Nonlinear response of nitrate to NOx reduction in China during the COVID-19 pandemic

Nonlinear effect of NOx concentration decrease on secondary aerosol formation in the Beijing-Tianjin-Hebei region: Evidence from smog chamber experiments and field observations

During the COVID-19 lockdown in the Beijing-Tianjin-Hebei (BTH) region in China, large decrease in nitrogen oxides (NOx) emissions, especially in the transportation sector, could not avoid the occurrence of heavy PM2.5 pollution where nitrate dominated the PM2.5 mass increase. To experimentally reveal the effect of NOx control on the formation of PM2.5 secondary components (nitrate in particular), photochemical simulation experiments of mixed volatile organic compounds (VOCs) under various NOx concentrations with smog chamber were performed. The proportions of gaseous precursors in the control experiment were comparable to ambient conditions typically observed in the BTH region. Under relatively constant VOCs concentrations, when the initial NOx concentration was reduced to 40% of that in the control experiment (labelled as NOx,0), the particle mass concentration was not significantly reduced, but when the initial NOx concentration decreased to 20 % of NOx,0, the mass concentration of particles as well as nitrate and organics showed a sudden decrease. A "critical point" where the mass concentration of secondary aerosol started to decline as the initial NOx concentration decreased, located at 0.2-0.4 NOx,0 (or 0.18-0.44 NO2,0) in smog chamber experiments. The oxidation capacity and solar radiation intensity played key roles in the mass concentration and compositions of the formed particles. In field observations in the BTH region in the autumn and winter seasons, the "critical point" exist at 0.15-0.34 NO2,0, which coincided mostly with the laboratory simulation results. Our results suggest that a reduction of NOx emission by >60% could lead to significant reductions of secondary aerosol formation, which can be an effective way to further alleviate PM2.5 pollution in the BTH region.

The significant contribution of nitrate to a severe haze event in the winter of Guangzhou, China

A severe haze pollution occurred in Guangzhou from January 14 to 16, 2021, during which the mass concentration of PM2.5 ranged from 76 to 243 μg m-3. This level of pollution was rarely observed in recent years considering the improved air quality in Guangzhou. Therefore, it is crucial to comprehensively study the formation mechanisms of this severe haze pollution to prevent its reoccurrence. During the haze period, the concentrations of NO and NO2 sharply increased by 7.4 and 3.8 times, respectively, and total volatile organic compounds (TVOCs) increased 7 times, suggesting enhanced primary emissions from vehicles due to stagnant meteorological conditions. Nitrate concentration (43 ± 20 μg m-3) increased 6.7 times and became the dominant species in PM2.5 during the haze period. Notably, gaseous NH3, HONO and HNO3 also exhibited a sharp increase, suggesting the important role of nitrate chemistry in the evolution of haze pollution. The simulation results from chemical box model revealed that the OH + NO2 reaction was the dominant formation pathway for nitrate production (82 %) during the haze period. The net production rate of ROx radicals (including OH, HO2 and RO2) was 4.4 times higher during the haze period (5.8 ppb h-1) compared to the pre-haze period (1.3 ppb h-1). This was mainly attributed to the enhanced HONO and OVOCs photolysis, which increased from 0.6 ppb h-1 to 3.1 ppb h-1 and 0.4 ppb h-1 to 2.1 ppb h-1, respectively. Furthermore, the sensitivity tests demonstrated the reductions in VOCs and NOx were both beneficial for controlling nitrate production by influencing OH production and N2O5 uptake rate. These findings provide insights into the formation mechanisms of nitrate production during severe haze pollution and suggest that joint mitigation of PM2.5 and O3 can be achieved through the control of VOCs emission.

Revisiting the dynamics of gaseous ammonia and ammonium aerosols during the COVID-19 lockdown in urban Beijing using machine learning models

The concentration of atmospheric ammonia (NH3) in urban Beijing substantially decreased during the COVID-19 lockdown (24 January to 3 March 2020), likely due to the reduced human activities. However, quantifying the impact of anthropogenic interventions on NH3 dynamics is challenging, as both meteorology and chemistry mask the real changes in observed NH3 concentrations. Here, we applied machine learning techniques based on random forest models to decouple the impacts of meteorology and emission changes on the gaseous NH3 and ammonium aerosol (NH4+) concentrations in Beijing during the lockdown. Our results showed that the meteorological conditions were unfavorable during the lockdown and tended to cause an increase of 8.4 % in the NH3 concentration. In addition, significant reductions in NOx and SO2 emissions could also elevate NH3 concentrations by favoring NH3 gas-phase partitioning. However, the observed NH3 concentration significantly decreased by 35.9 % during the lockdown, indicating a significant reduction in emissions or enhanced chemical sinks. Rapid gas-to-particle conversion was indeed found during the lockdown. Thus, the observed reduced NH3 concentrations could be partially explained by the enhanced transformation into NH4+. Therefore, the sum of NH3 and NH4+ (collectively, NHx) is a more reliable tracer than NH3 or NH4+ alone to estimate the changes in NH3 emissions. Compared to that under the scenario without lockdowns, the NHx concentration decreased by 26.4 %. We considered that this decrease represents the real decrease in NH3 emissions in Beijing due to the lockdown measures, which was less of a decrease than that based on NH3 only (35.9 %). This study highlights the importance of considering chemical sinks in the atmosphere when applying machine learning techniques to link the concentrations of reactive species with their emissions.

Establishing an emission inventory for ammonia, a key driver of haze formation in the southern North China plain during the COVID-19 pandemic

Despite the significant reduction in atmospheric pollutant levels during the COVID-19 lockdown, the presence of haze in the North China Plain remained a frequent occurrence owing to the enhanced formation of secondary inorganic aerosols under ammonia-rich conditions. Quantifying the increase or decrease in atmospheric ammonia (NH3) emissions is a key step in exploring the causes of the COVID-19 haze. Historic activity levels of anthropogenic NH3 emissions were collected through various yearbooks and studies, an anthropogenic NH3 emission inventory for Henan Province for 2020 was established, and the variations in NH3 emissions from different sources between COVID-19 and non-COVID-19 years were investigated. The validity of the NH3 emission inventory was further evaluated through comparison with previous studies and uncertainty analysis from Monte Carlo simulations. Results showed that the total NH3 emissions gradually increased from north-west to south-east, totalling 751.80 kt in 2020. Compared to the non-COVID-19 year of 2019, the total NH3 emissions were reduced by approximately 4 %, with traffic sources, waste disposal and biomass burning serving as the sources with the top three largest reductions, approximately 33 %, 9.97 % and 6.19 %, respectively. Emissions from humans and fuel combustion slightly increased. Meanwhile, livestock waste emissions decreased by only 3.72 %, and other agricultural emissions experienced insignificant change. Non-agricultural sources were more severely influenced by the COVID-19 lockdown than agricultural sources; nevertheless, agricultural activities contributed 84.35 % of the total NH3 emissions in 2020. These results show that haze treatment should be focused on reducing NH3, particularly controlling agricultural NH3 emissions.

The worldwide COVID-19 lockdown impacts on global secondary inorganic aerosols and radiative budget

Global lockdown measures to prevent the spread of the coronavirus disease 2019 (COVID-19) led to air pollutant emission reductions. While the COVID-19 lockdown impacts on both trace gas and total particulate pollutants have been widely investigated, secondary aerosol formation from trace gases remains unclear. To that end, we quantify the COVID-19 lockdown impacts on NOx and SO2 emissions and sulfate-nitrate-ammonium aerosols using multiconstituent satellite data assimilation and model simulations. We find that anthropogenic emissions over major polluted regions were reduced by 19 to 25% for NOx and 14 to 20% for SO2 during April 2020. These emission reductions led to 8 to 21% decreases in sulfate and nitrate aerosols over highly polluted areas, corresponding to >34% of the observed aerosol optical depth declines and a global aerosol radiative forcing of +0.14 watts per square meter relative to business-as-usual scenario. These results point to the critical importance of secondary aerosol pollutants in quantifying climate impacts of future mitigation measures.

Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the "Air Pollution Complex"

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the "air pollution complex" was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades.

Impact of primary emission variations on secondary inorganic aerosol formation: Prospective from COVID-19 lockdown in a typical northern China city

Hourly observations in northern China city of Taiyuan were performed to compare secondary inorganic aerosol (SIA) reaction mechanisms, and emission effects on SIA during the pre-lock and COVID-19 lock days. Emission control implemented and meteorological conditions during lock days both caused beneficial impact on air quality. NO₂ showed the highest decrease ratio of -49.5%, while the relative fraction of NO₃^- in PM_2.5 increased the most (2.7%). Source apportionment revealed the top three contributors to PM_2.5 were secondary formation (SF), coal combustion (CC), and vehicle exhaust (VE) during both pre-lock and lock days. EC _lock/pre were all lower than 1, suggesting the overall reduction of primary emissions during lock days, while the higher ratio of (SIA/EC) _lock/pre (1.01-1.36) indicated the enhanced secondary formation in lock days. The ratio of SIA of pollution to clean days during lock periods considerably higher by 23.7% compared with that in pre-lock periods, which was indicated SIA secondary formation was more pronounced and contributed great to pollution days in lock periods though secondary formation existed in pre-lock and lock periods. Enhanced secondary formation of NO₃^- and SO₄^2- during lock days might be mainly due to the increased in aqueous and gas-phase reactions, respectively. Except for SF, high contribution of VE and CC were also important for high SIA concentration in pre-lock and lock days, respectively. The decreased contribution of VE weakens its contribution to SIA formation, indicating the effectiveness of VE emission control, as confirmed during the COVID-19 pandemic. This study highlights the aqueous and gas-phase reactions for nitrate and sulfate, respectively, which contributed to heavy pollution, as well as indicated the important role of VE on SIA formation, suggesting the urgent need to further strengthen controls on vehicle emissions.

Exploring the driving factors of haze events in Beijing during Chinese New Year holidays in 2020 and 2021 under the influence of COVID-19 pandemic

Unexpected outbreak of the 2019 novel coronavirus (COVID-19) has profoundly altered the way of human life and production activity, which posed visible impacts on PM_2.5 and its chemical species. The abruptly emergency reduction in human activities provided an opportunity to explore the synergetic impacts of multi-factors on shaping PM_2.5 pollution. Here, we conducted two comprehensive observation measurements of PM_2.5 and its chemical species from 1 January to 16 February in Beijing 2020 and the same lunar date in 2021, to investigate temporal variations and reveal the driving factors of haze before and after Chinese New Year (CNY). Results show that mean PM_2.5 concentrations during the whole observation were 63.83 and 66.86 μg/m³ in 2020 and 2021, respectively. Higher secondary inorganic species were observed after CNY, and K⁺, Cl^- showed three prominent peaks which associated closely with fireworks burnings from suburb Beijing and surroundings, verifying that they could be used as two representative tracers of fireworks. Further, we explored the impacts of meteorological conditions, regional transportation as well as chemical reactions on PM_2.5. We found that unfavorable meteorological conditions accounted for 11.0 % and 16.9 % of PM_2.5 during CNY holidays in 2020 and 2021, respectively. Regional transport from southwest and southeast (south) played an important role on PM_2.5 during the two observation periods. Higher ratio of NO₃^-/SO₄^2- were observed under high O_X and low RH conditions, suggesting the major pathway of NO₃^- and SO₄^2- formation could be photochemical process and aqueous-phase reaction. Additionally, nocturnal chemistry facilitated the formation of secondary components of both inorganic and organic. This study promotes understandings of PM_2.5 pollution in winter under the influence of COVID-19 pandemic and provides a well reference for haze and PM_2.5 control in future.

Responses of sulfate and nitrate to anthropogenic emission changes in eastern China - in perspective of long-term variations

We investigate responses of sulfate (SO₄^2-) and nitrate (NO₃^-) to anthropogenic emission changes in 2006-2017 by fixing meteorology at the 2009 level using nested 3D chemical transport model GEOS-Chem. We find that sulfate concentration decreases following SO₂ emissions, but with a relatively smaller reduction rate (by 16 % in North China Plain (NCP) and 28 % in Yangtze River Delta (YRD)) due to larger sulfur oxidation ratio (SOR) at lower SO₂ level. SOR follows a power law with SO₂ emissions in general except in winter in NCP, when and where both SO₂ emission reduction and atmospheric oxidation capacity are critical to the inter-annual variations of SOR. Nitrate concentration ([pNO₃^-]) decreases along with NOx emission reduction in summer, but increases slightly in winter in 2011-2017. Equilibrium with gas phase HNO₃, NO₃^- in particle phase (pNO₃^-) is determined by total HNO₃ (TN = [pNO₃^-] + [gHNO₃]) oxidized from NO₂ and gas-particle partitioning (ε(NO₃^-) = [pNO₃^-]/TN). TN is decreasing faster in summer (~33 %) than in winter (~25 %) in 2011-2017. In contrast, ε(NO₃^-) changes marginally in summer (within 5 %) but increases by 36 % in NCP and by 51 % in YRD in winter in 2006-2017. The increasing of ε(NO₃^-) in winter is attributed to the strong reduction of [pSO₄^2-], which increases the relative abundance of NH₃ and thus favors partitioning of NO₃^- to the particle phase. The effect of increasing ε(NO₃^-) overcomes that of decreasing TN in winter. We suggest reduce SO₂ emissions to further reduce [pSO₄^2-] in eastern China. In addition, we recommend reduce NOx emissions in summer, and reduce atmospheric oxidation capacity and relative abundance of NH₃ in winter to reduce [pNO₃^-].

Synergetic PM2.5 and O3 control strategy for the Yangtze River Delta, China

PM_2.5 concentrations have dramatically reduced in key regions of China during the period 2013-2017, while O₃ has increased. Hence there is an urgent demand to develop a synergetic regional PM_2.5 and O₃ control strategy. This study develops an emission-to-concentration response surface model and proposes a synergetic pathway for PM_2.5 and O₃ control in the Yangtze River Delta (YRD) based on the framework of the Air Benefit and Cost and Attainment Assessment System (ABaCAS). Results suggest that the regional emissions of NOx, SO₂, NH₃, VOCs (volatile organic compounds) and primary PM_2.5 should be reduced by 18%, 23%, 14%, 17% and 33% compared with 2017 to achieve 25% and 5% decreases of PM_2.5 and O₃ in 2025, and that the emission reduction ratios will need to be 50%, 26%, 28%, 28% and 55% to attain the National Ambient Air Quality Standard. To effectively reduce the O₃ pollution in the central and eastern YRD, VOCs controls need to be strengthened to reduce O₃ by 5%, and then NOx reduction should be accelerated for air quality attainment. Meanwhile, control of primary PM_2.5 emissions shall be prioritized to address the severe PM_2.5 pollution in the northern YRD. For most cities in the YRD, the VOCs emission reduction ratio should be higher than that for NOx in Spring and Autumn. NOx control should be increased in summer rather than winter when a strong VOC-limited regime occurs. Besides, regarding the emission control of industrial processes, on-road vehicle and residential sources shall be prioritized and the joint control area should be enlarged to include Shandong, Jiangxi and Hubei Province for effective O₃ control.

Effect of restricted emissions during COVID-19 on atmospheric aerosol chemistry in a Greater Cairo suburb: Characterization and enhancement of secondary inorganic aerosol production

To prevent the rapid spreading of the COVID-19 pandemic, the Egyptian government had imposed partial lockdown restrictions which led emissions reduction. This served as ideal conditions for a natural experiment, for study the effect of partial lockdown on the atmospheric aerosol chemistry and the enhanced secondary inorganic aerosol production in a semi-desert climate area like Egypt. To achieve this objective, SO₂, NO₂, and PM_2.5 and their chemical compositions were measured during the pre-COVID, COVID partial lockdown, and post-COVID periods in 2020 in a suburb of Greater Cairo, Egypt. Our results show that the SO₂, NO₂, PM_2.5 and anthropogenic elements concentrations follow the pattern pre-COVID > post-COVID > COVID partial lockdown. SO₂ and NO₂ reductions were high compared with their secondary products during the COVID partial lockdown compared with pre-COVID. Although, PM_2.5, anthropogenic elements, NO₂, SO₂, SO₄ ^2-, NO₃ ^-, and NH₄ ⁺ decreased by 39%, 38-55%, 38%, 32.9%. 9%, 14%, and 4.3%, respectively, during the COVID partial lockdown compared with pre-COVID, with the secondary inorganic ions (SO₄ ^2-, NO₃ ^-, and NH₄ ⁺) being the dominant components in PM_2.5 during the COVID partial lockdown. Moreover, the enhancement of NO₃ ^- and SO₄ ^2- formation during the COVID partial lockdown was high compared with pre-COVID. SO₄ ^2- and NO₃ ^- formation enhancements were significantly positive correlated with PM_2.5 concentration. Chemical forms of SO₄ ^2- and NO₃ ^- were identified in PM_2.5 based on their NH₄ ⁺/SO₄ ^2- molar ratio and correlation between NH₄ ⁺ and both NO₃ ^- and SO₄ ^2-. The particles during the COVID partial lockdown were more acidic than those in pre-COVID.

Responses of nitrogen and sulfur deposition to NH3 emission control in the Yangtze River Delta, China

NH₃ emission control has proven to be of great importance in reducing PM_2.5 concentrations in China, while how it affects nitrogen/sulfur (N/S) deposition is still unclear. This study expanded the response surface model method to quantify the responses of N/S deposition to the emission control of precursors (NO_x, SO₂, NH₃, VOCs and primary PM_2.5) in the Yangtze River Delta, China. NH₃ control was found to have higher efficiency in reducing N/S deposition than NO_x and SO₂ alone. The reduced N deposition response to NH₃ emission control was higher in the northern part of the YRD region, whereas oxidized N deposition decreased sharply in the region with a low N critical load. Synergetic effect was found in reducing N deposition when we controlled the NH₃ and NO_x emissions simultaneously. Compared with the sum effect of individual NH₃ and NO_x emission control, the extra benefits from the synergy controls accounted for 4.4% (1.23 kg N·ha^-1·yr^-1) of the total N deposition, of which 81% came from the oxidized N deposition. The YRD region could receive the largest synergetic effect with a 1:1 ratio of NO_x:NH₃ emission reduction. The NH₃ emission control increases the dry deposition of acid substances and worsens acid rain though it reduces the wet S/oxidized N deposition. These findings highlight the effectiveness of NH₃ emission control and suggest a multi-pollutant control strategy for reducing N/S deposition. The response surface model method for deposition also provides a reference for other regions in China and other countries.

Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India

The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM_2.5 concentrations and an enhancement in the O₃ concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O₃ formation, comprising 89.4%, 83.1%, and 88.9% of the O₃ sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O₃ concentrations at the surface layer. Compared with the Pre1 period, the O₃ enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O₃ removal rate by horizontal transport. During the Tri period, a slower consumption of O₃ by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O₃. Emission and aerosol processes constituted the major positive contributions to the net surface PM_2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM_2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM_2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM_2.5 production from emission and aerosol processes. The increased vertical transport rate of PM_2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM_2.5 during the Lock periods.

Spatiotemporal neural network for estimating surface NO2 concentrations over north China and their human health impact

Atmospheric nitrogen dioxide (NO₂) is an important reactive gas pollutant harmful to human health. The spatiotemporal coverage provided by traditional NO₂ monitoring methods is insufficient, especially in the suburban and rural areas of north China, which have a high population density and experience severe air pollution. In this study, we implemented a spatiotemporal neural network (STNN) model to estimate surface NO₂ from multiple sources of information, which included satellite and in situ measurements as well as meteorological and geographical data. The STNN predicted NO₂ with high accuracy, with a coefficient of determination (R²) of 0.89 and a root mean squared error of 5.8 μg/m³ for sample-based 10-fold cross-validation. Based on the surface NO₂ concentration determined by the STNN, we analyzed the spatial distribution and temporal trends of NO₂ pollution in north China. We found substantial drops in surface NO₂ concentrations ranging between 9.1% and 33.2% for large cities during the 2020 COVID-19 lockdown when compared to those in 2019. Moreover, we estimated the all-cause deaths attributed to NO₂ exposure at a high spatial resolution of about 1 km, with totals of 6082, 4200, and 18,210 for Beijing, Tianjin, and Hebei Provinces in 2020, respectively. We observed remarkable regional differences in the health impacts due to NO₂ among urban, suburban, and rural areas. Generally, the STNN model could incorporate spatiotemporal neighboring information and infer surface NO₂ concentration with full coverage and high accuracy. Compared with machine learning regression techniques, STNN can effectively avoid model overfitting and simultaneously consider both spatial and temporal correlations of input variables using deep convolutional networks with residual blocks. The use of the proposed STNN model, as well as the surface NO₂ dataset, can benefit air quality monitoring, forecasting, and health burden assessments.

Decisive role of ozone formation control in winter PM2.5 mitigation in Shenzhen, China

During the COVID-19 lockdown, atmospheric PM_2.5 in the Pearl River Delta (PRD) showed the highest reduction in China, but the reasons, being a critical question for future air quality policy design, are not yet clear. In this study, we analyzed the relationships among gaseous precursors, secondary aerosols and atmospheric oxidation capacity in Shenzhen, a megacity in the PRD, during the lockdown period in 2020 and the same period in 2021. The comprehensive observational datasets showed large lockdown declines in all primary and secondary pollutants (including O₃). We found that, however, the daytime concentrations of secondary aerosols during the lockdown period and normal period were rather similar when the corresponding odd oxygen (O_x≡O₃+NO₂, an indicator of photochemical processing avoiding the titration effect of O₃ by freshly emitted NO) were at similar levels. Therefore, reduced O_x, rather than the large reduction in precursors, was a direct driver to achieve the decline in secondary aerosols. Moreover, O_x was also found to determine the spatial distribution of intercity PM_2.5 levels in winter PRD. Thus, an effective strategy for winter PM_2.5 mitigation should emphasize on control of winter O₃ formation in the PRD and other regions with similar conditions.

Revisiting Total Particle Number Measurements for Vehicle Exhaust Regulations

Road transport significantly contributes to air pollution in cities. Emission regulations have led to significantly reduced emissions in modern vehicles. Particle emissions are controlled by a particulate matter (PM) mass and a solid particle number (SPN) limit. There are concerns that the SPN limit does not effectively control all relevant particulate species and there are instances of semi-volatile particle emissions that are order of magnitudes higher than the SPN emission levels. This overview discusses whether a new metric (total particles, i.e., solids and volatiles) should be introduced for the effective regulation of vehicle emissions. Initially, it summarizes recent findings on the contribution of road transport to particle number concentration levels in cities. Then, both solid and total particle emission levels from modern vehicles are presented and the adverse health effects of solid and volatile particles are briefly discussed. Finally, the open issues regarding an appropriate methodology (sampling and instrumentation) in order to achieve representative and reproducible results are summarized. The main finding of this overview is that, even though total particle sampling and quantification is feasible, details for its realization in a regulatory context are lacking. It is important to define the methodology details (sampling and dilution, measurement instrumentation, relevant sizes, etc.) and conduct inter-laboratory exercises to determine the reproducibility of a proposed method. It is also necessary to monitor the vehicle emissions according to the new method to understand current and possible future levels. With better understanding of the instances of formation of nucleation mode particles it will be possible to identify its culprits (e.g., fuel, lubricant, combustion, or aftertreatment operation). Then the appropriate solutions can be enforced and the right decisions can be taken on the need for new regulatory initiatives, for example the addition of total particles in the tailpipe, decrease of specific organic precursors, better control of inorganic precursors (e.g., NH3, SOx), or revision of fuel and lubricant specifications.

Grey Correlation Analysis of Haze Impact Factor PM2.5

In recent years, frequent severe haze weather has formed in China, including some of the most populated areas. We found that these smog-prone areas are often relatively a “local climate” and aim to explore this series of scientific problems. This paper uses remote sensing and data mining methods to study the correlation between haze weather and local climate. First, we select Beijing, China and its surrounding areas (East longitude 115°20′11″–117°40′35″, North latitude 39°21′11″–41°7′51″) as the study area. We collected data from meteorological stations in Beijing and Xianghe from March 2014 to February 2015, and analyzed the meteorological parameters through correlation analysis and a grey correlation model. We study the correlation between the six influencing factors of temperature, dew point, humidity, wind speed, air pressure and visibility and PM2.5, so as to analyze the correlation between haze weather and local climate more comprehensively. The results show that the influence of each index on PM2.5 in descending order is air pressure, wind speed, humidity, dew point, temperature and visibility. The qualitative analysis results confirm each other. Among them, air pressure (correlation 0.771) has the greatest impact on haze weather, and visibility (correlation 0.511) is the weakest.