Evidence map›Paper›PMID 33469790›Full record

ArticleEnvironmental science and pollution research international2021

Dynamic simulation for comprehensive water resources policies to improve water-use efficiency in coastal city.

Ziyao An, Jingjing Yan, Jinghua Sha, Yufang Ma, Siyu Mou

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Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ziyao AnSchool of Economics and Management, China University of Geosciences, Beijing, 100083, China.
Jingjing YanSchool of Economics and Management, China University of Geosciences, Beijing, 100083, China. yanjingjing312@hotmail.com.
Jinghua ShaSchool of Economics and Management, China University of Geosciences, Beijing, 100083, China.
Yufang MaSchool of Economics and Management, China University of Geosciences, Beijing, 100083, China.
Siyu MouSchool of Economics and Management, China University of Geosciences, Beijing, 100083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coastal cities play an important role in regional economic development and sustainable development strategies of water resources and their ecological environment. As a typical coastal city in Hebei Province, Qinhuangdao city is facing severe problems, such as water shortages and water environment deterioration, while social and economic development continues. Based on input-output analysis, we established a dynamic optimization model among Qinhuangdao city's socioeconomic development, water resources and water environment. The 2013-2030 simulation after introducing comprehensive water resources policies of regional development, examines the regional socioeconomic development, optimizes the water resources supply structure and improves the water environment under the optimal scenario, and evaluates policy feasibility through cost-benefit analysis (CBA). The simulation results suggest that under the optimal scenario, the water-use efficiency (WE) of Qinhuangdao is improved by 59.14% and the proportion of reclaimed water and desalinated seawater in the water supply structure is increased by 13.70%. In addition, it has achieved an average annual gross regional production (GRP) growth rate of 6.36% and an average annual chemical oxygen demand (COD) emission rate of 17.95%. Moreover, the net present value (NPV) of the projects under the optimal scenario is 1.534 billion Chinese yuan (CNY), which means that the policy is economically feasible. Our research is helpful to improve the WE, optimize the water supply structure and protect the hydrogeological environment in coastal cities with water shortages and can provide a reference for Qinhuangdao city and other similar coastal cities to realize the rational utilization of water resources and regional sustainable development.

Indexed as

WaterWater ResourcesChinaCitiesConservation of Natural ResourcesEconomic DevelopmentWater SupplyWaterCoastal citiesCost-benefit analysisDynamic optimization modelWater resources policiesWater supply structure

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.