Land Use and Climate Change Impacts on the Hydrology of the Bago River Basin,Myanmar

Assessment of land use and climate change impacts on the hydrological cycle is important for basin scale water resources management. This study aims to investigate the potential impacts of land use and climate change on the hydrology of the Bago River Basin in Myanmar. Two scenarios from the representative concentration pathways (RCPs): RCP4.5 and RCP8.5 recommended by the Intergovernmental Panel on Climate Change, Fifth Assessment Report (IPCC AR5) were used to project the future climate of 2020s, 2050s, and 2080s. Six general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were selected to project the future climate in the basin. An increase of average temperature in the range of 0.7 to 1.5 °C and 0.9 to 2.7 °C was observed under RCP 4.5 and RCP 8.5, respectively, in future periods. Similarly, average annual precipitation shows a distinct increase in all three periods with the highest increase in 2050s. A well calibrated and validated Soil and Water Assessment Tool (SWAT) was used to simulate the land use and climate change impacts on future stream flows in the basin. It is observed that the impact of climate change on stream flow is higher than the land use change in the near future. The combined impacts of land use and climate change can increase the annual stream flow up to 68 % in the near future. The findings of this study would be beneficial to improve land and water management decisions and in formulating adaptation strategies to reduce the negative impacts, and harness the positive impacts of land use and climate change in the Bago River Basin.     

Potential Impact of Climate Change on Residential Energy Consumption in Dhaka City

This study aimed to assess the impacts of climate change on residential energy consumption in Dhaka city of Bangladesh. The monthly electricity consumption data for the period 2011–2014 and long-term climate variables namely monthly rainfall and temperature records (1961–2010) were used in the study. An ensemble of six global circulation models (GCMs) of coupled model intercomparison project phase 5 (CMIP5) namely, BCCCSM1-1, CanESM2, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, and NorESM1-M under four representative concentration pathway (RCP) scenarios were used to project future changes in rainfall and temperature. The regression models describing the relationship between historical energy consumption and climate variables were developed to project future changes in energy consumptions. The results revealed that daily energy consumption in Dhaka city increases in the range of 6.46–11.97 and 2.37–6.25 MkWh at 95% level of confidence for every increase of temperature by 1 °C and daily average rainfall by 1 mm, respectively. This study concluded that daily total residential energy demand and peak demand in Dhaka city can increase up to 5.9–15.6 and 5.1–16.7%, respectively, by the end of this century under different climate change scenarios.     

The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China

Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.     

Statistical Modeling of Health Effects on Climate-Sensitive Variables and Assessment of Environmental Burden of Diseases Attributable to Climate Change in Nepal

An ecological time-series study is conducted to quantify health-effect coefficients associated with climate-sensitive variables namely temperature, rainfall, relative humidity, and wind speed and estimate environmental burden of diseases attributed to temperature as the main climatic variable together with climate change in Nepal. The study is based upon daily data of climate-sensitive variables and hospitalizations collected for 5 years between 2009 and 2014. Generalized linear model is used to estimate health-effect coefficients accounting distributed lag effects. Results show 3.08%, 10.14%, and 3.27% rise in water-borne, vector-borne, and renal disease hospitalizations, respectively, and 3.67% rise in water- and vector-borne disease deaths per 1 °C rise in average temperature. Similarly, 2.45% and 1.44% rise in heart disease hospitalization and all-cause mortality, respectively per 1 °C rise in absolute difference of average temperature with its overall average (20 °C). The computed attributable fractions are 0.3759, 0.6696, 0.2909, and 0.1024 for water-borne, vector-borne, renal, and heart disease hospitalizations, respectively, and 0.0607 and 0.4335 for all-cause mortality and disease-specific mortality of water- and vector-borne diseases, respectively. The percent change in attributable burdens due to climate change are found to be 4.32%, 4.64%, 7.20%, and ?2.29% for water-borne, vector-borne, renal, and heart disease hospitalizations, respectively, and ?1.39% and 6.55% for all-cause deaths and water-borne and vector-borne disease deaths, respectively. In conclusion, climate-sensitive variables have significant effects on many major health burdens in Nepal. In the context of changing climatic scenarios around the world including that of Nepal, such changes are bound to affect the health burden of Nepalese people.     

Spatial and temporal dynamic of trophic relevant parameters in a subtropical coastal lagoon in Brazil

Coastal lagoons are ecologically and economically important environments but a relative low number of studies were carried out in subtropical and permanently closed coastal lagoons. The present study aimed at assessing the temporal and spatial dynamic of trophic relevant water quality parameters in the small, deep and freshwater Peri coastal lagoon, South Brazil. During the 19 sampled months (March/2008-September/2009) spatial homogeneity (horizontal and vertical) was registered in all seasons for all variables, a condition related to the strong wind influence and low human occupation in the lagoon watershed. Seasonal variations of the water quality could be observed and they can be explained mainly by variation on temperature, wind forces and direction and rainfall, characteristic from the subtropical weather. Comparing this study with two others conducted in Peri lagoon in 1996 and 1998, no critical differences that evidence alteration in the water quality were found, but climate differences may have influenced in some small variations observed. The use of four trophic state indices indicated that indices designed for temperate lakes are inappropriate for the subtropical Peri lagoon. The lagoon was classified as oligotrophic for nutrients concentrations and meso-eutrophic for transparency and chlorophyll-a, which can be explained by the high densities and monodominance of the cyanobacterium Cylindrospermopsis raciborskii and the high recycling rates observed in warmer water bodies, when compared to the temperate ones.     

Transformation effect of resource-based cities based on PSM-DID model: An empirical analysis from China

Promoting sustainable development in resource-based cities is required to accelerate transformative economic development, which also can promote harmonious development and accelerate progress of industrialization while playing a critical role in China's urbanization. However, the role of regional sustainable development plans within resource-based cities is unclear. This paper selected 87 resource-based cities as the treated group, matching propensity scores of city characteristics on a total of 253 cities in China from 2008 to 2018. The paper used the difference-in-differences method to evaluate the impact of the implementation of the “National Plan for Resource-based City Sustainable Development (2013-2020)”, measuring six years before and five years post-planning implementation. We found: (1) The implementation of the plan has promoted economic, social, and ecological transformation by 19.6%, 55.4% and 74.5% respectively (p < 0.01), but there appeared to be no additional effects on sustainable utilization of resources. (2) Among driving factors, market development affected all forms of transformation the most. (3) The impact of this transformation varied by stages of urban development according to the full life cycle of the resource-based city and its local resources. Specifically, the transformation effect of the growing type city in economic, social, ecological and resource transformation was the strongest among that of all type stages.     

2015—2020年全国重污染天变化趋势及时空分布特征分析

2015—2020年,全国重污染发生天数、比例及城市数量整体呈逐年下降趋势。与2015年相比,2020年全国337个地级及以上城市重污染天数减少1 847 d,降幅达55.2%;重污染天数比例下降1.6个百分点;发生过重污染天气的城市数量减少60个。其中,全国细颗粒物重污染天数整体呈下降趋势,沙尘重污染天数随气象条件的差异波动变化,臭氧重污染天数呈波动上升趋势。"十四五"期间,消除重污染天气的主要对象仍是细颗粒物重污染。应将天山北坡城市群、"2+26"城市、汾渭平原及苏皖鲁豫交界地区作为"十四五"期间污染减排的重点关注区域。此外,需遏制"2+26"城市臭氧重污染上升势头。     

Modeling distribution changes of vegetation in China under future climate change

Climatic change will result in great changes in vegetation. In this paper, a biogeographical model, the BIOME1, was used to predict potential vegetation distribution in China under climate change. Firstly, the BIOME1 was validated according to the climate–vegetation relationships in China. Kappa statistics showed that the validated BIOME1 was able to capture the geographical patterns of vegetation more accurately. Then, the validated BIOME1 was used to predict the distribution of vegetation of China under two climatic scenarios produced by a Regional Circulation Model, RegCM2/CN. The simulation results showed obvious northward shifts of the boreal, temperate deciduous and evergreen and tropical forests, a large expansion of tropical dry forest/savanna and reduction of tundra on the Tibetan Plateau. Three vulnerable regions sensitive to climate changes are pointed out, i.e., Northern China, the Tibetan Plateau and Southwestern China (mainly Hengduan Mountains in Yunnan Province and west of Sichuan Province). In recent decades, China has experienced dramatic industrialization and population growth, which exert strong pressure on the environment of China. The consequences of climate changes warrant more attention for maintaining a sustainable environment for China.     

Predicting climate change effects on surface soil organic carbon of Louisiana,USA

This study aimed to assess the degree of potential temperature and precipitation change as predicted by the HadCM3 (Hadley Centre Coupled Model, version 3) climate model for Louisiana, and to investigate the effects of potential climate change on surface soil organic carbon (SOC) across Louisiana using the Rothamsted Carbon Model (RothC) and GIS techniques at the watershed scale. Climate data sets at a grid cell of 0.5°?×?0.5° for the entire state of Louisiana were collected from the HadCM3 model output for three climate change scenarios: B2, A2, and A1F1, that represent low, higher, and even higher greenhouse gas emissions, respectively. Geo-referenced datasets including USDA-NRCS Soil Geographic Database (STATSGO), USGS Land Cover Dataset (NLCD), and the Louisiana watershed boundary data were gathered for SOC calculation at the watershed scale. A soil carbon turnover model, RothC, was used to simulate monthly changes in SOC from 2001 to 2100 under the projected temperature and precipitation changes. The simulated SOC changes in 253 watersheds from three time periods, 2001–2010, 2041–2050, and 2091–2100, were tested for the influence of the land covers and emissions scenarios using SAS PROC GLIMMIX and PDMIX800 macro to separate Tukey-Kramer (p?p?p?p?相似文献   

Energy-related carbon emissions mitigation potential for the construction sector in China

China is undertaking a huge number of building and infrastructure projects. As a large consumer of energy-intensive building material, the construction activities provoke large direct carbon emissions in upstream industrial sectors (i.e. embodied carbon emissions). This paper aims to explore how construction-related climate policies could contribute to future national carbon emission mitigation efforts by employing a demand-side input-output model and scenario analysis. First, a hypothetical extraction approach is used to estimate the overall carbon emissions induced by the construction sector in the base year. Then scenario analysis is conducted to quantify the sector's technical potential for carbon mitigation in 2030 and 2050. We find that implementing construction-related climate measures in China could mitigate 2.5 Gt construction-induced CO2 in 2030, and 6.4 Gt in 2050 — more than Europe's annual total carbon emissions in 2015. More efficient electricity use could make a substantial contribution in the short-term. However, material-related initiatives, especially those focused on metal recycling, could yield significant carbon mitigation from 2030 onwards. Our findings suggest China to optimize the relationship between urbanization and construction to comply with the country's climate commitments better. Mechanisms to reform supply-side incentives, such as mandatory carbon labelling for construction material throughout the supply chain, could offer immediate benefits.     

Meta-Modeling to Assess the Possible Future of Paris Agreement

In the meta-modeling approach, one builds a numerically tractable dynamic optimization or game model in which the parameters are identified through statistical emulation of a detailed large scale numerical simulation model. In this paper, we show how this approach can be used to assess the economic impacts of possible climate policies compatible with the Paris Agreement. One indicates why it is appropriate to assume that an international carbon market, with emission rights given to different groups of countries will exist. One discusses the approach to evaluate correctly abatement costs and welfare losses incurred by different groups of countries when implementing climate policies. Finally, using a recently proposed meta-model of game with a coupled constraint on a cumulative CO₂ emissions budget, we assess several new scenarios for possible fair burden sharing in climate policies compatible with the Paris Agreement.     

The spatiotemporal dynamics of urbanisation and local climate: A case study of Islamabad,Pakistan

Rapid and unplanned urbanisation, together with climate change, are increasingly affecting the local climatic conditions of urban settlements. Spatiotemporal analysis using land use/land cover (LULC), land surface temperature (LST), and local climatic zone (LCZ) assessments have been helpful in understanding the urbanisation characteristics and morphology. Islamabad, the capital and the only planned city of Pakistan, has witnessed a consistent rise in local temperatures, increased built-up areas, and reduced vegetation cover during the past decades. This study explores the spatiotemporal dynamics of LULC, LST, and LCZ in Islamabad using satellite remote sensing data and spectral indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results indicate a whopping increase in a built-up area in the city (113% during 2013 and 2019). A positive correlation between LST and NDBI, whereas a negative correlation between LST and NDVI clearly indicates how urbanisation (and reduction in vegetation cover) are impacting the local temperatures. Assessment and analysis of LCZs helped to understand the variations and deviations of current LULC from the master plan. It was observed that compact low-rise urban development is the most prevalent. The outcomes of this study are expected to inform the urban planners, climatologists, and policymakers with the knowledge helpful for devising climate-resilient development policies that could reduce thermal stresses in the capital cities.     

Polycyclic aromatic hydrocarbons (PAHs) in the air of Chinese cities

Polycyclic aromatic hydrocarbons (PAHs) were determined in the air of 37 cities and 3 rural locations across China during the winter, spring, summer and autumn of 2005, using polyurethane foam (PUF) disks as passive air samplers (PAS). Winter and autumn concentrations in cities exceeded spring and summer values. Concentrations were amongst the highest in the world; seasonally averaged autumn/winter values in some cities in the north and north-west of China exceeded proposed European Union air quality standards. Several factors, acting in combination, influenced air concentrations. A significant negative correlation was found between average annual city concentrations and the annual average temperature, while winter time PAH concentrations correlated with estimated coal consumption. The highest total PAH concentrations and loadings of high molecular weight compounds generally occurred in major cities located on higher land (500-2000 m), where relatively cold winters and higher coal consumption occurs. Lower values occurred in cities located in the south and east China and along the coastal regions. Molecular markers indicated incomplete combustion of fossil fuels dominated the urban air and gave evidence for photo-decomposition of selected compounds.     

Mesoscale ecohydrological modelling to analyse regional effects of climate change

Hydrological processes and crop growth were simulated for the state of Brandenburg (Germany) using the hydrological/vegetation/water quality model SWIM, which can be applied for mesoscale river basins or regions. Hydrological validation was carried out for three mesoscale river basins in the area. The crop growth module was validated regionally for winter wheat, winter barley and maize. After that the analysis of climate change impacts on hydrology and crop growth was performed, using a transient 1.5 K scenario of climate change for Brandenburg and restricting the crop spectrum to the three above mentioned crops. According to the scenario, precipitation is expected to increase. The impact study was done comparing simulation results for two scenario periods 2022–2030 and 2042–2050 with those for a reference period 1981–1992. The atmospheric CO₂ concentrations for the reference period and two scenario periods were set to 346, 406 and 436 ppm, respectively. Two different methods – an empirical one and a semi-mechanistic one – were used for adjustment of net photosynthesis to altered CO₂. With warming, the model simulates an increase of evapotranspiration (+9.5%, +15.4%) and runoff (+7.0%, +17.2%). The crop yield was only slightly altered under the climate change only scenario (no CO₂ fertilization effect) for barley and maize, and it was reduced for wheat (–6.2%, –10.3%). The impact of higher atmospheric CO₂ compensated for climate-related wheat yield losses, and resulted in an increased yield both for barley and maize compared to the reference scenario. The simulated combined effect of climate change and elevated CO₂ on crop yield was about 7% higher for the C₃ crops when the CO₂ and temperature interaction was ignored. The assumption that stomatal control of transpiration is taking place at the regional scale led to further increase in crop yield, which was larger for maize than for wheat and barley. The regional water balance was practically not affected by the partial stimulation of net photosynthesis due to higher CO₂, while the introduction of stomatal control of regional transpiration reduced evapotranspiration and enlarged notably runoff and ground water recharge.     

Assessment of Climate Change Effects on Canada's National Park System

To estimate the magnitude of climate change anticipated forCanada's 38 National Parks (NPs) and Park Reserves, seasonaltemperature and precipitation scenarios were constructed for 2050and 2090 using the Canadian Centre for Climate Modelling andAnalysis (CCCma) coupled model (CGCM1). For each park, we assessed impacts on physical systems, species, ecosystems andpeople. Important, widespread changes relate to marine andfreshwater hydrology, glacial balance, waning permafrost, increased natural disturbance, shorter ice season, northern andupward altitudinal species and biome shifts, and changed visitation patterns. Other changes are regional (e.g., combinedEast coast subsidence and sea level rise increase coastal erosionand deposition, whereas, on the Pacific coast, tectonic upliftnegates sea level rise). Further predictions concern individualparks (e.g., Unique fens of Bruce Peninsular NP will migratelakewards with lowered water levels, but structural regulation of Lake Huron for navigation and power generation would destroythe fens). Knowledge gaps are the most important findings. Forexample: we could not form conclusions about glacial massbalance, or its effects on rivers and fjords. Likewise, for theEast Coast Labrador Current we could neither estimate temperature and salinity effects of extra iceberg formation, nor the further effects on marine food chains, and breeding park seabirds. We recommend 1) Research on specific large knowledge gaps; 2) Climate change information exchange with protected area agencies in other northern countries; and 3) incorporating climate uncertainty into park plans and management. We discuss options for a new park management philosophy in the face of massive change and uncertainty.     

Environmental water demand assessment under climate change conditions

Measures taken to cope with the possible effects of climate change on water resources management are key for the successful adaptation to such change. This work assesses the environmental water demand of the Karkheh river in the reach comprising Karkheh dam to the Hoor-al-Azim wetland, Iran, under climate change during the period 2010–2059. The assessment of the environmental demand applies (1) representative concentration pathways (RCPs) and (2) downscaling methods. The first phase of this work projects temperature and rainfall in the period 2010–2059 under three RCPs and with two downscaling methods. Thus, six climatic scenarios are generated. The results showed that temperature and rainfall average would increase in the range of 1.7–5.2 and 1.9–9.2%, respectively. Subsequently, flows corresponding to the six different climatic scenarios are simulated with the unit hydrographs and component flows from rainfall, evaporation, and stream flow data (IHACRES) rainfall-runoff model and are input to the Karkheh reservoir. The simulation results indicated increases of 0.9–7.7% in the average flow under the six simulation scenarios during the period of analysis. The second phase of this paper’s methodology determines the monthly minimum environmental water demands of the Karkheh river associated with the six simulation scenarios using a hydrological method. The determined environmental demands are compared with historical ones. The results show that the temporal variation of monthly environmental demand would change under climate change conditions. Furthermore, some climatic scenarios project environmental water demand larger than and some of them project less than the baseline one.     

Adaptation to Climatic Variability and Change: Asian Perspectives on Agriculture and Food Security

The impacts of climate change on potential rice production in Asia are reviewed in the light of the adaptation to climatic variability and change. Collaborative studies carried out by IRRI and US-EPA reported that using process-based crop simulation models increasing temperature may decrease rice potential yield up to 7.4% per degree increment of temperature. When climate scenarios predicted by GCMs were applied it was demonstrated that rice production in Asia may decline by 3.8% under the climates of the next century. Moreover, changes in rainfall pattern and distribution were also found suggesting the possible shift of agricultural lands in the region. The studies however have not taken the impacts of climatic variability into account, which often produce extreme events like that caused by monsoons and El Niño. Shifts in rice-growing areas are likely to be constrained by land-use changes occurring for other developmental reasons, which may force greater cultivation of marginal lands and further deforestation. This should be taken into account and lead to more integrated assessment, especially in developing countries where land-use change is more a top-down policy rather than farmers' decision. A key question is: To what extent will improving the ability of societies to cope with current climatic variability through changing design of agricultural systems and practices help the same societies cope with the likely changes in climate?     

中国主要城市疫情管控期间大气环境改善效应研究

利用我国31个省会(省府)城市、直辖市站点大气污染物数据,对全国主要城市2020年新冠疫情管控期间以及复工复产后的大气污染状况进行统计学分析。结果表明:叠加疫情管控影响,相比往年,2020年春节假期前后全国主要城市整体上PM₁₀、NO₂、SO₂、CO平均质量浓度降幅分别达到22.46%、60.13%、13.71%、17.64%;疫情管控期间全国主要城市PM_2.5与PM₁₀偏相关系数为0.952,PM_2.5与SO₂、NO₂、CO的偏相关系数分别为0.705、0.791、0.831。复工复产初期相较疫情管控期间仅有NO₂平均质量浓度上升;随着复工复产进程深入,PM₁₀、SO₂、NO₂平均质量浓度则均有大幅度上升。采暖区SO₂和CO平均质量浓度在疫情管控期分别为非采暖区的2.6倍及1.6倍,两大区域在复工复产后各大气污染物质量浓度变化情况有所差异,也反映出采暖区与非采暖区的大气污染情况的不同。