No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Impacts of power generation on air quality in China—Part II: Future scenarios
Abstract
Power generation is an important source of air pollution in China since it is mostly from coal-fired power plants. Future power generation plans are needed to meet both increasing power needs and air quality improvement. In this study, five future power development scenarios in 2030 were considered. The REF scenario is the base case in which the growth was assumed to follow the existing projection (business as usual). The CAP scenario represents power sector in the trajectory to achieve 80% reduction by 2050 as proposed by IPCC, the LOW scenario reflects low cost of renewable to foster wind and solar development, the PEAK scenario allows China to peak its carbon emission by 2030, while the WEST scenario assumes that the coal power bases build all planned capacity by 2030 and no coal power in Beijing, Tianjin and Shanghai by 2030. Then, impacts of the scenarios on air quality were simulated with the Community Multiscale Air Quality (CMAQ) model in January and August 2030 with unchanged emissions from other sectors and the same meteorology in 2013. The results indicate that air quality gets worse in the REF scenario in both months compared to 2013. The CAP and WEST scenarios generally have larger impacts on pollutant concentrations than the LOW and PEAK scenarios. The four scenarios improve PM2.5 total mass and SO42− in North China, with maximum decreases of over 100 μg m−3 in January and over 10 μg m−3 in August in the Hohhot area. However, PM2.5 total mass and SO42− pollution are worsened in Shandong for CAP and WEST scenarios and in Chongqing for LOW and PEAK scenarios. NO3− and O3 get worsened in the four scenarios in large areas of the North China Plain (NCP), East and South China due to more NH3 available for NO3− formation associated with reduction in SO42− and aerosol radiative effects on UV radiation for O3 formation. Power development plans greatly affect air quality in Beijing, with decrease in PM2.5 and PM10, but increase in O3. Reducing NOx and SO2 combined with NH3 should be considered to reduce contribution of power generation to future air pollution in China.
... Some studies also investigated the co-benefit of reducing concentration of aerosol due to carbon mitigation in the future. For example, Hu et al. simulated the change of aerosol concentration under different emission scenarios with future power development [19]. ...
... Controls on common emission sources can achieve the cobenefits of aerosol pollution reduction and climate change mitigation. For example, improving energy structure and promoting renewable energy sources (such as wind and solar) can significantly reduce aerosol concentrations [19]. ...
... Sun et al.'s research shows the reduction of PM 2.5 under the stable weather condition will be more obvious, i.e., 7.7% in normal conditions and 14.2% in hazy conditions in Guanzhong Plain using box model [161]. Hu et al. get results that concentration of PM 2.5 will decrease by 100 μg m −3 in January in North China in 2030, while reduction is less obvious in summer (i.e., decrease by 10 μg m −3 in August in Hohhot area) [19]. ...
Fast growth of air pollution was experienced in China during the past decades, resulting in extremely large aerosol radiative forcing with up to ten times high compared to the global averages. The responses of surface air temperature to aerosol radiative effects range from − 0.1 to 1.1 K across China, with strong spatial and seasonal variations. Aerosol interaction with clouds can also affect radiation and precipitation. Under high pollution conditions, the frequency of heavy rain increases while the frequency of light rain decreases. Aerosols share common emission sources with CO2, implying that reducing common sources can be another manifestation of the interaction between aerosol and climate. Air pollution controls will contribute to the climate change mitigation by reducing CO2 emissions stemming from controls of pollution sources. On the other hand, potential co-benefits in reducing air pollution also come from the mitigation of climate change by reducing CO2 emission that potentially affects the aerosol concentrations. It is suggested that the PM2.5 (fine particulate matter with an aerodynamic diameter of 2.5 μm or less) concentration tends to decrease under future climate control scenarios. Such co-benefits are mostly associated with the reduction of common sources of CO2 and aerosol (noted as emission-driven interaction), rather than the variation of meteorological conditions associated with future climate change (noted as meteorology-driven interaction). Compared to emission-driven interaction, the impact by meteorology-driven interaction on aerosols is relatively smaller and varies geographically as the PM2.5 concentration is likely to increase in northern China while decrease in eastern China. The current review suggested that the co-benefits of reducing CO2 and aerosol pollutant in China, and their response in the context of future climate change, are worthy of further research.
... For example, Xue et al. simulated PM2.5 and ozone under nine emission reduction scenarios, and the anthropogenic emissions of each air pollutant were reduced by the same percentage, ranging from 10% to 90% for each scenario [25]. Some studies focus on research from a sectoral perspective (such as mobile source and power industry) or a certain air pollution control policy in scenario analysis [32,[35][36][37][38][39][40]. For example, Guo et al. and Zhang et al. use scenario analysis to predict the change of conventional pollutant concentration in the Beijing-Tianjin-Hebei region under different target years of vehicle emission control strategies [35,36]. ...
... For example, Guo et al. and Zhang et al. use scenario analysis to predict the change of conventional pollutant concentration in the Beijing-Tianjin-Hebei region under different target years of vehicle emission control strategies [35,36]. Hu et al. consider five scenarios of China's power development in 2030 and predicts spatial distribution of conventional pollutant concentration under different scenarios through model simulation on national scale [37]. Li et al. evaluated the air quality improvement potential and far-reaching influence of scattered coal consumption reduction in rural areas. ...
In the background of constructing a wold-class Guangdong-Hong Kong-Macao Great Bay Area (GBA), the growing demand for industrial, transportation and energy development in the Pearl River Delta (PRD) will put considerable pressure on improvement of regional air quality. It is important to choose a scientific development path to achieve both economic goal and air quality improvement target. This study uses scenario analysis method to construct three “industry-transport-energy” development scenarios within the region while the improvement level of air quality is simulated and analyzed. The results show that: (1) Considering the mutual constraints and influence relations between industry, transportation and energy in scenario analysis, the “industry-transport-energy” development scenario can be established to meets the same economic goal but has different development paths. (2) Along the historical track and established policy path, concentration of fine particulate matter (PM2.5) in the PRD can be reduced to 16.2 µg/m3 by 2035 as regional gross domestic product (GDP) reaching about 23.5 trillion. (3) Under the same economic goals, raising the proportion of emerging industries, freight by rail, public transport travel and non-fossil power to 95%, 10%, 73%, and 46% respectively leads to 29.6~49.2% reductions in the emissions of sulphur dioxide (SO2), nitrous oxides (NOx), primary PM2.5 and volatile organic compounds (VOCs) compared with those in 2017 that the regional PM2.5 concentration will further drop to 14.1 µg/m3. The results show that, under the constraints of economic development objectives, deepening structural adjustment can improve air quality, which gives advice for the PRD to choose its development path. Furthermore, this study can provide reference for the PRD to promote the transformation of industrial, transportation and energy development modes and structural adjustment under the dual objective of promoting the world-class bay area economic level and high-quality air level.
... Biofuels derived from biomass are considered substitutes for fossil fuels because their CO2 balance is zero (Hu et al., 2017;Sun et al., 2018). Raw materials used for biofuel generation include vegetable oils and sugars available from various industries such as sugar, oil, and paper (Pereda, 2018;Smith et al., 2018;Tandra et al., 2022). ...
The purpose of this research is to determine the impact of international palm oil prices, prices of its substitute and complementary goods, and the exchange rate on the competitiveness of 30 palm oil exporting countries over the period from 2011 to 2019, using monthly data. The symmetric comparative advantage index was estimated, and a convergence effect was found, whereby emerging countries exhibited greater specialization than industrialized countries. Unit root and cointegration tests were applied, in addition to FMOLS and DOLS methods. The analysis revealed that decreases in palm and vegetable oil prices, coupled with an increase in the exchange rate and prices of soybeans and biodiesel, enhanced the competitiveness of palm oil exports.
... There are quite a few studies on the simulation assessment of the impact of coal-fired power plants, including exploring the comparison of the impact of coal-fired industry with other industries [12,[15][16][17], exploring the role of coal-fired power plant emission reduction in future emission policies [18,19], simply exploring the impact of coal-fired power plant emissions [20][21][22], exploring the changes in the PM 2.5 concentration after the closure of coal-fired power plants [23], and exploring the impact of changes in the location of power plants on PM 2.5 concentrations [24]. However, most of these studies analyzed the impact of coal-fired power plants on air quality over a longer period of time (season, year) and less frequently analyzed that of high pollution event days. ...
Taichung Power Plant (TPP) is Taiwan’s largest coal-fired power plant and is considered a major source of air pollution. During periods of deteriorating air quality, it is often required to reduce the load to reduce emissions. However, frequent power load shedding not only requires cost but also requires safety considerations. Therefore, it is necessary to explore the role that thermal power plant emissions play in air pollution in Taiwan. This study employed the Community Multiscale Air Quality modeling system with the brute-force method to analyze the PM2.5 concentration contributed by TPP. The results showed that among the various air basins in Taiwan, the Yun-Chi-Nan air basin (YCNAB), located to the south of TPP, was most severely affected by TPP’s emissions, with an annual average affected concentration of 1.0 µg m−3 (3.3%). However, when serious PM2.5 pollution events (daily concentration > 70 µg/m3) occurred due to low wind speeds, the Central Taiwan air basin (CTAB), where TPP is located, became the area most severely affected by TPP’s emissions. The low wind speed was caused by the interaction between the easterly wind field around Taiwan and Taiwan’s north–south mountain ranges. When this happens, TPP’s emissions would have a greater impact on the PM2.5 concentration at nearby stations in the CTAB and YCNAB, up to about 11%. Overall, on pollution days caused by low wind speeds, the largest TPP load reduction (40%) still had a certain effect as an emergency measure to improve the high PM2.5 pollution in central and southern Taiwan.
... The NO 2 /SO 2 ratio can explain the energy structure characteristics of a region. NO 2 mainly comes from mobile sources such as vehicle exhaust emissions (Gu et al., 2019;Sun et al., 2020), while SO 2 mainly comes from stationary sources such as power generation, burning coal and industrial production (Hu et al., 2017;Shuma & Madyira, 2019;Yang et al., , 2019bYang et al., , 2019c. Sources of pollutants can be identified by analyzing changes in NO 2 /SO 2 ratio. ...
Currently, air quality has become central to global environmental policymaking. As a typical mountain megacity in the Cheng-Yu region, the air pollution in Chongqing is unique and sensitive. This study aims to comprehensively investigate the long-term annual, seasonal, and monthly variation characteristics of six major pollutants and seven meteorological parameters. The emission distribution of major pollutants is also discussed. The relationship between pollutants and the multi-scale meteorological conditions was explored. The results indicate that particulate matter (PM), SO2 and NO2 showed a “U-shaped” variation, while O3 showed an “inverted U-shaped” seasonal variation. Industrial emissions accounted for 81.84%, 58% and 80.10% of the total SO2, NOx and dust pollution emissions, respectively. The correlation between PM2.5 and PM10 was strong (R = 0.98). In addition, PM only showed a significant negative correlation with O3. On the contrary, PM showed a significant positive correlation with other gaseous pollutants (SO2, NO2, CO). O3 is only negatively correlated with relative humidity and atmospheric pressure. These findings provide an accurate and effective countermeasure for the coordinated management of air pollution in Cheng-Yu region and the formulation of the regional carbon peaking roadmap. Furthermore, it can improve the prediction accuracy of air pollution under multi-scale meteorological factors, promote effective emission reduction paths and policies in the region, and provide references for related epidemiological research.
Graphical abstract
... Los biocombustibles provienen de la biomasa y son considerados sustitutos de los combustibles de origen fósil debido a que su balance de CO2 es cero (Hu et al., 2017;Sun et al., 2018). Las materias primas utilizadas para la generación de biocombustibles son aceites vegetales y azúcares disponibles de diversas industrias como la azucarera, aceitera y del papel (Pereda, 2018), además de las obtenidas en negocios y hogares en los que se tiene disponibilidad de lignina, celulosa o hemicelulosa; todo ello con el objetivo de producir biocombustibles amigables con el medio ambiente (Chávez Altamirano et al., 2021;Llenque-Díaz et al., 2020). ...
La necesidad de energía de la población ha originado con el paso de los años problemas de contaminación ambiental asociados al uso de combustibles de origen fósil. La bioenergía es una alternativa que diversos países han propuesto para disminuir el volumen de gases contaminantes a la atmósfera; el biodiésel y bioetanol son los que presentan mayores ventajas comerciales en el mundo, aparte de que son necesarios para el cumplimiento de acuerdos internacionales en materia ambiental. El presente trabajo se enfoca en analizar la ventaja comparativa en 56 países respecto a la producción de biodiésel y bioetanol, para lo cual se utilizó el índice de la ventaja comparativa revelada (VCR) y el índice de la ventaja comparativa revelada normalizada (VCRN). Los resultados muestran que para la producción de biodiésel los países con mayor ventaja son España, Argentina, Brasil, Indonesia y la Unión Europea (conjunto de 28 países), mientras que en la producción de bioetanol sobresalen Colombia, Estados Unidos, Argentina, Brasil y la Unión Europea. Códigos JEL: Q24, E23 Recibido: 29/12/2021. Aceptado: 21/07/2022. Publicado: 01/12/2022.
... The Comprehensive Air Quality Model (CAMx) coupled with plume rise functions was used to simulate the dispersion of PM2.5 from 111 coal-fired power plants in India, and the analysis showed that the PM2.5 concentrations could be reduced by 30%-40% by eliminating the formation of secondary sulfates and nitrates [30]. Hu et al. adopted the Community Multiscale Air Quality (CMAQ) model to predict the impact of PM2.5 emissions from coal-fired power plants on air quality under five future power development scenarios in China [31]. Shi et al. used the CMAQ model to quantitatively estimate the contribution of different sectors of source emissions to ambient PM2.5 concentrations in China and found that power plants are also an important source of secondary inorganic aerosols [32]. ...
The Fenwei Plain (FWP) remains one of the worst PM2.5-polluted regions in China, although its air quality has improved in recent years. To evaluate the regional transport characteristics of PM2.5 emitted by coal-fired power plants in the FWP in wintertime, the primary PM2.5, SO2, and NOx emissions from coal-fired power plants with large units (≥ 300 MW) in 11 cities of the area in January 2019 were collected based on the Continuous Emission Monitoring System (CEMS). The spatial distribution and source contribution of primary and secondary PM2.5 concentrations were investigated using the Weather Research and Forecast (WRF) model and the California Puff (CALPUFF) model. The results showed that secondary PM2.5 was transported over a larger range than primary PM2.5 and that secondary nitrate was the main component of the total PM2.5 concentration, accounting for more than 70%. High concentrations of primary, secondary, and total PM2.5 mainly occurred in the Shaanxi region of the FWP, especially in Xianyang, where the PM2.5 concentrations were the highest among the 11 cities, even though its pollutant emissions were at moderate levels. The PM2.5 concentrations in Sanmenxia and Yuncheng primarily came from regional transport, accounting for 64% and 68%, respectively, while those in other cities were dominated by local emissions, accounting for more than 63%. The results may help to understand the regional transport characteristics of pollutants emitted from elevated point sources over a complex terrain.
... Current domestic research also focuses on the emission reduction effects of clean air measures in coal-intensive and energy-intensive sectors [10,11]. Energy-related air pollution control actions in China from 2013 dramatically improved the national air quality and led to the co-benefits of a cleaner and more efficient energy system [12,13]. Tong et al. pointed out the importance of energy structure adjustment for air quality compliance in the Beijing-Tianjin-Hebei region [14]. ...
Energy-related clean air measures in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) can yield substantial air quality improvement benefits and promote energy structure optimization. Here, we first evaluate the reduction effect of the stringent energy-related clean air measures in the GBA during the 13th Five-Year Plan period. First, a reduction of 19.3% emission in air pollutant equivalent was measured in 2020 compared to 2015. Second, we compare the energy structure development and air quality benefits of energy-environment policy scenarios by 2025 (SBAU, SA, SO) geared towards proposing integrated energy-environment development paths of air quality improvement. Under SBUA, SA and SO, the annual average PM2.5 concentration will be 21.7, 19.9 and 18.1 μg/m3, respectively, and the total energy demand would be controlled within 318.9, 300.6 and 282.3 Mtce in the GBA in 2025, reaching 7.5%, 8.4% and 9.4% of SO2, 23.5%, 29.3% and 35.4% of NOX, 18.2%, 19.6% and 22.7% of primary PM2.5, and 25.1%, 29.9% and 34.7% of VOCs emission reductions compared to 2020, respectively. Our study proposes that it is necessary for the GBA to jointly set up regional air quality improvement targets and issue integrated regional energy-environment policies in the process of building an “Air Quality Improvement Pioneering Demonstration Area”.
... The volume capacity method emphasizes the atmospheric environment volume in a city, which is an urban development limitation. Specifically, the volume capacity method includes the A-P value, box model, ADMS model, CALPUFF Model, AER-MOD model, and CMAQ model (Ahmadi et al., 2018;Zhou et al., 2020;Mallet et al., 2018;Abdul-Wahab et al., 2011;Demirarslan and Dogruparmak, 2016;Hu et al., 2017). The indicator system method is a comprehensive method incorporating economic and social indicators into the evaluation of UAECC (Guo et al., 2018). ...
Urban atmospheric environment protection is an important strategy for sustainable urban development. Nevertheless, serious atmospheric pollution problems caused by socioeconomic activities have become a global issue, which brings enormous pressure on human health. However, as the core of urban sustainability, the human health risk is not adopted as an element to evaluate the Urban Atmospheric Environment Carrying Capacity (UAECC) in previous studies. Therefore, this study develops an improved threshold method called the health risk-based threshold method to evaluate UAECC, by adding the principle of the Air Quality Health Index (AQHI) into the traditional threshold method. The effectiveness of the novel UAECC method is demonstrated by using the data collected from a sample of 13 cities in the Beijing-Tianjin-Hebei (BTH) region. Moreover, the case demonstration considers both the microscopic and macroscopic UAECC. The demonstration results suggest that (1) poor performance of UAECC happens in urban built-up areas; (2) the UAECC performance of cities located in the north part of BTH region behaves better than that in the south part; (3) PM2.5, PM10, and NO2 are three primary contributors to the UAECC performance in the BTH region; (4) the UAECC performance in the BTH region has been improved, while the single-factor of O3 deteriorated from 2015 to 2020. Furthermore, the evaluation results by using the improved method can provide valuable references for formulating tail-made policies towards different cities with different UAECC conditions.
... Xie et al. (2019) observed that power plants in east China were more efficient as compared to in other regions and also that large power plants performed better in terms of efficiency when compare to small ones. Hu et al. (2017a) predicted that air quality would get worse in case the power plants were operated at business as usual, while scenarios which considered 80% reduction in power plant emissions by 2050 and no coal based power in Beijing, Tianjin and Shanghai by 2030 showed reduction in PM 2.5 concentrations. Lin et al. (2020) observed that shifting to electric vehicles along with shift to renewable sources to generate the required extra power for vehicles have the maximum benefit in terms of air quality and health. ...
Coal based power plants are the biggest source of air pollution from power sector and thus it becomes imperative to study its contribution to air pollution in India. This study estimates impact of power generation on pollutant concentrations and associated mortality across India in current scenario and compares with three other control policy intervention scenarios in 2015. About 60% of total power generated in India in 2015 was from coal fired plants which contributed to about 49%, 34%, 6.6% & 6% of SO2, NOx, PMfine and CO emissions in India. Contribution of power plants to fine particulate matter (PM2.5) was the highest in winter (14.12 μg/m³) and lowest in monsoon (1.99 μg/m³). SO4⁻ and NO3⁻ contributed the most (65%-97%) to total PM2.5 attributed to power plants indicating maximum reduction in secondary inorganic aerosols due to implementation of regulating policies on power plants. Among the 3 control policy intervention scenarios on power plants, COPP scenario reflecting implementation of emission standards on current operating plants, was found to be the best scenario resulting in reduction of pollutant concentrations. It resulted in reduction of about 9 μg/m³ in PM2.5 concentration which in turn lead to 73,209 lives saved and increase in about 1.7 Years of life lost/person (YLL/person). On the other hand, in case of UCPP and CNPP scenarios where regulating policies were implemented only in under construction and new power plants respectively resulted in increased PM2.5 concentration of about 8.22 μg/m³ and 19.03 μg/m³ and also 50,200 and 1,15,894 extra premature mortality.
... SO 4 2− , NO 3 − , organic carbon (OC), and water-soluble organic carbon) when RH exceeded approximately 65% in winter. Hu et al. (2017a) predicted the impact of different future power generation plans in China on air quality using the CMAQ model. Uncertainties in the emission inventory can significantly impact the model predictions. ...
The EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation and their Effects in the Yangtze River Delta (EXPLORE-YRD) campaign was carried out between May and June 2018 at a regional site in Taizhou, China. The EXPLORE-YRD campaign helped construct a detailed air quality model to understand the formation of O3 and PM2.5 further, identify the key sources of elevated air pollution events, and design efficient emission control strategies to reduce O3 and PM2.5 pollution in YRD. In this study, we predicted the air quality during the EXPLORE-YRD campaign using the Weather Research and Forecasting/Community Multiscale Air Quality modelling system (WRF/CMAQ) and evaluated model performance on O3 and PM2.5 concentrations and compositions. Air quality was predicted using two sets of reanalysis data—NCEP Final (FNL) Operational Global Analysis and ECMWF Reanalysis v5.0 (ERA5)—and three horizontal resolutions of 36, 12, and 4 km. The results showed that PM2.5 concentration was generally under-predicted using both the FNL and ERA5 data. ERA5 yielded slightly higher PM2.5 predictions during the EXPLORE-YRD campaign. Both reanalysis data sets under-predicted the high PM2.5 pollution processes on 29–30 May 2018, indicating that reanalysis data is not essential for under-predicting extreme PM2.5 pollution processes. The performance of O3 was similar in both the reanalysis data sets, because O3 is mostly sensitive to temperature predictions and FNL and ERA5 yielded similar temperature results. Although the average performance of PM2.5 and O3 predictions yielded by FNL and ERA5 was similar, large differences were observed in certain locations on specific days (e.g. in Hangzhou between 29 May and June 6, 2018 and in Hefei on 1–3 June 2018). Therefore, the choice of reanalysis data could be an important factor affecting the predictions of PM2.5 and O3, depending on locations and episodes. Comparable results were obtained using predictions with different horizontal resolutions, indicating that grid resolution was not crucial for determining the model performance of both PM2.5 and O3 during the campaign.
... With rapid economic growth and dramatic increase in energy consumption, China has been experiencing serious environment problems related to air pollution, leading to adverse impacts on human health [1,2] and socioeconomic development [3]. The air pollution issue has attracted increasing attention of all aspects of the society [4,5]. In recent years, a number of studies have investigated the spatial and temporal distribution of air pollution and pollutants in China [6][7][8][9]. ...
The Beijing–Tianjin–Hebei (BTH) air pollution transmission channel and its surrounding areas are of importance to air pollution control in China. Based on daily data of air quality index (AQI) and air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) from 2015 to 2016, this study analyzed the spatial and temporal characteristics of air pollution and influencing factors in Henan Province, a key region of the BTH air pollution transmission channel. The result showed that non-attainment days and NAQI were slightly improved at the provincial scale during the study period, whereas that in Hebi, Puyang, and Anyang became worse. PM2.5 was the largest contributor to the air pollution in all cities based on the number of non-attainment days, but its mean frequency decreased by 21.62%, with the mean occurrence of O3 doubled. The spatial distribution of NAQI presented a spatial agglomeration pattern, with high-high agglomeration area varying from Jiaozuo, Xinxiang, and Zhengzhou to Anyang and Hebi. In addition, the NAQI was negatively correlated with sunshine duration, temperature, relative humidity, wind speed, and positively to atmospheric pressure and relative humidity in all four clusters, whereas relationships between socioeconomic factors and NAQI differed among them. These findings highlight the need to establish and adjust regional joint prevention and control of air pollution as well as suggest that it is crucially important for implementing effective strategies for O3 pollution control.
... Urban air quality is generally assessed in terms of the PM concentrations of key pollutants ( Wang et al. 2013), which have both health and environmental impacts ( Su et al. 2010). Many researchers have examined the effects of vehicular emissions on urban air quality under the influence of factors such as urbanization, industrialization, transport, and meteorology (Qin and Liao 2016; Hu et al. 2017;Zhang et al. 2017). Pollution levels are much higher along roads and at roadsides than at other types of sites. ...
In this study, we compared particulate matter (PM) measurements (including PM10, PM2.5, heavy metals, and black carbon) between the 2014 rainy season (August to October) and dry season (March to May) in different urban areas within Ho Chi Minh City, Vietnam. PM10 and PM2.5 concentrations varied widely among the sampling sites during each season, with relative PM concentrations increasing in the following order: city zoo < rural area < residential area < roadside < city road. Higher PM10 and PM2.5 concentrations observed on roads and at roadsides were strongly correlated with vehicle activity. Heavy metals were found to be important atmospheric PM components with ranged from 131.77±42.13 to 233.13±79.88 µg m-3. Changes in black carbon concentration in Ho Chi Minh City may have been related to changes in meteorological conditions, and may in turn influence ambient air quality. These results provide useful reference information for urban development planning and environmental policy.
Keywords: Aerosol • Black carbon • Ho Chi Minh City • PM2.5 • PM10 • Vietnam
... The impact of emissions from CPPs on air quality and health in China has been investigated in previous work [1,2,[15][16][17][18][19][20][21][22][23]. Early studies (e.g. ...
Coal-fired power plants (CPPs) dominate China's energy supply systems. Over the past two decades, the explosive growth of CPPs has led to negative air quality and health impacts in China, and a series of control policies have been implemented to alleviate those impacts. In this work, by combining a CPPs emission database over China (CPED), a regional chemical transport model (WRF-CMAQ), and the integrated exposure-response model, we summarized historical and ongoing emission control policies on CPPs over China, investigated the air quality and health impacts of China's CPPs during 2005-2020, and quantified the benefits of each policy. We found that despite the 97.4% growth of coal-fired power generation during 2005-2015, PM2.5 exposures caused by emissions from China's CPPs decreased from 9.0 μg m⁻³ in 2005 to 3.6 μg m⁻³ in 2015. The active emission control policies have decreased CPPs-induced PM2.5 exposures by 10.0 μg m⁻³ during 2005-2015. We estimated that upgrading end-of-pipe control facilities and early retirement of small and low-efficiency units could respectively reduce PM2.5 exposures by 7.9 and 2.1 μg m⁻³ during 2005-2015 and avoid 111 900 and 31 400 annual premature deaths. Since 2015, China's government has further required all CPPs to comply with the so-called 'ultra-low emission standards' before 2020 as a major component of China's clean air actions. If the policy is fully deployed, CPPs-induced PM2.5 exposures could further decrease by 2.5 μg m⁻³ and avoid 43 500 premature deaths annually. Our study confirms the effectiveness of tailored control policies for China's CPPs and reveals that those policies have played important roles in air quality improvement in China.
... Huang et al. qualitatively study the relationship between fuel consumption for electricity and the resulting contributions to ambient concentrations of major air pollutants from the power sector [12]. They extend their work quantitatively by studying five development scenarios in an air quality model [13]. Additionally, Peng et al. evaluate various decarbonization scenarios for the electric power grid, in order to develop pathways to mitigate peaking emissions by 2030 in China, while simultaneously maximizing the air quality and health benefits [14]. ...
In this paper, we present an analytical framework to establish a closed-form relationship between electricity generation expansion planning decisions and the resulting negative health externalities. Typical electricity generation expansion planning models determine the optimal technology-capacity-investment strategy that minimizes total investment costs, and fixed and variable operating & maintenance costs. However, the relationship between these long-term planning decisions and the associated health externalities is highly stochastic and non-linear, and thus, is computationally expensive to evaluate. Thus, we develop a closed-form metamodel by executing computer-based experiments of a generation expansion planning model, and analyzing the resulting model outputs in a United States Environmental Protection Agency (EPA) screening tool that approximates the associated human health externalities. A procedural guidance to verify the accuracy and to select key metamodel parameters to enhance its prediction capability is presented. Specifically, the metamodel presented in this paper can predict the resulting health damages of long-term power grid expansion decisions, thus enabling researchers and policy makers to quickly assess the health implications of power grid expansion decisions with a high degree of certainty.
... In the worldwide, coal consumption rate has been fast increasing for the last decade [2]. However, coal can't completely be consumed by combustion, and so cause some pollutants directly to let out to atmosphere, which can cause environment pollution and also seriously threaten to human health [3]. Among which, fine particle, i.e. particulate matter (PM), is one kind of biggest harmful pollutant. ...
In order to study the mechanism of fine particle removal from flue gas by emulsion liquid membrane (ELM), adsorption model was investigated. Three adsorption kinetics equations (first order, second order and third order) were applied to simulate the uptake of fine particle from flue gas by ELM. The results show that the experimental data was fitted better with the pseudo-second-order equation model than those with other equation models. In order to further study the diffusion mechanism, the intraparticle diffusion model and the liquid film diffusion model were employed to study the adsorption mechanisms of ELM. The result suggests that the two stage adsorptions happened for fine particle from flue gas by ELM and these steps accord with intraparticle diffusion models.
... Chemical transport models (CTMs) were often used to evaluate effects of emission controlling policies on air quality. For example, Hu et al. (2017) used the Community Multi-scale Air Quality (CMAQ) to estimate the future scenarios of power development in China and found the power development plans would decrease PM 2.5 and PM 10 in Beijing but increase O 3 . The scenarios included low cost renewable energy and aggressive wind and solar energy for low emissions, 80% emission reduction in power sector to cap CO 2 emissions and relocation of power plants to western areas. ...
Air pollutants have been an urgent environmental problem in India due to adverse impacts on human health and social-economical lost. Different control strategies have been discussed to reduce air pollution, but possible outputs have not been identified. In this study, the Community Multi-scale Air Quality (CMAQ) model was applied to simulate potential benefits from future emission control with unchanged meteorology. Fourteen scenarios towards energy, residential, agriculture, industry, and open burning were simulated and the changes in ozone (O3) and PM2.5 as well as health outcomes were evaluated. PM2.5 concentrations decreased significantly by reducing uses of solid fuels (S4), uses of diesel generating sets (S13) and applying new standards to industry facilities (S11) with maximum reductions of ∼50 μg/m³, ∼30 μg/m³ and ∼15 μg/m³ in north India, separately. Reducing uses of solid fuels caused significant O3 reduction by maximum >8 ppb (S4, December), significant effects also occurred when applying new standards to current power plants (S1) (∼4 ppb, October.) and in S13 (∼3 ppb, December). Combination of all possible strategies would reduce O3, primary PM components (PPM) and total PM2.5 in December by >20 ppb, >40 μg/m³ and >60 μg/m³ in north India, while O3 and secondary inorganic aerosol (SIA) would increase by 5 ppb and 2 μg/m³ in October in western and southern India. SIA also increased in part of northern regions in December by ∼2 μg/m³. A total of up to 0.68 million premature mortality and 43% years of life lost (YLL) would be avoided by applying all controlling strategies.
... In terms of the CO 2 emissions and CO 2 intensity forecast in China, previous studies focused on industries such as the textile industry (Lin and Moubarak 2014), iron and steel industry (Karali et al. 2016), civil aviation industry (Zhou et al. 2016), power sector (Hu et al. 2017), building sector (Yang et al. 2017), and industrial sector , and specific regions were also considered, e.g., Beijing city (Feng and Zhang 2012), Jiangsu province (Yue et al. 2013), and Shandong province (Ren et al. 2015). Some studies forecast the total CO 2 emissions and CO 2 intensity in China. ...
Due to the increasingly severe situation regarding adaptation to climate change, global attention has focused on whether China can fulfill its commitment to the Paris Agreement as the largest producer of carbon dioxide (CO2) emissions. In this study, the CO2 emissions and CO2 intensities in China during 2030 were forecast using three scenarios, seven indicators, and a back-propagation neural network. Under the business as usual (BAU), strategic planning (SP), and low carbon (LC) scenarios, the predicted CO2 emissions in China during 2030 are 13,908.00, 11,837.60, and 9102.50 million tonnes, respectively, and the predicted CO2 intensities are 1.8652, 1.7405, and 1.5382 when considering carbon capture, utilization, and storage (CCUS). Furthermore, China cannot fulfill its commitment under the BAU scenario, whereas China will fulfill its commitment on schedule under the SP scenario. Under the LC scenario, China will fulfill its commitment ahead of schedule to reduce the CO2 intensity by 60% in 2025, and it will even reduce the CO2 intensity by 65% in 2030. In addition, if the amounts of CCUS are not considered for measuring the CO2 intensity, China can still fulfill its commitment under the LC scenario, whereas it cannot fulfill its commitment by 2030 under the SP scenario. This study evaluated the fulfillment of China’s commitment in the Paris Agreement, demonstrated that CCUS plays an important role in reducing the CO2 intensity, and provided policy suggestions for the Chinese government regarding the reductions of the CO2 intensity.
... Power generation has enormous influence on air pollution in China since it is mostly from thermal power plants [14]. But wind power not only can improve the environmental quality, but also can save primary energy consumptions as shown in Table 3. Obviously, during 2008 to 2015, comparing with the thermal power, the wind power saves 238.87 million tons of coal equivalent in total. ...
... An integrated modeling of the power system and the environmental impacts has been applied to the power market in the U.S. [58,59]. For China, some efforts have been made to use the output from power system models for a subsequent evaluation of the air quality and carbon impacts [60]. Future efforts that lead to further integration would be valuable. ...
Electrification with decarbonized electricity is a central strategy for carbon mitigation. End-use electrification can also reduce air pollutant emissions from the demand sectors, which brings public health co-benefits. Here we focus on electrification strategies for China, a country committed to both reducing air pollution and peaking carbon emissions before 2030. Considering both coal-intensive and decarbonized power system scenarios for 2030, we assess the air quality, health and climate co-benefits of various end-use electrification scenarios for the vehicle and residential sectors relative to a non-electrified coal-intensive business-as-usual scenario (BAU). Based on an integrated assessment using the regional air pollution model WRF-Chem and epidemiological concentration–response relationships, we find that coal-intensive electrification (75% coal) does not reduce carbon emissions, but can bring significant air quality and health benefits (41,000–57,000 avoided deaths in China annually). In comparison, switching to a half decarbonized power supply (∼50% coal) for electrification of the transport and/or residential sectors leads to a 14–16% reduction in carbon emissions compared to BAU, as well as greater air quality and health co-benefits (55,000–69,000 avoided deaths in China annually) than coal intensive electrification. Furthermore, depending on which end-use sector is electrified, we find different regional distributions of air quality and health benefits. While electrifying the transport sector improves air quality throughout eastern China, electrifying the residential sector brings most benefits to the North China Plain region in winter where coal-based heating contributes substantially to air pollution.
... 7 The Chinese government has already made significant efforts to reduce environmental pollution by formulating specific policies, laws, and regulations to address pollutant emissions from the thermal power industry, especially as it relates to coal-fired power plants. 8,9 Since 1998, flue gas desulfurization (FGD) has been essential for coal-fired power plants in China (where sulfur content in coal exceeded 1%) at standard conditions. In 2003, the SO 2 emission limit was set at 400 mg/m 3 at standard conditions for newly built power plants; however, in 2011, it was revised to 100 mg/m 3 at standard conditions for newly built power plants. ...
This paper presents an enhancement method to improve desulfurization performance of Wet Flue Gas Desulfurization (WFGD) by adding a flow pattern controlling (FPC) device in the spraying tower. The FPC device is characterized by a modular design and composed of FPC units that are fixed under the spraying layers of the desulfurization tower. Two kinds of FPC unit, each with a different scale, are designed (i.e., Unit A and Unit B). The effects of the FPC unit and operational parameters on the desulfurization process are determined by experimentation. The experiments show that the FPC unit significantly improve desulfurization performance, compared with the common spraying column without aperture plate. The flow regime significantly changes and large amounts of bubbles develop above the perforated plate in FPC unit, which is beneficial to enhance gas liquid mass transfer. The design style and structural parameters of the PRC unit both significantly influence the desulfurization performance. According to the results, optimal desulfurization performance is achieved with four holes and an aperture ratio of 0.65 for Unit B. For L/G=10 L/m3, the desulfurization efficiency of Unit B reaches 77 % (approximate 22 % increase) with a pressure increase of 370 Pa. The relationship between the operational parameters and the different scale units is investigated under different test conditions. In addition, the results show that the range of improvement with the perforated plate is related to the gas-liquid flow regime in the unit. Finally, we attempt to build an empirical correlation formula of each influence factor on desulfurization efficiency and pressure drop, based on the experimental results.
... Also, some studies seek to project future emissions reductions and environmental impacts of China's power sector. Kroeze et al. (2004) project emissions reductions of greenhouse gases from electricity production in China and India under different scenarios for 1990-2020; He et al. (2016) forecast the carbon emission trajectory for the Chinese power sector under four scenarios by 2050, and Hu et al. (2016) simulate the impacts of power generation on air quality in 2030, under five scenarios based on the Community Multiscale Air Quality (CMAQ) model. ...
This paper assesses the benefits and costs of five policies seeking to improve the energy efficiency and sustainability of China's electric power sector in the 13th five-year plan. It also estimates for each policy, the cost per ton of coal saved and the cost per ton of CO2, SO2, NOx, PM and mercury abated. Results show that, compared with a business as usual (BAU) case, the implementation of these policies will reduce coal consumption and CO2 emissions by 9.61–13.77% and will eliminate more than half of air pollutant emissions, at an annualized cost in the range of $43.5–97.4 billion. Among the policies analyzed, the development of renewable power and the mandate for retrofits of existing coal-fired power plants (CFPPs) are the most promising for reducing energy consumption and emissions; the former has the highest potential for reducing coal usage and CO2 emissions; while the latter can contribute the most to the reduction of air pollutant emissions. The two most cost-effective policies for reducing coal consumption and air emissions are a) imposing technology standards for new CFPPs and b) mandating retrofits for existing CFPPs. In contrast, the adoption of low-sulfur coal is the costliest policy.
... In order to control coal use and reach peak CO 2 emissions, the Chinese government has set goals of increasing the share of non-fossil energy to 20 percent in the total primary energy consumption by 2030 [8]. A lot of research has focused on the contribution of non-fossil energy development to lowering coal consumption and alleviating air pollution in China [5,[9][10][11][12][13][14][15]. However, little research has investigated the impact of non-fossil energy development on water consumption. ...
Electric power generation poses a high stress to the water supply in China. In this study, we quantified China's water consumption by electricity generation from 2015 to 2030 by considering different scenarios of electric power generation structure and water consumption intensity, and analyzed water consumption by different sources of electric power and its regional disparity. We found there is a significant difference in water consumption among the presented six scenarios with water consumption varying from 1.78 to 3.62 gigatonnes (Gt) in the year 2030. We also found that water consumption by coal-fired power decreases while water consumption by natural gas and nuclear power increases. Water consumption was and will still be concentrated in the three northern and coastal areas of China. However, the development of renewable power and adoption of water saving technology would contribute to water consumption reduction in these regions. We used a decomposition model for investigating the scale, structure and technology effects of electric power generation on water consumption, and found they present positive, negative and negative effects, respectively. The strongest factor in reducing water consumption is the technology effect, highlighting the importance of adopting water conserving cooling technology. Our findings yield important hints for China's water conserving policy making in renewable power development, cooling technology choices and siting decisions.
... Since wind power generation is a sustainable and clean source of energy with environmentally friendly production using green and renewable power [25][26][27][28][29][30][31][32][33][34], it is essential and necessary to promote the development of wind energy in China to solve the conflict between the energy depletion and environmental pollution. Furthermore, it requires comprehensive insight into the status and the future of wind energy in order to realize the sustainable development of energy, environment and economy in China as well as provide a reference for Chinese policy makers. ...
Due to the rapid economic development in China, the conflict between the increasing traditional energy consumption and the severe environmental threats is more and more serious. To ease the situation, greater use of wind energy in China could be the solution for energy conservation and sustainable environment in the long run. This paper describes the presentation of wind power in China, which covers distribution, bases, installed capacity, power generation from the spatial perspective and the environmental benefit. In addition, grey model (GM(1,1) ) and scenario analysis are employed to forecast the installed capacity in China from 2017 to 2025, then the evaluation of two methods is presented. By this research, the results are shown as the following: (1) the North region has great wind energy with 2500-3000 giga watt (GW) and the offshore wind energy in the Southeast is abundant; (2) the Inner Mongolia base located in North China makes a great contribution to wind power as well as having great potential for wind power development with the potential of 1300 GW; (3) the growth rate of installed capacity and wind power generation in China is declining with 100% in 2006 to 30% in 2015, 107% in 2009 to 17% in 2015, respectively; (4) the "three North" region has made a great contribution to current installed capacity and wind power generation with 74% and 71%, respectively; (5) wind power has significant environmental benefits with coal reduction of 23,887 × 10⁴ tce, CO2 reduction of 66,854 × 10⁴ tons and SO2 reduction of 173 × 10⁴ tons in total from 2008 to 2015; (6) the installed capacity in China from 2017 to 2025 is predicted utilizing a GM(1,1) model with 38,311.1810 × 10³ GW in 2025, while, with a scenario analysis, the installed capacity will reach up to 40,000 × 10³ GW in 2025 under the high GDP growth rate and 29,000 × 10³ GW in 2025 under the low GDP growth rate, respectively. Finally, it can be concluded that China has a solid foundation for the wind power development due to its abundant wind resources and great potential for wind power. Furthermore, the sustainable development can be guaranteed, and reduction in energy usage as well as emissions can be achieved by promoting wind power widely and effectively.
... Environmental pollution caused by SO 2 , such as acid rain and fog haze, is recognized as a global problem that adversely effects economy and public health [1]. China currently has the highest sulfur dioxide emissions in the world; therefore, the Chinese government has committed to reducing environmental pollution through the development and enforcement of relevant policies, laws and regulations [2,3]. ...
By participating in the construction of China's Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and as the core zone of the GBA, the region (PRD) aims to have the ambient air quality basically reaching the level of the world-class bay areas by 2035. In this study, we developed three scenario strategies (Moderate Scenario (SM), Intensified Scenario (SI) and Radical Scenario (SR)) for the PRD in 2035 taking the average annual PM2.5 concentrations in the PRD reaching the world health organization interim target 3 (WHO-III, 15 μg/m³) as the constraint standard. Under each scenario, we formulated the structural adjustment and end-of-pipe control measures to predict the development of industry, transportation and energy in the PRD in 2035. The results show that the total emissions of SO2, NOx, PM (Particulate Matters) and NMVOCs (Non-methane Volatile Organic Compounds) were 152, 511, 205 and 382kt in the SM scenario, respectively, and were 114, 436, 177 and 325kt in the SI scenario, respectively, while they are 77, 344, 143 and 269kt in the SR scenario, respectively. We also consider the emission reduction of pollutants outside the PRD. In this study, the SM, SI and SR scenarios were combined with different national scenario inventories (DPEC) in 2035 and the WRF-CMAQ model was used to simulate these scenarios. The simulation results show that annual average concentrations of PM2.5 in the PRD under the SM-DPEC1, SI-DPEC2 and SR-DPEC3 scenarios were expected to reach 15.1, 14.6 and 14.8 μg/m³, respectively, which just meet the WHO-III standard. In the process of achieving WHO-III target in the future, the government and policy makers can match the most suitable scenario in the study by referring to the actual decline of air pollutant emissions in the main contributing regions outside the PRD under each scenario, so as to obtain the best feasible control strategy in the PRD.
Emission control strategies, meteorological factors, and interregional atmospheric transport of pollutants are considered significant factors that affect PM2.5 concentrations in a city. In this research, two multiple linear regression models are proposed to achieve an accurate estimation of PM2.5 concentrations in Zibo City, Shandong Province of China. The influence of policy was considered as dummy variables in the models. First, a PM2.5–meteorological–policy–interregional model was constructed to explore the diversity of influences from all the parameters mentioned above. Second, for easy predictions of PM2.5 concentrations in the future, a PM2.5–meteorological–policy model was constructed considering meteorological factors from ground monitoring and pertinent air control policies. Data needed to construct the models were obtained from the monthly statistical data from Zibo and surrounding cities from January 2014 to September 2019. Then, the model predictions were extended to July 2021 and compared with the actual series. Model verification was revealed using goodness-of-fit and significant testing statistics. In specific, temperature, wind velocity, and the implementation of relative policies had clear effects on the PM2.5 concentrations in Zibo. Furthermore, Jinan, the provincial capital bordering Zibo to the west, made the largest contribution to fluctuations in PM2.5 concentrations in Zibo. Accordingly, the implementation of strict policies and regulations was undoubtedly a better measure to reduce PM2.5 concentrations in a city under certain topographic and climatic conditions.
The prices of fossil fuels, the gap between energy supply and demand, energy security, environmental issues, and the reduction of greenhouse gas emissions commonly promote the development of biomass power generation in China. Compared to direct biomass combustion power generation and biogas power generation, liquid biofuel power generation has better application potential. Policies and finance environment of countries and organizations have promoted the extensive application of biofuel power generation in recent years, especially in China. Evaluation of internal combustion engine, gas turbine and fuel cell on the stationary power station and mobile generation shows that gas turbine is the main generator-set, the fuel cell is the fastest-growing and future generator-set, while the engine is the first choice in transport and low power generation field. As the second, third and fourth generation biofuels, biomethanol, bioethanol, biodiesel and others have been researched and widely used in power generation. In addition, power generation performance and emissions have been improved to some extent after biofuels supplying. For the future, combined heat and power (CHP) generation and integrated gasification combined cycle (IGCC) is imperative development trends of power generation for higher energy and exergy efficiency. CHP based on the various generating facilities will be the next choice and direction of energy use trends for transport.
The Clean Air Action is considered an important measure to control air pollution. Despite extensive studies on the benefits or the cost of the Clean Air Action, the overall effect of such an action on green development is largely unknown. This paper tries to fill this gap. Based on panel data of 278 Chinese cities, this paper begins with the construction of a comprehensive indicator, namely green production efficiency, to reflect the green development over the period 2011 to 2016, we then implement the quasi-difference-in-differences framework to identify the policy effect of the Clean Air Action on green development. The following findings are obtained: (1) The Clean Air Action has enhanced the green development of Chinese cities, especially in areas with relatively high reduction target and rich resource endowment; (2) The dynamic analysis reveals that the positive effect of the Clean Air Action on green development presents an intensifying trend with time. This paper provides new insights to understand the Clean Air Action, based on these findings, we propose that future policies should focus on the transformation of overall green development and take full account of regional heterogeneity.
As the world's largest developing country, China has undergone ever-increasing demand for electricity during the past few decades. In 1996, China launched the Green Light Program (GLP), which became a national energy conservation activity for saving lighting electricity as well as an effective reduction of the coal consumption for power generation. Despite the great success of the GLP, its effects on haze have not been investigated and well understood. This study focused on assessing the potential coal saving induced by the improvement of luminous efficacy, the core of the GLP, and on estimating the consequent effects on the haze in the North China Plain (NCP), where a large number of power plants are located and are often engulfed by severe haze. The estimated potential coal saving induced by the GLP can reach a massive value of 120–323 million tons, accounting for 6.7 %–18.0 % of the total coal consumption for thermal power generation in China. There was a massive potential emission reduction of air pollutants from thermal power generation in the NCP, which was estimated to be 20.0–53.8 Gg for NOx and 6.9–18.7 Gg for SO2 in December 2015. The potential emission reduction induced by the GLP plays important roles in the haze formation, because the NOx and SO2 are important precursors for the formation of particles. To assess the impact of the GLP on haze, sensitivity studies were conducted by applying a regional chemical–dynamical model (WRF-CHEM). The model results suggest that in the case of lower-limit emission reduction, the PM2.5 concentration decreased by 2–5 µg m-3 in large areas of the NCP. In the case of upper-limit emission reduction, there was much more remarkable decrease in PM2.5 concentration (4–10 µg m-3). This study is a good example to illustrate that scientific innovation can induce important benefits for environment issues such as haze.
China suffers from serious haze pollution characterized by extremely low visibility due to intensive air pollutant emissions. Designing effective visibility impairment control strategies requires quantitative measures of the contributions of different sources. In this study, a source-oriented Community Multiscale Air Quality model was applied to quantitatively determine the source contributions to visibility impairment in China in 2013. Emissions of air pollutants from seven source categories (power plants, residential sources, industries, transportation, open burning, dust, and agriculture) were separately tracked. The industrial sector dominates the visibility impairment in Beijing, Chongqing, Guangzhou, and Shanghai, contributing to 32.6–40.7% of the overall light extinction coefficient (bext). Agriculture and power sources contribute 13.0–16.7% and 12.6–14.9% to bext, respectively. The residential sector is the largest source of visibility impairment in Xi’an (39.5%). It also contributes 12.3–25.2% in Beijing, Chongqing, Guangzhou, and Shanghai. Transportation (6.3–10.2%), open burning (1.7–8.8%), and dust emission (1.0–3.6%) have relatively smaller contributions to bext in these cities. The source contributions to bext exhibit strong spatial and seasonal variations. Contributions from industrial, power, and residential sectors are higher in the North China Plain, Northeast China, and Sichuan Basin than in other regions of China. Industrial and residential emissions become the most important sources of visibility impairment in winter. In other seasons, industrial, power, and agriculture sources are important. The large spatial and seasonal variations in the sources of bext suggest that different pollutants mitigation programs should be designed for different regions and times of the year.
As the world's largest developing country, China undergoes the ever-increasing demand for electricity during the past few decades. In 1996, China launched the Green Lights Program (GLP), which becomes a national energy conservation activity for saving lighting electricity, as well as an effective reduction of the coal consumption for power generation. Despite of the great success of the GLP, its effects on haze pollution have not been investigated and well understood. This study focused to assess the potential coal-saving induced by the GLP and to estimate the consequent improvements of the haze pollutions in the North China Plain (NCP), because severe haze pollutions often occur in the NCP and a large amount of power plants locate in this region. The estimated potential coal-saving induced by the GLP can reach a massive value of 120–323 million tons, accounting for 6.7–18.0 % of the total coal consumption for thermal power generation in China. In December 2015, there was a massive potential emission reduction of air pollutants from thermal power generation in the NCP, which was estimated to be 20.0–53.8 Gg for NOx and 6.9–18.7 Gg for SO2. The potential emission reductions induced by the GLP played important roles in the haze formation, because the NOx and SO2 are important precursors for the formation of particles. To assess the impact of the GLP on haze pollution, sensitive studies were conducted by applying a regional chemical/dynamical model (WRF-CHEM). The model results suggest that in the lower limit case of emission reduction, the PM2.5 concentration decreases by 2–5 µg m−3 in large areas of the NCP. In the upper limit case of emission reduction, there was much more remarkable decrease in PM2.5 concentration (4–10 µg m−3). This study is a good example to illustrate that scientific innovation can induce important benefits on environment issues, such as haze pollution.
Over the past 20 years, the spatial distribution of electrical generation and its relationship to cross-regional power transmission has impacted China's power generation system and significantly affected the total amount of NO x and the aggregated nitrogen oxides intensity (ANI) of the system. An investigation of the driving mechanisms of ANI that considers the unevenness of regional electricity generation will be crucial to future improvements in the NO x efficiency of the electrical generation system in China. In this study, we built a decomposition model for ANI by incorporating the spatial distribution of electrical generation and found that the spatial distribution of electricity generation together with energy-related factors gradually caused decreases in ANI. The efficiency of electricity generation presented the dominant inhibitory effect on ANI, but its effect size has weakened since 2010. In contrast, the fossil fuel structure of thermal power shows an increasingly positive effect on changes in ANI. The primary energy composition only slightly affected changes in ANI. Moreover, the changed geographical distribution of electricity generation is non-negligible and has a positive effect on reduction of the ANI of the Chinese electrical generation system. The transferred amount of local NO x emissions by cross-provincial electricity transmission, however, could cause lead to additional environmental costs for generators. This issue should receive more attention in the future.
As the most important form of power generation accounting for around 75% in Chinese power generation structure, thermal power generation is emitting multiple air pollutants, leading to serious environmental impairments and human health issues. An investigation of trends in regional features of pollutant emission and control cost is critical to better decision makings. By integrating GAINS-China model and spatial autocorrelation analysis, this study estimates and analyzes air pollutant (SO2 and NOx) emission, mitigation potential and control cost of thermal power generation in China's 31 regions from 2015 to 2030. The Business-as-Usual Scenario and Policy-Reinforced Scenario are set for comparison to quantify the effects of increasingly reinforced national emission control policies. The results show that up to 2030, with reinforced control policies and implementation of more abatement technologies, obvious mitigation effects of SO2 and NOx emission can be recognized. The regions with huge mitigation potential and higher total control cost are mainly located in the eastern coastal regions with higher gross domestic product and more power generation (such as Zhejiang, Shandong, and Jiangsu), as well as in the regions with abundant energy reserve and tremendous power supplied to other regions (such as Inner Mongolia and Shanxi). The spatial autocorrelation analysis verifies that there is significant regional disparity, as well as agglomeration effects of pollutant emission of thermal power generation. The results presented by this study are expected to provide policy makers with reference when formulating emission control policies and regional goals for thermal power generation.
The most seriously PM2.5 polluted city agglomeration has been identified by using the spatial autocorrelation model and the clustering analysis methods. The results indicated that cities which had heaviest pollution of PM2.5 were mainly located in the North China Plain (NCP) including Beijing, Tianjin, Shandong province, Henan province and Hebei province. Monthly means of PM2.5 in the most seriously polluted city agglomeration presented a U-sharp pattern, with a downward trend from January to March, basically stable but a slightly decreasing trend from April to September, and a sharply increasing trend from October to December. Serious pollution of PM2.5 in the heating season, mostly during the wintertime, might be caused by the direct emissions and secondary formation of PM2.5 accompanied by the combustion of biomass and fossil fuels for residential heating. According to the results of potential source contribution function (PSCF) calculations, the northern cities of the NCP (Beijing, Tianjing and cities of Hebei Privince) tended to be more influenced by the air masses originated locally during the heating season, while the southern cities of the NCP (cities of Shandong Province and northern Henan Province) were influenced not only by air masses originated locally, but also by air masses originated from adjacent Anhui Province and Jiangsu Province. Extraneous polluted air masses might be the main cause of the high levels of PM2.5 found in northern Henan.
Ambient air pollution brought by the rapid economic development and industrial production in China has exerted a significant influence on socio-economic activities and public health, especially in the densely populated urban areas. Therefore, scientific examination of regional variation of urban air quality and its dominant factors is of great importance to regional environmental management. Based on daily air quality index (AQI) datasets spanning from 2014 to 2016, this study analysed the spatiotemporal characteristics of air quality across different regions throughout China and ascertained the determinants of urban air quality in disparate regions. The main findings are as follows: (1) The annual average value of the urban AQI in China decreased from 2014 to 2016, indicating a desirable trend in air quality at the national scale. (2) The attainment rate of the urban AQI exhibited an apparent spatially stratified heterogeneity, wherein North China retained a high AQI value. The increase of Moran’s I Index reported an apparent spillover effect among adjacent regions. (3) Both at the national and regional scales, the seasonal tendency of air quality in each year is similar, wherein good in summer and relatively poor in winter. (4) Results drawn from the Geographic Detector analysis show that dominant factors influencing AQI vary significantly across urban agglomerations. Topographical and meteorological variations in urban areas may lead to complex spatiotemporal variations in pollutant concentration. Whereas given the same natural conditions, the human-dominated factors, such as industrial structure and urban form, exert significant impacts on urban air quality.The spatial spillover effects and regional heterogeneity of urban air quality illustrated in this study suggest the governments and institutions should set priority to the importance of regional cooperation and collaboration in light of environment regulation and pollution prevention.
Purpose:
The incidence of localized prostate cancer has declined with shifts in prostate cancer screening. While recent population-based studies demonstrate a stable incidence of loco-regional prostate cancer, this categorized organ-confined, extra-prostatic and lymph node positive disease together. The contemporary incidence of prostate cancer with pelvic lymph node metastases (PLNM) however, remains unknown.
Methods:
We used Surveillance, Epidemiology and End Results (SEER) from 2004 to 2014 to identify men diagnosed with prostate cancer. We analyzed trends in the age-standardized prostate cancer incidence by stage. Impact of extent of disease on mortality was assessed by adjusted-Cox proportional hazard analysis.
Results:
During the study period, the annual incidence of non-metastatic prostate cancer declined from 5119.1 per million to 2931.9 per million (Incidence ratio [IR]: 0.57, 95% confidence interval [CI]: 0.56-0.58, p<0.01), while PLNM increased from 54.1 per million to 79.5 per million (IR: 1.47, 95%CI: 1.33-1.62, p<0.01). The incidence of distant metastases in men aged 75 years and over nadired in 2011 compared to 2004 (IR: 0.81, 95%CI: 0.74-0.90, p<0.01), and increased in 2012 (IR: 1.13, 95%CI: 1.02-1.24, p<0.05) compared to 2011. Risk of cancer specific mortality was significantly increased in men diagnosed with PLNM (hazard ratio [HR]: 4.5, 95% confidence interval [CI]: 4.2-4.9, p<0.01) and distant metastases (HR: 21.9, 95% CI: 21.2-22.7, p<0.01) compared to non-metastatic disease.
Conclusions:
The incidence of PLNM is increasing, coincident with a decline in detection of localized disease. Whether this portends an increase in the burden of advanced disease or simply reflects diminished lead-time remains unclear. However, this should be monitored closely, as the increase in N1 disease reflects an increase in incurable prostate cancer at diagnosis.
A high-resolution inventory of primary atmospheric pollutants from coal-fired power plants in Shaanxi in 2012 was built based on a detailed database compiled at unit level involving unit capacity, boiler size and type, commission time, corresponding control technologies, and average coal quality of 72 power plants. The pollutants included SO2, NOx, fine particulate matter (PM2.5), inhalable particulate matter (PM10), organic carbon (OC), elemental carbon (EC), carbon monoxide (CO) and non-methane volatile organic compounds (NMVOC). Emission factors for SO2, NOx, PM2.5 and PM10 were adopted from standardized official promulgation, supplemented by those from local studies. The estimated annual emissions of SO2, NOx, PM2.5, PM10, EC, OC, CO and NMVOC were 152.4, 314.8, 16.6, 26.4, 0.07, 0.27, 64.9 and 2.5kt, respectively. Small units (<100MW), which accounted for ~60% of total unit numbers, had less coal consumption but higher emission rates compared to medium (≥100MW and <300MW) and large units (≥300MW). Main factors affecting SO2, NOx, PM2.5 and PM10 emissions were decontamination efficiency, sulfur content and ash content of coal. Weinan and Xianyang were the two cities with the highest emissions, and Guanzhong Plain had the largest emission density. Despite the projected growth of coal consumption, emissions would decrease in 2030 due to improvement in emission control technologies and combustion efficiencies. SO2 and NOx emissions would experience significant reduction by ~81% and ~84%, respectively. PM2.5, PM10, EC and OC would be decreased by ~43% and CO and NMVOC would be reduced by ~16%.
China is now the largest power producer and consumer in the world. The coal-dominating fuel mix makes its power sector an important source for both CO2 and environmental pollutants. Coal supplies three quarters of China’s electricity generation, followed by hydropower, wind, nuclear, natural gas, and solar energy. Coal-fired power plants have been critical for meeting China’s electricity demand and powering the economic growth, while they also lead to environmental challenges such as severe air and water pollution, climate change, and resource exploitation. The unprecedented and unacceptable environmental crises decry a grand, urgent transition of China’s power sector to reduce pollution, mitigate greenhouse gas emissions and enhance efficiencies. Potential solutions include fuel switch, end-of-the-pipe removal of pollutants, energy efficiency improvement and resource conservation. Various policy instruments are in the toolbox for being applied in practice. To explore the current scientific understanding of power generation, environmental challenges, and potential solutions in China, this special issue puts together a comprehensive set of articles including reviews, cutting-edge researches, and critical commentaries.
In this paper, we reviewed four key themes in the study of clean power transition in China, the resources potential, the technology advancement, the air pollution control, and the policy and reform of the power sector. In each theme, we summarized the ongoing research development and highlighted some key areas for further study. Given that China’s power sector transition is a huge task, we hope this review will add some discussions into the ongoing conversation.
The excessive coal consumption plays an important role in the city haze in the Jing-Jin-Ji region. In this study, we evaluate health benefits resulting from coal control and air pollutants abatement in the Jing-Jin-Ji region employing the dose-response function. The estimation of total valuation has a range of 366.64–810.48 billion RMB for the whole region from 2015 to 2025 and the coal contribution to the economic benefits of air pollution mitigation is more than 50%. The considerable economic value of benefits makes it more attractive for the government to set stringent pollutants reduction target and the results are strong enough to provide air pollution control policy guidance.
As the fast growth of China’s economy, power generation has greatly increased in past decades. Majority of power generation in China is from coal-fired power plants. Large and still increasing amount of coal combustion for power generation emits numerous pollutants into atmosphere. Combining with emissions from other sources, power generation contributes to the severe air pollution in recent years. In this study, the historic trends and current status of the impact of power generation on air quality in China are overviewed. In 2012, the power sector contributed 30% of CO2, 33% of NOx, 23% of SO2, 8% of particulate matter (PM), 3% of CO, and less than 1% of VOCs emissions in China. The power sector contributed 15% of NOx, 13% of SO2, 27% of O3, 26% of fine particulate NO3− and 22% of fine particulate SO42− ambient concentrations. Coal consumption for power generation is keeping growing. Tremendous efforts have been made to limit emissions from power generation by installing flue-gas desulphurization systems on coal-fired power plant, resulting in reduction of SO2 and PM emissions recently. However, emissions of NOx, CO2, CO, and VOCs are still increasing. Over half of the power emissions and concentrations are distributed in East and North China, which include the Yangtze River Delta and the North China Plain, the two most developed and populous regions in China. Emissions from power generation contribute significant fractions of NOx, SO2, and particulate NO3− in winter, and significant fractions of O3 and particulate SO42− in summer.
We have updated the Regional Emission inventory in ASia (REAS) as version
2.1. REAS 2.1 includes most major air pollutants and greenhouse gases from
each year during 2000 and 2008 and following areas of Asia: East, Southeast,
South, and Central Asia and the Asian part of Russia. Emissions are estimated
for each country and region using updated activity data and parameters.
Monthly gridded data with a 0.25° × 0.25°
resolution are also provided. Asian emissions for each species in 2008 are as
follows (with their growth rate from 2000 to 2008): 56.9 Tg (+34%) for
SO2, 53.9 Tg (+54%) for NOx, 359.5 Tg (+34%) for CO,
68.5 Tg (+46%) for non-methane volatile organic compounds, 32.8 Tg
(+17%) for NH3, 36.4 Tg (+45%) for PM10, 24.7 Tg (+42%)
for PM2.5, 3.03 Tg (+35%) for black carbon, 7.72 Tg (+21%) for
organic carbon, 182.2 Tg (+32%) for CH4, 5.80 Tg (+18%) for
N2O, and 16.0 Pg (+57%) for CO2. By country, China and India were
respectively the largest and second largest contributors to Asian emissions.
Both countries also had higher growth rates in emissions than others because
of their continuous increases in energy consumption, industrial activities,
and infrastructure development. In China, emission mitigation measures have
been implemented gradually. Emissions of SO2 in China increased from
2000 to 2006 and then began to decrease as flue-gas desulphurization was
installed to large power plants. On the other hand, emissions of air
pollutants in total East Asia except for China decreased from 2000 to 2008
owing to lower economic growth rates and more effective emission regulations
in Japan, South Korea, and Taiwan. Emissions from other regions generally
increased from 2000 to 2008, although their relative shares of total Asian
emissions are smaller than those of China and India. Tables of annual
emissions by country and region broken down by sub-sector and fuel type, and
monthly gridded emission data with a resolution of 0.25° × 0.25° for the major sectors are available
from the following URL: http://www.nies.go.jp/REAS/.
Severe regional haze pollution events occurred in eastern and
central China in January 2013, which had adverse effects on the
environment and public health. Extremely high levels of particulate
matter with aerodynamic diameter of 2.5 μm or less
(PM2.5) with dominant components of sulfate and nitrate
are responsible for the haze pollution. Although heterogeneous
chemistry is thought to play an important role in the production of
sulfate and nitrate during haze episodes, few studies have
comprehensively evaluated the effect of heterogeneous chemistry on
haze formation in China by using the 3-D models due to of a lack of
treatments for heterogeneous reactions in most climate and chemical
transport models. In this work, the offline-coupled WRF-CMAQ model
with newly added heterogeneous reactions is applied to East Asia to
evaluate the impacts of heterogeneous chemistry and the
meteorological anomaly during January 2013 on regional haze
formation. The revised CMAQ with heterogeneous chemistry not only
captures the magnitude and temporal variation of sulfate and
nitrate, but also reproduces the enhancement of relative
contribution of sulfate and nitrate to PM2.5 mass from
clean days to polluted haze days. These results indicate the
significant role of heterogeneous chemistry in regional haze
formation and improve the understanding of the haze formation
mechanisms during the January 2013 episode.
The Fire INventory from NCAR version 1.0 (FINNv1) provides daily, 1 km resolution, global estimates of the trace gas and particle emissions from open burning of biomass, which includes wildfire, agricultural fires, and prescribed burning and does not include biofuel use and trash burning. Emission factors used in the calculations have been updated with recent data, particularly for the non-methane organic compounds (NMOC). The resulting global annual NMOC emission estimates are as much as a factor of 5 greater than some prior estimates. Chemical speciation profiles, necessary to allocate the total NMOC emission estimates to lumped species for use by chemical transport models, are provided for three widely used chemical mechanisms: SAPRC99, GEOS-CHEM, and MOZART-4. Using these profiles, FINNv1 also provides global estimates of key organic compounds, including formaldehyde and methanol. The uncertainty in the FINNv1 emission estimates are about a factor of two; but, the estimates agree closely with other global inventories of biomass burning emissions for CO, CO2, and other species with less variable emission factors. FINNv1 emission estimates have been developed specifically for modeling atmospheric chemistry and air quality in a consistent framework at scales from local to global. The product is unique because of the high temporal and spatial resolution, global coverage, and the number of species estimated. FINNv1 can be used for both hindcast and forecast or near-real time model applications and the results are being critically evaluated with models and observations whenever possible.
The main objective of this study is to investigate the formation and evolution mechanism of the regional haze in megacity Beijing by analyzing the process of a severe haze that occurred 20–27 September 2011. Mass concentration and size distribution of aerosol particles as well as aerosol optical properties were concurrently measured at the Beijing urban atmospheric environment monitoring station. Gaseous pollutants (SO2, NO-NO2-NOx, O3, CO) and meteorological parameters (wind speed, wind direction, and relative humidity) were simultaneously monitored. Meanwhile, aerosol spatial distribution and the height of planetary boundary layer (PBL) were retrieved from the signal of satellite and LIDAR (light detection and ranging). Concentrations of NO, NO2, SO2, O3, and CO observed during 23–27 September had exceeded the national ambient air quality standards for residents. The mass concentration of PM2.5 gradually accumulated during the measurement and reached at 220 μg m−3 on 26 September, and the corresponding atmospheric visibility was only 1.1 km. The daily averaged AOD in Beijing increased from ~ 0.16 at λ = 500 nm on 22 September and reached ~ 3.5 on 26 September. The key factors that affected the formation and evolution of this haze episode were stable anti-cyclone synoptic conditions at the surface, decreasing of the height of PBL, heavy pollution emissions from urban area, number and size evolution of aerosols, and hygroscopic growth for aerosol scattering. This case study may provide valuable information for the public to recognize the formation mechanism of the regional haze event over the megacity, which is also useful for the government to adopt scientific approach to forecast and eliminate the occurrence of regional haze in China.
This paper, which focuses on emissions from China's coal-fired power plants
during 1990–2010, is the second in a series of papers that aims to develop a
high-resolution emission inventory for China. This is the first time that
emissions from China's coal-fired power plants were estimated at unit level
for a 20-year period. This inventory is constructed from a unit-based database
compiled in this study, named the China coal-fired Power plant Emissions
Database (CPED), which includes detailed information on the technologies,
activity data, operation situation, emission factors, and locations of
individual units and supplements with aggregated data where unit-based
information is not available. Between 1990 and 2010, compared to a 479 %
growth in coal consumption, emissions from China's coal-fired power plants
increased by 56, 335, and 442 % for SO2, NOx, and
CO2, respectively, and decreased by 23 and 27 % for PM2.5
and PM10 respectively. Driven by the accelerated economic growth, large
power plants were constructed throughout the country after 2000, resulting
in a dramatic growth in emissions. The growth trend of emissions has been
effectively curbed since 2005 due to strengthened emission control measures
including the installation of flue gas desulfurization (FGD) systems and the
optimization of the generation fleet mix by promoting large units and
decommissioning small ones. Compared to previous emission inventories, CPED
significantly improved the spatial resolution and temporal profile of the power
plant emission inventory in China by extensive use of underlying data at
unit level. The new inventory developed in this study will enable a close
examination of temporal and spatial variations of power plant emissions in
China and will help to improve the performances of chemical transport models
by providing more accurate emission data.
China has been experiencing severe air pollution in recent decades. Although ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research & Forecasting model (WRF) and the Community Multi-scale Air Quality model (CMAQ) was conducted to provide detailed temporal and spatial information of ozone (O3), PM2.5 total and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, over-prediction of O3 generally occurs at low concentration range while under-prediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in Southern China than in Northern, Central and Sichuan basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of CMAQ model in reproducing severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.
This paper, which focuses on emissions from China's coal-fired power plants during 1990–2010, is the second in a series of papers that aims to develop high-resolution emission inventory for China. This is the first time that emissions from China's coal-fired power plants were estimated at unit level for a 20 year period. This inventory is constructed from a unit-based database compiled in this study, named the China coal-fired Power plant Emissions Database (CPED), which includes detailed information on the technologies, activity data, operation situation, emission factors, and locations of individual units and supplements with aggregated data where unit-based information is not available. Between 1990 and 2010, compared to a 479 % growth in coal consumption, emissions from China's coal-fired power plants increased by 56, 335 and 442 % for SO2, NOx and CO2, respectively, and decreased by 23 % for PM2.5. Driven by the accelerated economy growth, large power plants were constructed throughout the country after 2000, resulting in dramatic growth in emissions. Growth trend of emissions has been effective curbed since 2005 due to strengthened emission control measures including the installation of flue-gas desulfurization (FGD) systems and the optimization of the generation fleet mix by promoting large units and decommissioning small ones. Compared to previous emission inventories, CPED significantly improved the spatial resolution and temporal profile of power plant emission inventory in China by extensive use of underlying data at unit level. The new inventory developed in this study will enable a close examination for temporal and spatial variations of power plant emissions in China and will help to improve the performances of chemical transport models by providing more accurate emission data.
This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05 degrees x 0.05 degrees grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.
While several cohort studies report associations between chronic exposure to fine particles (PM2.5) and mortality, few have studied the effects of chronic exposure to ultrafine (UF) particles. In addition, few studies have estimated the effects of the constituents of either PM2.5 or UF particles.
We used a statewide cohort of over 100,000 women from the California Teachers Study who were followed from 2001 through 2007. Exposure data at the residential level were provided by a chemical transport model that computed pollutant concentrations from over 900 sources in California. Besides particle mass, monthly concentrations of 11 species and 8 sources or primary particles were generated at 4 km grids. We used a Cox proportional hazards model to estimate the association between the pollutants and all-cause, cardiovascular, ischemic heart disease (IHD) and respiratory mortality.
We observed statistically significant (p < 0.05) associations of IHD with PM2.5 mass, nitrate elemental carbon (EC), copper (Cu), and secondary organics and the sources gas- and diesel-fueled vehicles, meat cooking, and high sulfur fuel combustion. The hazard ratio estimate of 1.19 (95% CI: 1.08, 1.31) for IHD in association with a 10-µg/m(3) increase in PM2.5 is consistent with findings from the American Cancer Society cohort. We also observed significant positive associations between IHD and several UF components including EC, Cu, metals, and mobile sources.
Using an emissions-based model with a 4 km spatial scale, we observed significant positive associations between IHD mortality and both fine and ultrafine particle species and sources. Our results suggest that the exposure model effectively measured local exposures and facilitated the examination of the relative toxicity of particle species.
China committed itself to reduce the carbon intensity of its economy (the amount of CO2 emitted per unit of GDP) by 40-45% during 2005-2020. Yet, between 2002 and 2009, China experienced a 3% increase in carbon intensity, though trends differed greatly among its 30 provinces. Decomposition analysis shows that sectoral efficiency gains in nearly all provinces were offset by movement towards a more carbon-intensive economic structure. Such a sectoral shift seemed to be heavily affected by the growing role of investments and capital accumulation in China/'s growth process which has favoured sectors with high carbon intensity. Panel data regressions show that changes in carbon intensity were smallest in sectors dominating the regional economy (so as not to endanger these large sectors, which are the mainstay of the provincial economy), whereas scale and convergence effects played a much smaller role.
Rapid industrialization and urbanization in developing countries has led to an increase in air pollution, along a similar trajectory to that previously experienced by the developed nations. In China, particulate pollution is a serious environmental problem that is influencing air quality, regional and global climates, and human health. In response to the extremely severe and persistent haze pollution experienced by about 800 million people during the first quarter of 2013 (refs 4, 5), the Chinese State Council announced its aim to reduce concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 micrometres) by up to 25 per cent relative to 2012 levels by 2017 (ref. 6). Such efforts however require elucidation of the factors governing the abundance and composition of PM2.5, which remain poorly constrained in China. Here we combine a comprehensive set of novel and state-of-the-art offline analytical approaches and statistical techniques to investigate the chemical nature and sources of particulate matter at urban locations in Beijing, Shanghai, Guangzhou and Xi'an during January 2013. We find that the severe haze pollution event was driven to a large extent by secondary aerosol formation, which contributed 30-77 per cent and 44-71 per cent (average for all four cities) of PM2.5 and of organic aerosol, respectively. On average, the contribution of secondary organic aerosol (SOA) and secondary inorganic aerosol (SIA) are found to be of similar importance (SOA/SIA ratios range from 0.6 to 1.4). Our results suggest that, in addition to mitigating primary particulate emissions, reducing the emissions of secondary aerosol precursors from, for example, fossil fuel combustion and biomass burning is likely to be important for controlling China's PM2.5 levels and for reducing the environmental, economic and health impacts resulting from particulate pollution.
The influence of air pollutants, especially aerosols, on regional and global climate has been widely investigated, but only a very limited number of studies report their impacts on everyday weather. In this work, we present for the first time direct (observational) evidence of a clear effect of how a mixed atmospheric pollution changes the weather with a substantial modification in the air temperature and rainfall. By using comprehensive measurements in Nanjing, China, we found that mixed agricultural burning plumes with fossil fuel combustion pollution resulted in a decrease in the solar radiation intensity by more than 70%, a decrease in the sensible heat by more than 85%, a temperature drop by almost 10 K, and a change in rainfall during both daytime and nighttime. Our results show clear air pollution–weather interactions, and quantify how air pollution affects weather via air pollution–boundary layer dynamics and aerosol–radiation–cloud feedbacks. This study highlights cross-disciplinary needs to investigate the environmental, weather and climate impacts of the mixed biomass burning and fossil fuel combustion sources in East China.
Significance
International trade affects global air pollution and transport by redistributing emissions related to production of goods and services and by potentially altering the total amount of global emissions. Here we analyze the trade influences by combining an economic-emission analysis on China’s bilateral trade and atmospheric chemical transport modeling. Our focused analysis on US air quality shows that Chinese air pollution related to production for exports contributes, at a maximum on a daily basis, 12–24% of sulfate pollution over the western United States. The US outsourcing of manufacturing to China might have reduced air quality in the western United States with an improvement in the east, due to the combined effects of changes in emissions and atmospheric transport.
We have updated the Regional Emission inventory in ASia (REAS) as
version 2.1. REAS 2.1 includes most major air pollutants and greenhouse
gases from each year during 2000 and 2008 and following areas of Asia:
East, Southeast, South, and Central Asia and the Asian part of Russia.
Emissions are estimated for each country and region using updated
activity data and parameters. Monthly gridded data with a 0.25 ×
0.25° resolution are also provided. Asian emissions for each species
in 2008 are as follows (with their growth rate from 2000 to 2008): 56.9
Tg (+34%) for SO2, 53.9 Tg (+54%) for NOx, 359.5
Tg (+34%) for CO, 68.5 Tg (+46%) for non-methane volatile organic
compounds, 32.8 Tg (+17%) for NH3, 36.4 Tg (+45%) for
PM10, 24.7 Tg (+42%) for PM2.5, 3.03 Tg (+35%) for
black carbon, 7.72 Tg (+21%) for organic carbon, 182.2 Tg (+32%) for
CH4, 5.80 Tg (+18%) for N2O, and 16.7 Pg (+59%)
for CO2. By country, China and India were respectively the
largest and second largest contributors to Asian emissions. Both
countries also had higher growth rates in emissions than others because
of their continuous increases in energy consumption, industrial
activities, and infrastructure development. In China, emission
mitigation measures have been implemented gradually. Emissions of
SO2 in China increased from 2000 to 2006 and then began to
decrease as flue-gas desulfurization was installed to large power
plants. On the other hand, emissions of air pollutants in total East
Asia except for China decreased from 2000 to 2008 owing to lower
economic growth rates and more effective emission regulations in Japan,
South Korea, and Taiwan. Emissions from other regions generally
increased from 2000 to 2008, although their relative shares of total
Asian emissions are smaller than those of China and India. Tables of
annual emissions by country and region broken down by sub-sector and
fuel type, and monthly gridded emission data with a resolution of 0.25
× 0.25° for the major sectors are available from the following
url: http://www.nies.go.jp/REAS/
.
Using OMI (Ozone Monitoring Instrument) tropospheric NO2
columns and a nested-grid 3-D global chemical transport model
(GEOS-Chem), we investigated the growth in NOx emissions from
coal-fired power plants and their contributions to the growth in
NO2 columns in 2005-2007 in China. We first developed a
unit-based power plant NOx emission inventory for 2005-2007
to support this investigation. The total capacities of coal-fired power
generation have increased by 48.8% in 2005-2007, with 92.2% of the total
capacity additions coming from generator units with size ≥300 MW. The
annual NOx emissions from coal-fired power plants were
estimated to be 8.11 Tg NO2 for 2005 and 9.58 Tg
NO2 for 2007, respectively. The modeled summer average
tropospheric NO2 columns were highly correlated
(R2 = 0.79-0.82) with OMI measurements over grids dominated
by power plant emissions, with only 7-14% low bias, lending support to
the high accuracy of the unit-based power plant NOx emission
inventory. The ratios of OMI-derived annual and summer average
tropospheric NO2 columns between 2007 and 2005 indicated that
most of the grids with significant NO2 increases were related
to power plant construction activities. OMI had the capability to trace
the changes of NOx emissions from individual large power
plants in cases where there is less interference from other
NOx sources. Scenario runs from GEOS-Chem model suggested
that the new power plants contributed 18.5% and 10% to the annual
average NO2 columns in 2007 in Inner Mongolia and North
China, respectively. The massive new power plant NOx
emissions significantly changed the local NO2 profiles,
especially in less polluted areas. A sensitivity study found that
changes of NO2 shape factors due to including new power plant
emissions increased the summer average OMI tropospheric NO2
columns by 3.8-17.2% for six selected locations, indicating that the
updated emission information could help to improve the satellite
retrievals.
1] The published literature debates the extent to which naturally occurring stratospheric ozone intrusions reach the surface and contribute to exceedances of the U.S. National Ambient Air Quality Standard (NAAQS) for ground-level ozone (75 ppbv implemented in 2008). Analysis of ozonesondes, lidar, and surface measurements over the western U.S. from April to June 2010 show that a global high-resolution (70–86 ppbv at surface sites. With a stratospheric ozone tracer defined relative to a dynamically varying tropopause, we find that stratospheric intrusions can episodically increase surface MDA8 ozone by 20–40 ppbv (all model estimates are bias corrected), including on days when observed ozone exceeds the NAAQS threshold. These stratospheric intrusions elevated background ozone concentrations (estimated by turning off North American anthropogenic emissions in the model) to MDA8 values of 60–75 ppbv. At high-elevation western U.S. sites, the 25th–75th percentile of the stratospheric contribution is 15–25 ppbv when observed MDA8 ozone is 60–70 ppbv, and increases to $17–40 ppbv for the 70–85 ppbv range. These estimates, up to 2–3 times greater than previously reported, indicate a major role for stratospheric intrusions in contributing to springtime high-O 3 events over the high-altitude western U.S., posing a challenge for staying below the ozone NAAQS threshold, particularly if a value in the 60–70 ppbv range were to be adopted. (2012), Springtime high surface ozone events over the western United States: Quantifying the role of stratospheric intrusions, J. Geophys. Res., 117, D00V22, doi:10.1029/2012JD018151.
This paper suggests that the rapid increase in urbanization and human activities has important impacts on visibility in the Pearl River Delta (PRD) region. A long-term trend of visibility in Guangzhou (one of the largest cities in PRD) shows that between 1954 and 2006, there is a rapid change in visibility. Between 1954 and 1972, low visibility has the smallest occurrence (less than a few days per year). Between 1972 and 1980, the visibility condition is within a transition period, and the occurrence of low visibility increases rapidly. Between 1980 and 2006, the occurrence of low visibility remains very high (150 days year−1), suggesting that the city of Guangzhou is often under low-visibility conditions since the 1980s. In order to understand the causes of the low visibility in Guangzhou, we analyze physical and chemical characterizations of a low-visibility event occurring between 15 and 29 November 2005. The analysis suggests that high concentration of aerosol particles is a major cause for the low visibility. The threshold aerosol concentration that is corresponding to the low visibility (<10 km) is about 120 μg m−3. Further analysis indicates that the relationship between aerosol concentrations and visibility appears in a non-linearity correlation. When aerosol concentrations are very high (above 120 μg m−3), the change in visibility is not sensitive to aerosol concentration. By contrast, when aerosol concentrations are <120 μg m−3, the change in visibility is very sensitive to aerosol concentrations. This study also shows that absorbing aerosol particles (such as element carbon (EC)) play important roles in the reduction of visibility. In most cases, the extremely low visibility (<2 km) is often resulted from high EC concentrations (above 15 μg m−3). In averaged condition, small scattering aerosol particles (<1 μm in radius) have the largest contribution to the reduction of visibility (about 70%). By contrast, large scattering particles have the smallest contribution to the reduction of visibility. This analysis implies that the persistent low visibility is mainly resulted from small aerosol particles, including both scattering and absorbing particles. In order to improve the visibility in the Guangzhou region, the reduction of small particle emissions is urgently needed. This study suggests that there are two important steps to improve the visibility in Guangzhou. First, the aerosol concentration should be reduced to less than the threshold value (120 μg m−3). Second, a further decrease in aerosols from its threshold value will lead to a significant improvement in visibility due to the non-linearity relationship between aerosol and visibility.
The Community Multiscale Air Quality modeling system is used to study the intercontinental transport of air pollution across the Pacific region. Baseline simulations are conducted for January, April, July, and October 2001 at a 108 km horizontal grid resolution. A sensitivity simulation is conducted for April 2001 to study the impact of Asian anthropogenic emissions on the United States's air quality. Process analysis is conducted to study pollutant formation and transport and to quantify the relative contributions of atmospheric processes to ozone (O3) and fine particulate matter (PM2.5). Model simulations are evaluated with available surface, aircraft, and satellite observations. Simulated meteorology basically captures the synoptic pattern, but precipitation amounts are significantly underpredicted. Most of the PM2.5 components are overestimated over the United States and most gases are underestimated over east Asia. Simulated NO2 and CO columns agree well with satellite observations. Aerosol optical depths and tropospheric O3 residuals are underpredicted, especially in July. The simulated horizontal fluxes and process analyses show that the transport in the lower free troposphere followed by a large-scale subsidence over the United States provides a major Asian pollution export pathway for most pollutants, while the transport in the planetary boundary layer also plays an important role, especially for CO, O3, PM2.5, and SO4 2-. The background concentrations of O3 and SO4 2- in the western United States can increase by ~1 ppb (~2.5%) and 0.4 mug m-3 (~20%) in monthly average, up to 2.5 ppb and 1.0 mug m-3 in daily average, respectively, due to the Asian emissions in April.
To reduce airborne soot, organics and sulphates, tailored strategies for
each must be established and coal use limited, say Qiang Zhang, Kebin He
and Hong Huo.
The Fire INventory from NCAR version 1.0 (FINNv1) provides daily, 1 km resolution, global estimates of the trace gas and particle emissions from open burning of biomass, which includes wildfire, agricultural fires, and prescribed burning and does not include biofuel use and trash burning. Emission factors used in the calculations have been updated with recent data, particularly for the non-methane organic compounds (NMOC). The resulting global annual NMOC emission estimates are as much as a factor of 5 greater than some prior estimates. Chemical speciation profiles, necessary to allocate the total NMOC emission estimates to lumped species for use by chemical transport models, are provided for three widely used chemical mechanisms: SAPRC99, GEOS-CHEM, and MOZART-4. Using these profiles, FINNv1 also provides global estimates of key organic compounds, including formaldehyde and methanol. The uncertainty in the FINNv1 emission estimates are about a factor of two; but, the estimates agree closely with other global inventories of biomass burning emissions for CO, CO2, and other species with less variable emission factors. FINNv1 emission estimates have been developed specifically for modeling atmospheric chemistry and air quality in a consistent framework at scales from local to global. The product is unique because of the high temporal and spatial resolution, global coverage, and the number of species estimated. FINNv1 can be used for both hindcast and forecast or near-real time model applications and the results are being critically evaluated with models and observations whenever possible.
Several studies have reported associations between long-term exposure to ambient fine particulate matter (PM) and cardiovascular mortality. However, the health impacts of long-term exposure to specific constituents of PM(2.5) (PM with aerodynamic diameter < or = 2.5 microm) have not been explored.
We used data from the California Teachers Study, a prospective cohort of active and former female public school professionals. We developed estimates of long-term exposures to PM(2.5) and several of its constituents, including elemental carbon, organic carbon (OC), sulfates, nitrates, iron, potassium, silicon, and zinc. Monthly averages of exposure were created using pollution data from June 2002 through July 2007. We included participants whose residential addresses were within 8 and 30 km of a monitor collecting PM(2.5) constituent data. Hazard ratios (HRs) were estimated for long-term exposure for mortality from all nontraumatic causes, cardiopulmonary disease, ischemic heart disease (IHD), and pulmonary disease.
Approximately 45,000 women with 2,600 deaths lived within 30 km of a monitor. We observed associations of all-cause, cardiopulmonary, and IHD mortality with PM(2.5) mass and each of its measured constituents, and between pulmonary mortality and several constituents. For example, for cardiopulmonary mortality, HRs for interquartile ranges of PM(2.5), OC, and sulfates were 1.55 [95% confidence interval (CI), 1.431.69], 1.80 (95% CI, 1.681.93), and 1.79 (95% CI, 1.582.03), respectively. Subsequent analyses indicated that, of the constituents analyzed, OC and sulfates had the strongest associations with all four outcomes.
Long-term exposures to PM(2.5) and several of its constituents were associated with increased risks of all-cause and cardiopulmonary mortality in this cohort. Constituents derived from combustion of fossil fuel (including diesel), as well as those of crustal origin, were associated with some of the greatest risks. These results provide additional evidence that reduction of ambient PM(2.5) may provide significant public health benefits.
Several epidemiologic studies provide evidence of an association between daily mortality and particulate matter < 2.5 pm in diameter (PM2.5). Little is known, however, about the relative effects of PM2.5 constituents. We examined associations between 19 PM2.5 components and daily mortality in six California counties.
We obtained daily data from 2000 to 2003 on mortality and PM2.5 mass and components, including elemental and organic carbon (EC and OC), nitrates, sulfates, and various metals. We examined associations of PM2.5 and its constituents with daily counts of several mortality categories: all-cause, cardiovascular, respiratory, and mortality age > 65 years. Poisson regressions incorporating natural splines were used to control for time-varying covariates. Effect estimates were determined for each component in each county and then combined using a random-effects model.
PM2.5 mass and several constituents were associated with multiple mortality categories, especially cardiovascular deaths. For example, for a 3-day lag, the latter increased by 1.6, 2.1, 1.6, and 1.5% for PM2.5, EC, OC, and nitrates based on interquartile ranges of 14.6, 0.8, 4.6, and 5.5 pg/m(3), respectively. Stronger associations were observed between mortality and additional pollutants, including sulfates and several metals, during the cool season.
This multicounty analysis adds to the growing body of evidence linking PM2.5 with mortality and indicates that excess risks may vary among specific PM2.5 components. Therefore, the use of regression coefficients based on PM2.5 mass may underestimate associations with some PM2.5 components. Also, our findings support the hypothesis that combustion-associated pollutants are particularly important in California.
We evaluate the sensitivity of tropospheric OH, O3, and O3 precursors to photochemical effects of aerosols not usually included in global models: (1) aerosol scattering and absorption of ultraviolet radiation and (2) reactive uptake of HO', NO2, and NO3. Our approach is to couple a global 3-D model of tropospheric chemistry (GEOS- CHEM) with aerosol fields from a global 3-D aerosol model (GOCART). Reactive uptake by aerosols is computed using reaction probabilities from a recent review (gamma(sub HO2) = 0.2, gamma(sub NO2) = 10(exp -4), gamma(sub NO3) = l0(exp -3). Aerosols decrease the O3 - O((sup 1)D) photolysis frequency by 5-20% at the surface throughout the Northern Hemisphere (largely due to mineral dust) and by a factor of 2 in biomass burning regions (largely due to black carbon). Aerosol uptake of HO2 accounts for 10-40% of total HOx radical ((triple bonds)OH + peroxy) loss in the boundary layer over polluted continental regions (largely due to sulfate and organic carbon) and for more than 70% over tropical biomass burning regions (largely due to organic carbon). Uptake of NO2 and NO3 accounts for 10-20% of total HNO3 production over biomass burning regions and less elsewhere. Annual mean OH concentrations decrease by 9% globally and by 5-35% in the boundary layer over the Northern Hemisphere. Simulated CO increases by 5- 15 ppbv in the remote Northern Hemisphere, improving agreement with observations. Simulated boundary layer O3 decreases by 15- 45 ppbv over India during the biomass burning season in March and by 5-9 ppbv over northern Europe in August, again improving comparison with observations. We find that particulate matter controls would increase surface O3 over Europe and other industrial regions.
As the fast growth of China’s economy, power generation has greatly increased in past decades. Majority of power generation in China is from coal-fired power plants. Large and still increasing amount of coal combustion for power generation emits numerous pollutants into atmosphere. Combining with emissions from other sources, power generation contributes to the severe air pollution in recent years. In this study, the historic trends and current status of the impact of power generation on air quality in China are overviewed. In 2012, the power sector contributed 30% of CO2, 33% of NOx, 23% of SO2, 8% of particulate matter (PM), 3% of CO, and less than 1% of VOCs emissions in China. The power sector contributed 15% of NOx, 13% of SO2, 27% of O3, 26% of fine particulate NO3− and 22% of fine particulate SO42− ambient concentrations. Coal consumption for power generation is keeping growing. Tremendous efforts have been made to limit emissions from power generation by installing flue-gas desulphurization systems on coal-fired power plant, resulting in reduction of SO2 and PM emissions recently. However, emissions of NOx, CO2, CO, and VOCs are still increasing. Over half of the power emissions and concentrations are distributed in East and North China, which include the Yangtze River Delta and the North China Plain, the two most developed and populous regions in China. Emissions from power generation contribute significant fractions of NOx, SO2, and particulate NO3− in winter, and significant fractions of O3 and particulate SO42− in summer.
Integrating variable energy resources, notably solar and wind, requires better understanding of where, when and how much of variable resources are available. China’s ambitious solar energy development goal will be greatly facilitated by the resources assessment at higher spatial and temporal resolution. We utilized 10-year hourly solar irradiation data from 2001 to 2010 from 200 representative locations to develop provincial solar availability profiles. We found that China has a potential stationary solar capacity from 4700 GW to 39300 GW, distributed solar about 200 GW, and the annual solar output could reach 6900 TWh to 70100 TWh. Resources are most concentrated in northwest provinces, topped by Inner Mongolia, Xinjiang and Gansu. The challenge of solar development in China is integration rather than resources. The spatial and temporal variation of the solar resource show an efficient, robust, and inter-connected national grid and sound energy planning would be necessary to facilitate the integration of these vastly available but variable solar resources.
A source-oriented Community Multiscale Air Quality (CMAQ) model driven by the meteorological fields generated by the Weather Research and Forecasting (WRF) model was used to study the dry and wet deposition of nitrate (NO3(-)), sulfate (SO4(2-)), and ammonium (NH4(+)) ions in the Jiuzhaigou National Nature Reserve (JNNR), China from June to August 2010 and to identify the contributions of different emission sectors and source regions that were responsible for the deposition fluxes. The model performance is evaluated in this paper and the source contribution analyses are presented in a companion paper. The results show that WRF is capable of reproducing the observed precipitation rates with a Mean Normalized Gross Error (MNGE) of 8.1%. Predicted wet deposition fluxes of SO4(2-) and NO3(-) at the Long Lake (LL) site (3100m a.s.l.) during the three-month episode are 2.75 and 0.34kgS(N) ha(-1), which agree well with the observed wet deposition fluxes of 2.42 and 0.39kgS(N)ha(-1), respectively. Temporal variations in the weekly deposition fluxes at LL are also well predicted. Wet deposition flux of NH4(+) at LL is over-predicted by approximately a factor of 3 (1.60kgNha(-1)vs. 0.56kgNha(-1)), likely due to missing alkaline earth cations such as Ca(2+) in the current CMAQ simulations. Predicted wet deposition fluxes are also in general agreement with observations at four Acid Deposition Monitoring Network in East Asia (EANET) sites in western China. Predicted dry deposition fluxes of SO4(2-) (including gas deposition of SO2) and NO3(-) (including gas deposition of HNO3) are 0.12 and 0.12kgS(N)ha(-1) at LL and 0.07 and 0.08kgS(N)ha(-1) at Jiuzhaigou Bureau (JB) in JNNR, respectively, which are much lower than the corresponding wet deposition fluxes. Dry deposition flux of NH4(+) (including gas deposition of NH3) is 0.21kgNha(-1) at LL, and is also much lower than the predicted wet deposition flux. For both dry and wet deposition fluxes, predictions from the 12-km resolution nested domain are similar to those from the 36-km resolution parent domain.
Copyright © 2015 Elsevier B.V. All rights reserved.
China’s power sector accounts for 25% of the world coal consumption–fully about 13% of total global carbon emissions from fossil fuel. Decarbonizing China’s power sector will shape how the country and to a large extent the world uses energy and addresses pollution and climate change. Combining methods of GIS modeling and wind and solar capacity factor simulation, this study utilized 200 representative locations each independently for wind and solar, with 10 years of hourly wind speed and solar irradiation data to investigate provincial capacity and output potentials from 2001 to 2010, and to build wind and solar availability profiles. This study then examined the implications of the solar and wind variability and availability in the context of an overall energy strategy for China by using a system optimization model: SWITCH-China to analyze the feasibility, costs and benefits of China’s clean power transition under three key policy scenarios: Reference Scenario, Low Cost Renewable Scenario, and Carbon Cap Scenario. By optimizing capacity expansion and hourly generation dispatch simultaneously, SWITCH-China is uniquely suited to explore both the value of and synergies among various power system technology options, providing policymakers and industry leaders with important information about the optimal development of the electricity grid. China’s power sector is in the midst of fast development, and today’s investment decisions will have a large impact on the country’s ability to achieve its environmental and carbon mitigation goals. Concerted actions are needed to enable such a transition, including introducing a meaningful carbon price, coordinating the investment decisions, and building the necessary infrastructure for moving energy around.
Emissions of NOx, SO2 and primary nitrate and sulfate from seven regions in China (North, Northeast, East, Central, South, Southwest and Northwest) were separately tracked in a source-oriented Community Multiscale Air Quality (CMAQ) model to quantify the local and inter-regional contributions to PM2.5 nitrate and sulfate concentrations in different cities and provinces. In January, high concentrations of nitrate (∼30 μg m−3) occurred in the North China Plain (NCP) and the Middle and Lower Yangtze Plain (MLYP), as well as the Sichuan Basin. NOx emissions from North, Central and East China were transported over long distances to form rather uniform concentration of nitrate in the NCP and MLYP regions and significantly impacted nitrate concentrations in downwind regions as far as the Pearl River Delta (PRD) region in South China. Wintertime sulfate concentrations demonstrated a more significant inter-regional southward transport pattern and wider spatial distributions than nitrate. The top-five ranked provinces with combined nitrate and sulfate concentrations (Chongqing, Sichuan, Guizhou, Anhui and Hunan) were all affected by emissions from the North, Central and East China, in addition to their local region emissions. In August, slower northerly and northeasterly wind reduced inter-regional transport. Nitrate and sulfate concentrations peaked in North China as dilution was more severely restricted by mountain ranges further north. Three of the top five high concentration provinces (Tianjin, Hebei and Beijing) were located in North China and had more than 55% of local region contributions. Emissions from North China accounted for ∼20% in the remaining two provinces (Shandong in East China and Henan in Central China). In addition to emissions from North China, ∼30% or more of the nitrate and sulfate concentrations in four of the top five high concentration provinces (Tianjin, Henan, Hebei and Shandong) were due to emissions from East China. Time series of daily regional contributions in three megacities (Beijing, Shanghai and Chongqing) and a large city cluster (PRD) also indicated stronger and more frequent inter-regional transport in winter than in summer. Although the cities were mostly affected by local region emissions, influences of long range transport were especially obvious for sulfate concentration in the PRD region in winter, where emissions from North, East and Central China often accounted for more than 80% of the total concentrations. The results from this study suggest that provincial or region-level emission controls alone may not be sufficient to effectively reduce nitrate and sulfate concentrations in many areas and coordinated local and inter-regional emission control strategies are necessary for the country.
Long-term air pollution data with high temporal and spatial resolutions are needed to support the research of physical and chemical processes that affect the air quality, and the corresponding health risks. However, such datasets were not available in China until recently. For the first time, this study examines the spatial and temporal variations of PM2.5, PM10, CO, SO2, NO2, and 8 h O3 in 31 capital cities in China between March 2013 and February 2014 using hourly data released by the Ministry of Environmental Protection (MEP) of China. The annual mean concentrations of PM2.5 and PM10 exceeded the Chinese Ambient Air Quality Standards (CAAQS), Grade I standards (15 and 40 μg/m3 for PM2.5 and PM10, respectively) for all cities, and only Haikou, Fuzhou and Lasa met the CAAQS Grade II standards (35 and 70 μg/m3 for PM2.5 and PM10, respectively). Observed PM2.5, PM10, CO and SO2 concentrations were higher in cities located in the North region than those in the West and the South-East regions. The number of non-attainment days was highest in the winter, but high pollution days were also frequently observed in the South-East region during the fall and in the West region during the spring. PM2.5 was the largest contributor to the air pollution in China based on the number of non-attainment days, followed by PM10, and O3. Strong correlation was found between different pollutants except for O3. These results suggest great impacts of coal combustion and biomass burning in the winter, long range transport of windblown dust in the spring, and secondary aerosol formation throughout the year. Current air pollution in China is caused by multiple pollutants, with great variations among different regions and different seasons. Future studies should focus on improving the understanding of the associations between air quality and meteorological conditions, variations of emissions in different regions, and transport and transformation of pollutants in both intra- and inter-regional contexts.
In this study, we present a regional insight into characteristics and formation process of the widespread extreme haze pollution in northern China during January of 2013 using integrated satellite observations and ground measurements. Different from common regional pollution, dense haze clouds during the most polluted period not only wandered over northern China for more than one week, but also exhibited large spatial variations with some abrupt peak values in Beijing. High UV Aerosol Index (UVAI) values >2.5 indicate prevalent absorbing aerosols in upper part of the haze clouds. CALIPSO vertical detection shows that the haze layers were more than 3 km thick, with strong extinction within 1 km near surface and elevated dust layers above. Top of the more than 2 km thick dust plumes can reach 5 km, having a substantial contribution to the haze clouds. Movement of high aerosol loading regions with aerosol optical depth (AOD) exceeding 2.0 shows a notable superposition of different pollution processes within boundary layer, which largely enhanced the haze pollution. Peak value of PM10 in industrial cities of Hebei was around 1000 μg/m3, almost twice of that in usual pollution. Subsequent peak values of PM10 from south to north confirm the intense regional transport, which could be the main cause of sudden record-breaking particle concentration in Beijing. Anomalous weather conditions facilitated the unusual heavy pollution became extremely severe. Our results indicate close connections between variation of atmospheric circulation and the regional heavy pollution over northern China.
The North China Plain (NCP) and the Yangtze River Delta (YRD) in China have been experiencing severe particulate matter (PM) pollution problems associated with the rapid economic growth and the accelerated urbanization. In this study, hourly mass concentrations of PM2.5 and PM10 during June 1st–August 31st, 2013 were collected in 13 cities located in or adjacent to the NCP region and 20 cities located in the YRD region. The overall average PM2.5 and PM10 concentrations were 77.0 μg/m3 and 136.2 μg/m3 in the NCP region, respectively, and 42.8 μg/m3 and 74.9 μg/m3 in the YRD region, respectively. The frequencies of occurrence of concentrations exceeding the China's Ambient Air Quality Standard (AAQS) (BG3095-12) Grade I standards were 83% for PM2.5 and 93% for PM10 in the NCP region, and 51% for PM2.5 and 66% for PM10 in the YRD region. Strong temporal correlation for both PM2.5 and PM10 between cities within 250 km was frequently observed. PM2.5 was found to be negatively associated with wind speed. On the PM2.5 episode days (when the 24 h PM2.5 concentration is greater than 75 μg/m3), average PM2.5 concentrations were 2–4 times greater compared to the non-episode days. The PM2.5 to PM10 ratio increased from 0.50 (0.57) on the non-episode days to 0.64 (0.64) on the episode days in the NCP (YRD) region. No distinct weekday/weekend difference was observed for PM2.5, PM10, and other gaseous pollutants (CO, SO2, NO2, and O3) in all cities. The results presented in this paper will serve as an important basis for future regional air quality modeling and source apportionment studies.
Average PM2.5 concentrations of ∼250 μg m−3 and peak concentrations of ∼500 μg m−3 were observed in Xi'an, the largest city in Northwest China during an extreme event in January 2013. The source-oriented versions of the Community Multi-scale Air Quality (CMAQ) model with anthropogenic emissions from Emissions Database for Global Atmospheric Research (EDGAR) were used to study the source contributions of six different source categories including energy production, industries, transportation, residential activities, “other” (agriculture, biomass, waste burning, and biogenic sources), and windblown dust to primary and secondary inorganic PM2.5 (nitrate and sulfate) during this episode. The model generally captured the variation and magnitude of PM2.5 concentrations at monitoring sites. The monthly average concentration of the predicted PM2.5 in Xi'an was >200 μg m−3, comparing favorably with the measurement of ∼250 μg m−3. Predicted concentrations of elemental carbon (EC), organic aerosol (OA), sulfate, nitrate, and ammonium were 6, 35, 18, 22, and 12 μg m−3, respectively. Chemically unresolved PM2.5 components (PM2.5 Other) were ∼80 μg m−3. Industries and residential activities dominated EC, organic carbon (OC) and PM2.5 Other, contributing 85%, 95%, and 83%, respectively. Energy production (mainly coal combustion) was the dominating source for secondary nitrate, contributing 46%. Other local and upwind sources were also important, contributing 43% and 11% of total nitrate, respectively. Primary sulfate was ∼10 μg m−3 in vicinity surrounding point sources. Secondary sulfate from upwind sources was also important with concentrations of ∼4–5 μg m−3. Secondary sulfate formed by SO2 emitted from local sources was dominated by energy production. Based on the contributions of different sources to primary components and secondary nitrate and sulfate, the contributions of different sources to PM2.5 total mass in Xi'an during the extremely polluted months are: energy 5%, industries 58%, transportation 2%, residential activities 16%, dust 4%, and other (including other components, inexplicit sources, and upwind sources) 15%.