Temporal-spatial distributions of road silt loadings and fugitive road dust emissions in Beijing from 2019 to 2020.

Road silt loading (sL) is an important parameter in the fugitive road dust (FRD) emissions. In this study, the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) combined with the AP-42 method was firstly developed to quickly measure and estimate the sLs of paved roads in Beijing, China. The annual average sLs in Beijing was 0.59±0.31 g/m2 in 2020, and decreased by 22.4% compared with that in 2019. The seasonal variations of sLs followed the order of spring > winter > summer > autumn in the two years. The seasonal mean road sLs on the same type road in the four seasons presented a decline trend from 2019 to 2020, especially on the Express way, decreasing 47.4%-72.7%. The road sLs on the different type roads in the same season followed the order of Major arterial ∼ Minor arterial ∼ Branch road > Express road, and Township road ∼ Country highway > Provincial highway ∼ National highway. The emission intensities of PM10 and PM2.5 from FRD in Beijing in 2020 were lower than those in 2019. The PM10 and PM2.5 emission intensities at the four planning areas in the two years all presented the order of the capital functional core area > the urban functional expansion area > the urban development new area > the ecological conservation and development area. The annual emissions of PM10 and PM2.5 from FRD in Beijing in 2020 were 74,886 ton and 18,118 ton, respectively, decreasing by ∼33.3% compared with those in 2019.

Air pollutant emissions from the asphalt industry in Beijing, China.

Improving our understanding of air pollutant emissions from the asphalt industry is critical for the development and implementation of pollution control policies. In this study, the spatial distribution of potential maximum emissions of volatile organic compounds (VOCs) in the complete life cycle of asphalt mixtures, as well as the particulate matter (PM), asphalt fume, nonmethane hydrocarbons (NMHCs), VOCs, and benzoapyrene (BaP) emissions from typical processes (e.g., asphalt and concrete mixing stations, asphalt heating boilers, and asphalt storage tanks) in asphalt mixing plants, were determined in Beijing in 2017. The results indicated that the potential maximum emissions of VOCs in the complete life cycle of asphalt mixtures were 18,001 ton, with a large contribution from the districts of Daxing, Changping, and Tongzhou. The total emissions of PM, asphalt fume, NMHC, VOCs, and BaP from asphalt mixing plants were 3.1, 12.6, 3.1, 23.5, and 1.9 × 10-3 ton, respectively. The emissions of PM from asphalt and concrete mixing stations contributed the most to the total emissions. The asphalt storage tank was the dominant emission source of VOCs, accounting for 96.1% of the total VOCs emissions in asphalt mixing plants, followed by asphalt heating boilers. The districts of Daxing, Changping, and Shunyi were the dominant regions for the emissions of PM, asphalt fume, NMHC, and BaP, while the districts of Shunyi, Tongzhou, and Changping contributed the most emissions of VOCs.

A new approach to developing a fugitive road dust emission inventory and emission trend from 2006 to 2010 in the beijing metropolitan area, china.

The USEPA emission factor (AP-42) of fugitive road dust (FRD) is widely used in establishing emission inventories. However, road silt loading sampling for AP-42 is expensive, time consuming, and dangerous. Therefore, a new method for establishing emission inventories based on road dust-fall (DF) monitors is described. Between January 2006 and December 2010, DF was monitored at 40 sites (80 samples), and background dust fall (DF) was monitored at 14 sites in the Beijing metropolitan area. Also during this period, 58 samples of road silt loadings were taken and used in the AP-42 emission factor equation to calculate FRD with particulate matter ≤10 µm in diameter [FRD(PM)] emission from the roads. Simultaneous measurement of FRD(PM) emissions calculated by AP-42 and ΔDF (i.e., the difference between the DF and DF) measured using gauges showed that the FRD(PM) emission for road dust was proportional to the ΔDF ( = 0.92). The FRD(PM) emission (kg km × 30 d) was calculated using the monitored ΔDF (t km × 30 d) by the formulation FRD(PM) = 278.3 × ΔDF - 1151.2. The ΔDF showed a general decline from 2006 to 2010. In particular, there was a sharp decline in August, September, and October 2008 due to strict dust controls enforced during the 2008 Olympic Games. Although there was a small increase in ΔDF after the Games, by the end of 2010 values were still lower than those before the Games. Using the 2006 ΔDF value as a benchmark, ΔDF values declined by 24.7, 33.0, 38.3, and 31.4% in 2007, 2008, 2009, and 2010, respectively. Based on using AP-42 calculations from silt loading and traffic information in 2007, the FRD(PM) emission distribution in the Beijing metropolitan area was mapped, and there were 2.05 × 10 tons of FRD(PM) emitted in 2007. The FRD(PM) from 2006 to 2010 was calculated by the ΔDF values.

[Emission Factors and Emission Inventory of Agricultural Machinery in Beijing Under Real-world Operation].

This study aimed to establish the emission factors and the emission inventory of agricultural machinery in Beijing in 2017 under real-world operation. The emissions of typical harvesters, tractors, agricultural transport vehicles, and farm construction machinery under real-world operation were tested by a portable emission measurement system. The results showed that different operation modes have a greater impact on the tailpipe emissions of agricultural machinery. The CO, NOx, HC, and PM emissions were relatively stable when the engine is idling and moving compared to when the excavator is performing actual work. According to the classification and emission standards of various types of machinery, a relatively perfect emission factor system of agricultural machinery in Beijing was established, which can provide reference and support for relevant research and management decisions. According to the emission factors of agricultural machinery and fuel consumption in Beijing, the emissions of CO, NOx, HC, and PM in 2017 were 2566.60, 1239.29, 563.08, and 538.32 t, respectively. The total pollutants of transport machinery, tractors, and combined harvester accounted for 98%, 95%, 95%, and 98% of the total concentrations of CO, NOx, HC, and PM, respectively. Therefore, transport machinery, tractor, and combined harvester should be the key control objects in the reduction of agricultural machinery pollution.

[Methods and Application of Road Fugitive Dust Emission Factor Localization].

Size distribution and emission factors are the basic information used in emission characteristic studies and emission inventory establishment. The silt loadings of typical roads in the Tongzhou district of Beijing were sampled and tested. A particulate matter resuspension and measurement system and a particle size spectrometer were used to measure the size distribution and particle size multiplier of the fugitive road dust in this study. The localized PM2.5 emission factors for the fugitive road dust were obtained by experiment and investigation. The results showed that the ratio of the particles with sizes from 0 µm to 2.5 µm was similar for different road types; the ratio of PM2.5 to PM10 in the fugitive road dust was between 0.28 and 0.32. The particle size multiplier of PM2.5 was between 0.18-0.20 g·(km·vehicle)-1 for the different types of roads. The PM2.5 emission factors for highways, national roads, provincial roads, county roads, and township roads were 0.06, 0.14, 0.31, 0.30, and 0.39 g·(km·vehicle)-1, respectively. The silt loadings of different type roads showed great differences; thus, field sampling of the silt loading is necessary in the emission factor localization process.

[Methods for Determining and Applications of High-Resolution Vehicle Emission Inventory at County Scale].

This study proposes a method for high-resolution vehicle emission inventories at county scale based on field investigations and Google Earth satellite images, using the Tongzhou district of Beijing as an example for data analysis. VKT and the corresponding emissions of each pollutant were calculated using the number of registered vehicles and the real-time traffic volumes, respectively. The results showed that the mileage calculated based on the method using registered vehicles is about 37% less than that based on real-time traffic volumes, with the latter method providing data closer to the actual situation. The mileage for small passenger cars, large passenger vehicles, and medium-duty trucks were underestimated, and that for light trucks, heavy trucks, low-speed trucks were overestimated based on the registered vehicle method. Emissions from small passenger cars were also underestimated by about 51%, using the registered vehicle method. For emissions of large passenger vehicles, light trucks, and medium-duty trucks, there was less difference between the two methods. Based on the registered vehicle method, emissions of heavy trucks, low-speed trucks, and motorcycles were overestimated by about 41%, 30%, and 30%, respectively.

[Motor Vehicle Pollution Control Scenarios of Beijing Subsidiary Administrative Center Based on Road Traffic Flow].

In this study, the scenario analysis method was used to establish motor vehicle exhaust emission inventories based on road-traffic-flow information of the Beijing subsidiary administrative center under different scenarios, with a base year of 2015. The pollutant emissions in 2020 and 2025 were forecast by calculating the motor vehicle pollutant emission inventories of future road-traffic-flow information and various scenarios. The results showed that the kilometers travelled via motor vehicles and the road network density of the Beijing subsidiary administrative center both will increase continuously over the next 10 years. Compared with the baseline scenario, each control scenario had a certain degree of reduction in pollutant emissions, and the reduction rates increased with the strengthening of the measures. The emission reductions of pollutants were significant in the new energy vehicle promotion scenario, especially for NOx and PM. The effect of emission reduction of every pollutant was significant in the outgoing vehicle restriction scenario. Elimination of highly polluting vehicles had a significant effect in the short term, but the effect of long-term reduction was weak. The combined scenario achieved the best reduction rate of pollutant emissions, with CO, NOx, HC, and PM decreasing by 39.0%, 58.7%, 49.2%, and 55.5%, respectively.

[Evaluation on the Effectiveness of Vehicle Exhaust Emission Control Measures During the APEC Conference in Beijing].

Vehicle emission is one of the primary factors affecting the quality of atmospheric environment in Beijing. In order to improve the air quality during APEC conference, strict control measures including vehicle emission control were taken in Beijing during APEC meeting. Based on the activity level data of traffic volume, vehicle speed and vehicle types, the inventory of motor vehicle emissions in Beijing was developed following bottom-up methodology to assess the effectiveness of the control measures. The results showed that the traffic volume of Beijing road network during the APEC meeting decreased significantly, the vehicle speed increased obviously, and the largest decline of traffic volume was car. CO, NOx, HC and PM emissions of vehicle exhaust were reduced by 15.1%, 22.4%, 18.4% and 21.8% for freeways, 29.9%, 36.4%, 32.7% and 35.8% for major arterial, 35.7%, 41.7%, 38.4% and 41.2% for minor arterial, 40.8%, 46.5%, 43.1% and 46.0% for collectors, respectively. The vehicles exhaust emissions inventory before and during APEC conference was developed based on bottom-up emissions inventory method. The results indicated that CO, NOx, HC and PM emissions of vehicle exhaust were reduced by 37.5%, 43.4%, 39.9% and 42.9% in the study area, respectively.

[Emission Characteristics of Vehicle Exhaust in Beijing Based on Actual Traffic Flow Information].

The basic data of traffic volume, vehicle type constitute and speed on road networks in Beijing was obtained fly modei simulation and field survey. Based on actual traffic flow information and. emission factors data with temporal and spatial distribution features, emission inventory of motor vehicle exhaust in Beijing was built on the ArcGIS platform, meanwhile, the actual road emission characteristics and spatial distribution of the pollutant emissions were analyzed. The results showed that the proportion of passenger car was higher than 89% on each type of road in the urban, and the proportion of passenger car was the highest in suburban roads as well while the pickup truck, medium truck, heavy truck, motorbus, tractor and motorcycle also occupied a certain proportion. There was a positive correlation between the pollutant emission intensity and traffic volume, and the emission intensity was generally higher in daytime than nighttime, but the diurnal variation trend of PM emission was not clear for suburban roads and the emission intensity was higher in nighttime than daytime for highway. The emission intensities in urban area, south, southeast and northeast areas near urban were higher than those in the western and northern mountainous areas with lower density of road network. The ring roads in urban and highways in suburban had higher emission intensity because of the heavy traffic volume.

[Emission Factors of Vehicle Exhaust in Beijing].

Based on the investigation of basic data such as vehicle type composition, driving conditions, ambient temperature and oil quality, etc., emission factors of vehicle exhaust pollutants including carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC) and particulate matter(PM) were calculated using COPERT IV model. Emission factors of typical gasoline passenger cars and diesel trucks were measured using on-board measurement system on actual road. The measured and modeled emission factors were compared and the results showed that: the measured emission factors of CO, NOx and HC were 0. 96, 0. 64 and 4. 89 times of the modeled data for passenger cars conforming to the national IV emission standard. For the light, medium and heavy diesel trucks conforming to the national III emission standard, the measured data of CO emission factors were 1.61, 1. 07 and 1.76 times of the modeled data, respectively, the measured data of NOx emission factors were 1. 04, 1. 21 and 1. 18 times of the modeled data, and the measured data of HC emission factors were 3. 75, 1. 84 and 1. 47 times of the modeled data, while the model data of PM emission factors were 1. 31, 3. 42 and 6. 42 times of the measured data, respectively.

[Influence of traffic restriction on road and construction fugitive dust].

By monitoring the road and construction dust fall continuously during the "Good Luck Beijing" sport events, the reduction of road and construction dust fall caused by traffic restriction was studied. The contribution rate of road and construction dust to particulate matter of Beijing atmosphere environment, and the emission ratio of it to total local PM10 emission were analyzed. The results show that the traffic restriction reduces road and construction dust fall significantly. The dust fall average value of ring roads was 0.27 g x (m2 x d)(-1) in the "traffic restriction" period, and the values were 0.81 and 0.59 g x (m2 x d)(-1) 1 month and 7 days before. The dust fall average value of major arterial and minor arterial was 0.21 g x (m2 x d)(-1) in the "traffic restriction" period, and the values were 0.54 and 0.58 g x (m2 x d)(-1) 1 month and 7 days before. The roads emission reduced 60%-70% compared with before traffic restriction. The dust fall average values of civil architecture and utility architecture were 0.61 and 1.06 g x (m2 x d)(-1) in the "traffic restriction" period, and the values were 1.15 and 1.55 g x (m2 x d)(-1) 20 days before. The construction dust reduced 30%-47% compared with 20 days before traffic restriction. Road and construction dust emission are the main source of atmosphere particulate matter in Beijing, and its contribution to ambient PM10 concentration is 21%-36%. PM10 emitted from roads and constructions account for 42%-72% and 30%-51% of local emission while the local PM10 account for 50% and 70% of the total emission.

[Relationship between wind velocity and PM10 concentration & emission flux of fugitive dust source].

In the emission factor models of man-made fugitive dust, the wind velocity parameter has little been accounted for. PM10 concentration and wind velocity were measured near a unpaved road and in a construction site. PM10 emission flux was calculated using the measured data. The relationship between PM10 concentration and emission flux and wind velocity was studied. The results show that the PM10 concentration is high in the condition of static and slight wind. PM10 concentration descend with the wind velocity increased, and the concentration reaches to the minimum value when the wind velocity reach to 1.0-2.0 m/s, then with the wind velocity increasing (> 1.0-2.0 m/s), the PM10 concentration increases quickly. The emission flux increased with the wind velocity increasing, and the speed increasement become more after the wind velocity was faster than 2.0 m/s. The man-made fugitive dust was divided into mechanism operation and wind erosion dust to research the emission mechanism. The results based on theory analysis and the measured data are consistent.

[Characteristics of fugitive dust emission from paved road near construction activities].

Because of the mud/dirt carryout from construction activities, the silt loading of paved road nearby is higher and the fugitive dust emission is stronger. By sampling and laboratory analysis of the road surface dust samples, we obtain the silt loading (mass of material equal to or less than 75 micromaters in physical diameter per unit area of travel surface) of paved roads near construction activities. The result show that silt loading of road near construction activities is higher than "normal road", and silt loading is negatively correlated with length from construction's door. According to AP-42 emission factor model of fugitive dust from roads, the emission factor of influenced road is 2 - 10 times bigger than "normal road", and the amount of fugitive dust emission influenced by one construction activity is "equivalent" to an additional road length of approximately 422 - 3 800 m with the baseline silt loading. Based on the spatial and temporal distribution of construction activities, in 2002 the amount of PM10 emission influenced by construction activities in Beijing city areas account of for 59% of fugitive dust from roads.

[Emission characteristics of paved roads fugitive dust in Beijing].

Based on sampling and laboratory analyzing silt loading of 82 city roads and 56 suburb paved roads in Beijing, we using AP-42 emission factor model studied emission characteristics of paved road fugitive dust, and analyzed two methods to determine silt loading of different roads. The results show that silt loading of expressway, major arterial, minor arterial and collectors in city areas is 0.17, 0.34, 1.48, 2.60 g/m2 respectively, and silt loading of national road, province road, county road, village road and municipal road in the suburbs areas is 0.18, 0.56, 1.58, 3.10, 1.58 g/m2 respectively. In the city areas, using the relationship of silt loading and traffic volume,and in the suburbs areas, using the average value of different type roads to determine the silt loading are better. Silt loading and emission factor are negatively correlated with traffic volume, but the emission strength is increased with the increase of traffic volume. Emission strength of different type roads was also studied. In the city areas, emission strength of major arterial is strongest and the value is 130.2 kg/(km x d), and in the suburbs areas, emission strength of national road is strongest and the value is 43.8 kg/(km x d).