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Energy and material recovery potential from municipal solid wastes (MSW) in Nigeria: Challenges and opportunities

  • Received: 28 September 2022 Revised: 19 November 2022 Accepted: 23 November 2022 Published: 20 December 2022
  • Municipal solid waste (MSW) generation is increasing in Nigeria. This poses serious environmental and public health issues because of its poor management. MSW has become a valuable resource which offers opportunities for socio-economic growth, thus the relevance of this review. The study adopted a secondary or desktop research method. The objectives of the study include identifying MSW generation rates in popular Nigerian cities, estimating daily and annual generation rates and the material and economic potential of the generated MSW. The average MSW composition for 22 cities was as follows: organics (56%), plastics (9%), paper (13%), glass and metal (3% each), textiles (2%) and others (14%). The estimated 34 million population living in the cities generates about 20378 tons of MSW each day (7.4 million tons per year). Valorization of the MSW finds applications in different—energy (power, transport, household), agriculture, construction and manufacturing. The energy potential of the generated organic, paper, plastic and textile wastes is about 947981358 kWh/ year, with a revenue potential of 1769409. This represents about 2.6% of the energy generated in Nigeria in the year 2020. The estimated revenue potential of trading the waste materials (plastic, metal, waste paper, textile and glass) for recycling ranges from 3.3 million to.4 billion. Converting wastes to raw materials will reduce the amount going to landfills/dumpsites and reduce the fiscal burden of waste management on municipalities. It will also create employment. Among others, the challenges facing MSW valorization in Nigeria include poor waste management, non-recognition of the informal waste sector, financial incapacity, etc. Thus, it is important to have adequate and effective policy and decision making.

    Citation: Chukwuebuka C. Okafor, Chinelo A. Nzekwe, Nixon N. Nduji, Charles C. Ajaero, Juliet C. Ibekwe. Energy and material recovery potential from municipal solid wastes (MSW) in Nigeria: Challenges and opportunities[J]. Clean Technologies and Recycling, 2022, 2(4): 282-307. doi: 10.3934/ctr.2022015

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  • Municipal solid waste (MSW) generation is increasing in Nigeria. This poses serious environmental and public health issues because of its poor management. MSW has become a valuable resource which offers opportunities for socio-economic growth, thus the relevance of this review. The study adopted a secondary or desktop research method. The objectives of the study include identifying MSW generation rates in popular Nigerian cities, estimating daily and annual generation rates and the material and economic potential of the generated MSW. The average MSW composition for 22 cities was as follows: organics (56%), plastics (9%), paper (13%), glass and metal (3% each), textiles (2%) and others (14%). The estimated 34 million population living in the cities generates about 20378 tons of MSW each day (7.4 million tons per year). Valorization of the MSW finds applications in different—energy (power, transport, household), agriculture, construction and manufacturing. The energy potential of the generated organic, paper, plastic and textile wastes is about 947981358 kWh/ year, with a revenue potential of 1769409. This represents about 2.6% of the energy generated in Nigeria in the year 2020. The estimated revenue potential of trading the waste materials (plastic, metal, waste paper, textile and glass) for recycling ranges from 3.3 million to.4 billion. Converting wastes to raw materials will reduce the amount going to landfills/dumpsites and reduce the fiscal burden of waste management on municipalities. It will also create employment. Among others, the challenges facing MSW valorization in Nigeria include poor waste management, non-recognition of the informal waste sector, financial incapacity, etc. Thus, it is important to have adequate and effective policy and decision making.



    Lattice dynamical systems arise from a variety of applications in electrical engineering, biology, chemical reaction, pattern formation and so on, see, e.g., [4,7,14,19,33]. Many researchers have discussed broadly the deterministic models in [6,12,34,39], etc. Stochastic lattice equations, driven by additive independent white noise, was discussed for the first time in [2], followed by extensions in [8,13,15,16,21,23,27,32,35,36,37,38,40].

    In this paper, we will study the long term behavior of the following second order non-autonomous stochastic lattice system driven by additive white noise: for given τR, t>τ and iZ,

    {¨u+νA˙u+h(˙u)+Au+λu+f(u)=g(t)+a˙ω(t),u(τ)=(uτi)iZ=uτ,˙u(τ)=(u1τi)iZ=u1τ, (1.1)

    where u=(ui)iZ is a sequence in l2, ν and λ are positive constants, ˙u=(˙ui)iZ and ¨u=(¨ui)iZ denote the fist and the second order time derivatives respectively, Au=((Au)i)iZ, A˙u=((A˙u)i)iZ, A is a linear operators defined in (2.2), a=(ai)iZl2, f(u)=(fi(ui))iZ and h(˙u)=(hi(˙ui))iZ satisfy certain conditions, g(t)=(gi(t))iZL2loc(R,l2) is a given time dependent sequence, and ω(t)=W(t,ω) is a two-sided real-valued Wiener process on a probability space.

    The approximation we use in the paper was first proposed in [18,22] where the authors investigated the chaotic behavior of random equations driven by Gδ(θtω). Since then, their work was extended by many scholars. To the best of my knowledge, there are three forms of Wong-Zakai approximations Gδ(θtω) used recenly, Euler approximation of Brownian [3,10,17,20,25,28,29,30], Colored noise [5,11,26,31] and Smoothed approximation of Brownian motion by mollifiers [9]. In this paper, we will focus on Euler approximation of Brownian and compare the long term behavior of system (1.1) with pathwise deterministic system given by

    {¨uδ+νA˙uδ+h(˙uδ)+Auδ+λuδ+f(uδ)=g(t)+aGδ(θtω),uδ(τ)=(uδτi)iZ=uδτ,˙uδ(τ)=(uδ,1τi)iZ=uδ,1τ, (1.2)

    for δR with δ0, τR, t>τ and iZ, where Gδ(θtω) is defined in (3.2). Note that the solution of system (1.2) is written as uδ to show its dependence on δ.

    This paper is organized as follows. In Section 2, we prove the existence and uniqueness of random attractors of system (1.1). Section 3 is devoted to consider the the Wong-Zakai approximations associated with system (1.1). In Section 4, we establish the convergence of solutions and attractors for approximate system (1.2) when δ0.

    Throughout this paper, the letter c and ci(i=1,2,) are generic positive constants which may change their values from line to line.

    In this section, we will define a continuous cocycle for second order non-autonomous stochastic lattice system (1.1), and then prove the existence and uniqueness of pullback attractors.

    A standard Brownian motion or Wiener process (Wt)tR (i.e., with two-sided time) in R is a process with W0=0 and stationary independent increments satisfying WtWsN(0,|ts|I). F is the Borel σ-algebra induced by the compact-open topology of Ω, and P is the corresponding Wiener measure on (Ω,F), where

    Ω={ωC(R,R):ω(0)=0},

    the probability space (Ω,F,P) is called Wiener space. Define the time shift by

    θtω()=ω(+t)ω(t),ωΩ, tR.

    Then (Ω,F,P,{θt}tR) is a metric dynamical system (see [1]) and there exists a {θt}tR-invariant subset ˜ΩΩ of full measure such that for each ωΩ,

    ω(t)t0ast±. (2.1)

    For the sake of convenience, we will abuse the notation slightly and write the space ˜Ω as Ω.

    We denote by

    lp={u|u=(ui)iZ,uiR, iZ|ui|p<+},

    with the norm as

    upp=iZ|ui|p.

    In particular, l2 is a Hilbert space with the inner product (,) and norm given by

    (u,v)=iZuivi,u2=iZ|ui|2,

    for any u=(ui)iZ, v=(vi)iZl2.

    Define linear operators B, B, and A acting on l2 in the following way: for any u=(ui)iZl2,

    (Bu)i=ui+1ui,(Bu)i=ui1ui,

    and

    (Au)i=2uiui+1ui1. (2.2)

    Then we find that A=BB=BB and (Bu,v)=(u,Bv) for all u,vl2.

    Also, we let Fi(s)=s0fi(r)dr, h(˙u)=(hi(˙ui))iZ, f(u)=(fi(ui))iZ with fi,hiC1(R,R) satisfy the following assumptions:

    |fi(s)|α1(|s|p+|s|), (2.3)
    sfi(s)α2Fi(s)α3|s|p+1, (2.4)

    and

    hi(0)=0,0<h1hi(s)h2,sR, (2.5)

    where p>1, αi and hj are positive constants for i=1,2,3 and j=1,2.

    In addition, we let

    β=h1λ4λ+h22,β<1ν, (2.6)

    and

    σ=h1λ4λ+h22(h2+4λ+h22). (2.7)

    For any u,vl2, we define a new inner product and norm on l2 by

    (u,v)λ=(1νβ)(Bu,Bv)+λ(u,v),u2λ=(u,u)λ=(1νβ)Bu2+λu2.

    Denote

    l2=(l2,(,),),l2λ=(l2,(,)λ,λ).

    Then the norms and λ are equivalent to each other.

    Let E=l2λ×l2 endowed with the inner product and norm

    (ψ1,ψ2)E=(u(1),u(2))λ+(v(1),v(2)),ψ2E=u2λ+v2,

    for ψj=(u(j),v(j))T=((u(j)i),(v(j)i))TiZE, j=1,2,ψ=(u,v)T=((ui),(vi))TiZE.

    A family D={D(τ,ω):τR,ωΩ} of bounded nonempty subsets of E is called tempered (or subexponentially growing) if for every ϵ>0, the following holds:

    limteϵtD(τ+t,θtω)2=0,

    where D=supxDxE. In the sequel, we denote by D the collection of all families of tempered nonempty subsets of E, i.e.,

    D={D={D(τ,ω):τR,ωΩ}:Dis tempered inE}.

    The following conditions will be needed for g when deriving uniform estimates of solutions, for every τR,

    τeγsg(s)2ds<, (2.8)

    and for any ς>0

    limteςt0eγsg(s+t)2ds=0, (2.9)

    where γ=min{σ2,α2βp+1}.

    Let ˉv=˙u+βu and ˉφ=(u,ˉv)T, then system (1.1) can be rewritten as

    ˙ˉφ+L1(ˉφ)=H1(ˉφ)+G1(ω), (2.10)

    with initial conditions

    ˉφτ=(uτ,ˉvτ)T=(uτ,u1τ+βuτ)T,

    where

    L1(ˉφ)=(βuˉv(1νβ)Au+νAˉv+λu+β2uβˉv)+(0h(ˉvβu)),
    H1(ˉφ)=(0f(u)+g(t)),G1(ω)=(0a˙ω(t)).

    Denote

    v(t)=ˉv(t)aω(t)andφ=(u,v)T.

    By (2.10) we have

    ˙φ+L(φ)=H(φ)+G(ω), (2.11)

    with initial conditions

    φτ=(uτ,vτ)T=(uτ,u1τ+βuτaω(τ))T,

    where

    L(φ)=(βuv(1νβ)Au+νAv+λu+β2uβv)+(0h(vβu+aω(t))),
    H(φ)=(0f(u)+g(t)),G(ω)=(aω(t)βaω(t)νAaω(t)).

    Note that system (2.11) is a deterministic functional equation and the nonlinearity in (2.11) is locally Lipschitz continuous from E to E. Therefore, by the standard theory of functional differential equations, system (2.11) is well-posed. Thus, we can define a continuous cocycle Φ0:R+×R×Ω×EE associated with system (2.10), where for τR, tR+ and ωΩ

    Φ0(t,τ,ω,ˉφτ)=ˉφ(t+τ,τ,θτω,ˉφτ)=(u(t+τ,τ,θτω,uτ),ˉv(t+τ,τ,θτω,ˉvτ))T=(u(t+τ,τ,θτω,uτ),v(t+τ,τ,θτω,vτ)+a(ω(t)ω(τ)))T=φ(t+τ,τ,θτω,φτ)+(0,a(ω(t)ω(τ)))T,

    where vτ=ˉvτ+aω(τ).

    Lemma 2.1. Suppose that (2.3)–(2.8) hold. Then for every τR, ωΩ, and T>0, there exists c=c(τ,ω,T)>0 such that for allt[τ,τ+T], the solution φ of system (2.11) satisfies

    φ(t,τ,ω,φτ)2E+tτφ(s,τ,ω,φτ)2Edsctτ(g(s)2+|ω(s)|2+|ω(s)|p+1)ds+c(φτ2E+2iZFi(uτ,i)).

    Proof. Taking the inner product (,)E on both side of the system (2.11) with φ, it follows that

    12ddtφ2E+(L(φ),φ)E=(H(φ),φ)E+(G(ω),φ)E. (2.12)

    For the second term on the left-hand side of (2.12), we have

    (L(φ),φ)E=βu2λ+β2(u,v)βv2+ν(Av,v)+(h(vβu+aω(t)),v).

    By the mean value theorem and (2.5), there exists ξi(0,1) such that

    β2(u,v)+(h(vβu+aω(t)),v)=β2(u,v)+iZhi(ξi(viβui+aiω(t)))(viβui+aiω(t))vi(β2h2β)uv+h1v2h2|(aω(t),v)|.

    Then

    (L(φ),φ)Eσφ2Eh12v2(βσ)u2λ+(h12βσ)v2βh2λuλvh2|(aω(t),v)|,

    which along with (2.6) and (2.7) implies that

    (L(φ),φ)Eσφ2E+h12v2σ+h16v2c|ω(t)|2a2. (2.13)

    As to the first term on the right-hand side of (2.12), by (2.3) and (2.4) we get

    (H(φ),φ)E=(f(u),˙u+βuaω(t))+(g(t),v)ddt(iZFi(ui))α2βiZFi(ui)+α1iZ(|ui|p+|ui|)|aiω(t)|+(g(t),v)ddt(iZFi(ui))α2βp+1iZFi(ui)+c|ω(t)|p+1ap+1+σλ4u2+ca2|ω(t)|2+σ+h16v2+cg(t)2. (2.14)

    The last term of (2.12) is bounded by

    (G(ω),φ)E=ω(t)(a,u)λ+βω(t)(a,v)νω(t)(Aa,v)σ4u2λ+1σa2λ|ω(t)|2+σ+h16v2+c|ω(t)|2a2. (2.15)

    It follows from (2.12)–(2.15) that

    ddt(φ2E+2iZFi(ui))+γ(φ2E+2iZFi(ui))+γφ2Ec(g(t)2+|ω(t)|2+|ω(t)|p+1), (2.16)

    where γ=min{σ2,α2βp+1}. Multiplying (2.16) by eγt and then integrating over (τ,t) with tτ, we get for every ωΩ

    φ(t,τ,ω,φτ)2E+γtτeγ(st)φ(s,τ,ω,φτ)2Edseγ(τt)(φτ2E+2iZFi(uτ,i))+ctτeγ(st)(g(s)2+|ω(s)|2+|ω(s)|p+1)ds, (2.17)

    which implies desired result.

    Lemma 2.2. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle Φ0 associated with system (2.10) has a closed measurable D-pullback absorbing set K0={K0(τ,ω):τR,ωΩ}D, where for every τR and ωΩ

    K0(τ,ω)={ˉφE:ˉφ2ER0(τ,ω)}, (2.18)

    where ˉφτtD(τt,θtω) and R0(τ,ω) is given by

    R0(τ,ω)=c+c|ω(τ)|2+c0eγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds, (2.19)

    where c is a positive constant independent of τ, ω and D.

    Proof. By (2.17), we get for every τR, tR+ and ωΩ

    φ(τ,τt,θτω,φτt)2E+γττteγ(sτ)φ(s,τt,θτω,φτt)2Edseγt(φτt2E+2iZFi(uτt,i))+cττteγ(sτ)(g(s)2+|ω(sτ)ω(τ)|2+|ω(sτ)ω(τ)|p+1)dseγt(φτt2E+2iZFi(uτt,i))+c0teγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds. (2.20)

    By (2.1) and (2.8), the last integral on the right-hand side of (2.20) is well defined. For any sτt,

    ˉφ(s,τt,θτω,ˉφτt)=φ(s,τt,θτω,φτt)+(0,a(ω(sτ)ω(τ)))T,

    which along with (2.20) implies that

    ˉφ(τ,τt,θτω,ˉφτt)2E+γττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Eds2φ(τ,τt,θτω,φτt)2E+2γττteγ(sτ)φ(s,τt,θτω,φτt)2Eds+2a2(|ω(τ)|2+γττteγ(sτ)|ω(sτ)ω(τ)|2ds)4eγt(ˉφτt2E+a2|ω(t)ω(τ)|2+iZFi(uτt,i))+c|ω(τ)|2+c0eγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds. (2.21)

    By (2.3) and (2.4) we have

    iZFi(uτt,i)1α2iZfi(uτt,i)uτt,i1α2maxuτtsuτt|fi(s)|uτt2. (2.22)

    Using ˉφτtD(τt,θtω), (2.1) and (2.22), we find

    lim supt+4eγt(ˉφτt2E+a2|ω(t)ω(τ)|2+iZFi(uτt,i))=0, (2.23)

    which along with (2.21) implies that there exists T=T(τ,ω,D)>0 such that for all tT,

    ˉφ(τ,τt,θτω,ˉφτt)2E+γττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Edsc+c|ω(τ)|2+c0eγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds, (2.24)

    where c is a positive constant independent of τ, ω and D. Note that K0 given by (2.18) is closed measurable random set in E. Given τR, ωΩ, and DD, it follows from (2.24) that for all tT,

    Φ0(t,τt,θtω,D(τt,θtω))K0(τ,ω), (2.25)

    which implies that K0 pullback attracts all elements in D. By (2.1) and (2.9), one can easily check that K0 is tempered, which along with (2.25) completes the proof.

    Next, we will get uniform estimates on the tails of solutions of system (2.10).

    Lemma 2.3. Suppose that (2.3)–(2.9) hold. Then for every τR, ωΩ, D={D(τ,ω):τR,ωΩ}D and ε>0, there exist T=T(τ,ω,D,ε)>0 and N=N(τ,ω,ε)>0 such that for alltT, the solution ˉφ of system (2.10) satisfies

    |i|N|ˉφi(τ,τt,θτω,ˉφτt,i)|2Eε,

    where ˉφτtD(τt,θtω) and |ˉφi|2E=(1νβ)|Bu|2i+λ|ui|2+|ˉvi|2.

    Proof. Let η be a smooth function defined on R+ such that 0η(s)1 for all sR+, and

    η(s)={0,0s1;1,s2.

    Then there exists a constant C0 such that |η(s)|C0 for sR+. Let k be a fixed positive integer which will be specified later, and set x=(xi)iZ, y=(yi)iZ with xi=η(|i|k)ui, yi=η(|i|k)vi. Note ψ=(x,y)T=((xi),(yi))TiZ. Taking the inner product of system (2.11) with ψ, we have

    (˙φ,ψ)E+(L(φ),ψ)E=(H(φ),ψ)E+(G,ψ)E. (2.26)

    For the first term of (2.26), we have

    (˙φ,ψ)E=(1νβ)iZ(B˙u)i(Bx)i+λiZ˙uixi+iZ˙viyi=12ddtiZη(|i|k)|φi|2E+(1νβ)iZ(B˙u)i((Bx)iη(|i|k)(Bu)i)12ddtiZη(|i|k)|φi|2E(1νβ)C0kiZ|(B(vβu+aω(t))i||ui+1|12ddtiZη(|i|k)|φi|2Eckφ2Eck|ω(t)|2a2, (2.27)

    where |φi|2E=(1νβ)|Bu|2i+λ|ui|2+|vi|2. As to the second term on the left-hand side of (2.26), we get

    (L(φ),ψ)E=β(1νβ)(Au,x)+(1νβ)((Au,y)(Av,x))+ν(Av,y)+λβ(u,x)+β2(u,y)β(v,y)+(h(vβu+aω(t)),y).

    It is easy to check that

    (Au,x)=iZ(Bu)i(η(|i|k)(Bu)i+(Bx)iη(|i|k)(Bu)i)iZη(|i|k)|Bu|2i2C0ku2,
    (Av,y)=iZ(Bv)i(η(|i|k)(Bv)i+(By)iη(|i|k)(Bv)i)iZη(|i|k)|Bv|2i2C0kv2,

    and

    (Au,y)(Av,x)C0kiZ|(Bu)i||vi+1|C0kiZ|(Bv)i||ui+1|2C0k(u2+v2).

    By the mean value theorem and (2.5), there exists ξi(0,1) such that

    β2(u,y)+(h(vβu+aω(t)),y)=β2iZη(|i|k)uivi+iZhi(ξi(viβui+aiω(t)))(viβui+aiω(t))η(|i|k)viβ(βh2)iZη(|i|k)|uivi|+h1iZη(|i|k)|vi|2h2iZη(|i|k)|viaiω(t)|.

    Then

    (L(φ),φ)EσiZη(|i|k)|φi|2Eh12iZη(|i|k)|vi|2(βσ)iZη(|i|k)((1νβ)|Bu|2i+λu2i)+(h12βσ)iZη(|i|k)|vi|2βh2λiZη(|i|k)|vi|((1νβ)(Bu)2i+λ|ui|2)12h2iZη(|i|k)|viaiω(t)|ckφ2E,

    which along with (2.6) and (2.7) implies that

    (L(φ),φ)EσiZη(|i|k)|φi|2E+h12iZη(|i|k)|vi|2ckφ2Eh2iZη(|i|k)|viaiω(t)|σiZη(|i|k)|φi|2E+h16iZη(|i|k)|vi|2ckφ2EciZη(|i|k)|ai|2|ω(t)|2. (2.28)

    As to the first term on the right-hand side of (2.26), by (2.3) and (2.4)we get

    (H(φ),ψ)E=iZη(|i|k)fi(ui)(˙ui+βuiaiω(t))+iZη(|i|k)gi(t)viddt(iZη(|i|k)Fi(ui))α2βp+1iZη(|i|k)Fi(ui)+ciZη(|i|k)|ω(t)|p+1|ai|p+1+σλ4iZη(|i|k)|ui|2+ciZη(|i|k)|ai|2|ω(t)|2+σ6iZη(|i|k)|vi|2+ciZη(|i|k)|gi(t)|2. (2.29)

    For the last term of (2.26), we have

    (G,ψ)E=ω(t)(a,x)λ+βω(t)(a,y)νω(t)(Aa,y)=ω(t)(1νβ)(Ba,Bx)νω(t)(Ba,By)+λω(t)(a,x)+βω(t)(a,y), (2.30)

    As to the first two terms on the right-hand side of (2.30), we get

    ω(t)(1νβ)(Ba,Bx)=ω(t)(1νβ)iZ(ai+1ai)(η(|i+1|k)ui+1η(|i|k)ui)(iZη(|i+1|k)u2i+1)12(iZη(|i+1|k)(ω(t)(1νβ)(ai+1ai))2)12+(iZη(|i|k)u2i)12(iZη(|i|k)(ω(t)(1νβ)(ai+1ai))2)12σλ8iZη(|i|k)u2i+c|ω(t)|2|i|ka2i, (2.31)

    and

    νω(t)(Ba,By)=νω(t)iZ(ai+1ai)(η(|i+1|k)vi+1η(|i|k)vi)σ6iZη(|i|k)v2i+c|ω(t)|2|i|ka2i. (2.32)

    The last two terms of (2.30) is bounded by

    λω(t)(a,x)+βω(t)(a,y)σλ8iZη(|i|k)u2i+σ+h16iZη(|i|k)v2i+c|ω(t)|2|i|ka2i. (2.33)

    It follows from (2.26)–(2.33) that

    ddt(iZη(|i|k)(|φi|2E+2Fi(ui)))+γ(iZη(|i|k)(|φi|2E+2Fi(ui)))+γiZη(|i|k)|φ|2Eckφ2E+ck|ω(t)|2+c|i|k|ai|p+1|ω(t)|p+1+c|i|k|gi(t)|2+c|i|k|ai|2|ω(t)|2, (2.34)

    where γ=min{σ2,α2βp+1}. Multiplying (2.34) by eγt, replacing ω by θτω and integrating on (τt,τ) with tR+, we get for every ωΩ

    iZη(|i|k)(|φi(τ,τt,θτω,φτt,i)|2E+2Fi(ui(τ,τt,θτω,uτt,i)))eγt(iZη(|i|k)(|φτt,i|2E+2Fi(uτt,i)))+ckττteγ(sτ)φ(s,τt,θτω,φτt)2Eds+ck0eγs|ω(s)ω(τ)|2ds+c|i|k|ai|p+10eγs|ω(s)ω(τ)|p+1ds+c|i|k|ai|20eγs|ω(s)ω(τ)|2ds+c0eγs|i|k|gi(s+τ)|2ds. (2.35)

    For any sτt,

    ˉφ(s,τt,θτω,ˉφτt)=φ(s,τt,θτω,φτt)+(0,a(ω(sτ)ω(τ)))T,

    which along with (2.35) implies that

    iZη(|i|k)(|ˉφi(τ,τt,θτω,ˉφτt,i)|2E+2Fi(ui(τ,τt,θτω,uτt,i)))4eγt(iZη(|i|k)(|ˉφτt,i|2E+|ai|2|ω(t)ω(τ)|2+Fi(uτt,i)))+ckττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Eds+ck0eγs|ω(s)ω(τ)|2ds+c|i|k|ai|p+10eγs|ω(s)ω(τ)|p+1ds+c|i|k|ai|20eγs|ω(s)ω(τ)|2ds+c0eγs|i|k|gi(s+τ)|2ds+2|i|k|ai|2|ω(τ)|2. (2.36)

    By (2.1) and (2.8), the last four integrals in (2.36) are well defined. By (2.3) and (2.4), we obtain

    iZη(|i|k)Fi(ui,τt)1α2iZη(|i|k)fi(uτt,i)uτt,i1α2maxuτtsuτt|fi(s)|uτt2,

    which along with ˉφτtD(τt,θtω) and (2.1) implies that

    lim supt+4eγt(iZη(|i|k)(|ˉφτt,i|2E+|ai|2|ω(t)ω(τ)|2+Fi(uτt,i)))=0.

    Then there exists T1=T1(τ,ω,D,ε)>0 such that for all tT1,

    4eγt(iZη(|i|k)(|ˉφτt,i|2E+|ai|2|ω(t)ω(τ)|2+Fi(uτt,i)))ε4. (2.37)

    By (2.1) and (2.24), there exist T2=T2(τ,ω,D,ε)>T1 and N1=N1(τ,ω,ε)>0 such that for all tT2 and kN1

    ckττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Eds+ck0eγs|ω(s)ω(τ)|2dsε4. (2.38)

    By (2.8), there exists N2=N2(τ,ω,ε)>N1 such that for all kN2,

    2|i|k|ai|2|ω(τ)|2+c0eγs|i|k|gi(s+τ)|2dsε4. (2.39)

    By (2.1) again, we find that there exists N3=N3(τ,ω,ε)>N2 such that for all kN3,

    c|i|k|ai|p+10eγs|ω(s)ω(τ)|p+1ds+c|i|k|ai|20eγs|ω(s)ω(τ)|2dsε4. (2.40)

    Then it follows from (2.36)–(2.40) that for all tT2 and kN3

    |i|2k|ˉφi(τ,τt,θτω,ˉφτt,i)|2EiZη(|i|k)|ˉφi(τ,τt,θτω,ˉφτt,i)|2Eε.

    This concludes the proof.

    As a consequence of Lemma 2.2 and Lemma 2.3, we get the existence of D-pullback attractors for Φ0 immediately.

    Theorem 2.1. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle Φ0 associated with system (2.10) has a unique D-pullback attractors A0={A0(τ,ω):τR, ωΩ}D in E.

    In this section, we will approximate the solutions of system (1.1) by the pathwise Wong-Zakai approximated system (1.2). Given δ0, define a random variable Gδ by

    Gδ(ω)=ω(δ)δ,for allωΩ. (3.1)

    From (3.1) we find

    Gδ(θtω)=ω(t+δ)ω(t)δandt0Gδ(θsω)ds=t+δtω(s)δds+0δω(s)δds. (3.2)

    By (3.2) and the continuity of ω we get for all tR,

    limδ0t0Gδ(θsω)ds=ω(t). (3.3)

    Note that this convergence is uniform on a finite interval as stated below.

    Lemma 3.1. ([17]). Let τR, ωΩ and T>0. Then for every ε>0, there exists δ0=δ0(ε,τ,ω,T)>0 such that for all and ,

    By Lemma 3.1, we find that there exist and such that for all and ,

    (3.4)

    By (3.3) we find that is an approximation of the white noise in a sense. This leads us to consider system (1.2) as an approximation of system (1.1).

    Let and , the system (1.2) can be rewritten as

    (3.5)

    with initial conditions

    where

    Denote

    By (3.5) we have

    (3.6)

    with initial conditions

    where

    Note that system (3.6) is a deterministic functional equation and the nonlinearity in (3.6) is locally Lipschitz continuous from to . Therefore, by the standard theory of functional differential equations, system (3.6) is well-posed. Thus, we can define a continuous cocycle associated with system (3.5), where for , and

    where .

    For later purpose, we now show the estimates on the solutions of system (3.6) on a finite time interval.

    Lemma 3.2. Suppose that (2.3)–(2.8) hold. Then for every , , and , there exist and such that for all and, the solution of system (3.6) satisfies

    Proof. Taking the inner product on both side of the system (3.6) with , it follows that

    (3.7)

    By the similar calculations in (2.13)–(2.15), we get

    (3.8)
    (3.9)

    and

    (3.10)

    It follows from (3.7)–(3.10) that

    (3.11)

    where . Multiplying (3.11) by and integrating on with , we get for every

    which implies the desired result.

    In what follows, we derive uniform estimates on the solutions of system (3.5) when is sufficiently large.

    Lemma 3.3. Suppose that (2.3)–(2.8) hold. Then for every , , , and , there exists such that for all, the solution of system (3.5) satisfies

    where and is given by

    (3.12)

    where is a positive constant independent of , and .

    Proof. Multiplying (3.11) by , replacing by and integrating on with , we get for every

    (3.13)

    By (2.1), (2.8) and (3.2), the last integral on the right-hand side of (3.13) is well defined. For any ,

    which along with (3.13) shows that

    (3.14)

    Note that (2.3) and (2.4) implies that

    which along with , (2.1) and (3.2) implies that

    (3.15)

    Then (3.14) and (3.15) can imply the desired estimates.

    Next, we show that system (3.5) has a -pullback absorbing set.

    Lemma 3.4. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle associated with system (3.5) has a closed measurable -pullback absorbing set , where for every and

    (3.16)

    where is given by (3.12).In addition, we have for every and

    (3.17)

    where is defined in (2.19).

    Proof. Note given by (3.16) is closed measurable random set in . Given , , and , it follows from Lemma 3.3 that there exists such that for all ,

    which implies that pullback attracts all elements in . By (2.1), (2.8) and (3.2), we can prove is tempered. The convergence (3.17) can be obtained by Lebesgue dominated convergence as in [17].

    We are now in a position to derive uniform estimates on the tail of solutions of system (3.5).

    Lemma 3.5. Suppose that (2.3)–(2.8) hold. Then for every , and , there exist , and such that for all and , the solution of system (3.5) satisfies

    where and .

    Proof. Let be a smooth function defined in Lemma 2.3, and set , with , . Note . Taking the inner product of system (3.6) with , we have

    (3.18)

    For the first term of (3.18), we have

    (3.19)

    where . By the similar calculations in (2.28)–(2.33), we get

    (3.20)
    (3.21)

    and

    (3.22)

    It follows from (3.18)–(3.22) that

    (3.23)

    where . Multiplying (3.23) by , replacing by and integrating on with , we get for every

    (3.24)

    For any ,

    which along with (3.24) shows that

    (3.25)

    By (2.1) and (2.8), the last four integrals on the right-hand side of (3.24) are well defined. Note that (2.3) and (2.4) implies that

    Since , we find

    which along with (2.1) and (3.2) shows that there exist and such that for all and ,

    (3.26)

    By Lemma 3.3, (2.1) and (3.2), there exist and such that for all , and

    (3.27)

    By (2.8), there exists such that for all ,

    (3.28)

    By (2.1) and (3.2) again, we find that there exists such that for all and ,

    (3.29)

    Then it follows from (3.25)–(3.29) that for all , and ,

    This concludes the proof.

    By Lemma 3.4, has a closed -pullback absorbing set, and Lemma 3.5 shows that is asymptotically null in with respect to . Therefore, we get the existence of -pullback attractors for .

    Lemma 3.6. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle associated with (3.5) has a unique -pullback attractors , in .

    For the attractor of , we have the uniform compactness as showed below.

    Lemma 3.7. Suppose that (2.3)–(2.9) hold. Then for every , , there exists such that is precompact in .

    Proof. Given , we will prove that has a finite covering of balls of radius less than . By (3.2) we have

    (3.30)

    By , there exists such that for all ,

    (3.31)

    Similarly, there exists between and such that , which along with (2.1) implies that there exists such that for all and ,

    (3.32)

    Let . By (3.30)–(3.32) we get for all and ,

    (3.33)

    By (3.4), there exist and such that for all and ,

    which along with (3.33) implies that for all and ,

    (3.34)

    where . Denote by

    and

    (3.35)

    with and being as in (3.12) and (3.34). By (3.12) and (3.35) we find that for all ,

    (3.36)

    By (3.35) and (3.36), we find that for all , and . Therefore, for every , ,

    (3.37)

    By Lemma 3.5, there exist and such that for all and ,

    (3.38)

    for any . By (3.38) and the invariance of , we obtain

    (3.39)

    We find that (3.37) implies the set is bounded in a finite dimensional space and hence is precompact. This along with (3.39) implies has a finite covering of balls of radius less than in . This completes the proof.

    In this section, we will study the limiting of solutions of (3.5) as . Hereafter, we need an additional condition on : For all and ,

    (4.1)

    where is a positive constant, and .

    Lemma 4.1. Suppose that (2.3)–(2.7) and (4.1) hold. Let and are the solutions of (2.10) and (3.5), respectively. Then for every , , and , there exist and such that for all and ,

    Proof. Let and , where , , and are the solutions of (2.11) and (3.6), respectively. By (2.11) and (3.6) we get

    (4.2)

    where

    Taking the inner product of (4.2) with in , we have

    (4.3)

    For the second term on the left-hand side of (4.3), using the similar calculations in (2.13) we have

    (4.4)

    For the first term on the right-hand side of (4.3), by (4.1) we get

    (4.5)

    As to the last term of (4.3), we have

    (4.6)

    It follows from (4.3)–(4.6) that

    (4.7)

    By Lemma 2.1 and Lemma 3.2, there exists and such that for all and ,

    which along with (4.7) shows that for all and

    (4.8)

    Applying Gronwall's inequality and Lemma 3.1 to (4.8), we see that for every , there exists such that for all and

    (4.9)

    On the other hand, we have

    which along with (4.9) implies the desired result.

    Finally, we establish the upper semicontinuity of random attractors as .

    Theorem 4.1. Suppose that (2.3)–(2.9) and (4.1) hold. Then for every and ,

    (4.10)

    where .

    Proof. Let and in . Then by Lemma 4.1, we find that for all , and ,

    (4.11)

    By (3.16)–(3.17) we have, for all and ,

    (4.12)

    Then by (4.11), (4.12) and Lemma 3.7, (4.10) follows from Theorem 3.1 in [24] immediately.

    In this paper we use similar idea in [30] but apply to second order non-autonomous stochastic lattice dynamical systems with additive noise. we establish the convergence of solutions of Wong-zakai approximations and the upper semicontinuity of random attractors of the approximate random system as the step-length of the Wiener shift approaches zero. In addition, as to the second order non-autonomous stochastic lattice dynamical systems with multiplicative noise, we can use the similar method in [29] to get the corresponding results.

    The authors would like to thank anonymous referees and editors for their valuable comments and constructive suggestions.

    The authors declare no conflict of interest.



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