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Research article Special Issues

Heterogeneity and spillover effects of carbon emission trading on green innovation

  • Received: 13 August 2022 Revised: 18 November 2022 Accepted: 14 December 2022 Published: 01 February 2023
  • The massive emission of greenhouse gases poses a serious threat to the ecological environment. In this context, the relevant effects of the carbon emission trading (CET) market, which promotes greenhouse gas emission reduction by market means, have been widely investigated. Taking the China's CET pilot as a research target, the heterogeneity and spillover effects of CET on green innovation are explored by using the sample data of 279 prefecture-level cities in China from 2008 to 2019. The results are as follows. First, on the whole, CET significantly promotes strategic green innovation, but it has no significant effect on substantive green innovation. Second, the green innovation effect of CET varies with the level of green innovation, and the heterogeneous effects of green innovation are also reflected in different degrees of marketization, fiscal decentralization and government environmental concern. Third, CET has a positive spillover effect on green innovation, and the spillover effect is more significant than the direct effect, accounting for 74.8% of the total effect. Finally, some corresponding policy suggestions are put forward according to the above research conclusions.

    Citation: Yanhong Feng, Qingqing Hu. Heterogeneity and spillover effects of carbon emission trading on green innovation[J]. Mathematical Biosciences and Engineering, 2023, 20(4): 6468-6497. doi: 10.3934/mbe.2023279

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  • The massive emission of greenhouse gases poses a serious threat to the ecological environment. In this context, the relevant effects of the carbon emission trading (CET) market, which promotes greenhouse gas emission reduction by market means, have been widely investigated. Taking the China's CET pilot as a research target, the heterogeneity and spillover effects of CET on green innovation are explored by using the sample data of 279 prefecture-level cities in China from 2008 to 2019. The results are as follows. First, on the whole, CET significantly promotes strategic green innovation, but it has no significant effect on substantive green innovation. Second, the green innovation effect of CET varies with the level of green innovation, and the heterogeneous effects of green innovation are also reflected in different degrees of marketization, fiscal decentralization and government environmental concern. Third, CET has a positive spillover effect on green innovation, and the spillover effect is more significant than the direct effect, accounting for 74.8% of the total effect. Finally, some corresponding policy suggestions are put forward according to the above research conclusions.



    In this paper, we study the pointwise long time behavior of the solution for the nonlinear wave equation with frictional and visco-elastic damping terms

    {2tuc2Δu+ν1tuν2tΔu=f(u),u|t=0=u0(x),ut|t=0=u1(x), (1)

    in multi-dimensional half space Rn+:=R+×Rn1, with absorbing and radiative boundary condition

    (a1x1u+a2u)(x1=0,x,t)=0. (2)

    x=(x1,x) is the space variable with x1R+:=(0,), x=(x2,,xn)Rn1, t>0 is the time variable. ν1 and ν2 are positive constant viscosities, a1 and a2 are constants. The Laplacian Δ=nj=12xj, f(u) is the smooth nonlinear term and f(u)=O(|u|k) when k>0.

    Over the past few decades, many mathematicians have concentrated on solving different kinds of damped nonlinear wave equations. The first kind is called the frictional damped wave equation, which is given as follows

    {2tuc2Δu+νtu=f(u),u|t=0=u0(x),ut|t=0=u1(x), (3)

    see [9,19,20,23] for the references. It is showed that for the long time, the fundamental solution for the linear system of (3) behaves like the Gauss kernel e|x|2C(t+1)(t+1)n2. The second kind is called the visco-elastic damped wave, which is given by the following

    {2tuc2ΔuνtΔu=f(u),u|t=0=u0(x),ut|t=0=u1(x). (4)

    One can refer to [22] for the decaying rate of the linear solution, [11,12] for the asymptotic profiles of the linear problem, [4,21] for the nonlinear equation, etc. In [9], the authors studied the fundamental solution for the linear system of (4). The results show that the hyperbolic wave transport mechanism and the visco-elastic damped mechanism interact with each other so that the solution behaves like the convented heat kernel, i.e., e(|x|ct)2C(t+1)(t+1)3n34 for the odd dimensional case and e(|x|ct)2C(t+1)(t+1)3n14+H(ct|x|)(1+t)3n24(ct|x|+t)12 for the even dimensional case. The solution exhibits the generalized Huygens principle. For other damped wave equations, one can refer to [2,27] for the damped abstract wave equation, and [14,15,16] for the existence and large time behavior of the solutions for the Cauchy problem of mixed damping (both frictional and visco-elastic damping terms are involved) wave equation.

    For the initial-boundary value problem of the different damped wave equations, many authors studied the global well-posedness existence, long time behaviors, global attractors and decaying rate estimates of some elementary wave by using delicate energy estimate method, for example [1,13,25,26,28,29]. In this paper, we will use the pointwise estimate technique to give the long time behavior of the solution for system (1) with boundary condition (2). The main part of this technique is the construction and estimation of the Green's functions for the following linear systems:

    {2tG1c2ΔG1+ν1tG1ν2tΔG1=0,x1,y1>0,xRn1,t>0,G1(x1,x,0;y1)=δ(x1y1)δ(x),G1t(x1,x,0;y1)=0,a1x1G1(0,x,t;y1)+a2G1(0,x,t;y1)=0; (5)
    {2tG2c2ΔG2+ν1tG2ν2tΔG2=0,x1,y1>0,xRn1,t>0,G2(x1,x,0;y1)=0,G2t(x1,x,0;y1)=δ(x1y1)δ(x),a1x1G2(0,x,t;y1)+a2G2(0,x,t;y1)=0. (6)

    The way of estimating the Green's functions Gi was initiated by [17] and developed by [3,5,6,8,10,18,24] and the reference therein. Following the scheme in [10], we will find the relations between the fundamental solutions for the linear Cauchy problem and Green's functions for the linear half space problem, by comparing their symbols in the transformed tangential-spatial and time variables. Then the Green's functions can be described in terms of the fundamental solutions and the boundary surface operator.

    With the help of the accurate expression of Green's functions for the linear half space problem and the Duhamel's principle, we get the pointwise long time behavior for the nonlinear solution αxu, |α|1. We only treat the case a1a2<0. The boundary condition of Dirichlet type (a1=0) and Neumann type (a2=0) are much simpler. For the case of a1a2>0, the linear problem is unstable. The main results of our paper are given as follows:

    Theorem 1.1. Let n=2,3 be the spatial dimension, k>1+2n. Assume the initial data (u0(x),u1(x))(Hl+1Wl,1)×(HlWl,1), l[n2]+2, and satisfy

    |αxu0,αxu1|O(1)ε(1+|x|2)r,  r>n2,  |α|1,

    ε sufficiently small, then there exists a unique global classical solution to the problem (1) with the mixed boundary condition (2) while a1a20. The solution has the following pointwise estimate:

    |αxu(x,t)|O(1)ε(1+t)|α|/2(1+t+|x|2)n2.

    Moreover, we get the following optimal Lp(Rn+) estimate of the solution

    αxu(,t)Lp(Rn+)O(1)ε(1+t)n2(11p)|α|2,  p(1,].

    Remark 1. We can develop a similar theorem for the case of higher space dimension with a suitable choice of k which guarantees the existence of the solution. In Section 2.2, the approximation used in the calculation of the singular part depends on the space dimension. One could modify the short wave part expression of Green's functions for the linear half space problem to prove the results for the general case.

    Notations. Let C and O(1) be denoted as generic positive constants. For multi-indices α=(α1,,αn), αx=α1x1αnxn, |α|=ni=1αi. Let Lp denotes the usual Lp space on xRn+. For nonnegative integer l, we denote by Wl,p(1p<) the usual Lp Soblev space of order l: Wl,p={uLp:αxuLp(|α|l)}(l1),W0,p=Lp. The norm is denoted by Wl,p= uWl,p=|α|lαxuLp. When p=2, we define Wl,2=Hl for all l0. We denote Dδ:={ξCn||Im(ξi)|δ,i=1,2,,n}. Introduce the Fourier transform and Laplace transform of f(x,t) as follows:

    f(ξ,t):=F[f](ξ,t)=Rneiξxf(x,t)dx,f(x,s):=L[f](x,s)=0estf(x,t)dt.

    The rest of paper is arranged as follows: in Section 2, we study the fundamental solutions for the linear Cauchy problem and give a pointwise description of the fundamental solutions in (x,t) variables. We also describe the fundamental solutions in other transformed variables. In Section 3, the Green's functions for the half space problem are constructed in the transformed tangential-spatial and time domain. By comparing the symbols in the transformed space, we get the relationship between the fundamental solutions and the Green's functions. Finally in Section 4, we give the long time behavior of the solution for the nonlinear problem. Some useful lemmas are given in Appendix.

    The fundamental solutions for the linear damped wave equations are defined by

    {2tG1c2ΔG1+ν1tG1ν2tΔG1=0G1(x,0)=δ(x),G1t(x,0)=0, (7)
    {2tG2c2ΔG2+ν1tG2ν2tΔG2=0G2(x,0)=0,G2t(x,0)=δ(x). (8)

    Applying the Fourier transform to (7) and (8) in the space variable x, one can compute the fundamental solutions Gi(ξ,t) (i=1,2) in the Fourier space,

    G1(ξ,t)=σ+eσtσeσ+tσ+σ,  G2(ξ,t)=eσ+teσtσ+σ,σ±=ν1+ν2|ξ|22±12ν21+(2ν1ν24c2)|ξ|2+ν22|ξ|4.

    In [16], authors have studied the pointwise estimates of the fundamental solutions by long wave-short wave decomposition in the Fourier space. Here we will use the local analysis and inverse Fourier transform to get the pointwise structures of the fundamental solutions in the physical variables (x,t). Outside the finite Mach number region |x|3(t+1), one can use the weighted energy estimates to get the exponentially decaying estimates of solution in time and space. Inside the finite Mach number region |x|4(t+1), we will use the long wave short wave decomposition to get the long wave regular parts and short wave singular parts. Here the long wave and short wave are defined as follows:

    f(x,t)=fL(x,t)+fS(x,t),F[fL]=H(1|ξ|ε0)F[f](ξ,t),F[fS]=(1H(1|ξ|ε0))F[f](ξ,t),

    with the parameter ε01, the Heaviside function H(x) is defined by

    H(x)={1,  x>0,0,  x<0.

    Long wave component. When |ξ|ε01, we have the following Taylor expansion for σ± and σ+σ:

    {σ+=c2|ξ|2ν1+o(|ξ|2),σ=ν1+(ν2+c2ν1)|ξ|2+o(|ξ|2),
    σ+σ=ν1+(ν1ν22c2)|ξ|2ν1+o(|ξ|2).

    Then

    σ+eσt=(c2|ξ|2ν1+o(|ξ|2))e(ν1+(ν2+c2ν1)|ξ|2+o(|ξ|2))t=c2ν1|ξ|2eν1t+o(|ξ|2)eCt,σeσ+t=(ν1+(ν2+c2ν1)|ξ|2+o(|ξ|2))e(c2|ξ|2ν1+o(|ξ|2))t=ν1ec2ν1|ξ|2t+O(|ξ|2)eC|ξ|2t,1σ+σ=1ν1+O(|ξ|2).

    So we can approximate the fundamental solutions as follows

    σ+eσtσeσ+tσ+σ=c2|ξ|2ν21eν1t+ec2ν1|ξ|2t+o(|ξ|2)eCt+O(|ξ|2)eC|ξ|2t,eσ+teσtσ+σ=1ν1ec2ν1|ξ|2t1ν1eν1t+O(|ξ|2)eCt+o(|ξ|2)eC|ξ|2t.

    Using Lemma 5.1 in Appendix, for |α|0 we have

    |DαxGL1(x,t)|O(1)(e|x|2C(t+1)(1+t)n+|α|2+e|x|+tC),|DαxGL2(x,t)|O(1)(e|x|2C(t+1)(1+t)n+|α|2+e|x|+tC).

    Short wave component. We adopt the local analysis method to give a description about all types of singular functions for the short wave component of the fundamental solutions. When |ξ|N for N sufficiently large, we have the following Taylor expansion for σ±:

    {σ+=c2ν2+c2(ν1ν2c2)ν321|ξ|2+O(|ξ|4),σ=σ+(ν1+ν2|ξ|2).

    This non-decaying property results in the singularities of the fundamental solution Gi in spatial variable. To investigate the singularities, we approximate the spectra σ± by σ±:

    {σ+=c2ν2+c2(ν1ν2c2)ν32(11+|ξ|2+1(1+|ξ|2)2)+c2(ν1ν2c2)ν32O((1+|ξ|2)3),σ=σ+(ν1+ν2|ξ|2),
    infξDε0|σ(ξ)σ+(ξ)|>0,supξDε0Re(σ±(ξ))J0,  supξDε0|ξ|8|σ±(ξ)σ±(ξ)|<  as  |ξ|.

    Therefore, the approximated analytic spectra σ± given above satisfy

    |σ+eσtσeσ+tσ+σσ+eσtσeσ+tσ+σ, eσ+teσtσ+σeσ+teσtσ+σ|O(1)(1+|ξ|2)4.

    By Lemma 5.4 in the Appendix, we have

    F1[σ+eσtσeσ+tσ+σσ+eσtσeσ+tσ+σ](,t)L(Rn)=O(1),F1[eσ+teσtσ+σeσ+teσtσ+σ](,t)L(Rn)=O(1),

    which asserts that all singularities are contained in σ+eσtσeσ+tσ+σ, eσ+teσtσ+σ. Moreover, one can also prove that the errors of this approximation decay exponentially fast in the space-time domain, just like the proof in [7].

    Now we seek out all the singularities. For the short wave part of G1(ξ,t), one breaks

    σ+eσtσeσ+tσ+σ=eσ+tσ+eσ+tσ+σ+σ+eσtσ+σ.

    The first term is

    eσ+t=ec2tν2ec2(ν1ν2c2)tν3211+|ξ|2+c2(ν1ν2c2)tν321(1+|ξ|2)2+c2(ν1ν2c2)tν32O(1(1+|ξ|2)3)=ec2tν2(1+c2(ν1ν2c2)tν3211+|ξ|2+c2(ν1ν2c2)tν321(1+|ξ|2)2)+ec2tν2c2(ν1ν2c2)tν32O(1(1+|ξ|2)3)=ec2tν2+c2(ν1ν2c2)ν32tec2tν21+|ξ|2+c2(ν1ν2c2)ν32tec2tν2(1+|ξ|2)2+tec2tν2c2(ν1ν2c2)ν32O(1(1+|ξ|2)3).

    It can be estimated as follows

    |F1[eσ+t]ec2t/ν2δ(x)tc2(ν1ν2c2)ν32ec2t/ν2Yn(x)|Ce|x|+tC.

    The second term contains no singularities and we have

    σ+eσ+tσ+σ=c2ν22ec2t/ν21+|ξ|2+ec2tν2O(1(1+|ξ|2)2),

    so

    |F1[σ+eσ+tσ+σ]+c2v22ec2t/v2Yn(x)|Ce|x|+tC.

    For the third term, the function F1[σ+eσtσ+σ] does not contain singularities in x variable due to its asymptotic when |ξ| for t>0 :

    |σ+eσtσ+σ|K0e|ξ|2t/C1J0t1+|ξ|2,

    K0>0 and J0 is a constant. One has that there exist generic constant C>0 such that for δ=(ε0,ε0),

    Im(ξk)=δ1kn|σ+eσtσ+σ|dξCRne|ξ|2t/CJ0t(1+|ξ|)2dξ=CΓ(n)0er2t/CJ0t(1+r)2rn1drCet/CLn(t), (9)

    where

    Ln(t){1,n=1,log(t),n=2,tn22,n3.

    We denote

    j1(x,t):=F1[σ+eσtσ+σ],

    following the way of proof for Lemma 5.4, we get

    |j1(x,t)|Ce(|x|+t)/CLn(t)

    from (9). So the following estimate for GS1(x,t) hold,

    |GS1(x,t)j1(x,t)ec2t/ν2δn(x)(tc2ν32(ν1ν2c2)+c2ν22)ec2t/ν2Yn(x)|e|x|+tC.

    For the short wave part of G2(ξ,t), one breaks

    eσ+teσtσ+σ=eσ+tσ+σeσtσ+σ.

    The first term is

    eσ+tσ+σ=ν12ec2t/ν21+|ξ|2+ec2tν2O(1(1+|ξ|2)2),

    and we have

    |F1[eσ+tσ+σ]ν12ec2t/ν2Yn(x)|Ce|x|+tC.

    The second term contains no singularities. If denoting

    j2(x,t)F1(eσtσ+σ),

    then there exists C>0 such that

    |j2(x,t)|Ce(|x|+t)/CLn(t),

    and we have the following estimate for GS2(x,t),

    |GS2(x,t)j2(x,t)ν12ec2t/ν2Yn(x)|Ce|x|+tC.

    Hence the short wave components have the following estimates in the finite Mach number region |x|4(t+1):

    |GS1(x,t)j1(x,t)ec2tν2δn(x)(tc2(ν1ν2c2)ν32+c2ν22)ec2tν2Yn(x)|Ce|x|+tC.|GS2(x,t)j2(x,t)ν12ec2tν2Yn(x)|Ce|x|+tC.

    Outside the finite Mach number region |x|3(t+1).

    We choose the weighted function w to be w=e(|x|at)/M, M and a will be determined later. It satisfies

    wt=aMw,w=xM|x|w,Δw=wM2.

    Consider the linear damped wave equation outside the finite Mach number region:

    {2tuic2Δui+ν1tuiν2tΔui=0,|x|3(t+1),ui|t=0=0,uit|t=0=0,ui||x|=3(t+1)=Gi||x|=3(t+1). (10)

    Denote the outside finite Mach number region {xRn,|x|3(t+1)} by Dt and its boundary by Dt. Multiplying each side of the equation in (10)1 by wut and integrating with respective to x on Dt, choosing 2<a<3, M sufficiently large such that ν1>c2M and ν12+a2Mν22M2>0, we have

    c2DtwtuiuidSx+ν2DtwtuituidSx=12ddtDtw((tui)2+c2|ui|2)dx+Dt(ν1w12wt12ν2Δw)(tui)2dx+c2Dttuiwuidx+ac22MDtw|ui|2dx+ν2Dtw|tui|2dx=12ddtDtw((tui)2+c2|ui|2)dx+Dt(ν1+a2Mν22M2)w(tui)2dx+c2DtwtuixM|x|uidx+ac22MDtw|ui|2dx+ν2Dtw|tui|2dx12ddtDtw((tui)2+c2|ui|2)dx+Dtw(ac24M|ui|2+(ν12+a2Mν22M2)(tui)2+ν2|tui|2)dx.

    On the boundary Dt, by the structures of the fundamental solutions in the finite Mach number region |x|4(t+1), we have

    |tui|,|ui|,|tui|CeCt, xDt.

    So

    ddtDtw((tui)2+c2|ui|2)dx+2δ0Dtw((tui)2+c2|ui|2)dxCeCt, (11)

    δ0=min{a4M,ν12+a2Mν22M2}.

    One can also get similar estimates for any higher order derivatives l:

    l|α|=1(ddtRnw((tαxui)2+c2|αxui|2)dx)        +δ|α|Rnw((tαxui)2+c2|αxui|2)dx)CeCt. (12)

    Integrating (11) and (12) over t, using Sobolev's inequality, we have

    sup(x,t)Dt((tαxui)2+c2|αxui|2)Ce(|x|at)/CCe(|x|+t)/C,  for |α|<ln2,

    since |x|3(t+1). This means that the fundamental solutions Gi(i=1,2) satisfy the following estimate outside the finite Mach number region Dt:

    |DαxGi(x,t)|Ce(|x|+t)/C,  for |α|<ln2.

    To summarize, we have the following pointwise estimates for the fundamental solutions:

    Lemma 2.1. The fundamental solutions have the following estimates for all xRn, |α|0:

    |Dαx(G1(x,t)j1(x,t)ec2t/ν2δn(x)(tc2ν32(ν1ν2c2)+c2ν22)ec2t/ν2Yn(x))|O(1)(e|x|2C(t+1)(t+1)n+|α|2+e(|x|+t)/C),|Dαx(G2(x,t)j2(x,t)ν12ec2t/ν2Yn(x))|O(1)(e|x|2C(t+1)(t+1)n+|α|2+e(|x|+t)/C).

    Here

    |j1(x,t),j2(x,t)|O(1)Ln(t)e(|x|+t)/C,L2(t)=log(t),  Ln(t)=tn22  for  n3,Y2(x)=O(1)12πBesselK0(|x|),  Yn(x)=O(1)e|x||x|n2  for  n3.

    BesselK0(|x|) is the modified Bessel function of the second kind with degree 0.

    Applying Laplace transform in t and Fourier transform in x to the equations in (7) and (8), denoting the transformed variables by s and ξ respectively, we get the transformed fundamental solutions in (ξ,s) variables:

    G1(ξ,s)=s+ν1+ν2|ξ|2s2+ν1s+(c2+ν2s)|ξ|2,  G2(ξ,s)=1s2+ν1s+(c2+ν2s)|ξ|2.

    Now we give a lemma:

    Lemma 2.2.

    12πReiξ1x1s2+ν1s+ν2s|ξ|2+c2|ξ|2dξ1=1ν2s+c2eλ|x1|2λ,

    where λ=λ(ξ,s)=(ν2s+c2)|ξ|2+s2+ν1sν2s+c2.

    Proof. We prove it by using the contour integral and the residue theorem. Note that

    12πReiξ1x1s2+ν1s+ν2s|ξ|2+c2|ξ|2dξ1=12π1ν2s+c2Reiξ1x1ξ21+|ξ|2+s2+ν1sν2s+c2dξ1=12π1ν2s+c2Reiξ1x1(ξ1λi)(ξ1+λi)dξ1.

    Define a closed path γ containing Γ:=[R,R] while R is a positive constant, Ω=γΓ={z|z=Reiθ}.

    If x1>0, set 0θπ, R is chosen to be sufficiently large such that λi is contained in the domain surrounded by γ. Consider the contour integral over path γ. The contribution of the integration over Ω approaches to 0 when R, therefore by the residue theorem, we have for x1>0,

    12π1ν2s+c2Reiξ1x1(ξ1λi)(ξ1+λi)dξ1=12π1ν2s+c22πiRes(eiξ1x1(ξ1λi)(ξ1+λi)|ξ1=λi)=eλx12(ν2s+c2)λ.

    The computation for the case x1<0 is similar. Set πθ2π,

    12π1ν2s+c2Reiξ1x1(ξ1λi)(ξ1+λi)dξ1=12π1ν2s+c22πiRes(eiξ1x1(ξ1λi)(ξ1+λi)|ξ1=λi)=eλx12(ν2s+c2)λ.

    Hence we prove this lemma.

    With the help of Lemma 2.2, we get the expression of fundamental solutions G1 and G2 in (x1,ξ,s) variables:

    G1(x1,ξ,s)=1ν2s+c2(ν2δ(x1)+c2(s+ν1)ν2s+c2eλ|x1|2λ),G2(x1,ξ,s)=eλ|x1|2λ(ν2s+c2).

    In particular, when ˉx1>0, we have

    G1(ˉx1,ξ,s)=c2(s+ν1)(ν2s+c2)2eλˉx12λ,  G2(ˉx1,ξ,s)=eλˉx12λ(ν2s+c2).

    In this section, we will give the pointwise estimates of the Green's functions for the initial boundary value problem. Firstly, we compute the transformed Green's functions in the partial-Fourier and Laplace transformed space. Then by comparing the symbols of the fundamental solutions and the Green's functions in this transformed space, we get the simplified expressions of Green's functions for the initial-boundary value problem. With the help of the pointwise estimates of the fundamental solutions and boundary operator, we finally get the sharp estimates of Green functions for the half space linear problem.

    Before computing, we make the initial value zero by considering the error function Ri(x1,x,t;y1)=Gi(x1,x,t;y1)Gi(x1y1,x,t), which satisfies the following system:

    {2tRic2ΔRi+ν1tRiν2tΔRi=0,xRn+,t>0,Ri|t=0=0,Rit|t=0=0,(a1x1+a2)Ri(0,x,t;y1)=(a1x1+a2)Gi(x1y1,x,t)|x1=0.

    Taking Fourier transform only with respect to the tangential spatial variable x, Laplace transform with respect to time variable t, the following ODE system can be obtained:

    {(s2+ν1s)Ri(c2+ν2s)Rix1x1+(c2+ν2s)|ξ|2Ri=0,(a1x1+a2)Ri(0,ξ,s;y1)=(a1y1a2)Gi(y1,ξ,s)=(a1λ+a2)Gi(y1,ξ,s).

    Solving it and dropping out the divergent mode as x1+, using the boundary relationship, we have

    Ri(x1,ξ,s;y1)=a1λ+a2a2a1λeλx1Gi(y1,ξ,s)=a1λ+a2a2a1λGi(x1+y1,ξ,s),

    where λ is defined in Lemma 2.2.

    Therefore the transformed Green's functions Gi(x1,ξ,s;y1) (i=1,2) are

    Gi(x1,ξ,s;y1)=Gi(x1y1,ξ,s)a1λ+a2a2a1λGi(x1+y1,ξ,s)=Gi(x1y1,ξ,s)+Gi(x1+y1,ξ,s)2a2a2a1λGi(x1+y1,ξ,s),

    which reveal the connection between fundamental solutions and the Green's functions.

    Hence,

    Gi(x1,x,t;y1)=Gi(x1y1,x,t)+Gi(x1+y1,x,t)F1ξxL1st[2a2a2a1λ]x,tGi(x1+y1,x,t).

    Now we estimate the boundary operator F1ξxL1st[2a2a2a1λ]. The function 1a2a1λ has the poles in the right half time space if a1a2>0, which suggests that the boundary term will grow exponentially in time. In the following we only consider the case a1a2<0.

    Instead of inverting the boundary symbol, we follow the differential equation method. Notice that

    F1ξxL1st[2a2a2a1λGi(x1+y1,ξ,s)]=2a2a1x1+a2Gi(x1+y1,x,t),

    setting

    g(x1,x,t)2a2a1x1+a2Gi(x1,x,t),

    then the function g(x1,x,t) satisfies

    (a2+a1x1)g=2a2Gi(x1,x,t).

    Solving this ODE gives

    g(x1,x,t)=2γx1eγ(zx1)Gi(z,x,t)dz=2γ0eγzGi(x1+z,x,t)dz. (13)

    Summarizing previous results we obtain

    Lemma 3.1. The Green's functions Gi(x1,x,t;y1) (i=1,2) of the linear initial-boundary value problem (5) and (6) can be represented as follows

    Gi(x1,x,t;y1)=GLi(x1,x,t;y1)+GSi(x1,x,t;y1).

    Meanwhile, the following estimates hold:

    |DαxGLi(x1,x,t;y1)|O(1)(e(x1y1)2+(xy)2C(t+1)(t+1)n+|α|2+e(x1+y1)2+(xy)2C(t+1)(t+1)n+|α|2),|α|0;
    |GS1(x1,x,t;y1)|O(1)(j1(x1y1,x,t)+j1(x1+y1,x,t)+ec2tν2(δn(x1y1,x)+δn(x1+y1,x))+ec2tν2(tc2ν32(ν1ν2c2)+c2ν22)(Yn(x1y1,x)+Yn(x1+y1,x)))

    and

    |GS2(x1,x,t;y1)|O(1)(j1(x1y1,x,t)+j2(x1+y1,x,t)+ν12ec2tν2(Yn(x1y1,x)+Yn(x1+y1,x))).

    Proof. Note that

    Gi(x1,x,t;y1)=Gi(x1y1,x,t)+Gi(x1+y1,x,t)g(x1+y1,x,t),

    based on the long-wave short-wave decomposition of the fundamental solutions

    Gi(x,t)=GLi(x,t)+GSi(x,t),

    we can write

    GLi(x1,x,t;y1)=O(1)(GLi(x1y1,x,t)+GLi(x1+y1,x,t)),GSi(x1,x,t;y1)=O(1)(GSi(x1y1,x,t)+GSi(x1+y1,x,t)),

    and get the estimates directly from Lemma 2.1 and (13).

    The study of boundary operator in the last section suggests that we can only consider the case a1a2<0 for the nonlinear stability. In [15,16], they proved a threshold k=1+2n between global and non-global existence of small data solutions. Here under the assumption of k>1+2n, the global in time existence of solution for the initial-boundary value problem can be proved using the fixed point theorem of Banach, which is similar to the proof given by [16], we omit the details.

    Now we give the pointwise long time behavior of the solution for the nonlinear problem and prove the Theorem 1.1. The Green's functions Gi(x1,x,t;y1)(i=1,2) give the representation of the solution u(x,t):

    αxu(x,t)=αxRn+(G1(x1,xy,t;y1)u0(y)+G2(x1,xy,t;y1)u1(y))dy+αxt0Rn+G2(x1,xy,tτ;y1)f(u)(y,τ)dydταxI(x,t)+αxN(x,t). (14)

    The initial part αxI(x,t) contains two parts:

    \begin{align*} \begin{aligned} &\partial_{{\bf{x}}}^\alpha\mathcal{I}({\bf{x}},t) = \partial_{{\bf{x}}}^\alpha\mathcal{I}^L({\bf{x}},t)+\partial_{{\bf{x}}}^\alpha\mathcal{I}^S({\bf{x}},t), \end{aligned} \end{align*}

    where

    \begin{align*} \begin{aligned} &\partial_{{\bf{x}}}^\alpha\mathcal{I}^L({\bf{x}},t) = \partial_{{\bf{x}}}^\alpha\int_{\mathbb{R}^n_+}\left(\mathbb{G}_1^L(x_1,{\bf{x'-y'}},t;y_1)u_0({\bf{y}})+\mathbb{G}_2^L(x_1,{\bf{x'-y'}},t;y_1)u_1({\bf{y}})\right)d{\bf{y}}\\ &\partial_{{\bf{x}}}^\alpha\mathcal{I}^S({\bf{x}},t) = \partial_{{\bf{x}}}^\alpha\int_{\mathbb{R}^n_+}\left(\mathbb{G}_1^S(x_1,{\bf{x'-y'}},t;y_1)u_0({\bf{y}})+\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t;y_1)u_1({\bf{y}})\right)d{\bf{y}}. \end{aligned} \end{align*}

    By lemma 5.2, we have the following estimates in the finite Mach number region |{\bf{x}}|\le 4(t+1) ,

    \begin{align} \label{{4.3a}} \begin{aligned} &|\mathcal{I}^L({\bf{x}},t)|\le O(1)\varepsilon\int_{\mathbb{R}^n_+}\frac{e^{-\frac{(\bf{x-y})^2}{C(t+1)}}}{(t+1)^{\frac{n}{2}}}\left(1+|{\bf{y}}|^2\right)^{-r}d{\bf{y}}\\ \le& O(1)\varepsilon\left(\frac{e^{-\frac{{\bf{x}}^2}{C(t+1)}}}{(t+1)^{\frac{n}{2}}}+\left(1+t+\left|{\bf{x}}\right|^2\right)^{-\frac{n}{2}}\right), \end{aligned} \end{align} (15)
    \begin{align} \label{{4.3b}} \begin{aligned} &|\mathcal{I}^S({\bf{x}},t)|\\ \le& O(1)\varepsilon e^{-\frac{(|{\bf{x}}|+t)}{C}}\Bigg|\int_{\mathbb{R}^n}\Big(L_n(t) +\delta_n(\bf{x-y})\\ & \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ +\left[\frac{tc^2}{\nu_2^{3}}(\nu_1\nu_2-c^2)+\frac{c^2}{\nu_2^{2}}\right]Y_n(\bf{x-y})\Big)\left(1+|{\bf{y}}|^2\right)^{-r}d{\bf{y}} \Bigg|\\ &+O(1)\varepsilon e^{-\frac{(|{\bf{x}}|+t)}{C}}\left|\int_{\mathbb{R}^n}\left(L_n(t)+\nu_2^{-1}Y_n(\bf{x-y})\right)\left(1+|{\bf{y}}|^2\right)^{-r}d{\bf{y}}\right|\\ \le &O(1)\varepsilon\left(\frac{e^{-\frac{{\bf{x}}^2}{C(t+1)}}}{(t+1)^{\frac{n}{2}}}+\left(1+t+\left|{\bf{x}}\right|^2\right)^{-\frac{n}{2}}\right). \end{aligned} \end{align} (16)

    Hence we combine (15) and (16) to get the estimate of the first part in (14) when |\alpha| = 0

    \begin{align} \begin{aligned} \label{{4.3}} \left|\mathcal{I}({\bf{x}},t)\right| \le O(1)\varepsilon\left(\frac{e^{-\frac{{\bf{x}}^2}{C(t+1)}}}{(t+1)^{\frac{n}{2}}}+\left(1+t+\left|{\bf{x}}\right|^2\right)^{-\frac{n}{2}}\right). \end{aligned} \end{align} (17)

    Similarly, when |\alpha| = 1 , we have

    \begin{align*} \begin{aligned} &\left|\partial_{{\bf{x}}}^\alpha\mathcal{I}({\bf{x}},t)\right| = \left|\partial_{{\bf{x}}}^\alpha\mathcal{I}^L({\bf{x}},t)+\partial_{{\bf{x}}}^\alpha\mathcal{I}^S({\bf{x}},t)\right|\\ \le&O(1)\varepsilon\int_{ \mathbb{R}^n_+}\left(\frac{e^{-\frac{(x_1-y_1)^2+({\bf{x'-y'}})^2}{C(t+1)}}}{(t+1)^{\frac{n}{2}+\frac{1}{2}}}+\frac{e^{-\frac{(x_1+y_1)^2+({\bf{x'-y'}})^2}{C(t+1)}}}{(t+1)^{\frac{n}{2}+\frac{1}{2}}}\right)\left(1+|{\bf{y}}|^2\right)^{-r}d{\bf{y}}\\ &+1_{\{\partial^\alpha_{{\bf{x}}} = \partial_{x_1}\}}O(1)\varepsilon e^{-\frac{(|{\bf{x}}|+t)}{C}}\Bigg|\int_{\mathbb{R}^{n-1}}L_n(t)+\delta_n(x_1-y_1,{\bf{x'-y'}},t)\\ & \ \ \ \ \ \ +\delta_n(x_1+y_1,{\bf{x'-y'}},t)+\left(tc^2\nu_2^{-3}(\nu_1\nu_2-c^2)+c^2\nu_2^{-2}\right)\\ &\ \ \ \ \ \left(Y_n(x_1-y_1,{\bf{x'-y'}})+Y_n(x_1+y_1,{\bf{x'-y'}})\right)\left(1+|{\bf{y}}|^2\right)^{-r}d\bf{y'}|_{y_1 = 0}\Bigg|\\ &+O(1)\varepsilon e^{-\frac{(|{\bf{x}}|+t)}{C}}\Bigg|\int_{\mathbb{R}_+^n}L_n(t)+\delta_n(x_1-y_1,{\bf{x'-y'}},t)+\delta_n(x_1+y_1,{\bf{x'-y'}},t)\\ & \ \ \ \ \ +\left(tc^2\nu_2^{-3}(\nu_1\nu_2-c^2)+c^2\nu_2^{-2}\right)\\ & \ \ \ \ \ \ \left(Y_n(x_1-y_1,{\bf{x'-y'}})+Y_n(x_1+y_1,{\bf{x'-y'}})\right)\left(1+|{\bf{y}}|^2\right)^{-r}d{\bf{y}}\Bigg|\\ &+1_{\{\partial^\alpha_{{\bf{x}}} = \partial_{x_1}\}}O(1)\varepsilon e^{-\frac{(|{\bf{x}}|+t)}{C}}\Bigg|\int_{\mathbb{R}^{n-1}}(L_n(t)+\nu_1^{-1}Y_n(x_1-y_1,{\bf{x'-y'}})\\ & \ \ \ \ +\nu_1^{-1}Y_n(x_1+y_1,{\bf{x'-y'}}))\left(1+|{\bf{y}}|^2\right)^{-r}d\bf{y'}|_{y_1 = 0}\Bigg|\\ &+O(1)\varepsilon e^{-\frac{(|{\bf{x}}|+t)}{C}}\Bigg|\int_{\mathbb{R}^{n-1}}(L_n(t)+\nu_1^{-1}Y_n(x_1-y_1,{\bf{x'-y'}})\\ & \ \ \ \ +\nu_1^{-1}Y_n(x_1+y_1,{\bf{x'-y'}}))\left(1+|{\bf{y}}|^2\right)^{-r}d{\bf{y}}\Bigg|\\ \le&O(1)\varepsilon(1+t)^{-\frac{|\alpha|}{2}}\left(\frac{e^{-\frac{{\bf{x}}^2}{2C(t+1)}}}{(t+1)^{\frac{n}{2}}}+\left(1+t+\left|{\bf{x}}\right|^2\right)^{-r}\right)+O(1)\varepsilon e^{-(|{\bf{x}}|+t)/C}. \end{aligned} \end{align*}

    where

    \begin{align*} \begin{aligned} 1_{\{\partial^\alpha_{{\bf{x}}} = \partial_{x_1}\}} = \left\{\begin{array}{lll} 1,\ if\ \partial^\alpha_{{\bf{x}}} = \partial_{x_1},\\ 0,\ otherwise.\end{array}\right. \end{aligned} \end{align*}

    Here we use the integration by parts to estimate the short wave component part. Outside the finite Mach number region, we have

    \begin{align} \label{{4.5}} \begin{aligned} &\left|\partial_{{\bf{x}}}^\alpha\mathcal{I}({\bf{x}},t)\right|\le O(1)\varepsilon e^{-\nu_1t}\int_{ \mathbb{R}_+^n}e^{-|\bf{x-y}|}(1+{\bf{y}}^2)^{-r}d{\bf{y}}\\ \le& O(1)\varepsilon e^{-\nu_1t}(1+|{\bf{x}}|^2)^{-r},\quad|\alpha|\le1. \end{aligned} \end{align} (18)

    Based on the estimates of (17)-(18), the ansatz is posed for the solution as follows:

    \begin{align*} \begin{aligned} \left|\partial_{{\bf{x}}}^\alpha u({\bf{x}},t)\right| \le O(1)\varepsilon (1+t)^{-\frac{|\alpha|}{2}}(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}, \quad |\alpha|\le1. \end{aligned} \end{align*}

    Straightforward computations show that

    \begin{eqnarray*} \left|f(u)({\bf{x}},t)\right|\le O(1)\varepsilon^k(1+t+|{\bf{x}}|^2)^{-\frac{nk}{2}}. \end{eqnarray*}

    Now we justify the ansatz for the nonlinear term. For \mathcal N({\bf{x}},t) , we have

    \begin{align*} \begin{aligned} \left|\mathcal{N}({\bf{x}},t)\right| = &\left|\int_{0}^{t}\int_{ \mathbb{R}^n_+}\mathbb{G}_2(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\ \le&\left|\int_{0}^{t}\int_{\mathbb{R}^n_+}\mathbb{G}_2^L(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\&+\left|\int_{0}^{t}\int_{\mathbb{R}^n_+}\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\ = &\mathcal{N}_1+\mathcal{N}_2. \end{aligned} \end{align*}

    Using Lemma 5.3, one gets

    \begin{align*} \begin{aligned} \mathcal{N}_1&\le O(1)\varepsilon^k\Bigg|\int^t_0\int^\infty_0\int_{\mathbb{R}^{n-1}}\left(\frac{e^{-\frac{(x_1-y_1)^2+({\bf{x'-y'}})^2}{C(t-\tau+1)}}}{(t-\tau+1)^{\frac{n}{2}}}+\frac{e^{-\frac{(x_1+y_1)^2+({\bf{x'-y'}})^2}{C(t-\tau+1)}}}{(t-\tau+1)^{\frac{n}{2}}}\right)\\ &\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1+\tau+|{\bf{y}}|^2)^{-\frac{nk}{2}}d{\bf{y}}'dy_1d\tau\Bigg|\\ &\le O(1)\varepsilon^k\left|\int^t_0\int_{ \mathbb{R}^n}\frac{e^{-\frac{(x_1-y_1)^2+({\bf{x'-y'}})^2}{C(t-\tau+1)}}}{(t-\tau+1)^{\frac{n}{2}}}(1+\tau+|{\bf{y}}|^2)^{-\frac{nk}{2}}d{\bf{y}}d\tau\right|\\ &\le O(1)\varepsilon^k(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}, \end{aligned} \end{align*}
    \begin{align*} \begin{aligned} \mathcal{N}_2&\le O(1)\varepsilon^k\Bigg|\int^t_0\int_{ \mathbb{R}^n_+}e^{-\frac{c^2(t-\tau)}{\nu_2}}\left(L_n(t-\tau)+\nu_2^{-1}Y_n(x_1,{\bf{x'-y'}};y_1)\right)\\ &\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1+\tau+|{\bf{y}}|^2)^{-\frac{nk}{2}}d{\bf{y}}d\tau\Bigg|\\ &\le O(1)\varepsilon^k(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}. \end{aligned} \end{align*}

    Now we compute the estimate of \partial_{{\bf{x}}}^\alpha\mathcal{N} when |\alpha| = 1 :

    \begin{align*} \begin{aligned} \left|\partial_{{\bf{x}}}^\alpha\mathcal{N}({\bf{x}},t)\right| = &\left|\partial_{{\bf{x}}}^\alpha\int_{0}^{t}\int_{ \mathbb{R}^n_+}\mathbb{G}_2(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\ \le&\left|\int_{0}^{t}\int_{\mathbb{R}^n_+}\partial_{{\bf{x}}}^\alpha\mathbb{G}_2^L(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\ &+\left|\int_{0}^{t}\int_{\mathbb{R}^n_+}\partial_{{\bf{x}}}^\alpha\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\ = &\partial_{{\bf{x}}}^\alpha\mathcal{N}_1+\partial_{{\bf{x}}}^\alpha\mathcal{N}_2. \end{aligned} \end{align*}

    Similarly we have

    \begin{align*} \begin{aligned} \partial_{{\bf{x}}}^\alpha\mathcal{N}_1 = &\Bigg|O(1)\varepsilon^k\int^t_0\int^\infty_0\int_{\mathbb{R}^{n-1}}\left(\frac{e^{-\frac{(x_1-y_1)^2+({\bf{x'-y'}})^2}{C(t-\tau+1)}}}{(t-\tau+1)^{\frac{n}{2}+\frac{|\alpha|}{2}}}+\frac{e^{-\frac{(x_1+y_1)^2+({\bf{x'-y'}})^2}{C(t-\tau+1)}}}{(t-\tau+1)^{\frac{n}{2}+\frac{|\alpha|}{2}}}\right)\\ &\ \ \ \ \ (1+\tau+|{\bf{y}}|^2)^{-\frac{nk}{2}}d{\bf{y}}'dy_1d\tau\Bigg|\\ \le&\left|O(1)\varepsilon^k\int^t_0\int_{ \mathbb{R}^n}\frac{e^{-\frac{(x_1-y_1)^2+({\bf{x'-y'}})^2}{C(t-\tau+1)}}}{(t-\tau+1)^{\frac{n}{2}+\frac{|\alpha|}{2}}}(1+\tau+|{\bf{y}}|^2)^{-\frac{nk}{2}}d{\bf{y}}d\tau\right|\\ \le&O(1)\varepsilon^k(1+t)^{-\frac{|\alpha|}{2}}(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}, \end{aligned} \end{align*}
    \begin{align} \label{{10.0}} \begin{aligned} \partial_{{\bf{x}}}^\alpha\mathcal{N}_2 = &\left|\int_{0}^{t}\int_{\mathbb{R}^n_+}\partial_{{\bf{x}}}^\alpha\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\ = &1_{\{\partial_{{\bf{x}}}^\alpha = \partial_{x_1}\}}\left|\int_{0}^{t}\int_{\mathbb{R}^{n-1}}\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1) f(u)({\bf{y}},\tau)d{\bf{y}}'|_{y_1 = 0}d\tau\right|\\ &+\left|\int_{0}^{t}\int_{\mathbb{R}^n_+}\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1)\partial_{{\bf{y}}}^\alpha f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|. \end{aligned} \end{align} (19)

    The boundary term in (19) has the following estimates:

    \begin{align*} \begin{aligned} &\left|\int_{0}^{t}\int_{\mathbb{R}^{n-1}}\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}'|_{y_1 = 0}d\tau\right|\\ \le& \left|\left(\int_{0}^{t/2}+\int_{t/2}^t\right)\int_{\mathbb{R}^{n-1}}\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1)f(u)({\bf{y}},\tau)d{\bf{y}}'|_{y_1 = 0}d\tau\right|\\ \le&O(1)\varepsilon^k(1+t)^{-\frac{|\alpha|}{2}}(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}. \end{aligned} \end{align*}

    The second term in (19) satisfies

    \begin{align*} \begin{aligned} &\left|\int_{0}^{t}\int_{\mathbb{R}^n_+}\mathbb{G}_2^S(x_1,{\bf{x'-y'}},t-\tau;y_1)\partial_{{\bf{y}}}^\alpha f(u)({\bf{y}},\tau)d{\bf{y}}d\tau\right|\\ \le&\Bigg|O(1)\varepsilon^k\int^t_0\int_{ \mathbb{R}^n_+}e^{-\frac{c^2(t-\tau)}{\nu_2}}\left(L_n(t-\tau)+\nu_2^{-1}Y_n(x_1,{\bf{x'-y'}};y_1)\right)\\ \le& (1+\tau)^{-\frac{|\alpha|}{2}}(1+\tau+|{\bf{y}}|^2)^{-\frac{nk}{2}}d{\bf{y}}d\tau\Bigg|\\ \le& O(1)\varepsilon^k(1+t)^{-\frac{|\alpha|}{2}}(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}. \end{aligned} \end{align*}

    Therefore one has the following estimate for the nonlinear term

    \begin{align*} \begin{aligned} \left|\partial_{{\bf{x}}}^\alpha\mathcal{N}\right|\le O(1)\varepsilon^k(1+t)^{-\frac{|\alpha|}{2}}(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}, \quad|\alpha|\le1. \end{aligned} \end{align*}

    Outside the finite Mach number region,

    \begin{align*} \begin{aligned} \left|\partial_{{\bf{x}}}^\alpha\mathcal{N}\right|\le& O(1)\varepsilon^k\left|\int^t_0\int_{ \mathbb{R}^n_+}e^{-\nu_1(t-\tau)}e^{-|\bf{x-y}|}(1+\tau+|{\bf{y}}^2|)^{-\frac{nk}{2}}d{\bf{y}}d\tau\right|\\ \le&O(1)\varepsilon^k(1+t+|{\bf{x}}|^2)^{-\frac{nk}{2}}, \quad |\alpha|\le1. \end{aligned} \end{align*}

    Thus, we verify the ansatz and finish the proof of pointwise estimates of the solution.

    The L^p (p>1) estimate can be easily proved using the following equalities:

    \begin{align*} \begin{aligned} &\left(\int_{\mathbb{R}^{n}_+}(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}p} d{\bf{x}}\right)^{\frac{1}{p}} = \left(\int_{\mathbb{R}^{n}_+}(1+t)^{-\frac{n}{2}p}\left(1+\frac{|{\bf{x}}|^2}{1+t}\right)^{-\frac{n}{2}p}d{\bf{x}}\right)^{\frac{1}{p}}\\ = &(1+t)^{-\frac{n}{2}}(1+t)^{\frac{n}{2p}} = (1+t)^{-\frac{n}{2}(1-\frac{1}{p})}. \end{aligned} \end{align*}

    Hence we finish the proof of Theorem 1.1.

    Lemma 5.1. [10] In the finite Mach number region |{\bf{x}}|\le 4(t+1) , we have the following estimate for the inverse Fourier transform:

    \begin{align*} \begin{aligned} \left|\frac{1}{(2\pi)^n}\int_{|{\boldsymbol{\xi}}|\le\varepsilon_0}(i{\boldsymbol{\xi}})^\alpha e^{i {\boldsymbol{\xi}}\cdot {\bf{x}}}e^{-\frac{1}{\kappa}|{\boldsymbol{\xi}}|^2t}d{\boldsymbol{\xi}}\right| \le O(1)\frac{e^{-\frac{|{\bf{x}}|^2}{C(t+1)}}}{(1+t)^{\frac{n+|\alpha|}{2}}}+O(1)e^{-\frac{|{\bf{x}}|+t}{C}}, |\alpha|\ge 0. \end{aligned} \end{align*}

    Lemma 5.2. [9] We have the follow estimate for |\alpha|\le 1 and r>\frac{n}{2} ,

    \begin{align*} \begin{aligned} &\int_{\mathbb R^n}\frac{e^{-\frac{({\bf{x}}-{\bf{y}})^2}{C(t+1)}}}{(1+t)^{\frac{n}{2}+\frac{|\alpha|}{2}}}(1+|{\bf{y}}|^2)^{-r}d{\bf{y}}\le O(1)(1+t)^{-\frac{|\alpha|}{2}}\left(\frac{e^{-\frac{{\bf{x}}^2}{2C(t+1)}}}{(t+1)^{\frac{n}{2}}}+(1+t+|{\bf{x}}|^2)^{-r}\right). \end{aligned} \end{align*}

    Lemma 5.3. [9] For {\bf{x}}\in\mathbb R^n , |\alpha|\le 1 , we have

    \begin{align*} \begin{aligned} &\int_{0}^{t}\int_{ \mathbb{R}^n}e^{-\frac{\nu(t-\tau)}{2}}Y_n(\bf{x-y})(1+\tau)^{-\frac{|\alpha|}{2}}(1+\tau+|{\bf{y}}|^2)^\frac{nk}{2}d{\bf{y}}d\tau\\ \le& O(1)(1+t)^{-\frac{|\alpha|}{2}}(1+t+|{\bf{x}}|)^{-nk/2}, \end{aligned} \end{align*}
    \begin{align*} \begin{aligned} \int_{0}^{t}\int_{\mathbb{R}^n}\frac{e^{-\frac{({\bf{x}}-{\bf{y}})^2}{C(t-\tau+1)}}}{(1+t)^{\frac{n}{2}+\frac{|\alpha|}{2}}}(1+\tau+|{\bf{y}}|^2)^{-\frac{nk}{2}}d{\bf{y}}d\tau\le O(1)(1+t)^{-\frac{|\alpha|}{2}}(1+t+|{\bf{x}}|^2)^{-\frac{n}{2}}. \end{aligned} \end{align*}

    Lemma 5.4. [7] Suppose a function f\in L^1(\mathbb{R}^n) and its Fourier transform \mathcal{F}[f]({\boldsymbol{\xi}}) is analytic in \mathcal{D}_{\delta} and satisfies

    \begin{align*} \begin{aligned} |\mathcal{F}[f]({\boldsymbol{\xi}})|\le \frac{E}{(1+|{\boldsymbol{\xi}}|)^{n+1}}, \ \ \mathit{\mbox{for}} \ \ |Im(\xi_i)|\le\delta, \ \ \mathit{\mbox{and}}\ \ i = 1,2,\cdots, n. \end{aligned} \end{align*}

    Then, the function f({\bf{x}}) satisfies

    \begin{eqnarray*} |f({\bf{x}})|\le Ee^{-\delta |{\bf{x}}|/C}, \end{eqnarray*}

    for any positive constant C>1 .

    The authors would like to thank the referees very much for their valuable comments and suggestions which improve the presentation of papersignicantly.



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