China's air pollution control policies during the 12th Five Year Plan (2011–2015) are characterized by the targets of 10% nitrogen oxides (NOx) reduction and 8% sulfur dioxide (SO2) reduction from ...the 2010 levels. In this study, the Community Multi-scale Air Quality (CMAQ) modeling system was used to evaluate the impact of only SO2, only NOx, and joint SO2/NOx control measures on particulate matter pollution, the greatest concern for urban air quality in China. Four emission scenarios were developed for 2015, including a business-as-usual scenario, a reference NOx control scenario based on the governmental plan, an accelerated NOx control technology scenario, and a scenario assuming joint controls of NOx and SO2 based on the governmental plan. Under the planned NOx control measures, the annual mean concentrations of particulate matter less than or equal to 2.5 μm (PM2.5) decline by 1.5–6 μg m−3, i.e. 1.6%–8.5%, in the majority of eastern China. The largest reduction occurs in the middle reach of the Yangtze River. Under accelerated NOx control measures, the annual average PM2.5 concentration reductions (compared with the business-as-usual scenario) in eastern China are 65% higher than the reductions under planned control measures. The unusual increase of PM2.5 concentrations in the North China Plain and the Yangtze River Delta during January after the reductions of NOx emissions was an integrated effect of excessive NOx, the ammonia-rich inorganic aerosol chemistry, and the non-methane volatile organic compounds (NMVOC) sensitive photochemical regime. Under the joint controls of NOx and SO2, the annual mean PM2.5 concentrations decline over 3 μg m−3, i.e. 3.2%–13%, in the majority of eastern China, and some areas in the middle reach of the Yangtze River have reductions as large as 6–8.3 μg m−3, i.e. 5.0%–13%. The average PM2.5 concentration reductions in eastern China are 1.20 μg m−3, 3.14 μg m−3, 3.57 μg m−3, 4.22 μg m−3 in January, May, August, and November, respectively. The corresponding declining rates are 2.3%, 12.2%, 14.3%, and 8.1%, respectively. More stringent policies should be implemented in winter to reduce the heavy pollution periods. The annual average PM2.5 concentration reductions in three major city clusters are comparable with the average reductions of eastern China. Stringent regional control policies are required for the significant improvement of particulate air quality in major city clusters.
•The effects of China's NOx and SO2 control policies on PM pollution are assessed.•NOx and SO2 emissions in 2015 decrease by 23.4% and 18.9% from baseline projection.•Annual PM2.5 concentration declines 1.5–6 μg m−3 under national NOx control policy.•Annual PM2.5 concentration declines 3–8.3 μg m−3 under joint NOx and SO2 controls.•Current policies are not enough to improve the air quality in key regions of China.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
•Three types of data (CMAQ, ML-MMF, and ML) were employed to examine O3 responses to local NOx and VOC emissions.•Although the ML model showed significant improvement in the benchmark case, the ML ...predictions present a distorted O3 response to emissions compared with ML-MMF predictions.•The ML-MMF O3 isopleths emphasize the impact of transboundary pollution on the local O3 sensitivity.•Using data without support from CMAQ to forecast the air quality could mislead the controlled targets and future trends.
Current machine learning (ML) applications in atmospheric science focus on forecasting and bias correction for numerical modeling estimations, but few studies examined the nonlinear response of their predictions to precursor emissions. This study uses ground-level maximum daily 8-hour ozone average (MDA8 O3) as an example to examine O3 responses to local anthropogenic NOx and VOC emissions in Taiwan by Response Surface Modeling (RSM). Three different datasets for RSM were examined, including the Community Multiscale Air Quality (CMAQ) model data, ML-measurement-model fusion (ML-MMF) data, and ML data, which respectively represent direct numerical model predictions, numerical predictions adjusted by observations and other auxiliary data, and ML predictions based on observations and other auxiliary data.
The results show that both ML-MMF (r = 0.93–0.94) and ML predictions (r = 0.89–0.94) present significantly improved performance in the benchmark case compared with CMAQ predictions (r = 0.41–0.80). While ML-MMF isopleths exhibit O3 nonlinearity close to actual responses due to their numerical base and observation-based correction, ML isopleths present biased predictions concerning their different controlled ranges of O3 and distorted O3 responses to NOx and VOC emission ratios compared with ML-MMF isopleths, which implies that using data without support from CMAQ modeling to predict the air quality could mislead the controlled targets and future trends. Meanwhile, the observation-corrected ML-MMF isopleths also emphasize the impact of transboundary pollution from mainland China on the regional O3 sensitivity to local NOx and VOC emissions, which transboundary NOx would make all air quality regions in April more sensitive to local VOC emissions and limit the potential effort by reducing local emissions.
Future ML applications in atmospheric science like forecasting or bias correction should provide interpretability and explainability, except for meeting statistical performance and providing variable importance. Assessment with interpretable physical and chemical mechanisms and constructing a statistically robust ML model should be equally important.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Hebei has been recognized as one of the most polluted provinces in China, characterized by extremely high concentrations of fine particulate matter (PM2.5) in many of its cities, especially those ...located in the southern area of the province and highly potentially northward transported to Beijing. Source apportionment of PM2.5 is the basis and prerequisite of an effective control strategy. In this study, the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality (CMAQ) modeling system are applied to East Asia and North China at 36- and 12-km horizontal grid resolutions, and the source apportionment of PM2.5 in the three top polluted cities in Hebei, i.e., Shijiazhuang, Xingtai, and Handan, is performed using the Brute-Force method. It is concluded that the regional source contributions to PM2.5 are 27.9% in Shijiazhuang, 46.6% in Xingtai, and 40.4% in Handan. The major local contributors are industrial, domestic and agricultural sources in all the three cities with the contributions of 39.8%, 15.8%, and 10.6% in Shijiazhuang, 30.5%, 13.6%, and 6.9% in Xingtai, 35.9%, 13.5%, and 6.2% in Handan, respectively. As to the secondary aerosols of sulfate (SO42−), nitrate (NO3−), and ammonium (NH4+) in PM2.5, which are important chemical species in PM2.5 (about 30–40% in PM2.5) and cannot be further apportioned by receptor models, the regional source contributions to the total concentrations of SO42−, NO3−, and NH4+ are 40.9%, 62.0%, and 59.1% in Shijiazhuang, Xingtai, and Handan, respectively. The local industrial, domestic and agricultural contributions to those are 23.7%, 6.6%, and 29.8% in total in Shijiazhuang, 17.5%, 5.0%, and 17.7% in Xingtai, and 20.6%, 4.8%, and 17.8% in Handan, respectively. The regional joint controls of air pollution are more important in Xingtai and Handan than in Shijiazhuang, and the emission controls of agricultural sources need to be further considered in the future policy.
•PM2.5 source apportionment is pursued over the top three polluted cities in China (Shijiazhuang, Xingtai, and Handan).•Regional contributions play a non-negligible role in the three cities.•Spatial and sectoral contributions to the secondary species in PM2.5 are quantified.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
PM2.5 with its major chemical components were measured and analyzed during a concurrent haze in Jan. 1–19, 2013 at three sites (Shanghai, Beijing, and Huaniao, a remote isle over the East China Sea) ...to probe the sources and formation process of such a severe haze over three typical regions in China. The mean PM2.5 concentrations during the severely polluted days reached 180.8 μg m−3, 299.2 μg m−3, and 131.1 μg m−3 in Shanghai, Beijing, and the Huaniao Isle, respectively. The mass ratio of the sum of SO42−, NO3−, and NH4+ to PM2.5 were over 1/3 during the polluted days at all the three sites. Promoted gas-to-particle transformations from acidic SO2 and NOx to SO42− and NO3− under high relative humidity conditions played a major role in the formation of this severe haze. Significant contribution of traffic emissions to the haze formation over China was suggested to be one of the major sources in triggering the heavy haze over China. Specifically, there was a more contribution from traffic in Shanghai than in Beijing as indicated by the higher NO3−/SO42− ratio in Shanghai. In Beijing, the enhanced coal combustion for winter heating along with the traffic emission was suggested to be the major two sources of this haze episode. Typical pollution elements such as As, Cd, and Pb as well as Cl− and K+ were substantially enhanced in the severely polluted days. Although the Huaniao Isle is located in the remote oceanic area as a background site, pollution elements, secondary ions, and K+ all increased substantially during the polluted days. As visualized by the backward air mass trajectories associated with the potential source region identification technique, air masses that passed over Northern China and Yangtze River Delta evidently invaded the offshore areas of Eastern China. The ratios of As, Cd, Cu, Zn, and K+ to Al at the Huaniao Isle were closer to those of Beijing rather than Shanghai, indicating that the marine aerosol over the East China Sea had been significantly polluted via the long-range transport of anthropogenic pollutants originating from Northern China.
•Contrasting characteristics of aerosol at three regions in a severe haze event.•First observation of aerosol over East China Sea impacted by inland emissions.•Important role of vehicular emission in triggering the heavy haze.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
COVID-19 pandemic had expanded to the US since early 2020 and has caused nationwide economic loss and public health crisis. Until now, although the US has the most confirmed cases in the world and ...are still experiencing an increasing pandemic, several states insisted to re-open business activities and colleges while announced strict control measures. To provide a quantitative reference for official strategies, predicting the near future trend based on finer spatial resolution data and presumed scenarios are urgently needed. In this study, the first attempted COVID-19 case predicting model based on county-level demographic, environmental, and mobility data was constructed with multiple machine learning techniques and a hybrid framework. Different scenarios were also applied to selected metropolitan counties including New York City, Cook County in Illinois, Los Angeles County in California, and Miami-Dade County in Florida to assess the impact from lockdown, Phase I, and Phase III re-opening.
Our results showed that, for selected counties, the mobility decreased substantially after the lockdown but kept increasing with an apparent weekly pattern, and the weekly pattern of mobility and infections implied high infections during the weekend. Meanwhile, our model was successfully built up, and the scenario assessment results indicated that, compared with Phase I re-opening, a 1-week and a 2-week lockdown could reduce 4%–29% and 15%–55% infections, respectively, in the future week, while 2-week Phase III re-opening could increase 16%–80% infections. We concluded that the mandatory orders in metropolitan counties such lockdown should last longer than one week, the effect could be observed. The impact of lockdown or re-opening was also county-dependent and varied with the local pandemic. In future works, we expect to involve a longer period of data, consider more county-dependent factors, and employ more sophisticated techniques to decrease the modeling uncertainty and apply it to counties nationally and other countries.
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•County-level data were used to build up the COVID-19 prediction model by a machine learning hybrid framework.•Weekly pattern of mobility and infections proved the incubation days is 4-5 days and high infections on the weekend.•Compared with Phase I re-open, a 1-week and a 2-week lockdown can reduce 4-29% and 15-55% infections in the future week.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Ammonia (NH3) is one important precursor of inorganic fine particles; however, knowledge of the impacts of NH3 emissions on aerosol formation in China is very limited. In this study, we have ...developed China’s NH3 emission inventory for 2005 and applied the Response Surface Modeling (RSM) technique upon a widely used regional air quality model, the Community Multi-Scale Air Quality Model (CMAQ). The purpose was to analyze the impacts of NH3 emissions on fine particles for January, April, July, and October over east China, especially those most developed regions including the North China Plain (NCP), Yangtze River delta (YRD), and the Pearl River delta (PRD). The results indicate that NH3 emissions contribute to 8–11% of PM2.5 concentrations in these three regions, comparable with the contributions of SO2 (9–11%) and NO x (5–11%) emissions. However, NH3, SO2, and NO x emissions present significant nonlinear impacts; the PM2.5 responses to their emissions increase when more control efforts are taken mainly because of the transition between NH3-rich and NH3-poor conditions. Nitrate aerosol (NO3 –) concentration is more sensitive to NO x emissions in NCP and YRD because of the abundant NH3 emissions in the two regions, but it is equally or even more sensitive to NH3 emissions in the PRD. In high NO3 – pollution areas such as NCP and YRD, NH3 is sufficiently abundant to neutralize extra nitric acid produced by an additional 25% of NO x emissions. The 90% increase of NH3 emissions during 1990–2005 resulted in about 50–60% increases of NO3 – and SO4 2‑ aerosol concentrations. If no control measures are taken for NH3 emissions, NO3 – will be further enhanced in the future. Control of NH3 emissions in winter, spring, and fall will benefit PM2.5 reduction for most regions. However, to improve regional air quality and avoid exacerbating the acidity of aerosols, a more effective pathway is to adopt a multipollutant strategy to control NH3 emissions in parallel with current SO2 and NO x controls in China.
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IJS, KILJ, NUK, PNG, UL, UM
Human activities and population growth have increased the natural burden of reactive nitrogen (N) in the environment. Excessive N deposition on Earth’s surface leads to adverse feedbacks on ...ecosystems and humans. Similar to that of air pollution, emission control is recognized as an efficient means to control acid deposition. Control of nitrogen oxides (NOₓ = NO + NO₂) emissions has led to reduction in deposition of oxidized nitrogen (NOy, the sum of all oxidized nitrogen species, except nitrous oxide N₂O). Reduced forms of nitrogen (NHₓ = ammonia NH₃ + ammonium NH₄⁺) deposition have, otherwise, increased, offsetting the benefit of reduction in NOy deposition. Stringent control of NH₃ emissions is being considered. In this study, we assess the response of N deposition to N emission control on continental regions. We show that significant reduction of NHₓ deposition is unlikely to be achieved at the early stages of implementing NH₃ emission abatement. Per-unit NH₃ emission abatement is shown to result in only 60–80% reduction in NHₓ deposition, which is significantly lower than the demonstrated 80–120% benefit of controlling NOₓ emissions on NOy deposition. This 60–80% effectiveness of NHₓ deposition reduction per unit NH₃ emission abatement reflects, in part, the effects of simultaneous reductions in NOₓ and SO₂ emissions.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
This study integrates data from regional model simulations, reanalysis data set, radiosonde observations, lidar measurements, and satellite products to evaluate the direct radiative forcing effect of ...biomass burning and dust over East Asia. During March and April, we find an overall cooling effect of the dust of −5 to −9 W/m2. Biomass burning aerosols from Peninsular Southeast Asia exhibit a warming effect of 5–10 W/m2 over the source area, lower than that over the downwind area of 10–20 W/m2 because of significantly higher cloud coverage in South China. Dust and biomass burning aerosols are found to cool the near surface layer (0–1 km) by −0.5 and −0.3 K, respectively, and warm the upper air (1–5 km) by +0.1 and +0.2 K, respectively. In Taipei, simultaneous presences of dust and biomass burning lead to cooling of near‐surface air by −1.5 K and warming of upper air by +1 K.
Plain Language Summary
Biomass burning and dust are the largest natural emission sources of atmospheric aerosol. However, no solid consensus exists regarding whether biomass burning or dust contributes to a net warming or cooling effect. This study integrates data from regional climate model simulations, reanalysis data, radiosonde observations, lidar measurements, and satellite products to evaluate the climate effects of biomass burning and dust at a regional scale over East Asia. We find prominent warming effects by biomass burning in Peninsular Southeast Asia, which is more significant over the downwind area in South China than over the emission source area. Dust exhibits cooling effects, with a few exceptions over areas covered by semipersistent snow or ice. We also reveal that under conditions in which both biomass burning and dust aerosols are present, they exhibit an overall slight warming effect.
Key Points
Peninsular Southeast Asia biomass burning shows larger warming effect (10‐20 W/m2) over downwind region than over the source area (5‐10 W/m2)
Dust shows a cooling effect of up to ‐9 W/m2 with a few exceptions along north and east edges of Tibet Plateau due to snow or ice cover
Dust and biomass burning cool the near surface air and warm the upper air, and their radiative efficiencies decrease during transport
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Forests are an important biome that covers about one third of the global land surface and provides important ecosystem services. Since atmospheric deposition of nitrogen (N) can have both beneficial ...and deleterious effects, it is important to quantify the amount of N deposition to forest ecosystems. Measurements of N deposition to the numerous forest biomes across the globe are scarce, so chemical transport models are often used to provide estimates of atmospheric N inputs to these ecosystems. We provide an overview of approaches used to calculate N deposition in commonly used chemical transport models. The Task Force on Hemispheric Transport of Air Pollution (HTAP2) study intercompared N deposition values from a number of global chemical transport models. Using a multi-model mean calculated from the HTAP2 deposition values, we map N deposition to global forests to examine spatial variations in total, dry and wet deposition. Highest total N deposition occurs in eastern and southern China, Japan, Eastern U.S. and Europe while the highest dry deposition occurs in tropical forests. The European Monitoring and Evaluation Program (EMEP) model predicts grid-average deposition, but also produces deposition by land use type allowing us to compare deposition specifically to forests with the grid-average value. We found that, for this study, differences between the grid-average and forest specific could be as much as a factor of two and up to more than a factor of five in extreme cases. This suggests that consideration should be given to using forest-specific deposition for input to ecosystem assessments such as critical loads determinations.
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•Deposition to forest biomes is estimated with global chemical transport models.•Grid-average total nitrogen deposition to global forests is about 19 Tg N yr−1.•Global forest-specific deposition is 12% higher than the grid-average value.•Regionally, forest-specific deposition is up to 2 times higher than grid-average values.•Forest-specific deposition are important to evaluate critical load exceedances.
Estimates of nitrogen deposition to global forests by global models may be a factor of 2 or more higher if the forest-specific deposition is used, compared to the grid cell average value and is on average 12% higher for all global forests.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
A direct and quantitative linkage of air pollution-related health effects to emissions from different sources is critically important for decision-making. While a number of studies have attributed ...the PM2.5-related health impacts to emission sources, they have seldom examined the complicated nonlinear relationships between them. Here we investigate the nonlinear relationships between PM2.5-related premature mortality in the Beijing-Tianjin-Hebei (BTH) region, one of the most polluted regions in the world, and emissions of different pollutants from multiple sectors and regions, through a combination of chemical transport model (CTM), extended response surface model (ERSM), and concentration-response functions (CRFs). The mortalities due to both long-term and short-term exposures to PM2.5 are most sensitive to the emission reductions of primary PM2.5, followed by NH3, nonmethane volatile organic compounds and intermediate volatility organic compounds (NMVOC+IVOC). The sensitivities of long-term mortality to emissions of primary organic aerosol (POA), NMVOC+IVOC and SO2 do not change much with reduction ratio, whereas the sensitivities to primary inorganic PM2.5 (defined as all chemical components of primary PM2.5 other than POA), NH3 and NOx increase significantly with the increase of reduction ratio. The emissions of primary PM2.5, especially those from the residential and commercial sectors, contribute a larger fraction of mortality in winter (57–70%) than in other seasons (28-42%). When emissions of multiple pollutants or those from both local and regional emissions are controlled simultaneously, the overall sensitivity of long-term mortality is much larger than the arithmetic sum of the sensitivities to emissions of individual pollutants or from individual regions. This implies that a multi-pollutant, multi-sector and regional joint control strategy should be implemented to maximize the marginal health benefits. For NOx emissions, we suggest a nationwide control strategy which significantly enhances the effectiveness for reducing mortality by avoiding possible side effects when only the emissions within the BTH region are reduced.
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•PM2.5-related mortality is most sensitive to the emissions of primary PM2.5.•The mortality responds linearly to emission reduction of NMVOC, IVOC and SO2.•The mortality is more sensitive to primary PM2.5, NH3 and NOx at larger reductions.•Multi-pollutant and multi-region controls result in larger marginal health benefit.•A nationwide control strategy of NOx emissions is needed to enhance health benefit.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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