The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Boqiang Lin - One of the best experts on this subject based on the ideXlab platform.
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investigating spatial variability of co2 emissions in Heavy Industry evidence from a geographically weighted regression model
Energy Policy, 2021Co-Authors: Boqiang LinAbstract:Abstract China is now the world's largest carbon dioxide (CO2) emitter, and the government is under tremendous pressure to reduce CO2 emissions. The Heavy Industry sector is the largest contributor to the growth of CO2 emissions. Investigating the driving factors of this Industry's CO2 emissions has important practical value. This paper applies the geographically weighted regression model to survey this Industry's CO2 emissions. Empirical results show that urbanization exerts a heterogeneous impact on CO2 emissions across provinces and regions. This is mainly due to the differences in urban real estate and transportation infrastructure investments. Economic growth drives CO2 emissions, and this effect varies significantly by region and province on account of the differences in fixed-asset investment. It is more reasonable for local governments to develop emerging economies based on their specific conditions. Energy efficiency has the highest impact on CO2 emissions in the eastern region, because of the differences in R&D personnel investment and the number of patents granted. The energy consumption structure has the largest impact on CO2 emissions in the eastern region since it consumes more coal. Environmental regulations have a greater impact on CO2 emissions in the western region due to the differences in investment for industrial pollution control.
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investigating drivers of co2 emission in china s Heavy Industry a quantile regression analysis
Energy, 2020Co-Authors: Boqiang LinAbstract:Abstract High energy-consuming Heavy Industry is one of the main sources of China’s carbon dioxide (CO2) emissions. Based on 2005–2017 panel data of China’s 30 provinces, this paper uses a quantile regression model to investigate CO2 emissions in the Heavy Industry. The empirical results show that economic growth exerts a stronger influence on the Heavy Industry’s CO2 emissions in the 25th-50th quantile provinces, due to the difference in the fixed asset investment and Heavy industrial output. The impact of urbanization on CO2 emissions in the 10th-25th quantile provinces is lower than that in other quantile provinces because these provinces have the least number of college graduates. Energy efficiency has a smaller impact on CO2 emissions in the upper 90th quantile province, owing to the difference in R&D personnel investment and the number of patents granted. Similarly, environmental regulations have minimal impact on CO2 emissions in the upper 90th quantile province, since the growth rate of industrial pollution treatment investment in these provinces is the lowest. However, the impact of energy consumption structure on CO2 emissions in the 10th-25th and 25th-50th quantile provinces is the highest, because of the provincial differences in coal consumption.
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how to reduce energy intensity in china s Heavy Industry evidence from a seemingly uncorrelated regression
Journal of Cleaner Production, 2018Co-Authors: Kui Liu, Hongkun Bai, Jiangbo Wang, Boqiang LinAbstract:Abstract With rapid development and large scale urbanization, China's environmental and resource constraints are becoming increasingly severe. Compared to other industries, China's Heavy Industry is energy-intensive and emission-intensive, which exerts pressure on energy conservation policies. In this paper, by establishing a theoretical model of the impact factors of energy intensity, we investigate the effects of energy prices, ownership structure, and industrial concentration and R&D investment on the energy intensity of China's Heavy Industry, and seemingly unrelated regression model was used in the estimation of corresponding coefficients. The results show that increase in energy prices, decrease in state-owned enterprises and increase in industrial concentration may reduce the energy intensity of the Industry. Also, the study points to evidence that an increase in R&D investment may reduce the oil intensity of Heavy Industry.
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factor substitution and decomposition of carbon intensity in china s Heavy Industry
Energy, 2018Co-Authors: Kui Liu, Hongkun Bai, Shuo Yin, Boqiang LinAbstract:Abstract The Heavy Industry, which accounts for over 60% of China's total primary energy and electricity consumption, has contributed largely to the worsening environmental pollution and CO 2 emissions. This study adopts two-stage estimation based on translog cost function to decompose changes in energy related carbon intensity into substitution effect, technological progress effect, output effect and budget effect. The empirical results show that all the inputs (capital, labor and energy) are substitutes, and the substitution between labor and energy have the highest degree of responsiveness. This is a clear indication that increasing labor inputs in the production process will reduce energy consumption and CO 2 emission while improving the worsening environmental problems in China. Also, the empirical results show that about 45.77% change in carbon intensity is attributable to capital-energy and labor-energy substitutions, which affirms the success of any policy by the government to increase labor and capital inputs at the expense of energy use towards CO 2 mitigation agenda.
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energy substitution effect on china s Heavy Industry perspectives of a translog production function and ridge regression
Sustainability, 2017Co-Authors: Boqiang Lin, Kui LiuAbstract:A translog production function model with input factors including energy, capital, and labor is established for China’s Heavy Industry. Using the ridge regression method, the output elasticity of each input factor and the substitution elasticity between input factors are analyzed. The empirical results show that the output elasticity of energy, capital and labor are all positive, while the output elasticities of energy and capital are relatively higher, indicating that China’s Heavy Industry is energy- and capital-intensive. Simultaneously, all the input factors are substitutes, with the substitution between labor and energy having the highest degree of responsiveness. The substitution elasticity between labor and energy is decreasing, while the substitution elasticities of capital for energy and labor are increasing. More capital input can help to improve energy efficiency and thus accomplish the goal of energy conservation in China’s Heavy Industry.
Kui Liu - One of the best experts on this subject based on the ideXlab platform.
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how to reduce energy intensity in china s Heavy Industry evidence from a seemingly uncorrelated regression
Journal of Cleaner Production, 2018Co-Authors: Kui Liu, Hongkun Bai, Jiangbo Wang, Boqiang LinAbstract:Abstract With rapid development and large scale urbanization, China's environmental and resource constraints are becoming increasingly severe. Compared to other industries, China's Heavy Industry is energy-intensive and emission-intensive, which exerts pressure on energy conservation policies. In this paper, by establishing a theoretical model of the impact factors of energy intensity, we investigate the effects of energy prices, ownership structure, and industrial concentration and R&D investment on the energy intensity of China's Heavy Industry, and seemingly unrelated regression model was used in the estimation of corresponding coefficients. The results show that increase in energy prices, decrease in state-owned enterprises and increase in industrial concentration may reduce the energy intensity of the Industry. Also, the study points to evidence that an increase in R&D investment may reduce the oil intensity of Heavy Industry.
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factor substitution and decomposition of carbon intensity in china s Heavy Industry
Energy, 2018Co-Authors: Kui Liu, Hongkun Bai, Shuo Yin, Boqiang LinAbstract:Abstract The Heavy Industry, which accounts for over 60% of China's total primary energy and electricity consumption, has contributed largely to the worsening environmental pollution and CO 2 emissions. This study adopts two-stage estimation based on translog cost function to decompose changes in energy related carbon intensity into substitution effect, technological progress effect, output effect and budget effect. The empirical results show that all the inputs (capital, labor and energy) are substitutes, and the substitution between labor and energy have the highest degree of responsiveness. This is a clear indication that increasing labor inputs in the production process will reduce energy consumption and CO 2 emission while improving the worsening environmental problems in China. Also, the empirical results show that about 45.77% change in carbon intensity is attributable to capital-energy and labor-energy substitutions, which affirms the success of any policy by the government to increase labor and capital inputs at the expense of energy use towards CO 2 mitigation agenda.
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energy substitution effect on china s Heavy Industry perspectives of a translog production function and ridge regression
Sustainability, 2017Co-Authors: Boqiang Lin, Kui LiuAbstract:A translog production function model with input factors including energy, capital, and labor is established for China’s Heavy Industry. Using the ridge regression method, the output elasticity of each input factor and the substitution elasticity between input factors are analyzed. The empirical results show that the output elasticity of energy, capital and labor are all positive, while the output elasticities of energy and capital are relatively higher, indicating that China’s Heavy Industry is energy- and capital-intensive. Simultaneously, all the input factors are substitutes, with the substitution between labor and energy having the highest degree of responsiveness. The substitution elasticity between labor and energy is decreasing, while the substitution elasticities of capital for energy and labor are increasing. More capital input can help to improve energy efficiency and thus accomplish the goal of energy conservation in China’s Heavy Industry.
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using lmdi to analyze the decoupling of carbon dioxide emissions from china s Heavy Industry
Sustainability, 2017Co-Authors: Lin Boqiang, Kui LiuAbstract:China is facing huge pressure on CO2 emissions reduction. The Heavy Industry accounts for over 60% of China’s total energy consumption, and thus leads to a large number of energy-related carbon emissions. This paper adopts the Log Mean Divisia Index (LMDI) method based on the extended Kaya identity to explore the influencing factors of CO2 emissions from China’s Heavy Industry; we calculate the trend of decoupling by presenting a theoretical framework for decoupling. The results show that labor productivity, energy intensity, and Industry scale are the main factors affecting CO2 emissions in the Heavy Industry. The improvement of labor productivity is the main cause of the increase in CO2 emissions, while the decline in energy intensity leads to CO2 emissions reduction, and the Industry scale has different effects in different periods. Results from the decoupling analysis show that efforts made on carbon emission reduction, to a certain extent, achieved the desired outcome but still need to be strengthened.
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how efficient is china s Heavy Industry a perspective of input output analysis
Emerging Markets Finance and Trade, 2016Co-Authors: Boqiang Lin, Kui LiuAbstract:ABSTRACTHeavy Industry accounts for nearly 65% of the energy consumption and over 60% of the electricity consumption of China. Under the framework of real savings and green GDP, the huge energy consumption and carbon emissions will bring in huge natural resource losses, and then affect the total factor productivity (TFP) seriously. When taking the input–output relationship into consideration, the natural resource losses of Heavy Industry will decrease significantly. As the upstream of the industrial chain, Heavy Industry offered a large number of subsidies to the downstream industries by providing energy, raw materials, and taking on carbon emissions. This article verified the transfer of natural resource losses among industries, and estimated the real TFP of Heavy Industry from input–output and traditional perspective, respectively. The results showed that there was an increasing trend in the growth rate of Heavy Industry’s TFP in the perspective of input–output.
Alex Burdorf - One of the best experts on this subject based on the ideXlab platform.
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the influence of Industry related air pollution on birth outcomes in an industrialized area
Environmental Pollution, 2021Co-Authors: Arnold D. Bergstra, Bert Brunekreef, Alex BurdorfAbstract:Recent studies suggests that air pollution, from among others road traffic, can influence growth and development of the human foetus during pregnancy. The effects of air pollution from Heavy Industry on birth outcomes have been investigated scarcely. Our aim was to investigate the associations of air pollution from Heavy Industry on birth outcomes. A cross-sectional study was conducted among 4488 singleton live births (2012–2017) in the vicinity of a large industrial area in the Netherlands. Information from the birth registration was linked with a dispersion model to characterize annual individual-level exposure of pregnant mothers to air pollutants from Industry in the area. Associations between particulate matter (PM10), nitrogen oxides (NOX), sulphur dioxide (SO2), and volatile organic compounds (VOC) with low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA) were investigated by logistic regression analysis and with gestational age, birth weight, birth length, and head circumference by linear regression analysis. Exposures to NOX, SO2, and VOC (per interquartile range of 1.16, 0.42, and 0.97 μg/m3 respectively) during pregnancy were associated with LBW (OR 1.20, 95%CI 1.06–1.35, OR 1.20, 95%CI 1.00–1.43, and OR 1.21, 95%CI 1.08–1.35 respectively). NOX and VOC were also associated with PTB (OR 1.14, 95%CI 1.01–1.29 and OR 1.17, 95%CI 1.04–1.31 respectively). Associations between exposure to air pollution and birth weight, birth length, and head circumference were statistically significant. Higher exposure to PM10, NOX, SO2 and VOC (per interquartile range of 0.41, 1.16, 0.42, and 0.97 μg/m3 respectively) was associated with reduced birth weight of 21 g to 30 g. The 90th percentile Industry-related PM10 exposure corresponded with an average birth weight decrease of 74 g.
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the mediating role of risk perception in the association between Industry related air pollution and health
PLOS ONE, 2018Co-Authors: Arnold D. Bergstra, Bert Brunekreef, Alex BurdorfAbstract:textabstractBackground Heavy Industry emits many potentially hazardous pollutants into the air which can affect health. Awareness about the potential health impacts of air pollution from Industry can influence people’s risk perception. This in turn can affect (self-reported) symptoms. Our aims were to investigate the associations of air pollution from Heavy Industry with health symptoms and to evaluate whether these associations are mediated by people’s risk perception about local Industry. Methods A cross-sectional questionnaire study was conducted among children (2–18 years) and adults (19 years and above) living in the direct vicinity of an area with Heavy Industry. A dispersion model was used to characterize individual-level exposures to air pollution emitted from the Industry in the area. Associations between PM2.5 and NOX with presence of chronic diseases (adults) and respiratory symptoms (adults and children) were investigated by logistic regression analysis. Risk perception was indirectly measured by worries about local Industry (0–10 scale). Mediation analyses were performed to investigate the role of mediation by these worries. Results The response was 54% (2,627/4,877). In adults exposure to modelled PM2.5 from Industry (per μg/m3) was related with reported high blood pressure (OR 1.56, 95% CI 1.13–2.15) and exposure to modelled NOX (per μg/m3) was inversely related with cardiovascular diseases (OR 0.91, 95% CI 0.84–0.98). In children higher PM2.5 and NOX concentrations (per μg/m3) were related with wheezing (OR 2.00, 95% CI 1.24–3.24 and OR 1.13, 95% CI 1.06–1.21 respectively) and dry cough (OR 2.33, 95% CI 1.55–3.52 and OR 1.16, 95% CI 1.10–1.22 respectively). Parental worry about local Industry was an important mediator in exposure–health relations in children (indirect effect between 19–28% Conclusion Exposure from Industry was associated with self-reported reported high blood pressure among adults and respiratory symptoms among their children. Risk perception was found to mediate these associations for children.
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The effect of Industry-related air pollution on lung function and respiratory symptoms in school children
Environmental Health, 2018Co-Authors: Arnold D. Bergstra, Bert Brunekreef, Alex BurdorfAbstract:Heavy Industry emits many potentially hazardous pollutants into the air which can affect health. However, the effects of air pollution from Heavy Industry on lung function and respiratory symptoms have been investigated scarcely. Our aim was to investigate the associations of long-term air pollution from Heavy Industry with lung function and respiratory symptoms in school children. A cross-sectional lung function study was conducted among school children (7–13 years) in the vicinity of an area with Heavy Industry. Lung function measurements were conducted during school hours. Parents of the children were asked to complete a questionnaire about the health of their children. A dispersion model was used to characterize the additional individual-level exposures to air pollutants from the Industry in the area. Associations between PM2.5 and NOX exposure with lung function and presence of respiratory symptoms were investigated by linear and/or logistic regression analysis. Participation in the lung function measurements and questionnaires was 84% (665/787) and 77% (603/787), respectively. The range of the elevated PM2.5 and NOX five years average concentrations (2008–2012) due to Heavy Industry were 0.04–1.59 μg/m3 and 0.74–11.33 μg/m3 respectively. After adjustment for confounders higher exposure to PM2.5 and NOX (per interquartile range of 0.56 and 7.43 μg/m3 respectively) was associated with lower percent predicted peak expiratory flow (PEF) (B -2.80%, 95%CI -5.05% to − 0.55% and B -3.67%, 95%CI -6.93% to − 0.42% respectively). Higher exposure to NOX (per interquartile range of 7.43 μg/m3) was also associated with lower percent forced vital capacity (FVC) and percent predicted forced expiration volume in 1 s (FEV1) (B -2.30, 95% CI -4.55 to − 0.05 and B -2.73, 95%CI -5.21 to − 0.25 respectively). No significant associations were found between the additional exposure to PM2.5 or NOX and respiratory symptoms except for PM2.5 and dry cough (OR 1.40, 95%CI 1.00 to 1.94). Exposure to PM2.5 and NOX from Industry was associated with decreased lung function. Exposure to PM2.5 was also associated with parents’ reports of dry cough among their children.
Arnold D. Bergstra - One of the best experts on this subject based on the ideXlab platform.
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the influence of Industry related air pollution on birth outcomes in an industrialized area
Environmental Pollution, 2021Co-Authors: Arnold D. Bergstra, Bert Brunekreef, Alex BurdorfAbstract:Recent studies suggests that air pollution, from among others road traffic, can influence growth and development of the human foetus during pregnancy. The effects of air pollution from Heavy Industry on birth outcomes have been investigated scarcely. Our aim was to investigate the associations of air pollution from Heavy Industry on birth outcomes. A cross-sectional study was conducted among 4488 singleton live births (2012–2017) in the vicinity of a large industrial area in the Netherlands. Information from the birth registration was linked with a dispersion model to characterize annual individual-level exposure of pregnant mothers to air pollutants from Industry in the area. Associations between particulate matter (PM10), nitrogen oxides (NOX), sulphur dioxide (SO2), and volatile organic compounds (VOC) with low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA) were investigated by logistic regression analysis and with gestational age, birth weight, birth length, and head circumference by linear regression analysis. Exposures to NOX, SO2, and VOC (per interquartile range of 1.16, 0.42, and 0.97 μg/m3 respectively) during pregnancy were associated with LBW (OR 1.20, 95%CI 1.06–1.35, OR 1.20, 95%CI 1.00–1.43, and OR 1.21, 95%CI 1.08–1.35 respectively). NOX and VOC were also associated with PTB (OR 1.14, 95%CI 1.01–1.29 and OR 1.17, 95%CI 1.04–1.31 respectively). Associations between exposure to air pollution and birth weight, birth length, and head circumference were statistically significant. Higher exposure to PM10, NOX, SO2 and VOC (per interquartile range of 0.41, 1.16, 0.42, and 0.97 μg/m3 respectively) was associated with reduced birth weight of 21 g to 30 g. The 90th percentile Industry-related PM10 exposure corresponded with an average birth weight decrease of 74 g.
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the mediating role of risk perception in the association between Industry related air pollution and health
PLOS ONE, 2018Co-Authors: Arnold D. Bergstra, Bert Brunekreef, Alex BurdorfAbstract:textabstractBackground Heavy Industry emits many potentially hazardous pollutants into the air which can affect health. Awareness about the potential health impacts of air pollution from Industry can influence people’s risk perception. This in turn can affect (self-reported) symptoms. Our aims were to investigate the associations of air pollution from Heavy Industry with health symptoms and to evaluate whether these associations are mediated by people’s risk perception about local Industry. Methods A cross-sectional questionnaire study was conducted among children (2–18 years) and adults (19 years and above) living in the direct vicinity of an area with Heavy Industry. A dispersion model was used to characterize individual-level exposures to air pollution emitted from the Industry in the area. Associations between PM2.5 and NOX with presence of chronic diseases (adults) and respiratory symptoms (adults and children) were investigated by logistic regression analysis. Risk perception was indirectly measured by worries about local Industry (0–10 scale). Mediation analyses were performed to investigate the role of mediation by these worries. Results The response was 54% (2,627/4,877). In adults exposure to modelled PM2.5 from Industry (per μg/m3) was related with reported high blood pressure (OR 1.56, 95% CI 1.13–2.15) and exposure to modelled NOX (per μg/m3) was inversely related with cardiovascular diseases (OR 0.91, 95% CI 0.84–0.98). In children higher PM2.5 and NOX concentrations (per μg/m3) were related with wheezing (OR 2.00, 95% CI 1.24–3.24 and OR 1.13, 95% CI 1.06–1.21 respectively) and dry cough (OR 2.33, 95% CI 1.55–3.52 and OR 1.16, 95% CI 1.10–1.22 respectively). Parental worry about local Industry was an important mediator in exposure–health relations in children (indirect effect between 19–28% Conclusion Exposure from Industry was associated with self-reported reported high blood pressure among adults and respiratory symptoms among their children. Risk perception was found to mediate these associations for children.
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The effect of Industry-related air pollution on lung function and respiratory symptoms in school children
Environmental Health, 2018Co-Authors: Arnold D. Bergstra, Bert Brunekreef, Alex BurdorfAbstract:Heavy Industry emits many potentially hazardous pollutants into the air which can affect health. However, the effects of air pollution from Heavy Industry on lung function and respiratory symptoms have been investigated scarcely. Our aim was to investigate the associations of long-term air pollution from Heavy Industry with lung function and respiratory symptoms in school children. A cross-sectional lung function study was conducted among school children (7–13 years) in the vicinity of an area with Heavy Industry. Lung function measurements were conducted during school hours. Parents of the children were asked to complete a questionnaire about the health of their children. A dispersion model was used to characterize the additional individual-level exposures to air pollutants from the Industry in the area. Associations between PM2.5 and NOX exposure with lung function and presence of respiratory symptoms were investigated by linear and/or logistic regression analysis. Participation in the lung function measurements and questionnaires was 84% (665/787) and 77% (603/787), respectively. The range of the elevated PM2.5 and NOX five years average concentrations (2008–2012) due to Heavy Industry were 0.04–1.59 μg/m3 and 0.74–11.33 μg/m3 respectively. After adjustment for confounders higher exposure to PM2.5 and NOX (per interquartile range of 0.56 and 7.43 μg/m3 respectively) was associated with lower percent predicted peak expiratory flow (PEF) (B -2.80%, 95%CI -5.05% to − 0.55% and B -3.67%, 95%CI -6.93% to − 0.42% respectively). Higher exposure to NOX (per interquartile range of 7.43 μg/m3) was also associated with lower percent forced vital capacity (FVC) and percent predicted forced expiration volume in 1 s (FEV1) (B -2.30, 95% CI -4.55 to − 0.05 and B -2.73, 95%CI -5.21 to − 0.25 respectively). No significant associations were found between the additional exposure to PM2.5 or NOX and respiratory symptoms except for PM2.5 and dry cough (OR 1.40, 95%CI 1.00 to 1.94). Exposure to PM2.5 and NOX from Industry was associated with decreased lung function. Exposure to PM2.5 was also associated with parents’ reports of dry cough among their children.
Yijing Wang - One of the best experts on this subject based on the ideXlab platform.
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soil high cd exacerbates the adverse impact of elevated o3 on populus alba berolinensis l
Ecotoxicology and Environmental Safety, 2019Co-Authors: Sheng Xu, Bo Li, Pin Li, Xingyuan He, Wei Chen, Yan Li, Yijing WangAbstract:Abstract Pollution with both Heavy metal and ground-level ozone (O3) has been steadily increasing, especially in the cities with Heavy Industry. Little information is known about their combined impacts on urban tree. This study was aimed at characterizing the interactive effects of soil cadmium (Cd) addition and O3 fumigation on visible injury and growth, photosynthesis, oxidative stress, antioxidant enzyme activities, abscisic acid (ABA) content and bioaccumulation of Cd in one-year-old Populus alba 'Berolinensis' saplings by using open top chambers in Shenyang city with developed Heavy Industry, Northeast China. In this study, poplar saplings were grown in the pots containing soil with different concentrations of Cd (0, 100 and 500 mg kg−1) under ambient air (40 µg L−1) and elevated O3 (120 µg L−1). The results showed that EO and its combination with high Cd (500 mg kg−1) induced significant foliar injury symptoms, decreased root weight (by 41.6%) and total biomass (by 17.4%), inhibited net photosynthetic rate and stomatal conductance, and increased malondialdehyde and ABA contents after 4 weeks of O3 exposure. Elevated O3 exacerbated the accumulation of Cd in leaves and stems of poplar plants grown in the pots with high Cd-polluted soil. Our results also indicated that high Cd pollution in soil increased the susceptibility of plants to O3 and exacerbated the adverse impact of elevated O3 on physiological metabolisms of poplar species, which implied that it was very necessary to take into consideration for O3-tolerance of tree species during phytoremediation of Cd-polluted soil in Heavy industrial areas.