Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing.

With the decreasing regional-transported levels, the health risk assessment derived from fine particulate matter (PM2.5) has become insufficient to reflect the contribution of local source heterogeneity to the exposure differences. Here, we combined the both ultra-high-resolution PM2.5 concentration with population distribution to provide the personal daily PM2.5 internal dose considering the indoor/outdoor exposure difference. A 30-m PM2.5 assimilating method was developed fusing multiple auxiliary predictors, achieving higher accuracy (R2 = 0.78-0.82) than the chemical transport model outputs without any post-simulation data-oriented enhancement (R2 = 0.31-0.64). Weekly difference was identified from hourly mobile signaling data in 30-m resolution population distribution. The population-weighted ambient PM2.5 concentrations range among districts but fail to reflect exposure differences. Derived from the indoor/outdoor ratio, the average indoor PM2.5 concentration was 26.5 µg/m3. The internal dose based on the assimilated indoor/outdoor PM2.5 concentration shows high exposure diversity among sub-groups, and the attributed mortality increased by 24.0% than the coarser unassimilated model.

Updating emission inventories for vehicular organic gases: Indications from cold-start and temperature effects on advanced technology cars.

How would the organic gas emission inventories of future urban vehicles change with new features of advanced technology cars? Here, volatile organic compounds (VOCs) and intermediate volatile organic compounds (IVOCs) from a fleet of Chinese light-duty gasoline vehicles (LDGVs) were characterized by chassis dynamometer experiments to grasp the key factors affecting future inventory accuracy. Subsequently, the VOC and IVOC emissions of LDGVs in Beijing, China, from 2020 to 2035, were calculated and the spatial-temporal variations were recognized under a scenario of fleet renewal. With the tightening of emission standards (ESs), cold start contributed a larger fraction of the total unified cycle VOC emissions due to the imbalanced emission reductions between operating conditions. It took 757.47 ± 337.75 km of hot running to equal one cold-start VOC emission for the latest certified vehicles. Therefore, the future tailpipe VOC emissions would be highly dependent on discrete cold start events rather than traffic flows. By contrast, the equivalent distance was shorter and more stable for IVOCs, with an average of 8.69 ± 4.59 km across the ESs, suggesting insufficient controls. Furthermore, there were log-linear relationships between temperatures and cold-start emissions, and the gasoline direct-injection vehicles performed better adaptability under low temperatures. In the updated emission inventories, the VOC emissions were more effectively reduced than the IVOC emissions. The start emissions of VOCs were estimated to be increasingly dominant, especially in wintertime. By winter 2035, the contribution of VOC start emissions could reach 98.98 % in Beijing, while the fraction of IVOC start emissions would decrease to 59.23 %. Spatially allocation showed that the high emission regions of tailpipe organic gases from LDGVs have transferred from road networks to regions of intense human activities. Our results provide new insights into tailpipe organic gas emissions of gasoline vehicles, and can support future emission inventories and refined assessment of air quality and human health risk.

Comprehensive Assessment for the Impacts of S/IVOC Emissions from Mobile Sources on SOA Formation in China.

Semivolatile/intermediate-volatility organic compounds (S/IVOCs) from mobile sources are essential SOA contributors. However, few studies have comprehensively evaluated the SOA contributions of S/IVOCs by simultaneously comparing different parameterization schemes. This study used three SOA schemes in the CMAQ model with a measurement-based emission inventory to quantify the mobile source S/IVOC-induced SOA (MS-SI-SOA) for 2018 in China. Among different SOA schemes, SOA predicted by the 2D-VBS scheme was in the best agreement with observations, but there were still large deviations in a few regions. Three SOA schemes showed the peak value of annual average MS-SI-SOA was up to 0.6 ± 0.3 µg/m3. High concentrations of MS-SI-SOA were detected in autumn, while the notable relative contribution of MS-SI-SOA to total SOA was predicted in the coastal areas in summer, with a regional average contribution up to 20 ± 10% in Shanghai. MS-SI-SOA concentrations varied by up to 2 times among three SOA schemes, mainly due to the discrepancy in SOA precursor emissions and chemical reactions, suggesting that the differences between SOA schemes should also be considered in modeling studies. These findings identify the hotspot areas and periods for MS-SI-SOA, highlighting the importance of S/IVOC emission control in the future upgrading of emission standards.

An updated comprehensive IVOC emission inventory for mobile sources in China.

Intermediate volatility organic compounds (IVOCs) from mobile sources contribute significantly to secondary organic aerosol (SOA) formation. However, the assessments of IVOC emissions remain considerably uncertain due to the lack of localized measured data and detailed emission source classifications. This study established a comprehensive database of IVOC emission factors (EFs) for mobile sources based on the diversified measured EFs and correlations with hydrocarbons. The provincial-level IVOC emission inventories over China were further established by integrating activity data of various mobile sources. The national mobile source IVOC emissions were 507.5 Gg in 2017. The IVOC emissions of on-road and non-road mobile sources were roughly the same. Trucks and non-road construction machineries were the major contributors to IVOC emissions, accounting for >66 % of the total. The IVOC emission characteristics and spatial distributions from various mobile sources varied significantly with different types and usages. The IVOC emission inventories with detailed classifications can be used to evaluate emission control policies for mobile sources. Incorporating localized measured data would be beneficial for a better understanding for the atmospheric impacts of mobile source IVOC emissions.

Impacts of vehicle emission on air quality and human health in China.

The growing of vehicle population aggravates air pollution and threatens human health. In this study, based on the refined whole-process vehicle emission inventory considering volatile organic compounds (VOCs) evaporation emission, the CAMx model was applied to comprehensively quantify the impacts of the vehicle sector on the annual and seasonal concentrations of PM2.5 and O3 in China. Also, the health risks caused by long-term exposure to PM2.5 and O3 were evaluated. The model results showed that vehicle emission was an important source of severe O3 pollution in summer, with a contribution of more than 30% in most parts of China, but not an important source of serious PM2.5 pollution in winter, with a contribution of less than 20% in heavily polluted regions in China. Compared to tailpipe emission, vehicle VOCs evaporation emission led to increases of 25% and 47% to sectoral contribution to PM2.5 and O3. Health risk assessment results showed that attributable deaths caused by long-term exposure to PM2.5 and O3 were 975,029 and 46,043 in 2018, to which vehicle emission contributed approximately 12.5% and 22.2%, respectively.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown.

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing "pandemic haze," raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

A big data approach to improving the vehicle emission inventory in China.

Estimating truck emissions accurately would benefit atmospheric research and public health protection. Here, we developed a full-sample enumeration approach TrackATruck to bridge low-frequency but full-size vehicles driving big data to high-resolution emission inventories. Based on 19 billion trajectories, we show how big the emission difference could be using different approaches: 99% variation coefficients on regional total (including 31% emissions from non-local trucks), and ± as large as 15 times on individual counties. Even if total amounts are set the same, the emissions on primary cargo routes were underestimated in the former by a multiple of 2-10 using aggregated approaches. Time allocation proxies are generated, indicating the importance of day-to-day estimation because the variation reached 26-fold. Low emission zone policy reduced emissions in the zone, but raised emissions in upwind areas in Beijing's case. Comprehensive measures should be considered, e.g. the demand-side optimization.

Estimation of PM2.5 mortality burden in China with new exposure estimation and local concentration-response function.

The estimation of PM2.5-related mortality is becoming increasingly important. The accuracy of results is largely dependent on the selection of methods for PM2.5 exposure assessment and Concentration-Response (C-R) function. In this study, PM2.5 observed data from the China National Environmental Monitoring Center, satellite-derived estimation, widely collected geographic and socioeconomic information variables were applied to develop a national satellite-based Land Use Regression model and evaluate PM2.5 exposure concentrations within 2013-2015 with the resolution of 1 km × 1 km. Population weighted concentration declined from 72.52 µg/m3 in 2013 to 57.18 µg/m3 in 2015. C-R function is another important section of health effect assessment, but most previous studies used the Integrated Exposure Regression (IER) function which may currently underestimate the excess relative risk of exceeding the exposure range in China. A new Shape Constrained Health Impact Function (SCHIF) method, which was developed from a national cohort of 189,793 Chinese men, was adopted to estimate the PM2.5-related premature deaths in China. Results showed that 2.19 million (2013), 1.94 million (2014), 1.65 million (2015) premature deaths were attributed to PM2.5 long-term exposure, different from previous understanding around 1.1-1.7 million. The top three provinces of the highest premature deaths were Henan, Shandong, Sichuan, while the least ones were Tibet, Hainan, Qinghai. The proportions of premature deaths caused by specific diseases were 53.2% for stroke, 20.5% for ischemic heart disease, 16.8% for chronic obstructive pulmonary disease and 9.5% for lung cancer. IER function was also used to calculate PM2.5-related premature deaths with the same exposed level used in SCHIF method, and the comparison of results indicated that IER had made a much lower estimation with less annual amounts around 0.15-0.5 million premature deaths within 2013-2015.

The impact of marine shipping and its DECA control on air quality in the Pearl River Delta, China.

Marine trade has significantly expanded over the past decades aiding to the economic development of the maritime countries, yet, this has been associated with a considerable increase in pollution emission from shipping operation. This study aims at considering both sides of the spectrum at the same time, which is including both public and shipping business. Of the key significance would be to optimize the operation of the shipping industry, such that its impact on air pollution is minimized, without, however, significant escalation of its cost, and therefore to protect the whole seaborne trade. To do this, we considered the impacts of three control strategies, including the current emission control area (ECA) design, as well two additional ones. Thus the first scenario (DECA1) was based on the China's domestic emission control area (DECA), which was set up in 2016. The DECA1 scale was only 12 nautical miles, which was much smaller than the emission control areas in US or Europe. We defined the second scenario (DECA2), by stretching the zone to 200 nautical miles towards the ocean, modeling it on the ECA in North America. The third scenario (DECA3), on the other hand, expanded the 12 nautical miles control zone along the whole coastline. To investigate the impact of shipping emissions on air quality, a shipping emission calculation model and an air quality simulation model were used, and Pearl River Delta (PRD), China was chosen to serve as a case study. The study demonstrated that in 2013 marine shipping emissions contributed on average 0.33 and 0.60µg·m-3, respectively to the land SO2 and PM2.5 concentrations in the PRD, and that the concentrations were high along the coastline. The DECA1 policy could effectively reduce SO2 and PM2.5 concentrations in the port regions, and the average reduction in the land area were 9.54% and 2.7%, respectively. Compared with DECA1, DECA2 would not measurably improve the air quality, while DECA3 would effectively decrease the pollution in the entire coast area. Thus, instead of expanding emission control area far to the ocean, it is more effective to control emissions along the coastline to secure the best air quality and lower the health impacts. By doing this, 19 million dollars of fuel cost could be saved per year. The saved cost could help the ship owners to endure, considering the current low profits of the seaborne trade, and thus to protect the overall growth of the economy.

Shipping emission forecasts and cost-benefit analysis of China ports and key regions' control.

China established Domestic Emission Control Area (DECA) for sulphur since 2015 to constrain the increasing shipping emissions. However, future DECA policy-makings are not supported due to a lack of quantitive evaluations. To investigate the effects of current and possible Chinese DECAs policies, a model is presented for the forecast of shipping emissions and evaluation of potential costs and benefits of an DECA policy package set in 2020. It includes a port-level and regional-level projection accounting for shipping trade volume growth, share of ship types, and fuel consumption. The results show that without control measures, both SO2 and particulate matter (PM) emissions are expected to increase by 15.3-61.2% in Jing-Jin-Ji, the Yangtze River Delta, and the Pearl River Delta from 2013 to 2020. However, most emissions can be reduced annually by the establishment of a DECA that depends on the size of the control area and the fuel sulphur content limit. Costs range from 0.667 to 1.561 billion dollars (control regional shipping emissions) based on current fuel price. A social cost method shows the regional control scenarios benefit-cost ratios vary from 4.3 to 5.1 with large uncertainty. Chemical transportation model combined with health model method is used to get the monetary health benefits and then compared with the results from social cost method. This study suggests that Chinese DECAs will reduce the projected emissions at a favorable benefit-cost ratio, and furthermore proposes policy combinations that provide high cost-effective benefits as a reference for future policy-making.

Development of PM2.5 and NO2 models in a LUR framework incorporating satellite remote sensing and air quality model data in Pearl River Delta region, China.

High resolution pollution maps are critical to understand the exposure and health effect of local residents to air pollution. Currently, none of the single technologies used to measure or estimate concentrations of pollutants can provide sufficient resolved exposure data. Land use regression (LUR) models were developed to combine ground-based measurements, satellite remote sensing (SRS) and air quality model (AQM), together with geographic and local source related spatial inputs, to generate high resolution pollution maps for both PM2.5 and NO2 in Pearl River Delta (PRD), China. Four sets of LUR models (LUR without SRS or AQM, with SRS only, with AQM only, and with both SRS and AQM), all including local traffic emissions and land use variables, were compared to evaluate the contribution of SRS and AQM data to the performance of LUR models in PRD region. For NO2, the annual model with SRS estimate performed best, explaining 60.5% of the spatial variation. For PM2.5, the annual model with traditional predictor variables without SRS or AQM estimates showed the best performance, explaining 88.4% of the spatial variation. Pollution surfaces at 200 m*200 m resolution were generated according to the best performed models.

VOCs emission rate estimate for complicated industrial area source using an inverse-dispersion calculation method: A case study on a petroleum refinery in Northern China.

This study aimed to apply an inverse-dispersion calculation method (IDM) to estimate the emission rate of volatile organic compounds (VOCs) for the complicated industrial area sources, through a case study on a petroleum refinery in Northern China. The IDM was composed of on-site monitoring of ambient VOCs concentrations and meteorological parameters around the source, calculation of the relationship coefficient γ between the source's emission rate and the ambient VOCs concentration by the ISC3 model, and estimation of the actual VOCs emission rate from the source. Targeting the studied refinery, 10 tests and 8 tests were respectively conducted in March and in June of 2014. The monitoring showed large differences in VOCs concentrations between background and downwind receptors, reaching 59.7 ppbv in March and 248.6 ppbv in June, on average. The VOCs increases at receptors mainly consisted of ethane (3.1%-22.6%), propane (3.8%-11.3%), isobutane (8.5%-10.2%), n-butane (9.9%-13.2%), isopentane (6.1%-12.9%), n-pentane (5.1%-9.7%), propylene (6.1-11.1%) and 1-butylene (1.6%-5.4%). The chemical composition of the VOCs increases in this field monitoring was similar to that of VOCs emissions from China's refineries reported, which revealed that the ambient VOCs increases were predominantly contributed by this refinery. So, we used the ISC3 model to create the relationship coefficient γ for each receptor of each test. In result, the monthly VOCs emissions from this refinery were calculated to be 183.5 ± 89.0 ton in March and 538.3 ± 281.0 ton in June. The estimate in June was greatly higher than in March, chiefly because the higher environmental temperature in summer produced more VOCs emissions from evaporation and fugitive process of the refinery. Finally, the VOCs emission factors (g VOCs/kg crude oil refined) of 0.73 ± 0.34 (in March) and 2.15 ± 1.12 (in June) were deduced for this refinery, being in the same order with previous direct-measurement results (1.08-2.65 g VOCs/kg crude oil refined). An inverse-dispersion calculation method was applied to estimate VOCs emission rate for a petroleum refinery, being 183.5 ton/month (March) and 538.3 ton/month (June).

Characterizing ozone pollution in a petrochemical industrial area in Beijing, China: a case study using a chemical reaction model.

This study selected a petrochemical industrial complex in Beijing, China, to understand the characteristics of surface ozone (O3) in this industrial area through the on-site measurement campaign during the July-August of 2010 and 2011, and to reveal the response of local O3 to its precursors' emissions through the NCAR-Master Mechanism model (NCAR-MM) simulation. Measurement results showed that the O3 concentration in this industrial area was significantly higher, with the mean daily average of 124.6 µg/m(3) and mean daily maximum of 236.8 µg/m(3), which are, respectively, 90.9 and 50.6 % higher than those in Beijing urban area. Moreover, the diurnal O3 peak generally started up early in 11:00-12:00 and usually remained for 5-6 h, greatly different with the normal diurnal pattern of urban O3. Then, we used NCAR-MM to simulate the average diurnal variation of photochemical O3 in sunny days of August 2010 in both industrial and urban areas. A good agreement in O3 diurnal variation pattern and in O3 relative level was obtained for both areas. For example of O3 daily maximum, the calculated value in the industrial area was about 51 % higher than in the urban area, while measured value in the industrial area was approximately 60 % higher than in the urban area. Finally, the sensitivity analysis of photochemical O3 to its precursors was conducted based on a set of VOCs/NOx emissions cases. Simulation results implied that in the industrial area, the response of O3 to VOCs was negative and to NOx was positive under the current conditions, with the sensitivity coefficients of -0.16~-0.43 and +0.04~+0.06, respectively. By contrast, the urban area was within the VOCs-limitation regime, where ozone enhancement in response to increasing VOCs emissions and to decreasing NOx emission. So, we think that the VOCs emissions control for this petrochemical industrial complex will increase the potential risk of local ozone pollution aggravation, but will be helpful to inhibit the ozone formation in Beijing urban area through reducing the VOCs transport from the industrial area to the urban area.