Atmospheric Environmental Capacity Research Articles

Optimizing emission control strategies for mitigating PM2.5 and O3 pollution: A case study in the Yangtze River Delta region of eastern China

Effective mitigation of fine particulate matter (PM2.5) and ozone (O3) pollution necessitates collaborative regional emission control of major pollutants. In this study, we propose an approach based on source-receptor relationships (SRRs) and a mathematical programming (MP) model to quantify the regional atmospheric environmental capacity (AEC) constrained by certain air quality goals for PM2.5 and O3. We apply this method to optimize emission control strategies addressing a springtime case of concurrent high PM2.5 and O3 pollution in the Yangtze River Delta (YRD) region of eastern China in May 2014. Our analysis of SRRs reveals that O3 pollution is more contributed by regional transport compared to PM2.5, thereby limiting the potential for meeting the O3 target through anthropogenic emission reductions. Imposing various constraints on air quality goals and upper limits of emission reduction ratios yields significant variations in potential control pathways specific to source sectors and regions. To effectively mitigate PM2.5 pollution, substantial reductions in sulfur dioxide (SO2) and primary PM2.5 emissions are required, whereas ammonia (NH3) control demonstrates less effectiveness. Differentiated and coordinated efforts in controlling nitrogen oxide (NOx) and volatile organic compounds (VOCs) emissions are necessary to simultaneously achieve the desired PM2.5 and O3 targets. Evaluation of potential control pathways further emphasizes the effectiveness of implementing control measures on major precursor emissions to reduce PM2.5. However, meeting the O3 target remains challenging due to the complex nonlinearity involved in O3 formation. To attain the air quality goals for PM2.5 (<50 μg m−3) and daily maximum 1-h average (MDA1) O3 (<160 μg m−3) across the entire YRD, the estimated AEC values for SO2, NOx, NH3, VOCs, and primary PM2.5 are approximately 8.3, 79.4, 102.7, 186.9, and 13.0 kt mon−1, respectively, with corresponding emission reduction ratios of 95.6%, 75.5%, 33.1%, 45.1%, and 85.5% at the regional level.

Grid computing method for atmospheric environmental capacity coupled with ventilation coefficient using CALPUFF simulation and GIS spatial analysis technology

ABSTRACT Atmospheric environmental issues have evolved from point source pollution to regional pollution, leading to controlling specific air pollutant emissions. A-value method has been found suitable for estimating large-scale atmospheric environmental capacity rather than small-scale, resulting in the inaccuracy of developing air pollution control strategy. This study proposed a grid computing method based on the CALPUFF modelling system and GIS spatial analysis tool. The meteorological data from the MM5 model were used to simulate the spatial distribution of air pollutants. The meteorological flow field data was used to simulate the ventilation coefficient. The A value was revised with the simulated to achieve accurate results of atmospheric environment capacity. The credibility was verified by applying this method to Fengtai District, Beijing, China. The research area was divided into small partitions via the ArcGIS spatial analysis tool. The simulation results agreed well with the observation data from actual monitoring stations, even for the PM10 concentration with the most significant error (MRE: 7.05%−13.28%, RMSE: 11.62–17.89, R 2: 0.84–0.90). The GIS spatial analysis tools were applied to match the underlying surface types and overcome the restrictions of administrative boundary management. The study proposed four schemes to achieve differentiated air pollutant emission reduction and develop suitable control strategies. Furthermore, this method can be applied on different scales of natural geographic boundaries and realize the precise spatial management of atmospheric environmental capacity.

The dynamic multi-box algorithm of atmospheric environmental capacity

It is very important for air pollution prevention and control to accurately quantify atmospheric environment capacity (AEC) in the planetary boundary layer (PBL). This study developed a high temporal-resolution dynamic multi-box algorithm to estimate PM2.5 AEC with a PBL ceilometer and Doppler wind profile lidar in Beijing City. Compared with the traditional A-value method, two primary improvements are introducing the time coefficient and vertical multi-box assumption into the original box model. The algorithm can accurately calculate the PM2.5 AEC under different circulation patterns and predict the short-time dynamic change of AEC. The results show that the time coefficient effectively reduced the estimation errors when the initial PM2.5 concentration, horizontal wind speed and PBL heights change greatly with time, such situation is consistent with most circulation patterns. And the improvement of multi-box model is much more remarkable when the PM2.5 concentration and horizontal wind change greatly in the vertical direction, such as A, NE and W type circulations. The ideal AEC under polluted circulation patterns won't increase infinitely with wind speed and PBL height, generally less than 30 t/h. The horizontal advection has a much greater effect on expanding the capacity of PM2.5 than the vertical diffusion under clean circulation patterns, and the maximum value of ideal AEC can reach 50 t/h. The positive residual AEC under clean circulations indicates surplus capacity for PM2.5 because of vigorous turbulences, while weak diffusion and ventilation conditions under polluted circulations lead to negative residual AEC and insufficient capacity of atmosphere.

Analysis on the contribution rates of point and area source emissions to wuhan SO2, NO2, PM2.5 concentrations and atmospheric environmental capacity

Knowing the contribution rates and sharing rate of local source emissions to the atmospheric environmental capacity (AEC) is of great significance to the formulation of regional air pollution source control measures. Based on WRF-CALPUFF coupling models and the second pollution source survey data, Wuhan was taken as the research area, and the contribution rates of point and area source emissions to the SO2, NO2 and PM2.5 concentration in national pollutant control points (abbreviated as "national control points"), the AEC and its source emission sharing rate of each region were calculated. The results showed that WRF-CALPUFF had better reproducibility, the contribution rates of different pollution source emissions to the SO2, NO2 and PM2.5 concentration in national control points had obvious spatial distribution characteristics, and the contribution rates of key point sources to the SO2 concentration of each national control point exceeded 40%, while the contribution rates of the main urban area source to the NO2 and PM2.5 concentrations exceed 60%; the AEC of SO2, NO2 and PM2.5 in different regions had obvious seasonal and spatial changes, and the source emissions of NO2 and PM2.5 in the main urban area were 8.7 times and 3 times of its AEC, respectively. The calculation results from source sharing rate of regional AEC showed that the AEC of SO2 was mainly shared by point sources, and the AEC of NO2 and PM2.5 was mainly shared by area sources, but the sharing rate of SO2, NO2 and PM2.5 AEC from different regional source emissions showed different characteristics. The analysis of air quality improvement during the 7th Military World Games in 2019 and the COVID-19 pandemic in 2020 shows that the calculation formula about regional source sharing rate of AEC proposed in this paper is reasonable and the implementation of refined control to regional source emissions with the source sharing rate of regional AEC plays an important role on the continued improvement of Wuhan air quality.

Evaluation of Atmospheric Carrying Capacity of the Bohai Coast Jing-Jin-Ji Region

Li, M.; Li, W.; Li, T.; Lin, W., and Wang, F., 2020. Evaluation of atmospheric carrying capacity of the Bohai Coast Jing–Jin–Ji region. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 402–406. Coconut Creek (Florida), ISSN 0749-0208.To understand the level of atmospheric environmental carrying capacity in coastal areas, this article constructed an evaluation index system of atmospheric environmental carrying capacity, using the environmental capacity index and atmospheric environmental carrying capacity index to comprehensively evaluate the level of atmospheric environmental carrying capacity in Jing-Jin-Ji region from 2013 to 2016. The research showed that the level of atmospheric environmental carrying capacity in Jing-Jin-Ji region showed an upward trend from 2013 to 2016. Atmospheric conditions have shown great progress in improving air quality in recent years, and air quality is expected to improve further.

Impact of “blocking” structure in the troposphere on the wintertime persistent heavy air pollution in northern China

In the winters of 2012–2018, a total of 25 ‘ultra-long’ (≥6 days), wide-ranging pollution events occurred in northern China. The results showed that the atmospheric circulation pattern corresponding to 62.5% of the persistent ‘most serious’ and ‘more serious’ air pollution events in northern China were the blocking structures, and that 43.75% of the 500-hPa atmospheric circulation anomalies in the middle and high latitudes of Eurasia were ‘dual-blocking’, 18.75% of them were ‘single-blocking’. The abnormally stable blocking situation provided a special circulation background for the occurrence and maintenance of persistent heavy air pollution in northern China. The Okhotsk blocking is significantly positively correlated with the persistent ‘most serious’ air pollution events. ‘Stagnation’ of the blocking system and its dynamic effect play an important role in regulating atmospheric environmental capacity and accelerating the accumulation of aerosols during the persistent heavy pollution episodes. Due to the synergy between the weak wind effect of the leeward slope on the eastern side of the Loess Plateau in this region and the downward airflow of the large-scale blocking system, the effect of sustained suppression of atmospheric pollutant diffusion in northern China is more significant. The downward air flow along the eastern leeward slope of the Loess Plateau is very important for accumulation of air pollutants, which is controlled by the tropospheric blocking high. In addition, the ‘subsidence (temperature) inversion’ effect produced by the synergy between the downward airflow of the eastern leeward slope of the Loess Plateau and the large-scale blocking system creates a continuous and stable ‘warm-cover’ structure in the middle of the troposphere on the eastern of the Loess Plateau; this effect strengthens the radiation effect of aerosols in the atmospheric pollutants, as well as the ‘two-way feedback’ mechanism between adverse meteorological conditions in the boundary layer and atmospheric pollutants.

Intelligent Control Algorithm for Vehicle Exhaust Emission

In order to effectively control the emission of vehicle exhaust, it is necessary to analyse and study the control algorithm of vehicle exhaust emission. When using the current algorithm to control the vehicle exhaust emission, it cannot accurately calculate the ambient air capacity of nitric oxide, hydrocarbons, particulate matter and do not have synergistic control effect. On the basis of mathematical analysis, an intelligent control algorithm for vehicle exhaust emission is proposed. International Vehicle Emissions (IVE) model is used to calculate the emission of pollutants in the running and starting stages of the vehicle, so as to improve the precision of the vehicle exhaust emission. The box model and road traffic model are used to accurately calculate the atmospheric environmental capacity and analyse the pollutant emission reduction based on the calculation results. Through the PID control algorithm, the control of vehicle exhaust is completed and the synergistic control effect of the method is improved.

Dynamic early warning of regional atmospheric environmental carrying capacity

Economic development cannot exceed the maximum amount that the environment can support. Therefore, atmospheric environmental policy should be formulated based on the scientific assessment of regional atmospheric environmental carrying capacity. The establishment of an early warning model of atmospheric environmental carrying capacity can dynamically analyse regional atmospheric environmental carrying capacity, which contributes to discerning the change trend of the regional atmospheric environmental carrying capacity and the risk issue of the regional atmospheric environment. Additionally, it can provide theoretical reference for the formulation of relevant binding and restrictive policies. In this study, according to the daily monitoring data of atmospheric pollutants, we established a dynamic early warning model of regional atmospheric environmental carrying capacity based on the cloud model and Markov chain. The research results show that this model has an excellent early warning capability. Moreover, many regions in China have exceeded the atmospheric environmental carrying capacity, especially in North China and Central China. By 2020, North China and Central China for prediction of region with non-overloading are only 9.09% and 12.50%, respectively. China's regional atmospheric environmental carrying capacity is gradually improving. It is predicted that by 2024, regions with non-overloading in North China and Central China will reach 40.91% and 37.50%, respectively. From the overall aspect, there is currently no risk of serious overload in any region.

Estimating the remaining atmospheric environmental capacity using a single-box model in a high pollution risk suburb of Chengdu, China

The atmospheric pollution has been the public attention in recent years. In order to better coordinate economic development and atmospheric environmental management, China introduced the concept of atmospheric environmental capacity (AEC). The remaining atmospheric environmental capacity (RAEC) calculated by existing atmospheric pollution sources and AEC is an important basis for regional development and environmental protection. The RAEC of the high-pollution risk suburb of Chengdu in 2015 was estimated by the single-box model and analyzed on multiple time scales. The results show that the RAEC of SO2 and NO2 in this region is 3299 t/a and 2849 t/a, respectively under the annual time scale. However, in the daily time scale, the RAEC of NO2 is negative for 3 days, that is, there are 3 days with serious air pollution. Therefore, it is not appropriate to plan the industrial area only by relying on annual RAEC. Especially, RAEC displays inter-seasonal and monthly variability. On the one hand, in plain areas with low wind speed and little change in wind direction, achieving the prediction of atmospheric mixing layer height could give early warning of atmospheric pollution events. On the other hand, different management measures are taken on different time scales. On a long timescale, the regional energy structure should be optimized. On seasonal and monthly time scales, the production plans should be adapted to RAEC. On the daily time scale, it mainly deals with the serious atmospheric pollution accident timely.

Effectively controlling hazardous airborne elements: Insights from continuous hourly observations during the seasons with the most unfavorable meteorological conditions after the implementation of the APPCAP

Concentrations of PM2.5 and PM2.5-associated elements were observed hourly using an X-ray fluorescence-based online elemental analyzer at a chosen location within urban Beijing from November 28, 2016, to May 30, 2017, when nearly the lowest atmospheric environmental capacity was recorded after enforcing the Air Pollution Prevention and Control Air Plan (APPCAP). Throughout the study period, the PM2.5 concentrations were an average of 91.2 μg/m3, with 68 days exceeding the second tier of the Chinese ambient air quality standard (75 μg/m3). The PM2.5-associated hourly hazardous airborne element (HAE) concentrations ranged between 56 ng/m3 and 4374 ng/m3, accounting for an average of 0.2 ± 0.1 % of PM2.5, which were lower than or comparable with those reported in previous studies. Different from the traditional filter sampling offline analysis, dynamic variations and evolution of particulate HAEs were illustrated based on hourly observations, which showed that the concentrations of most HAEs declined with increasing mixed layer height (MLH) as expected, while slight increases in the Cr and Pb concentrations were observed when the MLH increased from 250 m to 500 m. Compared with the values in spring, As, Cr, Hg, Mn, Ni, Pb and Se increased by 135.0 %, 67.2 %, 110.1 %, 36.4 %, 32.4 %, 185.6 % and 63.9 % in winter, respectively. Based on hourly elemental data, the more robust source analysis showed that industrial emissions contributed substantially to Cr, Hg, Ni and Se (58.5 %, 42.7 %, 65.0 % and 62.0 %, respectively), vehicular sources primarily accounted for Mn (41.1 %) and almost all sources except for dust contributed equally to the Pb loading. A nonparametric wind regression analysis applied to 1-h HAE concentrations pinpointed distinct hot spots (high concentrations) for all HAEs except Cd in the northeast wind sector at wind speeds of approximately 0−6 km/h. Based on a potential source contribution function analysis, the areas in western China with intense coal consumption strongly contributed to the loading of As in Beijing. Cr, Hg, Ni, Pb and Se showed source areas that were similar to but larger than that of As; additionally, these elements exhibited moderate and strong hotspots in Shanxi Province with strong coal consumption and industrial production. Ni clearly originated from the coastal areas where the effect of shipping activities was intense.

The macroscopic mechanisms and associated atmospheric precursor environmental capacities that lead to secondary fine particle pollution

This paper establishes the kinetic equations in atmospheric chemistry that describe the macroscopic mechanisms of secondary fine particle pollution generated by precursors during atmospheric self-purification. The dynamic and static solutions of these equations can be applied to calculate quantitative relationships between the concentration ratio of precursors and secondary fine particles as well as the physical clearance power of the atmosphere, chemical reaction rate, and the scale of a contaminated area. The dynamic solution presented here therefore corresponds with a theoretical formula for calculating the overall rate constant for the oxidation reaction of reducing pollutants in the actual atmosphere based on their local concentrations and meteorological monitoring data. In addition, the static solution presented in this paper reveals the functional relationship between the concentration of secondary fine particles and precursor emission rate as well as atmospheric self-purification capacity. This result can be applied to determine the atmospheric environmental capacity of a precursor. Hourly records collected over the last 40 years from 378 weather stations in mainland China as well as the spatiotemporal distribution sequence of overall oxidation reaction rates from precursors show that when the reference concentration limit of secondary fine particles is 100 μmol m-3, the atmospheric environmental capacity of total precursors can be calculated as 24890×1010 mol yr-1. Thus, when the annual average concentration limit of given fine particles is 35 μg m-3 and the ratio of sulfate and nitrate to 30% and 20% of the total amount of fine particles, the capacities of SO2, NOx and NH3 are 1255, 1344, and 832 (1010g yr-1), respectively. The clearance density of precursors for different return periods across mainland China under above conditions are also provided in this study.

Many-Objective Optimal Power Dispatch Strategy Incorporating Temporal and Spatial Distribution Control of Multiple Air Pollutants

Traditional economic/environment dispatch usually aims to reduce emission, but neglects air pollutant dispersion and lacks target-oriented control. This paper proposes a many-objective optimal power dispatch (MaOOPD) strategy incorporating temporal and spatial distribution (TSD) control of multiple air pollutants. Ground level concentration, i.e., the TSD, of air pollutant is estimated by a novel air pollutant dispersion model specifically constructed for thermal power plants. A MaOOPD model is developed to cut generation cost, reduce CO2 emission, and control the TSD of PM2.5, SO2, and NO2 simultaneously. To determine a compromise solution, a decision-making method which exploits atmospheric environmental capacity margin is employed, so that actual needs of atmospheric environmental protection are captured. Case studies indicate that not only can the strategy reduce air pollution effectively, but also it can achieve a dynamic tradeoff among the objectives as weather conditions and background pollution vary, leading to an authentic economic environmental power dispatch.

Comparative Study of Environmental Assessment Methods in the Evaluation of Resources and Environmental Carrying Capacity—A Case Study in Xinjiang, China

Scientifically assessing the environmental carrying capacity (ECC) based on an evaluation of environmental quality standards (EQSs) holds great significance for establishing a long-term monitoring and early warning mechanism for resources and environmental carrying capacity (RECC) and for coordinating the sustainable development of ecological environments and regional economies. However, it remains unclear whether the evaluation of EQSs based on the short board effect is suitable for environmental assessments under different natural environments. In this research, Xinjiang is used as a case study. Based on the evaluation of EQSs, the atmospheric environmental carrying capacity (AECC), water environmental carrying capacity (WECC) and comprehensive environmental carrying capacity (CECC) are assessed using the short board effect and the weighted average. Additionally, the suitability of ECC evaluation in RECC evaluation is discussed. The results show the following: (1) In the atmosphere, the overload of inhalable particles (PM10) and fine particulate matter (PM2.5) is more serious, while in water, the overload of total nitrogen (TN) is more serious. (2) The percentages of the AECC, WECC and CECC in overloaded counties and cities based on the short board effect are 84%, 45%, and 51%, respectively, while the percentages based on the weighted average are 32%, 6% and 7%, respectively. (3) The extreme effects of a single pollutant can be eliminated by the weighted average, which is more suitable for environmental assessments in Xinjiang. (4) In evaluating RECC monitoring and early warning systems, weighted average evaluation is used to assess the elements, and short board effect evaluation is used in the comprehensive integration to prevent the influence of the amplification of a single index. Thus, the interference of non-key factors in the regional system on the final evaluation results is reduced.

The formation mechanism of air pollution episodes in Beijing city: Insights into the measured feedback between aerosol radiative forcing and the atmospheric boundary layer stability.

Based on the high-resolution observation of meteorological factors profiles, particulate matter concentration and aerosol radiative forcing (ARF) from 25 August to 17 November 2018 in Beijing, the feedback between ARF and the atmospheric boundary layer (ABL) stability was systematically investigated during air pollution episodes. There was the initial explosive growth in particulate matter (PM) concentration that PM2.5 sharply increased from ~8μgm-3 to ~100μgm-3, with aerosol optical depth (AOD) increasing from ~0.25 to ~0.58. This was the transport phase dominated by the southerly winds. As PM increased, the high aerosol loading scattered more solar radiation cooling the earth-atmosphere system (ARF at the top of the atmospheric column (TOA): from ~5Wm-2 to ~-52Wm-2). Meanwhile, high aerosol loading absorbed more solar radiation and heated the atmospheric layer with ARF at the interior of the atmospheric column (ATM) increasing from ~21Wm-2 to ~42Wm-2. The absorption and scattering effects of aerosol together cooled the surface (ARF at the surface of the atmospheric column (SFC): from ~-16Wm-2 to ~-90Wm-2). Thus, the ABL stability rapidly increased in the following cumulative phase and heavy pollution phase with a strong temperature inversion (inversion depth of ~300-1000m) occurring. In turn, the persistent temperature inversion caused the significant accumulation of moisture (water vapor density of ~5-10gm-3) and pollutants, and PM were prone to physicochemical reactions in the high-humidity environment, further increasing PM. It was the constant feedback effect between ARF and the ABL stability that continually reduced atmospheric environmental capacity and aggravated air pollution (PM2.5 and AOD reaching ~95-125μgm-3 and ~1.38-1.75, respectively). Finally, the feedback was broken by dry, clean and strong north winds appearing in Beijing in the dissipation phase.

The Analysis of Atmospheric Environment Capacity in the Winter of 2016 in Liaoning

The variations of atmospheric environmental capacity and its relationship to AQI and the height of the atmospheric mixing layer have been studied by using meteorological and environmental monitoring data from Shenyang, Dalian, Dandong and Jinzhou in the winter of 2016. The results show that the atmospheric environmental capacity is obviously different in four cities, but the daily variation trend of atmospheric environmental capacity for PM2.5, PM10, SO2, NO2 and CO is basically the same. The atmospheric environmental capacity and AQI show negative correlation and the correlation coefficients (R2) of the atmospheric environmental capacity to AQI in four cities are respectively 0.1016, 0.1109, 0.3014 and 0.1723. The correlation between the atmospheric environmental capacity of PM10 and the height of the atmospheric mixing layer show positive correlation and the average correlation coefficients(R2) in four cities.

A study on the spatiotemporal characteristics and change trend of the atmospheric environmental carrying capacity in the Jing-Jin-Ji region, China

The Jing-Jin-Ji region is one of the most atmospherically polluted regions in the world. In this study, the concepts, calculations, and classifications of the atmospheric environmental overloading index (AEOI) have been further developed. The AEOI has been calculated using the daily monitoring values of the concentrations of six main atmospheric pollutants from a total of 13 cities in the region from 2013.12.2 to 2017.04.18. Based on this index, the spatiotemporal characteristics and trends of the atmospheric environmental carrying capacity (AECC) are evaluated. In the temporal dimension, the regional AECC has gradually improved, and the amplitude of the average annual comprehensive AEOI has decreased, by up to 36.28% and 21.97%, respectively. In the spatial dimension, the AECC in the region decreases gradually from north to south. Regarding the change trend, decreasing comprehensive AEOI values were observed for 78.85% of the cities in the region. A significant reduction of up to 53.85% indicates a significant improvement in the regional AECC. Construction of a fluctuation network for the AEOI further confirmed the overall characteristics of the AEOI change in the atmospheric environment in this region, and the cities that are independent from the overall fluctuation could be identified.

Capacity Simulation Method Based on Regional Transfer Matrix and PM2.5 Concentration Target Constraint

Atmospheric environmental capacity is an important reference in environmental planning. To meet the PM2.5 standard, a new method is proposed to balance the capacity among cities of Guangdong, with screening of the most unfavorable meteorological year and combining it with the regional transportation calculated by the CAMx-PSAT module. Pollutant overloading and capacity scenarios were also calculated. The results showed that, under the constraints of the cities' annual PM2.5 ≤ 35 μg·m-3, the capacities of SO2, NOx, NH3, and PM2.5 in Guangdong were about 6.8×105 tons, 1.35×106 tons, 4.6×105 tons, and 5.1×105 tons, respectively. Based on the benchmark scenario, SO2 emissions in Guangdong were overloaded by 10%, and the emissions of NOx, NH3, and PM2.5 exceeded by 12%, 9%, and 20%, respectively, compared to those of the capacity scenario. Ranked by the number of overloaded species in Guangdong, the cities of Guangzhou, Foshan, Zhongshan, and Qingyuan were on top. When achieving the capacity scenario, the annual PM2.5 concentration in Guangdong was about 30 μg·m-3, which meets the national secondary ambient air quality standard.

Security-Constrained Unit Commitment Considering Differentiated Regional Air Pollutant Intensity

Conventional environmental-economic power dispatch methods constrain the total amount of emissions of power plants, and they succeed in reducing emissions from the power sector. However, they fail to address the mismatch between emission reductions and the resulting changes in regional air quality. This paper proposes an ecology- and security-constrained unit commitment (Eco-SCUC) model considering the differentiated impacts of generation-associated emissions on regional air quality. A Gaussian puff dispersion model is applied to capture the temporal-spatial transport of air pollutants. Additionally, an air pollutant intensity (API) index is defined for assessing the impacts of emissions on the air quality in regions with differentiated atmospheric environmental capacities. Then the API constraints are formulated based on air quality forecast and included in SCUC model. Moreover, the stochastic optimization is employed to accommodate wind power uncertainty, and the Benders decomposition technique is used to solve the formulated mixed-integer quadratic programming (MIQP) problem. Case studies demonstrate that the Eco-SCUC can cost-effectively improve air quality for densely-populated regions via shifting generation among units and can significantly reduce the person-hours exposed to severe air pollution. Furthermore, the benefits of wind power for air quality control are investigated.

贵阳市大气环境容量核算研究

贵阳市大气环境容量核算研究

Climate Change Characteristics of Atmospheric Environmental Capacity in Hebei Province during 1972-2013

Climate Change Characteristics of Atmospheric Environmental Capacity in Hebei Province during 1972-2013