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At present, the air quality of most cities in Henan Province is seriously polluted. This will do great harm to people's health and the sustainable development of society. In order to solve this situation and improve the air quality of Henan Province, it is necessary to make effective forecast for the future air quality. After comprehensive consideration of various prediction models, combined with the characteristics of air quality, this paper selects the grey model as the research tool. In order to improve the prediction accuracy of the model, a compound accumulative grey model is proposed in this paper. It has been proved that the accuracy of this model is higher than that of other models. The study found that the concentration of SO 2 and NO 2 in 18 cities in Henan province will continue to decline, reaching the first-level standard. PM 2.5 and PM 10 concentrations in all cities still exceeded the standard, with some cities exceeding the standard seriously. In the future, the focus of air control in Henan Province should be on PM 2.5 and PM 10. The forecast results can provide reference for related departments. [ABSTRACT FROM AUTHOR]

Tropospheric NO 2 and SO 2 concentrations are of great importance with regard to air quality, atmospheric chemistry, and climate change. Due to lack of surface monitoring stations, this study analyzes long term trend of NO 2 and SO 2 levels (2005–2014), retrieved from Ozone Monitoring Instrument (OMI) board on the NASA's Aura satellite, in an important region of China – Henan Province. Henan Province, located in North China Plain, has encountered serious air pollution problems including extremely high PM 2.5 concentrations and as one of the most polluted region in China. The satellite spatial images clearly show that high levels of both NO 2 and SO 2 are concentrated in north and northeastern regions with much lower levels observed in other parts of Henan. Both pollutants exhibit the highest levels in winter with the least in summer/spring. The temporal trend analysis based on moving average of deseasonalized and decyclic data indicates that for NO 2 , there is a continuous increasing pattern from 2005 to 2011 at 6.4% per year, thereafter, it shows a decreasing trend (10.6% per year). As for SO 2 , the increasing trend is about 16% per year from 2005 to 2007 with decreasing rate 7% per year from 2007 to 2014. The economic development with incredible annual 11% GDP growth in Henan is responsible for increasing levels of NO 2 and SO 2 . The observed decreasing SO 2 level starting in 2007 is due to reduced SO 2 emission, utilization of flue gas desulfurization (FGD) devices and to some extent, in preparation of Beijing 2008 Olympic Games. On the other hand, increasing vehicle numbers (155% from 2006 to 2012) and coal consumption (37% during the same span), along with the lack of denitration process for removing flue/exhaust gas NO x are responsible for increasing NO 2 trend until 2011. The ratio of SO 2 /NO 2 started decreasing in 2007 and dropped significantly from 2011 to 2013 indicating good performance of FGD and ever increasing NO x contribution from mobile sources. Unlike those observed in developed countries (US, EU and Japan) where a decreasing trend for both SO 2 and NO 2 has been observed since 1990s, the observed upward and downward trend found in Henan is similar to those found in North China Plain and other parts of China. The spatial and temporal trend analyses of SO 2 and NO 2 in four other regions in Henan further indicate a similar trend to those observed in Henan Province, albeit with different increasing and decreasing rate. The results provide regulatory agency to develop action plans to combat air pollution problem in general and SO 2 and NO 2 problems in particular in Henan. The implications of our findings and recommendations for decision makers are discussed in the paper. [ABSTRACT FROM AUTHOR]

Handan is a typical city affected by regional particulate pollution. In order to investigate particulate matter (PM) characterization, source contributions and health risks for the general populations, we collected PM samples at two sites affected by a pollution event (12–18 May 2020) during the COVID-19 pandemic and analyzed the major components (SNA, OCEC, WSIIs, and metal elements). A PCA-MLR model was used for source apportionment. The carcinogenic and non-carcinogenic risks caused by metal elements in the PM were assessed. The results show that the renewal of old neighborhoods significantly influences local PM, and primarily the PM10; the average contribution to PM10 was 27 μg/m3. The source apportionment has indicated that all other elements came from dust, except Cd, Pb and Zn, and the contribution of the dust source to PM was 60.4%. As PM2.5 grew to PM10, the PM changed from basic to acidic, resulting in a lower NH4+ concentration in PM10 than PM2.5. The carcinogenic risk of PM10 was more than 1 × 10−6 for both children and adults, and the excess mortality caused by the renewal of the community increased by 23%. Authorities should pay more attention to the impact of renewal on air quality. The backward trajectory and PSCF calculations show that both local sources and short-distance transport contribute to PM—local sources for PM10, and short-distance transport in southern Hebei, northern Henan and northern Anhui for PM2.5, SO2 and NO2. [ABSTRACT FROM AUTHOR]

With the rapid development of industrialization and urbanization, atmospheric pollution research is vital for regional sustainable development and related policies formulated by the government. Previous studies have mainly studied a single evaluation method to analyze the air quality index (AQI) or single air pollutant. This research integrated the Spearman coefficient (SC) correlation analysis, a random search (RS) algorithm and an excellent extreme gradient boosting (XGBoost) algorithm to evaluate the air pollution influence of industrialization and urbanization (APIIU). Industrialization, urbanization and meteorological indicators were used to measure the influence degree of APIIU on AQI and particulate matter 2.5 (PM2.5), respectively. The main findings were: (1) the APIIU-AQI and APIIU-PM2.5 of Henan Province, Hubei Province and Hunan Province had significant changes from 2017 to 2019; (2) the value of square of determination coefficient of real value (R2), the root mean square error (RMSE) and the mean absolute percentage error (MAPE) of APIIU-AQI and APIIU-PM2.5 in three provinces predicted by the SC-RS-XGBoost were 0.945, 0.103, 4.25% and 0.897, 0.205, 4.84%, respectively; (3) the predicted results were more accurate than using a SC-XGBoost, RS-XGBoost, traditional XGBoost, support vector regression (SVR) and extreme learning machine (ELM). [ABSTRACT FROM AUTHOR]

China has imposed an ultra-low emissions (ULE) standards policy regarding the emission concentrations of the thermal power industry, and the region of the Fen-Wei Plain (China), which is an important area regarding blue-sky protection, is in urgent need of accelerating the transformation of its thermal power units to conform with China's ULE standards. Based on China's high-resolution thermal power industry emission inventory, this study used the Comprehensive Air Quality Model with extensions (CAMX) to examine emissions from the thermal power industry and the associated impacts on the atmospheric environment of the Fen-Wei Plain. (1) Spatially, the highest emissions and the greatest air quality contributions were concentrated in the Shanxi and Henan areas, which are regions that have considerable power generation capacity. (2) In terms of species, NOX represented the largest air quality contribution and registered the smallest reduction. (3) Temporally, emission sources presented the greatest contributions in summer. (4) In terms of policy evaluation, implementation of ULE standards resulted in the reduction of the contribution of thermal power industry emissions to air quality by 56.82%, 27.44%, and 44.55% for SO2, NOX, and PM2.5, respectively. The results reflect the current levels of pollution on the Fen-Wei Plain attributable to the thermal power industry and provide insight in relation to decision-making processes regarding regional air quality management. [ABSTRACT FROM AUTHOR]

Although central to the promotion of regional economic development, industrial parks discharge large quantities of air pollutants and CO2, counter to the goals of air quality improvement and CO2 reductions in China. In this study, 13 industrial parks in seven cities in Henan Province were chosen to evaluate their emission of air pollutants and CO2 in 2017, their reduction potential under different green measures, and their air quality improvements under a Green Upgrade scenario. The results show that: (1) The total emissions of SO2, NOx, CO, PM10, PM2.5, VOCs and CO2 in the 13 industrial parks were 43, 39, 351, 19, 7, 18, 2 kt and 36 Mt, and would decrease by 72, 56, 19, 30, 26, 77 and 30%, respectively, under the Green Upgrade scenario. (2) The industrial process was the major source of CO, PM2.5, VOCs and NH3, whereas power plants were the largest source of SO2 and NOx, and they would be reduced by 93, 59, 94, 91, 23 and 28%, respectively, under the Green Upgrade scenario. (3) The terminal energy use sector (including industrial boilers and industrial process sources) was the main source of CO2, accounting for 75% of total CO2 emissions, and would be reduced by 76% under the Green Upgrade scenario. (4) WRF-CMAQ simulation results show that, under the Green Upgrade scenario, the concentration of PM2.5 in a transmission channel city would be improved by 1–36 μg/m3, with an annual average value of 9 μg/m3. Our results demonstrate the significant effect of the synergistic reduction in air pollutants and CO2 emissions using Green Technologies in industrial parks and the subsequent improvement in regional air quality. [ABSTRACT FROM AUTHOR]

Industrial parks play an extremely important role in the rapid development of China's economy. However, as the backbone of China's economic development, industrial parks also consume huge energy resources and cause serious pollution to the environment, making China face greater pressure on environmental issues. This article takes the Yongcheng Economic and Technological Development Area, a typical energy-intensive industrial park in Henan Province, as the research object to analyze its energy saving and emission reduction potential. Three scenarios (baseline scenario, energy cascade utilization scenario, and energy efficiency technology enhancement scenario) are set to quantify the energy-saving potential and air pollutant emission reduction of the park under different scenarios. The results show that in the energy cascade utilization scenario, by realizing the recycling of waste heat resources from heat source enterprises, it can bring energy saving of 6385 TJ, and reduce 0.35 kt SO2, 0.79 kt NOx, 0.067 kt PM10, and 0.035 kt PM2.5. And CO2 emission reductions have reached 604 kt. In the energy efficiency technology enhancement scenario, by eliminating relatively backward technologies and adding advanced energy-saving technologies, 7306 TJ energy saving could be achieved. SO2, NOx, PM10, PM2.5, and CO2 emission reductions are 0.37, 0.82, 0.038, 0.071, and 719 kt, respectively. The results of the CALPUFF model indicate that the pollutant concentrations of SO2, NOx, PM10, and PM2.5 in the spring and autumn are relatively high, while those in the summer and winter seasons are relatively low. In four seasons, the highest 1-h average concentration and dispersion range of four pollutants have been reduced both in the energy cascade utilization scenario and in the efficiency technology enhancement scenario. [ABSTRACT FROM AUTHOR]

The rapid development of peanut mechanization has increased the amount of dust expelled from peanut mechanized operations, which degrades the air quality and endangers the health of agricultural workers. Therefore, the purpose of this study is to figure out the characteristics of dust emission from mechanized peanut harvesting. To this end, the particulate matters of diameters ≤ 2.5 μm and ≤10 μm and the total suspended particles were sampled in real time during peanut harvesting in Henan Province, China, and the airborne particle concentrations and particle size distributions were measured. The dust particles discharged during the mechanized peanut harvesting were concentrated within the 2~30 µm size range. When the wind speed was reduced below the settling velocity of the largest particles, the more massive particles were carried in the downwind. The amount of free silica in the dust samples was determined by X-ray diffraction analysis. Both the total dust and free silica concentrations exceeded the occupational exposure and threshold limits. To improve the characteristics of dust emission, the microstructure and dispersion of the dust were also investigated. Reducing the agricultural operations during periods of high wind speed, low crop-moisture content, and low air humidity is recommended for reducing the dust exposure of workers. The results will provide guidance and technical support for reducing the dust emissions of mechanized harvesting operations, improving air quality, and reducing the health hazards to operators. [ABSTRACT FROM AUTHOR]

The Jing‐Jin‐Ji (Beijing‐Tianjin‐Hebei) and the surrounding Jin‐Lu‐Yu (Shanxi‐Shandong‐Henan) regions are experiencing severe problems with air pollution. To measure the change in pollutant concentrations over the next few years, the fractional order accumulation grey model is used to forecast the air quality indicators. The results show that the concentrations of fine particulate matter, particulate matter 10, and sulfur dioxide show a downward trend, and 8‐h O3 (annual) and 8‐h O3 (spring and summer) show an upward trend in these areas. There is a slight increase in nitrogen dioxide concentration in Shanxi, but its concentration in other areas shows a slight decline. The results obtained can provide a clear direction for air quality management decisions. [ABSTRACT FROM AUTHOR]