Air Pollution Control Policies Research Articles

Long-term (2008–2017) analysis of atmospheric composite aerosol and black carbon radiative forcing over a semi-arid region in southern India: Model results and ground measurement

To achieve an in-depth understanding of radiative forcing due to aerosols is a crucial challenge for climate change studies. The first-ever long-term measurement of direct shortwave composite and black carbon aerosol radiative properties over a semi-arid region, Anantapur, in southern India is presented. Long-term variations in Aerosol Optical Depth (AOD) and Black Carbon (BC) mass concentration from December 2007 to November 2017 are discussed with specific emphasis on intra-seasonal variation in aerosol optical properties, meteorology, transport pathways, and their implications for direct short wave radiative forcing over Anantapur. The intra-seasonal mean AOD showed strong seasonal dependence with the highest (0.47 ± 0.03) during summer and lowest (0.28 ± 0.03) during the monsoon. Meanwhile, the intra-seasonal mean (±σ) BC mass concentration was about 3.57 ± 0.45, 2.60 ± 0.58, 1.22 ± 0.18 and 2.24 ± 0.28 μg m−3 during winter, summer, monsoon and post-monsoon respectively. Furthermore, there is an obvious temporal variation in intra-seasonal BC mass concentration during the dry season (winter and summer). To be more specific, the intra-seasonal mean (±σ) BC mass concentration before 2012 (after 2012) during the dry season was about 3.37 ± 0.7 μg m−3 (2.80 ± 0.58 μg m−3), respectively. Concentration weighted trajectory analyses (CWT) revealed that the air masses originated from the continental and polluted environments located in the central and northern parts of India (except monsoon), in regulating BC mass concentration over measurement location. Further, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) derived aerosol vertical extinction profiles (532 nm) showed that majority aerosols (>250 Mm−1) are confined within 2 km from the surface during winter while in summer particles are distributed throughout the profile (~6 km) with extinction coefficient varying between 200 and 250 Mm−1. The Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model estimated intra-seasonal mean direct shortwave composite aerosol radiative forcing (DARF) in the atmosphere (ATM) was about 31.13 ± 3.36, 34.82 ± 3.89, 17.10 ± 1.15, and 17.44 ± 1.81 Wm-2 during winter, summer, monsoon and post-monsoon, respectively. The positive signs of ATM forcing in all seasons indicate a warming of the atmosphere, and the corresponding heating rate was around a factor of two higher during the dry season (0.92 ± 0.12 Kday−1) than the wet season (monsoon and post-monsoon) (0.49 ± 0.04 Kday−1). The intra-seasonal mean BC forcing in ATM before 2012 (After 2012) during the dry season was about 24.14 ± 2.85Wm-2(20.09 ± 2.59Wm-2), respectively. The contribution of BC alone to the composite forcing during the study period over the station was ~68%. These findings would be helpful for regional climate studies and making air pollution control policy over the region.

Effect of bromine and iodine chemistry on tropospheric ozone over Asia-Pacific using the CMAQ model

Recent studies have focused on the chemistry of tropospheric halogen species which are able to deplete tropospheric ozone (O3). In this study, the effect of bromine and iodine chemistry on tropospheric O3 within the annual cycle in Asia-Pacific is investigated using the CMAQ model with the newly embedded bromine and iodine chemistry and a blended and customized emission inventory considering marine halogen emission. Results indicate that the vertical profiles of bromine and iodine species show distinct features over land/ocean and daytime/nighttime, related to natural and anthropogenic emission distributions and photochemical reactions. The halogen-mediated O3 loss has a strong seasonal cycle, and reaches a maximum of −15.9 ppbv (−44.3%) over the ocean and −13.4 ppbv (−38.9%) over continental Asia among the four seasons. Changes in solar radiation, dominant wind direction, and nearshore chlorophyll-a accumulation all contribute to these seasonal differences. Based on the distances to the nearest coastline, the onshore and offshore features of tropospheric O3 loss caused by bromine and iodine chemistry are studied. Across a coastline-centric 400-km-wide belt from onshore to offshore, averaged maximum gradient of O3 loss reaches 1.1 ppbv/100 km at surface level, while planetary boundary layer (PBL) column mean of O3 loss is more moderate, being approximately 0.7 ppbv/100 km. Relative high halogen can be found over Tibetan Plateau (TP) and the largest O3 loss (approximately 4–5 ppbv) in the PBL can be found between the western boundary of the domain and the TP. Halogens originating from marine sources can potentially affect O3 concentration transported from the stratosphere over the TP region. As part of efforts to improve our understanding of the effect of bromine and iodine chemistry on tropospheric O3, we call for more models and monitoring studies on halogen chemistry and be considered further in air pollution prevention and control policy.

Spatial Heterogeneity Influences of Environmental Control and Informal Regulation on Air Pollutant Emissions in China.

High air pollutant emissions in China have become serious environmental issues threatening public health. While spatial heterogeneity plays an important role in environmental regulation in China, it is necessary to analyze the spatial heterogeneity influences of air pollution control policies and informal environmental regulation on air pollutant emissions in China. Based on the quantification of air pollution control policies, this paper incorporates the central government’s policy formulation and local government’s policy implementation into the intensity of air pollution control policy. This paper uses the panel data of China’s 30 provinces to examine the spatial impact of air pollution control policy and informal environmental regulation on air pollutant emissions. The results show that (a) air pollutant emissions represented by soot and dust emission intensity has a significant positive spatial spillover effect; (b) air pollution control policy and informal environmental regulation play significant inhibitory roles in air pollutant emissions; (c) informal environmental regulation has a negative moderating effect on the negative relationship between air pollution control policy and air pollutant emissions. Other implications for environmental management have also been discussed.

Investigation of artificial intelligence approaches (ANN-MLP, CAFIS) for the daily prediction of winter air pollutants (CO2, SO2, NOx, O3) in Hamedan city using meteorological data

Recently, several factors such as the physical growth of cities and the increased number of industries and cars, Hamedan city in Iran has faced the issue of air pollution. Due to the increased fuel consumption for heating purposes in the cold winters of this city, the pollution rate is higher in this season. Hamedan is surrounded by Alvand Mountains, which makes the air pollution control policies and air pollution management more important in this city. In the present study, the new methods of artificial neural network and meteorological data were used and compared as a tool for the prediction and warning of air pollution in Hamedan city. Highly accurate methods are available for the prediction of meteorological variables, which provide reliable data for the prediction of air pollution. In order to avoid over-training and assess the network compatibility with the lack of data, the minimum number of the data input data was used in this study. According to the results, the combined approaches of the artificial neural network were applicable in this regard, while ANN-MLP with the momentum learning rule and the TanhAxon transfer function yielded more accurate results compared to CAFIS.

Spatio-temporal variations and trends of major air pollutants in China during 2015-2018.

The Chinese government, as a policy response, has continued to invest efforts and resources to implement cost-effective air pollution control technologies and stringent regulation to reduce emissions from the most contributing sectors to protect the environment and public health. The higher density of monitoring stations (> 1600) distributed across China provides a timely opportunity to use them to study in detail the national pollution trends in light of more stringent air pollution control policies. In the present study, air quality datasets comprising hourly concentrations of PM2.5, O3, NO2, and SO2 collected across 1309, 1341, 1289, and 1347 monitoring stations respectively were obtained from the National Environmental Monitoring Centre over 4years (2015-2018) and trend analysis was performed. Results indicate that the overall annual trends for PM2.5 and SO2 were - 2.9 ± 2.7 and - 3.2 ± 3.2μg/m3/year, while the winter trends were - 4.8 ± 5.8 and - 6.9 ± 8.4μg/m3/year respectively across China. The daily maximum 8-h average (DMA8) ozone concentration showed a significant positive trend of 2.4 ± 4.6μg/m3/year, which was comparatively higher in summer at 4.4 ± 9.0μg/m3/year. On the other side, NO2 trend is not great in number (- 0.45 ± 2.0μg/m3/year). Overall, 62.2%, 61.8%, and 20.9% of PM2.5, SO2, and NO2 monitoring stations were associated with a negative trend of ≥ - 2μg/m3/year. For O3 DMA8 concentrations, 50.7% of the monitoring stations showed a significant positive trend of ≥ 2μg/m3/year. In light of the Chinese government's increasing impetus on combating air pollution and climate change via new policy regulations, it is important to understand the spatio-temporal distributions and relative contributions of the spectrum of gaseous pollutants to the pollution loads as well as identify changing emission loads across sectors. The results of this study will facilitate the formulation of evidence-based air pollution reduction strategies and policies.

Modelling public health benefits of various emission control options to reduce NO2 concentrations in Guangzhou

The local government of the megacity of Guangzhou, China, has established an annual average NO2 concentration target of 40 μg m−3 to achieve by 2020. However, the Guangzhou Ambient Air Quality Compliance Plan does not specify what constitutes compliance with this target. We investigated a range of ambition levels for emissions reductions required to meet different possible interpretations of compliance using a hybrid dispersion and land-use regression model approach. We found that to reduce average annual-mean NO2 concentration across all current monitoring sites to below 40 μg m−3 (i.e. a compliance assessment approach that does not use modelling) would require emissions reductions from all source sectors within Guangzhou of 60%, whilst to attain 40 μg m−3 everywhere in Guangzhou (based on model results) would require all-source emissions reduction of 90%. Reducing emissions only from the traffic sector would not achieve either interpretation of the target. We calculated the impacts of the emissions reductions on NO2-atttributable premature mortality to illustrate that policy assessment based only on assessment against a fixed concentration target does not account for the full public health improvements attained. Our approach and findings are relevant for NO2 air pollution control policy making in other megacities.

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Abstract. Future trends in air pollution and greenhouse gas (GHG) emissions for China are of great concern to the community. A set of global scenarios regarding future socio-economic and climate developments, combining shared socio-economic pathways (SSPs) with climate forcing outcomes as described by the Representative Concentration Pathways (RCPs), was created by the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP–RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China's future anthropogenic emission pathways. The DPEC is designed to integrate the energy system model, emission inventory model, dynamic projection model, and parameterized scheme of Chinese policies. The model contains two main modules, an energy-model-driven activity rate projection module and a sector-based emission projection module. The activity rate projection module provides the standardized and unified future energy scenarios after reorganizing and refining the outputs from the energy system model. Here we use a new China-focused version of the Global Change Assessment Model (GCAM-China) to project future energy demand and supply in China under different SSP–RCP scenarios at the provincial level. The emission projection module links a bottom-up emission inventory model, the Multi-resolution Emission Inventory for China (MEIC), to GCAM-China and accurately tracks the evolution of future combustion and production technologies and control measures under different environmental policies. We developed technology-based turnover models for several key emitting sectors (e.g. coal-fired power plants, key industries, and on-road transportation sectors), which can simulate the dynamic changes in the unit/vehicle fleet turnover process by tracking the lifespan of each unit/vehicle on an annual basis. With the integrated modelling framework, we connected five SSP scenarios (SSP1–5), five RCP scenarios (RCP8.5, 7.0, 6.0, 4.5, and 2.6), and three pollution control scenarios (business as usual, BAU; enhanced control policy, ECP; and best health effect, BHE) to produce six combined emission scenarios. With those scenarios, we presented a wide range of China's future emissions to 2050 under different development and policy pathways. We found that, with a combination of strong low-carbon policy and air pollution control policy (i.e. SSP1-26-BHE scenario), emissions of major air pollutants (i.e. SO2, NOx, PM2.5, and non-methane volatile organic compounds – NMVOCs) in China will be reduced by 34 %–66 % in 2030 and 58 %–87 % in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play a more important role in continuous emission reduction until 2050. In contrast, China's emissions will remain at a high level until 2050 under a reference scenario without active actions (i.e. SSP3-70-BAU). Compared to similar scenarios set from the CMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates of emission ranges are much lower than the estimates from the harmonized CMIP6 emissions dataset in 2020–2030, but their emission ranges become similar in the year 2050.

Ratio of PM2.5 to PM10 Mass Concentrations in Beijing and Relationships with Pollution from the North China Plain

Five years of PM2.5/PM10 ratios and their potential relationships with wind and relative humidity (RH) were analyzed for three areas in Beijing (northwestern mountainous area, urban area and southern suburbs), and these values were compared with those of five other cities, including Tianjin, Dalian, Hangzhou, Shanghai and Guangzhou. In the past five years, both PM2.5 and PM10 mass concentrations have decreased over the three Beijing regions, particularly during winters. The PM2.5/PM10 ratios have distinct seasonal characteristics, with more frequent high ratios in winter than in other seasons. The high ratio frequency decrease is most evident in winter and in the southern Beijing suburbs. This fine particle proportion decrease is related to air pollution control policies, including the national project ‘Coal to Gas’. High PM2.5/PM10 ratios are linked to heavy pollution levels and low wind speeds, indicating the importance of PM2.5 accumulation during pollution events in Beijing. The higher PM2.5/PM10 ratios in Beijing are also closely related to southerly winds and high humidity, indicating the contribution of anthropogenic pollution transported from the south. Due to similar geographic environments, Tianjin is similar to Beijing in terms of the frequency distribution characteristics of the PM2.5/PM10 ratios. The coastal city of Dalian is further north and not similar to Beijing or Tianjin, owing to a sea breeze influence. Different from Beijing and Tianjin, the southern cities of Hangzhou, Shanghai and Guangzhou show almost no change in the PM2.5/PM10 ratio frequency distribution with increases in wind speed and relative humidity.

High-resolution assessment of ammonia emissions in China: Inventories, driving forces and mitigation

Atmospheric ammonia (NH3) is a major air pollutant. China is a global hotspot of NH3 emissions and, as a consequence, comprehensive and high-resolution temporal and spatial assessments and mitigation potential of NH3 emissions are particularly important for the environment, human and ecosystem health. This study demonstrates that national NH3 emissions in China have increased by 102% from 1978 to 2017. Cropland was the major emitter accounting for 38–52% of the emissions, followed by livestock and waste disposal. These three sources accounted for approximately 80% of total emissions nationwide over the past four decades. NH3 hotspots (NH3 emission densities > 5 Mg N km−2 yr−1) were scattered in the Bohai Rim region, North China Plain, the Middle and Lower Yangtze River and the southeast coast in 1978. By 2017, the hotspots had expanded to a larger area of the North China Plain, the Middle and Lower Yangtze River and the Sichuan Basin. In 1978, these hotspots occupied about 2% the land area and contributed to about 46% of total NH3 emissions. By 2017, the hotspots expanded to about 12% of the land area and contributed to more than 70% of the emissions. This study also performed the driving force analysis and found that the population growth had a crucial impact on NH3 emissions with an annual contribution degree of 183%, while the per capita GDP and the urbanization were negatively correlated with NH3 emissions. The analysis of six mitigation scenarios indicates that adopting measures from the production side (including larger farm size, 4 R nutrient stewardship, low emission housing and waste treatment tail gas management) will generate 10–15% reduction potential, whereas encouraging healthy and reasonable diet scenario will reduce 26% by 2030. These findings substantially improve our understanding on NH3 emissions and have implications for air pollution control strategies and policy measures.

Occurrence and sources of chromophoric organic carbon in fine particulate matter over Xi'an, China

Understanding the characteristics and sources of atmospheric chromophores is essential to assess their impact on climate change and the quality of atmospheric environment. In this work, the fine particulate matter (PM2.5) samples of Xi'an, China in 2017 were analyzed by excitation-emission matrices and parallel factor analysis (EEM-PARAFAC) method to obtain the species, content, sources and seasonal variation characteristics of atmospheric chromophores. The results showed that humic-like (HULIS) chromophores and polycyclic aromatic hydrocarbons-like (PAHs-like) chromophores were the most abundant chromophores in the samples, accounting for 42% and 33%, respectively. With the aggravation of air pollution, the relative content of low-polarity chromophores increased markedly, while the relative content of polar chromophores decreased. The concentrations of atmospheric chromophores exhibited obvious seasonal variation characteristics: high in winter and low in summer. Similarly, the relative contributions of atmospheric chromophores from each source varied with the season. In addition, special weather and human activities had a significant influence on the source of atmospheric chromophores. Dust source was an important source of atmospheric chromophores, which was susceptible to long-range incoming air masses from northwestern regions in spring. However, the chromophores from the dust source were easily removed by wet precipitation, which was the same as the chromophores from the combustion source. The chromophores from the combustion source were susceptible to human activities. The contribution of combustion source to atmospheric chromophores was reduced due to the implementation of air pollution control policies during the Chinese Spring Festival. In summer, the formation of photochemical secondary chromophores was more significant than in other seasons, and the photochemical secondary chromophores increased due to the formation of liquid phase reactions under high relative humidity conditions.

Source apportionment for online dataset at a megacity in China using a new PTT-PMF model

Abstract Air pollution negatively impact human health and the environment. Source apportionment is an important research method for designing effective air pollution control policies. In this study, a new PTT-PMF (Partial Target Transformation-Positive matrix factor) source apportionment method (based on Multilinear Engine 2 program) was developed, to better recognize the extracted source categories, for online dataset. By incorporating measured source profiles, this model can automatically extract factors that have physical significance and close to actual source profiles. The accuracy of the PTT-PMF method was first evaluated by using several artificial datasets, and the results were favorable. Results of the new model can better explain similar sources such as dust and coal combustion (when lack of markers such as Ai and Si), comparing with the base run obtained using PMF. Then, this model was applied to online measurement data collected in Tianjin, China. Six factors were obtained and they were close to actual source profiles: dust (6.06%), coal combustion (4.70%), secondary sulfate sources (26.36%), secondary nitrate sources (42.91%), vehicle exhaust (9.97%) and biomass burning & SOC (10.01%). Time series of source contributions can also help to identify the source categories. The work presented here may advance receptor modelling techniques and could also enhance the validity of source apportionment results.

A Study of China's Air Pollution Prevention and Control Policy Framework from a Policy Instrument Perspective

Environmental pollution caused by rapid economic development like that seen in China over the past twenty years poses various threats to human health. People have started to place much more of an emphasis on environmental security, working to find a balance between sustainability and economic growth. In recent years, air pollution has emerged as a highly discussed topic of social and environmental relevance in China, due in part to persistent smog that affects everyday life and causes serious harm to human health. Although air pollution is normally associated with human activity, is can be caused by natural processes such as eruptions and forest fires, but is always characterized by the release of certain substances into the atmosphere which, when present in certain concentrations or for given durations, can harm human health, daily life, productivity, and other aspects. In humans, it mainly affects the respiratory system, notably the lungs, as well as the immune system. A series of studies both in China and overseas have shown, in certain cases, even low concentrations of air pollution can pose a great threat to human health. In this study, we conducted an analysis of air quality policies, focusing on the 2018 revision of the People's Republic of China's Law on the Prevention and Control of Air Pollution (LPCAP). We utilized the content analysis method and Strauss and Corbin's grounded theory to construct a policy framework, demarcate analysis units, code and classify policy texts, determine descriptive statistics, and analyze dimensional interactions. We used two dimensions (basic policy instruments classified as demand-, supply-, and environment-side; and air carrying capacity) to quantify and analyze the LPCAP, which enabled us to analyze the deficiencies and conflicts within policy instruments. The results show a higher utilization frequency of environment-side policy instruments, particularly regulation management and strategic measures. This reflects efforts by the government to create a favorable environment for improving air quality. Additionally, supply-side policy instruments are used far less frequently than environment-side policy instruments. Air quality legal policies and pollution control measures mainly consist of environment-side policy instruments; ecological thinking and air quality policies that are based mainly on supply-side and environment-side policy instruments; and social coordination policies that mainly use environment-side policy instruments. Based on the results of this study, we recommend an increase in the number of supply- and demand-side policy instruments, particularly the latter which includes promoting ecological thinking amongst citizens, to optimize and improve air pollution prevention and control policies.

Analyses of air pollution control measures and co-benefits in the heavily air-polluted Jinan city of China, 2013\u20132017

China has made great efforts in air pollution control since 2013. However, there is a lack of evaluation of environmental, health and economic co-benefits associated with the national and local air pollution control measures at a city level. We analyzed local air pollution control policies and implementation in Jinan, one of the most heavily air-polluted cities in China between 2013 and 2017. We assessed the changes in exhaust emissions, air quality, mortality and morbidity of associated specific-diseases, and related economic benefits. We also projected the future scenarios of PM2.5 concentration dropped to 15 μg/m3. There were significant decreases in exhaust emissions of SO2 and NOx in Jinan during the study period. Annual reductions in ambient air pollution were 72.6% for SO2, 43.1% for PM2.5, and 34.2% for PM10. A total of 2,317 (95%CI: 1,533–2,842) premature deaths and 15,822 (95%CI: 8,734–23,990) related morbidity cases had been avoided in 2017, leading to a total of US$ 317.7 million (95%CI: 227.5–458.1) in economic benefits. Decreasing PM2.5 concentrations to 15 μg/m3 would result in reductions of 70% in total PM2.5-related non-accidental mortality and 95% in total PM2.5-related morbidity, which translates into US$ 1,289.5 million (95%CI: 825.8–1,673.6) in economic benefits. The national and local air pollution control measures have brought significant environmental, health and economic benefits to a previously heavy polluted Chinese city.

Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China

Fine particulate matter (PM2.5) pollution has become a worldwide environmental concern because of its adverse impacts on human health. This study aimed to explore the spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing during the 2013–2018 period, and further analyzed the impacts of environmental protection policies implemented in recent years. Notably, this study employed various statistical methods, i.e., ordinary Kriging interpolation, spatial autocorrelation analysis, time-series analysis and the Bonferroni test, to evaluate the regional and seasonal differences of PM2.5 concentrations based on long-term monitoring data. The results illustrated that PM2.5 concentrations decreased on a yearly basis, demonstrating that air pollution control policies have achieved initial success. Furthermore, PM2.5 concentrations were higher in the winter and in the southern regions. Diurnal variation presented a bimodal distribution, which varied slightly with the season. Relative humidity and wind speed were the principal meteorological factors affecting the distribution of PM2.5 concentrations, while precipitation had essentially no effect. A high positive correlation between PM2.5 and gaseous pollutants (SO2, NO2, and CO) indirectly reflected the contribution of automobile exhaust and coal-fired emissions. Generally, PM2.5 concentrations demonstrated strong spatiotemporal variations, and meteorological factors and pollutant emissions played an important role in this.

Research on Air Pollution Control in China: From the Perspective of Quadrilateral Evolutionary Games

By constructing a quadrilateral evolutionary game model involving the central government, local governments, polluting enterprises, and the public, this paper attempts to comprehensively analyze the development and implementation of China’s air pollution control policies. Through the quadrilateral evolutionary game model, this paper systematically studies the evolutionary stable strategies of the four parties involved and obtains 27 equilibrium points, strategy sets, and their corresponding policy performance with the help of the four-dimensional dynamic system. The research results show that there are five equilibrium points that represent the least ideal scenarios, 14 equilibrium points that represent the less than ideal scenarios, four equilibrium points that represent the ideal scenarios, three equilibrium points that represent the more than ideal scenarios, and one equilibrium point that represents the most ideal scenarios. By analyzing the eight equilibrium points that represent the ideal, more than ideal and most ideal scenarios, especially the four stable points, this paper has obtained the conditions as well as policy implications of the four stable points in China’s air pollution control campaign.

Spatiotemporal trends of PM2.5 concentrations in central China from 2003 to 2018 based on MAIAC-derived high-resolution data

Long-term PM2.5 levels with high precision at fine spatiotemporal resolution are essential for quantitatively understanding the health risk of exposure to ambient fine particulate matter (PM2.5) and making effective air pollution control policies. The emerging statistically derived PM2.5 estimations from satellite remote sensing observations of aerosol optical depth (AOD) data are an effective alternative to reconstruct global, long-term, high spatiotemporal resolution PM2.5 information. However, studies on PM2.5 estimation and its application to exposure and health-related studies are limited in China due to the lack of historical in-situ measurements before 2013. In this study, we explored the long-term trends of PM2.5 exposure in central China, a hotspot that has recently been experiencing severe particulate pollution, at the local scale. We first developed a spatiotemporal model incorporating periodical characteristics within the data to estimate daily concentrations of historical PM2.5 at a fine scale of 1 km for 2003–2018. The linear effects of predictors including AOD, meteorological and land-use parameters and the non-linear interaction between AOD and meteorological parameters were considered in the modeling process. The most recently released high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction (MAIAC) was used to help to represent the fine-scale particle gradients. Our daily estimates correlated well with in-situ observations (cross-validation R2 = 0.59), achieving precision comparable to previous statistical models. Through linking with gridded demographic data, the population-weighted PM2.5 average during 2003 to 2018 was found to be high (62.23 μg/m3 for the whole domain) with obvious spatial variations and seasonality. An inverse U pattern was seen in the time series, with two inflection points around 2008 and 2015. Our model provides reliable particulate information with high spatial resolution and long-term temporal coverage, which can inform local-scale PM2.5-related epidemiological studies and health-risk assessments for central China.

Characteristics of Polycyclic Aromatic Hydrocarbons (PAHs) and Common Air Pollutants at Wajima, a Remote Background Site in Japan.

Background: Background sites are mainly affected by long-range-transported air pollutants, resulting in potential adverse effects on local atmospheric environments. A 4–5 year observational study was conducted to illustrate the air pollution profile at the Kanazawa University Wajima air monitoring station (KUWAMS), an ideal remote background site in Japan. Methods: Nine polycyclic aromatic hydrocarbons (PAHs) in the particulate phase and various air pollutants were continuously monitored for 4–5 years. Diagnostic ratios of PAHs and back-trajectory analysis were applied to trace the possible sources of the air pollutants collected at the sampling site. Results: The atmospheric concentration of PAHs in the atmosphere at the site decreased from 2014 to 2019, benefit from the predominant air pollution control policy in China and Japan. Common air pollutants including sulfur dioxide (SO2), nitrogen oxides (NOx), ozone, methane (CH4), and non-methane hydrocarbon (NMHC) were detected in low concentrations from 2016 to 2019, while ozone (O3) and particulate matter (PM2.5, PM with a diameter less than 2.5 μm) were present in high levels that exceeded the Japanese standards. Most air pollutants peaked in spring and showed evident diurnal variations in spring and summer. Conclusions: This is the first study to clarify the atmospheric behaviors of multiple air pollutants at a background site in Japan. Significant external air pollutant impact and unneglectable air pollution were demonstrated at KUWAMS, indicating the importance of studying atmospheric pollution at remote sites.

Using CESM-RESFire to understand climate–fire–ecosystem interactions and the implications for decadal climate variability

Abstract. Large wildfires exert strong disturbance on regional and global climate systems and ecosystems by perturbing radiative forcing as well as the carbon and water balance between the atmosphere and land surface, while short- and long-term variations in fire weather, terrestrial ecosystems, and human activity modulate fire intensity and reshape fire regimes. The complex climate–fire–ecosystem interactions were not fully integrated in previous climate model studies, and the resulting effects on the projections of future climate change are not well understood. Here we use the fully interactive REgion-Specific ecosystem feedback Fire model (RESFire) that was developed in the Community Earth System Model (CESM) to investigate these interactions and their impacts on climate systems and fire activity. We designed two sets of decadal simulations using CESM-RESFire for present-day (2001–2010) and future (2051–2060) scenarios, respectively, and conducted a series of sensitivity experiments to assess the effects of individual feedback pathways among climate, fire, and ecosystems. Our implementation of RESFire, which includes online land–atmosphere coupling of fire emissions and fire-induced land cover change (LCC), reproduces the observed aerosol optical depth (AOD) from space-based Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products and ground-based AErosol RObotic NETwork (AERONET) data; it agrees well with carbon budget benchmarks from previous studies. We estimate the global averaged net radiative effect of both fire aerosols and fire-induced LCC at -0.59±0.52 W m−2, which is dominated by fire aerosol–cloud interactions (-0.82±0.19 W m−2), in the present-day scenario under climatological conditions of the 2000s. The fire-related net cooling effect increases by ∼170 % to -1.60±0.27 W m−2 in the 2050s under the conditions of the Representative Concentration Pathway 4.5 (RCP4.5) scenario. Such considerably enhanced radiative effect is attributed to the largely increased global burned area (+19 %) and fire carbon emissions (+100 %) from the 2000s to the 2050s driven by climate change. The net ecosystem exchange (NEE) of carbon between the land and atmosphere components in the simulations increases by 33 % accordingly, implying that biomass burning is an increasing carbon source at short-term timescales in the future. High-latitude regions with prevalent peatlands would be more vulnerable to increased fire threats due to climate change, and the increase in fire aerosols could counter the projected decrease in anthropogenic aerosols due to air pollution control policies in many regions. We also evaluate two distinct feedback mechanisms that are associated with fire aerosols and fire-induced LCC, respectively. On a global scale, the first mechanism imposes positive feedbacks to fire activity through enhanced droughts with suppressed precipitation by fire aerosol–cloud interactions, while the second one manifests as negative feedbacks due to reduced fuel loads by fire consumption and post-fire tree mortality and recovery processes. These two feedback pathways with opposite effects compete at regional to global scales and increase the complexity of climate–fire–ecosystem interactions and their climatic impacts.

Spatiotemporal Variations and Contributing Factors of Air Pollutant Concentrations in Malaysia during Movement Control Order due to Pandemic COVID-19

The restriction of daily and economic-related activities due to COVID-19 pandemic via lockdown order has been reported to improve air quality. This study evaluated temporal and spatial variations of four major air pollutant concentrations across Malaysia before (March 4, 2020–March 17, 2020) and during the implementation of different phases of Movement Control Order (MCO) (March 18, 2020–May 12, 2020) from 65 official regulatory air quality stations. Results showed that restriction in daily and economic activities has remarkably reduced the air quality in all sub-urban, urban, and industrial settings with relatively small contributions from meteorological conditions. Overall, compared to before MCO, average concentrations of PM2.5, CO, and NO2 reduced by 23.1%, 21.74%, and 54.0%, respectively, while that of SO2 was constant. The highest reduction of PM2.5, CO, and NO2 were observed in stations located in urban setting, where 63% stations showed significant reduction (p < 0.05) for PM2.5 and CO, while all stations showed significant reduction in NO2 concentrations. It was also revealed that 70.5% stations recorded lower concentrations of PM2.5 during MCO compared to before MCO, despite that high numbers of local hotspots were observed simultaneously from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). Spatial analysis showed that the northern part of Peninsular had the highest significant reduction of PM2.5, while the highest of NO2 and CO reduction were found in stations located in the central region. All pollutants exhibit similar diurnal trends when compared between pre- and during MCO although significant lower readings were observed during MCO. This study gives confidence to regulatory body; the enforcement of strict air pollution prevention and control policies could help in reducing pollution.

Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM2.5 Concentration in China's Inland Cities: A Case Study from Chengdu Plain Economic Zone.

Particulate matter with a diameter less than 2.5 µm (PM2.5), one of the main sources of air pollution, has increasingly become a concern of the people and governments in China. Examining the socioeconomic factors influencing on PM2.5 concentration is important for regional prevention and control. Previous studies mainly concentrated on the economically developed eastern coastal cities, but few studies focused on inland cities. This study selected Chengdu Plain Economic Zone (CPEZ), an inland region with heavy smog, and used spatial econometrics methods to identify the spatiotemporal distribution characteristics of PM2.5 concentration and the socioeconomic factors underlying it from 2006 to 2016. Moran’s index indicates that PM2.5 concentration in CPEZ does have spatial aggregation characteristics. In general, the spatial clustering from the fluctuation state to the stable low state decreased by 1% annually on average, from 0.190 (p < 0.05) in 2006 to 0.083 (p < 0.1) in 2016. According to the results of the spatial Durbin model (SDM), socioeconomic factors including population density, energy consumption per unit of output, gross domestic product (GDP), and per capita GDP have a positive effect on PM2.5 concentration, while greening rate and per capita park space have a negative effect. Additionally, those factors have identified spatial spillover effects on PM2.5 concentration. This study could be a reference and support for the formulation of more efficient air pollution control policies in inland cities.