HCHO) plays a critical role in atmospheric photochemistry and public health. While existing studies have suggested that vehicular exhaust is an important source of HCHO, the operating condition-based diesel truck HCHO emission measurements remain severely limited due to the limited temporal resolution and accuracy of measurement techniques. In this study, we characterized the second-by-second HCHO emissions from 29 light-duty diesel trucks (LDDTs) in China over dynamometer and real-world driving tests using a portable online HCHO emission measurement system (PEMS-HCHO), considering various operating conditions. Our results suggested that the HCHO emissions from LDDTs might be underestimated by the widely used offline DNPH-HPLC method. The HCHO emissions at a 200 s cold start from China V LDDT can be up to 50 mg/start. Different driving conditions over dynamometer and real-world driving tests led to a 2-4 times difference in the HCHO emission factors (EFs). Under real-world hot-running conditions, the HCHO EFs of China III, IV, V, and VI LDDTs were 43.5 ± 35.7, 10.6 ± 14.2, 8.8 ± 5.1, and 3.2 ± 1.2 mg/km, respectively, which significantly exceeded the latest California low emission vehicle III HCHO emission standard (2.5 mg/km). These findings highlighted the significant impact of vehicle operating conditions on HCHO emissions and the urgency of regulating HCHO emissions from LDDTs in China.

A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China.

The conventional Ensemble Kalman filter (EnKF), which is now widely used to calibrate emission inventories and to improve air quality simulations, is susceptible to simulation errors of meteorological inputs, making accurate updates of high temporal-resolution emission inventories challenging. In this study, we developed a novel meteorologically adjusted inversion method (MAEInv) based on the EnKF to improve daily emission estimations. The new method combines sensitivity analysis and bias correction to alleviate the inversion biases caused by errors of meteorological inputs. For demonstration, we used the MAEInv to inverse daily carbon monoxide (CO) emissions in the Pearl River Delta (PRD) region, China. In the case study, 60% of the total CO simulation biases were associated with sensitive meteorological inputs, which would lead to the overestimation of daily variations of posterior emissions. Using the new inversion method, daily variations of emissions shrank dramatically, with the percentage change decreased by 30%. Also, the total amount of posterior CO emissions estimated by the MAEInv decreased by 14%, indicating that posterior CO emissions might be overestimated using the conventional EnKF. Model evaluations using independent observations revealed that daily CO emissions estimated by MAEInv better reproduce the magnitude and temporal patterns of ambient CO concentration, with a higher correlation coefficient (R, +37.0%) and lower normalized mean bias (NMB, -17.9%). Since errors of meteorological inputs are major sources of simulation biases for both low-reactive and reactive pollutants, the MAEInv is also applicable to improve the daily emission inversions of reactive pollutants.

[Volatile Organic Compound Emission Characteristics and Influences Assessment of a Petrochemical Industrial Park in the Pearl River Delta Region].

The petrochemical industry is one of the major emission sources of volatile organic compounds (VOCs). However, the current studies have mostly focused on the identification of the chemical characteristics of non-methane hydrocarbon (NMHC) VOCs species from the petroleum refining sub-sector. Research on the characteristics of VOCs components in oxygenated VOCs (OVOCs) species and other important sub-sectors is still lacking. Therefore, eight enterprises at a petrochemical industrial park in the Pearl River Delta region were carefully selected to represent three major subsectors, namely petroleum refining, synthetic materials, and organic chemicals, for the petrochemical industry. The VOCs (including 22 OVOCs species) from stack emissions and fugitive emissions, as well as nearby sensitive sites, were sampled, and the source reactivity (SR), the thresholds of malodor, and the carcinogenic and non-carcinogenic risks were assessed. The main results were as follows:① the VOCs concentrations of the stack emissions from the petrochemical industrial park were between 0.2-46.3 mg·m-3. The VOCs species were greatly affected by the type of after-treatment technology. A major VOC species emitted from the combustion-based after treatments was formaldehyde, whereas the species emitted from the non-combustion-based equipment were acetone, 1,3-butadiene, acrylic, and isobutane. ② The fugitive VOCs emissions from the petroleum storage tank area were dominated by alkanes, whereas the other fugitive emission sites and the sensitive sites were dominated by OVOCs such as acetone, formaldehyde, and ethyl acetate. ③ The SRs were mainly contributed by OVOCs, aromatics, and olefins, with average proportions of 43.1%, 24.2%, and 21.1%, respectively, with the major species being formaldehyde, acetaldehyde, m/p-xylene, ethylene, and toluene. ④ The malodor appeared both in fugitive emission areas and the sensitive sites. The main odor components were OVOCs such as n-butyraldehyde, propionaldehyde, hexanal, and valeraldehyde. ⑤ The non-carcinogenic risks occurred in the fugitive emission areas and the sensitive sites of resin, alcohol, and aldehyde production, which were mainly caused by OVOCs such as free acetaldehyde, acrolein, and propionaldehyde. No carcinogenic risk was found in any of the sampled sites. This research can provide scientific support for the formulation of priority VOCs species-based precise control strategies in petrochemical industrial parks.

Near-real-time estimation of hourly open biomass burning emissions in China using multiple satellite retrievals.

Open biomass burning (OBB) is an important source of air pollutants and greenhouse gases, but its dynamic emission estimation remains challenging. Existing OBB emission datasets normally provide daily estimates based upon Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals but tend to underestimate the emissions due to the coarse spatial resolution and sparse observation frequency. In this study, we proposed a novel approach to improve OBB emission estimations by fusing multiple active fires detected by MODIS, Visible Infrared Imaging Radiometer onboard the Suomi National Polar-orbiting Partnership (VIIRS S-NPP) and Himawari-8. The fusion of multiple active fires can capture the missing small fires and the large fires take place during the non-overpass time of MODIS observations. Also, regional-based fire radiative power (FRP) cycle reconstruction models and OBB emission coefficients were developed to address the large spatial discrepancies of OBB emission estimations across China and to promote the estimate to an hourly resolution. Using the new approach, hourly gridded OBB emissions in China were developed and can be updated with a lag of 1-day, or even near-real-time when real-time multiple active fires are available. OBB emissions in China based on this approach were more than 3 times of those in previous datasets. Evaluations revealed that the spatial distribution of the estimated PM2.5 emissions from this study was more consistent with the ambient PM2.5 concentrations during several episodes than existing datasets. The hourly OBB emissions provide new insight into its spatiotemporal variations, enhance timely and reliable air quality modeling and forecast, and support the formulation of accurate prevention and control policies of OBB.

A newly integrated dataset of volatile organic compounds (VOCs) source profiles and implications for the future development of VOCs profiles in China.

Volatile organic compounds (VOCs) source profiles can be used for a number of purposes, such as creating speciated air pollutant emission inventories and providing inputs to receptor and air quality models. In this study, we first collected and schematically evaluated more than 500 Chinese domestic source profiles from literature and field measurements, and then established a most up-to-date dataset of VOCs source profiles in China by integrating 363 selective VOCs profiles into 101 sector-based source profiles. The profile dataset covers eight major source categories and contains 447 VOCs species including non-methane hydrocarbons (NMHCs) species and oxygenated VOCs (OVOCs) species. The results shown that (1) VOCs composition characteristics exhibit variations for most Level-II source sectors and Level-III sub-sectors even under the same Level-I source category; (2) OVOCs, which were significantly missing in previous profiles, account for more than 95% in cooking and 20- 40% in non-road mobile, biomass burning and solvent use sources; (3) aromatics account for 20%-40% in most emission sources except cooking source, alkenes and alkynes account for ~20% in combustion sources (stationary combustion, mobile source and biomass burning), alkanes are abundant in gasoline-related emission sources(on-road mobile source and fuel oil storage and transportation); (4) missing OVOCs species could bring 30%-50% to ozone formation potentials in most emission sources; and (5) there are considerable differences in VOCs chemical groups and individual species for most emission sources between this dataset and the widely used U.S. SPECIATE database, indicating the importance of developing domestic VOCs source profiles. The dataset developed in this study can help support reactive VOCs species-based ozone control strategy and provide domestic profile data for source apportionment and air quality modeling in China and other countries or regions with similar emission source characteristics.

Insight into the characteristics of carbonaceous aerosols at urban and regional sites in the downwind area of Pearl River Delta region, China.

Carbonaceous aerosols (CAs) take up a substantial fraction of fine particle (PM2.5) in the atmosphere, yet high temporal resolution and seasonal variations of their emission sources and formation mechanisms are still poorly characterized in the regions with strong anthropogenic activities. In this study, the spatiotemporal characteristics of CAs and their subfractions, i.e., organic carbon (OC) and elemental carbon (EC), were studied in one of China's key city clusters, the Pearl River Delta (PRD) region. Results show that the annual mean OC and EC concentrations are 5.89 ± 3.32 µg/m3 and 1.60 ± 1.00 µg/m3 at the urban site, respectively. Such levels are consistently higher than those at the regional site (4.94 ± 3.34 µg/m3 of OC and 1.45 ± 0.82 µg/m3 of EC), suggesting the strong impact of human activities on OC and EC concentration. Moreover, the OC concentration peak sharply appears at 19:00 across all seasons at the urban site due to the direct influence of traffic exhaust and cooking activities. At regional site, OC peaks in fall afternoon due to intensive photochemical reactions derived combustion-related secondary organic carbon (SOCcom) contributions to the downwind PRD region. Correlations between SOCcom and influence factors were found at both regional and urban sites, suggesting that SOCcom formation is more regionally homogenous and mainly originates from the Zhaoqing-Foshan-Jiangmen belt. In addition, there are significantly different formation mechanisms of non-combustion-related secondary organic carbon (SOCnon-com) in the downwind PRD region. This study provides a solid evidence for collaborative efforts in the mitigation of secondary aerosols in the PRD region.

Anthropogenic atmospheric toxic metals emission inventory and its spatial characteristics in Guangdong province, China.

Atmospheric toxic metals (TMs) may cause adverse effects on the environment and human health due to their bioavailability and toxicity. High-resolution TMs emission inventory is important input data for assessing human exposure risks, especially synergistic toxicity of multiple toxic metals. By using the latest city- and enterprise-level environment statistical data, an emission inventory of five TMs (Hg, As, Pb, Cd, Cr) in Guangdong province for the year of 2014 was developed using a bottom-up approach. The total emissions of Hg, As, Pb, Cd and Cr in Guangdong were estimated as 17.70, 32.59, 411.34, 13.13, and 84.16 t, respectively. Major emission sources for each TM were different. Hg emissions were dominated by coal combustion (33%), fluorescent lamp (18%) and cement (17%). 78% of Hg emissions were in the form of Hg0, 19% of Hg2+, and only 3% of Hgp due to strict particulate matter control policies. Coal combustion (48%), nonferrous metal smelting (25%) and iron and steel industry (24%) were the major sources of As. Pb emissions primarily came from battery production (42%), iron and steel industry (21%) and gasoline combustion (17%). Cd and Cr emissions were dominated by nonferrous metal smelting (71%) and iron and steel industry (82%), respectively. Most of these TMs were emitted in the non-Pearl River Delta region, where the newly-built iron and steel industry, nonferrous metal smelting and cement production factories were intense. The uncertainties in the five TM emissions were high, due much to high uncertainties in TM emission factors and limited activity data. Thus, to improve the accuracy of these estimates, we recommend more field tests of TM emissions, especially for the industrial process sector. This study provides scientific support for formulating robust TMs control policies to alleviate the high risk of TMs exposure in Guangdong.

Infrared-active quadruple contrast FePt nanoparticles for multiple scale molecular imaging.

A single nanomaterial with multiple imaging contrasts and functions is highly desired for multiscale theragnosis. Herein, we demonstrate single 1-1.9 µm infrared-active FePt alloy nanoparticles (FePt NPs) offering unprecedented four-contrast-in-one molecular imaging - computed tomography (CT), magnetic resonance imaging (MRI), photoacoustic (PA) imaging, and high-order multiphoton luminescence (HOMPL) microscopy. The PA response of FePt NPs outperforms that of infrared-active gold nanorods by 3- to 5.6-fold under identical excitation fluence and particle concentrations. HOMPL (680 nm) of an isolated FePt NP renders spatial full-width-at-half-maximum values of 432 nm and 300 nm beyond the optical diffraction limit for 1230-nm and 920-nm excitation, respectively. The in vivo targeting function was successfully visualized using HOMPL, PA imaging, CT, and MRI, thereby validating FePt as a single nanomaterial system covering up to four types (Optical/PA/CT/MRI) of molecular imaging contrast, ranging from the microscopic level to whole-body scale investigation.