Optimizing contract allocation for risky conservation tenders

In the face of a shrinking budget for environmental activities, conservation agencies must design and implement agri-environmental policies that cost-effectively meet the environmental objectives. However, designing such programs is often challenging due to different uncertainties. For example, landholders may be exposed to risks when carrying out conservation projects. To minimise the negative impact of unexpected losses, landholders may require additional financial incentives as compensation for undertaking “risky” conservation projects. In such situations, the conservation agency risks over-spending public funds because of prohibitively high opportunity costs from landholders or failing to meet the environmental target. We used analytical and simulation approaches to explore optimal budget allocation in a target-constrained conservation tender. We also compared the performance of the tender with and without own-cost uncertainty. Results showed that as landholders’ own-cost uncertainty rises, the conservation agency is forced to allocate more funding to secure the same level of the environmental target. We found that the optimal funding level is sensitive to landholders’ competition uncertainty and the magnitude of expected losses.

     

Does national carbon pricing policy affect voluntary environmental disclosures? A global evidence

Environmental Economics and Policy Studies - This paper examines the relationship between institutional pressure of national carbon pricing policy and the voluntary environmental disclosures (VED)...     

Microplastics pollution in Bangladesh: current scenario and future research perspective

ABSTRACT

Microplastics are emerging environmental pollutants that have gained tremendous scientific interest in recent years. These micropollutants are omnipresent both in the terrestrial and aquatic environments posing a deleterious threat to the ecosystem and biodiversity. So, it is important to develop a deep understanding of the environmental fate and potential adverse impacts of microplastics on the aquatic and terrestrial environments. By critically reviewing the previously published scientific literature, the present synthesis briefly outlines the characteristics, occurrence and potential toxic effects of microplastics on terrestrial and aquatic biota. The article also focuses on some innovative approaches for sustainable remediation of macroplastics as well as microplastics. Since the concept of microplastics pollution has yet in its infancy in Bangladesh, this synthesis provides an overview of the current scenario of microplastics pollution and some future research recommendations in the context of Bangladesh which might be helpful to the novice researchers of this field.     

A comparative decision-making model for sustainable end-of-life vehicle management alternative selection using AHP and extent analysis method on fuzzy AHP

Environmental protection and sustainable development are getting increasing attention in the automobile industries. Environmental consciousness has increased, and sustainability has become an important requirement for the management of end-of-life vehicles (ELVs). The proper management of ELVs can bring improved sustainability performance for any society or organisation. There are several alternative options for ELVs management such as reuse, repair, reconditioning, remanufacturing and recycling. Environmental legislation is forcing original equipment manufacturers (OEMs) to manage their products at the end of their life cycle to reduce their potential environmental impact. An appropriate selection model for sustainable ELV management alternatives in the dynamic, competitive and regulatory environment can enable a firm to satisfy economic, environmental, social and technological requirements. This study proposes an integrated model to select the dimensions and criteria for evaluating sustainable alternatives for the proper management of ELVs. First, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to select the most important dimensions and criteria for sustainable alternative selection. Next, a hierarchy has been constructed to develop a systematic technique to solve the alternatives selection problem. An analytic hierarchy process (AHP) and extent analysis method on the fuzzy AHP (FEAHP) model have been used based on the hierarchy to evaluate the most suitable alternatives from the sustainability point of view. The strength of the proposed model is that it compares the results of both methods, the imprecision of experts’ opinions is considered in the evaluation process and the model is easy to use.     

How economics can further the success of ecological restoration

Restoration scientists and practitioners have recently begun to include economic and social aspects in the design and investment decisions for restoration projects. With few exceptions, ecological restoration studies that include economics focus solely on evaluating costs of restoration projects. However, economic principles, tools, and instruments can be applied to a range of other factors that affect project success. We considered the relevance of applying economics to address 4 key challenges of ecological restoration: assessing social and economic benefits, estimating overall costs, project prioritization and selection, and long‐term financing of restoration programs. We found it is uncommon to consider all types of benefits (such as nonmarket values) and costs (such as transaction costs) in restoration programs. Total benefit of a restoration project can be estimated using market prices and various nonmarket valuation techniques. Total cost of a project can be estimated using methods based on property or land‐sale prices, such as hedonic pricing method and organizational surveys. Securing continuous (or long‐term) funding is also vital to accomplishing restoration goals and can be achieved by establishing synergy with existing programs, public–private partnerships, and financing through taxation.     

One-step synthesis of N-doped metal/biochar composite using NH3-ambiance pyrolysis for efficient degradation and mineralization of Methylene Blue

A series of new biochar-supported composite based on the combination of biochar and metallic nanoparticles(NPs)were produced through single-step pyrolysis of FeCl_3–Ti(OBu)_4 laden agar biomass under NH_3 environment.The physiochemical properties of composites were characterized thoroughly.It has found that heating temperature and N-doping through NH_3-ambiance pyrolysis significantly influence the visible-light sensitivity and bandgap energy of composites.The catalytic activities of composites were measured by degradation of Methylene Blue(MB)in the presence or absence of H_2O_2 and visible-light irradiation.Our best catalyst(N–TiO_2–Fe_3O_4-biochar)exhibits rapid and high MB removal competency(99.99%)via synergism of adsorption,photodegradation,and Fenton-like reaction.Continuous production of O_2U~-and UOH radicles performs MB degradation and mineralization,confirmed by scavenging experiments and degradation product analysis.The local trap state Ti~(3+),Fe_3O_4,and N-carbon of the catalyst acted as active sites.It has suggested that the Ti~(3+)and N-doped dense carbon layer improve charge separation and shuttle that prolonged photo-Fenton like reaction.Moreover,the catalyst is highly stable,collectible,and recyclable up to 5 cycles with high MB degradation efficiency.This work provides a new insight into the synthesis of highly visible-light sensitized biocharsupported photocatalyst through NH_3-ambiance pyrolysis of NPs-laden biomass.     

平寨水库荧光溶解性有机质的来源、特征及其动态转化

利用三维激发发射矩阵光谱(3-D EEM)和平行因子分析,研究了三岔河流域平寨水库溶解有机质的来源、组成和转化情况。在平寨水库的入库水、表层水(0～5 m)、深层水(10～60 m)和出库水中,检测到了几种荧光溶解有机质组分,分别为陆源类腐殖质、自源类腐殖质和浮游植物源的类蛋白质(或类色氨酸或类酪氨酸)。陆源类腐殖质的荧光强度在入库水中略高于出库水,表明陆源类腐殖质在水库系统中相对稳定,大坝截流对其影响不大。自源类腐殖质的荧光强度在库区明显高于入库水和出库水,表明自源类腐殖质既由自源有机物分解产生,又在光化学、微生物和大坝物理拦截过程的影响下发生分解;其他荧光组分中也检测到相似的结果。水温、pH、溶解氧和有色溶解有机质表现出相似的季节变化,光化学和微生物以及大坝拦截是引起水库入库水、库区表层水、库区深层水和出库水中荧光溶解有机质时空动态变化的主要原因。     

How safe are standard certified motorcycle safety helmets? Malaysian postal delivery riders scenario

Objective: The objective of this study was to determine the proportion of motorcycle safety helmets (MSHs) used by postal delivery riders (PDRs) that comply with the Standards and Industrial Research Institute of Malaysia’s (SIRIM) MSH standard guidelines and identify factors that contribute toward compliance of used MSHs with the standards.

Methods: The presence of SIRIM certification label, the status of MSH, type of chinstrap, MSH crash history, and duration of MSH use were observed. The dependent variable was the results of the SIRIM testing procedures (SIRIM tests). MSHs that passed the SIRIM tests were considered “standard certified” MSHs.

Results: The odds of the complimentary MSHs passing all of the SIRIM tests were 3.7 times the odds of the self-purchased MSHs passing the tests. The odds of MSHs with the SIRIM certification label passing all of the SIRIM tests were 24.2 times the odds of MSHs without the SIRIM certification label, and the odds of MSHs used <3?years passing the SIRIM tests were 3.75 times the odds of the MSHs used ≥3.8?years.

Conclusion: PDRs provided with complimentary MSHs with the SIRIM certification label by the employer for their daily delivery routines and duration of MSH used for less than 3 years were found to be safe MSHs for male occupational riders in Malaysia.     

CDES: A pixel-based crowd density estimation system for Masjid al-Haram

CDES is an automatic crowd density estimation system that can be used to estimate crowd density from digital images taken at Masjid al-Haram. Developed using a combination of image processing and artificial intelligence (AI) technologies, CDES possesses the capability to count the number of people in moderately high crowds from a flexibly selected region of interest (ROI). Background removal and edge detection are first applied to the image for crowd feature extraction. Then, the extracted crowd foreground blob pixels are scaled accordingly to correct perspective distortion. Finally, the corrected pixel blobs act as input for the backpropagation (BP) neural network to estimate the number of people within the blob. Using the area of the selected ROI, the crowd density is calculated and classified into five ranges from very low to very high. The experimental results are presented.     

Space-time Bayesian small area disease risk models: development and evaluation with a focus on cluster detection

This paper extends the spatial local-likelihood model and the spatial mixture model to the space-time (ST) domain. For comparison, a standard random effect space-time (SREST) model is examined to allow evaluation of each model’s ability in relation to cluster detection. To pursue this evaluation, we use the ST counterparts of spatial cluster detection diagnostics. The proposed criteria are based on posterior estimates (e.g., misclassification rate) and some are based on post-hoc analysis of posterior samples (e.g., exceedance probability). In addition, we examine more conventional model fit criteria including mean square error (MSE). We illustrate the methodology with a real ST dataset, Georgia throat cancer mortality data for the years 1994–2005, and a simulated dataset where different levels and shapes of clusters are embedded. Overall, it is found that conventional SREST models fair well in ST cluster detection and in goodness-of-fit, while for extreme risk detection the local likelihood ST model does best.