Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign cur...Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.展开更多
Using daily BTC-USD data from September 19,2014 to January 21,2024,this paper re-examines whether weekends differ from weekdays for Bitcoin along three margins:average returns,close-to-close volatility,and trading act...Using daily BTC-USD data from September 19,2014 to January 21,2024,this paper re-examines whether weekends differ from weekdays for Bitcoin along three margins:average returns,close-to-close volatility,and trading activity.We implement Welch mean comparisons and HAC-robust OLS with month fixed effects(bandwidths 5,7,and 14).In the full sample and across subsamples(2016–2019;2020–2023;early 2024),we find no detectable weekend–weekday gap in average returns,while volatility and trading activity are lower on weekends.The patterns are robust to using squared returns as a volatility proxy.The joint evidence is consistent with liquidity and attention mechanisms—quieter weekends rather than compensating return premia.Replication files reproduce all tables and figures.展开更多
Cryptocurrency,a booming decentralised asset designed based on the blockchain architecture,is particularly important to the market at the present time by studying the volatility risk of cryptocurrencies.In this paper,...Cryptocurrency,a booming decentralised asset designed based on the blockchain architecture,is particularly important to the market at the present time by studying the volatility risk of cryptocurrencies.In this paper,we empirically analyse the volatility risk of cryptocurrencies through quantitative analysis models,comprehensively using the Markov state transition GARCH model with skewed distribution(Skew-MSGARCH)and the autoregressive conditional volatility density ARJI model introducing the Poisson jump factor,and selecting the earliest developed and the most mature currency price volatility daily return series,to deeply explore the volatility risk of digital cryptocurrencies.risk.Finally,it can be seen through in-depth analyses that the expectation factor and information inducement are the main reasons leading to the exacerbation of the volatility risk of digital cryptocurrencies.It is recommended that this situation be optimised and improved in terms of the value function of digital cryptocurrencies themselves and the implementation of systematic risk management and regulatory innovation.As an important component of the digital economy,blockchain technology can effectively regulate and improve the volatility of digital cryptocurrencies under macroeconomic policies,thereby maintaining the security and stability of emerging financial markets.展开更多
In this paper,we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options.Furthermore,we assume that the interest rates and the jump inte...In this paper,we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options.Furthermore,we assume that the interest rates and the jump intensities of the assets are stochastic.Under the proposed framework,first,we derive the analytical pricing formula for power options by using Fourier transform technique,Esscher transform and characteristic function.Then we provide the efficient approximation to calculate the analytical pricing formula of power options by using the FFT approach and examine the accuracy of the approximation by Monte Carlo simulation.Finally,we provide some sensitivity analysis of the model parameters to power options.Numerical examples show this model is suitable for empirical work in practice.展开更多
This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even br...This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even bring uncertainties to macroeconomic output.Especially in the carbon neutrality context,China's coal market is being reconstructed and responding to imbalances between supply and demand;identifying the CPVSs helps alleviate rising market instability and prevent energy-induced system risk.To achieve this objective,we explore causalities among 938 weekly coal prices reported by different coal-producing areas of China from 2006.9.4 to 2021.7.12 using the transfer entropy method.Then,coal price volatility influence is quantified to identify the CPVSs by conjointly using complex network theory and a rank aggregation method.The validity test demonstrates that the proposed hybrid method efficiently identifies the CPVSs as it correlates to many price determinants,e.g.,electricity and coal consumption and generation.The empirical results show that causalities among coal prices changed dramatically in 2016,2018,and 2020,affected by coal decapacity and carbon neutrality policies.Before 2018,coal-producing provinces with strong demand for coal and electricity,e.g.,Jiangxi,Chongqing,and Sichuan,were CPVSs;after 2019,those with comparative advantages in coal supply,e.g.,Gansu and Ningxia,were CPVSs.Overall,the coal market is unstable and sensitive to energy policy and external shocks.Policymakers and market participants are recommended to monitor and manage the CPVSs to improve energy security,avoid policy-induced instability and prevent risks caused by coal price fluctuations.展开更多
Motivated by a significant impact of price volatility on food security and economic stability inCameroon,this study aims to understand the factors influencing agricultural product price volatility(APPV)and formulateef...Motivated by a significant impact of price volatility on food security and economic stability inCameroon,this study aims to understand the factors influencing agricultural product price volatility(APPV)and formulateeffective policies for mitigating its negative impactand promoting sustainable economic growth.Specifically,this research used theautoregressive distributed lag-error correction model(ARDL-ECM)to analyse the impact of agricultural productivity,agricultural product imports,population,temperature variation,gross domestic product(GDP)per capita,and government expenditure on APPV based on the annual data from 2000 to 2021.The ARDL-ECM estimation results revealed that agricultural productivity(β=4.901),agricultural product imports(β=1.012),population(β=13.635),and GDP per capita(β=2.794)were positively related toAPPV,while temperature variation(β=-0.990)and government expenditure(β=-8.585)were negatively related toAPPVin the long term.However,temperature variation had a positive relationship with APPV in the short term.Moreover,the Granger causality test showed that there werebidirectional causality of APPV with agricultural productivityandagricultural product imports,and unidirectional causality of APPVwith population,temperature variation,GDP per capita,and government expenditure.The findings highlight the importance of public policies in stabilizing agricultural product prices by investing in agricultural research,improving access to agricultural inputs,strengthening farmer capacities,implementing climate adaptation measures,and enhancing rural infrastructure.Thesepolicies can reduce APPV,improve food security,and promote inclusive economic growth in Cameroon.展开更多
To investigate the volatility of atmospheric particulates and the evolution of other particulate properties(chemical composition,particle size distribution and mixing state)with temperature,a thermodenuder coupled wit...To investigate the volatility of atmospheric particulates and the evolution of other particulate properties(chemical composition,particle size distribution and mixing state)with temperature,a thermodenuder coupled with a single particle aerosol mass spectrometer was used to conduct continuous observations of atmospheric fine particles in Chengdu,southwest China.Because of their complex sources and secondary reaction processes,the average mass spectra of single particles contained a variety of chemical components(including organic,inorganic and metal species).When the temperature rose from room temperature to280℃,the relative areas of volatile and semi-volatile components decreased,while the relative areas of less or non-volatile components increased.Most(>80%)nitrate and sulfate existed in the form of NH_(4)NO_(3)and(NH_(4))_(2)SO_(4),and their volatilization temperatures were50–100℃and 150–280℃,respectively.The contribution of biomass burning(BB)and vehicle emission(VE)particles increased significantly at 280℃,which emphasized the important role of regional biomass burning and local motor vehicle emissions to the core of particles.With the increase in temperature,the particle size of the particles coated with volatile or semi-volatile components was reduced,and their mixing with secondary inorganic components was significantly weakened.The formation of K-nitrate(KNO_(3))and K-sulfate(KSO_(4))particles was dominated by liquid-phase processes and photochemical reactions,respectively.Reducing KNO_(3)and BB particles is the key to improving visibility.These new results are helpful towards better understanding the initial sources,pollution formation mechanisms and climatic effects of fine particulate matter in this megacity in southwest China.展开更多
Stock volatility constitutes an adverse psychological stressor,but few large-scale studies have focused on its impact on major adverse cardiovascular events(MACEs)and suicide.Here,we conducted an individual-level time...Stock volatility constitutes an adverse psychological stressor,but few large-scale studies have focused on its impact on major adverse cardiovascular events(MACEs)and suicide.Here,we conducted an individual-level time-stratified case-crossover study to explore the association of daily stock volatility(daily returns and intra-daily oscillations for three kinds of stock indices)with MACEs and suicide among more than 12 million individual decedents from all counties in the mainland of China between 2013 and 2019.For daily stock returns,both stock increases and decreases were associated with increased mortal-ity risks of all MACEs and suicide.There were consistent and positive associations between intra-daily stock oscillations and mortality due to MACEs and suicide.The excess mortality risks occurred at the cur-rent day(lag 0 d),persisted for two days,and were greatest for suicide and hemorrhagic stroke.Taking the present-day Shanghai and Shenzhen 300 Index as an example,a 1%decrease in daily returns was associated with 0.74%-1.04%and 1.77%increases in mortality risks of MACEs and suicide,respectively;the corresponding risk increments were 0.57%-0.85%and 0.92%for a 1%increase in daily returns and 0.67%-0.77%and 1.09%for a 1%increase in intra-daily stock oscillations.The excess risks were more pro-nounced among individuals aged 65-74 years,males,and those with lower education levels.Our findings revealed considerable health risks linked to sociopsychological stressors,which are helpful for the gov-ernment and general public to mitigate the immediate cardiovascular and mental health risks associated with stock market volatility.展开更多
Under high relative humidity(RH)conditions,the release of volatile components(such as acetate)has a significant impact on the aerosol hygroscopicity.In this work,one surface plasmon resonance microscopy(SPRM)measureme...Under high relative humidity(RH)conditions,the release of volatile components(such as acetate)has a significant impact on the aerosol hygroscopicity.In this work,one surface plasmon resonance microscopy(SPRM)measurement system was introduced to determine the hygroscopic growth factors(GFs)of three acetate aerosols separately or mixed with glucose at different RHs.For Ca(CH_(3)COO)_(2) or Mg(CH_(3)COO)_(2) aerosols,the hygroscopic growth trend of each time was lower than that of the previous time in three cyclic humidification from 70% RH to 90% RH,which may be due to the volatility of acetic acid leading to the formation of insoluble hydroxide(Ca(OH)_(2) or Mg(OH)_(2))under high RH conditions.Then the third calculated GF(using the Zdanovskii-Stokes-Robinson method)for Ca(CH_(3)COO)_(2) or Mg(CH_(3)COO)_(2) in bicomponent aerosols with 1:1 mass ratio were 3.20% or 5.33% lower than that of the first calculated GF at 90% RH.The calculated results also showed that the hygroscopicity change of bicomponent aerosol was negatively correlated with glucose content,especially when the mass ratio of Mg(CH_(3)COO)_(2) to glucose was 1:2,the GF at 90% RH only decreased by4.67% after three cyclic humidification.Inductively coupled plasma atomic emission spectrum(ICP-AES)based measurements also indicated that the changes of Mg^(2+)concentration in bicomponent was lower than that of the single-component.The results of this study reveal thatduring the efflorescence transitions of atmospheric nanoparticles,the organic acids diffusion rate may be inhibited by the coating effect of neutral organic components,and the particles aging cycle will be prolonged.展开更多
This study utilizes the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to investigate the dynamic relationship between Chinese and U.S. stock markets amid t...This study utilizes the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to investigate the dynamic relationship between Chinese and U.S. stock markets amid the COVID-19 pandemic. Initially, a univariate GARCH model is developed to derive residual sequences, which are then used to estimate the DCC model parameters. The research reveals a significant rise in the interconnection between the Chinese and U.S. stock markets during the pandemic. The S&P 500 index displayed higher sensitivity and greater volatility in response to the pandemic, whereas the CSI 300 index showed superior resilience and stability. Analysis and model estimation suggest that the market’s dependence on historical data has intensified and its sensitivity to recent shocks has heightened. Predictions from the model indicate increased market volatility during the pandemic. While the model is proficient in capturing market trends, there remains potential for enhancing the accuracy of specific volatility predictions. The study proposes recommendations for policymakers and investors, highlighting the importance of improved cooperation in international financial market regulation and investor education.展开更多
Black-Scholes Model (B-SM) simulates the dynamics of financial market and contains instruments such as options and puts which are major indices requiring solution. B-SM is known to estimate the correct prices of Europ...Black-Scholes Model (B-SM) simulates the dynamics of financial market and contains instruments such as options and puts which are major indices requiring solution. B-SM is known to estimate the correct prices of European Stock options and establish the theoretical foundation for Option pricing. Therefore, this paper evaluates the Black-Schole model in simulating the European call in a cash flow in the dependent drift and focuses on obtaining analytic and then approximate solution for the model. The work also examines Fokker Planck Equation (FPE) and extracts the link between FPE and B-SM for non equilibrium systems. The B-SM is then solved via the Elzaki transform method (ETM). The computational procedures were obtained using MAPLE 18 with the solution provided in the form of convergent series.展开更多
Initial success has been achieved in Hong Kong in controlling primary air pollutants,but ambient ozone levels kept increasing during the past three decades.Volatile organic compounds(VOCs)are important for mitigating ...Initial success has been achieved in Hong Kong in controlling primary air pollutants,but ambient ozone levels kept increasing during the past three decades.Volatile organic compounds(VOCs)are important for mitigating ozone pollution as its major precursors.This study analyzed VOC characteristics of roadside,suburban,and rural sites in Hong Kong to investigate their compositions,concentrations,and source contributions.Herewe showthat the TVOC concentrations were 23.05±13.24,12.68±15.36,and 5.16±5.48 ppbv for roadside,suburban,and rural sites between May 2015 to June 2019,respectively.By using Positive Matrix Factorization(PMF)model,six sources were identified at the roadside site over five years:Liquefied petroleum gas(LPG)usage(33%–46%),gasoline evaporation(8%–31%),aged air mass(11%–28%),gasoline exhaust(5%–16%),diesel exhaust(2%–16%)and fuel filling(75–9%).Similarly,six sources were distinguished at the suburban site,including LPG usage(30%–33%),solvent usage(20%–26%),diesel exhaust(14%–26%),gasoline evaporation(8%–16%),aged air mass(4%–11%),and biogenic emissions(2%–5%).At the rural site,four sources were identified,including aged airmass(33%–51%),solvent usage(25%–30%),vehicular emissions(11%–28%),and biogenic emissions(6%–12%).The analysis further revealed that fuel filling and LPG usage were the primary contributors to OFP and OH reactivity at the roadside site,while solvent usage and biogenic emissions accounted for almost half of OFP and OH reactivity at the suburban and rural sites,respectively.These findings highlight the importance of identifying and characterizing VOC sources at different sites to help policymakers develop targeted measures for pollution mitigation in specific areas.展开更多
Tomato is an important economic crop all over the world.Volatile flavors in tomato fruit are key factors influencing consumer liking and commercial quality.However,the regulatory mechanism controlling the volatile fla...Tomato is an important economic crop all over the world.Volatile flavors in tomato fruit are key factors influencing consumer liking and commercial quality.However,the regulatory mechanism controlling the volatile flavors of tomatoes is still not clear.Here,we integrated the metabolome and transcriptome of the volatile flavors in tomato fruit to explore the regulatory mechanism of volatile flavor formation,using wild and cultivated tomatoes with significant differences in flavors.A total of 35 volatile flavor compounds were identified,based on the solid phase microextraction-gas chromatography-mass spectrometry(SPME-GC-MS).The content of the volatiles,affecting fruit flavor,significantly increased in the transition from breaker to red ripe fruit stage.Moreover,the total content of the volatiles in wild tomatoes was much higher than that in the cultivated tomatoes.The content variations of all volatile flavors were clustered into 10 groups by hierarchical cluster and Pearson coefficient correlation(PCC)analysis.The fruit transcriptome was also patterned into 10 groups,with significant variations both from the mature green to breaker fruit stage and from the breaker to red ripe fruit stage.Combining the metabolome and the transcriptome of the same developmental stage of fruits by co-expression analysis,we found that the expression level of 1182 genes was highly correlated with the content of volatile flavor compounds,thereby constructing two regulatory pathways of important volatile flavors.One pathway is tetrahydrothiazolidine N-hydroxylase(SlTNH1)-dependent,which is regulated by two transcription factors(TFs)from the bHLH and AP2/ERF families,controlling the synthesis of 2-isobutylthiazole in amino acid metabolism.The other is lipoxygenase(Sl LOX)-dependent,which is regulated by one TF from the HD-Zip family,controlling the synthesis of hexanal and(Z)-2-heptenal in fatty acid metabolism.Dual-luciferase assay confirmed the binding of b HLH and AP2/ERF to their structural genes.The findings of this study provide new insights into volatile flavor formation in tomato fruit,which can be useful for tomato flavor improvement.展开更多
This study examines the volatility spillovers in four representative exchanges and for six liquid cryptocurrencies.Using the high-frequency trading data of exchanges,the heterogeneity of exchanges in terms of volatili...This study examines the volatility spillovers in four representative exchanges and for six liquid cryptocurrencies.Using the high-frequency trading data of exchanges,the heterogeneity of exchanges in terms of volatility spillover can be examined dynamically in the time and frequency domains.We find that Ripple is a net receiver on Coinbase but acts as a net contributor on other exchanges.Bitfinex and Binance have different net spillover effects on the six cryptocurrency markets.Finally,we identify the determinants of total connectedness in two types of volatility spillover,which can explain cryptocurrency or exchange interlinkage.展开更多
Furniture is identified as a vital volatile organic compound(VOC)emission source in the indoor environment.Leather has become the most common raw and auxiliary fabric material for upholstered furniture,particularly wi...Furniture is identified as a vital volatile organic compound(VOC)emission source in the indoor environment.Leather has become the most common raw and auxiliary fabric material for upholstered furniture,particularly with extensive consumption in sofas,due to its abundant resources and efficient functions.Despite being widely traded across the world,little research has been conducted on the VOCs released by leathermaterials and their health risk assessment in the indoor environment.Accordingly,this study investigated the VOC emissions of leather with different grades and the health risk of the inhalation exposure.Based on the ultra-fast gas phase electronic nose(EN)and GC-FID/Qtof,the substantial emissions of aliphatic aldehyde ketones(Aks),particularly hexanal,appear to be the cause of off-flavor in medium and low grade(MG and LG)sofa leathers.The health risk assessment indicated that leather materials barely pose non-carcinogenic and carcinogenic effects to residents.Given the abundance of VOC sources and the accumulation of health risks in the indoor environment,more stringent specifications concerning qualitative and quantitative content should be extended to provide VOC treatment basic for the manufacturing industry and obtain better indoor air quality.展开更多
Determining which variables affect price realized volatility has always been challenging.This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast.T...Determining which variables affect price realized volatility has always been challenging.This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast.The methodological proposal is based on using the best econometric and machine learning models to forecast realized volatility.In particular,the best forecasting from heterogeneous autoregressive and long short-term memory models are used to determine the influence of the Standard and Poor’s 500 index,euro-US dollar exchange rate,price of gold,and price of Brent crude oil on the realized volatility of natural gas.These financial assets influenced the realized volatility of natural gas in 87.4% of the days analyzed;the euro-US dollar exchange rate was the primary financial asset and explained 40.1% of the influence.The results of the proposed daily analysis differed from those of the methodology used to study the entire period.The traditional model,which studies the entire period,cannot determine temporal effects,whereas the proposed methodology can.The proposed methodology allows us to distinguish the effects for each day,week,or month rather than averages for entire periods,with the flexibility to analyze different frequencies and periods.This methodological capability is key to analyzing influences and making decisions about realized volatility.展开更多
VOCs(Volatile organic compounds)exert a vital role in ozone and secondary organic aerosol production,necessitating investigations into their concentration,chemical characteristics,and source apportionment for the effe...VOCs(Volatile organic compounds)exert a vital role in ozone and secondary organic aerosol production,necessitating investigations into their concentration,chemical characteristics,and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric pollution.FromJuly to October 2020,onlinemonitoringwas conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and reactivity.Additionally,the PMF(positive matrix factorization)method was utilized to identify the VOCs sources.Results indicated that the TVOCs(total VOCs)concentration was(96.7±63.4μg/m^3),with alkanes exhibiting the highest concentration of(36.1±26.4μg/m^3),followed by OVOCs(16.4±14.4μg/m^3).The key active components were alkenes and aromatics,among which xylene,propylene,toluene,propionaldehyde,acetaldehyde,ethylene,and styrene played crucial roles as reactive species.The sources derived from PMF analysis encompassed vehicle emissions,solvent and coating sources,combustion sources,industrial emissions sources,as well as plant sources,the contribution of which were 37.80%,27.93%,16.57%,15.24%,and 2.46%,respectively.Hence,reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels.展开更多
The paper analyzes the cryptocurrency ecosystem at both the aggregate and individual levels to understand the factors that impact future volatility.The study uses high-frequency panel data from 2020 to 2022 to examine...The paper analyzes the cryptocurrency ecosystem at both the aggregate and individual levels to understand the factors that impact future volatility.The study uses high-frequency panel data from 2020 to 2022 to examine the relationship between several market volatility drivers,such as daily leverage,signed volatility and jumps.Several known autoregressive model specifications are estimated over different market regimes,and results are compared to equity data as a reference benchmark of a more mature asset class.The panel estimations show that the positive market returns at the high-frequency level increase price volatility,contrary to what is expected from the classical financial literature.We attributed this effect to the price dynamics over the last year of the dataset(2022)by repeating the estimation on different time spans.Moreover,the positive signed volatility and negative daily leverage positively impact the cryptocurrencies’future volatility,unlike what emerges from the same study on a cross-section of stocks.This result signals a structural difference in a nascent cryptocurrency market that has to mature yet.Further individual-level analysis confirms the findings of the panel analysis and highlights that these effects are statistically significant and commonly shared among many components in the selected universe.展开更多
This study examined the interconnectedness and volatility correlation between cryptocurrency and traditional financial markets in the five largest African countries,addressing concerns about potential spillover effect...This study examined the interconnectedness and volatility correlation between cryptocurrency and traditional financial markets in the five largest African countries,addressing concerns about potential spillover effects,especially the high volatility and lack of regulation in the cryptocurrency market.The study employed both diagonal BEKK-GARCH and DCC-GARCH to analyze the existence of spillover effects and correlation between both markets.A daily time series dataset from January 1,2017,to December 31,2021,was employed to analyze the contagion effect.Our findings reveal a significant spillover effect from cryptocurrency to the African traditional financial market;however,the percentage spillover effect is still low but growing.Specifically,evidence is insufficient to suggest a spillover effect from cryptocurrency to Egypt and Morocco’s financial markets,at least in the short run.Evidence in South Africa,Nigeria,and Kenya indicates a moderate but growing spillover effect from cryptocurrency to the financial market.Similarly,we found no evidence of a spillover effect from the African financial market to the cryptocurrency market.The conditional correlation result from the DCC-GARCH revealed a positive low to moderate correlation between cryptocurrency volatility and the African financial market.Specifically,the DCC-GARCH revealed a greater integration in both markets,especially in the long run.The findings have policy implications for financial regulators concerning the dynamics of both markets and for investors interested in portfolio diversification within the two markets.展开更多
Ubiquitous contamination of the soil environment with volatile organic compounds(VOCs)has raised considerable concerns.However,there is still limited comprehensive surveying of soil VOCs on a national scale.Herein,65 ...Ubiquitous contamination of the soil environment with volatile organic compounds(VOCs)has raised considerable concerns.However,there is still limited comprehensive surveying of soil VOCs on a national scale.Herein,65 species of VOCswere simultaneously determined in surface soil samples collected from 63 chemical industrial parks(CIPs)across China.The results showed that the total VOC concentrations ranged from 7.15 to 1842 ng/g with a mean concentration of 326 ng/g(median:179 ng/g).Benzene homologs and halogenated hydrocarbons were identified as the dominant contaminant groups.Positive correlations between many VOC species indicated that these compounds probably originated from similar sources.Spatially,the hotspots of VOC pollution were located in eastern and southern China.Soils with higher clay content and a higher fraction of total organic carbon(TOC)content were significantly associated with higher soil VOC concentrations.Precipitation reduces the levels of highly water-soluble substances in surface soils.Both positive matrix factorization(PMF)and principal component analysis-multiple linear regression(PCA-MLR)identified a high proportion of industrial sources(PMF:59.2%and PCA-MLR:66.5%)and traffic emission sources(PMF:32.3%and PCA-MLR:33.5%).PMF,which had a higher R^(2) value(0.7892)than PCA-MLR(0.7683),was the preferred model for quantitative source analysis of soil VOCs.The health risk assessment indicated that the non-carcinogenic and carcinogenic risks of VOCs were at acceptable levels.Overall,this study provides valuable data on the occurrence of VOCs in soil from Chinese CIPs,which is essential for a comprehensive understanding of their environmental behavior.展开更多
文摘Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.
文摘Using daily BTC-USD data from September 19,2014 to January 21,2024,this paper re-examines whether weekends differ from weekdays for Bitcoin along three margins:average returns,close-to-close volatility,and trading activity.We implement Welch mean comparisons and HAC-robust OLS with month fixed effects(bandwidths 5,7,and 14).In the full sample and across subsamples(2016–2019;2020–2023;early 2024),we find no detectable weekend–weekday gap in average returns,while volatility and trading activity are lower on weekends.The patterns are robust to using squared returns as a volatility proxy.The joint evidence is consistent with liquidity and attention mechanisms—quieter weekends rather than compensating return premia.Replication files reproduce all tables and figures.
文摘Cryptocurrency,a booming decentralised asset designed based on the blockchain architecture,is particularly important to the market at the present time by studying the volatility risk of cryptocurrencies.In this paper,we empirically analyse the volatility risk of cryptocurrencies through quantitative analysis models,comprehensively using the Markov state transition GARCH model with skewed distribution(Skew-MSGARCH)and the autoregressive conditional volatility density ARJI model introducing the Poisson jump factor,and selecting the earliest developed and the most mature currency price volatility daily return series,to deeply explore the volatility risk of digital cryptocurrencies.risk.Finally,it can be seen through in-depth analyses that the expectation factor and information inducement are the main reasons leading to the exacerbation of the volatility risk of digital cryptocurrencies.It is recommended that this situation be optimised and improved in terms of the value function of digital cryptocurrencies themselves and the implementation of systematic risk management and regulatory innovation.As an important component of the digital economy,blockchain technology can effectively regulate and improve the volatility of digital cryptocurrencies under macroeconomic policies,thereby maintaining the security and stability of emerging financial markets.
文摘In this paper,we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options.Furthermore,we assume that the interest rates and the jump intensities of the assets are stochastic.Under the proposed framework,first,we derive the analytical pricing formula for power options by using Fourier transform technique,Esscher transform and characteristic function.Then we provide the efficient approximation to calculate the analytical pricing formula of power options by using the FFT approach and examine the accuracy of the approximation by Monte Carlo simulation.Finally,we provide some sensitivity analysis of the model parameters to power options.Numerical examples show this model is suitable for empirical work in practice.
基金supported by the National Natural Science Foundation of China(Grant No.72401207 and 42101300)Beijing Municipal Education Commission,China(Grant No.SM202110038001).
文摘This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even bring uncertainties to macroeconomic output.Especially in the carbon neutrality context,China's coal market is being reconstructed and responding to imbalances between supply and demand;identifying the CPVSs helps alleviate rising market instability and prevent energy-induced system risk.To achieve this objective,we explore causalities among 938 weekly coal prices reported by different coal-producing areas of China from 2006.9.4 to 2021.7.12 using the transfer entropy method.Then,coal price volatility influence is quantified to identify the CPVSs by conjointly using complex network theory and a rank aggregation method.The validity test demonstrates that the proposed hybrid method efficiently identifies the CPVSs as it correlates to many price determinants,e.g.,electricity and coal consumption and generation.The empirical results show that causalities among coal prices changed dramatically in 2016,2018,and 2020,affected by coal decapacity and carbon neutrality policies.Before 2018,coal-producing provinces with strong demand for coal and electricity,e.g.,Jiangxi,Chongqing,and Sichuan,were CPVSs;after 2019,those with comparative advantages in coal supply,e.g.,Gansu and Ningxia,were CPVSs.Overall,the coal market is unstable and sensitive to energy policy and external shocks.Policymakers and market participants are recommended to monitor and manage the CPVSs to improve energy security,avoid policy-induced instability and prevent risks caused by coal price fluctuations.
文摘Motivated by a significant impact of price volatility on food security and economic stability inCameroon,this study aims to understand the factors influencing agricultural product price volatility(APPV)and formulateeffective policies for mitigating its negative impactand promoting sustainable economic growth.Specifically,this research used theautoregressive distributed lag-error correction model(ARDL-ECM)to analyse the impact of agricultural productivity,agricultural product imports,population,temperature variation,gross domestic product(GDP)per capita,and government expenditure on APPV based on the annual data from 2000 to 2021.The ARDL-ECM estimation results revealed that agricultural productivity(β=4.901),agricultural product imports(β=1.012),population(β=13.635),and GDP per capita(β=2.794)were positively related toAPPV,while temperature variation(β=-0.990)and government expenditure(β=-8.585)were negatively related toAPPVin the long term.However,temperature variation had a positive relationship with APPV in the short term.Moreover,the Granger causality test showed that there werebidirectional causality of APPV with agricultural productivityandagricultural product imports,and unidirectional causality of APPVwith population,temperature variation,GDP per capita,and government expenditure.The findings highlight the importance of public policies in stabilizing agricultural product prices by investing in agricultural research,improving access to agricultural inputs,strengthening farmer capacities,implementing climate adaptation measures,and enhancing rural infrastructure.Thesepolicies can reduce APPV,improve food security,and promote inclusive economic growth in Cameroon.
基金supported by the Sichuan Natural Science Foundation (No.2022NSFSC0982)the Sichuan Science and Technology Program (No.2019YFS0476)the National Natural Science Foundation of China (No.41805095)。
文摘To investigate the volatility of atmospheric particulates and the evolution of other particulate properties(chemical composition,particle size distribution and mixing state)with temperature,a thermodenuder coupled with a single particle aerosol mass spectrometer was used to conduct continuous observations of atmospheric fine particles in Chengdu,southwest China.Because of their complex sources and secondary reaction processes,the average mass spectra of single particles contained a variety of chemical components(including organic,inorganic and metal species).When the temperature rose from room temperature to280℃,the relative areas of volatile and semi-volatile components decreased,while the relative areas of less or non-volatile components increased.Most(>80%)nitrate and sulfate existed in the form of NH_(4)NO_(3)and(NH_(4))_(2)SO_(4),and their volatilization temperatures were50–100℃and 150–280℃,respectively.The contribution of biomass burning(BB)and vehicle emission(VE)particles increased significantly at 280℃,which emphasized the important role of regional biomass burning and local motor vehicle emissions to the core of particles.With the increase in temperature,the particle size of the particles coated with volatile or semi-volatile components was reduced,and their mixing with secondary inorganic components was significantly weakened.The formation of K-nitrate(KNO_(3))and K-sulfate(KSO_(4))particles was dominated by liquid-phase processes and photochemical reactions,respectively.Reducing KNO_(3)and BB particles is the key to improving visibility.These new results are helpful towards better understanding the initial sources,pollution formation mechanisms and climatic effects of fine particulate matter in this megacity in southwest China.
基金supported by the National Key Research and Development Program(2022YFC3702701)the Shanghai Municipal Science and Technology Commission(21TQ015)the Shanghai International Science and Technology Partnership Project,China(21230780200).
文摘Stock volatility constitutes an adverse psychological stressor,but few large-scale studies have focused on its impact on major adverse cardiovascular events(MACEs)and suicide.Here,we conducted an individual-level time-stratified case-crossover study to explore the association of daily stock volatility(daily returns and intra-daily oscillations for three kinds of stock indices)with MACEs and suicide among more than 12 million individual decedents from all counties in the mainland of China between 2013 and 2019.For daily stock returns,both stock increases and decreases were associated with increased mortal-ity risks of all MACEs and suicide.There were consistent and positive associations between intra-daily stock oscillations and mortality due to MACEs and suicide.The excess mortality risks occurred at the cur-rent day(lag 0 d),persisted for two days,and were greatest for suicide and hemorrhagic stroke.Taking the present-day Shanghai and Shenzhen 300 Index as an example,a 1%decrease in daily returns was associated with 0.74%-1.04%and 1.77%increases in mortality risks of MACEs and suicide,respectively;the corresponding risk increments were 0.57%-0.85%and 0.92%for a 1%increase in daily returns and 0.67%-0.77%and 1.09%for a 1%increase in intra-daily stock oscillations.The excess risks were more pro-nounced among individuals aged 65-74 years,males,and those with lower education levels.Our findings revealed considerable health risks linked to sociopsychological stressors,which are helpful for the gov-ernment and general public to mitigate the immediate cardiovascular and mental health risks associated with stock market volatility.
基金supported by the National Natural Science Foundation of China(Nos.41905028,91544218,12134013,and 62127818)the National Key Researchand Development Program of China(No.2017YFC0209504)+3 种基金Anhui Provincial Natural Science Foundation(Nos.1908085MD114 and 2108085MD139)the Hefei Municipal Natural Science Foundation(No.2021007)the Key Research&Development program of Anhui Province(No.202104a05020010)the HFIPS Director’s Fund(Nos.YZJJ2022QN04 and BJPY2021A04)。
文摘Under high relative humidity(RH)conditions,the release of volatile components(such as acetate)has a significant impact on the aerosol hygroscopicity.In this work,one surface plasmon resonance microscopy(SPRM)measurement system was introduced to determine the hygroscopic growth factors(GFs)of three acetate aerosols separately or mixed with glucose at different RHs.For Ca(CH_(3)COO)_(2) or Mg(CH_(3)COO)_(2) aerosols,the hygroscopic growth trend of each time was lower than that of the previous time in three cyclic humidification from 70% RH to 90% RH,which may be due to the volatility of acetic acid leading to the formation of insoluble hydroxide(Ca(OH)_(2) or Mg(OH)_(2))under high RH conditions.Then the third calculated GF(using the Zdanovskii-Stokes-Robinson method)for Ca(CH_(3)COO)_(2) or Mg(CH_(3)COO)_(2) in bicomponent aerosols with 1:1 mass ratio were 3.20% or 5.33% lower than that of the first calculated GF at 90% RH.The calculated results also showed that the hygroscopicity change of bicomponent aerosol was negatively correlated with glucose content,especially when the mass ratio of Mg(CH_(3)COO)_(2) to glucose was 1:2,the GF at 90% RH only decreased by4.67% after three cyclic humidification.Inductively coupled plasma atomic emission spectrum(ICP-AES)based measurements also indicated that the changes of Mg^(2+)concentration in bicomponent was lower than that of the single-component.The results of this study reveal thatduring the efflorescence transitions of atmospheric nanoparticles,the organic acids diffusion rate may be inhibited by the coating effect of neutral organic components,and the particles aging cycle will be prolonged.
文摘This study utilizes the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to investigate the dynamic relationship between Chinese and U.S. stock markets amid the COVID-19 pandemic. Initially, a univariate GARCH model is developed to derive residual sequences, which are then used to estimate the DCC model parameters. The research reveals a significant rise in the interconnection between the Chinese and U.S. stock markets during the pandemic. The S&P 500 index displayed higher sensitivity and greater volatility in response to the pandemic, whereas the CSI 300 index showed superior resilience and stability. Analysis and model estimation suggest that the market’s dependence on historical data has intensified and its sensitivity to recent shocks has heightened. Predictions from the model indicate increased market volatility during the pandemic. While the model is proficient in capturing market trends, there remains potential for enhancing the accuracy of specific volatility predictions. The study proposes recommendations for policymakers and investors, highlighting the importance of improved cooperation in international financial market regulation and investor education.
文摘Black-Scholes Model (B-SM) simulates the dynamics of financial market and contains instruments such as options and puts which are major indices requiring solution. B-SM is known to estimate the correct prices of European Stock options and establish the theoretical foundation for Option pricing. Therefore, this paper evaluates the Black-Schole model in simulating the European call in a cash flow in the dependent drift and focuses on obtaining analytic and then approximate solution for the model. The work also examines Fokker Planck Equation (FPE) and extracts the link between FPE and B-SM for non equilibrium systems. The B-SM is then solved via the Elzaki transform method (ETM). The computational procedures were obtained using MAPLE 18 with the solution provided in the form of convergent series.
基金supported by Hong Kong Environment Protection Department(Quotation Ref.18-06532)Hong Kong Innovation and Technology Fund(ITS/193/20FP)Hong Kong Research Grants Council(No.26304921).
文摘Initial success has been achieved in Hong Kong in controlling primary air pollutants,but ambient ozone levels kept increasing during the past three decades.Volatile organic compounds(VOCs)are important for mitigating ozone pollution as its major precursors.This study analyzed VOC characteristics of roadside,suburban,and rural sites in Hong Kong to investigate their compositions,concentrations,and source contributions.Herewe showthat the TVOC concentrations were 23.05±13.24,12.68±15.36,and 5.16±5.48 ppbv for roadside,suburban,and rural sites between May 2015 to June 2019,respectively.By using Positive Matrix Factorization(PMF)model,six sources were identified at the roadside site over five years:Liquefied petroleum gas(LPG)usage(33%–46%),gasoline evaporation(8%–31%),aged air mass(11%–28%),gasoline exhaust(5%–16%),diesel exhaust(2%–16%)and fuel filling(75–9%).Similarly,six sources were distinguished at the suburban site,including LPG usage(30%–33%),solvent usage(20%–26%),diesel exhaust(14%–26%),gasoline evaporation(8%–16%),aged air mass(4%–11%),and biogenic emissions(2%–5%).At the rural site,four sources were identified,including aged airmass(33%–51%),solvent usage(25%–30%),vehicular emissions(11%–28%),and biogenic emissions(6%–12%).The analysis further revealed that fuel filling and LPG usage were the primary contributors to OFP and OH reactivity at the roadside site,while solvent usage and biogenic emissions accounted for almost half of OFP and OH reactivity at the suburban and rural sites,respectively.These findings highlight the importance of identifying and characterizing VOC sources at different sites to help policymakers develop targeted measures for pollution mitigation in specific areas.
基金supported by the National Natural Science Foundation of China(Grant Nos.32120103010,32002050)Beijing Joint Research Program for Germplasm Innovation and New Variety Breeding(Grant No.G20220628003-03)the Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences。
文摘Tomato is an important economic crop all over the world.Volatile flavors in tomato fruit are key factors influencing consumer liking and commercial quality.However,the regulatory mechanism controlling the volatile flavors of tomatoes is still not clear.Here,we integrated the metabolome and transcriptome of the volatile flavors in tomato fruit to explore the regulatory mechanism of volatile flavor formation,using wild and cultivated tomatoes with significant differences in flavors.A total of 35 volatile flavor compounds were identified,based on the solid phase microextraction-gas chromatography-mass spectrometry(SPME-GC-MS).The content of the volatiles,affecting fruit flavor,significantly increased in the transition from breaker to red ripe fruit stage.Moreover,the total content of the volatiles in wild tomatoes was much higher than that in the cultivated tomatoes.The content variations of all volatile flavors were clustered into 10 groups by hierarchical cluster and Pearson coefficient correlation(PCC)analysis.The fruit transcriptome was also patterned into 10 groups,with significant variations both from the mature green to breaker fruit stage and from the breaker to red ripe fruit stage.Combining the metabolome and the transcriptome of the same developmental stage of fruits by co-expression analysis,we found that the expression level of 1182 genes was highly correlated with the content of volatile flavor compounds,thereby constructing two regulatory pathways of important volatile flavors.One pathway is tetrahydrothiazolidine N-hydroxylase(SlTNH1)-dependent,which is regulated by two transcription factors(TFs)from the bHLH and AP2/ERF families,controlling the synthesis of 2-isobutylthiazole in amino acid metabolism.The other is lipoxygenase(Sl LOX)-dependent,which is regulated by one TF from the HD-Zip family,controlling the synthesis of hexanal and(Z)-2-heptenal in fatty acid metabolism.Dual-luciferase assay confirmed the binding of b HLH and AP2/ERF to their structural genes.The findings of this study provide new insights into volatile flavor formation in tomato fruit,which can be useful for tomato flavor improvement.
基金National Natural Science Foundation of China(Grant no.71771006)Science and Technology Support Plan of Guizhou(Grant no.2023-221).
文摘This study examines the volatility spillovers in four representative exchanges and for six liquid cryptocurrencies.Using the high-frequency trading data of exchanges,the heterogeneity of exchanges in terms of volatility spillover can be examined dynamically in the time and frequency domains.We find that Ripple is a net receiver on Coinbase but acts as a net contributor on other exchanges.Bitfinex and Binance have different net spillover effects on the six cryptocurrency markets.Finally,we identify the determinants of total connectedness in two types of volatility spillover,which can explain cryptocurrency or exchange interlinkage.
基金supported by the National Key Research and Development Program of China (No.2019YFC1904501).
文摘Furniture is identified as a vital volatile organic compound(VOC)emission source in the indoor environment.Leather has become the most common raw and auxiliary fabric material for upholstered furniture,particularly with extensive consumption in sofas,due to its abundant resources and efficient functions.Despite being widely traded across the world,little research has been conducted on the VOCs released by leathermaterials and their health risk assessment in the indoor environment.Accordingly,this study investigated the VOC emissions of leather with different grades and the health risk of the inhalation exposure.Based on the ultra-fast gas phase electronic nose(EN)and GC-FID/Qtof,the substantial emissions of aliphatic aldehyde ketones(Aks),particularly hexanal,appear to be the cause of off-flavor in medium and low grade(MG and LG)sofa leathers.The health risk assessment indicated that leather materials barely pose non-carcinogenic and carcinogenic effects to residents.Given the abundance of VOC sources and the accumulation of health risks in the indoor environment,more stringent specifications concerning qualitative and quantitative content should be extended to provide VOC treatment basic for the manufacturing industry and obtain better indoor air quality.
文摘Determining which variables affect price realized volatility has always been challenging.This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast.The methodological proposal is based on using the best econometric and machine learning models to forecast realized volatility.In particular,the best forecasting from heterogeneous autoregressive and long short-term memory models are used to determine the influence of the Standard and Poor’s 500 index,euro-US dollar exchange rate,price of gold,and price of Brent crude oil on the realized volatility of natural gas.These financial assets influenced the realized volatility of natural gas in 87.4% of the days analyzed;the euro-US dollar exchange rate was the primary financial asset and explained 40.1% of the influence.The results of the proposed daily analysis differed from those of the methodology used to study the entire period.The traditional model,which studies the entire period,cannot determine temporal effects,whereas the proposed methodology can.The proposed methodology allows us to distinguish the effects for each day,week,or month rather than averages for entire periods,with the flexibility to analyze different frequencies and periods.This methodological capability is key to analyzing influences and making decisions about realized volatility.
基金supported by the Natural Science Foundation of Hebei Province(Nos.D2019106042,D2020304038,and D2021106002)the National Natural Science Foundation of China(No.22276099)+1 种基金the State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex(No.2021080544)the Environmental Monitoring Research Foundation of Jiangsu Province(No.2211).
文摘VOCs(Volatile organic compounds)exert a vital role in ozone and secondary organic aerosol production,necessitating investigations into their concentration,chemical characteristics,and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric pollution.FromJuly to October 2020,onlinemonitoringwas conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and reactivity.Additionally,the PMF(positive matrix factorization)method was utilized to identify the VOCs sources.Results indicated that the TVOCs(total VOCs)concentration was(96.7±63.4μg/m^3),with alkanes exhibiting the highest concentration of(36.1±26.4μg/m^3),followed by OVOCs(16.4±14.4μg/m^3).The key active components were alkenes and aromatics,among which xylene,propylene,toluene,propionaldehyde,acetaldehyde,ethylene,and styrene played crucial roles as reactive species.The sources derived from PMF analysis encompassed vehicle emissions,solvent and coating sources,combustion sources,industrial emissions sources,as well as plant sources,the contribution of which were 37.80%,27.93%,16.57%,15.24%,and 2.46%,respectively.Hence,reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels.
文摘The paper analyzes the cryptocurrency ecosystem at both the aggregate and individual levels to understand the factors that impact future volatility.The study uses high-frequency panel data from 2020 to 2022 to examine the relationship between several market volatility drivers,such as daily leverage,signed volatility and jumps.Several known autoregressive model specifications are estimated over different market regimes,and results are compared to equity data as a reference benchmark of a more mature asset class.The panel estimations show that the positive market returns at the high-frequency level increase price volatility,contrary to what is expected from the classical financial literature.We attributed this effect to the price dynamics over the last year of the dataset(2022)by repeating the estimation on different time spans.Moreover,the positive signed volatility and negative daily leverage positively impact the cryptocurrencies’future volatility,unlike what emerges from the same study on a cross-section of stocks.This result signals a structural difference in a nascent cryptocurrency market that has to mature yet.Further individual-level analysis confirms the findings of the panel analysis and highlights that these effects are statistically significant and commonly shared among many components in the selected universe.
文摘This study examined the interconnectedness and volatility correlation between cryptocurrency and traditional financial markets in the five largest African countries,addressing concerns about potential spillover effects,especially the high volatility and lack of regulation in the cryptocurrency market.The study employed both diagonal BEKK-GARCH and DCC-GARCH to analyze the existence of spillover effects and correlation between both markets.A daily time series dataset from January 1,2017,to December 31,2021,was employed to analyze the contagion effect.Our findings reveal a significant spillover effect from cryptocurrency to the African traditional financial market;however,the percentage spillover effect is still low but growing.Specifically,evidence is insufficient to suggest a spillover effect from cryptocurrency to Egypt and Morocco’s financial markets,at least in the short run.Evidence in South Africa,Nigeria,and Kenya indicates a moderate but growing spillover effect from cryptocurrency to the financial market.Similarly,we found no evidence of a spillover effect from the African financial market to the cryptocurrency market.The conditional correlation result from the DCC-GARCH revealed a positive low to moderate correlation between cryptocurrency volatility and the African financial market.Specifically,the DCC-GARCH revealed a greater integration in both markets,especially in the long run.The findings have policy implications for financial regulators concerning the dynamics of both markets and for investors interested in portfolio diversification within the two markets.
基金supported by the Medical and Health Projects in Zhejiang Province(No.2022PY049)the Basic Scientific Research Project of Hangzhou Medical College(No.YS2021006)Key Discipline of Zhejiang Province in Public Health and Preventive Medicine(First Class,Category A),Hangzhou Medical College.
文摘Ubiquitous contamination of the soil environment with volatile organic compounds(VOCs)has raised considerable concerns.However,there is still limited comprehensive surveying of soil VOCs on a national scale.Herein,65 species of VOCswere simultaneously determined in surface soil samples collected from 63 chemical industrial parks(CIPs)across China.The results showed that the total VOC concentrations ranged from 7.15 to 1842 ng/g with a mean concentration of 326 ng/g(median:179 ng/g).Benzene homologs and halogenated hydrocarbons were identified as the dominant contaminant groups.Positive correlations between many VOC species indicated that these compounds probably originated from similar sources.Spatially,the hotspots of VOC pollution were located in eastern and southern China.Soils with higher clay content and a higher fraction of total organic carbon(TOC)content were significantly associated with higher soil VOC concentrations.Precipitation reduces the levels of highly water-soluble substances in surface soils.Both positive matrix factorization(PMF)and principal component analysis-multiple linear regression(PCA-MLR)identified a high proportion of industrial sources(PMF:59.2%and PCA-MLR:66.5%)and traffic emission sources(PMF:32.3%and PCA-MLR:33.5%).PMF,which had a higher R^(2) value(0.7892)than PCA-MLR(0.7683),was the preferred model for quantitative source analysis of soil VOCs.The health risk assessment indicated that the non-carcinogenic and carcinogenic risks of VOCs were at acceptable levels.Overall,this study provides valuable data on the occurrence of VOCs in soil from Chinese CIPs,which is essential for a comprehensive understanding of their environmental behavior.
