Integrated Source Apportionment Research Articles

A Nation-by-Nation Assessment of the Contribution of Southeast Asian Open Biomass Burning to PM2.5 in Thailand Using the Community Multiscale Air Quality-Integrated Source Apportionment Method Model

This study utilized the Community Multiscale Air Quality (CMAQ) model to assess the impact of open biomass burning (OBB) in Thailand and neighboring countries—Myanmar, Laos, Cambodia, and Vietnam—on the PM2.5 concentrations in the Bangkok Metropolitan Region (BMR) and Upper Northern Region of Thailand. The Upper Northern Region was further divided into the west, central, and east sub-regions (WUN, CUN, and EUN) based on geographical borders. The CMAQ model was used to simulate the spatiotemporal variations in PM2.5 over a wide domain in Asia in 2019. The Integrated Source Apportionment Method (ISAM) was utilized to quantify the contributions from OBB from each country. The results showed that OBB had a minor impact on PM2.5 in the BMR, but transboundary transport from Myanmar contributed to an increase in PM2.5 levels during the peak burning period from March to April. In contrast, OBB substantially impacted PM2.5 in the Upper Northern Region, with Myanmar being the major contributor in WUN and CUN and domestic burning being the major contributor to EUN during the peak months. Despite Laos having the highest OBB emissions, meteorological conditions caused the spread of PM2.5 eastward rather than into Thailand. These findings highlight the critical impact of regional transboundary transport and emphasize the necessity for collaborative strategies for mitigating PM2.5 pollution across Southeast Asia.

Research on Ozone Pollution Characteristics and Source Apportionment During the COVID-19 Lockdown in Jilin City in 2022

The increasing Ozone (O3) concentration in various regions of China has garnered significant attention, highlighting the need to understand the mechanisms of O3 formation. This study focuses on the source apportionment of O3 in Jilin City during and after the COVID-19 lockdown countermeasure, and also the influence of anthropogenic emissions on O3 concentration. The contributions of different O3 emission sources were quantified using the Weather Research and Forecasting Community Multi-Scale Air Quality (WRF-CMAQ) model in conjunction with the Integrated Source Apportionment Method (ISAM). The results indicate a significant increase in O3 concentrations during the lockdown in Jilin City, which were particularly characterized by long-distance transportation. Transportation is identified as the primary direct source of O3 in Jilin City, with Yongji County contributing the most among the six designated regions. This study highlights variations in the causes and sources of O3 pollution among the different regions of Jilin City. Simply controlling anthropogenic emissions is inadequate for effectively managing O3 pollution and may even worsen the situation. It is more effective to focus on controlling O3’s precursors. These findings improve the understanding of O3 pollution in Jilin City and provide valuable insights for developing O3 control policies. Similarly, this research is applicable to other countries and regions.

Source apportionment of PM2.5 episodes in the Taichung metropolitan area, Taiwan

To analyze the physicochemical mechanisms affecting the variation in fine suspended particulate matter (PM2.5) concentrations in Taichung City, the largest city in central Taiwan (the second largest city in Taiwan), during a high-pollution event from November 3 to 6, 2021, we applied the sulfur tracking method (STM) and integrated source apportionment method (ISAM) of the WRF/CMAQ model to simulate the impacts of various emission sources. The sources of pollution in Taichung City are very similar, which shows that the impacts of point, line, and area sources should not be neglected in addition to the boundary conditions. SO42− is mainly generated from point emissions and the production of H2O2, Fe, Mn, and O3. NO3− is also mainly generated from point sources in Taichung City, with HNO3 being the main source at noon and ANO3 at other times of the day. NH4+ is mainly generated from area sources in Taichung City. OM is more complex, mainly originating from line sources in Taichung City and other sources, such as point/area emissions in Taichung City and other emissions from Changhua County. The most important mechanism is low-volatility/semivolatile oxidized combustion of OC at noon, followed by low-volatility/semivolatile POA, which is produced in the morning or evening. EC mainly originates from line sources in Taichung City and Changhua County. In other nearby counties, EC is dominated by local emission sources. In addition, when the concentration of PM2.5 is high, the Neutralization Ratio (NR) is high and PM2.5 is relatively neutral or slightly alkaline. On the contrary, when the concentration of PM2.5 is low, the NR is lower than 1 and the aerosol is acidic. Besides, this study used positive matrix factorization (PMF), which indicates that the PM2.5 at the UAPRS originated from eight kinds of pollution, namely, windblown dust, oil cracking, iron and steel industry, sea salt, transport, Cl− containing exhaust, biomass burning, fossil combustion containing abundant SO42− and the heavy oil refining and coal combustion industry. The direction of the source of pollution can be traced by a conditional bivariate probability function (CBPF). Overall, fossil fuel combustion, mainly involving sulfate, is the largest source of pollution, with the heavy oil refining and coal combustion industry contributing less, and the remaining factors contribute relatively evenly.

Impacts of different vehicle emissions on ozone levels in Beijing: Insights into source contributions and formation processes

Beijing, with the highest number of motor vehicles in China, significantly contributes to O3 pollution through substantial NOx and VOC emissions in the on-road transportation sector. Understanding the unique impact of emissions from different vehicle types on O3 levels is crucial for developing targeted strategies for O3 pollution. This study applied the Community Multiscale Air Quality Modeling System (CMAQ) to comprehensively investigate the impacts of emissions from different vehicle types on O3 levels in various regions of Beijing and to provide valuable insights into source contributions and formation processes. The results revealed that various vehicle types exhibited different spatial-temporal emission patterns, with medium-heavy duty trucks (HDT) and mini-light passenger vehicles (LDPV) identified as the primary contributors to NOx (36.1 %) and VOC (57.6 %) emissions. Using the Integrated Source Apportionment Method (ISAM) coupled in CMAQ, we found the total vehicle emissions contributed to over 20 % of daily maximum 8–h average O3 (MDA8 O3) concentration, ranked as the second largest contributor after regional transport. Contributions to O3 formation from LDPV and medium-large passenger vehicles (MDPV) were 2.6–4.0 and 4.2–6.8 ppb and mainly concentrated in urban areas, while the contributions from mini-light duty trucks (LDT) and HDT were 3.5–4.8 and 3.7–6.2 ppb and mainly concentrated in suburban areas. Through scenario analysis that removed emissions from specific types of vehicles, we found removing LDPV emissions led to decreases in daytime O3 concentration by 0.3–3.8 ppb. In contrast, removing MDPV emissions led to notable O3 increases by 4.0–11.8 ppb at rush hours. Removing LDT and HDT emissions resulted in 0.6–8.0 ppb increases in nocturnal O3 concentrations while 0.8–2.0 ppb decreases during the afternoon. This research highlights the necessity of tailoring control strategies for different vehicle types to effectively reduce O3 levels in Beijing and provides useful information for decision-makers to formulate effective measures of vehicle management in the future.

Which pollutants and sources should be prioritized for control in multi-pollutants complex contaminated areas?

Risk assessment and source identification of multi-pollutants are essential for accurate control of soil contamination. However, complexity in pollutant properties and diversity in source types raise challenges to the target. Therefore, this study constructed a hierarchical ecological risk quantification method combined with risk ranking, risk of single pollutant using potential affected fraction (PAF), and joint risk of multi-pollutants employing msPAF. Taking regional contamination in South China as a case, the risk ranking was determined, while single and joint effects showed msPAF reaching 79.4 %, with risk as heavy metals (HMs) > per- and polyfluoroalkyl substances (PFASs) > polycyclic aromatic hydrocarbons (PAHs). Meanwhile, an integrated source apportionment method was established from three layers by principal component analysis to classify source types, multiple linear regression of distance to identify key sources, and positive matrix factorization to track omitted sources. Consequently, key sources were captured, with 80.8 %−93.2 % contribution of farmland and electroplating to three main HMs, 52.2 %−69.4 % contribution of roads to three main PAHs, and 71.1 %−73.2 % contribution of electroplating to two main PFASs. Further, omitted sources were tracked with contribution of 31.2 %−84.1 % to eight pollutants. The established methods can identify control targets, including high-risk pollutants and their key sources.

Source contributions to two super dust storms over Northern China in March 2021 and the impact of soil moisture

Two extremely devastating super dust storms (SDS) hit Mongolia and Northern China in March 2021, causing many deaths and substantial economic damage. Accurate forecasting of dust storms is of great importance for avoiding or mitigating their effects. One of the most critical factors affecting dust emissions is soil moisture, but its value in desert exhibits significant uncertainty. In this study, model experiments were conducted to simulate dust emissions using four soil moisture datasets. The results were compared with observations to assess the effects of soil moisture on the dust emission strength. The Integrated Source Apportionment Method (ISAM) was used to track the dust sources and quantify the contribution from each source region to the dust load over the North China Plain (NCP), Korea peninsula, and western Japan. The results show large differences in the dust load depending on the soil moisture datasets used. The high soil moisture in the NCEP dataset results in substantial underestimation of the dust emission flux and PM10 concentration. Despite a minor overestimation of PM10 concentrations in many Northern China cities, the ERA5 dataset yields the best simulation performance. During the two SDS events, about 7.5 Mt dust was released from the deserts in Mongolia and 2.8 Mt from the deserts in China. Source apportionment indicates that the Mongolian Gobi Desert is the dominant source of PM10 in the NCP, Korea peninsula, and western Japan, accounting for 60 %–80 %, while Inner Mongolia contributed 10 %–20 %.

The reward and penalty for ozone pollution control caused by natural sources and regional transport: A case study in Guangdong province

Ground-level O3 pollution in the Pearl River Delta region (PRD) is closely related to anthropogenic, natural emissions and regional transport. However, the interactions among different sources and natural intervention in modulating anthropogenic management have not been comprehensively assessed. Here, the WRF-CMAQ-MEGAN modeling system was utilized to simulate an O3 episode over PRD. The integrated source apportionment method (ISAM) and brute-force top-down combined with factor separation approach (BF-TD-FSA) were applied to quantify source contributions, impacts of individual or multiple sources on O3, and decouple interactions among various emissions; additionally, based on ISAM, O3 isopleths visualized MDA8 O3 response of different source types to anthropogenic perturbations. ISAM concluded considerable MDA8 O3 contributions of regional transport in PRD/NPRD (non-PRD areas in Guangdong province) (38.8 %/35.7 %), followed by anthropogenic (32.7 %/24.8 %), BVOC (biogenic volatile organic compounds, 23.8 %/20.3 %) and SNO (soil NO, ∼4 %) emissions. Compared to concentrated anthropogenic contributions, widespread natural contributions were observed across their source areas and along the transport pathways. The BF-TD also revealed that regional transport had the largest impact (>90 μg m−3) on MDA8 O3 while anthropogenic and BVOC emissions greatly affected downwind PRD (64.5 and 7.7 μg m−3). Negative synergy between anthropogenic and natural emissions (especially BVOC emission) suggested potential natural-induced intensification of anthropogenic impact during O3 management. The MDA8 O3 isopleths further demonstrated significant BVOC-induced reward and regional transport-induced penalty for anthropogenic NOx (ANOx) emission control benefits, leading to additional maximum MDA8 O3 decrease and increase by −27.5 and 13.8 μg m−3 in polluted high-emission grids. The natural-induced reward effect could impose loose requirements on anthropogenic reduction (decreased by 13.3 %–17.7 %) if there were no regional transport-induced control penalty. It is advisable to prioritize ANOx control and seek collaboration on air quality management with neighboring provinces to maximize the natural-induced control reward and achieve desired targets with minimal human efforts.

Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002–2020

In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality–Integrated Source Apportionment Method (CMAQ–ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21–40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> −20 μg/m3) after 2011 due to pollution control measures.

Regional transport characteristics of PM2.5 pollution events in Beijing during 2018–2021

Although air pollutant emissions have sharply reduced in recent years, the occurrence of PM2.5 pollution events remains an intractable environmental problem in Beijing, and regional transport is the key influence factor. However, it has been difficult to identify regional transport characteristics and the main contributors to pollution events in recent years. In this study, the relative contribution of regional transport was quantified (61.3%) in PM2.5 pollution events during 2018-2021 by the Community Multiscale Air Quality model embedded with the Integrated Source Apportionment Model (CMAQ-ISAM). The four regions with the largest fractional contributions to Beijing for all events were Shandong (7.7%), South Hebei (7.3%), Baoding (6.2%), and Langfang (5.8%). Pollution events were classified into the following types based on regional transport directions: local, southwest (SW), southeast (SE), south-mixed (SM), and others. Based on the transport distance, the SW, SE, and SM types can be subdivided into SW-short, SW-long, SE-short, SE-long, SM-short, SM-long distance from southwest, SM-long distance from southeast, and SM-long distance from southwest and southeast. SE-long was regarded as the most important type, with the highest relative frequency (20%). The transport directions were related to the southwest wind at 925 hPa and southeast wind at 1000 hPa in the south of the Beijing–Tianjin–Hebei (BTH) region, and the distance was mainly controlled by wind strength. The wind-field difference can be attributed to the low-pressure and high-pressure systems that control the BTH region. The results suggest that regional joint pollution control should be optimized based on the transport type.

Summertime tropospheric ozone source apportionment study in the Madrid region (Spain).

The design of emission abatement measures to effectively reduce high ground-level ozone (O3) concentrations in urban areas is very complex. In addition to the strongly non-linear chemistry of this secondary pollutant, precursors can be released by a variety of sources in different regions, and locally produced O3 is mixed with that transported from the regional or continental scales. All of these processes depend also on the specific meteorological conditions and topography of the study area. Consequently, high-resolution comprehensive modeling tools are needed to understand the drivers of photochemical pollution and to assess the potential of local strategies to reduce adverse impacts from high tropospheric O3 levels. In this study, we apply the Integrated Source Apportionment Method (ISAM) implemented in the Community Multiscale Air Quality (CMAQ v5.3.2) model to investigate the origin of summertime O3 in the Madrid region (Spain). Consistent with previous studies, our results confirm that O3 levels are dominated by non-local contributions, representing around 70 % of mean values across the region. Nonetheless, precursors emitted by local sources, mainly road traffic, play a more important role during O3 peaks, with contributions as high as 25 ppb. The potential impact of local measures is higher under unfavorable meteorological conditions associated with regional accumulation patterns. These findings suggest that this modeling system may be used in the future to simulate the potential outcomes of specific emission abatement measures to prevent high-O3 episodes in the Madrid metropolitan area.

Designing regional joint prevention and control schemes of PM2.5 based on source apportionment of chemical transport model: A case study of a heavy pollution episode

Fine particular matter (PM2.5) pollution still occurs frequently in China. Despite recognizing the importance of regional joint prevention and control (RJPC) for mitigating haze pollution, there is still a limited understanding of scheme design and effectiveness. In this study, with the Fenhe Plain in China serving as the case, the Integrated Source Apportionment Method (ISAM), incorporated into the Community Multiscale Air Quality Modeling System (CMAQ), was used to quantitively identify PM2.5 sources during a typical heavy pollution episode from Jan. 20th to 25th, 2021. Informed by source apportionment, we designed and assessed multiple RJPC scenarios for eliminating heavy pollution, yielding recommended RJPC schemes. Source apportionment results revealed a substantial increase in the contribution percentage of regions within a 350-km radius during the pollution episode compared to the non-polluted period. Sulfate was predominantly contributed from long-distance transport, whereas nitrate was chiefly contributed from closer regions. Ammonium exhibited higher local contributions than nitrate from the Fenhe Plain. Moreover, Taiyuan and Linfen were identified as PM2.5 exporters, whereas Sanmenxia, Jinzhong, and Luliang served as PM2.5 importers, and Yuncheng acted as a comprehensive city. The proposed specific RJPC schemes aimed at eliminating heavy pollution for the Fenhe Plain emphasized the importance of controlling emissions of particulate matter, ammonia, nitrogen oxides, and volatile organic compounds in areas within an approximate 350-km radius outside the Fenhe Plain, in addition to strengthening the local emission control. Nevertheless, only through the comprehensive and in-depth implementation of emission control measures across a larger area can PM2.5 compliance be achieved.

Chemical composition and origins of PM2.5 in Chiang Mai (Thailand) by integrated source apportionment and potential source areas

Upper Southeast Asian region lacks source apportionment studies of air pollution, particularly PM2.5, despite its persistence. This study aims to quantify PM2.5 source contributions and identify their potential source areas in urban Chiang Mai (Thailand) as a representative of the region, using the positive matrix factorization (PMF) receptor model and the potential source contribution function (PSCF). A total of 51 samples were collected and analyzed for water-soluble ions, organic carbon, elemental carbon, carbohydrates, carboxylates, and metals. An average PM2.5 concentration of 116 ± 35 and 35 ± 6 μg m−3 was found during smoke-haze (SH) and non-smoke-haze (NSH) periods, respectively. The average PMF-resolved contributions to PM2.5 in the SH period were the following: biomass burning (59.3 μg m−3) > secondary sulfate (26.2 μg m−3) > dust (16.1 μg m−3) > traffic (14.6 μg m−3). In contrast, those in the NSH period were the following: traffic (27.2 μg m−3) > dust (5.9 μg m-3) > biomass burning (2.5 μg m−3). The PSCF revealed that biomass burning has the main potential source area along the Thai-Myanmar border, while the secondary sulfate largely originated in Indian continent. Local pollution from traffic and dust contributed consistently but was minor in comparison. The source composition exhibited major seasonal change because of the lack of biomass burning and transboundary pollution in the wet season, where exhaust and non-exhaust traffic emissions became the main contributors. These findings offer insights into how regional PM2.5 affects the local pollution in the urban atmosphere.

On the sources of ambient SOA in PM2.5: An integrated analysis over Jinan city of China

Secondary organic aerosol (SOA) accounts for a significant fraction of fine particulate matter (PM2.5) and is a crucial component that affects climate and public health. However, the formation of SOA in urban areas remains unclear and sources contributed to SOA are poorly characterized. In this study, we combined ambient measurements and the Weather Research and Forecasting (WRF)-Community Multi-scale Air Quality (CMAQ) modeling system to investigate the evolution of SOA during winter over Jinan city in China. Relative contributions of different anthropogenic sources to ambient SOA were subsequently probed by the Integrated Source Apportionment Method (ISAM) to explore the impact of anthropogenic emissions. The mean concentration of SOA was 11.2 μg m−3, accounting for 29.4% in PM2.5, and SOA concentrations on clean days (4.9 μg m−3) increased by 4.8 times on polluted days (23.3 μg m−3), and strong correlation between the elevated PM2.5 episodes and increased SOA concentrations was found (R2 > 0.5). In addition, SOA concentrations and the proportion of SOA in PM2.5 were higher during the daytime (24.9 μg m−3, 32.4%) compared to nighttime (21.9 μg m−3, 25.1%) on polluted days, which is primarily attributed to the intense atmospheric photochemical reactions and anthropogenic activities. Mobile sources act as the dominant contributor to SOA (57.6%) and road diesel emissions (30.9%) made the largest contribution to SOA, followed by non-road mobile sources (17.4%) among subsectors in mobile sources. This study sheds new insights into ambient SOA formation and SOA source apportionment for typical megacities in China, guiding the design of source-oriented regulation efforts on SOA mitigation.

Maximizing ozone control by spatial sensitivity-oriented mitigation strategy in the Pearl River Delta Region, China

The Pearl River Delta (PRD) has long been plagued by severe O3 pollution, particularly during the autumn. A regional O3 pollution episode influenced by the Western Pacific Subtropical High in September 2021 was characterized by near-surface O3 escalation due to strong photochemical reactions within the planetary boundary layer. This event was targeted to develop effective control strategies through investigation of precursor control type and scope based on the high-order decoupled direct method (HDDM) and integrated source apportionment method (ISAM) of CMAQ. Generally, the majority of areas (67.0 %) were under NOx-limited regime, which should strengthen afternoon NOx control inferred by positive convex O3 responses. However, high emission and heavily polluted areas located in central PRD were under VOC-limited regime (11.6 %) or mixed regime (15.0 %). The remaining areas (6.4 %) were under NOx-titration or insensitive conditions. Regarding source apportionment, Guangdong province contributed 32.3 %–58.4 % to MDA8 O3 of PRD, especially higher proportion (>50 %) to central areas. Overall, local-focused NOx/VOC emission reductions had limited effects on O3 mitigation for receptor cities compared to regional-cooperative regulation. When region-wide VOC emission reduction was implemented, MDA8 O3 in VOC-limited grids exhibited the largest declines (2.3 %–4.1 %, 3.9– 7.0 μg·m−3). However, unified NOx control contributed to increasing MDA8 O3 in VOC-limited grids (most stations located for air quality evaluation) whereas decreased MDA8 O3 by 2.1 %– 5.7 %, 3.0– 8.2 μg·m−3 in large-scale NOx-limited grids. The sensitivity-oriented regional control avoided O3 rebound and achieved the greatest decline of 3.4 %– 5.0 %, 5.7– 8.4 μg·m−3 in VOC-limited grids; additionally, time-refined dynamic aggressive NOx control decreased peak O3 by an extra 1.2– 6 μg·m−3, both of which facilitate the regulation for the forecasting O3 episodes. These findings suggest that in heavily polluted environments, the enhancement of O3 regulation benefits requires meticulous, coordinated, and dynamic NOx and VOC controls spanning the entire region based on high-resolution analysis of heterogeneous O3-NOx-VOC sensitivity. Furthermore, emission reduction gains should be more reasonably reflected through increasing in-situ observations covering multi-sensitivity regions.

Modeling PM2.5 During Severe Atmospheric Pollution Episode in Lagos, Nigeria: Spatiotemporal Variations, Source Apportionment, and Meteorological Influences

AbstractIn 2021, the World Health Organization ranked Nigeria among the most polluted nations in the world, an indication of a deteriorating air quality, especially in the major urban areas of the country, which might pose adverse human health impacts. In this study, the Integrated Source Apportionment Method (ISAM) tool in the Community Multiscale Air Quality (CMAQ) model (CMAQ‐ISAM) was employed to quantify the contributions of eight emissions sectors to fine particulate matter (PM2.5) and its major components in Lagos during a prolonged severe atmospheric pollution episode (APE) in January 2021. The influence of meteorological conditions on the formation and dispersion of PM2.5 during the APE was also elucidated. Spatially, elevated PM2.5 concentrations were found in the northwestern region of Lagos, an urban area with larger anthropogenic emissions. Residential and industry were the two major sources of PM2.5. Residential contributed the most to total PM2.5 (∼40 μg/m3), followed by industry (∼20 μg/m3). High concentrations of secondary inorganic aerosols (SIA) at the northwest and upper northern areas of Lagos were majorly attributed to residential and industry sectors. In addition, sulfate accounted for the largest fraction of PM2.5, with residential, industry, and energy being its major sources. Residential, industry, and on‐road sectors dominated the contributions to nitrate, while residential and industry were the major contributors to ammonium. Furthermore, the elevated PM2.5 concentrations during the APE were greatly enhanced by unfavorable meteorological conditions. This study provides insights for designing effective emissions control strategies to mitigate future severe PM2.5 pollution episode in Lagos.

Modeling regional nitrogen cycle in the atmosphere: Present situation and its response to the future emissions control strategy

Reactive nitrogen (Nr) cycle in the atmosphere has an important affection on terrestrial ecosystems, which has not been fully understood and its response to the future emissions control strategy is not clear. Taking the Yangtze River Delta (YRD) as an example, we explored the regional Nr cycle (emissions, concentrations, and depositions) and its source apportionment in the atmosphere in January (winter) and July (summer) 2015 and projected its changes under emissions control by 2030 using the CMAQ model. We examined the characteristics of Nr cycle and found that Nr suspends in the air mainly as NO, NO2, and NH3 gases and deposits to the earth's surface mainly as HNO3, NH3, NO3−, and NH4+. Due to the higher NOx than NH3 emissions, oxidized nitrogen (OXN) but not reduced nitrogen (RDN) is the major component in Nr concentration and deposition, especially in January. Nr concentration and deposition show an inverse correlation, with a high concentration in January and low in July but the opposite for deposition. We further apportioned the regional Nr sources for both concentration and deposition using the Integrated Source Apportionment Method (ISAM) incorporated in the CMAQ model. It shows that local emissions are the major contributors and this characteristic is more significant in concentration than deposition, for RDN than OXN species, and in July than in January. The contribution from North China (NC) is important for Nr in YRD, especially in January. In addition, we revealed the response of Nr concentration and deposition to the emission control to achieve the target of carbon peak in the year 2030. After the emission reduction, the relative responses of OXN concentration and deposition are generally about 100 % to the reduction of NOx emissions (~50 %), while the relative responses of RDN concentration are higher than 100 % and the relative responses of RDN deposition are significantly lower than 100 % to the reduction of NH3 emissions (~22 %). Consequently, RDN will become the major component in Nr deposition. The smaller reduction of RDN wet deposition than sulfur wet deposition and OXN wet deposition will raise the pH of precipitation and help alleviate the acid rain problem, especially in July.

Comparison of ozone formation attribution techniques in the northeastern United States

Abstract. The Integrated Source Apportionment Method (ISAM) has been revised in the Community Multiscale Air Quality (CMAQ) model. This work updates ISAM to maximize its flexibility, particularly for ozone (O3) modeling, by providing multiple attribution options, including products inheriting attribution fully from nitrogen oxide reactants, fully from volatile organic compound (VOC) reactants, equally from all reactants, or dynamically from NOx or VOC reactants based on the indicator gross production ratio of hydrogen peroxide (H2O2) to nitric acid (HNO3). The updated ISAM has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3.2 and beyond). This study's primary objective is to document these ISAM updates and demonstrate their impacts on source apportionment results for O3 and its precursors. Additionally, the ISAM results are compared with the Ozone Source Apportionment Technology (OSAT) in the Comprehensive Air-quality Model with Extensions (CAMx) and the brute-force method (BF). All comparisons are performed for a 4 km horizontal grid resolution application over the northeastern US for a selected 2 d summer case study (9 and 10 August 2018). General similarities among ISAM, OSAT, and BF results add credibility to the new ISAM algorithms. However, some discrepancies in magnitude or relative proportions among tracked sources illustrate the distinct features of each approach, while others may be related to differences in model formulation of chemical and physical processes. Despite these differences, OSAT and ISAM still provide useful apportionment data by identifying the geographical and temporal contributions of O3 and its precursors. Both OSAT and ISAM attribute the majority of O3 and NOx contributions to boundary, mobile, and biogenic sources, whereas the top three contributors to VOCs are found to be biogenic, boundary, and area sources.

Differences between VOCs and NOx transport contributions, their impacts on O3, and implications for O3 pollution mitigation based on CMAQ simulation over the Yangtze River Delta, China

The relationship between O3 and its precursors during urban polluted episodes remains unclear. In this study, the simultaneous source apportionment of VOCs, NOx, and O3 over the Yangtze River Delta (YRD) region during the O3 polluted episode on July 24–30, 2018, was performed based on the Integrated Source Apportionment Method (ISAM) embedded in the Community Multiscale Air Quality Modeling System (CMAQ). The results of the ISAM were compared with those of the Brute Force Method (BFM) and Positive Matrix Factorization (PMF). Furthermore, the differences between the transport contributions of VOCs and NOx, and their impacts on O3 were analyzed. The results indicate that observations of VOCs species can be well captured by simulated VOCs, and the ISAM has a significant advantage in the source apportionment of VOCs, especially for sources emitting highly reactive species. In the clean and polluted periods, the local contribution percentages of VOCs in urban sites ranged from 60 % to 77 %, much higher than those of NOx (31 %–43 %) and O3 (16 %–33 %). NOx and O3 have strong transport abilities with high and close contribution percentages, which are highly correlated, mainly because oxygen atoms produced by the photolysis of NO2 in the aged air mass combined rapidly with O2 to form O3 during transport. The VOCs chemical loss caused by the oxidation of OH radicals during transport makes the ability of VOCs for long-distance transport much weaker than that of NOx. Furthermore, owing to the sufficient aging of VOCs, those contributed by long-distance transport have little effect on O3. To a certain extent, controlling one's NOx emissions can help other cities more, while controlling one's VOCs emissions can help itself more. Therefore, it is recommended to attach enough importance to joint prevention and control of NOx among cities and even long-distance areas to alleviate regional O3 pollution.

Role of meteorology-driven regional transport on O3 pollution over the Chengdu Plain, southwestern China

Owing to the complex mesoscale meteorological dynamics, deep basin topography and pollutants emissions, the Chengdu Plain (CDP) situated at west border of the Sichuan Basin (SCB) have suffered excessive ozone (O3) pollution in the warm season. However, the meteorology-driven mechanism and associated dominant processes underlying the elevated O3 levels are not well elucidated due to limited ambient measurements. Here, we adopted trace gases data measured by basin-wide network in combination with a high-resolution chemical transport model for characterizing a regional continuous O3 episode occurred from 10 to 18 August 2019. The extensive monitoring network shapes a much-detailed evolution map of O3 concentrations which depicts that O3 hotspots extend from metropolitan areas to suburban areas across the CDP. It is found that both advection of O3-rich air masses in the residual layer (RL) and regional transport of O3 and its precursors under prevailing winds exert profound influences on the elevation of ambient O3 across the CDP. As the convective boundary layer is destroyed after sunrise, vertical mixing effects cause the entrainment of O3-rich air masses in RL to the surface, affecting the redistribution of surface O3 concentration. In addition, process analysis (PA) and integrated source apportionment method (ISAM) results of the CMAQ model indicated that vertical transport and gas-phase chemistry were the main sources of O3 during the day, while dry deposition and horizontal advection were the main sinks of surface O3. O3 transport by boundary condition (BCO) was the largest contributor to all urban O3 concentrations in the CDP. Our findings highlight the regional transport mechanism of O3 in SCB under complex topographic conditions and point out the physical and chemical causes and sources of typical summer O3 pollution episodes in the SCB.

Why did air quality experience little improvement during the COVID-19 lockdown in megacities, northeast China?

To inhibit the COVID-19 (Coronavirus disease 2019) outbreak, unprecedented nationwide lockdowns were implemented in China in early 2020, resulting in a marked reduction of anthropogenic emissions. However, reasons for the insignificant improvement in air quality in megacities of northeast China, including Shenyang, Changchun, Jilin, Harbin, and Daqing, were scarcely reported. We assessed the influences of meteorological conditions and changes in emissions on air quality in the five megacities during the COVID-19 lockdown (February 2020) using the WRF-CMAQ model. Modeling results indicated that meteorology contributed a 14.7% increment in Air Quality Index (AQI) averaged over the five megacities, thus, the local unfavorable meteorology was one of the causes to yield little improved air quality. In terms of emission changes, the increase in residential emissions (+15%) accompanied by declining industry emissions (−15%) and transportation (−90%) emissions resulted in a slight AQI decrease of 3.1%, demonstrating the decrease in emissions associated with the lockdown were largely offset by the increment in residential emissions. Also, residential emissions contributed 42.3% to PM2.5 concentration on average based on the Integrated Source Apportionment tool. These results demonstrated the key role residential emissions played in determining air quality. The findings of this study provide a scenario that helps make appropriate emission mitigation measures for improving air quality in this part of China.